Search Results (5,014)

Lower-limb strength asymmetries are common in handball players and may negatively influence athletic performance while increasing injury risk. This study examined the effects of a six-week unilateral compound training program on lower-limb strength asymmetry, isokinetic strength, the hamstring-to-quadriceps (H/Q) ratio, body composition, and physical performance in competitive female handball players. Thirty highly trained female handball athletes (age: 18.75 ± 1.91 years) were randomly assigned to an experimental group (n = 14) or a control group (n = 16). The experimental group completed a unilateral compound training program consisting of unilateral resistance and plyometric exercises three times per week for six weeks, in addition to regular handball training, whereas the control group continued regular training only. Before and after the intervention, participants underwent assessments of body composition, isokinetic knee strength, bilateral strength asymmetry, H/Q ratios, 20 m sprint performance, change-of-direction (COD) ability, countermovement jump (CMJ), and single-leg CMJ performance. Significant group × time interaction effects were observed for body fat percentage, muscle percentage, muscle mass, knee flexor strength (both limbs), left knee extensor strength, bilateral quadriceps and hamstring asymmetries, H/Q ratios, sprint performance, COD performance, CMJ height, and single-leg jump performance (p < 0.05); the interaction for right knee extensor strength did not reach statistical significance (p = 0.072). The experimental group’s improvements coincided with substantial reductions in quadriceps (13.19% to 7.60%; −42.38%) and hamstring (16.65% to 7.83%; −52.97%) asymmetries, alongside changes in H/Q ratios, isokinetic strength, sprint performance (−4.68%), COD performance (−5.91%), CMJ height (+12.56%), and single-leg jump performance (+11.42–18.36%; partial η² = 0.19–0.46 across these primary outcomes). Given the relatively modest sample size, these percentage reductions should be interpreted with appropriate caution, as they may be subject to overestimation. Because the experimental group received three additional weekly training sessions relative to the control group, the observed improvements cannot be unambiguously attributed to the unilateral training modality itself, as opposed to the additional training volume. These findings suggest that adding a supplemental unilateral compound training program to regular handball training may improve lower-limb strength asymmetry and neuromuscular performance. However, because the intervention also increased total training volume, these effects cannot be attributed exclusively to the unilateral training modality itself. Full article

The countermovement jump (CMJ) is a common measure of lower-body power and neuromuscular performance. Incorporating an arm swing (AS) enhances CMJ outcomes, yet the contributions of anthropometrics, body composition (BC), and muscular power to performance are not fully understood in recreationally active adults. This study examined these factors in CMJ trials with and without AS. Thirty adults (15 males, 15 females; 18–25 years) performed CMJs on a force plate. Upper-body power was assessed via an 8 kg medicine ball throw, and lower-body power using a maximal cycling-based power test. Three-dimensional body scanning captured anthropometric data. Descriptive statistics, Pearson correlations, and hierarchical multiple regressions were conducted for the total sample and by sex. Jump height and peak power were significantly greater with AS than without (p < 0.001). Strong positive correlations were observed among jump- and power-related variables (r = 0.73–0.92). Body fat percentage showed moderate-to-strong negative associations with relative peak power, particularly in females. Regression analyses revealed that BC accounted for the largest proportion of variance in AS Peak Power, whereas upper-body power did not provide additional predictive value beyond anthropometrics and BC. These findings indicate that CMJ performance may be influenced primarily by lower-body mechanical capacity and BC, with adiposity consistently reducing relative power output. The results underscore the importance of BC in explosive performance training and support the use of AS-restricted jumps to isolate lower-body power during performance assessments. Full article

The purpose of this study was to evaluate the validity of the Vernier Go Direct force plate against a laboratory-grade AMTI force plate during squat jump (SJ) and countermovement jump (CMJ) assessments. Forty physically active university students (20 males and 20 females) performed both jump tests while vertical ground reaction force was recorded simultaneously by both systems. A total of 28 force-time variables were analyzed (9 from SJ and 19 from CMJ). For SJ, all parameters demonstrated excellent agreement (ICC = 0.986–0.997; CCC = 0.986–0.997) with small biases ranging from −4.0% to 3.6%. For CMJ, the parameters also showed good to excellent agreement (ICC = 0.846–0.999; CCC = 0.845–0.999) and minimal biases (−3.1% to 3.3%). These findings support the validity of the Vernier Go Direct force plate for measuring vertical jump performance and can serve as a cost-effective alternative for dynamic strength assessment, applied sports science research, and physical education settings. Full article

To address the high non-stationarity of COVID-19 pandemic time-series data and the severe error accumulation issue in long-horizon forecasting, a spatiotemporal two-branch multi-step forecasting model named CFC-FLCA is proposed. This model integrates closed-form continuous-time neural networks (CFC), a hybrid decomposition strategy combining variational mode decomposition (VMD) and jump plus AM-FM mode decomposition (JMD), and a cross-attention (CA) mechanism. First, the VMD-JMD hybrid mode decomposition method is applied to preprocess raw new case sequences. By leveraging the complementary advantages of the two decomposition algorithms, non-stationary sequences are adaptively decomposed into high-frequency noise components and low-to-mid-frequency trend-periodic components, eliminating random disturbance interference at the data source. On this basis, a time–frequency dual-branch feature extraction network is constructed. CFC provides ultra-long-range temporal dependency modeling capability; the time-domain branch adopts Legendre projection units (LPU) to extract robust temporal evolution features, while the frequency-domain branch employs frequency-enhanced units (FEU) to uncover latent periodic patterns that are difficult to capture using traditional time-domain methods. A cross-attention mechanism is introduced to dynamically learn the importance weights of time–frequency-domain features, enabling the adaptive deep integration of complementary information and effectively mitigating error accumulation in long-horizon forecasting. Multi-step forecasting experiments are conducted on real-world COVID-19 datasets from Belgium, the Czech Republic, and Ireland, with comprehensive comparisons against mainstream time series forecasting models. The experimental results demonstrate that the CFC-FLCA model outperforms all comparison models across all evaluation metrics for all prediction horizons. Full article

Objectives: High-intensity interval training (HIIT) has become an increasingly popular conditioning strategy in women’s basketball due to its effectiveness in improving physical performance. The aim of this study was to examine the effects of a six-week HIIT on combined aerobic and anaerobic capacity, running speed, agility, repeated sprint ability, and explosive power in elite female basketball players. Methods: Thirty elite female basketball players (21.81 ± 2.12 years) were randomly assigned to either a HIIT group (n = 15) or a control group (n = 15). Results: Pre- and post-intervention assessments included running speed (0–20 m); the 5–0–5, Zig-zag, and Pro-agility tests; vertical jump performance (CMJ, CMJA, and SJ); repeated sprint ability (RSA); aerobic capacity assessed by the 30–15 Intermittent Fitness Test; and VO₂max. Statistically significant Group × Time interaction effects emerged for running speed (5 m, 10 m, and 20 m), aerobic capacity (30–15 IFT and VO₂max), and Zig-zag agility performance (p < 0.05), indicating greater improvements in the HIIT group compared with the control group. Significant main effects of time were observed for RSA and vertical jump performance, indicating improvements in both groups; however, no significant Group × Time interactions were found. Conclusions: These findings suggest that a six-week HIIT is an effective and time-efficient conditioning strategy for enhancing aerobic capacity, sprint performance, and change-of-direction ability in elite female basketball players. Full article

Background: Team sports often involve high-intensity unilateral actions that can lead to neuromuscular asymmetries, increasing injury risk and reducing performance, particularly in young female athletes. Methods: This study quantified and compared inter-limb asymmetries in single-leg countermovement jumps (slCMJ) across sexes and sports in 96 youth elite athletes (16.42 ± 1.03 years; 1.83 ± 0.09 m; 74.36 ± 8.69 kg) from basketball, handball, and volleyball. Using a force plate, asymmetries were assessed, and statistical analyses (t-test, ANOVA) identified differences. Results: Females showed greater asymmetry in jump height (9.64 ± 6.43% vs. 6.48 ± 4.87%, p = 0.01, d = 0.59), whereas males exhibited higher asymmetry in time to take-off (10.32 ± 7.5% vs. 6.4 ± 4.7%, p = 0.003, d = 0.63). Volleyball players displayed the lowest asymmetry in jump height (7.05 ± 4.9%) compared to basketball (8.73 ± 7.2%) and handball (11.88 ± 9.7%, p = 0.05), and in relative maximum power (4.63 ± 3.7%) compared to basketball (7.75 ± 5.3%, p = 0.04) and handball (6.51 ± 4.7%). Conclusions: These findings highlight sex- and sport-specific neuromuscular asymmetry patterns, emphasizing their relevance for injury prevention and performance strategies. However, asymmetries are highly variable, influenced by multiple factors. Full article

Most studies investigating recovery in CrossFit^® have focused on the effects of a single training session, whereas the cumulative effects of consecutive sessions within a training microcycle remain poorly understood. This study aimed to evaluate perceived recovery and neuromuscular performance, assessed through the countermovement jump (CMJ) and handgrip strength tests, over a 72 h period following a habitual strength–power-emphasized CrossFit^® microcycle. Methods: Fourteen male CrossFit^® practitioners performed CMJ and handgrip strength tests and completed the Total Quality Recovery (TQR) scale before and at 24, 48, and 72 h after completing a strength–power-emphasized training microcycle. Results: Repeated-measures ANOVA revealed significant reductions in all variables 24 h after the microcycle compared with baseline values, followed by recovery to baseline within 48 h. Conclusions: These findings suggest that at least 48 h are required for the recovery of neuromuscular performance and perceived recovery following a habitual strength–power-emphasized CrossFit^® microcycle. Furthermore, the similar temporal responses observed across the three monitoring tools indicate that they may represent practical options for monitoring performance and recovery in CrossFit^® practitioners. Full article

This paper considers stochastic optimal control of stochastic differential delay equations (SDDEs) with jumps and Markov switching, and its economical applications. The Hamilton–Jacobi–Bellman (HJB) equation and the inverse HJB-equation are derived by applying the Dynkin’s formula and solution of the Dirichlet–Poisson problem for those SDDEs. Three cases of modified Ramsey stochastic models in economics are studied; namely, a Ramsey diffusion model with jumps, a Ramsey diffusion model with Markov switching, and a Ramsey diffusion model with jumps and Markov switching. We also present numerical examples for all three cases. The contributions of the paper are four-fold: introducing and studying three new models for SDDEs: with jumps, Markov switching and both; studying optimal control for those models; applications of these results to economics with Ramsey’s stochastic models; and numerical examples for these different models. Full article

To address the lack of compliance with the International Regulations for Preventing Collisions at Sea (COLREGs) in conventional timed elastic band (TEB)—based dynamic path planning for autonomous surface vessels (ASVs), this study proposes an intelligent path-planning framework that integrates an improved jump point search (JPS) algorithm with a COLREGs-aware TEB approach. At the global planning layer, an enhanced JPS algorithm incorporating redundant-node elimination and cubic Bezier curve smoothing is developed to construct the JPS–PB method, thereby reducing path redundancy and improving trajectory continuity. At the local planning layer, COLREGs encounter rules are reformulated as differentiable cost functions and embedded into the TEB optimization framework, enabling rule-compliant collision avoidance in typical maritime encounter scenarios, including head-on, crossing, and overtaking situations. Simulation results demonstrate that, compared with the conventional JPS algorithm, the proposed JPS-PB method reduces the path length by up to 8.6%, decreases the cumulative steering angle by 58.6%, and lowers the maximum steering angle by 88.6% on a 12 × 12 grid environment. Furthermore, compared with the conventional TEB algorithm, the proposed COLREGs–aware TEB (CTEB) increases the Distance at the Closest Point of Approach (DCPA) by 543%, 20.5%, 4.8%, and 13.8% in starboard-crossing encounters, head-on, overtaking, and special port-side-crossing encounter scenarios, respectively. Parameter sensitivity analyses further indicate that CTEB maintains stable collision-avoidance performance and rule-compliance capability under variations in the danger–distance threshold, danger–time threshold, and COLREGs cost weight. The results verify that the proposed JPS–PB+CTEB hybrid framework effectively improves path quality, dynamic obstacle-avoidance safety, and navigation-rule compliance for autonomous ASV operations. Full article

Purpose: To determine whether specific movement-pattern deficits and their hierarchical interaction during drop jump (DJ) tasks can predict injury occurrence in football players using a LESS-based observational screening approach. Methods: Seventy-two male football players (age: 21.4 ± 3.2 years; height: 178.2 ± 6.4 cm; body mass: 73.5 ± 7.1 kg) completed a standardised DJ assessment during the pre-season period. Movement quality was evaluated using a modified Landing Error Scoring System (LESS)-based observational protocol including six biomechanical domains related to lower-limb and trunk control. The occurrence of non-contact lower-limb injuries resulting in time loss was prospectively monitored throughout the competitive season. Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were performed to identify independent predictors of injury and evaluate model discrimination. Additionally, a Classification and Regression Tree (CART) model was implemented to identify hierarchical movement-based injury-risk profiles. Results: Eighteen players (25%) sustained at least one time-loss injury during the observation period. Injured players demonstrated significantly higher composite movement-error scores compared with non-injured players (6.1 ± 1.8 vs. 4.3 ± 1.5; p = 0.01). Dynamic knee valgus (OR = 2.84; 95% CI: 1.32–6.12; p = 0.008) and trunk control deficits (OR = 2.17; 95% CI: 1.08–4.36; p = 0.030) emerged as independent predictors of injury risk. The logistic regression model demonstrated acceptable discriminative capacity (AUC = 0.74; sensitivity = 0.72; specificity = 0.67). CART analysis identified three hierarchical movement-risk profiles: low risk (predicted probability < 0.15), moderate risk (0.15–0.40), and high risk (>0.40). Players exhibiting combined dynamic knee valgus and trunk control deficits demonstrated the highest injury probability. Conclusions: The present findings support the use of movement-pattern profiling during DJ tasks as a practical and clinically interpretable strategy for injury-risk stratification in football players. Rather than relying exclusively on composite movement-error scores, the interaction between dynamic knee valgus and trunk control deficits appears to represent a distinct neuromuscular risk phenotype associated with elevated injury probability. Integrating observational movement screening with hierarchical risk modelling may contribute to the development of more individualised injury-prevention strategies in football. Full article

Fire-induced temperature fields in double-steel-plate concrete structures are strongly governed by steel–concrete interfaces, where global temperature error alone is insufficient to characterize interface heat-transfer behavior. This study presents an interface-aware, surface-temperature-driven framework for rapid prediction of temperature fields and interpretation of interface behavior in fire-exposed composite structures. Full-field temperatures are reconstructed using surface-temperature histories, spatial coordinates, and material-region labels. To explicitly evaluate interface behavior, paired steel-side and concrete-side temperatures are extracted to compute temperature jumps and heat fluxes based on Fourier’s law. On this basis, an equivalent interface heat-transfer parameter $h_{\mathrm{eff}}$ is introduced as a physically interpretable descriptor that links interface temperature discontinuity and contact heat flux through $q_{\mathrm{contact}}=h_{\mathrm{eff}}(T_s-T_c)$. This formulation enables direct assessment of interface consistency from the predicted temperature field, rather than indirect inference from global error metrics. An FEM-generated dataset comprising 150 two-dimensional transient fire-heating cases is used, covering perfect-bond, constant-conductance, and temperature-dependent interface conditions. The proposed model achieves an overall validation RMSE of 7.73 °C. Local RMSEs are 11.91 °C, 14.86 °C, and 2.00 °C at the fire-exposed surface, front interface, and back interface, respectively. The predicted $h_{\mathrm{eff}}$ shows strong agreement with reference values, with a correlation coefficient of 0.956. In addition, the normalized contact heat-flux error decreases from 0.31 to 0.26. A locked checkpoint held-out test further confirms robustness, yielding an overall RMSE of 7.71 °C and an $h_{\mathrm{eff}}$ correlation of 0.946. The proposed framework is applicable to rapid thermal analysis of interface-dominated composite structures under fire exposure when surface-temperature histories, material-region labels, and paired interface samples are available. Overall, the results indicate that the method improves interface interpretability while maintaining accurate and computationally efficient temperature-field prediction. Full article

This paper presents an efficient numerical framework for solving the Merton jump–diffusion partial integro-differential equation (PIDE) arising in European option pricing. To address the nonlocal integral term generated by asset price jumps, we employ an IMEX Crank–Nicolson time-stepping scheme that preserves the tri-diagonal structure of the resulting linear system. A nonuniform spatial grid and fast Gaussian quadrature with spline interpolation are incorporated to enhance accuracy and computational efficiency. We establish the unconditional stability and convergence of the IMEX–Crank–Nicolson scheme through a detailed theoretical analysis. Numerical experiments confirm the theoretical results and illustrate the effectiveness of the proposed method for representative jump–diffusion parameters. Full article

Electrode-particle fracture and thermal runaway remain major safety and durability challenges for lithium-ion batteries. Deterministic degradation models are limited in representing random crack nucleation, long-range crack interactions, and critical transitions from stable operation to failure. A computational framework is proposed that combines a Lévy-jump-driven nonlocal stochastic partial differential equation (SPDE) model with a Bifurcation-Aware Physics-Informed Neural Network (BA-PINN). The framework couples fractional diffusion, peridynamic damage evolution, thermal feedback, state-space eigenvalue tracking, and damage-variance monitoring. Evaluation is conducted on controlled synthetic fracture simulations, Oxford battery cycling records, and open-access abuse-test records from the Battery Failure Databank. The damage-field results are interpreted as numerical consistency and surrogate-learning evidence, with direct experimental crack-map validation remaining outside the present dataset scope. On the simulated fracture dataset, the proposed method obtains a damage-field mean squared error of 0.023 ± 0.002 and a structural similarity index of 0.962 ± 0.006. For the evaluated thermal-runaway warning task, it achieves an AUC-ROC of 0.987 ± 0.004 and an average model-inferred warning lead time of 5.2 ± 0.2 h. These results demonstrate the methodological feasibility of combining stochastic nonlocal fracture modeling with bifurcation-aware learning. However, broader validation remains necessary, particularly using particle-resolved experiments and larger event-level thermal-runaway datasets. Full article

This paper deals with a system of G-stochastic differential equations with jumps, driven by G-Brownian motion and the G-Lévy process. By using Burkholder–Davis–Gundy inequalities, we prove the moment estimate and the Hölder regularity of the solution, under the linear growth and the global Lipschitz conditions of the coefficients with respect to the state variable uniformly in the time variable. Moreover, different stability properties are proved. Some illustrative examples from finance are employed in order to support our theoretical results. Full article

High countermovement-jump (CMJ) height prediction may reflect mechanical reconstruction rather than independent neuromuscular information. This study separated mechanically proximal variables from mechanically restricted force-expression, movement-organization, and tensiomyography (TMG) predictors. Sixty-six elite youth football players completed force-platform CMJ and rectus femoris TMG assessments. Jump height was reconstructed from mean propulsion force and propulsion duration. After excluding these variables and direct mechanical equivalents, Ridge, Elastic Net, GAM, and random forest models were evaluated using repeated nested cross-validation, with predictor-set, ablation, and held-out permutation-importance analyses. The mechanical benchmark almost perfectly reconstructed jump height (RMSE = 0.0027 m; predictive R² = 0.998). After mechanical restriction, random forests were the strongest prespecified single model family (RMSE = 0.0510 m; predictive R² = 0.296), whereas the fully nested one-standard-error model-selection pipeline provided a more conservative estimate of generalization (RMSE = 0.0548 m; predictive R² = 0.187). Within the retained predictor set, movement organization provided more information than force expression (predictive R² = 0.214 vs. 0.078). The TMG-only prediction was worse than the mean-level benchmark (predictive R² = −0.039), and adding TMG did not improve the CMJ base model. CMJ height is readily reconstructed from proximal propulsion mechanics. After their removal, movement organization retains modest predictive information, whereas single-muscle rectus femoris TMG did not provide useful standalone or incremental value in this cohort. Full article