Search results for " Models"
showing 10 items of 4240 documents
Sparse Distributed Representation of Odors in a Large-scale Olfactory Bulb Circuit
2013
In the olfactory bulb, lateral inhibition mediated by granule cells has been suggested to modulate the timing of mitral cell firing, thereby shaping the representation of input odorants. Current experimental techniques, however, do not enable a clear study of how the mitral-granule cell network sculpts odor inputs to represent odor information spatially and temporally. To address this critical step in the neural basis of odor recognition, we built a biophysical network model of mitral and granule cells, corresponding to 1/100th of the real system in the rat, and used direct experimental imaging data of glomeruli activated by various odors. The model allows the systematic investigation and g…
Comprehending city and its production in Africa through a systemic approach : example of the city of Diamniadio, Dakar
2022
For a long time, the analysis of the production of the city in Africa was based on an exogenous perception according to urban models theorized and experimented with in the Occidental countries, then diffused and applied through different mechanisms in the South, bearing witness to historical relations - through the making of the colonial city - and present relations - in the context of the making of new towns. After independence, researchers looked at the redefinition of the city in Africa with its complexity and plurality according to geographical and historical trajectories, proposing new urban theories that were more nuanced and linked to local and contextual realities. Therefore, follow…
Stochastic models for wind speed forecasting
2011
Abstract This paper is concerned with the problem of developing a general class of stochastic models for hourly average wind speed time series. The proposed approach has been applied to the time series recorded during 4 years in two sites of Sicily, a region of Italy, and it has attained valuable results in terms both of modelling and forecasting. Moreover, the 24 h predictions obtained employing only 1-month time series are quite similar to those provided by a feed-forward artificial neural network trained on 2 years data.
FROM DISCRETE KINETIC AND STOCHASTIC GAME THEORY TO MODELLING COMPLEX SYSTEMS IN APPLIED SCIENCES
2004
This paper deals with some methodological aspects related to the discretization of a class of integro-differential equations modelling the evolution of the probability distribution over the microscopic state of a large system of interacting individuals. The microscopic state includes both mechanical and socio-biological variables. The discretization of the microscopic state generates a class of dynamical systems defining the evolution of the densities of the discretized state. In general, this yields a system of partial differential equations replacing the continuous integro-differential equation. As an example, a specific application is discussed, which refers to modelling in the field of…
A Coherent derivation of an average ion model including the evolution of correlations between different shells
2013
We propose in this short note a method enabling to write in a systematic way a set of refined equations for average ion models in which correlations between populations are taken into account, starting from a microscopic model for the evolution of the electronic configura- tion probabilities. Numerical simulations illustrating the improvements with respect to standard average ion models are presented at the end of the paper.
Evaluation of enantioselective binding of propanocaine to human serum albumin by ultrafiltration and electrokinetic chromatography under intermediate…
2011
Abstract Stereoselectivity in protein binding can have a significant effect on the pharmacokinetic and pharmacodynamic properties of chiral drugs. In this paper, the enantioselective binding of propanocaine (PRO) enantiomers to human serum albumin (HSA), the most relevant plasmatic protein in view of stereoselectivity, has been evaluated by incubation and ultrafiltration of racemic PRO–HSA mixtures and chiral analysis of the bound and unbound fractions by electrokinetic chromatography using HSA as chiral selector. Experimental conditions for the separation of PRO enantiomers using HSA as chiral selector and electrokinetic chromatography have been optimised. Affinity constants and protein bi…
Factors influencing inclusion in digestive cancer clinical trials: A population-based study
2015
Inclusion in a randomized therapeutic trial represents an optimal therapeutic strategy.To determine the influence of demographic characteristics and deprivation on the enrolment of patients in digestive cancer clinical trials.Between 2004 and 2010, 4632 patients were recorded by the Burgundy Digestive Cancer Registry. According to a balancing score, the 136 patients included in a clinical trial were matched with 272 patients who met the eligibility criteria for trials. Deprivation was measured by the ecological European deprivation index. A conditional multivariate logistic regression was performed.Patients aged over 75 years were significantly less likely to be included in clinical trials …
Adaptive trial design: a general methodology for censored time to event data.
2008
Adaptive designs allow a clinical trial design to be changed according to interim findings without inflating type I error. The Inverse Normal method can be considered as an adaptive generalization of classical group sequential designs. The use of the Inverse Normal method for censored survival data was demonstrated only for the logrank statistic. However, the logrank statistic is inefficient in the presence of nuisance covariates affecting survival. We demonstrate, how the Inverse Normal method can be applied to Cox regression analysis. The required independence between test statistics of the different stages of the trial can be obtained by two different approaches. One is using the indepen…
An Extension of the DgLARS Method to High-Dimensional Relative Risk Regression Models
2020
In recent years, clinical studies, where patients are routinely screened for many genomic features, are becoming more common. The general aim of such studies is to find genomic signatures useful for treatment decisions and the development of new treatments. However, genomic data are typically noisy and high dimensional, not rarely outstripping the number of patients included in the study. For this reason, sparse estimators are usually used in the study of high-dimensional survival data. In this paper, we propose an extension of the differential geometric least angle regression method to high-dimensional relative risk regression models.
Salinity effects on asexual reproduction of Carybdea sp. (Cnidaria: Cubozoa)
2014
6 pages, 2 figures, 1 table, supplementary data http://plankt.oxfordjournals.org/content/36/2/585/suppl/DC1