Identification of temperature and moisture content fields using a combined neural network and clustering method approach

Studies on the dynamics of temperature and moisture content distributions in porous soils have provided important insight on their effect on the building hygrothermal behavior, where the interaction between both building and soil can contribute to reduce building thermal gains or looses. Hygrothermal aspects can be related to many attributes such as energy consumption, occupants' thermal comfort and health, and material deterioration. Recently, a great variety of mathematical models to predict thermal and moisture content profiles in porous media have been presented in the literature. Most of those models are based on analysis of multilayer measurements or on Fourier analysis. The development and validation of such mathematical models facilitate the understanding of heat and moisture flows at different soil depths. In this research, a radial basis function neural network (RBF-NN) approach, combined with Gath–Geva clustering method in order to predict the temperature and moisture content profiles in soils, has been presented. A set of data obtained from the computation of the coupled heat and moisture transfer in porous soils for the Curitiba city (Paraná State, Brazil) weather data file has been used by the RBF-NN modeling method. Simulation results indicate the potentialities of the RBF-NNs to learn, for the one step ahead identification, the behavior of temperature and moisture content profiles in the media at various depths.     

Antioxidant and antiglycation properties of Passiflora alata and Passiflora edulis extracts

The leaves of Passiflora alata Dryander and Passiflora edulis Sims, traditionally used in American countries to treat both anxiety and nervousness by folk medicine, are rich in polyphenols, which have been reported as natural antioxidants. In this study, the antioxidant activities of P. edulis and P. alata hydroalcoholic leaf extracts were verified in in vitro and ex vivo assays. P. alata showed a higher total reactive antioxidant potential than did P. edulis. The antioxidant activities of both extracts were significantly correlated with polyphenol contents. In addition, both extracts attenuated ex vivo iron-induced cell death, quantified by lactate dehydrogenase leakage, and effectively protected against protein damage induced by iron and glucose. These findings demonstrate that the P. alata and P. edulis leaf extracts have potent in vitro and ex vivo antioxidant properties and might be considered as possible new sources of natural antioxidants.     

The ParTriCluster Algorithm for Gene Expression Analysis

Analyzing gene expression patterns is becoming a highly relevant task in the Bioinformatics area. This analysis makes it possible to determine the behavior patterns of genes under various conditions, a fundamental information for treating diseases, among other applications. A recent advance in this area is the Tricluster algorithm, which is the first algorithm capable of determining 3D clusters (genes × samples × timestamps), that is, groups of genes that behave similarly across samples and timestamps. However, even though biological experiments collect an increasing amount of data to be analyzed and correlated, the triclustering problem remains a bottleneck due to its NP-Completeness, so its parallelization seems to be an essential step towards obtaining feasible solutions. In this work we propose and evaluate the implementation of a parallel version of the Tricluster algorithm using the filter-labeled-stream paradigm supported by the Anthill parallel programming environment. The results show that our parallelization scales well with the data size, being able to handle severe load imbalances that are inherent to the problem. Further more, the parallelization strategy is applicable to any depth-first searches.     

Discoloration process modeling by neural network

The photo-oxidation of acid orange 52 dye was performed in the presence of H₂O₂, utilizing UV light, aiming the discoloration process modeling and the process variable influence characterization. The discoloration process was modeled by the use of feedforward neural network. Each sample was characterized by five independent variables (dye concentration, pH, hydrogen peroxide volume, temperature and time of operation) and a dependent variable (absorbance). The neural model has also provided, through Garson Partition coefficients and the Pertubation method, the independent variable influence order determination. The results indicated that the time of operation was the predominant variable and reaction mean temperature was the lesser influent variable. The neural model obtained presented coefficients of correlation on the order 0.98, for sets of trainability, validation and testing, indicating the power of prediction of the model and its character of generalization.     

Effect of ionizing radiation on the properties of arc-induced long-period fiber gratings

We experimentally study the effect of ionizing radiation on the properties of long-period gratings fabricated in two pure-silica-core fibers with the arc-discharge technique. It is observed that the spectra of the gratings remain almost unchanged after being subjected to doses in excess of 0.5 MGy. The results also show that the gratings' temperature and strain sensitivities are not affected by gamma radiation.     

Heat,air and moisture transfer through hollow porous blocks

The combined heat, air and moisture transfer in building hollow elements is of paramount importance in the construction area for accurate energy consumption prediction, thermal comfort evaluation, moisture growth risk assessment and material deterioration analysis. In this way, a mathematical model considering the combined two-dimensional heat, air and moisture transport through unsaturated building hollow bricks is presented. In the brick porous domain, the differential governing equations are based on driving potentials of temperature, moist air pressure and water vapor pressure gradients, while, in the air domain, a lumped approach is considered for modeling the heat and mass transfer through the brick cavity. The discretized algebraic equations are solved using the MTDMA (MultiTriDiagonal-Matrix Algorithm) for the three driving potentials. Comparisons in terms of heat and vapor fluxes at the internal boundary are presented for hollow, massive and insulating brick blocks. Despite most of building energy simulation codes disregard the moisture effect and the transport multidimensional nature, results show those hypotheses may cause great discrepancy on the prediction of hygrothermal building performance.     

Nonlinear control of the doubly-fed induction generator in wind power systems

This paper describes the models of a wind power system, such as the turbine, generator, power electronics converters and controllers, with the aim to control the generation of wind power in order to maximize the generated power with the lowest possible impact in the grid voltage and frequency during normal operation and under the occurrence of faults. The presented work considers a wind power system equipped with the doubly-fed induction generator and a vector-controlled converter connected between the rotor and the grid. The paper presents comparative results between proportional-integral controllers and neural networks based controllers, showing that better dynamic characteristics can be obtained using neural networks based controllers.     

Biofilms of Listeria monocytogenes produced at 12 °C either in pure culture or in co-culture with Pseudomonas aeruginosa showed reduced susceptibility to sanitizers

The biofilm-forming ability of 21 Listeria monocytogenes isolates, previously pulsotyped and corresponding to 16 strains, from different origins was evaluated using the Calgary Biofilm Device, at 37 °C. Biofilms of 4 selected strains were also produced either on pure cultures or on co-cultures with Pseudomonas aeruginosa (PAO1), at 12 °C and at 37 °C. For these biofilms, the minimum biofilm eradication concentrations (MBECs) of 4 commercial dairy sanitizers (1 alkyl amine acetate based--T99, 2 chlorine based--T66 and DD, and 1 phosphoric acid based--BP) were determined. Listeria monocytogenes biofilms grown, either at 37 °C or 12 °C, were able to achieve similar cell densities by using different incubation periods (24 h and 7 d, respectively). In co-culture biofilms, P. aeruginosa was the dominant species, either at 37 °C or at 12 °C, representing 99% of a total biofilm population of 6 to 7 log CFU/peg. Co-culture biofilms were generally less susceptible than L. monocytogenes pure cultures. More interestingly, the biofilms produced at 12 °C were usually less susceptible to the sanitizers than when produced at 37 °C. Single or co-culture biofilms of L. monocytogenes and PAO1, particularly produced at 12 °C, retrieved MBEC values for agents T99 and BP that were, at times, above the maximum in-use recommended concentrations for these agents. The results presented here reinforce the importance of the temperature used for biofilm formation, when susceptibility to sanitizers is being assessed. PRACTICAL APPLICATION: Since most food plants have cold wet growth niches in production and storage areas, susceptibility testing should be performed on biofilms produced at refrigeration temperatures. Moreover, the efficiency of the sanitizers used in food industries should be performed on mixed culture biofilms, since in field conditions these will predominate. The results presented here highlight the importance of the temperature used for biofilm formation, when susceptibility to disinfectants is being assessed, as biofilms produced at lower temperature were less susceptible to sanitizers.