97 resultados para Process Error


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The acquisition and extinction of affective valence to neutral geometrical shape conditional stimuli was investigated in three experiments. Experiment 1 employed a differential conditioning procedure with aversive shock USs. Differential electrodermal responding was evident during acquisition and lost during extinction. As indexed by verbal ratings, the CS1 acquired negative valence during acquisition,which was reduced after extinction. Affective priming, a reaction time based demand free measure of stimulus valence, failed to provide evidence for affective learning. Experiment 2 employed pictures of happy and angry faces as USs.Valence ratings after acquisitionweremore positive for theCS paired with happy faces (CS-H) and less positive for the CS paired with angry faces (CS-A) than during baseline. Extinction training reduced the extent of acquired valence significantly for both CSs, however, ratings of the CS-A remained different from baseline. Affective priming confirmed these results yielding differences between CS-A and CS-H after acquisition for pleasant and unpleasant targets, but for pleasant targets only after extinction. Experiment 3 replicated the design of Experiment 2, but presented the US pictures backwardly masked. Neither rating nor affective priming measures yielded any evidence for affective learning. The present results confirm across two different experimental procedures that, contrary to predictions from dual process accounts of human learning, affective learning is subject to extinction.

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This paper presents a method for estimating the posterior probability density of the cointegrating rank of a multivariate error correction model. A second contribution is the careful elicitation of the prior for the cointegrating vectors derived from a prior on the cointegrating space. This prior obtains naturally from treating the cointegrating space as the parameter of interest in inference and overcomes problems previously encountered in Bayesian cointegration analysis. Using this new prior and Laplace approximation, an estimator for the posterior probability of the rank is given. The approach performs well compared with information criteria in Monte Carlo experiments. (C) 2003 Elsevier B.V. All rights reserved.

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The suspension Chinese Hamster Ovary cell line, 13-10-302, utilizing the metallothionein (MT) expression system producing recombinant human growth hormone (hGH) was studied in a serum-free and cadmium-free medium at different fermentation scales and modes of operation. Initial experiments were carried out to optimize the concentration of metal addition to induce the MT promoter. Subsequently, the cultivation of the 13-10-302 cell line was scaled up from spinner flasks into bioreactors, and the cultivation duration was extended with fed-batch and perfusion strategies utilizing 180 muM zinc to induce the promoter controlling expression of recombinant hGH. It was shown that a fed-batch process could increase the maximum cell numbers twofold, from 3.3 to 6.3 x 10(6) cell/mL, over those obtained in normal batch fermentations, and this coupled with extended fermentation times resulted in a fourfold increase in final hGH titer, from 135 +/- 15 to 670 +/- 70 mg/L at a specific productivity q(hGH) value of 12 pg cell(-1)d(-1). The addition of sodium butyrate increased the specific productivity of hGH in cells to a value of approximately 48 pg cell(-1)d(-1), resulting in a final hGH titer of over a gram per liter during fed-batch runs. A BioSep acoustic cell recycler was used to retain the cells in the bioreactor during perfusion operation. It was necessary to maintain the specific feeding rates (SFR) above a value of 0.2 vvd/(10(6) cell/mL) to maintain the viability and productivity of the 13-10-302 cells; under these conditions the viable cell number increased to over 107 cell/mL and resulted in a volumetric productivity of over 120 mg(hGH) L(-1)d(-1). Process development described in this work demonstrates cultivation at various scales and sustained high levels of productivity under cadmium free condition in a CHO cell line utilizing an inducible metallothionein expression system. (C) 2004 Wiley Periodicals, Inc.

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An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd

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In order to analyse the effect of modelling assumptions in a formal, rigorous way, a syntax of modelling assumptions has been defined. The syntax of modelling assumptions enables us to represent modelling assumptions as transformations acting on the set of model equations. The notion of syntactical correctness and semantical consistency of sets of modelling assumptions is defined and methods for checking them are described. It is shown on a simple example how different modelling assumptions act on the model equations and their effect on the differential index of the resulted model is also indicated.

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Analysis of a major multi-site epidemiologic study of heart disease has required estimation of the pairwise correlation of several measurements across sub-populations. Because the measurements from each sub-population were subject to sampling variability, the Pearson product moment estimator of these correlations produces biased estimates. This paper proposes a model that takes into account within and between sub-population variation, provides algorithms for obtaining maximum likelihood estimates of these correlations and discusses several approaches for obtaining interval estimates. (C) 1997 by John Wiley & Sons, Ltd.

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Chinese-style dried, shredded meat is traditionally prepared by sequential cooking, shredding, pre-drying, and final drying (roasting) of lean meat. In this study, shredded dried beef (a(w)<0.6) was prepared by omitting roasting but prolonging pre-drying. Sensory scores of the modified product were lower than those for the traditional product. When heat pump drying replaced traditional oven drying, drying time was shortened without significant difference in quality attributes. Desorption curves were established for shredded beef at several drying temperatures.