CHARACTERIZATION STUDY OF CAMBUCI FRUIT [Campomanesia phaea (O. Berg.) Landrum] AND ITS APPLICATION IN JELLY PROCESSING

CHARACTERIZATION STUDY OF CAMBUCI FRUIT [Campomanesia phaea (O. Berg.) Landrum] AND ITS APPLICATION IN JELLY PROCESSING The objective of this paper was to study possible differences of varieties of cambuci fruit reported by producers by means of fruit characterization and elaboration of jelly. The fruits were divided in four possible varieties groups, named as A, B, C and D, and submitted to analysis regarding weight, ash, moisture, pH, soluble solids, acidity, ratio, ascorbic acid and water activity. To the preparation of the jelly was chosen the variety A with two formulations, 50%50% and 40%60%, fruit and sugar respectively. Concerning the possible varieties of cambuci only water activity was not significantly different. The acidity and ratio of B variety are noteworthy, because it did differ from the others presenting a more satisfactory result for in natura consumption. All other tests presented statistic alteration of at least one variety, but since these data can be influenced by edaphoclimatic conditions they must be carefully observed. Lower results for pH, acidity, luminosity and degrees hue, were observed for the 60% sugar jelly sample, which contributed for its better results in the preference test for the attributes appearance, color, flavor and texture. The evaluation of attribute aroma of both samples (50% and 60%) did not differ.

AN EFFICIENT HPLC-UV METHOD FOR THE QUANTITATIVE DETERMINATION OF CEFADROXIL IN HUMAN PLASMA AND ITS APPLICATION IN PHARMACOKINETIC STUDIES

Cefadroxil is a semi-synthetic first-generation oral cephalosporin used in the treatment of mild to moderate infections of the respiratory and urinary tracts, skin and soft tissue infections. In this work a simple, rapid, economic and sensitive HPLC-UV method is described for the quantitative determination of cefadroxil in human plasma samples using lamivudine as internal standard. Sample pre-treatment was accomplished through protein precipitation with acetonitrile and chromatographic separation was performed with a mobile phase consisting of a mixture of sodium dihydrogen phosphate monohydrate solution, methanol and acetonitrile in the ratio of 90:8:2 (v/v/v) at a flow rate of 1.0mL/min. The proposed method is linear between 0.4 to 40.0 mu g/mL and its average recovery is 102.21% for cefadroxil and 97.94% for lamivudine. The method is simple, sensitive, reproducible, less time consuming for determination of cefadroxil in human plasma. The method can therefore be recommended for pharmacokinetics studies, including bioavailability and bioequivalence studies.

New Improved Version of J 1 ...J 4 Interferometry Method and its Application to Nanometric Vibration Measurements

Piezoelectric ceramics, such as PZT, can generate subnanometric displacements, bu t in order to generate multi- micrometric displacements, they should be either driven by high electric voltages (hundreds of volts ), or operate at a mechanical resonant frequency (in narrow band), or have large dimensions (tens of centimeters). A piezoelectric flextensional actuator (PFA) is a device with small dimensions that can be driven by reduced voltages and can operate in the nano- and micro scales. Interferometric techniques are very adequate for the characterization of these devices, because there is no mechanical contact in the measurement process, and it has high sensitivity, bandwidth and dynamic range. A low cost open-loop homodyne Michelson interferometer is utilized in this work to experimentally detect the nanovi brations of PFAs, based on the spectral analysis of the interfero metric signal. By employing the well known J 1 ...J 4 phase demodulation method, a new and improved version is proposed, which presents the following characteristics: is direct, self-consistent, is immune to fading, and does not present phase ambiguity problems. The proposed method has resolution that is similar to the modified J 1 ...J 4 method (0.18 rad); however, differently from the former, its dynamic range is 20% larger, does not demand Bessel functions algebraic sign correction algorithms and there are no singularities when the static phase shift between the interferometer arms is equal to an integer multiple of  /2 rad. Electronic noise and random phase drifts due to ambient perturbations are taken into account in the analysis of the method. The PFA nanopositioner characterization was based on the analysis of linearity betw een the applied voltage and the resulting displacement, on the displacement frequency response and determination of main resonance frequencies.

On the Limit of Frequency of Electrochemical Oscillators and Its Relationship to Kinetic Parameters

The class of electrochemical oscillators characterized by a partially hidden negative differential resistance in an N-shaped current potential curve encompasses a myriad of experimental examples. We present a comprehensive methodological analysis of the oscillation frequency of this class of systems and discuss its dependence on electrical and kinetic parameters. The analysis is developed from a skeleton ordinary differential equation model, and an equation for the oscillation frequency is obtained. Simulations are carried out for a model system, namely, the nickel electrodissolution, and the numerical results are confirmed by experimental data on this system. In addition, the treatment is further applied to the electro-oxidation of ethylene glycol where unusually large oscillation frequencies have been reported. Despite the distinct chemistry underlying the oscillatory dynamics of these systems, a very good agreement between experiments and theoretical predictions is observed. The application of the developed theory is suggested as an important step for primary kinetic characterization.

Bivariate gamma-geometric law and its induced Levy process

In this article we introduce a three-parameter extension of the bivariate exponential-geometric (BEG) law (Kozubowski and Panorska, 2005) [4]. We refer to this new distribution as the bivariate gamma-geometric (BGG) law. A bivariate random vector (X, N) follows the BGG law if N has geometric distribution and X may be represented (in law) as a sum of N independent and identically distributed gamma variables, where these variables are independent of N. Statistical properties such as moment generation and characteristic functions, moments and a variance-covariance matrix are provided. The marginal and conditional laws are also studied. We show that BBG distribution is infinitely divisible, just as the BEG model is. Further, we provide alternative representations for the BGG distribution and show that it enjoys a geometric stability property. Maximum likelihood estimation and inference are discussed and a reparametrization is proposed in order to obtain orthogonality of the parameters. We present an application to a real data set where our model provides a better fit than the BEG model. Our bivariate distribution induces a bivariate Levy process with correlated gamma and negative binomial processes, which extends the bivariate Levy motion proposed by Kozubowski et al. (2008) [6]. The marginals of our Levy motion are a mixture of gamma and negative binomial processes and we named it BMixGNB motion. Basic properties such as stochastic self-similarity and the covariance matrix of the process are presented. The bivariate distribution at fixed time of our BMixGNB process is also studied and some results are derived, including a discussion about maximum likelihood estimation and inference. (C) 2012 Elsevier Inc. All rights reserved.

Determination of trace elements in bovine semen samples by inductively coupled plasma mass spectrometry and data mining techniques for identification of bovine class

The reproductive performance of cattle may be influenced by several factors, but mineral imbalances are crucial in terms of direct effects on reproduction. Several studies have shown that elements such as calcium, copper, iron, magnesium, selenium, and zinc are essential for reproduction and can prevent oxidative stress. However, toxic elements such as lead, nickel, and arsenic can have adverse effects on reproduction. In this paper, we applied a simple and fast method of multi-element analysis to bovine semen samples from Zebu and European classes used in reproduction programs and artificial insemination. Samples were analyzed by inductively coupled plasma spectrometry (ICP-MS) using aqueous medium calibration and the samples were diluted in a proportion of 1:50 in a solution containing 0.01% (vol/vol) Triton X-100 and 0.5% (vol/vol) nitric acid. Rhodium, iridium, and yttrium were used as the internal standards for ICP-MS analysis. To develop a reliable method of tracing the class of bovine semen, we used data mining techniques that make it possible to classify unknown samples after checking the differentiation of known-class samples. Based on the determination of 15 elements in 41 samples of bovine semen, 3 machine-learning tools for classification were applied to determine cattle class. Our results demonstrate the potential of support vector machine (SVM), multilayer perceptron (MLP), and random forest (RF) chemometric tools to identify cattle class. Moreover, the selection tools made it possible to reduce the number of chemical elements needed from 15 to just 8.

Multi-element determination in Brazilian honey samples by inductively coupled plasma mass spectrometry and estimation of geographic origin with data mining techniques

Multi-element analysis of honey samples was carried out with the aim of developing a reliable method of tracing the origin of honey. Forty-two chemical elements were determined (Al, Cu, Pb, Zn, Mn, Cd, Tl, Co, Ni, Rb, Ba, Be, Bi, U, V, Fe, Pt, Pd, Te, Hf, Mo, Sn, Sb, P, La, Mg, I, Sm, Tb, Dy, Sd, Th, Pr, Nd, Tm, Yb, Lu, Gd, Ho, Er, Ce, Cr) by inductively coupled plasma mass spectrometry (ICP-MS). Then, three machine learning tools for classification and two for attribute selection were applied in order to prove that it is possible to use data mining tools to find the region where honey originated. Our results clearly demonstrate the potential of Support Vector Machine (SVM), Multilayer Perceptron (MLP) and Random Forest (RF) chemometric tools for honey origin identification. Moreover, the selection tools allowed a reduction from 42 trace element concentrations to only 5. (C) 2012 Elsevier Ltd. All rights reserved.

Preliminary Characterization of Novel Extra-cellular Lipase from Penicillium crustosum Under Solid-State Fermentation and its Potential Application for Triglycerides Hydrolysis

Current studies about lipase production involve the use of agro-industrial residues and newly isolated microorganisms aimed at increasing economic attractiveness of the process. Based on these aspects, the main objective of this work is to perform the partial characterization of enzymatic extracts produced by a newly isolated Penicillium crustosum in solid-state fermentation. Lipase extract presented optimal temperature and pH of 37 A degrees C and 9-10, respectively. The concentrated enzymatic extract showed more stability at 25 A degrees C and pH 7. The enzymes kept 100% of their enzymatic activity until 60 days of storage at 4 and -10 A degrees C. The stability under calcium salts indicated that the hydrolytic activity presented decay with the increase of calcium concentration. The specificity under several substrates indicated good enzyme activities in triglycerides from C4 to C18.

A Bayesian destructive weighted Poisson cure rate model and an application to a cutaneous melanoma data

In this article, we propose a new Bayesian flexible cure rate survival model, which generalises the stochastic model of Klebanov et al. [Klebanov LB, Rachev ST and Yakovlev AY. A stochastic-model of radiation carcinogenesis - latent time distributions and their properties. Math Biosci 1993; 113: 51-75], and has much in common with the destructive model formulated by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)]. In our approach, the accumulated number of lesions or altered cells follows a compound weighted Poisson distribution. This model is more flexible than the promotion time cure model in terms of dispersion. Moreover, it possesses an interesting and realistic interpretation of the biological mechanism of the occurrence of the event of interest as it includes a destructive process of tumour cells after an initial treatment or the capacity of an individual exposed to irradiation to repair altered cells that results in cancer induction. In other words, what is recorded is only the damaged portion of the original number of altered cells not eliminated by the treatment or repaired by the repair system of an individual. Markov Chain Monte Carlo (MCMC) methods are then used to develop Bayesian inference for the proposed model. Also, some discussions on the model selection and an illustration with a cutaneous melanoma data set analysed by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)] are presented.

MR-Radix: a multi-relational data mining algorithm

Abstract Background Once multi-relational approach has emerged as an alternative for analyzing structured data such as relational databases, since they allow applying data mining in multiple tables directly, thus avoiding expensive joining operations and semantic losses, this work proposes an algorithm with multi-relational approach. Methods Aiming to compare traditional approach performance and multi-relational for mining association rules, this paper discusses an empirical study between PatriciaMine - an traditional algorithm - and its corresponding multi-relational proposed, MR-Radix. Results This work showed advantages of the multi-relational approach in performance over several tables, which avoids the high cost for joining operations from multiple tables and semantic losses. The performance provided by the algorithm MR-Radix shows faster than PatriciaMine, despite handling complex multi-relational patterns. The utilized memory indicates a more conservative growth curve for MR-Radix than PatriciaMine, which shows the increase in demand of frequent items in MR-Radix does not result in a significant growth of utilized memory like in PatriciaMine. Conclusion The comparative study between PatriciaMine and MR-Radix confirmed efficacy of the multi-relational approach in data mining process both in terms of execution time and in relation to memory usage. Besides that, the multi-relational proposed algorithm, unlike other algorithms of this approach, is efficient for use in large relational databases.