Baked product development based fermented legumes and cereals for schoolchildren snack

The objective of this work was to develop three foodstuffs based on mixes of wheat and fermented and non-fermented legumes, for the purpose of contributing with a healthy alternative for school snacks. To this aim, refined wheat flour was partially substituted with whole legume flours for the preparation of cakes, brownies and cookies, foodstuffs traditionally consumed by school age children. Cakes were formulated substituting 20% of wheat flour with Phaseolus vulgaris flour, brownies with 30% of Cajanus cajan flour and cookies with 30% of Vigna sinensis flour, using fermented and non-fermented legumes in the three products. When these products were subjected to sensorial evaluation through a test of degree of acceptability and using a hedonic scale of 7 points, values higher than 5 in the attributes taste, color and overall appraisal were found for all the products. In addition, the preference was measured with a group of 90 school children, corroborating the results obtained at laboratory level. Chemical characterization showed protein contents between 12 and 13% for the cake, 10 and 11% for the brownies and 10% for the cookies and protein digestibilities in vitro of 91%, 87% and 93%, respectively. The calorie supply, calculated per portion was of 199 kcal, 246 kcal and 237 kcal, for cakes, brownies and cookies, respectively. It was concluded that it is technically possible to incorporate fermented and non-fermented Phaseolus vulgaris, Vigna sinensis and Cajanus cajan, to highly consumed products such as cakes, brownies and cookies with a higher nutritional content and well-accepted by school-age children.     

Effects of Postharvest Putrescine Treatment on Extending Shelf Life and Reducing Mechanical Damage in Apricot

ABSTRACT: Apricots ( Prunus armeniaca L. cv Mauricio) harvested at commercial ripening stage were treated with putrescine (1 mM), then mechanically damaged with a 25 N force and stored at 10 °C for 6 d. Putrescine treatment increased fruit firmness and reduced the bruising zones caused by the mechanical damage. Putrescine-treated fruits (both damaged and nondamaged) showed different physiological behavior than controls. Color change, weight loss, ethylene emission, and respiration rate were reduced in putrescine-treated fruits. The most remarkable effect of the mechanical damage was the significant increase in spermidine concentrations found after the compression in control apricots, which could be considered as a physiological marker of mechanical damage.     

Modeling transfer of Escherichia coli O157:H7 and Staphylococcus aureus during slicing of a cooked meat product

Cross contamination is one of the most important contributing factors in foodborne illnesses originating in household environments. The objective of this research was to determine the transfer coefficients between a contaminated domestic slicing machine and a cooked meat product, during slicing. The microorganisms tested were Staphylococcus aureus (Gram positive) and Escherichia coli O157:H7 (Gram negative). The results showed that both microorganisms were able to transfer to all slices examined (20 successively sliced) and at different inoculum levels on the blade (10⁸, 10⁶ and 10⁴ cfu/blade). The results also showed that the number of log cfu transferred per slice, during slicing, decreased logarithmically for both microorganisms at inoculum levels of 8 and 6 log cfu/blade. The type of microorganism significantly influenced transfer coefficients (p < 0.05) and there was an interaction between inoculum level and transfer coefficient for S. aureus (p < 0.05), but not E. coli O157:H7. Finally, to describe bacterial transfer during slicing, two models (log-linear and Weibull) were fitted to concentration on slice data for both microorganisms (at 6 and 8 log cfu/blade), obtaining a good fit to data (R²  0.73).     

A GPU-based implementation of the MRF algorithm in ITK package

The analysis of medical image, in particular Magnetic Resonance Imaging (MRI), is a very useful tool to help the neurologists on the diagnosis. One of the stages on the analysis of MRI is given by a classification based on the Markov Random Fields (MRF) method. It is possible to find in the literature several packages to carry out this analysis, and of course, the classification tasks. One of them is the Insight Segmentation and Registration Toolkit (ITK). The analysis of MRI is an expensive computational task. In order to reduce the execution time spent on the analysis of MRI, parallelism techniques can be used. Currently, Graphics Processing Units (GPUs) are becoming a good choice to reduce the execution time of several applications at a low cost. In this paper, the authors present a GPU-based classification using MRF from the sequential implementation that appears in the ITK package. The experimental results show a spectacular execution time reduction being the GPU-based implementation up to 118 times faster than the sequential implementation included in the ITK package. Moreover, this result is also observed by reducing the total power consumption in a significant amount.     

Optimization of ODHE membrane reactor based on mixed ionic electronic conductor using soft computing techniques

This work presents the optimization of the operating conditions of a membrane reactor for the oxidative dehydrogenation of ethane. The catalytic membrane reactor is based on a mixed ionic–electronic conducting material, i.e. Ba_0.5Sr_0.5Co_0.8Fe_0.2O_δ−3, which presents high oxygen flux above 750 °C under sufficient chemical potential gradient. Specifically, diluted ethane is fed into the reactor chamber and air (or diluted air) is flushed to the other side of the membrane. A framework based on Soft Computing techniques has been used to maximize the ethylene yield by simultaneously varying five operation variables: nominal reactor temperature (Temp); gas flow in the reaction compartment (QHC); gas flow in the oxygen-rich compartment (QAir); ethane concentration in the reaction compartment (%C₂H₆); and oxygen concentration in oxygen-rich compartment (%O₂). The optimization tool combines a genetic algorithm guided by a neural network model. This shows how the neural network model for this particular problem is obtained and the analysis of its behavior along the optimization process. The optimization process is analyzed in terms of: (1) catalytic figures of merit, i.e., evolution of yield and selectivity towards different products and (2) framework behavior and variable significance. The two experimental areas maximizing the ethylene yield are explored and analyzed. The highest yield reached in the optimization process exceeded 87%.     

Exophytic renal angiolipoma versus retroperitoneal liposarcoma

OBJECTIVE: To report a case of exophytic renal angiomyolipoma mimicking a retroperitoneal liposarcoma on magnetic resonance imaging. METHODS: A large, palpable abdominal mass was incidentally discovered during routine physical examination in a 61-year-old, hypertensive woman. A CT scan disclosed a retroperitoneal mass, 17 cm in diameter, adjacent to the kidney. The MRI findings were diagnostic of liposarcoma. The tumor was resected en bloc. RESULTS: The histopathological findings demonstrated angiomyolipoma. CONCLUSIONS: Exophytic angiomyolipoma can mimic retroperitoneal liposarcoma on MRI.     

Validation of data converter specifications with behavioral modeling simulations

The increasing complexity of data converter architectures makes it necessary to use behavioral models to simulate electrical performances and to determine the relevant data converter features. For this purpose, special input stimuli and specific output data processing are required. In view of that, it is necessary to offer a specific data-converter simulation environment that permit the designer to validate the data converter specification and to extract the basic blocks key features before starting the transistor level design. Pointed toward this objective, this paper analyses the most utilized architectures and identifies the basic (active and passive) building blocks used. Behavioral models of such basic blocks are discussed. The proposed behavioral models are then used in a pipeline and a Σ–Δ converter. Specific routines for the determination of data converter parameters are presented. Simulations show how specific features of basic blocks affect the overall performances. Thus, guidelines on how to design the circuit in order to meet specifications are given.     

Methotrexateloaded Nanoparticles: Analysis of Drug Content and Study of the Matrix Structure

Entrapment of methotrexate in biodegradable colloidal systems was studied. Nanospheres were characterized in terms of morphometrical properties, such as particle diameter and particle size distribution. The ability of two surfactants, and dextrans of different molecular weights to improve the entrapment of the drug in a polymeric matrix was also studied. The presence of sodium lauryl sulphate in the polymerization medium increased the drug content in the nanospheres, and this effect was more significant when Dextran T70 was added to the formulation. Thermal methods such as thermogravimetry, differential scanning calorimetry and thermomicroscopy were applied, in order to study the possible interactions between the polymer and the drug. Crystalline methotrexate domains were observed in the polybutylcyanoacrylate matrix by thermomicroscopy.