991 resultados para kinetics modeling


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The kinetics of growth of Leishmania performed in vitro after internalization of the promastigote form in the cell and the occurrence of the transformation of the parasite into the amastigote form have been described by several authors. They used explants of macrophages in hamster spleen cell culture or in a human macrophage lineage cell, the U937. Using microscopy, the description of morphologic inter-relationship and the analysis of the production of specific molecules, it has been possible to define some of the peculiarities of the biology of the parasite. The present study shows the growth cycle of Leishmania chagasi during the observation of kinetic analysis undertaken with a McCoy cell lineage that lasted for a period of 144 hours. During the process, the morphologic transformation was revealed by indirect immunofluorescence (IF) and the molecules liberated in the extra cellular medium were observed by SDS-PAGE at 24-hour intervals during the whole 144-hour period. It was observed that in the first 72 hours the promastigote form of L. chagasi adhered to the cell membranes and assumed a rounded (amastigote-like) form. At 96 hours the infected cells showed morphologic alterations; at 120 hours the cells had liberated soluble fluorescent antigens into the extra cellular medium. At 144 hours, new elongated forms of the parasites, similar to promastigotes, were observed. In the SDS-PAGE, specific molecular weight proteins were observed at each point of the kinetic analysis showing that the McCoy cell imitates the macrophage and may be considered a useful model for the study of the infection of the Leishmania/cell binomial.

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The electricity market restructuring, and its worldwide evolution into regional and even continental scales, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in a rising complexity in power systems operation. Several power system simulators have been developed in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex and constantly changing environment. The main contribution of this paper is given by the integration of several electricity market and power system models, respecting to the reality of different countries. This integration is done through the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The continuous development of Multi-Agent System for Competitive Electricity Markets platform provides the means for the exemplification of the usefulness of this ontology. A case study using the proposed multi-agent platform is presented, considering a scenario based on real data that simulates the European Electricity Market environment, and comparing its performance using different market mechanisms. The main goal is to demonstrate the advantages that the integration of various market models and simulation platforms have for the study of the electricity markets’ evolution.

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In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

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Dissertação para obtenção do Grau de Mestre em Lógica Computacional

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OBJECTIVE: The objective of the study was to develop a model for estimating patient 28-day in-hospital mortality using 2 different statistical approaches. DESIGN: The study was designed to develop an outcome prediction model for 28-day in-hospital mortality using (a) logistic regression with random effects and (b) a multilevel Cox proportional hazards model. SETTING: The study involved 305 intensive care units (ICUs) from the basic Simplified Acute Physiology Score (SAPS) 3 cohort. PATIENTS AND PARTICIPANTS: Patients (n = 17138) were from the SAPS 3 database with follow-up data pertaining to the first 28 days in hospital after ICU admission. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: The database was divided randomly into 5 roughly equal-sized parts (at the ICU level). It was thus possible to run the model-building procedure 5 times, each time taking four fifths of the sample as a development set and the remaining fifth as the validation set. At 28 days after ICU admission, 19.98% of the patients were still in the hospital. Because of the different sampling space and outcome variables, both models presented a better fit in this sample than did the SAPS 3 admission score calibrated to vital status at hospital discharge, both on the general population and in major subgroups. CONCLUSIONS: Both statistical methods can be used to model the 28-day in-hospital mortality better than the SAPS 3 admission model. However, because the logistic regression approach is specifically designed to forecast 28-day mortality, and given the high uncertainty associated with the assumption of the proportionality of risks in the Cox model, the logistic regression approach proved to be superior.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies

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Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

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J Biol Inorg Chem (2007) 12:691–698 DOI 10.1007/s00775-007-0219-9

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J Biol Inorg Chem (2006) 11: 433–444 DOI 10.1007/s00775-006-0090-0

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Trabalho de Projeto apresentado como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Química e Bioquímica