Search Results (1,242)

We present the results of the analysis of nine polarization and micro-variability observations of BL Lacertae using a turbulent cell model. We perform a similar analysis of a simulated TEMZ light curve generated with the Turbulent Extreme Multi-Zone (TEMZ) model and compare the results. Observations of short-timescale variability of flux and polarization are important to understanding the physical conditions in the blazar jet. We find that the micro-variations exhibited by the BL Lac data analyzed here are well fit by a turbulent cell model consisting of multiple pulses, with an average correlation coefficient of r~0.94. We compare these results with a similar analysis of light and polarization curves from a TEMZ simulation, which employs many more cells with physical properties related across cells following the Kolmogorov spectrum. We find that groups of turbulent cells identified in the TEMZ model by our analysis are similar to the input cell structure of the simulation. We find that the results from the actual BL Lac light curve and polarization curves match very well with the results from analyzing the TEMZ simulated light curves. We find no apparent trend or direct correlation between the cells determined from the flux curves and polarization degree, or polarization angle in either the BL Lac or the TEMZ data sets. Full article

The integration of outdoor camera images with three-dimensional (3D) geographic information on the observed scene is of interest for many video acquisition applications. To solve this data fusion problem, camera images have to be matched with the 3D geometry provided by a geographic information system (GIS). Considering a camera with a known geographical position, this paper proposes the use of a dense local azimuth–elevation map (LAEM) derived from a gridded digital elevation model (DEM) to represent the data and thus facilitate the matching of GIS and image data. To each regularly sampled azimuth and elevation angle pair, this map assigns the geographic point derived from the DEM viewed in this direction. The problem of computing the LAEM from the DEM is closely related to that of surface rendering, for which solutions exist in computer graphics. However, rendering software cannot be used directly in this case, since their view directions are constrained by the pinhole camera model and the apparent colour, rather than the position of the viewed point, is assigned to the viewing direction. Therefore, this paper also proposes a specific algorithm for the computation of the LAEM from the DEM. A MATLAB^® implementation of the algorithm is also provided, which is tailored to process the DEM dataset swissALTI3D from the Swiss Federal Office of Topography swisstopo. Full article

The wheels of lunar rovers are prone to bouncing during travel in the low gravity and rugged terrain conditions of the lunar surface, and poor matching of wheel alignment parameters can easily lead to tire wear in such conditions. Focusing on the double-wishbone suspension of lunar rovers, this study presents a wheel alignment parameter optimization method for tire wear reduction. First, a tire brush model is established, and it is determined that the toe angle and camber angle are the main factors affecting the tire wear work. And as the camber angle and toe angle increase, the tire wear work becomes greater. Then, a multi-body dynamic model of the double-wishbone independent suspension in a low-gravity environment is established. Taking the minimum tire wear as the optimization objective, the optimal solution set of alignment parameters such as the tire camber angle and toe angle obtained and the optimal hardpoint coordinate positions are determined. The variation range of the toe angle is optimized from [−0.55°, 1.58°] to [−0.37°, 1.32°]. After optimization, the variation in the toe angle is reduced by 20.4%, the change rate of the camber angle becomes smoother, and the comprehensive wear work of the tire is reduced by 17.47%. The research results provide theoretical guidance for the optimization of wheel alignment parameters of the double-wishbone suspension of the lunar rover. Full article

This study aims to address the acoustic resonance control problem of a three-dimensional nose landing gear (NLG) cavity. We propose a refined numerical approach based on an eigenvalue solver for the Helmholtz equation. A high-order finite element method (FEM) combined with perfectly matched layer (PML) boundary conditions was employed to accurately capture complex eigenmodes. The radiation damping characteristics of the system were then quantitatively characterized using the quality factor (Q-factor) and resonance frequency. Results indicate that the Helmholtz-type (0,0,0) mode dominates the cavity’s resonance response, with its frequency coinciding with the shear layer-driven Rossiter mode. This study reveals a strong coupling mechanism with the shear-layer-driven Rossiter mode at Mach 0.57, confirming that this interaction is the primary driver of cavity aeroacoustic tonal noise. Taking radiation damping as the core design parameter, a systematic sensitivity analysis was conducted on geometric modifications: aft door length, front door angle, cavity volume, and the introduction of a longitudinal gap. Key findings: shortening the aft door reduces the resonance peak by 8.5 dB; introducing a longitudinal gap with a 10% width reduces the Q-factor by approximately 50%; a combined control strategy (2.5% gap width and 6% cavity volume reduction) achieves 4.9 dB of noise attenuation. Finally, this study establishes a validated acoustic-damping control framework, providing quantitative design criteria and technical guidance for aeroacoustic noise control of NLG cavities. Full article

To address the challenges posed by strong environmental disturbance during field observations of dust dispersion at highway construction sites, this study investigates the transport and diffusion patterns of construction dust (PM₁₀) by integrating numerical simulation with on-site measurements. Based on particle sampling parameters and wind conditions obtained from the target project, a construction PM₁₀ dispersion model was established using computational fluid dynamics (CFD). The wind direction that best matched the measured field data was selected as the reference condition, and the dispersion behavior of construction dust was simulated under different wind speeds and particle mass flow rates. The results indicate that larger wind-direction angles facilitate vertical dispersion of particulate matter, and higher wind speeds enhance long-distance transport while reducing near-source concentrations. Dust-suppression performance increases with barrier height, and under a low wind speed of 2 m·s⁻¹, a 3 m barrier achieves a PM₁₀ suppression efficiency of 73.6%. These findings provide quantitative evidence and technical support for PM₁₀ control in highway construction environments. Full article

Existing theories leave gaps in explaining the mechanism of concrete cracking. To explain the mechanism of concrete cracking, after considering various methods, this paper finally selects the Particle Flow Code (PFC) based on the discrete element method (DEM) for the research. We selected concrete with single cracks and double cracks as the research object, and constructed a mesoscale model in PFC based on the parameters of the concrete. The model was verified by uniaxial compression tests and published experimental data, with simulated results matching experimental data within an acceptable error range. Simulate the situation of concrete cracking, plot the data into images, and analyze the patterns of the development of concrete cracks. During this process, we set the angle of crack formation and the number of cracks as variables. By analyzing the load–displacement curves and the crack evolution curves, we found that the mode of crack propagation changed from a linear extension to a branched expansion. It is also worth noting that when the inclination angle is 90 degrees, the bearing capacity of the specimen is the best, with its peak strength over 40% higher than that at 0° for single-fissure specimens and over 35% higher for double-fissure specimens, and the initial stiffness also reaches the maximum at this angle. Furthermore, throughout the entire testing process, the PFC based on the discrete element method was able to accurately capture the development process of concrete cracks. This study innovatively quantifies the evolution of tensile and shear cracks with inclination angle, clarifies the nonlinear correlation between peak strength and crack angle, and reveals the unique cracking behavior induced by double fissures, which is insufficiently studied in existing continuum simulations. The above findings not only enhance our understanding of the mechanism of concrete cracks, but also provide a reference for improving the strength of concrete. This study is limited to 2D uniaxial compression simulation, with the concrete microstructure idealized in the numerical model. Full article

The paper presents a method for generating a pseudo-panchromatic (PPAN) orthophotomosaic that is spectrally compatible with the multispectral (MS) orthophotomosaic, and it targets the fusion of unmanned aircraft system (UAS) RGB–MS orthophotomosaics when no true panchromatic band is available. In typical UAS imaging systems, RGB and multispectral sensors operate independently and exhibit different spectral responses and spatial resolutions, making the construction of a spectrally compatible substitution intensity a critical challenge for component substitution fusion. The conventional RGB-derived PPAN preserves spatial detail but is constrained by RGB–MS spectral incompatibility, expressed as reduced corresponding-band similarity. The proposed hybrid intensity (PPAN_E) increases the mean corresponding-band correlation from 0.842 (PPAN_A) to 0.928 (PPAN_E) and reduces the across-site mean SAM from 5.782° to 4.264°, while maintaining spatial sharpness comparable to the RGB-derived intensity. It is proposed that the PPAN_E orthophotomosaic be produced as a hybrid intensity (single band) image. Specifically, a multispectral-visible-derived intensity is resampled onto the RGB grid and statistically integrated with RGB spatial detail, followed by mild high-frequency enhancement to produce the final PPAN_E orthophotomosaic. Principal Component Analysis (PCA) fusion is applied to seven archaeological sites in Northern Greece. Spectral quality is evaluated on the MS grid using band-wise (corresponding-band) correlation and the Spectral Angle Mapper (SAM), while the spatial sharpness of the fused NIR orthophotomosaic is assessed using Tenengrad and Laplacian variance. The PPAN_E orthophotomosaic consistently increases correlations relative to PPAN_A (especially in Red Edge/NIR) and reduces the mean site-mean SAM. PPAN_C yields the lowest SAM but also the lowest spatial sharpness/clarity, whereas PPAN_E maintains spatial sharpness/clarity comparable to PPAN_A, supporting a balance between spectral consistency and spatial detail, as also confirmed through comparative evaluation against established component substitution fusion methods. The approach is reproducible and avoids full histogram matching; instead, it relies on explicitly defined linear standardization steps (mean–std normalization) and controlled spatial sharpening, and performs consistently across different scenes. Full article

For decades, zirconia- and ceramic-based materials have dominated dental crown fabrication due to their durability and aesthetic appeal. However, a fundamental shift is occurring as polymeric alternatives emerge with notable advantages: better adhesive bonding, versatile aesthetics, lower costs, and a lighter weight. The advances in polymer chemistry and additive manufacturing have significantly impacted prosthodontics, allowing the rapid creation of highly customized, patient-specific restorations with a precision previously impossible (achieved through advanced Computer-Aided Design software and standardized 3D-printing equipment) with traditional methods. This review provides a detailed analysis of 3D-printed polymeric dental crowns from various angles. It explores the materials science behind different polymers, compares manufacturing methods, and evaluates the mechanical performance and biocompatibility. Despite the progress, polymeric materials still fall short of matching the mechanical properties of advanced ceramics, especially in compressive strength and wear resistance. Moreover, there is limited long-term clinical data over five to ten years. The lack of standardized testing protocols complicates cross-study comparisons, and the regulatory pathways for patient-specific 3D-printed devices are still developing, creating uncertainty for manufacturers and clinicians. The future prospective looks promising in many ways such as innovations like four-dimensional printing, where materials respond dynamically to environmental stimuli, which could enable crowns that adapt to changing oral conditions. Nanocomposites with functionalized nanoparticles might enhance mechanical properties while maintaining printability. AI-driven design optimization could automate and improve the crown morphology, occlusal contacts, and fit. Incorporating bioactive materials could turn crowns into active therapeutic devices that promote remineralization and combat bacterial colonization. This review summarizes the current knowledge, highlights the key gaps, and suggests steps toward establishing polymeric 3D-printed crowns as viable long-term alternatives capable of competing with or surpassing traditional ceramic options. Full article

Resistance training machines are designed to provide either constant or variable resistance, with the latter intended to generate a machine resistive torque (MRT) that mirrors the natural fluctuations in human torque capability (HTC) across joint angles. Yet, achieving a precise match between MRT and HTC remains a persistent challenge. This study aimed to validate a novel variable-cam resistance system, the Variable Moment Arm Cam^® (VMAC^®), by examining torque output and muscle activation during leg extension across the full range of motion (100–0°), using repeated testing and direct comparison with an isokinetic dynamometer. Twenty-two young men completed four randomized sessions, two on the variable-cam system and two on the dynamometer, each separated by 72–96 h. Torque and muscle activity were recorded during six isometric contractions at 100°, 80°, 60°, 40°, 20°, and 0°. The variable-cam system produced torque and activation patterns broadly comparable to the dynamometer, with acceptable agreement across angles. Validity was highest at 60°, aligning with the region of peak torque, whereas greater variability emerged at the extremes of flexion and extension. Muscle activation profiles were similar between devices, though more variable than torque, underscoring the inherent complexity of neuromuscular assessment. Full article

The rapid development of the oil and gas industry has led to increasingly severe challenges for buried pipelines when crossing complex geological environments. Especially in fault zones induced by seismic action, the pipe–soil interaction mechanism and the rapid judgment of pipeline mechanical response urgently require in-depth research. This study conducted pipe–soil interaction tests on pipeline uplift under seismic-frequency loading, and for the first time, proposed a modified soil-spring method suitable for typical soft clay under seismic wave frequencies of 1–5 Hz. Through numerical simulation, the axial strain response of pipelines under normal fault movement was systematically analyzed. Considering comprehensively various variables such as fault dip angle, seismic wave frequency, internal pipeline pressure and wall thickness variation, this study extracted the maximum and minimum strain characteristics of the pipe top and pipe bottom, established a diversified intelligent prediction system for fault geological hazards, constructed the optimal machine learning model matching the type of normal fault geological hazards, and realized full-process intelligent modeling from model selection to parameter optimization. The research results can provide technical support for the seismic design and safety status prediction of pipelines under normal faulting conditions. Full article

To address the complex dynamic mechanisms and lack of static operation data in trench-digging for transverse planting of Salix psammophila sand barriers, a transverse trench-digging device was designed. Based on the discrete element method, the Hertz–Mindlin with JKR Cohesion model was used to simulate sandy soil. The Box–Behnken experiment was adopted to optimize the single auger structure with helix angle and soil-cutting angle as factors and trench depth and working torque as indices, yielding the optimal parameters of 30° soil-cutting angle and 20.37° helix angle (5.52 cm trench depth, 2.6 N·m maximum torque). The optimized auger was integrated into the device, and a further Box–Behnken experiment was conducted under a 20 cm fixed descending depth of the lifting platform. With auger rotation speed, shaft spacing and lifting speed as factors, and trench depth, soil compaction and Salix psammophila insertion depth as indices, the optimal operating parameters were determined as 257.25 r/min, 7 cm and 9 cm/s, corresponding to 6.7 cm trench depth, 33.37 kPa soil compaction and 14.87 cm insertion depth. This study clarifies the effects of auger and operation parameters on trench-digging quality, provides a basis for the design and parameter matching of dynamic continuous operation equipment, and offers a reference for the R&D of mechanized transverse planting equipment for Salix psammophila sand barriers, which is of practical value for reducing sand control costs and improving efficiency. Full article

Indoor positioning in hospitals is challenging because global navigation satellite systems signals are unavailable and existing solutions struggle with complex indoor propagation and high maintenance requirements. Fingerprinting-based methods using Wi-Fi, Bluetooth Low Energy (BLE), or magnetic field depend on extensive site surveys, while time or angle-based systems such as ultra-wide band, angle of arrival, and Wi-Fi round trip time require additional infrastructure. Recent machine learning approaches improve performance but remain limited by Pedestrian Dead Reckoning (PDR) drift and unstable spatial representations. This study proposes an AI-generated spatial pattern matching framework that integrates an AI-based PDR model with BLE Received Signal Strength Indicator (RSSI) to construct a user RSSI surface. Spatial similarity between user-generated patterns and the pre-built radio map is evaluated using Surface Correlation (SC), and a bi-directional candidate generation strategy with SC-based heading correction is employed to mitigate inertial drift. Experiments in a real hospital setting show that the proposed method achieves robust and accurate localization even in complex indoor environments where conventional fingerprinting and PDR techniques often fail. The results indicate that combining AI-driven inertial modeling with SC-based spatial pattern matching offers a practical and infrastructure-friendly solution for hospital indoor positioning. Full article

We investigate the potential of frequent repeat imagery acquired by the PlanetScope Dove small satellite constellation to overcome temporal and spatial limitations in automated surface topography mapping. While individual PlanetScope Dove stereo pairs produce low-quality Digital Surface Models (DSMs) with large height uncertainties, the high temporal frequency enables multiple DSMs to enhance accuracy through multiple-pair image matching. We present a fully automated SETSM framework by improving the quality of PlanetScope Dove DSMs based on SETSM Multi-Pair Matching Procedure (SETSM MMP). This framework enhances stereo pair quality through an optimized stereo pair selection by sequential conditional filtering and a Weighted Stereo Pair Index (WSPI). A novel inter-plane vertical coregistration, which minimizes scaling errors between single stereo pair DSMs, was developed to improve consistency and accuracy in DSM quality without reference surfaces. Applied to the cloud-obscured Pantasma crater region in Nicaragua, the optimized stereo pair selection automatically selects well-defined stereo pairs. The inter-plane vertical coregistration without existing reference surfaces achieves up to a 43% Root Mean Square Error (RMSE) reduction and 26% improvement in distribution within a 5 m vertical error. DSM quality correlated strongly with tile size, stereo pair convergence angle, asymmetric angle and terrain-dependent scale variability. The proposed framework provides fully automatic, high quality PlanetScope Dove DSMs without Ground Control Points (GCPs). Full article

Accurate target localization via matching real-time UAV images with reference satellite imagery is essential for autonomous environmental perception. Nonetheless, operational constraints and weather conditions often necessitate oblique photography. This large-tilt mode causes significant perspective and radiometric distortions, resulting in a substantial domain gap between UAV and vertical satellite imagery. The scarcity of datasets featuring extreme viewpoint shifts and fine-grained ground-truth labels hinders the validation of image matching algorithms in multi-tilt-angle environments. To address this issue, we introduce the multiple-tilt-angle dataset (MTA-Dataset), containing 1892 UAV images with tilt angles spanning $\left[0°,\right.\left.90°\right)$ and flight altitudes up to 300 m, supported by high-precision five-point manual annotations. Based on this benchmark, we evaluate state-of-the-art matching algorithms and propose a spatial-resolution-based cropping strategy. Experimental results demonstrate that, as the UAV tilt angle increases within the range of $\left[0°,\right.\left.90°\right)$, although the expanding field of view provides richer contextual information, the localization errors of all methods increase significantly and matching precision drops sharply due to severe geometric distortions in far-field regions and interference from redundant background information, with performance deteriorating most drastically in the $\left[50°,\right.\left.90°\right)$ range. With the integration of our strategy, the average matching localization errors of SuperPoint + SuperGlue baseline for UAV images within the tilt-angle ranges of $\left[50°,\right.\left.60°\right)$, $\left[60°,\right.\left.70°\right)$, $\left[70°,\right.\left.80°\right)$, and $\left[80°,\right.\left.90°\right)$ are reduced by 33.49 m, 37.86 m, 98.3 m, and 109.95 m, respectively. Our study provides a more comprehensive evaluation framework for robust UAV–satellite image matching algorithms in multi-tilt-angle scenarios. Full article

Hyperspectral imaging in the long-wave infrared (LWIR) range enables identification of chemical compositions and material properties, but reconstructing 3D models from gimballed pushbroom sensors remains challenging because their unique acquisition geometry is incompatible with conventional photogrammetric software designed for frame cameras. This study presents a workflow for creating explorable 3D models from multi-angle LWIR hyperspectral imagery by co-registering hyperspectral line-scan data with simultaneously acquired RGB frame camera imagery using deep learning-based image matching. The co-registered images are processed in commercial photogrammetric software (Agisoft Metashape), and a texture-to-image mapping algorithm preserves correspondences between 3D model coordinates and original hyperspectral pixels across multiple viewing angles. Quantitative evaluation against reference data demonstrates that co-registration reduces geometric error approaching the accuracy of models built from high-resolution RGB imagery. The resulting models enable the retrieval of 8–50 spectral signatures per surface point, captured from different viewing geometries. This approach facilitates interactive exploration of angular variations in thermal infrared spectra, supporting material identification for non-Lambertian surfaces where single-angle observations may be insufficient for reliable classification. Full article