908 resultados para Informal inference
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The objective of this experiment was to test in vitro embryo production (IVP) as a tool to estimate fertility performance in zebu bulls using Bayesian inference statistics. Oocytes were matured and fertilized in vitro using sperm cells from three different Zebu bulls (V, T, and G). The three bulls presented similar results with regard to pronuclear formation and blastocyst formation rates. However, the cleavage rates were different between bulls. The estimated conception rates based on combined data of cleavage and blastocyst formation were very similar to the true conception rates observed for the same bulls after a fixed-time artificial insemination program. Moreover, even when we used cleavage rate data only or blastocyst formation data only, the estimated conception rates were still close to the true conception rates. We conclude that Bayesian inference is an effective statistical procedure to estimate in vivo bull fertility using data from IVP. © 2011 Mateus José Sudano et al.
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The system reliability depends on the reliability of its components itself. Therefore, it is necessary a methodology capable of inferring the state of functionality of these components to establish reliable indices of quality. Allocation models for maintenance and protective devices, among others, have been used in order to improve the quality and availability of services on electric power distribution systems. This paper proposes a methodology for assessing the reliability of distribution system components in an integrated way, using probabilistic models and fuzzy inference systems to infer about the operation probability of each component. © 2012 IEEE.
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Considering the importance of monitoring the water quality parameters, remote sensing is a practicable alternative to limnological variables detection, which interacts with electromagnetic radiation, called optically active components (OAC). Among these, the phytoplankton pigment chlorophyll a is the most representative pigment of photosynthetic activity in all classes of algae. In this sense, this work aims to develop a method of spatial inference of chlorophyll a concentration using Artificial Neural Networks (ANN). To achieve this purpose, a multispectral image and fluorometric measurements were used as input data. The multispectral image was processed and the net training and validation dataset were carefully chosen. From this, the neural net architecture and its parameters were defined to model the variable of interest. In the end of training phase, the trained network was applied to the image and a qualitative analysis was done. Thus, it was noticed that the integration of fluorometric and multispectral data provided good results in the chlorophyll a inference, when combined in a structure of artificial neural networks.
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Background: Mycobacterium spp. is one of the most important species of zoonotic pathogens that can be transmitted from cattle to humans. The presence of these opportunistic, pathogenic bacteria in bovine milk has emerged as a public-health concern, especially among individuals who consume raw milk and related dairy products. To address this concern, the Brazilian control and eradication program focusing on bovine tuberculosis, was established in 2001. However, bovine tuberculosis continues to afflict approximately 1,3 percent of the cattle in Brazil. In the present study, 300 samples of milk from bovine herds, obtained from both individual and collective bulk tanks and informal points of sale, were cultured on Löwenstein-Jensen and Stonebrink media. Polymerase chain reaction (PCR)-based tests and restriction-enzyme pattern analysis were then performed on the colonies exhibiting phenotypes suggestive of Mycobacterium spp., which were characterized as acid-fast bacilli.Results: Of the 300 bovine milk samples that were processed, 24 were positively identified as Mycobacterium spp.Molecular identification detected 15 unique mycobacterial species: Mycobacterium bovis, M. gordonae, M. fortuitum, M. intracellulare, M. flavescens, M. duvalii, M. haemophilum, M. immunogenum, M. lentiflavum, M. mucogenicum, M. novocastrense, M. parafortuitum, M. smegmatis, M. terrae and M. vaccae. The isolation of bacteria from the various locations occurred in the following proportions: 9 percent of the individual bulk-tank samples, 7 percent of the collective bulk-tank samples and 8 percent of the informal-trade samples. No statistically significant difference was observed between the presence of Mycobacterium spp. in the three types of samples collected, the milk production profiles, the presence of veterinary assistance and the reported concerns about bovine tuberculosis prevention in the herds.Conclusion: The microbiological cultures associated with PCR-based identification tests are possible tools for the investigation of the presence of Mycobacterium spp. in milk samples. Using these methods, we found that the Brazilian population may be regularly exposed to mycobacteria by consuming raw bovine milk and related dairy products. These evidences reinforces the need to optimize quality programs of dairy products, to intensify the sanitary inspection of these products and the necessity of further studies on the presence of Mycobacterium spp. in milk and milk-based products. © 2013 Franco et al.; licensee BioMed Central Ltd.
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