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At least 1,207 records · Page 67

A RADIO-SELECTED SAMPLE OF GAMMA-RAY BURST AFTERGLOWS

We present a catalog of radio afterglow observations of gamma-ray bursts (GRBs) over a 14 year period from 1997 to 2011. Our sample of 304 afterglows consists of 2995 flux density measurements (including upper limits) at frequencies between 0.6 GHz and 660 GHz, with the majority of data taken at 8.5 GHz frequency band (1539 measurements). We use this data set to carry out a statistical analysis of the radio-selected sample. The detection rate of radio afterglows has stayed unchanged almost at 31% before and after the launch of the Swift satellite. The canonical long-duration GRB radio light curve at 8.5 GHz peaks at three to six days in the source rest frame, with a median peak luminosity of 10{sup 31} erg s{sup -1} Hz{sup -1}. The peak radio luminosities for short-hard bursts, X-ray flashes, and the supernova-GRB classes are an order of magnitude or more fainter than this value. There are clear relationships between the detectability of a radio afterglow and the fluence or energy of a GRB, and the X-ray or optical brightness of the afterglow. However, we find few significant correlations between these same GRB and afterglow properties and the peak radio flux density. We also produce synthetic light curves at centimeter and millimeter bands using a range of blast wave and microphysics parameters derived from multiwavelength afterglow modeling, and we use them to compare to the radio sample. Finding agreement, we extrapolate this behavior to predict the centimeter and millimeter behavior of GRBs observed by the Expanded Very Large Array and the Atacama Large Millimeter Array.

79 ASTRONOMY AND ASTROPHYSICS↗

Proteomics Goes to Court: A Statistical Foundation for Forensic Toxin/Organism Identification Using Bottom-Up Proteomics

Bottom-up proteomics is increasingly being used to characterize unknown environmental, clinical, and forensic samples. Proteomics-based bacterial identification typically proceeds by tabulating peptide “hits” (i.e. confidently identified peptides) associated with the organisms in a database; those organisms with enough hits are declared present in the sample. This approach has proven successful in laboratory studies, however, important research gaps remain. First, the common-practice reliance on unique peptides for identification is susceptible to a phenomenon known as signal erosion. Second, no general guidelines are available for determining how many hits are needed to make a confident identification. These gaps inhibit the transition of this approach to real-world samples where conditions vary and large databases may be needed. We propose statistical criteria for organism identification that applies regardless of sample quality or data analysis pipeline. These criteria are straightforward, producing a p-value on the result. We test the criteria on LC-MS/MS datasets representing 919 different bacterial and toxin datasets acquired with multiple data collection platforms. Results reveal a >95% correct species-level identification rate, demonstrating the effectiveness and robustness of proteomics-based organism/toxin identification.

Jarman, Kristin H.↗

SDSS-IV MaNGA IFS GALAXY SURVEY—SURVEY DESIGN, EXECUTION, AND INITIAL DATA QUALITY

The MaNGA Survey (Mapping Nearby Galaxies at Apache Point Observatory) is one of three core programs in the Sloan Digital Sky Survey IV. It is obtaining integral field spectroscopy for 10,000 nearby galaxies at a spectral resolution of R ∼ 2000 from 3622 to 10354 Å. The design of the survey is driven by a set of science requirements on the precision of estimates of the following properties: star formation rate surface density, gas metallicity, stellar population age, metallicity, and abundance ratio, and their gradients; stellar and gas kinematics; and enclosed gravitational mass as a function of radius. We describe how these science requirements set the depth of the observations and dictate sample selection. The majority of targeted galaxies are selected to ensure uniform spatial coverage in units of effective radius (R{sub e}) while maximizing spatial resolution. About two-thirds of the sample is covered out to 1.5 R{sub e} (Primary sample), and one-third of the sample is covered to 2.5 R{sub e} (Secondary sample). We describe the survey execution with details that would be useful in the design of similar future surveys. We also present statistics on the achieved data quality, specifically the point-spread function, sampling uniformity, spectral resolution, sky subtraction, and flux calibration. For our Primary sample, the median r -band signal-to-noise ratio is ∼70 per 1.4 Å pixel for spectra stacked between 1 R{sub e} and 1.5 R{sub e}. Measurements of various galaxy properties from the first-year data show that we are meeting or exceeding the defined requirements for the majority of our science goals.

79 ASTRONOMY AND ASTROPHYSICS↗

Part 2: Forensic attribution profiling of Russian VX in food using liquid chromatography-mass spectrometry

This work is part two of a three-part series in this issue of a Sweden-United States collaborative effort towards the understanding of the chemical attribution signatures of Russian VX (VR) in synthesized samples and complex food matrices. We describe the sourcing of VR present in food based on chemical analysis of attribution signatures by liquid chromatography-tandem mass spectrometry (LC-MS/MS) combined with multivariate data analysis. Analytical data was acquired from seven different foods spiked with VR batches that were synthesized via six different routes in two separate laboratories. The synthesis products were spiked at a lethal dose into seven food matrices: water, orange juice, apple purée, baby food, pea purée, liquid eggs and hot dog. After acetonitrile sample extraction, the samples were analyzed by LC-MS/MS operated in MRM mode. A multivariate statistical calibration model was built on the chemical attribution profiles from 118 VR spiked food samples. Using the model, an external test-set of the six synthesis routes employed for VR production was correctly identified with no observable major impact of the food matrices to the classification. The overall performance of the statistical models was found to be exceptional (94%) for the test set samples retrospectively classified to their synthesis routes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Monte Carlo techniques for solving transport problems

The Monte Carlo procedure is a model sampling technique. A model is established, and the behavior of sample units in this model is followed. A sufficient number of sample units are followed to obtain a statistical average or macroscopic quantities, which are the quantities of interest. This technique was used in crude form by Fermi in connection with the building of the first atomic pile. Later, Von Neumann and Ulam developed and used the Monte Carlo procedure extensively in developing the atomic bomb. Since then this technique has gained considerable use in nuclear reactor problems (refs. 1 and 2), and we at the Lewis Research Center have been extending it to thermal radiation (refs. 3 and 4), rarefied gas flows, and plasma flow problems (ref. 5). This technique, which requires a large number of sample histories to obtain solutions with small variances, is receiving greater use because of the development of the high-speed electronic computers.

SAMPLED DATA SYSTEM↗

Statistical analysis of catalogs of extragalactic objects. III - The Shane-Wirtanen and Zwicky catalogs

Statistical investigation of clustering in the galaxy catalogs compiled by Zwicki et al. (1961-1968) and Shane and Wirtanen (1967). The covariance and power spectrum of the angular distributions are estimated. The space region surveyed in the Zwicki catalog is found to represent a 'fair sample of the universe' in that the statistical nature of the clustering in this catalog is found to be mirrored at smaller angular scales in the deeper survey of Shane and Wirtanen.

Peebles, P. J. E.↗

Optimizing metaproteomics database construction: lessons from a study of the vaginal microbiome

Metaproteomics, a method for untargeted, high-throughput identification of proteins in complex samples, provides functional information about microbial communities and can tie functions to specific taxa. Metaproteomics often generates less data than other omics techniques, but analytical workflows can be improved to increase usable data in metaproteomic outputs. Identification of peptides in the metaproteomic analysis is performed by comparing mass spectra of sample peptides to a reference database of protein sequences. Although these protein databases are an integral part of the metaproteomic analysis, few studies have explored how database composition impacts peptide identification. Here, we used cervicovaginal lavage (CVL) samples from a study of bacterial vaginosis (BV) to compare the performance of databases built using six different strategies. We evaluated broad versus sample-matched databases, as well as databases populated with proteins translated from metagenomic sequencing of the same samples versus sequences from public repositories. Smaller sample-matched databases performed significantly better, driven by the statistical constraints on large databases. Additionally, large databases attributed up to 34% of significant bacterial hits to taxa absent from the sample, as determined orthogonally by 16S rRNA gene sequencing. We also tested a set of hybrid databases which included bacterial proteins from NCBI RefSeq and translated bacterial genes from the samples. These hybrid databases had the best overall performance, identifying 1,068 unique human and 1,418 unique bacterial proteins, ~30% more than a database populated with proteins from typical vaginal bacteria and fungi. Our findings can help guide the optimal identification of proteins while maintaining statistical power for reaching biological conclusions.

59 BASIC BIOLOGICAL SCIENCES↗

Paleomagnetism of the Mesozoic in Alaska

Over 400 oriented cores of Permian, Triassic, Jurassic, and Cretaceous sedimentary and igneous rocks were collected from 34 sites at 10 areas throughout southern Alaska. After magnetic cleaning in successively higher alternating fields 179 samples were considered to be stable and to give statistically consistent results within each site and age group. Due to the lack of a sufficient number of stable samples, the results from Permian, Triassic, and Cretaceous rocks were inconclusive. The nine remaining Jurassic sites represent 100 samples from three general areas in southern Alaska. The southern Alaskan Jurassic paleomagnetic pole is significantly different from the North American Jurassic pole. This suggests that since the Jurassic, southern Alaska must have moved approximately 18 degrees north and rotated 52 degrees clockwise to reach its present position. Tectonic interpretation of these results give a possible explanation for many of the geologic features observed in southern Alaska.

Packer, D. R.↗

Information density and efficiency of two-dimensional /2-D/ sampled imagery

Information density and efficiency (i.e., the ratio of information density to data density) are used as criteria for assessing the quality of 2-D sampled and quantized imagery as a function of the statistical properties of random radiance fields, the spatial response (PSF or MTF) and sensitivity of imaging systems, and the sampling and quantization intervals. Computational results are intuitively satisfying: they are consistent with experimental and theoretical results obtained by earlier investigators concerned with the performance of TV cameras, and they provide useful guidelines for optimizing the design of line-scan and sensor-array imaging systems, especially if these systems use a digital communication link for transmitting data.

Huck, F. O.↗

GALAXY ENVIRONMENTS OVER COSMIC TIME: THE NON-EVOLVING RADIAL GALAXY DISTRIBUTIONS AROUND MASSIVE GALAXIES SINCE z = 1.6

We present a statistical study of the environments of massive galaxies in four redshift bins between z = 0.04 and z = 1.6, using data from the Sloan Digital Sky Survey and the NEWFIRM Medium Band Survey. We measure the projected radial distribution of galaxies in cylinders around a constant number density selected sample of massive galaxies and utilize a statistical subtraction of contaminating sources. Our analysis shows that massive primary galaxies typically live in group halos and are surrounded by 2-3 satellites with masses more than one-tenth of the primary galaxy mass. The cumulative stellar mass in these satellites roughly equals the mass of the primary galaxy itself. We further find that the radial number density profile of galaxies around massive primaries has not evolved significantly in either slope or overall normalization in the past 9.5 Gyr. A simplistic interpretation of this result can be taken as evidence for a lack of mergers in the studied groups and as support for a static evolution model of halos containing massive primaries. Alternatively, there exists a tight balance between mergers and accretion of new satellites such that the overall distribution of galaxies in and around the halo is preserved. The latter interpretation is supported by a comparison to a semi-analytic model, which shows a similar constant average satellite distribution over the same redshift range.

79 ASTRONOMY AND ASTROPHYSICS↗

A multivariate approach to ensure statistical reproducibility of climate model simulations

Effective utilization of novel hybrid architectures of pre-exascale and exascale machines requires transformations to global climate modeling systems that may not reproduce the original model solution bit-for-bit. Round-off level differences grow rapidly in these non-linear and chaotic systems. This makes it difficult to isolate bugs/errors from innocuous growth expected from round-off level differences. Here, we apply two modern multivariate two sample equality of distribution tests to evaluate statistical reproducibility of global climate model simulations using standard monthly output of short (~ 1-year) simulation ensembles of a control model and a modified model of US Department of Energy's Energy Exascale Earth System Model (E3SM). Both the tests are able to identify changes induced by modifications to some model tuning parameters. We also conduct formal power analyses of the tests by applying them on designed suites of short simulation ensembles each with an increasingly different climate from the control ensemble. The results are compared against those from another such test. These power analyses provide a framework to quantify the degree of differences that can be detected confidently by the tests for a given ensemble size (sample size). This will allow model developers using the tests to make an informed decision when accepting/rejecting an unintentional non-bit-for-bit change to the model solution.

Mahajan, Salil↗

Astrometric Detection of Extrasolar Planets: Results of a Feasibility Study with the Palomar 5 Meter Telescope

The detection of extrasolar planets around stars like the Sun remains an important goal of astronomy. We present results from Palomar 5 m observations of the open cluster NGC 2420 in which we measure some of the sources of noise that will be present in an astrometric search for extrasolar planets. This is the first time that such a large aperture has been used for high-precision astrometry. We find that the atmospheric noise is 150 micro-arcsec hr(exp 1/2) across a 90 sec field of view and that differential chromatic refraction (DCR) can be calibrated to 128 micro-arcsec for observations within 1 hr of the meridian and 45 deg of zenith. These results confirm that a model for astrometric measurements can be extrapolated to large apertures. We demonstrate, based upon these results, that a large telescope achieves the sensitivity required to perform a statistically significant search for extra solar planets. We describe an astrometric technique to detect planets, the astrometric signals expected, the role of reference stars, and the sources of measurement noise: photometric noise, atmospheric motion between stars, sky background, instrumental noise, and DCR. For the latter, we discuss a method to reduce the noise further to 66 micro-arcsecond for observations within 1 hr of the meridian and 45 deg of zenith. We discuss optimal lists of target stars taken from the latest Gliese & Jahreiss catalog of nearby stars with the largest potential astrometric signals, declination limits for both telescope accessibility and reduced DCR, and galactic latitude limits for a sufficiant number of reference stars. Two samples are described from which one can perform statistically significant searches for gas giant planets around nearby stars. One sample contains 100 "solar class" stars with an average stellar mass of 0.82 solar mass; the other maximizes the number of stars, 574, by searching mainly low-mass M stars. We perform Monte Carlo simulations of the statistical significance of the expected results by using measured and estimated noise quantities. We show the semimajor axis parameter spaces that are searched for each star and how an increase in the length of the observing program expands these spaces. The search over semimajor axis parameter space relates to the theory of gas giant planet formation.

Pravdo, Steven H.↗

Comparing generalized ensemble methods for sampling of systems with many degrees of freedom

Here, we compare two standard replica exchange methods using temperature and dielectric constant as the scaling variables for independent replicas against two new corresponding enhanced sampling methods based on non-equilibrium statistical cooling (temperature) or descreening (dielectric). We test the four methods on a rough 1D potential as well as for alanine dipeptide in water, for which their relatively small phase space allows for the ability to define quantitative convergence metrics. We show that both dielectric methods are inferior to the temperature enhanced sampling methods, and in turn show that temperature cool walking (TCW) systematically outperforms the standard temperature replica exchange (TREx) method. We extend our comparisons of the TCW and TREx methods to the 5 residue met-enkephalin peptide, in which we evaluate the Kullback-Leibler divergence metric to show that the rate of convergence between two independent trajectories is faster for TCW compared to TREx. Finally we apply the temperature methods to the 42 residue amyloid-β peptide in which we find non-negligible differences in the disordered ensemble using TCW compared to the standard TREx. All four methods have been made available as software through the OpenMM Omnia software consortium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stochastic modeling of phosphorus transport in the Three Gorges Reservoir by incorporating variability associated with the phosphorus partition coefficient

Phosphorus (P) fate and transport plays a crucial role in the ecology of rivers and reservoirs in which eutrophication is limited by P. A key uncertainty in models used to help manage P in such systems is the partitioning of P to suspended and bed sediments. By analyzing data from field and laboratory experiments, we stochastically characterize the variability of the partition coefficient (Kd) and derive spatio-temporal solutions for P transport in the Three Gorges Reservoir (TGR). We formulate a set of stochastic partial different equations (SPDEs) to simulate P transport by randomly sampling Kd from the measured distributions, to obtain statistical descriptions of the P concentration and retention in the TGR. The correspondence between predicted and observed P concentrations and P retention in the TGR combined with the ability to effectively characterize uncertainty suggests that a model that incorporates the observed variability can better describe P dynamics and more effectively serve as a tool for P management in the system. This study highlights the importance of considering parametric uncertainty in estimating uncertainty/variability associated with simulated P transport.

Partition coefficient↗

Quickest Detection for Changes in Maximal kNN Coherence of Random Matrices

This paper addresses the problem of quickest detection of a change in the maximal coherence between columns of a n p random matrix based on a sequence of matrix observations having a single unknown change point. The random matrix is assumed to have identically distributed rows and the maximal coherence is defined as the largest of the ( 2 p) correlation coefficients associated with any row. Likewise the κ nearest neighbor (kNN) coherence is defined as the κ-th largest of these correlation coefficients. The forms of the preand postchange distributions of the observed matrices are assumed to belong to the family of elliptically contoured densities with sparse dispersion matrices but are otherwise unknown. A nonparametric stopping rule is proposed that is based on the maximal kNN sample coherence between columns of each observed random matrix. This is a summary statistic that is related to a test of existence of a hub vertex in a sample correlation graph having degree at least κ. Performance bounds on the delay and false alarm performance of the proposed stopping rule are obtained in the purely high-dimensional regime where p → ∞ and n is fixed. When the prechange dispersion matrix is diagonal it is shown that, among all functions of the proposed summary statistic, the proposed stopping rule is asymptotically optimal under a minimax quickest change detection model as the stopping threshold approaches infinity. Furthermore, the theory developed also applies to sequential hypothesis testing and fixed sample size tests.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Prognostic significance of high YY1AP1 and PCNA expression in colon adenocarcinoma

Highlights: • YY1AP1 expression might play an important role in the tumorgenesis of colon adenocarcinoma. • YY1AP1 expression is related with colon adenocarcinoma patient M-class/distant metastasis. • High YY1AP1 indicates poor overall survival of colon adenocarcinoma patients. • Cox proportional-hazards model analysis indicated YY1AP1 as an independent predictor for overall survival. To investigate the relationship between YY1AP1 and various clinicopathological features of colon adenocarcinoma (COAD), we conducted immunohistochemical (IHC) analyses of human tissue microarrays. We found that YY1AP1 protein expression was significantly higher in tumor tissue of the colon and liver, and was significantly lower in tumor tissue of the kidney. An analysis that employed the SurvExpress database indicated that increased expression of YY1AP1 mRNA was significantly associated with the overall survival of COAD patients. To clarify the validity of YY1AP1 or PCNA as determined by the IHC analysis was performed on 59 paired samples from COAD and adjacent normal tissue. Statistically significant differences of immunoreactivity for YY1AP1 or PCNA protein expression was observed between COAD tissue and adjacent normal tissue. High protein expression levels of YY1AP1 and PCNA were also found to be significantly correlated with M-class and distant metastasis. We also determined that YY1AP1 was correlated with PCNA expression in COAD samples, and Kaplan-Meier survival curves indicated that YY1AP1 protein expression was significantly associated with poor survival. Finally, a univariate analysis demonstrated that YY1AP1 protein expression was related to YY1AP1 score, and multivariate analysis revealed that the YY1AP1 protein expression level was an independent risk factor of overall COAD survival. Taken together, our findings indicate that YY1AP1 expression plays an important role in the tumorigenesis and progression of COAD and could serve as a clinical prognostic indicator for COAD.

60 APPLIED LIFE SCIENCES↗

Bayesian Analysis of the Cosmic Microwave Background

There is a wealth of cosmological information encoded in the spatial power spectrum of temperature anisotropies of the cosmic microwave background! Experiments designed to map the microwave sky are returning a flood of data (time streams of instrument response as a beam is swept over the sky) at several different frequencies (from 30 to 900 GHz), all with different resolutions and noise properties. The resulting analysis challenge is to estimate, and quantify our uncertainty in, the spatial power spectrum of the cosmic microwave background given the complexities of "missing data", foreground emission, and complicated instrumental noise. Bayesian formulation of this problem allows consistent treatment of many complexities including complicated instrumental noise and foregrounds, and can be numerically implemented with Gibbs sampling. Gibbs sampling has now been validated as an efficient, statistically exact, and practically useful method for low-resolution (as demonstrated on WMAP 1 and 3 year temperature and polarization data). Continuing development for Planck - the goal is to exploit the unique capabilities of Gibbs sampling to directly propagate uncertainties in both foreground and instrument models to total uncertainty in cosmological parameters.

methods - statistical↗

A multiparametric analysis of the Einstein sample of early-type galaxies. 1: Luminosity and ISM parameters

We have conducted bivariate and multivariate statistical analysis of data measuring the luminosity and interstellar medium of the Einstein sample of early-type galaxies (presented by Fabbiano, Kim, & Trinchieri 1992). We find a strong nonlinear correlation between L(sub B) and L(sub X), with a power-law slope of 1.8 +/- 0.1, steepening to 2.0 +/- if we do not consider the Local Group dwarf galaxies M32 and NGC 205. Considering only galaxies with log L(sub X) less than or equal to 40.5, we instead find a slope of 1.0 +/- 0.2 (with or without the Local Group dwarfs). Although E and S0 galaxies have consistent slopes for their L(sub B)-L(sub X) relationships, the mean values of the distribution functions of both L(sub X) and L(sub X)/L(sub B) for the S0 galaxies are lower than those for the E galaxies at the 2.8 sigma and 3.5 sigma levels, respectively. We find clear evidence for a correlation between L(sub X) and the X-ray color C(sub 21), defined by Kim, Fabbiano, & Trinchieri (1992b), which indicates that X-ray luminosity is correlated with the spectral shape below 1 keV in the sense that low-L(sub X) systems have relatively large contributions from a soft component compared with high-L(sub X) systems. We find evidence from our analysis of the 12 micron IRAS data for our sample that our S0 sample has excess 12 micron emission compared with the E sample, scaled by their optical luminosities. This may be due to emission from dust heated in star-forming regions in S0 disks. This interpretation is reinforced by the existence of a strong L(sub 12)-L(sub 100) correlation for our S0 sample that is not found for the E galaxies, and by an analysis of optical-IR colors. We find steep slopes for power-law relationships between radio luminosity and optical, X-ray, and far-IR (FIR) properties. This last point argues that the presence of an FIR-emitting interstellar medium (ISM) in early-type galaxies is coupled to their ability to generate nonthermal radio continuum, as previously argued by, e.g., Walsh et al. (1989). We also find that, for a given L(sub 100), galaxies with larger L(sub X)/L(sub B) tend to be stronger nonthermal radio sources, as originally suggested by Kim & Fabbiano (1990). We note that, while L(sub B) is most strongly correlated with L(sub 6), the total radio luminosity, both L(sub X) and L(sub X)/L(sub B) are more strongly correlated with L(sub 6 CO), the core radio luminosity. These points support the argument (proposed by Fabbiano, Gioia, & Trinchieri 1989) that radio cores in early-type galaxies are fueled by the hot ISM.

Eskridge, Paul B.↗