Search Results (230)

Background: The purpose of this study was to evaluate Achilles tendon ruptures (ATR) in NHL players and the effects on return to play and player performance metrics. The incidence, mechanism of injury, management strategy, return to play (RTP), and post-injury were assessed from official online sports databases. Methods: A retrospective review of NHL players who sustained a partial or complete tear of the Achilles tendon from 2008 to 2024 was performed. Data were collected from NHL injury databases and media reports, and included player demographics, injury mechanism, treatment, and post-injury performance metrics. A Wilcoxon signed rank test was used to compare pre-injury and post-injury performance metrics, with significance set at p < 0.05. Results: Here, 15 NHL players with a mean age of 27.8 years were identified, with a prevalence rate of 0.125 injuries per 10,000 athletic exposures. Overall, 73.3% of ATRs were non-contact in nature, with 60.0% of ATRs occurring during off-season training. Fourteen players were managed with non-operative treatment, with no re-ruptures reported. The RTP rate was 93.3%, with players missing a mean number of 45.7 games. However, there was a deterioration in post-injury performance metrics, including games played per season, plus/minus rating, and time on ice per game post-injury. Conclusions: This study found that Achilles tendon ruptures are an uncommon injury in NHL players, with a prevalence rate of 0.125 injuries per 10,000 athletic exposures. A high RTP rate of 93.3% was observed in this cohort. However, there was a deterioration in post-injury performance metrics, including games played per season, plus/minus rating, and time on ice per game post-injury, highlighting the potential devastating sequelae of ATRs in elite NHL athletes. Full article

Earthquake-triggered landslides pose significant hazards to lives and infrastructure. While existing seismic landslide models primarily focus on seismic and terrain variables, they often overlook the dynamic nature of hydrologic conditions, such as seasonal soil moisture variability. This study addresses this gap by incorporating satellite-based soil moisture data from NASA’s Soil Moisture Active Passive (SMAP) mission into the assessment of seismic landslide occurrence. Using landslide inventories from five major earthquakes (Nepal 2015, New Zealand 2016, Papua New Guinea 2018, Indonesia 2018, and Haiti 2021), a balanced global dataset of landslide and non-landslide cases was compiled. Exploratory analysis revealed a strong association between elevated pre-event soil moisture and increased landslide occurrence, supporting its relevance in seismic slope failure. Moreover, a Random Forest model was trained and tested on the dataset and demonstrated excellent predictive performance. To assess the generalizability of the model, a leave-one-earthquake-out cross-validation approach was also implemented, in which the model trained on four events was tested on the fifth. This approach outperformed comparable models that did not consider soil moisture, such as the United States Geological Survey (USGS) seismic landslide model, confirming the added value of satellite-based soil moisture data in improving seismic landslide susceptibility assessments. Full article

Background: Soccer is a physically demanding sport characterized by frequent high-intensity efforts, which are particularly relevant in women’s competitions. Improving high-speed running and aerobic capacity has been linked to better on-field performance. Strength training has shown promise in enhancing these physical attributes, but its application in young female soccer players remains underexplored. This study aimed to investigate the effects of a 10-week in-season strength training program on physical performance and match running demands in young female soccer players. Methods: Thirty-two U18 Danish female professional soccer players from two comparable teams voluntarily participated in the study. Teams were allocated to either an experimental group, performing twice-weekly strength training (EG, n = 16) or a control group (CG, n = 16). Vertical jump performance and Yo-Yo IR2 performance as an estimation for maximal oxygen uptake (VO₂max) were assessed both pre and post intervention. Additionally, players’ match external demands (i.e., total distance, distance covered at speeds above 23 km·h⁻¹, and maximum velocity achieved) were monitored using Global Positioning System devices during four matches before and after the intervention. Results: Significant within-group differences were observed across all variables for the EG (p = 0.001; ES = 1.08 to 1.45, large), without differences in the CG (p > 0.01). Between-group analysis indicated significant differences favoring the EG in all variables (F = 27.40 to 47.17; p = 0.001). Conclusions: The application of a 10-week strength training program led to improvements in physical and match running performance among young female soccer players, underscoring the importance of incorporating strength training programs into female soccer periodization to enhance performance. Full article

The aim of this systematic review was to examine the effects of high-intensity interval training (HIIT) on physical performance and body composition in female basketball players. The review followed PRISMA guidelines, and the protocol was registered in the PROSPERO database (registration number: CRD420251006285). A comprehensive search was conducted across PubMed, Scopus, Web of Science, and Google Scholar. Nine studies that met the inclusion criteria were analyzed, with intervention durations ranging from 4 to 12 weeks. Despite differences in protocols, a majority of studies reported improvements in VO_2max (6/9), explosive strength (7/9), agility (5/6), and speed (5/6) and reductions in body mass and fat percentage (3/3). These findings highlight HIIT as an effective method for enhancing both aerobic and anaerobic capacities, as well as optimizing body composition. Despite variations in study protocols, HIIT consistently offers improvements in performance, irrespective of training level. The results underscore the importance of HIIT in preparing athletes, not only during the preseason but also throughout the competition period. Coaches should consider integrating HIIT into training programs, adjusting intensity and volume based on the season to optimize performance and prevent overtraining. Full article

This study examined the effects of a short-term ballistic training program on neuromuscular performance and strength-deficit (SDef) in elite youth female soccer players. Twenty-two under-20 athletes completed a 4-week intervention during the pre-season phase, comprising 12 loaded and 8 unloaded ballistic training sessions performed at maximal intended velocity. Pre- and post-intervention assessments included vertical jumps (squat jump [SJ], countermovement jump [CMJ]), sprinting speed (5, 10, and 20 m), one-repetition maximum (1RM) and peak force (PF) in the half-squat (HS), and peak power and velocity during jump squats (JS) at 30% of 1RM. SDef was calculated as the percentage difference in PF between 1RM in the HS and 30% 1RM. Significant improvements were observed in SJ, CMJ, sprint speed, 1RM-strength, and bar-derived mechanical outputs (ES = 1.18–1.66; p < 0.05), with no significant changes in SDef. These results indicate that elite youth female soccer players can improve strength-, power-, and speed-related capacities without compromising force production at higher movement velocities (thus maintaining their SDef). The improvements observed likely reflect the combined effect of a high-frequency, velocity-oriented training approach and a concurrent reduction in traditional technical–tactical (i.e., soccer-specific) training volume. This is the first study to demonstrate that ballistic exercises alone—when properly structured—can enhance neuromuscular performance in female soccer players without increasing SDef. These findings provide practical guidance for practitioners aiming to optimize physical development in team-sport athletes without relying on heavier training loads or extended resistance training sessions—and, especially, without compromising their ability to apply force at higher velocities. Full article

Background: Pre-season training is critical for developing tolerance to high physical demands in professional soccer, and nitric oxide (NO) precursors such as dietary nitrate (NO₃⁻) and citrulline malate (CM) can support performance and recovery during this demanding phase. This study aimed to examine the effects of a four-week supplementation protocol combining 500 mg of NO₃⁻ from amaranth extract and 8 g of CM (NIT + CM) on external training load and post-match recovery in professional female soccer players during pre-season. Methods: A randomized, double-blind, placebo-controlled trial was conducted with 34 female soccer players who received either the NIT + CM product or a placebo for four weeks during pre-season. Global positioning system (GPS)-derived external load was recorded throughout the intervention. Performance tests—a countermovement jump (CMJ) test and the Wingate anaerobic test (WAnT)—and blood sampling for plasma NO₃⁻ and nitrite (NO₂⁻) concentrations were conducted at baseline and the day after a competitive match. Results: The supplementation with NIT + CM increased maximal speed (Vmax) throughout training and match play. During post-match testing, the NIT + CM group exhibited a significantly smaller decline in mean (P_mean) and minimum (P_min) power during the WAnT, along with reduced power loss in both the first (0–15 s) and second (15–30 s) intervals. Plasma NO₃⁻ concentrations significantly increased from baseline in the NIT + CM group and remained elevated 24 h after the final dose, confirming sustained systemic exposure. Conclusions: Chronic NIT + CM supplementation may enhance Vmax and help preserve anaerobic performance the day after a match. These effects could reflect improved tolerance to high training loads and sustained NO₃⁻ availability during recovery. Full article

Background: Pre-season training is pivotal for optimizing athletic performance in collegiate basketball, yet the effectiveness of such programs in improving body composition (BC) under NCAA-mandated hourly restrictions remains underexplored. The aim of this study was to evaluate the impact of a four-week, NCAA Division II-compliant strength and conditioning (SC) program on BC in women’s basketball. Methods: Sixteen student athletes (20.6 ± 1.8 y; 173.9 ± 6.5 cm; 76.2 ± 20.2 kg) completed an eight-hour-per-week micro-cycle incorporating functional conditioning, Olympic-lift-centric resistance, and on-court skill development. Lean body mass (LBM) and body-fat percentage (BF%) were assessed using multi-frequency bioelectrical impedance on Day 1 and Day 28. Linear mixed-effects models were used to evaluate the fixed effect of Time (Pre, Post), including random intercepts for each athlete and covariate adjustment for age and height (α = 0.05). Results The LBM significantly increased by 1.49 kg (β = +1.49 ± 0.23 kg, t = 6.52, p < 0.001; 95% CI [1.02, 1.96]; R² semi-partial = 0.55), while BF% decreased by 1.27 percentage points (β = −1.27 ± 0.58%, t = −2.20, p = 0.044; 95% CI [−2.45, −0.08]; R² = 0.24). Height positively predicted LBM (β = +1.02 kg/cm, p < 0.001), whereas age showed no association (p > 0.64). Conclusions: A time-constrained, NCAA-compliant SC program meaningfully enhances lean mass and moderately reduces adiposity in collegiate women’s basketball athletes. These findings advocate for structured, high-intensity, mixed-modality training to maximize physiological readiness within existing regulatory frameworks. Future research should validate these results in larger cohorts and integrate performance metrics to further elucidate functional outcomes. Full article

The COVID-19 pandemic severely impacted Japan’s inbound tourism, but recent recovery trends highlight the growing importance of Chinese tourists. Understanding their motivations is crucial for revitalizing the industry. Building on our previous framework, this study applies Transformer-based natural language processing (NLP) models and principal component analysis (PCA) to analyze large-scale user-generated content (UGC) and identify key motivational factors influencing Chinese tourists’ visits to Hokkaido. Traditional survey-based approaches to tourism motivation research often suffer from response biases and small sample sizes. In contrast, we leverage a pre-trained Transformer model, RoBERTa, to score motivational factors like self-expansion, excitement, and cultural observation. PCA is subsequently used to extract the most significant factors across different destinations. Findings indicate that Chinese tourists are primarily drawn to Hokkaido’s natural scenery and cultural experiences, and the differences in these factors by season. While the model effectively aligns with manual scoring, it shows limitations in capturing more abstract motivations such as excitement and self-expansion. This research advances tourism analytics by applying AI-driven methodologies, offering practical insights for destination marketing and management. Future work can extend this approach to other regions and cross-cultural contexts, further enhancing AI’s role in understanding evolving traveler preferences. Full article

Background: Prevention and clinical management of musculoskeletal injuries have historically focused on the assessment and training of modifiable physical factors, but perceptual decision-making has only recently been recognized as a potentially important capability. Immersive virtual reality (VR) systems can measure the speed, accuracy, and consistency of body movements corresponding to stimulus–response instructions for the completion of a forced-choice task. Methods: A cohort of 26 female college soccer players (age 19.5 ± 1.3 years) included 10 players who participated in a baseline assessment, 10 perceptual-response training (PRT) sessions, a post-training assessment that preceded the first soccer practice, and a post-season assessment. The remaining 16 players completed an assessment prior to the team’s first pre-season practice session, and a post-season assessment. The assessments and training sessions involved left- or right-directed neck rotation, arm reach, and step-lunge reactions to 40 presentations of different types of horizontally moving visual stimuli. The PRT program included 4 levels of difficulty created by changes in initial stimulus location, addition of distractor stimuli, and increased movement speed, with ≥90% response accuracy used as the criterion for training progression. Perceptual latency (PL) was defined as the time elapsed from stimulus appearance to initiation of neck rotation toward a peripheral virtual target. The speed–accuracy tradeoff was represented by Rate Correct per Second (RCS) of PL, and inconsistency across trials derived from their standard deviation for PL was represented by intra-individual variability (IIV). Perceptual Decision Efficiency (PDE) represented the ratio of RCS to IIV, which provided a single value representing speed, accuracy, and consistency. Statistical procedures included the bivariate correlation between RCS and IIV, dependent t-test comparisons of pre- and post-training metrics, repeated measures analysis of variance for group X session pre- to post-season comparisons, receiver operating characteristic analysis, and Kaplan–Meier time to injury event analysis. Results: Statistically significant (p < 0.05) results were found for pre- to post-training change, and pre-season to post-season group differences, for RCS, IIV, and PDE. An inverse logarithmic relationship was found between RCS and IIV (Spearman’s Rho = −0.795). The best discriminator between injured and non-injured statuses was PDE ≤ 21.6 (93% Sensitivity; 42% Specificity; OR = 9.29). Conclusions: The 10-session PRT program produced significant improvement in perceptual decision-making that appears to provide a transfer benefit, as the PDE metric provided good prospective prediction of musculoskeletal injury. Full article

The accurate delineation of shrub crown boundaries is critical for ecological monitoring, land management, and understanding vegetation dynamics in fragile ecosystems such as semi-arid shrublands. While traditional image processing techniques often struggle with overlapping canopies, deep learning methods, such as convolutional neural networks (CNNs), offer promising solutions for precise segmentation. This study employed high-resolution imagery captured by unmanned aircraft systems (UASs) throughout the shrub growing season and explored the effectiveness of transfer learning for both semantic segmentation (Attention U-Net) and instance segmentation (Mask R-CNN). It utilized pre-trained model weights from two previous studies that originally focused on tree crown delineation to improve shrub crown segmentation in non-forested areas. Results showed that transfer learning alone did not achieve satisfactory performance due to differences in object characteristics and environmental conditions. However, fine-tuning the pre-trained models by unfreezing additional layers improved segmentation accuracy by around 30%. Fine-tuned pre-trained models show limited sensitivity to shrubs in the early growing season (April to June) and improved performance when shrub crowns become more spectrally unique in late summer (July to September). These findings highlight the value of combining pre-trained models with targeted fine-tuning to enhance model adaptability in complex remote sensing environments. The proposed framework demonstrates a scalable solution for ecological monitoring in data-scarce regions, supporting informed land management decisions and advancing the use of deep learning for long-term environmental monitoring. Full article

Exercise training in extreme temperatures concurrent with hypohydration status may potentiate the development of acute kidney injury (AKI) in young, healthy persons. Background/Objectives: It is unknown how repeated training bouts in ambient higher temperatures and humidity may influence measures of AKI. The purpose of this study was to investigate hydration status and renal biomarkers related to AKI in NCAA Division I female soccer athletes during preseason conditioning. Methods: A convenience sample of n = 21 athletes were recruited (mean ± SEM; age: 19.3 ± 0.25 y; height: 169.6 ± 1.36 cm; mass: 68.43 ± 2.46 kg; lean body mass: 45.91 ± 1.13 kg; fat mass: 22.51 ± 1.69 kg; body fat %: 32.22 ± 1.32%). The average temperature was 27.43 ± 0.19 °C, and the humidity was 71.69 ± 1.82%. Body composition, anthropometric, workload, and 14 urine samples were collected throughout the preseason training period for urine specific gravity (USG), creatinine (uCr), cystatin C (uCyst-C), and neutrophil gelatinase-associated lipocalin (uNGAL) analyses. Results: Our investigation showed that, when compared to baseline (D0), the athletes maintained a USG-average euhydrated status (1.019 ± 0.001) and were euhydrated prior to each exhibition game (D5-Pre: p = 0.03; 1.011 ± 0.001; D10-Pre: p = 0.0009; 1.009 ± 0.001); uCr was elevated on D8 (p = 0.001; 6.29 ± 0.44 mg·dL⁻¹·LBM⁻¹) and D10-Post (p = 0.02; 6.61 ± 0.44 mg·dL⁻¹·LBM⁻¹); uCyst-C was elevated on D6 through D10 (p = 0.001; ~0.42 ± 0.01 mg·dL⁻¹); no differences were found in uNGAL concentration. The highest distance (m) displaced was found during exhibition games (D5: p = <0.0001; ~8.6 km and D10: p = <0.0001; ~9.6 km). During the preseason conditioning, the athletes maintained a euhydrated status (~1.019) via USG, an increase in uCr that averaged within a normal range (208 mg·dL⁻¹), and an increase in uCyst-C to near AKI threshold levels (0.42 mg·L⁻¹) for several practice sessions, followed by an adaptive decline. No differences were found in uNGAL, which may be explained by athlete variation, chosen time sample collection, and variation in training and hydration status. Conclusions: The athletes maintained a euhydrated status, and this may help explain why urinary markers did not change or meet the reference threshold for AKI. Full article

This paper presents a novel approach for predicting Particulate Matter (PM) concentrations using mobile camera devices. In response to persistent air pollution challenges across Japan, we developed a system that utilizes cutting-edge transformer-based deep learning architectures to estimate PM values from imagery captured by smartphone cameras. Our approach employs Contrastive Language–Image Pre-Training (CLIP) as a multimodal framework to extract visual features associated with PM concentration from environmental scenes. We first developed a baseline through comparative analysis of time-series models for 1D PM signal prediction, finding that linear models, particularly NLinear, outperformed complex transformer architectures for short-term forecasting tasks. Building on these insights, we implemented a CLIP-based system for 2D image analysis that achieved a Top-1 accuracy of 0.24 and a Top-5 accuracy of 0.52 when tested on diverse smartphone-captured images. The performance evaluations on Graphics Processing Unit (GPU) and Single-Board Computer (SBC) platforms highlight a viable path toward edge deployment. Processing times of 0.29 s per image on the GPU versus 2.68 s on the SBC demonstrate the potential for scalable, real-time environmental monitoring. We consider that this research connects high-performance computing with energy-efficient hardware solutions, creating a practical framework for distributed environmental monitoring that reduces reliance on costly centralized monitoring systems. Our findings indicate that transformer-based multimodal models present a promising approach for mobile sensing applications, with opportunities for further improvement through seasonal data expansion and architectural refinements. Full article

Objectives: Adolescents’ health is positively influenced by the performance of physical activity. Regarding soccer, a very popular sport, the aims of the study were to assess changes in body composition and body image of late adolescent players during pre- and in-season training periods, analyzing the relationships between dissatisfaction and body composition parameters. Methods: A sample of 16–19-year-old male soccer players was examined longitudinally by three surveys. The body composition was assessed by anthropometric method. Body image perception was evaluated using two different figural scales related to shape and muscularity. Results: During the period examined, fat-free mass increased, and changes in perceived and ideal figures occurred, showing a desire toward more robust and muscular figures. Body image dissatisfaction was generally low, with a decrease in muscle dissatisfaction during the period. Body composition parameters significantly predicted body image dissatisfaction. Conclusions: Our findings suggest anthropometric and body image perception changes during soccer training with improvements in body composition parameters and a decrease in musculature dissatisfaction. These results highlight the importance of incorporating physical and psychological monitoring into training programs to support the healthy development of athletes’ body image and body composition. Full article

Background: Previous work has found that combining plyometric and resistance training in a single session can be effective in improving maximum strength (muscle contraction ability), vertical jumping, and sprint acceleration performance in young soccer players. However, the literature is scarce in relation to young rugby union players. Thus, the purposes of the present study were to examine the effects of a 6-week combined training (CT) programme that combined plyometric and resistance training in the same session on physical performance measures in adolescent male rugby union players and whether a 4-week period of plyometric training exclusion (Detraining) affects training adaptations. Methods: The participants (n = 15) completed a 6-week CT intervention and 4 weeks of plyometric detraining during the schoolboy rugby union in-season. A performance testing battery was conducted pre-intervention, post-intervention, and 4 weeks post-intervention. Results: A repeated measures ANOVA showed a significant effect for time on CMJ variables (mean power, mean force, and modified reactive strength index [RSI]), 3RM back squat strength, and 505 test time (p < 0.05). Pairwise comparisons revealed that CMJ variables (mean force, mean power, and peak power), 3RM back squat strength, and 505 test performance significantly increased from pre-intervention to post-intervention (p < 0.05). The 4-week plyometric detraining period significantly augmented CMJ variables (mean force, mean power, and modified RSI) and performance measures (standing broad jump [SBJ], 20 m sprint time, 505 test, and 3RM strength). Conclusions: The findings indicate that a 6-week CT programme can augment measures of lower-body power, maximal strength, and change of direction performance in adolescent male rugby union players, and a 4-week resistance training-only period (plyometric detraining) does not negatively affect performance adaptations. Full article

Research on the dynamic mechanisms driving the accumulation of anthropogenic marine debris (AMD) in highly dynamic environments, such as extensive sandy beaches, remains limited. Unmanned aerial vehicles (UAVs) can be used to map macro-marine litter in these environments over large temporal and spatial scales, but several challenges remain in their interpretation. In this study, secondary school students participated in a citizen science initiative, during which they identified, marked, and classified waste items using a series of UAV orthophotos collected along an 800 m extended Italian beach in different seasons. A specific training program and a collection of working tools were developed to support these activities, which were carried out under the constraints imposed by the COVID-19 pandemic. The accuracy of the citizen science approach was evaluated by comparing its results with standard in situ visual census surveys conducted in the same area. This methodology not only enabled an analysis of the temporal dynamics of AMD accumulation but also served an important educational function. The effectiveness of the learning experience was estimated using pre- and post-activity questionnaires. The results indicate a clear improvement in the students’ knowledge, interest, and awareness regarding marine litter, highlighting the potential of citizen science to both support environmental monitoring and promote sustainability education among younger generations. Full article