23 resultados para Bodies of specific vehicles.


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

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

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PURPOSE:To assess whether late introduction of a specific COX-2 inhibitor (Meloxicam) can treat and/or prevent the progression of tumors in the stomach of rats submitted to duodenogastric reflux. METHODS: Seventy five male Wistar rats, weighing 150 grams, were submitted to the induction of duodenogastric reflux through the pylorus. At 36 weeks of follow-up were established three experimental groups: DGR36 sacrificed immediately, DGR54 and DGR54MLX both sacrificed at 54th week of follow-up . The animals of the latter group were fed with a rat chow premixed with Meloxicam (2.0 mg/ kg feed; 0.3 mg / kg bw / day) and the other two with standard rat chow. The lesions found in the pyloric mucosa and gastrojejunal anastomosis were analyzed macroscopically and histologically. For statistical analysis was adjusted a generalized linear model assuming a binomial distribution with LOGIT link function. RESULTS: No significant differences were found when comparing the incidences of benign tumor lesions (Adenomatous Hyperplasia), p=0.4915, or malignant (Mucinous Adenocarcinoma), p=0.2731, among groups. CONCLUSION: Late introduction of specific COX-2 inhibitor (Meloxicam) did not treat and was not able to prevent the progression of tumoral lesions induced by duodenogastric reflux in the rat stomachs.

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The accurate determination of thermophysical properties of milk is very important for design, simulation, optimization, and control of food processing such as evaporation, heat exchanging, spray drying, and so forth. Generally, polynomial methods are used for prediction of these properties based on empirical correlation to experimental data. Artificial neural networks are better Suited for processing noisy and extensive knowledge indexing. This article proposed the application of neural networks for prediction of specific heat, thermal conductivity, and density of milk with temperature ranged from 2.0 to 71.0degreesC, 72.0 to 92.0% of water content (w/w), and 1.350 to 7.822% of fat content (w/w). Artificial neural networks presented a better prediction capability of specific heat, thermal conductivity, and density of milk than polynomial modeling. It showed a reasonable alternative to empirical modeling for thermophysical properties of foods.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The fuel consumption is an important factor in the vehicle development due the fact that it has a direct effect on its trade aims. Besides that, it is known that the petrol is a scarce fuel. In this paper it is presented a procedure of fuel consumption calculation for a vehicle traveling in driving schedule. In such calculation it has been taken into account the operational conditions (load, pavement, climbing road, among others) and the building characteristics (map engine, transmission, frontal area, tire, among others) of road vehicles. There has also been an application of the theoretical model developed in a sample Mercedes-Benz do Brasil vehicle which has been compared with the values of experimental tests. Copyright © 1997 Society of Automotive Engineers, Inc.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)