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Multiple scattering poses a fundamental limitation in deep imaging, especially for high-resolution optical imaging methods. The amalgamation of reflection matrix measurements and optical coherence tomography (OCT) has afforded significant advantages for deep imaging through highly scattering media. To empirically exhibit the superior performance of reflection matrix OCT (RMOCT), this study proposes a unique method to ascertain the actual resolutions at each imaging point. In contrast to conventional theoretical lateral resolutions, these resolutions are derived by applying time-reversal decomposition to the time-gated reflection matrix. Moreover, the concept of contribution rate, which quantifies the imaging contributions for each point, is introduced by considering the local imaging point itself and its neighboring points. The contribution rate provides a quantitative evaluation of the imaging quality afforded by a system. To the best of our knowledge, this study represents the comprehensive assessment of the practical performance of RMOCT in terms of actual resolving power and imaging quality. [ABSTRACT FROM AUTHOR]

This paper focuses on minimizing the optical reflection on spherical fused silica lenses using femtosecond (fs) laser nanostructuring. A unique type of nanopillar formation has been observed on SiO 2 surfaces possessing antireflective properties when irradiated with a specific number of overlapping pulses, polarization, and fluence levels. Maintaining precise control over these sensitive technological parameters such as defocus and incident angle during the processing of geometrically complex shapes presents a significant challenge. This study proposes a theoretical optical arrangement to address this limitation by the design of a custom scanner system optimized for curved surfaces. The paper details the optimization process of such a bent image space (inverse-hypercentric) optical system using Zemax OpticStudio. Although the practical realization of the arrangement has not been performed, simulations are conducted to prove the functionality of the concept. Furthermore, we propose a practical method for segmented structuring of spherical surfaces based on consecutive repositioning and irradiation using an industrial robotic arm. By constructing the optical model, the necessary resolution of the segmentation has been calculated for a typical F-Theta scanner system and experimental verification has been performed. [ABSTRACT FROM AUTHOR]

Leaf wetness duration is a crucial factor in plant disease management. Current optical methods use standard RGB images to classify leaf wetness as a binary problem, i.e., wet or dry. Green leaves absorb red light, whereas water reflects it. Based on this difference, an experimental platform was built to semi-automatically measure droplet deposition on grape leaves while capturing red laser images using an RGB camera. The setup measured changes in leaf mass and area of scanned leaves to determine the water mass per leaf area as a measure of leaf wetness. A sprayer was used to apply water droplets to the leaves. As the amount of deposited water increased, the mean red channel intensity decreased, with more bright spots in the images. These bright spots were more distinguishable as droplets in the green channel. Segmented leaf area, mean red channel intensity, and the number of identified droplets were used as image features. A generalised additive model was employed to predict the leaf wetness value with extracted features. The R-squared value for the prediction of the validation dataset was 0.71. Image resolution and leaf orientation were identified as factors that influenced the model accuracy. The measurement method introduced in this study shows potential for accurately quantifying leaf wetness, and implies that in practice detecting leaf wetness can be integrated into a multi-classification problem, thereby broadening the potential applications of optical methods. • A novel non-contact optical method was developed to quantify leaf wetness. • The effect of water droplets on leaves on the images in visible light were analysed. • Factors influencing this method were identified for further development. • A semi-auto system was built to accurately measure the deposition on leaves. [ABSTRACT FROM AUTHOR]

Light reflection and diffusion mechanism in the crystalline phase-controlled BSS-HNPs. [Display omitted] • This is the first study on black hollow TiO 2 nanoparticles that can be applied as a painting pigment to correlate the color and the change in the crystal system in the LiDAR application field. • Various crystalline-phase black hollow nanoparticles were synthesized using a simple sol–gel method, followed by calcination at different temperatures, NaBH 4 reduction, and etching. The formation of nanomaterials was analyzed using various methods, and the change in bandgap energy following the crystalline phase was determined using the DFT calculation method.. • Examining the conversion of crystalline phases from anatase to rutile on TiO 2 and exploring the connection between bandgap energy, refractive index, and NIR reflectance have resulted in significant enhancements in NIR reflectance. • True blackness and the change in the refractive index for NIR reflectance were thoroughly explained by the light reflection mechanism, light interference effect, and bond length of the crystal system. The development of highly NIR reflective black single-shell hollow nanoparticles (BSS-HNPs) can overcome the Light Detection and Ranging (LiDAR) sensor limitations of dark-tone materials. The crystalline phase of TiO 2 and the refractive index can be controlled by calcination temperature. The formation of hollow structure and the refractive index is expected to simultaneously increase the light reflection and LiDAR detectability. The BSS-HNPs are synthesized using the sol–gel method, calcination, NaBH 4 reduction, and etching to form a hollow structure with true blackness. The computational bandgap calculation is conducted to determine the bandgap energy (E g) of the white and black TiO 2 with different crystalline structures. The blackness of the as-synthesized materials is determined by the Commission on Illumination (CIE) L * a * b * color system. The hydrophilic nature of BSS-HNPs enables the formulation of hydrophilic paints, allowing the mono-layer coating. With the synergistic effects of hollow structure and the refractive index, BSS-HNPs manifested superb NIR reflectance at LiDAR detection wavelengths. The high detectability, blackness, and hollow structure of BSS-HNPs can expand the variety of LiDAR-detectable dark-tone materials. [ABSTRACT FROM AUTHOR]

The development of efficient all perovskite tandem solar cells has faced challenges related to current matching and optical losses. In this work, a design of a non‐coplanar three‐terminal (3T) all perovskite tandem solar cell is presented, which consists of a p‐i‐n inverted NiOX‐based CsPbI2Br perovskite top cell, and a FA0.6MA0.4Sn0.5Pb0.5I3 perovskite bottom cell with back‐contact (BC) device structure. It effectively mitigated the optical losses introduced in non‐absorbing layers and resulted in a 2.9% absolute efficiency improvement compared to that of planar sandwich‐type 3T tandems. Both optical and electrical characteristics of the multi‐terminal tandem cells are investigated. Then, it is focused on understanding the impact of top cell thickness on overall non‐coplanar BC 3T‐tandem performance, considering low‐energy photon optical reflection and carrier transport distance. Following optimizations of energy level and device structure, an efficiency of 32.16% is achieved, with non‐coplanar BC 3T device architecture: top cell consisting of hole extraction layer (ITO/NiOx), CsPbI2Br absorber layer, and electron extraction layer (ZnO/FA0.6MA0.4Sn0.5Pb0.5I3/SnO2/Ag); and bottom cell (Ni/NiOx/FA0.6MA0.4Sn0.5Pb0.5I3/SnO2/Ag); bottom perovskite layer has two functions, one is electron transport layer for top cell, and the other is low‐energy photon absorption layer in bottom cell. It provides insight and a promising pathway for manufacturing high‐efficient all perovskite tandem solar cells. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive analysis of the orthorhombic CsCuO, focusing on its structural, electronic, mechanical, and optical properties, which uses the first‐principles plane wave pseudopotential technique and local density approximation methods based on density functional theory. The derived structural parameters closely match the previously reported experimental data. The calculated results show that CsCuO is mechanically stable and exhibits a certain toughness. Research on electronic properties shows that CsCuO is a direct‐bandgap semiconductor. Charge density and population analysis show that covalent bonds are formed between O and Cu. The optical property results show that CsCuO has good passability to incident light, indicating that CsCuO is an excellent transparent material. In the visible and infrared light regions, CsCuO has a low absorption coefficient, mainly manifested as ultraviolet absorption. Reflection is mainly distributed in the high‐energy region and does not exceed 25% in the visible light region. It can be used in fields that require less light reflection and the manufacture of medical ultraviolet disinfection equipment. [ABSTRACT FROM AUTHOR]

A high sensitivity sensor is proposed to measure axial strain, magnetic field, and refractive index. Hollow‐core fiber (HCF) and single mode fiber (SMF) are fused together to form the "SMF–HCF–SMF," then tapering HCF, and finally forming a sensor. The light in the sensor structure forms an antiresonant reflection optical waveguide mechanism. The sensor has particularly thin waist circumference, therefore the surface evanescent field of the sensor is easily affected by environmental parameters, making it particularly sensitive to environmental parameters. The axial strain sensitivity obtained by the sensor is as high as −31.87 pm/µε. The magnetic field sensitivity obtained by combining the sensor with magnetostrictive material Terfenol‐D in the range of 10–40 mT is 123.9 pm/mT. The sensor measures the refractive index of NaCl solution with a sensitivity of up to 2109.308 nm/RIU (RIU: refractive index unit). Additionally, the sensor has good stability and repeatability when measuring three physical quantities. The sensor has a compact structure, stable performance, simple manufacturing, and can measure multiple parameters in biochemical engineering, industrial structural health detection, and marine resource detection. [ABSTRACT FROM AUTHOR]

Resonances of free excitons at energies A ~ 1.0409 eV, B ~ 1.0445 eV, and C ~ 1.2690 eV were detected in reflection spectra of single crystals of the direct-gap compound CuInSe2 at a temperature of 8.6 K. The appearance of the three reflection resonances A, B, and C could be explained by removal of degeneracy from valence-band energy levels due to the influence of crystal field and spin–orbit interaction on the tetragonal lattice of CuInSe2 with ΔCF ~ 5.4 meV and ΔSO ~ 224 meV. Measurements of the temperature dependence of the reflection spectra in the range 8.6–90 K showed the energies of free-exciton resonances A and B increased because of deformation of the unit cell (tetragonal stretching) of the CuInSe2 lattice with the chalcopyrite structure. The binding energies of free excitons A and B were determined as 10.7 and 152 meV based on temperature quenching of exciton resonances A ~ 1.0409 eV and B ~ 1.0445 eV [ABSTRACT FROM AUTHOR]

Aiming to address the problem of robot path planning in environments containing narrow passages, this paper proposes a novel global path planning method: the DSR (Dual-source Light Continuous Reflection Exploration) algorithm. This algorithm, inspired by the natural reflection of light, employs the concept of continuous reflection for path planning. It can efficiently generate an asymptotically optimal path on the map containing narrow passages. The DSR algorithm has been evaluated on different maps with narrow passages and compared with other algorithms. In comparison with the bidirectional Rapidly-exploring Random Tree algorithm, the DSR algorithm achieves a significant reduction in both path length (by 27.08% and 34.35%) and time consumption (by 98.47% and 91.03%). Numerical simulations and experimental analysis have demonstrated the excellent performance of the DSR algorithm. • A novel global path planning method based on the idea of dual-source light continuous reflection is proposed. • The starting point and the target point are set as two "light sources" that can emit multiple explorative routes. • Explorative routes will have continuous reflection after encountering obstacles. • The algorithm has a powerful path planning ability on the map that contains narrow passages. [ABSTRACT FROM AUTHOR]

α-RuCl3, a narrow-band Mott insulator with a large work function, offers intriguing potential as a quantum material or as a charge acceptor for electrical contacts in van der Waals devices. In this work, we perform a systematic study of the optical reflection contrast of α-RuCl3 nanoflakes on oxidized silicon wafers and estimate the accuracy of this imaging technique to assess the crystal thickness. Via spectroscopic micro-ellipsometry measurements, we characterize the wavelength-dependent complex refractive index of α-RuCl3 nanoflakes of varying thickness in the visible and near-infrared. Building on these results, we simulate the optical contrast of α-RuCl3 nanoflakes with thicknesses below 100 nm on SiO2/Si substrates under different illumination conditions. We compare the simulated optical contrast with experimental values extracted from optical microscopy images and obtain good agreement. Finally, we show that optical contrast imaging allows us to retrieve the thickness of the RuCl3 nanoflakes exfoliated on an oxidized silicon substrate with a mean deviation of −0.2 nm for thicknesses below 100 nm with a standard deviation of only 1 nm. Our results demonstrate that optical contrast can be used as a non-invasive, fast, and reliable technique to estimate the α-RuCl3 thickness. [ABSTRACT FROM AUTHOR]

In industrial production, the orientation of facility components can indicate whether the facility is on a regular operating track. For example, when a component gets loose, the orientation variation of the component would exceed the normal range. A common approach for orientation measurement is to attach an inertial measurement unit (IMU) to the target device. However, the IMU requires additional power maintenance. This article presents LightGyro, a cheap and efficient batteryless scheme to measure the orientation, in which we attach a reflective film to the target device and use a camera to capture the light spot on the reflective film. The basic idea of LightGyro is to extract the light spots in the captured frame and use their pixel coordinates to infer the orientation. It is difficult to recognize a single light spot, because the spot lacks distinctive features. To solve the problem, we switch light sources on and off to regulate the appearance of light spots and utilize frame subtraction to extract light spots. The depth of field of light spot is lost in the process of camera projection, which is necessary for the orientation measurement. To address the issue, we propose a light array-based reflection model to extract the depth of field from the relative positions of multiple light spots. To the best of our knowledge, this is the first work to utilize reflection to measure orientation. Experiment results show that the orientation error of LightGyro decreases with the increasing length of the reflection route and the orientation error can achieve less than 1ˆ. [ABSTRACT FROM AUTHOR]

To address the technical challenge of identifying tiny defects, especially dust and point defects, on mobile phone flat glass, an automatic optical inspection system is established. The system investigates algorithms including imaging principles, target detection models, data augmentation, foreground segmentation, and image fusion. The system builds an automatic optical inspection platform to collect glass defect samples. It illuminates the glass samples with a combined total reflection–grazing light source, collects the defect sample data, segments the background and defects of the collected data, generates the defect mask, and extracts the complete defects of the cell phone flat glass. The system then seamlessly integrates the extracted defects with a flawless background using Poisson editing and outputs the location information of the defects and the label output to automatically generate the dataset. The deep learning network YOLOv5 works as the core algorithm framework, into which the Constructive Block Attention Module and the small target detection layer are specifically added to enhance the capability of the model to detect small defects. According to the experimental results, the combined lighting effectively improves the precision of detecting dust and bright spots. Additionally, with the adoption of novel data augmentation techniques, the enhanced YOLOv5 model is capable of effectively addressing the challenges posed by inefficient sample data and non-uniform distribution, thus mitigating network generalization issues. Furthermore, this data augmentation approach facilitates the rapid adaptation of the same detection tasks to diverse environmental scenarios, enabling the expedited and efficient deployment of the model across various industrial settings. The mean average precision (MAP) of the optimal model in the validation set reached 98.36%, 2.62% higher than that of the original YOLOv5. In addition, its false acceptance rate (FAR) is 1.27%, its false rejection rate (FRR) was 2.47%, its detection speed was 64 fps, and its correct detection rate in the validation set was 98.75%, which meets the current industrial detection requirements by and large. In this way, this paper achieved the automated inspection of mobile phone flat glass with high robustness, high precision, and a low false acceptance rate and false rejection rate, significantly reducing material losses in the factories and the likelihood of error occurrence in follow-on products. This method can be applied to the multi-scale and multi-type detection of glass defects. [ABSTRACT FROM AUTHOR]

Organisms often have superior abilities. For example, the moth's eyes block the reflection of light, preventing even the slightest light from escaping. Morpho butterflies have vivid colors despite their lack of pigmentation. The superhydrophobicity of lotus leaves is another example, which is attributed to their characteristic surface structure. We have recreated an interesting property by mimicking the structure of rose petals. When a drop of water falls on a rose petal, it adheres to the petal like a sphere. The droplets stay in place when the petals are inverted in this state. This phenomenon is called the rose petal effect. The surface of the petals is lined with microscale hemispherical structures, and each surface has additional nanoscale grooves. The effect is due to the hierarchical structure of nano- and microstructures. When water is dropped onto these structures, the surfaces of the nanostructures become air pockets, preventing water from entering the grooves. This results in stronger water repellency compared to that of the same material with a smooth surface. In contrast, when water penetrates the microstructure, the surface area becomes larger than that of a smooth surface, increasing adhesion. This is called the Wenzel mode. Here, we attempted to reproduce this structure on film using a combination of high-throughput techniques; ultraviolet nanoimprint lithography (UV-NIL) and roll pressing. The manufacturing process comprises two main steps. First, a nanopillar structure called a moth-eye structure is fabricated over the entire surface using UV-NIL. This serves the same purpose as the nanoglobe structure. Next, microscale holes are drilled on the surface using a roll press method. The resulting depressions immobilize water droplets and improve adhesion. Despite the strong water repellency obtained through this method, with a contact angle of more than 140±b°, up to 9 µL of water droplets remained attached to the film even when the film was turned over. Because this method can impart adhesion at any position on the water-repellent surface, it can be applied to microdroplet transport. [ABSTRACT FROM AUTHOR]

In this paper, we study terahertz generation through optical rectification in reflection at normal incidence in a dielectric nonlinear crystal. We first analyze, with a nonlinear optical model, the sample parameters (thickness, absorption at both laser and terahertz wavelengths, etc.) for which a terahertz optical rectification reflection scheme is preferable to the common transmission scheme. Then, we report our experimental observations of a reflected terahertz signal generated at the surface of a ZnTe crystal. The reflected terahertz signal shares all the characteristics of a signal generated in transmission but is not limited by absorption losses in the crystal, thereby providing a broader bandwidth. At high pump laser power, the signal exhibits saturation, which is caused by the decrease of the nonlinear susceptibility due to photocarriers generated by two-photon absorption. This reflection scheme could be of great importance for terahertz microscopy of opaque materials like, e.g., humid samples or samples exhibiting strong absorption bands or to study samples for which the transmitted signal cannot be recorded. [ABSTRACT FROM AUTHOR]

Automated testing of GUI elements on electronic screens by machine vision is widely used in smart manufacturing production lines. However, in the complex environment of factories, interference factors such as light reflection, platform vibration, and placement angle make it difficult for testing robots to recognize and locate GUI elements on the equipment's screen to be tested. In addition, the recognition algorithms based on screen GUI elements currently have problems such as slow detection speed and large model size, which limit the deployment of detection models on test robots. To address these problems, this paper proposes a lightweight model that can overcome the interference of the factory environment based on the YOLOv5 algorithm for recognizing GUI elements. First, a reinforced position and channel attention module (PCA) is proposed to enhance the extraction and fusion ability of weak feature elements affected by interference; then, a three-way feature pyramid network (TWFPN) module is constructed at the intermediate feature layer of the neck structure to provide more accurate localization information. Meanwhile, the loss function of the original algorithm is replaced with SIoU to improve the convergence speed. Finally, a lightweight structure combining the Ghost module and PConv is introduced into the model to reduce the model parameters and improve the detection speed. The method was evaluated on the constructed feature-enhanced GUI (FE_GUI) dataset. The final model shows a 2.7% improvement in average accuracy (mAP@0.5), a 30% reduction in model weight, and an increase in detection speed to 85 FPS compared to the original YOLOv5. The results demonstrate that the method solves the issues of element recognition and model deployment for a vision test system and surpasses existing models in terms of recognition accuracy and detection speed. [ABSTRACT FROM AUTHOR]

Planar assemblies of plasmonic nanoparticles have been extensively used for surface-enhanced Raman scattering (SERS) applications. Understanding the assembly of nanoparticles helps us to fabricate desired sensing substrates. In the current study, we develop a technique for monitoring the assembly of gold nanoparticles (AuNPs) in real-time using optical reflection spectroscopy. The system is integrated with a flow cell enabling the control of the assembly kinetics. The effect of flow velocity on the assembly kinetics is elucidated via monitoring the reflection spectrum. For low AuNP density, the reflection spectrum shows a dip close to 522 nm, whereas for higher densities, a prominent peak is observed close to 550 nm. For a fixed assembly time, the density of particles monotonically increases by increasing the flow rate. The signatures of the particle assembly from the experiments are compared to the computationally derived reflection spectra to understand their underlying origins. The transition from a dip to a peak as a function of density is shown to arise because of destructive and constructive interference from the various interfaces. Furthermore, we demonstrate that the assembly of AuNPs within flow cells is more efficient and rapid as compared to the immersion technique. Finally, the applicability of the in situ prepared substrates for SERS applications was determined using mercapto-benzoic acid as a Raman reporter molecule, and concentrations as low as 0.196 μM could be measured with the fabricated sensor. The proposed real-time tracking method can be used for realizing ultrasensitive SERS-based sensors tailor-made for a specific sensing application. [ABSTRACT FROM AUTHOR]

Aluminum (Al) toxicity is an important factor restricting the normal growth of plants in acidic soil. Rhododendron (Ericaceae) can grow relatively well in acidic soil. To uncover the adaptive mechanisms of photosynthesis under Al stress, the influence of Al stress on the photosynthetic activities of Al-sensitive (Baijinpao) and Al-resistant (Kangnaixin) rhododendron cultivars was examined by measuring gas exchange, chlorophyll fluorescence, and the modulated reflection of light at 820 nm. Under Al stress conditions, the net photosynthetic rate and stomatal conductance of the rhododendron leaves decreased, whereas the intercellular CO2 concentration increased. The Al stress treatment damaged the oxygen-evolving complex of the rhododendron seedlings, while also inhibiting electron transport on the photosystem II (PSII) donor side. In addition, the exposure to Al stress restricted the oxidation of plastocyanin (PC) and the photosystem I (PSI) reaction center (P700) and led to the re-reduction of PC+ and P700+. The comparison with Kangnaixin revealed an increase in the PSII connectivity in Baijinpao. Additionally, the donor-side electron transport efficiency was more inhibited and the overall activity of PSII, PSI, and the intersystem electron transport chain decreased more extensively in Baijinpao than in Kangnaixin. On the basis of the study findings, we concluded that Al stress adversely affects photosynthesis in rhododendron seedlings by significantly decreasing the activity of PSII and PSI. Under Al stress, Kangnaixin showed stronger tolerance compared with Baijinpao. [ABSTRACT FROM AUTHOR]

We present light measurements in Arctic sea ice obtained during the year-long MOSAiC drift through the central Arctic Ocean in 2019–2020. Such measurements are important as sea ice plays a fundamental role in the Arctic climate and ecosystem. The partitioning of solar irradiance determines the availability of radiation energy for thermodynamic processes and primary productivity. However, observations of light partitioning along the vertical path through the ice are rare. The data we present were collected by two measurement systems, the lightharp and the lightchain, both measuring autonomously multi-spectral light intensity in different depths within the ice. We present the dataset, retrieval methods for derived optical properties, and the conversion into the final, freely available data product, following standardized conventions. We particularly focus on the specifications of the newly developed lightharp system. Combined with the interdisciplinary and multi-instrument setup of MOSAiC, we expect great potential of the dataset to foster our understanding of light transmission and reflection in the sea-ice cover and interactions with physical sea-ice properties and the polar ecosystem. [ABSTRACT FROM AUTHOR]

Converting non‐visual light into photocurrent while maintaining high visual transparency is vital for semitransparent organic solar cells (ST‐OSCs) application, yet often challenging over insufficient invisible light‐harvesting. Herein, spectrally selective optical manipulation for ST‐OSCs with high visual light transparency and full‐spectral non‐visual light reflection is proposed by matching the optical admittance of ultrathin Ag films using ZnS and MgF2. The reflection of optically enhanced ST‐OSCs at the spectral region beyond the human eye's response spectrum is improved and the transmission in the visual region is simultaneously enhanced. By further integrating an anti‐reflective structure, the optimal structure boosts the average visible transmittance and power conversion efficiency of ST‐OSCs to 44.3% and 12.6%, respectively, yielding a record light utilization efficiency of 5.6%. Corresponding flexible ST‐OSCs with high mechanical stability implies that this work provides a facile and universal strategy for ST‐OSCs aiming at building integrated photovoltaics. [ABSTRACT FROM AUTHOR]

Perfect light transmission into a dielectric at the Brewster angle is one of the simplest effects of macroscopic electromagnetism. The common wisdom states that absorption in the dielectric violates Brewster angle and leads to a non‐vanishing reflection. Yet, incorporating anisotropy may recover perfect transmission of p‐polarized light into the absorbing medium. Unlike the ordinary "lossless" Brewster angle, perfect transmission in this case is accompanied by phase singularities of the reflection amplitude. In this paper, phase singularities and the associated topological charges are theoretically examined as emerging in the wavelength‐incidence angle space upon perfect transmission into absorbing uniaxial dielectrics. The analytical criterion of perfect light transmission into an anisotropic medium is derived, phase singularities are demontrated in these scenarios, and their dynamics are studied as a function of material parameters. Finally, by lowering the symmetry of the problem, this phenomenon is translated into a different parameter space of wave vector components, and illustrate the feasibility of this phenomenon with available optically anisotropic materials. The results may become valuable for the development of novel analog computing schemes and holography approaches. [ABSTRACT FROM AUTHOR]

In this study, we enhanced odometry performance by integrating vision sensors with LiDAR sensors, which exhibit contrasting characteristics. Vision sensors provide extensive environmental information but are limited in precise distance measurement, whereas LiDAR offers high accuracy in distance metrics but lacks detailed environmental data. By utilizing data from vision sensors, this research compensates for the inadequate descriptors of LiDAR sensors, thereby improving LiDAR feature matching performance. Traditional fusion methods, which rely on extracting depth from image features, depend heavily on vision sensors and are vulnerable under challenging conditions such as rain, darkness, or light reflection. Utilizing vision sensors as primary sensors under such conditions can lead to significant mapping errors and, in the worst cases, system divergence. Conversely, our approach uses LiDAR as the primary sensor, mitigating the shortcomings of previous methods and enabling vision sensors to support LiDAR-based mapping. This maintains LiDAR Odometry performance even in environments where vision sensors are compromised, thus enhancing performance with the support of vision sensors. We adopted five prominent algorithms from the latest LiDAR SLAM open-source projects and conducted experiments on the KITTI odometry dataset. This research proposes a novel approach by integrating a vision support module into the top three LiDAR SLAM methods, thereby improving performance. By making the source code of VA-LOAM publicly available, this work enhances the accessibility of the technology, fostering reproducibility and transparency within the research community. [ABSTRACT FROM AUTHOR]

The remote monitoring of vital signs via wearable devices holds significant potential for alleviating the strain on hospital resources and elder-care facilities. Among the various techniques available, photoplethysmography stands out as particularly promising for assessing vital signs such as heart rate, respiratory rate, oxygen saturation, and blood pressure. Despite the efficacy of this method, many commercially available wearables, bearing Conformité Européenne marks and the approval of the Food and Drug Administration, are often integrated within proprietary, closed data ecosystems and are very expensive. In an effort to democratize access to affordable wearable devices, our research endeavored to develop an open-source photoplethysmographic sensor utilizing off-the-shelf hardware and open-source software components. The primary aim of this investigation was to ascertain whether the combination of off-the-shelf hardware components and open-source software yielded vital-sign measurements (specifically heart rate and respiratory rate) comparable to those obtained from more expensive, commercially endorsed medical devices. Conducted as a prospective, single-center study, the research involved the assessment of fifteen participants for three minutes in four distinct positions, supine, seated, standing, and walking in place. The sensor consisted of four PulseSensors measuring photoplethysmographic signals with green light in reflection mode. Subsequent signal processing utilized various open-source Python packages. The heart rate assessment involved the comparison of three distinct methodologies, while the respiratory rate analysis entailed the evaluation of fifteen different algorithmic combinations. For one-minute average heart rates' determination, the Neurokit process pipeline achieved the best results in a seated position with a Spearman's coefficient of 0.9 and a mean difference of 0.59 BPM. For the respiratory rate, the combined utilization of Neurokit and Charlton algorithms yielded the most favorable outcomes with a Spearman's coefficient of 0.82 and a mean difference of 1.90 BrPM. This research found that off-the-shelf components are able to produce comparable results for heart and respiratory rates to those of commercial and approved medical wearables. [ABSTRACT FROM AUTHOR]

The paper deals with the optical radiation interaction with solids. It is shown that none of the existing ideas about the light reflection gives explanations to the known phenomena arising from the interaction between optical radiation and a solid. It is suggested that the optical radiation reflection is a collective process associated with the self-organization of electrons with a photon. This suggestion explains a number of physical phenomena that have not been explained before, for example, the Goos–Hänchen and Imbert–Fedorov beam shifts, which are natural processes in such representation of reflection. [ABSTRACT FROM AUTHOR]

Nanofibrous membranes, characterized by their flexibility, high porosity, and tunable structure, are emerging as a promising contender for advanced transparent materials with sufficient breathability and pliability. However, the considerable surface light reflection and internal light scattering of nanofibrous membranes pose a challenging task in achieving transparency. In this study, transparent nanofibrous membranes are fabricated by constructing a topological structure with optimized optical transmission channels, which provide the minimum equivalent thickness to minimize light loss in nanofibrous membranes. The resultant fabricated membrane exhibits a high light transmittance of up to 81%, along with a sufficient porosity of 84% and flexibility. Additionally, the membrane demonstrated effective PM0.3–10 removal efficiency (>91%), low air pressure drops (<110 Pa), high air permeability (≈104 mm s−1), and good waterproof performance. Therefore, the prepared transparent nanofibrous membrane may serve as a transparent air filtration window screen to enhance indoor comfort for people. [ABSTRACT FROM AUTHOR]

This article provides an updated review of advances in the field of mirror-based laser beam deflectors, including laser scanners. We propose a taxonomy of these techniques based mainly on the principle of operation, and we direct the reader to the literature related to the individual subgroups of deflectors and to some of the most representative examples. This review is limited to the continuous or quasi-continuous mode of operation. The following techniques for steering mirror deflection are distinguished: electromagnetic, piezo, electrothermal, electrostatic and pressure actuators. Electromagnetic voice coils and piezo deflectors form one subgroup of fast steering mirror techniques. The main technical parameters and the useable properties of each group of techniques are specified. This review forms the first part of a general overview of laser beam deflectors, which will continue with a review of refractive and diffraction deflectors. [Display omitted] • The first part of a general overview of laser beam deflectors, which will next cover refractive and diffraction deflectors. • Actualised overview of advances in specular reflection by light laser beam deflectors, including laser scanners. • New approach and taxonomy of the presented techniques. • References to the earlier reviews of subgroups. • Main steering mirror techniques distinguished: electromagnetic, piezo, electrothermal, electrostatic and pressure actuators. [ABSTRACT FROM AUTHOR]

Recently, UVC LEDs, which emit deep ultraviolet light, have found extensive applications across various fields. This study demonstrates the design and implementation of thin films of three-dimensional photonic crystals (3D PhCs) as reflectors to enhance the light output power (LOP) of UVC LEDs. The 3D PhC reflectors were prepared using the self-assembly of silica nanospheres on a UVC LED lead frame substrate via the evaporation-induced method (side) and the gravitational sedimentation method (bottom), respectively. These PhCs with the (111) crystallographic plane were deposited on the side wall and bottom of the UVC LED lead frame, acting as functional materials to reflect UVC light. The LOP of UVC LEDs with 3D PhC reflectors at a driving current of 100 mA reached 19.6 mW. This represented a 30% enhancement compared to commercial UVC LEDs with Au-plated reflectors, due to the UVC light reflection by the photonic band gaps of 3D PhCs in the (111) crystallographic plane. Furthermore, after aging tests at 60 °C and 60% relative humidity for 1000 h, the relative LOP of UVC LEDs with 3D PhC reflectors decreased by 7%, which is better than that of commercial UVC LEDs. Thus, this study offers potential methods for enhancing the light output efficiency of commercial UVC light-emitting devices. [ABSTRACT FROM AUTHOR]

Coating thickness is a critical quality attribute of many coated tablets. Functional coatings ensure correct drug release kinetics or protection from light, while non-functional coatings are generally applied for cosmetic reasons. Traditionally, coating thickness is assessed indirectly via offline methods, such as weight gain or diameter growth. In the past decade, several methods, including optical coherence tomography (OCT) and Raman spectroscopy, have emerged to perform in-line measurements of various subclasses of coating formulations. However, there are some obstacles. For example, when using OCT, a major challenge is scattering pigments, such as titanium dioxide and iron oxide, which make the interface between the coating and the tablet core difficult to detect. This work explores novel OCT image evaluation techniques using unsupervised machine learning to compute image metrics. Certain image metrics of highly scattering coatings are correlated with the tablet thickness, and hence indirectly with the coating thickness. The method was demonstrated using a titanium dioxide rich coating formulation. The results are expected to be applicable to other scattering coatings and will significantly broaden the applicability of OCT to at-line and in-line coating thickness measurements of a much larger class of coating formulations. [Display omitted] • Optical coherence tomography for indirect coating thickness measurement of highly scattering coatings. • Machine learning for image analysis to extract and quantify light reflection. • Non-destructive coating thickness measurement through light reflection properties. [ABSTRACT FROM AUTHOR]

Structured light with multiple degrees of freedom has inspired many advanced applications, and its nonlinear control plays an important role in the interactions between light and matter. Stimulated Brillouin scattering (SBS) based on light–sound coupling can be used to realize wavefront‐reversal nonlinear reflection of ordinary light; consequently, it is used to correct wavefront aberrations in high‐power laser systems. However, high‐fidelity wavefront reversal of structured light with orbital angular momentum and high‐reflectivity single‐end SBS of weak incident waves remain challenging. Here, the authors propose a cross‐pump focused SBS scheme that enables wavefront reversal with high fidelity, low threshold, and high reflectivity for arbitrary structured light. The authors demonstrate the capability of this approach to perform conformal and enhanced SBS reflections with a fidelity of >95% and reflectivity of >100%. Compared with the conventional focused SBS configuration, the SBS threshold is reduced by more than ten times, and wavefront reversal of weakly structured light is realized. This proof‐of‐principle study provides a high‐performance SBS platform with potential implications for high‐power structured lasers, high signal‐to‐noise‐ratio microscopy imaging, and the development of nonlinear optics with structured light. [ABSTRACT FROM AUTHOR]

In recent years, hypertension has become one of the leading causes of illness and death worldwide. Changes in lifestyle among the population have led to an increasing prevalence of hypertension. This study proposes a non-contact blood pressure estimation method that allows patients to conveniently monitor their blood pressure values. By utilizing a webcam to track facial features and the region of interest (ROI) for obtaining forehead images, independent component analysis (ICA) is employed to eliminate artifact signals. Subsequently, physiological parameters are calculated using the principle of optical wave reflection. The Nelder–Mead (NM) simplex method is combined with the particle swarm optimization (PSO) algorithm to optimize the empirical parameters, thus enhancing computational efficiency and accurately determining the optimal solution for blood pressure estimation. The influences of light intensity and camera distance on the experimental results are also discussed. Furthermore, the measurement time is only 10 s. The superior accuracy and efficiency of the proposed methodology are demonstrated by comparing them with those in other published literature. [ABSTRACT FROM AUTHOR]

As LEDs continue to miniaturize, in addition to the side‐wall defect effect causing a decrease in LED luminous efficiency, the reduction in LED size also leads to the emergence of downward and lateral light emission. These non‐forward emissions are prone to total internal reflection and significant refraction at interfaces between packaging layers and air, consequently diminishing forward light emission. To mitigate the loss of forward luminance and ambient light reflection, we propose a secondary‐optical design and simulate the physical model by commercial software. The simulation result shows that the loss was reduced from 40.06% to 18.51% with Hexagonal Structure, and the ambient light reflection was reduce from 25.41% to 4.78%. With the addition of microlens array, loss can be further reduced to 2.67%, and ambient light reflection was reduced to 5.34%. [ABSTRACT FROM AUTHOR]

Shrinking LEDs reduces Internal Quantum Efficiency (IQE) and challenges light collection[1]. This study employs LightTools® for geometric optical simulations to create a secondary optical structure with reflector and a black matrix, enhancing Micro‐LED efficiency. This approach significantly reduces light emission loss from the original 40% to 4.54%. and ambient light reflection from the original 25% to 4.85%. [ABSTRACT FROM AUTHOR]

Current low-light image enhancement techniques prioritize increasing image luminance but fail to address issues including loss of intricate distortion of colors and image details. In order to address these issues that has been overlooked by all parties, this paper suggests a multi-module optimization network for enhancing low-light images by integrating deep learning with Retinex theory. First, we create a decomposition network to separate the lighting components and reflections from the low-light image. We incorporated an enhanced global spatial attention (GSA) module into the decomposition network to boost its flexibility and adaptability. This module enhances the extraction of comprehensive information from the image and safeguards against information loss. To increase the illumination component's luminosity, we subsequently constructed an enhancement network. The Multiscale Guidance Block (MSGB) has been integrated into the improvement network, together with multilayer extended convolution to expand the sensing field and enhance the network's capability for feature extraction. Our proposed method out-performs existing ways in both objective measures and personal evaluations, emphasizing the virtues of the procedure outlined in this paper. [ABSTRACT FROM AUTHOR]

Organic photothermal materials have attracted increasing attention because of their structural diversity, flexibility, and compatibility. However, their energy conversion efficiency is limited owing to the narrow absorption spectrum, strong reflection/transmittance, and insufficient nonradiative decay. In this study, two quinoxaline‐based D–A‐D–A‐D‐type molecules with ethyl (BQE) or carboxylate (BQC) substituents were synthesized. Strong intramolecular charge transfer provided both molecules with a broad absorption range of 350–1000 nm. In addition, the high reorganization energy and weak molecular packing of BQE resulted in efficient nonradiative decay. More importantly, the self‐assembly of BQE leads to a textured surface and enhances the light‐trapping efficiency with significantly reduced light reflection/transmittance. Consequently, BQE achieved an impressive solar‐thermal conversion efficiency of 18.16 % under 1.0 kW m−2 irradiation with good photobleaching resistance. Based on this knowledge, the water evaporation rate of 1.2 kg m−2 h−1 was attained for the BQE‐based interfacial evaporation device with an efficiency of 83 % under 1.0 kW m−2 simulated sunlight. Finally, the synergetic integration of solar‐steam and thermoelectric co‐generation devices based on BQE was realized without significantly sacrificing solar‐steam efficiency. This underscores the practical applications of BQE‐based technology in effectively harnessing photothermal energy. This study provides new insights into the molecular design for enhancing light‐trapping management by molecular self‐assembly, paving the way for photothermal‐driven applications of organic photothermal materials. [ABSTRACT FROM AUTHOR]

Real-time and accurate location detection is a key link to ensure the safety of operating machines and workers in production and life. Compared with traditional static multi-anchor nodes, mobile anchor node assisted localization is greener and more energy-saving. In this paper, we first propose a static trajectory based on a light reflection model. Compared with other static models, this model has fewer times in the field, overcomes the collinearity problem and uniform beacon distribution, and ensures that all sensor nodes can receive good enough beacon quality for localization. Secondly, an RSSI-based improved weighted centroid localization algorithm and an RSSI-based improved weighted centroid collaborative localization algorithm are proposed. The two-strategy optimal location beacon set screening method is used to reduce location misjudgment. In order to improve the accuracy of centroid localization, a weighted centroid localization algorithm based on distance and hop number is designed. Moreover, a collaborative localization strategy is aiming at improving beacon density. Experimental results show that both the algorithm and static trajectory can guarantee better beacon coverage rate and localization success rate under different experimental conditions, and at the same time have higher accuracy. [ABSTRACT FROM AUTHOR]

Copyright of lnternational Journal of Geography & Geography Education is the property of Marmara University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Knowledge of a person's level of skin pigmentation, or so-called "skin tone", has proven to be an important building block in improving the performance and fairness of various applications that rely on computer vision. These include medical diagnosis of skin conditions, cosmetic and skincare support, and face recognition, especially for darker skin tones. However, the perception of skin tone, whether by the human eye or by an optoelectronic sensor, uses the reflection of light from the skin. The source of this light, or illumination, affects the skin tone that is perceived. This study aims to refine and assess a convolutional neural network-based skin tone estimation model that provides consistent accuracy across different skin tones under various lighting conditions. The 10-point Monk Skin Tone Scale was used to represent the skin tone spectrum. A dataset of 21,375 images was captured from volunteers across the pigmentation spectrum. Experimental results show that a regression model outperforms other models, with an estimated-to-target distance of 0.5. Using a threshold estimated-to-target skin tone distance of 2 for all lights results in average accuracy values of 85.45% and 97.16%. With the Monk Skin Tone Scale segmented into three groups, the lighter exhibits strong accuracy, the middle displays lower accuracy, and the dark falls between the two. The overall skin tone estimation achieves average error distances in the LAB space of 16.40 ± 20.62 . [ABSTRACT FROM AUTHOR]

Hollow cubic nanoheterojunction in SnS 2 /CdS is obtained via in situ sulfuration-hydrothermal-chemical deposition. The SnS 2 /CdS nanoheterojunction (SnS 2 /CdS-3) exhibits remarkable enhanced photocatalytic HER (∼1424.56 μmol g−1 h−1) and photodegradation than normal CdS (∼72/∼28 folds) and SnS 2 (∼148/∼29 folds). In this structure, the SnS 2 /CdS heterojunction with greater Fermi levels gradient can promote interface carrier drive to optimize carrier efficiency, the hollow cubic structure can provide numerous active sites to decreased overpotential and promote electron diffusion, and increase light reflections, including inhibiting photocorrosion and maintaining structural stability. [Display omitted] • Heterojuction with greater Fermi levels gradient can optimize carrier efficiency. • Hollow cubic structure can increase active sites to promote electron diffusion. • Hollow cubic structure can shorten carrier pathway to inhibit photocorrosion. [ABSTRACT FROM AUTHOR]

To develop novel inorganic red pigments without harmful elements, we focused on the band structure of Ca2(Mg, Co)WO6 and attempted to narrow its bandgap by replacing the W6+ sites in the host structure of Mo6+. Ca2Mg1−xCoxW1−yMoyO6 (0.10 ≤ x ≤ 0.30; 0.45 ≤ y ≤ 0.60) samples were synthesized by a sol-gel method using citric acids, and the crystal structure, optical properties, and color of the samples were characterized. The Ca2Mg1−xCoxW1−yMoyO6 solid solution was successfully formed, which absorbed visible light at wavelengths below 600 nm. In addition, the absorption wavelength shifted to longer wavelengths with increasing Mo6+ content. This is because a new conduction band composed of a Co3d-W5d-Mo4d hybrid orbital was formed by Mo6+ doping to reduce the bandgap energy. Thus, the color of the samples gradually changed from pale orange to dark red, with a hue angle (h°) of less than 35°. Based on the above results, the optical absorption wavelength of the Ca2Mg1−xCoxW1−yMoyO6 system can be controlled to change the color by adjusting the bandgap energy. [ABSTRACT FROM AUTHOR]

The interaction of rarefied gases with functionalized surfaces is of great importance in technical applications such as gas separation membranes and catalysis. To investigate the influence of functionalization and rarefaction on gas flow rate in a defined geometry, pressure-driven gas flow experiments with helium and carbon dioxide through plain and alkyl-functionalized microchannels are performed. The experiments cover Knudsen numbers from 0.01 to 200 and therefore the slip flow regime up to free molecular flow. To minimize the experimental uncertainty which is prevalent in micro flow experiments, a methodology is developed to make optimal use of the measurement data. The results are compared to an analysis-based hydraulic closure model (ACM) predicting rarefied gas flow in straight channels and to numerical solutions of the linearized S-model and BGK kinetic equations. The experimental data shows that if there is a difference between plain and functionalized channels, it is likely obscured by experimental uncertainty. This stands in contrast to previous measurements in smaller geometries and demonstrates that the surface-to-volume ratio of 0.4 μ m - 1 seems to be too small for the functionalization to have a strong influence and highlights the importance of geometric scale for surface effects. These results also shed light on the molecular reflection characteristics described by the TMAC. [ABSTRACT FROM AUTHOR]

In nature, leafhoppers cover their body surfaces with brochosomes as a protective coating. These leafhopper-produced brochosomes are hollow, buckyball-shaped, nanoscopic spheroids with through-holes distributed across their surfaces, representing a class of deployable optical materials that are rare in nature. Despite their discovery in the 1950s, it remains unknown why the sizes of brochosomes and their through-holes consistently fall within the range of hundreds of nanometers across different leafhopper species. Here, we demonstrate that the hierarchical geometries of brochosomes are engineered within a narrow size range with through-hole architecture to significantly reduce light reflection. By utilizing two-photon polymerization three-dimensional printing to fabricate high-fidelity synthetic brochosomes, we investigated the optical form-to-function relationship of brochosomes. Our results show that the diameters of brochosomes are engineered within a specific size range to maximize broadband light scattering, while the secondary through-holes are designed to function as short-wavelength, low-pass filters, further reducing light reflection. These synergistic effects enable brochosomes to achieve a substantial reduction in specular reflection, by up to approximately 80 to 94%, across a broadband wavelength range. Importantly, brochosomes represent a biological example demonstrating short-wavelength, low-pass filter functionality. Furthermore, our results indicate that the geometries of natural brochosomes may have evolved to effectively reduce reflection from ultraviolet to visible light, thereby enabling leafhoppers to evade predators whose vision spectrum encompasses both ultraviolet and visible light. Our findings offer key design insights into a class of deployable bioinspired optical materials with potential applications in omnidirectional antireflection coatings, optical encryption, and multispectral camouflage. [ABSTRACT FROM AUTHOR]

This paper introduces a novel and cost-effective method for detecting adulterated diesel, specifically targeting contamination with kerosene, by leveraging machine learning and the refractive index values of mixed diesel samples. It proposes a laser-based sensor, employing COMSOL simulations for synthetic data generation to facilitate machine learning training. This innovative approach not only streamlines the detection process by eliminating the need for expensive equipment and specialized personnel but also enables on-site testing without extensive sample preparation. The sensor's design, utilizing light refraction and reflection principles, allows for the accurate measurement of diesel adulteration levels. Validation results showcase the machine learning models' high precision in predicting adulteration percentages, as evidenced by an R-squared value of 0.999 and a mean absolute error of 0.074. This research signifies a leap in sensor technology, offering a practical solution for rapid diesel adulteration detection, especially in developing countries, by minimizing reliance on advanced laboratory analyses. The sensor's design aligns with the requirements for low-cost IoT technology, presenting a versatile tool for various applications. [ABSTRACT FROM AUTHOR]

Efficient energy transfer is crucial in electromagnetic communication. Therefore, producing a waveguide coupler that achieves broadband, nonreflective transmission is a challenging task. With the advancement of silicon-based integrated photonic circuits, fiber-to-chip coupling has become increasingly important. Although various couplers have been developed for fiber-to-chip coupling, they often have limitations such as long coupling length, low coupling efficiency, and narrow bandwidth. This is due to the inability to eliminate reflections between the two waveguides. Here, we introduce a method using universal impedance matching theory and transformation optics to eliminate reflections between two waveguides. The coupler, called the universal impedance matching coupler, using this method has the shortest subwavelength coupling length, a 99.9 % coupling efficiency, and a broad bandwidth. [ABSTRACT FROM AUTHOR]

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Photovoltaics (PVs) on building facades, either building‐integrated or building‐attached, offer a large energy yield potential especially in densely populated urban areas. Targeting this potential requires the availability of planning tools such as insolation forecasts. However, calculating the PV potential of facade surfaces in an urban environment is challenging. Complex time‐dependent shadowing and light reflections must be considered. In this contribution, we present fast ray tracing calculations for insolation forecasts in large urban environments using clustering of Sun positions into typical days. We use our approach to determine time resolved PV capacity factors for rooftops and facades in a wide variety of environments, which is particularly useful for energy system analyses. The advantage of our approach is that the determined capacity factors for one geographic location can be easily extended to larger geographic regions. In this contribution, we perform calculations in three exemplary environments and extend the results globally. Especially for facade surfaces, we find that there is a pronounced intra‐day and also seasonal distribution of PV potentials that strongly depends on the degree of latitude. The consideration of light reflections in our ray tracing approach causes an increase in calculated full load hours for facade surfaces between 10% and 25% for most geographical locations. [ABSTRACT FROM AUTHOR]