ELLIPSE FITTING USING FINITE RATE OF INNOVATION PRINCIPLES

We address the problem of parameter estimation of an ellipse from a limited number of samples. We develop a new approach for solving the ellipse fitting problem by showing that the x and y coordinate functions of an ellipse are finite-rate-of-innovation (FRI) signals. Uniform samples of x and y coordinate functions of the ellipse are modeled as a sum of weighted complex exponentials, for which we propose an efficient annihilating filter technique to estimate the ellipse parameters from the samples. The FRI framework allows for estimating the ellipse parameters reliably from partial or incomplete measurements even in the presence of noise. The efficiency and robustness of the proposed method is compared with state-of-art direct method. The experimental results show that the estimated parameters have lesser bias compared with the direct method and the estimation error is reduced by 5-10 dB relative to the direct method.

A prior for steepness in stock-recruitment relationships, based on an evolutionary persistence principle

Priors are existing information or beliefs that are needed in Bayesian analysis. Informative priors are important in obtaining the Bayesian posterior distributions for estimated parameters in stock assessment. In the case of the steepness parameter (h), the need for an informative prior is particularly important because it determines the stock-recruitment relationships in the model. However, specifications of the priors for the h parameter are often subjective. We used a simple population model to derive h priors based on life history considerations. The model was based on the evolutionary principle that persistence of any species, given its life history (i.e., natural mortality rate) and its exposure to recruitment variability, requires a minimum recruitment compensation that enables the species to rebound consistently from low critical abundances (Nc). Using the model, we derived the prior probability distributions of the h parameter for fish species that have a range of natural mortality, recruitment variabilities, and Nt values.

Parameterizing probabilities for estimating age-composition distributions for mixture models

When estimating parameters that constitute a discrete probability distribution {pj}, it is difficult to determine how constraints should be made to guarantee that the estimated parameters { pˆj} constitute a probability distribution (i.e., pˆj>0, Σ pˆj =1). For age distributions estimated from mixtures of length-at-age distributions, the EM (expectationmaximization) algorithm (Hasselblad, 1966; Hoenig and Heisey, 1987; Kimura and Chikuni, 1987), restricted least squares (Clark, 1981), and weak quasisolutions (Troynikov, 2004) have all been used. Each of these methods appears to guarantee that the estimated distribution will be a true probability distribution with all categories greater than or equal to zero and with individual probabilities that sum to one. In addition, all these methods appear to provide a theoretical basis for solutions that will be either maximum-likelihood estimates or at least convergent to a probability distribut

O comércio intra-industrial brasileiro de 1990 a 2013: mensuração, decomposição e os determinantes

Em uma relação de bilateral,o comérciointra-industrial (CII)acontece quando os dois países exportam e importam produtos pertencentes a uma mesma indústria. Conforme apontam diversas pesquisas relacionadas a esse assunto, o intercâmbio intra-indústriade produtos tem aumentado sua participação nas transações bilaterais. Não obstante, os resultados mensurados para o comércio entre o Brasil e o resto do mundo revelam a predominância do engajamento inter-industrial em detrimento do intra-industrial. Observando dados de comércio que abrangem todos os produtos catalogados com seis dígitos no Sistema Harmonizado, esta dissertação investiga o comércio intra-industrial brasileiro entre o período de 1990 a 2013 sob suas duas formas: o intercâmbio de bens diferenciados horizontalmente e verticalmente. Ademais, a pesquisa de mensuração do CII vertical se dedica a definição dos lados superior e inferior, a fim de verificar se o Brasil é exportador ou importador líquido de bens verticalmente diferenciados de qualidade relativamente superior. Dentre a amostra de 57 países, as relações bilaterais em que o índice de Grubel e Lloyd (GL) se mostrou mais expressivo foram Argentina, Estados Unidos, México, Alemanha, Suécia, Uruguai, França, Itália, Reino Unido e Colômbia. Com relação aos setores que mais contribuíram para o índice que mensura o shareintra-industrial do comércio, destacam-se os ramos produtores de materiais de transporte e máquinas e materiais elétricos, também merecendo menção o setor de produtos químicos.Utilizando técnicas econométricas usuais da abordagem de dados em painel, a investigação dos determinantes do CII nos leva à aceitação da hipótese que relaciona o CII à presença de economias de escala. Além disso, os parâmetros estimados revelam que a distância geográfica que separa o Brasil de seu parceiro comercial prejudica mais o comércio intra-industrial vis-à-vis o inter-industrial. O processo de integração desencadeado pelo MERCOSUL, por sua vez, mostrou efeito positivo sobre o comércio intra-industrialvertical.

Lymph Node Colonization Dynamics after Oral Salmonella Typhimurium Infection in Mice

An understanding of how pathogens colonize their hosts is crucial for the rational design of vaccines or therapy. While the molecular factors facilitating the invasion and systemic infection by pathogens are a central focus of research in microbiology, the population biological aspects of colonization are still poorly understood. Here, we investigated the early colonization dynamics of Salmonella enterica subspecies 1 serovar Typhimurium (S. Tm) in the streptomycin mouse model for diarrhea. We focused on the first step on the way to systemic infection - the colonization of the cecal lymph node (cLN) from the gut - and studied roles of inflammation, dendritic cells and innate immune effectors in the colonization process. To this end, we inoculated mice with mixtures of seven wild type isogenic tagged strains (WITS) of S. Tm. The experimental data were analyzed with a newly developed mathematical model describing the stochastic immigration, replication and clearance of bacteria in the cLN. We estimated that in the beginning of infection only 300 bacterial cells arrive in the cLN per day. We further found that inflammation decreases the net replication rate in the cLN by 23%. In ccr7-/- mice, in which dendritic cell movement is impaired, the bacterial migration rate was reduced 10-fold. In contrast, cybb-/- mice that cannot generate toxic reactive oxygen species displayed a 4-fold higher migration rate from gut to cLN than wild type mice. Thus, combining infections with mixed inocula of barcoded strains and mathematical analysis represents a powerful method for disentangling immigration into the cLN from replication in this compartment. The estimated parameters provide an important baseline to assess and predict the efficacy of interventions. © 2013 Kaiser et al.

Interactions between the bloom-forming dinoflagellates Prorocentrum donghaiense and Alexandrium tamarense in laboratory cultures

Interactions between Prorocentrum donghaiense and Alexandrium tamarens, two bloom-forming dinoflagellates, were investigated using bi-algal cultures. All R donghaiense died, but A. tamarense was hardly affected by the end of the experiment when the initial cell density was set at 1.0 X 10(4) cells mL(-1) for P. donghaiense and 0.28 x 10(4) cells mL(-1) for A. tamarense. However, significant growth suppression occurred in either species when the initial cell density of P donghaiense increased to I. 0 X 105 Cells mL(-1) in the bi-algal culture, but no out-competement was observed. The simultaneous assay on the culture filtrates showed that P donghaiense filtrate prepared at a lower initial density (1.0 X 10(4) cells mL(-1)) stimulated growth of the co-cultured A. tanzarense (0.28 x 10(4) cells mL(-1)), but filtrate at a higher initial density (1.0 x 10(5) cells mL(-1)) depressed its growth. The filtrate of A. tamarense at a density of 0.28 x 10(4) cells mL(-1) killed all R donghaiense at a lower density (1.0 x 10(4) cells mL(-1)), but only exhibited an inhibitory effect on it at a higher density (1.0 x 10(5) cells mL(-1)). It is likely that these two species of microalgae interfere with each other mainly by releasing allelochemical substance(s) into the culture medium, and a direct cell-to-cell contact was not necessary for their mutual interaction. The allelopathic test further proved that A. tamarense could affect the growth of co-cultured P. donghaiense by producing allelochemical(s); moreover, A. tamarense culture filtrate at the stationary growth phase (SP) had a strongly inhibitory effect on P donghaiense compared to that at the exponential phase (EP). Results also demonstrated a dose-dependent relationship between the microalgal initial cell density and the degree of the allelopathic effect. The growth of R donghaiense and A. tamarense in the bi-algal cultures was simulated using a mathematical model to quantify the interaction. The estimated parameters from the model showed that the inhibition exerted by A. tamarense on P. donghaiense was about 17 and 8 times stronger than the inhibition P. donghaiense exerted on A. tamarense, when the initial cell density was set at 1.0 X 10(4) and 1.0 X 10(5) cells mL(-1) for P donghaiense, respectively. and 0.28 x 10(4) cells mL(-1) for A. tamarense in the bi-algal cultures. A. tamarense seems to have a survival strategy that is superior to that of P. donghaiense in bi-algal cultures under controlled laboratory conditions. (c) 2006 Elsevier B.V. All rights reserved.

Optymalizacja metod analizy Főrsterowskiego rezonansowego przeniesienia energii (FRET) pojedynczych cząsteczek

Wydział Chemii: Zakład Chemii Fizycznej

Parameter Optimisation for Woodwind Single-Reed Models

Time-domain modelling of single-reed woodwind instruments usually involves a lumped model of the excitation mechanism. The parameters of this lumped model have to be estimated for use in numerical simulations. Several attempts have been made to estimate these parameters, including observations of the mechanics of isolated reeds, measurements under artificial or real playing conditions and estimations based on numerical simulations. In this study an optimisation routine is presented, that can estimate reed-model parameters, given the pressure and flow signals in the mouthpiece. The method is validated, tested on a series of numerically synthesised data. In order to incorporate the actions of the player in the parameter estimation process, the optimisation routine has to be applied to signals obtained under real playing conditions. The estimated parameters can then be used to resynthesise the pressure and flow signals in the mouthpiece. In the case of measured data, as opposed to numerically synthesised data, special care needs to be taken while modelling the bore of the instrument. In fact, a careful study of various experimental datasets revealed that for resynthesis to work, the bore termination impedance should be known very precisely from theory. An example is given, where the above requirement is satisfied, and the resynthesised signals closely match the original signals generated by the player.

The estimation and improvement of the selectivity in crustacean and fish trawls

Tese de dout., Ciências e Tecnologias das Pescas, Faculdade de Ciências do Mar e do Ambiente, Univ. do Algarve, 2003

Modeling reaction kinetics and mass transfer in ozonation in water solutions

This dissertation is based on four articles dealing with modeling of ozonation. The literature part of this considers some models for hydrodynamics in bubble column simulation. A literature review of methods for obtaining mass transfer coefficients is presented. The methods presented to obtain mass transfer are general models and can be applied to any gas-liquid system. Ozonation reaction models and methods for obtaining stoichiometric coefficients and reaction rate coefficients for ozonation reactions are discussed in the final section of the literature part. In the first article, ozone gas-liquid mass transfer into water in a bubble column was investigated for different pH values. A more general method for estimation of mass transfer and Henry’s coefficient was developed from the Beltrán method. The ozone volumetric mass transfer coefficient and the Henry’s coefficient were determined simultaneously by parameter estimation using a nonlinear optimization method. A minor dependence of the Henry’s law constant on pH was detected at the pH range 4 - 9. In the second article, a new method using the axial dispersion model for estimation of ozone self-decomposition kinetics in a semi-batch bubble column reactor was developed. The reaction rate coefficients for literature equations of ozone decomposition and the gas phase dispersion coefficient were estimated and compared with the literature data. The reaction order in the pH range 7-10 with respect to ozone 1.12 and 0.51 the hydroxyl ion were obtained, which is in good agreement with literature. The model parameters were determined by parameter estimation using a nonlinear optimization method. Sensitivity analysis was conducted using object function method to obtain information about the reliability and identifiability of the estimated parameters. In the third article, the reaction rate coefficients and the stoichiometric coefficients in the reaction of ozone with the model component p-nitrophenol were estimated at low pH of water using nonlinear optimization. A novel method for estimation of multireaction model parameters in ozonation was developed. In this method the concentration of unknown intermediate compounds is presented as a residual COD (chemical oxygen demand) calculated from the measured COD and the theoretical COD for the known species. The decomposition rate of p-nitrophenol on the pathway producing hydroquinone was found to be about two times faster than the p-nitrophenol decomposition rate on the pathway producing 4- nitrocatechol. In the fourth article, the reaction kinetics of p-nitrophenol ozonation was studied in a bubble column at pH 2. Using the new reaction kinetic model presented in the previous article, the reaction kinetic parameters, rate coefficients, and stoichiometric coefficients as well as the mass transfer coefficient were estimated with nonlinear estimation. The decomposition rate of pnitrophenol was found to be equal both on the pathway producing hydroquinone and on the path way producing 4-nitrocathecol. Comparison of the rate coefficients with the case at initial pH 5 indicates that the p-nitrophenol degradation producing 4- nitrocathecol is more selective towards molecular ozone than the reaction producing hydroquinone. The identifiability and reliability of the estimated parameters were analyzed with the Marcov chain Monte Carlo (MCMC) method. @All rights reserved. No part of the publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of the author.

Trajectory and Force Control of a Direct Drive Arm

Using the MIT Serial Link Direct Drive Arm as the main experimental device, various issues in trajectory and force control of manipulators were studied in this thesis. Since accurate modeling is important for any controller, issues of estimating the dynamic model of a manipulator and its load were addressed first. Practical and effective algorithms were developed fro the Newton-Euler equations to estimate the inertial parameters of manipulator rigid-body loads and links. Load estimation was implemented both on PUMA 600 robot and on the MIT Serial Link Direct Drive Arm. With the link estimation algorithm, the inertial parameters of the direct drive arm were obtained. For both load and link estimation results, the estimated parameters are good models of the actual system for control purposes since torques and forces can be predicted accurately from these estimated parameters. The estimated model of the direct drive arm was them used to evaluate trajectory following performance by feedforward and computed torque control algorithms. The experimental evaluations showed that the dynamic compensation can greatly improve trajectory following accuracy. Various stability issues of force control were studied next. It was determined that there are two types of instability in force control. Dynamic instability, present in all of the previous force control algorithms discussed in this thesis, is caused by the interaction of a manipulator with a stiff environment. Kinematics instability is present only in the hybrid control algorithm of Raibert and Craig, and is caused by the interaction of the inertia matrix with the Jacobian inverse coordinate transformation in the feedback path. Several methods were suggested and demonstrated experimentally to solve these stability problems. The result of the stability analyses were then incorporated in implementing a stable force/position controller on the direct drive arm by the modified resolved acceleration method using both joint torque and wrist force sensor feedbacks.

Prediction leaching of potassium using the convective-dispersive and the convective log-normal transfer function models

There is increasing concern about soil enrichment with K+ and subsequent potential losses following long-term application of poor quality water to agricultural land. Different models are increasingly being used for predicting or analyzing water flow and chemical transport in soils and groundwater. The convective-dispersive equation (CDE) and the convective log-normal transfer function (CLT) models were fitted to the potassium (K+) leaching data. The CDE and CLT models produced equivalent goodness of fit. Simulated breakthrough curves for a range of CaCl2 concentration based on parameters of 15 mmol l(-1) CaCl2 were characterised by an early peak position associated with higher K+ concentration as the CaCl2 concentration used in leaching experiments decreased. In another method, the parameters estimated from 15 mmol l(-1) CaCl2 solution were used for all other CaCl2 concentrations, and the best value of retardation factor (R) was optimised for each data set. A better prediction was found. With decreasing CaCl2 concentration the value of R is required to be more than that measured (except for 10 mmol l(-1) CaCl2), if the estimated parameters of 15 mmol l(-1) CaCl2 are used. The two models suffer from the fact that they need to be calibrated against a data set, and some of their parameters are not measurable and cannot be determined independently.

Efficient and cost-effective experimental determination of kinetic constants and data: the success of a Bayesian systematic approach to drug transport, receptor binding, continuous culture and cell transport kinetics

Details about the parameters of kinetic systems are crucial for progress in both medical and industrial research, including drug development, clinical diagnosis and biotechnology applications. Such details must be collected by a series of kinetic experiments and investigations. The correct design of the experiment is essential to collecting data suitable for analysis, modelling and deriving the correct information. We have developed a systematic and iterative Bayesian method and sets of rules for the design of enzyme kinetic experiments. Our method selects the optimum design to collect data suitable for accurate modelling and analysis and minimises the error in the parameters estimated. The rules select features of the design such as the substrate range and the number of measurements. We show here that this method can be directly applied to the study of other important kinetic systems, including drug transport, receptor binding, microbial culture and cell transport kinetics. It is possible to reduce the errors in the estimated parameters and, most importantly, increase the efficiency and cost-effectiveness by reducing the necessary amount of experiments and data points measured. (C) 2003 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

The REFLEX project: Comparing different algorithms and implementations for the inversion of a terrestrial ecosystem model against eddy covariance data

We describe a model-data fusion (MDF) inter-comparison project (REFLEX), which compared various algorithms for estimating carbon (C) model parameters consistent with both measured carbon fluxes and states and a simple C model. Participants were provided with the model and with both synthetic net ecosystem exchange (NEE) of CO2 and leaf area index (LAI) data, generated from the model with added noise, and observed NEE and LAI data from two eddy covariance sites. Participants endeavoured to estimate model parameters and states consistent with the model for all cases over the two years for which data were provided, and generate predictions for one additional year without observations. Nine participants contributed results using Metropolis algorithms, Kalman filters and a genetic algorithm. For the synthetic data case, parameter estimates compared well with the true values. The results of the analyses indicated that parameters linked directly to gross primary production (GPP) and ecosystem respiration, such as those related to foliage allocation and turnover, or temperature sensitivity of heterotrophic respiration, were best constrained and characterised. Poorly estimated parameters were those related to the allocation to and turnover of fine root/wood pools. Estimates of confidence intervals varied among algorithms, but several algorithms successfully located the true values of annual fluxes from synthetic experiments within relatively narrow 90% confidence intervals, achieving >80% success rate and mean NEE confidence intervals <110 gC m−2 year−1 for the synthetic case. Annual C flux estimates generated by participants generally agreed with gap-filling approaches using half-hourly data. The estimation of ecosystem respiration and GPP through MDF agreed well with outputs from partitioning studies using half-hourly data. Confidence limits on annual NEE increased by an average of 88% in the prediction year compared to the previous year, when data were available. Confidence intervals on annual NEE increased by 30% when observed data were used instead of synthetic data, reflecting and quantifying the addition of model error. Finally, our analyses indicated that incorporating additional constraints, using data on C pools (wood, soil and fine roots) would help to reduce uncertainties for model parameters poorly served by eddy covariance data.

Forecasting with difference and trend stationary models

Although difference-stationary (DS) and trend-stationary (TS) processes have been subject to considerable analysis, there are no direct comparisons for each being the data-generation process (DGP). We examine incorrect choice between these models for forecasting for both known and estimated parameters. Three sets of Monte Carlo simulations illustrate the analysis, to evaluate the biases in conventional standard errors when each model is mis-specified, compute the relative mean-square forecast errors of the two models for both DGPs, and investigate autocorrelated errors, so both models can better approximate the converse DGP. The outcomes are surprisingly different from established results.