Search Results (2,538)

Background: Currently, expected goal models are tools that enable quantitative analysis in the study of conventional sports, although they have seen very little application in the Paralympic context. Objective: To present a trained expected goals model for 5-a-side blind soccer games based on an analysis of 164 offensive plays by the national team that won first place at the 2022 IBSA Copa América. The novelty of this work lies in being, to our knowledge, the first expected goals (xG) model developed for Paralympic blind football (B1): conventional xG weights cannot be transferred directly because shooting in F5 is governed by auditory orientation, the absence of an offside rule, a smaller rebound-walled pitch, and fully blind executors, so a sport-specific, reproducible and SHAP-interpretable benchmark is required where none previously existed. Materials and Methods: The SHapley Additive exPlanations library was used to analyze the data via partial dependency plots, dependency scatter plots, waterfall plots, decision plots, and SHAP heatmaps. Additionally, ten machine learning algorithms were compared, including logistic regression, random forest, extra trees, gradient boosting, XGBoost, LightGBM, CatBoost, support vector machine, k-nearest neighbors, and multilayer perceptron, using a 70/30 stratification process with fivefold stratified cross-validation to define the main hyperparameters. Results: The most consistent model was CatBoost (F1 = 0.778; AUC-ROC = 0.913; AUC-PR = 0.828; MCC = 0.729; Brier = 0.072), which allowed for independent analysis and evaluation of the dataset. The five main offensive variables were determined to be (i) distance to the goal before the shot; (ii) lateral coordinate; (iii) absolute magnitude of the shooting angle; (iv) magnitude of the progression vector; (v) proximity to the side kickboard. However, none of these variables proved to be decisive in the tournament (n = 24), a characteristic that the model captured as a significant negative contribution from the opponent variable. Conclusions: The expected goals model considered for this study serves as a starting point for further analysis of tactical variables in 5-a-side soccer for the blind. Because the model was trained on a single team in a single tournament with few positive cases, these results should be read as preliminary, hypothesis-generating tactical insights rather than validated performance estimates, and require external validation before transfer to other teams or competitions. Full article

The present study aims to analyze the development of achievement motivation and self-efficacy belief in the context of elite sports schools. A total of 658 athletes (349 female, 309 male) from Year 5 onwards participated in the central trials and performance assessments in track and field for elite sports schools between 2016 and 2025. In addition to the analysis of physical and athletic performance, the following aspects were also documented: achievement motivation, need for achievement motives and general self-efficacy beliefs. Firstly, differences between the genders were measured in terms of fear of failure and confidence, exhibiting a small effect size ranging from 0.175 to 0.25 and a significance of 0.001 and 0.026. A subsequent analysis of the Kruskal–Wallis test, pertaining to the various groups with differing performance levels, revealed significant disparities in self-discipline (p = 0.010), goal setting (p = 0.013) and confidence (p = 0.029). The effect sizes for these differences ranged from 0.08 to 0.14, indicating a modest magnitude of impact. The psychological profile of the top athletes, which is based on the psychological determinants of the study, differs significantly from that of the other groups of athletes at time t₁ (p = 0.001). It is recommended that appropriate training and guidance from coaches and sports psychologists be provided, given that confidence and self-efficacy expectations are key predictors of physical and athletic performance. Full article

Paper-based packaging is widely promoted as a sustainable alternative to plastic; however, functional coatings can reduce fibre integrity and lead to burden shifting in industrial recycling systems. This review examines how these effects undermine the environmental benefits expected from fibre-based packaging and weaken progress towards high-quality circularity, as required by current EU sustainability policy. By comparing leading assessment schemes (PTS, CEPI, 4evergreen) with industrial evidence, we identify a systemic gap: laboratory-focused recyclability tests often overlook fibre-quality degradation and the resulting limitations for circular material loops. To close this gap, we propose a sustainability-oriented extension module based on three measurable ISO-anchored indicators—fibre length, fines fraction and WRV—that prevent “recyclable-only-on-paper” claims and support genuinely sustainable recycling performance. Case studies demonstrate how high laboratory yields can mask low industrial recyclability and thus hinder circular economy objectives. This study contributes to sustainability science by operationalising recyclability in a manner consistent with EU circularity goals and by providing a transparent method to protect fibre value in multiple loop cycles. Full article

This study aims to explore perceptions of English as a Second Language (ESL) students on integrations of local culture into English language teaching using Artificial Intelligence approaches. Research samples included 511 ESL students of the English Faculty of four public universities in Vietnam’s Mekong Delta region. The input factor dimensions comprise demographics, level of local culture integration, facilities, and curriculum-related factors. The output factor was necessities for local culture–English-teaching integration. Two supervised machine learning algorithms, Decision Tree (DT) and Support Vector Machine (SVM), were applied with oversampling to address data imbalance issues. Results indicated that the oversampling case achieved the highest performance. The research shows that the DT model was slightly better than the SVM with an accuracy of 97% and AUC of 98%. Feature importance analysis identified curriculum, facilities, and students’ hometown as key predictors. The findings provided empirical evidence to support data-informed curriculum reform in culturally responsive English language teaching. This study also develops a novel method to explore students’ perceptions and offers practical suggestions for improving academic quality. This study is expected to enhance institutional student recruitment while contributing to the region’s sustainable development and the broader goal of preserving intangible cultural heritage in Vietnam’s Mekong Delta. Full article

Population aging has made aging in place (AIP) a central goal of sustainable welfare and urban governance, yet older adults’ perceived feasibility of remaining in their current home under conditions of vulnerability remains unevenly distributed. This study conceptualizes AIP intention under anticipated mobility limitation as a stratified condition of social sustainability, asking who expects to remain in the community as a supported and recognized member when mobility declines. Using the 2023 National Survey of Older Koreans (N = 9951), it examines older adults’ stated intention to remain in their current residence under mobility limitation through weighted logistic regression. The results show that this intention is structured most strongly by housing inequality: non-owner tenure reduces the likelihood of intending to remain in place, whereas housing satisfaction increases it. Co-residence with adult children is positively associated with this intention, while activities of daily living limitations are negatively associated with it. Beyond material and health conditions, social participation intention and digital adaptability increase the likelihood of intending to remain in place, whereas age discrimination in public institutions reduces it. Government trust is negatively associated with the intention to remain in place. Because the survey does not directly measure older adults’ awareness, availability, evaluation, or use of alternative residential or care facilities, this association is treated only as a discussion point rather than as an empirically tested mechanism: higher institutional trust may be linked to greater openness to publicly supported alternatives. The findings demonstrate that the perceived feasibility of AIP is not merely an individual preference, but an unevenly distributed possibility shaped by housing security, institutional inclusion, and civic capacity. Sustainable aging policy should integrate housing support, anti-discrimination measures, digital inclusion, and community participation. Full article

The temporal dynamics of shot quality in elite football remain poorly understood, despite well-documented declines in physical and technical performance during matches. This study aimed to analyze the evolution of advanced shot metrics across match halves and 15 min intervals in elite men’s and women’s international competitions. A total of 4074 shots from the UEFA European Championships were examined. To ensure methodological consistency among the three advanced shooting metrics (expected goals, xG; expected shot impact timing, xSIT; and expected goals on target, xGOT), analyses were restricted to shots on target (men: 775; women: 554), as xGOT can only be calculated for on-target attempts. Shot quality was assessed using xG, xSIT and xGOT. Differences between halves were evaluated using the Mann–Whitney U test, while temporal trends were analyzed through linear mixed-effects models. Results showed no significant differences between halves in shot distribution or quality metrics in either competition (all p > 0.05). Likewise, no significant temporal variations were found across the six match intervals for any metric. Women’s football exhibited a largely stable quality of shots on target throughout the match. In men’s competitions, although a significant difference in xG was observed (p = 0.04, effect sizes were trivial (d = −0.17), and no consistent patterns emerged in xSIT or xGOT. No sex-related differences were observed. Overall, shot quality remained stable despite match progression, suggesting that changes in goal frequency are not driven by variations in the intrinsic quality of shooting opportunities. Therefore, these findings suggest that optimizing the contextual conditions that facilitate the creation of shooting opportunities may be as important as, or more important than, focusing solely on shooting execution. Full article

To supply hydrogen to the geographically decoupled demand sites, efficient hydrogen transport is necessary. The existing natural gas pipelines represent a promising transport solution, with the blended hydrogen content expected to steadily increase. An open issue of hydrogen blending is the mixing behavior. Therefore, the effects of different geometric parameters (diameters, angles), operating conditions (velocities, concentrations), and injection layouts (single- and multi-point) on the mixture quality during direct injection of hydrogen into a natural gas pipeline are studied using 3D CFD. The main goal is to find parameters and layouts leading to sufficient mixing quality over a range of operating conditions. The mixing quality is determined based on the coefficient of variation (COV). The results show that the momentum flux ratio is a key parameter governing the mixing behavior. However, a high momentum flux ratio alone does not guarantee sufficient uniformity for all operating conditions. For the investigated range, single-point injection cannot ensure reliable mixing quality, whereas multi-point layouts with higher hydrogen inlet velocities achieve sufficient uniformity. Full article

This study explored parental concerns regarding their sons’ experiences in a professional football academy, using a case study methodology over a twelve-year period. Drawing on over 60 interviews with parenting pairs, the research identified that concerns were shaped by internal (e.g., personal beliefs), semi-internal (e.g., peer influence, agent input), and external (e.g., social media, educational trends) information sources. These sources often led to misaligned expectations between parents and the academy. The findings highlighted the prevalence of misinformation. In response, a series of targeted interventions were implemented, including structured communication strategies, shared mental models (SMMs), and a refined parent–academy code of conduct. These changes facilitated more integrated parent–athlete–coach relationships and improved clarity around developmental processes. Although causality cannot be established, the frequency of parental complaints decreased over time. This study emphasizes the need for academies to proactively engage parents as key stakeholders through clear, consistent, and evidence-informed communication, ultimately supporting a more coherent developmental experience for athletes. These findings have broad implications for talent development environments aiming to balance athlete and parent welfare with high-performance goals. Full article

While digitalization is expected to increase the demand for continuing workforce training in European economies, large-scale, cross-country panel data on macro-level relationships between participation in adult learning and digitalization remain insufficient. This study examines how digital diffusion, employment in the information and communication technologies sector, research and development intensity, and institutional quality are associated with adult learning participation across EU-27 member states. An unbalanced panel dataset covering the 27 EU member states for the period 2015–2023 was created from Eurostat and Sustainable Development Goals monitoring indicators. The empirical strategy includes cross-sectional dependence diagnostics, unit root and cointegration tests, fixed-effects estimation with Driscoll–Kraay standard errors, moderation analysis, and robustness checks based on alternative covariance specifications and first differences. The level-fixed-effects results show positive associations between individual internet use, as a proxy for economy-wide digital diffusion, and research and development intensity with adult learning participation (β = 0.110, p < 0.01; β = 2.451, p < 0.01, respectively). Employment in the information and communication technologies sector is not statistically significant, and institutional quality does not significantly moderate the association between individual internet use and adult learning participation. In hypothesis terms, H1 (digital diffusion) and H3 (research and development intensity) are supported in the level specification, whereas H2 (information and communication technologies employment) and H4 (institutional quality moderation) are not supported. When standard errors are clustered at the country level, the key coefficients lose significance, so these level estimates are descriptive structural associations rather than causal effects. The first-difference estimator does not reproduce the level relationships, indicating that the findings primarily reflect cross-country structural associations rather than within-country dynamic effects. Country-group analysis reveals a fourfold difference in mean adult learning participation between the lowest and highest digital diffusion quartiles (5.3% vs. 20.3%). The findings inform EU digital and skills policy by suggesting that the expansion of digital infrastructure should be coordinated with adult learning targets within the 2030 Digital Compass framework. Full article

Academic motivation and achievement are central to student success in applied STEM, engineering, and technical and vocational education and training (TVET); however, despite extensive research, the evidence remains fragmented across theoretical traditions, educational levels, and disciplinary settings. This structured narrative review synthesizes research on the factors shaping academic motivation, achievement, and career readiness in these contexts. A literature search was conducted in Web of Science, Scopus, ScienceDirect, PubMed, and PsycINFO for studies published between 2010 and 2025. A total of 58 studies met the inclusion criteria from an initial pool of 2184 records. Guided by self-determination theory, achievement goal theory, social cognitive career theory, and expectancy–value theory, this review identifies self-efficacy, perceived competence, task value, intrinsic/extrinsic motivation, goal orientation, metacognitive skills, teacher and peer support, curriculum relevance, and industry-aligned learning opportunities as key factors associated with student engagement, achievement, and career-related development. The synthesis shows that these factors operate through an integrated motivational core linking motivational regulation, self-belief, task value, and goal orientation. The findings suggest that student success is shaped by the interaction between individual beliefs, social support, instructional conditions, and perceived links between learning and future professional pathways. Practical implications are discussed for designing student-centered, career-relevant, and motivation-supportive learning environments in engineering and TVET. Full article

The expansion of remote work has transformed labour market conditions across the developed world, yet access to home-based work remains unequally distributed along occupational, sectoral, regional, and organisational lines. Post-pandemic evidence on the persistence of these inequalities is particularly scarce in Central and Eastern European economies, where historically low remote work prevalence, manufacturing-intensive industrial structures, and pronounced regional disparities create a distinctive structural context. Drawing on primary survey data collected from 390 employees in Slovakia in 2025, this study pursues two interrelated empirical goals: to identify the factors predicting a mismatch between the structural feasibility of working from home and its actual availability to employees, and to examine the determinants of experienced work discomfort. Binary logistic regression, multiple linear regression, and a battery of group difference tests were employed across the two analytical strands. The results reveal a pronounced capital–periphery gradient in remote work access, with employees outside the capital city facing dramatically higher odds of mismatch, and identify organisational support as the most practically actionable determinant of work discomfort. Notably, experiencing a mismatch between remote work feasibility and access was not associated with higher discomfort, a finding that challenges assumptions common in the Western European literature and points to the moderating role of contextual expectations in post-communist labour markets. The findings offer directly applicable evidence for employers seeking to reduce work-related strain through targeted support measures, and for policymakers designing regulatory frameworks to promote equitable access to flexible work arrangements across regions and sectors. Full article

Ensemble learning has been widely adopted in fraud detection; however, conventional ensemble strategies rely on uniform or performance-based weighting schemes that treat explainability as a post hoc annotation rather than an architectural component. This study addresses the research goal of whether SHAP attribution values can serve as a principled, instance-specific weighting mechanism within an ensemble, thereby embedding interpretability directly into the aggregation process. A SHAP-Weighted Ensemble (SWE) framework is proposed in which the L2 norm of each base model’s SHAP attribution vector, computed at prediction time, is used to derive instance-specific voting weights via Softmax normalization. Three linear base learners (logistic regression, robust LR, calibrated linear SVM) are combined, with LinearSHAP providing exact attribution values. A comprehensive evaluation protocol was applied on a real-world vehicle insurance claims dataset, including bootstrap 95% confidence intervals, McNemar’s test, a three-way ablation study comparing equal weighting, SWE, and validation-AUC weighting, F1-optimal threshold selection, expected calibration error, and cost-sensitive evaluation under asymmetric misclassification costs. The central finding is that SWE achieves performance statistically comparable to both simpler baselines across all evaluated metrics (ROC-AUC = 0.774, 95% CI [0.681, 0.862]; F1 = 0.679, 95% CI [0.569, 0.774]; McNemar p = 1.000), while producing a transparent, per-claim weighting trace that equal-weight voting cannot provide. A KernelSHAP influence analysis conducted directly on the SWE confirms that SHAP-derived weights are substantially aligned with actual model influence ratios (LR: 1.05×, LR_R: 1.05×, SVM: 0.81×), validating the weighting mechanism empirically. An exploratory analysis of a seven-model equal-weight diagnostic ensemble reveals a negative correlation (r = −0.721, p = 0.067) between individual model performance and ensemble influence; a theoretically coherent finding that does not reach statistical significance at conventional thresholds. The primary contribution of SWE is architectural and interpretability-driven: it produces an auditable, instance-level model-weighting mechanism grounded in SHAP attribution theory, supporting regulatory accountability under GDPR Article 22 and the EU AI Act. Full article

Firms are increasingly expected to pursue multiple sustainability priorities, but the implementation consequences of expanding sustainability agendas remain insufficiently understood. This study investigates whether and how sustainability overload reduces sustainability execution consistency. Drawing on the attention-based view and the corporate sustainability tensions perspective, the study proposes that a broad and simultaneous sustainability agenda exceeds managers’ attentional and coordination capacity, thereby weakening implementation coherence across departments. Specifically, the study hypothesizes that sustainability overload increases managerial attention strain, which in turn increases interunit priority divergence, ultimately reducing sustainability execution consistency. To test this sequential mechanism, a randomized experimental vignette study was conducted with 300 middle- and senior-level managers working in Türkiye-based firms operating in sustainability-exposed sectors. Participants were assigned to either a focused sustainability strategy condition or an overloaded sustainability strategy condition. The results support all proposed hypotheses. The overloaded condition increased managerial attention strain and interunit priority divergence, while reducing perceived sustainability execution consistency. PROCESS Model 6 analysis confirmed the sequential mediation mechanism. The findings suggest that sustainability implementation depends not only on the breadth of sustainability goals, but also on whether these goals are organized through a manageable priority architecture. The study contributes to sustainability strategy implementation research by highlighting managerial attention and cross-functional divergence as mechanisms linking sustainability overload to execution inconsistency. Full article

Background and Objectives: Tracheostomy is frequently performed in critically ill patients requiring prolonged invasive mechanical ventilation; however, factors associated with intermediate-term mortality after tracheostomy remain poorly characterized. This study aimed to identify clinical and procedural factors associated with 90-day all-cause mortality after tracheostomy in ICU patients. Materials and Methods: This retrospective multicenter cohort study included 292 adult patients who underwent tracheostomy in two tertiary ICUs between 1 October 2023 and 1 June 2025. Demographic characteristics, admission diagnoses, comorbidities, clinical severity scores, procedural variables, microbiological culture results, and survival data were collected. Univariate analyses, multivariable binary logistic regression, Cox proportional hazards regression, receiver operating characteristic (ROC) analysis, and Kaplan–Meier survival analysis were performed. Results: The overall 90-day all-cause mortality rate was 74.7%. Age, Charlson Comorbidity Index, and APACHE II score were significantly associated with 90-day mortality in univariate analyses, whereas tracheostomy timing and technique were not. In multivariable logistic regression analysis, the Charlson Comorbidity Index and APACHE II score were independently associated with mortality. Cox proportional hazards regression confirmed that both APACHE II score and Charlson Comorbidity Index were independently associated with mortality over time. ROC analysis demonstrated moderate discriminative performance for age, Charlson Comorbidity Index, and APACHE II score. Conclusions: In critically ill patients undergoing tracheostomy, 90-day mortality was high and was driven primarily by acute illness severity and comorbidity burden rather than procedural characteristics. These findings support incorporating biological vulnerability, expected recovery potential, and goals-of-care discussions into tracheostomy decision-making. Full article

Global climate change is causing an increase in extreme rainfall events, which impacts the risk of hydrometeorological disasters. To support disaster mitigation and early warning systems, accurate and reliable rainfall predictions are required. Although ensemble forecasting is widely used to model atmospheric uncertainty, raw ensemble results often exhibit insufficient bias and dispersion. Therefore, post-processing techniques are needed to improve the quality of probabilistic predictions. The most commonly used calibration method is Bayesian Model Averaging (BMA). This study conducted a scoping review of peer-reviewed papers on ensemble forecast calibration using BMA, based on the PRISMA-ScR framework. Furthermore, this study presents a comprehensive bibliometric analysis involving co-authorship networks of productive authors and bibliometric maps with clustered terms. A total of 35 relevant articles were identified from 49 screened publications. The bibliometric analysis revealed that “ensemble forecasting” and “Gaussian distribution” are the most dominant terms in the research network, indicating that Gaussian-based approaches remain more widely used in ensemble forecast calibration studies. In contrast, studies explicitly applying Gamma-based approaches are still relatively limited despite their relevance for modeling asymmetric rainfall data. The results obtained in this study highlight the importance of developing and integrating more appropriate probability distributions, such as those within the Extreme Value Theory framework, into BMA models. These findings suggest that the selection of appropriate probabilistic distributions in BMA-based calibration frameworks plays an important role in improving forecast reliability and the representation of uncertainty in rainfall prediction. Furthermore, the development of more suitable probability distributions, including Extreme Value Theory (EVT)-based distributions, has strong potential to enhance probabilistic calibration performance for asymmetric rainfall data. This approach is expected to improve the accuracy and reliability of extreme rainfall predictions. The findings of this study provide an important contribution to the development of early warning systems for hydrometeorological disasters and support the achievement of Sustainable Development Goals (SDGs). Full article