Search Results (9,253)

Long-wave infrared (LWIR) airborne optical systems for ground imaging are widely utilized in applications such as ground reconnaissance, agricultural monitoring, counterterrorism, and other fields. Traditional oblique-view ground-imaging optical systems suffer from a critical drawback compared to nadir-view systems: the significant variation in object distances between distant and nearby targets. This disparity leads to inconsistent ground resolution (GR), manifesting in images where distant targets exhibit significantly lower resolution than nearby ones. This characteristic is highly detrimental to information acquisition and three-dimensional modeling of the system. Furthermore, the limited field of view of fixed focal length systems prevents the unmanned aerial vehicle (UAV) from acquiring target information effectively across varying flight altitudes. To address this issue, this paper designs an oblique imaging optical system capable of achieving both constant GR and zoom functionality in the LWIR band. By controlling the ground resolution, a LWIR continuous zoom optical system was designed. The system maintains constant GR over the entire field of view. Its modulation transfer function (MTF) approaches the diffraction limit across the full field of view, and the spot diagram remains within Airy’s disk at each view angle. The radius of the spot diagram is smaller than that of the Airy disk, indicating that the geometric aberrations of the system are well corrected. The imaging performance is primarily determined by the wavelength and the F-number. In the case of LWIR, the longer wavelength results in a larger Airy disk radius. The system meets imaging quality requirements and is suitable for air-to-ground target reconnaissance imaging. Full article

Bone marrow cell classification and nucleus segmentation in microscopic images are fundamental tasks for computer-aided diagnosis of lymphocytic leukemia. However, bone marrow cells from different subtypes exhibit high morphological similarity, and structural information is often constrained under optical microscopic imaging, posing challenges for stable and effective feature representation. To address this issue, we propose MTLL (Multitask Model on Lymphocytic Leukemia), a novel multitask approach that performs cell classification and nucleus segmentation within a unified network to exploit their complementary information. The model constructs a hybrid backbone for shared feature representation based on a CNN-Transformer architecture, in which Fuse-MBConv modules are tightly integrated with multilayer multi-scale transformers to enable deep fusion of local texture and global semantic information. For the segmentation branch, we design an AM (Atrous Multilayer Perceptron) decoder that combines atrous spatial pyramid pooling with multilayer perceptrons to fuse multi-scale information and accurately delineate nucleus boundaries. The classification branch incorporates prior knowledge of cell nuclei structures to capture subtle variations in cellular morphology and texture, thereby enhancing the model’s ability to distinguish between leukemia subtypes. Experimental results demonstrate that the MTLL model significantly outperforms existing advanced single-task and multi-task models in both lymphocytic leukemia classification and cell nucleus segmentation. These results validate the effectiveness of the multi-task feature-sharing strategy for lymphocytic leukemia diagnosis using bone marrow microscopic images. Full article

Photochromic molecules, capable of reversible isomerization under specific light irradiation, are pivotal for developing advanced photo-responsive materials. Azobenzene derivatives, in particular, are renowned for their significant conformational change, excellent reversibility, and high photostability. This study presents a novel cyclic diazo compound (CDTA) comprising two azobenzene units connected via flexible glycol chains. The photo-responsive behavior of CDTA doped into the liquid crystal 4-cyano-4′-octylbiphenyl (8CB) was systematically investigated. The composite exhibits a pronounced photo-induced phase transition from a liquid crystalline to an isotropic state under 365 nm UV irradiation, accompanied by a reversible change in light transmittance. The response kinetics were found to be highly dependent on temperature and dopant concentration. At 35 °C, the UV response time was accelerated to 6.8 s, attributed to the transition of the host 8CB from a smectic to a nematic phase. Furthermore, the composite demonstrated dual responsiveness: optical switching under UV light and electrical switching under an applied field in its nematic state. This work elucidates the interaction between molecular structure and photo-response in a liquid crystalline matrix, offering insights for designing next-generation smart windows and adaptive optical devices. Full article

Infrared and visible image fusion aims to integrate complementary information from heterogeneous images captured by different optical sensors based on distinct imaging principles; however, existing methods often exhibit modality bias, leading to weakened targets or the loss of crucial texture details. To address this, we propose MBFTFuse, an adversarial fusion network based on modality balancing and feature tracing, which consists of a triple-path generator and dual discriminators. The architecture employs a generator with a triple-path structure: a central modality-balancing path for deep feature fusion and dual edge feature-tracing paths for modality-specific enhancement. Specifically, a multi-cognitive modality-balancing module is introduced to achieve feature weight equilibrium, while a Feature-Tracing Attention Module self-enhances single-modality features to compensate for information loss in the fusion results. Furthermore, a pixel loss based on intensity histograms is designed to optimize inter-modal balance at the pixel level. Comparative experiments against nine state-of-the-art methods across three public datasets demonstrate that MBFTFuse effectively highlights infrared targets while preserving intricate visible textures. The superior performance of this method in both quantitative metrics and downstream object detection tasks contributes to extending the boundaries of sensor-driven computer vision technologies. Full article

Polarized side-scattering techniques are widely used in aerosol detection, oceanographic optics, and biomedical sensing due to their high sensitivity to weak optical signals in low-scattering coefficient media. Conventional polarized Monte Carlo methods face significant challenges in such regimes due to geometric mismatch, where photon exit positions deviate substantially from the detector plane. This study addresses the geometric mismatch issue in polarized Monte Carlo simulations for side scattering in low-scattering media (scattering coefficient ${\mu }_s=$ 1 cm⁻¹), where photon exit positions often deviate from the detector plane. We propose a novel algorithm incorporating backward ray tracing with geometric projection correction to enhance simulation accuracy. Experimental validation was conducted using 532 nm laser illumination on both 500 nm polystyrene microspheres (${\mu }_s=$ 0.21 cm⁻¹) and 5 nm TiO₂ nanoparticles (${\mu }_s=$ 1.06 × 10⁻⁶–1.06 × 10⁻⁵ cm⁻¹). The results demonstrate excellent agreement between simulations and experiments, confirming the algorithm’s capability to accurately capture the polarization characteristics of side-scattered light. This work provides a high-fidelity simulation tool for designing optical sensors in low-scattering media and holds direct applicability in nanoparticle concentration sensing and aerosol monitoring. Full article

Diamond antireflection techniques are of high interest for optical windows operating at extreme conditions. Herein, diamond antireflective microstructures in mid-infrared (MIR) spectral range were theoretically designed and experimentally fabricated. Finite difference time domain (FDTD) simulations were used to optimize the transmission performance of the diamond microstructures. Based on the simulation results, the optimized microstructures were fabricated by femtosecond (fs) laser direct writing (1030 nm, 300 fs, 25 kHz) followed by wet etching. After wet etching, the laser-modified zones and the accumulated graphitized clusters were effectively removed, thereby achieving the desired depth. The influences of laser power and scanning strategy on the morphology evolution of diamond microstructures were investigated. It was found that at the optimal conditions, the transmittance of the diamond increased from 70.9% to 81.4% (single-side) over a broad spectrum from 8 to 22 μm. This work demonstrates a promising hybrid fs laser/wet etching technique for diamond antireflective microstructures in MIR spectral range. Full article

In the automotive industry, the most critical factor affecting dimensional stability during the forming of Advanced High-Strength Steels (AHSSs) is the springback phenomenon. This study systematically investigates the springback behavior of four distinct dual-phase steel grades (DP450, DP600, DP800, and DP1000) in U-shaped body-in-white (BIW) structures across 180 distinct scenarios. The experimental design varied sheet thicknesses (1.2, 1.6, 2 mm), die clearance angles (5°, 10°, 15°), and bending radii (R6, R8, R10, R12, R14). Numerical simulations using Autoform R8 were validated against Atos 3D optical scanning data, achieving values exceeding 0.90 for all grades. Quantitative validation metrics showed exceptional fidelity for lower-strength grades with error margins below 1.1%, while the maximum deviation was limited to 3.1% for the ultra-high-strength DP1000 grade. The findings demonstrate that while increasing material strength substantially intensifies springback, the strategic augmentation of sheet thickness and optimization of die radius effectively mitigate these deviations, thereby enhancing process stability. Full article

Virtual plant models combined with ray-tracing simulations are an established tool for evaluating plant–light interactions. Current approaches often simplify leaf surface properties by assuming diffuse reflectance behavior, despite experimental evidence that leaf reflectance is direction-dependent across much of the visible spectrum. This study investigates whether incorporating measured, spectrally resolved and direction-dependent (BRDF) reflectance properties into these models affects simulation outcomes. Using virtual 3D cucumber (Cucumis sativus) plant models with PhongShader-based optical leaf characteristics for BRDF consideration, light absorption and local photon flux densities were simulated under a wide range of lighting conditions, including diffuse and directed sunlight scenarios. While total light absorption at the leaf level is only marginally affected (mean absolute percentage error, MAPE < 2%), spectral distortions in leaf surroundings, especially under direct light, exceeded 8% in the blue wavelength range. Beyond their relevance for estimating photosynthetic rates, such distortions directly affect the spectral composition within the canopy, which is particularly critical in greenhouse applications where optical sensors are used to monitor spectral ratios and, therefore, require the accurate prior simulation of canopy light conditions. This is particularly relevant for setups with directional artificial lighting. The findings suggest that BRDF modeling is not critical for calculating photosynthetic rates under most conditions, but is required in spectral analyses or for optimizing artificial lighting designs. Full article

Optical coherence tomography (OCT) is a non-invasive, high-resolution imaging technique widely used in medical diagnosis, biomedical research and other fields. It plays an important role in the early detection and accurate diagnosis of diseases. The superluminescent light-emitting diode (SLED) is the ideal light source for OCT systems, where the stability of its drive current and operating temperature directly determines the imaging quality of OCT. Existing driving and temperature control schemes for similar light sources predominantly rely on microcontrollers or field programmable gate arrays (FPGAs), a reliance which often results in complex system architectures and difficulties in balancing simplicity with control precision. To address these issues, a stable and compact SLED source driver module designed for OCT was developed in this study, integrating both a constant-current drive circuit and a temperature control circuit. The negative feedback control and improved current-limiting protection are employed in the constant-current drive circuit to maintain stable SLED operation and reduce the circuit footprint. A miniature dedicated temperature control chip is adopted in the temperature control circuit. The operating temperature of the SLED is acquired by linearizing the negative temperature coefficient (NTC) thermistor value and regulated through a proportional-integral-derivative (PID) compensation circuit. The size of the fabricated module (including casing) is less than 10 × 8 × 3 cm³. Experimental results show that the driver module achieves a drive current control accuracy of 0.1% and a temperature control accuracy of 0.01 °C. The output optical power fluctuation is less than 0.005 mW and the average axial resolution for OCT is 6.5992 μm with a standard deviation of 0.0107 μm. This light source driver module successfully balances control precision with structural simplicity, demonstrating excellent applicability in OCT systems. Full article

This study investigates the effects of organic salts, including sodium citrate (SC), calcium citrate (CC), and calcium lactate (CL), on the structure–property–function relationships of thermoplastic starch/poly(butylene adipate-co-terephthalate) (TPS/PBAT) films for active packaging applications. TPS incorporated with organic salts was prepared via twin-screw extrusion, blended with PBAT, and further processed into blown films. The films were systematically characterized using ¹H NMR, FTIR, and SEM, together with optical, mechanical, water vapor permeability, and antimicrobial evaluations against Staphylococcus aureus. The results revealed that SC primarily modulated hydrogen-bonding interactions within the starch matrix, resulting in improved structural homogeneity, balanced mechanical properties, and the highest antimicrobial activity among all formulations. In contrast, CL and CC promoted ionic crosslinking through Ca²⁺–starch interactions, leading to increased stiffness and Young’s modulus but reduced polymer chain mobility and limited release of active species, particularly in CC-containing systems. These differences in molecular interactions were consistent with variations in film microstructure, where SC-containing films exhibited more uniform morphologies, while calcium-based systems showed denser but less permeable structures. Furthermore, films containing SC and CL at appropriate concentrations achieved a favorable balance between transparency, water vapor barrier properties, and antimicrobial performance. Overall, this study provides new mechanistic insights into how monovalent and divalent organic salts govern intermolecular interactions, microstructure, and functional performance in TPS/PBAT systems. The findings highlight the critical role of additive type and concentration in designing biodegradable active packaging materials with tunable mechanical, barrier, and antimicrobial properties. Full article

The shift toward lightweight powertrain architectures necessitates a detailed characterization of polymer gears to verify their efficiency and durability. This study investigated the effectiveness of non-contact structured-light 3D scanning for evaluating the surface topography and dimensional tolerance quality of polymer gears produced via distinct manufacturing technologies. A structured-light 3D scanner was used to capture dense point clouds (exceeding 6 million points) of gears produced by three methods: conventional hobbing (POM-C), Material Extrusion (MEX) with carbon fiber reinforcement, and Selective Laser Sintering (SLS). The manufactured parts were compared against the nominal Computer Aided Design (CAD) models to evaluate their geometrical deviations in accordance with DIN 3961 and surface roughness parameters per ISO 25178. The experimental results revealed a consistent ranking of manufacturing quality. The conventionally hobbed POM-C gear exhibited superior precision, achieving DIN quality grades of Q9–Q10 and the smoothest surface finish (S_a = 5.0 µm). Among additive manufacturing techniques, SLS-printed PA 12 showed intermediate quality (Q11, S_a = 12 µm), whereas MEX-printed PPS-CF exhibited significant deviations (exceeding Q12) and the highest surface irregularity (S_a = 25 µm) due to stair-stepping effects. These findings indicate that while additive manufacturing offers geometric flexibility, conventional hobbing retains a decisive advantage in dimensional precision. The optical scanning methodology demonstrated here constitutes an efficient metrological framework for gear quality control, with potential applications extending to the quality assurance of additively manufactured adaptive fixtures and assembly tooling, including automotive assembly operations. Full article

Silicone hydrogels offer high oxygen permeability but suffer from poor wettability. This study integrates a TRISS-based system (0–2.0 wt%) with a fixed PVP/NVP matrix (1.0/0.5 wt%) to enhance hydration-induced dimensional stability and surface properties. Fabricated via cast-molding, the lenses demonstrated that TRISS incorporation significantly enhances oxygen transport. Specifically, the 2.0 wt% TRISS formulation (S2.0) achieved an ~1.9-fold increase in oxygen-induced current (from 0.97 μA in pure-HEMA to 1.86 μA) while strongly suppressing hydration-induced swelling. To counter TRISS’s inherent hydrophobicity, the PVP/NVP matrix acted as a vital compensatory mechanism, driving the equilibrium contact angle down to 56.04° and avoiding the severe hydrophobic plateau (93.79°) of the additive-free comparator. S2.0 maintained a robust oxygen response alongside improved wettability. In conclusion, this system defines a workable low-silicone design window accommodating up to 2.0 wt% TRISS without wettability loss or optical degradation (>97%). Crucially, by leveraging TRISS to mitigate swelling-induced mechanical stress and PVP/NVP to ensure stable wettability, this structurally robust hydrogel provides a highly viable foundational matrix for future smart contact lenses equipped with diagnostic micro-components. Full article

This study proposes a principal component analysis-based convolutional neural network (PC-CNN) to correct atmospheric turbulence-induced aberrations. Unlike traditional Zernike polynomials (ZPs)-based methods (ZP-CNN), PC-CNN avoids mode aliasing and cross-coupling via the strict orthogonality of principal components (PCs). A coefficient magnification strategy is incorporated to further enhance efficacy, maximally preserving the intrinsic physical information within the PCs coefficients. A series of systematic experiments was conducted under conditions from weak to strong turbulence, characterized by $D/r_0$ from 1 to 25, where $D$ is the pupil diameter and $r_0$ is the atmospheric coherence length. Quantitative results show PC-CNN achieves a lower mean relative error (MRE) in coefficient prediction than ZP-CNN under equivalent conditions. It also yields a higher Strehl ratio, reduced speckles, and enhanced spot clarity while requiring fewer basis terms, demonstrating high stability and robustness in strong turbulence. These findings emphasize that basis function orthogonality and physically informed preprocessing are critical design principles for deep-learning-based wavefront sensor-less adaptive optics (AO), establishing a robust foundation for real-time intelligent AO systems in astronomy and free-space optical communications. Full article

Light-based diagnostic and therapeutic approaches are increasingly important in modern biomedicine, with organic dyes emerging as versatile optical agents due to their tunable photophysical properties. Precise control over absorption and emission characteristics has enabled their application in fluorescence, photoacoustic, and Raman imaging, as well as in photodynamic and photothermal therapies. However, challenges related to biocompatibility, aqueous stability, and in vivo performance remain critical for clinical translation. Organic dyes that absorb in the near-infrared region are particularly attractive because of their deeper tissue penetration and reduced background interference. This review highlights key structure property relationships of organic dyes and summarizes current design strategies, including chromophore modification, peripheral functionalization for water solubility, and self-assembled nanotheranostic systems. Recent biomedical applications in cancer diagnosis and therapy, bacterial detection, and imaging-guided treatment are discussed, along with future directions for advancing dye-based technologies in healthcare. Full article

Eye-tracking is a key enabling technology for smart eyewear, supporting hands-free interaction, accessibility, and context-aware human–machine interfaces under strict constraints on size, power consumption, and computational complexity. While camera-based solutions provide high accuracy, their integration into lightweight and low-power wearable platforms remains challenging. This paper is a feasibility study for the design, simulation, and experimental evaluation of a photosensor oculography (PSOG) eye-tracking system that is fully integrated into an eyewear frame, based on near-infrared (NIR) emitters and photodiodes. The proposed approach combines simulation-driven optimization of the optical constellation, a multi-frequency modulation and demodulation scheme enabling parallel source discrimination and robust ambient-light rejection, and a resource-efficient signal acquisition pipeline suitable for embedded implementation. Eye rotations in azimuth and elevation are inferred from differential reflectance patterns of ocular regions (sclera, iris, and pupil) using lightweight regression techniques, including shallow neural networks and Gaussian process regression, selected to balance estimation accuracy with computational and power constraints. System performance is evaluated using a controllable artificial-eye platform under defined geometric and illumination conditions, enabling repeatable assessment of gaze-estimation accuracy and algorithmic behavior. Sub-degree errors are achieved in this controlled setting, demonstrating the feasibility and potential effectiveness of the proposed architecture. Practical considerations for translation to real-world smart eyewear, including human-subject validation, anatomical variability, calibration strategies, and embedded deployment, are discussed and identified as directions for future work. By detailing the optical design methodology, modulation strategy, and algorithmic trade-offs, this work clarifies the distinct contributions of the proposed PSOG system relative to existing frame-integrated and camera-free eye-tracking approaches, and provides a foundation for further development toward wearable and augmented-reality applications. Full article