scholarly journals 0034 When Should You Sleep to Maximize Alertness?

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A14-A14
Author(s):  
F Vital-Lopez ◽  
T J Doty ◽  
T J Balkin ◽  
J Reifman
Keyword(s):  
Experimental Studies ◽  
Sleep Time ◽  
Research Area ◽  
Time Of Day ◽  
Sleep Restriction ◽  
Negative Effects ◽  
Medicine Research ◽  
Fatigue Management ◽  
Army Medical Research ◽  
The Military

Abstract Introduction Working under sleep-restricted conditions may curtail safety and productivity. We could potentially minimize the negative effects of sleep restriction by optimizing the timing of sleep. However, to date, there are no algorithms that can determine the optimal sleep time to maximize alertness when most needed. Methods Our previously validated unified model of performance predicts the recuperative effects of sleep on alertness. Here, we extended this model to predict the likelihood of an individual falling and remaining asleep at any given moment, as a function of recent sleep history and time of day. Then, we combined the model with an optimization algorithm to provide optimal sleep recommendations for a given work/rest schedule. Specifically, using the model to predict the effectiveness of different sleep schedules, the algorithm determines when to sleep and for how long, so as to maximize alertness at desired times. The algorithm takes as inputs the 1) user-provided sleep history, 2) periods when the user has an opportunity to sleep, and 3) desired periods for maximum alertness, and provides as outputs sleep recommendations that are physiologically feasible and optimize alertness for the desired period. We assessed the algorithm by computing and comparing sleep recommendations for five previously published experimental studies of sleep restriction, including diurnal and nocturnal sleep. Results Compared to the original sleep schedules in the studies, our algorithm identified sleep recommendations that increased the predicted alertness by up to 33% and by 18% on average. These results suggest that the algorithm can tailor the timing of sleep to each specific sleep-restriction condition so as to maximize its benefits. Conclusion Our algorithm provides automated, customized guidance to enhance the recuperative benefits of limited sleep opportunities to maximize alertness at the most needed times. As such, it is the first quantitative sleep optimization tool for fatigue-management systems. Support This work was sponsored by the Military Operational Medicine Research Area Directorate of the U.S. Army Medical Research and Development Command, Ft. Detrick, MD.

Time-of-day modulation of homeostatic and allostatic sleep responses to chronic sleep restriction in rats

2012 ◽  
Vol 302 (12) ◽  
pp. R1411-R1425 ◽  
Author(s):  
S. Deurveilher ◽  
B. Rusak ◽  
K. Semba
Keyword(s):  
Eye Movement ◽  
Recovery Period ◽  
Sleep Time ◽  
Time Of Day ◽  
Male Rats ◽  
Sleep Restriction ◽  
Rapid Eye Movement ◽  
Rapid Eye Movement Sleep ◽  
Delta Power ◽  
Chronic Sleep

To study sleep responses to chronic sleep restriction (CSR) and time-of-day influences on these responses, we developed a rat model of CSR that takes into account the polyphasic sleep patterns in rats. Adult male rats underwent cycles of 3 h of sleep deprivation (SD) and 1 h of sleep opportunity (SO) continuously for 4 days, beginning at the onset of the 12-h light phase (“3/1” protocol). Electroencephalogram (EEG) and electromyogram (EMG) recordings were made before, during, and after CSR. During CSR, total sleep time was reduced by ∼60% from baseline levels. Both rapid eye movement sleep (REMS) and non-rapid eye movement sleep (NREMS) during SO periods increased initially relative to baseline and remained elevated for the rest of the CSR period. In contrast, NREMS EEG delta power (a measure of sleep intensity) increased initially, but then declined gradually, in parallel with increases in high-frequency power in the NREMS EEG. The amplitude of daily rhythms in NREMS and REMS amounts was maintained during SO periods, whereas that of NREMS delta power was reduced. Compensatory responses during the 2-day post-CSR recovery period were either modest or negative and gated by time of day. NREMS, REMS, and EEG delta power lost during CSR were not recovered by the end of the second recovery day. Thus the “3/1” CSR protocol triggered both homeostatic responses (increased sleep amounts and intensity during SOs) and allostatic responses (gradual decline in sleep intensity during SOs and muted or negative post-CSR sleep recovery), and both responses were modulated by time of day.

What Are the Factors Affecting Total Sleep Time During Video Polysomnography in Infants?

2020 ◽  
Author(s):  
Grace R. Paul ◽  
Don Hayes ◽  
Dmitry Tumin ◽  
Ish Gulati ◽  
Sudarshan Jadcherla ◽  
...  
Keyword(s):  
Total Sleep Time ◽  
Sleep Time ◽  
Time Of Day ◽  
Apnea Hypopnea Index ◽  
Clinical Factors ◽  
Initial Management ◽  
Factors Affecting ◽  
Modifiable Factors ◽  
Key Points ◽  
Medical Complexity

Objective The aim of the study is to investigate factors affecting total sleep time (TST) during infant polysomnography (PSG) and assess if <4 hours of TST is sufficient for accurate interpretation. Study Design Overall, 242 PSGs performed in 194 infants <6 months of chronological age between March 2013 and December 2015 were reviewed to identify factors that affect TST, including age of infant, location and timing of study, presence of medical complexity, and presence of nasal tubes. A continuum of apnea-hypopnea index (AHI) in relation to TST was reviewed. Data were examined in infants who had TST <4 hours and low AHI. Results Greater TST (p < 0.001) was noted among infants during nocturnal PSGs, at older chronological and post-menstrual ages, and without medical complexity. The presence of nasogastric/impedance probes reduced TST (p = 0.002). Elevated AHIs were identified even in PSGs with TST <4 hours. Short TST may have affected interpretation and delayed initial management in one infant without any inadvertent complications. Conclusion Clinical factors such as PMA and medical complexity, and potentially modifiable factors such as time of day and location of study appeared to affect TST during infant PSGs. TST < 4 hours can be sufficient to identify high AHI allowing physician interpretation. Key Points

Time-of-Day Mediates the Influences of Extended Wake and Sleep Restriction on Simulated Driving

2012 ◽  
Vol 29 (5) ◽  
pp. 572-579 ◽  
Author(s):  
Raymond W. Matthews ◽  
Sally A. Ferguson ◽  
Xuan Zhou ◽  
Charli Sargent ◽  
David Darwent ◽  
...  
Keyword(s):  
Time Of Day ◽  
Sleep Restriction ◽  
Simulated Driving

EVALUATION OF TOXIOLOGICAL INDICATORS OF MONTHMORRILLONITE CLAY FOR THE PURPOSE OF USING THEM AS ALUMOSILICATE SOBENT AGAINST THE NEGATIVE EFFECT OF MYCOTOXINS ON THE BODY OF ANIMALS AND BIRDS

2021 ◽  
Vol 1 (1) ◽  
pp. 72-78
Keyword(s):  
Experimental Studies ◽  
The Body ◽  
Montmorillonite Clay ◽  
Test Substance ◽  
Negative Effects ◽  
Experimental Animals ◽  
Eyelid Edema ◽  
White Rats ◽  
Mucous Membranes ◽  
Negative Effect

The article presents the results of laboratory studies to assess the toxicological parameters of montmorillonite clay from the Pogadaevskoye deposit in the West Kazakhstan region in order to use them as an aluminosilicate sorbent in the composition of feeds that reduce the negative effects of mycotoxins on the body of animals and birds. The relevance of research is associated with the cultivation of healthy and highly productive animals and poultry in order to ensure the food security of the Republic of Kazakhstan.The studies carried out to assess the toxicological parameters of montmorillonite clay in order to use them as an aluminosilicate sorbent in experimental animals (rabbits and white rats) allowed the following results to be obtained: Visual study of the intensity of erythema when exposed to the test substance on the skin of rabbits showed their absence (0 points). The study of the intensity of edema (an increase in the thickness of the skin clutch of rabbits) when exposed to the test substance on the skin of rabbits showed no reaction (0 points). Studies evaluating the irritating effect of the test substances on the mucous membranes of the eyes of rabbits by symptoms of damage showed the absence of hyperemia (0 points). Weak eyelid edema (1 point), the minimum amount of discharge in the corner of the eye (1 point). The results of studies on the classification assessment of the test substance for the severity of the irritant effect on the eyes of rabbits showed that the average total score of the severity of the irritative effect corresponds to 1 point. A comprehensive analysis of the results obtained on the basis of scientific and experimental studies to assess the toxicological indicators of montmorillonite clay from the Pogadaevskoye deposit in relation to irritating effects on the skin and mucous membranes of experimental animals (rabbits) showed their harmlessness.

scholarly journals Synthesis, Characterization and Development of Energy Harvesting Techniques Incorporated with Antennas: A Review Study

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2772 ◽  
Author(s):  
Husam Hamid Ibrahim ◽  
Mandeep S. J. Singh ◽  
Samir Salem Al-Bawri ◽  
Mohammad Tariqul Islam
Keyword(s):  
Energy Harvesting ◽  
Research Area ◽  
Voltage Regulation ◽  
Input Power ◽  
Energy Sources ◽  
Promising Alternative ◽  
Significant Research ◽  
Rf Energy ◽  
Self Powered ◽  
The Military

The investigation into new sources of energy with the highest efficiency which are derived from existing energy sources is a significant research area and is attracting a great deal of interest. Radio frequency (RF) energy harvesting is a promising alternative for obtaining energy for wireless devices directly from RF energy sources in the environment. An overview of the energy harvesting concept will be discussed in detail in this paper. Energy harvesting is a very promising method for the development of self-powered electronics. Many applications, such as the Internet of Things (IoT), smart environments, the military or agricultural monitoring depend on the use of sensor networks which require a large variety of small and scattered devices. The low-power operation of such distributed devices requires wireless energy to be obtained from their surroundings in order to achieve safe, self-sufficient and maintenance-free systems. The energy harvesting circuit is known to be an interface between piezoelectric and electro-strictive loads. A modern view of circuitry for energy harvesting is based on power conditioning principles that also involve AC-to-DC conversion and voltage regulation. Throughout the field of energy conversion, energy harvesting circuits often impose electric boundaries for devices, which are important for maximizing the energy that is harvested. The power conversion efficiency (PCE) is described as the ratio between the rectifier’s output DC power and the antenna-based RF-input power (before its passage through the corresponding network).

scholarly journals Risk compensation and bicycle helmets: a false conclusion and uncritical citations

2018 ◽  
Author(s):  
Igor Radun ◽  
Jenni Radun ◽  
Mahsa Esmaeilikia ◽  
Timo Lajunen
Keyword(s):  
General Public ◽  
Head Injuries ◽  
Experimental Studies ◽  
Research Area ◽  
Risk Compensation ◽  
Policy Makers ◽  
Bicycle Helmets ◽  
False Conclusion ◽  
Helmet Laws ◽  
The Impact

Some researchers and many anti-helmet advocates often state that because cyclists are wearing a helmet they feel safer and take more risks. This hypothesis - risk compensation – if true, would reduce, annul or even reverse the assumed benefits of helmets in reducing head injuries. Consequently, this hypothesis is often used to oppose mandatory helmet laws. In this article, we illustrate how one of the few studies that attempted to experimentally test the hypothesis in relation to bicycle helmets arrives at a false conclusion. As a result it is often cited as evidence of risk compensation. Given the lack of experimental studies in this research area, the impact of a single study in shaping the opinions of the general public and of policy makers can be significant.

2B-Alert Web 2.0: An Open-Access Tool for Predicting Alertness and Optimizing the Benefits of Caffeine (Preprint)

2021 ◽  
Author(s):  
Jaques Reifman ◽  
Kamal Kumar ◽  
Luke Hartman ◽  
Andrew Frock ◽  
Tracy J. Doty ◽  
...  
Keyword(s):  
Night Shift ◽  
Sleep Loss ◽  
Time Of Day ◽  
Caffeine Consumption ◽  
Fatigue Management ◽  
Potential Benefits ◽  
Computer Based ◽  
Evening Shift ◽  
Alertness Level ◽  
The U.S

BACKGROUND One-third of the U.S. population experiences sleep loss, with the potential to impair physical and cognitive performance, and result in reduced productivity and imperil safety during work and daily activities. Computer-based fatigue-management systems, with the ability to predict the effects of sleep schedules on alertness and identify safe and effective caffeine interventions that maximize its stimulating benefits, could help mitigate cognitive impairment due to limited sleep. To provide these capabilities to broad communities, we previously released the 2B-Alert Web, a publicly available tool for predicting the average alertness level of a group of individuals as a function of time of day, sleep history, and caffeine consumption. OBJECTIVE Here, we aimed to enhance the capability of the 2B-Alert Web by providing the means for the tool to automatically recommend safe and effective caffeine interventions (time and dose) that lead to optimal alertness levels at user-specified times, under any sleep-loss condition. METHODS We incorporated a recently developed caffeine-optimization algorithm into the predictive models of the original 2B-Alert Web, allowing the system to search for and identify viable caffeine interventions that result in user-specified alertness levels at desired times of the day. To assess the potential benefits of this new capability, we simulated four sleep-deprivation conditions (sustained operations, restricted sleep with morning or evening shift, and night shift with daytime sleep) and compared the alertness levels resulting from the algorithm’s recommendations with those based on the U.S. Army caffeine-countermeasure guidelines. In addition, we enhanced the usability of the tool by adopting a drag-and-drop graphical interface for the creation of sleep and caffeine schedules. RESULTS For the four simulated conditions, the 2B-Alert Web-proposed interventions increased average alertness by 36 to 94% and decreased peak alertness impairment by 31 to 71%, while using equivalent or smaller doses of caffeine as the corresponding U.S. Army guidelines. CONCLUSIONS The enhanced capability of this evidence-based, publicly available tool increases the efficiency by which diverse communities of users can identify safe and effective caffeine interventions to mitigate the effects of sleep loss in the design of research studies and work/rest schedules. 2B-Alert Web is accessible at: <https://2b-alert-web.bhsai.org>.

scholarly journals 0304 Greater Slow-Wave Activity is Associated with Deteriorating Mood Across Sleep Restriction

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A115-A115
Author(s):  
O R Larson ◽  
C W Jones ◽  
M Basner ◽  
D F Dinges
Keyword(s):  
Slow Wave ◽  
Power Spectral Analysis ◽  
Sleep Time ◽  
Wave Activity ◽  
Slow Wave Activity ◽  
Mood Disturbance ◽  
Sleep Restriction ◽  
Linear Regression Models ◽  
Time In Bed ◽  
Rem Latency

Abstract Introduction Mood progressively deteriorates over consecutive days of sleep restriction. The neurobiological processes active during sleep that influence the risk of mood disturbance are unknown. This study investigated the relationships between physiological sleep parameters (i.e., slow-wave activity (SWA), slow-wave energy (SWE), rapid eye-movement (REM) sleep duration and latency), and self-reported measures of mood across sleep restriction. Methods N=181 healthy participants (48.1% female; 30±6.8 yrs) had valid polysomnography (PSG) and mood data. The study design included two baseline nights (8h time in bed [TIB]) followed by five nights of 4h TIB. PSG (EEG derivations C3-A2, Fz-A1, O2-A1) was collected on the second baseline night (B2), first night of 4h TIB (SR1), and the fifth night of 4h TIB (SR5). The Profile of Mood States was assayed on days following PSG. Power spectral analysis for SWE and SWA was conducted (delta power; band: 0.5-4.5 Hz). General linear regression models were used to independently assess the slope of SWE, SWA, percent REM of total sleep time (TST), and REM latency on mood disturbance across sleep restriction. Results At baseline, higher SWE (unadjusted; r=0.21; P=0.004) and SWA (unadjusted; r=0.19; P=0.007) were associated with greater mood disturbance; these relations were attenuated when adjusted for age and sex. No relation was found between mood and REM latency or REM percent of TST. The slope of mood disturbance from B2 to SR5 was associated with greater percentage increases in C3 SWA on SR5 relative to B2 (β=0.039; P=0.008); this association was not observed for SWE (β=-0.016; P=0.48). The slope of REM latency and REM percent of TST were not associated with the slope of mood disturbance. Conclusion Our results indicate that greater SWA due to sleep restriction was associated with greater mood disturbance, suggesting that less SWA may confer resilience to mood disturbances resulting from sleep restriction. Support This work was supported by National Institute of Health NIH R01NR004281 and National Space and Biomedical Research Institute NSRBI NCC 5-98.

scholarly journals Citizens’ Spatial Footprint on Twitter—Anomaly, Trend and Bias Investigation in Istanbul

2020 ◽  
Vol 9 (4) ◽  
pp. 222 ◽  
Author(s):  
Ayse Giz Gulnerman ◽  
Himmet Karaman ◽  
Direnc Pekaslan ◽  
Serdar Bilgi
Keyword(s):  
Social Media ◽  
Spatial Data ◽  
Central Area ◽  
Research Area ◽  
Time Of Day ◽  
Activity Levels ◽  
Social Media Data ◽  
Time Space ◽  
The City ◽  
Media Data

Social media (SM) can be an invaluable resource in terms of understanding and managing the effects of catastrophic disasters. In order to use SM platforms for public participatory (PP) mapping of emergency management activities, a bias investigation should be undertaken with regard to the data related to the study area (urban, regional or national, etc.) to determine the spatial data dynamics. Thus, such determinations can be made on how SM can be used and interpreted in terms of PP. In this study, the city of Istanbul was chosen for social media data research area, as it is one of the most crowded cities in the world and expecting a major earthquake. The methodology for the data investigation is: 1. Obtain data and engage sampling, 2. Identify the representation and temporal biases in the data and normalize it in response to representation bias, 3. Identify general anomalies and spatial anomalies, 4. Manipulate the trend of the dataset with the discretization of anomalies and 5. Examine the spatiotemporal bias. Using this bias investigation methodology, citizen footprint dynamics in the city were determined and reference maps (most likely regional anomaly maps, representation maps, time-space bias maps, etc.) were produced. The outcomes of the study can be summarized in four steps. First, highly active users generate the majority of the data and removing this data as a general approach within a pseudo-cleaning process means concealing a large amount of data. Second, data normalization in terms of activity levels, changes the anomaly outcome resulting from diverse representation levels of users. Third, spatiotemporally normalized data present strong spatial anomaly tendency in some parts of the central area. Fourth, trend data is dense in the central area and the spatiotemporal bias assessments show the data density varies in terms of the time of day, day of week and season of the year. The methodology proposed in this study can be used to extract the unbiased daily routines of the social media data of the regions for the normal days and this can be referred for the emergency or unexpected event cases to detect the change or impacts.

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