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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

A Simplified Approach to Cloud Masking with VIIRS in the S-NPP/JPSS Era

The quantitative detection of clouds in satellite imagery has a number of important applications in weather analysis. The proper interpretation of satellite imagery for improved situational awareness depends on knowing where the clouds are at all times of the day. Additionally, many products derived from infrared measurements need accurate cloud information to mask out regions where retrieval of geophysical parameters in the atmosphere or on the surface are not possible. Thus, the accurate detection of the presence of clouds in satellite imagery on a global basis is important to the product developers and the operational weather community to support their decision‐making process. This abstract describes an application of a two‐channel bispectral composite threshold (BCT) approach applied to VIIRS imagery. The simplified BCT approach uses only the 10.76 and 3.75 micrometer spectral channels in two spectral tests; a straightforward infrared threshold test with the longwave channel and a shortwave minus longwave channel difference test. The key to the success of this approach as demonstrated in past applications to GOES and MODIS data is the generation of temporally and spatially dependent thresholds used in the tests from a previous number of days at similar observations to the current data. The presentation will present an overview of the approach and intercomparison results with other satellites, methods, and against verification data.

Jedlovec, Gary J.↗
NASA NTRSDate not supplied

Graph Convolutional Network-Strengthened Topic Modeling for Scientific Papers

Machine learning has been woven into statistics to modernize topic modeling over textual documents written in natural language, and scientific paper search and recommendation can consequently offer higher accuracy instead of counting on traditional keyword-based search. However, topic distribution of a paper resulted from existing topic modeling techniques only relies on the statistics of words contained in the paper itself. We argue that community users’ views of a paper may also provide insights at the time of recommendation. For example, if a paper on fake image detection has been cited heavily by machine learning papers, such a feature should be absorbed in the embedding of this paper, so that it can be recommended for future query on machine learning. In this paper, we present a Graph Convolutional Network-strengthened Topic Modeling (GCN-TM) method, which employs GCN technique to refine topic modeling of scientific papers. A citation-oriented knowledge graph is constructed, and topic modeling is mapped to feature embedding of the comprising papers. On top of its own topics carried in its content, each paper learns topics from its neighbors and revise its embedding accordingly. Our empirical studies over real-life scientific literature has proved the necessity and effectiveness of our proposed approach.

Jia Zhang↗
NASA NTRS2001

Ectomycorrhizal fungal associates of Pinus contorta in soils associated with a hot spring in Norris Geyser Basin, Yellowstone National Park, Wyoming

Molecular methods and comparisons of fruiting patterns (i.e., presence or absence of fungal fruiting bodies in different soil types) were used to determine ectomycorrhizal (EM) associates of Pinus contorta in soils associated with a thermal soil classified as ultra-acidic to extremely acidic (pH 2 to 4). EM were sampled by obtaining 36 soil cores from six paired plots (three cores each) of both thermal soils and forest soils directly adjacent to the thermal area. Fruiting bodies (mushrooms) were collected for molecular identification and to compare fruiting body (above-ground) diversity to below-ground diversity. Our results indicate (i) that there were significant decreases in both the level of EM infection (130 +/- 22 EM root tips/core in forest soil; 68 +/- 22 EM root tips/core in thermal soil) and EM fungal species richness (4.0 +/- 0.5 species/core in forest soil; 1.2 +/- 0.2 species/core in thermal soil) in soils associated with the thermal feature; (ii) that the EM mycota of thermal soils was comprised of a small set of dominant species and included very few rare species, while the EM mycota of forest soils contained a few dominant species and several rare EM fungal species; (iii) that Dermocybe phoenecius and a species of Inocybe, which was rare in forest soils, were the dominant EM fungal species in thermal soils; (iv) that other than the single Inocybe species, there was no overlap in the EM fungal communities of the forest and thermal soils; and (v) that the fungal species forming the majority of the above-ground fruiting structures in thermal soils (Pisolithus tinctorius, which is commonly used in remediation of acid soils) was not detected on a single EM root tip in either type of soil. Thus, P. tinctorius may have a different role in these thermal soils. Our results suggest that this species may not perform well in remediation of all acid soils and that factors such as pH, soil temperature, and soil chemistry may interact to influence EM fungal community structure. In addition, we identified at least one new species with potential for use in remediation of hot acidic soil.

Pinus/microbiology↗
DOE OSTI2023

Performance of methods for SARS-CoV-2 variant detection and abundance estimation within mixed population samples

The accurate identification of SARS-CoV-2 (SC2) variants and estimation of their abundance in mixed population samples (e.g., air or wastewater) is imperative for successful surveillance of community level trends. Assessing the performance of SC2 variant composition estimators (VCEs) should improve our confidence in public health decision making. Here, we introduce a linear regression based VCE and compare its performance to four other VCEs: two re-purposed DNA sequence read classifiers (Kallisto and Kraken2), a maximum-likelihood based method (Lineage deComposition for Sars-Cov-2 pooled samples (LCS)), and a regression based method (Freyja). We simulated DNA sequence datasets of known variant composition from both Illumina and Oxford Nanopore Technologies (ONT) platforms and assessed the performance of each VCE. We also evaluated VCEs performance using publicly available empirical wastewater samples collected for SC2 surveillance efforts. Bioinformatic analyses were performed with a custom NextFlow workflow (C-WAP, CFSAN Wastewater Analysis Pipeline). Relative root mean squared error (RRMSE) was used as a measure of performance with respect to the known abundance and concordance correlation coefficient (CCC) was used to measure agreement between pairs of estimators. Based on our results from simulated data, Kallisto was the most accurate estimator as it had the lowest RRMSE, followed by Freyja. Kallisto and Freyja had the most similar predictions, reflected by the highest CCC metrics. We also found that accuracy was platform and amplicon panel dependent. For example, the accuracy of Freyja was significantly higher with Illumina data compared to ONT data; performance of Kallisto was best with ARTICv4. However, when analyzing empirical data there was poor agreement among methods and variations in the number of variants detected (e.g., Freyja ARTICv4 had a mean of 2.2 variants while Kallisto ARTICv4 had a mean of 10.1 variants). This work provides an understanding of the differences in performance of a number of VCEs and how accurate they are in capturing the relative abundance of SC2 variants within a mixed sample (e.g., wastewater). Such information should help officials gauge the confidence they can have in such data for informing public health decisions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Computer-aided Abnormality Detection in Chest Radiographs in a Clinical Setting via Domain-adaptation

Deep learning (DL) models are being deployed at medical centers to aid radiologists for diagnosis of lung conditions from chest radiographs. Such models are often trained on a large volume of publicly available labeled radiographs. These pre-trained DL models’ ability to generalize in clinical settings is poor because of the changes in data distributions between publicly available and privately held radiographs. In chest radiographs, the heterogeneity in distributions arises from the diverse conditions in X-ray equipment and their configurations used for generating the images. In the machine learning community, the challenges posed by the heterogeneity in the data generation source is known as domain shift, which is a mode shift in the generative model. In this work, we introduce a domain-shift detection and removal method to overcome this problem. Our experimental results show the proposed method’s effectiveness in deploying a pre-trained DL model for abnormality detection in chest radiographs in a clinical setting.

Dubey, Abhishek↗
NASA NTRS1998

Rapid System to Quantitatively Characterize the Airborne Microbial Community

Bioaerosols have been linked to a wide range of different allergies and respiratory illnesses. Currently, microorganism culture is the most commonly used method for exposure assessment. Such culture techniques, however, generally fail to detect between 90-99% of the actual viable biomass. Consequently, an unbiased technique for detecting airborne microorganisms is essential. In this Phase II proposal, a portable air sampling device his been developed for the collection of airborne microbial biomass from indoor (and outdoor) environments. Methods were evaluated for extracting and identifying lipids that provide information on indoor air microbial biomass, and automation of these procedures was investigated. Also, techniques to automate the extraction of DNA were explored.

Macnaughton, Sarah J.↗
NASA NTRS2012

Using Total Lightning Observations to Enhance Lightning Safety

Lightning is often the underrated threat faced by the public when it comes to dangerous weather phenomena. Typically, larger scale events such as floods, hurricanes, and tornadoes receive the vast majority of attention by both the general population and the media. This comes from the fact that these phenomena are large, longer lasting, can impact a large swath of society at one time, and are dangerous events. The threat of lightning is far more isolated on a case by case basis, although millions of cloud-to-ground lightning strikes hit this United States each year. While attention is given to larger meteorological events, lightning is the second leading cause of weather related deaths in the United States. This information raises the question of what steps can be taken to improve lightning safety. Already, the meteorological community s understanding of lightning has increased over the last 20 years. Lightning safety is now better addressed with the National Weather Service s access to the National Lightning Detection Network data and enhanced wording in their severe weather warnings. Also, local groups and organizations are working to improve public awareness of lightning safety with easy phrases to remember, such as "When Thunder Roars, Go Indoors." The impacts can be seen in the greater array of contingency plans, from airports to sports stadiums, addressing the threat of lightning. Improvements can still be made and newer technologies may offer new tools as we look towards the future. One of these tools is a network of sensors called a lightning mapping array (LMA). Several of these networks exist across the United States. NASA s Short-term Prediction Research and Transition Center (SPoRT), part of the Marshall Spaceflight Center, has access to three of these networks from Huntsville, Alabama, the Kennedy Space Center, and Washington D.C. The SPoRT program s mission is to help transition unique products and observations into the operational forecast environment. SPoRT has been collaborating with the Huntsville National Weather Service (NWS) Office since 2003 and has since included several other offices to better implement LMA observations into real-time applications. Much of that work has focused on the LMA s ability to detect intra-cloud lightning in addition to cloud-to-ground lightning strikes. Combined, these observations are called total lightning. With total lightning observations, NWS offices can enhance their situational awareness and improve severe weather warnings. Just as importantly, the observed intra-cloud flashes often precede the first cloud-to-ground strike by a few minutes. SPoRT and its partner NWS offices are working to develop visualizations and applications to better utilize these data. However, there is a drawback. The LMAs have a short range of no more than 200 km. This is being addressed with the next generation geostationary satellite, GOES-R, which will boast the Geostationary Lightning Mapper (GLM). SPoRT, in conjunction with NOAA s GOES-R Proving Ground, is working to prepare the end user community for the GLM era using the LMA observations as a demonstration tool. Working collaboratively with our NWS partners, SPoRT is working to determine how best to integrate these future observations to improve both severe storm warnings and lightning safety.

Stano, Geoffrey T.↗
DOE OSTI2020

Optical follow-up of gravitational wave triggers with DECam during the first two LIGO/VIRGO observing runs

Gravitational wave (GW) events detectable by LIGO and Virgo have several possible progenitors, including black hole mergers, neutron star mergers, black hole–neutron star mergers, supernovae, and cosmic string cusps. A subset of GW events is expected to produce electromagnetic (EM) emission that, once detected, will provide complementary information about their astrophysical context. To that end, the LIGO–Virgo Collaboration (LVC) sends GW candidate alerts to the astronomical community so that searches for their EM counterparts can be pursued. The DESGW group, consisting of members of the Dark Energy Survey (DES), the LVC, and other members of the astronomical community, uses the Dark Energy Camera (DECam) to perform a search and discovery program for optical signatures of LVC GW events. DESGW aims to use a sample of GW events as standard sirens for cosmology. Due to the short decay timescale of the expected EM counterparts and the need to quickly eliminate survey areas with no counterpart candidates, it is critical to complete the initial analysis of each night’s images as quickly as possible. We discuss our search area determination, imaging pipeline, and candidate selection processes. We review results from the DESGW program during the first two LIGO–Virgo observing campaigns and introduce other science applications that our pipeline enables.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

NREL Hydrogen Sensor Testing Laboratory

Relevance: Detection is recognized as a critical element for hydrogen facility safety design and supports risk mitigation. Detection methodologies will support validation of H2 behavior research. Hydrogen point sensors play a critical role for safety and process monitoring, but other methodologies can be developed. Approach: NREL Sensor Laboratory tests and verifies sensor performance for manufacturers, developers, end-users, regulatory agencies and SDOs/CDOs NREL deployment activity supports regulatory requirement verification, hydrogen behavior models, and method development for use by stakeholders. Accomplishments and Progress: NREL's R&D accomplishments have supported developers, industry, and SDOs by providing sensor performance and deployment expertise not otherwise available. Development of alternative detection strategies for hydrogen applications have been initiated. HyWAM and advanced detection methodologies deployments at H2@Scale Facilities are being implemented. Collaborations: Collaboration with government laboratories, universities, private organizations and regulatory agencies has leveraged the NREL Sensor Laboratory's success in advancing hydrogen safety sensors and process control. Proposed Future Work: NREL will support hydrogen deployment by the proper implementation of hydrogen sensors and advanced detection strategies. NREL will continue to support science-based codes and standards. This effort will be guided by the needs of the hydrogen community.

codes and standards↗
DOE OSTI2023

Elucidating the Formation of Ethynylbutatrienylidene (HCCCHCCC; X 1 A′) in the Taurus Molecular Cloud (TMC-1) via the Gas-phase Reaction of Tricarbon (C 3 ) with the Propargyl Radical (C 3 H 3 )

Abstract The recent astronomical detection of ethynylbutatrienylidene (HCCCHCCC)—a high-energy isomer of triacetylene (HCCCCCCH) and hexapentaenylidene (H 2 CCCCCC)—in TMC-1 puzzled the laboratory astrophysics community since proposed reaction pathways could not synthesize the ethynylbutatrienylidene (HCCCHCCC) under cold molecular cloud conditions. Exploiting a retrosynthesis coupled with electronic structure calculations and astrochemical modeling, we reveal that observed fractional abundance of ethynylbutatrienylidene (HCCCHCCC) of 1.3 ± 0.2 × 10 −11 can be quantitatively replicated though the barrierless and exoergic reaction of tricarbon (C 3 ) with the resonantly stabilized propargyl radical (C 3 H 3 ) after a few 10 5 yr—typical ages of cold molecular clouds. Our study provides persuasive evidence that previously assumed “dead” reactants such as tricarbon (C 3 ) and the propargyl radical (C 3 H 3 ) provide fundamental molecular building blocks in molecular mass growth processes leading to exotic, high-energy isomers of hydrocarbons: ethynylbutatrienylidene (HCCCHCCC).

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1985

Evaluation of Thematic Mapper Performance as Applied to Hydrocarbon Exploration

The role data from the first three LANDSAT satellites have in geologic exploration and their current level of acceptance is reviewed and the advantages of LANDSAT 4 TM data over MSS data are discussed. Specially enhanced Thematic Mapper imager can make a very significant contribution to the oil and gas and mineral exploration industries. The TM's increased spatial resolution enables the production of larger scale imagery, which greatly increases the amount of geomorphic and structural information interpretable. TM's greater spectral resolution, combined with the smaller, more homogeneous pixels, should enable a far greater confidence in mapping lithologies and detecting geobotanical anomalies from space. The results from its applications to hydrocarbon and mineral exploration promise to bring the majority of the geologic exploration community into that final stage of acceptance and routine application of the satellite data.

Everett, J. R.↗
NASA NTRS1988

Geological and vegetational applications of Shuttle Imaging Radar-B, Mineral County, Nevada

Multiple-incidence angle and multi-azimuth radar data were acquired from a Shuttle platform over test sites in Nevada in October 1984. An attempt was made to correlate these data with ground features for the purpose of evaluating the use of such data for geological and vegetational assessment. Standard ecological parameters with respect to the flora (community composition, dominance, and relative cover) were recorded in the field at the time of overflight. Although a total of 33 species representing 11 plant families were recognized, and plant cover ranged from 13 to 26 percent, radar data could not be used to separate plant communities. The signal return is more a function of abiotic conditions than vegetative characteristics. Illumination geometry plays an important role in the ability to detect strike-slip and dip-slip faults. Local incidence angle is the most important parameter, and SIR-B data takes with small incidence angles are superior for identifying certain styles of faulting. Look direction is critical for detecting faults with a dip-slip component. New structural features were not observed. Problems with radar antenna power and recording significantly affected data quality.

Borengasser, M. X.↗
NASA NTRS1987

Research in Natural Laminar Flow and Laminar-Flow Control, part 1

Since the mid 1970's, NASA, industry, and universities have worked together to conduct important research focused at developing laminar flow technology that could reduce fuel consumption for general aviation, commuter, and transport aircraft by as much as 40 to 50 percent. The symposium was planned in view of the recent accomplishments within the areas of laminar flow control and natural laminar flow, and the potential benefits of laminar flow technology to the civil and military aircraft communities in the United States. Included were technical sessions on advanced theory and design tool development; wind tunnel and flight research; transition measurement and detection techniques; low and high Reynolds number research; and subsonic and supersonic research.

Hefner, Jerry N.↗
NASA NTRS2020

Corrigendum to: Volatiles in Lunar Felsite Clasts: Impact-related Delivery of Hydrous Material to an Ancient Dry Lunar Crust

Hydrous components were measured in nominally anhydrous minerals, primarily lunar feldspar, and reported by Simon et al. (2020). In the feldspar mineral structure, these components are contained in the form of OH, H2O, and/or NH4+molecules (Johnson, 2006 and references therein). The advantages of the ion microprobe technique employed by Simon et al. (2020) include high spatial resolution, apparent insensitivity to crystal orientation, high precision, and low detection limits, but unlike complementary spectroscopy techniques (i.e., FTIR) they preclude assignment of molecular species(Mosenfelder et al. 2015). Convention in the lunar sample community is to report major elemental abundances and hydrogen as oxides, H2O is the oxide for H. This convention was not followed by Simon et al. (2020), but rather the measured hydrogen component was reported as H to avoid the appearance of assigning the measured hydrogen concentration to a specific molecular species. The speciation of the hydrous component in terrestrial feldspars varies predominantly between OH and H2O, with no apparent correlation to feldspar composition, and only slight correlation to volcanic-to-plutonic igneous rock type (Johnson and Rossman, 2004).

J. I. Simon↗
NASA NTRS2022

Mapping invasive alien species in grassland ecosystems using airborne imaging spectroscopy and remotely observable vegetation functional traits

Lespedeza cuneata (sericea lespedeza; hereafter “sericea”) is an invasive species brought to the U.S. from East Asia in the 1890s to be used as forage. However, it has now become a growing ecological and economic threat in grasslands of several states in the U.S. southern Great Plains including Oklahoma, Kansas, Missouri, and Nebraska. Here, we demonstrate the capability of airborne imaging spectroscopy to map sericea in a large natural grassland within the Tallgrass Prairie Preserve, the largest protected tallgrass prairie in the world, located in northeastern Oklahoma. Through this research, we investigated which remotely observable vegetation functional traits (referring to biochemical, physiological, and structural traits) contribute to distinguishing sericea from cooccurring native species and whether we can detect sericea remotely through quantifying these functional traits using imaging spectroscopic data (also known as hyperspectral data). To achieve these objectives, full-range airborne hyperspectral data with spatial resolution of 1 m were collected from the study area in August 2020. In addition, a total of 12 vegetation functional traits were measured through field sampling for model development. We first identified functional traits that contributed to separating sericea from other species, and then used them in a classification model to detect sericea in our study site. We found total carotenoids (sum of neoxanthin, violaxanthin, antheraxanthin, zeaxanthin, and lutein), chlorophyll a + b (sum of chlorophyll a and chlorophyll b), total nitrogen, canopy height, potassium, and magnesium as the main functional traits contributing to the detection of sericea; an overall classification accuracy of approximately 94% was reported. However, the proposed approach overestimated sericea cover in species-rich plant communities. Overall, our findings demonstrated an essential role for airborne remote sensing in 1) direct mapping of invasive plants and 2) quantifying functional traits associated with success strategies of invasive species. Eventually, experiments like ours can aid in developing large-scale and science-driven management practices to both identify the current extent, and to control the spread of invasive species in grasslands and similar short-stature environments. This will not only improve management practices but will have major societal and economic benefits.

Hamed Gholizadeh↗
DOE OSTI2023

Forward Physics Facility

High-energy collisions at the High-Luminosity Large Hadron Collider will produce a large number of particles along the beam collision axis, outside of the acceptance of existing LHC experiments. The proposed Forward Physics Facility (FPF), to be located 617--682 meters from the ATLAS interaction point along the beam collision axis and shielded by concrete and rock, will host a suite of experiments to probe Standard Model processes and search for physics beyond the Standard Model. The FPF is supported by a rapidly growing user community of 400 physicists, and four pathfinder detectors that are currently operating at the LHC have already yielded promising results, including the first direct detection of collider neutrinos. Here we provide an Executive Summary, and then briefly summarize the status of the FPF, including its rich science case, the facility itself, the proposed FPF experiments and their technical readiness, the preliminary schedule and budget profile, and plans for international participation. Submitted to the DOE/NSF HEPAP Particle Physics Projects Prioritization Panel~(P5)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Microbial reduction of low-crystallinity tripuhyite (FeSbO 4 ): Implications for Sb(V) cycling in contaminated environments

Tripuhyite (FeSbO 4 ) is an important antimony (Sb)-bearing mineral that controls Sb mobility in contaminated environments, yet its structural stability during microbial reduction remains unresolved. Understanding how FeSbO 4 behaves under anoxic conditions is therefore necessary to predict natural Sb cycling. Here, this study examined how an anaerobic microbial community interacts with FeSbO 4 and alters its structural and redox behavior. Across all conditions, FeSbO 4 released measurable Sb(V), demonstrating that the mineral undergoes partial dissolution in anoxic environment even without microbial activity. However, when extensive microbial Fe(III) reduction occurred in the presence of the electron shuttle anthraquinone-2,6-disulfonate (AQDS), the released Sb was re-immobilized. This indicates that microbial reduction processes modulate Sb mobility. Microbial community analysis showed the enrichment of acetate-utilizing Fe(III)-reducing bacteria as key drivers of Fe reduction. Although secondary Fe minerals were not detected, X-ray absorption fine structure measurements and scanning electron microscopy images revealed the formation of an Sb(III)-bearing phase consistent with valentinite (Sb 2 O 3 ) in the AQDS-amended treatment. This transformation suggests that AQDS not only enhances Fe(III) reduction but is also linked to Sb(V) reduction, and facilitates the immobilization of reduced Sb(III) as Sb 2 O 3 . Overall, this work provides the first evidence that FeSbO 4 is susceptible to microbially mediated redox transformations, and that these processes can significantly alter the mobility and speciation of Sb in reducing environments.

Electron transfer mediator↗
DOE OSTI2021

Gulf of Mexico blue hole harbors high levels of novel microbial lineages

Exploration of oxygen-depleted marine environments has consistently revealed novel microbial taxa and metabolic capabilities that expand our understanding of microbial evolution and ecology. Marine blue holes are shallow karst formations characterized by low oxygen and high organic matter content. They are logistically challenging to sample, and thus our understanding of their biogeochemistry and microbial ecology is limited. We present a metagenomic and geochemical characterization of Amberjack Hole on the Florida continental shelf (Gulf of Mexico). Dissolved oxygen became depleted at the hole’s rim (32 m water depth), remained low but detectable in an intermediate hypoxic zone (40–75 m), and then increased to a secondary peak before falling below detection in the bottom layer (80–110 m), concomitant with increases in nutrients, dissolved iron, and a series of sequentially more reduced sulfur species. Microbial communities in the bottom layer contained heretofore undocumented levels of the recently discovered phylum Woesearchaeota (up to 58% of the community), along with lineages in the bacterial Candidate Phyla Radiation (CPR). Thirty-one high-quality metagenome-assembled genomes (MAGs) showed extensive biochemical capabilities for sulfur and nitrogen cycling, as well as for resisting and respiring arsenic. One uncharacterized gene associated with a CPR lineage differentiated hypoxic from anoxic zone communities. Overall, microbial communities and geochemical profiles were stable across two sampling dates in the spring and fall of 2019. The blue hole habitat is a natural marine laboratory that provides opportunities for sampling taxa with under-characterized but potentially important roles in redox-stratified microbial processes.

59 BASIC BIOLOGICAL SCIENCES↗