A dozen colliding wind X-ray binaries in the star cluster R136 in the 30Doradus region

We analyzed archival Chandra X-ray observations of the central portion of the 30 Doradus region in the Large Magellanic Cloud. The image contains 20 X-ray point sources with luminosities between $5 \times 10^{32}$ and $2 \times 10^{35}$ erg s$^{-1}$ (0.2 -- 3.5 keV). A dozen sources have bright WN Wolf-Rayet or spectral type O stars as optical counterparts. Nine of these are within $\sim 3.4$pc of R136, the central star cluster of NGC2070. We derive an empirical relation between the X-ray luminosity and the parameters for the stellar wind of the optical counterpart. The relation gives good agreement for known colliding wind binaries in the Milky Way Galaxy and for the identified X-ray sources in NGC2070. We conclude that probably all identified X-ray sources in NGC2070 are colliding wind binaries and that they are not associated with compact objects. This conclusion contradicts Wang (1995) who argued, using ROSAT data, that two earlier discovered X-ray sources are accreting black-hole binaries. Five of the eighteen brightest stars in R136 are not visible in our X-ray observations. These stars are either single, have low mass companions or very wide orbits. The resulting binary fraction among early type stars is then unusually high (at least 70%).Comment: 23 pages, To appear in August in Ap

Clumped stellar winds in supergiant high-mass X-ray binaries: X-ray variability and photoionization

The clumping of massive star winds is an established paradigm confirmed by multiple lines of evidence and supported by stellar wind theory. The purpose of this paper is to bridge the gap between detailed models of inhomogeneous stellar winds in single stars and the phenomenological description of donor winds in supergiant high-mass X-ray binaries (HMXBs). We use results from time-dependent hydrodynamical models of the instability in the line-driven wind of a massive supergiant star to derive the time-dependent accretion rate onto a compact object in the Bondi-Hoyle-Lyttleton approximation. The strong density and velocity fluctuations in the wind result in strong variability of the synthetic X-ray light curves. The model predicts a large scale X-ray variability, up to eight orders of magnitude, on relatively short timescales. The apparent lack of evidence for such strong variability in the observed HMXBs indicates that the details of accretion process act to reduce the variability due to the stellar wind velocity and density jumps. We, also, study the absorption of X-rays in the clumped stellar wind by means of a 2-D stochastic wind model and find that absorption of X-rays changes strongly at different orbital phases. Furthermore, we address the photoionization in the clumped wind, and show that the degree of ionization is affected by the wind clumping. A correction factor for the photoionization parameter is derived. It is shown that the photoionization parameter is reduced by a factor Xi compared to the smooth wind models with the same mass-loss rate, where Xi is the wind inhomogeneity parameter. We conclude that wind clumping must also be taken into account when comparing the observed and model spectra of the photoionized stellar wind.Comment: 12 pages, MNRAS accepte

Leak-before-break: Global perspectives and procedures

Structural integrity of components containing fluids is critical for economic, environmental and safety issues. Any risk of catastrophic failure, in the form of either brittle or ductile manner, is not acceptable across the industries. Consequently, many efforts have been invested in the structural integrity aspect to improve the assessment methodologies. One of the ways to aid the decision whether or not to live with the defect is through the demonstration of Leak-Before-Break (LBB). LBB which is a well-established practice in the nuclear industry, albeit as a defence-in-depth argument or to justify the elimination of pipe whip restraints, also finds its applicability in other industries. A review of the available procedures, their associated limitations and the research carried out in the last thirty years is presented in this paper. Application of this concept within non-nuclear industries is also discussed

Autophagy Induction as a Therapeutic Strategy for Neurodegenerative Diseases.

Autophagy is a major, conserved cellular pathway by which cells deliver cytoplasmic contents to lysosomes for degradation. Genetic studies have revealed extensive links between autophagy and neurodegenerative disease, and disruptions to autophagy may contribute to pathology in some cases. Autophagy degrades many of the toxic, aggregate-prone proteins responsible for such diseases, including mutant huntingtin (mHTT), alpha-synuclein (α-syn), tau, and others, raising the possibility that autophagy upregulation may help to reduce levels of toxic protein species, and thereby alleviate disease. This review examines autophagy induction as a potential therapy in several neurodegenerative diseases-Alzheimer's disease, Parkinson's disease, polyglutamine diseases, and amyotrophic lateral sclerosis (ALS). Evidence in cells and in vivo demonstrates promising results in many disease models, in which autophagy upregulation is able to reduce the levels of toxic proteins, ameliorate signs of disease, and delay disease progression. However, the effective therapeutic use of autophagy induction requires detailed knowledge of how the disease affects the autophagy-lysosome pathway, as activating autophagy when the pathway cannot go to completion (e.g., when lysosomal degradation is impaired) may instead exacerbate disease in some cases. Investigating the interactions between autophagy and disease pathogenesis is thus a critical area for further research

Production of dust by massive stars at high redshift

The large amounts of dust detected in sub-millimeter galaxies and quasars at high redshift pose a challenge to galaxy formation models and theories of cosmic dust formation. At z > 6 only stars of relatively high mass (> 3 Msun) are sufficiently short-lived to be potential stellar sources of dust. This review is devoted to identifying and quantifying the most important stellar channels of rapid dust formation. We ascertain the dust production efficiency of stars in the mass range 3-40 Msun using both observed and theoretical dust yields of evolved massive stars and supernovae (SNe) and provide analytical expressions for the dust production efficiencies in various scenarios. We also address the strong sensitivity of the total dust productivity to the initial mass function. From simple considerations, we find that, in the early Universe, high-mass (> 3 Msun) asymptotic giant branch stars can only be dominant dust producers if SNe generate <~ 3 x 10^-3 Msun of dust whereas SNe prevail if they are more efficient. We address the challenges in inferring dust masses and star-formation rates from observations of high-redshift galaxies. We conclude that significant SN dust production at high redshift is likely required to reproduce current dust mass estimates, possibly coupled with rapid dust grain growth in the interstellar medium.Comment: 72 pages, 9 figures, 5 tables; to be published in The Astronomy and Astrophysics Revie

Prediction of second neurological attack in patients with clinically isolated syndrome using support vector machines

The aim of this study is to predict the conversion from clinically isolated syndrome to clinically definite multiple sclerosis using support vector machines. The two groups of converters and non-converters are classified using features that were calculated from baseline data of 73 patients. The data consists of standard magnetic resonance images, binary lesion masks, and clinical and demographic information. 15 features were calculated and all combinations of them were iteratively tested for their predictive capacity using polynomial kernels and radial basis functions with leave-one-out cross-validation. The accuracy of this prediction is up to 86.4% with a sensitivity and specificity in the same range indicating that this is a feasible approach for the prediction of a second clinical attack in patients with clinically isolated syndromes, and that the chosen features are appropriate. The two features gender and location of onset lesions have been used in all feature combinations leading to a high accuracy suggesting that they are highly predictive. However, it is necessary to add supporting features to maximise the accuracy. © 2013 IEEE