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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Implied alignment: a synapomorphy-based multiple-sequence alignment method and its use in cladogram search

A method to align sequence data based on parsimonious synapomorphy schemes generated by direct optimization (DO; earlier termed optimization alignment) is proposed. DO directly diagnoses sequence data on cladograms without an intervening multiple-alignment step, thereby creating topology-specific, dynamic homology statements. Hence, no multiple-alignment is required to generate cladograms. Unlike general and globally optimal multiple-alignment procedures, the method described here, implied alignment (IA), takes these dynamic homologies and traces them back through a single cladogram, linking the unaligned sequence positions in the terminal taxa via DO transformation series. These "lines of correspondence" link ancestor-descendent states and, when displayed as linearly arrayed columns without hypothetical ancestors, are largely indistinguishable from standard multiple alignment. Since this method is based on synapomorphy, the treatment of certain classes of insertion-deletion (indel) events may be different from that of other alignment procedures. As with all alignment methods, results are dependent on parameter assumptions such as indel cost and transversion:transition ratios. Such an IA could be used as a basis for phylogenetic search, but this would be questionable since the homologies derived from the implied alignment depend on its natal cladogram and any variance, between DO and IA + Search, due to heuristic approach. The utility of this procedure in heuristic cladogram searches using DO and the improvement of heuristic cladogram cost calculations are discussed. c2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.

Non-NASA Center↗
DOE OSTI2024

A General Materials Data Science Framework for Quantitative 2D Analysis of Particle Growth from Image Sequences

Abstract Phase transformations are a challenging problem in materials science, which lead to changes in properties and may impact performance of material systems in various applications. We introduce a general framework for the analysis of particle growth kinetics by utilizing concepts from machine learning and graph theory. As a model system, we use image sequences of atomic force microscopy showing the crystallization of an amorphous fluoroelastomer film. To identify crystalline particles in an amorphous matrix and track the temporal evolution of the particle dispersion, we have developed quantitative methods of 2D analysis. 700 image sequences were analyzed using a neural network architecture, achieving 0.97 pixel-wise classification accuracy as a measure of the correctly classified pixels. The growth kinetics of isolated and impinged particles were tracked throughout time using these image sequences. The relationship between image sequences and spatiotemporal graph representations was explored to identify the proximity of crystallites from each other. The framework enables the analysis of all image sequences without the requirement of sampling for specific particles or timesteps for various materials systems.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Generalized Levy-walk model for DNA nucleotide sequences

We propose a generalized Levy walk to model fractal landscapes observed in noncoding DNA sequences. We find that this model provides a very close approximation to the empirical data and explains a number of statistical properties of genomic DNA sequences such as the distribution of strand-biased regions (those with an excess of one type of nucleotide) as well as local changes in the slope of the correlation exponent alpha. The generalized Levy-walk model simultaneously accounts for the long-range correlations in noncoding DNA sequences and for the apparently paradoxical finding of long subregions of biased random walks (length lj) within these correlated sequences. In the generalized Levy-walk model, the lj are chosen from a power-law distribution P(lj) varies as lj(-mu). The correlation exponent alpha is related to mu through alpha = 2-mu/2 if 2 < mu < 3. The model is consistent with the finding of "repetitive elements" of variable length interspersed within noncoding DNA.

NASA Discipline Number 14-10↗
NASA NTRS1989

A NASTRAN DMAP alter for linear buckling analysis under dynamic loading

A modification to the NASTRAN solution sequence for transient analysis with direct time integration (COSMIC NASTRAN rigid format 9) was developed and incorporated into a DMAP alter. This DMAP alter calculates the buckling stability of a dynamically loaded structure, and is used to predict the onset of structural buckling under stress-wave loading conditions. The modified solution sequence incorporates the linear buckling analysis capability (rigid format 5) of NASTRAN into the existing Transient solution rigid format in such a way as to provide a time dependent eigensolution which is used to assess the buckling stability of the structure as it responds to the impulsive load. As a demonstration of the validity of this modified solution procedure, the dynamic buckling of a prismatic bar subjected to an impulsive longitudinal compression is analyzed and compared to the known theoretical solution. In addition, a dynamic buckling analysis is performed for the analytically less tractable problem of the localized dynamic buckling of an initially flawed composite laminate under transverse impact loading. The addition of this DMAP alter to the transient solution sequence in NASTRAN facilitates the computational prediction of both the time at which the onset of dynamic buckling occurs in an impulsively loaded structure, and the dynamic buckling mode shapes of that structure.

Aiello, Robert A.↗
DOE OSTI2014

Recruiting Human Microbiome Shotgun Data to Site-Specific Reference Genomes

The human body consists of innumerable multifaceted environments that predispose colonization by a number of distinct microbial communities, which play fundamental roles in human health and disease. In addition to community surveys and shotgun metagenomes that seek to explore the composition and diversity of these microbiomes, there are significant efforts to sequence reference microbial genomes from many body sites of healthy adults. To illustrate the utility of reference genomes when studying more complex metagenomes, we present a reference-based analysis of sequence reads generated from 55 shotgun metagenomes, selected from 5 major body sites, including 16 sub-sites. Interestingly, between 13% and 92% (62.3% average) of these shotgun reads were aligned to a then-complete list of 2780 reference genomes, including 1583 references for the human microbiome. However, no reference genome was universally found in all body sites. For any given metagenome, the body site-specific reference genomes, derived from the same body site as the sample, accounted for an average of 58.8% of the mapped reads. While different body sites did differ in abundant genera, proximal or symmetrical body sites were found to be most similar to one another. The extent of variation observed, both between individuals sampled within the same microenvironment, or at the same site within the same individual over time, calls into question comparative studies across individuals even if sampled at the same body site. This study illustrates the high utility of reference genomes and the need for further site-specific reference microbial genome sequencing, even within the already well-sampled human microbiome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

A Microfluidic DNA Library Preparation Platform for Next-Generation Sequencing

Next-generation sequencing (NGS) is emerging as a powerful tool for elucidating genetic information for a wide range of applications. Unfortunately, the surging popularity of NGS has not yet been accompanied by an improvement in automated techniques for preparing formatted sequencing libraries. To address this challenge, we have developed a prototype microfluidic system for preparing sequencer-ready DNA libraries for analysis by Illumina sequencing. Our system combines droplet-based digital microfluidic (DMF) sample handling with peripheral modules to create a fully-integrated, sample-in library-out platform. In this report, we use our automated system to prepare NGS libraries from samples of human and bacterial genomic DNA. E. coli libraries prepared on-device from 5 ng of total DNA yielded excellent sequence coverage over the entire bacterial genome, with .99% alignment to the reference genome, even genome coverage, and good quality scores. Furthermore, we produced a de novo assembly on a previously unsequenced multi-drug resistant Klebsiella pneumoniae strain BAA-2146 (KpnNDM). The new method described here is fast, robust, scalable, and automated. Our device for library preparation will assist in the integration of NGS technology into a wide variety of laboratories, including small research laboratories and clinical laboratories.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Cyote-attack Chain Estimator

Attack Chain Estimator (ACE) Application Overview The Attack Chain Estimator (ACE) Application is a sophisticated tool designed for the ingestion, classification, sequencing, and enrichment of cybersecurity threat reports. This application leverages advanced machine learning models and extensive historical data to provide comprehensive insights into cyber threats, specifically targeting Industrial Control Systems (ICS). Purpose The primary functions of the ACE Application include: Ingestion of Cybersecurity Threat Reporting: Capable of ingesting text-based threat reports in markdown or text file format. Supports ingestion of structured data from other sources in STIX/JSON format. Classification of Report’s Text-Based Events: Utilizes a DeBERTa classifier, specifically trained on cybersecurity data, to map the events to MITRE ATT&CK for ICS Tactics and Techniques. Classification is performed using multiple Jupyter notebooks and machine learning workflows hosted as FastAPI microservices: regex_data deberta_base_35_train_hft_classifier_mlflow.ipynb hft_regex_classifier_mlflow.ipynb param_train_hft_classifier_mlflow.ipynb regex_tactic_tech.ipynb Ordering of Tactics, Techniques, and Observable Events: Sequences the identified tactics, techniques, and events to form a coherent attack chain. Enrichment with Historical Attack Chain Details: Enhances the attack chain with details from historical attacks using a Markov model developed from CyOTE Precursor Analysis Report data. The Markov model is available as a FastAPI endpoint for seamless integration. Enrichment with Adversary Emulation Capabilities Data: Integrates adversary emulation capabilities data using MITRE Caldera for OT adversary abilities UUIDs. Export of Output Files: Provides options to export the enriched attack chain in JSON or CSV formats. Routing of Output to Other Applications: Facilitates routing of output to various platforms and applications, including: Threat Intelligence Platforms COREII Scout for Threat Intelligence Analysis COREII Modeling and Simulation for Adversary Emulation Technical Description The ACE Application is an advanced cybersecurity tool designed to provide detailed threat analysis and sequence generation. It is built on a robust architecture that integrates natural language processing, machine learning, and historical data modeling. Key Components: Data Ingestion Module: Handles the input of threat reports and data from various formats, ensuring flexibility in data sources. Classification Engine: Employs DeBERTa-based classifiers hosted as FastAPI microservices to analyze and classify threat report events in accordance with the MITRE ATT&CK framework for ICS. Sequence Generator: Orders the classified events into a logical attack chain, providing clear insight into the sequence of tactics and techniques used in the threat. Enrichment Engine: Integrates historical data and adversary emulation capabilities to enhance the attack chain with valuable context and additional details. The historical data enrichment is powered by a Markov model, which is available as a FastAPI endpoint. Export and Routing Module: Facilitates the export of the enriched attack chain in multiple formats and routes the output to designated applications for further analysis or emulation.

Paul, Tony [Idaho National Laboratory (INL), Idaho↗
DOE OSTI2025

Behavior of Single-Line-Ground Faults in Inverter-Based Resource Dominated Grids Explained

It has been observed by protection engineers that it is difficult for a protective relay to identify the faulted phase during a single-line-ground (SLG) fault in a power system with a high ingression of inverter-based resources (IBR) using currents (phase or sequence). Further studies using electromagnetic transient (EMT) simulation show that the initial operating conditions of the IBRs influence the response of phase currents during an SLG fault. In this letter, we conduct a quantitative analysis using sequence components. We find that the pre-fault condition determines the relative position of the current contributed by the grid versus that from the IBR, and further dictates which phase has the largest magnitude during an SLG condition. Finally, this finding is further verified by the EMT simulation results.

electromagnetic transient simulation↗
NASA NTRS2002

VIZARD: analysis of Affymetrix Arabidopsis GeneChip data

SUMMARY: The Affymetrix GeneChip Arabidopsis genome array has proved to be a very powerful tool for the analysis of gene expression in Arabidopsis thaliana, the most commonly studied plant model organism. VIZARD is a Java program created at the University of California, Berkeley, to facilitate analysis of Arabidopsis GeneChip data. It includes several integrated tools for filtering, sorting, clustering and visualization of gene expression data as well as tools for the discovery of regulatory motifs in upstream sequences. VIZARD also includes annotation and upstream sequence databases for the majority of genes represented on the Affymetrix Arabidopsis GeneChip array. AVAILABILITY: VIZARD is available free of charge for educational, research, and not-for-profit purposes, and can be downloaded at http://www.anm.f2s.com/research/vizard/ CONTACT: moseyko@uclink4.berkeley.edu.

Non-NASA Center↗
DOE OSTI2013

The structure of the SBP-Tag–streptavidin complex reveals a novel helical scaffold bridging binding pockets on separate subunits

The structure of the SBP-Tag–streptavidin complex reveals a novel mode of peptide recognition in which a single peptide binds simultaneously to biotin-binding pockets from adjacent subunits of streptavidin. The molecular details of peptide recognition suggest how the SBP-Tag can be further modified to become an even more useful tag for a wider range of biotechnological applications. The 38-residue SBP-Tag binds to streptavidin more tightly (K{sub d} ≃ 2.5–4.9 nM) than most if not all other known peptide sequences. Crystallographic analysis at 1.75 Å resolution shows that the SBP-Tag binds to streptavidin in an unprecedented manner by simultaneously interacting with biotin-binding pockets from two separate subunits. An N-terminal HVV peptide sequence (residues 12–14) and a C-terminal HPQ sequence (residues 31–33) form the bulk of the direct interactions between the SBP-Tag and the two biotin-binding pockets. Surprisingly, most of the peptide spanning these two sites (residues 17–28) adopts a regular α-helical structure that projects three leucine side chains into a groove formed at the interface between two streptavidin protomers. The crystal structure shows that residues 1–10 and 35–38 of the original SBP-Tag identified through in vitro selection and deletion analysis do not appear to contact streptavidin and thus may not be important for binding. A 25-residue peptide comprising residues 11–34 (SBP-Tag2) was synthesized and shown using surface plasmon resonance to bind streptavidin with very similar affinity and kinetics when compared with the SBP-Tag. The SBP-Tag2 was also added to the C-terminus of β-lactamase and was shown to be just as effective as the full-length SBP-Tag in affinity purification. These results validate the molecular structure of the SBP-Tag–streptavidin complex and establish a minimal bivalent streptavidin-binding tag from which further rational design and optimization can proceed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Genomes OnLine database (GOLD) v.7: updates and new features

The Genomes Online Database (GOLD) (https://gold.jgi.doe.gov) is an open online resource, which maintains an up-to-date catalog of genome and metagenome projects in the context of a comprehensive list of associated metadata. Information in GOLD is organized into four levels: Study, Biosample/Organism, Sequencing Project and Analysis Project. Currently GOLD hosts information on 33 415 Studies, 49 826 Biosamples, 313 324 Organisms, 215 881 Sequencing Projects and 174 454 Analysis Projects with a total of 541 metadata fields, of which 80 are based on controlled vocabulary (CV) terms. GOLD provides a user-friendly web interface to browse sequencing projects and launch advanced search tools across four classification levels. Users submit metadata on a wide range of Sequencing and Analysis Projects in GOLD before depositing sequence data to the Integrated Microbial Genomes (IMG) system for analysis. GOLD conforms with and supports the rules set by the Genomic Standards Consortium (GSC) Minimum Information standards. The current version of GOLD (v.7) has seen the number of projects and associated metadata increase exponentially over the years. This paper provides an update on the current status of GOLD and highlights the new features added over the last two years.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Consistent Feature Extraction From Vector Fields: Combinatorial Representations and Analysis Under Local Reference Frames

This dissertation presents research on addressing some of the contemporary challenges in the analysis of vector fields—an important type of scientific data useful for representing a multitude of physical phenomena, such as wind flow and ocean currents. In particular, new theories and computational frameworks to enable consistent feature extraction from vector fields are presented. One of the most fundamental challenges in the analysis of vector fields is that their features are defined with respect to reference frames. Unfortunately, there is no single “correct” reference frame for analysis, and an unsuitable frame may cause features of interest to remain undetected, thus creating serious physical consequences. This work develops new reference frames that enable extraction of localized features that other techniques and frames fail to detect. As a result, these reference frames objectify the notion of “correctness” of features for certain goals by revealing the phenomena of importance from the underlying data. An important consequence of using these local frames is that the analysis of unsteady (time-varying) vector fields can be reduced to the analysis of sequences of steady (timeindependent) vector fields, which can be performed using simpler and scalable techniques that allow better data management by accessing the data on a per-time-step basis. Nevertheless, the state-of-the-art analysis of steady vector fields is not robust, as most techniques are numerical in nature. The residing numerical errors can violate consistency with the underlying theory by breaching important fundamental laws, which may lead to serious physical consequences. This dissertation considers consistency as the most fundamental characteristic of computational analysis that must always be preserved, and presents a new discrete theory that uses combinatorial representations and algorithms to provide consistency guarantees during vector field analysis along with the uncertainty visualization of unavoidable discretization errors. Together, the two main contributions of this dissertation address two important concerns regarding feature extraction from scientific data: correctness and precision. The work presented here also opens new avenues for further research by exploring more-general reference frames and more-sophisticated domain discretizations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2001

Signature lipids and stable carbon isotope analyses of Octopus Spring hyperthermophilic communities compared with those of Aquificales representatives

The molecular and isotopic compositions of lipid biomarkers of cultured Aquificales genera have been used to study the community and trophic structure of the hyperthermophilic pink streamers and vent biofilm from Octopus Spring. Thermocrinis ruber, Thermocrinis sp. strain HI 11/12, Hydrogenobacter thermophilus TK-6, Aquifex pyrophilus, and Aquifex aeolicus all contained glycerol-ether phospholipids as well as acyl glycerides. The n-C(20:1) and cy-C(21) fatty acids dominated all of the Aquificales, while the alkyl glycerol ethers were mainly C(18:0). These Aquificales biomarkers were major constituents of the lipid extracts of two Octopus Spring samples, a biofilm associated with the siliceous vent walls, and the well-known pink streamer community (PSC). Both the biofilm and the PSC contained mono- and dialkyl glycerol ethers in which C(18) and C(20) alkyl groups were prevalent. Phospholipid fatty acids included both the Aquificales n-C(20:1) and cy-C(21), plus a series of iso-branched fatty acids (i-C(15:0) to i-C(21:0)), indicating an additional bacterial component. Biomass and lipids from the PSC were depleted in (13)C relative to source water CO(2) by 10.9 and 17.2 per thousand, respectively. The C(20-21) fatty acids of the PSC were less depleted than the iso-branched fatty acids, 18.4 and 22.6 per thousand, respectively. The biomass of T. ruber grown on CO(2) was depleted in (13)C by only 3.3 per thousand relative to C source. In contrast, biomass was depleted by 19.7 per thousand when formate was the C source. Independent of carbon source, T. ruber lipids were heavier than biomass (+1.3 per thousand). The depletion in the C(20-21) fatty acids from the PSC indicates that Thermocrinis biomass must be similarly depleted and too light to be explained by growth on CO(2). Accordingly, Thermocrinis in the PSC is likely to have utilized formate, presumably generated in the spring source region.

Carbon Isotopes/analysis↗
DOE OSTI2019

Data Analysis for DNA Stable Isotope Probing Experiments Using Multiple Window High-Resolution SIP

DNA stable isotope probing (DNA-SIP) allows for the identification of microbes that assimilate isotopically labeled substrates into DNA. Here we describe the analysis of sequencing data using the multiple window high-resolution DNA-SIP method (MW-HR-SIP). MW-HR-SIP has improved accuracy over other methods and is easily implemented on the statistical platform R. Here, we also discuss key experimental parameters to consider when designing DNA-SIP experiments and how these parameters affect accuracy of analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

IMG-ABC. A knowledge base to fuel discovery of biosynthetic gene clusters and novel secondary metabolites

In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMG’s comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC’s focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in lphaproteobacteria . IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG’s extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1996

Sequence, overproduction and purification of Vibrio proteolyticus ribosomal protein L18 for in vitro and in vivo studies

A strategy suggested by comparative genomic studies was used to amplify the entire Vibrio proteolyticus (Vp) gene for ribosomal protein L18. Vp L18 and its flanking regions were sequenced and compared with the deduced amino acid (aa) sequences of other known L18 proteins. A 26-aa residue segment at the carboxy terminus contains many strongly conserved residues and may be critical for the L18 interaction with 5S rRNA. This approach should allow rapid characterization of L18 from large numbers of bacteria. Both Vp L18 and Escherichia coli (Ec) L18 were overproduced and purified using a T7 expression vector which fuses an N-terminal peptide segment (His-tag) containing 6 histidine residues to the recombinant protein. The purified fusion proteins, Vp His::L18 and Ec His::L18, were both found to bind to either the Vp 5S or Ec 5S rRNAs in vitro. Vp His::L18 protein was also shown to incorporate into Ec ribosomes in vivo. This His-tag strategy likely will have general applicability for the study of ribosomal proteins in vitro and in vivo.

Non-NASA Center↗
DOE OSTI2016

The DOE Joint Genome Institute Enabling Advances in Energy & Environmental Research (2016 Fact Sheet)

The U.S. Department of Energy (DOE) Joint Genome Institute (JGI) is the only federally-funded high-throughput genome sequencing and analysis facility dedicated to genomes of non-medical microbes, microbial communities, plants, fungi and other targets relevant to DOE missions in energy, climate, and environment. DOE JGI provides collaborators around the world with access to massive-scale DNA sequencing to underpin modern systems biology research and provide fundamental data on key genes that may link to biological functions, including microbial metabolic pathways and enzymes that are used to generate fuel molecules, affect plant biomass formation, degrade contaminants, or capture CO 2 . The information can then be used to optimize organisms for biofuels production and other DOE missions.

09 BIOMASS FUELS↗