Juan C. Domínguez

A Novel Method To Quantify the Adulteration of Extra Virgin Olive Oil with Low-Grade Olive Oils by UV−Vis

A simple and novel method to quantify adulterations of extra virgin olive oil (EVOO) with refined olive oil (ROO) and refined olive-pomace oil (ROPO) is described here. This method consists of calculating chaotic parameters (Lyapunov exponent, autocorrelation coefficients, and two fractal dimensions, CPs) from UV-vis scans of adulterated EVOO samples. These parameters have been successfully linearly correlated with the ROO or ROPO concentrations in 396 EVOO adulterated samples. By an external validation process, when the adulterating agent concentration is less than 10%, the integrated CPs/UV-vis model estimates the adulterant agent concentration with a mean correlation coefficient (estimated versus real concentration of low grade olive oil) greater than 0.97 and a mean square error of less than 1%. In light of these results, this detector is suitable not only to detect adulterations but also to measure impurities when, for instance, a higher grade olive oil is transferred to another storage tank in which lower grade olive oil was stored that had not been adequately cleaned.

Linear and non linear chemometric models to quantify the adulteration of extra virgin olive oil

Two mathematical methods to quantify adulterations of extra virgin olive oil (EVOO) with refined olive oil (ROO), refined olive-pomace oil (ROPO), sunflower (SO) or corn (CO) oils have been described here. These methods are linear and non linear models based on chaotic parameters (CPs, Lyapunov exponent, autocorrelation coefficients and two fractal dimensions) which were calculated from UV-vis scans (190-900 nm wavelength) of 817 adulterated EVOO samples. By an external validation process, linear and non linear integrated CPs/UV-vis models estimate concentrations of adulterant agents with a mean correlation coefficient (estimated versus real concentration of cheaper oil) greater than 0.80 and 0.97 and a mean square error less than 1% and 0.007%, respectively. In the light of the results shown in this paper, the adulteration of EVOO with ROO, ROPO, SO and CO can be suitably detected by only one chaotic parameter integrated on a radial basis network model.

Self-organizing maps and learning vector quantization networks as tools to identify vegetable oils.

Self-organizing map (SOM) and learning vector quantification network (LVQ) models have been explored for the identification of edible and vegetable oils and to detect adulteration of extra virgin olive oil (EVOO) using the most common chemicals in these oils, viz. saturated fatty (mainly palmitic and stearic acids), oleic and linoleic acids. The optimization and validation processes of the models have been carried out using bibliographical sources, that is, a database for developing learning process and internal validation, and six other different databases to perform their external validation. The models performances were analyzed by the number of misclassifications. In the worst of the cases, the SOM and LVQ models are able to classify more than the 94% of samples and detect adulterations of EVOO with corn, soya, sunflower, and hazelnut oils when their oil concentrations are higher than 10, 5, 5, and 10%, respectively.

Chaotic parameters and their role in quantifying noise in the output signals from UV, TGA and DSC apparatus

Two fractal dimensions and the Liapunov exponent (LE) have been applied to detect noisy output signals from UV spectrophotometer (UV), thermogravimetric analyzer (TGA) and differential scanning calorimeter (DSC) apparatus of 1-ethyl-3-methylimidazolium ethylsulfate ionic liquid ([emim][EtSO(4)]). The data collected from these three pieces of equipment were classified before calculating LE, regularization (RD) and box dimensions (BD). The RD and LE are able individually to detect and quantify noisy output signals with a mean error value less than 5% in all cases tested. Given that the LE can be calculated using a really simple method, this chaotic parameter has been selected as the most suitable to detect noise of signals from these apparatus.

Self-organizing maps and learning vector quantization networks as tools to identify vegetable oils and detect adulterations of extra virgin olive oil

Abstract Unsupervised models have been explored for the identification of edible and vegetable oils and to detect adulteration of extra virgin olive oil (EVOO) using the most common chemicals in these oils such as saturated fatty, oleic and linoleic acids. The optimization and validation processes of the models have been carried out using bibliographical sources. A database for developing learning process and internal validation, and six other different databases to perform their external validation has been used. In the worst of the cases, the unsupervised models are able to classify more than the 94 % of samples and detect adulterations of EVOO with promising results. The adulteration of EVOO with corn, soya, sunflower and hazelnut oils can be detected when their oil concentrations are higher than 10, 5, 5 and 10 %, respectively.

Predominio de Campylobacter jejuni en casos de gastroenteritis bacteriana en el adulto

enfermedades infecciosas como la fiebre Q los Ac antifosfolípido son independientes de la actividad de la ß 2 glucoproteína I, y al no interferirse ésta los fenómenos trombóticos estarían ausentes. Ninguno de los pacientes con fiebre Q de la serie de Ordi et al presentaron Ac frente a la glucoproteína I. De los 199 pacientes con enfermedades infecciosas de la serie de Sanmarco tan sólo uno con infección por VIH-1, presentó estos anticuerpos. Estos datos contrastan con el 33% de positividad en enfermedades autoinmunes. Cuenca Luque et al presentaron un caso similar, si bien la positividad de los Ac anticardiolipina ocurrió durante la convalecencia. Gálvez et al presentaron un caso similar con positividad de los Ac anticardiolipina durante la fase aguda de la infección y con trombosis venosa profunda. Estudios recientes de la universidad de Tejas justifican los cambios de hipercoagulabilidad en infecciones por rickettsias mediante lesión endotelial, activación de la coagulación con generación de trombina, activación plaquetaria, incremento de factores antifibrinolíticos, consumo de factores anticoagulantes y posiblemente elevación de citocinas que promueven la coagulación. En pacientes con fiebre Q pueden aparecer fenómenos trombóticos y constatarse Ac antifosfolípidos, siendo actualmente discutible su implicación etiopatogénica. El tratamiento recomendado es la anticoagulación prolongada entre 3-6 meses.

Thermal properties and thermal degradation kinetics of phenolic and wood flour-reinforced phenolic foams:

In the present work, the thermal stability, changes in chemical structure during thermal degradation, and the kinetics of thermal degradation of a phenolic foam were studied. An 8.5 wt% of Pinus radiata wood flour reinforcement was added to the phenolic foam. A commercial phenolic resol was used as the matrix for the foam. The wood flour-reinforced foam showed a structure similar to the phenolic foam according to the Fourier transform infrared spectroscopy results. The wood flour increased the thermal stability of the phenolic foam in the first stage of thermal degradation (T 5% ), decreased it in the second step (T 25% ), and negligibly influenced the final stage. The activation energies of the degradation processes of the studied materials were obtained by the Kissinger-Akahira-Sunose and Flynn-Wall-Ozawa model-free kinetic methods and a 2-Gaussian distributed activation energy model. The values of the activation energies obtained by the model-free kinetic methods for the first degradation stage of the phenolic foams were in a range between 110 and 170 kJ mol−1, whereas for the wood flour it was 162 kJ mol−1 for almost all of the conversion range of its main degradation stage. The applied models showed good fits for all the materials, and the activation energies calculated were in agreement with the values found in the literature.

Development of new biomass-based furan/glass composites manufactured by the double-vacuum-bag technique

The present study addresses the development of new biomass-based furan resin/glass fibre composites manufactured by the double-vacuum-bag technique using a two-stage cure cycle to allow removal of water from the resin. The volumetric composition and mechanical properties of the composites are measured and analysed with focus on the porosity content. The so-called matrix correlated porosity factor is determined to be 0.096, meaning that the furan matrix itself contains 8.8% porosity. In the optimal case of no matrix porosity, stiffness of the composites compares well with the stiffness of conventional thermosetting/glass composites, but with lower strength. The findings of the present study show that a more efficient water removal during manufacturing, a lower porosity content and a less brittle stress–strain behaviour of the furan matrix are to be addressed to further improve the properties of the composites.

Ionic liquids: determination of their aqueous content using differential scanning calorimeter equipment, chaotic parameters and a radial basis network model.

A new computerized approach to the determination of water in 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide, 1-butyl-3-methylimidazolium hexafluorophosfate and 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide ionic liquids (ILs) using the differential scanning calorimeter (DSC) scans of their mixtures with water is presented here. This approach consists of a combination of chaotic algorithms and a radial basis network (RBN). The data collected (heat flow signal) from DSC scans of ILs and water mixtures are used to calculate six chaotic parameters (two Liapunov exponents, two correlation parameters and two fractal dimensions), and then, these values are transferred into an RBN trained computer for modeling and estimating output. The predicted results using the RBN were compared with the measurements of water content carried out by the Karl Fischer technique and the difference between the real and predicted values was less than 0.05 and 4.9% in the internal and external validation, respectively. Such an integrated chaotic parameters (CPs)/RBN system is capable of detecting and quantifying water content in the aforementioned ILs, based on the created models and patterns, without any previous knowledge of this thermal process.

Combining autohydrolysis and ionic liquid microwave treatment to enhance enzymatic hydrolysis of Eucalyptus globulus wood

The combination of autohydrolysis and ionic liquid microwave treatments of eucalyptus wood have been studied to facilitate sugar production in a subsequent enzymatic hydrolysis step. Three autohydrolysis conditions (150 °C, 175 °C and 200 °C) in combination with two ionic liquid temperatures (80 °C and 120 °C) were compared in terms of chemical composition, enzymatic digestibility and sugar production. Morphology was measured (using SEM) and the biomass surface was visualized with confocal fluorescence microscopy. The synergistic cooperation of both treatments was demonstrated, enhancing cellulose accessibility. At intermediate autohydrolysis conditions (175 °C) and low ionic liquid temperature (80 °C), a glucan digestibility of 84.4% was obtained. Using SEM micrographs, fractal dimension (as a measure of biomass complexity) and lacunarity (as a measure of homogeneity) were calculated before and after pretreatment. High fractals dimensions and low lacunarities correspond to morphologically complex and homogeneous samples, that are better digested by enzyme cocktails.