Processing of hierarchical syntactic strusture in music

Hierarchical structure with nested nonlocal dependencies is a key feature of human language and can be identified theoretically in most pieces of tonal music. However, previous studies have argued against the perception of such structures in music. Here, we show processing of nonlocal dependencies in music. We presented chorales by J. S. Bach and modified versions inwhich the hierarchical structure was rendered irregular whereas the local structure was kept intact. Brain electric responses differed between regular and irregular hierarchical structures, in both musicians and nonmusicians. This finding indicates that, when listening to music, humans apply cognitive processes that are capable of dealing with longdistance dependencies resulting from hierarchically organized syntactic structures. Our results reveal that a brain mechanism fundamental for syntactic processing is engaged during the perception of music, indicating that processing of hierarchical structure with nested nonlocal dependencies is not just a key component of human language, but a multidomain capacity of human cognition.

Algoritmo SOM com estrutura hierárquica e dinâmica aplicado a compressão de imagens

ln this work the implementation of the SOM (Self Organizing Maps) algorithm or Kohonen neural network is presented in the form of hierarchical structures, applied to the compression of images. The main objective of this approach is to develop an Hierarchical SOM algorithm with static structure and another one with dynamic structure to generate codebooks (books of codes) in the process of the image Vector Quantization (VQ), reducing the time of processing and obtaining a good rate of compression of images with a minimum degradation of the quality in relation to the original image. Both self-organizing neural networks developed here, were denominated HSOM, for static case, and DHSOM, for the dynamic case. ln the first form, the hierarchical structure is previously defined and in the later this structure grows in an automatic way in agreement with heuristic rules that explore the data of the training group without use of external parameters. For the network, the heuristic mIes determine the dynamics of growth, the pruning of ramifications criteria, the flexibility and the size of children maps. The LBO (Linde-Buzo-Oray) algorithm or K-means, one ofthe more used algorithms to develop codebook for Vector Quantization, was used together with the algorithm of Kohonen in its basic form, that is, not hierarchical, as a reference to compare the performance of the algorithms here proposed. A performance analysis between the two hierarchical structures is also accomplished in this work. The efficiency of the proposed processing is verified by the reduction in the complexity computational compared to the traditional algorithms, as well as, through the quantitative analysis of the images reconstructed in function of the parameters: (PSNR) peak signal-to-noise ratio and (MSE) medium squared error

Processing of hierarchical syntactic strusture in music

Hierarchical structure with nested nonlocal dependencies is a key feature of human language and can be identified theoretically in most pieces of tonal music. However, previous studies have argued against the perception of such structures in music. Here, we show processing of nonlocal dependencies in music. We presented chorales by J. S. Bach and modified versions inwhich the hierarchical structure was rendered irregular whereas the local structure was kept intact. Brain electric responses differed between regular and irregular hierarchical structures, in both musicians and nonmusicians. This finding indicates that, when listening to music, humans apply cognitive processes that are capable of dealing with longdistance dependencies resulting from hierarchically organized syntactic structures. Our results reveal that a brain mechanism fundamental for syntactic processing is engaged during the perception of music, indicating that processing of hierarchical structure with nested nonlocal dependencies is not just a key component of human language, but a multidomain capacity of human cognition.

Caracterização comportamental e avaliação da qualidade de leite em caprinos da raça saanen no semiárido nordestino

Goats are social animals which groups are organized from dominance hierarchies, established by agonistic behaviors. The quality and productivity of the goat s milk can be influenced by the dominance hierarchy. In this context, the objectives of our work were describe the social and food behavior of Saanen goats in a semi-extensive production system; characterize the social organization from the assessment of dominance hierarchies in two seasonal periods and correlate the physicochemical quality of the goats milk according hierarchical position. The experiment was conducted in the EMPARN s experimental station, located in the district of Cruzeta/RN. We utilized 17 multiparous goats of the Saanen race, with different age and weight. The observations were performed in precipitation and drought phases. The scan method recorded the trough permanence and agonistic interactions by method "all occurrences" in the pasture the alimentary behaviors of eat, ruminate on foot, ruminate lying, leisure on foot, leisure lying and walk, by the focal animal sampling method. The goats milk was submitted to analyzes of: density, protein, fat, lactose, CSS and total solids. The animals spend most of the time feeding themselves, and the activities that demand greater energy expenditure are done in the morning. The animals changed the hierarchical structure during the seasonal periods because of the withdrawal of some individuals of the group, having more aggressive behavior in the rainy season. The dominant animal the lowet production, the more CSS and the lesser fat, the goat in the middle of the hierarchy was the one that obtained the best production and quality. We conclude that the Saanen goats adapt to the environment and the conditions of the group to ensure better survival and its production is influenced by the internal dynamics of the group

Hierarquia de dominância durante a obtenção de Alimento em cebus apella e cebus libidinosus em Cativeiro

The analysis of the index of hierarchy and structural models of the formation of groups allowed to establish the hierarchical position of members of two groups of the genus Cebus. By the analyses of the hierarchical positions and the application of tests to obtain a food resource (TORA), we know the difference between these groups and groups in the wild. The results show a high ranking for both Cebus apella, as well as Cebus libidinosus. The results have enabled us to establish that the hierarchical structure in groups of Cebus in captivity: a) can be fixed and rigid different from highly flexible hierarchical structure studied in groups of wild b) even which similar hierarchy indices, there are differences in the hierarchical structure presents between C. apella and C. libidinosus in captivity c) hierarchy directly influence the behavioral patterns of obtaining food in Cebus

Algoritmos de agrupamento aplicados a dados de expressão gênica de câncer: um estudo comparativo

The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have proposed new clustering methods that take advantage of characteristics of the gene expression data, the medical community has a preference for using classic clustering methods. There have been no studies thus far performing a large-scale evaluation of different clustering methods in this context. This work presents the first large-scale analysis of seven different clustering methods and four proximity measures for the analysis of 35 cancer gene expression data sets. Results reveal that the finite mixture of Gaussians, followed closely by k-means, exhibited the best performance in terms of recovering the true structure of the data sets. These methods also exhibited, on average, the smallest difference between the actual number of classes in the data sets and the best number of clusters as indicated by our validation criteria. Furthermore, hierarchical methods, which have been widely used by the medical community, exhibited a poorer recovery performance than that of the other methods evaluated. Moreover, as a stable basis for the assessment and comparison of different clustering methods for cancer gene expression data, this study provides a common group of data sets (benchmark data sets) to be shared among researchers and used for comparisons with new methods