Search Results (429)

A transient numerical framework incorporating dynamic mesh techniques was developed to simulate the launch process. On this basis, a thermal–fluid–structural multi-physics coupling paradigm was proposed to interpret the evolution of the flow field and the associated load response throughout the entire firing sequence. The results show that flow development follows a multi-stage dynamic pattern, comprising gas-impact filling, gap-jet formation, and subsequent free-jet expansion. A pronounced spatially heterogeneous phase lag was observed in the pressure–Mach number response. This phenomenon arises from a mismatch among the characteristic time scales of pressure-wave propagation, flow inertia, and shock–boundary-layer interaction. Quantitative analysis further indicates that the spatial superposition of high-temperature zones, high-Mach regions, and elevated-pressure areas activates a thermal–fluid–structural positive-feedback loop that drives the local peak temperature to approximately 2.5 × 10³ K. The temperature response lags behind the pressure maximum by approximately 30–50 ms, reflecting the governing time scale of thermal inertia. In addition, vortical structures near the tube base account for nearly 15% of the total thrust. These findings provide a theoretical foundation for predicting transient peak loads in concentric cylindrical systems and for optimizing instantaneous thermal protection strategies. 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

Emerging landslides and severe floods highlight the urgent need to analyse and support predictive models and early warning systems. Soil moisture is a crucial parameter and it can now be determined from space with a resolution of a few tens of meters, potentially leading to the continuous global monitoring of landslide risk. We address this issue by determining the volumetric water content (VWC) of a testbed in Southern Italy (bare soil with significant flood and landslide hazard) through the comparison of two different satellite observations on the same day. In the first observation (Sentinel-1 mission of the European Space Agency, C-band Synthetic Aperture Radar (SAR)), the back-scattered radar signal is used to determine the VWC from the dielectric constant in the microwave range, using a time-series approach to calibrate the algorithm. In the second observation (hyperspectral PRISMA mission of the Italian Space Agency), the short-wave infrared (SWIR) reflectance spectra are used to calculate the VWC from the spectral weight of a vibrational absorption line of liquid water (wavelengths 1800–1950 nm). As the main result, we obtained a Pearson’s correlation coefficient of $0.4$ between the VWC values measured with the two techniques and a separate ground-truth confirmation of absolute VWC values in the range of 0.10–0.30 within $\pm 0.05$. This overlap validates that both SAR and hyperspectral data can be well calibrated and mapped with 30 m ground resolution, given the absence of artifacts or anomalies in this particular testbed (e.g., vegetation canopy or cloud presence). If hyperspectral data in the SWIR range become more broadly available in the future, our systematic procedure to synchronise these two technologies in both space and time can be further adapted to cross-validate the global high-resolution soil moisture dataset. Ultimately, multi-mission data integration could lead to quasi-real-time hydrogeological risk monitoring from space. Full article

Land seismic data are always contaminated by surface waves, which demonstrate strong energy, low velocity, and long vibrations. Such noises often mask deep effective reflections, seriously reducing the data’s signal-to-noise ratio while limiting the imaging accuracy of complex deep structures and the efficiency of hydrocarbon reservoir identification. To address this critical technical bottleneck, this paper proposes a surface wave joint reconstruction method based on stationary phase analysis, combining the cross-correlation seismic interferometry method with the convolutional seismic interferometry method. This approach integrates cross-correlation and convolutional seismic interferometry techniques to achieve coordinated reconstruction of surface waves in both shot and receiver domains while introducing adaptive weight factors to optimize the reconstruction process and reduce interference from erroneous data. As a purely data-driven framework, this method does not rely on underground medium velocity models, achieving efficient noise reduction by adaptively removing reconstructed surface waves through multi-channel matched filtering. Application validation with field seismic data from the piedmont regions of western China demonstrates that this method effectively suppresses high-energy surface waves, significantly restores effective signals, improves the signal-to-noise ratio of seismic data, and greatly enhances the clarity of coherent events in stacked profiles. This study provides a reliable technical approach for noise reduction in seismic data under complex near-surface conditions, particularly suitable for hydrocarbon exploration in regions with developed scattering sources such as mountainous areas in western China. It holds significant practical application value and broad dissemination potential for advancing deep hydrocarbon resource exploration and improving the quality of complex structural imaging. Full article

This work presents the fabrication and characterization of a bow-tie antenna integrated uni-traveling carrier photodiode (UTC-PD) on a silicon carbide (SiC) substrate for efficient terahertz (THz) wave generation. The proposed device exploits the superior thermal conductivity and mechanical robustness of SiC to overcome the self-heating limitations associated with conventional indium phosphide (InP)-based photodiodes. An epitaxial layer transfer technique was utilized to bond InP/InGaAs UTC-PD structures onto SiC. The study systematically examines the influence of critical geometric parameters, specifically the mesa diameter and length between the antenna arms, on the emitted THz intensity in the 300 GHz frequency band. Experimental results show that the THz radiation efficiency is primarily governed by the mesa diameter, reflecting the trade-off between light absorption, device capacitance, and bandwidth, while the length between the antenna arms exhibits only a weak influence within the investigated parameter range. The fabricated device demonstrates strong linearity between photocurrent and THz output power up to 7.5 mA, after which saturation occurs due to space-charge effects. This work provides crucial insights for optimizing SiC-based bow-tie antenna integrated UTC-PD devices to realize robust, high-power THz sources vital for future high-data-rate wireless communication systems such as beyond 5G and 6G networks. Full article

Predicting internal quality parameters, such as Brix and water content, of apples, is essential for quality control. Existing near-infrared (NIR) and hyperspectral imaging (HSI)-based techniques have limited applicability due to their dependence on equipment and environmental sensitivity. In this study, a transportable quality assessment system was proposed using spatiotemporal domain analysis with long-wave infrared (LWIR)-based thermal diffusion phenomics, enabling non-destructive prediction of the internal Brix of apples during transport. After cooling, the thermal gradient of the apple surface during the cooling-to-equilibrium interval was extracted. This gradient was used as an input variable for multiple linear regression, Ridge, and Lasso models, and the prediction performance was assessed. Overall, 492 specimens of 5 cultivars of apple (Hongro, Arisoo, Sinano Gold, Stored Fuji, and Fuji) were included in the experiment. The thermal diffusion response of each specimen was imaged at a sampling frequency of 8.9 Hz using LWIR-based thermal imaging, and the temperature changes over time were compared. In cross-validation of the integrated model for all cultivars, the coefficient of determination (R²_cv) was 0.80, and the RMSEcv was 0.86 °Brix, demonstrating stable prediction accuracy within ±1 °Brix. In terms of cultivar, Arisoo (Cultivar 2) and Fuji (Cultivar 5) showed high prediction reliability (R²_cv = 0.74–0.77), while Hongro (Cultivar 1) and Stored Fuji (Cultivar 4) showed relatively weak correlations. This is thought to be due to differences in thermal diffusion characteristics between cultivars, depending on their tissue density and water content. The LWIR-based thermal diffusion analysis presented in this study is less sensitive to changes in reflectance and illuminance compared to conventional NIR and visible light spectrophotometry, as it enables real-time measurements during transport without requiring a separate light source. Surface heat distribution phenomics due to external heat sources serves as an index that proximally reflects changes in the internal Brix of apples. Later, this could be developed into a reliable commercial screening system to obtain extensive data accounting for diversity between cultivars and to elucidate the effects of interference using external environmental factors. Full article

Ensuring friction stir welding (FSW) joint quality typically relies on ultrasonic testing (UT) and radiographic testing (RT), but achieving complete coverage is challenging, and echo-based defect discrimination becomes difficult in dissimilar joints. Laser ultrasonics is a promising non-contact technique that remotely assesses weld quality and provides high spatial resolution at the generation and detection points. This study establishes a laser-ultrasonic method for defect detection in dissimilar Cu–Al FSW joints. Slit-like artificial defects (0.1–2.5 mm deep in 5 mm thick plates) were introduced at the Al-side interface of specimens fabricated with an Al-offset tool. Experiments and numerical simulations were used to evaluate wave modes and irradiation configurations, focusing on intensity-attenuation ratios of specific wave types, including longitudinal and Rayleigh waves. On the non-slit surface, attenuation of reflected longitudinal waves enabled detection of defects ≥0.5 mm deep. On the slit surface, Rayleigh-wave attenuation allowed identification of defects as shallow as 0.1 mm, although slit-side irradiation may be less practical during joining. These results demonstrate that defect identification in dissimilar materials can be achieved by evaluating wave-intensity attenuation rather than relying solely on the presence of reflected echoes, suggesting potential for implementing laser ultrasonics in in-process monitoring of FSW joints. Full article

Background: Elastography is a non-invasive technique used to assess tissue stiffness. There are two main types of elastography: shear-wave elastography and strain imaging. Both are useful for evaluating the degree of liver fibrosis (LF). Shear-wave imaging is influenced by fibrosis and hepatic congestion, whereas strain imaging primarily reflects fibrosis progression and is less affected by congestion. We previously reported the clinical usefulness of combinational elastography in patients with heart failure (HF). However, its prognostic significance in this population remains unclear. Accordingly, in this prospective study, we aimed to evaluate the prognostic impact of combinational elastography in patients with HF. Methods: We included 77 patients with HF (median age: 79 years). Shear-wave imaging was used to obtain shear-wave velocity (Vs), whereas the liver fibrosis index (LF index) was derived from strain imaging. The Vs/LF index (V/L) was used as a prognostic indicator based on combinational elastography. Cardiac events were defined as cardiac death or hospitalization due to HF. Results: During a median follow-up of 716 days, 17 cardiac deaths or hospitalizations for HF were observed. The V/L demonstrated a cut-off value of 1.2 for predicting cardiac death or hospitalization for HF, with an area under the curve of 0.80, sensitivity of 0.82, and specificity of 0.68. Kaplan–Meier analysis demonstrated that patients with a high V/L (≥1.2) had significantly higher rates of hospitalization for HF than those with a low V/L (<1.2; log-rank test, p < 0.001). Conclusions: Combinational elastography demonstrated prognostic utility in patients with HF and may serve as a novel, non-invasive tool for assessing hepatic congestion. Full article

Non-destructive evaluation techniques are increasingly recognised as effective alternatives to destructive testing for estimating the compressive strength of lightweight aggregate concrete (LWAC). Among these, ultrasonic pulse velocity (UPV) is a well-established and widely employed method, characterised by its speed, non-invasiveness, and relative simplicity of implementation. In this study, an experimental dataset comprising 640 core segments from 160 cylindrical specimens, provided for analysis, was investigated. Each segment was described by physical and processing variables or features, including lightweight aggregate (LWA) and concrete densities, casting and vibration times, experimental dry density, and P-wave velocity obtained through UPV testing. A segregation index, derived from UPV measurements and defined as the ratio of local to mean P-wave velocity within each specimen, was also considered, following approaches previously suggested in the literature. A range of machine learning techniques was applied to assess the predictive capacity of local P-wave velocity and segregation index. Most ensemble-based methods and support vector regression (SVR) achieved the highest predictive performance when the segregation index was excluded, suggesting that its inclusion did not improve the predictive ability of the models. By contrast, Gaussian process regression (GPR) showed slight improvements when the segregation index was included. The results confirmed that the P-wave velocity measured by UPV testing is a reliable non-destructive predictor of compressive strength in LWAC. At the same time, the added value of the segregation index remained negligible under conditions of low segregation, as reflected by segregation index values above 0.8. These findings highlight the practical potential of integrating UPV-based measurements with data-driven modelling to enhance the reliability of concrete characterisation and quality control. Full article

This paper presents a joint design approach for intelligent reflecting surface (IRS)-assisted multi-user millimeter-wave (mmWave) systems. Our goal is to maximize the sum-rate of all users by optimizing the hybrid beamforming at the base station and the low-resolution phase shifters (e.g., 1 bit) at the IRS. To address this, we first adopt a zero-force (ZF) technique to design fully-digital (FD) beamforming and develop a cross-entropy optimization (CEO) framework-based iterative algorithm to calculate IRS phase shifts. Specifically, in this framework, the probability distributions of IRS elements are updated by minimizing the CE, which can generate a solution close to the optimal one with a sufficiently high probability. Then, based on the obtained FD beamforming, an alternating minimization method is applied to acquire hybrid beamforming. Simulation results show that our proposed joint design scheme can achieve enhanced performance compared to the existing schemes while maintaining a lower computational complexity. Full article

A reflective all-fiber optical current transformer based on a spatial non-reciprocal phase modulation technique is investigated by theoretical analysis and experimental measurement. The modulation unit, composed of a phase delay wave plate (LiNbO₃) and two Faraday rotators, achieves flexible frequency adjustment by converting modulation from the time domain to the spatial domain. Therefore, the avoidance of the impact caused by delay coils is achieved in principle. The absence of intrinsic frequency limitations eliminates the demand for precise timing control in demodulation, thereby simplifying the demodulation circuit and reducing the cost and size of the transformer. In previous studies, redundancies were identified in the optical path coupling devices. The half-wave voltage of the modulator is excessively high, and its size is considerable due to constraints inherent in the manufacturing process. The measurement range is within 1800 A. The scheme simplifies some optical path components. By optimizing the phase delay wave plate, the half-wave voltage of the modulator is significantly reduced by a factor of 150. Experimental results demonstrate that the current transformer exhibits excellent detection consistency within the rated current range of 30–3600 A (1–120%), the response time is within 3 ms, and the measurement error and peak error reach 0.052% and 0.127%. This configuration provides a novel option for the design and practical application of all-fiber optical current transformers. Full article

Maritime vision systems for unmanned surface vehicles confront challenges in small-object detection, specular reflections and low-light conditions. This paper introduces WA-YOLO, a water-aware training framework that incorporates lightweight attention modules (ECA/CBAM) to enhance the model’s discriminative capacity for small objects and critical features, particularly against cluttered water ripples and glare backgrounds; employs advanced bounding box regression losses (e.g., SIoU) to improve localization stability and convergence efficiency under wave disturbances; systematically explores the efficacy trade-off between high-resolution input and tiled inference strategies to tackle small-object detection, significantly boosting small-object recall (APS) while carefully evaluating the impact on real-time performance on embedded devices; and introduces physically inspired data augmentation techniques for low-light and strong-reflection scenarios, compelling the model to learn more robust feature representations under extreme optical variations. WA-YOLO achieves a compelling +2.1% improvement in mAP@0.5 and a +6.3% gain in APS over YOLOv8 across three test sets. When benchmarked against the advanced RT-DETR model, WA-YOLO not only surpasses its detection accuracy (0.7286 mAP@0.5) but crucially maintains real-time performance at 118 FPS on workstations and 17 FPS on embedded devices, achieving a superior balance between precision and efficiency. Our approach offers a simple, reproducible and readily deployable solution, with full code and pre-trained models publicly released. Full article

Alzheimer’s disease (AD) is considered one of the leading causes of death in the United States, and there is no effective cure for it. Understanding the neuropathological mechanisms underlying AD is essential for identifying early, reliable biomarkers and developing effective therapies. In this paper, we report on a comprehensive multimodal study of AD pathology using the 5xFAD mouse model. We employed light-scattering techniques, Partial Wave Spectroscopy (PWS) and Inverse Participation Ratio (IPR), to detect nanoscale structural alterations in brain tissues, nuclear components, and mitochondria. To support the light-scattering experiments, behavior, and histopathological studies were conducted. These analyses revealed significant increases in structural heterogeneity and mass density fluctuations in the brains of 5xFAD mice compared with Non-transgenic controls. Behavioral assessment performed using the Novel Object Recognition test demonstrated memory impairment in 5xFAD mice, reflected by a reduced recognition index. Histopathological analysis further revealed increased amyloid beta plaques and microglia activation in the hippocampus and cortex of 5xFAD mice compared with Non-transgenic controls. An increase in structural disorder within brain tissues can be attributed to higher mass density fluctuations, likely arising from macromolecular rearrangement driven by amyloid beta aggregation and neuroinflammatory responses as the disease progresses. Our findings suggest that PWS and IPR-derived metrics provide sensitive biophysical indicators of early cellular and subcellular disruption, offering potential as quantitative biomarkers for the detection of AD. Full article

Background/Objectives: The timely evaluation of blood clot formation and breakdown is essential in the care of patients with severe bleeding or critical illness. Resonant acoustic rheometry is a novel, non-contact ultrasound method that measures changes in the viscoelastic properties of blood in a standard microplate format. Here, we present the first clinical description of whole blood coagulation and fibrinolysis assessed with resonant acoustic rheometry, with paired thromboelastography measurements for comparison. Methods: In this retrospective analysis, whole blood samples from three critically ill patients were divided and tested under four different conditions that included a control mixture, kaolin activation, tissue factor activation, and a tissue factor mixture supplemented with tissue plasminogen activator. The resonant acoustic rheometry system obtained real time measurements of resonant surface waves and displacements from the samples. Heat maps and spectrograms of the resonant surface waves were analyzed to determine the onset of clotting, the rate of viscoelastic stiffening, the time to maximum rigidity, and the onset as well as magnitude of fibrinolysis. These measurements were compared with thromboelastography reaction time, clot strength, fibrinogen contribution, and lysis values. Results: Resonant acoustic rheometry detected reproducible transitions from liquid to clot and from clot to lysis in all samples. Activator-dependent changes in clot initiation and propagation matched the expected hierarchy observed in thromboelastography. Significantly, samples exposed to tissue plasminogen activator demonstrated a clear fall in resonant frequency and a corresponding rise in surface displacement that reflected fibrinolysis. The technique also reproduced clinically meaningful patterns of hemostasis that aligned with each patient’s underlying disease. Conclusions: Whole blood clotting can be measured with resonant acoustic rheometry in a manner that aligns with established clinical assays. These results suggest strong potential for future use of resonant acoustic rheometry as a cost-effective, complementary platform for rapid, scalable, and clinically informative hemostatic assessment. Full article

The present work focuses on wave scattering generated by an inverse T-type compound breakwater in the presence of the ocean current. The boundary value problem (BVP) is investigated using two distinct strategies: an exact formulation derived from the eigenfunction expansion method (EEM) and a computational framework developed with the boundary element method (BEM). A comparison of outcomes from both techniques with established studies confirms the consistency and accuracy of the present formulations. Reflection and transmission coefficients, along with the time-domain simulations of the free surface, are evaluated under different wave conditions and structural configurations. In the long-wave region, the reflection coefficient exhibits strong dependence on the wavenumber, with higher values observed as the height and width of the porous section increase. Increasing the friction coefficient within the porous layer considerably reduces wave transmission to the leeside, demonstrating the important role of friction in energy dissipation. Furthermore, greater ocean current velocity leads to an increase in the reflection curve, highlighting the significant effect of hydrodynamic conditions on wave–structure interaction. The time-domain simulations of the free surface are also presented to provide a clear visualization of the wave behavior on the surface, both with and without the presence of an ocean current. The findings shed light on the combined influence of breakwaters and ocean currents, enabling the development of coastal protection measures that enhance resilience, sustainability, and safety from erosion and damage. Full article