10 resultados para Spatial Database Systems

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Temporal, spatial and diel variation in the distribution and abundance of organisms is an inherent property of ecological systems. The present study describes these variations and the composition of decapod larvae from the surface waters of St Paul`s Rocks. The expeditions to the archipelago were carried out in April, August and November 2003, March 2004 and May 2005. Surface plankton samples were collected during the morning and dusk periods, inside the inlet and in increasing distances around the archipelago (similar to 150, 700 and 1500 m). The identification resulted in 51 taxa. Seven species, six genera and larvae of the families Pandalidae and Portunidae were identified for the first time in the area. The mean larval density varied from zero to 150.2 +/- 69.6 individuals 100 m(-3) in the waters surrounding the archipelago and from 1.7 +/- 3.0 to 12,827 +/- 15,073 individuals 100 m(-3) inside the inlet. Significant differences on larval density were verified between months and period of the day, but not among the three sites around the archipelago. Cluster and non-metric multidimensional scaling analysis indicated that the decapod larvae community was divided into benthic and pelagic assemblages. Indicator species analysis (ISA) showed that six Brachyura taxa were good indicators for the inlet, while three sergestids were the main species from the waters around the archipelago. These results suggest that St Paul`s Rocks can be divided into two habitats, based on larval composition, density and diversity values: the inlet and the waters surrounding the archipelago.

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Wild primates occupy large home ranges and travel long distances to reach goals. However, how primates are able to remember goal locations and travel efficiently is unclear. Few studies present consistent results regarding what reference system primates use to navigate, and what kind of spatial information they recognize. We analysed the pattern of navigation of one wild group of black capuchin monkeys, Cebus nigritus, at Atlantic Forest for 100 days in Carlos Botelho State Park (PECB), Brazil. We tested predictions based on the alternative hypotheses that black capuchin monkeys navigate using a sequence of landmarks as an egocentric reference system or an allocentric reference system, or both, depending on availability of food resources. The group location was recorded using a GPS device collecting coordinates at 5 min intervals, and route maps were generated using ArcView v9.3.1. The study group travelled through habitual routes during less than 30% of our study sample, and revisited resources from different starting points, using different paths and routes, even when prominent landmarks near feeding locations were not visible. The study group used habitual routes more frequently when high-quality foods were scarce, and navigated using different paths when revisiting food sources. Results support the hypothesis that black capuchin monkeys at PECB navigate using both egocentric and allocentric systems of reference, depending on the quality and distribution of the food resource they find. (C) 2010 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

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Objective. To identify the existence of spatial and temporal patterns in the occurrence of intentional homicides in the municipality of Sao Paulo (MSP), Brazil, and to discuss the analytical value of taking such patterns into account when designing studies that address the dynamics and factors associated with the incidence of homicides. Methods. A longitudinal ecological study was conducted, having as units of analysis 13 205 census tracts and the 96 census districts that congregate these sectors in Sao Paulo. All intentional homicides reported in the city between 2000 and 2008 were analyzed. The gross homicide rates per 100 000 population was calculated as well as the global and local Bayesian estimates for each census tract during the study period. To verify the possibility of identifying different patterns of the spatial distribution of homicides, we used BoxMap and Moran's I index. Results. The homicide trends in the city of Sao Paulo in the last decade were not homogeneous and systematic. Instead, seven patterns of spatial distribution were identified; that is, seven spatial regimes for the occurrence of intentional homicides, considering the homicide rates within each census tract as well as the rates in adjacent tracts. These spatial distribution regimes were not contained within the limits of the census tracts and districts. Conclusions. The results show the importance of analyzing the spatial distribution of social phenomena without restriction of political and administrative boundaries.

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Robust analysis of vector fields has been established as an important tool for deriving insights from the complex systems these fields model. Traditional analysis and visualization techniques rely primarily on computing streamlines through numerical integration. The inherent numerical errors of such approaches are usually ignored, leading to inconsistencies that cause unreliable visualizations and can ultimately prevent in-depth analysis. We propose a new representation for vector fields on surfaces that replaces numerical integration through triangles with maps from the triangle boundaries to themselves. This representation, called edge maps, permits a concise description of flow behaviors and is equivalent to computing all possible streamlines at a user defined error threshold. Independent of this error streamlines computed using edge maps are guaranteed to be consistent up to floating point precision, enabling the stable extraction of features such as the topological skeleton. Furthermore, our representation explicitly stores spatial and temporal errors which we use to produce more informative visualizations. This work describes the construction of edge maps, the error quantification, and a refinement procedure to adhere to a user defined error bound. Finally, we introduce new visualizations using the additional information provided by edge maps to indicate the uncertainty involved in computing streamlines and topological structures.

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Spatial data warehouses (SDWs) allow for spatial analysis together with analytical multidimensional queries over huge volumes of data. The challenge is to retrieve data related to ad hoc spatial query windows according to spatial predicates, avoiding the high cost of joining large tables. Therefore, mechanisms to provide efficient query processing over SDWs are essential. In this paper, we propose two efficient indices for SDW: the SB-index and the HSB-index. The proposed indices share the following characteristics. They enable multidimensional queries with spatial predicate for SDW and also support predefined spatial hierarchies. Furthermore, they compute the spatial predicate and transform it into a conventional one, which can be evaluated together with other conventional predicates by accessing a star-join Bitmap index. While the SB-index has a sequential data structure, the HSB-index uses a hierarchical data structure to enable spatial objects clustering and a specialized buffer-pool to decrease the number of disk accesses. The advantages of the SB-index and the HSB-index over the DBMS resources for SDW indexing (i.e. star-join computation and materialized views) were investigated through performance tests, which issued roll-up operations extended with containment and intersection range queries. The performance results showed that improvements ranged from 68% up to 99% over both the star-join computation and the materialized view. Furthermore, the proposed indices proved to be very compact, adding only less than 1% to the storage requirements. Therefore, both the SB-index and the HSB-index are excellent choices for SDW indexing. Choosing between the SB-index and the HSB-index mainly depends on the query selectivity of spatial predicates. While low query selectivity benefits the HSB-index, the SB-index provides better performance for higher query selectivity.

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The aim of this research was to evaluate economic costs of respiratory and circulatory diseases in the municipality of Cubatao, in the state of Sao Paulo, Brazil. Data on hospital admissions and on missed working days due to hospitalization (for age group 14 to 70 years old) from the database of Sistema Unico de Sa de (SUS - Brazilian National Health System) were used. Results: Based on these data, it was calculated that R$ 22.1 million were spent in the period 2000 to 2009 due to diseases of the respiratory and circulatory systems. Part of these expenses can be directly related to the emission of atmospheric pollutants in the city. In order to estimate the costs related to air pollution, data on Cubatao were compared to data from two other municipalities that are also located at the coast side (Guaruja and Peru be), but which have little industrial activity in comparison to Cubatao. It was verified that, in both, average per capita costs were lower when compared to Cubatao, but that this difference has been decreasing in recent years.

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OBJECTIVE: To identify clusters of the major occurrences of leprosy and their associated socioeconomic and demographic factors. METHODS: Cases of leprosy that occurred between 1998 and 2007 in Sao Jose do Rio Preto (southeastern Brazil) were geocodified and the incidence rates were calculated by census tract. A socioeconomic classification score was obtained using principal component analysis of socioeconomic variables. Thematic maps to visualize the spatial distribution of the incidence of leprosy with respect to socioeconomic levels and demographic density were constructed using geostatistics. RESULTS: While the incidence rate for the entire city was 10.4 cases per 100,000 inhabitants annually between 1998 and 2007, the incidence rates of individual census tracts were heterogeneous, with values that ranged from 0 to 26.9 cases per 100,000 inhabitants per year. Areas with a high leprosy incidence were associated with lower socioeconomic levels. There were identified clusters of leprosy cases, however there was no association between disease incidence and demographic density. There was a disparity between the places where the majority of ill people lived and the location of healthcare services. CONCLUSIONS: The spatial analysis techniques utilized identified the poorer neighborhoods of the city as the areas with the highest risk for the disease. These data show that health departments must prioritize politico-administrative policies to minimize the effects of social inequality and improve the standards of living, hygiene, and education of the population in order to reduce the incidence of leprosy.

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Texture image analysis is an important field of investigation that has attracted the attention from computer vision community in the last decades. In this paper, a novel approach for texture image analysis is proposed by using a combination of graph theory and partially self-avoiding deterministic walks. From the image, we build a regular graph where each vertex represents a pixel and it is connected to neighboring pixels (pixels whose spatial distance is less than a given radius). Transformations on the regular graph are applied to emphasize different image features. To characterize the transformed graphs, partially self-avoiding deterministic walks are performed to compose the feature vector. Experimental results on three databases indicate that the proposed method significantly improves correct classification rate compared to the state-of-the-art, e.g. from 89.37% (original tourist walk) to 94.32% on the Brodatz database, from 84.86% (Gabor filter) to 85.07% on the Vistex database and from 92.60% (original tourist walk) to 98.00% on the plant leaves database. In view of these results, it is expected that this method could provide good results in other applications such as texture synthesis and texture segmentation. (C) 2012 Elsevier Ltd. All rights reserved.

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Abstract Background The organization of the connectivity between mammalian cortical areas has become a major subject of study, because of its important role in scaffolding the macroscopic aspects of animal behavior and intelligence. In this study we present a computational reconstruction approach to the problem of network organization, by considering the topological and spatial features of each area in the primate cerebral cortex as subsidy for the reconstruction of the global cortical network connectivity. Starting with all areas being disconnected, pairs of areas with similar sets of features are linked together, in an attempt to recover the original network structure. Results Inferring primate cortical connectivity from the properties of the nodes, remarkably good reconstructions of the global network organization could be obtained, with the topological features allowing slightly superior accuracy to the spatial ones. Analogous reconstruction attempts for the C. elegans neuronal network resulted in substantially poorer recovery, indicating that cortical area interconnections are relatively stronger related to the considered topological and spatial properties than neuronal projections in the nematode. Conclusion The close relationship between area-based features and global connectivity may hint on developmental rules and constraints for cortical networks. Particularly, differences between the predictions from topological and spatial properties, together with the poorer recovery resulting from spatial properties, indicate that the organization of cortical networks is not entirely determined by spatial constraints.

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Abstract Background Recent medical and biological technology advances have stimulated the development of new testing systems that have been providing huge, varied amounts of molecular and clinical data. Growing data volumes pose significant challenges for information processing systems in research centers. Additionally, the routines of genomics laboratory are typically characterized by high parallelism in testing and constant procedure changes. Results This paper describes a formal approach to address this challenge through the implementation of a genetic testing management system applied to human genome laboratory. We introduced the Human Genome Research Center Information System (CEGH) in Brazil, a system that is able to support constant changes in human genome testing and can provide patients updated results based on the most recent and validated genetic knowledge. Our approach uses a common repository for process planning to ensure reusability, specification, instantiation, monitoring, and execution of processes, which are defined using a relational database and rigorous control flow specifications based on process algebra (ACP). The main difference between our approach and related works is that we were able to join two important aspects: 1) process scalability achieved through relational database implementation, and 2) correctness of processes using process algebra. Furthermore, the software allows end users to define genetic testing without requiring any knowledge about business process notation or process algebra. Conclusions This paper presents the CEGH information system that is a Laboratory Information Management System (LIMS) based on a formal framework to support genetic testing management for Mendelian disorder studies. We have proved the feasibility and showed usability benefits of a rigorous approach that is able to specify, validate, and perform genetic testing using easy end user interfaces.