Search Results (64,299)

In padel, an emerging racket sport, evidence regarding competition demands in adolescent players remains limited. Therefore, this study aimed to analyze absolute external load during official competition in male and female U18 padel players. A total of 18 official matches from the Spanish Championship of Regional Teams were analyzed. Eighteen U18 players (9 females: age 15.1 ± 1.5 years, height 162.9 ± 8.2 cm, body mass 54.6 ± 9.1 kg; 9 males: age 15.4 ± 1.8 years, height 175.1 ± 9.4 cm, body mass 67.2 ± 11.0 kg), competing at the regional and national levels, were monitored using OLIVER™ inertial devices. External load variables included playing time, total distance, high-intensity accelerations and decelerations, changes of direction, time spent at high metabolic power, session volume, session intensity, and maximum speed. Statistical analysis was performed using linear mixed models to compare differences between sexes. Male players showed significantly higher values than female players in playing time (82.34 ± 23.95 vs. 51.03 ± 12.39 min; p < 0.001) and total distance (3958.50 ± 242.57 vs. 2225.54 ± 257.29 m; p < 0.001). They also presented significantly greater values in high-intensity external load variables, including accelerations, decelerations, changes of direction, time spent at high metabolic power, session volume, and session intensity (all p ≤ 0.009). No significant differences were found for maximum speed (p = 0.074). These findings suggest that official competition demands differ according to sex in U18 padel and may help inform more specific training prescriptions and load-monitoring strategies. Full article

Fused Filament Fabrication (FFF) is a widely used additive manufacturing technology due to its versatility, low cost, and broad material compatibility. However, achieving high dimensional accuracy in FFF parts remains challenging because dimensional deviations are affected by material shrinkage, process parameters, and part geometry. This study analyses the dimensional deviations of PLA hollow cylindrical specimens manufactured by FFF, with particular attention to the different behaviour of outer and inner diameters. The methodology combines an iterative design-adjustment procedure with a neural-network-based compensation approach. First, specimens with different geometries were printed and measured to evaluate the evolution of dimensional error after successive design corrections. Then, the influence of print speed and layer thickness was analysed through the volumetric material flow rate, and the resulting data were used to train separate feedforward neural networks for the outer and inner diameters. The results showed that outer and inner diameters followed different deviation trends, confirming that they should be analysed independently. Print speed, layer thickness, and material flow affected dimensional accuracy in different ways depending on the measured diameter. The proposed neural network approach provided a practical means of estimating compensated design diameters within the experimental domain analysed, reducing the need for repeated trial and error adjustments. However, the results should be interpreted within the experimental limits of the study, particularly regarding the use of a single material, a single printer, and a limited validation dataset. Overall, the study provides a practical workflow for improving dimensional accuracy in FFF parts and highlights the importance of diameter-specific compensation strategies. Full article

Waste from the fruit juice industry presents high sugar and phenolic contents, high humidity and biological activities and cumbersome disposal or low-added valorization. Orange-peel waste (OPW) represents 35–55% w/w of processed fruit, with oranges being the main citric crop. OPW saccharification leads to sugar-rich hydrolysates that can be further processed via fermentative and catalytic routes. In this work, OPW enzymatic hydrolysis was studied via batch and fed-batch processing using either a 50 mM citrate buffer or a 9 g/L NaCl solution with pH control by adding CaCO₃ to ensure high enzyme activity across the enzymatic process. Preliminary runs showed that particle size of 3.4 mm diameter and a 300 r.p.m. stirring speed, a six-blade Rushton turbine and wall baffles were adequate to reach high sugar yields in batch. Further scale-up in batch at medium solid loading (12.5% w/w) and fed-batch operation at high-solid loading (20% w/w) led to high yields and glucose and fermentable sugars (up to 74 and 136 g/L, respectively, when using the saline solution and CaCO₃ as pH-controlling agent, in only 50 h; notably shorter and higher than when using the citrate buffer). Fractal kinetic models have been shown to accurately represent the compositional change across all batch and fed-batch conditions, highlighting NaCl reaction medium and alkali-driven pH control as the most appropriate approach to achieve high yields at low process times, a promising result for further developments at demonstration and industrial scales using automatic pH control. Full article

Skeletal kinetic mechanisms are essential for reducing the computational cost of ammonia combustion simulations while retaining the key chemical features governing ignition, flame propagation, and NO formation. This study extends the DRG-CSP-ANN reduction and optimization framework to ammonia combustion over a broader multi-condition parameter space, aiming to develop a compact skeletal mechanism applicable to different pressures, equivalence ratios, and temperatures. Sixteen detailed ammonia combustion mechanisms were first assessed against experimental data covering ignition delay time, laminar flame speed, and NOx species concentrations over wide ranges of pressure, temperature, equivalence ratio, and oxidizer composition. Based on the overall error evaluation, the detailed mechanism with the most balanced predictive performance was selected as the parent mechanism. The parent mechanism was then reduced using the Directed Relation Graph and Computational Singular Perturbation methods, yielding an initial skeletal mechanism, RA-Ori, with 20 species and 76 reactions. To compensate for the accuracy loss caused by mechanism reduction, an Artificial Neural Network surrogate was constructed to optimize the pre-exponential factors of selected sensitive reactions within their evaluated uncertainty ranges, leading to the final mechanism, RA-ANN. The validation results show that RA-ANN reasonably reproduces ignition delay times, laminar flame speeds, and NO concentrations under different ammonia combustion conditions. Quantitatively, RA-ANN reduces the overall error from 0.335 for RA-Ori to 0.206, corresponding to a 38.4% reduction, while maintaining the same compact size. Its overall error is close to that of the parent detailed mechanism and lower than that of several existing skeletal mechanisms considered in this work. These results demonstrate that the proposed DRG-CSP-ANN strategy can construct a compact ammonia skeletal mechanism that achieves a favorable balance between computational efficiency, predictive accuracy, and applicability over representative multi-condition ammonia combustion regimes. Full article

Tooth segmentation from dental meshes is a fundamental step in clinical applications such as computer-aided orthodontics and dental implantation. Compared with mature image segmentation, deep learning-based mesh segmentation research is currently in a high-speed development stage. This study follows a dual-flow personalized feature learning scheme based on meshes and researches high-resolution mesh segmentation problems for clinical needs, proposing a dual-flow deep learning architecture called Position Shape Network (PSNet). Its basic idea includes continuously adjusting the feature map size in the network layer to enhance the model’s generalization ability and designing a reasonable branch structure to personalize the learning of position attributes represented by coordinates and shape attributes represented by surface perimeter area. In addition, it is proposed that the resolution of the validation set should be determined by comprehensively analyzing and simplifying errors to ensure the credibility of the model evaluation. Under this evaluation system, PSNet was compared with relevant authoritative methods in experiments, and the results verified the rationality and efficiency of the method and viewpoint proposed in this paper. Full article

Vernacular settlements in hot–humid regions preserve climate-responsive spatial knowledge, yet evidence on how linked outdoor, transitional, and indoor spaces jointly shape microclimate and thermal comfort remains limited. This study investigates a compact Hakka settlement in southern Jiangxi, China, by integrating field measurements, calibrated simulation, PET-based thermal-comfort assessment, and parametric scenario comparison to examine microclimatic differentiation across cold alleys, patios, halls, semi-open interfaces, and interior rooms. The results reveal clear microclimatic gradients across the linked vernacular spatial sequence. During the summer afternoon peak, cold alleys reduced air temperature by approximately 2.5 °C and PET by approximately 8.5 °C relative to ordinary streets, while semi-enclosed spaces adjacent to patios reduced air temperature by approximately 4.0 °C but increased relative humidity by 8–12%, indicating a cooling–moisture trade-off. Measured and simulated air temperature and wind speed showed satisfactory agreement and reproduced the main thermal and ventilation hierarchy across the connected spaces. Parametric comparison further identified case-based geometry-performance tendencies under the tested boundary conditions: within the tested cold-alley scenarios, widths of approximately 0.8–1.4 m combined with an H/W ratio close to 3:1 showed relatively favorable airflow-temperature performance in terms of shading continuity, moderated airflow, and reduced summer thermal exposure. The findings suggest that thermal comfort in compact hot–humid vernacular settlements depends on radiant-load reduction, moderated ventilation, and thermal buffering rather than on ventilation enhancement alone. Beyond the case-specific evidence, this study contributes a sequence-based, locally calibratable approach for preliminary retrofit appraisal in comparable compact hot–humid vernacular settlements. Full article

In the field of traditional aging state evaluation of paper materials, traditional detection technologies such as ink drop method and chemical analysis have inherent limitations including sample damage, strong subjectivity, and inability to realize large-area detection. To address these problems, a non-contact and non-destructive testing method based on air-coupled ultrasonic technology was developed in this study, to achieve objective and quantitative characterization of paper roughening degree and ink wettability. The system adopted a LabVIEW-based host computer to control scanning and signal acquisition. Based on the propagation and scattering mechanism of ultrasound in the porous fiber structure of paper, the amplitude difference and pixel distribution of C-scan images were extracted as core characteristic parameters. The experimental results show that, with a 400 kHz air-coupled probe and 200 mm/s scanning speed, the roughening degree of paper can be quantitatively characterized by the amplitude difference of ultrasonic transmission signals. The amplitude difference increases significantly with the rise of water content, and the difference in roughening characteristics between newsprint and Xuan paper can be clearly distinguished. The ink wettability can be judged by the pixel distribution of the C-scan image: the higher the proportion of intermediate color pixels, the closer the ink circularity is to 1, and the better the ink wettability. All test results are highly consistent with the national standard GB/T 18739-2008. The constructed air-coupled ultrasonic testing system can provide reliable technical support for quality control and aging evaluation of paper cultural relics and high-grade paper by characterizing both surface roughening and internal porous structure (which are coupled during paper aging), without any contact or damage to the samples. Full article

Rapid, accurate, and scalable ion sensing technologies are highly desirable for future flexible healthcare and lab-on-a-chip applications. Here, we present a fully roll-to-roll (R2R) gravure-printed single-walled carbon nanotube complementary ring oscillator (SWCNT-cRO)-based microfluidic ion sensing platform fabricated on a flexible substrate. The proposed platform combines scalable printed complementary electronics with frequency-based ion sensing via electrostatically induced top-gating in aqueous microfluidic environments. The fabricated SWCNT-cRO devices exhibited stable oscillation characteristics, with a high device yield (>80%) and continuous manufacturing capability at a web speed of 5.4 m/min. Printable ethanolamine/zirconium acetylacetonate-based n-doping technology enabled complementary SWCNT transistor operation, while multilayer CYTOP/FG-3650 encapsulation ensured stable electrical operation under ionic aqueous conditions. After integration into a polydimethylsiloxane-based microfluidic channel, the oscillation frequency of the SWCNT-cRO was systematically modulated by Na⁺ concentration and pH. The sensing mechanism was based on electrostatically induced carrier modulation in n-type SWCNT transistors, resulting in variations in propagation delay and corresponding shifts in oscillation frequency. Compared with conventional ion-sensitive transistor platforms, the proposed approach offers scalable manufacturing, non-contact ion sensing, elimination of external reference electrodes, and direct compatibility with digital frequency-signal processing systems. This work establishes a promising strategy for future low-cost, disposable, and flexible microfluidic sensing platforms for wearable healthcare and lab-on-a-chip applications, ion sensing, and thin-film transistors. Full article

Routine monitoring in racehorses requires indicators that are reproducible and practical under real training conditions. This observational study evaluated the short-term reproducibility of cardiovascular and speed indicators in French Standardbred trotters, with a particular focus on cardiac cost (CC), defined as the ratio of heart rate to speed (beats·m⁻¹). The full dataset comprised 483 sessions from 60 trotters and was used to describe age-related patterns. For reproducibility analyses, consecutive monitored sessions within the same horse were grouped into follow-up blocks when the interval between two successive sessions did not exceed 7 days. Only follow-up blocks containing at least three sessions were retained, resulting in 36 blocks, 126 sessions, and 18 horses. Each session included a warm-up, two 2000 m work blocks at increasing intensity, and recovery periods, while heart rate and speed were recorded using a Polar Team Pro system. Adjusted intraclass correlation coefficients indicated moderate reproducibility for CC during the first work block (CC B1: 0.67, 95% CI 0.48–0.78), heart rate recovery (HRR) after B1 (0.60, 0.40–0.73) and B2 (0.66, 0.47–0.78), and V150 (0.59, 0.39–0.73), whereas V180, recovery speed, and CC during B2 showed poor reproducibility. Reproducibility of CC B1 and HRR was preserved after adjustment for ambient temperature. In the full dataset, V200 increased with age, consistent with previous field-test literature. The minimal detectable change was 0.04 beats·m⁻¹ for CC B1 and 26 bpm for HRR after B1. These findings suggest that CC B1, HRR, and V150 may be useful indicators for short-term monitoring, although results should be interpreted considering the single-yard design. Full article

Rapid detection of Pseudomonas aeruginosa and its virulence factor ExoU is essential for improving patient outcomes. In this study, a CRISPR–Cas13a-based diagnostic assay combined with recombinase polymerase amplification (RPA) was developed to detect P. aeruginosa and the exoU gene in blood samples. The assay demonstrated robust amplification, with detection limits of 6 log₁₀ and 8 log₁₀ CFU/mL in Luria–Bertani medium and blood, respectively, and a 100% specificity, without cross-reactivity against four Gram-negative bacilli and Staphylococcus aureus reference strains. The utilisation of a fluorescence-based readout facilitated unambiguous discrimination between P. aeruginosa and P. aeruginosa/exoU⁺ isolates vs. negative controls. In conclusion, these results support the potential of RPA/CRISPR-Cas13a diagnostics for the rapid identification of P. aeruginosa and its ExoU virulence factor. Further optimisation and clinical validation are required to confirm its utility as a bedside diagnostic test, where its application would speed up clinical decisions in the treatment of these infections. Full article

In emergency response, dispatch speed and trauma-center activation depend on accurate severity classification. Current classifiers face two problems: extreme class imbalance and a semantic gap that leaves numerical models blind to textual severity cues. Resampling methods adjust class distributions but add no new information, while LLM-based hybrids exhibit feature dilution, where numerical priors override semantic reasoning. We propose SAFE (Semantic-Augmented Fusion Ensemble), a framework that routes features through parallel branches: XGBoost for numerical data and a Small Language Model for text. Structured records are enriched into narratives with severity-predictive keywords. The branches merge through class-adaptive probability fusion, governed by an analytically derived condition that preserves minority-class detections against majority-biased priors. On the US Accidents dataset and UK road accident records, Severe Recall rises from 30.7% (RF + SMOTE) to 91.2%, with overall accuracy reaching 83.3%; Serious Recall reaches 54.5% against 33.8% (XGBoost + SMOTE-ENN) on UK data. Keyword enrichment is essential: its removal collapses recall regardless of model size. SAFE enables severity-aware triage using only structured records that transportation agencies already collect. Deployment efficiency remains practical. SAFE achieves 188.4 ms mean per-sample latency at 5.3 samples/s on consumer hardware (Qwen3-4B INT8, 6.41 GB memory footprint), supporting operational batch classification of incident records. Full article

Array Gm-APD LiDAR is highly vulnerable to strong backscattering caused by dynamic smoke. Conventional depth imaging methods cannot rapidly identify the smoke occlusion state, which greatly reduces the target recovery quality of the reconstructed depth image. To solve this problem, this paper presents a non-parametric algorithm for rapid smoke detection and depth imaging for array Gm-APD LiDAR. The proposed method does not rely on parameter estimation of the echo model. Instead, it determines the presence of smoke occlusion by calculating the Pearson correlation coefficient between the echo signal obtained from the superposition of all array pixels and the instrument response function. In this way, the method rapidly identifies smoke interference in a single depth image, performs fast denoising, and reconstructs the depth image. In a dynamic smoke environment with an average attenuation length of no more than 5.1, the proposed algorithm achieves 100% accuracy in occlusion discrimination based on 250 frames of array data. When the smoke occlusion rate reaches 96% and the average attenuation length is 2.29, the method obtains a target recovery of 0.71, which is 86.8% higher than that of the conventional algorithm. These results indicate that the proposed method has strong practical value for array Gm-APD LiDAR, especially for high-speed depth imaging in harsh atmospheric environments with severe obscuration. Full article

This study examines how urban transportation systems influence the spatial spread of infectious diseases by developing a modified Susceptible–Exposed–Infected–Recovered (SEIR) model with explicit intercity travel dynamics. The model distinguishes between two mobility mechanisms: travel volume, represented by the departure rate g, and travel speed, represented by the arrival rate $\alpha$. Using the next-generation matrix (NGM) approach, we derive the basic reproduction number $R_0$ and analyse how within-city and transit-phase transmission contribute to epidemic spread. The results show that travel volume and travel speed affect mobility-driven transmission through distinct mechanisms. Increasing g increases the number of travelers entering the transit system and therefore amplifies the aggregate number of transit-mediated infections, although the per-capita transit reproduction expression is governed primarily by $\alpha$ and ${\beta }_d^T$ under the reduced next generation matrix formulation formulation. By contrast, increasing $\alpha$ shortens the time spent in transit, reduces the exposure window during travel, and lowers the per-capita contribution of transit-based infection to $R_0$. Numerical simulations illustrate these effects and support the conclusion that reducing travel volume can mitigate intercity epidemic spread by decreasing the number of potentially exposed travelers. Comparative case studies for Brazil, New Zealand, China, and Algeria are used to evaluate the model under different epidemiological settings and socioeconomic contexts. These socioeconomic indicators are treated as contextual background rather than as direct inputs to the mathematical model. The qualitative predictions of the ordinary differential equation (ODE) model are further cross-validated using an agent-based simulation implemented in NetLogo. Overall, the study shows that separating travel volume from travel speed provides a more precise understanding of mobility-driven disease transmission and can support the design of targeted travel-related control measures. Full article

Modeling and controlling multilayer complex network dynamics is challenging under coexisting crosslayer interactions, higher-order couplings, and decentralized strategic decisions. Most existing schemes focus on graph-based pairwise structures and overlook topological cavities, mesoscale loops, and layered self-interested actions. This paper presents TopoGame-MND, an algebraic-topological and game-theoretic framework for multilayer network dynamics. We first build a filtration-driven simplicial lifting to unify pairwise and higher-order interactions into a weighted multilayer simplicial complex. A topological state operator using generalized Hodge Laplacians and persistent homology is then constructed to characterize cross-scale diffusion, circulation, and structural inconsistency. A distributed potential-game mechanism is developed with a topology-aware utility, followed by a proximal mirror-best-response algorithm with consensus correction. We prove Nash equilibrium existence and uniqueness, global potential monotone descent, linear convergence, computational complexity, and input-to-state robustness. Simulations on multiplex and interdependent networks validate that TopoGame-MND outperforms baselines in regulation speed, oscillation energy, failure resilience, and robustness, providing a unified way to connect higher-order topology and distributed decision optimization. Full article

Wire Arc Additive Manufacturing (WAAM) has emerged as a cost-effective and high-deposition-rate technique for fabricating large-scale metallic components; however, the complex thermal history inherent to the process leads to heterogeneous microstructures that can significantly influence tribological performance. In this study, the dry sliding wear behavior of WAAM-fabricated austenitic stainless steel 308L (SS308L) was systematically investigated using a pin-on-disk configuration. The influence of applied normal load (1.5–15 N) and sliding speed (0.03–0.229 m/s) on wear volume, specific wear rate, coefficient of friction (COF), and tangential force was evaluated. Optical microstructural observations indicated features consistent with a ferritic–austenitic solidification structure, including regions resembling polygonal ferrite, Widmanstätten ferrite, and austenitic dendritic morphologies. Wear results showed that wear volume and cross-sectional area increased monotonically with increasing load, while the effect of sliding speed was comparatively less significant. The specific wear rate remained on the order of 10⁻⁴ mm³/N·m with minor variations across test conditions. The COF decreased with increasing load up to 10 N, followed by a speed-dependent response at higher loads. The findings demonstrate that load is the dominant factor governing wear behavior in WAAM SS308L, while microstructural heterogeneity may contribute to frictional stability and wear resistance. This study provides valuable insight into the structure–tribology relationship of WAAM stainless steels and supports the optimization of process parameters for wear-critical applications. Full article