Clustering of Local Group distances: publication bias or correlated measurements? I. The Large Magellanic Cloud

The distance to the Large Magellanic Cloud (LMC) represents a key local rung of the extragalactic distance ladder. Yet, the galaxy's distance modulus has long been an issue of contention, in particular in view of claims that most newly determined distance moduli cluster tightly - and with a small spread - around the "canonical" distance modulus, (m-M)_0 = 18.50 mag. We compiled 233 separate LMC distance determinations published between 1990 and 2013. Our analysis of the individual distance moduli, as well as of their two-year means and standard deviations resulting from this largest data set of LMC distance moduli available to date, focuses specifically on Cepheid and RR Lyrae variable-star tracer populations, as well as on distance estimates based on features in the observational Hertzsprung-Russell diagram. We conclude that strong publication bias is unlikely to have been the main driver of the majority of published LMC distance moduli. However, for a given distance tracer, the body of publications leading to the tightly clustered distances is based on highly non-independent tracer samples and analysis methods, hence leading to significant correlations among the LMC distances reported in subsequent articles. Based on a careful, weighted combination, in a statistical sense, of the main stellar population tracers, we recommend that a slightly adjusted canonical distance modulus of (m-M)_0 = 18.49 +- 0.09 mag be used for all practical purposes that require a general distance scale without the need for accuracies of better than a few percent.Comment: 35 pages (AASTeX preprint format), 5 postscript figures; AJ, in press. For full database of LMC distance moduli, see http://astro-expat.info/Data/pubbias.htm

Applications of Modern Statistical Methods to Analysis of Data in Physical Science

Modern methods of statistical and computational analysis offer solutions to dilemmas confronting researchers in physical science. Although the ideas behind modern statistical and computational analysis methods were originally introduced in the 1970’s, most scientists still rely on methods written during the early era of computing. These researchers, who analyze increasingly voluminous and multivariate data sets, need modern analysis methods to extract the best results from their studies. The first section of this work showcases applications of modern linear regression. Since the 1960’s, many researchers in spectroscopy have used classical stepwise regression techniques to derive molecular constants. However, problems with thresholds of entry and exit for model variables plagues this analysis method. Other criticisms of this kind of stepwise procedure include its inefficient searching method, the order in which variables enter or leave the model and problems with overfitting data. We implement an information scoring technique that overcomes the assumptions inherent in the stepwise regression process to calculate molecular model parameters. We believe that this kind of information based model evaluation can be applied to more general analysis situations in physical science. The second section proposes new methods of multivariate cluster analysis. The K-means algorithm and the EM algorithm, introduced in the 1960’s and 1970’s respectively, formed the basis of multivariate cluster analysis methodology for many years. However, several shortcomings of these methods include strong dependence on initial seed values and inaccurate results when the data seriously depart from hypersphericity. We propose new cluster analysis methods based on genetic algorithms that overcomes the strong dependence on initial seed values. In addition, we propose a generalization of the Genetic K-means algorithm which can accurately identify clusters with complex hyperellipsoidal covariance structures. We then use this new algorithm in a genetic algorithm based Expectation-Maximization process that can accurately calculate parameters describing complex clusters in a mixture model routine. Using the accuracy of this GEM algorithm, we assign information scores to cluster calculations in order to best identify the number of mixture components in a multivariate data set. We will showcase how these algorithms can be used to process multivariate data from astronomical observations

Gravitational conundrum? Dynamical mass segregation versus disruption of binary stars in dense stellar systems

Upon their formation, dynamically cool (collapsing) star clusters will, within only a few million years, achieve stellar mass segregation for stars down to a few solar masses, simply because of gravitational two-body encounters. Since binary systems are, on average, more massive than single stars, one would expect them to also rapidly mass segregate dynamically. Contrary to these expectations and based on high-resolution Hubble Space Telescope observations, we show that the compact, 15-30 Myr-old Large Magellanic Cloud cluster NGC 1818 exhibits tantalizing hints at the >= 2 sigma level of significance (> 3 sigma if we assume a power-law secondary-to-primary mass-ratio distribution) of an increasing fraction of F-star binary systems (with combined masses of 1.3-1.6 Msun) with increasing distance from the cluster center, specifically between the inner 10 to 20" (approximately equivalent to the cluster's core and half-mass radii) and the outer 60 to 80". If confirmed, this will offer support of the theoretically predicted but thus far unobserved dynamical disruption processes of the significant population of 'soft' binary systems---with relatively low binding energies compared to the kinetic energy of their stellar members---in star clusters, which we have access to here by virtue of the cluster's unique combination of youth and high stellar density.Comment: Accepted for publication in The Astrophysical Journal; 19 pages in AASTeX format; 3 figure

Topical anti-inflammatory activity of Polygonum cuspidatum extract in the TPA model of mouse ear inflammation

<p>Abstract</p> <p>Background</p> <p>This study tested the ability of a characterized extract of <it>Polygonum cuspidatum </it>(PCE) to inhibit mouse ear inflammation in response to topical application of 12-<it>O-</it>tetradecanoylphorbol-13-acetate (TPA).</p> <p>Methods</p> <p>A 50% (wt:vol) ethanolic solution of commercial 200:1 PCE was applied to both ears of female Swiss mice (n = 8) at 0.075, 0.15, 0.3, 1.25 and 2.5 mg/ear 30 min after TPA administration (2 μg/ear). For comparison, 3 other groups were treated with TPA and either 1) the vehicle (50% ethanol) alone, 2) indomethacin (0.5 mg/ear), or 3) <it>trans</it>-resveratrol (0.62 mg/ear). Ear thickness was measured before TPA and at 4 and 24 h post-TPA administration to assess ear edema. Ear punch biopsies were collected at 24 h and weighed as a second index of edema. Myeloperoxidase activity was measured in each ear punch biopsy to assess neutrophil infiltration.</p> <p>Results</p> <p>PCE treatment at all doses significantly reduced ear edema compared to the TPA control. The PCE response was dose-dependent and 2.5 mg PCE significantly inhibited all markers of inflammation to a greater extent than indomethacin (0.5 mg). MPO activity was inhibited at PCE doses ≥ 1.25 mg/ear. <it>Trans-</it>resveratrol inhibited inflammation at comparable doses.</p> <p>Conclusion</p> <p>PCE inhibits development of edema and neutrophil infiltration in the TPA-treated mouse ear model of topical inflammation.</p

{2,6-Bis[(2,6-diphenyl­phosphan­yl)­oxy]-4-fluoro­phenyl-κ3 P,C 1,P′}(6-methyl-2,2,4-trioxo-3,4-dihydro-1,2,3-oxathia­zin-3-ido-κN)palladium(II)

The title acesulfamate complex, [Pd(C30H22FO2P2)(C4H4NO4S)], contains a four-coordinate Pd(II) ion with the expected, although relatively distorted, square-planar geometry where the four L—Pd—L angles range from 79.58 (8) to 102.47 (7)°. The acesulfamate ligand is N-bound to Pd [Pd—N = 2.127 (2) Å] with a dihedral angle of 76.35 (6)° relative to the square plane. Relatively long phen­yl–acesulfamate C—H⋯O and phen­yl–fluorine C—H⋯F inter­actions consolidate the crystal packing

A major invasion of transposable elements accounts for the large size of the Blumeria graminis f.sp. tritici genome

Powdery mildew of wheat (Triticum aestivum L.) is caused by the ascomycete fungus Blumeria graminis f.sp. tritici. Genomic approaches open new ways to study the biology of this obligate biotrophic pathogen. We started the analysis of the Bg tritici genome with the low-pass sequencing of its genome using the 454 technology and the construction of the first genomic bacterial artificial chromosome (BAC) library for this fungus. High-coverage contigs were assembled with the 454 reads. They allowed the characterization of 56 transposable elements and the establishment of the Blumeria repeat database. The BAC library contains 12,288 clones with an average insert size of 115kb, which represents a maximum of 7.5-fold genome coverage. Sequencing of the BAC ends generated 12.6Mb of random sequence representative of the genome. Analysis of BAC-end sequences revealed a massive invasion of transposable elements accounting for at least 85% of the genome. This explains the unusually large size of this genome which we estimate to be at least 174Mb, based on a large-scale physical map constructed through the fingerprinting of the BAC library. Our study represents a crucial step in the perspective of the determination and study of the whole Bg tritici genome sequenc

A highly conserved gene island of three genes on chromosome 3B of hexaploid wheat: diverse gene function and genomic structure maintained in a tightly linked block

The complexity of the wheat genome has resulted from waves of retrotransposable element insertions. Gene deletions and disruptions generated by the fast replacement of repetitive elements in wheat have resulted in disruption of colinearity at a micro (sub-megabase) level among the cereals. In view of genomic changes that are possible within a given time span, conservation of genes between species tends to imply an important functional or regional constraint that does not permit a change in genomic structure. The ctg1034 contig completed in this paper was initially studied because it was assigned to the Sr2 resistance locus region, but detailed mapping studies subsequently assigned it to the long arm of 3B and revealed its unusual features