Screening Botryosphaeria species for lipases: Production of lipase by Botryosphaeria ribis EC-01 grown on soybean oil and other carbon sources

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Evidence of ecotypic differentiation between populations of the tree species Parapiptadenia rigida due to flooding

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Migration of Tinuvin P, a UV stabilizer, from PET bottles into fatty-food simulants

Tinuvin P migration from Polyethyleneterephthalate (PET) bottles was investigated using several fatty-food simulants such as olive oil, soybean oil, n-heptane and iso-octane, at exposure conditions of 2-10 days at 40 degrees C (total immersion). The stability of several UV stabilizers (BHT, Cyasorb UV 5411, Tinuvin P, Tinuvin 326 and Tinuvin 327) in n-heptane and iso-octane was also studied. After 10 days at 40 degrees C, losses of 6% and 20% in iso-octane and n-heptane respectively, were verified for Tinuvin P. Other UV stabilizers at the same experimental conditions showed higher losses (up to 30% for Tinuvin 327). These results confirm that, when carrying out specific migration studies, the stability of the substance of interest should be established in the food simulant to avoid underestimating the real migration behaviour. In order to quantify UV stabilizer migration, n-heptane and iso-octane solutions were concentrated and directly analysed by SIM mode GC-MS. For olive and soybean oils, Tinuvin P was isolated using size-exclusion chromatography and quantified by SIM mode GC-MS. Iso-octane proved to be a move suitable fatty-food simulant than n-heptane for the migration study of Tinuvin P from PET. Higher levels of Tinuvin P migrated to olive and soybean oils rather than to n-heptane. These results suggest that the MERCOSUL recommended official methods for specific migration studies should be revised since the migration levels using n-heptane as a fatty-food simulant could be underestimated when compared to edible oils. Copyright (C) 1999 John Wiley & Sons, Ltd.

Anticandidal Efficacy of Cinnamon Oil Against Planktonic and Biofilm Cultures of Candida parapsilosis and Candida orthopsilosis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Pothomorphe umbellata: Antifungal activity against strains of Trichophyton rubrum

Trichophyton rubrum is a dermatophyte, which can cause infections in human skin, hair and nail. Pothomorphe umbellata (L.) Miq. (Piperaceae) is a native Brazilian plant, in which phytochemical studies have demonstrated the presence of steroids, 4-nerolidylcatechol, sesquiterpenes and essential oils. The objective of this study was to analyze the in vitro activity of extracts and fractions of P. umbellata on resistant strains of T. rubrum. The microdilution plate method was utilized to test Tr1, H6 and Delta TruMDR2 strains of T rubrum; Delta TruMDR2 strain was obtained from H6 by TruMDR2 gene rupture, which is involved in multiple drugs resistance. The highest antifungal activity to all strains was observed for dichloromethane and hexane fractions of the 70% ethanolic extract which showed minimal inhibitory concentration (MIC) and minimal fungicide concentration (MFC) of 78.13 mu g/mL. This antifungal activity was also obtained by 70% ethanolic extract, which presented MIC and MFC of 78.13 mu g/mL to Delta TruMDR2, whereas the MIC values for Tr1 and H6 were 78.13 and 156.25 mu g/mL, respectively. Our results suggest the potential for future development of new antifungal drugs from P umbellata, especially to strains presenting multiple resistance. (C) 2012 Elsevier Masson SAS. All rights reserved.

Atividade antibacteriana do óleo essencial de Melampodium divaricatum (Rich.) DC., Asteraceae

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

An Intelligent System for Petroleum Well Drilling Cutting Analysis

Cutting analysis is a important and crucial task task to detect and prevent problems during the petroleum well drilling process. Several studies have been developed for drilling inspection, but none of them takes care about analysing the generated cutting at the vibrating shale shakers. Here we proposed a system to analyse the cutting's concentration at the vibrating shale shakers, which can indicate problems during the petroleum well drilling process, such that the collapse of the well borehole walls. Cutting's images are acquired and sent to the data analysis module, which has as the main goal to extract features and to classify frames according to one of three previously classes of cutting's volume. A collection of supervised classifiers were applied in order to allow comparisons about their accuracy and efficiency. We used the Optimum-Path Forest (OPF), Artificial Neural Network using Multi layer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC) for this task. The first one outperformed all the remaining classifiers. Recall that we are also the first to introduce the OPF classifier in this field of knowledge. Very good results show the robustness of the proposed system, which can be also integrated with other commonly system (Mud-Logging) in order to improve the last one's efficiency.

Quantificação do linalol no óleo essencial da Aniba duckei Korstermans utilizando uma nova coluna capilar POLYH4-MD em Cromatografia Gasosa

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

Hydrogen production utilizing glycerol from renewable feedstocks-The case of Brazil

Various reports concerning catalytic reaction of glycerol for hydrogen production is available. However, economic analyses of this activity are not found yet. The objective of this work is to evaluate the process of hydrogen production via steam reforming of glycerol obtained through transesterification process of bio-oils. The thermochemical process of steam reforming process was determined due to high efficiency, feasibility and lower cost of design, development, operation and maintenance. These bio-oils come from feedstocks largely encountered in Brazil such as soybean, palm, castor bean, peanut and cotton seed as also come from residues such as defective coffee, tallow beef, wastewater (scum) and others. Various findings were obtained such as potential of production of glycerol utilizing residues (considering available amounts in the Brazilian states) and some vegetable feedstocks (considering production of harvested feedstock per hectare). Subsequently, production of hydrogen via steam reforming of generated glycerol, and foreseen electricity production via fuel cells were also determined. An additional estimation was paid for production of H-BIO, an innovative fuel developed by PETROBRAS (Petroleo Brasileiro S.A.), where hydrogen and bio-fuel are utilized and generates propane as co-product. About this work, it was concluded that high amounts of hydrogen and electricity could be produced considering an enormous potential from each cited feedstock being an attractive alternative as distributed electricity source and as an additional source for some activities, inclusively those that produce their own feedstocks such as abattoirs (beef tallow), and wastewater treatment plants. (C) 2010 Elsevier Ltd. All rights reserved.

Viscosity measuring cell using ultrasonic wave mode conversion

This work presents a cell to measure dynamic viscosity of liquids using ultrasonic wave mode conversion from longitudinal to shear wave. The strategy used to obtain the viscosity is based on the measurement of the complex reflection coefficient of shear waves at a solid-liquid interface. Viscosity measurements of automotive oils (SAE90 and SAE140) were obtained in the frequency range from 1 to 10 MHz. These results are compared with the Maxwell model with two relaxation times, showing the dependency of viscosity with frequency. Several parameters affecting viscosity measurements, including the solid material properties, liquid viscosity, and operating frequency are discussed.

Viscosity measurement of Newtonian liquids using the complex reflection coefficient

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

Identification of lubricant contamination by biodiesel using vibration analysis and neural network

Purpose - The purpose of this paper is to provide information on lubricant contamination by biodiesel using vibration and neural network.Design/methodology/approach - The possible contamination of lubricants is verified by analyzing the vibration and neural network of a bench test under determinated conditions.Findings - Results have shown that classical signal analysis methods could not reveal any correlation between the signal and the presence of contamination, or contamination grade. on other hand, the use of probabilistic neural network (PNN) was very successful in the identification and classification of contamination and its grade.Research limitations/implications - This study was done for some specific kinds of biodiesel. Other types of biodiesel could be analyzed.Practical implications Contamination information is presented in the vibration signal, even if it is not evident by classical vibration analysis. In addition, the use of PNN gives a relatively simple and easy-to-use detection tool with good confidence. The training process is fast, and allows implementation of an adaptive training algorithm.Originality/value - This research could be extended to an internal combustion engine in order to verify a possible contamination by biodiesel.