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At least 1,171 records · Page 65

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NASA NTRS2016

Lunar Entry Downmode Options for Orion

For Exploration Missions 1 and 2, the Orion capsules will be entering the Earth's atmosphere with speeds in excess of 11 km/s. In the event of a degraded Guidance, Navigation, and Control system, attempting the nominal guided entry may be inadvisable due to the potential for failures that result in a loss of vehicle (or crew, when crew are aboard). In such a case, a method of assuring Earth capture, water landing, and observence of trajectory constraints (heating, loads) is desired. Such a method should also be robust to large state uncertainty and variations in entry interface states. This document will explore four approaches evaluated and their performance in ensuring a safe return of the Orion capsule in the event of onboard system degradation.

Smith, Kelly M.↗

DOE OSTI2026

Spatially Mapping the CO 2 Alkaline Sorbent Diffuse Microenvironment Using Operando Raman Spectroscopy

When designing a chemical process, the local balance of transport and kinetics, collectively referred to as the diffuse microenvironment, plays a critical role in performance but is difficult to directly observe. This work demonstrates a method of two-dimensional spatial chemical mapping of the diffuse microenvironment in the context of alkali metal hydroxide direct air capture of carbon dioxide using a custom operando gas-absorption flow cell along with confocal Raman spectroscopy. Notably, we observe the concentration boundary layer near the gas–liquid interface and elucidate the interplay of carbonate and bicarbonate ions within it while inferring local hydroxide depletion through continuum modeling. These first of their kind observations provide a technique to compare the performance of direct air capture solvents based on diffuse microenvironment dynamics while also providing metrics important for air contactor design such as boundary layer thickness. Overall, this work showcases a new experimental platform to study interfacial diffuse microenvironments in and outside of the field of direct air capture of carbon dioxide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Deep learning methods for drug response prediction in cancer: Predominant and emerging trends

Cancer claims millions of lives yearly worldwide. While many therapies have been made available in recent years, by in large cancer remains unsolved. Exploiting computational predictive models to study and treat cancer holds great promise in improving drug development and personalized design of treatment plans, ultimately suppressing tumors, alleviating suffering, and prolonging lives of patients. A wave of recent papers demonstrates promising results in predicting cancer response to drug treatments while utilizing deep learning methods. These papers investigate diverse data representations, neural network architectures, learning methodologies, and evaluations schemes. However, deciphering promising predominant and emerging trends is difficult due to the variety of explored methods and lack of standardized framework for comparing drug response prediction models. To obtain a comprehensive landscape of deep learning methods, we conducted an extensive search and analysis of deep learning models that predict the response to single drug treatments. A total of 61 deep learning-based models have been curated, and summary plots were generated. Based on the analysis, observable patterns and prevalence of methods have been revealed. This review allows to better understand the current state of the field and identify major challenges and promising solution paths.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1987

Variability analysis in low count rate sources

A method, based on the chi-square statistics, is described for detecting pulselike time variability in low count rate sources observed with photon-counting instruments. This method can be used even in the presence of observational gaps, takes full advantage of the filtering effect due to binning with different bin sizes, and takes into account the arbitrariness introduced by the binning phase. The procedure developed to limit the dependence of the results on the binning phase and ensure statistically correct results is described along with the application of the proposed procedure to a model of a variable source. Monte Carlo simulations are used to show how the method can be used to derive the characteristic variability time scales and that the method is more sensitive than the nonparametric Kolmogorov-Smirnov test in detecting variability to a given confidence level.

Collura, A.↗

DOE OSTI2024

Observation of d(t,n) α Neutrons Following d(d,p)t Reactions in a Deuterium Gas Cell: An Attempt to Repeat Ruhlig’s 1938 Observation of Secondary Reactions

In order to benchmark methods used to calculate reaction-in-flight fusion reactions in inertial confinement fusion and address issues related to the first claimed observation of d(t,n)α reactions in 1938, secondary d(t,n)α reactions have been observed following d(d,p)t reactions in deuterium gas. A pulsed 200-nA, 2.2-MeV deuterium beam from the Triangle Universities Nuclear Laboratory FN tandem accelerator was injected into a cylindrical multiatmosphere deuterium gas target. The incident beam traversed along the target cylinder’s 3-cm symmetry axis after its passage through a Havar entrance foil. Two different Havar foil thicknesses were used to obtain 1.5- and 0.6-MeV deuteron beams entering the deuterium cell. The cylinder’s radius was 2 cm to allow for d(d,p)t tritons emitted perpendicular to the beam to range out in the deuterium gas. The neutron emission from the cell was observed via its time of flight to a liquid scintillator placed at various angles to the beam direction, at a distance of 243 cm. Pulse-shape-discrimination techniques were used to separate neutron and gamma-ray signals seen in the liquid scintillator. The observed probability of ~2 × 10 –4 for inducing secondary d(t,n)α fusion in the gas cell per d(d,p)t reaction is consistent with theoretical expectations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2011

Interplanetary Propagation of Coronal Mass Ejections

Although more than ten thousand coronal mass ejections (CMEs) are produced during each solar cycle at the Sun, only a small fraction hits the Earth. Only a small fraction of the Earth-directed CMEs ultimately arrive at Earth depending on their interaction with the solar wind and other large-scale structures such as coronal holes and CMEs. The interplanetary propagation is essentially controlled by the drag force because the propelling force and the solar gravity are significant only near the Sun. Combined remote-sensing and in situ observations have helped us estimate the influence of the solar wind on the propagation of CMEs. However, these measurements have severe limitations because the remote-sensed and in-situ observations correspond to different portions of the CME. Attempts to overcome this problem are made in two ways: the first is to model the CME and get the space speed of the CME, which can be compared with the in situ speed. The second method is to use stereoscopic observation so that the remote-sensed and in-situ observations make measurements on the Earth-arriving part of CMEs. The Solar Terrestrial Relations Observatory (STEREO) mission observed several such CMEs, which helped understand the interplanetary evolution of these CMEs and to test earlier model results. This paper discusses some of these issues and updates the CME/shock travel time estimates for a number of CMEs.

Gopalswamy, Nat↗

DOE OSTI2022

Combined $\mathrm{APOGEE}$-$\mathrm{GALAH}$ stellar catalogues using the Cannon

APOGEE and GALAH are two high resolution multi-object spectroscopic surveys that provide fundamental stellar parameters and multiple elemental abundance estimates for about half a million stars in the Milky Way. Both surveys observe in different wavelength regimes and use different data reduction pipelines leading to significant offsets and trends in stellar parameters and abundances for the common stars observed in both surveys. Such systematic differences/offsets in stellar parameters and abundances make it difficult to effectively utilize them to investigate Galactic abundance trends in spite of the unique advantage provided by their complementary sky coverage and different Milky Way components they observe. Hence, we use the Cannon data-driven method selecting a training set of 4418 common stars observed by both surveys. This enables the construction of two catalogues, one with the APOGEE-scaled and the other with the GALAH-scaled stellar parameters. Using repeat observations in APOGEE and GALAH, we find high precision in metallicity (~0.02–0.4 dex) and alpha abundances (~0.02–0.03 dex) for spectra with good signal-to-noise ratio (SNR >; 80 for APOGEE and SNR > 40 for GALAH). We use open and globular clusters to validate our parameter estimates and find small scatter in metallicity (0.06 dex) and alpha abundances (0.03 dex) in APOGEE-scaled case. The final catalogues have been cross-matched with the Gaia EDR3 catalogue to enable their use to carry out detailed chemo-dynamic studies of the Milky Way from perspectives of APOGEE and GALAH.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1984

Software reliability: Additional investigations into modeling with replicated experiments

The effects of programmer experience level, different program usage distributions, and programming languages are explored. All these factors affect performance, and some tentative relational hypotheses are presented. An analytic framework for replicated and non-replicated (traditional) software experiments is presented. A method of obtaining an upper bound on the error rate of the next error is proposed. The method was validated empirically by comparing forecasts with actual data. In all 14 cases the bound exceeded the observed parameter, albeit somewhat conservatively. Two other forecasting methods are proposed and compared to observed results. Although demonstrated relative to this framework that stages are neither independent nor exponentially distributed, empirical estimates show that the exponential assumption is nearly valid for all but the extreme tails of the distribution. Except for the dependence in the stage probabilities, Cox's model approximates to a degree what is being observed.

Nagel, P. M.↗

NASA NTRS1990

Modeling of solar oscillation power spectra

To produce accurate estimates of the line-profile parameters of a model used to represent the spectral features in a solar oscillation power spectrum, it is necessary to (1) select the appropriate probability density function when deriving the maximum-likelihood function to be employed for the parameter estimation and (2) allow for the redistribution of spectral power caused by gaps in the data string. This paper describes a maximum-likelihood method for estimating the model parameters (based on the observed power spectrum statistics) that accounts for redistribution of spectral power caused by gaps in the data string, by convolving the model with the power spectrum of the observed window function. The accuracy and reliability of the method were tested using both artificial and authentic solar oscillation power spectrum data. A comparison of this method with various least-squares techniques is also presented.

Anderson, Edwin R.↗

NASA NTRSDate not supplied

A Novel Framework for Multi-Path Data Fusion in Earth Observation and New Observing Strategies: Applications to Predicting Forest Canopy Height

Exponential growth of data from Earth Observation (EO) assets has necessitated the development of sophisticated methods for data interpretation and management. NASA’s New Observing Strategy (NOS) approach aims to coordinate operations among complex heterogenous systems of constellations, requiring advanced Artificial Intelligence and Machine Learning (AI/ML) techniques. Despite significant advancements in AI/ML across various domains, the EO and machine learning for satellite (SatML) fields remain fragmented, often relying on adapted techniques rather than domain-specific solutions. We present a novel end-to-end data fusion framework tailored specifically for EO and SatML, addressing this gap by facilitating rapid development of AI/ML applications. This framework, called, Multimodal Earth Observation Workflow for Machine Learning (MEOW-ML), sup- ports the entire AI/ML lifecycle, from dataset manipulation, to model training, evaluation, and logging, and is designed to expedite the development of next-generation NOS deployments and SOTA in EO. We apply our framework to predict canopy height model (CHM) derived from lidar data. We integrate multiple data modalities through a hierarchical, multi-path model architecture, effectively identifying and leveraging the unique strengths of each data source to enhance predictive accuracy. Our experiments demonstrate that the multi-path architecture outperforms traditional single-path models and provides significant advantages in both accuracy and computational efficiency.

Mark Moussa↗

NASA NTRS1974

Data processing of Martian topographic information obtained from ground-based radar and spectroscopy and from Mariners 6 and 7. Martian topography elevations: Data processing

Papers are presented which were published as a result of a project involving the preparation of a topographical elevation contour map of Mars from all data sources available through 1969, as well as the observation of Mars by spectroscopic methods in 1971 to provide additional pressure data for topographic information. Topics of the papers include: the analysis of large-scale Martian topography variations - data preparation from earth based radar, earth based CO2 spectroscopy, and Mariners 6 and 7 CO2 spectroscopy; the analysis of water content in observed Martian white clouds; and Martian, lunar, and terrestrial crusts - a three-dimensional exercise in comparative geophysics.

Anderson, K. A.↗

DOE OSTI2021

An efficient LC-MS method for isomer separation and detection of sugars, phosphorylated sugars, and organic acids

Abstract Assessing central carbon metabolism in plants can be challenging due to the dynamic range in pool sizes, with low levels of important phosphorylated sugars relative to more abundant sugars and organic acids. Here, we report a sensitive liquid chromatography–mass spectrometry method for analysing central metabolites on a hybrid column, where both anion-exchange and hydrophilic interaction chromatography (HILIC) ligands are embedded in the stationary phase. The liquid chromatography method was developed for enhanced selectivity of 27 central metabolites in a single run with sensitivity at femtomole levels observed for most phosphorylated sugars. The method resolved phosphorylated hexose, pentose, and triose isomers that are otherwise challenging. Compared with a standard HILIC approach, these metabolites had improved peak areas using our approach due to ion enhancement or low ion suppression in the biological sample matrix. The approach was applied to investigate metabolism in high lipid-producing tobacco leaves that exhibited increased levels of acetyl-CoA, a precursor for oil biosynthesis. The application of the method to isotopologue detection and quantification was considered through evaluating 13C-labeled seeds from Camelina sativa. The method provides a means to analyse intermediates more comprehensively in central metabolism of plant tissues.

Plant Sciences↗

DOE OSTI2025

Estimating Eigenenergies from Quantum Dynamics: A Unified Noise-Resilient Measurement-Driven Approach

Ground state energy estimation in physical, chemical, and materials sciences is one of the most promising applications of quantum computing. In this work, we introduce a new hybrid approach that finds the eigenenergies by collecting real-time measurements and post-processing them using the machinery of dynamic mode decomposition (DMD). From the perspective of quantum dynamics, we establish that our approach can be formally understood as a stable variational method on the function space of observables available from a quantum many-body system. We also provide strong theoretical and numerical evidence that our method converges rapidly even in the presence of a large degree of perturbative noise, and show that the method bears an isomorphism to robust matrix factorization methods developed independently across various scientific communities. Our numerical benchmarks on spin and molecular systems demonstrate an accelerated convergence and a favorable resource reduction over state-of-the-art algorithms. The DMD-centric strategy can systematically mitigate noise and stands out as a leading hybrid quantum-classical eigensolver.

Shen, Yizhi↗

NASA NTRS1988

A ground-based technique for millimeter wave spectroscopic observations of stratospheric trace constituents

Recent concern over possible long term stratospheric changes caused by the introduction of man-made compounds has increased the need for instrumentation that can accurately measure stratospheric minor constituents. The technique of radio spectroscopy at millimeter wavelengths was first used to observe rotational transitions of stratospheric ozone nearly two decades ago, but has not been highly developed until recently. A ground-based observing technique is reported which employs a millimeter-wave superheterodyne receiver and multichannel filter spectrometer for measurements of stratospheric constituents that have peak volume mixing ratios that are less than 10 to the -9th, more than 3 orders of magnitude less than that for ozone. The technique is used for an extensive program of observations of stratospheric chlorine monoxide and also for observations of other stratospheric trace gases such as (O-16)3, vibrationally excited (O-16)3, (O-18)2(O-16), N2O, HO2, and HCN. In the present paper, analysis of the observing technique is given, including the method of calibration and analysis of sources of error. The technique is found to be a reliable means of observing and monitoring important stratospheric trace constituents.

Parrish, A.↗

NASA NTRS1988

The complete visual light curve of SN 1987A: Thirteen months of FES observations

Visual brightness measurements of SN 1987A are being obtained with the IUE acquisition camera and star tracker Fine Error Sensor, (FES) as part of each ultraviolet observation. Due to IUE's around-the-clock operation and lack of clouds, the FES record of SN 1987A provides the most complete set of visual photometry of the supernova made by any single instrument. The data illustrate the photometric limitations of the FES (+ or - 0.03 mag). Use of differential photometric methods are recommended for IUE observers desiring accurate photometry from FES measurements made during their observing shifts.

Sonneborn, G.↗

NASA NTRS2016

Characterization of the High-Albedo NEA 3691 Bede

Characterization of NEAs provides important inputs to models for atmospheric entry, risk assessment and mitigation. Diameter is a key parameter because diameter translates to kinetic energy in atmospheric entry. Diameters can be derived from the absolute magnitude, H(PA=0deg), and from thermal modeling of observed IR fluxes. For both methods, the albedo (pv) is important - high pv surfaces have cooler temperatures, larger diameters for a given Hmag, and shallower phase curves (larger slope parameter G). Thermal model parameters are coupled, however, so that a higher thermal inertia also results in a cooler surface temperature. Multiple parameters contribute to constraining the diameter. Observations made at multiple observing geometries can contribute to understanding the relationships between and potentially breaking some of the degeneracies between parameters. We present data and analyses on NEA 3691 Bede with the aim of best constraining the diameter and pv from a combination of thermal modeling and light curve analyses. We employ our UKIRT+Michelle mid-IR photometric observations of 3691 Bede's thermal emission at 2 phase angles (27&43 deg 2015-03-19 & 04-13), in addition to WISE data (33deg 2010-05-27, Mainzer+2011). Observing geometries differ by solar phase angles and by moderate changes in heliocentric distance (e.g., further distances produce somewhat cooler surface temperatures). With the NEATM model and for a constant IR beaming parameter (eta=constant), there is a family of solutions for (diameter, pv, G, eta) where G is the slope parameter from the H-G Relation. NEATM models employing Pravec+2012's choice of G=0.43, produce D=1.8 km and pv≈0.4, given that G=0.43 is assumed from studies of main belt asteroids (Warner+2009). We present an analysis of the light curve of 3691 Bede to constrain G from observations. We also investigate fitting thermophysical models (TPM, Rozitis+11) to constrain the coupled parameters of thermal inertia (Gamma) and surface roughness, which in turn affect diameter and pv. Surface composition can be related to pv. This study focuses on understanding and characterizing the dependency of parameters with the aim of constraining diameter, pv and thermal inertia for 3691 Bede.

Wooden, Diane H.↗

NASA NTRS2016

Characterization of the High-Albedo NEA 3691 Bede

magnitude↗

DOE OSTI2022

A unifying Bayesian framework for merging X-ray diffraction data

Novel X-ray methods are transforming the study of the functional dynamics of biomolecules. Key to this revolution is detection of often subtle conformational changes from diffraction data. Diffraction data contain patterns of bright spots known as reflections. To compute the electron density of a molecule, the intensity of each reflection must be estimated, and redundant observations reduced to consensus intensities. Systematic effects, however, lead to the measurement of equivalent reflections on different scales, corrupting observation of changes in electron density. Here, we present a modern Bayesian solution to this problem, which uses deep learning and variational inference to simultaneously rescale and merge reflection observations. We successfully apply this method to monochromatic and polychromatic single-crystal diffraction data, as well as serial femtosecond crystallography data. We find that this approach is applicable to the analysis of many types of diffraction experiments, while accurately and sensitively detecting subtle dynamics and anomalous scattering.

59 BASIC BIOLOGICAL SCIENCES↗