Search Results (117)

γ-photon tomography, which leverages the high penetration and electrical neutrality of high-energy γ-photons, offers a promising non-contact approach for industrial flow field monitoring. However, γ-photon flow-field images are inherently grayscale and exhibit probabilistic statistical imaging characteristics, leading to color banding artifacts when processed by mainstream colorization algorithms like DeOldify, which compromise structural continuity and visual consistency. To address this issue, this paper proposes a Structure Enhancement Colorization Network (SECN) model for γ-photon flow-field image colorization. A U-Net + GAN framework is employed, with ResNet101 as the generator backbone. It integrates structure-aware enhancement and multi-scale attention modules, while the discriminator incorporates enhanced blocks for improved boundary and texture discrimination. By adaptively fusing global–local features across channel and spatial dimensions, the SECN model effectively suppresses color banding artifacts and enhances structural consistency. To validate the effectiveness of the proposed algorithm, two CFD-simulated γ-photon flow-field image colorization scenarios—namely a large-scale vortex wake and a horizontal wake—are used as evaluation targets. In terms of image quality metrics, the proposed colorization algorithm achieves PSNR, SSIM, FID, and MAE values of 32.5831, 0.8612, 17.8514, and 0.0191, respectively, corresponding to improvements over DeOldify of 4.54%, 2.82%, 5.18%, and 11.16%. When considering information entropy, the proposed colorization algorithm achieves an average entropy value of 4.0257, marking a 4.44% increase compared to DeOldify’s 3.8543, demonstrating superior information preservation and reduced uncertainty in reconstructing complex probabilistic structures. Furthermore, from the perspective of parameter inversion, the temperature inversion MAPE is 7.60%, which is a significant reduction of 18.42% compared to that of DeOldify. Full article

The growing need for remote patient monitoring, accelerated by the global pandemic and an aging population, necessitates the development of advanced non-contact technologies for measuring vital signs. In this study, an integrated, non-contact system for accurately measuring heart rate (HR) and body temperature (BT) is developed and validated. The proposed system combines a 60 GHz radar sensor and infrared (IR) sensor for HR and BT measurements, respectively, enhanced with advanced signal processing and an AI-based computer vision algorithm. A Window Filter and a Peak Uniformity algorithm were applied to the raw radar signal to mitigate noise and motion artifacts. For Temp measurement, an IR sensor with a narrow five-degree field of view (FOV) was integrated with a YOLO Pose-based tracking system using a camera and servo motors to automatically orient the sensor towards the user’s face. The system was validated with 30 healthy adult participants, benchmarked against a MAX30102 PPG sensor and Braun ThermoScan 7 for BT and BT measurements, respectively. The advanced signal processing reduced the HR Mean Absolute Error from 13.73 BPM to 5.28 BPM (p = 0.002), while the AI-guided IR sensor reduced the BT MAE from 4.10 °C to 1.64 °C (p < 0.001). These findings demonstrate that integrating 60 GHz radar with AI-driven tracking provides a promising approach for home-based trend monitoring. Full article

Objective: The aim of this study was to determine the optimal region-of-interest (ROI) pixel size for fractal dimension analysis on panoramic radiographs that best reflects implant stability assessed by resonance frequency analysis (ISQ) and to investigate whether implant stability can be directly estimated from radiographic images. Materials and Methods: This retrospective cross-sectional study included 65 patients for whom panoramic radiographs and resonance frequency analysis measurements were available. All panoramic images were converted to TIFF format and standardized to a resolution of 2627 × 1646 pixels. All radiographic images were obtained using the same panoramic imaging device and standardized acquisition protocol. Exposure parameters were adjusted within the manufacturer’s recommended range to ensure optimal image quality while maintaining methodological consistency across patients. During ROI selection, care was taken to avoid cortical bone margins, overlapping anatomical structures, and radiographic artifacts in order to ensure that the analyzed regions represented trabecular bone adjacent to the implant surface. Fractal dimension analysis was performed in the cervical peri-implant bone region, starting from the first bone–implant contact and extending apically, using three different ROI configurations. The ROI size was defined as 30 pixels apically and 10 pixels horizontally for FMD1, 30 × 20 pixels for FMD2, and 30 × 30 pixels for FMD3. Implant stability was assessed using ISQ values. Data distribution was evaluated using the Shapiro–Wilk test. Associations between ISQ and fractal dimension measurements were analyzed using Pearson and Spearman correlation analyses. Multiple linear regression models adjusted for age and sex were constructed to assess independent associations. Results: The mean age of the participants was 50.0 ± 9.9 years, and the mean ISQ value was 78.6 ± 5.9. The mean fractal dimension values were 1.466 ± 0.055 for FMD1, 1.595 ± 0.031 for FMD2, and 1.655 ± 0.046 for FMD3. No significant association was found between ISQ and FMD1 or FMD3. A weak positive correlation was observed between ISQ and FMD2; however, this association did not remain statistically significant after correction for multiple comparisons. In multiple linear regression analysis, ISQ was identified as an independent predictor of FMD2, but not of FMD1 or FMD3. Age and sex had no significant effect on fractal dimension measurements. Conclusions: Fractal dimension measurements derived from panoramic radiographs showed a weak association with implant stability that was dependent on the selected ROI pixel size. Among the evaluated configurations, the 30 × 20-pixel ROI at the cervical peri-implant region demonstrated the strongest association with ISQ values, suggesting that this ROI configuration showed the most consistent association with ISQ values among the tested ROI sizes. Full article

When is an unknown, confined environment traversable for a specific ground robot using only touch? We answer by (i) giving an environment-anchored definition of traversability, expressed through the max-min value $T^{★}(E;A)={sup}_{\pi \in {\Pi }_{S\to G}}{inf}_{s\in [0,1]}\varphi \left(\pi \left(s\right)\right)$, where the bottleneck margin $\varphi$ aggregates the clearance, curvature ($\rho \ge R_{min}$), slope/step, and friction constraints, and (ii) introducing an on-policy, tactile certificate (TC) that maintains a conservative, monotone lower bound $T_t$ using partial contact histories. The TC fuses pessimistic free-space from contacts and the body envelope, the M3 decaying contact memory as a risk prior, and local bend/FSR proxies; a certificate is issued when $T_t>0$ and the explored corridor graph connects S to G. Relative to Papers 1–2 (tactile traversal; offline software assurance), this work formalizes traversability itself and provides a tactile-only, online certificate computable during runs. In a retrospective analysis of 660 trials across Indoor/Outdoor/Dark lighting environments, (H1) the early TC margin predicts success and traversal time better than contact/dwell heuristics (higher AUC/$R^2$), (H2) the TC predictivity is lighting-invariant, and (H3) speed-gating M3 by a TC margin recovers part of the CB-V speed gap without degrading success. Artifacts include the TC implementation, explored-corridor graphs, and per-trial TC time series added to the Paper-1 log bundle; these materials are available from the corresponding author upon reasonable request. Full article

Continuous blood pressure (BP) monitoring is essential for the prevention and management of cardiovascular diseases. Traditional cuff-based methods cause discomfort during repeated measurements, and wearable sensors require direct skin contact, limiting their applicability. Radar-based contactless BP measurement has emerged as a promising alternative. However, radar pulse wave (RPW) signals are susceptible to motion artifacts, respiratory interference, and environmental clutter, posing persistent challenges to estimation accuracy and robustness. In this paper, we propose MARU-MTL, a Mamba-enhanced multi-task learning framework for continuous BP estimation using a single millimeter-wave radar sensor. To address signal quality degradation, a Variational Autoencoder-based Signal Quality Index (VAE-SQI) mechanism is proposed to automatically screen RPW segments without manual annotation. To capture long-range temporal dependencies across cardiac cycles, we integrate a Bidirectional Mamba module into the bottleneck of a U-Net backbone, enabling linear-time sequence modeling with respect to the segment length. We also introduce a multi-task learning strategy that couples BP regression with arterial blood pressure waveform reconstruction to strengthen physiological consistency. Extensive experiments on two datasets comprising 55 subjects demonstrate that MARU-MTL achieves mean absolute errors of 3.87 mmHg and 2.93 mmHg for systolic and diastolic BP, respectively, meeting commonly used AAMI error thresholds and achieving metrics comparable to BHS Grade A. Full article

Ground-penetrating radar (GPR) is a key non-destructive technique for subsurface reconstruction, widely valued for its ability to image buried structures without disruption. Among its various implementations, vehicle-mounted GPR has emerged as particularly suitable for highway tunnel assessment due to its rapid non-contact operation. However, current systems are often constrained by closely spaced antennas that generate strong direct coupling and consequently limit detection depth. To mitigate this issue, this paper proposes an antenna decoupling method based on coherent difference imaging. A differential decoupling model is first established to characterize the relationship between conventional transceiver signals and the derived differential signals, explicitly accounting for parameters such as antenna height and target depth. Furthermore, a coherent difference imaging algorithm is developed, employing a sliding-window coherence process to resolve dual-peak artifacts and restore focused target images. Simulations validate consistent performance across varying antenna heights, while experiments demonstrate over 37.2 dB isolation in the 1–3 GHz band and markedly improved imaging focus compared to conventional configurations, thereby enhancing buried target detection and supporting reliable data interpretation. Full article

Microneedle array (MNA) electrodes have garnered significant attention for their capacity to record high-fidelity surface bioelectrical signals over extended periods and convenience. However, accuracy limitations in 3D-printed metal MNA electrodes, particularly concerning surface roughness and insufficient tip sharpness, have been reported. Additionally, the prevalent use of nonporous metal substrates often results in poor flexibility. This study proposes a novel MNA electrode featuring a lightweight flexible substrate and sharp, smooth microneedles. Utilizing micron-level metal 3D printing with 316L stainless steel, we fabricated the electrodes in a single step. We evaluated the MNA electrode-skin interface impedance via frequency sweep and assessed mechanical properties using porcine skin, followed by the collection and analysis of bioelectrical signals. The results demonstrate that the contact impedance of the MNA electrode is comparable to that of standard gold cup electrodes, with validated flexibility and strength. Furthermore, the MNA electrodes achieved a high signal-to-noise ratio and minimal motion artifacts during recording, thereby enhancing both comfort and signal quality. The efficient production process facilitates the broader application of metal MNA electrodes. Full article

Small-scale two-phase flows are subject to intense capillary accelerations that must be treated with care in order to avoid artifacts often associated with the numerical methodologies used, such as excessive fragmentation of structures. This analysis proposes a formulation of capillary actions for compressible viscous two-phase flows within the framework of discrete mechanics, where the concept of mass is abandoned in favor of a law of motion that describes the conservation of accelerations, one related to inertia and the other to external actions. With the introduction of the capillary term, the sum of a capillary potential gradient and the dual curl of a vector potential is consistent with the other terms of the law of motion, a formal Helmholtz–Hodge decomposition. This fully compressible formulation reproduces the capillary waves generated by the source terms and the contact and shock discontinuities in the two immiscible fluids. This methodology completely eliminates parasitic currents due mainly to the presence of residual curl in the capillary source terms. Several classic examples demonstrate the validity of this approach. Full article

In the marine environment, numerous factors endanger the preservation of underwater rock surfaces as well as submerged archeological artifacts, including physical, chemical, and biological processes. Limestone and marble are common materials used in artifacts due to their availability and long-term durability. However, such surfaces provide a suitable substrate for the settlement of micro- and macro-organisms, causing so-called biofouling, which significantly contributes to stone deterioration. Previous studies have demonstrated the applicability of antifouling coatings containing ionic liquids (ILs) on marble surfaces and assessed their durability for up to 15 days under submerged environments. To further corroborate these results, additional physical studies (colorimetric, contact angles, capillarity water absorption measurements, and UV aging) were carried out on treated limestone. Washout tests were also performed on both lithotypes to verify the coatings’ stability under medium-term underwater exposures. The results of these investigations are reported here. Our data confirm that the application of IL-based coatings had no effect on the intrinsic properties of the limestone surfaces, as previously reported for marble, including resistance to daily UV irradiation. In addition, laboratory tests demonstrated good coating durability against seawater erosive action for up to 6 months. Full article

Drowsy driving and sudden medical emergencies are major contributors to traffic accidents, necessitating continuous, non-intrusive driver monitoring. Since current technologies often struggle to balance accuracy with practicality, this study presents the design, fabrication, and validation of a smart steering wheel prototype. The device integrates dry-contact electrocardiogram (ECG), photoplethysmography (PPG), and inertial sensors to facilitate multimodal physiological monitoring. The system underwent a two-stage evaluation involving a single participant: laboratory validation benchmarking acquired signals against medical-grade equipment, followed by real-world testing in a custom electric research vehicle to assess performance under dynamic conditions. Laboratory results demonstrated that the prototype captured high-quality signals suitable for reliable heart rate variability analysis. Furthermore, on-road evaluation confirmed the system’s operational functionality; despite increased noise from motion artifacts, the ECG signal remained sufficiently robust for continuous R-peak detection. These findings confirm that the multimodal smart steering wheel is a feasible solution for unobtrusive driver monitoring. This integrated platform provides a solid foundation for developing sophisticated machine-learning algorithms to enhance road safety by predicting fatigue and detecting adverse health events. Full article

At-rest PPG signals have been explored for detecting atrial fibrillation (AF), yet current signal-processing techniques do not achieve perfect accuracy even under low-motion artifact (MA) conditions. This study evaluates the effectiveness of a single-degree-of-freedom time–frequency (SDOF-TF) method in analyzing at-rest PPG signals for AF detection. The method leverages the influence of MA on the instant parameters of each harmonic, which is identified using an SDOF model in which the tissue–contact–sensor (TCS) stack is treated as an SDOF system. In this model, MA induces baseline drift and time-varying system parameters. The SDOF-TF method enables the quantification and removal of MA and noise, allowing for the accurate extraction of the arterial pulse waveform, heart rate (HR), heart rate variability (HRV), respiration rate (RR), and respiration modulation (RM). Using data from the MIMIC PERform AF dataset, the method achieved 100% accuracy in distinguishing AF from non-AF cases based on three features: (1) RM, (2) HRV derived from instant frequency and instant initial phase, and (3) standard deviation of HR across harmonics. Compared with non-AF, the RM for each harmonic was increased by AF. RM exhibited an increasing trend with harmonic order in non-AF subjects, whereas this trend was diminished in AF subjects. Full article

This article reviews recent advances in microwave and radar techniques for non-contact measurement of human vital signs in dynamic conditions. The focus is on solutions that work when the subject is moving or performing everyday activities, rather than lying motionless in clinical settings. This review covers innovative biodegradable and flexible antenna designs for wearable devices operating in multiple frequency bands and supporting efficient 5G/IoT connectivity. Particular attention is paid to ultra-wideband (UWB) radar, Doppler sensors, and microwave reflectometry combined with advanced signal-processing and deep learning algorithms for robust estimation of respiration, heart rate, and other cardiopulmonary parameters in the presence of body motion. Applications in telemedicine, home monitoring, sports, and search and rescue are discussed, including localization of people trapped under rubble by detecting their vital sign signatures at a distance. This paper also highlights key challenges such as inter-subject anatomical variability, motion artifacts, hardware miniaturization, and energy efficiency, which still limit widespread deployment. Finally, related developments in microwave imaging and early detection of pathological tissue changes are briefly outlined, highlighting the shared components and processing methods. In general, microwave techniques show strong potential for unobtrusive, continuous, and environmentally sustainable monitoring of human physiological activity, supporting future healthcare and safety systems. Full article

The Jingbaoer Grassland Jade Mine situated approximately 20 km northwest of Mazongshan Town in Gansu Province, China, represents an important source of nephrite dating back to the pre-Qin period. In this study, 58 representative nephrite samples were analyzed to investigate their mineralogical and geochemical characteristics using polarized light microscopy, scanning electron microscopy (SEM), electron probe microanalysis (EPMA), and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). The mine is situated near the contact zone between the Silurian Gongpoquan Group and Devonian granite, with surrounding rocks primarily consisting of Precambrian dolomitic marble. The nephrite displays diverse colors—white, bluish-white, sugar-white, and cyan—with darker tones and abundant manganese-stained dendritic and flocculent inclusions. It shows a relative density of 2.82–2.99, a refractive index of 1.60–1.62, and a vitreous to greasy luster. Texturally, the jade is predominantly composed of micro-fibrous interwoven tremolite, occasionally exhibiting oriented recrystallization textures. Minor minerals include diopside, apatite, titanite, chlorite, epidote, allanite, rutile, and graphite. Chemically, the samples are rich in SiO₂, MgO, and CaO, with trace amounts of FeO, MnO, Al₂O₃, and Na₂O. Notably, Sr and Sm are enriched, Nb is slightly depleted, and Eu shows a distinct negative anomaly. The average total rare earth content is 4.25 µg/g. The study suggests that the deposits in the research area are typical of the contact-metasomatic type, formed through multi-stage hydrothermal metasomatism between acidic granitic intrusions and dolomitic marble, creating favorable conditions for the formation of high-quality tremolite jade. Comparative analysis with jade artifacts excavated from the Tomb of Marquis Yi of Zeng suggests a possible provenance link to the Jingbaoer deposit, providing valuable evidence for the historical mining and distribution of nephrite during the Warring States period. Full article

Motion artifacts (MA) are a key factor affecting the accuracy of a measured arterial pulse signal at rest. This paper presents a generalized time–frequency method for MA removal that is built upon a single-degree-of-freedom (SDOF) model of MA, where MA is manifested as time-varying system parameters (TVSPs) of the SDOF system for the tissue–contact-sensor (TCS) stack between an artery and a sensor. This model distinguishes the effects of MA and respiration on the instant parameters of harmonics in a measured pulse signal. Accordingly, a generalized SDOF-model-based time–frequency (SDOF-TF) method is developed to obtain the instant parameters of each harmonic in a measured pulse signal. These instant parameters are utilized to reconstruct the pulse signal with MA removal and extract heart rate (HR) and respiration parameters. The method is applied to analyze seven measured pulse signals at rest under different physiological conditions using a tactile sensor and a PPG sensor. Some observed differences between these conditions are validated with the related findings in the literature. As compared to instant frequency, the instant initial phase of a harmonic extracts respiration parameters with better accuracy. Since HR variability (HRV) affects arterial pulse waveform (APW), the extracted APW with a constant HR serves better for deriving arterial indices. Full article

Investigating the pore structure and understanding the relationship between pore characteristics and mechanical properties are crucial to research in the study of cement mortar. At present, the segmentation of large-scale concrete pores is mainly conducted using traditional algorithms or software, which are time-consuming and operate in a semi-automated manner. However, the application of these methods faces challenges when analyzing large-scale rock pores due to factors such as a lack of data, artifacts, and inconsistent contrast. In this study, six series of cement mortars were subjected to real-time CT scanning under uniaxial loading (RT-CT) to collect real-time three-dimensional data on the evolution of pore structures during loading. To address issues such as artifacts and inconsistent contrast, a new augmentation method was proposed to overcome artifacts and enhance contrast consistency. Finally, the augmented dataset was utilized for training, and the Fast R-CNN algorithm served as the framework for developing the pore recognition model. The results indicate that the improved algorithm demonstrates enhanced convergence and greater accuracy in pore segmentation. A mathematical model is developed to relate uniaxial compressive strength (UCS) to pore fractal dimension and porosity, based on pore segmentation analysis. The fractal dimensions evolution of each specimen is consistent with the progressive failure indicated by the strain-stress curve. Under uniaxial loading, specimens with a 4:1 cement–sand ratio exhibited peak strength. The incorporation of fractals improved particle contact, thereby facilitating the formation of the skeletal structure. These efforts contribute to improving the identification of the deformation of cement mortars. Full article