3,522 research outputs found

    Chandra observation of the fast X-ray transient IGR J17544-2619: evidence for a neutron star?

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    IGR J17544-2619 belongs to a distinct group of at least seven fast X-ray transients that cannot readily be associated with nearby flare stars or pre-main sequence stars and most probably are X-ray binaries with wind accretion. Sofar, the nature of the accretor has been determined in only one case (SAX J1819.3-2525/V4641 Sgr). We carried out a 20 ks Chandra ACIS-S observation of IGR J17544-2619 which shows the source in quiescence going into outburst. The Chandra position confirms the previous tentative identification of the optical counterpart, a blue O9Ib supergiant at 3 to 4 kpc (Pellizza, Chaty & Negueruela, in prep.). This is the first detection of a fast X-ray transient in quiescence. The quiescent spectrum is very soft. The photon index of 5.9+/-1.2 (90% confidence error margin) is much softer than 6 quiescent black hole candidates that were observed with Chandra ACIS-S (Kong et al. 2002; Tomsick et al. 2003). Assuming that a significant fraction of the quiescent photons comes from the accretor and not the donor star, we infer that the accretor probably is a neutron star. A fit to the quiescent spectrum of the neutron star atmosphere model developed by Pavlov et al. (1992) and Zavlin et al. (1996) implies an unabsorbed quiescent 0.5--10 keV luminosity of (5.2+/-1.3) x 10^32 erg/s. We speculate on the nature of the brief outbursts.Comment: accepted for publication in Astronomy & Astrophysic

    Physical and psychological scars: The impact of breast cancer on women's body image

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    Whilst breast cancer remains the most common cancer amongst women in the United Kingdom, advances in medicine have seen survival rates improve over the years and the number of women living with the residual consequences of the disease and its treatment is growing. Women are likely to undergo a number of treatments at once, or in succession of one another, each of which brings about various changes to appearance, e.g. hair loss. These wide ranging appearance alterations can impose an adverse impact on body image, causing substantial distress for many women (Dahl et al., 2010). This article reviews research exploring the body image of women with breast cancer, a group who experience a wide range of changes to their appearance as a side effect of treatment for the disease

    Accurate multimodal probabilistic prediction of conversion to Alzheimer's disease in patients with mild cognitive impairment

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    Accurately identifying the patients that have mild cognitive impairment (MCI) who will go on to develop Alzheimer's disease (AD) will become essential as new treatments will require identification of AD patients at earlier stages in the disease process. Most previous work in this area has centred around the same automated techniques used to diagnose AD patients from healthy controls, by coupling high dimensional brain image data or other relevant biomarker data to modern machine learning techniques. Such studies can now distinguish between AD patients and controls as accurately as an experienced clinician. Models trained on patients with AD and control subjects can also distinguish between MCI patients that will convert to AD within a given timeframe (MCI-c) and those that remain stable (MCI-s), although differences between these groups are smaller and thus, the corresponding accuracy is lower. The most common type of classifier used in these studies is the support vector machine, which gives categorical class decisions. In this paper, we introduce Gaussian process (GP) classification to the problem. This fully Bayesian method produces naturally probabilistic predictions, which we show correlate well with the actual chances of converting to AD within 3 years in a population of 96 MCI-s and 47 MCI-c subjects. Furthermore, we show that GPs can integrate multimodal data (in this study volumetric MRI, FDG-PET, cerebrospinal fluid, and APOE genotype with the classification process through the use of a mixed kernel). The GP approach aids combination of different data sources by learning parameters automatically from training data via type-II maximum likelihood, which we compare to a more conventional method based on cross validation and an SVM classifier. When the resulting probabilities from the GP are dichotomised to produce a binary classification, the results for predicting MCI conversion based on the combination of all three types of data show a balanced accuracy of 74%. This is a substantially higher accuracy than could be obtained using any individual modality or using a multikernel SVM, and is competitive with the highest accuracy yet achieved for predicting conversion within three years on the widely used ADNI dataset

    The Discovery of Argon in Comet C/1995 O1 (Hale-Bopp)

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    On 30.14 March 1997 we observed the EUV spectrum of the bright comet C/1995 O1 (Hale-Bopp) at the time of its perihelion, using our EUVS sounding rocket telescope/spectrometer. The spectra reveal the presence H Ly beta, O+, and, most notably, Argon. Modelling of the retrieved Ar production rates indicates that comet Hale-Bopp is enriched in Ar relative to cosmogonic expectations. This in turn indicates that Hale-Bopp's deep interior has never been exposed to the 35-40 K temperatures necessary to deplete the comet's primordial argon supply.Comment: 9 pages, 2 figures. ApJ, 545, in press (2000

    A comprehensive analysis of methods for assessing polygenic burden on Alzheimer’s disease pathology and risk beyond APOE

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    Genome-wide association studies have identified dozens of loci that alter the risk to develop Alzheimer’s disease. However, with the exception of the APOE-Δ4 allele, most variants bear only little individual effect and have, therefore, limited diagnostic and prognostic value. Polygenic risk scores aim to collate the disease risk distributed across the genome in a single score. Recent works have demonstrated that polygenic risk scores designed for Alzheimer’s disease are predictive of clinical diagnosis, pathology confirmed diagnosis and changes in imaging biomarkers. Methodological innovations in polygenic risk modelling include the polygenic hazard score, which derives effect estimates for individual single nucleotide polymorphisms from survival analysis, and methods that account for linkage disequilibrium between genomic loci. In this work, using data from the Alzheimer’s disease neuroimaging initiative, we compared different approaches to quantify polygenic disease burden for Alzheimer’s disease and their association (beyond the APOE locus) with a broad range of Alzheimer’s disease-related traits: cross-sectional CSF biomarker levels, cross-sectional cortical amyloid burden, clinical diagnosis, clinical progression, longitudinal loss of grey matter and longitudinal decline in cognitive function. We found that polygenic scores were associated beyond APOE with clinical diagnosis, CSF-tau levels and, to a minor degree, with progressive atrophy. However, for many other tested traits such as clinical disease progression, CSF amyloid, cognitive decline and cortical amyloid load, the additional effects of polygenic burden beyond APOE were of minor nature. Overall, polygenic risk scores and the polygenic hazard score performed equally and given the ease with which polygenic risk scores can be derived; they constitute the more practical choice in comparison with polygenic hazard scores. Furthermore, our results demonstrate that incomplete adjustment for the APOE locus, i.e. only adjusting for APOE-Δ4 carrier status, can lead to overestimated effects of polygenic scores due to APOE-Δ4 homozygous participants. Lastly, on many of the tested traits, the major driving factor remained the APOE locus, with the exception of quantitative CSF-tau and p-tau measures

    Spatial Correlation Function of X-ray Selected AGN

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    We present a detailed description of the first direct measurement of the spatial correlation function of X-ray selected AGN. This result is based on an X-ray flux-limited sample of 219 AGN discovered in the contiguous 80.7 deg^2 region of the ROSAT North Ecliptic Pole (NEP) Survey. Clustering is detected at the 4 sigma level at comoving scales in the interval r = 5-60 h^-1 Mpc. Fitting the data with a power law of slope gamma=1.8, we find a correlation length of r_0 = 7.4 (+1.8, -1.9) h^-1 Mpc (Omega_M=0.3, Omega_Lambda=0.7). The median redshift of the AGN contributing to the signal is z_xi=0.22. This clustering amplitude implies that X-ray selected AGN are spatially distributed in a manner similar to that of optically selected AGN. Furthermore, the ROSAT NEP determination establishes the local behavior of AGN clustering, a regime which is poorly sampled in general. Combined with high-redshift measures from optical studies, the ROSAT NEP results argue that the AGN correlation strength essentially does not evolve with redshift, at least out to z~2.2. In the local Universe, X-ray selected AGN appear to be unbiased relative to galaxies and the inferred X-ray bias parameter is near unity, b_X~1. Hence X-ray selected AGN closely trace the underlying mass distribution. The ROSAT NEP AGN catalog, presented here, features complete optical identifications and spectroscopic redshifts. The median redshift, X-ray flux, and X-ray luminosity are z=0.41, f_X=1.1*10^-13 cgs, and L_X=9.2*10^43 h_70^-2 cgs (0.5-2.0 keV), respectively. Unobscured, type 1 AGN are the dominant constituents (90%) of this soft X-ray selected sample of AGN.Comment: 17 pages, 8 figures, accepted for publication in ApJ, a version with high-resolution figures is available at http://www.eso.org/~cmullis/papers/Mullis_et_al_2004b.ps.gz, a machine-readable version of the ROSAT NEP AGN catalog is available at http://www.eso.org/~cmullis/research/nep-catalog.htm

    Evolution of the Cluster X-ray Luminosity Function

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    We report measurements of the cluster X-ray luminosity function out to z=0.8 based on the final sample of 201 galaxy systems from the 160 Square Degree ROSAT Cluster Survey. There is little evidence for any measurable change in cluster abundance out to z~0.6 at luminosities less than a few times 10^44 ergs/s (0.5-2.0 keV). However, between 0.6 < z < 0.8 and at luminosities above 10^44 ergs/s, the observed volume densities are significantly lower than those of the present-day population. We quantify this cluster deficit using integrated number counts and a maximum-likelihood analysis of the observed luminosity-redshift distribution fit with a model luminosity function. The negative evolution signal is >3 sigma regardless of the adopted local luminosity function or cosmological framework. Our results and those from several other surveys independently confirm the presence of evolution. Whereas the bulk of the cluster population does not evolve, the most luminous and presumably most massive structures evolve appreciably between z=0.8 and the present. Interpreted in the context of hierarchical structure formation, we are probing sufficiently large mass aggregations at sufficiently early times in cosmological history where the Universe has yet to assemble these clusters to present-day volume densities.Comment: 15 pages, 10 figures, accepted for publication in Ap

    ADIPLS -- the Aarhus adiabatic oscillation package

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    Development of the Aarhus adiabatic pulsation code started around 1978. Although the main features have been stable for more than a decade, development of the code is continuing, concerning numerical properties and output. The code has been provided as a generally available package and has seen substantial use at a number of installations. Further development of the package, including bringing the documentation closer to being up to date, is planned as part of the HELAS Coordination Action.Comment: Astrophys. Space Sci., in the pres
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