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.

Identification of structural damage in flexible structures using system norm and neural networks

Nowadays there is great interest in damage identification using non destructive tests. Predictive maintenance is one of the most important techniques that are based on analysis of vibrations and it consists basically of monitoring the condition of structures or machines. A complete procedure should be able to detect the damage, to foresee the probable time of occurrence and to diagnosis the type of fault in order to plan the maintenance operation in a convenient form and occasion. In practical problems, it is frequent the necessity of getting the solution of non linear equations. These processes have been studied for a long time due to its great utility. Among the methods, there are different approaches, as for instance numerical methods (classic), intelligent methods (artificial neural networks), evolutions methods (genetic algorithms), and others. The characterization of damages, for better agreement, can be classified by levels. A new one uses seven levels of classification: detect the existence of the damage; detect and locate the damage; detect, locate and quantify the damages; predict the equipment's working life; auto-diagnoses; control for auto structural repair; and system of simultaneous control and monitoring. The neural networks are computational models or systems for information processing that, in a general way, can be thought as a device black box that accepts an input and produces an output. Artificial neural nets (ANN) are based on the biological neural nets and possess habilities for identification of functions and classification of standards. In this paper a methodology for structural damages location is presented. This procedure can be divided on two phases. The first one uses norms of systems to localize the damage positions. The second one uses ANN to quantify the severity of the damage. The paper concludes with a numerical application in a beam like structure with five cases of structural damages with different levels of severities. The results show the applicability of the presented methodology. A great advantage is the possibility of to apply this approach for identification of simultaneous damages.

Heavy metals availability and fractions in soil amended with biosolid composts

The heavy metals when linked to organic matter have a behavior in the soil that is still little known. This study aimed to evaluate the effect of sewage-sludge-based composts when incorporated in the soil, in relation to heavy metals availability. Five composts were incorporated using sugar-cane bagasse, sewage sludge and cattle manure in the respective proportions: 75-0-25, 75-12.5-12.5, 75-25-0, 50-50-0 and 0-100-0 (composts with 0, 12.5, 25, 50 and 100% sewage sludge). The experiment consisted of 6 treatments (5 composts and a control with mineral fertilization) in randomized blocks with a split-plot design. The control and the treatment of 0% sewage sludge received inorganic nitrogen (N). All the treatments received the same amount of N (8.33 g) K (5.80 g) and K (8.11 g) per pot. Tomato plants were cultivated in 24.0 L pots in a greenhouse in Jaboticabal, SP, Brazil. The concentrations of heavy metals were determined in the soil samples at day 0 after compost incorporation. The higher the sewage sludge doses, the higher heavy metal contents in the soil. Among extractants, Melhlich-1 extracted the highest amount of heavy metals, while DTPA extracted the lowest one. The residual fraction presented the highest heavy metal content, followed by Fe oxides crystalline and amorphous to Cu, Cr and Mn, and Mn oxides, and Fe amorphous to Zn, indicating strong associations to oxides and clays. There were significant positive correlations between Mn contents in the plant and Mn linked to Fe oxide amorphous and crystalline.

Dry matter yield and nutritional value of Marandu grass under nitrogen fertilization and irrigation in cerrado in São Paulo

The aim of this study was to evaluate dry matter yield and nutritional value of palisade grass (Brachiaria brizantha cv. Marandu) using nitrogen doses and sprinkler irrigation in two periods of the year, aiming at reducing seasonality of forage production. It was used a randomized block design in a split-plot scheme, with five doses of nitrogen (0, 50, 100, 150, and 200 kg/ha/cut), and the sub-plots were defined by the seasons of the year (wet and dry season), with and without irrigation. During the wet season, in the plots with and without irrigation, doses of 175 and 161 kg/ha/cut promoted the highest dry matter yields. During the dry season, 171 kg ha -1N with irrigation resulted in the highest dry matter yield. During the same season, there was no response to N fertilization in the lack of irrigation. Average contents of CP were 10% with and without irrigation. Contents of neutral detergent fiber decreased with nitrogen doses, while acid detergent fiber was not affected by fertilization. Plots under irrigation reached the maximal acid detergent fiber content at N dose of 60 kg ha -1. Irrigation promotes increase of 15% increase in dry matter yield and it increases contents of neutral detergent fiber. © 2010 Sociedade Brasileira de Zootecnia.

Application of molecular markers on genetic improvement and reproduction in the post-genomic Era: Emerging biotechnologies and perspectives in livestock

Background: New challenges are rising in the animal protein market, and one of the main world challenges is to produce more in shorter time, with better quality and in a sustainable way. Brazil is the largest beef exporter in volume hence the factors affecting the beef meat chain are of major concern in countrýs economy. An emerging class of biotechnological approaches, the molecular markers, is bringing new perspectives to face these challenges, particularly after the publication of the first complete livestock genome (bovine), which has triggered a massive initiative to put in practice the benefits of the so called the Post-Genomic Era. Review: This article aimed at showing the directions and insights in the application of molecular markers on livestock genetic improvement and reproduction as well at organizing the progress so far, pointing some perspectives of these emerging technologies in Brazilian ruminant production context. An overview on the nature of the main molecular markers explored in ruminant production is provided, which describes the molecular bases and detection approaches available for microsatellites (STR) and single nucleotide polymorphisms (SNP). A topic is dedicated to review the history of association studies between markers and important trait variation in livestock, showing the timeline starting on quantitative trait loci (QTL) identification using STR markers and ending in high resolution SNP panels to proceed whole genome scans for phenotype/genotype association. Also the article organizes this information to reveal how QTL prospection using STR could open ground to the feasibility of marker-assisted selection and why this approach is quickly being replaced by studies involving the application of genome-wide association using SNP research in a new concept called genomic selection. Conclusion: The world's scientific community is dedicating effort and resources to apply SNP information in livestock selection through the development of high density panels for genomic association studies, connecting molecular genetic data with phenotypes of economic interest. Once generated, this information can be used to take decisions in genetic improvement programs by selecting animals with the assistance of molecular markers.

Expression of annexin-A1 and galectin-1 anti-inflammatory proteins and mRNA in chronic gastritis and gastric cancer

Objective. The anti-inflammatory proteins annexin-A1 and galectin-1 have been associated with tumor progression. This scenario prompted us to investigate the relationship between the gene and protein expression of annexin-A1 (ANXA1/AnxA1) and galectin-1 (LGALS1/Gal-1) in an inflammatory gastric lesion as chronic gastritis (CG) and gastric adenocarcinoma (GA) and its association with H. pylori infection. Methods. We analyzed 40 samples of CG, 20 of GA, and 10 of normal mucosa (C) by the quantitative real-time PCR (qPCR) technique and the immunohistochemistry assay. Results. High ANXA1 mRNA expression levels were observed in 90% (36/40) of CG cases (mean relative quantification RQ = 4.26 ± 2.03) and in 80% (16/20) of GA cases (mean RQ = 4.38 ± 4.77). However, LGALS1 mRNA levels were high (mean RQ = 2.44 ± 3.26) in 60% (12/20) of the GA cases, while low expression was found in CG (mean RQ = 0.43 ± 3.13; P < 0.01). Normal mucosa showed modest immunoreactivity in stroma but not in epithelium, while stroma and epithelium displayed an intense immunostaining in CG and GA for both proteins. Conclusion. These results have provided evidence that galectin-1 and mainly annexin-A1 are overexpressed in both gastritis and gastric cancer, suggesting a strong association of these proteins with chronic gastric inflammation and carcinogenesis. © 2013 Yvana Cristina Jorge et al.

Cyp17a1 and cyp19a1 in the zebrafish testis are differentially affected by oestradiol

Oestrogens can affect expression of genes encoding steroidogenic enzymes in fish gonads. However, little information is available on their effects at the protein level. In this context, we first analysed the expression of key steroidogenic enzyme genes and proteins in zebrafish testis, paying attention also to other cell types than Leydig cells. Gene expression was analysed by quantitative PCR on fluorescence-activated cell-sorting fractions coupled or not to differential plating, while protein synthesis was studied by immunohistochemistry using specific antibodies against zebrafish Cyp17a1, Cyp19a1a and Cyp19a1b. Furthermore, we have evaluated the effect of oestrogen treatment (17β-oestradiol (E2), 10 nM) on the localization of these enzymes after 7 and 14 days of in vivo exposure in order to study how oestrogen-mediated modulation of their expression is linked to oestrogen effects on spermatogenesis. The major outcomes of this study are that Leydig cells express Cyp17a1 and Cyp19a1a, while testicular germ cells express Cyp17a1 and both, Cyp19a1a and Cyp19a1b. As regards Cyp17a1, both protein and mRNA seem to be quantitatively dominating in Leydig cells. Moreover, E2 exposure specifically affects only Leydig cell Cyp17a1 synthesis, preceding the disruption of spermatogenesis. The oestrogen-induced suppression of the androgen production capacity in Leydig cells is a major event in altering spermatogenesis, while germ cell steroidogenesis may have to be fuelled by precursors from Leydig cells. Further studies are needed to elucidate the functionality of steroidogenic enzymes in germ cells and their potential role in testicular physiology. © 2013 Society for Endocrinology.

3D geovisualisation techniques applied in spatial data mining

The increase in the number of spatial data collected has motivated the development of geovisualisation techniques, aiming to provide an important resource to support the extraction of knowledge and decision making. One of these techniques are 3D graphs, which provides a dynamic and flexible increase of the results analysis obtained by the spatial data mining algorithms, principally when there are incidences of georeferenced objects in a same local. This work presented as an original contribution the potentialisation of visual resources in a computational environment of spatial data mining and, afterwards, the efficiency of these techniques is demonstrated with the use of a real database. The application has shown to be very interesting in interpreting obtained results, such as patterns that occurred in a same locality and to provide support for activities which could be done as from the visualisation of results. © 2013 Springer-Verlag.

Anthropogenic influences on Cd, Cr,Cu, Ni, Pb and Zn concentrations in soils and sediments in a watershed with sugar cane crops at São Paulo State, Brazil

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

Lead-germanate glasses and fibers: A practical alternative to tellurite for nonlinear fiber applications

We report on the fabrication of novel lead-germanate glasses and fibers. We have characterized these glasses in terms of their thermal properties, Raman spectra and refractive indices (both linear and nonlinear) and present them as viable alternatives to tellurite glasses for applications requiring highly nonlinear optical fibers. © 2013 Optical Society of America.

Quality management, environmental management maturity, green supply chain practices and green performance of Brazilian companies with ISO 14001 certification: Direct and indirect effects

This study aims to test a new conceptual model based on the relationship between quality management (QM), environmental management maturity (EMM), adoption of external practices of green supply chain management (GSCM) (green purchasing and collaboration with customers) and green performance (GP) with data from 95 Brazilian firms with ISO 14001. To our knowledge, such links and relationships are not simultaneously identified and tested in the literature. The results indicate the validation of all of the research hypotheses. This paper highlights that an improvement in green performance will require attention to quality management, environmental management maturity, and green supply chain. (C) 2014 Elsevier Ltd. All rights reserved.

Clinical Trial Evaluating Color Change and Tooth Sensitivity Throughout and Following In-office Bleaching

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

DNA methylation patterns of steroid receptor genes ESR1, ESR2 and PGR in deep endometriosis compromising the rectum

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

Information flows and environments in business contexts: the meat sector case of Salmanca/Spain

Organizational environments are related to hierarchic levels existing in a determined organization, and they influence in the formal and informal flows origin and in their monitoring and/or extinction. Informational environments are a result of organizational environments, of which focus is information and knowledge. Information flows are a fundamental element to informational environments, in a way that there´s no informational environments if there´s no information flows. Informational flows are natural reflections from their environments, in terms of content and in the way they occur. This qualitative and quantitative research was developed in three stages, in a way to allow the comprehension of the phenomena related to information and knowledge environments and information flows that occur in the meat sector from the Province of Salamanca, Spain. We used Laurence Bardin´s ‘Analysis of Content’, more specifically the ‘Categorical Analysis’ technique to data analysis. As data collection procedure we accomplished a field research, applying a questionnaire as an intentional sample of the meat industries segment from the Province of Salamanca, Spain. From data tabulation and analysis, we infer that information environments and flows are relevant to these companies business development, as well as we emphasized the need of information and knowledge management deployment, in a way to insure organizational processes quality, industrial chain production and companies competition to conquer potential markets.