3 resultados para STREPTOMYCES DAUFPE 3060
em Repositório Científico do Instituto Politécnico de Lisboa - Portugal
Resumo:
Este artigo foca a problemática da demonstração na matemática escolar. Apresenta parte de um estudo que teve como objetivo identificar as formas como os alunos validam os resultados matemáticos, relacionando-as com a prática social desenvolvida na aula. O estudo situa-se num paradigma interpretativo e, focando-se nos significados dos participantes— uma turma de 9.º ano, de onde foi selecionado um grupo de quatro alunos para alvo de registo vídeo e áudio, e a respetiva professora—, foi orientado pelas seguintes questões: 1) qual a natureza da demonstração no contexto escolar?, 2) qual o papel da demonstração na atividade matemática escolar?, e 3) como se relaciona a concretização da demonstração com a prática social desenvolvida na aula de Matemática? Os resultados discutidos no presente artigo reportam-se ao papel das funções da demonstração na evolução dos alunos para a utilização de esquemas demonstrativos dedutivos, quer nas situações pautadas pela existência de uma fase de conjeturação quer nas situações caracterizadas pela ausência de conjeturação.
Resumo:
Laccases are multi-copper oxidases that oxidise a wide range of substrates including phenol and aniline derivatives, which could be further involved in coupling reactions leading to the formation of dimeric and trimeric structures. This paper describes the enzyme-mediated dimerisation of several ortho and meta, para-disubstituted aromatic amines into phenazine ("head-to-tail" dimers) and phenoxazinone chromophores. The redox properties of substituted aromatic amines were studied by cyclic voltammetry and the kinetic constants of CotA and Trametes versicolor laccases were measured for selected aromatic amines. The structure of novel enzymatically synthesised phenazine and phenoxazinone dyes using CotA laccase was assessed by NMR and MS. Overall our data show that this enzymatic green process is an efficient alternative to the classic chemical oxidation of aromatic amines and phenols, with an impact on the broad field of applications of these heterocyclic compounds.
Resumo:
Many learning problems require handling high dimensional datasets with a relatively small number of instances. Learning algorithms are thus confronted with the curse of dimensionality, and need to address it in order to be effective. Examples of these types of data include the bag-of-words representation in text classification problems and gene expression data for tumor detection/classification. Usually, among the high number of features characterizing the instances, many may be irrelevant (or even detrimental) for the learning tasks. It is thus clear that there is a need for adequate techniques for feature representation, reduction, and selection, to improve both the classification accuracy and the memory requirements. In this paper, we propose combined unsupervised feature discretization and feature selection techniques, suitable for medium and high-dimensional datasets. The experimental results on several standard datasets, with both sparse and dense features, show the efficiency of the proposed techniques as well as improvements over previous related techniques.