Search Results (313)

Due to the growth in the application of antibacterial nanomaterials (NMs), there is an increased potential for ingestion by humans. Evidence shows that NMs can induce dysbiosis in the gut microbiota in vivo. However, in vitro investigation of the antibacterial activity of NMs on gut-relevant, commensal bacteria has been neglected, with studies predominantly assessing NM toxicity against pathogenic bacteria. The current study investigates the antibacterial activity of copper oxide (CuO) NMs to Escherichia coli K12, Enterococcus faecalis, and Lactobacillus casei using a combination of approaches and evaluates the importance of reactive oxygen species (ROS) production as a mechanism of toxicity. The impact of CuO NMs (100, 200, and 300 μg/mL) on the growth and viability of bacterial strains was assessed via plate counts, optical density (OD) measurements, well and disc diffusion assays, and live/dead fluorescent imaging. CuO NMs reduced the viability of all bacteria in a concentration-dependent manner in all assays except the diffusion assays. The most sensitive methods were OD measurements and plate counts. The sensitivity of bacterial strains varied depending on the method, but overall, the results suggest that E. coli K12 is the most sensitive to CuO NM toxicity. The production of ROS by all bacterial strains was observed via DCFH-DA fluorescent imaging following exposure to CuO NMs (300 μg/mL). Overall, the data suggests that CuO NMs have antibacterial activity against gut-relevant bacteria, with evidence that NM-mediated ROS production may contribute to reductions in bacterial viability. Our findings suggest that the use of a combination of assays provides a robust assessment of the antibacterial properties of ingested NMs, and in particular, it is recommended that plate counts and OD measurements be prioritised in the future when screening the antibacterial properties of NMs. Full article

Optical coherence tomography (OCT) employs light to acquire high-resolution 3D images and is widely applied in fields such as ophthalmology and forensic science. A popular technique for visualizing the top view (en face) is to slice it with flat horizontal plane or apply statistical functions along the depth axis. However, when the target appears as a thin layer, strong reflections from other layers can interfere with the target, rendering the flat-plane approach ineffective. We apply Otsu-based thresholding to extract the object’s foreground, then use least squares (with Tikhonov regularization) to fit a polynomial curve that describes the sample’s structural morphology. The surface is then used to obtain the latent fingerprint image and its residues at different depths from a translucent tape, which cannot be analyzed using conventional en face OCT due to strong reflection from the diffusive surface, achieving FSIM of 0.7020 compared to traditional en face of 0.6445. The method is also compatible with other signal processing techniques, as demonstrated by a thermal-printed label ink thickness measurement confirmed by a microscopic image. Our approach empowers OCT to observe targets embedded in samples with arbitrary postures and morphology, and can be easily adapted to various optical imaging technologies. Full article

There is a common need for optical sequence images with high spatiotemporal resolution. As a solution, Synthetic Aperture Radar (SAR)-to-optical translation tends to bring high temporal continuity of optical images and low interpretation difficulty of SAR images. Existing studies have been focused on converting a single SAR image into a single optical image, failing to utilize the advantages of repeated observations from SAR satellites. To make full use of periodic SAR images, it is proposed to investigate the sequential SAR-to-optical translation, which represents the first effort in this topic. To achieve this, a model based on a diffusion framework has been constructed, with twelve Transformer blocks utilized to effectively capture spatial and temporal features alternatively. A variational autoencoder is employed to encode and decode images, enabling the diffusion model to learn the distribution of features within optical image sequences. A conditional branch is specifically designed for SAR sequences to facilitate feature extraction. Additionally, the capture time is encoded and embedded into the Transformers. Two sequence datasets for the sequence translation task were created, comprising Sentinel-1 Ground Range Detected data and Sentinel-2 red/green/blue data. Our method was tested on new datasets and compared with three state-of-the-art single translation methods. Quantitative and qualitative comparisons validate the effectiveness of the proposed method in maintaining radiometric and spectral consistency. Full article

Floods, exacerbated by climate change, necessitate timely and accurate situational awareness to support effective disaster response. While electro-optical (EO) satellite imagery has been widely employed for flood assessment, its utility is significantly limited under conditions such as cloud cover or nighttime. Synthetic Aperture Radar (SAR) provides consistent imaging regardless of weather or lighting conditions but it remains challenging for human analysts to interpret. To bridge this modality gap, we present diffusion-based SAR-to-EO image translation (DSE), a novel framework designed specifically for enhancing the interpretability of SAR imagery in flood scenarios. Unlike conventional GAN-based approaches, our DSE leverages the Brownian Bridge Diffusion Model to achieve stable and high-fidelity EO synthesis. Furthermore, it integrates a self-supervised SAR denoising module to effectively suppress SAR-specific speckle noise, thereby improving the quality of the translated outputs. Quantitative experiments on the SEN12-FLOOD dataset show that our method improves PSNR by 3.23 dB and SSIM by 0.10 over conventional SAR-to-EO baselines. Additionally, a user study with SAR experts revealed that flood segmentation performance using synthetic EO (SynEO) paired with SAR was nearly equivalent to using true EO–SAR pairs, with only a 0.0068 IoU difference. These results confirm the practicality of the DSE framework as an effective solution for EO image synthesis and flood interpretation in SAR-only environments. Full article

Prognostication of neurodevelopmental outcomes for neonates with hypoxic–ischemic encephalopathy (HIE) is primarily reliant on structural assessment using conventional brain magnetic resonance imaging in the clinical setting. Diffuse optical tomography (DOT) can provide complementary information on brain function at the bedside, further enhancing prognostic accuracy. The predictive accuracy and generalizability of DOT-based neuroimaging markers are unknown. This study aims to test the feasibility of prospectively recruiting and retaining neonates for 12 months in a larger study that investigates the prognostic utility of DOT-based biomarkers of HIE. The study will recruit 25 neonates with HIE over one year and follow them beyond NICU discharge at 6 and 12 months of age. Study subjects will undergo resting-state DOT measurement within 7 days of life for a 30–45-min period without sedation. A customized neonatal cap with 10 sources and eight detectors per side will be used to quantify cortical functional connectivity and to generate brain networks using MATLAB-based software (version 24.2). The Ages and Stages Questionnaires—3rd edition will be used for standardized developmental assessments at follow-up. This feasibility study will help refine the design and sample-size calculation for an adequately powered larger study that determines the clinical utility of DOT-based neuroimaging in perinatal brain injury. Full article

A double-sided telecentric zoom optical system can ensure the measurement and detection accuracy for different workpiece sizes and plays a crucial role in industrial detection. The conventional double-sided telecentric mechanical zoom system is faced with the problem of complex structure and difficult focusing. To address these issues, a liquid lens is applied to design a non-displacement double-sided telecentric zoom system in this paper. Here, the design method of the conventional double telecentric zoom system is analyzed first; then, the liquid lenses are substituted for the mechanical motion groups. Finally, a double-sided telecentric zoom system with a detection range of 25~60 mm and a magnification of −0.44×~−0.183× has been designed and optimized by Zemax software. The design results show that in the process of magnification, the root mean square radius of the diffuse spot in the system is smaller than the pixel size during the process of zooming. The modulation transfer function values at the Nyquist frequency of 80 lp/mm are all above 0.4, distortion is controlled within 0.2, and telecentricity is less than 0.5°, indicating that the system has excellent imaging quality, low distortion, and high telecentric and other characteristics, which meet system requirements. The design method proposed in this paper can provide an effective solution for the rapid conversion of displacement zoom systems to non-displacement zoom systems. Full article

Cardiac allograft vasculopathy (CAV) is a leading cause of allograft dysfunction and failure. CAV prevention, early detection, and management are essential to increasing allograft survival. In this comprehensive review, we discuss various invasive and non-invasive modalities that are being utilized for CAV detection. Invasive coronary angiography provides a visualization of vascular anatomy but is limited in detecting the microvasculature and diffuse and early structural changes. The addition of intracoronary assessment techniques, including intravascular ultrasound, optical coherence tomography, and coronary flow reserve assessment, offer(s) superior sensitivity in identifying CAV. Non-invasive imaging modalities, such as cardiac magnetic resonance imaging, computed tomography angiography, and positron emission tomography, provide complementary insights into CAV with myocardial perfusion and allograft function while reducing procedural risks. Our aim is to guide clinicians in selecting appropriate imaging strategies tailored to individual recipients, to improve detection, monitoring, and outcomes in CAV. Full article

Ghost imaging (GI) is an imaging modality typically based on correlations between a single-pixel (bucket) detector collecting the electromagnetic field which was transmitted through or reflected from an object and a high-resolution detector which measures the field that did not interact with the object. When using partially coherent sources, fluctuations can be introduced into a beam by rotating or translating a diffuser, and then the beam is split into two beams with identical intensity fluctuations. In computational GI, the diffuser with an unknown scatter distribution is replaced by a diffuser with a known scatter distribution so that the reference beam and high-resolution detector can be discarded. In this work, we wish to examine how the relation between the diffuser’s autocorrelation length and its spatial displacement affects the quality of image reconstruction obtained with these methods. We first analyze this general question theoretically and simulatively, and we then present some specific, proof-of-principle results we obtained in an optical setup. Finally, we discuss the relation between theory and experiment, suggesting some general conclusions regarding the preferred working points. Full article

This work presents a novel and comprehensive framework for optimizing fiber optic evanescent wave (FOEW) localized surface plasmon resonance (LSPR) sensors by investigating the unique interaction between evanescent waves and plasmonic nanoparticles. Unlike propagating light, the evanescent wave is a localized, non-propagating field that interacts exclusively with absorbing media near the fiber surface. This characteristic highlights the importance of prioritizing nanoparticle absorption over total extinction in FOEW sensor design. The optical response of silver nanoparticles was modeled across a size range of 10–100 nm, showing that absorption increases with particle number. Among the sizes tested, 30 nm silver nanoparticles exhibited the highest absorption efficiency, which was confirmed experimentally. An analytical adsorption kinetics model based on diffusion transport further predicted that smaller nanoparticles yield higher surface coverage, a result validated through atomic force microscopy (AFM) and scanning electron microscopy (SEM) imaging. Refractive index (RI) sensitivity tests conducted on sensors fabricated with 10 nm, 20 nm, and 30 nm silver nanoparticles revealed that while smaller nanoparticles produced higher initial absorption due to greater surface density, the 30 nm particles ultimately provided superior RI sensitivity due to their enhanced absorption efficiency. These findings underscore the significance of absorption-centered nanoparticle design in maximizing FOEW LSPR sensor performance. Full article

Tabletop 3D display is an emerging display form that enables multiple users to share viewing around a central tabletop, making it promising for the application of collaborative work. However, achieving an ideal ring-shaped viewing zone with a large radial viewing angle remains a challenge for most current tabletop 3D displays. This paper presents a tabletop 3D display based on a panoramic annular lens array to realize a large radial viewing angle. Each panoramic annular lens in the array is designed with a block-structured panoramic front unit and a relay lens system, enabling the formation of a ring-shaped viewing zone and increasing the radial angle of the outgoing light. Additionally, the diffusion characteristics of the optical diffusing screen component are analyzed under large angles of incidence after light passes through the panoramic annular lens array. Then, a method for generating the corresponding elemental image array is presented. The results of the simulation experiments demonstrate that the viewing range is improved to −78.4–−42.2° and 42.6–78.9°, resulting in a total radial viewing angle of up to 72.5°, and the proposed 3D display can present a 360° viewable 3D image with correct perspective and parallax. Full article

Increasing the proportion of clean energy within the energy structure is a crucial strategy for achieving energy transformation. Hydrogen and ammonia, as leaders in clean energy technologies, have garnered significant global attention. The combination of hydrogen and ammonia has emerged as a novel form of energy storage, transportation, and conversion; however, the safety aspects of their application process warrant closer attention. Research on hydrogen safety has been conducted extensively, with particular focus on the leakage, diffusion, combustion, and explosion processes. Both theoretical research and engineering applications have advanced significantly. In particular, hydrogen detection technology, primarily based on electrical measurement, has matured considerably, while schlieren imaging-based flow field visualization technology is progressing steadily. In contrast, safety research concerning ammonia remains in its early stages. Research on the leakage and diffusion characteristics of ammonia predominantly focuses on liquid ammonia, with a strong emphasis on engineering applications. Studies on the combustion and explosion characteristics of ammonia primarily address flame parameters and the combustion development laws. Ammonia serves as an efficient hydrogen storage medium. The conversion process involving hydrogen and ammonia will occur simultaneously in both time and space. Current research has not adequately addressed the safety concerns associated with the application process of hydrogen–ammonia mixtures. Future research on the safety of hydrogen–ammonia application processes should focus on the diffusion characteristics and combustion and explosion behaviors, as well as the development of electrical measurement detection technologies and optical flow field visualization techniques for hydrogen–ammonia mixtures. Full article

Extreme ultraviolet (EUV) imagers are key tools to monitor the space environment and forecast space weather. EUV filters are important components to block radiation in the ultraviolet (UV), visible, and near-infrared (IR) regions. In this study, various characterization methods were proposed for the nickel mesh-supported indium (In) filter, and their spectral characteristics were comprehensively studied. The material and thickness of the filter were chosen based on atomic scattering principles, determined through theoretical calculation and software simulation. The metal film was deposited using the vacuum-resistive thermal evaporation method. The measured transmission of the filter was 10.06% at 83.4 nm. The surface elements of the sample were analyzed using X-ray photoelectron spectroscopy (XPS). The surface and cross-sectional morphologies of the filter were observed using a scanning electron microscope (SEM). The impact of the oxide layer and carbon contamination on the filter’s transmittance was investigated using an ellipsometer. A multilayer “In-In₂O₃-C” model was established to determine the thickness of both the oxide layer and carbon contamination layer on the filter. This model introduces the filling factor based on the original model and considers the diffusion of the contamination layer, resulting in more accurate fitting results. The transmittance of the filter in the visible light range was measured using a UV-VIS spectrophotometer, and the measurement error was analyzed. This article provides preparation methods and test methods for the 83.4 nm EUV filter and conducts a detailed analysis of the spectral characteristics of the prepared optical filters, which hold significant value for space exploration applications. Full article

Background/Objectives: The aim of this study was to investigate the potential contribution of microaneurysms (MAs) and retinal cysts to the pathogenesis of macular non-perfusion in patients with diabetic macular edema (DME) using multimodal imaging. Methods: In this cross-sectional study, 42 eyes with DME were analyzed using color fundus photography, fluorescein angiography (FA) and optical coherence tomography (OCT). Macular non-perfusion within the central 3000 µm was categorized by location and extent into foveal avascular zone enlargement (FAZE), focal non-perfusion (FNP) and diffuse non-perfusion (DNP). A custom-developed software was used to assess the colocalization of retinal cysts on OCT with areas of non-perfusion on the corresponding FA images. Also, the presence of leaky MAs adjacent to retinal cysts on FA was verified. Results: Colocalization between retinal cysts and non-perfusion was observed in 32 of 42 (76%) eyes: 19 of 23 (83%) eyes with FAZE and 13 of 16 (81%) eyes with FAZE+FNP. No cysts colocalization was found in all three eyes (100%) presenting with DNP. None of the eyes presented with FNP alone. In the remaining seven eyes (four eyes with FAZE and three eyes with FAZE+FNP), no colocalization was noticed. At least one leaky MA adjacent to retinal cysts was identified in all eyes presented with colocalization. Conclusions: Retinal cysts may contribute to the development of limited non-perfusion in DME. Leaky MAs appear to be the primary source of cyst formation, which may lead to localized capillary occlusion in the macula. Full article

With the surge in digital farming, real-time quality management of fresh produce has become essential. For apples (Malus domestica Borkh.), consumer demand extends beyond sweetness, texture, and appearance to internal quality factors such as moisture content. Existing non-destructive methods, however, involve costly equipment, complex calibration, and sensitivity to environmental conditions. This study hypothesizes that thermal diffusivity indices derived from surface heating and cooling patterns can accurately predict apple moisture content non-destructively. A total of 823 apples from seven varieties were analyzed using a thermal imaging sensor in a 120-s process comprising 40 s of heating and 80 s of cooling. Key thermal diffusivity indices—minimum, maximum, mean, and max–min values—were extracted and correlated with actual moisture content measured via the drying method. Multiple linear regression and leave-one-out cross-validation confirmed that mean temperature-based models provided the most stable predictions ($R_{CV}^2$ ≥ 0.90 for some varieties). Frame optimization and artificial neural networks further improved prediction accuracy for varieties exhibiting higher variability. The proposed method is cost-effective, requires minimal calibration, and is less affected by surface reflectance, outperforming conventional optical methods (e.g., NIR spectroscopy, hyperspectral imaging), especially regarding robustness against surface reflectance variability and calibration complexity. This offers a practical solution for monitoring apple freshness and quality during sorting and distribution processes, with expanded research on sugar content and acidity expected to accelerate commercialization. Full article

Optimal needle trajectory selection is critical in biopsy procedures to minimize tissue damage and ensure diagnostic accuracy. Timely trajectory planning is essential, as it relies on preoperative CT imaging. Prolonged processing times increase the risk of patient movement, rendering the planned path invalid. Traditional methods relying on clinician expertise or slow algorithms struggle with complex anatomical modeling for structures such as blood vessels. We introduce a novel method that reframes trajectory planning as an optimal puncture site identification problem by leveraging optical principles and computer rendering. A 3D model of key anatomical structures is reconstructed from CT images and segmented using SegResNet (average Dice similarity coefficient of 0.9122). A virtual light source positioned at the target illuminates the space, assigning distinct absorption coefficients to tissues based on needle permissibility and risk. Diffuse reflection simulates needle angle, and accumulated absorption represents depth, capturing puncture constraints. This simulation generates a grayscale map on the skin surface, highlighting candidate puncture sites. Furthermore, we employ a random forest-based method to model clinician preferences. This model analyzes an RGB image derived from the grayscale distribution to automatically select the optimal path and determine the needle entry point. The experimental evaluation demonstrates an average computation time of just 1.905 s per sample, which is significantly faster than traditional methods that require seconds to minutes. Moreover, clinical assessment by a thoracic surgeon found that 78% of the recommended paths met clinical standards, with 0% deemed unsatisfactory. These findings suggest that our method provides a rapid, intuitive, and reliable decision-support tool, improving biopsy safety and efficiency. Full article