Light Attenuation Research Articles

A 30-year (1992-2021) time-series of Kd(PAR) at the North Sea - Baltic Sea transitional zone - trends in light attenuation and Chlorophyll a

Light attenuation is of fundamental importance for photosynthesis in marine and freshwater environments and quantified as Kd(PAR). A 30-year (1992–2021) long time-series of Kd(PAR) (n = 945) from Aarhus Bay, at the North Sea - Baltic Sea transition obtained with 1–5 measurements per month is analyzed. The time-series showed a weak but not statistically significant positive trend with an average Kd(PAR) of 0.30 ± 0.08 m−1. Monthly based time-series of Kd(PAR) showed, in comparison, significant differences with average maximum values in March of 0.38 ± 0.09 m−1 compared to a minimum in June of 0.26 ± 0.03 m−1. There were statistically significant positive Kd(PAR) trends in April and December and a negative trend in October. Accordingly, the depth limit of eelgrass and macroalgae decreased from 8 to 5 m in April. The strong variability in Kd(PAR) in February and March related to the phytoplankton spring bloom in Aarhus Bay both in timing and strength, given the strong and significant correlation between Chl a and Kd(PAR). Partitioning showed that non-Chl a attenuation related to CDOM and suspended matter increased from 0.20 m−1 to 0.29 m−1 between 1992 and 2007 but was constant from then on. The Chl a specific attenuation coefficient varied around an average of 0.019 ± 0.008 m2 (mg Chl a)−1 and showed only small variations over time. The frequency of CTD casts and light measurements decreased between 1992 (n = 52 per year) and 2022 (n = 15 per year) but no parallel trends in average Kd(PAR) were observed. No significant trend (1992–2021) in annual average Chl a concentrations in Aarhus Bay was detected. The importance of high-resolution measurements in time are emphasized and at least monthly to track the strong seasonal variation.

Non-Invasive Hemoglobin Assessment with NIR Imaging of Blood Vessels in Transmittance Geometry: Monte Carlo and Experimental Evaluation

Non-invasive methods for determining blood hemoglobin (Hb) concentration are urgently needed to avoid the painful and time-consuming process of invasive venous blood sampling. Many such methods rely on assessing the average attenuation of light over a tissue area where hemoglobin is the dominant chromophore, without separating those areas corresponding to vessels and bloodless tissue. In this study, we investigate whether it is possible to determine hemoglobin levels in the blood by assessing the changes in light intensity when passing through large vessels in comparison to adjacent tissues, using this as a Hb level predictor. Using Monte Carlo light transport modeling, we evaluate the accuracy of determining hemoglobin levels via light intensity contrast and vessel widths estimated in the transmittance illumination geometry and estimate the influence of physiologically significant parameters such as vessel depth, dermis vascularization, and melanin content in the epidermis on the blood Hb prediction error. The results show that physiological variations in tissue parameters limit the mean absolute error of this method to ~15 g/L for blood Hb levels varying in the 60–160 g/L range, which finding is also supported by experimental data obtained for volunteers with different total blood Hb levels that have been determined invasively. We believe the application of new approaches to the non-invasive assessment of Hb levels will lead to the creation of reliable and accurate devices that are applicable in point-of-care and clinical practice.

The dual nature of biomimetic melanin.

Melanin-inspired nanomaterials offer unique photophysical, electronic and radical scavenging properties that are widely explored for health and environmental preservation, or energy conversion and storage. The incorporation of functional melanin building blocks in more complex nanostructures or surfaces is typically achieved via a bottom-up approach starting from a molecular precursor, in most cases dopamine. Here we demonstrate that indeed, the oxidative polymerization of dopamine, for the synthesis of melanin-like polydopamine (PDA), leads to the simultaneous formation of more than one nanosized species with different compositions, morphologies and properties. In particular, a low-density polymeric structure and dense nanoparticles (NP) are simultaneously formed. The two populations could be separated and analyzed in real time using a chromatographic technique free of any stationary phase (flow field fractionation, FFF). The results following the synthesis of melanin-like PDA showed that the NP are formed only during the first 6 hours as a result of a supramolecular self-assembly-driven polymerization, while the formation of the polymer continues for about 36 hours. The two populations were also separated and characterized using TEM, UV-vis absorption spectroscopy, fluorescence and light scattering spectroscopy, DLS, FTIR, ζ-potential measurements, gel electrophoresis and pH titrations. Interestingly, very different properties between the two populations were observed: in particular the polymer contains a higher number of catechol units (8 mmol g-1 -OH) with respect to the NP (1 mmol g-1 -OH) and presents a much higher antioxidant activity. The attenuation of light by NP is more efficient than that by the polymer especially in the Vis-NIR region. Moreover, while the NP scatter light with an efficiency up to 27% they are not fluorescent, and the polymer does not scatter light but shows an excitation wavelength-dependent fluorescence typical of multi-fluorophoric uncoupled systems.

Face orientation recognition based on Kinectv2 and an improved ELM model

Abstract Face orientation recognition is a crucial component of human behavior analysis. Challenges such as face occlusion and varying lighting conditions frequently degrade recognition accuracy. This study introduces an innovative approach using the Kinect sensor’s skeleton tracking technology to capture face orientation images across different lighting scenarios. To enhance image quality, techniques such as light attenuation and compensation are applied. Furthermore, multiple feature vectors based on face orientation are extracted and fused, followed by the optimization of the Extreme Learning Machine (ELM) model through the Archimedean Optimization Algorithm (AOA). The developed AOA-ELM model for face orientation recognition is compared with traditional models, including Back Propagation (BP), Radial Basis Function (RBF), standard ELM, and Genetic Algorithm enhanced ELM (GA-ELM). The AOA-ELM model exhibits superior performance in estimating face orientation amidst lighting disturbances, achieving an accuracy exceeding 95% in varied lighting conditions, thereby outperforming other classification models.

Optics and quantitative assessment of corneal transparency

While some optical properties of cornea like its stromal birefringence had been known since the early nineteenth century, theories explaining its transparency remained inconclusive until the publication of David Maurice' emblematic paper in 1957 Maurice made a model calculation of light scattering by a single collagen fibril as a “dielectric needle”. The volume density of the fibrils being known, Maurice could demonstrate that in the absence of any order among the fibrils the cornea would be opaque. Maurice postulated the hexagonal structure which since has been confirmed by electron microscopy. In modern terms, the order among the collagen fibrils within a stromal collagen lamella is described by a “structure factor” in the radiative transfer equation. This term corresponds to a description of the structure in reciprocal space and is thus equivalent to the representation of crystalline lattices in the first Brillouin zone used for structural modelling in crystallography.In a recent study we further analysed the collagen structure of healthy and oedematous corneas on a nanometric level observed by transmission electron microscopy (TEM). By automated image analysis we could retrieve the so‐called “pair correlation function” and calculate light attenuation within the corresponding cornea. Our findings show that the 1/e light penetration depth within healthy cornea could be calculated as 7300 ± 800 μm, which explains well the transparency of healthy cornea. However, the photon mean free path of oedematous cornea turned out to be from two to three times that value. In oedematous cornea, the “dilution” effect of the scatters is in fact stronger than the degradation of transparency by the perturbation of the structure. The actual loss of transparency in oedematous cornea may therefore be attributed to scattering processes at the micrometric level induced by the augmented optical contrast at the sites of the keratocytes between the collagen lamellae.Perturbations in corneal transparency do not only hamper vision, they also impact optical imaging methods on cornea. This, in turn, permits to study the transparency properties of the corneal tissue. One of the main research interests of our group is to analyse corneal images recorded by optical coherence tomography (OCT) and to extract quantitative parameters like photon mean path length and the fraction of coherently transmitted light.Our partners could show that in the light scattering regime, a term in the radiation transfer equation may be neglected and the attenuation of the full field OCT signal in the volume of the tissue reduces to a Lambert–Beer law. We developed a data analysis algorithm based on Bayesian inference to extract the attenuation coefficient and used it for the analysis of ex vivo corneal high‐resolution FF‐OCT images.In a second step, we developed an image processing algorithm for clinical OCT images removing typical artefacts and compensating for inhomogeneous illumination and corneal curvature. We presently are able to extract corneal transparency parameters from routine clinical OCT images and to provide post‐op follow‐up after keratoplasty or other surgical interventions.

Rendering the Bluish Appearance of Snow: When Light Transmission Matters.

Material appearance is largely determined by complex light attenuation processes. The distinct bluish colorations that can be observed when light is transmitted through snow are among the most striking outcomes of these processes. In this article, we present a method for the predictive rendering of this phenomenon taking into account the variability of snow's physical and morphological characteristics. To achieve that, we employ an approach centered on the effective use of spectral transmittance data obtained using a first-principles light transport model for snow. The suitability of the proposed method to rendering applications is illustrated through the synthesis of images depicting the bluish appearance of snow under different illumination conditions.

StainedSweeper: Compact, Variable-Intensity Light-Attenuation Display with Sweeping Tunable Retarders.

Light Attenuation Displays (LADs) are a type of Optical See-Through Head-Mounted Display (OST-HMD) that present images by attenuating incoming light with a pixel-wise polarizing color filter. Although LADs can display images in bright environments, there is a trade-off between the number of Spatial Light Modulators (SLMs) and the color gamut and contrast that can be expressed, making it difficult to achieve both high-fidelity image display and a small form factor. To address this problem, we propose StainedSweeper, a LAD that achieves both the wide color gamut and the variable intensity with a single SLM. Our system synchronously controls a pixel-wise Digital Micromirror Device (DMD) and a nonpixel polarizing color filter to pass light when each pixel is the desired color. By sweeping this control at high speed, the human eye perceives images in a time-multiplexed, integrated manner. To achieve this, we develop the OST-HMD design using a reflective Solc filter as a polarized color filter and a color reproduction algorithm based on the optimization of the time-multiplexing matrix for the selected primary color filters. Our proof-of-concept prototype showed that our single SLM design can produce subtractive images with variable contrast and a wider color gamut than conventional LADs.

A Cascaded Multimodule Image Enhancement Framework for Underwater Visual Perception.

Underwater images usually exhibit severe color cast, hazy appearance, and/or dark regions because of the complex lighting absorption and scattering in water. How to increase the quality of these degraded underwater images has emerged as a key issue for various underwater application tasks. Recent efforts have been made to deal with single type degradation, however, it is still challenging to deal with multiple degradations that usually coexist in an underwater image with a general network. The degradations in underwater images can be divided into medium-agnostic (hazy or low-light which also encountered in in-air images) and medium-specific (color distortion caused by the specific light attenuation property in water) ones. According to this observation, this article proposes a cascaded multimodule underwater image enhancement (UIE) framework to address the coexisted multiple degradations. In the proposed framework, an in-air image enhancement module and a novel proposed adaptive color channel compensation network (AC 3 Net) are cascaded, in which the former focuses primarily on solving medium-agnostic degradations and the latter is for handling the medium-specific degradation. This framework has good flexibility by cascading different types of in-air image enhancement networks with AC 3 Net to achieve various UIE. The effectiveness of the proposed framework has been extensively validated on various degraded underwater images as well as different underwater visual perception tasks.

Enhancing Underwater Image Segmentation: A Semantic Approach to Segment Objects in Challenging Aquatic Environment

Aquatic image segmentation is complex due to the inherent complexity of light attenuation, color shifts, and vision limits in underwater settings. In order to improve underwater image segmentation and the delineation of objects in such conditions, this research study suggests a novel semantic technique. The suggested approach uses cutting-edge deep learning methods and a U-Net architecture with DenseNet-201 at its core. The dense connectivity patterns of DenseNet-201 make it possible to extract useful features, increasing gradient flow and feature reuse across the network. The model uses a combination of Dice Loss and Categorical Focal Loss is the loss function to enhance segmentation performance. It utilizes evaluation metrics like the IoU Score and F-Score, which give detailed insights into the model's performance on underwater picture segmentation tasks. According to the evaluation metrics, the "DenseNet201" architecture is the most effective one for underwater picture segmentation. On the test dataset, it received the highest Mean IoU Score (79.77/%) and F1 Score (84.85)%. Furthermore, it obtained competitive results for each class-wise IoU score, demonstrating strong segmentation performance for different object categories.

Links between Land Cover and In-Water Optical Properties in Four Optically Contrasting Swedish Bays

The optical complexity of coastal waters is mostly caused by the water discharged from land carrying optical components (such as dissolved and particulate matter) into coastal bays and estuaries, and increasing the attenuation of light. This paper aims to investigate the links between in-water optical properties in four Swedish bays (from the northern Baltic proper up to the Bothnian bay) and the land use and land cover (LULC) in the respective catchment of each bay. The optical properties were measured in situ over the last decade by various research and monitoring groups while the LULC in each bay was classified using the Copernicus Land Monitoring Service based on Landsat 8/OLI data. The absorption coefficient of colored dissolve organic matter (CDOM) at 440 nm, aCDOM (440), was significantly correlated to Wetlands which may act as sources of CDOM, while Developed areas (Agricultural and Urban classes) were negatively correlated. The Agriculture class was also negatively related to suspended particulate organic matter (SPOM), whilst Coniferous Forests and Mixed Forests as well as Meadows were positively correlated. SPOM seems thus to mostly originate from Natural classes, possibly due to the release of pollen and other organic matter. Overall, the methods applied here allow for a better understanding of effects of land use and land cover on the bio-optical properties, and thus coastal water quality, on a macroscopic scale.

Degradation of fishing grounds in North Waters of Banten Province, Indonesia

The high level of fishing activity with small fishing vessels has resulted in relatively high utilization of marine space in coastal areas, manifesting changes in fishing grounds. Thus, this research aimed to analyze water quality, fishing intensity and to determine the level of degradation of fishing grounds in the northern waters of Banten Province. This research was conducted from June to August 2023 in the northern waters of Banten Province. Data collection was carried out using survey, remote sensing, and interview methods. Water quality data consisting of sea surface temperature, brightness, salinity, light attenuation coefficient, total suspended solids, and chlorophyll-a were analyzed descriptively. Eco-friendly capture fisheries data were taken directly from 120 fishermen and analyzed based on the CCRF criteria. Degradation status was determined by combining weight of water quality conditions and eco-friendly capture fisheries. Based on the research results, the northern waters of Banten Province is in good condition for biota life. Fishing equipment is dominated by eco-friendly fishing gear. Nevertheless, several parts of northern waters in Banten Province have experienced light degradation of fishing areas (18.28%) and the heavy degradation (7.71%). The use of marine space for capture fisheries in the northern waters of Banten Province is relatively high, around 50 units of fishing gear for 1 hectare of water.Keywords:EnvironmentFishing intensityFishing gearSpatial mappingWater quality

(Invited) Piezocatalysis for Treating a Massive Industrial Dye Solution and Hydrogen Production

As a fossil fuel substitute, among the various renewable alternative energy sources, hydrogen fuel is a clean energy source being developed in advanced industrial nations worldwide. Photocatalytic water splitting yields hydrogen through redox reactions underlying direct water decomposition. Although water splitting is a promising method of yielding clean energy from the sunlight without contaminating byproducts, sunlight is a desultory source of energy, which limits the amount of solar radiation owing to its dependence on time (day or night), geographical position, and season.Redox reactions remain one of the most promising methods of producing hydrogen and decomposing industrial wastewater. However, for most critical practical industrial applications, the robust light attenuation of wastewater results in meager quantum yield, thus significantly limiting the commercial applications of photocatalysis. Therefore, novel approaches to evaluating parameters, including cost-effectivity, high efficiency, and long-time stability, are highly desirable for developing next-generation catalysts. In particular, such technology would be up-and-coming for simultaneously producing hydrogen gas and decomposing industrial wastewater without light irradiation. This talk will report how 2D transition metal dichalcogenides can be used for piezocatalyts for highly efficient wastewater treatment of a massive industrial dye solution and hydrogen production without applied light irradiation by utilizing a closed-loop system with a low-frequency natural water flow. Our newly developed piezoelectrocatalysts system provides the first evidence of the effective production of hydrogen gas and the simultaneous decomposition of dye molecules in wastewater without light irradiation, thus providing a promising method for treating industrial wastewater and producing clean energy.

Simultaneous Piezoelectrocatalytic Hydrogen-Evolution and Degradation of Water Pollutants By Quartz Microrods@Few-Layered MoS2 Hierarchical Heterostructures

Intense light attenuation in water/wastewater results in photocatalysts exhibiting a low quantum efficiency. This study develops a novel piezoelectrocatalysis system, which involves quartz microrods (MRs) abundantly decorated with active edge-sites MoS2 nanosheets to form quartz microrods@few-layered MoS2 hierarchical heterostructure (QMSH). Through theoretical calculations, quartz MR serves as a parallel-plate capacitor, which is self-powered to provide an internal electric field to the few-layered MoS2 nanosheets surrounding the quartz MR surfaces, and the piezoelectric potential (piezopotential) effectively facilitates redox reactions with the free carrier in MoS2. The self-powered quartz MRs in QMSH present an internal bias to the MoS2 nanosheets, thus yielding a piezoelectrocatalysis system. An efficient piezoelectrocatalytic hydrogen evolution reaction (HER) and decomposition of wastewater without light irradiation could achieve simultaneously. The second-order rate constant of QMSH is approximately 0.631 L mg-1min-1, which was 650-fold that of quartz MRs, indicating that the piezoelectric heterostructural catalysts display exceptionally high efficiency on piezo-electrocatalytic redox reactions rather than in the peizocatalytic process. The H2-production rate of QMSH catalysts approached approximately 6456 μmo1·g−1 h−1 and peaked at approximately 16.8 mmol g−1 in 8 h. The piezoelectrocatalytic process may be a promising method for treating industrial wastewater and producing clean energy.

Improved measurement of the light attenuation length of a high-quality linear alkylbenzene for the JUNO experiment

The Jiangmen Underground Neutrino Observatory (JUNO) experiment is the next-generation neutrino experiment that aims at exploring the neutrino mass hierarchy problem. Located 700m underground in Jiangmen, China, JUNO’s central detector is an acrylic sphere filled with 20kt of liquid scintillator with linear alkylbenzene (LAB) as solvent. To achieve the unprecedented energy resolution of σE/E⩽3%, the LAB used in JUNO is required for excellent transparency at the wavelength around 430nm. In cooperation with Jinling Petrochemical (Nanjing), the newly developed LAB shows an improved attenuation length. The resulting transparency of the LAB requires higher sensitivity in measurement. We have, therefore, upgraded the apparatus and the analysis method for higher precision. In this article, we present the upgraded apparatus and the analysis on improving the measurement error. Among the many new samples, the type NJ66 yields an attenuation length of approximately 30m. The analysis has applied statistical methods with Monte Carlo simulations. A new model is proposed to account for the deviations between data and the Beer–Lambert model. The long attenuation length of LAB observed in this study suggests feasibility to reach the goal on energy resolution required by JUNO.

A Simple Approach to Modeling Light Attenuation in the Sacramento–San Joaquin Delta Using Commonly Available Data

The diffuse attenuation coefficient of photosynthetically active radiation (KdPAR) is commonly used to predict light attenuation in aquatic productivity models, but obtaining measurements of PAR to compute KdPAR is difficult. In situ calculations of KdPAR require multiple measurements of PAR through the water column, and these measurements are infeasible for real-time recording. Instead, predictive models using surface-water measurements may be used. Traditional KdPAR models are based on open-ocean habitats and rely on chlorophyll—as a proxy measurement for phytoplankton abundance—as the main predictive parameter. However, elevated suspended sediments and dissolved organic materials may also affect KdPAR values of inland water bodies and estuaries. In this study, we leverage KdPAR calculations derived from in situ light measurements collected along with surface-water-quality parameters across the Sacramento-San Joaquin River Delta in California, USA (the Delta). Sampling occurred between January of 2013 and May of 2014. We also explored regional and seasonal effects, but these did not clearly affect the model. Ultimately, the best-performing model included surface-level turbidity only (R2 = 0.91). The simplicity of the model facilitates use of KdPAR estimates for a variety of purposes throughout the Delta, including euphotic depth calculations, and as inputs to primary-productivity and habitat-suitability models. We demonstrate the model’s usability with two open-sources data sets (one spatially dense, and one temporally dense), and estimate KdPAR, euphotic depth, and primary productivity within the Delta. We provide calculations for each estimation, allowing users to easily adopt these models and apply them to their own data or with open-sourced data, which are abundant.

Experimental study of transient particle suspension in bioreactors using a light attenuation technique

The culture of mesenchymal stromal cells relies on the use of suspended microcarriers as adhesion supports. During the particle suspension phases, the temporal evolution of the spatial distribution of particle concentrations is generally poorly characterized. In this study, the light attenuation technique was used to access this distribution and the duration of particle homogenization. Considering the minimal agitation rate Nref for which particle suspension was observed for all the microcarrier concentrations 〈C〉 studied, the results showed that using an agitation frequency close to Nref significantly increased the homogenization duration compared to N≃1.7×Nref. The transient microcarrier overconcentration was also determined locally. At N=Nref, the resuspension time was negatively impacted by 〈C〉, which also resulted in longer particle overconcentrations. A time-integral particle overconcentration term was considered to estimate the severity of inter-microcarrier collisions. The results suggested that increased agitation could limit time-cumulative overconcentrations beyond a particle concentration of 3 g/L.

Smart dimming sunglasses for photophobia using spatial light modulator

We present a smart sunglasses system engineered to assist individuals experiencing photophobia, particularly those highly sensitive to light intensity. The system integrates a high dynamic range (HDR) camera and a liquid crystal spatial light modulator (SLM) to dynamically regulate light, adapting to environmental scenes by modifying pixel transmittance through a specialized control algorithm, thereby offering adaptable light management to meet the users’ visual needs. Nonetheless, a conventional occlusion mask on the SLM, intended to block incoming light, emerges blurred and insufficient due to a misaligned focal plane. To address the challenge of imprecise light filtering, we introduce an optimization algorithm that meticulously adjusts the light attenuation process, effectively diminishing excessive brightness in targeted areas without adversely impacting regions with acceptable levels of luminance.

Multimodal optical clearing to minimize light attenuation in biological tissues

The biggest obstacle to optical imaging is light attenuation in biological tissues. Conventional clearing techniques, such as agent-based clearing, improve light penetration depth by reducing scattering, but they are hampered by drawbacks including toxicity, low efficiency, slowness, and superficial performance, which prevent them from resolving the attenuation problem on their own. Therefore, quick, safe, and effective procedures have been developed. One of them involves using standing ultrasonic waves to build light waveguides that function effectively in the tissue depth while minimizing scattering. Temporal optical clearing is another agent-free strategy that we introduced in our previous article. Whereas not deep, this technique minimizes both light absorption and scattering by pulse width variation in ultra-short pulse regime. Consequently, it can be a complementary method for ultrasonic optical clearing. In this work, we enhanced the light penetration depth in chicken breast tissue by 10 times (0.67–6.7 cm), setting a record in literature by integrating three clearing methods: agent-based, ultrasound-based, and temporal. Here, optical coherence tomography, Bear–Lambert, and fluorescence tests have been used to study the light penetration depth and optical clearing efficiency. Presented work is an essential step in development of diagnostic techniques for human body, from cells to organs.

Measurement of PMT charge nonlinearity using the continuous light attenuation method

We use a continuous neutral density attenuator to investigate the photomultiplier tube (PMT) charge nonlinearity which exists in the PMT response to external signals to be measured. The results show that this testing approach provides a reliable and practical method for characterizing the PMT nonlinearity, enabling optimization of the operation conditions and improving the measurement accuracy of PMT by mitigating the nonlinearity. This study helps to advance the research and measurements in the related fields using a PMT.

Restoration of Obscured Images

Abstract: For the aim of exploring the deep undersea world map, a picture of high quality without interfering objects is preferred. However, within the water, the image quality tends to be hampered by light scattering, water density, and light attenuation. effects. Besides, the dynamic interference may affect the important underwater map. during this paper, we proposed a multi-step and all-around underwater image processing system, especially for the underwater images taken in succession to enhance the image quality, remove the dynamic interference, and reconstruct the image. The first step involves utilizing the dark channel approach together with the improved gray world algorithm for brightness adaptation and color correction. Initially, it identifies and removes a dynamic interference regarding image enhancement. Secondly, we applied an upgraded total variation model to patch the blank at the value of resolution. Finally, the super-resolution of the small print is realized by applying an improved BP network. After simulation and experiments, our system proved to realize ideal results of image enhancement and reconstruction.