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A New Global Core Plasma Model of the Plasmasphere

The Global Core Plasma Model (GCPM) is the first empirical model for thermal inner magnetospheric plasma designed to integrate previous models and observations into a continuous in value and gradient representation of typical total densities. New information about the plasmasphere, in particular, make possible significant improvement. The IMAGE Mission Radio Plasma Imager (RPI) has obtained the first observations of total plasma densities along magnetic field lines in the plasmasphere and polar cap. Dynamics Explorer 1 Retarding Ion Mass Spectrometer (RIMS) has provided densities in temperatures in the plasmasphere for 5 ion species. These and other works enable a new more detailed empirical model of thermal in the inner magnetosphere that will be presented. Specifically shown here are the inner-plasmasphere RIMS measurements, radial fits to densities and temperatures for H(+), He(+), He(++), O(+), and O(+) and the error associated with these initial simple fits. Also shown are more subtle dependencies on the f10.7 P-value (see Richards et al. [1994]).

plasmasphere density↗

The Exoplanet Mass-Ratio Function From the MOA-II Survey: Discovery of a Break and Likely Peak at a Neptune Mass

We report the results of the statistical analysis of planetary signals discovered in MOA-II microlensing survey alert system events from 2007 to 2012. We determine the survey sensitivity as a function of planet star mass ratio, q, and projected planet star separation, s, in Einstein radius units. We find that the mass-ratio function is not a single power law, but has a change in slope at q approx.10(exp -4), corresponding to approx. 20 Stellar Mass for the median host-star mass of approx. 0.6 M. We find significant planetary signals in 23 of the 1474 alert events that are well-characterized by the MOA-II survey data alone. Data from other groups are used only to characterize planetary signals that have been identified in the MOA data alone. The distribution of mass ratios and separations of the planets found in our sample are well fit by a broken power-law model. We also combine this analysis with the previous analyses of Gould et al. and Cassan et al., bringing the total sample to 30 planets. The unbroken power-law model is disfavored with a p-value of 0.0022, which corresponds to a Bayes factor of 27 favoring the broken power-law model. These results imply that cold Neptunes are likely to be the most common type of planets beyond the snow line.

MOA-II microlensing survey alert↗

BAT AGN Spectroscopic Survey - III. An Observed Link Between AGN Eddington Ratio and Narrow-Emission-Line Ratios

We investigate the observed relationship between black hole mass (M(sub BH)), bolometric luminosity (L(sub bol)) and Eddington ratio (lambda(sub Edd)) with optical emission-line ratios ([N II] lambda6583/Halpha, [S II]lambda-lamda6716, 6731/Halpha, [O I] lamda6300/Halpha, [O III] lamda5007/Hbeta, [Ne III] lamda3869/Hbeta and He II lamda4686/Hbeta) of hard X-ray-selected active galactic nuclei (AGN) from the BAT AGN Spectroscopic Survey. We show that the [N II] lamda6583/Halpha ratio exhibits a significant correlation with lamda(sub Edd) (R(sub Pear) = -0.44, p-value 3 x 10(exp. -13) sigma = 0.28 dex), and the correlation is not solely driven by M(sub BH) or L(sub bol). The observed correlation between [N II] lamda6583/Halpha ratio and M(sub BH) is stronger than the correlation with L(sub bol), but both are weaker than the lamda(sub Edd) correlation. This implies that the large-scale narrow lines of AGN host galaxies carry information about the accretion state of the AGN central engine. We propose that [N II] lamda6583/Halpha is a useful indicator of Eddington ratio with 0.6 dex of rms scatter, and that it can be used to measure lambda(sub Edd) and thus M(sub BH) from the measured L(sub bol), even for high-redshift obscured AGN. We briefly discuss possible physical mechanisms behind this correlation, such as the mass-metallicity relation, X-ray heating, and radiatively driven outflows.

black hole physics – galaxies: active – galaxi↗

Biomass Retrieval from L-Band Polarimetric UAVSAR Backscatter and PRISM Stereo Imagery

The forest above-ground biomass (AGB) and spatial distribution of vegetation elements have profound effects on the productivity and biodiversity of terrestrial ecosystems. In this paper, we evaluated biomass estimation from L-band Synthetic Aperture Radar (SAR) data acquired by National Aeronautics and Space Administration (NASA) Uninhabited Aerial Vehicle SAR (UAVSAR) and the improvement of accuracy by adding canopy height information derived from stereo imagery acquired by Japan Aerospace Exploration Agency (JAXA) Panchromatic Remote Sensing Instrument for Stereo Mapping (PRISM) on-board the Advanced Land Observing Satellite (ALOS). Various models for prediction of forest biomass from UAVSAR data were investigated at pixel sizes of 1/4 ha (50 m x 50 m) and 1 ha. The variance inflation factor (VIF) was calculated for each of the explanatory variables in multivariable regression models to assess the multi-collinearity between explanatory variables. In addition, the t-and p-values were used to interpret the significance of the coefficients of each explanatory variables. The R(exp. 2), Root Mean Square Error (RMSE), bias and Akaike information criterion (AIC), and leave-one-out cross-validation (LOOCV) and bootstrapping were used to validate models. At 1/4-ha scale, the R(exp. 2) and RMSE of biomass estimation from a model using a single track of polarimetric UAVSAR data were 0.59 and 52.08 Mg/ha. With canopy height from PRISM as additional independent variable, R(exp. 2) increased to 0.76 and RMSE decreased to 39.74 Mg/ha (28.24%). At 1-ha scale, the RMSE of biomass estimation based on UAVSAR data of a single track was 39.42 Mg/ha with a R(exp. 2) of 0.77. With the canopy height from PRISM, R(exp. 2) increased to 0.86 and RMSE decreased to 29.47 Mg/ha (20.18%). The models using UAVSAR data alone underestimated biomass at levels above approximately 150 Mg/ha showing the saturation phenomenon. Adding canopy height from PRISM stereo imagery significantly improved the biomass estimation and elevated the saturation level in estimating biomass. Combined use of UAVSAR data acquired from opposite directions (odd and even tracks) slightly improved the biomass estimation.Combined use of UAVSAR data acquired from opposite directions (odd and even tracks) slightly improved the biomass estimation at 1/4-ha scale, R(exp. 2) increased from 0.59 to 0.66 and RMSE reduced from 52.08 to 48.57 Mg/ha. Averaging multiple acquisitions of UAVSAR data from the same look azimuth direction did not improve biomass estimation. A biomass map derived from NASA's LVIS (Laser Vegetation Imaging System) wave-form data was used as a reference for evaluation of the biomass maps from these models. The study has also shown that the errors decreased when deciduous, evergreen, and mixed forests were modeled separately but the improvement was not significant

Zhang, Zhiyu↗

Oculomotor Assessment of Diurnal Arousal Variations

Saccadic and pupillary responses are reliable indices of arousal decrement (e.g. fatigue), that might be exploited to improve work schedule guidelines. In this study, we tested the sensitivity of a short 30-s oculomotor test to detect diurnal arousal variations. Twelve participants (5 females, 7 males, 37.7+-11.9 years) volunteered to be assessed every hour (66+-20 min) for three consecutive working days, during their regular office-hours. We used a fully automated testing system, the FIT 2000 Fitness Impairment Tester (Pulse Medical Instruments Inc., Rockville, MD, USA), to measure and record saccadic peak velocity, pupil diameter, and latency and amplitude of the pupillary light reflex. In addition, we collected subjective levels of arousal using the Stanford Sleepiness Scale, and body core temperature. We analyzed the data using a linear mixed model approach for longitudinal data. Both saccadic velocity and subjective alertness decreased over the course of a day, while body core temperature increased (all p-values.05). The data also weakly suggested an increase of the pupil diameter (p 07). The findings support the use of oculomotor indices in the assessment of arousal and fatigue in applied settings.

saccadic velocity↗

Discovery of Activities via Statistical Clustering of Fixation Patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a piloting an aircraft, where activities with distinct visual signatures might be things like communicating, navigating, and monitoring. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. The method is in some respects similar to recurrence analysis, but here we compare not individual fixations, but groups of fixations aggregated over a fixed time interval. The duration of this interval is a parameter that we will refer to as delta. We assume that the environment has been divided into a set of N different areas-of-interest (AOIs). For a given interval of time of duration delta, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector. These proportions can be converted to integer counts by multiplying by delta divided by the average fixation duration (another parameter that we fix at 280 milliseconds). We compare different intervals by computing the chi-square statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. The method has been applied to approximately 100 hours of eye movement data collected from pilots in a high-fidelity B747 flight simulator, and the results have been compared to synthetic data in which the each activity is represented as first-order Markov process with random probabilities assigned to the AOIs. Randomly-generated synthetic activities can require thousands of fixations to be discriminated with statistical significance, while the human data can be clustered using averaging windows of some 10's of seconds, suggesting that the actual activities are much more narrowly focused than random Markov models.

activity analysis↗

Trends and Seasonal Variability of Atmospheric NO2 and HNO3 Concentrations Across Three Major African Biomes Inferred from Long-Term Series of Ground-Based and Satellite Measurements

In the framework of the INDAAF (International Network to study Deposition and Atmospheric chemistry in AFrica) programme, part of the ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure), European Research Infrastructure for the long-term observation of Aerosol, Cloud, and Trace gases, this paper aims to study trends and seasonal variability of surface atmospheric NO2 and HNO3 concentrations, and OMI (Ozone Monitoring Instrument) NO2 over 6 sites in tropical Africa. Sites are located in west and central Africa to represent the major African biomes: dry savanna (Banizoumbou, Niger and Katibougou, Mali), wet savanna (Djougou, Benin and Lamto, Côte d’Ivoire) and forest (Bomassa, Republic of Congo and Zoétélé, Cameroon). Ground-based NO2 and HNO3 concentrations were obtained over the period 1998–2015 using INDAAF passive samplers at a monthly basis, and NO2 Vertical Column Densities (VCDs) from OMI for a 1-degree grid cell around each sites were obtained from 2005 to 2015. Mean annual NO2 concentrations ranged from 2.3 plus or minus 1.2 to 0.9 plus or minus 0.4 parts per billion (ppb) from dry savannas to forests, representing a north-south gradient. In dry savannas, we observe two concentration peaks of NO2 appearing at the beginning and the end of the wet season both for ground-based and satellite measurements, whereas at wet savannas and forest sites, NO2 concentrations are highest in the dry season. The seasonality of surface NO2 observations provide further evidence for a large role of microbial soil NOx emissions in dry savannas and of biomass burning NOx emissions in wet savanna and forest sites. Mean annual HNO3 concentrations ranged from 0.4 to 0.5 ppb in dry and wet savannas to 0.2 to 0.3 ppb in forest. In dry ecosystems, higher HNO3 concentrations are measured in the early wet season, consistent with NO2 results. The analysis of a long-term dataset of surface O3 concentrations indicates that HNO3 production can mainly be explained by the photo-oxidation of NOx. Mann-Kendall and Seasonal Kendall statistical tests showed that NO2 surface concentrations have a significant decreasing seasonal and annual trends at multiple sites (p-value less than 0.05) ranging from -2.96 percent per year (at Zoétélé) to -0.64 percent per year (at Banizoumbou). HNO3 results indicate no trends except at Bomassa (1.07 percent per year). The decreasing NO2 ground-based concentration trends observed in wet savannas sites are correlated with OMI NO2 decreasing trends at these sites. Trends obtained for NO2 concentrations in wet savanna and forest ecosystems are consistent with trends of NOₓ biomass burning emissions.

Trends↗

Constraints on Mars Aphelion Cloud Belt phase function and ice crystal geometries

This study constrains the lower bound of the scattering phase function of Martian water ice clouds (WICs) throughthe implementation of a new observation aboard the Mars Science Laboratory (MSL). The Phase Function SkySurvey (PFSS) was a multiple pointing all-sky observation taken with the navigation cameras (Navcam) aboardMSL. The PFSS was executed 35 times during the Aphelion Cloud Belt (ACB) season of Mars Year 34 over a solarlongitude range of Ls = 61:4 156:5. Twenty observations occurred in the morning hours between 06:00 and 09:30 LTST, and 15 runs occurred in the evening hours between 14:30 and 18:00 LTST, with an operationallyrequired 2.5 h gap on either side of local noon due the sun being located near zenith. The resultant WIC phasefunction was derived over an observed scattering angle range of 18.3-152.61, normalized, and compared with 9modeled phase functions: seven ice crystal habits and two Martian WIC phase functions currently being implementedin models. Through statistical chi-squared probability tests, the five most probable ice crystal geometriesobserved in the ACB WICs were aggregates, hexagonal solid columns, hollow columns, plates, and bullet rosetteswith p-values greater than or equal to 0.60, 0.57,0.56,0.56, and 0.55, respectively. Droxtals and spheres had pvaluesof 0.35, and 0.2, making them less probable components of Martian WICs, but still statistically possibleones. Having a better understanding of the ice crystal habit and phase function of Martian water ice cloudsdirectly benefits Martian climate models which currently assume spherical and cylindrical particles.

Cooper, Brittney↗

Discovery of Activities via Statistical Clustering of Fixation Patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a pilot flying an airplane; in this case, activities with distinct visual signatures might be things like communicating, navigating, monitoring, etc. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. We compare, not individual fixations, but groups of fixations aggregated over a fixed time interval (Tau). We assume that the environment has been divided into a finite set of discrete areas-of-interest (AOIs). For a given time interval, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector, where N is the number of AOIs. These proportions can be converted to integer counts by multiplying by Tau divided by the average fixation duration, a parameter that we fix at 283 milliseconds. We compare different intervals by computing the chi-squared statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. We cluster the intervals, first by merging adjacent intervals that are sufficiently similar, optionally shifting the boundary between non-merged intervals to maximize the difference. Then we compare and cluster non-adjacent intervals. The method is evaluated using synthetic data generated by a hand-crafted set of activities. While the method generally finds more activities than put into the simulation, we have obtained agreement as high as 80 percent between the inferred activity labels and ground truth.

Eye Movements↗

The Importance of Star Formation Intensity in Lyα Escape from Green Pea Galaxies and Lyman Break Galaxy Analogs

We have studied ultraviolet images of 40 Green Pea galaxies and 15 local Lyman Break Galaxy Analogs to understand the relation between Lyα photon escape and central UV photometric properties. We measured star formation intensity (SFI; star formation rate per unit area) from the central 250 pc region (S250 pc) using Cosmic Origins Spectrograph near-ultraviolet images from the Hubble Space Telescope. The measured S250 pc of our sample Green Peas ranges from 2.3–46M☉ yr−1 kpc−2, with a geometric mean of 15M☉ yr−1 kpc−2 and a standard deviation of 0.266 dex, forming a relatively narrow distribution. The Lyman Break Galaxy Analogs show a similarly narrow distribution of S250 pc (0.271 dex), though with a larger mean of 28M☉ yr−1 kpc−2. We show that while the Lyα equivalent width (EW(Lyα)) and the Lyα escape fraction ( f a esc Lyα) are not significantly correlated with the central SFI (S250 pc), both are positively correlated with the ratio of surface brightness to galaxy stellar mass (S250 pc/Mstar), with correlation coefficients (p-values) of 0.702 (1 × 10−8) and 0.529 (5 × 10−4) with EW(Lyα) and f a esc Lyα, respectively. These correlations suggest a scenario where intense central star formation can drive a galactic wind in galaxies with relatively shallow gravitational potential wells, thus clearing channels for the escape of Lyα photons.

Compact galaxies↗

A Universal Algorithm for the Detection of Bi-directional Gage Output Characteristics

A universal algorithm was developed that may be used to assess the bi-directional characteristics of the gage outputs of a wind tunnel strain-gage balance. The algorithm assumes that balance loads and gage outputs are described in the design format of the balance. It can also be applied to balance calibration data that is processed by using either the Iterative Method or the Non-Iterative Method. The algorithm uses an estimate of the bi-directional part of a gage output at load capacity as input. In addition, the statistical significance of the principle absolute value term in the regression model of either the gage output or the related primary load component is determined. A gage output is assumed to be bi-directional if two conditions are fulfilled: the bi-directional part of the output at load capacity exceeds 0.5 percent of the maximum output at load capacity; the p-value of the principle absolute value term of the regression model of the balance data is less than the threshold of 0.001. Data from the calibration of two six-component force balances and one five-component semi-span balance are used to illustrate the application of the universal detection algorithm.

wind tunnel test↗

Transcriptomic Analysis of Irradiated Mouse Retina Following Readaptation

Rodent models are used as analogs for studying the effects of spaceflight. NASA GeneLab provides access to relevant omics datasets generated from spaceflight and ground-based experiments allowing for additional retrospective analysis. In this study, we used GeneLab’s GLDS-203, a dataset generated by researchers at Loma Linda University to study the impact of prolonged unloading and/or low-dose radiation on mouse retina. We analyzed transcriptomics data from retina of mice irradiated with gamma-rays for 21 days followed by 7 days, 1 month, or 4 months of readaptation. We obtained raw gene counts from GeneLab and performed differential gene expression analysis after data normalization. For each of the three timepoints, we performed differential expression analysis to compare transcriptional profiles for retina from irradiated vs. non-irradiated (controls) mice, all exposed to gravity. We observed the highest number of differentially expressed genes at 7 days, followed by 1 month and 4 months. Enrichment analysis showed top pathways (adjusted p-value < 0.05) were related to transport along microtubule and photoreceptor cell development in the 7-day readaptation group. Fewer significantly enriched pathways were observed for the 1-month group and included mRNA metabolic processes and neuron differentiation. No significantly enriched pathways were found in the 4-month group. The Gene Ontology biological processes common between the 7 days and 1-month groups include visual perception, synapse organization, and perception of light stimulus. This analysis is part of a larger effort to characterize the molecular mechanisms involved in retinal readaptation following radiation exposure. Future analyses will include other related retina datasets in GeneLab repository to assess whether gene expression patterns are consistent across different study cohorts.

Prachi Kothiyal↗

Oxygen Deficiency in Spaceflight & its Impact on Plants’ Adaptive Changes

The goal of this study was to investigate the effects of hypoxic conditions in spaceflight. The distribution of genes involved with hypoxia in Arabidopsis thaliana and Brassica rapa were analyzed with the results from past spaceflight experiments to evaluate genes for future studies. Transcriptomes data of two different spaceflight studies of Arabidopsis thaliana from the NASA GeneLab database, GLDS-7 and GLDS-17, were compared. DNA microarrays were utilized for transcription profiling to conduct these studies. For GLDS-7, the response in spaceflight was studied with approaches that collected gene expression data. Leaves, hypocotyls, and root tissues were compared to the whole plant. For GLDS-17, seedlings and undifferentiated cultured cells were placed in the Biological Research in Canisters (BRIC), specifically BRIC-16. The genes related to hypoxia in Arabidopsis thaliana from these two studies were compared to genes in Brassica rapa with the TOAST database to evaluate similarities. When transcriptomes were analyzed for GLDS-7 and 17, genes that were considered significant had p-values ≤ 0.05 and log fold change values ≤ -1 or ≥1. Sixteen genes fulfilled the criteria. The genes related to hypoxia were alcohol dehydrogenase, elongation factor, ethylene-responsive factor, GUS, heat-shock proteins, NAP, RAP2.12, and RD20. The genes most impacted by spaceflight were heat-shock proteins. These genes were compared with Brassica rapa through Arabidopsis Ensemble Orthology from the TOAST Database. Similarities were seen in alcohol dehydrogenase, elongation factor, ethylene-responsive factor, heat-shock proteins, NAP, and RAP2.12. Overall, transcription profiling indicates that plants’ survival in spaceflight is dependent on adaptive changes with gene expression. This study also indicates that there are similarities in gene expression between Arabidopsis thaliana and Brassica rapa with comparable gene expression. Future studies could include analyzing additional species to understand which genes could be modified to ensure better yield of space crops amid hypoxic conditions.

hypoxia↗

Evaluating Plant Suberin Mutants for Enhanced Water and Nutrient Uptake to Increase Biomass Production Under Elevated CO2 Concentrations

Spaceflight cabin environments such as the International Space Station (ISS) typically have elevated CO2(1500-7000 μmol mol-1), which can affect plant growth and development. On earth, findings from FACE (Free-Air CO2Enrichment) and climate change studies have shown that plants grown at elevated (~ 700 μmol mol-1) CO2contain reduced levels of essential elements such as nitrogen, zinc, and iron. We hypothesized that spacecraft environments with elevated CO2 might likewise result in less nutritious crops for human consumption. Literature showed that quantitative differences in root suberin content could determine the permeability of the internal plant tissues to both water and solutes. To evaluate if there was a correlation between growth under elevated CO2and root suberin content we grew Arabidopsis thaliana, wild type (WT)(col-0), esb1(Enhanced Suberin 1) and horst1(Hydroxylase of Root Suberized Tissue)under ambient (~ 420± 25μmol mol-1) and elevated (800 ± 25, 1600 ± 25, 4000 ± 25 μmol mol-1) CO2concentrations. Comparing the growth of esb1and horst1plants to WT under ambient and elevated CO2concentrations, esb1showed significantly (P-value < 0.05) lower total fresh biomass whereas the horst1exhibited no significant difference. RNA sequencing revealed genes related to water uptake or nutrient availability stress upregulated due to the exposure to 800 and 1600 μmol mol-1CO2.Comparing the elemental composition of leaf tissue between WT and horst1plants grown under elevated CO2,we found an overall decrease in elemental composition for WT, whereas horst1showed an average increase of 30-60 % in the elemental contentsat1600 μmol mol-1compared to plants grown at ambient CO2. In conclusion, our results showed that horst1like modification to edible crops could improve the nutritional (elemental) content to supplement astronaut’s diet.

Anirudha R Dixit↗

Functional Task Tests in Partial Gravity During Parabolic Flight

BACKGROUND Understanding how critical mission tasks are performed in partial gravity such as on the moon or Mars is necessary to define effective and comprehensive countermeasure strategies for preserving crew performance during exploration missions. We studied the performance of tasks such as standing, walking, and jumping during the partial gravity phases of parabolic flight. We hypothesized that the acute effects of partial gravity on vestibular, proprioceptive, and sensorimotor functions would negatively impact performance. METHODS Twelve subjects were tested over three flights of 30 parabolas each, including 10 parabolas at 0.25g, 10 parabolas at 0.5g, and 10 parabolas at 0.75g. Subjects also performed tests in 1g between parabolas. During the sit-to-stand with obstacle walk task, subjects rose from a seated position and walked as quickly as possible straight ahead towards a cone (4 m distance), walked around the cone making a 180° left turn, returned, and sat in the chair. On the way to and from the cone, subjects stepped over a 30 cm high obstacle. For the recovery from fall task, subjects lay prone for the pull-up phase and initial 10 sec of the parabola. Then they were asked to rise as quickly as possible and maintain a quiet stance for 10 sec. The tandem rail balance task involved standing with both feet on a 4.5 cm wide rail. The time ended when subjects either stepped off the rail or grabbed on to support straps. The jump down task started with the subjects standing on a 30 cm high platform, then the subjects were instructed to step off the platform, land with both feet simultaneously, and settle in a quiet stance. The cone of stability task involved subjects leaning about the ankles as far as they could in the anterior, posterior, and lateral directions without unfolding their arms or taking a step. The center of pressure distance between endpoints was calculated. Data were collected using inertial measurement units (Opal V2, APDM, Portland, OR) worn on the head and trunk, heart rate monitors (RS800CX, Polar, Kempele, Finland), and a force plate (Bertec, Columbus, OH). RESULTS Gravity level had a significant effect on performance, with the greatest changes from 1g tending to be at the 0.25g level (Table 1). Lower gravity levels were associated with increased times to complete the sit-to-stand obstacle walk task and the recovery from fall task, decreased change in heart rate during the recovery from fall task, decreased rail balance times, and increased cone of stability distance in the anterior-posterior direction. Table 1. Functional task performance at different gravity levels during parabolic flight. Measure0.25g0.5g0.75g1gp-valueSit-to-stand with obstacle walk time (sec)9.8 ±1.4*7.2 ±0.76.9 ±0.8*7.4 ±0.9<0.001Recovery from fall time to settle (sec)5.3 ± 0.9*4.6 ± 0.84.2 ± 0.64.3 ± 0.70.002Recovery from fall change in heart rate (bpm)6.0 ± 7.3*11.2 ± 6.5*14.9 ± 4.915.9 ± 6.5<0.001Rail balance with eyes open time (sec)2.7 ±0.8*4.8 ±2.16.6 ±4.78.4 ±6.70.031Rail balance with eyes closed time (sec)1.6 ±0.4*2.1 ±0.42.4 ±0.62.6 ±0.8<0.001Jump down time to settle (sec)2.1 ± 0.41.9 ± 0.42.0 ± 0.31.8 ± 0.30.328Cone of stability –anterior-posterior (cm)20.8 ±2.7*18.8 ±2.218.6 ±1.717.9 ±2.00.039Cone of stability –lateral (cm)26.8 ±6.624.4 ±2.123.0 ±2.123.8 ±2.30.215p-value: one-way repeated measures analysis of variance; *Significant pairwise difference from 1g (p<0.05). DISCUSSION These data suggest that there is a dose-response relationship between gravity level and functional task performance. The largest changes in performance were expected at the lowest gravity level (0.25g) because subjects would no longer be able to use the gravitational reference for the perception of upright. Understanding the extent of performance deficits informs the risks and design of countermeasures for exploration spaceflight missions. ACKNOWLEDGEMENT This work is supported by NASA’s Human Research Program Human Health Countermeasures Element.

T R Macaulay↗

Changes in Oculomotor Behavior and PVT Reaction Time During One Night of Sleep Deprivation

INTRODUCTION: The Psychomotor Vigilance Test (PVT) is a widely used objective measure of sustained attention, alertness, and fatigue. Previous studies consistently show that prolonged wakefulness and disrupted sleep patterns lead to increased lapses of attention and slower reaction times. These findings have critical implications for various professions, including healthcare, aviation, transportation safety, and spaceflight. In this study, we employed linear mixed models (LMM) to investigate hourly-measured 5-minute PVT reaction times during one night of total sleep deprivation. Our goal was to characterize the contribution of homeostatic sleep pressure (time awake) and circadian phase (salivary melatonin levels) on the dynamics of PVT reaction time. MATERIALS & METHODS: Data from twelve human participants were used in the analysis. Participants were healthy non-smokers, aged 18 and 40, with normal sleep habits defined as Pittsburg Sleep Quality Index scores < 5, and Morningness – Eveningness Questionnaire scores > 42 and < 58, respectively. Participants followed a constant-routine protocol and arrived at the NASA sleep laboratory approximately 1 to 2 hours after their habitual waking time. Tympanic temperature was measured every 30 min to provide a real-time estimate of circadian phase. Participants were required to stay awake throughout the laboratory experiment, which continued until their tympanic temperature had returned to baseline levels. This approach ensured that we could capture each participant's circadian trough and recovery, typically occurring between 24 and 26 hours after waking. The PVT and saliva melatonin were measured every hour, starting approximately from 3 hours after awakening. More information about the measurement protocol can be found in the publication by Stone et al. We used PVT reaction times between 100 and 10000 ms to calculate Reciprocal Reaction Times (RRTs). LMM models were employed to assess the contribution of time awake and saliva melatonin levels on changes in RRTs. Two models were created: the first model treated time awake as a fixed effect and the second model considered both the salivary melatonin level and time awake as fixed effects. Participants were included as a random effect in both models. We compared the models using an Analysis of Variance (ANOVA). The models were computed using the 'lmer' function from the 'lme4' package in R, and LMM p-values were determined using Satterthwaite's method. RESULTS: We found that time awake had a statistically significant effect on PVT RRTs during one night of sleep deprivation [χ2 = 2132.4, df = 1, p < 0.001]. In addition, the model including both saliva melatonin levels and time awake was statistically significantly better than one that uses just time awake [χ2 = 17.4, df = 1, p < 0.001]. DISCUSSION & CONCLUSION: As expected, these preliminary results suggest that the time awake and circadian phase each contribute to performance reductions as measured by the PVT. Future analyses will explore the contributions of other factors to the model.

sleep deprivation↗

Relating Aerial Infrared Thermography Defects to Photovoltaic Performance: Preprint

In this research, we examine the relationship between aerial IR defect analysis and photovoltaic (PV) performance data for twelve utility- and commercial-scale solar sites in the United States. To do this, we fuse the site diagram geoJSON's, aerial infrared thermography (aIRT) defect analyses, and associated inverter time series, allowing for a direct comparison between site defects and time series data. Defect analyses were provided by Zeitview, under its Solar Insights platform. Following the data fusion process, we look at the relationship between system performance and aIRT defects. We investigate the relationship between degradation and hotspot defects, as well as the relationship between AC power data and offline strings and misaligned modules. In general, system degradation was not affected by long-term or balance-of-system (BoS) defects as they occurred infrequently in the data set. However, for one system, a near statistically significant relationship (p-value=0.057) was found when comparing the degradation of inverter blocks with several multi-hotspot defects to all other inverter blocks without this particular defect. There was strong alignment when comparing short-term recoverable module defects such as stuck trackers and offline strings to time series data. In general, we found that when an inverter block has more than 80% of modules flagged for one of these defects, its AC power time data is flat-lined and the inverter block is not producing.

aerial inspection↗

Measuring the Muon Neutrino Magnetic Moment in the NOvA Near Detector

Measuring an enhanced neutrino magnetic moment would be a clear indication of physics beyond the Standard Model, shedding light on the correct beyond Standard Model theory or the potential Majorana nature of neutrinos. It would manifest in the NOvA near detector as an excess of neutrino-on-electron elastic scattering interactions at low electron recoil energies. Leveraging an intense and highly pure muon neutrino beam, along with a finely segmented liquid scintillator detector technology specifically designed for electromagnetic shower separation, enables NOvA to achieve a potentially world-leading sensitivity in probing the effective muon neutrino magnetic moment. This analysis, based on neutrino data collected between 2014 and 2021, corresponding to an exposure of $13.8\times10^{20}$ protons-on-target, yields a result consistent with the Standard Model-only hypothesis with a p-value of 0.31. An upper limit on the effective muon neutrino magnetic moment is set at $\mu_{\nu_\mu}<19.1\times 10^{-10}\mu_B$ at $90\%$ confidence level. Despite facing statistical limitations stemming from low cross section of the signal process, systematic uncertainties have a significant impact on this result. To address these challenges, the NOvA Test Beam experiment focuses on mitigating some of the largest systematic uncertainties within NOvA by investigating particle interactions and energy deposition in a small-scale replica NOvA detector. This thesis describes the calibration of the NOvA Test Beam detector, which is a crucial step in analysing the Test Beam data before they can be utilised to reduce NOvA systematic uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗