29 resultados para UNFAIR COMPETITION


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Crematogaster cf. victima is a common inhabitant in the sheet web nests of the social spider Anelosimus eximius in the central Amazon basin near Manaus. A number of other ant species were found foraging on the non-sticky webs of A. eximius, but none of these reached the web occupation frequency found in C. cf. victima, nor, with the exception of an unidentified species of Pheidole, did they form satellite nests in the web, as did this species. Many prey which escaped the knock-down threads of the sheet web of A. eximius colonies were captured by ants in the lower web portions which they dominated. Furthermore, prey which were rejected by A. eximius, especially large, heavily sclerotized beetles, were also consumed by this ant. Repeated observations and experiments suggest that C. cf. victima is able to deter A. eximius activity through aerial venom release. Resources lost by A. eximius colonies to ants, especially C. cf. victima, in colonial web area and prey, may pose significant costs and may reduce colony growth.

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We study a one-dimensional extended Peierls-Hubbard model coupled to intracell and intercell phonons for a half-filled band. The calculations are made using the Hartree-Fock and adiabatic approximations for arbitrary temperature. In addition to static spin, charge, and bond density waves, we predict intermediate phases that lack inversion symmetry, and phase transitions that reduce symmetry on increasing temperature.

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In blowflies, larval aggregation in patches of food can be both intra- and interspecific, depending upon the degree to which competitors are clumped among the patches. In the present study, the implications of spatial aggregation for larval competition was investigated in experimental populations of the introduced blowfly Chrysomya putoria and the native Cochliomyia macellaria, using data from survival to adulthood in a range of single- and double-species larval cultures. The reduction in C. macellaria survival rate in the presence of C. putoria suggests that the former species is the inferior competitor. The results on survival to adulthood for both species in single- and double-species cultures can be explained in the light of the relationship between the level of intra- and interspecific aggregation and the efficiency of the larval feeding process. The possible implications of these results for the population biology of both species in natural environments are discussed.

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Toxocariasis is caused by infection of man by Toxocara canis and Toxocara, cati larvae, the common roundworm of dogs and cats. Because larvae are difficult to detect in tissues, diagnosis is mostly based on serology. Non specific reactions are observed mainly due to cross-reactivity with Ascaris sp antigens. This investigation aimed at developing and evaluating an indirect antibody competition ELISA (IACE) employing a specific rabbit IgG anti-Toxocara canis excretory-secretory antigens as the competition antibody. in order to improve indirect ELISA specificity performed for toxocariasis diagnosis. For that, the rabbit IgG was previously absorbed by Ascaris suum adult antigens. Sensitivity and specificity of IACE were first evaluated in 28 serum samples of mice experimentally infected with T. canis embryonated eggs. Adopting cut-off value established in this population before infection, sensitivity and specificity were 100% after 20 days post-inoculation. For human population IACE was evaluated using sera from 440 patients with clinical signs of toxocariasis and the cut-off value was established with 60 serum samples from apparently healthy individuals. Using as reference test the indirect ELISA performed by Adolfo Lutz Institute, sensitivity was 60.2%, specificity was 98% and concordance was 77.3%. Repeatability of IACE was evaluated by the inter-reactions variation coefficient (2.4%).

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The aim of the present work was to carry out experimental comparison between humic substances (HS) and representative α-amino acids (methionine, methionine sulfoxide and cysteine hydrochloride) in relation to the complexation of biologically active trace elements (Al, Cu, Pb, Mn, Zn, Cd and Ni). A mobile time-controlled tangential-flow UF technique was applied to differentiate between HS-metal and α-aminoacids-metal complexes. Metal determinations were conventionally carried out using a ICP-OES. The results showed that HS may be considered as a selective complexing agents with higher metal bonding capability in relation to Al, Cu and Pb, the fact that may be clinically important.

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Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate wrong labels to a large portion or even the entire data set. This paper aims to address this problem by presenting a graph-based (network-based) semi-supervised learning method, specifically designed to handle data sets with mislabeled samples. The method uses teams of walking particles, with competitive and cooperative behavior, for label propagation in the network constructed from the input data set. The proposed model is nature-inspired and it incorporates some features to make it robust to a considerable amount of mislabeled data items. Computer simulations show the performance of the method in the presence of different percentage of mislabeled data, in networks of different sizes and average node degree. Importantly, these simulations reveals the existence of the critical points of the mislabeled subset size, below which the network is free of wrong label contamination, but above which the mislabeled samples start to propagate their labels to the rest of the network. Moreover, numerical comparisons have been made among the proposed method and other representative graph-based semi-supervised learning methods using both artificial and real-world data sets. Interestingly, the proposed method has increasing better performance than the others as the percentage of mislabeled samples is getting larger. © 2012 IEEE.

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Identification and classification of overlapping nodes in networks are important topics in data mining. In this paper, a network-based (graph-based) semi-supervised learning method is proposed. It is based on competition and cooperation among walking particles in a network to uncover overlapping nodes by generating continuous-valued outputs (soft labels), corresponding to the levels of membership from the nodes to each of the communities. Moreover, the proposed method can be applied to detect overlapping data items in a data set of general form, such as a vector-based data set, once it is transformed to a network. Usually, label propagation involves risks of error amplification. In order to avoid this problem, the proposed method offers a mechanism to identify outliers among the labeled data items, and consequently prevents error propagation from such outliers. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method. © 2012 Springer-Verlag.

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Intercropping is a cropping system for the production of greenhouse vegetables. It uses space more efficiently, thus reducing the cost of production. Intercropping tomato and lettuce has not been studied, but knowledge of the competitive and agroeconomic indices of these vegetables can help in the management of the intercropping system. The objectives of this study were to assess, through biological and agroeconomic indices, the competition between species and the profitability of intercropping tomato and lettuce at different times of transplantation over two growing seasons (autumn-winter and summer-winter) in greenhouse conditions. In autumn-winter, two experiments were conducted with a randomised complete-block design and five replicates. Tomato and lettuce were the main crops in the individual experiments. Treatments were arranged in a factorial of two cropping systems (intercropping and individual crops) with four transplants of the secondary crop (0, 10, 20 and 30 days after) plus an additional treatment (individual main crop). These two experiments were repeated in summer-winter. Tomato was the dominant crop regardless of transplant order. Intercropping systems established with transplants of both species on the same day had higher values of indices of competition and bio-agroeconomic efficiency than systems with longer periods of transplants between main and secondary crops. The intercropping of lettuce and tomato in greenhouses, regardless of transplant time or order, had bio-agroeconomic advantages over individual crops. The transplantation of tomato after lettuce is recommended for greater profitability.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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

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

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

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