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At least 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Coupled-channels study of fine structure in the {alpha} decay of platinum isotopes

The fine structure observed in the {alpha} decay of deformed platinum isotopes is investigated using the recently developed five-channel formalism, based on the coupled-channel Schroedinger equation with outgoing wave boundary conditions. The internal effect of daughter states is taken into account in dealing with the interaction matrix and the {alpha}-cluster formation. The available experimental data concerning {alpha}-decay half-lives and fine structures are reproduced. Some predictions are made especially for the {alpha} decay of neutron-rich isotopes, which could guide future experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Joint Management and Optimization of Residential Natural Gas and Electricity Distribution Networks Coupled via Fuel Cells

The attractive features of natural gas as well as the growing electric power demand worldwide have created increasing interest in natural-gas-based distributed generation applications for electric distribution networks. Here, this paper investigates the interdependency between a residential natural gas network and an electric distribution network that are linked together via fuel cells. The modeling of the natural gas network is introduced first, and then the algorithm for gas flow study is presented. The optimal placement and sizing of fuel cell based distributed generation systems are formulated to minimize the losses in both the natural gas network and the electric distribution grid, subject to the constraints imposed by both networks. In addition, a probabilistic model for both gas and electricity demands is developed based on historical electricity and natural gas demand data. A K-means clustering method is used to determine the hourly load states to solve the joint probabilistic optimization problem. Simulation studies are carried out on an integrated system consisting of the IEEE 69-bus distribution network and a radial 27-node natural gas network to verify the developed optimization model and the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Cellulose synthase gene expression profiling of Physcomitrella patens

Abstract The cellulose synthase ( CESA ) gene family of seed plants comprises six clades that encode isoforms with conserved expression patterns and distinct functions in cellulose synthesis complex ( CSC ) formation and primary and secondary cell wall synthesis. In mosses, which have rosette CSC s like those of seed plants but lack lignified secondary cell walls, the CESA gene family diversified independently and includes no members of the six functionally distinct seed plant clades. There are seven CESA isoforms encoded in the genome of the moss Physcomitrella patens . However, only Pp CESA 5 has been characterised functionally, and little information is available on the expression of other Pp CESA family members. We have profiled Pp CESA expression through quantitative RT ‐ PCR , analysis of promoter‐reporter lines, and cluster analysis of public microarray data in an effort to identify expression and co‐expression patterns that could help reveal the functions of Pp CESA isoforms in protein complex formation and development of specific tissues. In contrast to the tissue‐specific expression observed for seed plant CESA s, each of the Pp CESA s was broadly expressed throughout most developing tissues. Although a few statistically significant differences in expression of Pp CESA s were noted when some tissues and hormone treatments were compared, no strong co‐expression patterns were observed. Along with CESA phylogenies and lack of single Pp CESA mutant phenotypes reported elsewhere, broad overlapping expression of the Pp CESA s indicates a high degree of inter‐changeability and is consistent with a different pattern of functional specialisation in the evolution of the seed plant and moss CESA families.

Tran, M. L.↗
DOE OSTI2020

TripleGraph

RDF triplestores are great tools for online graph analytic processing (i.e., graph pattern query processing), but they do not provide graph mining capabilities (e.g., PageRank, connected-component analysis, node eccentricity, etc.). The software title “TripleGraph” is a graph analysis toolkit, which uses an RDF triplestore as its backend for creating, manipulating, mining, and programming with large scale property graphs. It allows users to run various graph mining algorithms easily. User can import edgelist-formatted (homogeneous graph) or JSON-formatted graph (property graph) into the RDF triplestore using the provided tool and perform various analysis such as (1) Node/edge retrieval and manipulation, (2) Pathfinding between two given nodes, (3) Running graph mining algorithms (PageRank/Personalized PageRank, Single Source Shortest Path/Multi-Source Shortest Path, Connected Component, Node Eccentricity, Peer Pressure Clustering). It supports standard graph data format and works with a standard SPARQL endpoint like Jena Fuseki. It allows users to perform online graph analytic processing and graph mining on the same platform (a triplestore).

Sangkeun, MattLee↗
DOE OSTI2012

Functional Annotation of Hierarchical Modularity

In biological networks of molecular interactions in a cell, network motifs that are biologically relevant are also functionally coherent, or form functional modules. These functionally coherent modules combine in a hierarchical manner into larger, less cohesive subsystems, thus revealing one of the essential design principles of system-level cellular organization and function–hierarchical modularity. Arguably, hierarchical modularity has not been explicitly taken into consideration by most, if not all, functional annotation systems. As a result, the existing methods would often fail to assign a statistically significant functional coherence score to biologically relevant molecular machines. We developed a methodology for hierarchical functional annotation. Given the hierarchical taxonomy of functional concepts (e.g., Gene Ontology) and the association of individual genes or proteins with these concepts (e.g., GO terms), our method will assign a Hierarchical Modularity Score (HMS) to each node in the hierarchy of functional modules; the HMS score and its p{value measure functional coherence of each module in the hierarchy. While existing methods annotate each module with a set of ‘‘enriched’’ functional terms in a bag of genes, our complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components. A hierarchical organization of functional modules often comes as a bi-product of cluster analysis of gene expression data or protein interaction data. Otherwise, our method will automatically build such a hierarchy by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. In addition, its underlying HMS scoring metric ensures that functional specificity of the terms across different levels of the hierarchical taxonomy is properly treated. We have evaluated our method using Saccharomyces cerevisiae data from KEGG and MIPS databases and several other computationally derived and curated datasets. The code and additional supplemental files can be obtained from http:// code.google.com/p/functional-annotation-of-hierarchical-modularity/ (Accessed 2012 March 13).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Evaluation of Seismic Artificial Intelligence with Uncertainty

Artificial intelligence has transformed the seismic community with deep learning models (DLMs) that are trained to complete specific tasks within workflows. However, there is still a lack of robust evaluation frameworks for evaluating and comparing DLMs. Here, we address this gap by designing an evaluation framework that jointly incorporates two crucial aspects: performance uncertainty and learning efficiency. To target these aspects, we meticulously construct the training, validation, and test splits using a clustering method tailored to seismic data and enact an expansive training design to segregate performance uncertainty arising from stochastic training processes and random data sampling. The framework’s ability to guard against misleading declarations of model superiority is demonstrated through the evaluation of PhaseNet (Zhu and Beroza, 2018), a popular seismic phase picking DLM, under three training approaches. Our framework helps practitioners choose the best model for their problem and set performance expectations by explicitly analyzing model performance with uncertainty at varying budgets of training data.

58 GEOSCIENCES↗
DOE OSTI2023

JIRIAF: JLAB Integrated Research Infrastructure Acros Facilities

The JIRIAF project aims to combine geographically diverse computing facilities into an integrated science infrastructure. This project starts by dynamically evaluating temporarily unallocated or idled compute resources from multiple providers. These resources are integrated to handle additional workloads without affecting local running jobs. This paper describes our approach to launch best-effort batch tasks which exploit these underutilized resources. Our system measures the real-time behavior of jobs running on a machine and learns to distinguish typical performance from outliers. Unsupervised ML techniques are used to analyze hardware-level performance measures, followed by a real-time cross-correlation analysis to determine which applications cause performance degradation. We then ameliorate bad behavior by throttling these processes. We demonstrate that problematic performance interference can be detected and acted on, which makes it possible to continue to share resources between applications and simultaneously maintain high utilization levels in a computing cluster. We relocate the CLAS12 data processing workflow to a remote data center for a case study, preventing file migration and temporal data persistency.

Lawrence, David↗
NASA NTRS1975

Delineation of the boundaries of a buried pre-glacial valley with LANDSAT-1 data

The continuity of a narrow meandering strip of Udoll (prairie) soils running east and west for approximately 40 miles across north central Indiana in an area predominantly of Udalfs (timber soils) was detected from LANDSAT-1 data taken on June 9, 1973. This data was processed through a clustering procedure and classified with resulting increased definition of the boundaries among soils grouped according to nine categories and vegetation to two categories of reflectance. This dark stretch of prairie soil is believed to have formed in the heavy textured, poorly drained glacial debris which filled a major pre-glacial tributary of the Teays River System. Ready identification and location of the valley has significance to soil survey and land classification people as a guide to soil classification and land use and to geologists as a guide to location of a potentially economically significant aquifer.

Peterson, J. B.↗
NASA NTRS1976

CO observations of NGC 1579 /S222/ and S239

The 2.6-mm lines of (C-12)O and (C-13)O have been observed toward the small galactic diffuse nebulae NGC 1579 (S222) and S239. The H92-alpha recombination line has also been detected from NGC 1579. Toward NGC 1579, evidence was observed for self-absorption in the (C-12)O line. For both regions, high-velocity wings and line broadening are observable in the (C-12)O line; the features observed toward S239 suggest ordered free-fall collapse of a localized region of the cloud onto a newborn stellar cluster. Examination of the available data suggests that NGC 1579 is both a reflection nebula (illuminated by LKH-alpha 101) and an obscured H II region excited by a star of spectral type near B1, while S239 is a reflection nebula or a Herbig-Haro object. The present studies of these regions show that line widening in CO is at least as important an indicator of star-formation activity as enhanced line emission.

Knapp, G. R.↗
NASA NTRS1978

The lunar highland melt-rock suite

Size can be used as a criterion to select 18 large (larger than 1 cm) samples from among 148 melt-rock fragments of all sizes. This selection provides a suite of large samples which represent the important chemical variants among highland melt rocks; each large sample has enough material for a number of sample-destructive studies, as well as for future reference. Cluster analysis of the total data base of 148 highland melt rocks shows six distinct groups: anorthosite, gabbroic anorthosite, anorthositic gabbro ('highland basalt'), low K Fra Mauro, intermediate-K Fra Mauro, and high-K. Large samples are available for four of the melt-rock groups (gabbroic anorthosite, anorthositic gabbro, low-K Fra Mauro, and intermediate-K Fra Mauro). This sample selection reveals two subgroups of anorthositic gabbro (one anorthite-poor with negative Eu anomaly and one anorthite-rich without Eu anomaly). There is a sharp distinction between those Apollo 16 melt rocks and glasses which have both been classified as 'gabbroic anorthosite'.

Vaniman, D. T.↗
NASA NTRS1980

The photometric properties of brightest cluster galaxies. II - SIT and CCD surface photometry

Surface photometry of the first-ranked galaxy in 108 Abell clusters is presented. Galaxy structure, as parameterized by simple Hubble law models, is found to correlate with galaxy absolute magnitude and cluster structure. All the structure data support the dynamical friction evolution model. Twenty-eight percent of the galaxies have multiple component nuclei; the short lifetimes of such systems provide the best available evidence that ongoing evolution actually occurs. Average magnitude and structure evolution rates are derived from the data.

Hoessel, J. G.↗
NASA NTRS1980

Computer classified Landsat data used as a forest stratifier

Results of two forest stratification projects are presented to show that Landsat data, when combined with guided clustering techniques, can provide detailed stratification of forest environment. It is shown that conifer species groupings, vegetative cover classes, and three size classes can be discriminated with accuracies ranging from 83 to 91%.

Fox, L., III↗
NASA NTRS1985

Lightning on Venus

On the night side of Venus, the plasma wave instrument on the Pioneer-Venus Orbiter frequently detects strong and impulsive low-frequency noise bursts when the local magnetic field is strong and steady and when the field is oriented to point down to the ionosphere. The signals have characteristics of lightning whistlers, and an attempt was made to identify the sources by tracing rays along the B-field from the Orbiter down toward the surface. An extensive data set strongly indicates a clustering of lightning sources near the Beta and Phoebe Regios, with additional significant clustering near the Atla Regio at the eastern edge of Aphrodite Terra. These results suggest that there are localized lightning sources at or near the planetary surface.

Scarf, F. L.↗
NASA NTRS1986

Multicolor photometry of field galaxies to B = 24

The redshifts and colors of nearly 10,000 galaxies at galactic latitudes SA57 and SA68 were determined by photometric scans which included UV and near-IR bands, covering 0.5 sq deg of sky. Slopes were calculated for UV, IR, red and blue counts of galaxies with respect to the brightness detected. It was found that galaxies of magnitudes over 20 show increasingly greater UV excess, which may be indicative of star formation regions. Future applications of the data generated for examining galaxy clustering patterns and evolutionary scenarios are discussed.

Koo, David C.↗
NASA NTRS1989

Global properties of infrared bright galaxies

Infrared flux densities of 182 galaxies, including 50 galaxies in the Virgo cluster, were analyzed using IRAS data for 12, 25, 60, and 100 microns, and the results were compared with data listed in the Point Source Catalog (PSC, 1985). In addition, IR luminosities, L(IRs), colors, and warm dust masses were derived for these galaxies and were compared with the interstellar gas masses and optical luminosities of the galaxies. It was found that, for galaxies whose optical diameter measures between 5 and 8 arcmin, the PSC flux densities are underestimated by a factor of 2 at 60 microns, and by a factor of 1.5 at 100 microns. It was also found that, for 49 galaxies, the mass of warm dust correlated well with the H2 mass, and that L(IR) correlated with L(H-alpha), demonstrating that the L(IR) measures the rate of star formation in these galaxies.

Young, Judith S.↗
NASA NTRS1993

A catalog of intracluster gas temperatures

We have searched the Einstein Monitor Proportional Counter (MPC) data base for observations of clusters of galaxies. By coadding the MPC spectra obtained during all pointed observations of clusters with IPC count rates greater than 0.1 counts/s, we have obtained sufficient photon statistics to estimate the X-ray temperature of 84 clusters. Combining the MPC results with EXOSAT and Ginga results reported in the literature yields a combined sample of 104 clusters with known X-ray temperatures. One of the best studied X-ray correlations between clusters is that between their X-ray luminosity and gas temperature. We show that the best-fit power-law relation for our combined cluster sample can be explained by the observed increase in the gas-to-stellar mass ratio between low- and high-temperature clusters. The statistical significance of any evolution in our combined X-ray sample has been examined and compared with the statistical properties of clusters culled from optical catalogs. We find that there is strong evidence for a decrease in the X-ray luminosity of optically rich clusters beyond z approximately about 0.06. This result is used to estimate the normalization of the primordial power spectrum of density fluctuations.

David, L. P.↗
NASA NTRS1995

Issues in ATM Support of High-Performance, Geographically Distributed Computing

This report experimentally assesses the effect of the underlying network in a cluster-based computing environment. The assessment is quantified by application-level benchmarking, process-level communication, and network file input/output. Two testbeds were considered, one small cluster of Sun workstations and another large cluster composed of 32 high-end IBM RS/6000 platforms. The clusters had Ethernet, fiber distributed data interface (FDDI), Fibre Channel, and asynchronous transfer mode (ATM) network interface cards installed, providing the same processors and operating system for the entire suite of experiments. The primary goal of this report is to assess the suitability of an ATM-based, local-area network to support interprocess communication and remote file input/output systems for distributed computing.

Claus, Russell W.↗