With rising melanoma incidence and mortality, early detection and surgical removal of primary lesions is essential. Multispectral imaging is a new, non-invasive technique that can facilitate skin cancer detection by measuring the reflectance spectra of biological tissues. Currently, incident illumination allows little light to be reflected from deeper skin layers due to high surface reflectance. A pilot study was conducted at the University Hospital Basel to evaluate, whether multispectral imaging with direct light coupling could extract more information from deeper skin layers for more accurate dignity classification of melanocytic lesions. 27 suspicious pigmented lesions from 23 patients were included (6 melanomas, 6 dysplastic nevi, 12 melanocytic nevi, 3 other). Lesions were imaged before excision using a prototype snapshot mosaic multispectral camera with incident and direct illumination with subsequent dignity classification by a pre-trained multispectral image analysis model. Using incident light, a sensitivity of 83.3% and a specificity of 58.8% were achieved compared to dignity as determined by histopathological examination. Direct light coupling resulted in a superior sensitivity of 100% and specificity of 82.4%. Convolutional neural network classification of corresponding red, green, and blue lesion images resulted in 16.7% lower sensitivity (83.3%, 5/6 malignant lesions detected) and 20.9% lower specificity (61.5%) compared to direct light coupling with multispectral image classification. Our results show that incorporating direct light multispectral imaging into the melanoma detection process could potentially increase the accuracy of dignity classification. This newly evaluated illumination method could improve multispectral applications in skin cancer detection. Further larger studies are needed to validate the camera prototype.

Greenhouses located at high latitudes and in cloudy areas often experience a low quality and quantity of light, especially during autumn and winter. This low daily light integral (DLI) reduces production rate, quality, and nutritional value of many crops. This study was conducted on Sakhiya RZ F1 tomato plants to evaluate the impact of LED lights on the growth and nutritional value of tomatoes in a greenhouse with low daily light due to cloudy weather. The treatments included LED growth lights in three modes: top lighting, intra-canopy lighting, and combined top and intra-canopy lighting. The results showed that although the combined top and intra-canopy lighting reached the maximum increase in tomato yield, exposure to intra-canopy LED lighting alone outperformed in tomato fruit yield increase (28.46%) than exposure to top LED lighting alone (12.12%) when compared to no supplemental lighting during the entire production year. Intra-canopy exposure demonstrated the highest increase in tomato lycopene (31.3%), while top and intra-canopy lighting exhibited the highest increase in vitamin C content (123.4%) compared to the control. The LED light treatment also had a very positive effect on the expression of genes responsible for metabolic cycles, including Psy1, LCY-β, and VTC2 genes, which had collinearity with the increase in tomato fruit production.

Nighttime driving presents a critical challenge to road safety due to insufficient lighting and increased risk of driver fatigue. Existing methods for monitoring driver fatigue, mainly focusing on behavioral analysis and biometric monitoring, face significant challenges under low-light conditions. Their effectiveness, especially in dynamic lighting environments, is limited by their dependency on specific environmental conditions and active driver participation, leading to reduced accuracy and practicality in real-world scenarios. This study introduces a novel \'Illumination Intelligent Adaptation and Analysis Framework (IIAAF)\', aimed at addressing these limitations and enhancing the accuracy and practicality of driver fatigue monitoring under nighttime low-light conditions. The IIAAF framework employs a multidimensional technology integration, including comprehensive body posture analysis and facial fatigue feature detection, per-pixel dynamic illumination adjustment technology, and a light variation feature learning system based on Convolutional Neural Networks (CNN) and time-series analysis. Through this integrated approach, the framework is capable of accurately capturing subtle fatigue signals in nighttime driving environments and adapting in real-time to rapid changes in lighting conditions. Experimental results on two independent datasets indicate that the IIAAF framework significantly improves the accuracy of fatigue detection under nighttime low-light conditions. This breakthrough not only enhances the effectiveness of driving assistance systems but also provides reliable scientific support for reducing the risk of accidents caused by fatigued driving. These research findings have significant theoretical and practical implications for advancing intelligent driving assistance technology and improving nighttime road safety.

In the deep-sea environment, the volume available for an in-situ gene sequencer is severely limited. In addition, optical imaging systems are subject to real-time, large-scale defocusing problems caused by ambient temperature fluctuations and vibrational perturbations. To address these challenges, we propose an edge detection algorithm for defocused images based on grayscale gradients and establish a defocus state detection model with nanometer resolution capabilities by relying on the inherent critical illumination light field. The model has been applied to a prototype deep-sea gene sequencing microscope with a 20× objective. It has demonstrated the ability to focus within a dynamic range of ±40 μm with an accuracy of 200 nm by a single iteration within 160 ms. By increasing the number of iterations and exposures, the focusing accuracy can be refined to 78 nm within a dynamic range of ±100 μm within 1.2 s. Notably, unlike conventional photoelectric hill-climbing, this method requires no additional hardware and meets the wide dynamic range, speed, and high-accuracy autofocusing requirements of deep-sea gene sequencing in a compact form factor.

Current international optical science research focuses on the non-visual effects of lighting on human cognition, mood, and biological rhythms to enhance overall well-being. Nocturnal roadway lighting, in particular, has a substantial impact on drivers\' physiological and psychological states, influencing behavior and safety. This study investigates the non-visual effects of correlated color temperature (CCT: 3000K vs. 4000K vs. 5000K) and illuminance levels (20 lx vs. 30 lx) of urban motor vehicle road lighting on driver alertness during various driving tasks. Conducted between 19:00 and 20:30, the experiments utilized a human-vehicle-light simulation platform. EEG (β waves), reaction time, and subjective evaluations using the Karolinska Sleepiness Scale (KSS) were measured. The results indicated that the interaction between CCT and illuminance, as well as between CCT and task type, significantly influenced driver alertness. However, no significant effect of CCT and illuminance on reaction time was observed. The findings suggest that higher illuminance (30 lx) combined with medium CCT (4000K) effectively reduces reaction time. This investigation enriches related research, provides valuable reference for future studies, and enhances understanding of the mechanisms of lighting\'s influence on driver alertness. Moreover, the findings have significant implications for optimizing the design of urban road lighting.

In the context in which severe visual impairment significantly affects human life, this article emphasizes the potential of Artificial Intelligence (AI) and Visible Light Communications (VLC) in developing future assistive technologies. Toward this path, the article summarizes the features of some commercial assistance solutions, and debates the characteristics of VLC and AI, emphasizing their compatibility with blind individuals\' needs. Additionally, this work highlights the AI potential in the efficient early detection of eye diseases. This article also reviews the existing work oriented toward VLC integration in blind persons\' assistive applications, showing the existing progress and emphasizing the high potential associated with VLC use. In the end, this work provides a roadmap toward the development of an integrated AI-based VLC assistance solution for visually impaired people, pointing out the high potential and some of the steps to follow. As far as we know, this is the first comprehensive work which focuses on the integration of AI and VLC technologies in visually impaired persons\' assistance domain.

The City of Toronto adopted a Vision Zero strategy in 2016 that aims to eliminate deaths and serious injuries from vehicular collisions. The strategy includes policies to improve lighting to reduce collision risks, and past research has suggested lighting as a road safety factor. We apply Bayesian spatial analysis (including Poisson log-normal regression modelling, shared component spatial modelling, and Bayesian spatiotemporal modelling) to publicly available data on traffic collisions where persons are killed or seriously injured (KSI) based on Day/Dark conditions. We assess (1) links between KSI risk and socioeconomic and built environment factors, (2) spatial distributions of relative Day & Dark KSI risk, and (3) area-specific trends in space and time for Day-Dark KSI risk change across Toronto neighbourhoods. Our analysis does not find significant associations between socioeconomic/built environment factors and KSI risk, but we uncover neighbourhoods with heightened Dark KSI risk and pronounced Day-Dark KSI changes compared to Toronto\'s mean area trend. Findings highlight the need for increased policy attention for impacts of lighting on collisions and provide insight for focus regions for improved Vision Zero policy development.

UNASSIGNED: The purpose of this study was to determine the effects of ambient lighting on intraocular pressure (IOP) rhythmicity and variability.
UNASSIGNED: IOP was continuously recorded by wireless telemetry from rats under light/dark (LD), dark/light (DL), asymmetric (6L18D and 18D6L), constant dark (DD), and constant light (LL) cycles. In some DD experiments, 1-hour light pulses were presented at varying times. IOP rhythmicity and variability were respectively quantified via cosinor analysis and peak detection algorithms that identified transient and sustained fluctuations.
UNASSIGNED: Rat IOP peaked at night and troughed during the day with LD amplitude of 8.7 ± 3.4 mm Hg. Rhythmicity persisted in DD and LL with a free-running period of 24.1 ± 0.3 and 25.2 ± 0.4 hours, respectively. Peak-to-trough amplitude was approximately 60% smaller in LL, often disappeared after 1 to 2 weeks as daytime IOP drifted 2.6 ± 1.5 mm Hg higher, and returned to approximately 60% larger in LD. Rhythmicity was similarly impacted but resynchronized to DL over 4 to 6 days. Rhythmicity was unaltered by short photoperiods (6L18D), but the nocturnal IOP elevation was markedly shortened by long photoperiods (18L6D) and temporarily lowered to daytime levels by light pulses during the subjective night. Transient and sustained event rate, amplitude, interval, and energy content were nearly identical in LD, DD, and LL.
UNASSIGNED: Aqueous humor dynamics of rat eyes are intrinsically configured to set IOP at daytime levels. Circadian clock input modulates these dynamics to elevate IOP at night. Light at night blocks this input, sending IOP back to daytime levels. Effects of abnormal lighting on IOP rhythmicity may contribute to pressure-related ocular neuropathies.

Artificial light at night (ALAN) is a recognized source of anthropogenic disturbance, although its effects on biological systems have not been fully explored. Within marine ecosystems, coastal areas are the most impacted by ALAN. Here, we focused on the Mediterranean sea urchin Paracentrotus lividus, which has a crucial role in shaping benthic ecosystems. Our objective was to investigate if ALAN affects the nocturnal locomotor behavior of P. lividus. A semi-controlled field study was conducted along a rocky shore near a promenade lit at night. Results suggested a potential impact of ALAN on the locomotor behavior of sea urchins. Individuals of P. lividus tended to move away from the light sources while its directions in dark conditions were uniform. Their locomotor performance, in presence of ALAN, was characterized by shorter latency time, lower sinuosity and higher mean speed at increasing light intensity, with potential cascading effect at the ecosystem level.

Light is recognized as an important component of the environment for laboratory animals. It supports vision, sets the phase of circadian clocks, and drives wide-ranging adjustments in physiological and behavioral state. Manipulating light is meanwhile a key experimental approach in the fields of vision science and chronobiology. Nevertheless, until recently, there has been no consensus on methods for quantifying light as experienced by laboratory animals. Widely adopted practices employ metrics such as illuminance (units = lux) that are designed to quantify light as experienced by human observers. These weight energy across the spectrum according to a spectral sensitivity profile for human vision that is not widely replicated for non-human species. Recently, a Consensus View was published that proposes methods of light measurement and standardization that take account of these species-specific differences in wavelength sensitivity. Here, we draw upon the contents of that consensus to provide simplified advice on light measurement in laboratory mammal experimentation and husbandry and quantitative guidance on what constitutes appropriate lighting for both visual and circadian function.