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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12

Sex Differences in Perceptions of Sleep Inertia Following Nighttime Awakenings

Study Objectives: The influence of biological sex on sleep inertia symptoms is currently unknown. We investigated the role of sex differences in the subjective experience and objective cognitive manifestation of sleep inertia following nighttime awakenings. Methods: Thirty-two healthy adults (16 female, 25.91 ± 5.63 years) completed a one-week at-home study with one experimental night during which sleep was measured by polysomnography and participants were awakened during their habitual sleep time. Participants completed a psychomotor vigilance task (PVT), Karolinska Sleepiness Scale (KSS), visual analog mood scales, and a descending subtraction task (DST) prior to sleep (baseline) and at 2, 12, 22, and 32 minutes after awakening. A series of mixed-effects models with Bonferroni-corrected post-hoc tests were used to examine the main effects of test bout and sex, and their interaction, with a random effect of participant, and order of wake-up and sleep history as covariates. Results: All outcomes except for percent correct on the DST showed a significant main effect of test bout, with worse performance after waking compared to baseline (all p s < .003). Significant effects of sex ( p = .002) and sex × test bout ( p = .01; R 2 M = .49, R 2 C = .69) were observed for KSS, with females reporting a greater increase in sleepiness from baseline to after waking compared to males. Conclusions : These results suggest that while females reported feeling sleepier than males following nighttime awakenings, their cognitive performance was comparable. Future research is needed to determine whether perceptions of sleepiness influence decision-making during the transition from sleep to wakefulness.

Sleep inertia↗

Sex Differences in Perceptions of Sleep Inertia Following Nighttime Awakenings

Study Objectives: The influence of biological sex on sleep inertia symptoms is currently unknown. We investigated the role of sex differences in the subjective experience and objective cognitive manifestation of sleep inertia following nighttime awakenings. Methods: Thirty-two healthy adults (16 female, 25.91 ± 5.63 years) completed a one-week at-home study with one experimental night during which sleep was measured by polysomnography and participants were awakened during their habitual sleep time. Participants completed a psychomotor vigilance task (PVT), Karolinska Sleepiness Scale (KSS), visual analog mood scales, and a descending subtraction task (DST) prior to sleep (baseline) and at 2, 12, 22, and 32 minutes after awakening. A series of mixed-effects models with Bonferroni-corrected post-hoc tests were used to examine the main effects of test bout and sex, and their interaction, with a random effect of participant, and order of wake-up and sleep history as covariates. Results: All outcomes except for percent correct on the DST showed a significant main effect of test bout, with worse performance after waking compared to baseline (all ps < .003). Significant effects of sex (p = .002) and sex × test bout (p = .01; R2M = .49, R2C = .69) were observed for KSS, with females reporting a greater increase in sleepiness from baseline to after waking compared to males. Conclusions: These results suggest that while females reported feeling sleepier than males following nighttime awakenings, their cognitive performance was comparable. Future research is needed to determine whether perceptions of sleepiness influence decision-making during the transition from sleep to wakefulness.

sleep inertia↗

Flood Detection with Synthetic Aperture Radar: A Case Study of Houston, Texas Following Hurricane Harvey (2017) using C- and X-Band Observations

Hurricane Harvey produced record-breaking rainfall of up to 60 inches resulting in extensive flooding in Houston, Texas, in late August and early September of 2017. The slow forward motion of the storm following landfall left much of the area unobservable to optical remote sensing instruments for several days due to cloud cover. The active nature of Synthetic Aperture Radar (SAR) instruments allows for observations through clouds, which can supplement efforts to estimate hurricane-induced flood impacts. A growing fleet of SAR constellations has helped lower the latency of imagery following a hurricane, allowing for more timely detections of flooding to help support emergency response efforts. In this study, we leverage publicly available C-band SAR observations from the European Space Agency’s Sentinel-1B (S1B) satellite, collected on 30 August, and X-band SAR imagery collected on 1 September by the Airbus TanDEM-X (TDX) satellite made available through the NASA Commercial Smallsat Data Acquisition (CSDA) program. For each dataset, one co-polarized, StripMap, Radiometric Terrain Corrected (RTC) image was used to create a binary water/no water classification map by referencing permanent water in the Cropland Data Layer (CDL) dataset to determine thresholds. A validation dataset of randomly distributed “ground truth” points was generated using optical imagery from PlanetScope on 31 August, where the domain had relatively little cloud cover. We found that the S1B- and TDX-derived open water maps achieved overall accuracies of 94.17% and 91.57%, respectively. The variation in performance is attributed to both the penetrative abilities of C- and X-band SAR wavelengths in vegetated areas and the increased spatial resolution of the commercial SAR (~3 m) over Sentinel-1 (30 m). While publicly available Sentinel-1 observations are commonly relied upon in response and recovery efforts, these results suggest that including commercial X-band SAR imagery could be beneficial by providing both increased spatial resolution and more frequent revisits when deriving post-event flood mapping products.

Alexander M Melancon↗

A Human-Autonomy Teaming Approach for a Flight-Following Task

Managing aircraft is becoming more complex with increasingly sophisticated automation responsible for more flight tasks. With this increased complexity, it is becoming more difficult for operators to understand what the automation is doing and why. Human involvement with increasingly autonomous systems must adjust to allow for a more dynamic relationship involving cooperation and teamwork. As part of an ongoing project to develop a framework for human-autonomy teaming (HAT) in aviation, a part-task study was conducted to demonstrate, evaluate and refine proposed critical aspects of HAT. These features were built into an automated recommender system on a ground station available from previous studies. Participants performed a flight-following task once with the original ground station (i.e., No HAT condition) and once with the HAT features enabled (i.e., HAT condition). Behavioral and subjective measures were collected; subjective measures are presented here. Overall, participants preferred the ground station with HAT features enabled compared to the station without the HAT features. Participants reported that the HAT displays and automation were preferred for keeping up with operationally important issues. Additionally, participants reported that the HAT displays and automation provided enough situation awareness to complete the task and reduced workload relative to the No HAT baseline.

ACFP↗

The Impact of New Accelerometer Transplant Data (ACH) on GRACE Follow-On Along-Orbit Inter-Satellite Laser Ranging Observations and Monthly Time-Variable Gravity and Mascon Solutions

GRACE-D accelerometer data show significant bias jumps since one month after the launch of the GRACE Follow-On (GRACE-FO) satellites in May 2018, making them inapplicable for correcting GRACE-FO products for non-gravitational accelerations. The GRACE-FO Science Data System (SDS) compensated this issue by transplanting the GRACE-C accelerometer data toward that of GRACE-D. Recently, GRACE-FO SDS implemented an updated transplant method, used in the latest release of GRACE-FO data. Here, we examine the impact of updated accelerometer transplant data (ACH) on GRACE-FO measurements at all levels: (a) Level-1B inter-satellite laser ranging residuals measured along satellite orbit, (b) Level-2 time-variable gravity solutions from all SDS centers (JPL, CSR, and GFZ), and (c) Level-3 mascon solutions. We show that inter-satellite laser ranging residuals are modified at low frequencies below 1 mHz, affecting the along-orbit analysis of large-scale time-variable gravity signals. When mapped into monthly Level-2 spherical harmonic coefficients of geopotential, the low-frequency change in inter-satellite ranging residuals leads to substantial improvement of coefficients associated with resonant orders (i.e., 15, 30, 45, etc.) and C 30 . We also present an improved SLR-derived C 30 which significantly improves the agreement with updated GRACE-FO C 30 at seasonal and interannual timescales. Moreover, we demonstrate the noise reduction in mass change estimates from new GRACE-FO Level-2 data over oceans, Greenland, and Antarctica for all SDS solutions. GRACE-FO mascon solutions show a moderate change in the updated release. Our comprehensive analyses demonstrate high-quality estimates of non-gravitational accelerations by the updated transplant method, resulting in more accurate GRACE-FO time-variable gravity and mass change observations.

Laser ranging interferometer↗