19 research outputs found

    Distances and ages of globular clusters using Hipparcos parallaxes of local subdwarfs

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    We discuss the impact of Population II and Globular Cluster (GCs) stars on the derivation of the age of the Universe, and on the study of the formation and early evolution of galaxies, our own in particular. The long-standing problem of the actual distance scale to Population II stars and GCs is addressed, and a variety of different methods commonly used to derive distances to Population II stars are briefly reviewed. Emphasis is given to the discussion of distances and ages for GCs derived using Hipparcos parallaxes of local subdwarfs. Results obtained by different authors are slightly different, depending on different assumptions about metallicity scale, reddenings, and corrections for undetected binaries. These and other uncertainties present in the method are discussed. Finally, we outline progress expected in the near future.Comment: Invited review article to appear in: `Post-Hipparcos Cosmic Candles', A. Heck & F. Caputo (Eds), Kluwer Academic Publ., Dordrecht, in press. 22 pages including 3 tables and 2 postscript figures, uses Kluwer's crckapb.sty LaTeX style file, enclose

    The RR Lyrae Distance Scale

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    We review seven methods of measuring the absolute magnitude M_V of RR Lyrae stars in light of the Hipparcos mission and other recent developments. We focus on identifying possible systematic errors and rank the methods by relative immunity to such errors. For the three most robust methods, statistical parallax, trigonometric parallax, and cluster kinematics, we find M_V (at [Fe/H] = -1.6) of 0.77 +/- 0.13, 0.71 +/- 0.15, 0.67 +/- 0.10. These methods cluster consistently around 0.71 +/- 0.07. We find that Baade-Wesselink and theoretical models both yield a broad range of possible values (0.45-0.70 and 0.45-0.65) due to systematic uncertainties in the temperature scale and input physics. Main-sequence fitting gives a much brighter M_V = 0.45 +/- 0.04 but this may be due to a difference in the metallicity scales of the cluster giants and the calibrating subdwarfs. White-dwarf cooling-sequence fitting gives 0.67 +/- 0.13 and is potentially very robust, but at present is too new to be fully tested for systematics. If the three most robust methods are combined with Walker's mean measurement for 6 LMC clusters, V_{0,LMC} = 18.98 +/- 0.03 at [Fe/H] = -1.9, then mu_{LMC} = 18.33 +/- 0.08.Comment: Invited review article to appear in: `Post-Hipparcos Cosmic Candles', A. Heck & F. Caputo (Eds), Kluwer Academic Publ., Dordrecht, in press. 21 pages including 1 table; uses Kluwer's crckapb.sty LaTeX style file, enclose

    Mutational hot spot in the DSPP gene causing dentinogenesis imperfecta type II

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    The current system for the classification of hereditary defects of tooth dentin is based upon clinical and radiographic findings and consists of two types of dentin dysplasia (DD) and three types of dentinogenesis imperfecta (DGI). However, whether DGI type III should be considered a distinct phenotype or a variation of DGI type II is debatable. In the 30 years since the classification system was first proposed, significant advances have been made regarding the genetic etiologies of inherited dentin defects. DGI type II is recognized as an autosomal dominant disorder with almost complete penetrance and a low frequency of de novo mutations. We have identified a mutation (c.52G→T, p.V18F) at the first nucleotide of exon 3 of the DSPP (dentin sialophosphoprotein) gene in a Korean family (de novo) and a Caucasian family. This mutation has previously been reported as causing DGI type II in a Chinese family. These findings suggest that this mutation site represents a mutational “hot spot” in the DSPP gene. The clinical and radiographic features of these two families include the classic phenotypes associated with both DGI type II and type III. Finding that a single mutation causes both phenotypic patterns strongly supports the conclusion that DGI type II and DGI type III are not separate diseases but rather the phenotypic variation of a single disease. We propose a modification of the current classification system such that the designation “hereditary opalescent dentin” or “DGI type II” should be used to describe both the DGI type II and type III phenotypes.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47595/1/439_2004_Article_1223.pd

    Initial data release from the INT Photometric H alpha Survey of the Northern Galactic Plane (IPHAS)

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    The INT/WFC Photometric Hα Survey of the Northern Galactic Plane (IPHAS) is an imaging survey being carried out in Hα, râ€Č and iâ€Č filters, with the Wide Field Camera (WFC) on the 2.5-m Isaac Newton Telescope (INT) to a depth of râ€Č= 20 (10σ). The survey is aimed at revealing the large scale organization of the Milky Way and can be applied to identifying a range of stellar populations within it. Mapping emission line objects enables a particular focus on objects in the young and old stages of stellar evolution ranging from early T-Tauri stars to late planetary nebulae. In this paper we present the IPHAS Initial Data Release, primarily a photometric catalogue of about 200 million unique objects, coupled with associated image data covering about 1600 deg2 in three passbands. We note how access to the primary data products has been implemented through use of standard virtual observatory publishing interfaces. Simple traditional web access is provided to the main IPHAS photometric catalogue, in addition to a number of common catalogues (such as 2MASS) which are of immediate relevance. Access through the AstroGrid VO Desktop opens up the full range of analysis options, and allows full integration with the wider range of data and services available through the Virtual Observatory. The IDR represents the largest data set published primarily through VO interfaces to date, and so stands as an exemplar of the future of survey data mining. Examples of data access are given, including a cross-matching of IPHAS photometry with sources in the UKIDSS Galactic Plane Survey that validates the existing calibration of the best data
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