Search results for "SIMULATION"
showing 10 items of 5095 documents
Antibacterial Activity of Flavonoids Against Methicillin-resistant Staphylococcus aureus strains
2000
An experimental and theoretical study was performed on the anti-staphylococcal activity of 18 natural and synthetic flavonoids against methicillin-resistant Staphylococcus aureus strains. The analysed flavonoids belong to three well-differentiated structural patterns: chalcones, flavanones and flavones. The quantitative analysis of the anti-staphylococcal activity of the compounds was carried out by determining their percent inhibition degree. The hierarchical cluster analysis method was used to analyse the anti-MRSA activity of the compounds. With this methodology, the flavonoids were classified into four groups according to their anti-staphylococcal activity (high, sufficient, intermediat…
The Induced Smoothed lasso: A practical framework for hypothesis testing in high dimensional regression.
2020
This paper focuses on hypothesis testing in lasso regression, when one is interested in judging statistical significance for the regression coefficients in the regression equation involving a lot of covariates. To get reliable p-values, we propose a new lasso-type estimator relying on the idea of induced smoothing which allows to obtain appropriate covariance matrix and Wald statistic relatively easily. Some simulation experiments reveal that our approach exhibits good performance when contrasted with the recent inferential tools in the lasso framework. Two real data analyses are presented to illustrate the proposed framework in practice.
Design-based estimation for geometric quantiles with application to outlier detection
2010
Geometric quantiles are investigated using data collected from a complex survey. Geometric quantiles are an extension of univariate quantiles in a multivariate set-up that uses the geometry of multivariate data clouds. A very important application of geometric quantiles is the detection of outliers in multivariate data by means of quantile contours. A design-based estimator of geometric quantiles is constructed and used to compute quantile contours in order to detect outliers in both multivariate data and survey sampling set-ups. An algorithm for computing geometric quantile estimates is also developed. Under broad assumptions, the asymptotic variance of the quantile estimator is derived an…
Nonlinear parametric quantile models
2020
Quantile regression is widely used to estimate conditional quantiles of an outcome variable of interest given covariates. This method can estimate one quantile at a time without imposing any constraints on the quantile process other than the linear combination of covariates and parameters specified by the regression model. While this is a flexible modeling tool, it generally yields erratic estimates of conditional quantiles and regression coefficients. Recently, parametric models for the regression coefficients have been proposed that can help balance bias and sampling variability. So far, however, only models that are linear in the parameters and covariates have been explored. This paper …
A hypothetical model of the influence of inorganic phosphate on the kinetics of pyruvate kinase
2000
This paper presents a simple solution to the problem of approximating the calculated curve of reaction progress to the measured curve which is usually disturbed by initial oscillation of auxiliary lactate dehydrogenase (LDH) reaction. The experiments leading to the determination of the apparent Km for phosphoenolpyruvate (PEP) and Vm were performed. For precise estimation of kinetic parameters (Km and Vm) of the M1 isozyme of pyruvate kinase (PK), measured by coupling it to LDH reaction, the sequence of Michaelis‐Menten for pyruvate kinase and second-order kinetics for lactate dehydrogenase reaction as well as a non-zero initial concentration of lactate was assumed. The functions of apparen…
On the stability and ergodicity of adaptive scaling Metropolis algorithms
2011
The stability and ergodicity properties of two adaptive random walk Metropolis algorithms are considered. The both algorithms adjust the scaling of the proposal distribution continuously based on the observed acceptance probability. Unlike the previously proposed forms of the algorithms, the adapted scaling parameter is not constrained within a predefined compact interval. The first algorithm is based on scale adaptation only, while the second one incorporates also covariance adaptation. A strong law of large numbers is shown to hold assuming that the target density is smooth enough and has either compact support or super-exponentially decaying tails.
Spatial moving average risk smoothing
2013
This paper introduces spatial moving average risk smoothing (SMARS) as a new way of carrying out disease mapping. This proposal applies the moving average ideas of time series theory to the spatial domain, making use of a spatial moving average process of unknown order to define dependence on the risk of a disease occurring. Correlation of the risks for different locations will be a function of m values (m being unknown), providing a rich class of correlation functions that may be reproduced by SMARS. Moreover, the distance (in terms of neighborhoods) that should be covered for two units to be found to make the correlation of their risks 0 is a quantity to be fitted by the model. This way, …
Misinterpretation risks of global stochastic optimisation of kinetic models revealed by multiple optimisation runs
2016
Abstract One of use cases for metabolic network optimisation of biotechnologically applied microorganisms is the in silico design of new strains with an improved distribution of metabolic fluxes. Global stochastic optimisation methods (genetic algorithms, evolutionary programing, particle swarm and others) can optimise complicated nonlinear kinetic models and are friendly for unexperienced user: they can return optimisation results with default method settings (population size, number of generations and others) and without adaptation of the model. Drawbacks of these methods (stochastic behaviour, undefined duration of optimisation, possible stagnation and no guaranty of reaching optima) cau…
A many-body approach to transport in quantum systems : From the transient regime to the stationary state
2022
We review one of the most versatile theoretical approaches to the study of time-dependent correlated quantum transport in nano-systems: the non-equilibrium Green's function (NEGF) formalism. Within this formalism, one can treat, on the same footing, inter-particle interactions, external drives and/or perturbations, and coupling to baths with a (piece-wise) continuum set of degrees of freedom. After a historical overview on the theory of transport in quantum systems, we present a modern introduction of the NEGF approach to quantum transport. We discuss the inclusion of inter-particle interactions using diagrammatic techniques, and the use of the so-called embedding and inbedding techniques w…
Basic networks: Definition and applications
2009
7 pages, 4 figures, 1 table.-- PMID: 19490867 [PubMed]