305 research outputs found
The H.E.S.S. central data acquisition system
The High Energy Stereoscopic System (H.E.S.S.) is a system of Imaging
Atmospheric Cherenkov Telescopes (IACTs) located in the Khomas Highland in
Namibia. It measures cosmic gamma rays of very high energies (VHE; >100 GeV)
using the Earth's atmosphere as a calorimeter. The H.E.S.S. Array entered Phase
II in September 2012 with the inauguration of a fifth telescope that is larger
and more complex than the other four. This paper will give an overview of the
current H.E.S.S. central data acquisition (DAQ) system with particular emphasis
on the upgrades made to integrate the fifth telescope into the array. At first,
the various requirements for the central DAQ are discussed then the general
design principles employed to fulfil these requirements are described. Finally,
the performance, stability and reliability of the H.E.S.S. central DAQ are
presented. One of the major accomplishments is that less than 0.8% of
observation time has been lost due to central DAQ problems since 2009.Comment: 17 pages, 8 figures, published in Astroparticle Physic
Arbitrary Choice of Basic Variables in Density Functional Theory. II. Illustrative Applications
Our recent theory (Ref. 1) enables us to choose arbitrary quantities as the
basic variables of the density functional theory. In this paper we apply it to
several cases. In the case where the occupation matrix of localized orbitals is
chosen as a basic variable, we can obtain the single-particle equation which is
equivalent to that of the LDA+U method. The theory also leads to the
Hartree-Fock-Kohn-Sham equation by letting the exchange energy be a basic
variable. Furthermore, if the quantity associated with the density of states
near the Fermi level is chosen as a basic variable, the resulting
single-particle equation includes the additional potential which could mainly
modify the energy-band structures near the Fermi level.Comment: 27 page
Second order analysis of geometric functionals of Boolean models
This paper presents asymptotic covariance formulae and central limit theorems
for geometric functionals, including volume, surface area, and all Minkowski
functionals and translation invariant Minkowski tensors as prominent examples,
of stationary Boolean models. Special focus is put on the anisotropic case. In
the (anisotropic) example of aligned rectangles, we provide explicit analytic
formulae and compare them with simulation results. We discuss which information
about the grain distribution second moments add to the mean values.Comment: Chapter of the forthcoming book "Tensor Valuations and their
Applications in Stochastic Geometry and Imaging" in Lecture Notes in
Mathematics edited by Markus Kiderlen and Eva B. Vedel Jensen. (The second
version mainly resolves minor LaTeX problems.
Whole Genome Sequence Data From Captive Baboons Implicate RBFOX1 in Epileptic Seizure Risk
In this study, we investigate the genetic determinants that underlie epilepsy in a captive baboon pedigree and evaluate the potential suitability of this non-human primate model for understanding the genetic etiology of human epilepsy. Archived whole-genome sequence data were analyzed using both a candidate gene approach that targeted variants in baboon homologs of 19 genes (n = 20,881 SNPs) previously implicated in genetic generalized epilepsy (GGE) and a more agnostic approach that examined protein-altering mutations genome-wide as assessed by snpEff (n = 36,169). Measured genotype association tests for baboon cases of epileptic seizure were performed using SOLAR, as well as gene set enrichment analyses (GSEA) and protein–protein interaction (PPI) network construction of top association hits genome-wide (p \u3c 0.01; n = 441 genes). The maximum likelihood estimate of heritability for epileptic seizure in the pedigreed baboon sample is 0.76 (SE = 0.77; p = 0.07). Among candidate genes for GGE, a significant association was detected for an intronic SNP in RBFOX1 (p = 5.92 × 10–6; adjusted p = 0.016). For protein-altering variants, no genome-wide significant results were observed for epilepsy status. However, GSEA revealed significant positive enrichment for genes involved in the extracellular matrix structure (ECM; FDR = 0.0072) and collagen formation (FDR = 0.017), which was reflected in a major PPI network cluster. This preliminary study highlights the potential role of RBFOX1 in the epileptic baboon, a protein involved in transcriptomic regulation of multiple epilepsy candidate genes in humans and itself previously implicated in human epilepsy, both focal and generalized. Moreover, protein-damaging variants from across the genome exhibit a pattern of association that links collagen-containing ECM to epilepsy risk. These findings suggest a shared genetic etiology between baboon and human forms of GGE and lay the foundation for follow-up research
Do rare variant genotypes predict common variant genotypes?
The synthetic association hypothesis proposes that common genetic variants detectable in genome-wide association studies may reflect the net phenotypic effect of multiple rare polymorphisms distributed broadly within the focal gene rather than, as often assumed, the effect of common functional variants in high linkage disequilibrium with the focal marker. In a recent study, Dickson and colleagues demonstrated synthetic association in simulations and in two well-characterized, highly polymorphic human disease genes. The converse of this hypothesis is that rare variant genotypes must be correlated with common variant genotypes often enough to make the phenomenon of synthetic association possible. Here we used the exome genotype data provided for Genetic Analysis Workshop 17 to ask how often, how well, and under what conditions rare variant genotypes predict the genotypes of common variants within the same gene. We found nominal evidence of correlation between rare and common variants in 21-30% of cases examined for unrelated individuals; this rate increased to 38-44% for related individuals, underscoring the segregation that underlies synthetic association
Cell shape analysis of random tessellations based on Minkowski tensors
To which degree are shape indices of individual cells of a tessellation
characteristic for the stochastic process that generates them? Within the
context of stochastic geometry and the physics of disordered materials, this
corresponds to the question of relationships between different stochastic
models. In the context of image analysis of synthetic and biological materials,
this question is central to the problem of inferring information about
formation processes from spatial measurements of resulting random structures.
We address this question by a theory-based simulation study of shape indices
derived from Minkowski tensors for a variety of tessellation models. We focus
on the relationship between two indices: an isoperimetric ratio of the
empirical averages of cell volume and area and the cell elongation quantified
by eigenvalue ratios of interfacial Minkowski tensors. Simulation data for
these quantities, as well as for distributions thereof and for correlations of
cell shape and volume, are presented for Voronoi mosaics of the Poisson point
process, determinantal and permanental point processes, and Gibbs hard-core and
random sequential absorption processes as well as for Laguerre tessellations of
polydisperse spheres and STIT- and Poisson hyperplane tessellations. These data
are complemented by mechanically stable crystalline sphere and disordered
ellipsoid packings and area-minimising foam models. We find that shape indices
of individual cells are not sufficient to unambiguously identify the generating
process even amongst this limited set of processes. However, we identify
significant differences of the shape indices between many of these tessellation
models. Given a realization of a tessellation, these shape indices can narrow
the choice of possible generating processes, providing a powerful tool which
can be further strengthened by density-resolved volume-shape correlations.Comment: Chapter of the forthcoming book "Tensor Valuations and their
Applications in Stochastic Geometry and Imaging" in Lecture Notes in
Mathematics edited by Markus Kiderlen and Eva B. Vedel Jense
Novel Associations of Nonstructural Loci with Paraoxonase Activity
The high-density-lipoprotein-(HDL-) associated esterase paraoxonase 1 (PON1) is a likely contributor to the antioxidant and antiatherosclerotic capabilities of HDL. Two nonsynonymous mutations in the structural gene, PON1, have been associated with variation in activity levels, but substantial interindividual differences remain unexplained and are greatest for substrates other than the eponymous paraoxon. PON1 activity levels were measured for three substrates—organophosphate paraoxon, arylester phenyl acetate, and lactone dihydrocoumarin—in 767 Mexican American individuals from San Antonio, Texas. Genetic influences on activity levels for each substrate were evaluated by association with approximately one million single nucleotide polymorphism (SNPs) while conditioning on PON1 genotypes. Significant associations were detected at five loci including regions on chromosomes 4 and 17 known to be associated with atherosclerosis and lipoprotein regulation and loci on chromosome 3 that regulate ubiquitous transcription factors. These loci explain 7.8% of variation in PON1 activity with lactone as a substrate, 5.6% with the arylester, and 3.0% with paraoxon. In light of the potential importance of PON1 in preventing cardiovascular disease/events, these novel loci merit further investigation
Genome-wide significant linkage of schizophrenia-related neuroanatomical trait to 12q24
The insula and medial prefrontal cortex (mPFC) share functional, histological, transcriptional and developmental characteristics and they serve higher cognitive functions of theoretical relevance to schizophrenia and related disorders. Meta-analyses and multivariate analysis of structural magnetic resonance imaging (MRI) scans indicate that gray matter density and volume reductions in schizophrenia are the most consistent and pronounced in a network primarily composed of the insula and mPFC. We used source-based morphometry, a multivariate technique optimized for structural MRI, in a large sample of randomly ascertained pedigrees (N = 887) to derive an insula-mPFC component and to investigate its genetic determinants. Firstly, we replicated the insula-mPFC gray matter component as an independent source of gray matter variation in the general population, and verified its relevance to schizophrenia in an independent case-control sample. Secondly, we showed that the neuroanatomical variation defined by this component is largely determined by additive genetic variation (h2 = 0.59), and genome-wide linkage analysis resulted in a significant linkage peak at 12q24 (LOD = 3.76). This region has been of significant interest to psychiatric genetics as it contains the Darier’s disease locus and other proposed susceptibility genes (e.g. DAO, NOS1), and it has been linked to affective disorders and schizophrenia in multiple populations. Thus, in conjunction with previous clinical studies, our data imply that one or more psychiatric risk variants at 12q24 are co-inherited with reductions in mPFC and insula gray matter concentration
Comparison of strategies for identification of regulatory quantitative trait loci of transcript expression traits
Abstract In order to identify regulatory genes, we determined the heritability of gene transcripts, performed linkage analysis to identify quantitative trait loci (QTLs), and evaluated the evidence for shared genetic effects among transcripts with co-localized QTLs in non-diseased participants from 14 CEPH (Centre d'Etude du Polymorphisme Humain) Utah families. Seventy-six percent of transcripts had a significant heritability and 54% of them had LOD score ≥ 1.8. Bivariate genetic analysis of 15 transcripts that had co-localized QTLs on 4q28.2-q31.1 identified significant genetic correlation among some transcripts although no improvement in the magnitude of LOD scores in this region was noted. Similar results were found in analysis of 12 transcripts, that had co-localized QTLs in the 13q34 region. Principal-component analyses did not improve the ability to identify chromosomal regions of co-localized gene expressions
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