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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

TICC Clustering Library v.1.0

SAND2024-01234O TICC is a clustering algorithm that labels a sequence of data points according to numerical properties. This library is a Python implementation of the algorithm described in "Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data" (Hallac et al. 2017). It includes documentation, performance improvements, examples, and test coverage. This library allows users to automatically segment a series of multivariate data points according to their covariance—that is, the way the values at each data point are changing in relation to one another. This is useful for identifying periods in which a system is behaving. For example, if a sensor is measuring a car's velocity, steering wheel angle, braking and acceleration, TICC can determine when the car was stopped, beginning/exiting a turn, slowing or accelerating at an intersection, or driving on straight or curved roads. TICC can be applied to measure multiple quantities at known times. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525

Dalbey, Keith↗
DOE OSTI2019

Materials data analytics for 9% Cr family steel

A materials data analytics (MDA) methodology was developed in this study to evaluate publicly available information on 9% Cr family steel and to handle nonlinear relationships and the sparsity in materials data for this alloy class. The overarching goal is to accelerate the design process as well as to reduce the time and expense associated with qualification testing of new alloys for fossil energy applications. Data entries in the analyzed data set for 82 iron–base alloy compositions, several processing parameters, and results of tensile mechanical tests selected for this study were arranged in 34 columns by 915 rows. While detailed microstructural information was not available, it is assumed that the compositional space for the 9 to 12% Cr steels is limited such that all data entries have a tempered martensitic microstructure during service. Establishing a hierarchy of first–order trends in the publicly available data requires the MDA to filter out the biases. Complexity of the phase transformations and microstructure evolution in the multicomponent alloys (using 21 chemical elements) with major influence on mechanical properties, leads to inefficiency in direct application of unbiased linear regression across the entire data space. To address the nonlinearity, analyses of tensile data were performed in composition–based clusters. Clusters corresponding to moderately frequent patterns and maximized information gain were further refined by using p–norm distance measures, matching the alloy classification groups adopted by industry. Lastly, the evolutionary method of propagating an ensemble of competing cluster–based models proved to be a viable option in dealing with scarce, multidimensional data.

36 MATERIALS SCIENCE↗
DOE OSTI2013

CONSTRAINING INTERMEDIATE-MASS BLACK HOLES IN GLOBULAR CLUSTERS

Decades after the first predictions of intermediate-mass black holes (IMBHs) in globular clusters (GCs) there is still no unambiguous observational evidence for their existence. The most promising signatures for IMBHs are found in the cores of GCs, where the evidence now comes from the stellar velocity distribution, the surface density profile, and, for very deep observations, the mass-segregation profile near the cluster center. However, interpretation of the data, and, in particular, constraints on central IMBH masses, require the use of detailed cluster dynamical models. Here we present results from Monte Carlo cluster simulations of GCs that harbor IMBHs. As an example of application, we compare velocity dispersion, surface brightness and mass-segregation profiles with observations of the GC M10, and constrain the mass of a possible central IMBH in this cluster. We find that, although M10 does not seem to possess a cuspy surface density profile, the presence of an IMBH with a mass up to 0.75% of the total cluster mass, corresponding to about 600 M{sub Sun }, cannot be excluded. This is also in agreement with the surface brightness profile, although we find it to be less constraining, as it is dominated by the light of giants, causing it to fluctuate significantly. We also find that the mass-segregation profile cannot be used to discriminate between models with and without IMBH. The reason is that M10 is not yet dynamically evolved enough for the quenching of mass segregation to take effect. Finally, detecting a velocity dispersion cusp in clusters with central densities as low as in M10 is extremely challenging, and has to rely on only 20-40 bright stars. It is only when stars with masses down to 0.3 M{sub Sun} are included that the velocity cusp is sampled close enough to the IMBH for a significant increase above the core velocity dispersion to become detectable.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Removal of spurious data in Bragg coherent diffraction imaging: an algorithm for automated data preprocessing

Bragg coherent diffraction imaging (BCDI) provides a powerful tool for obtaining high-resolution structural information from nanocrystalline materials. Here a BCDI sample consisting of a large number of randomly oriented nanoscale crystals is considered. Ideally, only one crystal is oriented to produce a Bragg peak on the detector. However, diffraction from other crystals often produces additional signals on the detector. Before the measured diffraction patterns can be processed into structural images, scientists routinely need to manually identify and remove the `alien' intensities from sources other than the intended crystal. With the development of modern high-coherence storage rings, such as the upgraded Advanced Photon Source (APS), the already slow process of manual preprocessing will be untenable for the large volumes of data that will be produced. An automated method of identifying and deleting alien intensities is proposed. This method exploits the fact that BCDI of a perfect crystal produces diffraction data with inversion symmetry around the Bragg peak. This approach uses the machine learning clustering method DBSCAN to distinguish between diffraction from multiple sources, and then calculates cluster size and inversion symmetry to assess whether clusters of intensity belong to desired data or alien signals. This approach can dramatically reduce the amount of time spent manually processing data, allowing BCDI data processing capabilities to keep pace with the technological advances of fourth-generation synchrotron light sources.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Analysis of the Amplitude of the Sunyaev–Zel’dovich Effect out to Redshift z = 0.8

The interaction of the cosmic microwave background (CMB) with the hot gas in clusters of galaxies, the so-called Sunyaev–Zel’dovich (SZ) effect, is a very useful tool that allows us to determine the physical conditions in such clusters and fundamental parameters of the cosmological models. In this work, we determine the dependence of the SZ surface brightness amplitude with redshift and mass of the clusters. We have used PLANCK+IRAS data in the microwave-far-infrared and a catalog with ≳10{sup 5} clusters of galaxies extracted from the SDSS by Wen et al. We estimate and subtract the dust emission from those clusters. From the residual flux, we extract its SZ flux densities. The absolute value of the SZ amplitude indicates that the gas mass is around 10% of the total mass for cluster masses of M∼10{sup 14} M{sub ⊙}. This amplitude is compatible with no evolution with redshift and proportional to M{sup 2.70±0.37} (using X-ray derived masses) or M{sup 2.51±0.38} (using weak-lensing derived masses), with some tension regarding the expectations of the self-similar dependence (amplitude proportional to M{sup 5/3}). Other secondary products of our analysis include that clusters have a dust emission with emissivity index β∼2 and temperature T∼25 K; we confirm that the CMB temperature agrees with a dependence of T{sub 0}(1+z) with clusters of much lower mass than those explored previously; and we find that the cluster masses derived by Wen et al. from a richness-mass relationship are biased by a factor of (1+z){sup −1.8} with respect to the X-ray and weak-lensing measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1975

Further observations of the Orion Nebula cluster

New spectral types for 16 stars, UBVRI photometry for 13 stars and UBVRIHKL photometry for 35 stars in the Orion Nebula cluster are presented. Analysis of these data together with those of Penston (1973) shows that the reddening law in the cluster is normal. Previous claims for high ratios of total to selective absorption are caused by mistaking infrared emission for a hole in the absorption at that wavelength. The distance modulus of M42 is 8.0 + or - 0.1 mag. Star formation in the cluster has been in progress over the last 10 million yr. The infrared colors of cluster stars are correlated with their range of variation in the optical region.

Penston, M. V.↗
NASA NTRS1979

Interactive color display for multispectral imagery using correlation clustering

A method for processing multispectral data is provided, which permits an operator to make parameter level changes during the processing of the data. The system is directed to production of a color classification map on a video display in which a given color represents a localized region in multispectral feature space. Interactive controls permit an operator to alter the size and change the location of these regions, permitting the classification of such region to be changed from a broad to a narrow classification.

Haskell, R. E.↗
NASA NTRS1979

A search for X-ray emission from rich clusters, extended halos around clusters, and superclusters

HEAO A-2 X-ray observations of rich clusters, extended halos around clusters, and superclusters are discussed. Concerning the optically richest clusters, results in the 0.2-60 keV energy range show that they appear to be relatively underluminous in X-rays. It is found that X-ray and microwave measurements for some rich clusters and for Abell 576 can be used to meaningfully constrain intracluster gas parameters and H(0); in addition, observations of Abell 576 show its luminosity to be less than earlier estimates. Extended halos around clusters were not detected in the data, and spectral observations of Abell 401 and 2147 reveal that they have typical cluster spectra with iron-line emission, while intensity measurements indicate that supercluster X-ray emission is not required.

Pravdo, S. H.↗
NASA NTRS2000

[Compton GRO Cycle 7]

The goals of this project were to use the improved location accuracy of combined BATSE/Ulysses-IPN gamma-ray burst (GRB) data to search for small-angle clustering within the burst population and to search for possible correlations between bursts and catalogs of known astrophysical objects. The research was completed in several phases due to the length of time needed to process the basic BATSE/Ulysses data and to develop the appropriate analysis algorithms. In the first phase, BATSE/Ulysses data were gathered from their respective sources and processed to yield, final BATSE burst catalog locations and final BATSE/Ulysses IPN timing annuli. The final data are published. In the next phase, traditional statistical analysis techniques were used to search a subset of the data for small-angle clustering and. correlations, and to produce upper limits. Next, the unique analysis techniques and software described in the proposal were developed and,applied to the final set of data (corresponding to the 4B catalog). The final search did not find any significant self-clustering or correlations with supernovae, AGN, or near by galaxy clusters. The investigation ruled-out earlier findings that indicated (with marginal significance) such results, and. provided stringent limits on the allowable fraction of bursts that are self-clustered and associated with selected known objects. An added benefit of this research came in 1998 when it was suggested that some gamma-ray bursts may be associated with supernova (SN) explosions. We responded rapidly and applied the tools of this investigation to study this possibility. Using combined BATSE/Ulysses data, we were able to completely rule out any association between bright bursts and known supernovae, thereby questioning the validity of any GRB/SN association. If a GRB/SN association exists, it must be only with a small fraction of weak bursts.

Kippen, R. Marc↗
DOE OSTI2023

Fast tree-based algorithms for DBSCAN for low-dimensional data on GPUs

DBSCAN is a well-known density-based clustering algorithm to discover arbitrary shape clusters. While conceptually simple in serial, the algorithm is challenging to efficiently parallelize on manycore GPU architectures. Common pitfalls, such as asynchronous range query calls, result in high thread execution divergence in many implementations. In this paper, we propose a new framework for GPU-accelerated DBSCAN, and describe two tree-based algorithms within that framework. Both algorithms fuse the search for neighbors with updating cluster information, but differ in their treatment of dense regions of the data. We show that the time taken to compute clusters is at most twice that of determination of the neighbors. We compare the proposed algorithms with existing CPU and GPU implementations, and demonstrate their competitiveness and performance using a fast traversal structure (bounding volume hierarchy) for low dimensional data. We also show that the memory usage can be reduced by processing object neighbors dynamically without storing them.

Prokopenko, Andrey↗
DOE OSTI2014

A Structure-Based Distance Metric for High-Dimensional Space Exploration with Multi-Dimensional Scaling

Although the Euclidean distance does well in measuring data distances within high-dimensional clusters, it does poorly when it comes to gauging inter-cluster distances. This significantly impacts the quality of global, low-dimensional space embedding procedures such as the popular multi-dimensional scaling (MDS) where one can often observe non-intuitive layouts. We were inspired by the perceptual processes evoked in the method of parallel coordinates which enables users to visually aggregate the data by the patterns the polylines exhibit across the dimension axes. We call the path of such a polyline its structure and suggest a metric that captures this structure directly in high-dimensional space. This allows us to better gauge the distances of spatially distant data constellations and so achieve data aggregations in MDS plots that are more cognizant of existing high-dimensional structure similarities. Our MDS plots also exhibit similar visual relationships as the method of parallel coordinates which is often used alongside to visualize the high-dimensional data in raw form. We then cast our metric into a bi-scale framework which distinguishes far-distances from near-distances. The coarser scale uses the structural similarity metric to separate data aggregates obtained by prior classification or clustering, while the finer scale employs the appropriate Euclidean distance.

Clustering↗
DOE OSTI2017

WIYN Open Cluster Study. LXXV. Testing the Metallicity Dependence of Stellar Lithium Depletion Using Hyades-aged Clusters. I. Hyades and Praesepe

WIYN/Hydra spectroscopy (at R ∼ 15,000) of the moderately metal-rich Praesepe and Hyades open clusters was used to study their main-sequence (MS) iron ([Fe/H]) and lithium (A(Li)) abundances. Self-consistent [Fe/H] and Li analyses of these clusters of consistent age, which we re-evaluate, confirms that they have consistent [Fe/H] and provides a foundation to investigate the poorly understood G-dwarf and F-dwarf Li-depletions. Neither phenomenon agrees with standard stellar evolution theory, but possible explanations abound. We supplement our A(Li) with previously published results placed on a uniform abundance scale. This creates the largest self-consistently analyzed sample of A(Li) in both the Hyades (90) and Praesepe (110). For each star, high-precision UBVRI photometry was used to determine a 10-color-based T{sub eff} and then to test for photometric peculiarities indicated by a large σ{sub Teff} (>75 K). The stars that have large σ{sub Teff} were predominantly found to be binaries or stars with peculiar (apparent) A(Li). When considering only proper-motion members that have low σ{sub Teff} and are also photometrically consistent with the cluster MS fiducial, each cluster has a more tightly defined Li morphology than previously observed and the two clusters’ A(Li) are indistinguishable. This suggests that clusters of consistent age and metallicity may have consistent Li-depletion trends across a broad range of T{sub eff}; no additional major parameters are required, at least for these two clusters. We propose that the combined Hyades and Praesepe data offer more rigorous constraints than does either cluster alone, and we discuss newly revealed features of the combined Li–T{sub eff} trend.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1981

X-ray observations and the cosmic distance scale

The physics of hot gas in the cores of distant clusters of galaxies can be studied in considerable detail through a specific combination of X-ray, microwave and optical observations. In principle, the X-ray luminosity of the gas can be calculated from these data, providing a measure of the cluster distance. These ideas and their application to Abell 2218, the only cluster for which even marginally suitable data yet exist are examined.

Boynton, P. E.↗
NASA NTRS2002

Distant Cluster Hunting: A Comparison of X-Ray and Optical Cluster Detection Techniques and Catalogs from the ROSAT Optical X-Ray Survey - II

We present and analyze the optical and X-ray catalogs of moderate-redshift cluster candidates from the ROSA TOptical X-Ray Survey, or ROXS. The survey covers the sky area contained in the fields of view of 23 deep archival ROSA T PSPC pointings, 4.8 square degrees. The cross-correlated cluster catalogs were con- structed by comparing two independent catalogs extracted from the optical and X-ray bandpasses, using a matched-filter technique for the optical data and a wavelet technique for the X-ray data. We cross-identified cluster candidates in each catalog. As reported in Paper 1, the matched-filter technique found optical counter- parts for at least 60% (26 out of 43) of the X-ray cluster candidates; the estimated redshifts from the matched filter algorithm agree with at least 7 of 1 1 spectroscopic confirmations (Az 5 0.10). The matched filter technique. with an imaging sensitivity of ml N 23, identified approximately 3 times the number of candidates (155 candidates, 142 with a detection confidence >3 u) found in the X-ray survey of nearly the same area. There are 57 X-ray candidates, 43 of which are unobscured by scattered light or bright stars in the optical images. Twenty-six of these have fairly secure optical counterparts. We find that the matched filter algorithm, when applied to images with galaxy flux sensitivities of mI N 23, is fairly well-matched to discovering z 5 1 clusters detected by wavelets in ROSAT PSPC exposures of 8000-60,000 s. The difference in the spurious fractions between the optical and X-ray (30%) and IO%, respectively) cannot account for the difference in source number. In Paper I, we compared the optical and X-ray cluster luminosity functions and we found that the luminosity functions are consistent if the relationship between X-ray and optical luminosities is steep (Lx o( L&f). Here, in Paper 11, we present the cluster catalogs and a numerical simulation of the ROXS. We also present color-magnitude plots for several of the cluster candidates, and examine the prominence of the red sequence in each. We find that the X-ray clusters in our survey do not all have a prominent red sequence. We conclude that while the red sequence may be a distinct feature in the color-magnitude plots for virialized massive clusters, it may be less distinct in lower mass clusters of galaxies at even moderate redshifts. Multiple, complementary methods of selecting and defining clusters may be essential, particularly at high redshift where all methods start to run into completeness limits, incomplete understanding of physical evolution, and projection effects.

Donahue, Megan↗
DOE OSTI2020

Deconvolute individual genomes from metagenome sequences through short read clustering

Metagenome assembly from short next-generation sequencing data is a challenging process due to its large scale and computational complexity. Clustering short reads by species before assembly offers a unique opportunity for parallel downstream assembly of genomes with individualized optimization. However, current read clustering methods suffer either false negative (under-clustering) or false positive (over-clustering) problems. Here we extended our previous read clustering software, SpaRC, by exploiting statistics derived from multiple samples in a dataset to reduce the under-clustering problem. Using synthetic and real-world datasets we demonstrated that this method has the potential to cluster almost all of the short reads from genomes with sufficient sequencing coverage. The improved read clustering in turn leads to improved downstream genome assembly quality.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Dark Matter Searches with Cherenkov Telescopes: Nearby Dwarf Galaxies or Local Galaxy Clusters?

In this paper, we compare dwarf galaxies and galaxy clusters in order to elucidate which object class is the best target for gamma-ray DM searches with imaging atmospheric Cherenkov telescopes (IACTs). We have built a mixed dwarfs+clusters sample containing some of the most promising nearby dwarf galaxies (Draco, Ursa Minor, Wilman 1 and Segue 1) and local galaxy clusters (Perseus, Coma, Ophiuchus, Virgo, Fornax, NGC 5813 and NGC 5846), and then compute their DM annihilation flux profiles by making use of the latest modeling of their DM density profiles. We also include in our calculations the effect of DM substructure. Willman 1 appears as the best candidate in the sample. However, its mass modeling is still rather uncertain, so probably other candidates with less uncertainties and quite similar fluxes, namely Ursa Minor and Segue 1, might be better options. As for galaxy clusters, Virgo represents the one with the highest flux. However, its large spatial extension can be a serious handicap for IACT observations and posterior data analysis. Yet, other local galaxy cluster candidates with more moderate emission regions, such as Perseus, may represent good alternatives. After comparing dwarfs and clusters, we found that the former exhibit annihilation flux profiles that, at the center, are roughly one order of magnitude higher than those of clusters, although galaxy clusters can yield similar, or even higher, integrated fluxes for the whole object once substructure is taken into account. Even when any of these objects are strictly point-like according to the properties of their annihilation signals, we conclude that dwarf galaxies are best suited for observational strategies based on the search of point-like sources, while galaxy clusters represent best targets for analyses that can deal with rather extended emissions. Finally, we study the detection prospects for present and future IACTs in the framework of the constrained minimal supersymmetric standard model. We find that the level of the annihilation flux from these targets is below the sensitivities of current IACTs and the future CTA.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A Knowledge Network-Based Approach to Facilitate Annotation of Clinical Pathway Component Clusters

Mining electronic health records (EHRs) to identify contextually related clinical concept clusters that tend to co-occur temporarily and consistently could improve data-driven clinical pathway (CP) construction. However, the automatic extraction of contextually related clinical concept clusters contains a vast amount of irrelevant information. Hence, this paper proposes a knowledge network-enabled literature-based discovery (LBD) approach to remove noise from clusters. The authors used published literature to filter spurious concepts from the clusters and used data from the US Department of Veterans Affairs’s major depressive disorder (MDD) cohort of Operation Enduring Freedom/Operation Iraqi Freedom (OEF/OIF) for their experimentation. The approach was applied to 2,967 clusters extracted from the MDD OEF/OIF database. The experimental results demonstrate that the proposed approach can filter 94% of the irrelevant information. Moreover, the authors applied various network mining algorithms to analyze the clusters and demonstrated that LBD, along with network mining techniques, is a useful method for finding accurate contextually related clinical concept clusters. This could help domain researchers perform advanced analytics in CPs.

Hasan, S M Shamimul↗
DOE OSTI2011

DPP-4 inhibitor des-F-sitagliptin treatment increased insulin exocytosis from db/db mice {beta} cells

Highlights: {yields} Anti-diabetic new drug, DPP-4 inhibitor, can affect the insulin exocytosis. {yields} DPP-4 inhibitor treatment altered syntaxin 1 expression. {yields} Treatment of db/db mice with DPP-4 inhibitor increased insulin release. -- Abstract: Incretin promotes insulin secretion acutely. Recently, orally-administered DPP-4 inhibitors represent a new class of anti-hyperglycemic agents. Indeed, inhibitors of dipeptidyl peptidase-IV (DPP-4), sitagliptin, has just begun to be widely used as therapeutics for type 2 diabetes. However, the effects of sitagliptin-treatment on insulin exocytosis from single {beta}-cells are yet unknown. We therefore investigated how sitagliptin-treatment in db/db mice affects insulin exocytosis by treating db/db mice with des-F-sitagliptin for 2 weeks. Perfusion studies showed that 2 weeks-sitagliptin treatment potentiated insulin secretion. We then analyzed insulin granule motion and SNARE protein, syntaxin 1, by TIRF imaging system. TIRF imaging of insulin exocytosis showed the increased number of docked insulin granules and increased fusion events from them during first-phase release. In accord with insulin exocytosis data, des-F-sitagliptin-treatment increased the number of syntaxin 1 clusters on the plasma membrane. Thus, our data demonstrated that 2-weeks des-F-sitagliptin-treatment increased the fusion events of insulin granules, probably via increased number of docked insulin granules and that of syntaxin 1 clusters.

60 APPLIED LIFE SCIENCES↗