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All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Perl Tools for Automating Satellite Ground Systems

The freeware scripting language Pert offers many opportunities for automating satellite ground systems for new satellites as well as older, in situ systems. This paper describes a toolkit that has evolved from of the experiences gained by using Pert to automate the ground system for the Compton Gamma Ray Observatory (CGRO) and for automating some of the elements in the Earth Observing System Data and Operations System (EDOS) ground system at Goddard Space Flight Center (GSFC). CGRO is an older ground system that was forced to automate because of fund cuts. Three 8 hour shifts were cut back to one 8 hour shift, 7 days per week. EDOS supports a new mission called Terra, launched December 1999 that requires distribution and tracking of mission-critical reports throughout the world. Both of these ground systems use Pert scripts to process data and display it on the Internet as well as scripts to coordinate many of the other systems that make these ground systems work as a coherent whole. Another task called Automated Multimodal Trend Analysis System (AMTAS) is looking at technology for isolation and recovery of spacecraft problems. This effort has led to prototypes that seek to evaluate various tools and technology that meet at least some of the AMTAS goals. The tools, experiences, and lessons learned by implementing these systems are described here.

McLean, David↗
DOE OSTI2022

Role of Bifunctional Ru/Acid Catalysts in the Selective Hydrocracking of Polyethylene and Polypropylene Waste to Liquid Hydrocarbons

Hydrogenolysis of C–C bonds over Ru-based catalysts has emerged as a deconstruction strategy to convert single-use polyolefin waste to liquid alkanes at relatively mild conditions, but this approach exhibits limitations, including methane formation resulting from terminal C–C bond scission. In this study, a variety of catalysts were investigated for the reductive deconstruction of polyethylene (PE) and polypropylene (PP) to identify supports that promote nonterminal C–C bond scission. We found that Ru nanoparticles supported on Brønsted-acidic zeolites with the faujasite (FAU) and Beta (BEA) topologies were highly active for the cleavage of C–C bonds in PE and PP, exhibiting improved liquid yields and suppressed methane formation. For the deconstruction of PE, supporting ruthenium nanoparticles (5 wt %) on FAU increased the yields of liquid alkanes to 67% compared to 33% over an inert silica support (5 wt % Ru/SiO 2 ) at 200 °C, 16 h, under 30 bar of H2. A dramatic selectivity enhancement toward liquid hydrocarbons was also observed for PP over Ru/FAU and Ru/BEA compared to Ru/SiO 2 . To understand the origin of this selectivity improvement, a combination of ex situ and operando characterization techniques were used to reveal that both catalyst structure and acidity play key roles in PE and PP conversion. Operando X-ray absorption spectroscopy studies with model polyolefins over Ru-supported catalysts with varying acidity levels revealed that the local chemical environment of Ru [0] during the reaction is consistent across multiple acidic supports, although the onset of reduction during synthesis of the nanoparticles varies across different supports. These results, combined with reactivity data, demonstrate the importance of the acid-noble metal cooperativity in promoting selective C–C bond scission toward liquid alkanes that shifts the mechanism from hydrogenolysis to ideal hydrocracking.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

Carrier Estimation Using Classic Spectral Estimation Techniques for the Proposed Demand Assignment Multiple Access Service

In any satellite communication, the Doppler shift associated with the satellite's position and velocity must be calculated in order to determine the carrier frequency. If the satellite state vector is unknown then some estimate must be formed of the Doppler-shifted carrier frequency. One elementary technique is to examine the signal spectrum and base the estimate on the dominant spectral component. If, however, the carrier is spread (as in most satellite communications) this technique may fail unless the chip rate-to-data rate ratio (processing gain) associated with the carrier is small. In this case, there may be enough spectral energy to allow peak detection against a noise background. In this thesis, we present a method to estimate the frequency (without knowledge of the Doppler shift) of a spread-spectrum carrier assuming a small processing gain and binary-phase shift keying (BPSK) modulation. Our method relies on an averaged discrete Fourier transform along with peak detection on spectral match filtered data. We provide theory and simulation results indicating the accuracy of this method. In addition, we will describe an all-digital hardware design based around a Motorola DSP56303 and high-speed A/D which implements this technique in real-time. The hardware design is to be used in NMSU's implementation of NASA's demand assignment, multiple access (DAMA) service.

Scaife, Bradley James↗
NASA NTRS1993

Hydrogen broadening and collision-induced line shifts of methane at 4200/cm

Many of the lines of the nu1 + nu4 and nu3 + nu4 bands of methane in the vicinity of 4200/cm have been assigned and are reported in the HITRAN data-base which is commonly used for atmospheric transmission calculations in the IR. The collision-induced broadening coefficients of hydrogen for more than 200 of these lines are reported. Also, by using the water-vapor lines which occur in the spectra as calibration marks, the frequencies of the broadened lines are determined. This permitted the collision-induced line shifts to be measured for lines sufficiently isolated from interfering blends: all of the shifts which could be reliably determined in this way were negative.

Margolis, Jack S.↗
DOE OSTI2026

Alleviating prior dependencies for DESI DR1 clustering fits through reparameterization

Bayesian analyses of the full-shape clustering of Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) exhibit prior-volume projection effects, whereby weakly constrained nuisance parameters of the Effective Field Theory of Large Scale Structure (EFTofLSS) shift marginalized cosmological posteriors away from the posterior maximum. We reanalyze DESI DR1 power spectrum multipoles using two complementary mitigation strategies: (i) nonlinear orthogonalization to decorrelate nuisance and cosmological parameter priors, and (ii) a fully reparameterization-invariant Jeffreys prior over all EFTofLSS coefficients, evaluated on-the-fly via closed-form Jacobians. Including data from DESI, Big-Bang Nuclesynthesis and a constraint on $n_{\mathrm{s}}$, baseline priors lead to multi-$σ$ projection in the Hubble parameter $H_{0}$ and dark energy equation of state parameters $w_{0}$ and $w_{a}$; the Jeffreys prior successfully recenters these posteriors to enclose the maximum a posteriori estimate within the 68% credible regions, demonstrating clear mitigation of projection effects for these late-time expansion parameters. A hybrid Jeffreys+baseline-Gaussian configuration controls residual over-broad tails in the physical cold dark matter density $ω_{\mathrm{c}}$ while preserving the volume correction, and is our favoured approach. We compare the credible intervals derived using our methodology to those obtained using Halo Occupation Distribution (HOD)-informed priors and to confidence intervals derived using frequentist profile likelihood analyses, finding agreement in both central values and degeneracy directions in the $w_{0}$--$w_{a}$ plane. This demonstrates that, once projection effects are properly controlled, we can make robust inferences about the late-time cosmological expansion independent of the statistical framework adopted.

Bonici, M. [Waterloo U.; Perimeter Inst. Theor. Ph↗
DOE OSTI2022

The Complete α 8 m Contributions to the 1s Lamb Shift in Hydrogen

Precision studies of simple atoms, such as hydrogen, play an essential role in tests of bound-state QED and determining fundamental constants, such as the Rydberg constant and the proton charge radius. One of the QED predictions is for the Lamb shift of hydrogenic energy levels and, in particular, of the ground state. Here, the value of the 1s Lamb shift in hydrogen and deuterium is required for an accurate determination of the Rydberg constant and the proton charge radius utilizing data from high-resolution spectroscopy of hydrogen and deuterium atoms, as well as for precision tests of bound-state QED. The dominant QED contribution to the uncertainty is due to the α 8 m external-field contributions. We discuss here our recent results on the two- and three-loop contributions, which essentially reduce the theoretical uncertainty. Combined with recent calculations of Laporta on the slope of the Dirac form factor in the three-loop level, our results allow for completion of calculations of α 8 m contributions to the Lamb shift of the ground state in the hydrogen atom.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1982

An empirical determination of the effects of sea state bias on Seasat altimetry

A linear empirical model has been developed for the correction of sea state bias effects, in Seasat altimetry data altitude measurements, that are due to (1) electromagnetic bias caused by the fact that ocean wave troughs reflect the altimeter signal more strongly than the crests, shifting the apparent mean sea level toward the wave troughs, and (2) an independent instrument-related bias resulting from the inability of height corrections applied in the ground processor to compensate for simplifying assumptions made for the processor aboard Seasat. After applying appropriate corrections to the altimetry data, an empirical model for the sea state bias is obtained by differencing significant wave height and height measurements from coincident ground tracks. Height differences are minimized by solving for the coefficient of a linear relationship between height differences and wave height differences that minimize the height differences. In more than 50% of the 36 cases examined, 7% of the value of significant wave height should be subtracted for sea state bias correction.

Born, G. H.↗
DOE OSTI2022

Doubling protected land area may be inefficient at preserving the extent of undeveloped land and could cause substantial regional shifts in land use

Abstract Projection of land use and land‐cover change is highly uncertain yet drives critical estimates of carbon emissions, climate change, and food and bioenergy production. We use new, spatially explicit land availability data in conjunction with a model sensitivity analysis to estimate the effects of additional land protection on land use and land cover. The land availability data include protected land and agricultural suitability and is incorporated into the Moirai land data system for initializing the Global Change Analysis Model. Overall, decreasing land availability is relatively inefficient at preserving undeveloped land while having considerable regional land‐use impacts. Current amounts of protected area have little effect on land and crop production estimates, but including the spatial distribution of unsuitable (i.e., unavailable) land dramatically shifts bioenergy production from high northern latitudes to the rest of the world, compared with uniform availability. This highlights the importance of spatial heterogeneity in understanding and managing land change. Approximately doubling the current protected area to emulate a 30% protected area target may avoid land conversion by 2050 of less than half the newly protected extent while reducing bioenergy feedstock land by 10.4% and cropland and grazed pasture by over 3%. Regional bioenergy land may be reduced (increased) by up to 46% (36%), cropland reduced by up to 61%, pasture reduced by up to 100%, and harvested forest reduced by up to 35%. Only a few regions show notable gains in some undeveloped land types of up to 36%. Half of the regions can reach the target using only unsuitable land, which would minimize impacts on agriculture but may not meet conservation goals. Rather than focusing on an area target, a more robust approach may be to carefully select newly protected land to meet well‐defined conservation goals while minimizing impacts to agriculture.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Poster Abstract: Leveraging Large Language Models to Reveal Interpretable Cooling Behaviors from Smart Thermostat Data

Frequent heatwaves and hot summers increasingly challenge occupant comfort, health, and energy grid stability. Addressing these challenges requires a detailed understanding of household cooling behaviors, such as thermostat adjustments and adaptive responses to extreme conditions. Traditional analyses often rely on aggregated numerical metrics that overlook subtle but important household-specific variations. In this study, we introduce a generalizable methodology that integrates large language models (LLMs) with vision capabilities to enable scalable and detailed analysis of residential thermostat data. Using Ecobee's Donate Your Data (DYD) dataset—which provides five-minute records of indoor temperatures, thermostat setpoints, and HVAC runtimes—we focus on two U.S. cities with contrasting summer climates : Austin (TX) and Phoenix (AZ). Because raw time-series data are not well suited for direct LLM analysis, we transform them into visual representations, such as daily indoor temperature trajectories and weekly runtime histograms, to better capture behavioral variations. Leveraging LLMs' visual interpretation, we extract descriptive behavioral features, including temperature preferences, time-of-day cooling orientation, anticipatory versus reactive heatwave responses, and behavioral consistency. These semantic features support unsupervised clustering to identify distinct occupant archetypes at scale, revealing differences—such as morning-centric anticipatory coolers versus households that shift toward warmer setpoints during heatwaves—that can inform demand response, resilience planning, and health-aware interventions. By converting raw numerical data into interpretable behavioral patterns, this methodology enables scalable and practical analysis of occupant behavior, supporting actionable insights for comfort, resilience, and energy management.

Nihar, Kopal↗
DOE OSTI2025

Regime Characterization of Offshore Wind Resource Using Unsupervised Learning

Predictability of wind resource conditions is critical for offshore wind design and operations. While many studies of extreme wind conditions focus on specific events such as low-level jets or ramps, these rely on threshold definitions that limit generality. Here we present a data-driven framework that combines principal component analysis (PCA), self-organizing maps (SOM), and k-means clustering to classify wind resource conditions as typical and anomalous from climatological data. Anomalies are defined not by fixed thresholds but by flagging samples located far from SOM node centers inside the baseline SOM structure. This reframes extremes as rare ebents and hence, likely difficult to anticipate by numerical weather prediction models. We applied this approach to 23 years (2000–2022) of hourly profiles from the NOW-23 hindcast model at the Humboldt Wind Energy Area. Classification is conducted on a feature space consisting of 10 m wind speed and direction, bulk shear and veer across 30–270 m, and a low-level jet index. Dimensionality reduction is achieved through PC. A 2 × 3 OM lattice trained on the PCA vectors identified six baseline regimes spanning weak to strong flow states. High quantization-error profiles are identified and re-clustered into four anomalous regimes. The baseline regimes exhibited clear seasonal and diurnal cycles. Meanwhile, the anomalous regimes represented <10 % of all hours but showed distinct combinations of speed, shear, and veer, when compared to the baseline regimes. Anomalous regimes are typically short-lived (~few hours), yet their transitions can lead to hub-height wind changes of −18 to +9 m s -1 . For a representative 15 MW turbine, these shifts imply rapid swings in capacity factor from near-full output to negligible generation. Validation with lidar buoy data showed 51% agreement in SOM labels across ~6,000 overlapping hours, with most mismatches confined to adjacent speed classes. HRRR comparisons further revealed that anomalous regimes were disproportionately associated with forecast biases exceeding 5 m s -1 . Together, these results reframe extremes in offshore wind from absolute maxima or minima to weather states that are difficult to anticipate from models.

17 WIND ENERGY↗
NASA NTRS1994

Martian aerosols: Near-infrared spectral properties and effects on the observation of the surface

Imaging sprectroscopic measurements (ISM) of Mars acquired by the ISM instrument on Phobos-2 are used to investigate the NIR spectral properties of aerosols and the effects of atmospheric scattering on inferred mineralogy of the surface. Estimates of aerosols spectra between 0.77 and 2.6 micrometers are derived above Tharsis and Ophir Planum. The spectral continua are consistent with the particle size distribution derived using data from the solar occultation experiment on-board the spacecraft (effective radius approximately = 1.2 micrometers, with an effective variance approximately = 0.2). The aerosols spectra contain water-ice absorption features and possibly absorptions due to clay and/or sulfates. The largest effect of the aerosols on surface spectra is in dark regions, where the continuum spectral slope becomes more negative and the 1-micrometers absorption due to Fe in pyroxene is shifted toward longer wavelengths. The effects of aerosols on spectra of bright regions are insufficiently large to change mineralogic interpretations based on ISM data, i.e., that bright regions in Tharsis are dominated spectrally by hematite, but that additional ferric minerals are probably present in other areas including Arabia.

Erard, Stephane↗
DOE OSTI2024

Temperature and CO 2 interactively drive shifts in the compositional and functional structure of peatland protist communities

Microbes affect the global carbon cycle that influences climate change and are in turn influenced by environmental change. Here, we use data from a long-term whole-ecosystem warming experiment at a boreal peatland to answer how temperature and CO 2 jointly influence communities of abundant, diverse, yet poorly understood, non-fungi microbial Eukaryotes (protists). These microbes influence ecosystem function directly through photosynthesis and respiration, and indirectly, through predation on decomposers (bacteria and fungi). Using a combination of high-throughput fluid imaging and 18S amplicon sequencing, we report large climate-induced, community-wide shifts in the community functional composition of these microbes (size, shape, and metabolism) that could alter overall function in peatlands. Importantly, we demonstrate a taxonomic convergence but a functional divergence in response to warming and elevated CO 2 with most environmental responses being contingent on organismal size: warming effects on functional composition are reversed by elevated CO 2 and amplified in larger microbes but not smaller ones. Furthermore, these findings show how the interactive effects of warming and rising CO 2 levels could alter the structure and function of peatland microbial food webs—a fragile ecosystem that stores upwards of 25% of all terrestrial carbon and is increasingly threatened by human exploitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Pre-training Vision Models for the Classification of Alerts from Wide-field Time-domain Surveys

Modern wide-field time-domain surveys facilitate the study of transient, variable and moving phenomena by conducting image differencing and relaying alerts to their communities. Machine learning tools have been used on data from these surveys and their precursors for more than a decade, and convolutional neural networks (CNNs), which make predictions directly from input images, saw particularly broad adoption through the 2010s. Since then, continually rapid advances in computer vision have transformed the standard practices around using such models. It is now commonplace to use standardized architectures pre-trained on large corpora of everyday images (e.g., ImageNet). In contrast, time-domain astronomy studies still typically design custom CNN architectures and train them from scratch. Here, we explore the effects of adopting various pre-training regimens and standardized model architectures on the performance of alert classification. We find that the resulting models match or outperform a custom, specialized CNN like what is typically used for filtering alerts. Moreover, our results show that pre-training on galaxy images from Galaxy Zoo tends to yield better performance than pre-training on ImageNet or training from scratch. We observe that the design of standardized architectures are much better optimized than the custom CNN baseline, requiring significantly less time and memory for inference despite having more trainable parameters. On the eve of the Legacy Survey of Space and Time and other image-differencing surveys, these findings advocate for a paradigm shift in the creation of vision models for alerts, demonstrating that greater performance and efficiency, in time and in data, can be achieved by adopting the latest practices from the computer vision field.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1995

Interdecadal Variations in the Alaska Gyre

Climatic dynamic topography variations in the Alaska gyre during the period 1968-1990 are described with an objective analysis of more than 12000 STD and XBT stations, and COADS wind stress data Interannual the dynamic height and SST variations were correlated and were consistent with recently described large-scale climatic shifts in the North Pacific. The gyre was centered more to the east, circulation appeared stronger, and SST was lower during the early to mid-1970s than during the 1980s. The Aleutian low (NP and PNA indices) intensified during the interim, but the response did not appear as a gyre spinup. Instead, the associated wind stress anomalies forced a slowly varying dynamic height anomaly across the eastern and northern part of the gyre through Ekman convergence, which had the effect of displacing the gyre's low somewhat to the WSW in the 1980s. The wind curl spectrum was white, and the slow oceanic response was modeled as stochastic-forced climate variability with a simple first-order Markov autoregression process. Forcing was assumed to be Ekman pumping of the pycnocline, and the damping coefficient was estimated from the data to be approx. 1 yr. A hindcast with observed winds gave estimated dynamic height patterns similar to those observed, with a canonical correlation of 0.79 at 99% confidence. This response was weak in the western half of the gyre, where slow baroclinic variability may have been influenced by long Rossby wave propagation. A simple autoregression simulation using artificial white noise forcing shows the evolution of decadal variations similar in nature to those observed. This result, along with the low frequency correlation between dynamic height and SST, suggests that the upper-ocean climatic variability in this region is primarily wind forced.

Lagerloef, Gary S.E.↗
NASA NTRS2014

NuSTAR Observations of the Magnetar 1E 2259+586

We report on new broad band spectral and temporal observations of the magnetar 1E 2259+586, which is located in the supernova remnant CTB 109. Our data were obtained simultaneously with the Nuclear Spectroscopic Telescope Array (NuSTAR) and Swift, and cover the energy range from 0.5-79 keV. We present pulse profiles in various energy bands and compare them to previous RXTE results. The NuSTAR data show pulsations above 20 keV for the first time and we report evidence that one of the pulses in the double-peaked pulse profile shifts position with energy. The pulsed fraction of the magnetar is shown to increase strongly with energy. Our spectral analysis reveals that the soft X-ray spectrum is well characterized by an absorbed double blackbody or blackbody plus power-law model in agreement with previous reports. Our new hard X-ray data, however, suggest that an additional component, such as a power law, is needed to describe the NuSTAR and Swift spectrum. We also fit the data with the recently developed coronal outflow model by Beloborodov for hard X-ray emission from magnetars. The outflow from a ring on the magnetar surface is statistically preferred over outflow from a polar cap.

X-rays: individual↗
DOE OSTI2020

Secondary-Source Core Reload Modeling with VERA

The CASL reactor simulation package VERA has been adapted to provide high-fidelity simulation capabilities for modeling source range detector response during subcritical reactor configurations. New features include the activation and shuffling of secondary-source assemblies, use of burned fuel neutron emission data from the ORIGEN depletion solver to the MPACT deterministic neutron transport solver, allowance of user-defined sources in MPACT based on material composition, ability to solve the subcritical source-driven system with neutron multiplication using the MPACT diffusion solver, and transfer of the calculated fission source from MPACT to the continuous-energy Monte Carlo solver Shift for final detector response evaluation using the CADIS methodology for variance reduction. These new capabilities were benchmarked against Watts Bar Unit 1 plant operating data for the first few fuel loading steps and were found to demonstrate excellent agreement with the measured data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2023

Interchangeable Use of GNSS and Seismic Data for Rapid Earthquake Characterization: 2021 Chignik Earthquake, Alaska

Earthquake magnitude estimation using peak ground velocities (PGV) derived from 13 Global Navigation Satellite Systems (GNSS) data has shown promise for rapid 14 characterization of damaging earthquakes. Here we examine the feasibility of using 15 GNSS-derived velocity waveforms as interchangeable data for ground motion estimation 16 and other products that typically rely on strong-motion seismic records. Our study 17 compares PGVs derived from high-rate GNSS to those computed from high-rate seismic 18 records (strong-motion and velocity), at co- and closely-located stations. The recent 2021 Manuscript Click here to access/download;Manuscript;Manuscript_Final.docx 2 19 Mw 8.2 Chignik earthquake in Alaska that was recorded on co-located GNSS and strong20 motion sensors provides the perfect opportunity to compare the two data streams and 21 their application in rapid response. The Chignik velocity records appear almost identical 22 at co-located GNSS and strong-motion stations when observed at frequencies < 0.25 Hz. 23 GNSS and strong-motion derived velocity data are further employed to generate rapid 24 estimates of PGV-derived moment magnitudes for the earthquake. The moment 25 magnitude estimates from GNSS and joint GNSS/seismic data are within ~ ±0.4 26 magnitude units (Fang et al., 2020) of the final magnitude (Mw 8.2). ShakeMaps 27 generated for the 2021 Chignik earthquake using GNSS and seismic PGVs show notable 28 agreement between them, and show negligible shifts in PGV contours when co-/closely 29 located GNSS and seismic stations are substituted for one another. Therefore, we posit 30 that GNSS is a powerful alternative or addition to seismic data and vice versa.

Earthquake rapid response↗
NASA NTRS2011

A Data Mining Project to Identify Cardiovascular Related Factors That May Contribute to Changes in Visual Acuity Within the US Astronaut Corps

Many of the cardiovascular-related adaptations that occur in the microgravity environment are due, in part, to a well-characterized cephalad-fluid shift that is evidenced by facial edema and decreased lower limb circumference. It is believed that most of these alterations occur as a compensatory response necessary to maintain a "normal" blood pressure and cardiac output while in space. However, data from both flight and analog research suggest that in some instances these microgravity-induced alterations may contribute to cardiovascular-related pathologies. Most concerning is the potential relation between the vision disturbances experienced by some long duration crewmembers and changes in cerebral blood flow and intra-ocular pressure. The purpose of this project was to identify cardiovascular measures that may potentially distinguish individuals at risk for visual disturbances after long duration space flight. Toward this goal, we constructed a dataset from Medical Operation tilt/stand test evaluations pre- (days L-15-L-5) and immediate post-flight (day R+0) on 20 (3 females, 17 males). We restricted our evaluation to only crewmembers who participated in both shuttle and space station missions. Data analysis was performed using both descriptive and analytical methods (Stata 11.2, College Station, TX) and are presented as means +/- 95% CI. Crewmembers averaged 5207 (3447 - 8934) flight hours across both long (MIR-23 through Expedition16) and short (STS-27 through STS-101) duration missions between 1988 and 2008. The mean age of the crew at the time of their most recent shuttle flight was 41 (34-44) compared to 47 (40-54) years during their time on station. In order to focus our analysis (we did not have codes to separate out subjects by symptomotology) , we performed a visual inspection of each cardiovascular measures captured during testing and plotted them against stand time, pre- to post-flight, and between mission duration. It was found that pulse pressure most clearly differentiated the two mission types. Statistical analysis confirmed that pulse pressure was significantly higher before [45.6; (42.1 to 49.1)] and after [50.7; (46.9 to 54.6)] time on station compared with their most recent shuttle flight [31.6 (27.8 to 35.4), and 32.2 (28.3 to 36.0) respectively] even after correcting differences in age and cumulative number of mission hours. Without knowing the identity of which long duration crewmembers demonstrated visual changes, we were limited to examining whether certain crew regulate components of pulse pressure, systolic and diastolic blood pressure, differently due to microgravity exposure. To that end, we stratified crew into tertiles based on either their pre-flight measure of systolic or diastolic blood pressure. Those crew in the highest tertile for both systolic (lower tertile (n=8; 103-111), middle tertile (n=7; 113-121), and upper tertile (n=5; 125-136) and diastolic blood pressure (lower tertile (n=8; 58-64), middle tertile (n=7; 67-73), and upper tertile (n=5; 75-81) demonstrated less variability in pulse pressure between R+0 and L-10 (Figure 2). Interestingly, those crewmembers with the highest resting systolic blood pressure demonstrated either no change or in some instances an increase in total peripheral resistance, where those in the lower tertiles had lower values of total peripheral resistance compared to pre-flight levels. In this study, it was found that crewmembers in the highest tertile for both systolic and diastolic blood pressure demonstrated less variability in pulse pressure and that the decrease in variability was due in part to lower levels of compliance as indicated by similar or higher levels of total peripheral resistance after compared with before flight levels. Whether there is a relation between blood pressure regulation and total peripheral resistance in crew presenting with negative changes in visual acuity remains unknown.

Westby, Christian M.↗