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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Molecular Microbial Analyses of the Mars Exploration Rovers Assembly Facility

During space exploration, the control of terrestrial microbes associated with robotic space vehicles intended to land on extraterrestrial solar system bodies is necessary to prevent forward contamination and maintain scientific integrity during the search for life. Microorganisms associated with the spacecraft assembly environment can be a source of contamination for the spacecraft. In this study, we have monitored the microbial burden of air samples of the Mars Exploration Rovers' assembly facility at the Kennedy Space Center utilizing complementary diagnostic tools. To estimate the microbial burden and identify potential contaminants in the assembly facility, several microbiological techniques were used including culturing, cloning and sequencing of 16S rRNA genes, DNA microarray analysis, and ATP assays to assess viable microorganisms. Culturing severely underestimated types and amounts of contamination since many of the microbes implicated by molecular analyses were not cultivable. In addition to the cultivation of Agrobacterium, Burkholderia and Bacillus species, the cloning approach retrieved 16s rDNA sequences of oligotrophs, symbionts, and y-proteobacteria members. DNA microarray analysis based on rational probe design and dissociation curves complemented existing molecular techniques and produced a highly parallel, high resolution analysis of contaminating microbial populations. For instance, strong hybridization signals to probes targeting the Bacillus species indicated that members of this species were present in the assembly area samples; however, differences in dissociation curves between perfect-match and air sample sequences showed that these samples harbored nucleotide polymorphisms. Vegetative cells of several isolates were resistant when subjected to treatments of UVC (254 nm) and vapor H202 (4 mg/L). This study further validates the significance of non-cultivable microbes in association with spacecraft assembly facilities, as our analyses have identified several non-cultivable microbes likely to contaminate the surfaces of spacecraft hardware.

microbial diversity MER 16S rDNA DNA microarray sp↗
DOE OSTI2021

Microbial diversity analysis of two full-scale seawater desalination treatment trains provides insights into detrimental biofilm formation

Detrimental biofilms on RO membranes remain a crucial challenge for seawater desalination. Comparative analysis of 16S rRNA gene amplicon sequencing data revealed differences and commonalities of biofilm communities associated with unit operations in the two largest seawater desalination facilities in the U.S., the Claude "Bud" Lewis Carlsbad Desalination Plant and the Tampa Bay Seater Desalination facility. At both plants, feedwater collected at a single time point was a poor indicator of the RO membrane communities, which showed far greater taxa diversity. The analysis of prefilter cartridges from the Carlsbad plant revealed similarly high taxon diversity as the RO module biofilms, with relevant differences. Algal sequences were enriched on the prefilter cartridges as were sequences representing Bdellovibrionota, which are predatory bacteria. Sequences representing opportunistic Gammaproteobacteria (i.e., Shewanella, Woesia) were present in significantly higher relative abundance on the RO membranes than in the prefilter cartridges, suggesting growth of certain taxa in the RO modules. Untargeted metabolomics distinguished intra- and inter-desalination plant biofilm samples, highlighting the potential value of this tool for biofilm monitoring. These findings underscore the value of omics tools for effective microbial monitoring, to understand biofouling dynamics within RO desalination plants, and to provide insight for the development of ecologically-informed biofilm control measures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

The draft genome of the C 3 panicoid grass species Dichanthelium oligosanthes

Comparisons between C 3 and C 4 grasses often utilize C 3 species from the subfamilies Ehrhartoideae or Pooideae and C 4 species from the subfamily Panicoideae, two clades that diverged over 50 million years ago. The divergence of the C 3 panicoid grass Dichanthelium oligosanthes from the independent C 4 lineages represented by Setaria viridis and Sorghum bicolor occurred approximately 15 million years ago, which is significantly more recent than members of the Bambusoideae, Ehrhartoideae, and Pooideae subfamilies. D. oligosanthes is ideally placed within the panicoid clade for comparative studies of C 3 and C 4 grasses. Here, we report the assembly of the nuclear and chloroplast genomes of D. oligosanthes , from high-throughput short read sequencing data and a comparative transcriptomics analysis of the developing leaf of D. oligosanthes , S. viridis , and S. bicolor . Physiological and anatomical characterizations verified that D. oligosanthes utilizes the C 3 pathway for carbon fixation and lacks Kranz anatomy. Expression profiles of transcription factors along developing leaves of D. oligosanthes and S. viridis were compared with previously published data from S. bicolor , Zea mays , and Oryza sativa to identify a small suite of transcription factors that likely acquired functions specifically related to C 4 photosynthesis. In conclusion, the phylogenetic location of D. oligosanthes makes it an ideal C 3 plant for comparative analysis of C 4 evolution in the panicoid grasses. This genome will not only provide a better C 3 species for comparisons with C 4 panicoid grasses, but also highlights the power of using high-throughput sequencing to address questions in evolutionary biology.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Dragonfly Mission Entry and Descent Modeling and Simulation Overview

Dragonfly is a New Frontiers Program mission, led by The Johns Hopkins Applied Physics Laboratory, that will deliver a rotorcraft lander to Saturn’s moon, Titan. The focus of this work is to analyze the trajectory of the entry vehicle from cruise stage separation until lander separation. This analysis is done by the NASA Langley Research Center Entry, Descent, and Landing team using the Program to Optimize Trajectories II. This paper provides an overview of the current design and the robustness of the overall entry sequence using a Monte Carlo uncertainty analysis. The work presented in this study includes the updated design, models, and analysis completed since the Dragonfly Entry, Descent, and Landing Mission Preliminary Design Review.

Simulation↗
NASA NTRSDate not supplied

Dragonfly Mission Entry and Descent Modeling and Simulation Overview

Dragonfly is a New Frontiers Program mission, led by The Johns Hopkins Applied Physics Laboratory, that will deliver a rotorcraft lander to Saturn’s moon, Titan. The focus of this work is to analyze the trajectory of the entry vehicle from cruise stage separation until lander separation. This analysis is done by the NASA Langley Research Center Entry, Descent, and Landing team using the Program to Optimize Trajectories II. This paper provides an overview of the current design and the robustness of the overall entry sequence using a Monte Carlo uncertainty analysis. The work presented in this study includes the updated design, models, and analysis completed since the Dragonfly Entry, Descent, and Landing Mission Preliminary Design Review.

Simulation↗
DOE OSTI2020

Platform for efficient large-scale storage and analysis of multi-omics data in plant and microbial systems (Final Technical Report)

Genomic variation at the sequence level fundamentally affects the phenotypic state of all organisms at all stages of development, while dynamic processes such as changes in the epigenome (e.g. DNA methylation state) and transcriptome regulate the specific phenotype expressed at any given state of development based upon that genomic variation. In plants, DNA methylation is a particularly important mechanism for both regulating transcriptomic expression and for management of genomic variations that could be deleterious to the organism due to the presence of active retrotransposons in plant genomes. While DNA methylation is heritable, it is also dynamic through a given plant’s development and life cycle, particularly during the development from seed to mature specimen suggesting variations in DNA methylation could be critical regulators of biologically and commercially important phenotypes such as time to flowering; in addition, plant DNA methylation is more complex than that of animals, with methylation of CHG and CHH trinucleotides evident in addition to the better-known CG methylation. The complexity of plant DNA methylation and its interplay with genomic sequence variation, transcriptomics and other epigenomic factors demand a storage and analysis framework that can cope with the complexity both within a single specimen and with analyses that span many individuals and even many species, such as attempts to extend models from model organisms to commercially relevant species. In addition to complexity, the rapid development and proliferation of sequencing technology has led to an explosion of data volume that conventional storage and analysis solutions will likely be unable to cope with in the long run. We proposed to study these with suitable distributed storage and computation and therefore for the application of cloud computing to biological analyses; integrate with existing data sources and compatible with virtually any interface use case, from fully automated shell scripts to notebooks and do all these at scale in this STTR grant.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2004

A DMAP Program for the Selection of Accelerometer Locations in MSC/NASTRAN

A new program for selecting sensor locations has been written in the DMAP (Direct Matrix Abstraction Program) language of MSC/NASTRAN. The program implements the method of Effective Independence for selecting sensor locations, and is executed within a single NASTRAN analysis as a "rigid format alter" to the normal modes solution sequence (SOL 103). The user of the program is able to choose among various analysis options using Case Control and Bulk Data entries. Algorithms tailored for the placement of both uni-axial and tri- axial accelerometers are available, as well as several options for including the model s mass distribution into the calculations. Target modes for the Effective Independence analysis are selected from the MSC/NASTRAN ASET modes calculated by the "SOL 103" solution sequence. The initial candidate sensor set is also under user control, and is selected from the ASET degrees of freedom. Analysis results are printed to the MSCINASTRAN output file (*.f06), and may include the current candidate sensors set, and their associated Effective Independence distribution, at user specified iteration intervals. At the conclusion of the analysis, the model is reduced to the final sensor set, and frequencies and orthogonality checks are printed. Example results are given for a pre-test analysis of NASA s five-segment solid rocket booster modal test.

Peck, Jeff↗
NASA NTRS1992

A phylogenetic analysis of the myxobacteria: basis for their classification

The primary sequence and secondary structural features of the 16S rRNA were compared for 12 different myxobacteria representing all the known cultivated genera. Analysis of these data show the myxobacteria to form a monophyletic grouping consisting of three distinct families, which lies within the delta subdivision of the purple bacterial phylum. The composition of the families is consistent with differences in cell and spore morphology, cell behavior, and pigment and secondary metabolite production but is not correlated with the morphological complexity of the fruiting bodies. The Nannocystis exedens lineage has evolved at an unusually rapid pace and its rRNA shows numerous primary and secondary structural idiosyncrasies.

Non-NASA Center↗
DOE OSTI2023

FUN-PROSE: A deep learning approach to predict condition-specific gene expression in fungi

mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1991

Dynamics of vegetation and soils of oak/saw palmetto scrub after fire: Observations from permanent transects

Ten permanent 15 m transects previously established in two oak/saw palmetto scrub stands burned in December 1986, while two transects remained unburned. Vegetation in the greater than 0.5 m and the less than 0.5 m layers on these transects was sampled at 6, 12, 18, 24, and 36 months postburn and determined structural features of the vegetation (height, percent bare ground, total cover). The vegetation data were analyzed from each sampling by height layer using detrended correspondence analysis ordination. Vegetation data for the greater than 0.5 m layer for the entire time sequence were combined and analyzed using detrended correspondence analysis ordination. Soils were sampled at 6, 12, 18, and 24 months postburn and analyzed for pH, conductivity, organic matter, exchangeable cations (Ca, Mg, K, Na), NO3-N, NH4-N, Al, available metals (Cu, Fe, Mn, Zn), and PO4-P. Shrub species recovered at different rates postfire with saw palmetto reestablishing cover greater than 0.5 m within one year, but the scrub oaks had not returned to preburn cover greater than 0.5 m in 3 years after the fire. These differences in growth rates resulted in dominance shifts after the fire with saw palmetto increasing relative to the scrub oaks. Overall changes in species richness were minor, although changes occurred in species richness by height layers due to different growth rates. Soils of well drained and poorly drained sites differed markedly. Soil responses to the fire appeared minor. Soil pH increased at 6 and 12 months postfire; calcium increased at 6 months postburn. Nitrate-nitrogen increased at 12 months postburn. Low values of conductivity, PO4-P, Mg, K, Na, and Fe at 12 months postburn may be related to heavy rainfall the preceding month. Seasonal variability in some soil parameters appeared to occur.

Schmalzer, Paul A.↗
NASA NTRS2014

Combustion Stability Characteristics of the Project Morpheus Liquid Oxygen / Liquid Methane Main Engine

The project Morpheus liquid oxygen (LOX) / liquid methane (LCH4) main engine is a Johnson Space Center (JSC) designed ~5,000 lbf-thrust, 4:1 throttling, pressure-fed cryogenic engine using an impinging element injector design. The engine met or exceeded all performance requirements without experiencing any in- ight failures, but the engine exhibited acoustic-coupled combustion instabilities during sea-level ground-based testing. First tangential (1T), rst radial (1R), 1T1R, and higher order modes were triggered by conditions during the Morpheus vehicle derived low chamber pressure startup sequence. The instability was never observed to initiate during mainstage, even at low power levels. Ground-interaction acoustics aggravated the instability in vehicle tests. Analysis of more than 200 hot re tests on the Morpheus vehicle and Stennis Space Center (SSC) test stand showed a relationship between ignition stability and injector/chamber pressure. The instability had the distinct characteristic of initiating at high relative injection pressure drop at low chamber pressure during the start sequence. Data analysis suggests that the two-phase density during engine start results in a high injection velocity, possibly triggering the instabilities predicted by the Hewitt stability curves. Engine ignition instability was successfully mitigated via a higher-chamber pressure start sequence (e.g., ~50% power level vs ~30%) and operational propellant start temperature limits that maintained \cold LOX" and \warm methane" at the engine inlet. The main engine successfully demonstrated 4:1 throttling without chugging during mainstage, but chug instabilities were observed during some engine shutdown sequences at low injector pressure drop, especially during vehicle landing.

Melcher, John C.↗
NASA NTRS1993

Habitable zones around main sequence stars

A mechanism for stabilizing climate on the earth and other earthlike planets is described, and the physical processes that define the inner and outer boundaries of the habitable zone (HZ) around the sun and main sequence stars are discussed. Physical constraints on the HZ obtained from Venus and Mars are taken into account. A 1D climate model is used to estimate the width of the HZ and the continuously habitable zone around the sun, and the analysis is extended to other main sequence stars. Whether other stars have planets and where such planets might be located with respect to the HZ is addressed. The implications of the findings for NASA's SETI project are considered.

Kasting, James F.↗
DOE OSTI2019

Genome Sequencing of Cladobotryum protrusum Provides Insights into the Evolution and Pathogenic Mechanisms of the Cobweb Disease Pathogen on Cultivated Mushroom

Cladobotryum protrusum is one of the mycoparasites that cause cobweb disease on cultivated edible mushrooms. However, the molecular mechanisms of evolution and pathogenesis of C. protrusum on mushrooms are largely unknown. Here, we report a high-quality genome sequence of C. protrusum using the single-molecule, real-time sequencing platform of PacBio and perform a comparative analysis with closely related fungi in the family Hypocreaceae. The C. protrusum genome, the first complete genome to be sequenced in the genus Cladobotryum, is 39.09 Mb long, with an N50 of 4.97 Mb, encoding 11,003 proteins. The phylogenomic analysis confirmed its inclusion in Hypocreaceae, with its evolutionary divergence time estimated to be ~170.1 million years ago. The genome encodes a large and diverse set of genes involved in secreted peptidases, carbohydrate-active enzymes, cytochrome P450 enzymes, pathogen–host interactions, mycotoxins, and pigments. Moreover, C. protrusum harbors arrays of genes with the potential to produce bioactive secondary metabolites and stress response-related proteins that are significant for adaptation to hostile environments. Knowledge of the genome will foster a better understanding of the biology of C. protrusum and mycoparasitism in general, as well as help with the development of effective disease control strategies to minimize economic losses from cobweb disease in cultivated edible mushrooms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Applications and challenges of forensic proteomics

Mass spectrometry-based proteomics has been a useful tool for addressing numerous questions in basic biology research for many years. This success, combined with the maturity of mass spectrometric instrumentation, the ever-increasing availability of protein sequence databases derived from genome sequencing, and the growing sophistication of data analysis methods, places proteomics in a position to have an important role in biological forensics. Because proteins contain information about genotype (sequence) and phenotype (expression levels), proteomics methods can both identify biological samples and characterize the conditions that produced them. In addition to serving as a valuable orthogonal method to genomic analyses, proteomics can be used in cases where nucleic acids are absent, degraded, or uninformative. Mass spectrometry provides both broad applicability and exquisite specificity, often without customized detection reagents like primers or antibodies. This review briefly introduces proteomics methods, and surveys a variety of forensic applications (including criminal justice, historical, archaeological, and national security areas). Finally, challenges and crucial areas for further research are addressed.

forensics, proteomics, mass spectrometry, protein,↗
DOE OSTI2019

The MAVRIC-Shift Sequence in SCALE for Radiation Transport and Shielding Calculations with Automated Variance Reduction and Parallel Computing

A new MAVRIC-Shift sequence has been implemented and tested within the SCALE Code System to provide parallel computing capabilities for radiation transport and shielding analysis with automated variance reduction. This new sequence provides the most widely used capabilities of the MAVRIC sequence and also features the highly scalable Shift Monte Carlo solver, thus enabling faster time-to-solution when run on multiple cores. This report provides a summary of the theory of variance reduction approaches in MAVRIC and the integration of Shift into the MAVRIC sequence of SCALE. Similarities and differences in methodologies between the traditional MAVRIC sequence and the new MAVRIC-Shift sequence are discussed. Validation cases are presented with models of radiation shielding experiments and verification is provided with a series of practical application cases of interest to the US Nuclear Regulatory Commission, the sponsors of this work, including spent nuclear fuel transportation and storage systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1975

A new structural analysis/synthesis capability - ACCESS

The creation of an efficient automated capability for minimum weight design of structures is reported. The ACCESS 1 computer program combines finite element analysis techniques and mathematical programming algorithms using an innovative collection of approximation concepts. Design variable linking, constraint deletion techniques and approximate analysis methods are used to generate a sequence of small explicit mathematical programming problems which retain the essential features of the design problem. Organization of the finite element analysis is carefully matched to the design optimization task. The efficiency of the ACCESS 1 program is demonstrated by giving results for several example problems.

Schmit, L. A.↗
DOE OSTI2021

Five key aspects of metaproteomics as a tool to understand functional interactions in host-associated microbiomes

Host-associated microbial communities (microbiomes) play critical roles in human, animal, and plant health and development. However, interactions between the host, members of the microbiome, and invading pathogens are in most cases still poorly understood. Such interactions are multidimensional and can alter the taxonomic composition and/or the functional metabolic activities of the microbiome in response to disease or treatment conditions. For example, after 2 days of antibiotic treatment, the mouse gut microbiome is altered and more susceptible to invasion by the pathogen Clostridioides difficile. Studies of these multidimensional interactions have been fueled by the ability to use high-throughput sequencing of phylogenetic marker genes to profile microbial community composition and shotgun metagenomics to profile functional potential. However, many protein-coding genes predicted from metagenomes are not necessarily expressed under a given condition, and thus, it is difficult to assess the activities and functional interactions in microbial communities based on DNA sequencing data alone. The physiological and pathological processes expressed in these communities under specific conditions are better reflected by the abundances of transcripts or proteins. In this Pearl, we provide a brief introduction to metaproteomics, which is a tool for the large-scale analysis of proteins in microbiomes that allows researchers to address a diversity of questions related to functions and interactions in microbiomes. The term “metaproteomics” was first used in 2004 for “the large-scale characterization of the entire protein complement of environmental microbiota at a given point in time”, and since then, a large array of metaproteomics approaches have been developed. Our objective in this Pearl is to highlight what we feel are 5 essential elements to be considered for a metaproteomics research campaign and to introduce nonexpert readers to the topic without going into too much technical detail.

59 BASIC BIOLOGICAL SCIENCES↗