SNR-calibrated Type Ia supernova models

Current Type Ia supernova (SN Ia) models can reproduce most visible+IR + UV observations. In the X-ray band, the determination of elemental abundance ratios in supernova remnants (SNRs) through their spectra has reached enough precision to constrain SN Ia models. Martínez-Rodríguez et al have shown that the Ca/S mass ratio in SNRs cannot be reproduced with the standard nuclear reaction rates for a wide variety of SN Ia models, and suggested that the 12C+16O reaction rate could be overestimated by a factor as high as ten. We show that the same Ca/S ratio can be obtained by simultaneously varying the rates of the reactions 12C + 16O, 12C + 12C, 16O + 16O, and 16O(¿, a)12C within the reported uncertainties. We also show that the yields of the main products of SN Ia nucleosynthesis do not depend on the details of which rates are modified, but can be parametrized by an observational quantity such as Ca/S. Using this SNR-calibrated approach, we then proceed to compute a new set of SN Ia models and nucleosynthesis for both Chandrasekhar and sub-Chandrasekhar mass progenitors with a 1D hydrodynamics and nucleosynthesis code. We discuss the nucleosynthesis of the models as a function of progenitor metallicity, mass, and deflagration-to-detonation transition density. The yields of each model are almost independent on the reaction rates modified for a common Ca/S ratio.Peer ReviewedPostprint (author's final draft

MODEL-BASED QUALITY ASSESSMENT AND BASE-CALLING FOR SECOND-GENERATION SEQUENCING DATA

Second-generation sequencing (sec-gen) technology can sequence millions of short fragments of DNA in parallel, and is capable of assembling complex genomes for a small fraction of the price and time of previous technologies. In fact, a recently formed international consortium, the 1,000 Genomes Project, plans to fully sequence the genomes of approximately 1,200 people. The prospect of comparative analysis at the sequence level of a large number of samples across multiple populations may be achieved within the next five years. These data present unprecedented challenges in statistical analysis. For instance, analysis operates on millions of short nucleotide sequences, or reads—strings of A,C,G, or T’s, between 30-100 characters long—which are the result of complex processing of noisy continuous fluorescence intensity measurements known as base-calling. The complexity of the base-calling discretization process results in reads of widely varying quality within and across sequence samples. This variation in processing quality results in infrequent but systematic errors that we have found to mislead downstream analysis of the discretized sequence read data. For instance, a central goal of the 1000 Genomes Project is to quantify across-sample variation at the single nucleotide level. At this resolution, small error rates in sequencing prove significant, especially for rare variants. Sec-gen sequencing is a relatively new technology for which potential biases and sources of obscuring variation are not yet fully understood. Therefore, modeling and quantifying the uncertainty inherent in the generation of sequence reads is of utmost importance. In this paper we present a simple model to capture uncertainty arising in the base-calling procedure of the Illumina/Solexa GA platform. Model parameters have a straightforward interpretation in terms of the chemistry of base-calling allowing for informative and easily interpretable metrics that capture the variability in sequencing quality. Our model provides these informative estimates readily usable in quality assessment tools while significantly improving base-calling performance

Overcoming bias and systematic errors in next generation sequencing data

Considerable time and effort has been spent in developing analysis and quality assessment methods to allow the use of microarrays in a clinical setting. As is the case for microarrays and other high-throughput technologies, data from new high-throughput sequencing technologies are subject to technological and biological biases and systematic errors that can impact downstream analyses. Only when these issues can be readily identified and reliably adjusted for will clinical applications of these new technologies be feasible. Although much work remains to be done in this area, we describe consistently observed biases that should be taken into account when analyzing high-throughput sequencing data. In this article, we review current knowledge about these biases, discuss their impact on analysis results, and propose solutions

The Origin of the Iron-Rich Knot in Tycho's Supernova Remnant

X-ray observations of supernova remnants (SNRs) allow us to investigate the chemical inhomogeneity of ejecta, offering unique insight into the nucleosynthesis in supernova explosions. Here we present detailed imaging and spectroscopic studies of the "Fe knot" located along the eastern rim of the Type Ia SNR Tycho (SN 1572) using Suzaku and Chandra long-exposure data. Surprisingly, the Suzaku spectrum of this knot shows no emission from Cr, Mn, or Ni, which is unusual for the Fe-rich regions in this SNR. Within the framework of the canonical delayed-detonation models for SN Ia, the observed mass ratios M_Cr/M_Fe < 0.023, M_Mn/M_Fe < 0.012, and M_Ni/M_Fe < 0.029 (at 90% confidence) can only be achieved for a peak temperature of (5.3-5.7) x 10^9 K and a neutron excess of < 2.0 x 10^-3. These constraints rule out the deep, dense core of a Chandrasekhar-mass white dwarf as the origin of the Fe knot, and favors either incomplete Si burning or the alpha-rich freeze-out regime, probably close to their boundary. An explosive He burning regime is a possible alternative, although this hypothesis is in conflict with the main properties of this SNR.Comment: 13 pages, 13 figures, accepted for publication in Ap

Simulación del performance de una planta de generación eléctrica de ciclo combinado tomando en cuenta las condiciones ambientales

La demanda de energía eléctrica en el país y el mundo ha aumentado de forma consistente en los últimos años. La energía eléctrica proveniente de plantas termoeléctricas es una opción viable que permite diversificar el mercado eléctrico y usar combustibles fósiles como el gas natural. La influencia de las condiciones meteorológicas en el performance de cualquier maquina pueden significar su viabilidad o inviabilidad desde un punto de vista técnico y económico. Las plantas de generación eléctrica de ciclo combinado no son una excepción a este hecho, más bien por lo contrario su gran magnitud física como maquinas las hacen más vulnerables a las variables climáticas. Condiciones ambientales como la temperatura del aire y la presión atmosférica influyen de manera significativa en el desempeño de una planta termoeléctrica, el presente trabajo estudia el efecto que tienen dichas variables climáticas en ciclo combinado que comprende un ciclo Brayton alimentado con gas natural y un ciclo Rankine de tres niveles de presión. Tomando en cuenta la presión atmosférica y temperatura ambiente local en La Joya y Majes (ubicados en el departamento de Arequipa) 8760 simulaciones off design por cada hora del año en ambas localizaciones fueron realizadas y posteriormente los resultados fueron comparados

DNA Methylation Patterns in Cord Blood of Neonates Across Gestational Age Association With Cell-Type Proportions

Background: A statistical methodology is available to estimate the proportion of cell types (cellular heterogeneity) in adult whole blood specimens used in epigenome-wide association studies (EWAS). However, there is no methodology to estimate the proportion of cell types in umbilical cord blood (also a heterogeneous tissue) used in EWAS. Objectives: The objectives of this study were to determine whether differences in DNA methylation (DNAm) patterns in umbilical cord blood are the result of blood cell type proportion changes that typically occur across gestational age and to demonstrate the effect of cell type proportion confounding by comparing preterm infants exposed and not exposed to antenatal steroids. Methods: We obtained DNAm profiles of cord blood using the Illumina HumanMethylation27k BeadChip array for 385 neonates from the Boston Birth Cohort. We estimated cell type proportions for six cell types using the deconvolution method developed by Houseman et al. (2012). Results: The cell type proportion estimates segregated into two groups that were significantly different by gestational age, indicating that gestational age was associated with cell type proportion. Among infants exposed to antenatal steroids, the number of differentially methylated CpGs dropped from 127 to 1 after controlling for cell type proportion. Discussion: EWAS utilizing cord blood are confounded by cell type proportion. Careful study design including correction for cell type proportion and interpretation of results of EWAS using cord blood are critical

Política fiscal en el manejo de los recursos hidráulicos: Un modelo de equilibrio general computable

We examine the impact of fiscal policy in the management of water resources by using a computable general equilibrium model. Several comparative static exercises are carried out to assess the effects of a particular fiscal policy on economic welfare. Finally, we state a set of fiscal policy recommendations for the efficient management of water in the production process for the Mexican case.

A DECISION-THEORY APPROACH TO INTERPRETABLE SET ANALYSIS FOR HIGH-DIMENSIONAL DATA

A ubiquitous problem in igh-dimensional analysis is the identification of pre-defined sets that are enriched for features showing an association of interest. In this situation, inference is performed on sets, not individual features. We propose an approach which focuses on estimating the fraction of non-null features in a set. We search for unions of disjoint sets (atoms), using as the loss function a weighted average of the number of false and missed discoveries. We prove that the solution is equivalent to thresholding the atomic false discovery rate and that our approach results in a more interpretable set analysis