Search NASA⌕ Search

SEARCH · Search NASA

Results for “Clustered patterns”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Ordering Traces Logically to Identify Lateness in Parallel Programs

Event traces are a valuable tool for understanding the behavior of parallel programs. Automatically analyzing a large trace, however, especially without a specific objective, is difficult. We aid this process by extracting a trace’s logical structure, an ordering of events derived from their happened before relationships. From this perspective, we can calculate delays relative to peers rather than duration and determine where they begin and how they propagate. The logical structure also acts as a platform for comparing and clustering processes as well as showing communication patterns in a trace visualization. We present an algorithm for determining this idealized logical structure from a trace and develop metrics to quantify delays and differences among processes. We implement this in our novel trace visualizer, Ravel, and apply our approach to several applications, demonstrating the accuracy of our extracted structure and its utility in analyzing these codes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Self-Organizing Maps and Their Applications to Data Analysis

Self-Organizing Maps(SOMs) are a form of unsupervised neural network that are used for visualization and exploratory data analysis of high dimensional datasets. Our goal was to understand how we can use a SOM to gain insights about datasets. We do this by first understanding the initialization, training, error metrics, and convergence properties of the SOM. Next we discuss the ways to interpret and visualize a Self-Organizing Map. Finally we used real datasets to understand what the Self-Organizing Map can tell us about labeled and unlabeled data. Based on experiments with our datasets we found that the Self-Organizing Map can tell us about the spacing and position of high dimensional clusters, help us find non-linear patterns, and give us insight into the shape of our data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1970

The application of automatic recognition techniques in the Apollo 9 SO-65 experiment

A synoptic feature analysis is reported on Apollo 9 remote earth surface photographs that uses the methods of statistical pattern recognition to classify density points and clusterings in digital conversion of optical data. A computer derived geological map of a geological test site indicates that geological features of the range are separable, but that specific rock types are not identifiable.

Macdonald, R. B.↗
NASA NTRS2002

Shear Instabilities as a Probe of Jupiter's Atmosphere

Linear wave patterns in Jupiter clouds with wavelengths strongly clustered around 300 km are commonly observed in the planet's equatorial atmosphere. We propose that the preferred wavelength is related to the thickness of an unstable shear layer within the clouds. We numerically analyze the linear stability of wavelike disturbances that have nonzero horizontal phase speeds in Jupiter's atmosphere and find that. if the static stability in the strongly clustered around 300 km are commonly observed in the planet's equatorial atmosphere. We propose that the preferred wavelength is related to the thickness of an unstable shear layer within the clouds. We numerically analyze the linear stability of wavelike disturbances that have nonzero horizontal phase speeds in Jupiter's atmosphere and find that. if the static stability in the shear layer is very low (but still nonnegative), a deep vertical shear layer like the one measured by the Galileo probe can generate the instabilities. The fastest growing waves grow exponentially within an hour, and their wavelengths match the observations. Close to zero values of static stability that permit the growth of instabilities are within the range of values measured by the Galileo probe in a hot spot. Our model probes Jupiter's equatorial atmosphere below the cloud deck and suggests that thick regions of wind shear and low static stability exist outside hot spots.

Bosak, Tanja↗
DOE OSTI2015

pcircle - A Suite of Scalable Parallel File System Tools

Most of the software related to file system are written for conventional local file system, they are serialized and can't take advantage of the benefit of a large scale parallel file system. "pcircle" software builds on top of ubiquitous MPI in cluster computing environment and "work-stealing" pattern to provide a scalable, high-performance suite of file system tools. In particular - it implemented parallel data copy and parallel data checksumming, with advanced features such as async progress report, checkpoint and restart, as well as integrity checking.

WANG, FEIYI↗
DOE OSTI2024

Double diffraction imaging of x-ray induced structural dynamics in single free nanoparticles

Abstract Because of their high photon flux, x-ray free-electron lasers (FEL) allow to resolve the structure of individual nanoparticles via coherent diffractive imaging (CDI) within a single x-ray pulse. Since the inevitable rapid destruction of the sample limits the achievable resolution, a thorough understanding of the spatiotemporal evolution of matter on the nanoscale following the irradiation is crucial. We present a technique to track x-ray induced structural changes in time and space by recording two consecutive diffraction patterns of the same single, free-flying nanoparticle, acquired separately on two large-area detectors opposite to each other, thus examining both the initial and evolved particle structure. We demonstrate the method at the extreme ultraviolet (XUV) and soft x-ray Free-electron LASer in Hamburg (FLASH), investigating xenon clusters as model systems. By splitting a single XUV pulse, two diffraction patterns from the same particle can be obtained. For focus intensities of about 2 × 10 12 W cm −2 we observe still largely intact clusters even at the longest delays of up to 650 picoseconds of the second pulse, indicating that in the highly absorbing systems the damage remains confined to one side of the cluster. Instead, in case of five times higher flux, the diffraction patterns show clear signatures of disintegration, namely increased diameters and density fluctuations in the fragmenting clusters. Future improvements to the accessible range of dynamics and time resolution of the approach are discussed.

Sauppe, M. (ORCID:0000000163123102)↗
DOE OSTI2015

First principles study of electronic structure for cubane-like and ring-shaped structures of M{sub 4}O{sub 4}, M{sub 4}S{sub 4} clusters (M = Mn, Fe, Co, Ni, Cu)

Spin-polarized DFT has been used to perform a comparative study of the geometric structures and electronic properties for isolated M{sub 4}X{sub 4} nano clusters between their two stable isomers - a planar rhombus-like 2D structure and a cubane-like 3D structure with M = Mn, Fe, Co, Ni, Cu ; X = O, S. These two structural patterns of the M{sub 4}X{sub 4} clusters are commonly found as building blocks in several poly-nuclear transition metal complexes in inorganic chemistry. The effects of the van der Waals corrections to the physical properties have been considered in the electronic structure calculations employing the empirical Grimme’s correction (DFT+D2). We report here an interesting trend in their relative structural stability - the isolated M{sub 4}O{sub 4} clusters prefer to stabilize more in the planar structure, while the cubane-like 3D structure is more favorable for most of the isolated M{sub 4}S{sub 4} clusters than their planar 2D counterparts. Our study reveals that this contrasting trend in the relative structural stability is expected to be driven by an interesting interplay between the s-d and p-d hybridization effects of the constituents’ valence electrons.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Evidence for C and Mg variations in the GD-1 stellar stream

ABSTRACT Dynamically cold stellar streams are the relics left over from globular cluster dissolution. These relics offer a unique insight into a now fully disrupted population of ancient clusters in our Galaxy. Using a combination of Gaia eDR3 proper motions, optical and near-UV colours, we select a sample of likely Red Giant Branch stars from the GD-1 stream for medium-low resolution spectroscopic follow-up. Based on radial velocity and metallicity, we are able to find 14 new members of GD-1, 5 of which are associated with the spur and blob/cocoon off-stream features. We measured C-abundances to probe for abundance variations known to exist in globular clusters. These variations are expected to manifest in a subtle way in globular clusters with such low masses ($\sim 10^4\,{\rm ~\textrm {M}_\odot }$) and metallicities ([Fe/H] ∼ −2.1 dex). We find that the C-abundances of the stars in our sample display a small but significant (3σ level) spread. Furthermore, we find ∼3σ variation in Mg-abundances among the stars in our sample that have been observed by APOGEE. These abundance patterns match the ones found in Galactic globular clusters of similar metallicity. Our results suggest that GD-1 represents another fully disrupted low-mass globular cluster where light-element abundance spreads have been found.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Comprehensive Genetic Characterization of Four Novel HIV-1 Circulating Recombinant Forms (CRF129_56G, CRF130_A1B, CRF131_A1B, and CRF138_cpx): Insights from Molecular Epidemiology in Cyprus

Molecular investigations of the HIV-1 pol region (2253–5250 in the HXB2 genome) were conducted on sequences obtained from 331 individuals infected with HIV-1 in Cyprus between 2017 and 2021. This study unveiled four distinct HIV-1 putative transmission clusters, encompassing 19 previously unidentified HIV-1 recombinants. These recombinants, each comprising eight, three, four, and four sequences, respectively, did not align with previously established Circulating Recombinant Forms (CRFs). To characterize these novel HIV-1 recombinants, near-full-length genome sequences were successfully obtained for 16 of the 19 recombinants (790–8795 in the HXB2 genome) using an in-house-developed RT-PCR assay. Phylogenetic analyses, employing MEGAX and Cluster-Picker, along with confirmatory neighbor-joining tree analyses of subregions, were conducted to identify distinct clusters and determine subtypes. The uniqueness of the HIV-1 recombinants was evident in their exclusive clustering within generated maximum likelihood trees. Recombination analyses highlighted the distinct chimeric nature of these recombinants, with consistent mosaic patterns observed across all sequences within each of the four putative transmission clusters. Conclusive genetic characterization identified four novel HIV-1 CRFs: CRF129_56G, CRF130_A1B, CRF131_A1B, and CRF138_cpx. CRF129_56G exhibited two recombination breakpoints and three fragments of subtypes CRF56_cpx and G. Both CRF130_A1B and CRF131_A1B featured seven recombination breakpoints and eight fragments of subtypes A1 and B. CRF138_cpx displayed five recombination breakpoints and six fragments of subtypes CRF22_01A1 and F2, along with an unclassified fragment. Additional BLAST analyses identified a Unique Recombinant Form (URF) of CRF138_cpx with three additional recombination sites, involving subtype F2, a fragment of unknown subtype origin, and CRF138_cpx. Post-identification, all putative transmission clusters remained active, with CRF130_A1B, CRF131_A1B, and CRF138_cpx clusters exhibiting further growth. Furthermore, international connections were identified through BLAST analyses, linking one sequence from the USA to the CRF130_A1B strain, and three sequences from Belgium and Cameroon to the CRF138_cpx strain. This study contributes valuable insights into the dynamic landscape of HIV-1 diversity and transmission patterns, emphasizing the need for ongoing molecular surveillance and global collaboration in tracking emerging viral variants.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Microhydration of the metastable N -Protomer of 4-Aminobenzoic acid by condensation at 80 K: H/D exchange without conversion to the more stable O- protomer

4-Aminobenzoic acid (4ABA) is a model scaffold for studying solvent-mediated proton transfer. Although protonation at the carboxylic group (O-protomer) is energetically favored in the gas phase, the N-protomer, where the proton remains on the amino group, can be kinetically trapped by electrospray ionization of 4ABA in an aprotic solvent such as acetonitrile. Here we report the formation of the hydrated deuterium isotopologues of the N-protomers, RND 3 + ·(H 2 O) n=1-3 , (R=C 6 H 4 COOD), which are generated by condensing water molecules onto the bare N-protomers in a liquid nitrogen cooled, radiofrequency octopole ion trap at 80 K. The product clusters are then transferred to a 20 K cryogenic ion trap where they are tagged with weakly bound D 2 molecules. The structures of these clusters are determined by analysis of their vibrational patterns obtained by resonant IR photodissociation. The resulting patterns confirm that the metastable N-protomer configuration remains intact even when warmed by sequential condensation of water molecules. Attachment of H 2 O molecules onto the RND 3 + head group also affords the opportunity to explore the possibility of H/D exchange between the acid scaffold and the proximal water network. The spectroscopic results establish that although the RND 3 + ·(H 2 O) n=1,2 clusters are formed without H/D exchange, the n = 3 cluster exhibits about 10% H/D exchange as evidenced by the appearance of the telltale HOD bands. Furthermore, the site of exchange on the acid is determined to be the acidic OH by the emergence of the OH stretching fundamental in the -COOH motif.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Iron-sulfur clusters: the road to room temperature

Abstract Iron-sulfur proteins perform a wide variety of reactions central to the metabolisms of all living organisms. Foundational to their reaction chemistry are the rich electronic structures of their constituent Fe-S clusters, which differ in important ways from the active sites of mononuclear Fe enzymes. In this perspective, we summarize the essential electronic structure features that make Fe-S clusters unique, and point to the need for studies aimed at understanding the electronic basis for their reactivity under physiological conditions. Specifically, at ambient temperature, both the ground state and a large number of excited states are thermally populated, and thus a complete understanding of Fe-S cluster reactivity must take into account the properties, energies, and reactivity patterns of these excited states. We highlight prior research toward characterizing the low-energy excited states of Fe-S clusters that has established what is now a consensus model of these excited state manifolds and the bonding interactions that give rise to them. In particular, we discuss the low-energy alternate spin states and valence electron configurations that occur in Fe-S clusters of varying nuclearities, and finally suggest that there may be unrecognized functional roles for these states. Graphical abstract

Skeel, Brighton A. (ORCID:000000018458088X)↗
DOE OSTI2023

Bioinformatics of cyanophycin metabolism genes and characterization of promiscuous isoaspartyl dipeptidases that catalyze the final step of cyanophycin degradation

Cyanophycin is a bacterial biopolymer used for storage of fixed nitrogen. It is composed of a backbone of L-aspartate residues with L-arginines attached to each of their side chains. Cyanophycin is produced by cyanophycin synthetase 1 (CphA1) using Arg, Asp and ATP, and is degraded in two steps. First, cyanophycinase breaks down the backbone peptide bonds, releasing β-Asp-Arg dipeptides. Then, these dipeptides are broken down into free Asp and Arg by enzymes with isoaspartyl dipeptidase activity. Two bacterial enzymes are known to possess promiscuous isoaspartyl dipeptidase activity: isoaspartyl dipeptidase (IadA) and isoaspartyl aminopeptidase (IaaA). We performed a bioinformatic analysis to investigate whether genes for cyanophycin metabolism enzymes cluster together or are spread around the microbial genomes. Many genomes showed incomplete contingents of known cyanophycin metabolizing genes, with different patterns in various bacterial clades. Cyanophycin synthetase and cyanophycinase are usually clustered together when recognizable genes for each are found within a genome. Cyanophycinase and isoaspartyl dipeptidase genes typically cluster within genomes lacking cphA1. About one-third of genomes with genes for CphA1, cyanophycinase and IaaA show these genes clustered together, while the proportion is around one-sixth for CphA1, cyanophycinase and IadA. We used X-ray crystallography and biochemical studies to characterize an IadA and an IaaA from two such clusters, in Leucothrix mucor and Roseivivax halodurans, respectively. The enzymes retained their promiscuous nature, showing that being associated with cyanophycin-related genes did not make them specific for β-Asp-Arg dipeptides derived from cyanophycin degradation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The many-body expansion for aqueous systems revisited: III. Hofmeister ion – water interactions

We report a Many Body Energy (MBE) analysis of aqueous ionic clusters containing anions and cations at the two opposite ends of the Hofmeister series, viz. the kosmotropes Ca2+, SO42- and chaotropes NH4+ and ClO4- with 9 water molecules to quantify the how these ions in altering the interaction between the water molecules in their immediate surrounding. The current results are contrasted to the ones reported earlier for water clusters as well as for alkali metal and halide ion aqueous clusters of the same size, which lie in the middle of the Hofmeister series. Through this analysis, noteworthy differences between the MBE of kosmotropes and chaotropes were identified. The MBE of kosmotropes is dominated by ion-water interactions that extends beyond the 4-body term, the point at which the MBE of pure water converges. The percentage contribution of the 2- B to the total cluster binding energy is noticeably larger. The disruption due to the dominant ion results in weak, unfavorable water-water interactions. The MBE for chaotropes, on the other hand, was found to converge more quickly as it more closely resembles that of pure water clusters. Chaotropes exhibit weaker overall binding energies and ion-water interactions with more favorable water-water interactions, somewhat recovering the pattern of the 2-4 body terms exemplified by pure water clusters. More importantly, both kosmotropic and chaotropic ions exhibit an anticorrelation between the 2-B ion-water (I-W) and water-water (W-W) interactions as well as between the 3-B (I-W-W) and (I-W) interactions. The consideration of two different structural arrangements (ion inside and outside of a water cluster) suggests that fully solvated (ion inside) chaotropes disrupt the hydrogen bonding network in a similar manner as partially solvated (ion outside) kosmotropes and offer useful insights into the modeling requirements of bulk vs. an interface. Finally, the 2-B contribution to the total Basis Set Superposition Error (BSSE) correction for the kosmotropic and chaotropic ions follows the previously reported erf profile vs. intermolecular distance. When scaled for the corresponding dimer energies and distances, a single profile fits the current results together with all previously reported ones for the pure water and halide water clusters.

Herman, Kristina M.↗
NASA NTRS1990

Fractal dimension of bioconvection patterns

Shallow cultures of the motile algal strain, Euglena gracilis, were concentrated to 2 x 10 to the 6th organisms per ml and placed in constant temperature water baths at 24 and 38 C. Bioconvective patterns formed an open two-dimensional structure with random branches, similar to clusters encountered in the diffusion-limited aggregation (DLA) model. When averaged over several example cultures, the pattern was found to have no natural length scale, self-similar branching, and a fractal dimension (d about 1.7). These agree well with the two-dimensional DLA.

Noever, David A.↗
NASA NTRS2006

Value, Cost, and Sharing: Open Issues in Constrained Clustering

Clustering is an important tool for data mining, since it can identify major patterns or trends without any supervision (labeled data). Over the past five years, semi-supervised (constrained) clustering methods have become very popular. These methods began with incorporating pairwise constraints and have developed into more general methods that can learn appropriate distance metrics. However, several important open questions have arisen about which constraints are most useful, how they can be actively acquired, and when and how they should be propagated to neighboring points. This position paper describes these open questions and suggests future directions for constrained clustering research.

constraints↗
NASA NTRS2011

Improve Data Mining and Knowledge Discovery Through the Use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykhian, Gholam Ali↗
NASA NTRS2011

Improve Data Mining and Knowledge Discovery through the use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykahian, Gholan Ali↗
DOE OSTI2016

Heavy-Duty Vehicle Port Drayage Drive Cycle Characterization and Development

In an effort to better understand the operational requirements of port drayage vehicles and their potential for adoption of advanced technologies, National Renewable Energy Laboratory (NREL) researchers collected over 36,000 miles of in-use duty cycle data from 30 Class 8 drayage trucks operating at the Port of Long Beach and Port of Los Angeles in Southern California. These data include 1-Hz global positioning system location and SAE J1939 high-speed controller area network information. Researchers processed the data through NREL's Drive-Cycle Rapid Investigation, Visualization, and Evaluation tool to examine vehicle kinematic and dynamic patterns across the spectrum of operations. Using the k-medoids clustering method, a repeatable and quantitative process for multi-mode drive cycle segmentation, the analysis led to the creation of multiple drive cycles representing four distinct modes of operation that can be used independently or in combination. These drive cycles are statistically representative of real-world operation of port drayage vehicles. When combined with modeling and simulation tools, these representative test cycles allow advanced vehicle or systems developers to efficiently and accurately evaluate vehicle technology performance requirements to reduce cost and development time while ultimately leading to the commercialization of advanced technologies that meet the performance requirements of the port drayage vocation. The drive cycles, which are suitable for chassis dynamometer testing, were compared to several existing test cycles. This paper presents the clustering methodology, accompanying results of the port drayage duty cycle analysis and custom drive cycle creation.

33 ADVANCED PROPULSION SYSTEMS↗