Application of Entropy and Fractal Dimension Analyses to the Pattern Recognition of Contaminated Fish Responses in Aquaculture

The objective of the work was to develop a non-invasive methodology for image acquisition, processing and nonlinear trajectory analysis of the collective fish response to a stochastic event. Object detection and motion estimation were performed by an optical flow algorithm in order to detect moving fish and simultaneously eliminate background, noise and artifacts. The Entropy and the Fractal Dimension (FD) of the trajectory followed by the centroids of the groups of fish were calculated using Shannon and permutation Entropy and the Katz, Higuchi and Katz-Castiglioni's FD algorithms respectively. The methodology was tested on three case groups of European sea bass (Dicentrarchus labrax), two of which were similar (C1 control and C2 tagged fish) and very different from the third (C3, tagged fish submerged in methylmercury contaminated water). The results indicate that Shannon entropy and Katz-Castiglioni were the most sensitive algorithms and proved to be promising tools for the non-invasive identification and quantification of differences in fish responses. In conclusion, we believe that this methodology has the potential to be embedded in online/real time architecture for contaminant monitoring programs in the aquaculture industry.

Feature Selection for Speech Emotion Recognition in Spanish and Basque: On the Use of Machine Learning to Improve Human-Computer Interaction

Study of emotions in human-computer interaction is a growing research area. This paper shows an attempt to select the most significant features for emotion recognition in spoken Basque and Spanish Languages using different methods for feature selection. RekEmozio database was used as the experimental data set. Several Machine Learning paradigms were used for the emotion classification task. Experiments were executed in three phases, using different sets of features as classification variables in each phase. Moreover, feature subset selection was applied at each phase in order to seek for the most relevant feature subset. The three phases approach was selected to check the validity of the proposed approach. Achieved results show that an instance-based learning algorithm using feature subset selection techniques based on evolutionary algorithms is the best Machine Learning paradigm in automatic emotion recognition, with all different feature sets, obtaining a mean of 80,05% emotion recognition rate in Basque and a 74,82% in Spanish. In order to check the goodness of the proposed process, a greedy searching approach (FSS-Forward) has been applied and a comparison between them is provided. Based on achieved results, a set of most relevant non-speaker dependent features is proposed for both languages and new perspectives are suggested.

Modelos de leitura em sites de FLE: reflexões sobre adequação e seleção de atividades para o desenvolvimento da autonomia leitora em aulas de francês

Esta pesquisa tem por objetivo discutir os modelos de leitura subjacentes ao trabalho proposto em sites de ensino de Francês de Língua Estrangeira (FLE). Para compreender como se apresentam os modelos de leitura nesses contextos, consideramos como base teórica de partida a concepção sócio-interacional da língua. Para tal, contextualizamos a necessidade de uma constante reflexão acerca do processo de ensino/aprendizagem de FLE. Em seguida, apresentamos a motivação para desenvolver a pesquisa e apresentamos, resumidamente, o nosso percurso metodológico. Destacamos a revisão bibliográfica, apresentando os modelos de leitura e as estratégias que envolvem essa atividade em meio virtual. O primeiro momento de nossa pesquisa foi de cunho exploratório porque não tínhamos conhecimento do universo de sites voltados para o ensino de FLE. A pesquisa é, também, de natureza documental uma vez que trabalhamos com sites tomados como documentos. Optamos pelo caráter descritivo pois, a partir da descrição, baseada nos critérios de análise, do material retirado dos sites que fazem parte do nosso corpus, é que respondemos e confirmamos nossas hipóteses. Nosso método de análise é o qualitativo porque buscamos interpretar, a partir de nossas observações dos documentos selecionados em um primeiro momento. Após estabelecer os critérios, partimos para a discussão e análise dos dados e, em seguida, fazemos algumas orientações aos professores que quiserem utilizar o material disponibilizado pelos sites analisados. No capítulo final, fazemos considerações sobre a pesquisa, apresentamos os resultados das análises, explicitamos a importância do trabalho para a construção do conhecimento acerca da leitura em meio virtual, e, finalmente, recomendamos novos estudos, diante do que encontramos, para que o ensino da leitura em Língua Estrangeira contribua para a formação de leitores autônomos

Frame-level features conveying phonetic information for language and speaker recognition

150 p.

Leukemia-Associated Mutations in Nucleophosmin Alter Recognition by CRM1: Molecular Basis of Aberrant Transport

Nucleophosmin (NPM) is a nucleocytoplasmic shuttling protein, normally enriched in nucleoli, that performs several activities related to cell growth. NPM mutations are characteristic of a subtype of acute myeloid leukemia (AML), where mutant NPM seems to play an oncogenic role. AML-associated NPM mutants exhibit altered subcellular traffic, being aberrantly located in the cytoplasm of leukoblasts. Exacerbated export of AML variants of NPM is mediated by the nuclear export receptor CRM1, and due, in part, to a mutationally acquired novel nuclear export signal (NES). To gain insight on the molecular basis of NPM transport in physiological and pathological conditions, we have evaluated the export efficiency of NPM in cells, and present new data indicating that, in normal conditions, wild type NPM is weakly exported by CRM1. On the other hand, we have found that AML-associated NPM mutants efficiently form complexes with CRM1HA (a mutant CRM1 with higher affinity for NESs), and we have quantitatively analyzed CRM1HA interaction with the NES motifs of these mutants, using fluorescence anisotropy and isothermal titration calorimetry. We have observed that the affinity of CRM1HA for these NESs is similar, which may help to explain the transport properties of the mutants. We also describe NPM recognition by the import machinery. Our combined cellular and biophysical studies shed further light on the determinants of NPM traffic, and how it is dramatically altered by AML-related mutations.