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Exogenous HA-SSTR2 gene expression can be quantified in a mouse model using functional and anatomic imaging [18 20].
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In the tumour model used, functional changes in physiological parameters appear to play a more important role in the adaptation to chronic hypoxia than hypoxia-induced alterations in VEGF expression and morphological changes of vasculature.
The purpose of this paper is to devise a method for the design of adaptive automaton models using functional decomposition.
The framework consists of (i) thermal modeling using 3D finite element analysis (FEA), (ii) surrogate modeling using functional Gaussian process, and (iii) Bayesian calibration based on the thermal imaging data.
In this paper, we report the validity of our models generated using functional feature hypotheses and topological descriptors.
A new thermodynamically consistent algorithm for the van der Waals model is designed, using functional entropy variables and a new temporal scheme employing a family of new quadrature rules.
Covariates were included in the model using different functional forms: linear, piecewise linear, power, and exponential functions.
Given the interdependence between WHO functional class and plasma BNP concentration, two models of bivariate analysis were analyzed: a model using WHO functional class and hyperbilirubinemia (both categorical data, Model 1) and a model using BNP and bilirubin concentration (both continuous data, Model 2).
For this reason, we estimate an econometric model using different functional specifications controlling for year of birth to isolate the LOGSE effect from the cohort effect.
*n = 26, † Bivariate model using WHO functional class and hyperbilirubinemia, ‡ Bivariate model using BNP and bilirubin concentration.
The functional effects of reduced UGTA1 enzymes expression were explored using functional models of prostate cancer.
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