Bovine leukocyte antigen (BoLA) DRB3 is a highly polymorphic gene in major histocompatibility complex(MHC) class II that plays a central role in immune responses and production factors. As of yet, molecular andevolutionary characteristics of BoLA-DRB3.2* have not been as fully understood as human and mouse.Therefore, we attempted to analyze variability and phylogeny of BoLA-DRB3.2* and illustra...

Members of Nemacheilidae Family, Turcinoemacheilus genus were subjected to molecular phylogenetic analysis in this study. This genus was reported in 2009 to inhabit in Karoon River drainage, in contrary to previous assumption that it was the endemic species in the Basin of Tigris River. It was sampled from three stations placed in different tributaries in Karoon drainage and evaluated to unders...

RAxML (Randomized Axelerated Maximum Likelihood) is a program for sequential and parallel Maximum Likelihood based inference of large phylogenetic trees. It can also be used for postanalyses of sets of phylogenetic trees, analyses of alignments and, evolutionary placement of short reads. It has originally been derived from fastDNAml which in turn was derived from Joe Felsentein’s dnaml which is...

Archived data from the WSR-88D network of weather radars in the US hold detailed information about the continent-scale migratory movements of birds over the last 20 years. However, significant technical challenges must be overcome to understand this information and harness its potential for science and conservation. We present an approximate Bayesian inference algorithm to reconstruct the veloc...

Psychophysical experiments have demonstrated that the brain integrates information from multiple sensory cues in a near Bayesian optimal manner. The present study proposes a novel mechanism to achieve this. We consider two reciprocally connected networks, mimicking the integration of heading direction information between the dorsal medial superior temporal (MSTd) and the ventral intraparietal (...

With the advent of high-performance computing, Bayesian methods are becoming increasingly popular tools for the quantification of uncertainty throughout science and industry. Since these methods can impact the making of sometimes critical decisions in increasingly complicated contexts, the sensitivity of their posterior conclusions with respect to the underlying models and prior beliefs is a pr...

Standard Bayesian inference can behave suboptimally if the model is wrong. We present a modification of Bayesian inference which continues to achieve good rates with wrong models. Our method adapts the Bayesian learning rate to the data, picking the rate minimizing the cumulative loss of sequential prediction by posterior randomization. Our results can also be used to adapt the learning rate in...

Abstract: Estimates of average cartel duration and the annual probability of cartel death are based on data for discovered cartels. It is recognized that these estimates could be biased because the population of discovered cartels may not be a representative sample of the latent population of cartels. This paper constructs a birth-death-discovery process to investigate the source and direction ...

We discuss Bayesian inference (BI) for the probabilistic identification of material parameters. This contribution aims to shed light on the use of BI for the identification of elastoplastic material parameters. For this purpose a single spring is considered, for which the stress-strain curves are artificially created. Besides offering a didactic introduction to BI, this paper proposes an approa...