Search results for "Bay"

Temporal Changes in Mollusk and Polychaete Communities in the Soft Bottom of Cullera Bay (Western Mediterranean)

2007

Abstract This study identifies the most abundant and significant species—from an ecological point of view—in the soft bottom of Cullera Bay (Spain) in order to study the seasonal (summer–winter) variations in the local communities of polychaete annelids and bivalve mollusks. This paper presents the results of the analysis of samples taken during two field campaigns (July 2002 and February 2003) of a series of five campaigns carried out in 2002 and 2003. For these field observations, twelve sampling stations were set up in the bay along three transects. At these stations, macrobenthos was collected using a Ponar grab. Only polychaete annelids and bivalve mollusks were selected from the sampl…

Ranking drivers of global carbon and energy fluxes over land

2015

The accurate estimation of carbon and heat fluxes at global scale is paramount for future policy decisions in the context of global climate change. This paper analyzes the relative relevance of potential remote sensing and meteorological drivers of global carbon and energy fluxes over land. The study is done in an indirect way via upscaling both Gross Primary Production (GPP) and latent energy (LE) using Gaussian Process regression (GPR). In summary, GPR is successfully compared to multivariate linear regression (RMSE gain of +4.17% in GPP and +7.63% in LE) and kernel ridge regression (+2.91% in GPP and +3.07% in LE). The best GP models are then studied in terms of explanatory power based o…

Bayesian joint models for longitudinal and survival data

2020

This paper takes a quick look at Bayesian joint models (BJM) for longitudinal and survival data. A general formulation for BJM is examined in terms of the sampling distribution of the longitudinal and survival processes, the conditional distribution of the random effects and the prior distribution. Next a basic BJM defined in terms of a mixed linear model and a Cox survival regression models is discussed and some extensions and other Bayesian topics are briefly outlined.

Bayesian network based pathway analysis of microarray data

2011

Hybridization of mouse lemurs: different patterns under different ecological conditions

2011

Abstract Background Several mechanistic models aim to explain the diversification of the multitude of endemic species on Madagascar. The island's biogeographic history probably offered numerous opportunities for secondary contact and subsequent hybridization. Existing diversification models do not consider a possible role of these processes. One key question for a better understanding of their potential importance is how they are influenced by different environmental settings. Here, we characterized a contact zone between two species of mouse lemurs, Microcebus griseorufus and M. murinus, in dry spiny bush and mesic gallery forest that border each other sharply without intermediate habitats…

A Bayesian direction-of-arrival model for an undetermined number of sources using a two-microphone array.

2014

Sound source localization using a two-microphone array is an active area of research, with considerable potential for use with video conferencing, mobile devices, and robotics. Based on the observed time-differences of arrival between sound signals, a probability distribution of the location of the sources is considered to estimate the actual source positions. However, these algorithms assume a given number of sound sources. This paper describes an updated research account on the solution presented in Escolano et al. [J. Acoust. Am. Soc. 132(3), 1257-1260 (2012)], where nested sampling is used to explore a probability distribution of the source position using a Laplacian mixture model, whic…

Graph Topology Learning and Signal Recovery Via Bayesian Inference

2019

The estimation of a meaningful affinity graph has become a crucial task for representation of data, since the underlying structure is not readily available in many applications. In this paper, a topology inference framework, called Bayesian Topology Learning, is proposed to estimate the underlying graph topology from a given set of noisy measurements of signals. It is assumed that the graph signals are generated from Gaussian Markov Random Field processes. First, using a factor analysis model, the noisy measured data is represented in a latent space and its posterior probability density function is found. Thereafter, by utilizing the minimum mean square error estimator and the Expectation M…

The complete mitochondrial genome of Bactrocera biguttula (Bezzi) (Diptera: Tephritidae) and phylogenetic relationships with other Dacini

2018

Bactrocera biguttula is an African olive fruit fly that does not attack cultivated olives but rather develops in the fruits of wild species of Olea and Noronhia. The complete mitochondrial genome of an individual specimen was characterized in comparison to other Bactrocera. The phylogenetic relationships of B. biguttula with other Dacini were investigated, with special focus on B. oleae, an agricultural pest known to attack cultivated and wild olives. The sequence had a total length of 15,829 bp, and included the typical features of insect mitogenomes, similarly to the other Bactrocera analysed. Start codons included ATG, ATC, ATT, and TCG (in COI). The majority of stop codons (TAA) were fu…

A Revised Timescale for Human Evolution Based on Ancient Mitochondrial Genomes

2013

Summary Background Recent analyses of de novo DNA mutations in modern humans have suggested a nuclear substitution rate that is approximately half that of previous estimates based on fossil calibration. This result has led to suggestions that major events in human evolution occurred far earlier than previously thought. Results Here, we use mitochondrial genome sequences from ten securely dated ancient modern humans spanning 40,000 years as calibration points for the mitochondrial clock, thus yielding a direct estimate of the mitochondrial substitution rate. Our clock yields mitochondrial divergence times that are in agreement with earlier estimates based on calibration points derived from e…

Weighted-average least squares (WALS): A survey

2016

Model averaging has become a popular method of estimation, following increasing evidence that model selection and estimation should be treated as one joint procedure. Weighted-average least squares (WALS) is a recent model-average approach, which takes an intermediate position between frequentist and Bayesian methods, allows a credible treatment of ignorance, and is extremely fast to compute. We review the theory of WALS and discuss extensions and applications.