961 resultados para Bacterial vaccines
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In the field of control systems it is common to use techniques based on model adaptation to carry out control for plants for which mathematical analysis may be intricate. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this line, this paper gives a perspective on the quality of results given by two different biologically connected learning algorithms for the design of B-spline neural networks (BNN) and fuzzy systems (FS). One approach used is the Genetic Programming (GP) for BNN design and the other is the Bacterial Evolutionary Algorithm (BEA) applied for fuzzy rule extraction. Also, the facility to incorporate a multi-objective approach to the GP algorithm is outlined, enabling the designer to obtain models more adequate for their intended use.
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The design phase of B-spline neural networks is a highly computationally complex task. Existent heuristics have been found to be highly dependent on the initial conditions employed. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this paper, the Bacterial Programming approach is presented, which is based on the replication of the microbial evolution phenomenon. This technique produces an efficient topology search, obtaining additionally more consistent solutions.
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The design phase of B-spline neural networks represents a very high computational task. For this purpose, heuristics have been developed, but have been shown to be dependent on the initial conditions employed. In this paper a new technique, Bacterial Programming, is proposed, whose principles are based on the replication of the microbial evolution phenomenon. The performance of this approach is illustrated and compared with existing alternatives.
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This paper presents a method of using the so-colled "bacterial algorithm" (4,5) for extracting a fuzzy rule base from a training set. The bewly proposed bacterial evolutionary algorithm (BEA) is shown. In our application one bacterium corresponds to a fuzzy rule system.
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Dissertação de mestrado, Engenharia Biológica, Faculdade de Ciências e Tecnologia, Universidade do Algarve; Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, 2015
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Senior thesis written for Oceanography 445
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Fitness centres are special places where conditions for microbiological proliferation should be considered. Moisture due to human perspiration and water condensation as a result of human physical activities are prevalent in this type of buildings. Exposure to microbial contaminants is clinically associated with respiratory disorders and people who work out in polluted environments would be susceptible to contaminants. This work studied the indoor air contamination in three gymnasiums in Lisbon. The sampling was performed at two periods: at the opening (morning) and closing (night) of the three gymnasiums. The airborne bacterial and fungal populations were sampled by impaction directly onto Tryptic Soy Agar (for bacteria) and Malt Extract Agar (for fungi) plates, using a Merck MAS-100 air sampler. Higher bacterial concentrations were found at night as compared to the morning but the same behaviour was not found for fungal concentrations. Gram-negative catalase positive cocci were the dominant bacteria in indoor air samples of the studied gymnasiums. In this study, 21 genera/species of fungal colonies were identified. Chrysosporium sp., Chrysonilia sp., Neoscytalidium hialinum, Sepedonium sp. and Penicillium sp. were the most prevalent species identified in the morning, while Cladosporium sp., Penicillium sp., Chrysosporium sp., Acremonium sp. and Chrysonilia sp. were more prevalent at night. A well-designed sanitation and maintenance program for gymnasiums is needed to ensure healthier space for indoor physical activity.
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Dissertation presented to obtain the Ph.D degree in Biology by Universidade Nova de Lisboa, Instituto de Tecnologia Química e Biológica, Instituto Gulbenkian de Ciência.
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Using low cost portable devices that enable a single analytical step for screening environmental contaminants is today a demanding issue. This concept is here tried out by recycling screen-printed electrodes that were to be disposed of and by choosing as sensory element a low cost material offering specific response for an environmental contaminant. Microcystins (MCs) were used as target analyte, for being dangerous toxins produced by cyanobacteria released into water bodies. The sensory element was a plastic antibody designed by surface imprinting with carefully selected monomers to ensure a specific response. These were designed on the wall of carbon nanotubes, taking advantage of their exceptional electrical properties. The stereochemical ability of the sensory material to detect MCs was checked by preparing blank materials where the imprinting stage was made without the template molecule. The novel sensory material for MCs was introduced in a polymeric matrix and evaluated against potentiometric measurements. Nernstian response was observed from 7.24 × 10−10 to 1.28 × 10−9 M in buffer solution (10 mM HEPES, 150 mM NaCl, pH 6.6), with average slopes of −62 mVdecade−1 and detection capabilities below 1 nM. The blank materials were unable to provide a linear response against log(concentration), showing only a slight potential change towards more positive potentials with increasing concentrations (while that ofthe plastic antibodies moved to more negative values), with a maximum rate of +33 mVdecade−1. The sensors presented good selectivity towards sulphate, iron and ammonium ions, and also chloroform and tetrachloroethylene (TCE) and fast response (<20 s). This concept was successfully tested on the analysis of spiked environmental water samples. The sensors were further applied onto recycled chips, comprehending one site for the reference electrode and two sites for different selective membranes, in a biparametric approach for “in situ” analysis.
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Dissertation presented to obtain the Ph.D. degree in Biology/ Molecular Biology
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Biochemistry, 2004, 43 (46), pp 14566–14576 DOI: 10.1021/bi0485833
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Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica
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Dissertation presented to obtain the Ph.D degree in Biology
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Dissertation presented to obtain the Ph.D degree in Biology.