Search Results (1,493)

Objectives: SailGP is an international professional mixed-sex sailing competition, which uses F50 foiling catamarans capable of reaching speeds up to ~100 km/h. This seminal study assesses injuries and illnesses observed by male and female sailors during trainings and competitions in SailGP’s third season. This study aims to assess injury and illness incidence, comparing results with other professional sailing events and high-performance sports. In addition, injury and illness risk factors (sex and position) will be explored with the goal to reduce morbidity for future seasons. Materials and Methods: This retrospective cohort design analysed medical records of male and female sailors during SailGP’s third season (April 2022 to May 2023). Risk factors assessed included sailor sex, sailor position (helm, strategist, grinder, flight controller and wing trimmer), sailing venue, wind speed and mechanism of injury/nature of illness. International Olympic Committee reporting guidelines on injuries and illnesses were followed, including the STROBE-SIIS checklist. Confidence intervals were set at 95%, statistical tests were two-sided and p-values < 0.05 were considered statistically significant. Results: A total of 40 on-water injuries were reported in 32 athletes. Injury incidence was greater during competitions than trainings, with strategists and then grinders being the most frequently injured positions. Competition injury incidence was 32.6 per 1000 h and 6.42 injuries per 365 days. Training injury incidence was 2.62 injuries per 1000 h and 3.82 injuries per 365 days. Knee, ankle, hand and head injuries were most prevalent, with three concussions observed during trainings and competitions (two female and one male). Direct impacts and falls during manoeuvres caused most injuries. Overall injury incidence (IRR = 2.69 [95% CI 1.41–5.16]), risk of training injuries (RR = 3.75 [95% CI 1.59–8.83], p = 0.001), risk of competition injuries (RR = 1.79 [95% CI 0.65–4.90], p = 0.25) and overall concussion risk (RR = 10.04 [95% CI 0.91–110.46], p = 0.02) were greater in females. Ten sailors accounted for 17 illnesses. Females had a 3.33 increase in training and competition illnesses (IRR = 3.33 [95% CI 0.94–11.81]). Conclusions: Competition injury incidence was higher than previous reported sailing studies. Knee injuries were most prevalent and direct impacts caused most injuries. Female sailors reported a higher injury and illness incidence. These results may guide injury prevention efforts and the development of an IOC-equivalent consensus statement. Future studies should examine time loss. Full article

With buildings accounting for 40% of global energy consumption, heating, ventilation, and air conditioning (HVAC) systems represent the single largest opportunity for emissions reduction, consuming up to 60% of commercial building energy while maintaining occupant comfort. This critical balance between energy efficiency and human comfort has traditionally relied on rule-based and model predictive control strategies. Given the multi-objective nature and complexity of modern HVAC systems, these approaches fall short in satisfying both objectives. Recently, reinforcement learning (RL) has emerged as a method capable of learning optimal control policies directly from system interactions without requiring explicit models. However, standard RL approaches frequently violate comfort constraints during exploration, making them unsuitable for real-world deployment where occupant comfort cannot be compromised. This paper addresses two fundamental challenges in HVAC control: the difficulty of constrained optimization in RL and the challenge of defining appropriate comfort constraints across diverse conditions. We adopt a safe RL with a neural barrier certificate framework that (1) transforms the constrained HVAC problem into an unconstrained optimization and (2) constructs these certificates in a data-driven manner using neural networks, adapting to building-specific comfort patterns without manual threshold setting. This approach enables the agent to almost guarantee solutions that improve energy efficiency and ensure defined comfort limits. We validate our approach through seven experiments spanning residential and commercial buildings, from single-zone heat pump control to five-zone variable air volume (VAV) systems. Our safe RL framework achieves energy reduction compared to baseline operation while maintaining higher comfort compliance than unconstrained RL. The data-driven barrier construction discovers building-specific comfort patterns, enabling context-aware optimization impossible with fixed thresholds. While neural approximation prevents absolute safety guarantees, reducing catastrophic safety failures compared to unconstrained RL while maintaining adaptability positions this approach as a developmental bridge between RL theory and real-world building automation, though the considerable gap in both safety and energy performance relative to rule-based control indicates the method requires substantial improvement for practical deployment. Full article

Introduction: Concussions are a growing concern in professional football due to their potential short- and long-term neurological consequences. Despite increasing global awareness, data on the epidemiology and clinical management of concussions in Portuguese football remain scarce. This preliminary exploratory study aimed to characterize the incidence, mechanisms, symptomatology, and medical response to concussions in Portugal’s Professional Football Leagues during the 2023/2024 season, based on reported cases. Methods: A retrospective observational analysis was conducted on head injuries reported by club medical teams during official matches in Liga Portugal First and Second Leagues. Collected variables included player position, time of injury, mechanism, symptoms, medical interventions and hospital referral. Results: Only six concussions were reported during official matches, with an overall incidence of 0.60 per 1000 player-hours. Most occurred in defenders, primarily due to head-to-head collisions, followed by ball impact, falls, and maxillofacial trauma. Injuries were more frequent during the final third of matches. Common symptoms included loss of consciousness, headache, and amnesia. Half of the players were referred to hospital care and underwent cranial CT scans. Among all variables analyzed, a statistically significant association was found between mechanism of injury and occurrence of amnesia (p = 0.014), with non-head-to-head impacts more frequently associated with amnesia. However, given the extremely limited sample size, this finding should be interpreted with extreme caution and requires replication in larger cohorts. Conclusions: This preliminary study suggests that defenders face a higher risk of head injuries, particularly from head-to-head impacts occurring late in matches. The prevalence of severe symptoms and the potential association between non-head-to-head impacts and amnesia highlight the need for more robust injury surveillance systems and underscore the importance of improved sideline assessment and return-to-play protocols. The findings emphasize the urgent need for comprehensive, standardized reporting mechanisms for concussions. Further research should explore long-term neurological effects and the effectiveness of preventive measures such as rule modifications, protective measures, and enhanced concussion management protocols, supported by more extensive and systematically collected data. Full article

Background and Objectives: Distal upper limb injuries are frequent in winter sports, but their functional impact is often underestimated. This study aimed to describe the epidemiology, mechanisms, and risk factors for injuries involving the forearm, wrist, hand, and fingers sustained during two consecutive winter seasons in the Italian Dolomites. Materials and Methods: All adult and willing patients presenting to the Emergency Department of Brixen Hospital after ski- or snowboard-related accidents between December 2023 and March 2025 completed a standardized 23-item questionnaire on demographics, experience level, environmental factors, equipment, and trauma mechanism. For the aim of this study only distal upper limb injuries were extracted and analyzed. Statistical analyses compared fracture versus non-fracture injuries, “good” versus “bad” fractures (AO classification and surgical complexity), and isolated ulnar collateral ligament (UCL) injuries. Results: A total of 195 patients were analyzed: 96 (49.2%) sustained a fracture and 33 (16.9%) presented with isolated UCL lesions. Fractures occurred more frequently on blue slopes (56.2% vs. 33.3%, p < 0.001), whereas non-fracture injuries predominated on red and off-piste slopes. Age, BMI, and skill level did not differ significantly between groups. Surgically classified complex distal forearm fractures were significantly more frequent in females (p < 0.005) but were not associated with environmental factors. UCL injuries occurred mainly on red slopes (54.5%) and were often related to pole entrapment during falls. None of the injured patients reported the use of protective wrist or thumb supports. Conclusions: Distal upper limb injuries are a common pattern of alpine sports trauma, with wrist fractures and skier’s thumb being predominant lesions. Low-speed falls on easy slopes are associated with wrist fractures, while UCL injuries are linked to intermediate slopes. Preventive strategies should include fall technique education, protective gloves, and improved pole ergonomics. Full article

The demand for higher data rates and energy efficiency in wireless communication systems drives power amplifiers (PAs) into nonlinear operation, causing signal distortions that hinder performance. Digital Pre-Distortion (DPD) addresses these distortions, but existing systems face challenges with complexity, adaptability, and resource limitations. This paper introduces DRL-DPD, a Deep Reinforcement Learning-based solution for DPD that aims to reduce computational burden, improve adaptation to dynamic environments, and minimize resource consumption. To ensure safety and regulatory compliance, we integrate an ad-hoc Safe Reinforcement Learning algorithm, CRE-DDPG (Cautious-Recoverable-Exploration Deep Deterministic Policy Gradient), which prevents ACLR measurements from falling below safety thresholds. Simulations and hardware experiments demonstrate the potential of DRL-DPD with CRE-DDPG to surpass current DPD limitations in both local and remote configurations, paving the way for more efficient communication systems, especially in the context of 5G and beyond. Full article

This paper introduces the Gesture-Based Physical Stability Classification and Rehabilitation System (GPSCRS), a low-cost, non-invasive solution for evaluating physical stability using an Arduino microcontroller and the DFRobot Gesture and Touch sensor. The system quantifies movement smoothness, consistency, and speed by analyzing “up” and “down” hand gestures over a fixed period, generating a Physical Stability Index (PSI) as a single metric to represent an individual’s stability. The system focuses on a temporal analysis of gesture patterns while incorporating placeholders for speed scores to demonstrate its potential for a comprehensive stability assessment. The performance of various machine learning and deep learning models for gesture-based classification is evaluated, with neural network architectures such as Transformer, CNN, and KAN achieving perfect scores in recall, accuracy, precision, and F1-score. Traditional machine learning models such as XGBoost show strong results, offering a balance between computational efficiency and accuracy. The choice of model depends on specific application requirements, including real-time constraints and available resources. The preliminary experimental results indicate that the proposed GPSCRS can effectively detect changes in stability under real-time conditions, highlighting its potential for use in remote health monitoring, fall prevention, and rehabilitation scenarios. By providing a quantitative measure of stability, the system enables early risk identification and supports tailored interventions for improved mobility and quality of life. Full article

Background/Objectives: Breastfeeding is the best source of food for newborns. Leading health organizations recommend exclusive breastfeeding for the first 6 months of life, followed by the gradual introduction of complementary foods. Evidence shows that breastfeeding offers numerous benefits for newborns, mothers, society as a whole, and the environment. Current breastfeeding rates fall below the established recommendations. This study aims to describe breastfeeding rates at hospital discharge and one month postpartum, analyze fluctuations in feeding types during this period, and identify any characteristics, preventive factors, and barriers to breastfeeding and mixed feeding. Methods: This is a multicenter observational study in the North Metropolitan area of Barcelona, with 411 participants surveyed by midwives. Results: In total, 79% of women were exclusively breastfeeding, 14% practiced mixed breastfeeding, and 7% used formula feeding at hospital discharge. At one month postpartum, these rates fluctuated to 64%, 23%, and 13%, respectively. Factors such as older age, having a university education, having 16 weeks of parental leave, and having a foreign-born status were positively associated with exclusive breastfeeding, while mental illness was associated with a lower prevalence. The use of breastfeeding accessories was not significantly associated with fluctuations in feeding type, but it was associated with maintaining mixed feeding. Conclusions: It is essential to implement individual and community interventions, educate healthcare professionals on factors that hinder breastfeeding, and promote workplace policies that support breastfeeding. Full article

By critically reviewing pseudo-static methods, it is demonstrated that approximating the earth pressure on a short heel’s vertical face (V-plane) using the Rankine solution for long-heel walls induces a negligible error. A finite element analysis is deployed to validate the pseudo-static results, with dynamic simulations incorporating 1–5 Hz sinusoidal seismic excitations to probe the resonance effects. The key results show that disregarding the impact of layered backfill placement on the initial stress states leads to non-conservative estimates of active earth pressure. Furthermore, the point of application of earth pressure rises significantly during strong shaking, and although the transient safety factors against sliding and overturning may fall below 1.0 during seismic events, the residual deformation analysis suggests that this does not necessarily lead to collapse. A significant amplification of bending moments and greater reductions in post-earthquake safety factors occur when the input frequency approaches the natural frequency of a wall. Finally, the paper proposes resonance prevention strategies for the seismic design of cantilever retaining walls, a methodology incorporating construction effects into the initial stress field modeling, and recommendations for selecting effective safety factors. Full article

Rice is one of the most important staple foods for the human population, necessitating continuous monitoring for mycotoxin risk in particular in the sub-tropical area, such as India. In the present study, a total of eighty-one samples comprising brown (n = 36) and polished (white) rice (n = 45) intended for direct human consumption were collected from markets across various districts of Tamil Nadu, India, and analysed for ochratoxin A (OTA) and fungal contamination. Aspergillus ochraceus, an ochratoxigenic fungus belonging to Aspergillus section Circumdati, exhibits optimal growth and OTA production at temperatures ranging from 25 °C to 30 °C. Among the fungal isolates, Aspergillus niger and A. ochraceus were the most prevalent, occurring in 50 out of 81 samples (62%). A. ochraceus demonstrated a significantly higher OTA-producing capacity compared to A. niger, with an OTA concentration range of 12.3–196.8 µg/kg and 0.2–2.8 µg/kg. Chemical analysis of fifty fungal-contaminated market rice samples revealed that 76% (38/50) were contaminated with OTA. Further, detectable levels of OTA were observed in 83% of brown rice and 69% of polished rice samples, with the highest frequency falling within the range of 1–<3 µg/kg. However, none of the tested rice samples exceeded the acceptable OTA threshold set by the Food Safety and Standards Authority of India (FSSAI) (20 µg/kg), with all concentrations falling below the national regulatory limit. This study represents further insight into OTA exposure in rice, with greater concern regarding brown rice than white rice, and emphasizes the necessity of implementing sound and safe storage practices, effective management strategies, and continuous monitoring programs to prevent OTA contamination throughout the Indian rice supply chain. Full article

Background: Seafarers are highly susceptible to work-related injuries, which can result in serious consequences or permanent disabilities. Understanding the frequency and characteristics of occupational injuries is crucial for developing effective prevention strategies and identifying their underlying patterns and causes. This study aimed to determine the frequency and characteristics of telemedicine-assisted work-related injuries among seafarers on board Italian-flagged vessels. Methods: A retrospective descriptive study was conducted to analyze occupational injuries using medical data recorded in the Centro Internazionale Radio Medico (C.I.R.M.) database from 1 January 2010 to 31 December 2022. Injuries in the database were coded according to the 10th revision of the International Classification of Diseases (ICD-10) by the World Health Organization (WHO). Variables extracted from the database included injury type, seafarers’ age, rank, nationality, worksite, gender, date of injury, affected body region, clinical outcomes, and other demographic and occupational characteristics. Injury frequency and characteristics (e.g., location, type, and cause) were analyzed and stratified by seafarers’ rank and worksite groups. Results: The analysis included 793 seafarers who sustained injuries. Their average age was 39.15 ± 10.49 years (range: 21 to 70 years). Deck ratings and engine officers accounted for 27.9% and 20% of those who claimed injuries, respectively. 39.2% of injured seafarers were aged between 30 and 40 years. In terms of affected body parts, the most reported injuries were to the hand/wrist (33.3%), followed by the knee/lower legs (21%), and the head/eye (19%). Open wounds (38%) and burns/abrasions (14%) were the most common types of injury. Slips/falls (32%), burns/explosions (16.6%), and overexertion while lifting or carrying (14.8%) were the leading causes of injury during the study period. Nearly 35% of injuries affected workers on the deck and were due mainly to slips/falls, 19% in the engine room were due to being caught in machinery or equipment, and 32.5% in the catering department were due to burns/explosions. Conclusions: One-third of seafarers who suffered work-related injuries sustained hand and/or wrist injuries, with slips/falls being a significant cause. The results of this study emphasize the need for preventative measures in the marine sector, particularly to reduce risks associated with slips and falls, overexertion, and other injury-causing factors. Campaigns for the larger use of protective equipment are desirable to reduce occupational accidents at sea and provide better health protection for seafarers. Full article

In recent years, the synergistic effect among production, maintenance, and quality control within manufacturing systems has garnered increasing attention in academic and industrial circles. In high-quality production settings, the real-time identification of minute process deviations holds significant importance for ensuring product quality. Traditional approaches, such as routine quality inspections or Shewhart control charts, exhibit limitations in sensitivity and response speed, rendering them inadequate for meeting the stringent requirements of high-precision quality control. To address this issue, this paper presents an integrated framework that seamlessly integrates stochastic process modeling, dynamic optimization, and quality monitoring. In the realm of quality monitoring, an exponentially weighted moving average (EWMA) control chart is employed to monitor the production process. The statistic derived from this chart forms a Markov process, enabling it to more acutely detect minor shifts in the process mean. Regarding maintenance strategies, a state-dependent preventive maintenance (PM) and corrective maintenance (CM) mechanism is introduced. Specifically, preventive maintenance is initiated when the system is in a statistically controlled state and the inventory level falls below a predefined threshold. Conversely, corrective maintenance is triggered when the EWMA control chart generates an out-of-control (OOC) signal. To facilitate continuous production during maintenance activities, an inventory buffer mechanism is incorporated into the model. Building upon this foundation, a joint optimization model is formulated, with system states, including equipment degradation state, inventory level, and quality state, serving as decision variables and the minimization of the expected total cost (ETC) per unit time as the objective. This problem is formalized as a constrained dynamic optimization problem and is solved using the genetic algorithm (GA). Finally, through a case study of the production process of vibroseis equipment, the superiority of the proposed model in terms of cost savings and system performance enhancement is empirically verified. Full article

Same-level-falls (SLFs) and falls-from-height (FFHs) remain major causes of severe injuries and fatalities on construction sites. Researchers are actively developing fall-prevention systems requiring accurate SLF and FFH detection in construction settings prone to false positives. In this study, a machine learning-based approach was established for accurate identification of SLF, FFH, and non-fall events using a single waist-mounted inertial measurement unit (IMU). A total of 48 participants executed 39 non-fall activities, 10 types of SLFs, and 8 types of FFHs, with a dummy used for falls exceeding 0.5 m. A two-stage feature extraction yielded 168 descriptors per data window, and an ensemble SHAP-PFI method selected the 153 most informative variables. The weighted XGBoost classifier, optimized via Bayesian techniques, outperformed other current boosting algorithms. Using 5-fold cross-validation, it achieved an average macro F1-score of 0.901 and macro Matthews correlation coefficient of 0.869, with a latency of 1.51 × 10⁻³ ms per window. Notably, the average lead times were 402 ms for SLFs and 640 ms for FFHs, surpassing the 130 ms inflation time required for wearable airbags. This pre-impact SLF and FFH detection approach delivers both rapid and precise detection, positioning it as a viable central component for wearable fall-prevention devices in fast-paced construction scenarios. Full article

The west coast of Korea is characterized by a macro-tidal environment, where beach exposure varies significantly with tidal levels, resulting in high spatial variability of beach width and erosion patterns. This study aims to establish an Erosion Control Line (ECL) for Mallipo Beach using long-term beach topographic data collected from 2009 to 2020. For each transect, beach width was statistically estimated for a 30-year return period by calculating the average and standard deviation of surveyed widths and applying the inverse function of the normal cumulative distribution. The variability of shoreline positions was analyzed as an indicator of shoreline sensitivity, allowing the identification of highly vulnerable sections. Based on these analyses, the ECL was derived for three tidal reference levels—Highest Water of Medium Tide (H.W.O.M.T), Highest Water of Neap Tide (H.W.O.N.T), and Mean Sea Level (M.S.L)—according to Korea Hydrographic and Oceanographic Agency (KHOA)’s tidal datums. When the H.W.O.N.T-based beach width was used to define the Target shoreLimit of Erosion Prevention (TLEP), several public facilities were found to fall within the erosion hazard zone. These findings underscore the need for institutionalized coastal setback policies in Korea and highlight the practical value of the proposed ECL method for managing erosion-prone zones. Full article

Unsupervised representation learning has emerged as a promising paradigm in machine learning, owing to its capacity to extract semantically meaningful features from unlabeled data. Despite recent progress, however, such methods remain vulnerable to collapse phenomena, wherein the expressiveness and diversity of learned representations are severely degraded. This phenomenon poses significant challenges to both model performance and generalizability. This paper presents a systematic investigation into two distinct forms of collapse: complete collapse and dimensional collapse. Complete collapse typically arises in non-contrastive frameworks, where all learned representations converge to trivial constants, thereby rendering the learned feature space non-informative. While contrastive learning has been introduced as a principled remedy, recent empirical findings indicate that it falls to prevent collapse entirely. In particular, contrastive methods are still susceptible to dimensional collapse, where representations are confined to a narrow subspace, thus restricting both the information content and effective dimensionality. To address these concerns, we conduct a comprehensive literature analysis encompassing theoretical definitions, underlying causes, and mitigation strategies for each collapse type. We further categorize recent approaches to collapse prevention, including feature decorrelation techniques, eigenvalue distribution regularization, and batch-level statistical constraints, and assess their effectiveness through a comparative framework. This work aims to establish a unified conceptual foundation for understanding collapse in unsupervised learning and to guide the design of more robust representation learning algorithms. Full article

Background: Falls are a leading cause of morbidity and loss of independence among older adults, and occupational therapy (OT) offers a unique, multidimensional approach to fall prevention. This systematic review evaluates the effectiveness of OT-based interventions for improving balance, mobility, functional performance, and psychological outcomes related to fall risk in older adults. Methods: This review followed PRISMA (2020) guidelines. A comprehensive search of PubMed, Scopus, Dialnet, and OTseeker was conducted from March to May 2025. The inclusion criteria targeted studies involving non-pharmacological, OT-led interventions in adults aged ≥65. Seventeen studies were selected, including randomized controlled trials, pilot studies, and quasi-experimental designs. The data extraction and quality appraisal were performed independently by two reviewers. Results: The included interventions varied among exercise-based programs (e.g., Tai Chi, Pilates), virtual reality training, home safety modifications, cognitive–behavioral therapy, and wearable technologies. Most of the studies reported significant improvements in postural balance, fear of falling, and functional independence. Environmental adaptations and educational strategies also yielded positive outcomes. However, a real-world fall incidence reduction was inconsistently reported, and the methodological heterogeneity limited the meta-analytic synthesis. Conclusions: Occupational therapy contributes significantly to fall prevention through multimodal, person-centered strategies that integrate physical, cognitive, and environmental components. Future research should aim to standardize the outcome measures, include high-risk populations, and assess the long-term efficacy and cost-effectiveness of OT-led programs. Full article