The Impact of Visual-sports Exercises Under Manipulated Lighting Conditions on Static and Functional Balance and Fear of Falling in the Elderly

Light-induced frost tolerance differs in winter and spring wheat plants

In smart interactive environments, such as digital museums or digital exhibition halls, it is important to accurately understand the user’s intent to ensure successful and natural interaction with the exhibition. In the context of predicting user intent, gaze estimation technology has been considered one of the most effective indicators among recently developed interaction techniques (e.g., face orientation estimation, body tracking, and gesture recognition). Previous gaze estimation techniques, however, are known to be effective only in a controlled lab environment under normal lighting conditions. In this study, we propose a novel deep learning-based approach to achieve a successful gaze estimation under various low-light conditions, which is anticipated to be more practical for smart interaction scenarios. The proposed approach utilizes a generative adversarial network (GAN) to enhance users’ eye images captured under low-light conditions, thereby restoring missing information for gaze estimation. Afterward, the GAN-recovered images are fed into the convolutional neural network architecture as input data to estimate the direction of the user gaze. Our experimental results on the modified MPIIGaze dataset demonstrate that the proposed approach achieves an average performance improvement of 4.53%–8.9% under low and dark light conditions, which is a promising step toward further research.

Control strategies used by older adults during multiple obstacle avoidance

Low-light stress will lead to abnormal soybean growth and a subsequent yield reduction. Association mapping is a useful alternative to linkage mapping for the detection of marker–phenotype associations. This study aimed to evaluate low-light-resistant soybean accessions and identify markers associated with low-light resistance. We assessed the plant height, stem diameter, number of bean pods, and cotyledon height of soybean plants under low and normal light conditions. These traits were evaluated in 185 soybean accessions, and the accessions 11HX-020, 11HX-025, 11HX-029, 11HX-064, 11HX-127, 11HX-166, 11HX-183, and 11HX-216 showed stable performance under low-light conditions. These 185 accessions were genotyped with 639 single-nucleotide polymorphism (SNP) markers and 98 simple sequence repeat (SSR) markers. A total of 75 markers—i.e., traits associated with low-light resistance—were identified. These associated markers were distributed on 14 linkage groups (LGs) of soybean, and some markers were associated with two or more traits. According to the results, excellent germplasm material and low-light-resistance related markers can be used for low-light resistance breeding of soybean and will help identify the low-light resistance genes.

Line follower robot is a type of autonomous robot designed to follow a specific trajectory, usually a black line on a white background. In order for the robot to follow the trajectory accurately, a sensor is required that is able to detect the difference in light intensity between the line and the background. This study evaluates the application of a photodiode sensor to a microcontroller-based line follower robot, focusing on the performance of the sensor under various lighting conditions and surfaces. The results show that the photodiode sensor is able to detect lines with high accuracy of almost 100% between black lines on a white surface. To achieve fast response speed and high trajectory stability, the optimal distance between the photodiode sensor and the surface must be maintained. Fast response speed and high trajectory stability are at a distance of 0.5 to 1.0 cm. Under normal lighting conditions (200-300 lux), the robot can follow the trajectory with optimal speed and precision. Under low lighting conditions (below 100 lux), the sensor is still able to detect the line, but the robot speed must be reduced to maintain accuracy. Under very bright lighting conditions (above 500 lux), the photodiode sensor shows a little difficulty in distinguishing lines if there is significant light reflection, but it can still be compensated by adjusting the sensor sensitivity. This research provides a solid foundation for further development in improving the performance of line follower robots in various practical applications.

Increasing the contrast of tread edge highlighters improves stair descent safety in older adults with simulated visual impairment

Regular visual monitoring of pavement defects through autonomous road inspection vehicles is critical to road infrastructure and traffic safety. Since autonomous road inspection vehicles need to operate reliably 24/7, automatic road crack segmentation under low-light conditions is particularly important for detecting road defects. However, most existing segmentation methods are designed for crack images captured under normal illumination conditions, resulting in a drastic degradation in performance when applied to low-light crack images. Low-light environments present challenges for crack segmentation due to insufficient photons and undesirable noise. To enhance crack segmentation in low-light conditions for autonomous road inspection vehicles, we propose a Cross-Light Contrastive Network(CLCNet) that incorporates normal-light crack images as auxiliary information. CLCNet comprises both light-level contrastive learning and segmentation-level contrastive learning components. Light-level contrastive learning treats images under different lighting conditions as distinct domains, aiming to learn illumination-robust features through style matrix analysis. Segmentation-level contrastive learning, on the other hand, ensures that embeddings from the same semantic class are more similar than those from different classes by comparing pixel-level embeddings. Our CLCNet can be implemented based on mainstream crack segmentation architectures and trained end-to-end using conventional crack segmentation datasets such as Crack500 and DeepCrack. We achieved superior performance over recent segmentation networks in both low-light and normal-light conditions.

The impact of low light intensities on plant disease outbreaks represents a major challenge for global crop security, as it frequently results in significant yield losses. However, the underlying mechanisms of the effect of low light on plant defense are still poorly understood. Here, using an RNA-seq approach, we found that the susceptibility of tomato to Pseudomonas syringae pv. tomato DC3000 (Pst DC3000) under low light was associated with the oxidation-reduction process. Low light conditions exacerbated Pst DC3000-induced reactive oxygen species (ROS) accumulation and protein oxidation. Analysis of gene expression and enzyme activity of ascorbate peroxidase 2 (APX2) and other antioxidant enzymes revealed that these defense responses were significantly induced by Pst DC3000 inoculation under normal light, whereas these genes and their associated enzyme activities were not responsive to pathogen inoculation under low light. Additionally, the reduced ascorbate to dehydroascorbate (AsA/DHA) ratio was lower under low light compared with normal light conditions upon Pst DC3000 inoculation. Furthermore, the apx2 mutants generated by a CRISPR-Cas9 gene-editing approach were more susceptible to Pst DC3000 under low light conditions. Notably, this increased susceptibility could be significantly reduced by exogenous AsA treatment. Collectively, our findings suggest that low-light-induced disease susceptibility is associated with increased cellular oxidative stress in tomato plants. This study sheds light on the intricate relationship between light conditions, oxidative stress, and plant defense responses, and may pave the way for improved crop protection strategies in low light environments.

This paper presents a new method for 3D face pose tracking in arbitrary illumination change conditions using color image and depth data acquired by RGB-D cameras (e.g., Microsoft Kinect, Asus Xtion Pro Live, etc.). The method is based on an optimization process of an objective function combining photometric and geometric energy. The geometric energy is computed from depth data while the photometric energy is computed at each frame by comparing the current face texture to its corresponding in the reference face texture defined in the first frame. To handle the effect of changing lighting condition, we use a facial illumination model in order to solve which lighting variations has to be applied to the current face texture making it as close as possible to the reference texture. We demonstrate the accuracy and the robustness of our method in normal lighting conditions by performing a set of experiments on the Biwi Kinect head pose database. Moreover, the robustness to illumination changes is evaluated using a set of sequences for different persons recorded in severe lighting condition changes. These experiments show that our method is robust and precise under both normal and severe lighting conditions.

RNA interference was used to simultaneously suppress the expression of the two genes that encode the PsbQ proteins of Photosystem II (PS II) in Arabidopsis thaliana, psbQ-1 (At4g21280) and psbQ-2 (At4g05180). Two independent PsbQ-deficient plant lines were examined. These plant lines produced little detectable PsbQ protein. Under normal growth light conditions, the wild type and mutant plants were visually indistinguishable. Additionally, analysis of steady state oxygen evolution rates and chlorophyll fluorescence characteristics indicated little alteration of photosynthetic capacity in the mutant plants. No loss of other PS II proteins was evident. Interestingly, flash oxygen yield analysis performed on thylakoid membranes isolated from the mutant and wild type plants indicated that the oxygen-evolving complex was quite unstable in the mutants. Furthermore, the lifetime of the S2 state of the oxygen-evolving complex appeared to be increased in these plants. Incubation of the wild type and mutant plants under low light growth conditions led to a significantly stronger observed phenotype in the mutants. The mutant plants progressively yellowed (after 2 weeks) and eventually died (after 3-4 weeks). The wild type plants exhibited only slight yellowing after 4 weeks under low light conditions. The mutant plants exhibited a large loss of a number of PS II components, including CP47 and the D2 protein, under low light conditions. Additionally, significant alterations of their fluorescence characteristics were observed, including an increased FO and decreased FV, yielding a large loss in PS II quantum efficiency (FV/FM). Analysis of QA- decay kinetics in the absence of 3-(3,4-dichlorophenyl)-1,1-dimethyl urea indicated a defect in electron transfer from QA- to QB, whereas experiments performed in the presence of this herbicide indicated that the recombination rate between QA- and the S2 state was strongly retarded. These results indicate that the loss of the PsbQ protein induces significant changes in Photosystem II function, particularly in low light-grown plants, and that the PsbQ protein is required for photoautotrophic growth under low light conditions.

Are there differences in muscular activation to maintain balance between individuals with chronic obstructive pulmonary disease and controls?

Metabolic flux of the oxidative pentose phosphate pathway under low light conditions in Synechocystis sp. PCC 6803

Factors contributing to enhanced freezing tolerance in wheat during frost hardening in the light

This study investigates the effect of normal and low light conditions on the anthesis, flowering, maturity, and growth parameters of different rice genotypes (Oryza sativa L.). The results demonstrate that low light intensity delays flowering initiation and extends the duration to 50% and 100% flowering, with variations across early, medium, and late genotypes. The time to maturity also increases under low light conditions, while plant height, number of leaves, and tillers per hill show significant changes. Specifically, low light stress enhances plant height but reduces leaf and tiller numbers, likely due to impaired photosynthesis. These findings are consistent with previous research indicating that low light negatively impacts growth and development by limiting energy production for vegetative and reproductive processes.

BackgroundIn northwest of China, mini Chinese cabbage (Brassica pekinensis) is highly valued by consumers, and is widely cultivated during winter in solar-greenhouses where low light (LL) fluence (between 85 and 150 μmol m−2 s−1 in day) is a major abiotic stress factor limiting plant growth and crop productivity. The mechanisms with which various NH4+: NO3− ratios affected growth and photosynthesis of mini Chinese cabbage under normal (200 μmol m−2 s−1) and low (100 μmol m−2 s−1) light conditions was investigated. The four solutions with different ratios of NH4+: NO3− applied were 0:100, 10:90, 15:85 and 25:75 with the set up in a glasshouse in hydroponic culture. The most appropriate NH4+: NO3− ratio that improved the tolerance of mini Chinese cabbage seedlings to LL was found in our current study.ResultsUnder low light, the application of NH4+: NO3− (10:90) significantly stimulated growth compared to only NO3− by increasing leaf area, canopy spread, biomass accumulation, and net photosynthetic rate. The increase in net photosynthetic rate was associated with an increase in: 1) maximum and effective quantum yield of PSII; 2) activities of Calvin cycle enzymes; and 3) levels of mRNA relative expression of several genes involved in Calvin cycle. In addition, glucose, fructose, sucrose, starch and total carbohydrate, which are the products of CO2 assimilation, accumulated most in the cabbage leaves that were supplied with NH4+: NO3− (10:90) under LL condition. Low light reduced the carbohydrate: nitrogen (C: N) ratio while the application of NH4+: NO3− (10:90) alleviated the negative effect of LL on C: N ratio mainly by increasing total carbohydrate contents.ConclusionsThe application of NH4+:NO3− (10:90) increased rbcL, rbcS, FBA, FBPase and TK expression and/or activities, enhanced photosynthesis, carbohydrate accumulation and improved the tolerance of mini Chinese cabbage seedlings to LL. The results of this study would provide theoretical basis and technical guidance for mini Chinese cabbage production. In practical production, the ratio of NH4+:NO3− should be adjusted with respect to light fluence for successful growing of mini Chinese cabbage.