Search Results (2,088)

Linear speed is a key performance determinant in ice hockey, yet no studies have compared continuous on-ice and off-ice velocity profiles across multiple competitive levels. This study examined continuous velocity curves and discrete sprint variables during 20 m on-ice (skating) and off-ice (running) sprints across three competitive levels. Sixty male ice hockey players (A-Team n = 20, U20A n = 20, U20B n = 20) completed maximal 20 m sprints in both conditions using a motorized resistance device. Bayesian analyses were used to evaluate continuous velocity profiles and discrete variables. Posterior estimates consistently favored greater off-ice velocity profiles than on-ice velocity profiles across all groups, particularly during the early portion of the sprint (P(diff) ~85%), although the practical meaningfulness of these differences remained uncertain. Discrete sprint variables showed stronger and more consistent practically meaningful differences (P(diff > SWC) = 66–99%). Between-group comparisons suggested a competitive hierarchy, with posterior estimates favoring greater velocity values in adults than lower competitive-level late adolescents (P(diff) ~87%). Practitioners should consider potential differences between on-ice and off-ice sprint performance and hierarchical trends across competitive levels when structuring training and assessment. Continuous velocity profiling may provide additional insight into velocity-development patterns, whereas discrete metrics may be more appropriate for routine team-level monitoring. Full article

Safe-separation-and-collision-avoidance unmanned aerial vehicle (UAV) swarms are increasingly used for inspection, emergency response, environmental monitoring, and search-and-rescue support in cluttered airspace where communication links may be delayed, degraded, or intermittently unavailable. These applications require heterogeneous vehicles to maintain situational awareness, allocate tasks, and avoid hazards under partial observability and changing team topology. To address these challenges, this paper proposes a Hierarchical Graph-Attention Multi-Agent Reinforcement Learning architecture (HG-MARL) for safe-separation-and-collision-avoidance heterogeneous UAV swarm coordination. The proposed framework decomposes the task into high-level resource allocation and low-level local-control execution, uses graph attention for changing swarm topology, and applies Transformer memory, action masking, potential-field reward shaping, and domain-randomized simulation training. In the multi-scenario simulation summaries, HG-MARL achieves 92.9%, 89.8%, and 82.6% task success in Scenarios A–C, respectively, improving upon MAPPO by 15.1, 21.4, and 20.1 percentage points. Summary-statistic Welch tests show that all six HG-MARL comparisons against MAPPO and QMIX yield $p<0.01$ with large effect sizes. Fair-control, reward-sensitivity, communication-degradation, safety-ablation, training-stability, latency, and transfer-oriented stress tests further support the contributions of the integrated architecture. The validation scope is simulator-based, with platform-level flight/HIL evaluation discussed as future work. These results suggest that HG-MARL is a promising simulation-validated framework for civilian UAV swarm coordination in collision-and-separation-critical and communication-degraded environments. Full article

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 accumulation of training and competition loads represents a critical determinant of musculoskeletal injury risk in professional team sports, yet contemporary monitoring systems remain limited by their reliance on single-domain temporal analysis that overlooks the multi-scale rhythmic patterns inherent in athletic workload signals. This study introduces FDTM (frequency-aware dual-stream temporal model), a deep learning framework that jointly encodes time-domain dependencies and frequency-domain spectral signatures from digital athlete monitoring streams to predict individual injury risk over a forward-looking seven-game horizon. The framework integrates a stacked bidirectional long short-term memory branch augmented with temporal self-attention pooling, a spectral encoding branch employing discrete Fourier transform decomposition across high-frequency (weekly), mid-frequency (bi-weekly), and low-frequency (seasonal) bands, and a cross-modal gated attention fusion module that adaptively balances temporal and spectral representations conditioned on player context. We evaluate FDTM on three heterogeneous public sports datasets spanning basketball (NBA game-log corpus 2013–2023), Australian rules football (AFL Player Workload Dataset), and soccer (SoccerMon open monitoring corpus), comprising 612 athletes and 247,830 player-game observations across ten competitive seasons. FDTM achieves AUC-ROC values of 0.858, 0.833, and 0.821 on the three datasets respectively, outperforming the strongest deep-learning baseline (FEDformer) by 2.0 to 3.3 percentage points and the strongest non-spectral baseline (TCN) by 3.2 to 4.5 percentage points while maintaining a Brier score below 0.04. Ablation studies confirm that the spectral branch contributes 5.1 percent to overall discriminative performance. SHAP attribution analyses identify high-frequency weekly components as the dominant injury-relevant signal, followed by low-frequency seasonal trends and the cumulative acute-to-chronic workload temporal feature, with gating-weight visualizations revealing dynamic modality contributions consistent with established sports science theory. Direct spectral analysis of the raw workload signal confirms that injury-preceding windows exhibit significantly elevated weekly-band power across all three datasets (Mann–Whitney U test, p < 1 × 10⁻⁷), and the architectural advantage is shown to be robust across 30 independent training seeds. These findings suggest that frequency-aware modeling may serve as a transferable methodology for sports engineering applications in injury prevention, return-to-play planning, and individualized rehabilitation, pending further external validation in female athletes and additional team sports. Full article

The Canadian cancer care landscape faces rising cancer incidence, persistent inequities, and increasing system pressures. Led by the Canadian Association of Provincial Cancer Agencies (CAPCA), this scoping review applied an implementation science lens to evaluate the scalability of innovative cancer care models across Canada. Using a mixed-methods design, innovations were identified through a scoping review (n = 42), grey literature analysis (>50), a pan-Canadian survey (n = 72), and key informant interviews (n = 24). Guided by the Consolidated Framework for Implementation Research (CFIR), this review assessed feasibility, barriers, and facilitators influencing adoption and scale-up of identified innovations. Results revealed widespread adoption across various domains including virtual oncology, artificial intelligence (AI)-driven tools, and expansion of team-based care. At-home models, including home infusion, palliative care, and pharmacist-led chronic disease clinics, demonstrated improved access, patient satisfaction, and reduced hospital burden. CFIR mapping revealed cross-cutting facilitators including strong stakeholder engagement, structured training, and demonstrated patient benefits. However, persistent barriers include regulatory variability, funding instability, digital infrastructure gaps, and workforce capacity constraints. This paper highlights implemented innovations in cancer care and identifies strategic scaling opportunities needed to ensure all people living in Canada benefit from high-quality, person-centred equitable cancer care. Full article

Background: Chemsex, or sexualized drug use, exists along a continuum ranging from non-problematic, consensual recreational practice across diverse populations to problematic behaviors linked with clinical vulnerabilities, substance dependence, or compulsive disorders. Within nursing practice, understanding this spectrum is essential to mitigate healthcare-related stigma. Objective: To map and synthesize evidence on stigma and attitudes among nurses regarding chemsex, identifying implications for practice and research. Methods: A scoping review was conducted following the Joanna Briggs Institute methodology and PRISMA-ScR guidelines. Searches were performed across PubMed/MEDLINE, Scopus, Web of Science, CINAHL, EMBASE, and LILACS. Studies involving nurses or healthcare teams focused on stigma, attitudes, or related constructs in chemsex care were included. Data underwent descriptive and thematic synthesis. Results: Six studies met the inclusion criteria, showing substantial heterogeneity. Only one focused exclusively on nurses. Stigma and attitudes were rarely assessed explicitly, emerging instead as underlying factors influencing clinical practice, communication, and patient engagement. Key themes included the necessity for non-judgmental care, significant gaps in knowledge and training, variability in clinical practice, and the impact of organizational barriers. A schematic representation was developed to illustrate the interrelationships between stigma, knowledge, professional attitudes, and structural factors influencing healthcare practice. Conclusions: This review positions stigma as a central mechanism influencing nursing care in chemsex contexts. The findings underscore critical gaps in nursing-specific evidence and emphasize the need for targeted training, validated measurement tools, and integrated care models. Strengthening stigma-informed, patient-centered approaches is essential to improve care delivery and health outcomes for this population. Full article

Background: Rink Hockey is a high-intensity contact sport with growing participation in Portugal, yet epidemiological data on injuries among senior and under-23 practitioners remain scarce. This study aimed to retrospectively describe self-reported injury occurrence, injury characteristics, and potential associations with demographic and sport-related variables among Portuguese Rink Hockey athletes. Methods: A retrospective, cross-sectional, self-reported e-survey was conducted among federated Portuguese Rink Hockey practitioners (under-23 and senior categories) during the 2024/2025 season. The questionnaire included 53 closed-ended items on sociodemographics, sport participation, equipment, training loads, and injury history. Injury prevalence, incidence rate, mean injuries per athlete, and associations were analyzed. Results: Among 181 respondents (68.5% male; age 22.3 ± 4.3 years; experience 15.8 ± 5.0 years), 89 (49.2%) reported at least one injury (mean 2.6 ± 2.7 injuries/athlete in the total sample; 3.3 ± 3.1 per injured athlete). Estimated incidence was 3.9 ± 5.9 injuries/1000 h (total sample) and 7.9 ± 6.2/1000 h (injured athletes). The knee (19.1%) was the most common injury localization, and muscular injuries (25.8%) were the most frequent type. Most injuries occurred during matches (46.0%), with contact with another player (27.0%) during offensive transition (40.4%) in areas surrounding the goal (57.3%) being the most frequently reported circumstances. Older and female athletes reported a higher injury prevalence than younger and males counterparts (66.7% vs. 33.3% [p = 0.042; ES = 0.174] and 61.4% vs. 43.5% [p = 0.026; ES = 0.166], respectively). Injury occurrence was positively associated with age (r = 0.262–0.158, p ≤ 0.05) and playing experience (r = 0.157, p ≤ 0.05). However, greater playing experience was associated with lower odds of joint injury (11–15 years: OR = 0.116, 95% CI [0.019; 0.695], p = 0.018; 16–19 years: OR = 0.116, 95% CI [0.019; 0.695], p = 0.018; and ≥20 years: OR = 0.056, 95% CI [0.006; 0.534], p = 0.012). Conclusions: Portuguese Rink Hockey practitioners exhibit a high injury burden, predominantly affecting the knee, with muscle injuries and contact/overuse mechanisms as major contributors. Age, sex, and experience were associated with injury occurrence. These findings may support the incorporation of targeted prevention strategies into multidisciplinary support teams. Full article

Background: Sexuality education is essential for adolescent health and well-being, yet in Italy it is not included in a mandatory national curriculum, resulting in heterogeneous implementation across regions. Within the ESPRIT project, a multidisciplinary training-of-trainers (ToT) model was developed to prepare professionals to support school-based peer-education pathways. This study aimed to describe the training model and perform a pilot evaluation of short-term knowledge outcomes among trained participants. Methods: A pilot non-randomized controlled comparative study was conducted within the ESPRIT project framework. A multidisciplinary Training Team developed a structured ToT pathway based on WHO guidance, national recommendations, and peer-education models. Ten advanced public health residents in Hygiene and Preventive Medicine attended a three-day residential training course. One month later, a 10-item knowledge questionnaire was administered to trained participants (n = 10) and untrained advanced public health residents (n = 10). Results: Trained participants achieved higher questionnaire scores than the comparator group (median score 8 [IQR 2] vs. 3.5 [IQR 2]; p < 0.0005). Conclusions: Structured ToT programmes may represent a promising approach for strengthening professional preparation in sexuality education. Larger studies with longer follow-up are needed to evaluate sustainability and real-world implementation. Full article

Background: Competitive sports represent a powerful physiological and psychological stressor capable of modulating neuroendocrine and immune pathways. Water polo, characterized by intense intermittent exertion and frequent physical contact, provides a unique model to investigate competition-related stress biology. Methods: Sixteen male Italian Serie C water polo players were enrolled in the study. Using a within-subject design, saliva samples were collected under controlled circadian conditions. Salivary biomarkers, including cortisol, IgA, and cytokines, were assessed both before and after training sessions and competitive matches. Results: Both training and competition elicited POST-session increases in salivary cortisol and cytokines, alongside reductions in IgA. However, competition produced significantly higher anticipatory and POST-session cortisol concentrations. A larger POST-session decreases in IgA compared with training was observed. Cytokine concentrations increased from PRE- to POST-session in both conditions, with significantly greater induction during competition across the panel. During training, selected cytokines showed positive within-session correlations with cortisol, indicating coordinated hypothalamic–pituitary–adrenal–immune activation under lower psychosocial load. These associations were attenuated and less consistent during competition. Conclusions: Official competition amplifies endocrine and immune responses beyond those observed during match-like training in elite water polo players, despite comparable physical demands. Altered cytokine–cortisol coupling under competitive conditions suggests modulation of neuroendocrine–immune integration by psychosocial stress. Combined salivary profiling of cortisol, cytokines, and IgA represents a feasible, non-invasive approach for monitoring psychophysiological load in elite aquatic team sports. Full article

This study investigates the linguistic mechanisms of politeness and conversational implicature in digital classroom interactions at “1 Decembrie 1918” University of Alba Iulia (UAB), Romania. Rather the research adopts a corpus-based approach to analyze five authentic communicative situations extracted from institutional digital platforms (Moodle (version 4.3.2; R Core Team, 2023), Microsoft Teams, and institutional email exchanges) between academic staff and students during 2022–2024. The corpus comprises 247 naturally occurring discourse units. Through qualitative and quantitative analysis, the study identifies recurrent patterns of face-threatening acts (FTAs), mitigation strategies, and implicature generation in asynchronous and synchronous digital contexts. The findings reveal that digital mediation creates a distinctive pragmatic register in which participants use compressed politeness strategies, exploit contextual ambiguity, and rely on shared institutional knowledge to convey and decode implicature. Crucially, the study situates its results within the broader framework of the Romanian higher education system, reflecting ongoing tensions between hierarchical academic culture and digitalization imperatives introduced in the post-pandemic educational environment. Recommendations for digital communication literacy training at an institutional level are provided. Full article

This study presents a decentralized shared actor–critic framework for cooperative multi-robot coverage in continuous two-dimensional simulation. The method combines permutation-invariant local observations, continuous differential-drive control, and reward shaping based on stepwise Hungarian assignment distances, collision penalties, and time efficiency. Homogeneous teams of four, five, and six agents are evaluated in an obstacle-free environment using five independent training seeds. In the final training window, the full reward configuration achieved full-team success rates of 98.2 ± 2.9% for four agents, 85.1 ± 18.0% for five agents, and 96.3 ± 2.0% for six agents, with mean landmark coverage above 96% in all cases. The lower mean in the five-agent setting was associated with higher seed-level variability dominated by one low-success seed. Reward ablations without assignment shaping or collision penalties remained viable, and seed-level tests did not show a statistically significant final-window advantage of the full reward configuration. The full configuration reached the 80% rolling-success threshold earlier in median terms, with the clearest seed-level support in the four-agent setting. Within-environment comparison showed higher full-team success than MADDPG and MAPPO under the matched training horizon and final-window protocol. Deterministic arena-size transfer from $15\times 15$ to $30\times 30$ showed decreasing full-team success as arena size increased, while partial landmark coverage remained higher than strict full-team completion. The results support the method for small homogeneous teams in the tested obstacle-free simulation, while larger teams, external obstacles, aerial-robot dynamics, formal safety guarantees, and hardware deployment remain future work. Full article

The impact of the built environment on physical and mental health and wellbeing has been evidenced worldwide. Quality and design affect residents’ wellbeing and physical and mental health outcomes. A local authority planning team in London introduced new guidance to improve the quality of amenity space within residential developments. This paper aims to evaluate the early implementation of this guidance using Normalisation Process Theory. A qualitative design was employed using semi-structured interviews (n = 34), with a purposive sample of planning staff, applicants, review panel members and organisers and elected officials. Framework analysis was undertaken. All stakeholders perceived the introduction of the new amenity space guidance positively, but views of the planning officer training that accompanied it were more nuanced. Key factors influencing implementation included attitude towards and understanding of the new guidance, use of common language, workload, number of policy and guidance documents and a lack of a guidance template from the beginning. Further contextual barriers included the need for economic viability for developers and affordable housing in the area. To further embed and sustain implementation, it is recommended that the guidance continues to be used in a flexible manner with ongoing training and focused support for both planning officers and planning applicants. Full article

Objectives: Local positioning systems (LPSs) used in indoor team sports generate a large number of external load variables, often exceeding practical monitoring capacity. The redundancy and overlap among these variables make it difficult to identify the most informative metrics for performance analysis and load management. This study aimed to reduce the dimensionality of external load variables derived from LPS data and to identify data-driven external-load observation profiles using principal component analysis and clustering techniques. Methods: A total of 188 observations from indoor team sports (basketball, handball, and futsal) were analyzed. Continuous external load variables were standardized and subjected to principal component analysis (PCA), with component retention based on a ≥90% cumulative explained variance threshold. K-means clustering was applied in both the full standardized feature space and the PCA-reduced space. The optimal number of clusters was determined using silhouette analysis and the elbow method. Agreement between clustering solutions was assessed using Adjusted Rand Index (ARI) and Normalized Mutual Information (NMI). Cluster characteristics were further examined using descriptive statistics and variable separation analysis. Results: The first two principal components explained 53.7% of the total variance, representing high-intensity external load and neuromuscular load dimensions, while 12 components were required to exceed 90% cumulative explained variance. Clustering analysis consistently identified three moderately separated clusters in both the full and PCA-reduced spaces. The PCA-based solution demonstrated improved separation (silhouette = 0.362) compared to the full-space solution (silhouette = 0.319). Agreement between clustering approaches was high (ARI = 0.981; NMI = 0.971), indicating that dimensionality reduction largely preserved the main clustering structure within the analyzed dataset. The most discriminative variables included jump load, acceleration load, metabolic power, and anaerobic activity distance. Conclusions: A large set of external load variables can be reduced into interpretable latent dimensions that support exploratory external-load profile identification. The combination of PCA and clustering provides an exploratory and structure-preserving framework for summarizing complex external-load datasets and identifying latent load dimensions. These findings may assist future monitoring strategies; however, the practical utility of the identified profiles requires prospective validation before implementation in training-load management. Full article

Maintenance management increasingly depends on effective information flow and coordination between internal teams and external service providers. This study investigates the use of Business Process Model and Notation (BPMN) to support the formalization of Computerized Maintenance Management System (CMMS) workflows and improve transparency, decision-making, and interorganizational coordination. A single case study was conducted in the maintenance department of an electricity distribution company characterized by tacit knowledge, informal communication practices, and limited process formalization. Existing corrective maintenance workflows were analyzed and modeled using BPMN to identify inefficiencies, decision points, and opportunities for improvement. The proposed BPMN models were aligned with CMMS operational states associated with anomaly management and work-order execution processes and supported by a procedural manual. Results obtained during a three-month observation period suggest reductions in training time, email communications, and dependence on individual decision-makers, together with increased use of CMMS workflow functionalities and improved process traceability. These findings provide preliminary evidence, derived from operational indicators within a single case study, that BPMN-supported process formalization may contribute to workflow standardization, operational clarity, and knowledge management in maintenance-intensive environments. Given the single-case design and limited observation period, the results should be interpreted as context-specific and not directly generalizable to the broader energy sector. Full article

Background/Objectives: The Observational Clinical Human Reliability Assessment (OCHRA) system evaluates surgical performance by identifying intraoperative errors, yet evidence on error patterns and procedural safety in laparoscopic cholecystectomy (LC) remains limited. This study aimed to assess LC safety using established parameters and to describe intraoperative errors through the OCHRA system in patients with gallstone disease in Veracruz, Mexico. Methods: An observational, retrospective, analytical study was conducted between January 2022 and March 2025. Surgical videos from 11 surgical teams were reviewed. Intraoperative errors were classified using the OCHRA system across the three key steps of LC, while procedural safety was assessed through achievement of the Critical View of Safety (CVS) using the Doublet Photographic Score (DPS). Comparisons were performed according to the Parkland Grading Scale. Statistical analysis was conducted using SPSS version 26. Results: A total of 106 patients were included (67% women; mean age 45 ± 13 years; BMI 25.1 ± 3.2 kg/m²). Total LC was performed in 95% of cases and subtotal LC in 5%. Parkland grade 3 was the most frequent (32.1%). Overall, 3180 operative steps were evaluated, and 705 errors (22.1%) were identified. Procedural errors predominated across all phases (97–99%), mainly due to step repetition or additional steps, whereas execution errors were uncommon (1–3%). A satisfactory CVS was achieved in 54.7% of cases. No bile duct injuries were observed. Conclusions: The OCHRA system enabled detailed the identification of intraoperative error patterns and their relationship with surgical difficulty. Higher anatomical severity was associated with increased procedural errors and lower rates of adequate CVS achievement. These findings support structured video-based performance assessment as a complementary tool to established safety principles, with the potential to guide targeted training and improve surgical consistency in laparoscopic cholecystectomy. Full article