1,245 research outputs found
Luminous Type II Short-Plateau Supernovae 2006Y, 2006ai, and 2016egz: A Transitional Class from Stripped Massive Red Supergiants
The diversity of Type II supernovae (SNe II) is thought to be driven mainly
by differences in their progenitor's hydrogen-rich (H-rich) envelope mass, with
SNe IIP having long plateaus ( days) and the most massive H-rich
envelopes. However, it is an ongoing mystery why SNe II with short plateaus
(tens of days) are rarely seen. Here we present optical/near-infrared
photometric and spectroscopic observations of luminous Type II short-plateau
SNe 2006Y, 2006ai, and 2016egz. Their plateaus of about -- days and
luminous optical peaks ( mag) indicate significant pre-explosion
mass loss resulting in partially-stripped H-rich envelopes and early
circumstellar material (CSM) interaction. We compute a large grid of
MESA+STELLA single-star progenitor and light-curve models with various
progenitor zero-age main-sequence (ZAMS) masses, mass-loss efficiencies,
explosion energies, Ni masses, and CSM densities. Our model grid shows a
continuous population of SNe IIP--IIL--IIb-like light-curve morphology in
descending order of H-rich envelope mass. With large Ni masses
(), short-plateau SNe II lie in a confined parameter
space as a transitional class between SNe IIL and IIb. For SNe 2006Y, 2006ai,
and 2016egz, our findings suggest high-mass red supergiant (RSG) progenitors
(--) with small H-rich envelope masses
() that experience enhanced mass
loss () for the last few
decades before the explosion. If high-mass RSGs result in rare short-plateau
SNe II, then these events might ease some of the apparent under-representation
of higher-luminosity RSGs in observed SN II progenitor samples.Comment: 26 pages, 16 figures, submitted to Ap
zCall: a rare variant caller for array-based genotyping
Summary: zCall is a variant caller specifically designed for calling rare single-nucleotide polymorphisms from array-based technology. This caller is implemented as a post-processing step after a default calling algorithm has been applied. The algorithm uses the intensity profile of the common allele homozygote cluster to define the location of the other two genotype clusters. We demonstrate improved detection of rare alleles when applying zCall to samples that have both Illumina Infinium HumanExome BeadChip and exome sequencing data available
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Mapping Copy Number Variation by Population Scale Genome Sequencing
Genomic structural variants (SVs) are abundant in humans, differing from other forms of variation in extent, origin and functional impact. Despite progress in SV characterization, the nucleotide resolution architecture of most SVs remains unknown. We constructed a map of unbalanced SVs (that is, copy number variants) based on whole genome DNA sequencing data from 185 human genomes, integrating evidence from complementary SV discovery approaches with extensive experimental validations. Our map encompassed 22,025 deletions and 6,000 additional SVs, including insertions and tandem duplications. Most SVs (53%) were mapped to nucleotide resolution, which facilitated analysing their origin and functional impact. We examined numerous whole and partial gene deletions with a genotyping approach and observed a depletion of gene disruptions amongst high frequency deletions. Furthermore, we observed differences in the size spectra of SVs originating from distinct formation mechanisms, and constructed a map of SV hotspots formed by common mechanisms. Our analytical framework and SV map serves as a resource for sequencing-based association studies.Organismic and Evolutionary Biolog
Patterns and rates of exonic de novo mutations in autism spectrum disorders
Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified1,2. To identify further genetic risk factors, we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n= 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant and the overall rate of mutation is only modestly higher than the expected rate. In contrast, there is significantly enriched connectivity among the proteins encoded by genes harboring de novo missense or nonsense mutations, and excess connectivity to prior ASD genes of major effect, suggesting a subset of observed events are relevant to ASD risk. The small increase in rate of de novo events, when taken together with the connections among the proteins themselves and to ASD, are consistent with an important but limited role for de novo point mutations, similar to that documented for de novo copy number variants. Genetic models incorporating these data suggest that the majority of observed de novo events are unconnected to ASD, those that do confer risk are distributed across many genes and are incompletely penetrant (i.e., not necessarily causal). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5 to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case-control study provide strong evidence in favor of CHD8 and KATNAL2 as genuine autism risk factors
Analysis of Rare, Exonic Variation amongst Subjects with Autism Spectrum Disorders and Population Controls
We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD. © 2013 Liu et al
Luminous Type II Short-Plateau Supernovae 2006Y, 2006ai, and 2016egz: A Transitional Class from Stripped Massive Red Supergiants
The diversity of Type II supernovae (SNe II) is thought to be driven mainly by differences in their progenitor's hydrogen-rich (H-rich) envelope mass, with SNe IIP having long plateaus (similar to 100 days) and the most massive H-rich envelopes. However, it is an ongoing mystery why SNe II with short plateaus (tens of days) are rarely seen. Here, we present optical/near-infrared photometric and spectroscopic observations of luminous Type II short-plateau SNe 2006Y, 2006ai, and 2016egz. Their plateaus of about 50-70 days and luminous optical peaks (less than or similar to-18.4 mag) indicate significant pre-explosion mass loss resulting in partially stripped H-rich envelopes and early circumstellar material (CSM) interaction. We compute a large grid of MESA+STELLA single-star progenitor and light-curve models with various progenitor zero-age main-sequence (ZAMS) masses, mass-loss efficiencies, explosion energies, Ni-56 masses, and CSM densities. Our model grid shows a continuous population of SNe IIP-IIL-IIb-like light-curve morphology in descending order of H-rich envelope mass. With large Ni-56 masses (greater than or similar to 0.05M(circle dot)), short-plateau SNe II lie in a confined parameter space as a transitional class between SNe IIL and IIb. For SNe 2006Y, 2006ai, and 2016egz, our findings suggest high-mass red supergiant (RSG) progenitors (M-ZAMS similar or equal to 18-22M(circle dot)) with small H-rich envelope masses (M-Henv similar or equal to 1.7 M-circle dot) that have experienced enhanced mass loss (M similar or equal to 10(-2) M-circle dot yr(-1)) for the last few decades before the explosion. If high-mass RSGs result in rare short-plateau SNe II, then these events might ease some of the apparent underrepresentation of higher-luminosity RSGs in observed SN II progenitor samples
The genetic architecture of type 2 diabetes
The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes
Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV
Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript −1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio
Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an
Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis
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