5 resultados para data-driven modelling

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Empirical phylogeographic studies have progressively sampled greater numbers of loci over time, in part motivated by theoretical papers showing that estimates of key demographic parameters improve as the number of loci increases. Recently, next-generation sequencing has been applied to questions about organismal history, with the promise of revolutionizing the field. However, no systematic assessment of how phylogeographic data sets have changed over time with respect to overall size and information content has been performed. Here, we quantify the changing nature of these genetic data sets over the past 20years, focusing on papers published in Molecular Ecology. We found that the number of independent loci, the total number of alleles sampled and the total number of single nucleotide polymorphisms (SNPs) per data set has improved over time, with particularly dramatic increases within the past 5years. Interestingly, uniparentally inherited organellar markers (e.g. animal mitochondrial and plant chloroplast DNA) continue to represent an important component of phylogeographic data. Single-species studies (cf. comparative studies) that focus on vertebrates (particularly fish and to some extent, birds) represent the gold standard of phylogeographic data collection. Based on the current trajectory seen in our survey data, forecast modelling indicates that the median number of SNPs per data set for studies published by the end of the year 2016 may approach similar to 20000. This survey provides baseline information for understanding the evolution of phylogeographic data sets and underscores the fact that development of analytical methods for handling very large genetic data sets will be critical for facilitating growth of the field.

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We present a measurement of the semileptonic mixing asymmetry for B0 mesons, asld, using two independent decay channels: B0→μ +D -X, with D -→K +π -π -; and B0→μ +D *-X, with D * -→D ̄0π -, D ̄0→ K +π - (and charge conjugate processes). We use a data sample corresponding to 10.4fb -1 of pp̄ collisions at √s=1.96TeV, collected with the D0 experiment at the Fermilab Tevatron collider. We extract the charge asymmetries in these two channels as a function of the visible proper decay length of the B0 meson, correct for detector-related asymmetries using data-driven methods, and account for dilution from charge-symmetric processes using Monte Carlo simulation. The final measurement combines four signal visible proper decay length regions for each channel, yielding asld=[0.68±0.45(stat)±0.14(syst)]%. This is the single most precise measurement of this parameter, with uncertainties smaller than the current world average of B factory measurements. © 2012 American Physical Society.

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A measurement of differential cross sections for the production of a pair of isolated photons in proton-proton collisions at root s = 7 TeV is presented. The data sample corresponds to an integrated luminosity of 5.0 fb(-1) collected with the CMS detector. A data-driven isolation template method is used to extract the prompt diphoton yield. The measured cross section for two isolated photons, with transverse energy above 40 and 25 GeV respectively, in the pseudorapidity range vertical bar eta vertical bar < 2.5, vertical bar eta vertical bar (sic) [1.44, 1.57] and with an angular separation Delta R > 0.45, is 17.2 +/-0.2 (stat) +/-1.9 (syst) +/- 0.4 (lumi) pb. Differential cross sections are measured as a function of the diphoton invariant mass, the diphoton transverse momentum, the azimuthal angle difference between the two photons, and the cosine of the polar angle in the Collins-Soper reference frame of the diphoton system. The results are compared to theoretical predictions at leading, next-to-leading, and next-to-next-to-leading order in quantum chromodynamics.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Determining the variability of carbon dioxide emission from soils is an important task as soils are among the largest sources of carbon in biosphere. In this work the temporal variability of bare soil CO2 emissions was measured over a 3-week period. Temporal changes in soil CO2 emission were modelled in terms of the changes that occurred in solar radiation (SR), air temperature (T-air), air humidity (AR), evaporation (EVAP) and atmospheric pressure (ATM) registered during the time period that the experiment was conducted. The multiple regression analysis (backward elimination procedure) includes almost all the meteorological variables and their interactions into the final model (R-2 = 0.98), but solar radiation showed to be the one of the most relevant variables. The present study indicates that meteorological data could be taken into account as the main forces driving the temporal variability of carbon dioxide emission from bare soils, where microbial activity is the sole source of carbon dioxide emitted. (C) 2003 Elsevier B.V. All rights reserved.