Search Results (2,852)

Optical metasurfaces fabricated via electron beam lithography (EBL) are increasingly pivotal for biosensing and bioimaging applications. However, charge accumulation on insulating glass substrates persists as a critical barrier, causing distortion of the incident electron beam and degradation of patterning fidelity manifested as pattern deflection, increased line-edge roughness (LER), and overlay inaccuracy. Here, we evaluate three charge-mitigation strategies: optimization of electron-beam resist (EBR) thickness, spin-coated conductive polymer layers, and thin metal capping layers. A reduction in EBR thickness from 800 nm to 150 nm led to a significant improvement in LER attributed to a shortened charge dissipation path. The introduction of a conductive polymer further enhanced pattern integrity, whereas the most substantial improvement was attained by depositing a 20 nm Au layer, which offers a highly conductive pathway for rapid charge dissipation and resulted in the lowest LER of 0.24. Our comparison establishes a clear hierarchy of effectiveness and identifies metal capping as the most reliable approach for high-fidelity nanofabrication on insulating substrates, thereby offering practical solutions for advancing glass-based photonic and meta-optical devices. Full article

For the method of focused ion beam (FIB) milling to fabricate lithium tantalate (LiTaO₃) metasurfaces, the use of a Cr-Pt mask can enhance imaging contrast and enable superior drift correction. However, removing the Pt component necessitates the volatile and toxic etchant aqua regia, presenting considerable safety risks. This work introduces a novel lift-off strategy that incorporates thin Ag or Au sacrificial layers (≤30 nm) between the LiTaO₃ substrate and Cr-Pt mask. Systematic evaluation identifies Ag or Au as optimal candidates due to their high sputtering yield for efficient FIB patterning and compatibility with a low-toxicity KI + I₂ etchant. Experiments showed complete mask removal within 60 s while preserving structural fidelity: atomic force microscopy (AFM) results reveal a surface roughness comparable to conventional aqua regia processing, and scanning microscope (SEM) imaging confirms intact sidewall angles (10–11°). The second-harmonic generation (SHG) measurements reveal comparable optical performance upon the introduction of Ag or Au sacrificial layers. This approach eliminates hazardous etchant and maintains process precision, offering a scalable and safer fabrication route for LiTaO₃-based photonic devices. Full article

To address the issue of climate change caused by greenhouse gases, extensive research has been conducted on technologies for separating and capturing carbon dioxide. This study aimed to investigate the internal flow behavior and relative spatial distribution of CO₂-related features inside a vortex tube using the Schlieren method. Due to the presence of numerous components in a typical counter-flow vortex tube that may cause optical refraction along the measurement path, a simplified tube with a single nozzle was designed and manufactured for the experiments. The experiments consisted of CO₂ single-phase flow and air–CO₂ mixture flow tests. Images captured during the experiments were processed using Gaussian filtering and background correction to enhance the visibility of boundary layers and internal flow structures. Based on the pixel intensity values of the processed Schlieren images, relative intensity distributions associated with CO₂-related flow behavior inside the tube were estimated and visualized. The experimental results revealed that, in both CO₂ single-phase and air–CO₂ mixture flows, regions of relatively high Schlieren intensity consistently appeared at specific locations within the tube. These observations indicate that the internal flow structure and relative distribution patterns are sensitive to the local flow features near the nozzle region under the tested conditions. The temporal evolution of the normalized Schlieren pixel intensity and its standard deviation was quantitatively evaluated, in a relative sense, to characterize the development of vortex flow structures under different operating conditions. The proposed visualization and analysis framework provides a systematic qualitative approach, supported by relative quantitative indicators, for investigating vortex-induced flow behavior. This framework may serve as a foundation for future studies that integrate complementary diagnostics and numerical analyses to further explore the vortex-based gas separation mechanism. Full article

Coastal sandbars play a crucial role in shoreline protection, yet monitoring their dynamics remains challenging due to the cost and limited temporal coverage of traditional surveys. This study assesses the feasibility of using Sentinel-2 multispectral imagery combined with the logarithmic band ratio method to automatically detect submerged sandbar crests along three morphologically distinct beaches on the northwestern Mediterranean coast. Pseudo-bathymetry was derived from log-transformed band ratios of blue-green and blue-red reflectance used to extract the sandbar crest and validated against high-resolution in situ bathymetry. The blue-green band ratio achieved higher accuracy than the blue-red band ratio, which performed slightly better in very shallow waters. Its application across single, single/double, and double shore-parallel bar systems demonstrated the robustness and transferability of the approach. However, the method requires relatively clear or calm water conditions, and breaking-wave foam, sunglint, or cloud cover conditions limit the number of usable satellite images. A temporal analysis at a dissipative beach further revealed coherent bar migration patterns associated with storm events, consistent with observed hydrodynamic forcing. The proposed method is cost-free, computationally efficient, and broadly applicable for large-scale and long-term sandbar monitoring where optical water clarity permits. Its simplicity enables integration into coastal management frameworks, supporting sediment-budget assessment and resilience evaluation in data-limited regions. Full article

This work reports the design and realization of a silicon-based micro photovoltaic generator (MPG) fabricated using a standard 0.18 μm complementary metal oxide semiconductor (CMOS) technology. The device harvests optical energy and converts it into electrical power through the photovoltaic effect, leveraging a network of engineered p–n junctions formed within the semiconductor. A grid-structured architecture is adopted, in which patterned p-type regions are embedded inside an n-well platform. This configuration expands the effective junction area, increases carrier-collection paths, and strengthens the internal electric field, thereby enhancing photocurrent generation. To further improve optical coupling, a specialized post-CMOS treatment is introduced. A wet etching is used to selectively remove the silicon dioxide layer that normally covers the junction regions in CMOS processes. Eliminating this dielectric layer enables direct photon penetration into the depletion region minimizes reflection-related losses, resulting in a significant improvement in device performance. Under an illumination intensity of 1000 W/m², the fabricated microgenerator delivers an open-circuit voltage of 0.49 V, a short-circuit current of 239 µA, and a maximum output power of 90 µW. The device exhibits an overall energy conversion efficiency of 12.9%, confirming the effectiveness of the grid-like junction design and the post-processing oxide removal. Full article

Lakes in the Amur River Basin (ARB) are increasingly influenced by climate variability and human activities, yet long-term basin-scale patterns of colored dissolved organic matter (CDOM) remain unclear. In this study, we developed a support vector regression (SVR) model to retrieve lake CDOM from Landsat 5/7/8 imagery and generated a 40-year (1984–2023) CDOM dataset for 69 large lakes. The model provides a reliable tool for multi-decadal, large-area water quality monitoring considering its robust performance (R² = 0.88, rRMSE = 22.4%, MAE = 2.63 m⁻¹). Trend analysis revealed a significant rise in CDOM since 1999, particularly across the Mongolian Plateau and Northeast China Plain. Among the 69 lakes, 27 exhibited increasing CDOM, while 4 showed declines, highlighting pronounced regional variability. Variance partitioning indicated that human activities, especially irrigation and grazing, account for ~30% of CDOM variation, exceeding the contribution of any single climatic driver, whereas temperature represents the dominant climate driver (12.8%). Shallow systems were more sensitive to external disturbances, while deep lakes responded more strongly to thermal conditions. This study delivers the first long-term satellite-based CDOM assessment in the ARB and underscores the combined impacts of climate change and land-use pressures on lake optical dynamics. Full article

Lakes play a crucial role in maintaining agricultural irrigation water sources, regulating climate, and supporting the long-term resilience of regional ecosystems. However, accurately delineating the boundaries between lakes and land remains challenging due to seasonal hydrological fluctuations, spectral obfuscation with farmland, and the limitations of single-sensor methods. This study constructs a multi-source remote sensing framework integrating Sentinel-1 SAR, Sentinel-2 optical data, DEM, and key environmental variables to identify the water body, near-water body, and non-water surface of Weishan Lake, a major irrigation source in northern China. The study systematically compares various methods, including the optical index method, SAR-based threshold segmentation, and machine learning classifiers. The results show that the random forest model has higher accuracy and temporal robustness. Introducing the “near-water body” category allows for more accurate characterization of transitional areas sensitive to seasonal hydrological and agricultural processes. Migration tests of the model in three external lake systems demonstrate its strong generalization ability, while correlation analysis and SHAP-based analysis indicate that NDVI and elevation are the main factors influencing the spatial pattern of water and land. The proposed framework supports sustainable irrigation management by enabling accurate water boundary monitoring and enhancing the understanding of agricultural hydrological interactions. Full article

Objectives: To evaluate the changes in retinal function and neural conduction along the visual pathways after 12 months of treatment with Citicoline oral solution in patients with open-angle glaucoma (OAG). Methods: In this randomized, prospective, double-blind study, 29 OAG patients were enrolled. Fifteen patients (Citicoline Group, 15 eyes) received Citicoline oral solution (Neurotidine^®, 500 mg/day), and 14 patients (Placebo Group, 14 eyes) received placebo for 12 months. Visual field (VF), pattern electroretinogram (PERG), visual evoked potentials (VEP), and Retinocortical Time (RCT) were assessed at baseline and after 6 and 12 months. Brain Diffusion Tensor Imaging (DTI)-Magnetic Resonance Imaging (MRI) was performed at baseline and at 12 months. Results: PERG, VEP, and RCT baseline values were comparable between groups (p > 0.01) at baseline. After 12 months of Citicoline treatment, significant (p < 0.01) increases in PERG P50–N95 and VEP N75-P100 amplitudes, and significant shortening of PERG P50, VEP P100 implicit times and RCT were observed. VEP implicit times shortening significantly correlated with the changes in VF Mean Deviation, and RCT shortening was associated with changes in DTI-MRI metrics in the lateral geniculate nucleus and on optic radiations, without reaching the level of significance. No significant changes were found in the Placebo Group. Conclusions: In OAG, Citicoline oral solution enhances retinal function likely through neuromodulation processes and changes post-retinal visual pathway connectivity. This could explain the improvement of visual field defects. Full article

Lensless microscopy is a well-established imaging approach that replaces traditional lenses with phase modulators, enabling compact, low-cost, and computationally driven analysis of biological samples. In this work, we show how ray tracing simulations can be used to optimize lensless imaging systems for automated classification, particularly for detecting red blood cell (RBC) disease. Rather than improving the machine learning classification algorithm, our focus is on refining optical parameters such as element spacing and modulator type to maximize classification performance. We modeled a lensless microscope in Zemax OpticStudio (ray tracing) and compared the results against Fourier optics simulations. Despite not explicitly modeling diffraction, ray tracing produced classification results largely consistent with wave optics simulations, confirming its effectiveness for parameter optimization in lensless imaging setups used for classification tasks. Furthermore, to show the flexibility of the ray tracing model, we introduced a microlens array (MLA) as the phase modulator and performed the classification task on the generated patterns. These results establish ray tracing as an efficient tool for the optical design of lensless microscopy systems intended for machine learning based biomedical applications. The developed lensless microscopy model enables the generation of datasets for training neural networks. Full article

Background: Conventional absorption-based computed tomography has a limited ability to resolve lung microarchitectures that are critical for histological subtype discrimination. This study evaluated the potential of X-ray Dark-Field Imaging Computed Tomography (XDFI CT) using synchrotron radiation for non-destructive, three-dimensional visualization of human lung cancer microstructures. Methods: Surgically resected human lung cancer specimens (n = 4) were examined, including acinar-predominant adenocarcinoma (n = 1), adenocarcinoma after concurrent chemoradiation therapy (n = 1), keratinizing squamous cell carcinoma (n = 1), and metastatic hepatocellular carcinoma in the lung (n = 1). Image acquisition was performed at beamline BL-14B of the Photon Factory (Tsukuba, Japan), using a monochromatic 19.8 keV synchrotron X-ray beam and a crystal analyzer-based refraction-contrast optical system. Imaging findings were qualitatively correlated with corresponding histopathological sections. Results: Synchrotron radiation XDFI CT enabled clear visualization of normal distal lung microanatomy, including alveolar walls and associated vascular structures, which served as internal references adjacent to tumor regions. Distinct microstructural features—such as invasive growth patterns, fibrotic or keratinized stroma, necrosis, and treatment-related remodeling—were identifiable and varied according to histological subtype. Tumor–normal tissue transitional zones were consistently delineated in all specimens. Conclusions: Synchrotron radiation XDFI CT provides high-resolution, non-destructive volumetric imaging of lung cancer tissues and reveals subtype-associated microarchitectural features. This technique may complement conventional histopathology by enabling three-dimensional virtual histologic assessment of lung cancer specimens. Full article

This study examines the influence of internal infill geometry, infill density, and short-term mineral oil exposure on the tensile and microstructural behavior of Fused Deposition Modeling (FDM) 3D-printed Polylactic Acid (PLA) and Carbon-Fiber-Reinforced PLA (PLA+CF). Standardized ISO 527-2 specimens were fabricated using linear, triangular, and hexagonal infill patterns at 30%, 60%, and 100% densities, followed by seven-day immersion in mineral oil. Mechanical testing and quantitative optical image analysis were performed to correlate porosity characteristics with tensile response. For PLA, the linear 30% infill achieved the highest tensile strength (31.5 MPa), while the hexagonal pattern exhibited the greatest ductility (ε = 4.9%). Oil exposure caused slight reductions in strength (−1.2%) and modulus (−4.1%) but increased elongation by 76%, indicating mild matrix plasticization. For PLA+CF, tensile strength and stiffness increased with density, reaching 33.4 MPa and 500 MPa at 100% infill, while oil exposure enhanced strength by 6.9% and reduced the average pore size from 475 µm² to 146 µm². Overall, the results demonstrate that optimizing infill topology, density, and fiber reinforcement significantly improves load transfer efficiency and environmental stability. These findings establish quantitative correlations between pore morphology and tensile behavior, providing a framework for the predictive design of environmentally resilient FDM polymer–composite components for semi-lubricated or tribological applications. Full article

Terrace construction is a critical engineering practice for soil and water conservation as well as sustainable agricultural development on the Loess Plateau (LP), China, where high-precision dynamic monitoring is essential for informed regional ecological governance. To address the challenges of inadequate extraction accuracy and poor model generalization in time-series terrace mapping amid complex terrain and spectral confounding, this study proposes a novel Swin Transformer-based Terrace Dual-Branch Deformable Boundary Network (STDBNet) that seamlessly integrates multi-source remote sensing (RS) data with deep learning (DL). The STDBNet model integrates the Swin Transformer architecture with a dual-branch attention mechanism and introduces a boundary-assisted supervision strategy, thereby significantly enhancing terrace boundary recognition, multi-source feature fusion, and model generalization capability. Leveraging Sentinel-2 multi-temporal optical imagery and terrain-derived features, we constructed the first 10-m-resolution spatiotemporal dataset of terrace distribution across the LP, encompassing nine annual periods from 2017 to 2025. Performance evaluations demonstrate that STDBNet achieved an overall accuracy (OA) of 95.26% and a mean intersection over union (MIoU) of 86.84%, outperforming mainstream semantic segmentation models including U-Net and DeepLabV3+ by a significant margin. Further analysis reveals the spatiotemporal evolution dynamics of terraces over the nine-year period and their distribution patterns across gradients of key terrain factors. This study not only provides robust data support for research on terraced ecosystem processes and assessments of soil and water conservation efficacy on the LP but also lays a scientific foundation for informing the formulation of regional ecological restoration and land management policies. Full article

In infrared detectors, the readout circuits usually cause horizontal or vertical streak noise, whereas the infrared focal plane arrays experience triangular nonuniform fixed-pattern noise. In addition, imaging devices suffer from optically relevant fixed-pattern noise owing to the temperature. When the infrared camera is in orbit, it is affected by the photon effect, temperature change, and time drift. This makes the nonuniformity correction coefficients pertaining to the ground no longer applicable, resulting in the degradation of the nonuniformity correction effect. The existing methods are not fully applicable to triangular fixed-pattern noise or the fixed-pattern noise caused by detector optics. To address this situation, this paper proposes a nonuniformity correction method, namely infrared image sequences based on the optimization of $L_{2,1}$ group sparsity in the spatiotemporal domain. We established a nonuniformity correction model of differential operators in the spatiotemporal domain for infrared image sequences by applying the time-domain differential operator constraints to the images to denoise the image. This enables the adaptive correction of the nonuniformity of the above types of noise. We demonstrate that the proposed method is effective for triangular nonuniform and optically induced fixed-pattern noises. The proposed method was extensively evaluated using publicly available datasets and datasets containing image sequences of different scenes captured by a high-resolution infrared camera of the Qilu-2 satellite. The method has high robustness and good processing results with effective ghost suppression and significant reduction of nonuniform noise. Full article

Extramammary Paget’s disease (EMPD) is a rare cutaneous adenocarcinoma typically arising on apocrine gland-rich skin. This suprapubic location is exceptionally rare. Its nonspecific erythematous plaques often mimic benign inflammatory or infectious dermatoses, delaying diagnosis. We report an 80-year-old male who presented with a chronic suprapubic plaque. Videodermoscopy and line-field confocal optical coherence tomography (LC-OCT) highlighted irregular vascular patterns and pagetoid cells, raising suspicion for EMPD and guiding a biopsy. Histopathology confirmed carcinoma in situ, and immunostains (CK7 positive, CK20 negative) supported a primary cutaneous origin. Comprehensive screening ruled out associated malignancies; however, guidelines note that colon, rectal, prostate, and bladder cancers are the most frequent synchronous tumors and suggest considering tailored internal malignancy screening. Wide local excision achieved clear margins; after one year, there is no recurrence. The literature indicates that recurrence remains frequent after surgery and may not correlate with margin width, necessitating careful long-term surveillance. For patients unfit for surgery, alternative therapies include radiotherapy, topical imiquimod, and photodynamic therapy, though photodynamic therapy appears palliative rather than curative. Non-invasive imaging modalities, such as LC-OCT, provide high-resolution “virtual histology,” enhancing early diagnosis and reducing the need for repeated biopsies. Early recognition, appropriate staging, and multidisciplinary management are crucial for improving outcomes. Full article

Lately the nonlinear optical third-harmonic generation (THG) microscopy is starting to emerge as a laboratory standard for label-free studies in biological samples. In this study, the THG signals produced from corn starch granules are investigated. In particular, the polarization-dependent THG (P-THG) signals emerging from the outer layer (shell) of the starch granules are compared with the P-THG signals originating from their inner portion (core). By rotating the linear polarization of the excitation beam, two distinct P-THG modulation patterns are revealed within single granules, corresponding to their shells and to their structurally different cores. These patterns are analyzed using a theoretical framework that describes THG from an orthorhombic crystal symmetry, characteristic of corn starch. This allows us to extract point-by-point in the granules the ratios of the ${\chi }^{\left(3\right)}$ susceptibility tensor elements and the average molecular orientations. Then, the anisotropy ratio (AR = ${\chi }_{xxxx}^{\left(3\right)}$/${\chi }_{yyyy}^{\left(3\right)}$) is defined and used as a quantitative descriptor of the local molecular arrangements. Our results show that the shells and cores exhibit distinct AR values, probing the anisotropy in the molecular arrangements between the two regions. This study establishes P-THG as a powerful contrast mechanism for probing structural anisotropy in biological samples beyond conventional THG intensity-only microscopy. Full article