Search Results (2,321)

Background: Previous research has identified center of mass vertical oscillation and leg stiffness as the most common variables differentiating Natural and Groucho running techniques. The aim was to assess the inter-session reliability and inter-technique sensitivity of synchronized inertial measurement units and contact grids in quantifying kinematic and kinetic differences between Natural and Groucho running techniques. Methods: Eleven physically active and healthy males ran at a speed 50% higher than transition speed. Two sessions for Natural and two for Groucho running were performed, each lasting 1 min. Results: Most variables exhibited a similar inter-session reliability across running techniques, except contact time and center of mass vertical displacement, ranging from moderate to good (ICC = 0.538–0.897). A statistically significant difference between running techniques was found for all variables (p < 0.05), except for contact time and center of mass vertical oscillation (p > 0.05), likely due to inconsistency in reliability depending on the running technique, which may have covered the underlying differences. Conclusions: We can conclude that the combination of synchronized inertial measurement units and contact grids showed potentially acceptable reliability and sufficient sensitivity to recognize and differentiate between Natural and Groucho running techniques. The results may contribute to a broader understanding of the differences between these two running techniques and encourage the increased use of these devices within therapeutic, recreational, and sports running contexts. Full article

Background/Objectives: National Football League (NFL) American football players are exposed to osteoarthritis risk factors of obesity and high joint loads. We sought to examine the association between total body mass (TBM), lean body mass (LBM), body fat percentage (BF%), and normalized compressive knee joint reaction forces (JRFcomp), peak knee adductor moments (KAM), and vertical ground reaction forces (vGRF) in NFL draft-eligible players during a high-speed run. Methods: A total of 125 participants ran a single trial at 5.5–6.5 m/s for 5 s on an instrumented treadmill. Bilateral vGRF and knee joint kinetics were calculated using inverse dynamics. Body composition was assessed using bioelectrical impedance. Results: LBM demonstrated significant moderate associations with vGRF (left, r(123) = −0.56, p < 0.001; right, r(123) = −0.60, p < 0.001) and low-to-negligible associations with KAM (left, r(123) = −0.20, p = 0.026; right, r(123) = −0.30, p < 0.001) and JRFcomp (left, r(123) = −0.39, p = 0.020; right, r(123) = −0.38, p = 0.015), respectively. TBM showed significant moderate negative associations with vGRF (left, r(123) = −0.56, p < 0.001; right, r(123) = −0.61, p < 0.001) and low-to-negligible associations with KAM (left, r(123) = −0.21, p = 0.021; right, r(123) = −0.28, p = 0.002) and JRFcomp (left, r(123) = −0.39, p < 0.001; right, r(123) = −0.37, p < 0.001), respectively. BF% showed significant low-to-negligible negative associations with JRFcomp (left, r(123) = −0.21, p < 0.001; right, r(123) = −0.22, p < 0.001) and vGRF (left, r(123) = −0.39, p < 0.001; right, r(123) = −0.41, p < 0.001), respectively, and no significant associations with KAM, p > 0.05. The heavier group exhibited significantly lower normalized JRFcomp, and vGRF, p < 0.05. Conclusions: Heavier, but not fatter, players attenuate knee loads. Dampening may be a short-term protective strategy for joints of heavier players. Full article

In Japan, the shortage of airport ground-handling personnel has become a serious concern with the growing demand for aviation, necessitating improvements in operational efficiency. Accordingly, the expectations for automating aircraft ground support equipment (GSE) vehicles are growing to achieve labor savings. This study evaluated the changes in GSE traffic flow performance (travel speed, travel time, and number of stops) through traffic simulations under various scenarios of automated-driving GSEs penetrating the entire airport restricted areas. We simulated the traffic flow at Tokyo International Airport using the observation data of each GSE driving through the airport. Simulation results indicated that GSEs experience a reduced travel speed in some vehicle corridors when automated-driving GSEs, considering the safety risks associated with existing automated technology, run at lower speeds to ensure reliable driving performance. Consequently, the total travel time of the GSEs for the entire airport increases. These results confirm that the penetration of automated-driving GSEs can be facilitated by implementing measures, such as developing technology for reliable driving performance or operational rules at intersections to enable these vehicles to run at a speed equivalent to that of manned GSEs and to prevent speed reduction and travel time increase in airport vehicle corridors. Full article

Arbitrary zones are commonly used to describe and monitor external load (EL) during training and competitions. However, in recent years, relative speed zones have gained interest as they allow a more detailed description of the demands of each individual player, with their benefits largely unknown. This study aimed to (i) identify differences in EL methodological approaches using arbitrary and relative running speed zones; (ii) examine the effect of the methodological approaches to identify fast and slow basketball players during competition and training; and (iii) determine the effect of the season stage on the methodological approaches. Twelve players from a Spanish fourth-division basketball team were observed for a full season of matches and training using inertial devices with ultra-wideband indoor tracking technology and micro-sensors. Relative velocity zones were based on the maximum velocity achieved during each match quarter and were retrospectively recalculated into four zones. A linear mixed model (LMM) compared fast and slow players based on speed profiles between arbitrary and relative thresholds and during each competition stage. All players surpassed peak speeds of 24 km·h⁻¹ during the season, exceeding typical values reported in elite basketball (20–24.5 km·h⁻¹). Arbitrary thresholds produced greater distances in high-speed running (Zones 3 and 4) and yielded lower values in low-speed activity (Zone 1), with differences of ~100 m and ~120–250 m, respectively (p < 0.001), particularly for fast-profile players. These discrepancies were consistent across most stages of the season, although relative zones better captured variations in Zone 1 across time. Training sessions also elicited +8.7% to +40.7% greater distances > 18 km·h⁻¹ compared to matches. The speed zone methodology substantially influenced EL estimates and affected how player EL was interpreted across time. Arbitrary and relative approaches offer unique applications, with coaches and sport scientists encouraged to be aware that using a one-size-fits-all approach may lead to misrepresentation of individual player demands, especially when tracking changes in performance or managing fatigue throughout a competitive season. Full article

This study investigates the transverse loads acting on high-speed train bogie frames under actual service conditions. To enable direct identification, the locating arms were instrumented as bending sensors and calibrated under realistic lateral-stop constraints, ensuring robustness of the measurement channels. Field tests were conducted on a CR400BF high-speed EMU over a 226 km route at six speed levels (260–390 km/h), with gyroscope and GPS signals employed to recognize typical operating conditions, including straights, curves, and switches (straight movement and diverging movements). The results show that the proposed recognition method achieves high accuracy, enabling rapid and effective identification and localization of typical operating conditions. Under switch conditions, the bogie frame transverse loads are characterized by low-frequency, large-amplitude fluctuations, with overall RMS levels being higher in diverging switches and straight-through depot switches. Curve parameters and speed levels exert significant influence on the amplitude of the transverse-load trend component. On curves with identical parameters, the trend-component amplitude exhibits a quadratic nonlinear relationship with train speed, decreasing first and then increasing in the opposite direction as speed rises. In mainline curves and straight sections, the RMS values of transverse loads on Axles 1 and 2 scale proportionally with speed level, with the leading axle in the direction of travel consistently producing higher transverse loads than the trailing axle. When load samples are balanced across both running directions, the transverse load spectra of Axles 1 and 2 at the same speed level show negligible differences, while the spectrum shape index increases proportionally with speed level. Full article

Accurate interpretation of physical test results is essential to objectively measure parameters both at a single point in time and throughout longitudinal assessments. This is particularly relevant for tests of speed and change of direction, which are among the most commonly used assessments for soccer players at different levels. This study aimed to quantify the impact of start-line distance (30 cm vs. 100 cm) on linear sprint splits (5–30 m), change-of-direction (COD), and T-test performance in elite youth soccer players, while also examining potential order effects. The study involved 82 youth soccer players (14–19 y; 180.68 ± 6.97 cm; 71.65 ± 7.91 kg; BMI 21.90 ± 1.57) from an elite academy, divided into two groups. The first group started trials at 30 cm from the starting line, then at 100 cm, while the second group performed in the reverse order. All participants underwent a standard sequence of tests: anthropometric measurements, 5, 10, 20, and 30 m sprints, change-of-direction running, and the T-test. The longer start (100 cm) improved sprint times with large effects tapering with distance: 5 m (Hedges’ g = 1.00, 95% CI 0.80–1.25; Δ = 0.076 s, 0.060–0.093; 6.99%), 10 m (g = 1.37, 1.14–1.68; Δ = 0.102 s, 0.086–0.119; 5.63%), 20 m (g = 1.58, 1.36–1.88; Δ = 0.112 s, 0.096–0.127; 3.66%), 30 m (g = 1.48, 1.26–1.80; Δ = 0.114 s, 0.097–0.131; 2.71%). COD also improved (rank-biserial r = 0.516, 0.294–0.717; Δ = 0.075 s, 0.034–0.116; 1.00%) and the T-test improved (g = 0.61, 0.37–0.86; Δ = 0.107 s, 0.068–0.145; 1.26%). Order effects on Δ were evident for 30 m (Welch t = −3.05, p_Holm = 0.0157, d = −0.67) and COD (MWU p_Holm = 0.0048, r = −0.43). Protocols must specify and report the start geometry; the order should be randomised or counter-balanced, particularly for 30 m and COD. Full article

In the context of low carbon, achieving accurate forecasting of electrical energy is critical for power management with the continuous development of power systems. For the sake of improving the performance of load forecasting, an improved MNet-Atten electric vehicle charging load forecasting based on composite decomposition and the evolutionary predator–prey and strategy model is proposed. In this light, through the data decomposition theory, each subsequence is processed using complementary ensemble empirical mode decomposition and filters out high-frequency white noise by using singular value decomposition based on matrix operation, which improves the anti-interference ability and computational efficiency of the model. In the model construction stage, the MNet-Atten prediction model is developed and constructed. The convolution module is used to mine the local dependencies of the sequences, and the long term and short-term features of the data are extracted through the loop and loop skip modules to improve the predictability of the data itself. Furthermore, the evolutionary predator and prey strategy is used to iteratively optimize the learning rate of the MNet-Atten for improving the forecasting performance and convergence speed of the model. The autoregressive module is used to enhance the ability of the neural network to identify linear features and improve the prediction performance of the model. Increasing temporal attention to give more weight to important features for global and local linkage capture. Additionally, the electric vehicle charging load data in a certain region, as an example, is verified, and the average value of 30 running times of the combined model proposed is 117.3231 s, and the correlation coefficient PCC of the CEEMD-SVD-EPPS-MNet-Atten model is closer to 1. Furthermore, the CEEMD-SVD-EPPS-MNet-Atten model has the lowest MAPE, RMSE, and PCC. The results show that the model in this paper can better extract the characteristics of the data, improve the modeling efficiency, and have a high data prediction accuracy. Full article

Although laboratory testing to assess aerobic capacity has been a ‘gold standard’ in sports science, its high costs and time-consuming protocols may not be feasible for monitoring and tracking progress in limited conditions. In dancesport athletes, several field-based aerobic tests have been proposed, but the majority of them have been developed for ballet or contemporary dancers at the individual level, while the data among dance couples engaging in standard dance styles is lacking. Therefore, the main purpose of this study was to validate a newly developed Ballroom Aerobic Test (BAT) protocol against objective methods. Twelve standard dancesport couples (age: 20.4 ± 3.9 years; height: 172.1 ± 8.7 cm; weight: 60.1 ± 9.4 kg) with 8.2 ± 3.4 years of training and competing experience participated in this study. Ventilatory and metabolic parameters were generated using the MetaMax^® 3B portable gas analyzer (the BAT), while the KF1 (an increase in speed by 0.5 km * h⁻¹ by every minute) and Bruce protocols were followed in laboratory-based settings on the running ergometer. Large to very large correlations were obtained between the BAT and KF1/Bruce protocols for the absolute maximal oxygen uptake (VO₂max; r = 0.88 and 0.87) and relative VO₂max (r = 0.88 and 0.85), respiratory exchange ratio (RER; r = 0.78 and 0.76), expiratory ventilation (VE; r = 0.86 and 0.79), tidal volume (VT; r = 0.75; 95% CI = 0.57–0.87; p < 0.001), ventilatory equivalent for O₂ (VE/VO₂; r = 0.81 and 0.80) and CO₂ (VE/VCO₂; r = 0.78 and 0.82), and dead space (VD/VT; r = 0.70 and 0.74). The Bland–Altman plots indicated no systematic and proportional biases between the BAT and KF1 protocols (standard error of estimate; SEE = ± 3.36 mL * kg⁻¹ * min⁻¹) and the BAT and Bruce protocols (SEE = ± 3.75 mL * kg⁻¹ * min⁻¹). This study shows that the BAT exhibits satisfactory agreement properties against objective methods and is a valid dance protocol to accurately estimate aerobic capacity in dancesport athletes participating in standard dance styles. Full article

The two groups of EU economies, the euro area and the non-euro area, are statistically analyzed taking into account the fulfillment of the euro area financial criteria and economic performance over the period 2000–2023. Compliance with financial criteria, economic performance, and their significant influencing factors are presented comparatively for the two groups of countries. The long-run equilibrium between economic growth and its factors is identified by econometric approaches with the error correction model (ECM) and autoregressive distributed lag (ARDL) models for the two data panels. In the short term, economic shocks are taken into account to compare their different influences on economic growth within the two groups of countries. The GMM system is used to model economic convergence at the EU level over the period under review. Comparisons between GDP growth and its theoretical values from econometric models have led to interesting conclusions regarding the existence and characteristics of economic convergence at the group and EU level. EU countries outside the euro area have higher economic growth rates than euro area economies over the period 2000–2023. In the long run, investment brings a higher increase in economic development in EU countries outside the euro area than in euro area countries. Economic shocks have been felt more deeply on economic growth in the euro area than in the non-euro area. The speed of adjustment towards long-run equilibrium in econometric models is slower for non-euro area economies than in the euro area over a one-year period. At the level of the European Monetary Union, change policies have a faster impact on economic development and a faster speed of adjustment towards equilibrium. Full article

With the rapid development of artificial intelligence technology in the field of intelligent manufacturing, convolutional neural networks (CNNs) have shown excellent performance and generalization capabilities in industrial applications. However, the huge computational and resource requirements of CNNs have brought great obstacles to their deployment on low-end hardware platforms. To address this issue, this paper proposes a scalable CNN accelerator that can operate on low-performance Field-Programmable Gate Arrays (FPGAs), which is aimed at tackling the challenge of efficiently running complex neural network models on resource-constrained hardware platforms. This study specifically optimizes depthwise separable convolution and the squeeze-and-excite module to improve their computational efficiency. The proposed accelerator allows for the flexible adjustment of hardware resource consumption and computational speed through configurable parameters, making it adaptable to FPGAs with varying performance and different application requirements. By fully exploiting the characteristics of depthwise separable convolution, the accelerator optimizes the convolution computation process, enabling flexible and independent module stackings at different stages of computation. This results in an optimized balance between hardware resource consumption and computation time. Compared to ARM CPUs, the proposed approach yields at least a 1.47× performance improvement, and compared to other FPGA solutions, it saves over 90% of Digital Signal Processors (DSPs). Additionally, the optimized computational flow significantly reduces the accelerator’s reliance on internal caches, minimizing data latency and further improving overall processing efficiency. Full article

Sports footwear is widely used across a range of physical activities. A key factor distinguishing running shoes from other types of footwear is the “drop,” the millimeter difference between the heel and the forefoot. This study aimed to analyze the influence of different drops (0, 5, and 10 mm) on ground reaction forces during walking and to examine the effects of sex and body mass index (BMI) under these conditions. An observational, descriptive, and cross-sectional study was conducted with 117 participants (56 men and 61 women). The Dinascan/IBV^® dynamometric platform (Instituto de Biomecánica de Valencia, Valencia, Spain) was used to measure ground reaction forces during walking (braking, take-off, propulsion, and swing forces), walking speed, and stance time. The descriptive analysis revealed comparable values for the left and right limbs, with slightly higher values observed in the right limb. Statistically significant differences were found in stance time, braking force, and swing force between the 0 mm and 10 mm drop conditions. Take-off force showed highly significant differences when comparing the 0–5 mm and 0–10 mm drop conditions. Sex-based differences were observed in all variables at the initial proposed drop condition of 0 mm, except for walking speed, possibly due to anatomical and physiological differences. Significant differences were found in stance time at 0 mm drop, braking force, and propulsion force. Highly significant values were obtained for take-off force and during the swing phase. A strong correlation was found between ground reaction forces and BMI with the different proposed drops in all forces studied, except for the support force, where a moderate correlation was obtained. Although shoe drop was found to influence ground reaction forces in this study, it is one of several factors that affect gait biomechanics. Other footwear characteristics, such as sole stiffness, material composition, weight, and elasticity, also play important roles in walking performance. Therefore, shoe drop should be considered an important but not exclusive parameter when selecting footwear. However, these results are limited to healthy young adults and may not be generalizable to other age groups or populations. Full article

With the growing deployment of electric buses (e-buses), accurate energy use modelling has become essential for fleet optimisation and operational planning. Using the SORT methodology, this study analyses instantaneous energy consumption and recuperation (IECR). Three vehicle configurations were tested (one battery with pantograph, four batteries, and eight batteries), each with ten repeatable runs. Four approaches were compared: a baseline linear regression, an extended linear model (ELM) due to the state, a feed-forward neural network, and a recurrent neural network (RNN). The extended linear model achieved a determination coefficient of R² = 0.9124 (residual standard deviation 4.26) compared with R² = 0.7859 for the baseline, while the determination coefficient for the RNN is 0.9343, and the RNN provided the highest accuracy on the test set (the correlation coefficient between real and predicted values is 0.9666). The results confirm the dominant influence of speed and acceleration on IECR and show that battery configuration mainly affects consumption during acceleration. Literature-consistent findings indicate that regenerative systems can recover 25–51% of braking energy, with advanced control methods further improving recovery. Despite non-normality and temporal dependence of residuals, the state-aware linear model remains interpretable and competitive, whereas recurrent networks offer superior fidelity. These results support real-time energy management, charging optimisation, and reliable range prediction for electric buses in urban public transport. Full article

To the film thicknesses of grease-lubricated ball bearings, the viscosity of the base oil is considered in the Elastohydrodynamic Lubrication (EHL) equations. For very low speeds, the grease film thickness is much larger than the calculated base oil film thickness. Initially, the grease film thickness decreases with speed to a minimum value, followed by an increase, thus generating a “V-shape pattern”. To evidence this behavior of grease film in a ball bearing, the authors used the method of measuring electrical resistance. Using an oil with a viscosity close to a grease base oil viscosity, a relationship was obtained between the electrical resistance of the ball bearing and the average film thickness in the ball–race contacts. Based on this relationship, the variation in the grease film thickness was obtained by measuring electrical resistance at a bearing speed between 1 and 500 rpm for short running periods of 60 s. A “V-shape pattern” was evidenced with a minimum value of grease film thickness at around 10 rpm. Additionally, the electrical resistance methodology was considered, evidencing the good stability of the film thickness for long operation time at speeds between 200 rpm and 1500 rpm. After 8 running hours, minor fragmentation of the soap filaments was observed under the scanning electron microscope compared to the fresh grease structure, without affecting the thickness of the grease film. Full article

Background: Childhood overweight and obesity are increasing public health concerns globally, with a high prevalence in Chile, particularly in rural areas. Excess weight may impair physical fitness, affecting children’s overall health and development. Objectives: This study aimed to compare the physical fitness of schoolchildren with normal weight (NW) and overweight/obesity (OW/OB) from a rural school in Maule, Chile. Methods: A total of 87 students (boys and girls, aged 9–14 years) were evaluated and classified into NW and OW/OB groups based on their body mass index. Physical fitness was assessed using the 6 min walk test (6MWT) for cardiovascular endurance, handgrip strength (HGS) and squat jump (SJ) for muscular strength, 20 m sprint for speed, and 4 × 10 m shuttle run for agility. Results: Significant differences were found between groups in most physical fitness components. The NW group covered 11.13% more distance in the 6MWT than the OW/OB group (p < 0.001; d = 1.28). NW children also performed better in the 20 m sprint (p = 0.023; d = 1.02) and the 4 × 10 m shuttle run (p < 0.001; d = 0.72). SJ was higher in the NW group (p = 0.004; d = 0.45). No significant differences were found in HGS (p = 0.893; d = 0.01). Conclusions: Children with normal weight demonstrated better physical fitness compared to their overweight or obese peers. These findings support the need for targeted strategies to prevent overweight and obesity in rural schoolchildren to improve physical health and functional capacities. Full article

Additively manufactured thermoplastic polyurethane (TPU 95A) is widely used in engineering, yet its machining behavior remains insufficiently explored. This study investigates the post-processing machinability of FDM-fabricated TPU 95A using CNC milling, with a particular focus on material removal rate (MRR) and surface roughness (Ra). A full factorial design of experiments (81 runs) is conducted, considering four input parameters such as spindle speed (N; 2000, 4000, 6000 rpm) and feed rate (F; 100, 200, 300 mm/min) on the CNC vertical machining center, together with infill density (ϕ; 33%, 66%, 100%) and layer thickness (LT; 1.0, 1.5, 2.0 mm). MRR is modeled and optimized across all densities, achieving strong fit (R² = 0.94; Adj-R² = 0.93). The optimum conditions are found to be MRR ≈ 1251 mm³/min at F = 300 mm/min, ϕ = 100%, N ≈ 3500 rpm and LT ≈ 1.05 mm. Ra can only be measured for 100% infill specimens, as lower infill surfaces violate profile measurement requirements. Its regression model shows weak explanatory power (R² = 0.14; Adj-R² = 0.03) and is excluded from optimization. Instead, Ra is reported descriptively: milling reduced roughness from ≈25–30 μm (as-printed) to ≈13.8 μm under favorable conditions. Overall, the study highlights machining’s role in the hybrid manufacturing practice. Full article