Search Results (324)

The Qiangtang Basin (Tibetan Plateau) poses significant geophysical challenges for seismic exploration due to near-surface widespread permafrost and steeply dipping Mesozoic strata induced by the Cenozoic Indo-Eurasian collision. These seismic geological conditions considerably contribute to lower signal-to-noise ratios (SNRs) with complex wavefields, to some extent reducing the reliability of conventional seismic imaging and structural interpretation. To address this, the common-reflection-surface (CRS) stack method, derived from optical paraxial ray theory, is implemented to transcend horizontal layer model constraints, offering substantial improvements in high-SNR prestack gather generation and prestack depth migration (PSDM) imaging, notably for permafrost zones. Using 2D seismic data from the basin, we detailedly compare the CRS stack with conventional SNR enhancement techniques—common midpoint (CMP) FlexBinning, prestack random noise attenuation (PreRNA), and dip moveout (DMO)—evaluating both theoretical foundations and practical performance. The result reveals that CRS-processed prestack gathers yield superior SNR optimization and signal preservation, enabling more robust PSDM velocity model building, while comparative imaging demonstrates enhanced diffraction energy—particularly at medium (20–40%) and long (40–60%) offsets—critical for resolving faults and stratigraphic discontinuities in PSDM. This integrated validation establishes CRS stacking as an effective preprocessing foundation for the depth-domain imaging of complex permafrost geology, providing critical improvements in seismic structural resolution and reduced interpretation uncertainty for hydrocarbon exploration in permafrost-bearing basins. Full article

In integrated PNT systems, due to defects in satellite signals and long-wave signals, VLF signals can be an essential supplement. However, there is currently a lack of VLF timing systems in the world, and it is impossible to evaluate the impact of the propagation delay of these signals. Based on the theory of very-low-frequency propagation, this paper determines the waveguide mode propagation at ultra-long distances as the main research direction, establishes a signal phase change model, gives a theoretical formula for the phase velocity of VLF signals, and analyzes the main factors affecting the phase velocity of VLF signal propagation. Finally, combined with historical observation data, the phase change is predicted, compared, and analyzed. The results show that the theoretical calculation is consistent with the measured data. The average error of the delay prediction is 0.015 microseconds per 100 km, and the maximum error of the delay prediction is 0.152 microseconds per 100 km. Full article

Void defects, manifested as distributed porosity, are common in metal additive manufacturing (AM) and can significantly degrade the mechanical performance and reliability of fabricated components. To enable real-time quality control during fabrication, this study proposes a grating laser ultrasonic method for the online evaluation of porosity in AM parts. Based on the theoretical relationship between surface acoustic wave (SAW) velocity and material porosity, a non-contact detection approach is developed, allowing the direct inference of porosity from the measured SAW velocities without requiring knowledge of the exact source–detector distance. Numerical simulations are conducted to analyze SAW propagation under varying porosity conditions and to validate the inversion model. Experimental measurements on aluminum alloy specimens with different porosity levels further confirm the sensitivity of SAW signals to internal voids. The results show consistent waveform and spectral trends between the simulation and experiment, supporting the feasibility of the proposed method for practical applications. Overall, the findings demonstrate the potential of this approach for the accurate online monitoring of void defects in metal AM components. Full article

Advances in Industry 4.0 and the emergence of Industry 5.0 are driving the development of intelligent, sustainable manufacturing systems, where embedded sensing and real-time health diagnostics play a critical role. However, implementing robust predictive maintenance in production environments remains challenging due to the variability in machine operations and the lack of access to internal control data. This paper introduces a lightweight, embedded-compatible framework for health status signature extraction based on empirical mode decomposition (EMD), leveraging only data from a single triaxial accelerometer. The core of the proposed method is a cycle-synchronized segmentation strategy that uses accelerometer-derived velocity profiles and cross-correlation to align signals with machining cycles, eliminating the need for controller or encoder access. This ensures process-aware decomposition that preserves the operational context across diverse and dynamic machining conditions to address the inadequate segmentation of unstable process data that often fails to capture the full scope of the process, resulting in misinterpretation. The performance is evaluated on a challenging real-world manufacturing benchmark where the extracted intrinsic mode functions (IMFs) are analyzed in the frequency domain, including quantitative evaluation. As results show, the proposed method shows its effectiveness in detecting subtle degradations, following a low computational footprint, and its suitability for deployment in embedded predictive maintenance systems on brownfield or controller-limited machinery. Full article

Emotion recognition is an essential social ability that continues to develop across adolescence, a period of critical socio-emotional changes. In the present study, we examine how signals from different sensory modalities, specifically touch and facial expressions, are integrated into a holistic understanding of another’s feelings. Adolescents (n = 30) and young adults (n = 30) were presented with dynamic faces displaying either a positive (happy) or a negative (sad) expression. Crucially, facial expressions were anticipated by a tactile stimulation, either positive or negative. Across two experiments, we use different tactile primes, both in first-person experience (experiment 1) and in the vicarious experience of touch (experiment 2). We measured accuracy and reaction times to investigate whether tactile stimuli affect facial emotional processing. In both experiments, results indicate that adolescents were more sensitive than adults to the influence of tactile primes, suggesting that sensory cues modulate adolescents’ accuracy and velocity in evaluating emotion facial expression. The present findings offer valuable insights into how tactile experiences might shape and support emotional development and interpersonal social interactions. Full article

Current non-destructive testing (NDT) methods, such as those based on wave velocity measurements, lack the sensitivity necessary to detect early-stage damage in concrete structures. Similarly, common signal processing techniques often assume linearity and stationarity among the signal data. By analyzing wave attenuation measurements using advanced signal processing techniques, mainly Hilbert–Huang transform (HHT), this work aims to enhance the early detection of damage in concrete. This study presents a novel energy-based technique that integrates complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and Hilbert spectrum analysis (HSA), to accurately capture nonlinear and nonstationary signal behaviors. Ultrasonic non-destructive testing was performed in this study on manufactured concrete specimens subjected to micro-damage characterized by internal microcracks smaller than 0.5 mm, induced through controlled freeze–thaw cycles. The recorded signals were decomposed from the time domain using CEEMDAN into frequency-ordered intrinsic mode functions (IMFs). A multi-criteria selection strategy, including damage index evaluation, was employed to identify the most effective IMFs while distinguishing true damage-induced energy loss from spurious nonlinear artifacts or noise. Localized damage was then analyzed in the frequency domain using HSA, achieving an up to 88% reduction in wave energy via Marginal Hilbert Spectrum analysis, compared to 68% using Fourier-based techniques, demonstrating a 20% improvement in sensitivity. The results indicate that the proposed technique enhances early damage detection through wave attenuation analysis and offers a superior ability to handle nonlinear, nonstationary signals. The Hilbert Spectrum provided a higher time-frequency resolution, enabling clearer identification of damage-related features. These findings highlight the potential of CEEMDAN-HSA as a practical, sensitive tool for early-stage microcrack detection in concrete. Full article

Background and Objectives: Anterior cruciate ligament (ACL) injury rates remain high and have a significant impact on female football players. This study aims to evaluate knee kinematics and lower limb muscle activity in players at risk of ACL injury compared to healthy players through three side-cutting tests. It also investigates how the amplitude of a change in direction influences stabilization parameters. Materials and Methods: A cross-sectional case–control study was conducted with 16 second division female futsal players (23.93 ± 5.16 years), divided into injured (n = 8) and healthy groups (n = 8). Injured players had a history of non-contact knee injury involving valgus collapse, without undergoing surgical intervention. Three change of direction tests, namely the Change of Direction and Acceleration Test (CODAT), Go Back (GOB) test, and Turn (TURN) test, were used for evaluation. The peak and range of knee joint angles and angular velocities across three planes, along with the average rectified and peak envelope EMG signals of the Biceps Femoris (BF), Semitendinosus (ST), Vastus Medialis (VM), and Lateral Gastrocnemius (LG), were recorded during the preparation and load phases. Group differences were analyzed using two-factor mixed-model ANOVA with pairwise comparisons. Statistical significance was set at p < 0.05. Results: Injured players demonstrated lower external tibial rotation angular velocity and a greater range of motion in tibial external rotation compared to healthy players. Additionally, the injured group showed significantly higher average rectified muscle activity in VM and LG both increased by 4% during the load phase. The CODAT and TURN tests elicited higher BF and VM muscle activity, compared to the GOB test. The TURN test also showed greater extension angular velocity in the sagittal plane. Conclusions: The results revealed differences in knee kinematics and muscle activity between players at risk of ACL injury and healthy players, influenced by the amplitude of directional changes. Players altered transverse plane mechanics and increased VM and LG activation during LOAD may reflect a dysfunctional motor pattern, while the greater sagittal plane angular velocity and VM and BF activation from the CODAT and the TURN test highlight their higher potential to replicate ACL injury mechanisms compared to the GOB test. Full article

Outdoor cleaning robots must operate reliably across diverse and unstructured surfaces, yet many existing systems lack the adaptability to handle terrain variability. This paper proposes a terrain-aware cleaning framework that dynamically adjusts robot behavior based on real-time surface classification and slope estimation. A 128-channel LiDAR sensor captures signal intensity images, which are processed by a ResNet-18 convolutional neural network to classify floor types as wood, smooth, or rough. Simultaneously, pitch angles from an onboard IMU detect terrain inclination. These inputs are transformed into fuzzy sets and evaluated using a Mamdani-type fuzzy inference system. The controller adjusts brush height, brush speed, and robot velocity through 81 rules derived from 48 structured cleaning experiments across varying terrain and slopes. Validation was conducted in low-light (night-time) conditions, leveraging LiDAR’s lighting-invariant capabilities. Field trials confirm that the robot responds effectively to environmental conditions, such as reducing speed on slopes or increasing brush pressure on rough surfaces. The integration of deep learning and fuzzy control enables safe, energy-efficient, and adaptive cleaning in complex outdoor environments. This work demonstrates the feasibility and real-world applicability for combining perception and inference-based control in terrain-adaptive robotic systems. Full article

Background/Objectives: This study focuses on the motion planning and control of an active ankle–foot orthosis (AFO) that leverages biomechanical insights to mitigate footdrop, a deficit that prevents safe toe clearance during walking. Methods: To adapt the motion of the device to the user’s walking speed, a geometric model was used, together with real-time measurement of the user’s gait cycle. A geometric speed-adaptive model also scales a trapezoidal ankle-velocity profile in real time using the detected gait cycle. The algorithm was tested at three different walking speeds, with a prototype of the AFO worn by a test subject. Results: At walking speeds of 0.44 and 0.61 m/s, reduced tibialis anterior (TA) muscle activity was confirmed by electromyography (EMG) signal measurement during the stance phase of assisted gait. When the AFO was in assistance mode after toe-off (initial and mid-swing phase), it provided an average of 48% of the estimated required power to make up for the deliberate inactivity of the TA muscle. Conclusions: Kinematic analysis of the motion capture data showed that sufficient foot clearance was achieved at all three speeds of the test. No adverse effects or discomfort were reported during the experiment. Future studies should examine the device in populations with footdrop and include a comprehensive evaluation of safety. Full article

This study researches and discusses the impact of different manufacturing-induced effects of additive manufacturing (AM), such as anisotropy on sound propagation and attenuation, on the production of test specimens for ultrasonic testing (UT). It was shown that a linear, alternating hatching pattern led to strong anisotropy in sound velocity and attenuation, with a deviation in sound velocity and gain of over 840 m/s and 9 dB, depending on the measuring direction. Furthermore, it was demonstrated that the build direction exhibits distinct acoustic properties. The influence of surface roughness on both the reflector and coupling surfaces was analyzed. It was demonstrated that post-processing of the reflector surface is not necessary, as varying roughness levels did not significantly change the signal amplitude. However, for high frequencies, pre-treatment of the coupling surface can improve sound transmission up to 6 dB at 20 MHz. Finally, the reflection properties of flat bottom holes (FBH) in reference blocks produced by AM and electrical discharge machining (EDM) were compared. The equivalent reflector size (ERS) of the FBH, which refers to the size of an idealized defect with the same ultrasonic reflection behavior as the measured defect, was determined using the distance gain size (DGS) method—a method that uses the relationship between reflector size, scanning depth, and echo amplitude to evaluate defects. The findings suggest that printed FBHs achieve an improved match between the ERS and the actual manufactured reflector size with a deviation of less than 13%, thereby demonstrating the potential for producing standardized test blocks through additive manufacturing. Full article

This study investigates the influence of bedrock material conditions on the seismic behavior of the Niedzica earth dam in southern Poland. It examines the dam’s dynamic response to a real seismic event—the 2004 Podhale earthquake—and evaluates how different foundation conditions affect structural performance under spatially varying ground motions. A spatially varying ground motion excitation model was developed, incorporating both wave coherence loss and wave passage effects. Seismic data was collected from three monitoring stations: two located in fractured bedrock beneath the dam and one installed in the surrounding intact Carpathian flysch. From these recordings, two key spatiotemporal parameters were experimentally determined: the seismic wave velocity and the spatial scale parameter (α), which reflects the degree of signal incoherence. For the fractured bedrock beneath the dam, the wave velocity was 2800 m/s and α = 0.43; for the undisturbed flysch, it was 3540 m/s and α = 0.82. A detailed 3D finite element model of the dam was developed in ABAQUS and subjected to time history analyses under three excitation scenarios: (1) uniform input, (2) non-uniform input with coherence loss, and (3) non-uniform input including both coherence loss and wave passage effects. The results show that the dam’s seismic response is highly sensitive to the choice of spatiotemporal parameters. Using generalized values from the flysch reduced predicted shear stresses by up to 16% compared to uniform excitation. However, when the precise parameters for the fractured bedrock were applied, the reductions increased to as much as 24%. This change in response is attributed to the higher incoherence of seismic waves in fractured material, which causes greater desynchronization of ground motion across the dam’s foundation. Even small-scale geological differences—when properly reflected in the spatiotemporal model—can significantly influence seismic safety evaluations of large-scale structures. Ultimately, shifting from regional to site-specific parameters enables a more realistic assessment of dynamic stress distribution. Full article

With the advancement of 5G-Advanced Non-Terrestrial Network (5G-A NTN) mobile communication technologies, direct satellite connectivity for mobile devices has been increasingly adopted. In the highly dynamic environment of low-Earth-orbit (LEO) satellite communications, the synchronization of satellite–ground signals remains a critical challenge. In this study, a Doppler frequency-shift estimation method applicable to high-mobility LEO scenarios is proposed, without reliance on the Global Navigation Satellite System (GNSS). Rapid access to satellite systems by mobile devices is enabled without the need for additional time–frequency synchronization infrastructure. The generation mechanism of satellite–ground Doppler frequency shifts is analyzed, and a relationship between satellite velocity and beam-pointing direction is established. Based on this relationship, a Doppler frequency-shift estimation method, referred to as DFS-BP (Doppler frequency-shift estimation using beam pointing), is developed. The effects of Earth’s latitude and satellite orbital inclination are systematically investigated and optimized. Through simulation, the estimation performance under varying minimum satellite elevation angles and terminal geographic locations is evaluated. The algorithm may provide a novel solution for Doppler frequency-shift compensation in Non-Terrestrial Networks (NTNs). Full article

This study presents the experimental results of an energy harvesting system comprising a cylindrical bluff body coupled with a cantilever beam. A piezoelectric sensor was installed on the beam to generate electrical voltage during the object’s vibrations at the beam’s free end. The research aimed to evaluate the impact of the bluff body’s mass and diameter on the efficiency of the piezoelectric energy harvesting system. Vibrations of the test object were induced by airflow within a chamber of a closed-loop wind tunnel. Five different bluff body masses were analyzed for each of three cylindrical diameters across an airflow velocity range of 1 m/s to 10 m/s. These experiments allowed for the recording of a series of voltage signals over time. The signals were then subjected to Fast Fourier Transform (FFT) analysis. Subsequently, the relationship between vibration frequency and airflow velocity was examined. The peak-to-peak voltage value was also analyzed to provide an overall assessment of the energy harvesting efficiency of the system under investigation. Finally, the 0–1 test for chaos was additionally employed as a diagnostic tool to assess the complexity of system dynamics based on time series data. This test allowed for distinguishing between oscillatory behavior and cases where the system became trapped in a potential well, revealing key transitions in dynamic regimes. Full article

This study focuses on determining the high-frequency decay parameter kappa (k) and its site component (k₀) for sixteen accelerometric stations installed in suitable locations in North Macedonia. Kappa characterizes the attenuation of ground motion at high frequencies, describing the decrease in the acceleration amplitude spectrum. It is defined using a regression line in log-linear space, starting from the point where the S-wave amplitude spectrum begins to decay rapidly. The site characteristics of the stations are determined through geophysical and borehole investigations, as well as HVSR mean curves derived from earthquake data. The strong-motion data used in this analysis originate from earthquake events with a moment magnitude greater than 3 (M_W > 3), an epicentral distance less than 120 km (R_epi < 120 km), and a focal depth lower than 30 km (h < 30 km). The records undergo visual inspection and filtering, with those having a signal-to-noise ratio (SNR) below 3 excluded from further analysis. The study examines the correlation between kappa values and various parameters, including magnitude, epicentral distance, average shear-wave velocity in the top 30 m depth (V_S30), and fundamental site frequency (f₀). The importance of this study is the application in the future evaluation/update of seismic hazard analysis of the region. Full article

In order to improve the injection molding quality of the car lamp shell, orthogonal test, signal-to-noise ratio, gray correlation analysis, and CRITIC weight method were used to analyze the influence of mold temperature, melt temperature, injection time, velocity to pressure control, pressure holding pressure and pressure holding time on the shrinkage index and the total deformation of warpage, and fully consider the difference and correlation between the evaluation parameters. The multi-objective optimization is transformed into single-objective optimization, and the optimal parameter set is obtained. The experimental results show that, compared with the initial analysis results, the indentation index of the headlight shell is reduced by 33.95%, the total warpage deformation is reduced by 13.99%, and the forming quality of the headlight shell is improved. The research results provide a theoretical reference value for multi-objective optimization of plastic injection molding process parameters. Full article