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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
DOE OSTI2023

Quantitative Characterization of Hyper-Local Atmospheric Greenhouse Gas Sources

Atmospheric greenhouse gas (GHG) emissions are often characterized using stationary, tower-based sensors. Ground based sensors reside in the turbulent boundary layer and are subject to intense concentration impulses from hyper-local (<100m) point sources of emissions. These high frequency spikes are often filtered out in broader emission flux studies, losing valuable information about how hyper-local sources influence receptors. In this study, we investigated how empirical atmospheric data can be used to locate and quantify a concurrently measured hyper-local point source in a dense urban setting. An eddy covariance style tower and a low-cost sensor tower were deployed in various locations around an urban, hyper-local CO2/CH4 emissions source (a continuously measured restaurant exhaust vent). A model using different processing and statistical techniques was built to examine the most effective procedures for source isolation, directional location, and emission quantification. Using excess concentrations above a minimum baseline, we identify the source using bivariate polar plots and quantify the relationship between source size, receptor distance, and statistical proxies. Furthermore, we find that varying statistical thresholds allows for identification of less influential sources which are drowned out by larger or closer sources. Finally, we show that large sources can be effectively characterized using low-cost sensors, a valuable outcome informing how networks for monitoring larger areas could be implemented. This work may provide a basis for source identification and monitoring protocols for networks that feature sensors influenced by hyper-local point sources, subject to site-specific assumptions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Multifaceted radiation detection and classification system

A system identifying a source of radiation is provided. The system includes a radiation source detector and a radiation source identifier. The radiation source detector receives measurements of radiation; for one or more sources, generates a detection metric indicating whether that source is present in the measurements; and evaluates the detection metrics to detect whether a source is present in the measurements. When the presence of a source in the measurements is detected, the radiation source identifier for one or more sources, generates an identification metric indicating whether that source is present in the measurements; generates a null-hypothesis metric indicating whether no source is present in the measurements; evaluates the one or more identification metrics and the null-hypothesis metric to identify the source, if any, that is present in the measurements.

Labov, Simon E.↗
DOE OSTI2022

Multifaceted radiation detection and classification system

A system identifying a source of radiation is provided. The system includes a radiation source detector and a radiation source identifier. The radiation source detector receives measurements of radiation; for one or more sources, generates a detection metric indicating whether that source is present in the measurements; and evaluates the detection metrics to detect whether a source is present in the measurements. When the presence of a source in the measurements is detected, the radiation source identifier for one or more sources, generates an identification metric indicating whether that source is present in the measurements; generates a null-hypothesis metric indicating whether no source is present in the measurements; evaluates the one or more identification metrics and the null-hypothesis metric to identify the source, if any, that is present in the measurements.

Labov, Simon E.↗
NASA NTRS1999

A Source Survey in a High Galactic Latitude Field

The subject grant is for work on the study of X-ray sources detected in a 20 ks high Galactic latitude pointing with the ROSAT PSPC. The purpose of the study is to: compare the detected source population with the log N - log S relationship; and to identify sources which show variability or particularly anomalous X-ray behavior. As detailed below, several concrete identifications of sources detected in this observation have been made, and the overall flux distribution of the detected sources is typical of the overall population at high latitude. No highly variable sources, were identified. This summary serves as the final report for this study.

Slane, Patrick O.↗
NASA NTRS1976

Advances in gamma-ray burst astronomy

The paper reviews the current status of observational research into the highly puzzling problem of cosmic gamma-ray bursts. Up to now there is no convincing temporal or spatial correlation with any known celestial processes or objects. The typical burst source strength is somewhere between 10 to the 26th power ergs and 10 to the 52nd power ergs. A list of 39 confirmed and 9 unconfirmed cosmic gamma-ray bursts observed by satellite is given, showing times of occurrence and in some cases, the size in erg per square centimeter. Several approaches to the problem of source object identification are discussed: (1) accumulation of observation statistics with their present poor resolution and research for correlative phenomena, (2) mapping out celestial source distributions with moderate resolution in order to search for galactic or other anisotropies in direction or to look for repeating source regions, and (3) very high-accuracy localization of the source directions of one or several bursts in order to pinpoint a tiny fraction of the celestial sphere for correlative radio, optical and X-ray studies. Planned future instrumentation for deep space probes and multiple-balloon studies is described.

Cline, T. L.↗
NASA NTRS1999

"X-Ray Transients in Star-Forming Regions" and "Hard X-Ray Emission from X-Ray Bursters"

This grant funded work on the analysis of data obtained with the Burst and Transient Experiment (BATSE) on the Compton Gamma-Ray Observatory. The goal of the work was to search for hard x-ray transients in star forming regions using the all-sky hard x-ray monitoring capability of BATSE. Our initial work lead to the discovery of a hard x-ray transient, GRO J1849-03. Follow-up observations of this source made with the Wide Field Camera on BeppoSAX showed that the source should be identified with the previously known x-ray pulsar GS 1843-02 which itself is identified with the x-ray source X1845-024 originally discovered with the SAS-3 satellite. Our identification of the source and measurement of the outburst recurrence time, lead to the identification of the source as a Be/X-ray binary with a spin period of 94.8 s and an orbital period of 241 days. The funding was used primarily for partial salary and travel support for John Tomsick, then a graduate student at Columbia University. John Tomsick, now Dr. Tomsick, received his Ph.D. from Columbia University in July 1999, based partially on results obtained under this investigation. He is now a postdoctoral research scientist at the University of California, San Diego.

Halpern, Jules P.↗
NASA NTRS1988

Geobotanical remote sensing for determination of aggregate source material

Aggregate source material suitable for facility and roadbed construction is often a very limited and highly valuable resource. The location of suitable source material is crucial to construction operations once facility requirements are established. The application of airborne and spaceborne remote sensing to terrain information requirements has proved attractive because of the rapid processing time and extensive spatial coverage associated with remotely gathered imagery. Source material identification may be improved by the remote sensing of vegetation associated with the material, particularly in areas of high vegetative cover. A research study employing remote sensing techniques was initiated to determine if vegetation could be used to discriminate parent materials for suitability as aggregate source material. Two test sites representing potential alluvial and residual source areas were selected in a semiarid region of Central California. Methods developed for the study included field observations of vegetation characteristics associated with the two parent material types along with the analysis of Thematic Mapper Simulator data flown over the test sites. The most useful images were those composites that included bands from two of the techniques (i.e., a Perpendicular Vegetation Index (PVI) band combined with principal components bands).

Minor, Timothy↗
NASA NTRS1978

XUV spectra of the 1973 June 15 solar flare observed from Skylab. III - A list of spectral lines from 1000 to 1940 A

A wavelength list of spectral lines between 1000 and 1940 A is presented for the solar flare that occurred on June 15, 1973. The spectra were recorded by the NRL spectrograph on Skylab. The spectral resolution is 0.06 A. Intensities, identifications, and estimates of line widths are given. The intensity of the continuum is also given at 50-A intervals between 1400 and 1900 A. The wavelength list includes about 1400 lines; about 30% of these lines are not indentified. Because of the high wavelength resolution, this line list will be useful as a source of identification for some stellar as well as solar spectra. In particular, the list should be a useful aid in the identification of lines in the spectra of stars with classifications close to that of the sun. Spectra of such stars may be obtained from the recently launched IUE spacecraft. It is also interesting to compare the list with some of the spectra of early-type stars recorded by Copernicus.

Cohen, L.↗
DOE OSTI2024

Proteomics Analysis of Human Contaminant Proteins

Complete characterization of unknowns via proteomics remains challenging. There exist regions of mass spectrometry-based proteomics data where empirical measurements are not attributed to peptides, and/or sequenced peptides from mass spectra are not attributed to any source. These uncharacterized regions are known as the “dark” proteome. Many proteomics tools rely on some a priori knowledge of sample composition; few tools allow for investigation of unknowns without relying on composition assumptions. Further, the potential low abundance of minor traces in these uncharacterized regions can make elucidation of the “dark” proteome challenging. Herein, we describe the development and evaluation of approaches to study the “dark” proteome and move towards an untargeted approach for more complete characterization, namely by studying minor human protein traces in non-human samples and combining that approach with non-human source organism identification without relying on assumptions. Human protein markers, in the form of genetically variant peptides, have been extensively examined in a variety of human matrices, including blood, plasma, and hair, but have yet to be investigated in non-human samples, such as cell cultures, as human contaminant traces. Genetically variant peptides are those that are found in proteins carrying single nucleotide polymorphisms. In this work, we aimed to (1) investigate the feasibility of detecting human contaminant genetically variant peptides (GVPs) in a diverse set of non-human organisms using public proteomics data and a computational pipeline, as well as to (2) develop a combined capability for untargeted source organism characterization and GVP detection. To our knowledge, this is the first report of applying these approaches towards a more complete proteomic characterization of unknowns. We successfully demonstrate the feasibility of broad human contaminant GVP detection in proteomics data, develop a better understanding of GVP detectability, characterize the sample-to-sample variability in GVP detection, and identify a core set of GVPs that can potentially be used as markers indicative of the human contaminant traces portion of the “dark” proteome. Further, we developed and evaluated a combined pipeline, MARLOWE-GVP, that enables both untargeted source organism characterization and GVP detection. We show high accuracy of correct source organism characterization and high degree of similarity of human contaminant GVP detection compared to the conventional approach. Success on both these efforts have allowed us to advance our understanding and characterization of the “dark” proteome.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2001

Mapping Rice Production in China with AVHRR Imagery

The study of rice agriculture is necessary for both the importance of rice as a vital food source and because of the fact that cultivating it has an unfortunate byproduct, namely methane gas. As a food source, rice is a staple for a large majority of the world's population, especially in Asia. Because the populations of many Asian nations are increasing at rapid rates, the production of rice will need to similarly increase. In 1989, it was estimated that the demand for rice would increase by 65% by the year 2019. Rice crops are considered to be one of the primary anthropogenic sources of methane gas. A reason for concern is that this gas is a so-called "greenhouse" trace gas and given its increasing levels in the atmosphere, is thought to contribute to the suspected global warming phenomenon. Some estimate that methane may contribute up to 20% to the global warming effect. Trace gas emissions from anthropogenic sources is an issue that generates great worldwide interest because of the fact that mankind is very likely affecting the current and future climate in potentially negative ways. In an effort to better understand these effects, scientists and engineers are conducting research on all of the varied fronts which relate to climate change and biosphere/atmosphere interactions. The study of global warming through increasing concentrations of greenhouse gases is one area which has received much media and scientific attention. Research fueled by debates on this topic is being conducted on numerous, interrelated fronts in an effort to better understand the complex relationship between human activities and the earth's climate. The research ranges from attempting to verify if the observed data even supports the existence of an anthropogenically generated global-warming phenomenon, to identification of sources and sinks of the trace gases, to measuring the source strengths, to studies which focus on modeling the processes which generate the gases, and finally, to trying to project their impact on the global climatic system. Some of the more commonly known sources of greenhouse gases are related to industry and transportation. Carbon dioxide, CO2, from automobile emissions is one such example. Lesser known are sources from natural and cultivated vegetation, such as the methane, CH4, resulting from rice cropping. While the concentration of atmospheric methane is significantly less than that of carbon dioxide, CH4 has been estimated to have up to 32 times the insulating capability of carbon dioxide, making it an important gas to monitor. The remainder of this chapter will provide some additional background information on the effects of atmospheric methane, and the role that rice agriculture plays as a source in the methane budget. This will be followed by a brief description of efforts to model this source of atmospheric methane. Finally, this chapter will end with a statement of the hypotheses of this thesis, at which time a description of the information contained in the rest of this document will be provided.

Paliouras, Eleni J.↗
DOE OSTI2025

Identification of shared viral sequences in peat moss metagenomes reveals elements of a possible Sphagnum core virome

Viruses are an understudied component of plant microbiomes. Identifying viruses that are shared between individual plants, or members of the “core virome”, could reveal stable viral populations with the potential to modulate the composition and function of the microbiome. Here, we examined the virome associated with Sphagnum mosses, a keystone species that has direct influence over the fate of peatland carbon stores. We analyzed bulk metagenomes and metatranscriptomes generated from Sphagnum field samples collected over a ten-month period to identify virus-like sequences shared among plants. Individual Sphagnum samples harbored distinct DNA and RNA viromes where only a small percentage (< 1%) of the total number of identified viral contigs were shared among all samples. Based on taxonomic classification, the shared viral contigs represent bacterial viruses, or phage (Caudoviricetes), as well as viruses of eukaryotes, namely nucleocytoplasmic large DNA viruses (Nucleocytoviricota) and RNA viruses (Riboviria). We linked the shared phage-like contigs to viral regions within sequenced genomes of bacterial taxa that are members of the Sphagnum core microbiome, suggesting that these contigs represent temperate phage or degraded prophage. The putative nucleocytoplasmic large DNA viruses and RNA viruses were phylogenetically diverse and showed sequence similarity to viruses associated with a broad range of hosts and environmental sources. The identification of shared viral contigs suggested that, despite the compositional heterogeneity between samples, Sphagnum mosses may harbor a core virome. Future work validating the presence of the core virome is warranted as it may aid in understanding how persistent viruses impact microbiome ecology and symbiont evolution within this climatically relevant keystone species.

Metagenomics↗
DOE OSTI2026

Global Explainability of A Deep Abstaining Classifier for Cancer Pathology Reports

We present a global explainability method to characterize sources of errors in a real-world multitask deep abstaining classifier (DAC), in the context of cancer histology prediction. Our multitask classifier, currently deployed for automated annotation of cancer pathology reports from NCI-SEER registries, was trained and evaluated on 1.04 million hand-annotated samples and makes simultaneous predictions of cancer site, subsite, histology, laterality, and behavior for each report. The DAC framework enables the model to abstain on ambiguous reports and confusing classes to achieve the target accuracy on the retained (non-abstained) samples, but at the cost of decreased coverage. Requiring 97% accuracy on the histology task caused our model to retain only 22% of all samples, mostly the less ambiguous and common classes. Local explainability with the GradInp technique provided a computationally efficient way of obtaining contextual reasoning for hundreds of thousands of individual predictions. Our method, involving dimensionality reduction of approximately 13000 aggregated local explanations (ALE), offers a tractable path to true global explainability. It enabled identification of sources of errors in histology classification, globally, as hierarchical complexity among classes, label noise, insufficient information, and conflicting evidence. This suggests several strategies for iterative improvement of our DAC, including well-designed exclusion criteria, focused annotation, and reduced penalties for errors involving hierarchically related classes.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1994

Optical identification of the supersoft X-ray source 1E 0035.4 in the Small Magellanic Cloud

We report the identification of the optical counterpart of the Small Magellanic Cloud (SMC) super-soft X-ray source 1E0035.4- 7230 with a variable star of the magnitude B = 19.9-20.2 within the 40 arcsecs Einstein error box. The star shows strong UV excess, a hot, blue continuum and weak lines of high ionization. The lines are red-shifted by 3-4 A, indicating SMC membership. This object appears similar to CAL 83 and CAL 87 and is probably a binary system hosting an accreting, hydrogen burning white dwarf.

Orio, M.↗
DOE OSTI2020

Data for training and testing radiation detection algorithms in an urban environment

The detection, identification, and localization of illicit nuclear materials in urban environments is of utmost importance for national security. Most often, the process of performing these operations consists of a team of trained individuals equipped with radiation detection devices that have built-in algorithms to alert the user to the presence nuclear material and, if possible, to identify the type of nuclear material present. To encourage the development of new detection, radioisotope identification, and source localization algorithms, a dataset consisting of realistic Monte Carlo-simulated radiation detection data from a 2 in. × 4 in. × 16 in. NaI(Tl) scintillation detector moving through a simulated urban environment based on Knoxville, Tennessee, was developed and made public in the form of a Topcoder competition. The methodology used to create this dataset has been verified using experimental data collected at the Fort Indiantown Gap National Guard facility. Realistic signals from special nuclear material and industrial and medical sources are included in the data for developing and testing algorithms in a dynamic real-world background.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Narrow-Band Least-Squares Infrasound Array Processing

Infrasound data from arrays can be used to detect, locate, and quantify a variety of natural and anthropogenic sources from local to remote distances. However, many array processing methods use a single broad frequency range to process the data, which can lead to signals of interest being missed due to the choice of frequency limits or simultaneous clutter sources. In this work, we introduce a new open-source Python code that processes infrasound array data in multiple sequential narrow frequency bands using the least-squares approach. We test our algorithm on a few examples of natural sources (volcanic eruptions, mass movements, and bolides) for a variety of array configurations. Our method reduces the need to choose frequency limits for processing, which may result in missed signals, and it is parallelized to decrease the computational burden. Improvements of our narrow-band least-squares algorithm over broad-band least-squares processing include the ability to distinguish between multiple simultaneous sources if distinct in their frequency content (e.g., microbarom or surf vs. volcanic eruption), the ability to track changes in frequency content of a signal through time, and a decreased need to fine-tune frequency limits for processing. We incorporate a measure of planarity of the wavefield across the array (sigma tau, στ) as well as the ability to utilize the robust least trimmed squares algorithm to improve signal processing and insight into array performance. Our implementation allows for more detailed characterization of infrasound signals recorded at arrays that can improve monitoring and enhance research capabilities.

58 GEOSCIENCES↗
DOE OSTI2023

Student Programs Office Overview [Slides]

The Student Programs further the Laboratory’s goal of developing and mentoring the next generation of scientific, technical, and professional staff by supporting 2,000+ interns at all levels (high school, undergraduate, graduate, and postgraduate) along with 2,000+ mentors and 70 division student liaisons. The activities include internship promotion and external engagement, intern identification and sourcing, training and orientation, professional and career development, social and community engagement, and compliance.

99 GENERAL AND MISCELLANEOUS↗