Effect of annealing atmosphere on phase formation and electrical characteristics of bismuth ferrite thin films

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Xylanases from fungi: properties and industrial applications

Xylan is the principal type of hemicellulose. It is a linear polymer of beta-D-xylopyranosyl units linked by (1-4) glycosidic bonds. In nature, the polysaccharide backbone may be added to 4-O-methyl-alpha-D-glucuronopyranosyl units, acetyl groups, alpha-L-arabinofuranosyl, etc., in variable proportions. An enzymatic complex is responsible for the hydrolysis of xylan, but the main enzymes involved are endo-1,4-beta-xylanase and beta-xylosidase. These enzymes are produced by fungi, bacteria, yeast, marine algae, protozoans, snails, crustaceans, insect, seeds, etc., but the principal commercial source is filamentous fungi. Recently, there has been much industrial interest in xylan and its hydrolytic enzymatic complex, as a supplement in animal feed, for the manufacture of bread, food and drinks, textiles, bleaching of cellulose pulp, ethanol and xylitol production. This review describes some properties of xylan and its metabolism, as well as the biochemical properties of xylanases and their commercial applications.

Particle Competition and Cooperation in Networks for Semi-Supervised Learning with Concept Drift

Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not be stable over time. However, most learning algorithms produced so far are based on the assumption that data comes from a fixed distribution, so they are not suitable to handle concept drifts. Moreover, some concept drifts applications requires fast response, which means an algorithm must always be (re) trained with the latest available data. But the process of labeling data is usually expensive and/or time consuming when compared to unlabeled data acquisition, thus only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are also based on the assumption that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenge in machine learning. Recently, a particle competition and cooperation approach was used to realize graph-based semi-supervised learning from static data. In this paper, we extend that approach to handle data streams and concept drift. The result is a passive algorithm using a single classifier, which naturally adapts to concept changes, without any explicit drift detection mechanism. Its built-in mechanisms provide a natural way of learning from new data, gradually forgetting older knowledge as older labeled data items became less influent on the classification of newer data items. Some computer simulation are presented, showing the effectiveness of the proposed method.

Influence of Hydrogen Peroxide Bleaching Gels on Color, Opacity, and Fluorescence of Composite Resins

The aim of the present study was to evaluate the effect of 20% and 35% hydrogen peroxide bleaching gels on the color, opacity, and fluorescence of composite resins. Seven composite resin brands were tested and 30 specimens, 3-mm in diameter and 2-mm thick, of each material were fabricated, for a total of 210 specimens. The specimens of each tested material were divided into three subgroups (n=10) according to the bleaching therapy tested: 20% hydrogen peroxide gel, 35% hydroxide peroxide gel, and the control group. The baseline color, opacity, and fluorescence were assessed by spectrophotometry. Four 30-minute bleaching gel applications, two hours in total, were performed. The control group did not receive bleaching treatment and was stored in deionized water. Final assessments were performed, and data were analyzed by two-way analysis of variance and Tukey tests (p<0.05). Color changes were significant for different tested bleaching therapies (p<0.0001), with the greatest color change observed for 35% hydrogen peroxide gel. No difference in opacity was detected for all analyzed parameters. Fluorescence changes were influenced by composite resin brand (p<0.0001) and bleaching therapy (p=0.0016) used. No significant differences in fluorescence between different bleaching gel concentrations were detected by Tukey test. The greatest fluorescence alteration was detected on the brand Z350. It was concluded that 35% hydrogen peroxide bleaching gel generated the greatest color change among all evaluated materials. No statistical opacity changes were detected for all tested variables, and significant fluorescence changes were dependent on the material and bleaching therapy, regardless of the gel concentration.

Calcium silicate and organic mineral fertilizer applications reduce phytophagy by Thrips palmi Karny (Thysanoptera: Thripidae) on eggplants (Solanum melongena L.)

Thrips palmi Karny (Thysanoptera: Thripidae) is a phytophagous insect associated with the reduction of eggplant productivity. The aim of this study was to evaluate the effect of calcium silicate and/or an organic mineral fertilizer, together or separately, in increasing the resistance of eggplants to T. palmi. The treatments were calcium silicate, organic mineral fertilizer, calcium silicate associated with this fertilizer and the control. Mortality and number of lesions caused by nymphs of this insect on eggplant leaves were evaluated after 3, 6, 9 and 12 leaf applications of these products. The calcium silicate and the organic mineral fertilizer reduced both the population of T. palmi and the damage caused by its nymphs, suggesting a possible increase in eggplant resistance to this pest as a result of the treatments.

Microscopic and dielectric analyses of vanadium and tungsten modified barium zirconium titanate ceramics

Dielectric spectroscopy was used in this study to examine polycrystalline vanadium and tungstendoped BaZr 0.1Ti 0.90O 3 (BZT10:2V and BZT10:2W) ceramics obtained by the mixed oxide method. According to X-ray diffraction analyses, addition of vanadium and tungsten lead to ceramics free of secondary phases. SEM analyses reveal that both dopants result in slower oxygen ion motion and consequently lower grain growth rate. Temperature dependence dielectric study showed normal ferroelectric to paraelectric transition well above the room temperature for the BZT10 and BZT10:2V ceramics. However, BZT10:2W ceramic showed a relaxor-like behavior near phase transition characterized by the empirical parameter γ. Piezoelectric force microscopy images reveals that the piezoelectric coefficient is strongly influenced by type of donor dopant suggesting promising applications for dynamic random access memories and data-storage media. Copyright © 2010 American Scientific Publishers All rights reserved.

Architecture for peer-to-peer databases with routing queries using ant colony algorithm and semantic support

In a peer-to-peer network, the nodes interact with each other by sharing resources, services and information. Many applications have been developed using such networks, being a class of such applications are peer-to-peer databases. The peer-to-peer databases systems allow the sharing of unstructured data, being able to integrate data from several sources, without the need of large investments, because they are used existing repositories. However, the high flexibility and dynamicity of networks the network, as well as the absence of a centralized management of information, becomes complex the process of locating information among various participants in the network. In this context, this paper presents original contributions by a proposed architecture for a routing system that uses the Ant Colony algorithm to optimize the search for desired information supported by ontologies to add semantics to shared data, enabling integration among heterogeneous databases and the while seeking to reduce the message traffic on the network without causing losses in the amount of responses, confirmed by the improve of 22.5% in this amount. © 2011 IEEE.

Sparse arrays and image compounding techniques for non-destructive testing using guided acoustic waves

Piezoelectric array transducers applications are becoming usual in the ultrasonic non-destructive testing area. However, the number of elements can increase the system complexity, due to the necessity of multichannel circuitry and to the large amount of data to be processed. Synthetic aperture techniques, where one or few transmission and reception channels are necessary, and the data are post-processed, can be used to reduce the system complexity. Another possibility is to use sparse arrays instead of a full-populated array. In sparse arrays, there is a smaller number of elements and the interelement spacing is larger than half wavelength. In this work, results of ultrasonic inspection of an aluminum plate with artificial defects using guided acoustic waves and sparse arrays are presented. Synthetic aperture techniques are used to obtain a set of images that are then processed with an image compounding technique, which was previously evaluated only with full-populated arrays, in order to increase the resolution and contrast of the images. The results with sparse arrays are equivalent to the ones obtained with full-populated arrays in terms of resolution. Although there is an 8 dB contrast reduction when using sparse arrays, defect detection is preserved and there is the advantage of a reduction in the number of transducer elements and data volume. © 2013 Brazilian Society for Automatics - SBA.

Local data fusion algorithm for fire detection through mobile robot

Multisensor data fusion is a technique that combines the readings of multiple sensors to detect some phenomenon. Data fusion applications are numerous and they can be used in smart buildings, environment monitoring, industry and defense applications. The main goal of multisensor data fusion is to minimize false alarms and maximize the probability of detection based on the detection of multiple sensors. In this paper a local data fusion algorithm based on luminosity, temperature and flame for fire detection is presented. The data fusion approach was embedded in a low cost mobile robot. The prototype test validation has indicated that our approach can detect fire occurrence. Moreover, the low cost project allow the development of robots that could be discarded in their fire detection missions. © 2013 IEEE.

Semi-supervised learning with concept drift using particle dynamics applied to network intrusion detection data

Concept drift, which refers to non stationary learning problems over time, has increasing importance in machine learning and data mining. Many concept drift applications require fast response, which means an algorithm must always be (re)trained with the latest available data. But the process of data labeling is usually expensive and/or time consuming when compared to acquisition of unlabeled data, thus usually only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are based on assumptions that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenging task in machine learning. Recently, a particle competition and cooperation approach has been developed to realize graph-based semi-supervised learning from static data. We have extend that approach to handle data streams and concept drift. The result is a passive algorithm which uses a single classifier approach, naturally adapted to concept changes without any explicit drift detection mechanism. It has built-in mechanisms that provide a natural way of learning from new data, gradually "forgetting" older knowledge as older data items are no longer useful for the classification of newer data items. The proposed algorithm is applied to the KDD Cup 1999 Data of network intrusion, showing its effectiveness.

Effect of oxidizing and reducing atmospheres on Ba(Ti0.90 Zr0.10)O3:2V ceramics as characterized by piezoresponse force microscopy

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Partitioning the relative contribution of one-phase and two-phase seed dispersal when evaluating seed dispersal effectiveness

Seed dispersal effectiveness (SDE) is a conceptual framework that aims at quantifying the contribution of seed dispersal vectors to plant fitness. While it is well recognized that diplochorous dispersal systems, characterized by two successive dispersal steps performed by two different vectors (Phase I=primary seed dispersal and Phase II=secondary seed dispersal) which are common in temperate and tropical regions, little attention has been given to distinguishing the relative contribution of one-phase and two-phase dispersal to overall SDE. This conceptual gap probably results from the lack of a clear methodology to include Phase II dispersal into the calculation of SDE and to quantify its relative contribution. We propose a method to evaluate the relative contribution of one-phase and two-phase dispersal to SDE and determine whether two seed dispersers are better than one. To do so, we used the SDE landscape and an extension of the SDE landscape, the Phase II effect landscape, which measures the direction and magnitude of the Phase II dispersal effect on overall SDE. We used simulated and empirical data from a diplochorous dispersal system in the Peruvian Amazon to illustrate this new approach. Our approach provides the relative contribution of one-phase SDE (SDE1) and two-phase SDE (SDE2) to overall SDE and quantifies how much SDE changes with the addition of Phase II dispersal. Considering that the seed dispersal process is context dependent so that Phase II depends on Phase I, we predict the possible range of variation of SDE according to the variation of the probability of Phase II dispersal. In our specific study system composed of two primate species as primary dispersal vectors and different species of dung beetles as secondary dispersal vectors, the relative contribution of SDE1 and SDE2 to overall SDE varied between plant species. We discuss the context dependency of the Phase II dispersal and the potential applications of our approach. This extension to the conceptual framework of SDE enables quantitative evaluation of the effect of Phase II dispersal on plant fitness and can be easily adapted to other biotic and/or abiotic diplochorous dispersal systems.

Bone morphogenetic proteins: promising molecules for bone healing, bioengineering, and regenerative medicine

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)