Search results for " Bayesian"
showing 10 items of 124 documents
A hierarchical Bayesian Beta regression approach to study the effects of geographical genetic structure and spatial autocorrelation on species distri…
2019
Global climate change (GCC) may be causing distribution range shifts in many organisms worldwide. Multiple efforts are currently focused on the development of models to better predict distribution range shifts due to GCC. We addressed this issue by including intraspecific genetic structure and spatial autocorrelation (SAC) of data in distribution range models. Both factors reflect the joint effect of ecoevolutionary processes on the geographical heterogeneity of populations. We used a collection of 301 georeferenced accessions of the annual plant Arabidopsis thaliana in its Iberian Peninsula range, where the species shows strong geographical genetic structure. We developed spatial and nonsp…
Does the genetic diversity among pubescent white oaks in southern Italy, Sicily and Sardinia islands support the current taxonomic classification?
2020
AbstractMolecular diversity analysis of deciduous pubescent oaks was conducted for populations from Calabria, Sicily and Sardinia. The aims of this study were twofold. First, to provide data on the genetic diversity of pubescent oaks from an understudied area which currently exhibits one of the highest concentrations of pubescent oak species in Europe. Second, to verify if these groups of oaks are genetically distinct and if their identification is in accordance with the current taxonomic classification. Molecular analyses of leaf material of 480 trees from seventeen populations belonging to putatively different pubescent oak species (Quercus amplifolia,Q. congesta,Q. dalechampii,Q. ichnusa…
Empirical Bayes improves assessments of diversity and similarity when overdispersion prevails in taxonomic counts with no covariates
2019
Abstract The assessment of diversity and similarity is relevant in monitoring the status of ecosystems. The respective indicators are based on the taxonomic composition of biological communities of interest, currently estimated through the proportions computed from sampling multivariate counts. In this work we present a novel method to estimate the taxonomic composition able to work even with a single sample and no covariates, when data are affected by overdispersion. The presence of overdispersion in taxonomic counts may be the result of significant environmental factors which are often unobservable but influence communities. Following the empirical Bayes approach, we combine a Bayesian mo…
Dealing with physical barriers in bottlenose dolphin (Tursiops truncatus) distribution
2019
Abstract Worldwide, cetacean species have started to be protected, but they are still very vulnerable to accidental damage from an expanding range of human activities at sea. To properly manage these potential threats we need a detailed understanding of the seasonal distributions of these highly mobile populations. To achieve this goal, a growing effort has been underway to develop species distribution models (SDMs) that correctly describe and predict preferred species areas. However, accuracy is not always easy to achieve when physical barriers, such as islands, are present. Indeed, SDMs assume, if only implicitly, that the spatial effect is stationary, and that correlation is only depende…
Bayesian approach to urinary ESBL-producing Escherichia coli
2014
This is a retrospective study about the prevalence of ESBL-producing Escherichia coli (EEC) in urinary specimens from patients from the Comunitat Valenciana from January 2007 to December 2008. Data were retrieved from RedMIVA, and Bayesian generalized linear mixed models were considered to study the prevalence of EEC with regard to demographical and microbiological factors. The total number of infections considered was 164,502, the amount of urinary isolates was 70,827 belonging to 49,304 different patients, and 5,161 (7.3%) of the urinary isolates were EEC. Three out of four E. coli were isolated in women (76.8%), men showed higher rates of EEC (9.7% in men vs. 6.5% in women). EEC patients…
Particle identification in ALICE: a Bayesian approach
2016
We present a Bayesian approach to particle identification (PID) within the ALICE experiment. The aim is to more effectively combine the particle identification capabilities of its various detectors. After a brief explanation of the adopted methodology and formalism, the performance of the Bayesian PID approach for charged pions, kaons and protons in the central barrel of ALICE is studied. PID is performed via measurements of specific energy loss ($\mathrm{d}E/\mathrm{d}x$) and time-of-flight. PID efficiencies and misidentification probabilities are extracted and compared with Monte Carlo simulations using high-purity samples of identified particles in the decay channels ${\rm K}^0_S \righta…
Genetic structure and differentiation from early bronze age in the mediterranean island of sicily: Insights from ancient mitochondrial genomes
2022
Sicily is one of the main islands of the Mediterranean Sea, and it is characterized by a variety of archaeological records, material culture and traditions, reflecting the history of migrations and populations’ interaction since its first colonization, during the Paleolithic. These deep and complex demographic and cultural dynamics should have affected the genomic landscape of Sicily at different levels; however, the relative impact of these migrations on the genomic structure and differentiation within the island remains largely unknown. The available Sicilian modern genetic data gave a picture of the current genetic structure, but the paucity of ancient data did not allow so far to make p…
An Autonomic System for Estimating Human Presence through Bayesian Networks
2010
In the Ambient Intelligence (AmI) context, a relevant research topic is represented by the methods for determining users' presence in order to design context-aware systems capable of monitoring the environment in which they operate, and of timely reacting to changes. This work describes an autonomic software agent comprising a double-level reasoning. At the lower level, a Bayesian network merges the available sensory information related to the users' presence, whereas the upper level performs a meta-reasoning on the system performance and configuration in order to enable the system self-assessment. Experimental results show the validity of the proposed method on a sample scenario.
Multi-sensor Fusion through Adaptive Bayesian Networks
2011
Common sensory devices for measuring environmental data are typically heterogeneous, and present strict energy constraints; moreover, they are likely affected by noise, and their behavior may vary across time. Bayesian Networks constitute a suitable tool for pre-processing such data before performing more refined artificial reasoning; the approach proposed here aims at obtaining the best trade-off between performance and cost, by adapting the operating mode of the underlying sensory devices. Moreover, self-configuration of the nodes providing the evidence to the Bayesian network is carried out by means of an on-line multi-objective optimization.
An innovative approach to manage uncertainties and stock diversity in the EPBD cost-optimal methodology
2018
The EU Energy Performance of Buildings Directive (EPBD) 2010/31/EU is a step in the right direction to promote near zero energy buildings (NZEB) in a step-wise manner, starting with minimum energy performance and cost optimal thresholds for “reference buildings” (RBs) for each category. Nevertheless, a standard method for defining RBs does not exist, which led to a great divergence between MS in the level of detail used to define RBs for the EPBD cost-optimal analysis. Such lack of harmonisation between MS is further evident given the resulting large discrepancies in energy performance indicators even between countries having similar climate. Furthermore, discrepancies of 30% or higher betw…