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Optimização de estratégias de alimentação para identificação de parâmetros de um modelo de E. coli. utilização do modelo em monitorização e controlo

Veloso, Ana C.A.
Fonte: Universidade do Minho Publicador: Universidade do Minho
Tipo: Tese de Doutorado
POR
Relevância na Pesquisa
56%
Os principais objectivos desta tese são: o desenho óptimo de experiências para a identificação de coeficientes de rendimento de um modelo não estruturado de um processo de fermentação semicontínua de Escherichia coli; a verificação experimental das trajectórias de alimentação obtidas por simulação; o desenvolvimento de estratégias de monitorização avançada para a estimação em linha de variáveis de estado e parâmetros cinéticos; e por fim o desenvolvimento de uma lei de controlo adaptativo para controlar a taxa específica de crescimento, com base em estratégias de alimentação de substrato com vista à maximização do crescimento e/ou produção. São apresentadas metodologias para o desenho óptimo de experiências, que visam a optimização da riqueza informativa das mesmas, quantificada por índices relativos à Matriz de Informação de Fisher. Embora, o modelo utilizado para descrever a fermentação semi-contínua de E. coli não esteja ainda optimizado em termos cinéticos e de algumas dificuldades encontradas na implementação prática dos resultados obtidos por simulação para o desenho óptimo de experiências, a qualidade da estimativa dos parâmetros, especialmente os do regime respirativo...

Aplicação de projeto experimental ótimo à reação de interesterificação de estearina de palma com óleo de linhaça.; Optimum experimental design application to interesterification reaction of stearin palm with linseed oil.

Angelo, Juliana Francisco de
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 28/06/2007 PT
Relevância na Pesquisa
56.03%
A rapidez da passagem do estágio da bancada para a produção industrial, a rentabilidade econômica do projeto e o custo de investimento da implantação do projeto proposto são medidas da eficiência no desenvolvimento de processos químicos. Com o projeto de experimentos obtém-se uma redução de custo na etapa da experimentação, pela redução no número de experimentos, além de permitir um projeto de um produto com custo e qualidade otimizados. Neste trabalho, o projeto experimental ótimo é aplicado a dados experimentais da reação de interesterificação química da estearina de palma com óleo de linhaça. A gordura obtida pela reação de interesterificação é uma gordura isenta de gorduras trans e possui características nutricionais interessantes devido ao óleo de linhaça, que é a maior fonte do ácido graxo alfa-linolênico, um ácido graxo da família ômega-3. Os dados experimentais são utilizados para desenvolver modelos matemáticos aos quais é aplicada a otimização. Com isto, são previstos pontos ótimos, que são testados. Novos experimentos são realizados na vizinhança dos pontos ótimos. São aplicados os critérios de projeto experimental ótimo D-ótimo e G-ótimo para propor novas condições para a realização de experimentos. Uma vez obtidos estes pontos eles são adicionados aos modelos iniciais para a obtenção de novos parâmetros e é aplicada uma nova etapa de otimização. Nesta metodologia...

Identification of yield coefficients in an E. coli model : an optimal experimental design using genetic algorithms

Veloso, Ana C. A.; Rocha, I.; Ferreira, E. C.
Fonte: Pergamon Publicador: Pergamon
Tipo: Conferência ou Objeto de Conferência
Publicado em //2005 ENG
Relevância na Pesquisa
65.77%
An optimal experimental design for yield coefficients estimation in an unstructured growth model of fed-batch fermentation of E. coli is presented. The feed profile is designed by optimisation of a scalar function based on the Fischer Information Matrix. A genetic algorithm is proposed as the optimisation method due to its efficiency and independence on the initial values.; Programa de Desenvolvimento Educativo para Portugal (PRODEP).; Fundação para a Ciência e a Tecnologia (FCT) – PRAXISXXI/BD/16961/98.

Optimização de estratégias de alimentação para identificação de parâmetros de um modelo de E. coli. utilização do modelo em monitorização e controlo

Veloso, Ana C. A.
Fonte: Universidade do Minho Publicador: Universidade do Minho
Tipo: Tese de Doutorado
Publicado em 12/02/2007 POR
Relevância na Pesquisa
56%
Doutoramento em Engenharia Química e Biológica; Os principais objectivos desta tese são: o desenho óptimo de experiências para a identificação de coeficientes de rendimento de um modelo não estruturado de um processo de fermentação semicontínua de Escherichia coli; a verificação experimental das trajectórias de alimentação obtidas por simulação; o desenvolvimento de estratégias de monitorização avançada para a estimação em linha de variáveis de estado e parâmetros cinéticos; e por fim o desenvolvimento de uma lei de controlo adaptativo para controlar a taxa específica de crescimento, com base em estratégias de alimentação de substrato com vista à maximização do crescimento e/ou produção. São apresentadas metodologias para o desenho óptimo de experiências, que visam a optimização da riqueza informativa das mesmas, quantificada por índices relativos à Matriz de Informação de Fisher. Embora, o modelo utilizado para descrever a fermentação semi-contínua de E. coli não esteja ainda optimizado em termos cinéticos e de algumas dificuldades encontradas na implementação prática dos resultados obtidos por simulação para o desenho óptimo de experiências, a qualidade da estimativa dos parâmetros...

Optimal experimental design for estimating the kinetic parameters of the Bigelow model

Cunha, Luís M.; Oliveira, Fernanda A. R.; Brandão, Teresa R.S.; Oliveira, Jorge C.
Fonte: Elsevier Publicador: Elsevier
Tipo: Artigo de Revista Científica
Publicado em //1997 ENG
Relevância na Pesquisa
65.84%
The optimum experimental design for systems following the Bigelow model was studied by determining the sampling conditions that lead to a minimum confidence region for a number of observations equal to the number of parameters. For isothermal conditions, it was found that this corresponds to the sampling times when the fractional concentration of the decaying factor (ηi) is equal to e−1 and that the experiments should be performed in the limit range of temperatures chosen. These results are identical to those described in the literature for a first-order Arrhenius model. For non-isothermal experiments with linearly increasing temperature, the optimal experimental design is obtained with a maximum heating rate, a minimum initial temperature and sampling times when the product of the fractional concentrations is e−2 (with η1 congruent with 0.70 and η2 congruent with 0.19). The influence of the heating rate on the precision of the estimates is more significant for high z values and the influence of the initial temperature is more significant for low values of the heating rate.

Optimal Experimental Design for Model Discrimination

Myung, Jay I.; Pitt, Mark A.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em /07/2009 EN
Relevância na Pesquisa
65.92%
Models of a psychological process can be difficult to discriminate experimentally because it is not easy to determine the values of the critical design variables (e.g., presentation schedule, stimulus structure) that will be most informative in differentiating them. Recent developments in sampling-based search methods in statistics make it possible to determine these values, and thereby identify an optimal experimental design. After describing the method, it is demonstrated in two content areas in cognitive psychology in which models are highly competitive: retention (i.e., forgetting) and categorization. The optimal design is compared with the quality of designs used in the literature. The findings demonstrate that design optimization has the potential to increase the informativeness of the experimental method.

Development of a multidose formulation for a humanized monoclonal antibody using experimental design techniques

Gupta, Supriya; Kaisheva, Elizabet
Fonte: Springer-Verlag Publicador: Springer-Verlag
Tipo: Artigo de Revista Científica
Publicado em 04/04/2003 EN
Relevância na Pesquisa
55.98%
The purpose of this study was to identify optimal preservatives for a multidose formulation of a humanized monoclonal antibody using experimental design techniques. The effect of antimicrobial parenteral preservatives (benzyl alcohol, chlorobutanol, methyl paraben, propylparaben, phenol, and m-cresol) on protein stability was assessed using size-exclusion chromatography, differential scanning calorimetry, right-angle light scattering, UV spectroscopy, and potency testing using a cell-based fluorescence-activated cell sorting method. A quick, cost-effective preservative screening test was designed. Combinations of preservatives were examined using an I-optimal experimental design. The protein was most stable in the presence of methylparaben and propylparaben, and was compatible with benzyl alcohol and chlorobutanol at low concentrations. Phenol and m-cresol were not compatible with the protein. The I-optimal experimental design indicated that as an individual preservative, benzyl alcohol was promising. The model also indicated several effective combinations of preservatives that satisfied the antimicrobial efficacy and physical stability constraints. The preservative screening test and the experimental design approach were effective in identifying optimal concentrations of antimicrobial preservatives for a multidose protein formulation; (1) benzyl alcohol...

Optimal Experimental Design for Parameter Estimation of a Cell Signaling Model

Bandara, Samuel; Schlöder, Johannes P.; Eils, Roland; Bock, Hans Georg; Meyer, Tobias
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
65.9%
Differential equation models that describe the dynamic changes of biochemical signaling states are important tools to understand cellular behavior. An essential task in building such representations is to infer the affinities, rate constants, and other parameters of a model from actual measurement data. However, intuitive measurement protocols often fail to generate data that restrict the range of possible parameter values. Here we utilized a numerical method to iteratively design optimal live-cell fluorescence microscopy experiments in order to reveal pharmacological and kinetic parameters of a phosphatidylinositol 3,4,5-trisphosphate (PIP3) second messenger signaling process that is deregulated in many tumors. The experimental approach included the activation of endogenous phosphoinositide 3-kinase (PI3K) by chemically induced recruitment of a regulatory peptide, reversible inhibition of PI3K using a kinase inhibitor, and monitoring of the PI3K-mediated production of PIP3 lipids using the pleckstrin homology (PH) domain of Akt. We found that an intuitively planned and established experimental protocol did not yield data from which relevant parameters could be inferred. Starting from a set of poorly defined model parameters derived from the intuitively planned experiment...

Optimal Experimental Design Strategies for Detecting Hormesis

Dette, Holger; Pepelyshev, Andrey; Wong, Weng Kee
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
65.94%
Hormesis is a widely observed phenomenon in many branches of life sciences ranging from toxicology studies to agronomy with obvious public health and risk assessment implications. We address optimal experimental design strategies for determining the presence of hormesis in a controlled environment using the recently proposed Hunt-Bowman model. We propose alternative models that have an implicit hormetic threshold, discuss their advantages over current models, construct and study properties of optimal designs for (i) estimating model parameters, (ii) estimating the threshold dose, and (iii) testing for the presence of hormesis. We also determine maximin optimal designs that maximize the minimum of the design efficiencies when we have multiple design criteria or there is model uncertainty where we have a few plausible models of interest. We apply these optimal design strategies to a teratology study and show that the proposed designs outperform the implemented design by a wide margin for many situations.

Optimal experimental design applied to DC resistivity problems

Coles, Darrell Ardon, 1971-
Fonte: Massachusetts Institute of Technology Publicador: Massachusetts Institute of Technology
Tipo: Tese de Doutorado Formato: 323 p.
ENG
Relevância na Pesquisa
65.9%
The systematic design of experiments to optimally query physical systems through manipulation of the data acquisition strategy is termed optimal experimental design (OED). This dissertation introduces the state-of-the-art in OED theory and presents a new design methodology, which is demonstrated by application to DC resistivity problems. The primary goal is to minimize inversion model errors and uncertainties, where the inversion is approached via nonlinear least squares with L1 smoothness constraints. An equally important goal is to find ways to expedite experimental design to make it practical for a wider variety of surveying situations than is currently possible.A fast, sequential ED strategy is introduced that designs surveys accumulatively by an efficient method that maximizes the determinant of the Jacobian matrix. An analysis of electrode geometries for multielectrode data acquisition systems reveals that experiment-space can be usefully decimated by using special subsets of observations, reducing design CPU times. Several techniques for decimating model-space are also considered that reduce design times.A law of diminishing returns is observed; compact, information-dense designed surveys produce smaller model errors than comparably sized random and standard surveys...

Reconsidering optimal experimental design for conjoint analysis

Esteban-Bravo, Mercedes; Leszkiewicz, Agata; Vidal-Sanz, Jose M.
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: info:eu-repo/semantics/draft; info:eu-repo/semantics/workingPaper Formato: application/pdf; text/plain
Publicado em /11/2012 ENG
Relevância na Pesquisa
65.91%
The quality of Conjoint Analysis estimations heavily depends on the alternatives presented in the experiment. An efficient selection of the experiment design matrix allows more information to be elicited about consumer preferences from a small number of questions, thus reducing experimental cost and respondent's fatigue. The statistical literature considers optimal design algorithms (Kiefer, 1959), and typically selects the same combination of stimuli more than once. However in the context of conjoint analysis, replications do not make sense for individual respondents. In this paper we present a general approach to compute optimal designs for conjoint experiments in a variety of scenarios and methodologies: continuous, discrete and mixed attributes types, customer panels with random effects, and quantile regression models. We do not compute good designs, but the best ones according to the size (determinant or trace) of the information matrix of the associated estimators without repeating profiles as in Kiefer's methodology. We handle efficient optimization algorithms to achieve our goal, avoiding the use of widespread ad-hoc intuitive rules.; Research funded by two research projects, S-0505/TIC-0230 by the Comunidad de Madrid and ECO2011-30198 by MICINN agency of Spanish Government

A study on the accuracy and precision of external mass transfer and diffusion coefficients jointly estimated from pseudo-experimental simulated data

Abreu, Isabel; Oliveira, F. A. R.; Drumond, M. C.
Fonte: Elsevier Publicador: Elsevier
Tipo: Artigo de Revista Científica
Publicado em //1998 ENG
Relevância na Pesquisa
65.97%
Optimal experimental designs for maximum precision in the estimation of diffusivities (D) and mass transfer coefficients (Kc) for solute transport from/to a solid immersed in a fluid were determined. Diffusion in the solid was considered to take place according to Fick's second law. It was found that the optimal design was dependent on the Biot number. In the range of Biot numbers tested (0.1±200), the first sampling time corresponded to values of fractional loss/uptake between 0.10 and 0.32, and the second sampling time corresponded to values of fractional loss/uptake between 0.67 and 0.82. Pseudo-experimental data were simulated by applying randomly generated sets of errors, taken from a normal distribution with 5% standard deviation, to data calculated using given values of the model parameters. Both optimal and heuristic designs (for which the sampling times corresponded to values of fractional loss/uptake from 0.30 to 0.95) were analyzed. The accuracy and precision of the estimates obtained by non-linear regression were compared. It was confirmed that optimal designs yield best results in terms of precision, although it was concluded that the joint estimation of D and Kc should, in general, be avoided. For intermediate values of the Biot number...

Identification yield coefficients in a baker’s yeast model : an optimal experimental design approach

Rocha, Cristina M. R.; Ferreira, E. C.
Fonte: Universidade do Minho Publicador: Universidade do Minho
Tipo: Conferência ou Objeto de Conferência
Publicado em //1996 ENG
Relevância na Pesquisa
65.78%
The main objective of this work is to elaborate methodologies that allow the identification of yield coefficients through complete measurements of the state. Experimental design strategies are proposed in order to optimize the richness of data coming out from the experiments, quantified by indexes related to the Fisher information matrix. The objectives of the experimental planning have been addressed in terms of the programming of input trajectories. The experimental planning is envisaged for baker’s yeast aiming at the computation of the substrate feed trajectories.

A study on the accuracy and precision of external mass transfer and diffusion coefficients jointly estimated from pseudo-experimental simulated data

Azevedo, I.C.A.; Oliveira, F.A.R.; Drumond, M.C.
Fonte: Elsevier Publicador: Elsevier
Tipo: Artigo de Revista Científica
Publicado em //2000 ENG
Relevância na Pesquisa
65.97%
Optimal experimental designs for maximum precision in the estimation of diffusivities (D) and mass transfer coefficients (Kc) for solute transport from/to a solid immersed in a fluid were determined. Diffusion in the solid was considered to take place according to Fick's second law. It was found that the optimal design was dependent on the Biot number. In the range of Biot numbers tested (0.1±200), the first sampling time corresponded to values of fractional loss/uptake between 0.10 and 0.32, and the second sampling time corresponded to values of fractional loss/uptake between 0.67 and 0.82. Pseudo-experimental data were simulated by applying randomly generated sets of errors, taken from a normal distribution with 5% standard deviation, to data calculated using given values of the model parameters. Both optimal and heuristic designs (for which the sampling times corresponded to values of fractional loss/uptake from 0.30 to 0.95) were analyzed. The accuracy and precision of the estimates obtained by non-linear regression were compared. It was confirmed that optimal designs yield best results in terms of precision, although it was concluded that the joint estimation of D and Kc should, in general, be avoided. For intermediate values of the Biot number...

Optimal experimental design in an EGFR signaling and down-regulation model

Casey, Fergal P.; Baird, Dan; Feng, Qiyu; Gutenkunst, Ryan N.; Waterfall, Joshua J.; Myers, Christopher R.; Brown, Kevin S.; Cerione, Richard A.; Sethna, James P.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 12/10/2006
Relevância na Pesquisa
65.9%
We apply the methods of optimal experimental design to a differential equation model for epidermal growth factor receptor (EGFR) signaling, trafficking, and down-regulation. The model incorporates the role of a recently discovered protein complex made up of the E3 ubiquitin ligase, Cbl, the guanine exchange factor (GEF), Cool-1 (Beta-Pix), and the Rho family G protein Cdc42. The complex has been suggested to be important in disrupting receptor down-regulation. We demonstrate that the model interactions can accurately reproduce the experimental observations, that they can be used to make predictions with accompanying uncertainties, and that we can apply ideas of optimal experimental design to suggest new experiments that reduce the uncertainty on unmeasurable components of the system.; Comment: 13 pages, 9 figures in main text. 7 pages, 7 figures in supplementary material. Submitted to IEE Proceedings Systems Biology

Optimal experimental design and some related control problems

Pronzato, Luc
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 29/02/2008
Relevância na Pesquisa
65.92%
This paper traces the strong relations between experimental design and control, such as the use of optimal inputs to obtain precise parameter estimation in dynamical systems and the introduction of suitably designed perturbations in adaptive control. The mathematical background of optimal experimental design is briefly presented, and the role of experimental design in the asymptotic properties of estimators is emphasized. Although most of the paper concerns parametric models, some results are also presented for statistical learning and prediction with nonparametric models.; Comment: Available at http://www.elsevier.com/locate/automatica

A First-Order Algorithm for the A-Optimal Experimental Design Problem: A Mathematical Programming Approach

Ahipasaoglu, Selin Damla
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 10/11/2013
Relevância na Pesquisa
65.85%
We develop and analyse a first-order algorithm for the A-optimal experimental design problem. The problem is first presented as a special case of a parametric family of optimal design problems for which duality results and optimality conditions are given. Then, two first-order (Frank-Wolfe type) algorithms are presented, accompanied by a detailed time-complexity analysis of the algorithms and computational results on various sized problems.

Approximate D-optimal Experimental Design with Simultaneous Size and Cost Constraints

Harman, Radoslav; Benková, Eva
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 12/08/2014
Relevância na Pesquisa
65.9%
Consider an experiment with a finite set of design points representing permissible trial conditions. Suppose that each trial is associated with a cost that depends on the selected design point. In this paper, we study the problem of constructing an approximate D-optimal experimental design with simultaneous restrictions on the size and on the total cost. For the problem of size-and-cost constrained D-optimality, we formulate an equivalence theorem and rules for the removal of redundant design points. We also propose a simple monotonically convergent "barycentric" algorithm that allows us to numerically compute a size-and-cost constrained approximate D-optimal design.

An optimal experimental design perspective on redial basis function regression

Fokoue, Ernest; Goel, Prem
Fonte: Rochester Instituto de Tecnologia Publicador: Rochester Instituto de Tecnologia
Tipo: Tese de Doutorado
EN_US
Relevância na Pesquisa
65.95%
This paper provides a new look at radial basis function regression that reveals striking similarities with the traditional optimal experimental design framework. We show theoreti- cally and computationally that the so-called relevant vectors derived through the relevance vector machine (RVM) and corresponding to the centers of the radial basis function net- work, are very similar and often identical to the support points obtained through various optimal experimental design criteria like D-optimality. This allows us to provide a sta- tistical meaning to the relevant centers in the context of radial basis function regression, but also opens the door to a variety of ways of approach optimal experimental design in multivariate settings.

On the advancement of optimal experimental design with applications to infectious diseases.

Price, David James
Fonte: Universidade de Adelaide Publicador: Universidade de Adelaide
Tipo: Tese de Doutorado
Publicado em //2015
Relevância na Pesquisa
96.15%
In this thesis, we investigate the optimal experimental design of some common biological experiments. The theory of optimal experimental design is a statistical tool that allows us to determine the optimal experimental protocol to gain the most information about a particular process, given constraints on resources. We focus on determining the optimal design for experiments where the underlying model is a Markov chain | a particularly useful stochastic model. Markov chains are commonly used to represent a range of biological systems, for example: the evolution and spread of populations and disease, competition between species, and evolutionary genetics. There has been little research into the optimal experimental design of systems where the underlying process is modelled as a Markov chain, which is surprising given their suitability for representing the random behaviour of many natural processes. While the first paper to consider the optimal experimental design of a system where the underlying process was modelled as a Markov chain was published in the mid 1980's, this research area has only recently started to receive significant attention. Current methods of evaluating the optimal experimental design within a Bayesian framework can be computationally inefficient...