Inbreeding, Average Relatedness Coefficient and Effective Population Size In Jaffarabadi Buffaloes Raised In Brazil

The major aim of this study was to evaluate the inbreeding (F), average relatedness coefficient (AR) and effective population size (Ne) in the Jaffarabadi buffalo breed from Brazil. Pedigree information of 1,272 animals born from 1966 was used. The effective population size was calculated in two ways: first, computed via individual increase in inbreeding and second estimated by individual increase in coancestry. The known generation numbers were 1.24, 1.76 and 2.64 for complete, equivalent and maximum generation, respectively. The effective size computed via individual increase in coancestry was small with a value of 10.82 +/- 1.29. The effective size computed by individual increase in inbreeding (10.40 +/- 3.69) was very similar but a little smaller than the previous reported value. The average values of F and AR for the population reference (1,059) were 4.22 and 12.5 percent. The mean of F for inbred animals (319) was 14.0%. The F and AR means were 5.7 and 13.3% for animals with at least 1.5 known equivalent generation and 9.3 and 15.97% for individuals having at least 2.5 equivalent generations known. It was found 78 matings between half sibs (6.14%) and 67 matings (5.27%) between parent-offspring. The estimated inbreeding increase per generation by considering maximum generation, complete generation and equivalent generation were 1.21%, 5.18% and 3.57%, respectively. Considering the uncompleted pedigree, the estimated inbreeding for the reference population could be underestimated.

The NINJA-2 project: detecting and characterizing gravitational waveforms modelled using numerical binary black hole simulations

The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave (GW) astrophysics communities. The purpose of NINJA is to study the ability to detect GWs emitted from merging binary black holes (BBH) and recover their parameters with next-generation GW observatories. We report here on the results of the second NINJA project, NINJA-2, which employs 60 complete BBH hybrid waveforms consisting of a numerical portion modelling the late inspiral, merger, and ringdown stitched to a post-Newtonian portion modelling the early inspiral. In a 'blind injection challenge' similar to that conducted in recent Laser Interferometer Gravitational Wave Observatory (LIGO) and Virgo science runs, we added seven hybrid waveforms to two months of data recoloured to predictions of Advanced LIGO (aLIGO) and Advanced Virgo (AdV) sensitivity curves during their first observing runs. The resulting data was analysed by GW detection algorithms and 6 of the waveforms were recovered with false alarm rates smaller than 1 in a thousand years. Parameter-estimation algorithms were run on each of these waveforms to explore the ability to constrain the masses, component angular momenta and sky position of these waveforms. We find that the strong degeneracy between the mass ratio and the BHs' angular momenta will make it difficult to precisely estimate these parameters with aLIGO and AdV. We also perform a large-scale Monte Carlo study to assess the ability to recover each of the 60 hybrid waveforms with early aLIGO and AdV sensitivity curves. Our results predict that early aLIGO and AdV will have a volume-weighted average sensitive distance of 300 Mpc (1 Gpc) for 10M circle dot + 10M circle dot (50M circle dot + 50M circle dot) BBH coalescences. We demonstrate that neglecting the component angular momenta in the waveform models used in matched-filtering will result in a reduction in sensitivity for systems with large component angular momenta. This reduction is estimated to be up to similar to 15% for 50M circle dot + 50M circle dot BBH coalescences with almost maximal angular momenta aligned with the orbit when using early aLIGO and AdV sensitivity curves.

Breeding sites of the leaf frog phyllomedusa tetraploidea (hylidae, phyllomedusinae) in a forest remnant in southern Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)