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At least 307 records · Page 17

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↗

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↗

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.↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

Data Analyst - A Device for Continuous Repeating Real-Time Assay of HPGe, CZT, or Scintillation Gamma Spectra - 18574

There are many situations where a continuous repeating series of quantitative gamma spectral assays is desirable. These include measurements of fluid going through a pipe, of items on a conveyor passing under a detector, a detector aimed at the ground on a moving platform, or a detector in free air as a plume of radioactivity drifts by. While Canberra and many others have built and deployed many of these devices, they have all been custom built for that particular application, and rather expensive. The Data Analyst [DA] is a general purpose device that is designed to fulfill many of these applications without modification, but can be fairly-easily modified if needed. The DA is a small [12 x 18 x 5 cm], low-power [3 W] box that accepts the input from external MCAs, controls the acquisition cycle, analyzes the results, and transmits them to the outside world when needed. The detector-MCAs supported are HPGe with Lynx MCA, NaI or CeBr or LaBr with Osprey MCA, and CZT or CsI with internal MCAs. The DA internal software used for analysis is the full standard Genie analysis software, which is very widely used and well accepted in the industry. This allows exported spectral files to be reviewed and confirmed by Experts, and reanalyzed if needed. The DA hardware is totally autonomous. As soon as power is applied, it starts the pre-programmed sequences of acquisition and analysis. Multiple analysis sequences [called Workflows] can be in operation simultaneously, e.g. with different count times and different nuclide libraries. Only the detector with MCA, and the DA are required in the field. A PC can be connected to the DA locally or remotely via WiFi, USB, or Ethernet. The PC is needed to setup the DA, and to readout the results. The DA also supports [with application-specific programming] external Inputs/Outputs either for recording with the analysis results or for use in the computation of the result, e.g. temperature, flow rate, pressure, ... ]. The DA also has an internal GPS receiver with external antenna. Applications of the DA that are discussed include stack gas effluent activity where a portion of the effluent stream was extracted to flow through a shield with a HPGe detector and Lynx MCA, and measurement of reactor coolant activity where a shielded CZT detector and MCA were aimed at various sections of reactor primary coolant during a maintenance outage. Potential other applications are also described. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Atrogin-1, a muscle-specific F-box protein highly expressed during muscle atrophy

Muscle wasting is a debilitating consequence of fasting, inactivity, cancer, and other systemic diseases that results primarily from accelerated protein degradation by the ubiquitin-proteasome pathway. To identify key factors in this process, we have used cDNA microarrays to compare normal and atrophying muscles and found a unique gene fragment that is induced more than ninefold in muscles of fasted mice. We cloned this gene, which is expressed specifically in striated muscles. Because this mRNA also markedly increases in muscles atrophying because of diabetes, cancer, and renal failure, we named it atrogin-1. It contains a functional F-box domain that binds to Skp1 and thereby to Roc1 and Cul1, the other components of SCF-type Ub-protein ligases (E3s), as well as a nuclear localization sequence and PDZ-binding domain. On fasting, atrogin-1 mRNA levels increase specifically in skeletal muscle and before atrophy occurs. Atrogin-1 is one of the few examples of an F-box protein or Ub-protein ligase (E3) expressed in a tissue-specific manner and appears to be a critical component in the enhanced proteolysis leading to muscle atrophy in diverse diseases.

NASA Discipline Musculoskeletal↗

MetaHCR: a web-enabled metagenome data management system for hydrocarbon resources

The ever-increasing metagenomic data necessitate appropriate cataloguing in a way that facilitates the comparison and better contextualization of the underlying investigations. To this extent, information associated with the sequencing data as well as the original sample and the environment where it was obtained from is crucial. To date, there are not any publicly available repositories able to capture environmental metadata pertaining to hydrocarbon-rich environments. As such, contextualization and comparative analysis among sequencing datasets derived from these environments is to a certain degree hindered or cannot be fully evaluated. The metagenomics data management system for hydrocarbon resources (MetaHCRs) enables the capturing of marker gene and whole metagenome sequencing data as well as over 300 contextual attributes associated with samples, organisms, environments and geological properties, among others. Moreover, MetaHCR implements the Minimum Information about any Sequence–hydrocarbon resource specification from the Genomic Standards Consortium; it integrates a user-friendly web interface and relational database model, and it enables the generation of complex custom search. MetaHCR has been tested with 36 publicly available metagenomic studies, and its modular architecture can be easily customized for other types of environmental and metagenomics studies.

59 BASIC BIOLOGICAL SCIENCES↗

Performance analysis of multiple PRF technique for ambiguity resolution

For short wavelength spaceborne synthetic aperture radar (SAR), ambiguity in Doppler centroid estimation occurs when the azimuth squint angle uncertainty is larger than the azimuth antenna beamwidth. Multiple pulse recurrence frequency (PRF) hopping is a technique developed to resolve the ambiguity by operating the radar in different PRF's in the pre-imaging sequence. Performance analysis results of the multiple PRF technique are presented, given the constraints of the attitude bound, the drift rate uncertainty, and the arbitrary numerical values of PRF's. The algorithm performance is derived in terms of the probability of correct ambiguity resolution. Examples, using the Shuttle Imaging Radar-C (SIR-C) and X-SAR parameters, demonstrate that the probability of correct ambiguity resolution obtained by the multiple PRF technique is greater than 95 percent and 80 percent for the SIR-C and X-SAR applications, respectively. The success rate is significantly higher than that achieved by the range cross correlation technique.

Chang, C. Y.↗

A comparison of methods used to unveil the genetic and metabolic pool in the built environment

BACKGROUND:A majority of indoor residential microbes originate from humans, pets, and outdoor air and are not adapted to the built environment (BE). Consequently, a large portion of the microbes identified by DNA-based methods are either dead or metabolically inactive. Although many exceptions have been noted, the ribosomal RNA fraction of the sample is more likely to represent either viable or metabolically active cells. We examined methodological variations in sample processing using a defined, mock BE microbial community to better understand the scope of technique-based vs. biological-based differences in both ribosomal transcript (rRNA) and gene (DNA) sequence community analysis. Based on in vitro tests, a protocol was adopted for the analysis of the genetic and metabolic pool (DNA vs. rRNA) of air and surface microbiomes within a residential setting. RESULTS:We observed differences in DNA/RNA co-extraction efficiency for individual microbes, but overall, a greater recovery of rRNA using FastPrep (> 50%). Samples stored with various preservation methods at - 80°C experienced a rapid decline in nucleic acid recovery starting within the first week, although post-extraction rRNA had no significant degradation when treated with RNAStable. We recommend that co-extraction samples be processed as quickly as possible after collection. The in vivo analysis revealed significant differences in the two components (genetic and metabolic pool) in terms of taxonomy, community structure, and microbial association networks. Rare taxa present in the genetic pool showed higher metabolic potential (RNA:DNA ratio), whereas commonly detected taxa of outdoor origins based on DNA sequencing, especially taxa of the Sphingomonadales order, were present in lower relative abundances in the viable community. CONCLUSIONS:Although methodological variations in sample preparations are high, large differences between the DNA and RNA fractions of the total microbial community demonstrate that direct examination of rRNA isolated from a residential BE microbiome has the potential to identify the more likely viable or active portion of the microbial community. In an environment that has primarily dead and metabolically inactive cells, we suggest that the rRNA fraction of BE samples is capable of providing a more ecologically relevant insight into the factors that drive indoor microbial community dynamics.

59 BASIC BIOLOGICAL SCIENCES↗

Fractal landscapes in biological systems: long-range correlations in DNA and interbeat heart intervals

Here we discuss recent advances in applying ideas of fractals and disordered systems to two topics of biological interest, both topics having common the appearance of scale-free phenomena, i.e., correlations that have no characteristic length scale, typically exhibited by physical systems near a critical point and dynamical systems far from equilibrium. (i) DNA nucleotide sequences have traditionally been analyzed using models which incorporate the possibility of short-range nucleotide correlations. We found, instead, a remarkably long-range power law correlation. We found such long-range correlations in intron-containing genes and in non-transcribed regulatory DNA sequences as well as intragenomic DNA, but not in cDNA sequences or intron-less genes. We also found that the myosin heavy chain family gene evolution increases the fractal complexity of the DNA landscapes, consistent with the intron-late hypothesis of gene evolution. (ii) The healthy heartbeat is traditionally thought to be regulated according to the classical principle of homeostasis, whereby physiologic systems operate to reduce variability and achieve an equilibrium-like state. We found, however, that under normal conditions, beat-to-beat fluctuations in heart rate display long-range power law correlations.

Non-NASA Center↗

A NASTRAN DMAP alter for linear buckling analysis under dynamic loading

A unique 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 prediction of both time and mode of buckling.

Aiello, Robert A.↗

Scaling features of noncoding DNA

We review evidence supporting the idea that the DNA sequence in genes containing noncoding regions is correlated, and that the correlation is remarkably long range--indeed, base pairs thousands of base pairs distant are correlated. We do not find such a long-range correlation in the coding regions of the gene, and utilize this fact to build a Coding Sequence Finder Algorithm, which uses statistical ideas to locate the coding regions of an unknown DNA sequence. Finally, we describe briefly some recent work adapting to DNA the Zipf approach to analyzing linguistic texts, and the Shannon approach to quantifying the "redundancy" of a linguistic text in terms of a measurable entropy function, and reporting that noncoding regions in eukaryotes display a larger redundancy than coding regions. Specifically, we consider the possibility that this result is solely a consequence of nucleotide concentration differences as first noted by Bonhoeffer and his collaborators. We find that cytosine-guanine (CG) concentration does have a strong "background" effect on redundancy. However, we find that for the purine-pyrimidine binary mapping rule, which is not affected by the difference in CG concentration, the Shannon redundancy for the set of analyzed sequences is larger for noncoding regions compared to coding regions.

Non-NASA Center↗