Search Results (210)

High-performance hydrogen gas sensors have gained considerable interest for their crucial function in reducing H₂ explosion risk. Although MoS₂ has good potential for chemical sensing, its application in hydrogen detection at room temperature is limited by slow response and incomplete recovery. In this work, Pd-doped MoS₂ thin films are deposited on a Si substrate, forming Pd-doped MoS₂/Si heterojunctions via magnetron co-sputtering. The incorporation of Pd nanoparticles significantly enhances the catalytic activity for hydrogen adsorption and facilitates more efficient electron transfer. Owing to its distinct structural characteristics and sharp interface properties, the fabricated Pd-doped MoS₂/Si heterojunction device exhibits excellent H₂ sensing performance under room temperature conditions. The gas sensor device achieves an impressive sensing response of ~6.4 × 10³% under 10,000 ppm H₂ concentration, representing a 110% improvement compared to pristine MoS₂. Furthermore, the fabricated heterojunction device demonstrates rapid response and recovery times (24.6/12.2 s), excellent repeatability, strong humidity resistance, and a ppb-level detection limit. These results demonstrate the promising application prospects of Pd-doped MoS₂/Si heterojunctions in the development of advanced gas sensing devices. Full article

With the rapid development of smart devices and the Internet of Things (IoT), the explosive growth of data has placed increasingly higher demands on real-time processing and intelligent decision making. Cloud-edge collaborative computing has emerged as a mainstream architecture to address these challenges. However, in sky-ground integrated systems, the limited computing capacity of edge devices and the inconsistency between cloud-side fusion results and edge-side detection outputs significantly undermine the reliability of edge inference. To overcome these issues, this paper proposes a cloud-edge collaborative model adaptation framework that integrates deep reinforcement learning via Deep Q-Networks (DQN) with local feature transfer. The framework enables category-level dynamic decision making, allowing for selective migration of classification head parameters to achieve on-demand adaptive optimization of the edge model and enhance consistency between cloud and edge results. Extensive experiments conducted on a large-scale multi-view remote sensing aircraft detection dataset demonstrate that the proposed method significantly improves cloud-edge consistency. The detection consistency rate reaches 90%, with some scenarios approaching 100%. Ablation studies further validate the necessity of the DQN-based decision strategy, which clearly outperforms static heuristics. In the model adaptation comparison, the proposed method improves the detection precision of the A321 category from 70.30% to 71.00% and the average precision (AP) from 53.66% to 53.71%. For the A330 category, the precision increases from 32.26% to 39.62%, indicating strong adaptability across different target types. This study offers a novel and effective solution for cloud-edge model adaptation under resource-constrained conditions, enhancing both the consistency of cloud-edge fusion and the robustness of edge-side intelligent inference. Full article

Quantum Dots (QDs) are small semiconductor nanoparticles (<10 nm) with strong, relatively stable, and tunable luminescent properties, which are increasingly applied in the sensing and detection of various analytes, including metal ions, biomarkers, explosives, proteins, RNA/DNA fragments, pesticides, drugs, and pollutants. In this review, we critically assess recent developments and advancements in luminescent QD-based sensors from an analytical perspective. We collected, tabulated, and analyzed relevant data reported in 124 peer-reviewed articles. The key analytical figures of merit, including the limit of detection (LOD), excitation and emission wavelengths, and size of the particles were extracted, tabulated, and analyzed with graphical representations. We calculated the geometric mean and median LODs from those tabulated publications. We found the following geometric mean LODs: 38 nM for QD-fluorescent-based sensors, 26 nM for QD-phosphorescent-based sensors, and an impressively low 0.109 pM for QD-chemiluminescent-based sensors, which demonstrate by far the best sensitivity in QD-based detection. Moreover, AI-based sensing methods, including the ATTBeadNet model, optimized principal component analysis(OPCA) model, and Support Vector Machine (SVM)-based system, were reviewed as they enhance the analytical performance of the detection. Despite these advances, there are still challenges that include improvements in recovery values, biocompatibility, stability, and overall performance. This review highlights trends to guide the future design of robust, high-performance, QD-based luminescent sensors. Full article

Maximal and explosive strength—defined as the ability to rapidly generate high levels of force—are widely recognized as critical for performance in strength–power sports such as track and field throwing. However, their interrelationship remains insufficiently examined, particularly in the upper body of elite athletes. This study examined the relationship between early force production (≤250 ms, subdivided into early phase: 0–100 ms; late phase: 100–250 ms) and peak isometric upper-body push and pull force in elite Swedish track and field throwers. A total of 30 athletes (17 females, 13 males; aged 18–34 years), all competing nationally or internationally in discus, hammer, shot put, or javelin, participated in a cross-sectional assessment. Isometric force was measured during bench press (push) and supine bench row (pull) using a custom-built device. Force output was recorded at 50, 100, 150, 200, and 250 ms, along with peak force. The results showed a progressive increase in the correlation between force at early time points and peak force. Associations were weak to moderate at 50–100 ms (r = 0.07–0.55) and became strong to very strong at 150–250 ms (r = 0.64–0.92). These patterns were consistent across sexes and test types. The findings suggest that maximal strength becomes increasingly important as force production time extends beyond 100 ms. Coaches may benefit from assessing both early and peak force characteristics to inform strength profiling and guide training focus, though further research is needed to determine their impact on performance. Full article

Background and Objectives: This study aims to investigate the relationship between isokinetic knee strength and competition performance in elite male ski mountaineering sprint athletes and to identify strength parameters that predict performance and contribute to injury prevention. Materials and Methods: Thirteen male athletes participating in the Ski Mountaineering Turkey Cup final stage were included. Isokinetic knee flexion (FLX) and extension (EXT) strength of dominant (DM) and non-dominant (NDM) legs were measured at angular velocities of 60°/s and 180°/s using the DIERS-Myolin Isometric Muscle Strength Analysis System. Competition performance was evaluated using the ISMF scoring system. Data were analyzed using SPSS 26.0 with Pearson correlation and multiple regression analyses after normality, linearity, and homoscedasticity checks. Results: Strong positive correlations were found between hamstring strength at high angular velocities (180°/s) and performance (DM FLX: r = 0.809; NDM FLX: r = 0.880). Extension strength showed moderate correlations at low velocities (60°/s) (DM EXT: r = 0.677; NDM EXT: r = 0.699). Regression analysis revealed that DM FLX at 180°/s and DM EXT at 60°/s explained 49% of performance variance (Adj. R² = 0.498). For NDM legs, only 180°/s FLX was a significant predictor (β = 1.468). Conclusions: High-velocity hamstring strength plays a critical role in ski mountaineering sprint performance, particularly during sudden directional changes and dynamic balance. Quadriceps strength at low velocities contributes to prolonged climbing phases. Moreover, identifying and addressing bilateral strength asymmetries may support injury prevention strategies in elite ski mountaineering athletes. These findings provide scientific support for designing training programs targeting explosive hamstring strength, bilateral symmetry, and injury risk reduction, essential for optimizing performance in the 2026 Winter Olympics sprint discipline. Full article

Background: Understanding the relationship between physical fitness and body mass index (BMI) is critical for promoting adolescent health, particularly in Saudi Arabia, where cultural norms and rising obesity rates present unique challenges. This study aimed to investigate the impact of BMI, gender, and physical activity levels on lower limb strength and endurance, as measured by the Standing Long Jump (SLJ) and the 1 min Sit-to-Stand (STS) test, respectively. Methods: This cross-sectional study included 100 healthy Saudi adolescents (44 boys, 56 girls) aged 10–18 years. Lower limb strength and endurance were assessed using SLJ (cm) and STS (repetitions/min). Anthropometric measurements included BMI (kg/m²), weight (kg), and height (cm), while physical activity was assessed using the Physical Activity Questionnaire for Adolescents (PAQ-A). Mediation analysis was conducted to examine the potential indirect effects of BMI, PAQ-A score, and age on the relationship between SLJ and STS performance. Results: Boys significantly outperformed girls in both the STS (mean difference = 25.2 repetitions/min; p < 0.001) and SLJ (mean difference = 73.4 cm; p < 0.001). No significant gender differences were found in PAQ-A scores (p = 0.987). A strong positive correlation was observed between SLJ and STS performance (r = 0.768; p < 0.01). BMI was not significantly correlated with SLJ or STS performance. STS repetitions predicted superior SLJ performance both before (β = 0.55, p < 0.001) and after (β = 0.47, p = 0.004) adjustment for BMI, age, PAQ score, and gender. BMI transmitted only a small, non-significant share of this link (indirect β = 0.08, p = 0.122), indicating that the STS–SLJ association is largely direct (model R² for SLJ = 0.84). Conclusions: Explosive lower limb strength and gender were significant predictors of lower-body endurance, whereas BMI showed a limited association with performance. These findings underscore the importance of incorporating gender-specific strategies in adolescent fitness assessments and interventions, with a cautionary interpretation of BMI as a performance indicator. Full article

Cellulosic raw materials are the most common source of carbon on Earth and are in great demand for the production of high-value-added products. Cellulosic feedstocks represent a strong matrix consisting of cellulose, lignin, and hemicelluloses. The efficient transformation of cellulosic raw materials into fermentable sugars requires the use of effective pretreatment strategies. The methods employed for pretreatment should be efficient, have low operating costs, and exhibit lower environmental impact. The present review describes pretreatment methods like liquid hot water (LHW) and steam explosion (SE) and highlights peculiar features, benefits and disadvantages of these processes. The effectiveness of these pretreatment methods and their effect on cellulosic raw materials strongly depends on the type of feedstock (component composition), pretreatment method, and pretreatment conditions (pressure, temperature, time, etc.). The LHW pretreatment requires neither addition of chemicals and catalysts nor grinding stage, but requires high energy inputs. The SE pretreatment is regarded as environmentally friendly and requires lower energy inputs, but contributes to the formation of toxic compounds. The life cycle assessment approach demonstrated that the SE pretreatment outperforms dilute acid pretreatment methods and allows the reduction of energy inputs, thereby improving the environmental performance of the process, while the LHW method improves long-term energy security and creates a greener future. Full article

(1) Background: Research examining the combined influence of anthropometric characteristics, chronological age, and training age on motor performance in handball is limited. Given the sport’s demands and the participation of both adolescent and adult athletes, understanding these relationships is essential for talent identification, personalized training, and long-term athlete development. This study aimed to explore how these variables affect motor performance indicators such as speed, agility, and explosive power. (2) Methods: A cross-sectional study was conducted involving 29 male handball players. Anthropometric data (height and body weight), chronological age, and training age were collected. Motor performance was assessed using a 30 m sprint, a vertical jump test, and an agility test. (3) Results: Chronological age showed a strong positive correlation with training age (r = 0.819), and moderate correlations with height, body weight, vertical jump, agility, and sprint time. Training age was moderately correlated with vertical jump (r = 0.465) and agility (r = 0.439). Height and body weight were positively associated with sprint time. BMI exhibited low but consistent correlations with all motor tests. Regression analysis revealed that height significantly predicted sprint performance (β = 0.401, p = 0.033), while BMI was not a significant predictor. No significant regression models were found for agility or vertical jump performance. (4) Conclusions: The results suggest that both chronological and training age influence certain aspects of motor performance in handball players. Height may serve as a useful predictor of sprint ability, but anthropometric indicators such as BMI appear insufficient for explaining performance in agility or explosive power tasks. These findings support the use of multidimensional and individualized approaches in athletic assessment and training design. Full article

Hydrogen is receiving a lot of attention from researchers as a clean energy source and one of the most promising sources of energy for the future. Detection of hydrogen before it reaches explosive conditions is a central issue in the safe use of hydrogen. Hydrogen sensors are devices that detect the hydrogen concentration in the environment and are capable of outputting an electrical signal proportional to the magnitude of the hydrogen concentration. Palladium (Pd) has become one of the preferred materials for the preparation of hydrogen sensors due to its strong hydrogen absorbing ability. In this paper, the intrinsic mechanism of hydrogen absorption by Pd metal is revealed, and the performance of various types of Pd-based hydrogen sensors is reviewed. Full article

Water transportation is a critical component of the overall transportation system. However, the gradual increase in traffic density has led to a corresponding rise in accident occurrences. This study proposes a quantitative framework for analyzing the evolutionary paths of maritime traffic accident risks by integrating complex network theory and link prediction methods. First, 371 maritime accident investigation reports were analyzed to identify the underlying risk factors associated with such incidents. A risk evolution network model was then constructed, within which the importance of each risk factor node was evaluated. Subsequently, several node similarity indices based on node importance were proposed. The performance of these indices was compared, and the optimal indicator was selected. This indicator was then integrated into the risk evolution network model to assess the interdependence between risk factors and accident types, ultimately identifying the most probable evolution paths from various risk factors to specific accident outcomes. The results show that the risk evolution path shows obvious characteristics: “lookout negligence” is highly correlated with collision accidents; “improper route selection” plays a critical role in the risk evolution of grounding and stranding incidents; “improper on-duty” is closely linked to sinking accidents; and “illegal operation” show a strong association with fire and explosion events. Additionally, the average risk evolution paths for collisions, groundings, and sinking accidents are relatively short, suggesting higher frequencies of occurrence for these accident types. This research provides crucial insights for managing water transportation systems and offers practical guidance for accident prevention and mitigation. Full article

Maritime safety is crucial as vessels underpin global trade, but engine room explosions threaten crew safety, the environment, and assets. With modern ship designs growing more complex, numerical simulation has become vital for analyzing and preventing such events. This study examines safety risks from alternative fuel explosions in ship engine rooms, using the Trinitrotoluene (TNT)-equivalent method. A finite element model of a double-layer cabin explosion is developed, and simulations using blastFOAM in OpenFOAM v9 analyze shock wave propagation and stress distribution. Four explosion locations and five scales were tested, revealing that explosion scale is the most influential factor on shock wave intensity and structural stress, followed by equipment layout, with location having the least—though still notable—impact. Near the control room, an initial explosion caused a peak overpressure of 2.4 × 10⁶ Pa. Increasing the charge mass from 10 kg to 50 kg raised overpressure to 3.9 × 10⁶ Pa, showing strong dependence of blast intensity on explosive mass. Equipment absorbs and reflects shock waves, amplifying localized stresses. The findings aid in optimizing engine room layouts and improving explosion resistance, particularly for alternative fuels like liquefied natural gas (LNG), enhancing maritime safety and sustainability. Full article

Background: We examined the effects of linear position transducer placement during Smith machine (SM) and free weight (FW) full squats on the mean velocity and the load–velocity relationship in trained women. In addition, we examined the relationship between the load–velocity characteristics and jump performance, to determine which testing approach is more appropriate for both the testing and transfer of training effects. Methods: Eleven trained women were assessed for 1-RM in FW and SM full back squats. Linear position transducers (LPTs) were attached to the barbell (BAR) and to the belt (BELT) during FW and SM full back squats. The mean velocity was measured across progressively increasing loads (30–100%). The load–velocity relationships were modeled using linear regression, and the velocity values, as well as the load–velocity parameters, were compared across all conditions (SM BAR, SM BELT, FW BAR, and FW BELT). Squat jump, countermovement jump, and drop jump performance were also assessed using an optical measurement system. Results: In SM compared to FW, 1-RM was higher (92.9 ± 16.2 kg vs. 85.1 ± 14.5 kg, p < 0.05, d = 0.53). A strong agreement was observed between the FW BAR and FW BELT (Lin’s concordance correlation coefficient CCC = 0.96–0.99), as well as between the SM BAR and FW BAR (CCC = 0.95–0.97) at low-to-moderate intensities (30–70% 1-RM), suggesting that these conditions can be used interchangeably. However, the SM BELT systematically showed lower mean velocity values at 30–80% 1-RM and exhibited low agreement across all other conditions. In contrast, the FW BELT mean velocity was lower than that of the FW BAR and SM BAR only at higher intensities (>80% 1-RM). V0 and mean velocities at low-to-moderate loads (30–70% 1-RM) showed strong correlations with all jump types, with relationships gradually weakening as the load increased (r = 0.63–0.93, p < 0.05). The highest correlations were observed in the SM BAR and FW BELT conditions. Lastly, the relative strength demonstrated a consistent relationship with squat jump and drop jump performance exclusively in the FW condition (r = 0.71 and 0.72, p < 0.05). Conclusions: The FW BAR and FW BELT showed strong agreement at submaximal loads and may be used interchangeably, while the SM BELT showed a lower mean velocity and low agreement with other conditions. The load–velocity relationship parameters and mean velocity at low-to-moderate loads correlated strongly with the jump performance. Coaches and practitioners can use bar-mounted and belt-mounted LPTs interchangeably during FW squats for velocity-based training at submaximal intensities when working with trained women. Additionally, tracking the mean velocity at low-to-moderate loads provides valuable insights into lower-body explosive performance, supporting more precise and individualized training prescriptions and performance monitoring. Full article

Increasing the proportion of clean energy within the energy structure is a crucial strategy for achieving energy transformation. Hydrogen and ammonia, as leaders in clean energy technologies, have garnered significant global attention. The combination of hydrogen and ammonia has emerged as a novel form of energy storage, transportation, and conversion; however, the safety aspects of their application process warrant closer attention. Research on hydrogen safety has been conducted extensively, with particular focus on the leakage, diffusion, combustion, and explosion processes. Both theoretical research and engineering applications have advanced significantly. In particular, hydrogen detection technology, primarily based on electrical measurement, has matured considerably, while schlieren imaging-based flow field visualization technology is progressing steadily. In contrast, safety research concerning ammonia remains in its early stages. Research on the leakage and diffusion characteristics of ammonia predominantly focuses on liquid ammonia, with a strong emphasis on engineering applications. Studies on the combustion and explosion characteristics of ammonia primarily address flame parameters and the combustion development laws. Ammonia serves as an efficient hydrogen storage medium. The conversion process involving hydrogen and ammonia will occur simultaneously in both time and space. Current research has not adequately addressed the safety concerns associated with the application process of hydrogen–ammonia mixtures. Future research on the safety of hydrogen–ammonia application processes should focus on the diffusion characteristics and combustion and explosion behaviors, as well as the development of electrical measurement detection technologies and optical flow field visualization techniques for hydrogen–ammonia mixtures. Full article

The purpose of this study was to investigate the benefits of a 12-week plyometric training program intervention on lower limb joint mobility, explosive strength, advanced layup success rates, and injury rates. The study recruited 15 collegiate male basketball players as participants. They underwent basketball training five times per week, each lasting two hours, and additionally received plyometric training twice a week. The study utilized image processing software (ImageJ, version 1.54f, National Institutes of Health, Bethesda, MD, USA) to measure the lower limb joint mobility during the take-off phase of a layup and employed a force plate to assess the explosive strength of the lower limbs during the jump. Furthermore, the study examined the success rate and injury rate of advanced layups—including crossover layups, spin layups, and straight-line layups—as well as the sports injury rate. The results demonstrated that plyometric training significantly enhanced the hip, knee, and ankle joint mobility as well as lower limb explosive strength, with a strong positive correlation between these variables. Furthermore, plyometric training improved joint mobility and lower limb explosive strength. The success rate of advanced layups increased from 50% to 72%, while the sports injury rate decreased from 18% to 8%. In conclusion, plyometric training significantly improved participants’ lower limb joint mobility and explosive strength, which in turn enhanced advanced layup performance and reduced the sports injury rate. Although this study provided preliminary evidence supporting the effectiveness of plyometric training, further research is needed to examine its long-term effects and other influencing factors. Full article

The low quality of business process event logs—particularly the widespread occurrence of incomplete traces—poses significant challenges to the reliability, accuracy, and efficiency of process mining analysis. In real-world scenarios, these data imperfections severely undermine the practical value of process mining techniques. The primary research problem addressed in this study is the inefficiency and limited effectiveness of existing Petri-net-based incomplete trace repair approaches, which often struggle to accurately recover missing events in the presence of complex and nested loop structures. To tackle these limitations, we aim to develop a faster and more accurate approach for repairing incomplete event logs. Specifically, we propose a novel repair approach based on process trees as an alternative to traditional Petri nets, thus alleviating issues such as state space explosion. Our approach incorporates process tree model decomposition and innovative branch indexing techniques, enabling rapid localization of candidate branches for repair and a significant reduction in the solution space. Furthermore, by leveraging activity information within the traces, our approach achieves efficient and precise repair of loop nodes through a single traversal of the process tree. To comprehensively evaluate our approach, we conduct experiments on four real-life and five synthetic event logs, comparing performance against state-of-the-art techniques. The experimental results demonstrate that our approach consistently delivers repair accuracies exceeding 70%, with time efficiency improved by up to three orders of magnitude. These findings validate the superior accuracy, efficiency, and scalability of the proposed approach, highlighting its strong potential for practical applications in business process mining. Full article