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In the realm of computer vision, object detection holds significant importance and has demonstrated commendable performance across various scenarios. However, it typically requires favorable visibility conditions within the scene. Therefore, it is imperative to explore methodologies for conducting object detection under low-visibility circumstances. With its balanced combination of speed and accuracy, the state-of-the-art YOLOv8 framework has been recognized as one of the top algorithms for object detection, demonstrating outstanding performance results across a range of standard datasets. Nonetheless, current YOLO-series detection algorithms still face a significant challenge in detecting objects under low-light conditions. This is primarily due to the significant degradation in performance when detectors trained on illuminated data are applied to low-light datasets with limited visibility. To tackle this problem, we suggest a new model named Grouping Offset and Isolated GiraffeDet Target Detection-YOLO based on the YOLOv8 architecture. The proposed model demonstrates exceptional performance under low-light conditions. We employ the repGFPN feature pyramid network in the design of the feature fusion layer neck to enhance hierarchical fusion and deepen the integration of low-light information. Furthermore, we refine the repGFPN feature fusion layer by introducing a sampling map offset to address its limitations in terms of weight and efficiency, thereby better adapting it to real-time applications in low-light environments and emphasizing the potential features of such scenes. Additionally, we utilize group convolution to isolate interference information from detected object edges, resulting in improved detection performance and model efficiency. Experimental results demonstrate that our GOI-YOLO reduces the parameter count by 11% compared to YOLOv8 while decreasing computational requirements by 28%. This optimization significantly enhances real-time performance while achieving a competitive increase of 2.1% in Map50 and 0.6% in Map95 on the ExDark dataset.

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This publication presents an annotated accident dataset which fuses traffic data from radar detection sensors, weather condition data, and light condition data with traffic accident data (as illustrated in Fig. 1) in a format that is easy to process using machine learning tools, databases, or data workflows. The purpose of this data is to analyze, predict, and detect traffic patterns when accidents occur. Each file contains a timeseries of traffic speeds, flows, and occupancies at the sensor nearest to the accident, as well as 5 neighboring sensors upstream and downstream. It also contains information about the accident type, date, and time. In addition to the accident data, we provide baseline data for typical traffic patterns during a given time of day. Overall, the dataset contains 6 months of annotated traffic data from November 2020 to April 2021. During this timeframe, and 361 accidents occurred in the monitored area around Chattanooga, Tennessee. This dataset served as the basis for a study on topology-aware automated accident detection for a companion publication [1].

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Camera-based object detection is integral to advanced driver assistance systems (ADAS) and autonomous vehicle research, and RGB cameras remain indispensable for their spatial resolution and color information. This study investigates exposure time optimization for such cameras, considering image quality in dynamic ADAS scenarios. Exposure time, the period during which the camera sensor is exposed to light, directly influences the amount of information captured. In dynamic scenarios, such as those encountered in typical driving scenarios, optimizing exposure time becomes challenging due to the inherent trade-off between Signal-to-Noise Ratio (SNR) and motion blur, i.e., extending exposure time to maximize information capture increases SNR, but also increases the risk of motion blur and overexposure, particularly in low-light conditions where objects may not be fully illuminated. The study introduces a comprehensive methodology for exposure time optimization under various lighting conditions, examining its impact on image quality and computer vision performance. Traditional image quality metrics show a poor correlation with computer vision performance, highlighting the need for newer metrics that demonstrate improved correlation. The research presented in this paper offers guidance into the enhancement of single-exposure camera-based systems for automotive applications. By addressing the balance between exposure time, image quality, and computer vision performance, the findings provide a road map for optimizing camera settings for ADAS and autonomous driving technologies, contributing to safety and performance advancements in the automotive landscape.

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Plant cell suspension cultures (PCSCs) are in vitro-cultured cells that can divide indefinitely in a sterile growth medium. These PCSCs can be derived from various plant tissues, such as the root, stem, leaves, or seeds, and are maintained in a suitable culture medium containing nutrients, vitamins, hormones, and other essential components necessary for their growth. PCSCs have extensive applications in biotechnology, particularly in producing pharmaceutical and chemical compounds. This chapter presents a protocol for generating cell lines from Arabidopsis thaliana root callus under different light conditions, which can be used to investigate the effects of light on plant cell growth and development. The protocol described in this chapter is a valuable tool for researchers interested in utilizing PCSCs in their studies.

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In recent years, significant advances have been made in the development of Advanced Driver Assistance Systems (ADAS) and other technology for autonomous vehicles. Automated object detection is a crucial component of autonomous driving; however, there are still known issues that affect its performance. For automotive applications, object detection algorithms are required to perform at a high standard in all lighting conditions; however, a major problem for object detection is poor performance in low-light conditions due to objects being less visible. This study considers the impact of training data composition on object detection performance in low-light conditions. In particular, this study evaluates the effect of different combinations of images of outdoor scenes, from different times of day, on the performance of deep neural networks, and considers the different challenges encountered during the training of a neural network. Through experiments with a widely used public database, as well as a number of commonly used object detection architectures, we show that more robust performance can be obtained with an appropriate balance of classes and illumination levels in the training data. The results also highlight the potential of adding images obtained in dusk and dawn conditions for improving object detection performance in day and night.

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Viruses can spread through contaminated aerosols and contaminated surface materials, and effective disinfection techniques are essential for virus inactivation. Nonthermal plasma-generated reactive oxygen and nitrogen species can effectively inactivate the coronavirus. We aim to interpret the coronavirus inactivation level and mechanism of surface interaction with materials with and without dielectric barrier discharge (DBD) plasma treatment. Nonthermal plasma, particularly surface-type DBD plasma, can inactivate human coronavirus 229E (HCoV-229E) on porous (paper, wood, mask) and nonporous (plastic, stainless steel, glass, Cu) materials. Virus inactivation was analyzed using a 50% tissue culture infectivity dose (TCID50) using cell line, flow cytometry, and immunofluorescence. Surfaces contaminated with HCoV-229E were treated at different time intervals (0-5 h) with and without plasma exposure (natural decay in ambient air conditions). HCoV-229E persistence conformed to the following order: plastic > cover glass > stainless steel > mask > wood > paper > Cu with and without plasma exposure. HCoV-229E was more stable in plastic, cover glass, and stainless steel in 5 h, and the viable virus titer gradually decreased from its initial log10 order of 6.892 to 1.72, 1.53, and 1.32 TCID50/mL, respectively, under plasma exposure. No virus was observed in Cu after treatment for 5 h. The use of airflow, ambient nitrogen, and argon did not promote virus inactivation. Flow cytometry and immunofluorescence analysis demonstrated a low expression level of spike protein (fluorescence intensity) during plasma treatment and in E and M genes expression compared with the virus control.

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Lighting conditions are an important factor affecting dry-cured products. This study investigated the effects of treatments with different light intensities (0 lx, 1000 lx, 25000 lx) and different light sources including red light, blue light, UV-light on oxidation leve and flavor change in dry-cured Wuchang fish. The results showed that dry-cured Wuchang fish exhibited an attractive brown-yellow color, the highest oxidation degree of myoglobin (Mb), the highest fat oxidation under the light conditions of 25000 lx light intensity and UV-light irradiation. This phenomenon was observed that the degree of Mb oxidation was increased, while the degree of fat oxidation was increased. At 25000 lx light intensity and UV-light irradiation, dry-cured Wuchang fish showed an ignificantly decreased fatty acid conten (especially oleic acid and linoleic acid), significantly increased characteristic volatile compound contents (22 for 25,000 lx light intensity and 27 for UV-light irradiation), which contributed to the improvement of quality stability of dry-cured Wuchang fish. Our findings provide theoretical support for the industrial application of exogenous light in dry-cured Wuchang fish.

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Plants can activate protective and defense mechanisms under biotic and abiotic stresses. Their roots naturally grow in the soil, but when they encounter sunlight in the top-soil layers, they may move away from the light source to seek darkness. Here we investigate the skototropic behavior of roots, which promotes their fitness and survival. Glutamate-like receptors (GLRs) of plants play roles in sensing and responding to signals, but their role in root skototropism is not yet understood. Light-induced tropisms are known to be affected by auxin distribution, mainly determined by auxin efflux proteins (PIN proteins) at the root tip. However, the role of PIN proteins in root skototropism has not been investigated yet. To better understand root skototropism and its connection to the distance between roots and light, we established five distance settings between seedlings and darkness to investigate the variations in root bending tendencies. We compared differences in root skototropic behavior across different expression lines of Arabidopsis thaliana seedlings (atglr3.7 ko, AtGLR3.7 OE, and pin2 knockout) to comprehend their functions. Our research shows that as the distance between roots and darkness increases, the root's positive skototropism noticeably weakens. Our findings highlight the involvement of GLR3.7 and PIN2 in root skototropism.

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Overwintering plants survive subzero temperatures by cold acclimation (CA), wherein they acquire freezing tolerance through short-term exposure to low temperatures above 0°C. The freezing tolerance of CA plants increases when they are subsequently exposed to mild subzero temperatures, a phenomenon known as second-phase cold hardening (2PH). Here, we explored the molecular mechanism and physiological conditions of 2PH. The results show that, compared with supercooling, a freezing treatment during 2PH after CA enhanced the freezing tolerance of Arabidopsis. This required CA as a pretreatment, and was designated as second-phase freezing acclimation (2PFA). Light increased the effect of 2PFA to enhance freezing tolerance after CA. C-repeat binding factor and cold-regulated genes were downregulated by light during the 2PFA treatment, a different transcription profile from that during CA. The freezing tolerance of 2PFA plants was decreased by the presence of the photosynthetic electron transfer inhibitor 3-(3,4-dichlorophenyl)-1,1-dimethylurea during the 2PFA treatment. Compared with wild-type plants, phototropin1,2 and phyb mutants showed lower freezing tolerance after 2PFA treatment. These results show that exposure to freezing after CA increases freezing tolerance as a secondary process, and that freezing under light conditions further increases freezing tolerance via pathways involving photoreceptors and photosynthetic electron transfer.

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Historically, forest thinning in Japan was conducted to obtain high-quality timber from plantations. Today, in contrast, thinning is also motivated by forest water balance and climate change considerations. It is in this context that the present study examines the effects of thinning on the ecophysiological responses of remaining trees, which are inadequately understood, especially in relation to changes in the magnitude and duration of transpiration. Sap flux densities were measured in both outer and inner sapwood to obtain stand-scale transpiration for two years in the pre-thinning state and three years post-thinning. The effects of thinning on transpiration were quantitatively evaluated based on canopy conductance models. The larger increases in outer sap flux density were found in the first year after the treatment, while those in inner sap flux density were detected in the second and third years. The remaining trees required a few of years to adjust to improved light conditions of the lower crown, resulting in a delayed response of inner sap flux density. As a result of this lag, transpiration was reduced to 71 % of the pre-thinning condition in the first year, but transpiration recovered to the pre-thinning levels in the second and third years due to compensating contributions from inner sap flow. In terms of more accurately chronicling the thinning effect, the distribution of sap flux density with respect to its radial pattern, is necessary. Such measurements are key to more comprehensively examining the ecophysiological response of forest plantations to thinning and, ultimately, its effect on the forest water balance.

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The light conditions are of utmost importance in any microalgae production process especially involving artificial illumination. This also applies to a chrysolaminarin (soluble 1,3-ß-glucan) production process using the diatom Phaeodactylum tricornutum. Here we examine the influence of the amount of light per gram biomass (specific light availability) and the influence of two different biomass densities (at the same amount of light per gram biomass) on the accumulation of the storage product chrysolaminarin during nitrogen depletion in artificially illuminated flat-panel airlift photobioreactors. Besides chrysolaminarin, other compounds (fucoxanthin, fatty acids used for energy storage [C16 fatty acids], and eicosapentaenoic acid) are regarded as well. Our results show that the time course of C-allocation between chrysolaminarin and fatty acids, serving as storage compounds, is influenced by specific light availability and cell concentration. Furthermore, our findings demonstrate that with increasing specific light availability, the maximal chrysolaminarin content increases. However, this effect is limited. Beyond a certain specific light availability (here: 5 µmolphotons gDW -1 s-1 ) the maximal chrysolaminarin content no longer increases, but the rate of increase becomes faster. Furthermore, the conversion of light to chrysolaminarin is best at the beginning of nitrogen depletion. Additionally, our results show that a high biomass concentration has a negative effect on the maximal chrysolaminarin content, most likely due to the occurring self-shading effects.

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Selecting suitable light conditions according to the plant growth characteristics is one of the important approaches to cultivating high-quality vegetable seedlings. To determine the more favorable LED light conditions for producing high-quality tomato and cucumber seedlings in plant factories with artificial light (PFALS), the growth characteristics of tomato and cucumber seedlings under seven LED light environments (CK, B, UV-A, FR, B+UV-A, UV-A+FR, and B+FR) and the development of these seedlings after transplanting into a plastic greenhouse were investigated. The results showed that the seedling height and hypocotyl length increased in treatments with far-red light supplementation (FR, UV-A+FR, and B+FR), but decreased in the B treatment, in both varieties. The seedling index of tomato seedlings increased in the B+UV-A treatment, while that of cucumber seedlings increased in the FR treatment. After transplanting into a plastic greenhouse, tomato plants that radiated with UV-A had greater flower numbers on the 15th day after transplanting. In cucumber plants of the FR treatment, the flowering time was significantly delayed, and the female flower exhibited at a lower node position. By using a comprehensive scoring analysis of all detected indicators, light environments with UV-A and FR were more beneficial for improving the overall quality of tomato and cucumber seedlings, respectively.

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Images captured under complex conditions frequently have low quality, and image performance obtained under low-light conditions is poor and does not satisfy subsequent engineering processing. The goal of low-light image enhancement is to restore low-light images to normal illumination levels. Although many methods have emerged in this field, they are inadequate for dealing with noise, color deviation, and exposure issues. To address these issues, we present CGAAN, a new unsupervised generative adversarial network that combines a new attention module and a new normalization function based on cycle generative adversarial networks and employs a global-local discriminator trained with unpaired low-light and normal-light images and stylized region loss. Our attention generates feature maps via global and average pooling, and the weights of different feature maps are calculated by multiplying learnable parameters and feature maps in the appropriate order. These weights indicate the significance of corresponding features. Specifically, our attention is a feature map attention mechanism that improves the network's feature-extraction ability by distinguishing the normal light domain from the low-light domain to obtain an attention map to solve the color bias and exposure problems. The style region loss guides the network to more effectively eliminate the effects of noise. The new normalization function we present preserves more semantic information while normalizing the image, which can guide the model to recover more details and improve image quality even further. The experimental results demonstrate that the proposed method can produce good results that are useful for practical applications.

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The circadian clock mechanism, which is evolutionarily conserved across various organisms, plays a crucial role in synchronizing physiological responses to external conditions, primarily in response to light availability. By maintaining homeostasis of biological processes and behavior, the circadian clock serves as a key regulator. This biological mechanism also coordinates diurnal oscillations of the immune response during infections. However there is limited information available regarding the influence of circadian oscillation on immune regulation, especially in lower vertebrates like teleost fish. Therefore, the present study aimed to investigate the effects of light and the timing of infection induction on the antiviral immune response in zebrafish. To explore the relationship between the timing of infection and the response activated by viral pathogens, we used a zebrafish model infected with tilapia lake virus (TiLV). Our findings demonstrated that light availability significantly affects the antiviral immune response and the functioning of the molecular clock mechanism during TiLV infection. This is evident through alterations in the expression of major core clock genes and the regulation of TiLV replication and type I IFN pathway genes in the kidney of fish maintained under LD (light-dark) conditions compared to constant darkness (DD) conditions. Moreover, infection induced during the light phase of the LD cycle, in contrast to nocturnal infection, also exhibited similar effects on the expression of genes associated with the antiviral response. This study indicates a more effective mechanism of the zebrafish antiviral response during light exposure, which inherently involves modification of the expression of key components of the molecular circadian clock. It suggests that the zebrafish antiviral response to infection is regulated by both light and the circadian clock.

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Trematodes localizing in the lenses of fish change the behavior of their hosts. These behavioral changes are widely suggested to be parasitic manipulations of host behavior aimed at increasing the possibility of eye flukes completing their life cycle. It is often assumed that fish change their behavior due to the vision deterioration caused by trematode larvae. We checked this assumption by testing Salvelinus malma infected with eye flukes (Diplostomum pseudospathaceum) under different lighting conditions. We suggested that if the parasite alters the host's behavior through vision impairment, then in the dark (when fish do not rely on vision to navigate), the difference in the behavior of infected and uninfected fish would disappear. Eye flukes, indeed, changed fish behavior, making their hosts less vigilant. We believe this is the first evidence of possible parasitic manipulation in this study system. However, contrary to expectations, the difference in the behavior of infected and control fish was independent of the lighting conditions. Our results suggest that mechanisms of behavioral change other than vision impairment should be taken into account in this fish-eye fluke study system.

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Temporally heterogeneous environments is hypothesized to correlate with greater plasticity of plants, which has rarely been supported by direct evidence. To address this issue, we subjected three species from different ranges of habitats to a first round of alternating full light and heavy shading (temporally heterogeneous light experience), constant moderate shading and full light conditions (temporally homogeneous light experiences, control) and a second round of light-gradient treatments. We measured plant performance in a series of morphological, biomass, physiological and biochemical traits at the end of each round. Compared to constant full light experience, temporally heterogeneous light conditions induced immediate active biochemical responses (in the first round) with improved late growth in biomass (during the second round); constant moderate shading experience increased photosynthetic physiological and biomass performances of plants in early response, and decreased their late growth in biomass. The karst endemic species of Kmeria septentrionalis showed greater improvement in late growth of biomass and lower decrease in biochemical performance, due to early heterogeneous experience, compared to the non-karst species of Lithocarpus glaber and the karst adaptable species of Celtis sinensis. Results suggested plants will prefer to produce morphological and physiological responses that are less reversible and more costly in the face of more reliable environmental cues at early stage in spite of decreased future growth potential, but to produce immediate biochemical responses for higher late growth potential when early environmental cues are less reliable, to avoid the loss of high costs and low profits. Typical karst species should be more able to benefit from early temporally heterogeneous experience, due to long-term adaptation to karst habitats of high environmental heterogeneity and low resource availability.

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Estimation of age-at-death represents a central focus in forensic human identification, as it is a key parameter used in the identification of unidentified bodies. In 1992, Lamendin et al. published a simple technique for estimating the age-at-death of adult skeletal remains based on two dental criteria: the gingival regression and the extent of dentine translucency. Although Lamendin's technique is widely used in forensic contexts and the evaluation of root translucency is a key element in the technique, the light conditions for measuring this parameter have not been adequately established. The aim of the present study is to analyse the influence of colour temperature and illuminance level of a LED light source when root translucency is evaluated to optimize the use of Lamendin's technique for age-at-death estimation. The results describe how light settings may affect the visual perception of root translucency by different examiners and, therefore, affect the accuracy of the age-at-death estimation methods and techniques based on this parameter.

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Light, as a primary source of energy, directly or indirectly influences virtually all morphological modifications occurring in both shoots and roots. A pot experiment was conducted to assess the growth patterns of one-year-old Pleioblastus pygmaeus plants' rhizome-root systems and their responses to different light intensities from 11 March to 26 December 2016. The experiment design scheme was 3.87% (L1), 11.25% (L2), 20.25% (L3), 38.76% (L4), 60.70% (L5), and 100% full sunlight (control CK). The results indicated that along the growing period from March to December, eight of the eleven studied parameters of the rhizome-root system showed significant variability and diverse growth patterns. In addition, light intensity is a key factor for determining P. pygmaeus plants' rhizome and root growth. Specifically, the light intensity had a significant, positive, and linear/or almost linear impact on the number of old and new rhizomes, old rhizome length, new rhizome diameter, as well as the culm root diameter. A nonlinear and positive relationship was found between light intensity and the listed three parameters, i.e., new rhizome length, new rhizome internode length, and rhizome root length. The value of the above-mentioned three parameters significantly increased when affected from 0% to 40-60% of full sunlight and then gradually increased until 100% of full sunlight. The ratio of aboveground dry weight to underground dry weight (A/U ratio) showed a single peak curve with increasing light intensity and presented the highest value under ca. 55% full sunlight. Furthermore, 40% full sunlight (equal to an average light of 2232 lux) might be the threshold for P. pygmaeus rhizome-root system growth. When the light intensity was below 40%, the generalized additive models (GAMs) predicted value of most studied parameters decreased to lower than zero. In conclusion, current study provides a solid basis for understanding the dynamic growth and development of P. pygmaeus rhizome-root system, and its responses to different light conditions, which could be used as inputs to P. pygmaeus plant cultivation.

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Elevational changes in vegetation are associated with changes in environmental factors, an example of which is provided by the shade-tolerant Abies mariesii and less shade-tolerant Abies veitchii, which dominate forests at high and low elevations, respectively, in subalpine zones of central Japan. In this study, we sought to establish the factors underlying the differential elevational dominance of these two species from the perspective of sapling growth and survival. It is assumed that the growth and survival of saplings is greater at higher rates of surplus production (the value obtained by subtracting the minimum net production to maintain the current sapling leaf mass from the total net production), as sapling leaf mass gradually declines with time if saplings cannot maintain the current sapling leaf mass, thereby increasing the risk of premature mortality. In this regard, we aimed to verify the following two hypotheses: (1) at low elevations, the surplus production rate of A. veitchii is greater than that of A. mariesii in canopy gaps, and vice versa in the forest understory; and (2) at high elevation, the surplus production rate of A. mariesii is greater than that of A. veitchii in both forest understory and canopy gaps. The results obtained in this study were consistent with our two stated hypotheses. In addition, at the low elevation site, the rate of the growth in height of A. veitchii in canopy gaps was greater than that of A. mariesii, indicating that A. veitchii can dominate after disturbance at low elevations. The findings of this study indicate that the differential elevational distribution of the two Abies species can be attributed to interspecific differences in surplus production rates. We believe that these findings will be useful for predicting changes in the distribution of vegetation in response to climate change.

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In the past years, several works on urban object detection from the point of view of a person have been made. These works are intended to provide an enhanced understanding of the environment for blind and visually challenged people. The mentioned approaches mostly rely in deep learning and machine learning methods. Nonetheless, these approaches only work with direct and bright light, namely, they will only perform correctly on daylight conditions. This is because deep learning algorithms require large amounts of data and the currently available datasets do not address this matter. In this work, we propose UrOAC, a dataset of urban objects captured in a range of different lightning conditions, from bright daylight to low and poor night-time lighting conditions. In the latter, the objects are only lit by low ambient light, street lamps and headlights of passing-by vehicles. The dataset depicts the following objects: pedestrian crosswalks, green traffic lights and red traffic lights. The annotations include the category and the bounding-box of each object. This dataset could be used for improve the performance at night-time and under low-light conditions of any vision-based method that involves urban objects. For instance, guidance and object detection devices for the visually challenged or self-driving and intelligent vehicles.