Soil sampling intensity and spatial distribution pattern of soils attributes and corn yield in no-tillage system

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

Lead distribution in organic matter of loamy oxisol treated with manure and its effect on microbial biomass

This paper reports a study regarding the distribution of lead in the organic matter fractions of a loamy oxisol treated with stable manure, and its effect on the soil microbial biomass. The experimental design was a completely randomized factorial with three replicates. Treatments were four lead (Pb) rates (0, 200, 400, and 600 mg kg(-1) soil), two levels of manure (0 and 30 Mg ha(-1)) and two sampling times (30 and 60 days after lead application). Total and soil lead soluble in Mehlich 1 extractant, and Ph in the different fractions of the organic matter (fulvic acid, humic acid, and residual) were evaluated along with the soil microbial biomass. Data showed that lead, applied as PbCl2, was concentrated in the residual fraction. The application of manure at the rate of 30 Mg ha(-1) did not affect lead distribution in the fractions until 60 days after incorporation. Lead extracted by Mehlich 1 increased as function of the quantity applied. Manure stimulated the growth of the soil microbial biomass which was reduced by the 200 mg kg(-1) doses of lead, with manure application, increasing, however, with larger rates. Mehlich 1 extracted only part of the lead present in the residual fraction.

Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUÇÃO: A malaria é uma doença endêmica na região da Amazônia Brasileira, e a detecção de possíveis fatores de risco pode ser de grande interesse às autoridades em saúde pública. O objetivo deste artigo é investigar a associação entre variáveis ambientais e os registros anuais de malária na região amazônica usando métodos bayesianos espaço-temporais. MÉTODOS: Utilizaram-se modelos de regressão espaço-temporais de Poisson para analisar os dados anuais de contagem de casos de malária entre os anos de 1999 a 2008, considerando a presença de alguns fatores como a taxa de desflorestamento. em uma abordagem bayesiana, as inferências foram obtidas por métodos Monte Carlo em cadeias de Markov (MCMC) que simularam amostras para a distribuição conjunta a posteriori de interesse. A discriminação de diferentes modelos também foi discutida. RESULTADOS: O modelo aqui proposto sugeriu que a taxa de desflorestamento, o número de habitants por km² e o índice de desenvolvimento humano (IDH) são importantes para a predição de casos de malária. CONCLUSÕES: É possível concluir que o desenvolvimento humano, o crescimento populacional, o desflorestamento e as alterações ecológicas associadas a estes fatores estão associados ao aumento do risco de malária. Pode-se ainda concluir que o uso de modelos de regressão de Poisson que capturam o efeito temporal e espacial em um enfoque bayesiano é uma boa estratégia para modelar dados de contagem de malária.

Insulin and glucose sensitivity, insulin secretion and beta-cell distribution in endocrine pancreas of the fruit bat Artibeus lituratus

The fruit bat Artibeus lituratus absorbs large amounts of glucose in short periods of time and maintains normoglycemia even after a prolonged starvation period. Based on these data, we aimed to investigate various aspects related with glucose homeostasis analyzing: blood glucose and insulin levels, intraperitoneal glucose and insulin tolerance tests (ipGTT and ipITT), glucose-stimulated insulin secretion (2.8, 5.6 or 8.3 mmol/L glucose) in pancreas fragments, cellular distribution of beta cells, and the amount of pAkt/Akt in the pectoral muscle and liver. Blood glucose levels were higher in fed bats (6.88 +/- 0.5 mmol/L) than fasted bats (4.0 +/- 0.8 mmol/L), whereas insulin levels were similar in both conditions. The values of the area-under-the curve obtained from ipGTT were significantly higher when bats received 2 (5.5-fold) or 3 g/kg glucose (7.5-fold) b.w compared to control (saline). These bats also exhibited a significant decrease of blood glucose values after insulin administration during the iplTT. Insulin secretion from fragments of pancreas under physiological concentrations of glucose (5.6 or 8.3 mmol/L) was similar but higher than in 2.8 mmol/L glucose 1.8- and 2.0-fold, respectively. These bats showed a marked beta-cell distribution along the pancreas, and the pancreatic beta cells are not exclusively located at the central part of the islet. The insulin-induced Akt phosphorylation was more pronounced in the pectoral muscle, compared to liver. The high sensitivity to glucose and insulin, the proper insulin response to glucose, and the presence of an apparent large beta-cell population could represent benefits for the management of high influx of glucose from a carbohydrate-rich meal, which permits appropriate glucose utilization. (C) 2010 Elsevier B.V. All rights reserved.

Detection and Identification of Abnormalities in Customer Consumptions in Power Distribution Systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Power flow for primary distribution networks considering uncertainty in demand and user connection

This paper presents a method for calculating the power flow in distribution networks considering uncertainties in the distribution system. Active and reactive power are used as uncertain variables and probabilistically modeled through probability distribution functions. Uncertainty about the connection of the users with the different feeders is also considered. A Monte Carlo simulation is used to generate the possible load scenarios of the users. The results of the power flow considering uncertainty are the mean values and standard deviations of the variables of interest (voltages in all nodes, active and reactive power flows, etc.), giving the user valuable information about how the network will behave under uncertainty rather than the traditional fixed values at one point in time. The method is tested using real data from a primary feeder system, and results are presented considering uncertainty in demand and also in the connection. To demonstrate the usefulness of the approach, the results are then used in a probabilistic risk analysis to identify potential problems of undervoltage in distribution systems. (C) 2012 Elsevier Ltd. All rights reserved.

Strategic capacitor placement in distribution systems by minimisation of harmonics amplification because of resonance

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

Scintigraphic validation of AC Biosusceptometry to study the gastric motor activity and the intragastric distribution of food in humans

Abnormal intragastric distribution of food (IDF) and a phasic contractility in the proximal stomach have been related to dyspeptic symptoms. Thus, the behaviour of the stomach and the proximal region, in particular, continues to attract attention and demand for reliable and comfortable techniques. The aims of this study were to employ AC Biosus-ceptometry (ACB) and scintigraphy to evaluate IDF and gastric motor activity in humans. Fifteen healthy volunteers ingested 60 mL of yogurt containing 2 mCi of Tc-99m and 4 g of ferrite. Each volunteer had gastric motility and IDF evaluated twice on separate days; on one occasion by ACB and another by scintigraphy. Digital signal processing was performed in MatLab (Mathworks Inc., Natick, MA, USA). Results were expressed as mean +/- SD. Similar results of distal accumulation time (P < 0.001) were obtained for scintigraphy (6.93 +/- 3.25 min) and for ACB (7.04 +/- 3.65 min). Fast Fourier Transform revealed two dominant frequencies (P > 0.9). Besides the well-know frequency of 3 cpm, our results showed identical frequencies in proximal stomach recordings (P < 0.001) for scintigraphic (1.01 +/- 0.01 cpm) and ACB (0.98 +/- 0.06 cpm). In summary, our data showed that scintigraphy and ACB are promising techniques to evaluate several aspects of gastric motility. Moreover, ACB is non-invasive, radiation-free and deserves the same importance as conventional methods for this kind of analysis.

Geographical Distribution and Demographic Characteristics of Gestational Trophoblastic Disease

OBJECTIVE: To outline the geographical distribution pattern of gestational trophoblastic disease (GTD) in a referral center in Bahia, Brazil, and determine the demographics of the disease.STUDY DESIGN: We conducted a study of data retrieved from medical records of 140 GTD patients referred to our Trophoblastic Diseases Center in 2002-2007, assessing geographical distribution across health care districts, demographics, referral sources, and previous pregnancy status.RESULTS: The most common GTD types were hydatidiform mole (106, 75.7%), invasive mole (32, 22.9%), choriocarcinoma (1, 0.7%), and placental site trophoblastic tumor (1, 0.7%). GTD incidence was 8.5 in 1,000 deliveries. Most patients originated from the coastal region (East district), which includes the state capital (77.9%). The 20-34 age group predominated (65%). Education level (67.9% attended elementary school only) and employment rate (42.9%) were low. Secondary hospitals were the principal source of referral (84.3%), followed by self-referrals (15.7%). Regarding previous pregnancy status, 42.1% (n = 59) had had term pregnancy, 39.3% (n = 55) no pregnancy, 15% (n = 21) miscarriage, and 0.7% (n = 1) ectopic pregnancy; 4 patients (2.9%) had previous hydatidiform mole.CONCLUSION: GTD predominated in the peak fertility age group and among patients of unfavorable sociodemographic status. (J Reprod Med 2010;55:305-310)

Spatial distribution of trachoma cases in the City of Bauru, State of São Paulo, Brazil, detected in 2006: defining key areas for improvement of health resources

Introduction: The objective of this study was to analyze the spatial behavior of the occurrence of trachoma cases detected in the City of Bauru, State of São Paulo, Brazil, in 2006 in order to use the information collected to set priority areas for optimization of health resources. Methods: the trachoma cases identified in 2006 were georeferenced. The data evaluated were: schools where the trachoma cases studied, data from the 2000 Census, census tract, type of housing, water supply conditions, distribution of income and levels of education of household heads. In the Google Earth® software and TerraView® were made descriptive spatial analysis and estimates of the Kernel. Each area was studied by interpolation of the density surfaces exposing events to facilitate to recognize the clusters. Results: of the 66 cases detected, only one (1.5%) was not a resident of the city's outskirts. A positive association was detected of trachoma cases and the percentage of heads of household with income below three minimum wages and schooling under eight years of education. Conclusions: The recognition of the spatial distribution of trachoma cases coincided with the areas of greatest social inequality in Bauru City. The micro-areas identified are those that should be prioritized in the rationalization of health resources. There is the possibility of using the trachoma cases detected as an indicator of performance of micro priority health programs.

Spatial Distribution of Seropositive Dogs to Leptospira spp. and Evaluation of Leptospirosis Risk Factors Using a Decision Tree

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.

Immunocytochemical characterization of the pregeniculate nucleus and distribution of retinal and neuropeptide Y terminals in the suprachiasmatic nucleus of the Cebus monkey

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

Mechanical behavior of ceramic veneer in zirconia-based restorations: a 3-dimensional finite element analysis using microcomputed tomography data

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

Tests of proportional hazards and proportional odds models for grouped survival data

In this paper, we derive score test statistics to discriminate between proportional hazards and proportional odds models for grouped survival data. These models are embedded within a power family transformation in order to obtain the score tests. In simple cases, some small-sample results are obtained for the score statistics using Monte Carlo simulations. Score statistics have distributions well approximated by the chi-squared distribution. Real examples illustrate the proposed tests.

Choosing between Cox proportional hazards and logistic models for interval-censored data via bootstrap

This work develops a new methodology in order to discriminate models for interval-censored data based on bootstrap residual simulation by observing the deviance difference from one model in relation to another, according to Hinde (1992). Generally, this sort of data can generate a large number of tied observations and, in this case, survival time can be regarded as discrete. Therefore, the Cox proportional hazards model for grouped data (Prentice & Gloeckler, 1978) and the logistic model (Lawless, 1982) can befitted by means of generalized linear models. Whitehead (1989) considered censoring to be an indicative variable with a binomial distribution and fitted the Cox proportional hazards model using complementary log-log as a link function. In addition, a logistic model can be fitted using logit as a link function. The proposed methodology arises as an alternative to the score tests developed by Colosimo et al. (2000), where such models can be obtained for discrete binary data as particular cases from the Aranda-Ordaz distribution asymmetric family. These tests are thus developed with a basis on link functions to generate such a fit. The example that motivates this study was the dataset from an experiment carried out on a flax cultivar planted on four substrata susceptible to the pathogen Fusarium oxysoprum. The response variable, which is the time until blighting, was observed in intervals during 52 days. The results were compared with the model fit and the AIC values.