5 resultados para Colonial Word

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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The effects of spatial competition among colonial marine organisms are often evident in the contact zones between colonies. These effects are especially pronounced when the interaction results in overgrowth or necrosis of one of the competitors. Ascidians, one of the dominant taxonomic groups in subtidal sessile communities, have specialized morula cells that provide a defense against microbial infections. Injuries resulting from interspecific competitive interactions might also act as a stimulus for this defensive mechanism. Therefore, we expected to see the recruitment of morula cells in tissues near competitor contact zones. To test the hypothesis that spatial competition elicits this immune response, we placed colonies of the ascidian Didemnum perlucidum from southeastern Brazil in four different types of competitive situations: (1) overgrowth of the competitor, (2) stand-off interactions, (3) overgrowth by the competitor, and (4) free of competitors. Our results indicate that competitive interactions increase the population of morula cells in contact zones, as more cells were observed in interactions that resulted in the overgrowth of individuals of D. perlucidum, and fewer cells were observed in colonies that were free of competitors. We identified the defensive function of the morula cells by showing the presence of the enzyme phenoloxidase within its vacuoles. Phenoloxidase is a widespread enzyme among animals and plants, and is frequently used in defense by synthesizing toxic quinones from polyphenol substrates. This is the first study to document the presence of morula cells in didemnid ascidians and the mobilization of these cells by spatial competition by heterospecifics, and one of the first studies to identify phenoloxidase activity in morula cells.

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Complex networks have been employed to model many real systems and as a modeling tool in a myriad of applications. In this paper, we use the framework of complex networks to the problem of supervised classification in the word disambiguation task, which consists in deriving a function from the supervised (or labeled) training data of ambiguous words. Traditional supervised data classification takes into account only topological or physical features of the input data. On the other hand, the human (animal) brain performs both low- and high-level orders of learning and it has facility to identify patterns according to the semantic meaning of the input data. In this paper, we apply a hybrid technique which encompasses both types of learning in the field of word sense disambiguation and show that the high-level order of learning can really improve the accuracy rate of the model. This evidence serves to demonstrate that the internal structures formed by the words do present patterns that, generally, cannot be correctly unveiled by only traditional techniques. Finally, we exhibit the behavior of the model for different weights of the low- and high-level classifiers by plotting decision boundaries. This study helps one to better understand the effectiveness of the model. Copyright (C) EPLA, 2012

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The automatic disambiguation of word senses (i.e., the identification of which of the meanings is used in a given context for a word that has multiple meanings) is essential for such applications as machine translation and information retrieval, and represents a key step for developing the so-called Semantic Web. Humans disambiguate words in a straightforward fashion, but this does not apply to computers. In this paper we address the problem of Word Sense Disambiguation (WSD) by treating texts as complex networks, and show that word senses can be distinguished upon characterizing the local structure around ambiguous words. Our goal was not to obtain the best possible disambiguation system, but we nevertheless found that in half of the cases our approach outperforms traditional shallow methods. We show that the hierarchical connectivity and clustering of words are usually the most relevant features for WSD. The results reported here shed light on the relationship between semantic and structural parameters of complex networks. They also indicate that when combined with traditional techniques the complex network approach may be useful to enhance the discrimination of senses in large texts. Copyright (C) EPLA, 2012

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Portable system of energy dispersive X-ray fluorescence was used to determine the elemental composition of 68 pottery fragments from Sambaqui do Bacanga, an archeological site in Sao Luis, Maranhao, Brazil. This site was occupied from 6600 BP until 900 BP. By determining the element chemical composition of those fragments, it was possible to verify the existence of engobe in 43 pottery fragments. Obtained from two-dimensional graphs and hierarchical cluster analysis performed in fragments of stratigraphies from surface and 113-cm level, and 10 to 20, 132 and 144-cm level, it was possible to group these fragments in five distinct groups, according to their stratigraphies. The results of data grouping (two-dimensional graphics) are in agreement with hierarchical cluster analysis by Ward method. Copyright (C) 2011 John Wiley & Sons, Ltd.

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O texto versa sobre o papel dos mestres-construtores na produção da arquitetura nas vilas e cidades coloniais brasileiras, focalizando o sistema de empreitada em etapas e o papel dos riscos e traças na concepção, execução, louvação e prestação de contas das edificações. Questiona a ideia de autoria única, apontando atores e assinaturas múltiplas. Analisa os conhecimentos necessários, especialmente relacionados à geometria prática, discutindo a relação dialética entre teoria e prática, e as fronteiras tênues entre erudição e costume.