Radius measurements of cataclysmic variable accretion disks

Abstract. Cataclysmic variables (CVs) are interacting binary systems with a white dwarf primary and a low-mass main sequence star secondary. The secondary star fills its Roche lobe and transfers mass onto the white dwarf. Often the gas flow forms an accretion disk around the primary. CVs are characterised by outbursts caused by changes in the mass transfer. In outbursts they can brighten from a couple of magnitudes to tens of magnitudes. Between the outbursts CVs are said to be in quiescence. Accretion disks in cataclysmic variables are the main source of emission in visual wavelengths. Thus, with their assistance, much has been revealed about the stars forming CVs and the ongoing mass transfer process between them. The outburst cycle has been thought to affect the size of the accretion disk: its radius has been thought to shrink in quiescence and expand in outburst. This idea has been recently questioned, and the seemingly varying radius might be caused by radii measurement methods tracking the location of the gas stream hitting the accretion disk instead the actual edge of the disk. In this thesis the standard model for CVs is reviewed and the formation of characteristically double-peaked emission lines from accretion disks is explained. The knowledge is then applied to measuring the radius of the accretion disk of OY Carinae in quiescence. It is found to be close to its theoretical maximum value, not significantly smaller as it should be if the disk size varied during the outburst cycle. This result backs up the idea of a consistently large accretion disk

Kinematics of the outer accretion disk in cataclysmic variables

Abstract. This Masters thesis focuses on studying the kinematics of the outer accretion disk in cataclysmic variables. Cataclysmic variables are a type of interacting binary stars featuring a white dwarf and a main sequence star. Accretion disks in cataclysmic variables are born, when a secondary star still in main sequence overfills its Roche lobe and starts leaking gas towards the primary star (the white dwarf). The extent of the accretion disk has been a cause for discussion; methods measuring it from the hot spot, the place where accretion stream hits the disk, characteristically lead to smaller radii than measuring the radius from outer disk velocities. However, disk size estimates from the outer disk velocities heavily depend on the velocity field. The aim here is to check how close the outer accretion disk is to Keplerian velocities and simple three-body orbits. To do this, they are compared to simulated accretion disks using Smoothed Particle Hydrodynamics. Same comparisons are then done against observational data using Doppler tomography. Our study finds that the Keplerian velocity at the tidal truncation limit can safely be used as a lower limit for orbit-averaged disk. Furthermore, last non-intersecting three-body orbit seems to trace the disk edge quite well, and it can be used as an estimate for accretion disk size

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

Abstract The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared to information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known non-pathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification. This article is protected by copyright. All rights reserved.Peer reviewe