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Estimating the dim light melatonin onset of adolescents within a 6-h sampling window: the impact of sampling rate and threshold method.

Sleep medicine
OBJECTIVE/BACKGROUND: Circadian rhythm sleep-wake disorders (CRSWDs) often manifest during the adolescent years. Measurement of circadian phase such as the dim light melatonin onset (DLMO) improves diagnosis and treatment of these disorders, but fina...

Computational classification of different wild-type zebrafish strains based on their variation in light-induced locomotor response.

Computers in biology and medicine
Zebrafish larvae display a rapid and characteristic swimming behaviour after abrupt light onset or offset. This light-induced locomotor response (LLR) has been widely used for behavioural research and drug screening. However, the locomotor responses ...

A Neural Network Model for K(λ) Retrieval and Application to Global Kpar Monitoring.

PloS one
Accurate estimation of diffuse attenuation coefficients in the visible wavelengths Kd(λ) from remotely sensed data is particularly challenging in global oceanic and coastal waters. The objectives of the present study are to evaluate the applicability...

Evaluation of extra virgin olive oil stability by artificial neural network.

Food chemistry
The stability of extra virgin olive oil in polyethylene terephthalate bottles and tinplate cans stored for 6 months under dark and light conditions was evaluated. The following analyses were carried out: free fatty acids, peroxide value, specific ext...

Enhancing 3D human pose estimation with NIR single-pixel imaging and time-of-flight technology: a deep learning approach.

Journal of the Optical Society of America. A, Optics, image science, and vision
The extraction of 3D human pose and body shape details from a single monocular image is a significant challenge in computer vision. Traditional methods use RGB images, but these are constrained by varying lighting and occlusions. However, cutting-edg...

Artificial intelligence model substantially improves stratum corneum moisture content prediction from visible-light skin images and skin feature factors.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Appropriate skin treatment and care warrants an accurate prediction of skin moisture. However, current diagnostic tools are costly and time-consuming. Stratum corneum moisture content has been measured with moisture content meters or from...

A machine learning potential for simulating infrared spectra of nanosilicate clusters.

The Journal of chemical physics
The use of machine learning (ML) in chemical physics has enabled the construction of interatomic potentials having the accuracy of ab initio methods and a computational cost comparable to that of classical force fields. Training an ML model requires ...

Tunable grating surfaces with high diffractive efficiency optimized by deep neural networks.

Optics letters
High diffractive efficiency gratings, as a core component in optics, can engineer light transport and separation. This Letter predicts a grating surface with high diffractive efficiency within the visible light wave band with the aid of deep neural n...

Measuring laser beams with a neural network.

Applied optics
A deep neural network (NN) is used to simultaneously detect laser beams in images and measure their center coordinates, radii, and angular orientations. A dataset of images containing simulated laser beams and a dataset of images with experimental la...