Bioaccessibility of calcium, iron and zinc from three legume samples

Legumes can be a source of mineral elements but also of antinutritional factors which can affect their absorption. An in vitro method including gastrointestinal digestion was used to estimate mineral bioavailability. Soluble (bioaccessible) and insoluble calcium, iron and zinc from white beans, chickpeas and lentils were determined after gastrointestinal digestion. The influence of the original sample weight on the soluble mineral fraction was also estimated. The results obtained show that white beans are the legumes with the highest bioaccessible calcium and iron contents. Lentils have a high iron content but its bioaccessibility is much lower than that of iron from white beans and chickpeas. An increase in sample weight increases the amount of bioaccessible element available for intake, but the increase is not always proportional.     

A theoretical model for the automatic generation of tag clouds

This paper presents a new approach to information retrieval from non-structured attributes in databases, which involves the processing of text attributes. To make retrieval more effective, frequent text sequences are extracted and mathematically represented as intermediate forms which permit a clearer and more precise definition of operations on texts. These intermediate forms appear to users in the form of tag clouds to facilitate content identification, exploration, and querying. In this sense, tag cloud visualization is a simple, user-friendly visual interface to data. This paper proposes a theoretical model for the representation of frequent text sequences and their operations as well as a general procedure for generating tag clouds from text attributes in databases. The tag clouds thus obtained were compared with conventional tag clouds composed of single terms. Our study showed that automatically generated multi-term tag clouds provide better results than mono-term tag clouds.     

Numerical Modelling of Thin-Walled Stainless Steel Structural Elements in Case of Fire

In this paper, the structural response of stainless steel thin-walled elements submitted to fire is analysed numerically by means of the geometrically and materially non-linear Finite Element program SAFIR, including imperfections. In order to make these simulations, two main changes in the program were made: (i) the code was changed in order to deal with the stainless steel 2D material constitutive law to be used with shell elements and (ii) the possibility of the program to take into account residual stresses with shell finite elements was introduced. The stainless steel stress–strain relationship at high temperatures was based on the one presented in part 1.2 of Eurocode 3. To model the strain hardening exhibited by the stainless steels, using the shell element formulation, an approximation to the Eurocode 3 constitutive law was needed. Local and global geometrical imperfections were considered in the simulations. The paper shows the influence of the residual stresses on the ultimate load-carrying capacity of thin-walled stainless steel structural elements in case of fire.     

The magnetics diagnostic set for ITER

The current status of the ITER magnetics diagnostic is summarised. The various risks are discussed on the basis of when they could be present during ITER operation and appropriate mitigation is reviewed. An implementation risk or common mode operation failure risk to the magnetic diagnostic can only be mitigated by diversity. All identified risks are being handled with ongoing research and development to minimise these risks. A reasonable level of design and manufacturing diversity has been therefore introduced in the procurement and installation plans, in order to optimise overall reliability avoiding dispersion of resources.     

Determination of anthocyanin content in C.V Monastrell grapes during ripening period using several procedures

The accumulation of anthocyanins in grape skin and their evolution during ripening were evaluated in Monastrell grapes grown at four different sites growing season. Of the different techniques used for this purpose, we used one chromatographic [high‐performance liquid chromatography (HPLC)] and three spectrophotometric (Saint‐Cricq, Fragoso‐García and Lamadon) methods. The grapes from two of the sites (Agüeros and Rubializas) presented much higher values of anthocyanin (1279 and 1207 mg kg^?1 respectively) compounds than the grapes from the other two sites. Of the different methods used, HPLC proved to be an invaluable tool for identifying and quantifying individual anthocyanins in a sample, while the Fragoso‐García technique was the best of the spectrophotometric methods for laboratories that do not have access to HPLC equipment. Application of principal component determination (PCA) to our experimental data resulted satisfactory classification of wines in terms of their geographical origin. High correlation coefficients were observed among the different spectrophotometric techniques (0.88 between Fragoso‐García and Saint Cricq; and 0.92 between Lamadon and Saint Cricq) and lower coefficients between HPLC and the spectrophotometric techniques.     

A global optimum approach for one-layer neural networks

The article presents a method for learning the weights in one-layer feedforward neural networks minimizing either the sum of squared errors or the maximum absolute error, measured in the input scale. This leads to the existence of a global optimum that can be easily obtained solving linear systems of equations or linear programming problems, using much less computational power than the one associated with the standard methods. Another version of the method allows computing a large set of estimates for the weights, providing robust, mean or median, estimates for them, and the associated standard errors, which give a good measure for the quality of the fit. Later, the standard one-layer neural network algorithms are improved by learning the neural functions instead of assuming them known. A set of examples of applications is used to illustrate the methods. Finally, a comparison with other high-performance learning algorithms shows that the proposed methods are at least 10 times faster than the fastest standard algorithm used in the comparison.     

Hemodynamic changes in patients developing effective hypovolemia after total paracentesis

BACKGROUND/AIMS: In many centers paracentesis is considered the treatment of choice for tense ascites. However, the mechanism of effective hypovolemia after paracentesis, the main complication associated with this procedure, remains unknown. In the current study, systemic hemodynamics was sequentially studied before and after total paracentesis in 46 patients with cirrhosis and tense ascites. The aim of the study was to assess the mechanism of effective hypovolemia after paracentesis. METHODS: Plasma renin activity and aldosterone, mean arterial pressure, cardiac output (ECO-Doppler) and systemic vascular resistance were measured before, and 3 h, 6 h and 6 days after total paracentesis associated with plasma volume expansion. RESULTS: Effective hypovolemia after paracentesis (defined as 50% increase in plasma renin activity up to a level over 4 ng x m(-1) x h(-1) at the 6th day after paracentesis) occurred in 20 cases [plasma renin activity increased from 8+/-17 to 19+/-2.7 ng x m(-1) x h(-1)]. In the remaining 26 cases no changes in plasma renin activity [8.5+/-2.4 vs. 8.7+/-2.2 ng x m(-1) x h(-1)] were observed. The amounts of ascitic fluid volume removed were similar. Effective hypovolemia after paracentesis was associated with a significant decrease in mean arterial pressure (89+/-2 vs. 81+/-3 mmHg) and systemic vascular resistance [1263+/-67 vs. 1014+/-80 dyn x s(-1) x cm(-5)] 6 days after treatment. In contrast, no significant changes in these parameters were observed in patients not developing this complication. In the whole group of patients a significant inverse relation was observed between changes in plasma renin activity and in systemic vascular resistance (r=0.74;p< 0.001). CONCLUSIONS: These results indicate that effective hypovolemia after paracentesis in cirrhosis is predominantly due to an accentuation of the arteriolar vasodilation already present in these patients.     

Canonical STATIS: Biplot analysis of multi-table group structured data based on STATIS-ACT methodology

Frequently multivariate experimental data taken over multiple occasions is found to produce a multivariate multi-table experiment. Neither the separate analysis of each occasion, using MANOVA or canonical variate analysis, nor the joint analysis using the STATIS-ACT methodology for multiple tables, are adequate to capture the real structure of the data matrices, since the first account for group structure but not time evolution and the second confuses the “between” and “within” group variabilities. A method baptized Canonical STATIS, based on STATIS-ACT methodology, is proposed. The method permits to account for data group structure as well as time evolution on the various occasions by obtaining common or stable canonical variates across multiple occasions or data sets. A simultaneous representation of groups, variables and occasions (biplot) is obtained, thereby widening the capabilities of classical methods.