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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Phenotypic characterization of xpr, a global regulator of extracellular virulence factors in Staphylococcus aureus

We recently described a Tn551 insertion in the chromosome of Staphylococcus aureus S6C that resulted in drastically reduced expression of extracellular lipase (M. S. Smeltzer, S. R. Gill, and J. J. Iandolo, J. Bacteriol. 174:4000-4006, 1992). The insertion was localized to a chromosomal site (designated omega 1058) distinct from the lipase structural gene (geh) and the accessory gene regulator (agr), both of which were structurally intact in the lipase-negative (Lip-) mutants. In this report, we describe a phenotypic comparison between strains S6C, a hyperproducer of enterotoxin B; KSI9051, a derivative of S6C carrying the Tn551 insertion at omega 1058; ISP546, an 8325-4 strain that carries a Tn551 insertion in the agr locus; and ISP479C, the parent strain of ISP546 cured of the Tn551 delivery plasmid pI258repA36. Compared with their respective parent strains, ISP546 and KSI9051 produced greatly reduced amounts of lipase, alpha-toxin, delta-toxin, protease, and nuclease. KSI9051 also produced reduced amounts of staphylococcal enterotoxin B. Coagulase production was increased in ISP546 but not in KSI9051. Using a mouse model, we also demonstrated that ISP546 and KSI9051 were far less virulent than ISP479C and S6C. We have designated the genetic element defined by the Tn551 insertion at omega 1058 xpr to denote its role as a regulator of extracellular protein synthesis. We conclude that xpr and agr are similar and possibly interactive regulatory genes that play an important role in pathogenesis of staphylococcal disease.

NASA Discipline Cell Biology↗
NASA NTRS1992

Identification of a mouse B-type cyclin which exhibits developmentally regulated expression in the germ line

To begin to examine the function of cyclins in mammalian germ cells, we have screened an adult mouse testis cDNA library for the presence of B-type cyclins. We have isolated cDNAs that encode a murine B-type cyclin, which has been designated cycB1. cycB1 was shown to be expressed in several adult tissues and in the midgestation mouse embryo. In the adult tissues, the highest levels of cycB1 transcripts were seen in the testis and ovary, which contain germ cells at various stages of differentiation. The major transcripts corresponding to cycB1 are 1.7 and 2.5 kb, with the 1.7 kb species being the predominant testicular transcript and the 2.5 kb species more abundant in the ovary. Examination of cDNAs corresponding to the 2.5 kb and 1.7 kb mRNAs revealed that these transcripts encode identical proteins, differing only in the polyadenylation signal used and therefore in the length of their 3' untranslated regions. Northern blot and in situ hybridization analyses revealed that the predominant sites of cycB1 expression in the testis and ovary were in the germinal compartment, particularly in early round spermatids in the testis and growing oocytes in the ovary. Thus cycB1 is expressed in both meiotic and postmeiotic cells. This pattern of cycB1 expression further suggests that cycB1 may have different functions in the two cell types, only one of which correlates with progression of the cell cycle.

NASA Discipline Developmental Biology↗
NASA NTRS2004

Expression of gibberellin 3 beta-hydroxylase gene in a gravi-response mutant, weeping Japanese flowering cherry

Expressions of the gibberellin biosynthesis gene were investigated in a normal upright type and a gravi-response mutant, a weeping type of Japanese flowering cherry (Prunus spachiana), that is unable to support its own weight and elongates downward. A segment of the gibberellin 3 beta-hydroxylase cDNA of Prunus spachiana (Ps3ox), which is responsible for active gibberellin synthesis, was amplified by using real-time RT-PCR. The content of Ps3ox mRNA in the weeping type was much greater than that in the upright type, while the endogenous gibberellin level was much higher in the elongating zone of the weeping type. These results suggest that the amount and distribution of synthesized gibberellin regulate secondary xylem formation, and the unbalanced distribution of gibberellin affects the gravi-response of the Prunus tree.

Gravitropism/physiology↗
NASA NTRS2008

Spectroscopic Confirmation of a Massive Red-sequence Selected Galaxy Cluster at Z=1.34 in the SpARCS-South Cluster Survey

The Spitzer Adaptation of the Red-sequence Cluster Survey (SpARCS) is a z'-passband imaging survey, consisting of deep (z' approx. 24 AB) observations made from both hemispheres using the CFHT 3.6m and CTIO 4m telescopes. The survey was designed with the primary aim of detecting galaxy clusters at z > 1. In tandem with pre-existing 3.6 micron observations from the Spitzer Space Telescope SWIRE Legacy Survey, SpARCS detects clusters using an infrared adaptation of the two-filter red-sequence cluster technique. The total effective area of the SpARCS cluster survey is 41.9 sq deg. In this paper, we provide an overview of the 13.6 sq deg Southern CTIO/MOSAICII observations. The 28.3 sq deg Northern CFHT/MegaCam observations are summarized in a companion paper by Muzzin et al. (2008a). In this paper, we also report spectroscopic confirmation of SpARCS J003550-431224, a very rich galaxy cluster at z = 1.335, discovered in the ELAIS-S1 field. To date, this is the highest spectroscopically confirmed redshift for a galaxy cluster discovered using the red-sequence technique. Based on nine confirmed members, SpARCS J003550-431224 has a preliminary velocity dispersion of 1050+/-230 km/s. With its proven capability for efficient cluster detection, SpARCS is a demonstration that we have entered an era of large, homogeneously-selected z > 1 cluster surveys.

Wilson, Gillian↗
NASA NTRS2010

Seagrass Health Modeling and Prediction with NASA Science Data

Previous research has demonstrated that MODIS data products can be used as inputs into the seagrass productivity model developed by Fong and Harwell (1994). To further explore this use to predict seagrass productivity, Moderate Resolution Imaging Spectroradiometer (MODIS) custom data products, including Sea Surface Temperature, Light Attenuation, and Chlorophyll-a have been created for use as model parameter inputs. Coastal researchers can use these MODIS data products and model results in conjunction with historical and daily assessment of seagrass conditions to assess variables that affect the productivity of the seagrass beds. Current monitoring practices involve manual data collection (typically on a quarterly basis) and the data is often insufficient for evaluating the dynamic events that influence seagrass beds. As part of a NASA-funded research grant, the University of Mississippi, is working with researchers at NASA and Radiance Technologies to develop methods to deliver MODIS derived model output for the northern Gulf of Mexico (GOM) to coastal and environmental managers. The result of the project will be a data portal that provides access to MODIS data products and model results from the past 5 years, that includes an automated process to incorporate new data as it becomes available. All model parameters and final output will be available through the use National Oceanic and Atmospheric Administration?s (NOAA) Environmental Research Divisions Data Access Program (ERDDAP) tools as well as viewable using Thematic Realtime Environmental Distributed Data Services (THREDDS) and the Integrated Data Viewer (IDV). These tools provide the ability to create raster-based time sequences of model output and parameters as well as create graphs of model parameters versus time. This tool will provide researchers and coastal managers the ability to analyze the model inputs so that the factors influencing a change in seagrass productivity can be determined over time.

Robinson, Harold D.↗
NASA NTRS2019

Polarimetric Retrievals of Cloud Droplet Number Concentrations

Cloud droplet number concentration (Nd) is an important parameter of liquid clouds and is crucial to understanding aerosol-cloud interactions. It couples boundary layer aerosol composition, size and concentration with cloud reflectivity. It affects cloud evolution, precipitation, radiative forcing, global climate and, through observation, can be used to partially monitor the first indirect effect. With its unique combination of multi-wavelength, multi-angle, total and polarized reflectance measurements, the Research Scanning Polarimeter (RSP) retrieves Nd with relatively few assumptions. The approach involves measuring cloud optical thickness, mean droplet extinction cross-section and cloud physical thickness. Polarimetric observations are capable of measuring the effective variance, or width, of the droplet size distribution. Estimating cloud geometrical thickness is also an important component of the polarimetric Nd retrieval, which is accomplished using polarimetric measurements in a water vapor absorption band to retrieve the amount of in-cloud water vapor and relating this to physical thickness. We highlight the unique abilities and quantify uncertainties of the polarimetric approach. We validate the approach using observational data from the North Atlantic and Marine Ecosystems Study (NAAMES). NAAMES targets specific phases in the seasonal phytoplankton lifecycle and ocean-atmosphere linkages. This study provides an excellent opportunity for the RSP to evaluate its approach of sensing Nd over a range of concentrations and cloud types with in situ measurements from a Cloud Droplet Probe (CDP). The RSP and CDP, along with an array of other instruments, are flown on the NASA C-130 aircraft, which flies in situ and remote sensing legs in sequence. Cloud base heights retrieved by the RSP compare well with those derived in situ (R=0.83) and by a ceilometer aboard the R.V. Atlantis (R=0.79). Comparing geometric mean values from 12 science flights throughout the NAAMES-1 and NAAMES-2 campaigns, we find a strong correlation between Nd retrieved by the RSP and CDP (R=0.96). A linear least squares fit has a slope of 0.92 and an intercept of 0.3 cm−3. Uncertainty in this comparison can be attributed to cloud 3D effects, nonlinear liquid water profiles, multilayered clouds, measurement uncertainty, variation in spatial and temporal sampling, and assumptions used within the method. Radiometric uncertainties of the RSP measurements lead to biases on derived optical thickness and cloud physical thickness, but these biases largely cancel out when deriving Nd for most conditions and geometries. We find that a polarimetric approach to sensing Nd is viable and the RSP is capable of accurately retrieving Nd for a variety of cloud types and meteorological conditions.

Droplet concentration↗
NASA NTRSDate not supplied

Building a Real-Time Flood Prediction Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the use of applied remote sensing analyses is increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP National Program partnered with the local government of Howard County, Maryland, to investigate the use of machine learning for advanced flood risk detection, and to test the feasibility of integrating this approach into the county’s flood early warning system. To strengthen the efforts of the Howard County Office of Emergency Management (OEM), the project developed a statistical model capable of hindcasting the two severe flash flood events that devastated Ellicott City and transitioned to a ‘Long Short-Term Memory’ based sequence-to-sequence deep learning model with 8-hour forecast capability. The team combined data inputs from public sources including river and precipitation gauges, NASA and NOAA Earth observations, and numerical weather model products using scripts written in the Google Colaboratory Python scripting environment. In addition to designing the deep learning architecture, the team trained and tested the model, and evaluated its performance using Nash-Sutcliffe Efficiency. The final product, the Sequentially Trained Real-time EstimAted Model (STREAM) predicts stage height for the Hudson Branch gauge in Ellicott City using data products available in near real-time, including the High-Resolution Rapid Refresh model’s accumulated precipitation forecasts supplemented by stream gauge data from the OEM and the U.S. Geological Survey. STREAM was incorporated into an online dashboard in a user-friendly interface capable of triggering the alarms that initiate emergency response protocols up to 8 hours in advance of a predicted severe flood event. The project demonstrated the potential for the integration of open data and Earth observations into a flood risk forecasting tool capable of informing near real-time decision making.

NASA DEVELOP↗
NASA NTRSDate not supplied

Building a Real-Time Predictive Flood Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the use of applied remote sensing analyses is increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP National Program partnered with the Howard County government in Maryland to investigate the use of machine learning for advanced flood risk detection, and to test the feasibility of integrating this approach into the county’s flood early warning system. To strengthen the efforts of the Howard County Office of Emergency Management (OEM), the project developed a prediction model capable of hindcasting the two severe flash flood events that devastated Ellicott City, and transitioned to an Long Short-Term Memory (LSTM) based sequence-to-sequence deep learning model with 8-hour forecast capability. The team combined data inputs from public sources including river and precipitation gauges, NASA and NOAA Earth observations, and numerical weather model products using scripts written in the Google Colaboratory Python scripting environment. In addition to designing the deep learning architecture, the team trained and tested the model, and evaluated its performance using the Nash-Sutcliffe Efficiency (NSE). The final product, called the Sequentially Trained Real-time EstimAted Model (STREAM), predicts stage height for the Hudson Branch gauge in Ellicott City using data products available in near real-time, including the High-Resolution Rapid Refresh (HRRR) model’s accumulated precipitation forecasts supplemented by stream gauge data from the OEM and the U.S. Geological Survey. STREAM was incorporated into an online dashboard in a user-friendly interface capable of triggering the alarms that initiate the OEM’s emergency response protocols up to 8 hours in advance of a predicted severe flood event. The project demonstrated the potential for the integration of open data and Earth observations into a flood risk forecasting tool capable of informing near real-time decision making.

Ryan Hammock↗
NASA NTRS2002

Boosting with Averaged Weight Vectors

AdaBoost is a well-known ensemble learning algorithm that constructs its constituent or base models in sequence. A key step in AdaBoost is constructing a distribution over the training examples to create each base model. This distribution, represented as a vector, is constructed to be orthogonal to the vector of mistakes made by the previous base model in the sequence. The idea is to make the next base model's errors uncorrelated with those of the previous model. Some researchers have pointed out the intuition that it is probably better to construct a distribution that is orthogonal to the mistake vectors of all the previous base models, but that this is not always possible. We present an algorithm that attempts to come as close as possible to this goal in an efficient manner. We present experimental results demonstrating significant improvement over AdaBoost and the Totally Corrective boosting algorithm, which also attempts to satisfy this goal.

Oza, Nikunj C.↗
NASA NTRS2004

AveBoost2: Boosting for Noisy Data

AdaBoost is a well-known ensemble learning algorithm that constructs its constituent or base models in sequence. A key step in AdaBoost is constructing a distribution over the training examples to create each base model. This distribution, represented as a vector, is constructed to be orthogonal to the vector of mistakes made by the pre- vious base model in the sequence. The idea is to make the next base model's errors uncorrelated with those of the previous model. In previous work, we developed an algorithm, AveBoost, that constructed distributions orthogonal to the mistake vectors of all the previous models, and then averaged them to create the next base model s distribution. Our experiments demonstrated the superior accuracy of our approach. In this paper, we slightly revise our algorithm to allow us to obtain non-trivial theoretical results: bounds on the training error and generalization error (difference between training and test error). Our averaging process has a regularizing effect which, as expected, leads us to a worse training error bound for our algorithm than for AdaBoost but a superior generalization error bound. For this paper, we experimented with the data that we used in both as originally supplied and with added label noise-a small fraction of the data has its original label changed. Noisy data are notoriously difficult for AdaBoost to learn. Our algorithm's performance improvement over AdaBoost is even greater on the noisy data than the original data.

Oza, Nikunj C.↗
DOE OSTI2026

Depth-resolved sagebrush root metabolomics, rhizosphere microbial communities, and geochemistry at the East River Watershed

This data set consists of results from soil nutrient profile, untargeted metabolomics, mass spec imaging, and amplicon sequencing. Data for soil nutrient profile includes common cations (Ca, Mg, Na, and K etc.) extracted from 3 digesting steps – ammonia acetate (for exchangeable cations), nitric acid (for acid dissolved fraction), and hydrofluoric acid/perchloric acid (HF/HClO4) for whole soil digestion. It also includes concentration of organic carbon, inorganic nitrogen (ammonia and nitrate) and phosphorus (Bray-1 P and nitric acid extract), and total nitrogen and phosphorus. Data for untargeted metabolomics includes metabolomic profile for root exudate/tissues and soil extracts from depths at surface soil to saprolite, that were measured using gas chromatography – mass spectrometry (GC-MS), and liquid chromatography – tandem mass spectrometry (LC-MS/MS). Data for mass spec imaging includes spatial distribution of metabolites that were detected and annotated with Fourier transformation ion cyclotron resonance mass spectrometer (FTICR-MS). Data for amplicon sequencing includes the base paired 16S and ITS ribosomal RNA sequences from Miseq Illumina sequencing. All samples were collected from 2 sampling campaign October 2022 and June 2023. Collectively, these datasets enable a mechanistic evaluation of how nutrient acquisition, especially nitrogen and phosphorus, differs between shallow roots operating in soil and deep roots functioning within the fractured bedrock zone. All files are provided as comma-separated values (CSV) fies (.csv) and (GZIP) file (.gz). The compressed .gz FASTQ files can be read directly in R using the dada2 package as part of the amplicon sequence analysis workflow. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. This research was performed on a project award 60563 (https://dx.doi.org/10.46936/expl.proj.2022.60563/60008727) from the Environmental Molecular Sciences Laboratory, a DOE Office of Science User Facility sponsored by the Biological and Environmental Research program under Contract No. DE-AC05-76RL01830.

EARTH SCIENCE > AGRICULTURE > SOILS > CARBON↗
NASA NTRS1997

A low molecular weight artificial RNA of unique size with multiple probe target regions

Artificial RNAs (aRNAs) containing novel sequence segments embedded in a deletion mutant of Vibrio proteolyticus 5S rRNA have previously been shown to be expressed from a plasmid borne growth rate regulated promoter in E. coli. These aRNAs accumulate to high levels and their detection is a promising tool for studies in molecular microbial ecology and in environmental monitoring. Herein a new construct is described which illustrates the versatility of detection that is possible with aRNAs. This 3xPen aRNA construct carries a 72 nucleotide insert with three copies of a unique 17 base probe target sequence. This aRNA is 160 nucleotides in length and again accumulates to high levels in the E. coli cytoplasm without incorporating into ribosomes. The 3xPen aRNA illustrates two improvements in detection. First, by appropriate selection of insert size, we obtained an aRNA which provides a unique and hence, easily quantifiable peak, on a high resolution gel profile of low molecular weight RNAs. Second, the existence of multiple probe targets results in a nearly commensurate increase in signal when detection is by hybridization. These aRNAs are naturally amplified and carry sequence segments that are not found in known rRNA sequences. It thus may be possible to detect them directly. An experimental step involving RT-PCR or PCR amplification of the gene could therefore be avoided.

Non-NASA Center↗
DOE OSTI2024

Impact of Inverter-Based Resources on Grid Protection: A Review of Negative-Sequence Current Generation

The increasing integration of inverter-based resources (IBRs) in power grids poses challenges to traditional protection systems, primarily due to their different fault current signatures compared to conventional synchronous generators. Unlike synchronous generators whose fault response is dictated by their physical design, IBRs exhibit a wide range of fault characteristics due to manufacturer-specific control algorithms and settings. This dependence on proprietary control schemes makes modeling IBR behavior during faults significantly more complex, especially considering the rapid evolution of inverter technology and the diverse control strategies employed. While much research has focused on the positive-sequence current injections of IBRs during symmetrical faults, the understanding of negative-sequence current generation during non-symmetrical faults remains limited. This report provides an overview of current research on IBRs' negative-sequence current generation during unbalanced faults and its impact on protection schemes based on negative-sequence components. It covers both type III wind turbines and full-size converter-based IBRs. Additionally, this report reviews strategies for grid-forming controlled inverters to generate negative-sequence current during unbalanced faults, in addition to grid-following controlled ones.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1995

DNA CTG triplet repeats involved in dynamic mutations of neurologically related gene sequences form stable duplexes

DNA triplet repeats, 5'-d(CTG)n and 5'-d(CAG)n, are present in genes which have been implicated in several neurodegenerative disorders. To investigate possible stable structures formed by these repeating sequences, we have examined d(CTG)n, d(CAG)n and d(CTG).d(CAG)n (n = 2 and 3) using NMR and UV optical spectroscopy. These studies reveal that single stranded (CTG)n (n > 2) forms stable, antiparallel helical duplexes, while the single stranded (CAG)n requires at least three repeating units to form a duplex. NMR and UV melting experiments show that the Tm increases in the order of [(CAG)3]2 < [(CTG)3]2 << (CAG)3.(CTG)3. The (CTG)3 duplex is stable and exhibits similar NMR spectra in solutions containing 0.1-4 M NaCl and at a pH range from 4.6 to 8.8. The (CTG)3 duplex, which contains multiple-T.T mismatches, displays many NMR spectral characteristics similar to those of B-form DNA. However, unique NOE and 1H-31P coupling patterns associated with the repetitive T.T mismatches in the CTG repeats are discerned. These results, in conjunction with recent in vitro studies suggest that longer CTG repeats may form hairpin structures, which can potentially cause interruption in replication, leading to dynamic expansion or deletion of triplet repeats.

NASA Discipline Exobiology↗
NASA NTRS1995

Partial gene sequences for the A subunit of methyl-coenzyme M reductase (mcrI) as a phylogenetic tool for the family Methanosarcinaceae

Representatives of the family Methanosarcinaceae were analyzed phylogenetically by comparing partial sequences of their methyl-coenzyme M reductase (mcrI) genes. A 490-bp fragment from the A subunit of the gene was selected, amplified by the PCR, cloned, and sequenced for each of 25 strains belonging to the Methanosarcinaceae. The sequences obtained were aligned with the corresponding portions of five previously published sequences, and all of the sequences were compared to determine phylogenetic distances by Fitch distance matrix methods. We prepared analogous trees based on 16S rRNA sequences; these trees corresponded closely to the mcrI trees, although the mcrI sequences of pairs of organisms had 3.01 +/- 0.541 times more changes than the respective pairs of 16S rRNA sequences, suggesting that the mcrI fragment evolved about three times more rapidly than the 16S rRNA gene. The qualitative similarity of the mcrI and 16S rRNA trees suggests that transfer of genetic information between dissimilar organisms has not significantly affected these sequences, although we found inconsistencies between some mcrI distances that we measured and and previously published DNA reassociation data. It is unlikely that multiple mcrI isogenes were present in the organisms that we examined, because we found no major discrepancies in multiple determinations of mcrI sequences from the same organism. Our primers for the PCR also match analogous sites in the previously published mcrII sequences, but all of the sequences that we obtained from members of the Methanosarcinaceae were more closely related to mcrI sequences than to mcrII sequences, suggesting that members of the Methanosarcinaceae do not have distinct mcrII genes.

NASA Discipline Number 52-30↗
NASA NTRS1992

A detailed phylogeny for the Methanomicrobiales

The small subunit rRNA sequence of twenty archaea, members of the Methanomicrobiales, permits a detailed phylogenetic tree to be inferred for the group. The tree confirms earlier studies, based on far fewer sequences, in showing the group to be divided into two major clusters, temporarily designated the "methanosarcina" group and the "methanogenium" group. The tree also defines phylogenetic relationships within these two groups, which in some cases do not agree with the phylogenetic relationships implied by current taxonomic names--a problem most acute for the genus Methanogenium and its relatives. The present phylogenetic characterization provides the basis for a consistent taxonomic restructuring of this major methanogenic taxon.

NASA Discipline Number 52-30↗
NASA NTRS2000

Phylogeny of marine Bacillus isolates from the Gulf of Mexico

The phylogeny of 11 pigmented, aerobic, spore-forming isolates from marine sources was studied. Forty-two biochemical characteristics were examined, and a 16S rDNA sequence was obtained for each isolate. In a phylogenetic tree based on 16S sequencing, four isolates (NRRL B-14850, NRRL B-14904, NRRL B-14907, and NRRL B-14908) clustered with B. subtilis and related organisms; NRRL B-14907 was closely related to B. amyloliquefaciens. NRRL B-14907 and NRRL B-14908 were phenotypically similar to B. amyloliquefaciens and B. pumilus, respectively. Three strains (NRRL B-14906, NRRL B-14910, and NRRL B-14911) clustered in a clade that included B. firmus, B. lentus, and B. megaterium. NRRL B-14910 was closely related phenotypically and phylogenetically to B. megaterium. NRRL B-14905 clustered with the mesophilic round spore-producing species, B. fusiformis and B. sphaericus; the isolate was more closely related to B. fusiformis. NRRL B-14905 displayed characteristics typical of the B. sphaericus-like organisms. NRRL B-14909 and NRRL B-14912 clustered with the Paenibacillus species and displayed characteristics typical of the genus. Only NRRL B-14851, an unusually thin rod that forms very small spores, may represent a new Bacillus species.

NASA Discipline Exobiology↗