Sensor-Based Estimation of Dim Light Melatonin Onset Using Features of Two Time Scales

2021 ◽  
Vol 2 (3) ◽  
pp. 1-15
Author(s):  
Cheng Wan ◽  
Andrew W. Mchill ◽  
Elizabeth B. Klerman ◽  
Akane Sano
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Light Exposure ◽  
Biological Activities ◽  
Second Step ◽  
Sampled Data ◽  
Dim Light Melatonin Onset ◽  
Dim Light ◽  
Using Data ◽  
Mean Square Errors

Circadian rhythms influence multiple essential biological activities, including sleep, performance, and mood. The dim light melatonin onset (DLMO) is the gold standard for measuring human circadian phase (i.e., timing). The collection of DLMO is expensive and time consuming since multiple saliva or blood samples are required overnight in special conditions, and the samples must then be assayed for melatonin. Recently, several computational approaches have been designed for estimating DLMO. These methods collect daily sampled data (e.g., sleep onset/offset times) or frequently sampled data (e.g., light exposure/skin temperature/physical activity collected every minute) to train learning models for estimating DLMO. One limitation of these studies is that they only leverage one time-scale data. We propose a two-step framework for estimating DLMO using data from both time scales. The first step summarizes data from before the current day, whereas the second step combines this summary with frequently sampled data of the current day. We evaluate three moving average models that input sleep timing data as the first step and use recurrent neural network models as the second step. The results using data from 207 undergraduates show that our two-step model with two time-scale features has statistically significantly lower root-mean-square errors than models that use either daily sampled data or frequently sampled data.

scholarly journals Pontryagin maximum principle for state constrained optimal sampled-data control problems on time scales

2021 ◽  
Author(s):  
Piernicola Bettiol ◽  
Loic Bourdin
Keyword(s):  
Maximum Principle ◽  
Time Scales ◽  
Time Scale ◽  
Pontryagin Maximum Principle ◽  
Control Problems ◽  
Maximal Velocity ◽  
Sampled Data ◽  
Data Control ◽  
Sampled Data Control ◽  
Inequality State

In this paper we consider optimal sampled-data control problems on time scales with inequality state constraints. A Pontryagin maximum principle is established, extending to the state constrained case existing results in the time scale literature. The proof is based on the Ekeland variational principle and on the concept of implicit spike variations adapted to the time scale setting. The main result is then applied to continuous-time min-max optimal sampled-data control problems and a maximal velocity minimization problem for the harmonic oscillator with sampled-data control is numerically solved for illustration.

scholarly journals Chronotype-Dependent Changes in Sleep Habits Associated with Dim Light Melatonin Onset in the Antarctic Summer

2019 ◽  
Vol 1 (3) ◽  
pp. 352-366 ◽  
Author(s):  
Ana Silva ◽  
Diego Simón ◽  
Bruno Pannunzio ◽  
Cecilia Casaravilla ◽  
Álvaro Díaz ◽  
...  
Keyword(s):  
Light Exposure ◽  
Time Windows ◽  
Sleep Onset ◽  
Onset Time ◽  
Sleep Habits ◽  
Subtle Difference ◽  
Dim Light Melatonin Onset ◽  
Dim Light ◽  
The Antarctic ◽  
The Impact

Dim light melatonin onset (DLMO) is the most reliable measure of human central circadian timing. Its modulation by light exposure and chronotype has been scarcely approached. We evaluated the impact of light changes on the interaction between melatonin, sleep, and chronotype in university students (n = 12) between the Antarctic summer (10 days) and the autumn equinox in Montevideo, Uruguay (10 days). Circadian preferences were tested by validated questionnaires. A Morningness–Eveningness Questionnaire average value (47 ± 8.01) was used to separate late and early participants. Daylight exposure (measured by actimetry) was significantly higher in Antarctica versus Montevideo in both sensitive time windows (the morning phase-advancing and the evening phase-delaying). Melatonin was measured in hourly saliva samples (18–24 h) collected in dim light conditions (<30 lx) during the last night of each study period. Early and late participants were exposed to similar amounts of light in both sites and time windows, but only early participants were significantly more exposed during the late evening in Antarctica. Late participants advanced their DLMO with no changes in sleep onset time in Antarctica, while early participants delayed their DLMO and sleep onset time. This different susceptibility to respond to light may be explained by a subtle difference in evening light exposure between chronotypes.

scholarly journals Effects of light exposure and sleep displacement on dim light melatonin onset

1999 ◽  
Vol 8 (3) ◽  
pp. 163-174 ◽  
Author(s):  
M. C. M. Gordijn ◽  
D. G. M. Beersma ◽  
H. J. Korte ◽  
R. H. Hoofdakker
Keyword(s):  
Light Exposure ◽  
Dim Light Melatonin Onset ◽  
Dim Light

scholarly journals GNSS-to-GNSS time offsets: study on the broadcast of a common reference time

GPS Solutions ◽  
2021 ◽  
Vol 25 (2) ◽  
Author(s):  
Ilaria Sesia ◽  
Giovanna Signorile ◽  
Tung Thanh Thai ◽  
Pascale Defraigne ◽  
Patrizia Tavella
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Reference Time ◽  
Single Time ◽  
Common Reference ◽  
Prediction Quality ◽  
Common Time ◽  
Time Offset ◽  
The Impact ◽  
Low Uncertainty

AbstractWe present two different approaches to broadcasting information to retrieve the GNSS-to-GNSS time offsets needed by users of multi-GNSS signals. Both approaches rely on the broadcast of a single time offset of each GNSS time versus one common time scale instead of broadcasting the time offsets between each of the constellation pairs. The first common time scale is the average of the GNSS time scales, and the second time scale is the prediction of UTC already broadcast by the different systems. We show that the average GNSS time scale allows the estimation of the GNSS-to-GNSS time offset at the user level with the very low uncertainty of a few nanoseconds when the receivers at both the provider and user levels are fully calibrated. The use of broadcast UTC prediction as a common time scale has a slightly larger uncertainty, which depends on the broadcast UTC prediction quality, which could be improved in the future. This study focuses on the evaluation of two different common time scales, not considering the impact of receiver calibration, at the user and provider levels, which can nevertheless have an important impact on GNSS-to-GNSS time offset estimation.

scholarly journals 111 Artificial Light-Triggered Sleep Deprivation May Lead to Allodynia in Rodent Model

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A45-A46
Author(s):  
Skyler Kanegi ◽  
Armen Akopian
Keyword(s):  
Sleep Deprivation ◽  
Light Exposure ◽  
Light Stimulus ◽  
Continuous Light ◽  
Artificial Light ◽  
Light Cycle ◽  
Tissue Samples ◽  
Mechanical Threshold ◽  
Dim Light ◽  
Von Frey Filaments

Abstract Introduction The combination of artificial light and lack of exposure to natural light can delay the circadian clock, dysregulate the circadian cycle, and decrease alertness upon waking. This effect has been especially significant during the COVID-19 pandemic, where overexposure to artificial light at improper hours has contributed to increased rates of clinical insomnia. Artificial light may also contribute to concomitant neurological conditions such as primary headache, but the mechanisms by which light triggers sleep deprivation-induced headache are not well-understood. Methods To measure pain sensitivity, we habituated 13 wild-type male mice to von Frey filaments applied to the periorbital area until there was no response to 0.6g stimulus. We then applied 5 lux of continuous dim light to mice during their usual 12-hour dark cycle. The 12-hour light cycle remained unchanged with 200 lux continuous light. Three groups of mice experienced the dim light stimulus for one, three, or five consecutive days. Ambulation and rest activity were measured using SOF-812 Activity Monitor machines. After the experiment concluded, we waited 24 hours and measured mechanical threshold using von Frey filaments at 1, 3, 5, 8, and every 3 days subsequently until mice no longer responded to 0.6g stimulus. Results Artificial light triggered changes in circadian behavior including increased number of rest periods during 12-hour dark (dim light) cycle and shortened sleep duration during 12-hour light cycle. Following the artificial light stimulus, there was a significant decrease in mechanical threshold (P&lt;0.05), representing allodynia. The one-day group displayed one day of significant allodynia. The three-day group displayed three days of significant allodynia. The five-day group displayed five days of significant allodynia. Conclusion Artificial light may trigger circadian dysregulation, and the duration of artificial light exposure seemed to be directly correlated to the duration of allodynia up to one week after the stimulus was removed. We will repeat these experiments and analyze CNS and PNS tissue samples to understand the underlying physiological and biochemical bases of how artificial light triggers sleep deprivation-induced headache. This knowledge could increase our understanding of the pathophysiology and comorbidity of sleep deprivation and headache. Support (if any) Funding was received from the National Institute of Health (NS104200).

scholarly journals Locally and Remotely Forced Subtropical AMOC Variability: A Matter of Time Scales

2020 ◽  
Vol 33 (12) ◽  
pp. 5155-5172
Author(s):  
Quentin Jamet ◽  
William K. Dewar ◽  
Nicolas Wienders ◽  
Bruno Deremble ◽  
Sally Close ◽  
...  
Keyword(s):  
Time Series ◽  
Time Scales ◽  
North Atlantic ◽  
Time Scale ◽  
Low Frequency ◽  
Meridional Overturning Circulation ◽  
Open Boundary ◽  
Overturning Circulation ◽  
Decadal Scale ◽  
Meridional Overturning

AbstractMechanisms driving the North Atlantic meridional overturning circulation (AMOC) variability at low frequency are of central interest for accurate climate predictions. Although the subpolar gyre region has been identified as a preferred place for generating climate time-scale signals, their southward propagation remains under consideration, complicating the interpretation of the observed time series provided by the Rapid Climate Change–Meridional Overturning Circulation and Heatflux Array–Western Boundary Time Series (RAPID–MOCHA–WBTS) program. In this study, we aim at disentangling the respective contribution of the local atmospheric forcing from signals of remote origin for the subtropical low-frequency AMOC variability. We analyze for this a set of four ensembles of a regional (20°S–55°N), eddy-resolving (1/12°) North Atlantic oceanic configuration, where surface forcing and open boundary conditions are alternatively permuted from fully varying (realistic) to yearly repeating signals. Their analysis reveals the predominance of local, atmospherically forced signal at interannual time scales (2–10 years), whereas signals imposed by the boundaries are responsible for the decadal (10–30 years) part of the spectrum. Due to this marked time-scale separation, we show that, although the intergyre region exhibits peculiarities, most of the subtropical AMOC variability can be understood as a linear superposition of these two signals. Finally, we find that the decadal-scale, boundary-forced AMOC variability has both northern and southern origins, although the former dominates over the latter, including at the site of the RAPID array (26.5°N).

scholarly journals A EEG-based emotion recognition model with rhythm and time characteristics

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Jianzhuo Yan ◽  
Shangbin Chen ◽  
Sinuo Deng
Keyword(s):  
Emotion Recognition ◽  
Time Scales ◽  
Time Scale ◽  
Short Term Memory ◽  
Recognition Model ◽  
Memory Network ◽  
Long Short Term Memory ◽  
Valence And Arousal ◽  
Memory Characteristics

Abstract As an advanced function of the human brain, emotion has a significant influence on human studies, works, and other aspects of life. Artificial Intelligence has played an important role in recognizing human emotion correctly. EEG-based emotion recognition (ER), one application of Brain Computer Interface (BCI), is becoming more popular in recent years. However, due to the ambiguity of human emotions and the complexity of EEG signals, the EEG-ER system which can recognize emotions with high accuracy is not easy to achieve. Based on the time scale, this paper chooses the recurrent neural network as the breakthrough point of the screening model. According to the rhythmic characteristics and temporal memory characteristics of EEG, this research proposes a Rhythmic Time EEG Emotion Recognition Model (RT-ERM) based on the valence and arousal of Long–Short-Term Memory Network (LSTM). By applying this model, the classification results of different rhythms and time scales are different. The optimal rhythm and time scale of the RT-ERM model are obtained through the results of the classification accuracy of different rhythms and different time scales. Then, the classification of emotional EEG is carried out by the best time scales corresponding to different rhythms. Finally, by comparing with other existing emotional EEG classification methods, it is found that the rhythm and time scale of the model can contribute to the accuracy of RT-ERM.

Clinical efficacy of dim light melatonin onset testing in diagnosing delayed sleep phase syndrome

2009 ◽  
Vol 10 (5) ◽  
pp. 549-555 ◽  
Author(s):  
Shadab A. Rahman ◽  
Leonid Kayumov ◽  
Ekaterina A. Tchmoutina ◽  
Colin M. Shapiro
Keyword(s):  
Clinical Efficacy ◽  
Sleep Phase ◽  
Dim Light Melatonin Onset ◽  
Delayed Sleep Phase Syndrome ◽  
Delayed Sleep Phase ◽  
Dim Light ◽  
Delayed Sleep

scholarly journals Fast Comparison of High-Precision Time Scales Using GNSS Receivers

2017 ◽  
Vol 2017 ◽  
pp. 1-4
Author(s):  
Vojtech Vigner ◽  
Jaroslav Roztocil
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
High Performance ◽  
Data Format ◽  
Common View ◽  
Log Files ◽  
Gnss Receivers ◽  
Precision Time ◽  
The Common ◽  
The Difference

Comparison of high-performance time scales generated by atomic clocks in laboratories of time and frequency metrology is usually performed by means of the Common View method. Laboratories are equipped with specialized GNSS receivers which measure the difference between a local time scale and a time scale of the selected satellite. Every receiver generates log files in CGGTTS data format to record measured differences. In order to calculate time differences recorded by two receivers, it is necessary to obtain these logs from both receivers and process them. This paper deals with automation and speeding up of these processes.

Enhancement of Radar Imagery by Maximum Entropy Processing

1977 ◽  
Vol 21 (3) ◽  
pp. 241-243 ◽  
Author(s):  
Clanton E. Mancill
Keyword(s):  
Maximum Entropy ◽  
Signal To Noise Ratio ◽  
Super Resolution ◽  
Doppler Frequency ◽  
Frequency Measurement ◽  
Entropy Method ◽  
Frequency Resolution ◽  
Sampled Data ◽  
Maximum Entropy Spectrum ◽  
Using Data

The maximum entropy spectrum (MES), a sampled data power spectrum estimator, is applied to the enhancement of imagery obtained by synthetic array radar (SAR) imaging systems. MES offers better frequency resolution than conventional Fourier transform methods for certain signal classes. Since azimuth ground resolution in SAR systems is obtained by doppler frequency measurement of the radar return, the method is capable of enhancing the resolution of SAR maps. The principal signal requirement is adequate signal-to-noise ratio. The maximum entropy method has been tested using data obtained by the Hughes FLAMR radar system. The super-resolution capabilities of the method are demonstrated using FLAMR images of corner reflector arrays.

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