Search Results (5,122)

Fin-stabilized guided rockets exhibit ballistic characteristics such as low initial velocity, high flight altitude, and long flight duration, which render their impact point accuracy and flight stability highly susceptible to the influence of wind. In this paper, the four-dimensional nonlinear angular motion equations describing the changes in attack angle and the law of axis swing of a dual-spin rocket are established, and the phase trajectory and equilibrium point stability characteristics of the nonlinear angular motion system under windy conditions are analyzed. Aiming at the problem that the equilibrium point of the angular motion system cannot be solved analytically with the change in wind speed, a phase trajectory projection sequence method based on the Poincaré cross-section and stroboscopic mapping is proposed to analyze the effect of wind on the angular motion bifurcation characteristics of a dual-spin rocket. The possible instability of angular motion caused by nonlinear aerodynamics under strong wind conditions is explored. This study is of reference significance for the launch control and aerodynamic design of guided rockets in complex environments. Full article

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

Studying nonlinear oscillations in mechanical systems is fundamental to understanding complex dynamic behavior in engineering applications. While classical analytical methods remain valuable for systems with limited complexity, they become increasingly inadequate when nonlinearities are strong and geometrically induced, as in the case of large-amplitude oscillations. This paper presents a combined numerical and experimental investigation of a mechanical system composed of two coupled pendulums, exhibiting significant nonlinear behavior due to elastic deformation throughout their motion. A mathematical model of the system was developed using the MatLab/Simulink ver.6.1 environment, considering gravitational, inertial, and nonlinear elastic restoring forces. One of the major challenges in accurately modeling such systems is accurately representing damping, particularly in the absence of dedicated dampers. In this work, damping coefficients were experimentally identified through decrement measurements and incorporated into the simulation model to improve predictive accuracy. The simulation outputs, including angular displacements, velocities, accelerations, and phase trajectories over time, were validated against experimental results obtained via high-precision inertial sensors. The comparison shows a strong correlation between numerical and experimental data, with minimal relative errors in amplitude and frequency. This research represents the first stage of a broader study aimed at analyzing forced and parametrically excited oscillations. Beyond validating the model, the study contributes to the design of a robust experimental framework suitable for further exploration of nonlinear dynamics. The findings have practical implications for the development and control of mechanical systems subject to dynamic loads, with potential applications in automation, vibration analysis, and system diagnostics. Full article

Taking a composite goaf in goaf-side entry retaining as our research focus, a kilogram-level spontaneous combustion experiment was carried out, and limit parameters for coal spontaneous combustion characteristics were assessed. Combined with the key parameters of the site, a numerical model of a multi-area composite goaf was constructed, and the distribution features of the dangerous area for coal spontaneous combustion in the lower layer of in goaf-side entry retaining were determined by means of the upper and lower layer composite superposition division method. The results show that at a floating coal thickness in the goaf of 1.9 m, the lower limit of oxygen concentration C_min, upper limit of air leakage intensity, and corresponding seepage velocity are 6%, 0.282 cm⁻³·s⁻¹·cm⁻², and 11.28 × 10⁻³ m/s respectively. The dangerous area regarding residual coal on the intake side is 23~38 m away from the working face, while that on the return air side is concentrated amid the goaf at 23~75 m, and that on the flexible formwork wall is concentrated at 0~121 m. The research results are of crucial practical importance for the prevention and control of coal spontaneous combustion within a composite goaf. Full article

The automotive suspension must perform competently to support comfort and safety when driving. Traditionally, car suspension control tuning is performed through trial and error or with classical techniques that cannot guarantee optimal performance under varying road conditions. The study aims at designing a Linear Quadratic Regulator-based Bacterial Memetic Algorithm (LQR-BMA) for suspension systems of automobiles. BMA combines the bacterial foraging optimization algorithm (BFOA) and the memetic algorithm (MA) to enhance the effectiveness of its search process. An LQR control system adjusts the suspension’s behavior by determining the optimal feedback gains using BMA. The control objective is to significantly reduce the random vibration and oscillation of both the vehicle and the suspension system while driving, thereby making the ride smoother and enhancing road handling. The BMA adopts control parameters that support biological attraction, reproduction, and elimination-dispersal processes to accelerate the search and enhance the program’s stability. By using an algorithm, it explores several parts of space and improves its value to determine the optimal setting for the control gains. MATLAB 2024b software is used to run simulations with a randomly generated road profile that has a power spectral density (PSD) value obtained using the Fast Fourier Transform (FFT) method. The results of the LQR-BMA are compared with those of the optimized LQR based on the genetic algorithm (LQR-GA) and the Virus Evolutionary Genetic Algorithm (LQR-VEGA) to substantiate the potency of the proposed model. The outcomes reveal that the LQR-BMA effectuates efficient and highly stable control system performance compared to the LQR-GA and LQR-VEGA methods. From the results, the BMA-optimized model achieves reductions of 77.78%, 60.96%, 70.37%, and 73.81% in the sprung mass displacement, unsprung mass displacement, sprung mass velocity, and unsprung mass velocity responses, respectively, compared to the GA-optimized model. Moreover, the BMA-optimized model achieved a −59.57%, 38.76%, 94.67%, and 95.49% reduction in the sprung mass displacement, unsprung mass displacement, sprung mass velocity, and unsprung mass velocity responses, respectively, compared to the VEGA-optimized model. Full article

Four-dimensional (4D) flow MRI has shown promise for the assessment of aortic hemodynamics. However, data analysis traditionally requires manual and time-consuming human input at several stages. This limits reproducibility and affects analysis workflows, such that large-cohort 4D flow studies are lacking. Here, a fully automated artificial intelligence (AI) 4D flow analysis pipeline was developed and evaluated in a cohort of over 350 subjects. The 4D flow MRI analysis pipeline integrated a series of previously developed and validated deep learning networks, which replaced traditionally manual processing tasks (background-phase correction, noise masking, velocity anti-aliasing, aorta 3D segmentation). Hemodynamic parameters (global aortic pulse wave velocity (PWV), peak velocity, flow energetics) were automatically quantified. The pipeline was evaluated in a heterogeneous single-center cohort of 379 subjects (age = 43.5 ± 18.6 years, 118 female) who underwent 4D flow MRI of the thoracic aorta (n = 147 healthy controls, n = 147 patients with a bicuspid aortic valve [BAV], n = 10 with mechanical valve prostheses, n = 75 pediatric patients with hereditary aortic disease). Pipeline performance with BAV and control data was evaluated by comparing to manual analysis performed by two human observers. A fully automated 4D flow pipeline analysis was successfully performed in 365 of 379 patients (96%). Pipeline-based quantification of aortic hemodynamics was closely correlated with manual analysis results (peak velocity: r = 1.00, p < 0.001; PWV: r = 0.99, p < 0.001; flow energetics: r = 0.99, p < 0.001; overall r ≥ 0.99, p < 0.001). Bland–Altman analysis showed close agreement for all hemodynamic parameters (bias 1–3%, limits of agreement 6–22%). Notably, limits of agreement between different human observers’ quantifications were moderate (4–20%). In addition, the pipeline 4D flow analysis closely reproduced hemodynamic differences between age-matched adult BAV patients and controls (median peak velocity: 1.74 m/s [automated] or 1.76 m/s [manual] BAV vs. 1.31 [auto.] vs. 1.29 [manu.] controls, p < 0.005; PWV: 6.4–6.6 m/s all groups, any processing [no significant differences]; kinetic energy: 4.9 μJ [auto.] or 5.0 μJ [manu.] BAV vs. 3.1 μJ [both] control, p < 0.005). This study presents a framework for the complete automation of quantitative 4D flow MRI data processing with a failure rate of less than 5%, offering improved measurement reliability in quantitative 4D flow MRI. Future studies are warranted to reduced failure rates and evaluate pipeline performance across multiple centers. Full article

In modern vehicles, Autonomous Driving Systems (ADSs) are designed to operate partially or fully without human intervention. The ADS pipeline comprises multiple layers, including sensors, perception, localization, mapping, path planning, and control. The Robot Operating System (ROS) is a widely adopted framework that supports the modular development and integration of these layers. Among them, the path-planning and control layers remain particularly challenging due to several limitations. Classical path planners often struggle with non-smooth trajectories and high computational demands. Meta-heuristic optimization algorithms have demonstrated strong theoretical potential in path planning; however, they are rarely implemented in real-time ROS-based systems due to integration challenges. Similarly, traditional PID controllers require manual tuning and are unable to adapt to system disturbances. This paper proposes a ROS-based ADS architecture composed of eight integrated nodes, designed to address these limitations. The path-planning node leverages a meta-heuristic optimization framework with a cost function that evaluates path feasibility using occupancy grids from the Hector SLAM and obstacle clusters detected through the DBSCAN algorithm. A dynamic goal-allocation strategy is introduced based on the LiDAR range and spatial boundaries to enhance planning flexibility. In the control layer, a modified Pure Pursuit algorithm is employed to translate target positions into velocity commands based on the drift angle. Additionally, an adaptive PID controller is tuned in real time using the Differential Evolution (DE) algorithm, ensuring robust speed regulation in the presence of external disturbances. The proposed system is practically validated on a four-wheel differential drive robot across six scenarios. Experimental results demonstrate that the proposed planner significantly outperforms state-of-the-art methods, ranking first in the Friedman test with a significance level less than 0.05, confirming the effectiveness of the proposed architecture. Full article

Aiming at the goal of preparing high-quality coatings, this paper reviews the progress on circular arc source structure and magnetic field arc controlling technology in arc ion plating (AIP), with a focus on design characteristics of the different structures and configuration optimization of the corresponding magnetic fields. The circular arc source, due to its simple structure, convenient installation, flexible target combination, high cooling efficiency, and high ionization rate and deposition rate, has shown significant application potential in AIP technology. In terms of magnetic field arc controlling technology, this paper delves into the design progress of various magnetic field configurations, including fixed magnetic fields generated by permanent magnets, dynamic rotating magnetic fields, axially symmetric magnetic fields, rotating transverse magnetic fields, and multi-mode alternating electromagnetic coupling fields. By designing the magnetic field distribution reasonably, the trajectory and velocity of the arc spot can be controlled precisely, thus reducing the generation of macroparticles, improving target utilization, and enhancing coating uniformity. In particular, the introduction of multi-mode magnetic field coupling technology has broken through the limitations of traditional single magnetic field structures, achieving comprehensive optimization of arc spot motion and plasma transport. Hopefully, these research advances provide an important theoretical basis and technical support for the application of AIP technology in the preparation for high-quality decorative and functional coatings. Full article

Background and Objectives: Type 2 diabetes mellitus (T2DM) is associated with subclinical cardiovascular changes, such as increased arterial stiffness and myocardial dysfunction. Vitamin D deficiency has been recognized as a potential contributing factor to vascular disease; however, its impact on early cardiac changes associated with T2DM remains poorly understood. Our aim was to evaluate the association between serum levels of 25-hydroxyvitamin D3 [25(OH)D3], arterial stiffness, and left ventricular global longitudinal strain (LV GLS) in patients with T2DM who do not have a clinically evident cardiovascular disease. Material and methods: This cross-sectional study evaluated the carotid intima–media thickness (IMT), aortic pulse wave velocity (PWVao), LV GLS, and serum 25(OH)D3 levels in patients diagnosed with T2DM (n = 65) compared to healthy control subjects (n = 55). Independent predictors of arterial stiffness were identified by a multivariate logistic regression analysis. Results: Patients with T2DM showed a significant increase in IMT and PWVao, a reduction in LV GLS, and low levels of 25(OH)D3 compared to subjects in the control group (all p < 0.05). Both vitamin D deficiency and T2DM were found to be independently associated with an increased arterial stiffness, with odds ratios of 2.4 and 4.8, respectively. A significant inverse relationship was identified between 25(OH)D3 levels and markers of arterial stiffness, as well as LV GLS, suggesting a possible association between the vitamin D status and the early onset of cardiovascular dysfunction. Conclusions: Patients with T2DM show early signs of heart and blood vessel problems, even with an ejection fraction that remains within normal limits. There is a significant correlation between vitamin D deficiency and increased arterial stiffness, along with impaired LV GLS, indicating its possible involvement in cardiovascular complications associated with diabetes. These findings support the utility of integrating vascular, myocardial, and vitamin D assessments in early cardiovascular risk stratification for T2DM patients. Full article

SYNGAP1-related disorder is a rare neurodevelopmental disorder characterized by intellectual and motor disabilities, including disordered gait control. Currently, there have been few studies that have assessed the gait of individuals with SYNGAP1-related disorder using technology-based collection techniques. The purpose of this investigation was to characterize the kinematic gait pattern of these individuals using camera-based motion capture technology during treadmill walking. Both linear and non-linear analysis techniques were used to analyze bilateral lower-limb joint motion and compare the results to age-matched neurotypical individuals. Results indicate that joint range of motion and velocity were decreased in the patient population relative to the neurotypical participants with the non-linear measures of angle–angle and phase portrait areas reflecting similar outcomes. The combination of linear and non-linear measures provide complementary information that, when used in combination, can provide deeper insights into the coordination and control of gait than if either of the measurement techniques are used in isolation. Such information can be useful to clinicians and therapists to develop targeted interventions designed to improve the gait of individuals with SYNGAP1-related disorder. Full article

Nokoué Lake is located in the south of Benin and is fed by the Ouémé and Sô Rivers. Its hydrosedimentary dynamics were modelled using Telemac2D, incorporating the main environmental factors of this complex ecosystem. The simulations accounted for flow rates and suspended solids concentrations during periods of high and low water. The main factors controlling sediment transport were identified. The model was validated using field measurements of water levels and suspended solids. The results show that the north–south current velocity ranges from 0.5 to 1 m/s during periods of high water and 0.1 to 0.5 m/s during low-water periods. Residual currents are influenced by rainfall, river discharge, and tides. Complex circulation patterns are caused by increased river flow during high water, while tides dominate during low water and transitional periods. The northern, western, and south-eastern parts of the lake have weak residual currents and are, therefore, deposition zones for fine sediments. The estimated average annual suspended solids load for 2022–2023 is 17 Mt. The model performance shows a strong agreement between the observed and simulated values: R² = 0.91 and NSE = 0.93 for water levels and R² = 0.86 and NSE = 0.78 for sediment transport. Full article

This research introduces an innovative passive vibration control methodology employing acoustic black hole (ABH) structures to mitigate vibration transmission in electric automotive steering machines—a prevalent issue adversely affecting driving comfort and vehicle safety. Leveraging the inherent bending wave manipulation properties of ABH configurations, we conceive an integrated vibration suppression framework synergizing advanced computational modeling with intelligent optimization algorithms. A high-fidelity finite element (FEM) model integrating ABH-attached steering machine system was developed and subjected to experimental validation via rigorous modal testing. To address computational challenges in design optimization, a hybrid modeling strategy integrating parametric design (using Latin Hypercube Sampling, LHS) with Kriging surrogate modeling is proposed. Systematic parameterization of ABH geometry and damping layer dimensions generated 40 training datasets and 12 validation datasets. Surrogate model verification confirms the model’s precise mapping of vibration characteristics across the design space. Subsequent multi-objective genetic algorithm optimization targeting RMS velocity suppression achieved substantial vibration attenuation (29.2%) compared to baseline parameters. The developed methodology provides automotive researchers and engineers with an efficient suitable design tool for vibration-sensitive automotive component design. Full article

Background: Pharmaceutical compounds frequently co-occur in environmental waters, but studies on their combined effects on animals and humans remain limited. The present study investigated the individual and combined short-term effects of ketoprofen (Kp, a nonsteroidal anti-inflammatory drug inhibiting cyclooxygenase-2), valproic acid (VPA, an anticonvulsant acting as a voltage-gated sodium channel modulator), and meropenem (Mp, a β-lactam antibiotic) at environmentally relevant concentrations on zebrafish behavior, acetylcholinesterase (AChE) activity, and oxidative status. Methods: Adult zebrafish were exposed for 4 days to Kp, VPA, Mp, and their binary and ternary mixtures. Behavioral effects were assessed using 3D novel tank and social behavior tests, while the oxidative stress response was assessed through malondialdehyde (MDA) content, superoxide dismutase (SOD), and glutathione peroxidase (GPx) activities. Results: Zebrafish exposed to Mp showed a notable increase in immobility, whereas those exposed to VPA and Mp + Kp exhibited a significant augmentation of average velocity and counter-clockwise rotations. All treated groups exhibited a notable increase in the time spent near the walls (thigmotaxis), and except for the control and Mp-exposed zebrafish, the other groups mostly stayed in the bottom tank zone (geotaxis). Kp, VPA + Kp, and VPA + Mp + Kp treatments impaired social behavior, with zebrafish displaying less interest in conspecifics. Biochemical analysis demonstrated that both the individual drugs and their combination caused oxidative stress, characterized by decreased GPx activity and increased SOD activity and MDA levels. Moreover, AChE activity was more strongly inhibited in zebrafish exposed to the binary and ternary mixtures than to individual drugs. Conclusions: The results indicate that acute exposure to individual and/or combined pharmaceuticals induces behavioral changes, oxidative damage, and AChE inhibition in zebrafish, highlighting the need to assess the effects of pharmaceutical mixtures for comprehensive ecosystem risks evaluation. Full article

Waterborne transportation serves as a critical pillar of trunk-line freight systems, offering unparalleled advantages in transport capacity, energy efficiency, and cost-effectiveness. As cargo throughput demands escalate, optimizing lock capacity becomes imperative. This study investigates ship sinkage dynamics through computational fluid dynamics (CFD) simulations for a representative inland cargo vessel navigating the Three Gorges on the Yangtze River. We develop a predictive sinkage model that integrates four key hydrodynamic parameters: ship velocity, draft, water depth, and bank clearance, applicable to both open shallow water and lockage conditions. The model enables determination of maximum safe drafts for lock transit by analyzing upstream/downstream water levels and corresponding chamber depths. Our results demonstrate the technical feasibility of enhancing single-lock cargo capacity while maintaining safety margins. These findings provide (1) a scientifically grounded framework for draft control optimization, and (2) actionable insights for lock operation management. The study establishes a methodological foundation for balancing navigational safety with growing throughput requirements in constrained waterways. Full article

In the context of the mining industry, the belt conveyor is a critical piece of equipment. The motor constitutes the primary component of the belt conveyor apparatus, and its stable and accurate operation can significantly influence the performance of the belt conveyor apparatus. This paper introduces an integrated control approach combining vector control methodology with active disturbance rejection control (ADRC) for velocity regulation and model predictive control (MPC) for current tracking. The ADRC framework actively compensates for load disturbances and parameter variations during speed control, while MPC achieves precise current regulation with minimal tracking error. Validation involved comprehensive MATLAB/Simulink R2024a simulations modeling PMSM behavior under mining-specific operating conditions. The results demonstrate substantial improvements in dynamic response characteristics and disturbance rejection capabilities compared to conventional control strategies. The proposed methodology effectively addresses critical challenges in mining conveyor applications, enhancing operational reliability and system longevity. Full article