Results 91 to 100 of about 10,870,567 (191)

Functional Brain Response to Emotional Muical Stimuli in Depression, Using INLA Approach for Approximate Bayesian Inference

open access: yesBasic and Clinical Neuroscience, 2021
Introduction: One of the vital skills which has an impact on emotional health and well-being is the regulation of emotions. In recent years, the neural basis of this process has been considered widely.
Parisa Naseri   +5 more
doaj  

A new perspective on Listeria monocytogenes evolution.

open access: yesPLoS Pathogens, 2008
Listeria monocytogenes is a model organism for cellular microbiology and host-pathogen interaction studies and an important food-borne pathogen widespread in the environment, thus representing an attractive model to study the evolution of virulence.
Marie Ragon   +6 more
doaj   +1 more source

Respective ability of InlA and InlAm to promote bacterial entry into hEcad- and mEcad-expressing cells. [PDF]

open access: yes, 2013
Bacterial entry into hEcad-expressing human epithelial cells (LoVo) (A for Lm and B for Li) and mEcad-expressing mouse epithelial cells (Nme) (C for Lm and D for Li) was performed by counting intracellular gentamicin resistant bacteria following 1 hr of ...
Olivier Disson (7017)   +3 more
core   +1 more source

Dynamic spatiotemporal modeling of the infected rate of visceral leishmaniasis in human in an endemic area of Amhara regional state, Ethiopia.

open access: yesPLoS ONE, 2019
Visceral Leishmaniasis is a very dangerous form of leishmaniasis and, shorn of appropriate diagnosis and handling, it leads to death and physical disability.
Anteneh Asmare Godana   +2 more
doaj   +1 more source

US county-level food insecurity and COVID-19 mortality: a Bayesian spatial analysis with R-INLA

open access: yesAmerican Journal of Epidemiology
Abstract The objective of our study was to evaluate the relationship between county-level food insecurity (FI) and the risk of Coronavirus-2019 (COVID-19) mortality in the United States during the early pandemic (March 25, 2020-December 25, 2021), while accounting for geographic contributions to that risk.
Christian A Maino Vieytes   +6 more
openaire   +2 more sources

Bayesian Computing with INLA: A Review [PDF]

open access: yes, 2016
The key operation in Bayesian inference is to compute high-dimensional integrals. An old approximate technique is the Laplace method or approximation, which dates back to Pierre-Simon Laplace (1774).
Simpson, Daniel P.   +11 more
core   +1 more source

InlAm mediates mouse Ncad-dependent internalization. [PDF]

open access: yes, 2013
(A) Mouse CT26 cells were transfected with scrambled siRNAs or mNcad-specific siRNAs. Bacteria internalization was evaluated by counting intracellular gentamicin resistant bacteria. Values are expressed as a mean + SD (n = 3).
Olivier Disson (7017)   +3 more
core   +1 more source

Desempeño predictivo de R-INLA SPDE para el Mapeo Digital de Suelos

open access: yes, 2021
El mapeo digital de suelos (MDS) permite describir la variabilidad espacial de una propiedad edáfica a treves de modelos de predicción espacial que explican la relación que existe entre la variable de interés y covariables sitio-especificas. Entre los modelos estadísticos más incipientes en aplicaciones de MDS está la regresión bayesiana ajustada con ...
Giannini Kurina, Franca   +4 more
openaire   +1 more source

Predicting spatio-temporal dynamics of dengue using INLA (integrated nested laplace approximation) in Yogyakarta, Indonesia

open access: yesBMC Public Health
Introduction Dengue is a mosquito-borne disease caused by the dengue virus, primarily transmitted by Aedes aegypti and Aedes albopictus. Its incidence fluctuates due to spatial and temporal factors, necessitating robust modeling approaches for prediction
Marko Ferdian Salim   +2 more
doaj   +1 more source

sdmTMB: An R Package for Fast, Flexible, and User-Friendly Generalized Linear Mixed Effects Models with Spatial and Spatiotemporal Random Fields

open access: yesJournal of Statistical Software
Geostatistical spatial or spatiotemporal data are common across scientific fields. However, appropriate models to analyze these data, such as generalized linear mixed effects models (GLMMs) with Gaussian Markov random fields (GMRFs), are computationally ...
Sean C. Anderson   +4 more
doaj   +1 more source

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