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NASA NTRS2003

A Step Beyond Simple Keyword Searches: Services Enabled by a Full Content Digital Journal Archive

The problems of managing and searching large archives of scientific journal articles can potentially be addressed through data mining and statistical techniques matured primarily for quantitative scientific data analysis. A journal paper could be represented by a multivariate descriptor, e.g., the occurrence counts of a number key technical terms or phrases (keywords), perhaps derived from a controlled vocabulary ( e . g . , the American Meteorological Society's Glossary of Meteorology) or bootstrapped from the journal archive itself. With this technique, conventional statistical classification tools can be leveraged to address challenges faced by both scientists and professional societies in knowledge management. For example, cluster analyses can be used to find bundles of "most-related" papers, and address the issue of journal bifurcation (when is a new journal necessary, and what topics should it encompass). Similarly, neural networks can be trained to predict the optimal journal (within a society's collection) in which a newly submitted paper should be published. Comparable techniques could enable very powerful end-user tools for journal searches, all premised on the view of a paper as a data point in a multidimensional descriptor space, e.g.: "find papers most similar to the one I am reading", "build a personalized subscription service, based on the content of the papers I am interested in, rather than preselected keywords", "find suitable reviewers, based on the content of their own published works", etc. Such services may represent the next "quantum leap" beyond the rudimentary search interfaces currently provided to end-users, as well as a compelling value-added component needed to bridge the print-to-digital-medium gap, and help stabilize professional societies' revenue stream during the print-to-digital transition.

Boccippio, Dennis J.↗
NASA NTRS2012

The Herschel Multi-tiered Extragalactic Survey: HerMES

The Herschel Multi-tiered Extragalactic Survey, HerMES, is a legacy program designed to map a set of nested fields totalling approx. 380 deg(exp 2). Fields range in size from 0.01 to approx. 20 deg (exp 2), using Herschel-SPIRE (at 250, 350 and 500 micron), and Herschel-PACS (at 100 and 160 micron), with an additional wider component of 270 deg. (exp. 2) with SPIRE alone. These bands cover the peak of the redshifted thermal spectral energy distribution from interstellar dust and thus capture the re-processed optical and ultra-violet radiation from star formation that has been absorbed by dust, and are critical for forming a complete multi-wavelength understanding of galaxy formation and evolution. The survey will detect of order 100,000 galaxies at 5-sigma in some of the best studied fields in the sky. Additionally, HerMES is closely coordinated with the PACS Evolutionary Probe survey. Making maximum use of the full spectrum of ancillary data, from radio to X-ray wavelengths, it is designed to: facilitate redshift determination; rapidly identify unusual objects; and understand the relationships between thermal emission from dust and other processes. Scientific questions HerMES will be used to answer include: the total infrared emission of galaxies; the evolution of the luminosity function; the clustering properties of dusty galaxies; and the properties of populations of galaxies which lie below the confusion limit through lensing and statistical techniques. This paper defines the survey observations and data products, outlines the primary scientific goals of the HerMES team, and reviews some of the early results.

multi-tiered↗
NASA NTRS2021

A NICER Look at Thermonuclear X-ray Bursts from Aql X-1

We present spectral and temporal properties of all the thermonuclear X-ray bursts observed from Aql X-1 by the Neutron StarInterior and Composition Explorer (NICER) between 2017 July and 2021 April. This is the first systematic investigation of alarge sample of type I X-ray bursts from Aql X-1 with improved sensitivity at low energies. We detect 22 X-ray bursts includingtwo short recurrence burst events in which the separation was only 451 s and 496 s. We perform time resolved spectroscopy of thebursts using the fixed and scaled background (fa method) approaches. We show that the use of a scaling factor to the pre-burstemission is the statistically preferred model in about 68% of all the spectra compared to the fixed background approach. Typically the fa values are clustered around 1–3, but can reach up to 11 in a burst where photospheric radius expansion is observed. Such fa values indicate a very significant increase in the pre-burst emission especially at around the peak flux moments of the bursts.We show that the use of the fa factor alters the best fit spectral parameters of the burst emission. Finally, we employed a reflectionmodel instead of scaling the pre-burst emission. We show that reflection models also do fit the spectra and improve the goodnessof the fits. In all cases we see that the disc is highly ionized by the burst emission and the fraction of the reprocessed emission tothe incident burst flux is typically clustered around 20%

Tolga Güver↗
NASA NTRS2016

The XXL Survey I. Scientific Motivations - Xmm-Newton Observing Plan - Follow-up Observations and Simulation Programme

The quest for the cosmological parameters that describe our universe continues to motivate the scientific community to undertake very large survey initiatives across the electromagnetic spectrum. Over the past two decades, the Chandra and XMM-Newton observatories have supported numerous studies of X-ray-selected clusters of galaxies, active galactic nuclei (AGNs), and the X-ray background. The present paper is the first in a series reporting results of the XXL-XMM survey; it comes at a time when the Planck mission results are being finalized. Aims. We present the XXL Survey, the largest XMM programme totaling some 6.9 Ms to date and involving an international consortium of roughly 100 members. The XXL Survey covers two extragalactic areas of 25 deg2 each at a point-source sensitivity of approx. 5 x 10(exp 15) erg/s/sq cm in the [0.5-2] keV band (completeness limit). The surveys main goals are to provide constraints on the dark energy equation of state from the space-time-distribution of clusters of galaxies and to serve as a pathfinder for future, wide-area X-ray missions. We review science objectives, including cluster studies, AGN evolution, and large-scale structure, that are being conducted with the support of approximately 30 follow-up programs. Methods. We describe the 542 XMM observations along with the associated multi- and numerical simulation programmes. We give a detailed account of the X-ray processing steps and describe innovative tools being developed for the cosmological analysis. Results. The paper provides a thorough evaluation of the X-ray data, including quality controls, photon statistics, exposure and background maps, and sky coverage. Source catalogue construction and multi-associations are briefly described. This material will be the basis for the calculation of the cluster and AGN selection functions, critical elements of the cosmological and science analyses. Conclusions. The XXL multi- data set will have a unique lasting legacy value for cosmological and extragalactic studies and will serve asa calibration resource for future dark energy studies with clusters and other X-ray selected sources. With the present article, we release the XMM XXL photon and smoothed images along with the corresponding exposure maps.

X-rays: general – large-scale structure of Unive↗
NASA NTRS2012

Observations of How Magnetofluid Turbulence Dissipates at Small Scales

The solar wind is a turbulent magneto fluid that can be studied intensively at multiple scales. Investigations using single spacecraft have revealed much about the properties of the solar wind throughout the heliosphere (from 0.3 AU to 100 AU). More recently, data from multiple spacecraft have provided further details of both the statistical properties of the turbulence and its small-scale structure. In particular, high time resolution magnetic field measurements from the four Cluster spacecrafl have led to the conclusion that at spatial scales of order the proton inertial length and smaller, the turbulence becomes strongly anisotropic and the power in fluctuations that are perpendicular to the (local) magnetic field is measured to be much larger than that in fluctuations that are parallel to the magnetic field. As the spatial scales approach the electron inertial length, the power is almost completely dissipated. Various analysis techniques and theoretical ideas have been put forward to account for the properties of those measurements. The talk will describe the current state of observations, theory and simulations.

Goldstein, M. L.↗
NASA NTRS2017

Classifying Multi-Model Wheat Yield Impact Response Surfaces Showing Sensitivity to Temperature and Precipitation Change

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (minus 2 to plus 9 degrees Centigrade) and precipitation (minus 50 to plus 50 percent). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.

Classification; Climate change; Crop model; Ensemb↗
NASA NTRS2005

INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS

Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.

Iverson, David L.↗
NASA NTRS1980

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

Several possibilities were considered for defining the data set in which the same test areas could be used for each of the four different spatial resolutions being evaluated. The LARSYS CLUSTER was used to sort the vectors into spectral classes to reduce the within-spectral class variability in an effort to develop training statistics. A data quality test was written to determine the basic signal to noise characteristics within the data set being used. Because preliminary analysis of the LANDSAT MSS data revealed the presence of high cirrus clouds, other data sets are being sought.

Hoffer, R. M.↗
NASA NTRS1997

Computer Supported Indexing: A History and Evaluation of NASA's MAI System

Computer supported indexing systems may be categorized in several ways. One classification scheme refers to them as statistical, syntactic, semantic or knowledge-based. While a system may emphasize one of these aspects, most systems actually combine two or more of these mechanisms to maximize system efficiency. Statistical systems can be based on counts of words or word stems, statistical association, and correlation techniques that assign weights to word locations or provide lexical disambiguation, calculations regarding the likelihood of word co-occurrences, clustering of word stems and transformations, or any other computational method used to identify pertinent terms. If words are counted, the ones of median frequency become candidate index terms. Syntactical systems stress grammar and identify parts of speech. Concepts found in designated grammatical combinations, such as noun phrases, generate the suggested terms. Semantic systems are concerned with the context sensitivity of words in text. The primary goal of this type of indexing is to identify without regard to syntax the subject matter and the context-bearing words in the text being indexed. Knowledge-based systems provide a conceptual network that goes past thesaurus or equivalent relationships to knowing (e.g., in the National Library of Medicine (NLM) system) that because the tibia is part of the leg, a document relating to injuries to the tibia should he indexed to LEG INJURIES, not the broader MeSH term INJURIES, or knowing that the term FEMALE should automatically be added when the term PREGNANCY is assigned, and also that the indexer should be prompted to add either HUMAN or ANIMAL. Another way of categorizing indexing systems is to identify them as producing either assigned- or derived-term indexes.

Silvester, June P.↗
NASA NTRS2011

Space Radiation Effects on Human Cells: Modeling DNA Breakage, DNA Damage Foci Distribution, Chromosomal Aberrations and Tissue Effects

Future long-tem space travel will face challenges from radiation concerns as the space environment poses health risk to humans in space from radiations with high biological efficiency and adverse post-flight long-term effects. Solar particles events may dramatically affect the crew performance, while Galactic Cosmic Rays will induce a chronic exposure to high-linear-energy-transfer (LET) particles. These types of radiation, not present on the ground level, can increase the probability of a fatal cancer later in astronaut life. No feasible shielding is possible from radiation in space, especially for the heavy ion component, as suggested solutions will require a dramatic increase in the mass of the mission. Our research group focuses on fundamental research and strategic analysis leading to better shielding design and to better understanding of the biological mechanisms of radiation damage. We present our recent effort to model DNA damage and tissue damage using computational models based on the physics of heavy ion radiation, DNA structure and DNA damage and repair in human cells. Our particular area of expertise include the clustered DNA damage from high-LET radiation, the visualization of DSBs (DNA double strand breaks) via DNA damage foci, image analysis and the statistics of the foci for different experimental situations, chromosomal aberration formation through DSB misrepair, the kinetics of DSB repair leading to a model-derived spectrum of chromosomal aberrations, and, finally, the simulation of human tissue and the pattern of apoptotic cell damage. This compendium of theoretical and experimental data sheds light on the complex nature of radiation interacting with human DNA, cells and tissues, which can lead to mutagenesis and carcinogenesis later in human life after the space mission.

Ponomarev, A. L.↗
NASA NTRS1960

On Ion Clusters in the Interstellar Gas

In a recent paper V.I. Krassovsky (1958) predicts the occurrence of clusters of large numbers of atoms and molecules around ions in the interstellar gas. He then proposes a number of physicochemical processes that would be considerably enhanced by the high particle density in such clusters. In particular, he suggests that absorption by negative ions formed in the clusters would account for the interstellar extinction without any necessity for the presence of grains. Because of the important consequences that ion clusters could have, it is necessary to examine their occurrence more fully. This note re-examines the formation of ion clusters in space and shows that even ion-molecule pairs are essentially non-existent. Ion clusters have been considered by Bloom and Margenau (1952) from the same point of view as that used by Krassovsky, whose basic reference (Joffe and Semenov 1933) unfortunately is not available. A different approach has been used by Eyring, Hirschfelder, and Taylor (1936) following the methods of chemical equilibrium. Both the references cited here enable one to conclude that clustering is negligible. Therefore, the treatment of Eyring et al. is more appropriate than the method of Bloom and Margenau, which depends on the statistical equilibrium of an atmosphere in a force field.

Donn, Bertram↗
NASA NTRS2022

Effects of Debulking on the Fiber Microstructure and Void Distribution in Carbon Fiber Reinforced Plastics

Carbon Fiber Reinforced Plastics (CFRPs) are widely used due to their high stiffness to weight ratios. A common process manufacturers use to increase the strength to weight ratio is debulking. Debulking is the process of compacting a dry fibrous reinforcement prior to resin infusion. This process is meant to decrease the average inter-fiber distance, effectively increasing the fiber volume fraction of the sample. While this process is widely understood macroscopically its effects on fibrous microstructures have not yet been well characterized. The aim of this work is to compare the microstructures of three CFRP laminates, varying only the debulking step in the manufacturing process. High resolution serial sections of all three laminates were taken for analysis. Using these scans, the fiber positions were reconstructed. Statistical descriptors such as local fiber and void volume fractions, fiber orientation, and void distribution and morphology were then generated for each sample. Fiber clusters present within the material were identified and analyzed for each level of debulking applied. Using these descriptors, the effects of debulking on the morphology and organization of the composite microstructure was evaluated.

carbon fiber↗
NASA NTRS1981

A companion quasar to 3C345

The discovery of a new quasistellar object (QSO) which presents the strongest evidence to date for the membership of quasars in rich clusters is reported. During X-ray observations of quasar 3C345, a serendipitous X-ray source located 8 arcmin northeast of the quasar was discovered. The observed flux of the new source is 3.2 x 10 to the -13th erg/sq cm/sec in the 0.5-4.5 keV band. Three separate observations over a six-month period failed to show intensity variability in excess of the statistical uncertainty in the count rate. The spectrum shows a modest signal-to-noise ratio but four strong emission lines. It is suggested that the redshift agreement between the two QSOs indicates a common membership in a cluster of galaxies which may well be a rich cluster.

Margon, B.↗
NASA NTRS1974

The local complex of O and B stars. I - Distribution of stars and interstellar dust

The O-B5 stars, supergiants, young clusters, and associations within 1 kpc of the sun populate two flat systems inclined to each other by 19 to 22 deg. The historical background, statistical significance, composition, spatial arrangement of the contents, and interstellar extinction in the two belts are discussed. A more or less random distribution in space and in age characterizes the O-B5 stars of the 'galactic belt', which is aligned nearly along the Milky Way. The 'Gould belt' is inclined to the Milky Way (north in Sco-Oph and south in Orion), and exhibits a projected distribution of O-B5 stars in its mean plane that resembles a 'dragonfly', with five major features defining it. A crude 'diameter' of the system is 750 to 1000 pc, and the sun's position is eccentric, lying toward Ophiuchus. The nuclear age of the system, while not unique, may be characterized as 30 m.y. from the spectral type of the broad main-sequence turnup near B2-5. Most of the O-B2 stars and youngest stellar groups near the sun belong to the Gould belt, but both belts have approximately equal space densities of B3-B5 stars and similar average values of interstellar extinction.-

Stothers, R.↗
NASA NTRS1997

Surface Plasmon Resonance Evaluation of Colloidal Metal Aerogel Filters

We have fabricated aerogels containing gold, silver, and platinum nanoparticles for gas catalysis applications. By applying the concept of an average or effective dielectric constant to the heterogeneous interlayer surrounding each particle, we extend the technique of immersion spectroscopy to porous or heterogeneous media. Specifically, we apply the predominant effective medium theories for the determination of the average fractional composition of each component in this inhomogeneous layer. Hence, the surface area of metal available for catalytic gas reaction is determined. The technique is satisfactory for statistically random metal particle distributions but needs further modification for aggregated or surfactant modified systems. Additionally, the kinetics suggest that collective particle interactions in coagulated clusters are perturbed during silica gelation resulting in a change in the aggregate geometry.

Smith, David D.↗
NASA NTRS1998

Noble Metal Immersion Spectroscopy of Silica Alcogels and Aerogels

We have fabricated aerogels containing gold and silver nanoparticles for gas catalysis applications. By applying the concept of an average or effective dielectric constant to the heterogeneous interlayer surrounding each particle, we extend the technique of immersion spectroscopy to porous or heterogeneous media. Specifically, we apply the predominant effective medium theories for the determination of the average fractional composition of each component in this inhomogeneous layer. Hence, the surface area of metal available for catalytic gas reaction is determined. The technique is satisfactory for statistically random metal particle distributions but needs further modification for aggregated or surfactant modified systems. Additionally, the kinetics suggest that collective particle interactions in coagulated clusters are perturbed during silica gelation resulting in a change in the aggregate geometry.

Smith, David D.↗
NASA NTRS2006

Determination of the Cosmic Distance Scale from Sunyaev-Zel'dovich Effect and Chandra X-ray Measurements of High Redshift Galaxy Clusters

We determine the distance to 38 clusters of galaxies in the redshift range 0.14 less than or equal to z less than or equal to 0.89 using X-ray data from Chandra and Sunyaev-Zeldovich Effect data from the Owens Valley Radio Observatory and the Berkeley-Illinois-Maryland Association interferometric arrays. The cluster plasma and dark matter distributions are analyzed using a hydrostatic equilibrium model that accounts for radial variations in density, temperature and abundance, and, the statistical and systematic errors of this method are quantified. The analysis is performed via a Markov chain Monte Carlo technique that provides simultaneous estimation of all model parameters. W

Bonamente, Massimiliano↗
NASA NTRS2017

Probabilistic Forecasting of Surface Ozone with a Novel Statistical Approach

The recent change in the Environmental Protection Agency's surface ozone regulation, lowering the surface ozone daily maximum 8-h average (MDA8) exceedance threshold from 75 to 70 ppbv, poses significant challenges to U.S. air quality (AQ) forecasters responsible for ozone MDA8 forecasts. The forecasters, supplied by only a few AQ model products, end up relying heavily on self-developed tools. To help U.S. AQ forecasters, this study explores a surface ozone MDA8 forecasting tool that is based solely on statistical methods and standard meteorological variables from the numerical weather prediction (NWP) models. The model combines the self-organizing map (SOM), which is a clustering technique, with a step wise weighted quadratic regression using meteorological variables as predictors for ozone MDA8. The SOM method identifies different weather regimes, to distinguish between various modes of ozone variability, and groups them according to similarity. In this way, when a regression is developed for a specific regime, data from the other regimes are also used, with weights that are based on their similarity to this specific regime. This approach, regression in SOM (REGiS), yields a distinct model for each regime taking into account both the training cases for that regime and other similar training cases. To produce probabilistic MDA8 ozone forecasts, REGiS weighs and combines all of the developed regression models on the basis of the weather patterns predicted by an NWP model. REGiS is evaluated over the San Joaquin Valley in California and the northeastern plains of Colorado. The results suggest that the model performs best when trained and adjusted separately for an individual AQ station and its corresponding meteorological site.

Ozone variables↗