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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

NASA's Functional Task Test: High Intensity Exercise Improves the Heart Rate Response to a Stand Test Following 70 Days of Bedrest

Cardiovascular adaptations due to spaceflight are modeled with 6deg head-down tilt bed rest (BR) and result in decreased orthostatic tolerance. We investigated if high-intensity resistive and aerobic exercise with and without testosterone supplementation would improve the heart rate (HR) response to a 3.5-min stand test and how quickly these changes recovered following BR. During 70 days of BR male subjects performed no exercise (Control, n=10), high intensity supine resistive and aerobic exercise (Exercise, n=9), or supine exercise plus supplemental testosterone (Exercise+T, n=8; 100 mg i.m., weekly in 2-week on/off cycles). We measured HR for 2 min while subjects were prone and for 3 min after standing twice before and 0, 1, 6, and 11 days after BR. Mixed-effects linear regression models were used to evaluate group, time, and interaction effects. Compared to pre-bed rest, prone HR was elevated on BR+0 and BR+1 in Control, but not Exercise or Exercise+T groups, and standing HR was greater in all 3 groups. The increase in prone and standing HR in Control subjects was greater than either Exercise or Exercise+T groups and all groups recovered by BR+6. The change in HR from prone to standing more than doubled on BR+0 in all groups, but was significantly less in the Exericse+T group compared to the Control, but not Exercise group. Exercise reduces, but does not prevent the increase in HR observed in response to standing. The significantly lower HR response in the Exercise+T group requires further investigation to determine physiologic significance.

Laurie, Steven S.↗
DOE OSTI2016

Identifying Predictive Factors for Incident Reports in Patients Receiving Radiation Therapy

Purpose: To describe radiation therapy cases during which voluntary incident reporting occurred; and identify patient- or treatment-specific factors that place patients at higher risk for incidents. Methods and Materials: We used our institution's incident learning system to build a database of patients with incident reports filed between January 2011 and December 2013. Patient- and treatment-specific data were reviewed for all patients with reported incidents, which were classified by step in the process and root cause. A control group of patients without events was generated for comparison. Summary statistics, likelihood ratios, and mixed-effect logistic regression models were used for group comparisons. Results: The incident and control groups comprised 794 and 499 patients, respectively. Common root causes included documentation errors (26.5%), communication (22.5%), technical treatment planning (37.5%), and technical treatment delivery (13.5%). Incidents were more frequently reported in minors (age <18 years) than in adult patients (37.7% vs 0.4%, P<.001). Patients with head and neck (16% vs 8%, P<.001) and breast (20% vs 15%, P=.03) primaries more frequently had incidents, whereas brain (18% vs 24%, P=.008) primaries were less frequent. Larger tumors (17% vs 10% had T4 lesions, P=.02), and cases on protocol (9% vs 5%, P=.005) or with intensity modulated radiation therapy/image guided intensity modulated radiation therapy (52% vs 43%, P=.001) were more likely to have incidents. Conclusions: We found several treatment- and patient-specific variables associated with incidents. These factors should be considered by treatment teams at the time of peer review to identify patients at higher risk. Larger datasets are required to recommend changes in care process standards, to minimize safety risks.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Global estimates of the fitness advantage of SARS-CoV-2 variant Omicron

Abstract New variants of SARS-CoV-2 show remarkable heterogeneity in their relative fitness over both time and space. In this paper we extend the tools available for estimating the selection strength for new SARS-CoV-2 variants to a hierarchical, mixed-effects, renewal equation model. This formulation allows us to estimate selection effects at the global level while incorporating both measured and unmeasured heterogeneity among countries. Applying this model to the spread of Omicron in forty countries, we find evidence for very strong but very heterogeneous selection effects. To test whether this heterogeneity is explained by differences in the immune landscape, we considered several measures of vaccination rates and recent population-level infection as covariates, finding moderately strong, statistically significant effects. We also found a significant positive correlation between the selection advantage of Delta and Omicron at the country level, suggesting that other region-specific explanatory variables of fitness differences do exist. Our method is implemented in the Stan programming language, can be run on standard consumer-grade computing resources, and will be straightforward to apply to future variants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Validation Metrics for Fixed Effects and Mixed-Effects Calibration

The modern scientific process often involves the development of a predictive computational model. To improve its accuracy, a computational model can be calibrated to a set of experimental data. A variety of validation metrics can be used to quantify this process. Some of these metrics have direct physical interpretations and a history of use, while others, especially those for probabilistic data, are more difficult to interpret. In this work, a variety of validation metrics are used to quantify the accuracy of different calibration methods. Frequentist and Bayesian perspectives are used with both fixed effects and mixed-effects statistical models. Through a quantitative comparison of the resulting distributions, the most accurate calibration method can be selected. Two examples are included which compare the results of various validation metrics for different calibration methods. It is quantitatively shown that, in the presence of significant laboratory biases, a fixed effects calibration is significantly less accurate than a mixed-effects calibration. This is because the mixed-effects statistical model better characterizes the underlying parameter distributions than the fixed effects model. The results suggest that validation metrics can be used to select the most accurate calibration model for a particular empirical model with corresponding experimental data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

The use of copulas to practical estimation of multivariate stochastic differential equation mixed effects models

A system of stochastic differential equations (SDE) with mixed-effects parameters and multivariate normal copula density function were used to develop tree height model for Scots pine trees in Lithuania. A two-step maximum likelihood parameter estimation method is used and computational guidelines are given. After fitting the conditional probability density functions to outside bark diameter at breast height, and total tree height, a bivariate normal copula distribution model was constructed. Predictions from the mixed-effects parameters SDE tree height model calculated during this research were compared to the regression tree height equations. The results are implemented in the symbolic computational language MAPLE.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A hierarchical Bayesian model for background variation in radiation source localization

In this paper, we apply a new model to account for varying background radiation in radiological source localization. We present a hierarchical Bayesian model that simultaneously infers background and source location parameters without requiring separate estimation of the background radiation at each detector location. We employ a simplified photon transport model to reduce the computational expense of Bayesian model calibration. Furthermore, we demonstrate the model accuracy by localizing a cesium-137 source in a simulated city block, and we analyze experimental field measurements with varying background. In both cases, the model provides sufficient fidelity that we can locate the source while simultaneously estimating background radiation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

The relationship of leaf photosynthetic traits – V cmax and J max – to leaf nitrogen, leaf phosphorus, and specific leaf area: a meta‐analysis and modeling study

Abstract Great uncertainty exists in the global exchange of carbon between the atmosphere and the terrestrial biosphere. An important source of this uncertainty lies in the dependency of photosynthesis on the maximum rate of carboxylation ( V cmax ) and the maximum rate of electron transport ( J max ). Understanding and making accurate prediction of C fluxes thus requires accurate characterization of these rates and their relationship with plant nutrient status over large geographic scales. Plant nutrient status is indicated by the traits: leaf nitrogen (N), leaf phosphorus (P), and specific leaf area ( SLA ). Correlations between V cmax and J max and leaf nitrogen (N) are typically derived from local to global scales, while correlations with leaf phosphorus (P) and specific leaf area ( SLA ) have typically been derived at a local scale. Thus, there is no global‐scale relationship between V cmax and J max and P or SLA limiting the ability of global‐scale carbon flux models do not account for P or SLA . We gathered published data from 24 studies to reveal global relationships of V cmax and J max with leaf N, P, and SLA . V cmax was strongly related to leaf N, and increasing leaf P substantially increased the sensitivity of V cmax to leaf N. J max was strongly related to V cmax , and neither leaf N, P, or SLA had a substantial impact on the relationship. Although more data are needed to expand the applicability of the relationship, we show leaf P is a globally important determinant of photosynthetic rates. In a model of photosynthesis, we showed that at high leaf N (3 gm −2 ), increasing leaf P from 0.05 to 0.22 gm −2 nearly doubled assimilation rates. Finally, we show that plants may employ a conservative strategy of J max to V cmax coordination that restricts photoinhibition when carboxylation is limiting at the expense of maximizing photosynthetic rates when light is limiting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Strong correlation between stress drop and peak ground acceleration for recent M1–4 earthquakes in the San Francisco Bay Area

Theoretical and observational studies suggest that between-event variability in the median ground motions of larger ( M≥5 ) earthquakes is controlled primarily by the dynamic properties of the earthquake source, such as Brune-type stress drop. Analogous results remain equivocal for smaller events due to the lack of comprehensive and overlapping ground-motion and source-parameter datasets in this regime. Here in this paper, we investigate the relationship between peak ground acceleration (PGA) and dynamic stress drop for a new dataset of 5297 earthquakes that occurred in the San Francisco Bay area from 2002 through 2016. For each event, we measure PGA on horizontal-component channels of stations within 100 km and estimate stress drop from P-wave spectra recorded on vertical-component channels of the same stations. We then develop a nonparametric ground-motion prediction equation (GMPE) applicable for the moderate (M 1–4) earthquakes in our study region, using a mixed-effects generalization of the Random Forest algorithm. We use the Random Forest GMPE to model the joint influence of magnitude, distance, and near-site effects on observed PGA. We observe a strong correlation between dynamic stress drop and the residual PGA of each event, with the events with higher-than-expected PGA associated with higher values of stress drop. The strength of this correlation increases as a function of magnitude but remains significant even for smaller magnitude events with corner frequencies that approach the observable bandwidth of the acceleration records. Mainshock events are characterized by systematically higher stress drop and PGA than aftershocks of equivalent magnitude. Coherent local variations in the distribution of dynamic stress drop provide observational constraints to support the future development of nonergodic GMPEs that account for variations in median stress drop at different source locations.

58 GEOSCIENCES↗
NASA NTRS2019

Satellite Mapping of PM2.5 Episodes in the Wintertime San Joaquin Valley: A "Static" Model Using Column Water Vapor

The use of satellite Aerosol Optical Thickness (AOT) from imaging spectrometers has been successful in quantifying and mapping high PM2.5 (particulate matter mass <2.5µm diameter) episodes for pollution abatement and health studies. However, some regions have high PM2.5 but poor estimation success. The challenges in using Aerosol Optical Thickness (AOT) from imaging spectrometers to characterize PM2.5 worldwide was especially evident in the wintertime San Joaquin Valley (SJV). The SJV's attendant difficulties of high-albedo surfaces and very shallow, variable vertical mixing also occur in other significantly polluted regions around the world. We report on more accurate PM2.5 maps for the whole-winter period in the SJV, Nov 14, 2012?Dec 11, 2013. Intensive measurements by including NASA aircraft were made for several weeks in that winter, the DISCOVER-AQ California mission.We found success with a relatively simple method based on calibration and checking with surface monitors and a characterization of vertical mixing, and incorporating specific understandings of the region's climatology. We estimate PM2.5 to within ~7µgm?3 RMSE and with R values of ~0.9, based on remotely sensed MAIAC (Multi-Angle Implementation of Atmospheric Correction) observations, and that certain further work will improve that accuracy. Mapping is at 1km resolution. This allows a time sequence of mapped aerosols at 1km for cloud-free days. We describe our technique as a "static estimation". Estimation procedures like this one, not dependent on well-mapped source strengths or on transport error, should help full source-driven simulations by deconstructing processes. They also provide a rapid method to create a long-term climatology.Essential features of the technique are (a) daily calibration of the AOT to PM2.5 using available surface monitors, and (b) characterization of mixed-layer dilution using column water vapor (CWV, otherwise "precipitable water"). We noted that on multi-day timescales both water vapor and particles share near-surface sources and both fall to very low values with altitude; indeed, both are largely removed by precipitation. The existence of layers of H2O or aerosol not within the mixed layer adds complexity, but mixed-effects statistical regression captures essential proportionality of PM2.5 and the ratio variable (AOT/CWV). Accuracy is much higher than previous statistical models, and can be extended to the whole Aqua-satellite data record. The maps and time-series we show suggest a repeated pattern for large valleys like the SJV ? progressive stabilization of the mixing height after frontal passages: PM2.5 is somewhat more determined by day-by-day changes in mixing than it is by the progressive accumulation of pollutants (revealed as increasing AOT).

Chatfield, Robert B.↗
NASA NTRS2015

Techniques for Estimating Emissions Factors from Forest Burning: ARCTAS and SEAC4RS Airborne Measurements Indicate Which Fires Produce Ozone

Previous studies of emission factors from biomass burning are prone to large errors since they ignore the interplay of mixing and varying pre-fire background CO2 levels. Such complications severely affected our studies of 446 forest fire plume samples measured in the Western US by the science teams of NASA's SEAC4RS and ARCTAS airborne missions. Consequently we propose a Mixed Effects Regression Emission Technique (MERET) to check techniques like the Normalized Emission Ratio Method (NERM), where use of sequential observations cannot disentangle emissions and mixing. We also evaluate a simpler "consensus" technique. All techniques relate emissions to fuel burned using C(sub burn) = delta C(sub tot) added to the fire plume, where C(sub tot) approximately equals (CO2 + CO). Mixed-effects regression can estimate pre-fire background values of Ctot (indexed by observation j) simultaneously with emissions factors indexed by individual species i, delta epsilon lambda tau alpha−x(sub i)/(C(sub burn))i,j., MERET and "consensus" require more than two emissions indicators. Our studies excluded samples where exogenous CO or CH4 might have been fed into a fire plume, mimicking emission. We sought to let the data on 13 gases and particulate properties suggest clusters of variables and plume types, using non-negative matrix factorization (NMF). While samples were mixtures, the NMF unmixing suggested purer burn types. Particulate properties (bscat, babs, SSA, AAE) and gas-phase emissions were interrelated. Finally, we sought a simple categorization useful for modeling ozone production in plumes. Two kinds of fires produced high ozone: those with large fuel nitrogen as evidenced by remnant CH3CN in the plumes, and also those from very intense large burns. Fire types with optimal ratios of delta-NOy/delta- HCHO associate with the highest additional ozone per unit Cburn, Perhaps these plumes exhibit limited NOx binding to reactive organics. Perhaps these plumes exhibit limited NOx binding to reactive organics.

fires↗
NASA NTRS2016

Techniques for Estimating Emissions Factors from Forest Burning: ARCTAS and SEAC4RS Airborne Measurements Indicate which Fires Produce Ozone

Previous studies of emission factors from biomass burning are prone to large errors since they ignore the interplay of mixing and varying pre-fire background CO2 levels. Such complications severely affected our studies of 446 forest fire plume samples measured in the Western US by the science teams of NASA's SEAC4RS and ARCTAS airborne missions. Consequently we propose a Mixed Effects Regression Emission Technique (MERET) to check techniques like the Normalized Emission Ratio Method (NERM), where use of sequential observations cannot disentangle emissions and mixing. We also evaluate a simpler "consensus" technique. All techniques relate emissions to fuel burned using C(burn) = delta C(tot) added to the fire plume, where C(tot) approximately equals (CO2 = CO). Mixed-effects regression can estimate pre-fire background values of C(tot) (indexed by observation j) simultaneously with emissions factors indexed by individual species i, delta, epsilon lambda tau alpha-x(sub I)/C(sub burn))I,j. MERET and "consensus" require more than emissions indicators. Our studies excluded samples where exogenous CO or CH4 might have been fed into a fire plume, mimicking emission. We sought to let the data on 13 gases and particulate properties suggest clusters of variables and plume types, using non-negative matrix factorization (NMF). While samples were mixtures, the NMF unmixing suggested purer burn types. Particulate properties (b scant, b abs, SSA, AAE) and gas-phase emissions were interrelated. Finally, we sought a simple categorization useful for modeling ozone production in plumes. Two kinds of fires produced high ozone: those with large fuel nitrogen as evidenced by remnant CH3CN in the plumes, and also those from very intense large burns. Fire types with optimal ratios of delta-NOy/delta- HCHO associate with the highest additional ozone per unit Cburn, Perhaps these plumes exhibit limited NOx binding to reactive organics. Perhaps these plumes exhibit limited NOx binding to reactive organics

ozone↗
NASA NTRS2014

Revised (Mixed-Effects) Estimation for Forest Burning Emissions of Gases and Smoke, Fire/Emission Factor Typology, and Potential Remote Sensing Classification of Types for Ozone and Black-Carbon Simulation

We summarize recent progress (a) in correcting biomass burning emissions factors deduced from airborne sampling of forest fire plumes, (b) in understanding the variability in reactivity of the fresh plumes sampled in ARCTAS (2008), DC3 (2012), and SEAC4RS (2013) airborne missions, and (c) in a consequent search for remotely sensed quantities that help classify forest-fire plumes. Particle properties, chemical speciation, and smoke radiative properties are related and mutually informative, as pictures below suggest (slopes of lines of same color are similar). (a) Mixed-effects (random-effects) statistical modeling provides estimates of both emission factors and a reasonable description of carbon-burned simultaneously. Different fire plumes will have very different contributions to volatile organic carbon reactivity; this may help explain differences of free NOx(both gas- and particle-phase), and also of ozone production, that have been noted for forest-fire plumes in California. Our evaluations check or correct emission factors based on sequential measurements (e.g., the Normalized Ratio Enhancement and similar methods). We stress the dangers of methods relying on emission-ratios to CO. (b) This work confirms and extends many reports of great situational variability in emissions factors. VOCs vary in OH reactivity and NOx-binding. Reasons for variability are not only fuel composition, fuel condition, etc., but are confused somewhat by rapid transformation and mixing of emissions. We use "unmixing" (distinct from mixed-effects) statistics and compare briefly to approaches like neural nets. We focus on one particularly intense fire the notorious Yosemite Rim Fire of 2013. In some samples, NOx activity was not so suppressed by binding into nitrates as in other fires. While our fire-typing is evolving and subject to debate, the carbon-burned delta(CO2+CO) estimates that arise from mixed effects models, free of confusion by background-CO2 variation, should provide a solid base for discussion. (c) We report progress using promising links we find between emissions-related "fire types" and promising features deducible from remote observations of plumes, e.g., single scatter albedo, Angstrom exponent of scattering, Angstrom exponent of absorption, (CO column density)/(aerosol optical depth).

Remote sensing↗
DOE OSTI2016

Prospective Validation of a High Dimensional Shape Model for Organ Motion in Intact Cervical Cancer

Purpose: Validated models are needed to justify strategies to define planning target volumes (PTVs) for intact cervical cancer used in clinical practice. Our objective was to independently validate a previously published shape model, using data collected prospectively from clinical trials. Methods and Materials: We analyzed 42 patients with intact cervical cancer treated with daily fractionated pelvic intensity modulated radiation therapy and concurrent chemotherapy in one of 2 prospective clinical trials. We collected online cone beam computed tomography (CBCT) scans before each fraction. Clinical target volume (CTV) structures from the planning computed tomography scan were cast onto each CBCT scan after rigid registration and manually redrawn to account for organ motion and deformation. We applied the 95% isodose cloud from the planning computed tomography scan to each CBCT scan and computed any CTV outside the 95% isodose cloud. The primary aim was to determine the proportion of CTVs that were encompassed within the 95% isodose volume. A 1-sample t test was used to test the hypothesis that the probability of complete coverage was different from 95%. We used mixed-effects logistic regression to assess effects of time and patient variability. Results: The 95% isodose line completely encompassed 92.3% of all CTVs (95% confidence interval, 88.3%-96.4%), not significantly different from the 95% probability anticipated a priori (P=.19). The overall proportion of missed CTVs was small: the grand mean of covered CTVs was 99.9%, and 95.2% of misses were located in the anterior body of the uterus. Time did not affect coverage probability (P=.71). Conclusions: With the clinical implementation of a previously proposed PTV definition strategy based on a shape model for intact cervical cancer, the probability of CTV coverage was high and the volume of CTV missed was low. This PTV expansion strategy is acceptable for clinical trials and practice; however, we recommend daily image guidance to avoid systematic large misses in select patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Effects of hydrokinetic turbine sound on the behavior of four species of fish within an experimental mesocosm

The development of hydrokinetic energy technologies (e.g., tidal turbines) has raised concern over the potential impacts of underwater sound produced by hydrokinetic turbines on fish species likely to encounter these turbines. To assess the potential for behavioral impacts, we exposed four species of fish to varying intensities of recorded hydrokinetic turbine sound in a semi-natural environment. Although we tested freshwater species (redhorse suckers [Moxostoma spp], freshwater drum [Aplondinotus grunniens], largemouth bass [Micropterus salmoides], and rainbow trout [Oncorhynchus mykiss]), these species are also representative of the hearing physiology and sensitivity of estuarine species that would be affected at tidal energy sites. Here, we evaluated changes in fish position relative to different intensities of turbine sound as well as trends in location over time with linear mixed-effects and generalized additive mixed models. We also evaluated changes in the proportion of near-source detections relative to sound intensity and exposure time with generalized linear mixed models and generalized additive models. Models indicated that redhorse suckers may respond to sustained turbine sound by increasing distance from the sound source. Freshwater drum models suggested a mixed response to turbine sound, and largemouth bass and rainbow trout models did not indicate any likely responses to turbine sound. Lastly, findings highlight the importance for future research to utilize accurate localization systems, different species, validated sound transmission distances, and to consider different types of behavioral responses to different turbine designs and to the cumulative sound of arrays of multiple turbines.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Data driven investigation to understand the influence of total solids on biological biogas upgrading

In situ biogas upgrading achieves CO 2 conversion to CH 4 via hydrogenotrophic methanogenesis; however, gas-liquid mass transfer constraints limit the upgrading performance. Recognizing that optimization studies often underrepresent the effects of total solids (TS) and organic loading rate (OLR), this study undertook a holistic, statistics driven assessment of operating conditions for in situ H 2 assisted biogas upgrading, centering the analysis on TS and OLR. A dataset of 31 studies was compiled and comprised 99 observations. A rigorous analytical framework was employed, combining data standardization, fixed- and random-effects (REML) weighted regressions with cluster-robust errors, stratified analyses, and machine learning. Mixed-effects meta regression indicated that TS was the main factor explaining differences of methane fraction (CH 4 %) when considering the between studies heterogeneity. Focusing on a near-stoichiometric subset (H 2 /CO 2 ≈ 4:1), TS remained significant. Stratified results showed a stronger negative relationship between TS and CH 4 % in UASB reactors than in CSTRs, with a negative effect under mesophilic conditions and no significant effect under thermophilic conditions. A Random Forest model corroborated the statistical findings, consistently ranking H 2 /CO 2 ratio, OLR, TS, and hydrogen injection rate (HIR) as the most influential predictors. These findings delineate trends across increasing TS levels, particularly between 1% and 10%, and provide preliminary insights for TS above 15% in in situ biogas upgrading. They further provide insights for the influence of TS by reactor type and temperature, thereby advancing the evidence base for implementing biological CO 2 conversion to CH 4 in practice.

In situ biogas upgrading↗
NASA NTRS2010

60 Days of Head-down Bedrest Differentially Alters Venous Function in Lower and Upper Body Between Healthy Men and Women

The incidence of orthostatic intolerance after space flight is disproportionally higher in female compared to male crewmembers (83% vs. 20%). Experimental and human data suggest that the loss of orthostatic tolerance is due, at least in part, to microgravity-induced changes in venous compliance and that these changes are specific to the lower body. It is unknown however, whether the changes in venous compliance are different between males and females after space flight, and whether this is related to the disparity in orthostatic intolerance between the sexes. Using 6deg head-down bed rest (BR) as a model of space flight, we tested the following hypotheses; 1) females, compared to males, would experience a greater increase in venous compliance in dorsal foot veins as an effect of BR and 2) no differences in venous compliance would be found in dorsal hand veins between sexes and across BR days. Using 2-D ultrasound, dorsal hand (DHV) and foot vein (DFV) responses (diameter; expressed as sq mm) to 40 mmHg of congestion pressure (compliance) and to intravenous infusion of phenylephrine (PE; 3160ng/min) were determined in 10 females and 16 males before and after 60 days of BR. The relation between changes in vein diameter (in response to pressure and PE), sex, limb, and BR days were determined using a mixed-effect linear regression. It was found that after 60 days of BR, DFV dilator response to pressure was significantly greater in females and significantly less in males compared to pre-BR. As expected, there were no differences in DHV dilator response between sexes nor was there a significant difference between pre and post measures within groups. Notably, the venoconstrictor response to infusions of PE in the DHV and DFV where similar between sexes and across BR days. In conclusion, this study demonstrates that after 60 days of BR, dorsal foot veins are more compliant in women and less compliant in men. Moreover, the changes in lower body vein compliance in females do not appear to be due to changes in vasoconstrictor tone as their response to PE was preserved and similar to that in males. Taken together these data suggest that the higher incidence of orthostatic intolerance in females after space flight is due to increased venous compliance in the lower body which could translate to lower venous filling pressures and a reduced stroke volume.

Westby, Christian M.↗