Search Results (537)

The possibility of G-induced loss of consciousness (G-LOC) is a key concern when flying modern, high-performance aircraft. Currently, there are no identification methods available based on physiological data. This study aimed to determine whether specific pulse wave changes could be reliably identified using automatic computer algorithms to detect impending G-LOC. The pulse waves of 86 people who experienced G-LOC in a human centrifuge were analysed alongside an age-, gender-, nationality-, training-, and anti-G-equipment-matched control group using computer algorithm methods to analyse possible longer reductions in the G-LOC group. Based on this data, the study showed that centrifuge profiles with a gradual “onset run” using AGSM resulted in longer pulse wave flattening around the G-LOC in the G-LOC group than in the matched control group. However, this could not be verified in human centrifuge runs with active flight profiles and higher onset rates. Unfortunately, this means that the method used here would not currently be applicable in actual flight. In the future, the possibility of creating an identification method could be extended by incorporating additional physiological data. Full article

In this work, we present a detailed comparison of the SuSAv2 (SuperScaling Approach version 2) and RDWIA (Relativistic Distorted-Wave Impulse Approximation) models with measurements of charged-current neutrino-induced single-pion production from different experiments (T2K, MINERvA and MiniBooNE), studying the differences between the two theoretical descriptions. The neutrino energy range in these experiments spans from hundreds of MeV to roughly 20 GeV, and the nuclear targets are mainly composed of ${}^{12}$C. The SuSAv2 model uses the single-nucleon inelastic structure functions from the ANL-Osaka DCC model, which allows for a separation of pion production channels, distinguishing between the ${\pi }^{+}$, ${\pi }^{-}$ and ${\pi }^0$ final states. In the RDWIA approach, the Hybrid model developed by the Ghent group is used for the description of the boson–pion–nucleon vertex. Full article

Ocean surface currents (OSCs) are central to upper ocean dynamics and air–sea exchange, yet their retrieval from spaceborne synthetic aperture radar (SAR) is limited by wave-induced bias (WB). WB arises from the inherent motion of the scattering facets and from long-wave hydrodynamic and tilt modulations, and is therefore jointly controlled by sea state and radar viewing geometry. This study develops an observation geometry optimization framework. Five years of hourly ERA5 wind and wave reanalysis data over the Kuroshio are used as a representative ensemble of sea states to drive the KaDOP model, and an exhaustive grid search over line-of-sight (LOS) azimuth (0–360°) and incidence angle (20–60°) is performed to identify, for each location and season, the viewing geometry that minimizes the time-mean WB. These local optima are then summarized as mission-level metrics, including the minimum achievable WB, the coverage meeting prescribed WB thresholds, and the spatial coherence of the preferred LOS azimuth and incidence angle. Finally, the theoretical minima are compared with the fixed left-looking geometry of the Luojia-2 (LJ-2) satellite along a 213 km × 6 km observation corridor and with Gaofen-3 (GF-3) viewing geometries at four representative locations in the Kuroshio. Across these validation cases, the optimized geometry reduces mean absolute WB by about 20–60% for LJ-2 and 20–80% for GF-3, providing quantitative constraints for future SAR mission design targeting OSCs. Full article

Background: Women face underdiagnosed cardiovascular disease (CVD)/stroke risks due to sex-specific pathophysiological mechanisms, including hormonal variations such as oestrogen decline, adverse pregnancy outcomes (APOs), endothelial dysfunction, autoimmune-mediated factors, and sexual dimorphism in cardiac remodelling. Conventional risk assessment tools, predominantly calibrated to male pathophysiology, lack sensitivity in detecting these female-specific determinants. We hypothesise that artificial intelligence (AI), machine learning (ML) and deep learning (DL) may offer a transformative approach by integrating multimodal data, including pathological biomarkers, clinical history, and vascular imaging, to enable precision CVD/stroke risk stratification, pending rigorous external validation in sex-stratified cohorts. Method: This narrative review adopts a PRISMA-informed study selection framework and oversees gender-specific biomarkers, including vasoactive peptides (adrenomedullin), adipocytokines (adiponectin), inflammatory mediators (hs-CRP, IL-6), and thrombogenic factors (homocysteine, D-dimer), alongside clinical variables (APOs, autoimmune disorders) and ultrasonographic markers, carotid intima-media thickness (cIMT), plaque burden and plaque area (PA). Advanced ML/DL algorithms were employed to synthesise these heterogeneous datasets, identifying nonlinear interactions for better outcomes. Findings: Key insights reveal that hormonal dynamics (e.g., hypoestrogenism post-menopause) modulate CVD risk, while APOs induce persistent endothelial dysfunction and subclinical atherosclerosis. Biomarker sexual dimorphism is evident; hs-CRP exhibits higher baseline levels in women, whereas adiponectin declines with metabolic dysfunction. Radiomic features (cIMT progression, plaque morphology) are a well-established biomarker for CVD risk stratification. Conclusions: The integration of AI-driven multimodal systems holds the potential to enable a paradigm shift from population-based to personalised risk assessment, addressing critical gaps in female CVD health. However, this potential is currently at the early validation stage, and widespread clinical implementation requires prospective, externally validated, and ethnically diverse studies. Future applications should incorporate longitudinal biomarker profiling and advanced imaging, namely shear wave elastography and plaque radiomics, to optimise predictive models. Full article

Introduction: Caffeine is the most widely consumed psychoactive stimulant worldwide and acts primarily through antagonism of adenosine A1 and A2A receptors, thereby reducing sleep pressure and promoting wakefulness. Although its alerting and performance-enhancing effects are well established, its influence on sleep-related electroencephalography (EEG) has been investigated across diverse paradigms with substantial methodological heterogeneity. This systematic and mechanistic review aimed to synthesize human evidence on how caffeine affects sleep architecture, quantitative sleep EEG, and neurophysiological markers of sleep homeostasis, and to interpret these findings within current models of adenosine-mediated sleep–wake regulation. Materials and Methods: A systematic search of PubMed/MEDLINE, Web of Science, Scopus, Embase, PsycINFO, ResearchGate, and Google Scholar was conducted for studies published between January 1980 and January 2026, with the final search performed on 10 January 2026. Eligible studies were original human investigations examining caffeine exposure or administration and reporting sleep-related EEG outcomes, including polysomnographic sleep staging, spectral EEG analyses, or other EEG-derived sleep metrics. Two reviewers independently screened records and assessed eligibility, with disagreements resolved by consensus. Data on study design, participant characteristics, caffeine interventions, EEG methodology, and outcomes were extracted using a predefined form. Risk of bias was evaluated using the RoB 2 and ROBINS-I tools. Owing to marked heterogeneity across studies, findings were synthesized narratively within a mechanistic interpretive framework. Results: Thirty-two studies were included. Across highly heterogeneous paradigms—including acute bedtime or evening dosing, daytime or repeated caffeine use before nocturnal sleep, administration during prolonged wakefulness followed by recovery sleep, withdrawal protocols, and ambulatory/home EEG monitoring—the most consistent finding was suppression of low-frequency NREM EEG activity, particularly slow-wave activity and the lowest delta frequencies. Caffeine frequently increased faster EEG activity, including sigma/spindle and beta ranges, producing a lighter, more aroused, and more wake-like sleep EEG profile. These effects were especially prominent during early-night NREM sleep and in recovery sleep after sleep deprivation, where caffeine attenuated the expected homeostatic rebound in low-frequency power. REM-related effects were less consistent, but some studies reported delayed REM timing and subtler alterations in REM EEG. Emerging evidence further suggests that caffeine increases EEG complexity and shifts sleep dynamics toward a more excitation-dominant state. Several studies indicated that quantitative EEG measures were more sensitive than conventional sleep-stage variables in detecting caffeine-related sleep disruption. Dose, timing, habitual caffeine use, withdrawal state, age, circadian context, and adenosinergic genetic variation, particularly involving ADORA2A, moderated the magnitude of effects. We also highlighted the connection between current results and sports and sports science. Conclusions: Caffeine reliably alters the neurophysiological architecture of human sleep in a direction consistent with reduced sleep depth and weakened homeostatic recovery. The overall evidence supports a mechanistic model centered on adenosine receptor antagonism, attenuation of sleep-pressure build-up and expression, and a shift toward greater cortical arousal during sleep. Sleep EEG appears to be a sensitive marker of these effects, often revealing physiological disruption even when conventional sleep architecture changes are modest. Future research should prioritize larger and more diverse samples, pharmacokinetic and pharmacogenetic characterization, and ecologically valid high-resolution sleep monitoring to clarify the real-world and functional consequences of caffeine-induced EEG changes. Full article

This paper proposes a Hybrid-Field DD (HFDD) coupler designed for wireless power transfer (WPT) in mobile robots within smart manufacturing environments, utilizing a dual-coupling mechanism of magnetic and electric fields. The proposed coupler integrates Double-D coils for vertical magnetic field concentration with a split metal plate structure for enhanced electric field coupling in a compact, low-profile design. To evaluate the electromagnetic performance and the impact of inevitable eddy current interference, two distinct configurations—Front Plate Arrangement (FPA) and Back Plate Arrangement (BPA)—are analyzed through both theoretical modeling and 3D full-wave simulations (HFSSs). The comparative results demonstrate that the FPA model reduces the peak induced current intensity by 56.23 A/m compared to the BPA and achieves a peak leakage magnetic field intensity of 1.12 A/m, which is 28% lower than the 1.56 A/m observed in the BPA, offering a superior solution for suppressing leakage magnetic field and contributing to robust coupling stability. The high consistency between the proposed analytical methodology and numerical simulations underscores the theoretical robustness of the HFDD structure, establishing a clear design framework for efficient power transfer in robotic applications. Full article

In response to the need to monitor groundwater migration and structural damage to rock strata during tunnel excavation and coal mining, this paper presents a novel electromagnetic detection system that features continuous ground-based transmission and full-waveform underground observation. As the transmitted waveform is crucial for determining the distribution of induced eddy currents and the characteristics of the secondary field response, studying these response characteristics is essential for the system’s practical application. This study selects four typical transmission waveforms—step, triangular, half-sine and trapezoidal—and uses a tetrahedral, three-dimensional grid discretization method to analyze the transient electromagnetic full-wave response patterns of electrical and magnetic sources under different waveform excitations. This elucidates the propagation characteristics of electromagnetic fields in the medium. The research reveals that the waveform type during energization significantly influences the electromagnetic response, with the full-wave response characteristics of electrical and magnetic sources differing significantly in the near-source region and response trends converging in the far-source region. In practical detection, combining the advantages of the three-component responses of the electrical and magnetic sources can effectively improve detection accuracy. The findings of this study provide important theoretical support for optimizing the design of transient electromagnetic detection systems and precisely interpreting detection data. They also lay a theoretical foundation for electromagnetic detection applications in fields such as mineral resource exploration and engineering geological surveys. Full article

In recent years, the discovery of new ultra-deepwater reservoirs has significantly increased both the importance and the complexity of offshore oil production. One of the main challenges in qualifying structures to operate under such severe conditions is the fatigue limit state, particularly fatigue induced by ocean waves. Wave-induced fatigue remains, both at the design stage and during the operation of flexible risers, one of the most demanding issues for engineers responsible for ensuring their structural integrity. This study presents a state-of-the-art review of wave-induced fatigue analysis in flexible risers. It includes a brief historical overview of the problem, a summary of the fatigue assessment methodologies traditionally adopted in offshore engineering, a discussion of pioneering contributions to stress calculation, and an overview of the main research trends currently being pursued. These trends reflect emerging challenges related to fatigue life prediction, including the high computational cost of time-domain analyses, the presence of elevated contaminant levels in transported fluids, the development of new materials to reduce loads or enhance resistance to aggressive environments, and the assessment of remaining service life in the presence of damaged or corroded tensile wires. The potential use of monitored data to reduce uncertainties in numerical modelling is also addressed. Despite the challenges discussed, the main conclusion of this work is that ongoing technological developments are expected to ensure that flexible risers remain key components of offshore oil and gas production systems. Full article

Tidal-scale wave modulation is a critical yet complex process in macro-tidal estuaries. This study investigates semidiurnal wave modulations in the Changjiang River Estuary (CRE) using unique, long-term in situ observations and high-resolution ADCIRC–SWAN coupled simulations. Pronounced semidiurnal signals are identified in significant wave height (H_s), mean wave period, and wave direction. Observational results demonstrate that the modulation intensity is highest in Hangzhou Bay and the CRE mouth, decreasing gradually offshore. A key finding is that semidiurnal H_s maxima systematically coincide with peak flood currents and precede high water by approximately three hours. Long-term records confirm that this modulation persists year-round and intensifies during energetic events such as typhoons. The expression of the tidal signal depends on wave composition: wind-sea-dominated conditions exhibit stronger period modulation, whereas swell-dominated conditions favor coherent H_s modulation as kinematic tidal effects remain more apparent in the absence of strong local wind forcing. Numerical sensitivity experiments demonstrate that tidal currents are the primary driver of the observed wave modulation, while water-level effects are largely confined to shallow shoals. The results highlight that accurately reproducing the observed frequency–directional structure requires the inclusion of current-induced Doppler shifts and refraction. Beyond the classical following-current effects, the analysis suggests that the spatial deceleration of currents along the wave path acts as a kinematic trap that focuses wave action and sustains H_s intensification. This mechanism provides a physically plausible explanation for the observed phase relationship and points to the non-local nature of estuarine wave dynamics, where the wave state appears as an integrated response to cumulative current gradients along the propagation path. These findings emphasize the necessity of incorporating wave–current coupling in future coastal modeling and hazard forecasting. Full article

Welding is a critical joining process in civil and transportation infrastructure, enabling the fabrication of complex steel structural systems used in bridges, buildings, and other essential infrastructures. Despite strict adherence to established welding codes and standards, such as AWS D1.1 and AASHTO/AWS D1.5, welding flaws and service-induced defects can occur in welded components. Cause of defects and their structural impact, along with detection, sizing, and localization of these anomalies and flaws, are crucial for adequate maintenance, repair, or replacement planning without compromising the functionality of in-service components. Among available NDT techniques, ultrasonic testing (UT) remains one of the most widely adopted methods of weld inspection due to its depth of penetration, sensitivity to internal defects, and suitability for field deployment. Recent advancements in ultrasonic technologies, particularly Phased Array Ultrasonic Testing (PAUT), along with its emerging approaches such as Full Matrix Capture (FMC) and the Total Focusing Method (TFM), have significantly enhanced inspection accuracy, repeatability, and interpretability. These techniques enable flexile beam steering, multi-angle interrogation, and improved imaging of complex geometries. This paper presents a comprehensive review of PAUT for the inspection of welded steel infrastructure adhering to the recommendations and requirements of the relevant codes and standards, synthesizing the current literature on PAUT principles, wave modes, probe configurations, and data acquisition strategies. Emphasis is placed on the practical implementation of PAUT in civil infrastructure inspection, its advantages over conventional NDT methods, and its potential to support informed decisions related to quality acceptance, repair, and long-term maintenance planning. This paper concludes by identifying current challenges and future research directions for advanced ultrasonic inspection of welded steel structures. Full article

Beach nourishment is a widely adopted nature-based solution for coastal erosion; however, its design efficacy and morphodynamic resilience under extreme wave conditions remain inadequately quantified, posing challenges for coastal hazard assessment. This study integrates physical-model experiments and XBeach numerical simulations to investigate the hydrodynamic and morphodynamic behavior of nourished beaches subjected to typhoon-driven extreme wave conditions at a headland-bay beach on Meizhou Island, China. Physical-model experiments were conducted to examine shoreline response and sediment redistribution under extreme waves for three nourishment tests. XBeach simulations resolved wave-induced currents, water-level variations, and sediment transport processes, enabling continuous tracking of nearshore hydrodynamics and beach profile evolution for three nourishment tests during Typhoon Doksuri. Results indicate that nourishment geometry and groin configuration play a dominant role in wave breaking patterns, sediment transport pathways and erosion–deposition distributions. Groin positions strongly influence alongshore sediment transport. Relocating the groin to an accretional zone reduces lee-side erosion and promotes a more stable shoreline. Steeper nourishment foreshore slopes promote offshore wave shoaling and breaking, enhancing fast wave-energy dissipation, shifting erosion seaward and limiting landward erosion extent. Consistent responses from both experimental and numerical results demonstrate that nourishment stability under extreme wave conditions is better characterized by the combined effects of erosion extent, erosion length, erosion depth, erosion volume, and alongshore and cross-shore sediment redistribution. The integrated physical–numerical approach provides a practical framework for assessing beach nourishment stability during coastal hazard events and offers guidance for the design and evaluation of resilient beach nourishment in wave-dominated, typhoon-prone coastal regions. Full article

Ochratoxin A (OTA) is a highly toxic mycotoxin commonly detected in food and agricultural products, requiring sensitive analytical methods for reliable monitoring. Herein, we report an ultrasensitive turn-on electrochemical aptasensor for OTA detection based on a target-induced displacement of an aptamer–complementary DNA (cDNA) duplex assembled on an electrochemically reduced graphene oxide (ERGO)-modified glassy carbon electrode (GCE). In the absence of OTA, a methylene blue (MB)-labeled aptamer hybridized with cDNA is immobilized on the ERGO surface via π–π stacking interactions, forming a rigid duplex that suppresses electron transfer and yields a low electrochemical signal. Upon OTA binding, the aptamer undergoes a conformational transition into a G-quadruplex structure, leading to dissociation of the cDNA strand. This target-induced folding brings the MB redox tag into close proximity to the ERGO surface, markedly accelerating electron transfer and enhancing the cathodic reduction current of MB, thereby producing a pronounced signal-on response in square-wave voltammetry (SWV). The ERGO-modified electrode provides a conductive and stable interface without chemical linkers. Under optimized conditions, the aptasensor shows a linear response to OTA from 10 fM to 100 pM with an ultralow LOD of 0.67 fM, together with high selectivity, good reproducibility, and satisfactory stability. This work demonstrates a simple and effective turn-on aptasensing strategy for sensitive electrochemical detection of OTA. Full article

Piping systems must cope with the internal pressure of the fluid they carry. They are almost always well-designed for withstanding steady-flow pressures, but allowing for unsteady-flow pressures and for fatigue can be more challenging. Positive and negative gauge pressures induced by waterhammer waves are possibly the most extreme that piping is likely to face during its lifetime. It is widely accepted that this should be addressed by analyses during the design phase, but this is usually done under the assumption that consequential (non-hoop) structural movements do not affect the calculated pressures. However, the calculated pressures are used as input to the structural design. Commonly, attention focusses on static predictions of induced hoop stresses and on the risk of buckling, but attention sometimes has to be paid to dynamic responses. In these cases, the complexity of the structural analysis depends on the assumed degrees of freedom of possible movement, so it is desirable to avoid including unnecessary detail. The title of this paper poses one question that is frequently asked. However, the correct answer is not always obtained, partly because highly misleading answers were published in one early paper, the rebuttals to which were much less widely reported. The current contribution attempts to answer the question for both fixed and movable bends. Attention is paid to pressure transients arriving at bends from remote locations and potentially inducing pipe movement. Then, the opposite effect is considered, namely the generation of pressure transients by structural movements. To avoid distorting the picture by combining this with nominally unrelated causes, strong simplifications are made—e.g., disregarding all forms of energy dissipation. Full article

Sustainable feedstock management remains a major challenge in laser beam powder bed fusion (PBF-LB), where conventional reuse strategies are typically limited to sieving and blending rather than full material regeneration. Ultrasonic atomization (UA) offers a fundamentally different powder production route based on capillary-wave instabilities induced at the surface of a molten metal by high-frequency vibrations. In contrast to turbulence-driven atomization, droplet formation in UA is primarily governed by ultrasonic frequency and intrinsic thermophysical properties of the melt, enabling quasi-deterministic particle formation with high sphericity and reduced satellite formation. In this study, ultrasonic atomization was investigated as a closed-loop route for converting PBF-LB-manufactured 316L stainless steel parts into reusable powder. Printed rods were remelted and atomized under controlled variation of electric current and vibration amplitude. The resulting powders were characterized in terms of morphology, internal microstructure, particle size distribution, chemical composition, and gas impurity content. UA produced highly spherical particles with reduced internal porosity and improved flowability compared to the initial gas-atomized powder, while preserving the principal alloying elements. An increase in oxygen content was observed after recycling, attributed to selective high-temperature oxidation under residual oxygen in nominally inert conditions. The results establish a mechanistic framework for transforming consolidated PBF-LB material into secondary feedstock and identify key parameters governing structural and compositional stability in closed-loop recycling. Full article