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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 631 records · Page 35

Integrating FRET with Copilot: Automated Translation of Natural Language Requirements to Runtime Monitors

Runtime verification (RV) enables monitoring systems at runtime, to detect property violations early and limit their potential consequences. To provide the level of assurance required for ultra-critical systems, monitor specifications must faithfully reflect the original mission requirements, which are often written in ambiguous natural language. This paper presents an end-to-end framework to capture requirements in structured natural language and generate monitors that capture their semantics faithfully. We leverage NASA’s Formal Requirement Elicitation Tool (FRET), and the RV system Copilot. We extend FRET with mechanisms to capture additional information needed to generate monitors, and introduce OGMA, a new tool to bridge the gap between FRET and Copilot. With this framework, users can write requirements in an intuitive format and obtain real-time C monitors suitable for use in embedded systems. Our tool chain is available as open source.

FRET↗

Translational Line of Sight: a multi-omics longitudinal study of the murine retinal response to spaceflight hazard analogs

The space environment includes unique hazards like radiation and microgravity which adversely affect physiology and behavior of humans and rodent models. To better characterize the retinal response to spaceflight, we assessed a multi-omics NASA GeneLab dataset where 6-month-old female mice were gamma irradiated and/or hindlimb unloaded for 21 days followed by whole transcriptome shotgun sequencing (RNA-Seq) and reduced representation bisulfite sequencing (RRBS) of retina samples collected at 7 days, 1 month or 4 months post-exposure. We compared time-matched epigenomic and transcriptomic retinal profiles revealing a total of 4,178 differentially methylated loci or regions, and 457 differentially expressed genes. Highest correlation in methylation differences was seen across different conditions at the same time point (e.g., between radiation exposure and hindlimb unloaded at 7 days). Biological processes related to nucleotide metabolism were enriched in all groups with activation at 1 month and suppression at 7 days and 4 months. Genes and processes related to Notch and Wnt signaling showed alterations 4 months post-exposure. Interestingly, Notch3 and Lrg1 showed differential patterns in the NASA Twins Study in-flight samples and in response to stressors in the murine retina in the current study. A total of 23 genes were both differentially methylated and expressed, including genes involved in retinal disease or cataract development (Crybb3, Fgfr1, Pitpnm3, Sipa1l3, Sox9) and inflammatory response (B4galt6, Ppm1a, Sphk1). To our knowledge, the current multi-omics analysis is the first multi-omics study to interrogate the epigenomic and transcriptomic impacts of radiation and hindlimb unloading on the retina in isolation and in combination. The results provide an insight into the retinal response to individual spaceflight hazard analogs and their interplay at different post-exposure stages and contributes towards a mechanistic understanding of spaceflight-induced vision impairment using ground-based models.

Prachi Kothiyal↗

Light as a Reactive Countermeasure to Sleep Inertia: Translating Laboratory Findings to the Field

Sleep inertia describes the brief period of impaired alertness, mood, and cognitive performance experienced after waking. Under laboratory settings, light exposure upon waking during a habitual sleep period has been shown to improve sleep inertia symptoms. We investigated whether a field-deployable light-emitting device would help to mitigate sleep inertia in a real-world setting. Thirty-six participants (18 female; 26.6 years ± 6.1) completed an at-home, within-subject, randomized crossover study. Participants followed their habitual sleep-wake schedule for five nights before an adaptation and experimental night. Forty-five minutes after bedtime on the experimental night, participants received a phone call and were instructed to wear light-emitting glasses with the light either on (light condition) or off (control). A 5-minute psychomotor vigilance task (PVT), the Karolinska Sleepiness Scale (KSS), visual analog scales of mood (VASmood), and a 3-minute descending subtraction task (DST) were performed starting at +2, +12, +22, and +32 minutes after the call. Participants then went back to sleep and were called 45 minutes after lights out for the opposite condition. A series of mixed-effects models were performed with fixed effects of test bout, condition, test bout × condition, and a random effect of participant. Covariates included pre-sleep baseline scores, randomization order, sex, and sleep history. Participants rated themselves as more alert and energetic in the light condition compared to the control condition (VASalert-sleepy p = .01; VASlethargic-energetic p = .001). There was no effect of condition for DST outcomes, but there was a significant improvement in DST total responses in the light condition in a subset of participants waking from N3 (p = .03). There was a significant effect of condition for PVT outcomes, with faster responses (p < .001) and fewer lapses (p < .001) in the control condition. Our results under naturalistic at-home settings suggest that, similar to the in-laboratory study findings, the light intervention improved subjective alertness and mood, while working memory improved after waking from N3. Future studies of light interventions should include measures of visual acuity and comfort to assess the full feasibility and efficacy of interventions in real-world environments.

sleep inertia↗

Light as a Reactive Countermeasure to Sleep Inertia: Translating Laboratory Findings to the Field

Sleep inertia describes the brief period of impaired alertness, mood, and cognitive performance experienced after waking. Under laboratory settings, light exposure upon waking during a habitual sleep period has been shown to improve sleep inertia symptoms. We investigated whether a field-deployable light-emitting device would help to mitigate sleep inertia in a real-world setting.\ Thirty-six participants (18 female; 26.6 years ± 6.1) completed an at-home, within-subject, randomized crossover study. Participants followed their habitual sleep-wake schedule for five nights before an adaptation and experimental night. Forty-five minutes after bedtime on the experimental night, participants received a phone call and were instructed to wear light-emitting glasses with the light either on (light condition) or off (control). A 5-minute psychomotor vigilance task (PVT), the Karolinska Sleepiness Scale (KSS), visual analog scales of mood (VASmood), and a 3-minute descending subtraction task (DST) were performed starting at +2, +12, +22, and +32 minutes after the call. Participants then went back to sleep and were called 45 minutes after lights out for the opposite condition. A series of mixed-effects models were performed with fixed effects of test bout, condition, test bout × condition, and a random effect of participant. Covariates included pre-sleep baseline scores, randomization order, sex, and sleep history. Participants rated themselves as more alert and energetic in the light condition compared to the control condition (VASalert-sleepy p = .01; VASlethargic-energetic p = .001). There was no effect of condition for DST outcomes, but there was a significant improvement in DST total responses in the light condition in a subset of participants waking from N3 (p = .03). There was a significant effect of condition for PVT outcomes, with faster responses (p < .001) and fewer lapses (p < .001) in the control condition. Our results under naturalistic at-home settings suggest that, similar to the in-laboratory study findings, the light intervention improved subjective alertness and mood, while working memory improved after waking from N3. Future studies of light interventions should include measures of visual acuity and comfort to assess the full feasibility and efficacy of interventions in real-world environments.

sleep inertia↗

Light as a Reactive Countermeasure to Sleep Inertia: Translating Laboratory Findings to the Field

Sleep inertia describes the brief period of impaired alertness, mood, and cognitive performance experienced after waking. Under laboratory settings, light exposure upon waking during a habitual sleep period has been shown to improve sleep inertia symptoms. We investigated whether a field-deployable light-emitting device would help to mitigate sleep inertia in a real-world setting. Thirty-six participants (18 female; 26.6 years ± 6.1) completed an at-home, within-subject, randomized crossover study. Participants followed their habitual sleep-wake schedule for five nights before an adaptation and experimental night. Forty-five minutes after bedtime on the experimental night, participants received a phone call and were instructed to wear light-emitting glasses with the light either on (light condition) or off (control). A 5-minute psychomotor vigilance task (PVT), the Karolinska Sleepiness Scale (KSS), visual analog scales of mood (VASmood), and a 3-minute descending subtraction task (DST) were performed starting at +2, +12, +22, and +32 minutes after the call. Participants then went back to sleep and were called 45 minutes after lights out for the opposite condition. A series of mixed-effects models were performed with fixed effects of test bout, condition, test bout × condition, and a random effect of participant. Covariates included pre-sleep baseline scores, randomization order, sex, and sleep history. Participants rated themselves as more alert and energetic in the light condition compared to the control condition (VASalert-sleepy p = .01; VASlethargic-energetic p = .001). There was no effect of condition for DST outcomes, but there was a significant improvement in DST total responses in the light condition in a subset of participants waking from N3 (p = .03). There was a significant effect of condition for PVT outcomes, with faster responses (p < .001) and fewer lapses (p < .001) in the control condition. Our results under naturalistic at-home settings suggest that, similar to the in-laboratory study findings, the light intervention improved subjective alertness and mood, while working memory improved after waking from N3. Future studies of light interventions should include measures of visual acuity and comfort to assess the full feasibility and efficacy of interventions in real-world environments.

sleep inertia↗

Characterization of Errors in Satellite-Based HCHO/NO 2 Tropospheric Column Ratios With Respect to Chemistry, Column-to-PBL Translation, Spatial Representation, and Retrieval Uncertainties

The availability of formaldehyde (HCHO) (a proxy for volatile organic compound reactivity) and nitrogen dioxide (NO 2 ) (a proxy for nitrogen oxides) tropospheric columns from ultraviolet–visible (UV–Vis) satellites has motivated many to use their ratios to gain some insights into the near-surface ozone sensitivity. Strong emphasis has been placed on the challenges that come with transforming what is being observed in the tropospheric column to what is actually in the planetary boundary layer (PBL) and near the surface; however, little attention has been paid to other sources of error such as chemistry, spatial representation, and retrieval uncertainties. Here we leverage a wide spectrum of tools and data to quantify those errors carefully. Concerning the chemistry error, a well-characterized box model constrained by more than 500 h of aircraft data from NASA's air quality campaigns is used to simulate the ratio of the chemical loss of HO 2 + RO 2 (LRO x ) to the chemical loss of NO x (LNO x ). Subsequently, we challenge the predictive power of HCHO/NO 2 ratios (FNRs), which are commonly applied in current research, in detecting the underlying ozone regimes by comparing them to LRO x /LNO x . FNRs show a strongly linear (R 2 =0.94) relationship with LRO x /LNO x , but only on the logarithmic scale. Following the baseline (i.e., ln(LRO x /LNO x ) = −1.0 ± 0.2) with the model and mechanism (CB06, r2) used for segregating NO x -sensitive from VOC-sensitive regimes, we observe a broad range of FNR thresholds ranging from 1 to 4. The transitioning ratios strictly follow a Gaussian distribution with a mean and standard deviation of 1.8 and 0.4, respectively. This implies that the FNR has an inherent 20 % standard error (1σ) resulting from not accurately describing the RO x –HO x cycle. We calculate high ozone production rates (PO 3 ) dominated by large HCHO × NO 2 concentration levels, a new proxy for the abundance of ozone precursors. The relationship between PO 3 and HCHO × NO 2 becomes more pronounced when moving towards NO x -sensitive regions due to nonlinear chemistry; our results indicate that there is fruitful information in the HCHO × NO 2 metric that has not been utilized in ozone studies. The vast amount of vertical information on HCHO and NO 2 concentrations from the air quality campaigns enables us to parameterize the vertical shapes of FNRs using a second-order rational function permitting an analytical solution for an altitude adjustment factor to partition the tropospheric columns into the PBL region. We propose a mathematical solution to the spatial representation error based on modeling isotropic semivariograms. Based on summertime-averaged data, the Ozone Monitoring Instrument (OMI) loses 12 % of its spatial information at its native resolution with respect to a high-resolution sensor like the TROPOspheric Monitoring Instrument (TROPOMI) (> 5.5 × 3.5 km 2 ). A pixel with a grid size of 216 km 2 fails at capturing ∼ 65 % of the spatial information in FNRs at a 50 km length scale comparable to the size of a large urban center (e.g., Los Angeles). We ultimately leverage a large suite of in situ and ground-based remote sensing measurements to draw the error distributions of daily TROPOMI and OMI tropospheric NO 2 and HCHO columns. At a 68 % confidence interval (1σ), errors pertaining to daily TROPOMI observations, either HCHO or tropospheric NO 2 columns, should be above 1.2–1.5 × 10 16 molec. cm −2 to attain a 20 %–30 % standard error in the ratio. This level of error is almost non-achievable with the OMI given its large error in HCHO. The satellite column retrieval error is the largest contributor to the total error (40 %–90 %) in the FNRs. Due to a stronger signal in cities, the total relative error (< 50 %) tends to be mild, whereas areas with low vegetation and anthropogenic sources (e.g., the Rocky Mountains) are markedly uncertain (> 100 %). Our study suggests that continuing development in the retrieval algorithm and sensor design and calibration is essential to be able to advance the application of FNRs beyond a qualitative metric.

Amir H. Souri↗

Decoupling in the Vertical Shape of HCHO During a Sea Breeze Event: the Effect on Trace Gas Satellite Retrievals and Column-to-Surface Translation

The effect of sea breeze circulation on stratification of the vertical formaldehyde (HCHO) concentration vertical profiles is explored using a regional atmospheric chemical transport model (CTM) for three synoptically stagnant days focused on the east coast of the U.S in June 2018. During this event, a significant thermal contrast between the Atlantic Ocean and the terrestrial regions (12–17 °C), observed by moderate resolution imaging spectroradiometer (MODIS) and well-captured by the WRF-CMAQ model (15–18 °C), is conducive to monsoon-like flow, perpendicular to the shorelines, carrying clean marine air masses over the land within a few hundreds of meters above the surface. In contrast, the westerly continental polluted air masses prevail in higher altitudes. These two conflicting flows result in atypical vertical shapes of HCHO concentrations increasing with altitude. This decoupling pattern is so pronounced that we observe total column HCHO negatively correlate with surface concentrations. Comparisons of an accredited global model, GEOS-CF, to surface wind measurements and MODIS skin temperature indicate its poor representation of the sea breeze timing and strength, resulting in GEOS-CF HCHO vertical shapes being drastically different from the WRF-CMAQ. Based on radiative transfer calculations, the differences in the vertical distribution of HCHO between the WRF-CMAQ and that of GEOS-CF in the first 3 km are sufficient to induce a 20–30% error in air mass factors (thus total vertical HCHO column abundances). Through an experiment involving converting HCHO total columns to surface mixing ratios, we demonstrate that GEOS-CF allocates noticeably more HCHO molecules (40–150%) to the surface layer due to the misrepresentation of the vertical shape of HCHO during the sea breeze event. It is known that a significant fraction of the human population lives in coastal areas prone to detrimental effects caused by air pollution, and elevated pollutant concentrations usually occur in synoptically stagnant atmospheric conditions when local circulation patterns come into play; accordingly, our experiments emphasize the importance of the effect a priori profiles can have on satellite-derived applications under such conditions. To ensure that the quantitative representation of satellite-based trace gas retrievals on a daily basis is trustworthy and useable for air quality applications, atmospheric models providing a priori profiles for satellite retrievals should be well-tuned to reproduce complex local circulation such as sea-land breezes.

sea breeze↗