160 research outputs found

    Radio emission and jets from microquasars

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    To some extent, all Galactic binary systems hosting a compact object are potential `microquasars', so much as all galactic nuclei may have been quasars, once upon a time. The necessary ingredients for a compact object of stellar mass to qualify as a microquasar seem to be: accretion, rotation and magnetic field. The presence of a black hole may help, but is not strictly required, since neutron star X-ray binaries and dwarf novae can be powerful jet sources as well. The above issues are broadly discussed throughout this Chapter, with a a rather trivial question in mind: why do we care? In other words: are jets a negligible phenomenon in terms of accretion power, or do they contribute significantly to dissipating gravitational potential energy? How do they influence their surroundings? The latter point is especially relevant in a broader context, as there is mounting evidence that outflows powered by super-massive black holes in external galaxies may play a crucial role in regulating the evolution of cosmic structures. Microquasars can also be thought of as a form of quasars for the impatient: what makes them appealing, despite their low number statistics with respect to quasars, are the fast variability time-scales. In the first approximation, the physics of the jet-accretion coupling in the innermost regions should be set by the mass/size of the accretor: stellar mass objects vary on 10^5-10^8 times shorter time-scales, making it possible to study variable accretion modes and related ejection phenomena over average Ph.D. time-scales. [Abridged]Comment: 28 pages, 13 figures, To appear in Belloni, T. (ed.): The Jet Paradigm - From Microquasars to Quasars, Lect. Notes Phys. 794 (2009

    A look at the other 90 per cent: Investigating British Sign Language vocabulary knowledge in deaf children from different language learning backgrounds

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    In this study we present new data on deaf children's receptive and expressive vocabulary knowledge in British Sign Language (BSL) from a sample consisting of children with deaf parents, children with hearing parents, and children with additional needs. Their performance on three BSL vocabulary tasks was compared with (previously reported findings from) a sample of deaf fluent signers. We use these data to assess the effects of some key demographic/ child variables on deaf signing children's vocabulary and discuss findings in the relation to the meaning of 'normative' data and samples for this heterogeneous population. Findings show no effect of the presence of additional disabilities on participants' scores for any of the three tasks. As expected, chronological age is the most significant factor in performance on all vocabulary tasks while the number of deaf relatives only becomes statistically significant for the form recall task. This study contributes to the field of sign language assessment by seeking to identify key variables in heterogeneity and how these variables affect signed vocabulary acquisition with the long-term objective of informing intervention

    Towards Machine Wald

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    The past century has seen a steady increase in the need of estimating and predicting complex systems and making (possibly critical) decisions with limited information. Although computers have made possible the numerical evaluation of sophisticated statistical models, these models are still designed \emph{by humans} because there is currently no known recipe or algorithm for dividing the design of a statistical model into a sequence of arithmetic operations. Indeed enabling computers to \emph{think} as \emph{humans} have the ability to do when faced with uncertainty is challenging in several major ways: (1) Finding optimal statistical models remains to be formulated as a well posed problem when information on the system of interest is incomplete and comes in the form of a complex combination of sample data, partial knowledge of constitutive relations and a limited description of the distribution of input random variables. (2) The space of admissible scenarios along with the space of relevant information, assumptions, and/or beliefs, tend to be infinite dimensional, whereas calculus on a computer is necessarily discrete and finite. With this purpose, this paper explores the foundations of a rigorous framework for the scientific computation of optimal statistical estimators/models and reviews their connections with Decision Theory, Machine Learning, Bayesian Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty Quantification and Information Based Complexity.Comment: 37 page

    Young and Intermediate-age Distance Indicators

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    Distance measurements beyond geometrical and semi-geometrical methods, rely mainly on standard candles. As the name suggests, these objects have known luminosities by virtue of their intrinsic proprieties and play a major role in our understanding of modern cosmology. The main caveats associated with standard candles are their absolute calibration, contamination of the sample from other sources and systematic uncertainties. The absolute calibration mainly depends on their chemical composition and age. To understand the impact of these effects on the distance scale, it is essential to develop methods based on different sample of standard candles. Here we review the fundamental properties of young and intermediate-age distance indicators such as Cepheids, Mira variables and Red Clump stars and the recent developments in their application as distance indicators.Comment: Review article, 63 pages (28 figures), Accepted for publication in Space Science Reviews (Chapter 3 of a special collection resulting from the May 2016 ISSI-BJ workshop on Astronomical Distance Determination in the Space Age

    Common Genetic Variation And Age at Onset Of Anorexia Nervosa

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    Background Genetics and biology may influence the age at onset of anorexia nervosa (AN). The aims of this study were to determine whether common genetic variation contributes to AN age at onset and to investigate the genetic associations between age at onset of AN and age at menarche. Methods A secondary analysis of the Psychiatric Genomics Consortium genome-wide association study (GWAS) of AN was performed which included 9,335 cases and 31,981 screened controls, all from European ancestries. We conducted GWASs of age at onset, early-onset AN (< 13 years), and typical-onset AN, and genetic correlation, genetic risk score, and Mendelian randomization analyses. Results Two loci were genome-wide significant in the typical-onset AN GWAS. Heritability estimates (SNP-h2) were 0.01-0.04 for age at onset, 0.16-0.25 for early-onset AN, and 0.17-0.25 for typical-onset AN. Early- and typical-onset AN showed distinct genetic correlation patterns with putative risk factors for AN. Specifically, early-onset AN was significantly genetically correlated with younger age at menarche, and typical-onset AN was significantly negatively genetically correlated with anthropometric traits. Genetic risk scores for age at onset and early-onset AN estimated from independent GWASs significantly predicted age at onset. Mendelian randomization analysis suggested a causal link between younger age at menarche and early-onset AN. Conclusions Our results provide evidence consistent with a common variant genetic basis for age at onset and implicate biological pathways regulating menarche and reproduction.Peer reviewe

    GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors

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    Objective: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and crossvalidated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS metaanalysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. Methods: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. Results: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values &lt;5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. Conclusions: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.</p
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