Dense fine-mapping study identifies new susceptibility loci for primary biliary cirrhosis

We genotyped 2,861 cases of primary biliary cirrhosis (PBC) from the UK PBC Consortium and 8,514 UK population controls across 196,524 variants within 186 known autoimmune risk loci. We identified 3 loci newly associated with PBC (at P <5 × 10(-8)), increasing the number of known susceptibility loci to 25. The most associated variant at 19p12 is a low-frequency nonsynonymous SNP in TYK2, further implicating JAK-STAT and cytokine signaling in disease pathogenesis. An additional five loci contained nonsynonymous variants in high linkage disequilibrium (LD; r(2) > 0.8) with the most associated variant at the locus. We found multiple independent common, low-frequency and rare variant association signals at five loci. Of the 26 independent non-human leukocyte antigen (HLA) signals tagged on the Immunochip, 15 have SNPs in B-lymphoblastoid open chromatin regions in high LD (r(2) > 0.8) with the most associated variant. This study shows how data from dense fine-mapping arrays coupled with functional genomic data can be used to identify candidate causal variants for functional follow-up.

The Polish Competition Authority Submits a Draft Amendment to the Polish Competition Act: Revolution or Fine-Tuning?

This piece highlights and offers a brief analysis of the most important of the
proposed changes to Polish competition law. The draft proposal envisages introduction of, inter alia, financial penalties for individuals, two-stage merger review process, important changes to the leniency program (including introduction of leniency plus), as well as such new tools as remedies and settlements.

Using ancestry-informative markers to identify fine structure across 15 populations of European origin

The Wellcome Trust Case Control Consortium 3 anorexia nervosa genome-wide association scan includes 2907 cases from 15 different populations of European origin genotyped on the Illumina 670K chip. We compared methods for identifying population stratification, and suggest list of markers that may help to counter this problem. It is usual to identify population structure in such studies using only common variants with minor allele frequency (MAF) >5%; we find that this may result in highly informative SNPs being discarded, and suggest that instead all SNPs with MAF >1% may be used. We established informative axes of variation identified via principal component analysis and highlight important features of the genetic structure of diverse European-descent populations, some studied for the first time at this scale. Finally, we investigated the substructure within each of these 15 populations and identified SNPs that help capture hidden stratification. This work can provide information regarding the designing and interpretation of association results in the International Consortia. 

Electron-Impact Excitation Collision Strengths and Theoretical Line Intensities for Fine-Structure Transitions in S III

We present Maxwellian-averaged effective collision strengths for the electron-impact excitation of S III over a wide range of electron temperatures of astrophysical importance, log Te (K) = 3.0-6.0. The calculation incorporates 53 fine-structure levels arising from the six configurations—3s 23p 2, 3s3p 3, 3s 23p3d, 3s 23p4s, 3s 23p4p, and 3s 23p4d—giving rise to 1378 individual lines and is undertaken using the recently developed RMATRX II plus FINE95 suite of codes. A detailed comparison is made with a previous R-matrix calculation and significant differences are found for some transitions. The atomic data are subsequently incorporated into the modeling code CLOUDY to generate line intensities for a range of plasma parameters, with emphasis on allowed ultraviolet extreme-ultraviolet emission lines detected from the Io plasma torus. Electron density-sensitive line ratios are calculated with the present atomic data and compared with those from CHIANTI v7.1, as well as with Io plasma torus spectra obtained by Far-Ultraviolet Spectroscopic Explorer and Extreme-Ultraviolet Explorer. The present line intensities are found to agree well with the observational results and provide a noticeable improvement on the values predicted by CHIANTI.

Electron-impact excitation of FeII - Collision strengths and effective collision strengths for low-lying fine-structure forbidden transitions

Context. Absorption or emission lines of Fe II are observed in many astrophysical spectra and accurate atomic data are required to interpret these lines. The calculation of electron-impact excitation rates for transitions among even the lowest lying levels of Fe II is a formidable task for theoreticians.

Aims. In this paper, we present collision strengths and effective collision strengths for electron-impact excitation of Fe II for low-lying forbidden transitions among the lowest 16 fine-structure levels arising from the four LS states 3d(6)4s D-6(e), 3d(7) F-4(e), 3d(6)4s D-4(e), and 3d(7) P-4(e). The effective collision strengths are calculated for a wide range of electron temperatures of astrophysical importance from 30-100 000 K.

Methods. The parallel suite of Breit-Pauli codes are utilised to compute the collision cross sections for electron-impact excitation of Fe II and relativistic terms are included explicitly in both the target and the scattering approximation. 100 LS or 262-jj levels formed from the basis configurations 3d(6)4s, 3d(7), and 3d(6)4p were included in the wavefunction representation of the target, including all doublet, quartet, and sextet terms. Collision strengths for a total of 34191 individual transitions were computed.

Results. A detailed comparison is made with previous theoretical works and significant differences were found to occur in the effective collision strengths, particularly at low temperatures.

MHD wave modes resolved in fine-scale chromospheric magnetic structures

Within the last decade, due to significant improvements in the spatial and temporal resolution of chromospheric data, magneto hydrodynamic (MHD)wave studies in this fascinating region of the Sun's atmosphere have risen to the forefront of solar physics research. In this review we begin by reviewing the challenges and debates that have manifested in relation to MHD wave mode identification in fine-scale chromosphericmagnetic structures, including spicules, fibrils and mottles. Next we goon to discuss how the process of accurately identifying MHD wave modes also has a crucial role to play in estimating their wave energy flux.This is of cardinal importance for estimating what the possible contribution of MHD waves is to solar atmospheric heating. Finally, we detail how such advances in chromospheric MHD wave studies have also allowed us, for the first time, to implement cutting-edge magneto seismological techniques that provide new insight into the sub-resolution plasma structuring of the lower solar atmosphere.

These Fine Lines: Locating Noncitizenship in Political Protest in Europe

Since 2012, refugee protest camps and occupations have been established throughout Europe that contest the exclusion of refugees and asylum seekers, but that also make concrete demands for better living conditions and basic rights. It is a movement that is led by migrants as noncitizens, and so reveals new ways of thinking of the political agency and status of noncitizenship not as simply reactive to an absence of citizenship, but as a powerful and transgressive subjectivity in its own right. This paper argues that we should resist collapsing analysis back into the frameworks of citizenship, and instead be attentive to the politics of presence and solidarity manifest in these protest camps as a way of understanding, and engaging, noncitizen activism.

The signature of fine scale local adaptation in Atlantic salmon revealed from common garden experiments in nature

Understanding the extent, scale and genetic basis of local adaptation is important for conservation and management. Its relevance in salmonids at microgeographic scales, where dispersal (and hence potential gene flow) can be substantial, has however been questioned. Here we compare the fitness of communally-reared offspring of local and foreign Atlantic salmon Salmo salar from adjacent Irish rivers and reciprocal F1 hybrid crosses between them, in the wild ‘home’ environment of the local population. Experimental groups did not differ in wild smolt output but a catastrophic flood event may have limited our ability to detect freshwater performance differences, which were evident in a previous study. Foreign parr exhibited higher, and hybrids intermediate, emigration rates from the natal stream relative to local parr, consistent with genetically-based behavioural differences. Adult return rates were lower for the foreign compared to the local group. Overall lifetime success of foreigners and hybrids relative to locals was estimated at 31% and 40% (mean of both hybrid groups), respectively. The results imply a genetic basis to fitness differences among populations separated by only 50km, driven largely by variation in smolt to adult return rates. Hence even if supplementary stocking programs obtain broodstock from neighbouring rivers, the risk of extrinsic outbreeding depression may be high.

ALEA: Fine-Grain Energy Profiling with Basic Block Sampling

Energy efficiency is an essential requirement for all contemporary computing systems. We thus need tools to measure the energy consumption of computing systems and to understand how workloads affect it. Significant recent research effort has targeted direct power measurements on production computing systems using on-board sensors or external instruments. These direct methods have in turn guided studies of software techniques to reduce energy consumption via workload allocation and scaling. Unfortunately, direct energy measurements are hampered by the low power sampling frequency of power sensors. The coarse granularity of power sensing limits our understanding of how power is allocated in systems and our ability to optimize energy efficiency via workload allocation.
We present ALEA, a tool to measure power and energy consumption at the granularity of basic blocks, using a probabilistic approach. ALEA provides fine-grained energy profiling via sta- tistical sampling, which overcomes the limitations of power sens- ing instruments. Compared to state-of-the-art energy measurement tools, ALEA provides finer granularity without sacrificing accuracy. ALEA achieves low overhead energy measurements with mean error rates between 1.4% and 3.5% in 14 sequential and paral- lel benchmarks tested on both Intel and ARM platforms. The sampling method caps execution time overhead at approximately 1%. ALEA is thus suitable for online energy monitoring and optimization. Finally, ALEA is a user-space tool with a portable, machine-independent sampling method. We demonstrate two use cases of ALEA, where we reduce the energy consumption of a k-means computational kernel by 37% and an ocean modelling code by 33%, compared to high-performance execution baselines, by varying the power optimization strategy between basic blocks.