Search Results (263)

This study presents a computational, simulation-based investigation of the dielectric response of human hand tissues, skin, fat, muscle, and bone to radiofrequency (RF) electromagnetic fields emitted by mobile devices. The widespread adoption of handheld devices and the deployment of fifth-generation (5G) networks, including millimetre-wave (mmWave) bands, have intensified concerns regarding localized human exposure to RF radiation, particularly in the hand, which serves as the primary interface during device operation. Using validated dielectric property datasets, numerical simulations were performed across the frequency range of 0.5–40 GHz, employing the Finite-Difference Time-Domain (FDTD) method to solve Maxwell’s equations, with analytical evaluations conducted in Maple-18. A heterogeneous multilayer hand phantom was developed, and simulations were conducted under controlled exposure conditions, including a transmitted power of 1 W, antenna gain of 2 dBi, and incident power density of 5 W/m², consistent with ICNIRP and NCC safety guidelines. Tissue responses were assessed over a temperature range of 10–40 °C to account for thermal variability. The results demonstrate strong frequency- and temperature-dependent behaviour of dielectric properties, intrinsic impedance, reflection coefficient, attenuation, and specific absorption rate (SAR). At lower frequencies (<1 GHz), RF energy penetrated more deeply with distributed absorption and relatively low SAR values, whereas higher frequencies (3–40 GHz) produced highly localized absorption in superficial tissues, particularly skin and muscle. Increasing temperature led to significant increases in permittivity, conductivity, and SAR, with up to a twofold enhancement observed between 10 °C and 40 °C. These findings confirm that 5G and mmWave exposures result in predominantly surface-confined energy deposition in hand tissues. The study provides a robust computational framework for evaluating hand device electromagnetic interactions and offers quantitative insights relevant to antenna design, exposure compliance assessment, and the development of evidence-based safety guidelines. Full article

The constant growth of IP data traffic, driven by sustained annual increases surpassing 26%, is pushing current optical transport infrastructures towards their capacity limits. Since the deployment of new fiber cables is economically demanding, ultra-wideband transmission is emerging as a promising cost-effective solution, enabled by multi-band amplifiers and transceivers spanning the entire low-loss window of standard single-mode fibers. In this scenario, an accurate modeling of the frequency-dependent fiber parameters is essential to reliably model optical signal propagation. In particular, the combined impact of attenuation variations with frequency and inter-channel stimulated Raman scattering (SRS) fundamentally shapes the power evolution of wide wavelength division multiplexing (WDM) combs and directly affects nonlinear interference (NLI) generation, as well as the amount of ASE noise. In this work, we review a set of analytical approximations, based on phenomenological approaches, for frequency-dependent attenuation and Raman scattering gain, and analyze their impact on achieving an effective balance between computational efficiency and physical fidelity. Through extensive analyses performed with the open-source software GNPy (version 2.12, Telecom Infra Project) on an optical line system exploring multi-band scenarios spanning C+L+S, C+L+E, and U-to-E transmission, we demonstrate that the proposed approximations reproduce the reference SRS power evolution and NLI profiles with root mean square errors (RMSEs) consistently below 0.03 dB, and down to the 10⁻³–10⁻² dB range for the most accurate configurations. Although the current implementation does not yet provide a direct reduction in computational time, the proposed framework lays the groundwork for future developments toward closed-form or semi-analytical solutions, enabling more efficient modeling and optimization of ultra-wideband optical transmission. Full article

Subsurface exploration of Mars is essential for understanding its geological evolution and potential water ice distribution. Subsurface radar sounding is an effective technique for detecting layered structure and physical parameters beneath the Martian surface. However, existing methods often neglect the influence of loss tangent and rely on data-driven approaches without physical constraints, limiting their accuracy in high-lossy environments and reducing their physical interpretability. To overcome these limitations, this paper proposes a dual-branch physics-informed network (DBPINet) for the joint inversion of layer thickness, permittivity, and loss tangent of Martian layered media. This method introduces a dual signal loss tangent branch (DSLT-Branch) to extract frequency-dependent attenuation features from dual-frequency radar signals and incorporates a physics-informed loss function based on the electromagnetic transmission-line model to embed physical laws into the learning process. Multiple numerical and measured experiments demonstrate the effectiveness of DBPINet. Compared with the MLP-based baseline and the more advanced LMPINet, DBPINet achieves significant improvements in different layered subsurface models. Specifically, on the three-layer models, the mean absolute percentage error (MAPE) for layer thickness, permittivity, and loss tangent is reduced by 4.793%, 3.600% and 4.559%, respectively. Meanwhile, DBPINet exhibits enhanced robustness under noisy conditions. When applied to real Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) data acquired over the Medusae Fossae Formation (MFF) region, the inversion results reveal a three-layer subsurface structure (a volcanic ash surface layer, an ice-mixed basaltic middle layer, and a basaltic basement) that is consistent with existing geological interpretations. Full article

Frequency-selective attenuation is widely needed in integrated analog front-ends, yet conventional on-chip RC low-pass filters occupy unfeasibly large silicon areas for low-frequency cutoffs and inherently introduce cumulative phase lag. Motivated by the nonlinear, frequency-dependent state evolution of memristive devices, this work experimentally demonstrates a highly compact, capacitor-free memristor–resistor network that functions as a variable-cutoff, zero-phase-lag resistive attenuator. An Au/HfO₂/Au memristor (15 µm × 15 µm) is connected in series with a load resistor and characterized over a wide frequency range. By leveraging the finite time constant of internal ionic drift, the attenuation bandwidth is strictly programmable via the device’s initial resistance. Cutoff frequencies of approximately 10 Hz, 1 kHz, and 10 kHz are achieved for initial resistances of 400 k$\Omega \pm$30 k$\Omega$, 300 k$\Omega \pm$30 k$\Omega$, and 200 k$\Omega \pm$30 k$\Omega$, respectively. Remarkably, the nonlinear state-switching mechanism enables a steep post-cutoff attenuation rate approaching −60 dB/dec—equivalent to a cascaded third-order RC network—using only a single nanoscale device. Rather than functioning as a strictly linear time-invariant (LTI) filter, the proposed circuit operates as a state-adaptive edge-processor. Its inherent amplitude-dependent dynamics and total absence of reactive poles make it exceptionally suited for highly specialized, area-constrained applications, including zero-phase closed-loop noise suppression, frequency-to-amplitude conversion, and amplitude-aware event-driven sensory preprocessing. Full article

Ultrasonic sensing is an effective tool for characterizing heterogeneous concrete structures, yet quantitative interpretation of ultrasonic attenuation remains challenging due to aggregate-induced multiple scattering and spatial non-uniformity. This study proposes a path-integrated ultrasonic attenuation modeling framework for concrete with random aggregates. A quasi-one-dimensional discretized wave equation is coupled with a modified version of the Waterman–Truell effective medium theory, in which multiple scattering effects are corrected by incorporating a Percus–Yevick structure factor and a geometric equivalence scheme for non-spherical aggregates. By discretizing the propagation path into locally homogeneous layers, cumulative attenuation is evaluated through explicit path integration, allowing spatial variations in aggregate volume fraction to be captured. Low-frequency ultrasonic transmission experiments (25 kHz) are conducted using serially assembled concrete specimens with controlled aggregate contents. The results reveal pronounced path-dependent attenuation behavior governed by local aggregate distribution. Compared with classical and effective Waterman–Truell models, the proposed approach significantly improves prediction accuracy, achieving a mean absolute percentage error of 7.29%. The framework provides a physically interpretable and experimentally validated method for ultrasonic sensing of heterogeneous concrete, with potential applications in non-destructive evaluation and structural health monitoring of high-end concrete-based engineering structures. Full article

Intercomparison studies between satellite-based and ground-based radar systems are essential for advancing radar technologies and improving precipitation retrieval algorithms. This study conducted a systematic literature review of Global Precipitation Measurement Mission (GPM) Dual-Frequency Precipitation Radar (DPR) and ground-based radar intercomparison studies using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) method, focusing on peer-reviewed literature published between 2014 and 2024. The review synthesizes current knowledge of DPR precipitation detection and estimation, including the application of DPR in ground-based radar calibration, and discussions on retrieval methods and attenuation correction algorithms. Most studies used a volume-matching method to compare observations between datasets and examine S- and C-band radars from national networks. Most analyses occurred over the Northern Hemisphere, and individual ground-based radars were more frequently compared to DPR rather than examining mosaics. Beyond summarizing existing studies, this review identifies systematic, geographic, methodological, and algorithmic gaps that constrain comprehensive validation of DPR products. Recurrent bias patterns—such as precipitation-type-dependent errors and attenuation-related uncertainties—highlight priority areas for algorithm refinement and targeted validation campaigns. By synthesizing validation strategies and recurring performance limitations, this work provides a structured reference for future intercomparison studies, supports more standardized validation practices, and informs the development of improved precipitation retrieval algorithms, ground-based radar calibration practices, and next-generation satellite radar missions. Full article

Background/Objectives: The attenuation coefficient (AC) is a quantitative ultrasound parameter that describes the frequency-dependent reduction of acoustic energy as ultrasound waves propagate through biological tissues. Recently, AC has gained increasing relevance in abdominal ultrasound as an objective and reproducible biomarker for tissue characterization, particularly in the assessment of diffuse parenchymal diseases. Unlike conventional qualitative B-mode imaging, AC provides standardized numerical measurements that improve interobserver reproducibility and facilitate longitudinal monitoring. Methods: This review provides a comprehensive and critical overview of the current clinical applications of AC measurements in abdominal ultrasound, mainly focusing on liver steatosis quantification. Emphasis is placed on the comparative evaluation of commercially available AC-based technologies, highlighting their methodological differences, validation evidence, and diagnostic performance to support future efforts toward harmonization and standardization across ultrasound platforms. Results: Several studies have demonstrated a strong correlation between AC values and established reference standards, including magnetic resonance imaging–proton density fat fraction (MRI-PDFF) and histopathological grading, supporting its role in the noninvasive evaluation of liver steatosis. The growing clinical adoption of AC has been accompanied by the development of multiple vendor-specific software implementations integrated into modern ultrasound systems. Although these platforms share a common physical basis, they differ substantially in algorithmic design, signal processing strategies and region-of-interest selection. These differences may influence absolute AC values and diagnostic cutoff thresholds, therefore limiting direct comparability across systems. Another factor that further contributes to the heterogeneity of reported cutoff values is the variability in validation approaches, with some technologies validated against liver biopsy and others against MRI-PDFF. Conclusions: AC is a promising quantitative ultrasound biomarker for noninvasive liver steatosis assessment, showing strong correlation with histology and MRI-PDFF. However, inter-vendor variability currently limits cross-platform comparability. Standardized acquisition protocols, unified quality-control criteria, phantom-based cross-calibration, and consistent vendor-specific reporting are essential to ensure reliable longitudinal monitoring and broader clinical implementation. Full article

Surface electromyography (sEMG) signals are inevitably affected by noise during acquisition, thereby degrading signal quality and analytical reliability. Most existing denoising methods combine signal decomposition with thresholding, and their performance depends on empirically set decomposition parameters and threshold estimation. However, in high-rate repetitive motions such as rapid keystrokes, sustained high-duty-cycle muscle activation biases universal-threshold noise estimation, leading to unreliable thresholds. To overcome these issues, an sEMG denoising method that integrates the Walrus Optimizer (WO) with Variational Mode Decomposition (VMD) is proposed. WO is employed to optimize key VMD parameters, including the number of modes K and the penalty factor $\alpha$. Based on this method, an improved threshold estimation strategy is developed to accommodate high-duty-cycle sEMG during rapid keystrokes. It reduces thresholding-induced over-attenuation of meaningful myoelectric components. The dataset included 18 participants with sEMG recorded from six muscles during rapid keystroke tasks (10 trials per participant; 20 keystrokes per trial). Across input signal-to-noise ratios (SNRs) of 0, 5, 10, 15 dB, the proposed method achieved a median SNR improvement (ΔSNR) ranging from 2.75 to 6.65 dB and a median root-mean-square error (RMSE) reduction rate (ΔRMSE%) ranging from 27% to 53%, while maintaining spectral fidelity with a median of median frequency variation rate (ΔMDF%) below 3.48%.These results indicate that the proposed method provides an efficient and reliable solution for sEMG signal processing in rapid keystroke analysis. Full article

To mitigate the high contact forces and noise inherent in traditional hard-impact dampers, this work evaluates the efficacy of a soft viscoelastic vibro-impact interface for passive vibration suppression. This study investigates the nonlinear dynamic behavior of a cantilever beam equipped with a soft vibro-impact interface, combining theoretical modeling and experimental validation to explore energy redistribution and damping enhancement mechanisms. The system is excited under both free and forced vibration conditions, and its response is characterized through tip displacement, acceleration, and impact force measurements. Numerical simulations based on an impact-contact model accurately predict the amplitude-dependent broadening and frequency shift observed in the experiments, demonstrating that the soft impacts introduce nonlinear stiffness and effective damping. The comparison between theoretical and experimental frequency responses confirms that energy is transferred from the primary mode to higher harmonics, leading to broadband vibration attenuation. These findings provide experimental evidence of the nonlinear energy transfer mechanisms previously predicted, including harmonic resonance stimulation and non-resonant energy exchange. The results demonstrate that soft-contact vibro-impact dampers can be effectively tuned to exploit nonlinear dynamics for enhanced passive vibration suppression, bridging the gap between theoretical predictions and practical implementations. Full article

In adverse weather and rapidly changing scenes, fog severely reduces image contrast and obscures target textures, causing small-object detection to suffer from feature weakening and background interference. Many existing detectors, meanwhile, rely on computationally intensive feature modeling, making it difficult to achieve real-time inference while effectively mitigating fog-induced degradation. To address these challenges, we propose HS-MambaDet, a frequency-compensated hidden-state state-space detection network for accurate and efficient small-object detection in foggy environments. Specifically, we embed a lightweight SSD-based state-space modeling module with frequency-domain window attention (FWS-SSD) into the backbone, preserving long-range dependency modeling with low computational overhead while emphasizing informative high-frequency details and attenuating low-frequency haze interference. This study highlights a symmetry-inspired balance between global context modeling and local detail restoration. In the neck network, a multi-scale frequency-spatial fusion (MFSF) module further strengthens fine-grained object representations and cross-scale contextual interactions. In addition, we introduce a fog-aware detection loss to better supervise low-contrast and detail-deficient regions, improving detection robustness in foggy scenes. Extensive experiments on RTTS and Cityscapes demonstrate clear and consistent gains: HS-MambaDet outperforms representative one-stage, two-stage, and state-space-based detectors by up to 4.3% in mAP@0.5 and 6.5% in mAP@0.5:0.95, while maintaining competitive inference efficiency, thereby achieving a favorable accuracy-efficiency trade-off for foggy small-object detection. Full article

Display-driven optical stimuli underpin a major class of clinically validated digital therapeutics (DTx) now expanding from neuropsychiatric disorders to chronic diseases. The display’s optical characteristics—spectral power distribution, luminance, contrast, and temporal modulation—therefore define the delivered dose of these software-based interventions. In this context, blue-rich emission in the 450–480 nm band, particularly with evening exposure, can suppress melatonin via melanopsin-mediated intrinsically photo-sensitive retinal ganglion cell (ipRGC) pathways and perturb circadian timing, potentially attenuating therapeutic efficacy. This review summarizes clinical evidence for display-enabled DTx across major indications and synthesizes mechanistic and experimental data linking blue light to sleep and circadian disruption, with downstream mood, cognitive, cardiovascular, and metabolic effects, as well as increased risk of cancer and skin damage. This review distinguishes wavelength-dependent hazards by separating retinal photochemical risk in the roughly 415–450 nm range from circadian-disruptive melanopic effects in the 450–480 nm range, informing spectrum optimization for therapeutic use. It then synthesizes mitigation strategies spanning display emitter spectrum engineering, optical filtering or conversion films, and software controls such as color temperature tuning, high-frequency dimming, metameric spectrum design, and personalized circadian lighting. The review concludes with design, prescription, and standards considerations to align display output with therapeutic intent. Full article

Trigeminal neuralgia and orofacial pain often require effective local anesthesia with minimal side effects. Puerarin (PUE), a major bioactive flavonoid derived from Pueraria lobata, has shown potential analgesic properties. This study aimed to investigate the inhibitory effects of local PUE administration on the excitability of wide-dynamic-range (WDR) neurons in the spinal trigeminal nucleus caudalis (SpVc) and to compare its potency with the conventional local anesthetic lidocaine. Extracellular single-unit recordings were performed on SpVc WDR neurons in anesthetized rats. PUE (1 and 10 mM) or lidocaine (37 mM; 1%) was administered subcutaneously into the peripheral receptive field. Neuronal responses to graded non-noxious and noxious mechanical stimuli were quantified before and after drug application. Local administration of PUE significantly suppressed the mean firing frequency of SpVc WDR neurons in a dose-dependent and reversible manner. The inhibitory effect peaked at 10 min post-injection and recovered within 30 min. Notably, 10 mM PUE exerted an inhibitory magnitude (68.7 ± 6.4%) comparable to that of 37 mM lidocaine (58.1 ± 4.3%), indicating that PUE possesses approximately four-fold the inhibitory potency of lidocaine on a molar basis. The suppressive effect was consistent across both non-noxious and noxious stimulus intensities. These findings provide the first in vivo evidence that PUE effectively attenuates trigeminal nociceptive transmission, likely via the modulation of voltage-gated sodium channels and acid-sensing ionic channels at peripheral nerve terminals. As a natural dietary constituent with high potency and a low risk of systemic side effects, PUR represents a promising candidate for complementary and alternative medicine in the management of orofacial pain, such as temporomandibular disorders and trigeminal neuralgia. Full article

Infrasound, physically defined as sound at frequencies below 20 Hertz, can travel long distances with minimal attenuation and permeate biological tissues due to its marked particle displacement and deep penetration. Generated by both natural phenomena and human-made systems, infrasound has drawn increasing scientific and public attention regarding its potential physiological and psychological effects. Experimental studies demonstrate that infrasound can modulate mechanosensitive structures at the cellular level, particularly pressure-sensitive ion channels such as PIEZO1 and TRPV4, leading to intracellular calcium influx, oxidative stress, altered intercellular communication, and in some settings, apoptosis. These responses vary according to sound pressure levels, frequencies, exposure duration, and tissue type. In the cardiovascular system, higher sound pressures have been associated with mitochondrial injury and fibrosis, whereas low sound pressures may exert context-dependent protective effects. In animal models, prolonged or intense exposure to infrasound has been shown to induce neuroinflammatory responses and memory impairment. Short-term studies in humans at moderate intensities have reported minimal physiological changes, with psychological and contextual factors influencing symptom perception. Occupational environments such as factories and agricultural settings may contain elevated levels of infrasound, underscoring the importance of systematic measurements and exposure assessments. At the same time, controlled infrasound stimulation has shown potential as an adjunct modality in bone repair and tissue regeneration, highlighting its dual capacity as both a biological stressor and a possible therapeutic tool. Overall, existing data indicate that infrasound may be harmful at chronic exposure depending on intensity and frequency, yet beneficial when precisely regulated. Future research should standardize exposure metrics, refine measurement technologies, and clarify dose–response relationships to better define the health risks and therapeutic applications of infrasound. Full article

Using a quantile–frequency connectedness framework, this study analyzes the regime-contingent and horizon-specific transmission of shocks among AI assets, FinTech markets, and Blue Economy financial instruments. The empirical results reveal a distinctly asymmetric connectedness structure, whereby high-frequency spillovers intensify in upper-quantile states associated with liquidity stress and sentiment-driven trading, while low-frequency connectedness remains comparatively muted, thereby preserving cross-segment diversification potential. AI assets emerge as dominant net transmitters in short-horizon dynamics, reflecting rapid innovation cycles and speculative adjustments. FinTech markets exhibit stabilizing properties under median regimes but transition into net propagation roles when risk conditions escalate. Blue finance instruments act as conditional net absorbers, attenuating volatility originating from digital innovation-driven markets, particularly during adverse market states. By decomposing spillover intensities across quantiles and spectral bands, the analysis highlights a structural differentiation between innovation-sensitive digital assets and the comparatively stable behavior of blue-themed financial assets. These findings advance the understanding of nonlinear dependence, asymmetric contagion, and state-dependent co-movements in emerging financial ecosystems. The results provide actionable insights for systemic-risk measurement, cross-market shock diagnostics, and multi-asset portfolio construction in an increasingly interconnected global financial system. Full article

We quantify the transmission and absorption of 75–110 GHz radiation through ex vivo porcine skin. Millimeter waves are currently used in a range of technologies, including communication systems, fog-penetrating radar, and the detection of hidden weapons or drugs. They have also been proposed for use in non-lethal weaponry and, more recently, in targeted cancer therapies. Since pigs are often used as biological models for humans, determining how deeply millimeter waves penetrate a pig’s skin and influence the underlying tissues is essential for understanding their potential effects on humans. This experimental study aims to quantify that penetration and associated energy loss. The results show significant absorption in the skin and fat layer. Attenuation of over three orders of magnitude can be expected in penetration through a layer with a thickness of about 12 mm (−30 dB). The reflectance from the skin is similar at all frequencies. The values range from −10 to −20 dB, which probably depends on the texture of the skin. Therefore, most skin transfer loss is caused by absorption. Full article