Search Results (955)

Background and Objectives: To evaluate two-year functional, anatomical, and patient-reported outcomes after bilateral implantation of a diffractive implantable phakic contact lens (IPCL) for presbyopia correction in myopic patients within a high–solar-radiation Atlantic island environment. Methods: This retrospective observational study included 11 presbyopic myopic patients aged 40–50 years (22 eyes) who underwent bilateral diffractive IPCL implantation and completed a 2-year follow-up. Monocular defocus curves were recorded from +3.0 to −5.0 D and converted to logMAR. Functional visual range and area under the defocus curve (AUC) were calculated. Anatomical stability was assessed by central vault, pupil diameter, and crystalline lens rise measurements. Safety evaluation included slit-lamp examination for crystalline lens transparency and corneal integrity. Patient-reported outcomes were measured using the Quality of Vision (QoV) and Catquest-9SF questionnaires. Environmental parameters during implantation and follow-up were characterized using regional meteorological data. Results: Mean visual acuity remained ≤0.14 logMAR up to −2.5 D of defocus, with functional vision (≤0.2 logMAR) extending to approximately −3.0 D in about half of the eyes. Median vault at 2 years was 546 µm (IQR 361.5–667.3 µm). No cases of clinically significant cataract or corneal compromise were observed. QoV scores were low (1.41 ± 0.43) and Catquest-9SF scores high (3.70 ± 0.18), with no strong correlations between subjective and anatomical metrics. Visual performance remained stable within a consistent high-solar-radiation and atmospheric light-scattering environment. Conclusions: Diffractive IPCL implantation was associated with stable anatomical positioning, sustained functional visual performance across distances, and favorable patient-reported outcomes at 2 years. Within a consistent real-world environmental context, these findings provide a descriptive framework for understanding diffractive IPCL performance, while larger prospective studies are warranted. Full article

Cone-beam computed tomography (CBCT) is widely used in image-guided radiotherapy because of its low radiation dose and on-board acquisition capability. However, CBCT images often suffer from scatter artifacts, increased noise, reduced soft-tissue contrast, and inaccurate Hounsfield Unit (HU) values, which limit their direct use for accurate dose calculation and quantitative analysis. To address this limitation, we propose a CBCT-to-CT synthesis framework based on 2.5D context encoding (concatenating five adjacent slices along the channel dimension) and latent-space variational diffusion. The proposed method combines a Vector Quantized Variational Autoencoder (VQ-VAE) and a U-shaped Vision Transformer (U-ViT)-based latent-space Variational Diffusion Model (VDM) to translate CBCT images into synthetic CT (sCT) images in a compressed latent space. To incorporate inter-slice anatomical context while preserving the computational efficiency of 2D processing, five adjacent CBCT slices are concatenated along the channel dimension and used as input. We evaluated the proposed method on the SynthRAD2025 paired CBCT-CT dataset covering head-and-neck, thoracic, and abdominal regions. Under the provided benchmark setting, quantitative evaluation on the validation set showed that the proposed 2.5D model improved peak signal-to-noise ratio (PSNR) from 25.39 dB to 27.44 dB (averaged across regions), structural similarity index measure (SSIM) from 0.813 to 0.846, reduced mean squared error (MSE) from 0.00313 to 0.00200, and lowered Fréchet inception distance (FID) from 1009.33 to 869.53 compared with the 2D baseline. Qualitative results also showed improved anatomical consistency and reduced artifact-related distortions. These findings suggest that neighboring-slice context can enhance HU fidelity and overall image quality in a computationally practical synthesis framework, supporting the usefulness of efficient AI-based cross-modality reconstruction for radiotherapy-related imaging workflows. Full article

The functional performance and structural integrity of natural rock materials under fluctuating environmental stressors are pivotal for their advanced applications. As a non-ionizing and radiation-free technology, terahertz (THz) spectroscopy offers a safe and promising alternative for non-destructive testing (NDT), uniquely capable of being deployed in open and unshielded environments. However, limited penetration depth, exacerbated by both the dense geological matrix and the extreme sensitivity of THz waves to moisture states, has long hindered its widespread application in rock characterization. This study establishes a quantitative Terahertz Time-Domain Spectroscopy (THz-TDS) framework to characterize four lithologies under drying–wetting cycles. Exponential signal attenuation across thicknesses was quantified based on the Beer–Lambert law, with attenuation coefficients ranging from 0.15 to 0.74 per millimeter. Planar transmission imaging successfully visualizes lithologic and moisture-dependent heterogeneity: limestone exhibits a dense, homogeneous structure with stable amplitude distribution; sandstone and purple sandstone show parallel statistical trends, reflecting uniform pore networks; and granite demonstrates the most pronounced imaging contrast under varying moisture states, driven by complex grain-boundary scattering. The findings reveal that THz transmission is dictated by the synergistic effects of mineral compositions and pore structures: scattering at grain boundaries and fractures leads to significant energy dissipation, whereas clay-rich lithologies exhibit the highest sensitivity to moisture variations due to water adsorption and interfacial polarization effects. As an exploration of THz technology in the non-destructive evaluation of rock materials, these findings establish an analytical framework for the quantitative assessment of microstructure evolution. Full article

Considerable progress has been made in predicting nominal NVH behavior in electric drivetrains, but the acoustic scatter observed across manufactured units remains insufficiently understood. In practice, nominally identical drive units may still exhibit noticeably different tonal behavior because small deviations in gears, shafts, bearings, fits, centering features, or assembly phase modify the excitation, transfer, and radiation mechanisms of the system. This review examines how manufacturing and assembly variability influences NVH performance in electric drive units and e-axles, with particular focus on the rotor–shaft–gear–bearing–housing system. Unlike broader EV NVH reviews, the present work focuses specifically on variability-induced acoustic scatter and its propagation along the drivetrain NVH generation and transmission path. To support transparency and consistency, the literature search and selection process followed a structured, PRISMA-inspired approach across Scopus, Web of Science, Google Scholar, and SAE Mobilus for the 2015–2026 period. From 387 identified records, 50 studies were retained after duplicate removal, screening, and full-text assessment. The selected literature was synthesized into eight thematic categories: imbalance; run-out and eccentricity; bearing clearance and preload; spline and pilot centering; thermal effects; phase indexing; transmission error and sidebands; and end-of-line NVH diagnostics. The reviewed literature shows that manufacturing- and assembly-induced deviations can significantly alter transmission error, sideband structure, shaft-order content, and final tonal response, even when individual components remain within nominal tolerance limits. Beyond synthesizing the evidence base, the review organizes existing modeling and diagnostic practices into a structured framework for variability-aware NVH assessment, based on explicit deviation parameterization, hierarchical model fidelity, intermediate excitation metrics, thermal-state awareness, and closer integration with production and measurement data. Overall, the findings support a shift from nominal NVH assessment toward robustness-oriented, production-representative interpretation and future prediction of acoustic scatter in electric drivetrains. Full article

Millimeter-wave radar imaging plays an increasingly important role in autonomous driving road perception due to its robustness under adverse weather conditions. However, radar images are inherently contaminated by multiplicative speckle noise, which severely degrades structural continuity, weakens target boundaries, and limits the perception of road scenes and surrounding objects. To address this problem, this paper proposes a structural-prior deep learning network for millimeter-wave radar image enhancement. The proposed framework first introduces an adaptive Otsu-based masking strategy to extract salient scattering structures and generate a coarse image structural prior for subsequent restoration. Guided by this prior, the network performs progressive feature enhancement through a continuous attention mechanism that integrates residual channel attention, context-aware feature extraction, and convolutional block attention, thereby enabling effective multi-scale representation learning while suppressing signal-dependent speckle interference. In addition, a composite loss function is designed by combining logarithmic denoising gain, total variation regularization, and a $\beta$-index edge-preservation term to jointly improve noise suppression, spatial smoothness, and structural fidelity. The proposed method is evaluated on the synthetic UC Merced dataset under different noise intensities and via cross-domain inference on the real-world RADIATE millimeter-wave radar dataset for autonomous driving scenarios. Experimental results demonstrate that the proposed network consistently outperforms conventional filtering methods and representative deep learning baselines in terms of PSNR, SSIM, $\beta$-index, and ENL while providing a superior preservation of road structures, target contours, and scene geometry. Ablation studies further confirm the effectiveness of the structural-prior guidance and continuous attention design. Furthermore, the network achieves a rapid inference latency of 12.35 milliseconds. These results indicate that the proposed method provides an effective and robust solution for millimeter-wave radar image enhancement and offers practical value for downstream road-scene perception in autonomous driving environments. Full article

The long-term exposure of asphalt pavement to ultraviolet radiation causes significant performance degradation and reduces its service life. To enhance the UV resistance of asphalt, nanocomposite modifiers have been incorporated through mechanical blending. However, their effectiveness has been largely limited by poor component uniformity. To address this issue, UV-resistant antioxidant nano-TiO₂ was employed to modify the UV-shielding of layered porous carbon (PC), resulting in the synthesis of nano-TiO₂ intercalated PC (TiO₂/PC). The PC nanosheet was modified by TiO₂ nanoparticles via in situ growth, significantly improving the dispersion homogeneity of TiO₂. Comprehensive characterization (SEM/EDS/FT-IR/XPS) confirmed the successful synthesis of TiO₂/PC with well-defined interfacial bonding. Compared to control samples (PC, TiO₂, and TiO₂ + PC), the asphalt modified by TiO₂/PC-2 composite demonstrated superior UV aging resistance, lower physical aging indices and reduced rheological aging parameters. Moreover, TiO₂/PC modifier prominently suppressed the formation of oxidative groups (C=O/S=O), improved the colloidal stability, and delayed the sol–gel transition of the modified asphalt. The synergistic UV shielding mechanism was attributed to the enhanced UV absorption of TiO₂, multi-reflection and scattering within the PC matrix, and the radical scavenging capabilities of both components. These results provide new design insights for developing anti-UV aging modifiers for asphalt pavements. Full article

(1) Background: Currently, there is a problem of prompt determination of fat and protein content in the milk–air mixture of milking machines. (2) Methods: A design of a sensor prototype is proposed, combining measurements of light scattering (scatterometry) and fluorescence (fluorometry) to determine the component composition of the milk–air mixture formed during milking. (3) Results: An optical and electronic circuit of a flow sensor has been developed, using four sources of optical radiation: blue, green and red semiconductor lasers (light scattering in milk) and a UV LED (milk fluorescence), as well as an axial photodiode array for recording the light scattering indicatrix and the fluorescence intensity of the milk–air mixture. The use of three laser sources in the scatterometric circuit allows for the determination of the fat content in milk with an error of 0.05%, which is better than all currently known analogs. The developed sensor enables the detection of counterfeit milk containing palm oil instead of milk fat. It operates reliably in a temperature range of 5–35 °C and at milk flow rates of up to 100 mL/sec. (4) Conclusions: The sensor is capable of transmitting real-time data on the fat and protein content of milk to an RS-232 serial port, enabling integration into milking robots and automated milking systems. Full article

Radiation of X-ray pulsars is powered by accretion on the neutron star surface from a binary companion under the influence of a strong magnetic field. We study the beaming of this radiation in the case of subcritical X-ray pulsars, where it is formed in the accretion channel close to the neutron star surface. We solve equations of the hydrodynamics and radiative transfer of two coupled polarization modes in the accretion channel numerically, taking into account resonant Compton scattering and vacuum polarization. The beaming patterns are obtained for different accretion rates, photon energies, and polarizations, as well as for different models of the neutron star surface radiation. The calculated beaming patterns are converted into light curves for both the intensity and polarization, taking into account the effects of General Relativity. These beaming patterns and light curves are found to be strongly affected by the resonant Compton scattering for photon energies comparable with the electron cyclotron energy. In particular, the angular redistribution of radiation near the cyclotron resonance may reduce the light-curve modulation amplitude, which is consistent with observational indications of a suppressed pulsed fraction at these energies. Full article

We explore the interaction of a plane electromagnetic wave with a topological insulator (TI) cylinder that is coated with homogeneous magnetized ferrite. TIs display exotic electromagnetic responses due to topological magnetoelectric (TME) phenomena. An analytic theory for the electromagnetic scattering from a TI scatterer is developed. The analytical expressions of the polarized electromagnetic fields for the transverse magnetic (TM) case are formulated. The so-called unknown scattering coefficients are derived by implementing the boundary conditions (BCs) on the surface of a TI. The scattering characteristics of plane waves by a TI scatterer are numerically simulated and discussed. The numerical results demonstrate that the scattering characteristics are strongly influenced by the external magnetic field, axion angle, thickness of coating layer, and incident operating wave frequency. This work could provide valuable theoretical insights into the scattering phenomena of optical waves and find promising applications in optical manipulation, particle radiation force and torque, optical diagnosis, metamaterial structures, and wave optics in random media. Full article

Atmospheric aerosols strongly regulate surface solar irradiance in tropical coastal environments through scattering and absorption. This study examines aerosol–irradiance interactions over Penang, Malaysia, using Aerosol Robotic Network (AERONET) observations of aerosol optical depth (AOD), single scattering albedo (SSA), and extinction Ångström exponent (AE); NASA’s Prediction of Worldwide Energy Resource (POWER) irradiance data; and Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) reanalysis for aerosol compositional context. Bottom-of-atmosphere radiative forcing efficiency (BOA RFE) was quantified for global, direct and diffuse irradiance (GHI, DNI and DHI) under clear- and all-sky conditions during 2014–2018. Results show persistent aerosol-induced attenuation of surface radiation, with GHI and DNI RFE predominantly negative, while DHI RFE remains consistently positive, indicating redistribution of solar energy from direct to diffuse components. Time resolved analysis reveals daily GHI RFE typically ranging from approximately −0.5 to −3.5 W m⁻² per unit AOD, with episodic excursions below −4 W m⁻² per AOD during high-aerosol events, whereas DNI RFE frequently reaches values below −0.8 W m⁻² per AOD, confirming its greater sensitivity to aerosol extinction. In contrast, DHI RFE commonly exceeds +5 W m⁻² per AOD and intermittently surpasses +10 W m⁻² per AOD, reflecting enhanced scattering and multiple-scattering effects. AOD-stratified analysis demonstrates a nonlinear weakening of forcing efficiency with increasing aerosol burden, with mean GHI RFE decreasing from approximately −1.6 to −0.4 W m⁻² per AOD between low- and high-AOD regimes, accompanied by corresponding reductions in DNI (−0.35 to −0.1 W m⁻² per AOD) and DHI (+3.3 to +0.8 W m⁻² per AOD). Overall, aerosol loading is identified as the dominant control on BOA radiative forcing efficiency in this tropical coastal environment, while SSA and AE act as secondary modulators. Full article

Due to the widespread use of microwave electromagnetic radiation, this study examines the microwave electromagnetic properties and compressive strength of composites made from inexpensive components such as Mg_0.5Zn_0.5Fe₂O₄, polystyrene, and activated carbon. Experimental samples were fabricated using thermopressing. The formation of the dielectric core/shell structure for Mg-Zn/polystyrene composites (1:1) and composites with activated carbon additives at weight concentrations of 3, 6.6, and 9.0% was determined using SEM image analysis. Microwave properties were investigated by analyzing the frequency dependences of complex permittivity and magnetic permeability in the frequency range of 100 MHz–5 GHz. As shown by the simulation and experimental measurements of scattering parameters obtained, the compost shows improved microwave absorption properties in the frequency range of 1–5 GHz. Reflection loss spectra showed peaks with values of −17.8 and −18 dB in the frequency range of 2.5–5 GHz for samples with 4.8 wt. % and 6.6 wt. % carbon loading, respectively. The absorption bandwidths of −10 dB in the range of 1.7–2.13 GHz were observed in the best samples. Studies have shown that samples containing 9.0 wt. % of carbon material with thicknesses of 6–10 mm can be considered as an electromagnetic shielding material in the microwave range 1–5 GHz. It was shown that, despite a decrease in porosity from 15.59 to 7.17%, with an increase in the concentration of carbon material in the composites, the compressive strength also decreases from 62.05 to 36.45 MPa. The developed composites are potentially suitable as microwave absorbers for civil applications. Full article

A broadband low-RCS circularly polarized (CP) antenna based on a bi-functional, single-layer polarization conversion metasurface (PCM) is proposed in this manuscript. The designed bi-functional PCM unit cell achieves a polarization conversion ratio (PCR) exceeding 90% across an ultra-wideband from 15.8 GHz to 31.2 GHz. According to the principle of phase cancellation, they are configured as a checkerboard array to reduce the monostatic RCS. A co-design strategy was employed for the design of the feeding structure. Analysis reveals that the slot has a significant impact on the subarray PCR, leading to multiple zeros that affect the RCS reduction. Notably, further analysis indicates that an appropriate feed structure can compensate for the zeros caused by the slot, achieving a balance between radiation performance and scattering performance. The array exhibits an RCS reduction exceeding 6 dB over a wide frequency band from 15.9 to 31.3 GHz and realizes a circularly polarized far-field pattern with an axial ratio (AR) below 0.5 from 16.3 to 17 GHz and a maximum gain of 10.38 dBi. Measured results of the antenna prototype match the simulations well. The proposed integrated design offers a viable solution for stealth platforms. Full article

As a rigorous and comprehensive foundation for electromagnetic information theory (EIT), we develop a general theory that elucidates the universal stochastic structure of radiated electromagnetic (EM) fields and induced currents in generic EM information transmission systems. The framework encompasses arbitrary random scatterers, input information fields, and EM mutual coupling. The system is modeled as a multiply connected, arbitrary Riemannian manifold within the language of differential geometry. Our approach exploits exact Green’s functions (GFs) on manifolds to construct a novel electromagnetic random field theory (EM-RFT). Interpreted as response functions localized on the surfaces of transceivers and scatterers, the GFs allow us to treat the internal physical details of the EM system as a black box, redirecting analytical attention toward external input–output relations in line with signal processing and communication theory. This integration of random fields (RFs), electromagnetics, and GFs yields a unified framework for deriving and characterizing the stochastic structure of arbitrary EM information transmission systems. We rigorously establish that EM random fields satisfying Maxwell’s equations can always be constructed using system GFs driven by external information fields. The theory further decouples stochastic input RFs from random fluctuations associated with the communication medium (e.g., scatterers), and introduces general correlation propagators valid for arbitrary EM links. Using the Karhunen–Loève expansion, all EM random fields are represented as sums of random variables, providing both a simulation framework for arbitrary EM RFs and a basis for evaluating mutual information between input and output spatial domains at arbitrary locations in the system. Full article

It is found that the speckle structure of the photoinduced light scattering indicatrix of the LiNbO₃:Y³⁺(0.46 wt%) crystal and its behavior with the time of crystal irradiation with a laser undergo an atypical behavior caused by the features of the dissipation processes of laser-induced defects in the crystal. In the frequency range of 100–4000 cm⁻¹, the Raman spectra of the LiNbO₃:Y³⁺(0.46 wt%) single crystal were recorded upon excitation by visible (532 nm) and near-IR (785 nm) laser radiation. Five second-order Raman scattering lines were detected in the frequency range of 1000–2100 cm⁻¹, with the frequencies of two of them (of about 1790 cm⁻¹ and 1940 cm⁻¹) somewhat exceeding the doubled value of the frequencies of fundamental vibrations of the 4A₁(z)LO (longitudinal optical) and 9E(x,y) symmetry types, which allows us to attribute these lines to the overtones of the fundamental vibrations of 4A₁(z)LO and 9E(x,y). It is found that only one Raman scattering line is observed in the region of stretching vibrations of OH-groups (3200–3800 cm⁻¹). The frequency of this line is found to depend on the scattering geometry, varied within 3431–3438 cm⁻¹, and to be shifted to the low-frequency region by about 30–50 cm⁻¹ relative to the frequencies in the IR absorption spectrum. This finding may be due to the alternative prohibition rule due to the presence of the center of symmetry of the oxygen octahedra O₆ of the crystal structure. Full article

Cone-beam computed tomography (CBCT) offers advantages of low radiation dose and rapid acquisition but suffers from scatter-induced shading artifacts that limit diagnostic value compared to multi-detector CT (MDCT). While CycleGAN enables unpaired image translation, its uniform loss application struggles with localized artifact removal. We propose a two-stage learning framework with YOLO-based region correction loss. Stage 1 trains a standard CycleGAN to establish stable CBCT-MDCT domain mapping. Stage 2 fine-tunes the model by applying gradient magnitude minimization loss selectively to artifact regions detected by a pretrained YOLO detector, enabling focused correction while preserving anatomical structures. Using 11,000 2D CBCT slices from 17 patients (14 training, 3 testing) and 23,500 2D MDCT slices from 50 patients, our method achieves a 14.0% reduction in artifact score compared to baseline CycleGAN while maintaining high structural similarity (SSIM > 0.96). Independent evaluation using integral nonuniformity (INU) and shading index (SI) confirms consistent improvement across physics-based metrics. The self-regulating mechanism, where YOLO detection confidence naturally decreases as artifacts diminish, provides automatic adjustment without manual intervention. This work demonstrates that combining staged learning with object detection offers an effective solution for localized artifact removal in medical image translation, potentially improving diagnostic accuracy while preserving the low-dose benefits of CBCT. Full article