RESUMO A amputação é um recurso terapêutico utilizado para realizar a remoção de um membro, outro apêndice ou saliência do corpo, na ocorrência de lesões graves de nervos, artérias, partes moles e ossos. O objetivo desta pesquisa foi verificar a prevalência de amputações de membros no estado de Alagoas. Tratou-se de um estudo de dados secundários, com abordagem epidemiológica e observacional, no período de 2008 a 2015. As informações foram coletadas do banco de dados do SIHSUS. Foram registrados 361.585 procedimentos de amputações de membros no Brasil, com predominância nas regiões Sudeste, Nordeste e Sul, responsáveis por 88,13% desse total. Alagoas ocupou o 21º lugar em número de amputações entre os estados brasileiros: seus procedimentos ocorreram em seis microrregiões, destas, 3 foram responsáveis por 95% dos casos. A prevalência de amputação em Alagoas foi de 19,05 amputações/100 mil habitantes. Três tipos de procedimentos apresentam maior predominância: amputação de membros inferiores, dedos, pé e tarso, o que representa 95% das amputações.

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Redes Sociais e Complexas: um modelo computacional para a investigação da pós-graduação Brasileira em Ensino de Física Nascimento, J. O. do. 1* ; Pereira-Guizzo, C. S.; Moreira, D. M.; Monteiro, R. L. S.;Pereira, H. B. B.; Moret, M. A. AbstractWith the indexes belonging to theory and complex social networks, it is possible to analyze emergent properties in semantic networks. This article aims to describe and analyze a semantic network formed by keywords, belonging to the master's works, doctoral and free teaching made in the area of Physical Education, between 1996 In support of the study, we conducted calculations and analyze the belongings indices of social and complex networks. We also present the methodology used to construct the network, where the keywords given a careful pretreatment before a second step is with software. We noticed indications that the network presented the free topology of scale and the small world phenomenon. Finally, the analysis also indicated that most of the themes of the emerging hubs in the network are related to formation of the physics' teacher and not on methodologies for Physical Education in different educational levels.

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In this article, the performance of a hybrid artificial neural network (i.e. scale-free and small-world) was analyzed and its learning curve compared to three other topologies: random, scale-free and small-world, as well as to the chemotaxis neural network of the nematode Caenorhabditis Elegans. One hundred equivalent networks (same number of vertices and average degree) for each topology were generated and each was trained for one thousand epochs. After comparing the mean learning curves of each network topology with the C. elegans neural network, we found that the networks that exhibited preferential attachment exhibited the best learning curves.

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This article explores the structure of connections between the hospitals that are members of a hospital management innovation and learning network. This study was based on the assumption that there are limitations to encourage the communication and diffusion of knowledge between health service organizations if they are not effectively connected through social networks. Social Network Analysis was used as a strategy for monitoring the dissemination of information between hospitals. Theoretical concepts of diffusion of knowledge allowed emphasizing the role of the phenomena and communication and learning processes as the driving forces for health service innovation. The results showed weak interactions between hospitals and a lack of cohesion within the network. Therefore, there is a need for policies to promote the flow of data and information, which requires network openness to foster the exchange of innovative processes. Interactions between these hospitals in horizontal and disseminated structures have yet to be stimulated, established, incorporated, and developed by individuals, institutions and health service organizations.