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

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Freezing Behavior of Stratospheric Sulfate Aerosols Inferred from Trajectory Studies

Temperature histories based on 10-day back growth trajectories for six ER-2 flights during AASE I (1989) and AAOE (1987) are presented. These trajectories along with the properties of the observed PSC (polar stratospheric cloud) particles are used here to infer the physical state of the pre-existing sulfuric acid aerosols. Of all the ER-2 flights described here, only the PSCs observed on the flights of January 24 and 25, 1989 are consistent with the thermodynamics of liquid ternary solutions of H2SO4/HNO3/H2O Ib PSCs). For these two days, back trajectories indicate that the air mass was exposed to SAT (sulfuric acid tetrahydrate) melting temperatures about 24 hours prior to being sampled by the ER-2. For the remaining ER-2 flights (January, 16, 19, and 20 for the AASE I campaign and August 17 for the AAOE campaign), the observed PSCs were probably composed of amorphous solid solutions of HNO3 and H2O (Type Ic PSCs). Formation of such Type Ic PSCs requires the presence of solid H2SO4 aerosols since liquid aerosols yield ternary solutions. The 10-day back trajectories of these flights indicate that the air mass was not exposed to SAT melting temperatures during the past week and had experienced cooling/warming cycles prior to being sampled by the ER-2. These temperature histories, recent laboratory measurements and the properties of glassy solids suggest that stratospheric H2SO4 aerosols may undergo a phase transition to SAT upon warming at approximately 198 K after going through a cooling cycle to about 194 K or lower.

Tabazadeh, A.↗
NASA NTRS1995

Freezing Behavior of Stratospheric Sulfate Aerosols Inferred from Trajectory Studies

Based on the trajectory analysis presented in this paper, a new mechanism is described for the freezing of the stratospheric sulfate aerosols. Temperature histories based on 10-day back trajectories for six ER-2 flights during AASE-I (1989) and AAOE (1987) are presented. The mechanism requires, as an initial step, the cooling of a H2SO4/H2O aerosol to low temperatures. If a cooling cycle is then followed up by a warming to approximately 196-198 K, the aerosols may freeze due to the growth of the crystallizing embryos formed at the colder temperature. The HNO3 absorbed at colder temperatures may increase the nucleation rate of the crystalling embryos and therefore influence the crystallization of the supercooled aerosols upon warming. Of all the ER-2 flights described, only the polar stratospheric clouds (PSC), observed on the flights of January 24, and 25, 1989 are consistent with the thermodynamics of liquid ternary solutions of H2SO4/HNO3/H2O (type Ib PSCs). For those two days, back trajectories indicate that the air mass was exposed to sulfuric acid tetrahydrate (SAT) melting temperatures about 24 hours prior to being sampled by the ER-2. Temperature histories, recent laboratory measurements, and the properties of glassy solids suggest that stratospheric H2SO4 aerosols may undergo a phase transition to SAT upon warming at approximately 198 K after going through a cooling cycle to about 194 K or lower.

Tabazadeh, A.↗
DOE OSTI2023

Wassersplines for Neural Vector Field-Controlled Animation

Much of computer-generated animation is created by manipulating meshes with rigs. While this approach works well for animating articulated objects like animals, it has limited flexibility for animating less structured free-form objects. Here we introduce Wassersplines, a novel trajectory inference method for animating unstructured densities based on recent advances in continuous normalizing flows and optimal transport. The key idea is to train a neurally-parameterized velocity field that represents the motion between keyframes. Trajectories are then computed by advecting keyframes through the velocity field. We solve an additional Wasserstein barycenter interpolation problem to guarantee strict adherence to keyframes. Our tool can stylize trajectories through a variety of PDE-based regularizers to create different visual effects. We demonstrate our tool on various keyframe interpolation problems to produce temporally-coherent animations without meshing or rigging.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The single-cell transcriptome program of nodule development cellular lineages in Medicago truncatula

Legumes establish a symbiotic relationship with nitrogen-fixing rhizobia by developing nodules. Nodules are modified lateral roots that undergo changes in their cellular development in response to bacteria, but the transcriptional reprogramming that occurs in these root cells remains largely uncharacterized. Here, we describe the cell-type-specific transcriptome response of Medicago truncatula roots to rhizobia during early nodule development in the wild-type genotype Jemalong A17, complemented with a hypernodulating mutant (sunn-4) to expand the cell population responding to infection and subsequent biological inferences. The analysis identifies epidermal root hair and stele sub-cell types associated with a symbiotic response to infection and regulation of nodule proliferation. Trajectory inference shows cortex-derived cell lineages differentiating to form the nodule primordia and, posteriorly, its meristem, while modulating the regulation of phytohormone-related genes. Gene regulatory analysis of the cell transcriptomes identifies new regulators of nodulation, including STYLISH 4, for which the function is validated.

Cell Biology↗
DOE OSTI2022

Inferring protein expression changes from mRNA in Alzheimer’s dementia using deep neural networks

Identifying the molecular systems and proteins that modify the progression of Alzheimer’s disease and related dementias (ADRD) is central to drug target selection. However, discordance between mRNA and protein abundance, and the scarcity of proteomic data, has limited our ability to advance candidate targets that are mainly based on gene expression. Therefore, by using a deep neural network that predicts protein abundance from mRNA expression, here we attempt to track the early protein drivers of ADRD. Specifically, by applying the clei2block deep learning model to 1192 brain RNA-seq samples, we identify protein modules and disease-associated expression changes that were not directly observed at the mRNA level. Moreover, pseudo-temporal trajectory inference based on the predicted proteome became more closely correlated with cognitive decline and hippocampal atrophy compared to RNA-based trajectories. This suggests that the predicted changes in protein expression could provide a better molecular representation of ADRD progression. Furthermore, overlaying clinical traits on protein pseudotime trajectory identifies protein modules altered before cognitive impairment. These results demonstrate how our method can be used to identify potential early protein drivers and possible drug targets for treating and/or preventing ADRD.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Single-cell spatial metabolomics with cell-type specific protein profiling for tissue systems biology

Metabolic reprogramming in cancer and immune cells occurs to support their increasing energy needs in biological tissues. Here we propose Single Cell Spatially resolved Metabolic (scSpaMet) framework for joint protein-metabolite profiling of single immune and cancer cells in male human tissues by incorporating untargeted spatial metabolomics and targeted multiplexed protein imaging in a single pipeline. We utilized the scSpaMet to profile cell types and spatial metabolomic maps of 19507, 31156, and 8215 single cells in human lung cancer, tonsil, and endometrium tissues, respectively. The scSpaMet analysis revealed cell type-dependent metabolite profiles and local metabolite competition of neighboring single cells in human tissues. Deep learning-based joint embedding revealed unique metabolite states within cell types. Trajectory inference showed metabolic patterns along cell differentiation paths. Here we show scSpaMet’s ability to quantify and visualize the cell-type specific and spatially resolved metabolic-protein mapping as an emerging tool for systems-level understanding of tissue biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Investigating biological nitrogen fixation via single-cell transcriptomics

The extensive use of nitrogen fertilizers has detrimental environmental consequences, and it is essential for society to explore sustainable alternatives. One promising avenue is engineering root nodule symbiosis, a naturally occurring process in certain plant species within the nitrogen-fixing clade, into non-leguminous crops. Advancements in single-cell transcriptomics provide unprecedented opportunities to dissect the molecular mechanisms underlying root nodule symbiosis at the cellular level. This review summarizes key findings from single-cell studies in Medicago truncatula, Lotus japonicus, and Glycine max. We highlight how these studies address fundamental questions about the development of root nodule symbiosis, including the following findings: (i) single-cell transcriptomics has revealed a conserved transcriptional program in root hair and cortical cells during rhizobial infection, suggesting a common infection pathway across legume species; (ii) characterization of determinate and indeterminate nodules using single-cell technologies supports the compartmentalization of nitrogen fixation, assimilation, and transport into distinct cell populations; (iii) single-cell transcriptomics data have enabled the identification of novel root nodule symbiosis genes and provided new approaches for prioritizing candidate genes for functional characterization; and (iv) trajectory inference and RNA velocity analyses of single-cell transcriptomics data have allowed the reconstruction of cellular lineages and dynamic transcriptional states during root nodule symbiosis.

Lotus japonicus↗
DOE OSTI2021

Asc-Seurat: analytical single-cell Seurat-based web application

Abstract Background Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of transcriptomes, arising as a powerful tool for discovering and characterizing cell types and their developmental trajectories. However, scRNA-seq analysis is complex, requiring a continuous, iterative process to refine the data and uncover relevant biological information. A diversity of tools has been developed to address the multiple aspects of scRNA-seq data analysis. However, an easy-to-use web application capable of conducting all critical steps of scRNA-seq data analysis is still lacking. Summary We present Asc-Seurat, a feature-rich workbench, providing an user-friendly and easy-to-install web application encapsulating tools for an all-encompassing and fluid scRNA-seq data analysis. Asc-Seurat implements functions from the Seurat package for quality control, clustering, and genes differential expression. In addition, Asc-Seurat provides a pseudotime module containing dozens of models for the trajectory inference and a functional annotation module that allows recovering gene annotation and detecting gene ontology enriched terms. We showcase Asc-Seurat’s capabilities by analyzing a peripheral blood mononuclear cell dataset. Conclusions Asc-Seurat is a comprehensive workbench providing an accessible graphical interface for scRNA-seq analysis by biologists. Asc-Seurat significantly reduces the time and effort required to analyze and interpret the information in scRNA-seq datasets.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2020

Conditions of Loss Cone Filling by Scattering on the Curved Field Lines for 30 keV Protons During Geomagnetic Storm as Inferred From Numerical Trajectory Tracing

The rate of pitch angle scattering on the curved magnetic field lines is well parameterized by the ratio of the minimum field line curvature radius to the maximum effective particle gyroradius (K = RC/rg). The critical value of this ratio (Kcr) corresponding to the loss cone filling is of special interest since it corresponds to the low altitude isotropic boundaries (IBs). The early theoretical estimates gave Kcr = 8, whereas recent estimations of the K parameter on the field lines corresponding to the observed IBs during the geomagnetic storms revealed KIB values in the range of 3–30. We numerically trace the trajectories of the 30 keV protons in the magnetic field of the global magnetohydrodynamic simulation of the intense storm in order to infer statistical distribution of Kcr. The electric field and effects of nonstationarity are neglected in this study. It is found that although the Kcr values do show some variations during the course of the storm, its range is rather narrow 4 < Kcr < 8. The result suggests that higher KIB values found in the observational studies, if not caused by the magnetosphere-ionosphere mapping error, should be attributed to some other mechanism of pitch angle scattering. The Kcr values tend to be lower (4–6) during the main phase because the region of low K values approaches the Earth and the equatorial loss cone size becomes larger due to a larger equatorial magnetic field in the near earth region. The remaining variation of Kcr is explained by the presence of the guide component of the magnetic field.

S Dubyagin↗
DOE OSTI2023

Evaluating the Interplay between Trajectory Segmentation and Mode Inference Error

Travel behavior changes are essential to transportation decarbonization. Travel diaries, consisting of sequences of trips between places, are typically used to instrument human travel behavior. However, these diaries are only as accurate as the underlying methods used to construct them. Travel diary algorithms have been a popular research topic since the advent of Global Positioning System tracking surveys. These algorithms have typically been validated using prompted recall of presegmented trips, thus disregarding the continuity of mode inference. Phone operating systems have adopted battery-conserving techniques, but the resulting data collection errors have not been studied extensively. We introduce a framework to evaluate the accuracy of trip length computations and mode inference by analyzing continuous mode-segmented trajectories for groups of trips. We then use the framework to identify the input data quality and the impact of postprocessing. Our primary inputs to this evaluation are MobilityNet, a public dataset containing information from three artificial timelines covering 15 different travel modes, and sample open-source travel diary creation algorithms from the OpenPATH project. Our framework concretely shows that the variance of the distance error drops from (0.217, 0.0848) to (o.011, 0.0407) (Android, iOS) after postprocessing. Similarly, the weighted F-scores for mode inference increase from (0.25, 0.29) to (0.60, 0.74) (iOS, Android) between random forest and geographic information system-based models. We hope that this standardized method will be adapted to evaluate other, potentially proprietary, travel diary algorithms. Finally, the results can be used to understand and improve the state of the art in the travel diary creation field.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

A single-cell Arabidopsis root atlas reveals developmental trajectories in wild-type and cell identity mutants

In all multicellular organisms, transcriptional networks orchestrate organ development. The Arabidopsis root, with its simple structure and indeterminate growth, is an ideal model to investigate the spatiotemporal transcriptional signatures underlying developmental trajectories. To map gene expression dynamics across root cell types and developmental time, we built a comprehensive, organ-scale atlas at single cell resolution. In addition to estimating developmental progressions in pseudotime, we employed the mathematical concept of optimal transport to infer developmental trajectories and identify their underlying regulators. To demonstrate the utility of the atlas to interpret new datasets, we profiled mutants for two key transcriptional regulators at single cell resolution, shortroot and scarecrow. We report transcriptomic and in vivo evidence for tissue trans-differentiation underlying a mixed cell identity phenotype in scarecrow. Our results support the atlas as a rich community resource for unraveling the transcriptional programs that specify and maintain cell identity to regulate spatiotemporal organ development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

3D xRAGE simulation of inertial confinement fusion implosion with imposed mode 2 laser drive asymmetry

Low-mode asymmetries represent an important obstacle to achieving high-gain inertial confinement fusion implosions. As a step in learning how to control such effects, an OMEGA experiment with imposed mode 2 laser drive asymmetries was done to study the expected signatures of this type of asymmetry [M. Gatu Johnson et al., PRE 2018]. In the present work, a 3D xRAGE simulation including the stalk mount has been brought to bear on the data from that experiment. Furthermore, comprehensive comparisons between simulated and measured observables are made. Good agreement between simulated and measured x-ray image-inferred shell trajectories, bang times and neutron emission widths are seen, showing that the hydrodynamics are well captured in the simulation. Asymmetries seen in simulated and measured time-resolved and time-integrated x-ray images and areal densities also compare well, showing impact of both stalk and mode 2. On the other hand, important differences in measured and simulated neutron emission histories, yield, and ion temperature (T ion ) asymmetries are seen, suggesting that the simulation is overestimating shock yield. Overall, the results clearly demonstrate the importance of considering all asymmetry sources when interpreting measured signatures of asymmetry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1990

A flight experiment to measure rarefied-flow aerodynamics

A flight experiment to measure rarefied-flow aerodynamics of a blunt lifting body is being developed by NASA. This experiment, called the Rarefied-Flow Aerodynamic Measurement Experiment (RAME), is part of the Aeroassist Flight Experiment (AFE) mission, which is a Pathfinder design tool for aeroassisted orbital transfer vehicles. The RAME will use flight measurements from accelerometers, rate gyros, and pressure transducers, combined with knowledge of AFE in-flight mass properties and trajectory, to infer aerodynamic forces and moments in the rarefied-flow environment, including transition into the hypersonic continuum regime. Preflight estimates of the aerodynamic measurements are based upon environment models, existing computer simulations, and ground test results. Planned maneuvers at several altitudes will provide a first-time opportunity to examine gas-surface accommondation effects on aerodynamic coefficients in an environment of changing atmospheric composition. A description is given of the RAME equipment design.

Blanchard, Robert C.↗
NASA NTRS2015

X-Ray Analysis of the Proper Motion and Pulsar Wind Nebula for PSR J1741-2054

We obtained six observations of PSR J1741-2054 using the Chandra ACIS-S detector totaling approx.300 ks. By registering this new epoch of observations to an archival observation taken 3.2 yr earlier using X-ray point sources in the field of view, we have measured the pulsar proper motion at micron = 109 +/- 10 mas yr(exp. -1) in a direction consistent with the symmetry axis of the observed H(alpha) nebula. We investigated the inferred past trajectory of the pulsar but find no compelling association with OB associations in which the progenitor may have originated. We confirm previous measurements of the pulsar spectrum as an absorbed power law with photon index gamma = 2.68 +/- 0.04, plus a blackbody with an emission radius of (4.5(+3.2/-2.5))d(0.38) km, for a DM-estimated distance of 0.38d(0.38) kpc and a temperature of 61.7 +/- 3.0 eV. Emission from the compact nebula is well described by an absorbed power law model with a photon index of gamma = 1.67 +/- 0.06, while the diffuse emission seen as a trail extending northeast of the pulsar shows no evidence of synchrotron cooling. We also applied image deconvolution techniques to search for small-scale structures in the immediate vicinity of the pulsar, but found no conclusive evidence for such structures.

Analysis↗
NASA NTRSDate not supplied

Gravity Science With the Uranus Orbiter

The Cassini and Juno missions have considerably expanded our understanding of Saturn, Jupiter, and their moons. The spacecraft radio tracking data acquired by the NASA Deep Space Network (DSN) have enabled the accurate measurement of gravitational perturbations of these planetary bodies on the spacecraft trajectory. The inferred static zonal gravity fields have been key in understanding the interior structure and dynamics within Jupiter and Saturn. Repeated flybys of moons such as Titan and Enceladus can also constrain their interior properties, putting constraints on their formation and evolution, and potential habitability. The exploration of the Uranus system by NASA’s future flagship mission (Uranus Orbiter and Probe, UOP) holds the promise of making similar gains for Uranus and its moons. Here we address the gravity science that may be possible with UOP.

Erwan Mazarico↗
DOE OSTI2023

Deriving spatially explicit direct and indirect interaction networks from animal movement data

Abstract Quantifying spatiotemporally explicit interactions within animal populations facilitates the understanding of social structure and its relationship with ecological processes. Data from animal tracking technologies (Global Positioning Systems [“GPS”]) can circumvent longstanding challenges in the estimation of spatiotemporally explicit interactions, but the discrete nature and coarse temporal resolution of data mean that ephemeral interactions that occur between consecutive GPS locations go undetected. Here, we developed a method to quantify individual and spatial patterns of interaction using continuous‐time movement models (CTMMs) fit to GPS tracking data. We first applied CTMMs to infer the full movement trajectories at an arbitrarily fine temporal scale before estimating interactions, thus allowing inference of interactions occurring between observed GPS locations. Our framework then infers indirect interactions—individuals occurring at the same location, but at different times—while allowing the identification of indirect interactions to vary with ecological context based on CTMM outputs. We assessed the performance of our new method using simulations and illustrated its implementation by deriving disease‐relevant interaction networks for two behaviorally differentiated species, wild pigs ( Sus scrofa ) that can host African Swine Fever and mule deer ( Odocoileus hemionus ) that can host chronic wasting disease. Simulations showed that interactions derived from observed GPS data can be substantially underestimated when temporal resolution of movement data exceeds 30‐min intervals. Empirical application suggested that underestimation occurred in both interaction rates and their spatial distributions. CTMM‐Interaction method, which can introduce uncertainties, recovered majority of true interactions. Our method leverages advances in movement ecology to quantify fine‐scale spatiotemporal interactions between individuals from lower temporal resolution GPS data. It can be leveraged to infer dynamic social networks, transmission potential in disease systems, consumer–resource interactions, information sharing, and beyond. The method also sets the stage for future predictive models linking observed spatiotemporal interaction patterns to environmental drivers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Mass of a weakly measured photon

Bohmian mechanics has garnered significant attention as an interpretation of quantum theory since the paradigmatic experiments which inferred the average trajectories of photons in the nonrelativistic regime. These experiments were largely motivated by Wiseman's formulation of Bohmian mechanics, which grounded these trajectories in weak measurements. Recently, Wiseman's framework was extended to the relativistic regime by expressing the velocity field of single photons in terms of weak values of the photon energy and momentum. Here, we propose an operational, weak value-based definition for the Bohmian “local mass” of relativistic single particles. For relativistic wave functions satisfying the scalar Klein-Gordon equation, this mass coincides with the effective mass defined by de Broglie in his relativistic pilot-wave theory, a quantity closely connected with the quantum potential that is responsible for Bohmian trajectory self-bending and the anomalous photoelectric effect. Here, we demonstrate the relationship between the photon trajectories and the mass in an interferometric setup.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗