Search Results (812)

Railway transport is increasingly promoted as a sustainable and low-carbon mode of transportation. However, track-induced vibration propagation remains a significant challenge, particularly in metro systems situated near residential areas, where vibrations can transmit through the infrastructure into nearby buildings, disturbing residents and damaging structures. This study aimed to evaluate the cause of the significantly different vibration impact on nearby buildings caused by two nominally identical adjacent slab tracks on a metro line in Austria. Controlled weight drop tests were carried out in both track directions, and accelerations were measured to characterize wave transmission and energy dissipation. The data were processed using frequency response functions and Short-Time Fourier Transform to extract time–frequency signatures, modal parameters, and propagation delays. A three-dimensional finite element model of the railway superstructure was then calibrated against the experimental modal properties and transfer functions and used to simulate cracking or stiffness loss in the sleeper–slab region. The simulations reproduced the observed increase in slab acceleration and underground strain energy, linking the anomalous vibration transmission to hidden stiffness loss rather than to global design differences. Overall, the study demonstrates that combining impact testing, advanced signal processing, and calibrated finite element modelling provides an effective framework for diagnosing track defects and guiding the design and maintenance of more sustainable, low-vibration urban rail infrastructure. Full article

This paper develops an extended-state-observer (ESO)-enhanced actor–critic reinforcement learning (RL) scheme for the trajectory tracking control of 3-DOF marine vessels subject to uncertain hydrodynamics and environmental disturbances. A coordinate-consistent error construction is provided to obtain an exact strict-feedback second-order uncertain template. On this basis, an Hamilton–Jacobi–Bellman (HJB)-inspired optimised control structure is implemented: the critic approximates the optimal value-gradient and the actor generates the optimised control law. A key simplification is employed: rather than minimising the squared Bellman residual via complex gradients, we introduce an HJB-inspired actor–critic consistency regularisation through a weight-matching coupling. This yields computationally light online update laws and enables transparent Lyapunov-based stability analysis while not claiming exact HJB satisfaction or policy optimality. The ESO estimates lumped uncertainty and provides feedforward compensation, so the RL module learns only the observer residual. A composite Lyapunov analysis establishes the semi-global uniform ultimate boundedness of tracking errors and boundedness of all observer signals. Practical implementation with thruster allocation, explicit wind–wave–current disturbance shaping filters, and a theory-aligned ablation protocol are provided for reproducibility. Full article

Type 2 diabetes mellitus and prediabetes often develop silently and may remain undiagnosed for years. This is particularly relevant in regions where laboratory-based screening is not always readily accessible. Against this background, the present work explores whether multilead electrocardiography can provide physiologically meaningful markers potentially associated with disturbances in glucose metabolism. We developed and tested an upgraded wearable 12-lead ECG system capable of synchronized multichannel recording under controlled conditions. ECG signals were acquired in sitting and standing positions, with a sampling frequency of 500 Hz and a recording duration of one minute per posture. The hardware architecture included a high resolution analog front-end and wireless data transmission; the accompanying software provided acquisition control, preprocessing, visualization, and data storage within a unified framework. Signal processing focused on the extraction of rhythm-related and morphological parameters, with particular attention to ventricular repolarization indices. QT interval, heart rate–corrected QT (QTc), and QT dispersion (QTd) were calculated across leads, as these parameters are known to reflect heterogeneity of repolarization and autonomic influences on myocardial electrophysiology. The analysis was structured to ensure reproducible boundary detection and systematic feature formation rather than isolated parameter measurement. The study had a pilot character and included a limited and unbalanced sample (healthy n = 10; prediabetes n = 1; T2DM n = 1). For this reason, the results are presented descriptively and should be regarded as preliminary observations. In representative cases, differences in QT-related indices were noted between categories of glycemic status; however, the potential influence of age, sex, and other confounders cannot be excluded. A pilot expert comparison of T-wave end detection demonstrated close agreement between the automated algorithm and cardiologist assessment (mean Δ$T_{end}$ approximately −1 to −2 ms; MAE 10–24 ms). Diagnostic performance metrics such as ROC/AUC, sensitivity, and specificity were not calculated at this stage, as validation in a larger cohort with biochemical confirmation (HbA1c, OGTT) is required. The study demonstrates the technical feasibility of combining synchronized 12-lead wearable acquisition with structured multilead repolarization analysis. The proposed system should therefore be considered a research platform intended to support further clinical validation and methodological development rather than a finished screening solution. Full article

Traveling wave ultrasonic motors (TWUMs) are critical components in precision systems, yet their performance is susceptible to degradation under dynamic disturbances in harsh operating environments. This paper presents a monolithic U-shaped rotor designed to intrinsically achieve quasi-zero stiffness (QZS). Unlike conventional QZS systems that rely on assembling discrete positive and negative stiffness elements, the proposed design generates the target mechanical characteristic through the tailored nonlinear response of a unified U-shaped structure, thereby improving preload stability. Through exploring the critical parameters of the rotor cross-section, the finite element method (FEM) is employed to optimize the geometry configuration and characterize the mechanical performances. The simulation results show the QZS behavior demonstrating a stable force plateau of 320 ± 10 N across a 0.7 mm displacement range. A maximum von Mises stress of 788 MPa is obtained, well within the material’s safety margin, thereby ensuring the structural integrity. Experimental tests validate the effectiveness of the proposed design. This compact, monolithic U-shaped rotor provides a robust and reliable QZS solution, demonstrating significant potential for enhancing the stability of TWUMs in applications prone to harsh environments such as wide-range temperature fluctuations, thermal cycling conditions, and shock environments. Full article

Offshore operational environments are inherently stochastic, with waves, currents, and wind loads exerting a significant influence on vessel attitude and equipment stability. While Stewart platforms enable active motion compensation, conventional control strategies frequently suffer from time delays, actuator lag, and limited disturbance rejection, resulting in inadequate performance under complex sea conditions. To overcome these limitations, this paper presents a wave compensation control strategy for a Stewart platform that integrates deep learning-based prediction with active disturbance rejection control (ADRC). A bidirectional long short-term memory (BiLSTM) network is developed to predict vessel attitude in advance. The predicted attitude is transformed into actuator displacement commands through the inverse kinematics of the Stewart platform. An ADRC-based displacement controller is then designed to achieve fast and robust compensation under wave disturbances. Six-degree-of-freedom (6-DOF) dynamic models of a catamaran and a Stewart platform are established in Simulink and Simscape, and sea states 2, 4, and 6 are simulated using an enhanced Joint North Sea Wave Project (JONSWAP) wave spectrum. The simulation results show that, compared with Proportional–Integral–Derivative (PID) and ADRC methods, the proposed BiLSTM-ADRC strategy reduces the roll root mean squared error (RMSE) by 76.6% and 73.2%, and pitch RMSE by 64.1% and 58.1%, respectively, demonstrating an improved attitude stabilization performance. Full article

The autonomic nervous system (ANS) plays a key role in cardiovascular regulation by maintaining hemodynamic and metabolic homeostasis through balanced sympathetic and parasympathetic activity. While autonomic dysfunction is classically associated with diabetes, neurodegenerative diseases, autoimmune neuropathies, and chronic cardiovascular conditions, growing evidence suggests that disturbances in iron metabolism represent an underrecognized contributor to cardiac autonomic dysregulation. This narrative review summarizes data from 107 studies on ANS disorders, including 49 investigating cardiovascular involvement. Reported abnormalities included reduced heart rate variability and baroreflex sensitivity, prolonged P-wave duration and QT dispersion, and deviations in non-invasive autonomic testing parameters. In iron overload states, these changes appear to be driven primarily by oxidative stress, whereas in iron deficiency they are likely mediated by tissue hypoxia. Importantly, several studies indicate that normalization of iron homeostasis may partially reverse autonomic dysfunction. This potentially reversible component underscores the clinical relevance of screening for and correcting iron imbalance not only to improve hematological status but also to reduce cardiovascular risk. Large-scale, multicenter studies using standardized autonomic assessment protocols are required to clarify prognostic implications and inform evidence-based clinical guidelines. Full article

Accurate identification of hydrodynamic parameters is essential for high-fidelity modeling and control of unmanned underwater vehicles (UUVs). Compared with towing tank experiments and computational fluid dynamics simulations, system identification based on free-running trial data offers a cost-effective and scalable alternative. However, in real ocean environments, unmodeled lumped disturbances—such as shear currents, stratification-induced buoyancy variations, and wave-induced drift forces—strongly couple with the vehicle’s intrinsic dynamics. Conventional least-squares estimators and physics-informed neural networks tend to absorb environmental effects into the physical parameters, leading to physically inconsistent estimates. To address this challenge, this paper proposes a physics-guided hybrid network (PG-HyNet) with input-domain structural decoupling. The architecture explicitly separates the intrinsic rigid-body dynamics from spatially varying environmental disturbances by assigning dynamics-related states to a physics-constrained branch and position-dependent variables to a residual disturbance branch. A staged training strategy is introduced to stabilize identification and suppress parameter drift during optimization. The framework is validated using high-fidelity simulations incorporating shear currents, density stratification, and wave drift effects, as well as real-world lake trial data. The results demonstrate that PG-HyNet significantly improves robustness against disturbance-induced parameter compensation, enabling physically consistent hydrodynamic parameter recovery while accurately capturing spatially varying environmental disturbance effects. Full article

Many of the film thickness measurements that have been reported in the literature tend to focus on small pipe diameters, which may not be practical for a variety of industrial applications. Additionally, single-point measurements are unable to provide the necessary film thickness data around the circumference of the pipe as well as in the axial direction. This paper aims to experimentally study the behaviour of wavy liquid films, including wave frequency, wave velocity, wave width, and wave spacing. A Multi-Pin Film Sensor (MPFS) was used to extract the thickness of a free-falling liquid film in axial, circumferential, and temporal coordinates. The range of liquid Reynolds number Re_L used was 618–1670. It was found that the power spectral density of the disturbance waves showed a pronounced peak at the modal frequency of 6–8 Hz. The number of disturbance waves was found to be almost independent of Re_L. The axial interfacial wave seemed to travel at a constant velocity while the mean velocity in circumferential direction was negligible. The mean width of the disturbance waves was approximately 17.7% of the pipe diameter. Full article

The stabilization of rock mass vibrations in underground excavations presents a critical engineering challenge due to the interplay of viscoelastic dynamics, impulsive shocks from blasting or rock bursts, and time-varying delays induced by wave propagation and sensor–actuator networks. In this paper, an integral sliding mode control scheme is developed for a Kelvin–Voigt type hyperbolic system subject to such impulsive effects and time-varying delays. To preserve sliding surface continuity under impulsive disturbances, the impulse information is explicitly incorporated into the design of the integral sliding function. The resulting sliding mode dynamics, which include discrete state jumps, are analyzed using a piecewise Lyapunov functional combined with inequality techniques; sufficient conditions are derived to guarantee asymptotic stability. Moreover, a sliding mode control law is synthesized to ensure that the system trajectories reach and remain on the sliding manifold from the initial time onward, despite parameter uncertainties and external disturbances. Numerical simulations with parameters reflecting realistic mining scenarios verify the effectiveness of the proposed control strategy, demonstrating its potential for practical rock mass vibration stabilization in geotechnical engineering. Full article

Enhancing traffic flow stability is a critical approach for achieving energy conservation and emission reduction in road transportation. While existing cooperative car-following strategies for connected and automated vehicles (CAVs) are effective, their heavy reliance on reliable Vehicle-to-Everything (V2X) communication limits practical deployment. This study proposes an energy-optimal car-following model for CAVs, introducing a regulation term based on the predicted optimal speed difference. Rather than directly using predicted kinematic variables, this mechanism adjusts acceleration based on the difference in optimal velocity between predicted and current headways. This leverages the inherent filtering of the optimal velocity function to ensure smooth control. Linear and nonlinear stability analysis confirm the model’s effectiveness in suppressing traffic disturbances and suppression of stop-and-go wave propagation, thereby laying the theoretical foundation for smoother traffic flow and the resulting reductions in energy consumption and emissions. Simulations validate the theoretical findings. Compared to the classical Full Velocity Difference (FVD) model, the proposed model achieves significant reductions in energy consumption (38.82%), CO₂ emissions (39.41%), and NO_x emissions (83.46%). The model also reduces rear-end collision risks, ensuring higher safety. These findings indicate that the proposed ego-vehicle predictive framework provides a communication-independent and practically viable approach for improving the energy efficiency and stability of CAV traffic flow. Full article

Intentional high-power electromagnetic (EM) interference poses a serious threat to sensitive electronic systems and often manifests as ultra-wideband (UWB) sub- and nanosecond pulses. Metallic shielding enclosures with technological apertures are commonly used for protection; however, apertures enable electromagnetic coupling into the enclosure and limit shielding performance. While most existing studies focus on transient disturbances with durations exceeding the enclosure transit time, this work addresses an ultrashort high-power subnanosecond UWB plane-wave pulse whose duration is significantly shorter than the enclosure transit time, a regime that remains insufficiently explored. A time-domain numerical analysis is performed for a low-profile rectangular metallic enclosure with a front-wall aperture, focusing on internal EM field evolution, internal pulse formation, and polarization-dependent shielding effectiveness. Three-dimensional full-wave simulations were carried out using CST Microwave Studio over a 90 ns observation window. The results show that the incident pulse excites primary subnanosecond EM waves inside the enclosure, which subsequently generate secondary waves through multiple reflections from the enclosure walls. Their interaction produces complex, long-lasting, time-varying internal field patterns. Although attenuated, the resulting internal subnanosecond pulses repeatedly traverse the enclosure interior, forming a pulse train-like sequence that may pose a cumulative electromagnetic threat to internal electronics. A key contribution of this work is the quantification of time-dependent local shielding effectiveness for both electric and magnetic fields, derived directly from the internal pulse train-like series obtained in the time domain. The concept of local, time-dependent shielding effectiveness provides physical insight that cannot be obtained from a single globally averaged SE value. In the case of ultrashort electromagnetic pulse excitation, the internal field response of an enclosure is strongly non-stationary and highly non-uniform in space, with local field maxima occurring at specific times and locations despite good average shielding performance. Time-dependent local SE enables identification of worst-case temporal conditions, repeated high-amplitude internal exposures, and critical regions inside the enclosure where shielding is significantly weaker than suggested by global metrics. Therefore, while conventional SE remains useful as a summary measurand, local time-dependent SE is essential for assessing the actual electromagnetic risk to sensitive electronics under ultrashort pulse disturbances. In addition, a global shielding effectiveness metric mapped over selected enclosure cross-sections is introduced to enable rapid visual assessment of shielding performance. The analysis demonstrates a strong dependence of internal wave propagation, internal pulse formation, and both local and global shielding effectiveness on the polarization of the incident subnanosecond EM pulse. These findings provide new physical insight into aperture coupling and shielding behavior in the ultrashort-pulse regime and offer practical guidance for the assessment and design of compact shielding enclosures exposed to high-power UWB EM threats. Full article

Background/Objectives: Insomnia is common among adolescents and is associated with emotional, behavioral, and academic difficulties. Although high rates have been reported globally, evidence in Latin America—particularly in Peru—remains limited and heterogeneous. Many previous studies relied on small samples, descriptive designs, omitted key psychosocial variables, or were conducted during early pandemic waves, despite the rise in sleep disturbances following COVID-19 restrictions. This study aimed to estimate the prevalence of insomnia and identify associated factors among adolescents in northern Peru. Methods: An analytical cross-sectional study was conducted using secondary data from students attending five schools in Lambayeque, Peru. Insomnia was assessed using the Insomnia Severity Index (ISI). Sociodemographic, psychosocial, behavioral, and health-related variables—including self-esteem, family dysfunction, eating disorders, acne severity, mental health help-seeking, and digital behavior—were evaluated. Generalized linear models estimated prevalence ratios (PRs) and 95% confidence intervals (CIs). Results: Among 1313 adolescents (54.3% male; mean age 14.6 years), the prevalence of insomnia was 38.9% (95% CI: 36.1–41.5). In adjusted analyses, insomnia was associated with urban residence, non-Catholic religion, seeking mental health support, high social media use, internet use of 6–10 h/day, low self-esteem, eating disorders, greater acne severity, and experiencing the death of a family member due to COVID-19. Conclusions: Nearly four in ten adolescents reported insomnia, influenced by sociodemographic, psychosocial, and lifestyle-related factors. These findings provide updated post-pandemic evidence for the Peruvian context and highlight the multifactorial nature of adolescent insomnia. Further research is needed to clarify causal pathways and understand the long-term mental health implications of large-scale stressors such as the COVID-19 pandemic. Full article

Thin liquid film flows of nanofluids over porous surfaces are central to applications ranging from microfluidic thermal management to precision coating technologies. This study investigates the hydrodynamic and thermal stability of a nanofluid flowing down a non-uniformly heated inclined porous plane subject to the Beavers-Joseph slip boundary condition. Using the long-wave approximation, a nonlinear evolution equation governing the film thickness is derived. The stability characteristics are systematically analyzed via linear stability theory, weakly nonlinear analysis, and fast Fourier transform (FFT) numerical simulations. Quantitative results indicate that the porous medium permeability, density difference, and Marangoni number act as destabilizing factors; specifically, increasing the porous parameter $\beta$ (from 0 to 0.3), the density ratio ${\zeta }_0$ (from 0 to 5), and the Marangoni number $Mn$ (from 0 to 0.3) significantly reduces the critical Reynolds number and accelerates the onset of interfacial instabilities. In contrast, increasing the nanoparticle volume fraction $\varphi$ from 0 to 0.3 exerts a dominant stabilizing effect by elevating the critical Reynolds number and shrinking the unstable wavenumber domain. Furthermore, nonlinear simulations confirm that higher nanoparticle concentrations effectively suppress the saturation amplitude of disturbances, promoting the eventual stabilization of the liquid film. Full article

The foldable quadcopter unmanned aerial vehicle (UAV), transported by an autonomous underwater vehicle (AUV) and launched subaquatically, represents cutting-edge technology for expanding ocean-sensing capabilities. However, its launch stability is severely challenged by complex cross-media flow fields. To address this, this paper employs a high-fidelity CFD method validated by experimental data, combined with dynamic overlapping mesh technology. Within a high-precision numerical wave tank, it systematically investigates the evolution of unsteady hydrodynamic characteristics throughout the entire launch process—from the drone’s emergence from the launch tube to its crossing of the water-air interface. Findings reveal that elevated initial launch velocities substantially alter surface flow patterns, inducing shear stress imbalances and complex flow separation on the trailing surface. This significantly amplifies lateral disturbance forces and yawing moments, constituting primary sources of motion instability. More critically, this study first uncovers and quantifies the hydrodynamic interference mechanism during the synchronous launch of dual vehicles: the wake field generated by the lead vehicle imposes a significant flow-shielding effect on the trailing vehicle. This effect alters its longitudinal forces while introducing an asymmetric pressure distribution, thereby generating substantial lateral interference. This study’s profound elucidation of these core hydrodynamic mechanisms provides crucial theoretical foundations for developing safe launch strategies, trajectory prediction, and anti-interference controller design for future AUV-UAV cooperative systems. Full article

To address the performance degradation of antenna beams in marine-towed buoy arrays caused by roll and pitch motions under dynamic sea conditions, this paper proposes a multi-objective sparse array optimization method based on an improved chaotic sparrow search algorithm (CSSA). First, an electromagnetic disturbance model of the array under sea states 1~7 is quantitatively established by coupling wave spectrum theory and buoy dynamics, formulating comprehensive optimization models for both linear and planar arrays under disturbance. Subsequently, within the NSGA-II framework, with main lobe width and peak sidelobe level (PSLL) as dual optimization objectives, a modified sparrow search algorithm integrating density-weighted initialization and Tent chaotic mapping is introduced for efficient solution exploration. Simulation results demonstrate that the proposed method achieves a PSLL below −19.95 dB under sea states 1~3 and effectively suppresses sidelobe elevation and beam distortion even under sea states 4~7 with strong disturbances. This approach significantly enhances the radiation robustness and link stability of sparse arrays in complex marine environments. Full article