Strong Light Source Research Articles

Estimation of nighttime PM2.5 concentrations over Seoul using Suomi NPP/VIIRS Day/Night Band

With rapid economic development and urban growth, Seoul experiences severe air pollution due to fine particulate matter with an aerodynamic diameter of ≤2.5 μm (PM2.5), which is detrimental to human health. Although recent studies have extensively focused on estimating daytime PM2.5 concentrations using various types of satellite data, there remains a significant lack of research on nighttime PM2.5 estimations. This study estimated nighttime PM2.5 in Seoul from December 2018 to November 2019 using multiple linear regression (MLR) and random forest (RF) models. These models, which incorporated data on radiance, moon illumination fraction, and terrain height from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) on board the Suomi National Polar-orbiting Partnership satellite covering all moon phases, also utilized meteorological data from the ERA5 reanalysis by the European Centre for Medium-Range Weather Forecasts (ECMWF). To address multicollinearity, seasonal models were developed using forward stepwise regression and variance inflation factor analysis. DNB radiance analysis indicates that the high intensity of artificial light sources in Seoul significantly reduces the impact of moonlight, leading to notable changes in the DNB radiation associated with PM2.5 concentrations. Consequently, this study estimated nighttime PM2.5 over Seoul across all moon phases. These estimates were then validated through 10-fold cross-validation. The RF model exhibited superior accuracy, with a coefficient of determination (R2) of 0.65–0.90, compared to MLR, with R2 of 0.15–0.50, reflecting seasonal fluctuations in the model performance. The developed models can be applied to estimate reliable nighttime PM2.5 concentrations in megacities with strong artificial light sources, utilizing a comprehensive dataset from satellite observations for all moon phases. Additionally, our findings can serve as scientific data for establishing environmental policies by providing valuable insights into understanding air pollution primarily caused by PM2.5.

Hybrid six sigma based on recursive kalman filter and weibull distribution to estimate the lifespan of Bulb LEDs

The durability of LED bulbs ensures that the lights can operate for a long time without needing to be replaced or maintained too often. The brightness of high-power LED bulbs provides a strong and efficient light source, saves energy, and has a long lifespan. The traditional method of testing LED bulb life span has limitations such as long testing time, limited accuracy, high cost, inability to predict accurately, and failure to respond quickly. Therefore, the development of new and improved testing methods is necessary to effectively and accurately evaluate and ensure the durability of LED bulbs. This research paper proposes a hybrid Six Sigma method based on the recursive Kalman filter and Weibull distribution to estimate the lifespan of Bulb LEDs. The goal of the new method for evaluating LED bulb life is to provide accurate, reliable, and multi-dimensional information about the life of LED lamps, meeting the requirements of accuracy, diversity, time-saving, resources, credibility, and the ability to evaluate from a variety of perspectives. As a result of the research, the recursive Kalman filter method has strengths such as high accuracy, flexibility, saving computational resources, the ability to handle inaccurate data, and scalability. When applied to LED bulb life assessment, it provides an accurate and reliable estimate of LED lamp life. Research results on longevity testing were reduced from 1650 h to 710 h. The end-of-life test time is 710 h, and the aging time per life test cycle is 135 h. The cost of life testing is reduced from 2100.17 USD to 410.12 USD. This LED bulb lifespan testing method can be applied to similar types of LED products to improve the company's productivity and business efficiency.

Flare Removal Model Based on Sparse-UFormer Networks.

When a camera lens is directly faced with a strong light source, image flare commonly occurs, significantly reducing the clarity and texture of the photo and interfering with image processing tasks that rely on visual sensors, such as image segmentation and feature extraction. A novel flare removal network, the Sparse-UFormer neural network, has been developed. The network integrates two core components onto the UFormer architecture: the mixed-scale feed-forward network (MSFN) and top-k sparse attention (TKSA), creating the sparse-transformer module. The MSFN module captures rich multi-scale information, enabling the more effective addressing of flare interference in images. The TKSA module, designed with a sparsity strategy, focuses on key features within the image, thereby significantly enhancing the precision and efficiency of flare removal. Furthermore, in the design of the loss function, besides the conventional flare, background, and reconstruction losses, a structural similarity index loss has been incorporated to ensure the preservation of image details and structure while removing the flare. Ensuring the minimal loss of image information is a fundamental premise for effective image restoration. The proposed method has been demonstrated to achieve state-of-the-art performance on the Flare7K++ test dataset and in challenging real-world scenarios, proving its effectiveness in removing flare artefacts from images.

Bright Tripartite Quantum Steering Generated by Above‐Threshold Optical Parametric Oscillation

AbstractEinstein–Podolsky–Rosen (EPR) steering is the key resources in quantum information processing. EPR steering light sources typically obtained through spontaneous parametric down conversion below a threshold are relatively weak. Strong bright EPR steering light source can be obtained by operating the resonant cavity above the threshold. Here, the quantum steering correlations of the system above the threshold are analyzed using numerical simulations based on the quantum random trajectory method in Wigner representation. By employing the genuine multipartite EPR steering criterion, it is demonstrated that genuine bright tripartite EPR steering can be generated above the threshold, and investigate the influences of the nonlinear parameters on the genuine tripartite EPR steering. The scheme of bright EPR steering light source generated by cascaded nonlinear process can be used as a quantum repeater in quantum communication.

Phase retrieval algorithm applied to high-energy ultrafast lasers.

A standardized phase retrieval algorithm is presented and applied to an industry-grade high-energy ultrashort pulsed laser to uncover its spatial phase distribution. We describe in detail how to modify the well-known algorithm in order to characterize particularly strong light sources from intensity measurements only. With complete information about the optical field of the unknown light source at hand, virtual back propagation can reveal weak points in the light path such as apertures or damaged components.

Enzyme characterization of lactic acid bacteria isolated from duck excreta.

The production of lignocellulosic biomass waste in the agricultural sector of Indonesia is quite high annually. Utilization of lignocellulosic biomass waste through fermentation technology can be used as feed and biofuel. Fermentation technology requires the involvement of micro-organisms such as bacteria (lactic acid bacteria or LAB). LABs can be isolated from various sources, such as duck excreta. However, there have not been many reports of LAB from duck excreta. The present study aimed to characterize LAB enzymes isolated from duck excreta and obtain LAB enzymes with superior fermentation properties. A total of 11 LAB cultures obtained from duck excreta in Yogyakarta, Indonesia, were tested. Enzyme characterization of each LAB was performed using the API ZYM kit (BioMérieux, Marcy-I'Etoile, France). The bacterial cell suspension was dropped onto the API ZYM™ cupule using a pipette and incubated for 4 h at 37°C. After incubation, ZYM A and ZYM B were dripped onto the API ZYM cupule, and color changes were observed for approximately 10 s under a strong light source. Esterase activity was moderate for all LABs. The activity of α-chymotrypsin, β-glucuronidase, α-fucosidase, and α-mannosidase was not observed in a total of 10 LAB. The phosphohydrolase and amino peptidase enzyme activity of seven LABs was strong. Only six LAB samples showed protease activity. The glycosyl hydrolase (GH) activity was observed in a total of 8 LAB, while the activity of 2 LAB was strong (Lactococcus lactis subsp. lactis K5 and Lactobacillus brevis M4A). A total of 2 LABs have superior properties. L. lactis subsp. lactis K5 and L. brevis M4A have a high potential to be used in fermentation. They have the potential for further research, such as their effectiveness in fermentation, lignocellulose hydrolysis, feed additives, molecular characterization to detect specific enzymes, and their specific activities.

Caries prevalence and other dental pathological conditions in Vikings from Varnhem, Sweden

In a late Swedish Viking Age population dating from around 10th-12th century AD, the prevalence, distribution and location of dental caries were studied. Tooth wear, other dental pathology and anatomical variations were identified and recorded clinically and radiographically. A total of 3293 teeth were analyzed from 171 individuals with complete and partial dentitions, of which 133 were permanent and 38 deciduous/mixed dentition. The dentitions were studied clinically, using a dental probe under a strong light source, and radiographs were taken for 18 of the individuals to verify and complement the clinical caries registration. Almost half the population, 83 of 171 individuals (49%), had at least one carious lesion. All individuals with deciduous or mixed dentitions were caries-free. The number of teeth affected by caries among adults was 424 (13%) and the surface most susceptible to caries was the root surface. The tooth most commonly affected by caries was the first mandibular molar. Other findings included apical infections, which were detected clinically in 4% of the teeth, and one case of filed front teeth. The findings gave a unique understanding of life and death in this early Christian Viking community and indicated that it was common to suffer from dental caries, tooth loss, infections of dental origin and tooth pain. These Vikings also manipulated their teeth through filing, tooth picking and other occupational behaviors.

Athermalization of Optical System with Large Field of View for Image Navigation

Image navigation sensor is one of the most important sensing means for human to explore the extraterrestrial space environment, and optical system is a key component of image navigation sensor, directly determines the amount of information perceived. The optical system requirements of image navigation sensors are gradually developing towards large field of view and miniaturization. The fisheye lens is the first choice for large field of view imaging by selecting the appropriate optical structure, without adding other additional components, and has the advantages of small size and strong perception energy. However, as the image surface illuminance of fisheye lens will decrease sharply with the increase of the field of view, the change of temperature will also degrade the imaging quality of the system, and strong stray light sources such as the sun will easily enter the field of view, which will greatly affect the perception ability of the system. Because of this, effective design of these systems is quite difficult. In this paper, a reverse-telephoto structure was used for large-field imaging, and the degradation of imaging quality caused by temperature changes was eliminated by selecting appropriate optical and mechanical materials. Designed with a focal length of 6.7mm, an F number of 3.6, a viewing angle of 130°, a working band of 0.45μm to 0.65μm, an after work distance of 7mm, a total system length≤60mm, we tested our system in a -40°C to +60°C temperature range and measured the image quality. Through simulation analysis, the system in the whole field of view within our spot diagrams was≤5.5μm, optical transfer function was greater than 0.2 at 90lp/mm, and no vignetting occurred. Furthermore, the imaging illumination of the edge field of view was 0.72 times that of the center field of view, the f – tan (θ) relative distortion value of the center field of view was≤2.3%, and the f – θ relative distortion value of the edge field of view was≤2.7%. Compared to normal temperatures, the optical transfer function changes at -20°C and +40°C were 0.02 and 0.01, respectively. Thus, the system displayed the characteristics of excellent image quality, small size, high energy utilization rate and good non-thermal performance.

CAM-FRN: Class Attention Map-Based Flare Removal Network in Frontal-Viewing Camera Images of Vehicles

In recent years, active research has been conducted on computer vision and artificial intelligence (AI) for autonomous driving to increase the understanding of the importance of object detection technology using a frontal-viewing camera. However, using an RGB camera as a frontal-viewing camera can generate lens flare artifacts due to strong light sources, components of the camera lens, and foreign substances, which damage the images, making the shape of objects in the images unrecognizable. Furthermore, the object detection performance is significantly reduced owing to a lens flare during semantic segmentation performed for autonomous driving. Flare artifacts pose challenges in their removal, as they are caused by various scattering and reflection effects. The state-of-the-art methods using general scene image retain artifactual noises and fail to eliminate flare entirely when there exist severe levels of flare in the input image. In addition, no study has been conducted to solve these problems in the field of semantic segmentation for autonomous driving. Therefore, this study proposed a novel lens flare removal technique based on a class attention map-based flare removal network (CAM-FRN) and a semantic segmentation method using the images in which the lens flare is removed. CAM-FRN is a generative-based flare removal network that estimates flare regions, generates highlighted images as input, and incorporates the estimated regions into the loss function for successful artifact reconstruction and comprehensive flare removal. We synthesized a lens flare using the Cambridge-driving Labeled Video Database (CamVid) and Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago (KITTI) datasets, which are road scene open datasets. The experimental results showed that semantic segmentation accuracy in images with lens flare was removed based on CAM-FRN, exhibiting 71.26% and 60.27% mean intersection over union (mIoU) in the CamVid and KITTI databases, respectively. This indicates that the proposed method is significantly better than state-of-the-art methods.

Exploring the Core Parameters of CNC-Based Chiral Nematic Structures for Enhancing the Dissymmetry Factor of Right-Handed Circularly Polarized Luminescence.

The chiral nematic nanostructure formed from cellulose nanocrystal (CNC) self-assembly has shown great potential as a matrix for generating circularly polarized luminescent (CPL) light with a high dissymmetry factor. Exploring the relationship between the device composition and structure and the light dissymmetry factor is crucial to a common strategy for a strongly dissymmetric CPL light. In this study, we have compared the single-layered and double-layered CNC-based CPL devices with different luminophores, such as rhodamine 6G (R6G), methylene blue (MB), crystal violet (CV), and silicon quantum dots (Si QDs). We demonstrated that forming a double-layered structure of CNCs nanocomposites is a simple but effective pathway for enhancing the CPL dissymmetry factor for CNC-based CPL materials containing different luminophores. The |glum| values of double-layered CNC devices (dye@CNC5||CNC5) versus that of single-layered devices (dye@CNC5) are 3.25 times for Si QDs, 3.7 times for R6G, 3.1 times for MB, and 2.78 times for CV series. The different enhancement degrees of these CNC layers with a similar thickness may be due to the different pitch numbers in the chiral nematic liquid crystal layers whose photonic band gap (PBG) has been modified to match the emission wavelengths of dyes. Furthermore, the assembled CNC nanostructure has great tolerance to the addition of nanoparticles. Gold nanorods coated with the SiO2 layer (Au NR@SiO2) were added for enhancing the dissymmetry factor of MB in CNC composites (named MAS devices). When the strong longitudinal plasmonic band of the Au NR@SiO2 matched the emission wavelength of MB and the PBG of assembled CNC structures simultaneously, the increase in the glum factor and quantum yield of MAS composites was obtained. The good compatibility of the assembled CNC nanostructures makes it a universal platform for developing strong CPL light sources with a high dissymmetry factor.

A First Application of Machine and Deep Learning for Background Rejection in the ALPS II TES Detector

AbstractAxions and axion‐like particles are hypothetical particles predicted in extensions of the standard model and are promising cold dark matter candidates. The Any Light Particle Search (ALPS II) experiment is a light‐shining‐through‐the‐wall experiment that aims to produce these particles from a strong light source and magnetic field and subsequently detect them through a reconversion into photons. With an expected rate ≈1 photon per day, a sensitive detection scheme needs to be employed and characterized. One foreseen detector is based on a transition edge sensor (TES). Here, the machine and deep learning algorithms for the rejection of background events recorded with the TES are investigated. A first application of convolutional neural networks to classify time series data measured with the TES is also presented.

Strong Exciton–Exciton Scattering of Exfoliated van der Waals InSe toward Efficient Continuous-Wave Near-Infrared P-Band Emission

P-band emission is a superlinear low-coherence emission through exciton-exciton (X-X) scattering into photon-like states. It occurs without the prerequisites of population inversion or macroscopical coherence, rendering lower power consumption than the widely explored superlinear low-coherence emissions including superfluorescence, amplified spontaneous emission, and random lasing, and holds great potential for speckle-free imaging and interferometric sensing. However, competition processes including exciton dissociation and annihilation undermine its operation at room temperature and/or low excitation conditions. Here we report room-temperature P-band emission from InSe microflakes with excitation density of 1010 cm-2, offering 2-orders-of-magnitude lower operation density compared to the state-of-the-art superlinear low-coherence emissions. The efficient P-band emission is attributed to a large X-X scattering strength of 0.25 μeV μm2 due to enhanced spatial confinement along with intrinsic material metrics of 3D/2D exciton complex and asymmetric electron/hole mass. These findings open an avenue toward strong low-coherence near-infrared light sources based on van der Waals semiconductors.

Degradation Analysis of Organic Light-Emitting Diodes through Dispersive Magneto-Electroluminescence Response.

Understanding the stability and degradation of organic light-emitting diodes (OLEDs) under working conditions is a significant area of research for developing more effective OLEDs and further improving their performance. However, studies of degradation processes by in situ noninvasive methods have not been adequately developed. In this work, tris-(8-hydroxyquinolino) aluminum (Alq3)-based OLED degradation processes have been analyzed through the investigation of the device dispersive magneto-electroluminescence (MEL(B)) response measured at room temperature. By studying the change in the MEL(B) response during the device degradation under different external stimuli, such as exposing the device to the atmosphere and prolonged illumination by a strong visible light source, we have gained insight into the microscopic spin-dependent phenomena that control the recombination of e-h polaron pairs in the device. We found that the device degradation leads to a shorter e-h polaron lifetime, smaller dispersive parameter, and broader lifetime distribution function that shows increased disorder in the active layer. This study could offer a potential tool that may be beneficial for assessing the degradation of OLED devices based on various active layers.

Direct counterfactual quantum-communication protocol beyond a single-photon source

The direct counterfactual quantum communication protocol involving double chained Mach-Zehnder interferometers requires a single photon input. Here, we show that even with multiphoton light sources, including a strong coherent light source as inputs, the counterfactual communication can be achieved with success probability approaching unity in the ideal asymptotic limit. The path evolution of multiple photons is non-locally controlled. Thus, information is transmitted without any photons, or any other auxiliary information carriers, appearing in the public transmission channel. The effect is quantum since quantum measurements are essential requirement for this protocol. Furthermore, a modified scheme is proposed in which number of interferometers is reduced.

Flow mechanism of Gaussian light-induced vortex motion inside a nanofluid droplet

PurposeThe purpose of this study is to use a weak light source with spatial distribution to realize light-driven fluid by adding high-absorbing nanoparticles to the droplets, thereby replacing a highly focused strong linear light source acting on pure droplets.Design/methodology/approachFirst, Fe3O4 nanoparticles with high light response characteristics were added to the droplets to prepare nanofluid droplets, and through the Gaussian light-driven flow experiment, the Marangoni effect inside a nanofluid droplet was studied, which can produce the surface tension gradient on the air/liquid interface and induce the vortex motion inside a droplet. Then, the numerical simulation method of multiphysics field coupling was used to study the effects of droplet height and Gaussian light distribution on the flow characteristics inside a droplet.FindingsNanoparticles can significantly enhance the light absorption, so that the Gaussian light is enough to drive the flow, and the formation of vortex can be regulated by light distribution. The multiphysics field coupling model can accurately describe this problem.Originality/valueThis study is helpful to understand the flow behavior and heat transfer phenomenon in optical microfluidic systems, and provides a feasible way to construct the rapid flow inside a tiny droplet by light.

Estimation of Positions and Poses of Autonomous Underwater Vehicle Relative to Docking Station Based on Adaptive Extraction of Visual Guidance Features

The underwater docking of autonomous underwater vehicles (AUVs) is conducive to energy supply and data exchange. A vision-based high-precision estimation of “the positions and poses of an AUV relative to a docking station” (PPARD) is a necessary condition for successful docking. Classical binarization methods have a low success rate in extracting guidance features from fuzzy underwater images, resulting in an insufficient stability of the PPARD estimation. Based on the fact that guidance lamps are blue strong point light sources, this study proposes an adaptive calculation method of binary threshold for the guidance image. To decrease the failure of guidance feature extraction, a guidance image enhancement method is proposed to strengthen the characteristic that the guidance lamps are strong point light sources with a certain area. The PPARD is estimated through solving the minimum value of the imaging error function for the vision-based extracted guidance features. The experimental results showed that the absolute estimation error for each degree of freedom in the PPARD was at most 10%, which was lower than that of the orthogonal iteration (OI) method. In addition, the proposed guidance feature extraction method proved to be better than the classical methods, with the extraction success rate reaching 87.99%.

Image restoration for real-world under-display imaging.

Under-display imaging technique was recently proposed to enlarge the screen-to-body ratio for full-screen devices. However, existing image restoration algorithms have difficulty generalizing to real-world under-display (UD) images, especially to images containing strong light sources. To address this issue, we propose a novel method for building a synthetic dataset (CalibPSF dataset) and introduce a two-stage neural network to solve the under-display imaging degradation problem. The CalibPSF dataset is generated using the calibrated high dynamic range point spread function (PSF) of the under-display optical system and contains various simulated light sources. The two-stage network solves the color distortion and diffraction degradation in order. We evaluate the performance of our algorithm on our captured real-world test set. Comprehensive experiments demonstrate the superiority of our method in different dynamic range scenes.

Visual detection method based on line lasers for the detection of longitudinal tears in conveyor belts

This study proposes a novel method based on line lasers for longitudinal tear detection in conveyor belts. Unlike most of the existing methods directly based on the morphological characteristics easily influenced by the change in environmental light, this method transfers the characteristics of the belt to the linear characteristics of the laser line. As a strong light source, the linear laser is not easily affected by the change in light. A new improved gray-gravity center method (IGGM) was proposed to extract the centerline of the laser line, and then detect the longitudinal tear based on the characteristics of the centerline. The experimental results show that this method can remove the influence of the changes in environmental light, the laser line can retain the longitudinal tear features well, and IGGM can extract the centerline more accurately. Compared with other methods, this method has better accuracy and better real-time performance.

Sunquake with a second bounce, other sunquakes, and emission associated with the X9.3 flare of 6 September 2017

Aims.The 6 September 2017 X9.3 solar flare produced very unique observations of magnetic field transients and a few seismic responses, or sunquakes, detected by the Helioseismic and Magnetic Imager (HMI) instrument aboard Solar Dynamic Observatory (SDO) spacecraft, including the strongest sunquake ever reported. This flare was one of a few flares occurring within a few days or hours in the same active region. Despite numerous reports of the fast variations of magnetic field, and seismic and white light emission, no attempts were made to interpret the flare features using multi-wavelength observations. In this study, we attempt to produce the summary of available observations of the most powerful flare of the 6 September 2017 obtained using instruments with different spatial resolutions (this paper) and to provide possible interpretation of the flaring events, which occurred in the locations of some seismic sources (a companion Paper II).Methods.We employed non-linear force-free field extrapolations followed by magnetohydrodynamic simulations in order to identify the presence of several magnetic flux ropes prior to the initiation of this X9.3 flare. Sunquakes were observed using the directional holography and time–distance diagram detection techniques. The high-resolution method to detect the Hαline kernels in the CRISP instrument at the diffraction level limit was also applied.Results.We explore the availableγ-ray (GR), hard X-ray (HXR), Lyman-α, and extreme ultra-violet (EUV) emission for this flare comprising two flaring events observed by space- and ground-based instruments with different spatial resolutions. For each flaring event we detect a few seismic sources, or sunquakes, using Dopplergrams from the HMI/SDO instrument coinciding with the kernels of Hαline emission with strong redshifts and white light sources. The properties of sunquakes were explored simultaneously with the observations of HXR (with KONUS/WIND and the Reuven Ramaty High Energy Solar Spectroscopic Imager payload), EUV (with the Atmospheric Imaging Assembly (AIA/SDO and the EUV Imaging Spectrometer aboard Hinode payload), Hαline emission (with the CRisp Imaging Spectro-Polarimeter (CRISP) in the Swedish Solar Telescope), and white light emission (with HMI/SDO). The locations of sunquake and Hαkernels are associated with the footpoints of magnetic flux ropes formed immediately before the X9.3 flare onset.Conclusions.For the first time we present the detection of the largest sunquake ever recorded with the first and second bounces of acoustic waves generated in the solar interior, the ripples of which appear at a short distance of 5–8 Mm from the initial flare location. Four other sunquakes were also detected, one of which is likely to have occurred 10 min later in the same location as the largest sunquake. Possible parameters of flaring atmospheres in the locations with sunquakes are discussed using available temporal and spatial coverage of hard X-ray, GR, EUV, hydrogen Hα-line, and white light emission in preparation for their use in an interpretation to be given in Paper II.

Dental health of Vikings from Kopparsvik on Gotland

AbstractThe prevalence, distribution, and location of dental caries were studied in complete and partial human dentitions dating from the Viking Age dating (900–1050 AD) excavated in Kopparsvik on island of Gotland, Sweden. 18 individuals and a total of 370 teeth were examined, using a strong light source and dental probe. Carious lesions were found in a large number of the individuals, 14 out of 18. The percentage of teeth affected by caries (11,9%) corresponds well with studied skull materials from the same period. The surface most susceptible to caries was the occlusal surface, whereas only a few proximal lesions and one single carious root surface was found. The tooth most commonly affected by caries was the mandibular first molar. The tooth most commonly missing ante‐mortem was also the mandibular molar, and the tooth most commonly missing post mortem was the mandibular incisor. Other findings included apical infections, which were detected clinically in 3% of the teeth.