A Strategy to Design Efficient Fermentation Processes for Traditional Beverages Production: Prickly Pear Wine

This paper describes a methodology to establish an optimal process design for prickly pear wine production that preserves the peculiar and unique traits of traditional products, generating at the same time, technical information for appropriate design of both bioreactor and overall process. The strategy includes alcoholic fermentation optimization by the mixed native culture composed by Pichia fermentans and Saccharomyces cerevisiae, followed by malolactic fermentation optimization by Oenococcus oeni. The optimization criteria were based on multiple output functions: alcohol content, volatile compounds profile, organic acids profile, and compound contents related to color, which were analyzed by spectroscopy–chromatography methods and sensory analysis. The results showed that the mixed culture inoculated into a bioreactor containing prickly pear juice with 20 °Bx of fermentable sugars concentration, processed at a constant temperature of 20 °C for 240 h, leads to a fermented product with 9.93% (v/v) total alcohol content, and significant abundance of volatile compounds, which provide fruity and ethereal aromatic notes, complemented by a lively but not unpleasant acidity. This young wine was further subjected to malolactic fermentation at constant temperature (16 °C) for 192 h, decreasing malic acid, and balancing volatile compounds contents, thus resulting in a product with better aroma and flavor perception, and a velvety feeling of long aftertaste. Repeated assays showed that the process is stable, predictable, controllable, and reproducible. These results were used for process design and spreadsheet construction in order to simulate the process, and properly select and size the equipment required for such process.     

Chaotic synchronization using monolithic Chua oscillators†

This paper presents experimental evidence of the synchronization between two monolithic chaotic oscillators. These oscillators have been fabricated using g_m — C design techniques in a 2-4 μm double-poly n-well CMOS technology. The circuit realizes an oscillator from Chua's circuit family and features electrical control of the parameters in the piecewise-linear function and on-chip tuning of the oscillator natural frequencies. The area of the circuit including pads is 5 mm² and the power dissipation is less than l-8mW for a symmetrical biasing of ±2.5V.     

Phenotypic,genetic and technological characterization of Lactococcus garvieae strains isolated from a raw milk cheese

A series of Lactococcus garvieae strains isolated as the majority population of a Spanish traditional, starter-free cheese made from raw milk were phenotypically and genotypically characterised to address their biochemical potential, safety requirements, and technological properties. As expected, all L. garvieae cheese strains fermented lactose but grew slowly in UHT-treated milk. Enzymatic activities of L. garvieae were similar to those of Lactococcus lactis, although higher esterase and lipase activities were recorded for L. garvieae strains. Profiles of the volatile compounds produced from milk by L. garvieae and L. lactis strains were also comparable. L. garvieae strains did not produce haemolysin, gelatinase and the biogenic amines tyramine and histamine. Five L. garvieae stains showed tetracycline resistance encoded by a tet(M) gene. The use of L. garvieae strains as starter or adjunct cultures might be recommended for certain cheese types, provided that the safety of the strains has been demonstrated.     

Stability of emulsions formulated with high concentrations of sodium caseinate and trehalose

Stability of emulsions formulated with 10 wt.% oil (concentrated fish oil, CFO, sunflower oil, SFO, or olive oil, OO), sodium caseinate concentrations varying from 0.5 to 5 wt.%, giving oil-to-protein ratios of 20–2, and 0, 20, 30 or 40 wt.% aqueous trehalose solution was studied by Turbiscan. Particle size distribution, microstructure, and small angle X-ray scattering (SAXS) patterns were also obtained. The main mechanism of destabilization in a given formulation strongly depended on oil-to-protein ratio. As evidenced by the BS-profile changes with time, emulsions formulated with 0.5 and 1 wt.% NaCas destabilized mainly by creaming while for the 2 wt.% NaCas concentration, both creaming and flocculation mechanisms, were involved. The main destabilization mechanism for the 3, 4 or 5 wt.% NaCas emulsions was flocculation. Stability of emulsions was also affected by the content of trehalose in the aqueous phase. Trehalose diminished the volume-weighted mean diameter (D_4,3) and greatly improved stability.     

A pseudo-transient heat transfer simulation of a continuous casting process,employing the element-free Galerkin method

The present work has been conducted in order to develop a novel solution for the heat transfer problem during the continuous casting of steel billets and blooms, by using the element-free Galerkin method under a pseudo-transient moving cross-section slice approach. The transport laws, non-linear aspects and boundary conditions of the initial value problem have been specified. A detailed explanation concerning the characteristics inherent to the application of the element-free Galerkin method to this problem has also been provided. The feasibility and suitability of this novel approach has been verified by comparison with the numerical techniques proposed and the results reported by other researchers as well as an analytical solution of a simple 1-D alloy solidification problem. The results have revealed that this technique could be used successfully in the pseudo transient moving cross-section solution of the heat transfer problem involved in the continuous casting of blooms and square billets.     

A Neural-based Model for Fast Continuous and Global Robot Location

One of the problems in the field of mobile robotics is the estimation of the robot position in an environment. This paper proposes a model for estimating a confidence interval of the robot position in order to compare it with the estimation made by a dead-reckoning system. Both estimations are fused using heuristic rules. The positioning model is very valuable in estimating the current robot position with or without knowledge about the previous positions. Furthermore, it is possible to define the degree of knowledge of the robot previous position, making it possible to adapt the estimation by varying this knowledge degree. This model is based on a one-pass neural network which adapts itself in real time and learns about the relationship between the measurements from sensors and the robot position.     

Olive oil consumption and reduced incidence of hypertension: The SUN study

Olive oil, a major component of the Mediterranean diet, has been associated in some small clinical trials and cross-sectional studies with a reduction in blood pressure. The objective of this study was to assess the association of olive oil consumption with the incidence of hypertension in an epidemiologic cohort, the Seguimiento Universidad de Navarra (SUN) study. The SUN Project is a prospective cohort study whose members are all university graduates. The recruitment and follow-up of participants is made using mailed questionnaires. Diet was assessed using a semiquantitative food frequency questionnaire previously validated in Spain, with 136 items. Outcomes of interest were newly diagnosed cases of hypertension, as reported by participants in the follow-up questionnaires. Logistic regression models were fit to assess the risk of hypertension associated with olive oil consumption. For the present analysis, we have taken in consideration the first 6,863 participants, with at least 2 yr of follow-up. After a median follow-up time of 28.5 mon, the cumulative incidence of hypereension was 4.7% in men and 1.7% in women. A lower risk of hypertension was observed among participants with a higher olive oil consumption at baseline, but the results were not statistically significant (P=0.13 for the linear trend test in the multivariate model). However, among men, the adjusted odds ratios (OR) (95% confidence intervals) of hypertension for the second to fifth quintiles of olive oil consumption, compared with the first quintile, were 0.55 (0.28–1.10), 0.75 (0.39–1.43), 0.32 (0.15–0.70), and 0.46 (0.23–0.94), respectively (P=0.02 for linear trend). No association was found between olive oil consumption and the risk of hypertension among women. In conclusion, in a Mediterranean population, we found olive oil consumption to be associated with a reduced risk of hypertension only among men. The lack of association observed among women might be attributed to the overall lower incidence of hypertension found among females and the resulting lower statistical power.     

Environmental behavior of cement-based stabilized foundry sludge products incorporating additives

A series of experiments were conducted to stabilize the inorganic and organic pollutants in a foundry sludge from a cast iron activity using Portland cement as binder and three different types of additives, organophilic bentonite, lime and coal fly ash. Ecotoxicological and chemical behavior of stabilized mixes of foundry sludge were analyzed to assess the feasibility to immobilize both types of contaminants, all determined on the basis of compliance leaching tests. The incorporation of lime reduces the ecotoxicity of stabilized mixes and enhances stabilization of organic pollutants obtaining better results when a 50% of cement is replaced by lime. However, the alkalinity of lime increases slightly the leached zinc up to concentrations above the limit set under neutral conditions by the European regulations. The addition of organophilic bentonite and coal fly ash can immobilize the phenolic compounds but are inefficient to reduce the ecotoxicity and mobility of zinc of final products.     

iMLP: Applying Multi-Layer Perceptrons to Interval-Valued Data

Interval-valued data offer a valuable way of representing the available information in complex problems where uncertainty, inaccuracy or variability must be taken into account. In addition, the combination of Interval Analysis with soft-computing methods, such as neural networks, have shown their potential to satisfy the requirements of the decision support systems when tackling complex situations. This paper proposes and analyzes a new model of Multilayer Perceptron based on interval arithmetic that facilitates handling input and output interval data, but where weights and biases are single-valued and not interval-valued. Two applications are considered. The first one shows an interval-valued function approximation model and the second one evaluates the prediction intervals of crisp models fed with interval-valued input data. The approximation capabilities of the proposed model are illustrated by means of its application to the forecasting of daily electricity price intervals. Finally, further research issues are discussed. Research funded by Universidad Pontificia Comillas.