62 resultados para Spatial pattern


Relevância:

60.00% 60.00%

Publicador:

Resumo:

A expansão da obesidade em diversos países do mundo na última década tem resultado no aumento da morbidade e mortalidade por hipertensão arterial e suas complicações. O objetivo deste trabalho é analisar a distribuição espacial da obesidade e hipertensão arterial no estado de São Paulo no período de 2000 a 2010, a partir de registros hospitalares e internação do Sistema de Informações Hospitalares do Sistema Único de Saúde (SIH - SUS). Foram utilizados coeficientes de prevalência das doenças em cada município suavizadas pelo método bayesiano empírico, permitindo uma visualização do padrão espacial dessas morbidades no Estado. Foi explorada a dependência espacial destes padrões verificando a autocorrelação entre os indicadores por meio do cálculo do Índice de Autocorrelação Espacial de Moran. Além disso, estudou-se a correlação positiva (Pearson) entre obesidade e hipertensão. Os dados e os mapas mostraram clusters de 87 municípios onde há maior e menor prevalência de hipertensão e obesidade no espaço com forte autocorrelação entre os municípios vizinhos. O coeficiente correlação de Pearson encontrado para esses municípios foi de 0,404 e sugere associação entre as morbidades. As técnicas de análise espacial mostraram-se úteis para o planejamento de ações de saúde pública.

Relevância:

60.00% 60.00%

Publicador:

Resumo:

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relevância:

60.00% 60.00%

Publicador:

Resumo:

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relevância:

60.00% 60.00%

Publicador:

Resumo:

The Amazon River floodplain is an important source of atmospheric CO2 and CH4. Aquatic herbaceous vegetation (macrophytes) have been shown to contribute significantly to floodplain net primary productivity (NPP) and methane emission in the region. Their fast growth rates under both flooded and dry conditions make herbaceous vegetation the most variable element in the Amazon floodplain NPP budget, and the most susceptible to environmental changes. The present study combines multitemporal Radarsat-1 and MODIS images to monitor spatial and temporal changes in herbaceous vegetation cover in the Amazon floodplain. Radarsat-1 images were acquired from Dec/2003 to Oct/2005, and MODIS daily surface reflectance products were acquired for the two cloud-free dates closest to each Radarsat-1 acquisition. An object-based, hierarchical algorithm was developed using the temporal SAR information to discriminate Permanent Open Water (OW), Floodplain (FP) and Upland (UL) classes at Level 1, and then subdivide the FP class into Woody Vegetation (WV) and Possible Macrophytes (PM) at Level 2. At Level 3, optical and SAR information were combined to discriminate actual herbaceous cover at each date. The resulting maps had accuracies ranging from 80% to 90% for Level 1 and 2 classifications, and from 60% to 70% for Level 3 classifications, with kappa values ranging between 0.7 and 0.9 for Levels 1 and 2 and between 0.5 and 0.6 for Level 3. All study sites had noticeable variations in the extent of herbaceous cover throughout the hydrological year, with maximum areas up to four times larger than minimum areas. The proposed classification method was able to capture the spatial pattern of macrophyte growth and development in the studied area, and the multitemporal information was essential for both separating vegetation cover types and assessing monthly variation in herbaceous cover extent.

Relevância:

60.00% 60.00%

Publicador:

Resumo:

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Relevância:

60.00% 60.00%

Publicador:

Resumo:

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

Relevância:

40.00% 40.00%

Publicador:

Resumo:

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Relevância:

40.00% 40.00%

Publicador:

Resumo:

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Relevância:

30.00% 30.00%

Publicador:

Resumo:

The bubble crab Dotilla fenestrata forms very dense populations on the sand flats of the eastern coast of Inhaca Island, Mozambique, making it an interesting biological model to examine spatial distribution patterns and test the relative efficiency of common sampling methods. Due to its apparent ecological importance within the sandy intertidal community, understanding the factors ruling the dynamics of Dotilla populations is also a key issue. In this study, different techniques of estimating crab density are described, and the trends of spatial distribution of the different population categories are shown. The studied populations are arranged in discrete patches located at the well-drained crests of nearly parallel mega sand ripples. For a given sample size, there was an obvious gain in precision by using a stratified random sampling technique, considering discrete patches as strata, compared to the simple random design. Density average and variance differed considerably among patches since juveniles and ovigerous females were found clumped, with higher densities at the lower and upper shore levels, respectively. Burrow counting was found to be an adequate method for large-scale sampling, although consistently underestimating actual crab density by nearly half. Regression analyses suggested that crabs smaller than 2.9 mm carapace width tend to be undetected in visual burrow counts. A visual survey of sampling plots over several patches of a large Dotilla population showed that crab density varied in an interesting oscillating pattern, apparently following the topography of the sand flat. Patches extending to the lower shore contained higher densities than those mostly covering the higher shore. Within-patch density variability also pointed to the same trend, but the density increment towards the lowest shore level varied greatly among the patches compared.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Background: Leptospirosis is an important zoonotic disease associated with poor areas of urban settings of developing countries and early diagnosis and prompt treatment may prevent disease. Although rodents are reportedly considered the main reservoirs of leptospirosis, dogs may develop the disease, may become asymptomatic carriers and may be used as sentinels for disease epidemiology. The use of Geographical Information Systems (GIS) combined with spatial analysis techniques allows the mapping of the disease and the identification and assessment of health risk factors. Besides the use of GIS and spatial analysis, the technique of data mining, decision tree, can provide a great potential to find a pattern in the behavior of the variables that determine the occurrence of leptospirosis. The objective of the present study was to apply Geographical Information Systems and data prospection (decision tree) to evaluate the risk factors for canine leptospirosis in an area of Curitiba, PR.Materials, Methods & Results: The present study was performed on the Vila Pantanal, a urban poor community in the city of Curitiba. A total of 287 dog blood samples were randomly obtained house-by-house in a two-day sampling on January 2010. In addition, a questionnaire was applied to owners at the time of sampling. Geographical coordinates related to each household of tested dog were obtained using a Global Positioning System (GPS) for mapping the spatial distribution of reagent and non-reagent dogs to leptospirosis. For the decision tree, risk factors included results of microagglutination test (MAT) from the serum of dogs, previous disease on the household, contact with rats or other dogs, dog breed, outdoors access, feeding, trash around house or backyard, open sewer proximity and flooding. A total of 189 samples (about 2/3 of overall samples) were randomly selected for the training file and consequent decision rules. The remained 98 samples were used for the testing file. The seroprevalence showed a pattern of spatial distribution that involved all the Pantanal area, without agglomeration of reagent animals. In relation to data mining, from 189 samples used in decision tree, a total of 165 (87.3%) animal samples were correctly classified, generating a Kappa index of 0.413. A total of 154 out of 159 (96.8%) samples were considered non-reagent and were correctly classified and only 5/159 (3.2%) were wrongly identified. on the other hand, only 11 (36.7%) reagent samples were correctly classified, with 19 (63.3%) samples failing diagnosis.Discussion: The spatial distribution that involved all the Pantanal area showed that all the animals in the area are at risk of contamination by Leptospira spp. Although most samples had been classified correctly by the decision tree, a degree of difficulty of separability related to seropositive animals was observed, with only 36.7% of the samples classified correctly. This can occur due to the fact of seronegative animals number is superior to the number of seropositive ones, taking the differences in the pattern of variable behavior. The data mining helped to evaluate the most important risk factors for leptospirosis in an urban poor community of Curitiba. The variables selected by decision tree reflected the important factors about the existence of the disease (default of sewer, presence of rats and rubbish and dogs with free access to street). The analyses showed the multifactorial character of the epidemiology of canine leptospirosis.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

The density and aggregation patterns of nests of a species of Nasutitermes were determined in an area of 12,750 m(2). We found 131 nests in this area, and the distribution pattern was regular, with a density equaling 102.74 nests per hectare. Nest volume was determined from the height and diameter of 105 nests and varied from 1.59 to 192.46 dm(3). of the colonies, 70.5% had a volume below the mean value: 51.4% of these had volumes lower than 9 dm(3). Regression between the mean volumes and the distance of the 2 nearest nests was positive and significant (P < 0.001), suggesting competition between colonies.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Biological control of Diatraea saccharalis is regarded as one of the best examples of successful classical biological control in Brazil. Since the introduction of the exotic parasitoid, Cotesia flavipes, from Pakistan at the beginning of the 1970s, decrease in D. saccharalis infestation in sugarcane fields has been attributed to the effectiveness of this agent. Recently, the native Tachinidae fly parasitoids (Lydella minense and Paratheresia claripalpis) have also been implicated in this success. However, quantitative data confirming the actual contribution of these agents to the control of D. saccharalis are rather limited. The purpose of this study was to investigate the dynamics of the interactions between D. saccharalis and its parasitoids, emphasizing the temporal patterns of parasitism. To investigate this question, a large data set comprising information collected from two sugarcane mills located in the state of São Paulo, Brazil (Barra and Sao Joao sugarcane mills), was analysed. Basically, the data set contained monthly information about the number of D. saccharalis larvae and their parasitoids in each sample (man-hour per sample), the sugarcane varieties cultivated, the age of the sugarcane plants (only at the Sao Joao sugarcane mill) as well as the sugarcane cut at sampling time. The data were collected from March 1984 to March 1997 and from May 1982 to December 1996 for the Barra and Sao Joao sugarcane mills, respectively. Temporal inverse density-dependent parasitism was predominant for both parasitoid species with respect to all spatial scales. Although the temporal pattern of parasitism was not directly density dependent, it was evident that the tachinids and C. flavipes presented positive numerical responses according to variations in D. saccharalis densities through time.