Thermal and spectroscopic data to investigate the oxamic acid, sodium oxamate and its compounds with some bivalent transition metal ions

Synthesis, characterization, and thermal behavior of transition metal oxamates, M(NH(2)C(2)O(3))(2)center dot nH(2)O (M = Mn(II), Fe(II), Co(II), Ni(II), Cu(II), Zn(II)), as well as the thermal behavior of oxamic acid and its sodium salt (NaNH(2)C(2)O(3)) were investigated employing simultaneous thermogravimetry and differential scanning calorimetry (TG-DSC), experimental and theoretical infrared spectroscopy, TG-DSC coupled to FTIR, elemental analysis and complexometry. The results led to information about the composition, dehydration, thermal stability, thermal decomposition, as well as of the gaseous products evolved during the thermal decomposition of these compounds in dynamic air and N(2) atmospheres.

The effects of soil pollution and its relation with morbidity in shoreline areas

Soil and subsoil pollution is not only significant in terms of environmental loss, but also a matter of environmental and public health. Solid, liquid and gaseous residues are the major soil contamination agents. They originate from urban conglomerates and industrial areas in which it is impossible to emphasize the chemical, petrochemical and textile industry; thermoelectric, mining, and ironmaster activities. The contamination process can thus be defined as a compound addition to soil, from what qualitative and or quantitative manners can modify soil's natural characteristics and use, producing baneful and deteriorative effects on human health. Studies have shown that human exposition to high concentration of some heavy metals found on soil can cause serious health problems, such as pulmonary or kidney complications, liver and nervous system harm, allergy, and the chronic exposition that leads to death. The present study searches for the correlation among soil contamination, done through a geochemical baseline survey of an industrial contamination area on the shoreline of Sao Paulo state. The study will be conducted by spatial analysis using Geographical Information Systems for mapping and regression analysis. The used data are 123 soil samples of percentage concentration of heavy metals. They were sampled and spatially distributed by geostatistics methods. To verify if there is a relation between heavy metals soil pollution and morbidity an executed correlation and regression analysis will be done using the pollution registers as the independent variables and morbidity as dependable variables. It is expected, by the end of the study, to identify the areas relation between heavy metals soil pollution and morbidity, moreover to be able to provide assistance in terms of new methodologies that could facilitate soil pollution control programs and public health planning. © 2010 WIT Press.

Electrochemical Properties of Oxo-Manganese Complex Biomimicking Enzyme Active Sites and Its Electrocatalytic Application for Dopamine Determination

This work describes the characterization of the [Mn2 IV,IVO2(terpy)2(H2O)2]4+ complex in aqueous solution by UV-vis spectrophotometry, cyclic voltammetry, and linear sweep voltammetry with a rotating disk electrode. The pH effect, potential scan rate, effect of perfluorosulfonate polymer, and anion of supporting electrode on the electrochemical behavior of the modified electrode for better performance were investigated. The potential peak of the modified electrode was linearly dependent upon the ratio [ionic charge]/[ionic radius]. The modified electrode exerted an electrocatalytic effect on dopamine oxidation in aqueous solution with a decrease in the overpotential compared with the unmodified glassy carbon electrode. This way, the modified electrode showed an enzymatic biomimicking behavior. Tafel plot analyses were used to elucidate the kinetics and mechanism of dopamine oxidation. © 2013 Springer Science+Business Media New York.

Adoption and application of information technology in the Caribbean and its contribution to scientific, technological and human resource development

Includes bibliography

MR-Radix: a multi-relational data mining algorithm

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.

Improvement of gamete quality and its short-term storage: an approach for biotechnology in laboratory fish

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

Effect of Er:YAG laser on CaF2 formation and its anticariogenic action on human enamel: An in vitro study

Objective: The objective of this study was to evaluate the effect of Er: YAG laser on the formation of CaF2, after the application of acidulated phosphate fluoride (APF), and its influence on the anti-cariogenic action in human dental enamel. Background Data: Er:YAG laser was designed to promote ablation of the enamel. However, the possibility of using this energy to increase the enamel's resistance to caries has hardly been explored, and neither has its interaction with the use of fluorides. Materials and Methods: One hundred and twenty blocks of enamel were allocated to four groups of 30 blocks each: (1) C, control group; (2) Er:YAG, laser; (3) APF; and (4) Er:YAG+APF. Of these, 80 blocks were submitted to pH cycling for 14 days. In the other 40 blocks, fluoride (CaF2) was measured before cycling. After pH cycling, surface microhardness (SMH), microhardness in cross-section (converted to mineral contents % vol. min.), and fluoride after cycling (40 blocks) were also determined. Results: SMH decreased in all groups. The control group showed the highest decrease, and Er:YAG+APF showed the lowest decrease (p < 0.05). Groups APF and Er:YAG showed the same results (p > 0.05). Mineral content at depths 10, 20, and 40 μm was lower in the control and Er:YAG groups, and higher in groups APF and Er:YAG+APF. CaF2 (μgF/cm2) deposited before pH cycling was higher in the APF group when compared to the Er:YAG+APF group. Control and Er:YAG groups showed the lowest values (p > 0.05). Conclusion: It was concluded that Er:YAG laser influenced the deposition of CaF2 on the enamel and showed a superficial anti-cariogenic action, but not in depth.

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.