4 resultados para Emergence Traps

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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A clinical Klebsiella pneumoniae isolate carrying the extended-spectrum beta-lactamase gene variants bla(SHV-40), bla(TEM-116) and bla(GES-7) was recovered. Cefoxitin and ceftazidime activity was most affected by the presence of these genes and an additional resistance to trimethoprim-sulphamethoxazole was observed. The bla(GES-7) gene was found to be inserted into a class 1 integron. These results show the emergence of novel bla(TEM) and bla(SHV) genes in Brazil. Moreover, the presence of class 1 integrons suggests a great potential for dissemination of bla(GES) genes into diverse nosocomial pathogens. Indeed, the bla(GES-7) gene was originally discovered in Enterobacter cloacae in Greece and, to our knowledge, has not been reported elsewhere.

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Activities involving fauna monitoring are usually limited by the lack of resources; therefore, the choice of a proper and efficient methodology is fundamental to maximize the cost-benefit ratio. Both direct and indirect methods can be used to survey mammals, but the latter are preferred due to the difficulty to come in sight of and/or to capture the individuals, besides being cheaper. We compared the performance of two methods to survey medium and large-sized mammal: track plot recording and camera trapping, and their costs were assessed. At Jatai Ecological Station (S21 degrees 31`15 ``- W47 degrees 34`42 ``-Brazil) we installed ten camera traps along a dirt road directly in front of ten track plots, and monitored them for 10 days. We cleaned the plots, adjusted the cameras, and noted down the recorded species daily. Records taken by both methods showed they sample the local richness in different ways (Wilcoxon, T=231; p;;0.01). The track plot method performed better on registering individuals whereas camera trapping provided records which permitted more accurate species identification. The type of infra-red sensor camera used showed a strong bias towards individual body mass (R(2)=0.70; p=0.017), and the variable expenses of this method in a 10-day survey were estimated about 2.04 times higher compared to track plot method; however, in a long run camera trapping becomes cheaper than track plot recording. Concluding, track plot recording is good enough for quick surveys under a limited budget, and camera trapping is best for precise species identification and the investigation of species details, performing better for large animals. When used together, these methods can be complementary.

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We have studied an agent model which presents the emergence of sexual barriers through the onset of assortative mating, a condition that might lead to sympatric speciation. In the model, individuals are characterized by two traits, each determined by a single locus A or B. Heterozygotes on A are penalized by introducing an adaptive difference from homozygotes. Two niches are available. Each A homozygote is adapted to one of the niches. The second trait, called the marker trait has no bearing on the fitness. The model includes mating preferences, which are inherited from the mother and subject to random variations. A parameter controlling recombination probabilities of the two loci is also introduced. We study the phase diagram by means of simulations, in the space of parameters (adaptive difference, carrying capacity, recombination probability). Three phases are found, characterized by (i) assortative mating, (ii) extinction of one of the A alleles and (iii) Hardy-Weinberg like equilibrium. We also make perturbations of these phases to see how robust they are. Assortative mating can be gained or lost with changes that present hysteresis loops, showing the resulting equilibrium to have partial memory of the initial state and that the process of going from a polymorphic panmictic phase to a phase where assortative mating acts as sexual barrier can be described as a first-order transition. (C) 2009 Published by Elsevier Ltd.

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Scenarios for the emergence or bootstrap of a lexicon involve the repeated interaction between at least two agents who must reach a consensus on how to name N objects using H words. Here we consider minimal models of two types of learning algorithms: cross-situational learning, in which the individuals determine the meaning of a word by looking for something in common across all observed uses of that word, and supervised operant conditioning learning, in which there is strong feedback between individuals about the intended meaning of the words. Despite the stark differences between these learning schemes, we show that they yield the same communication accuracy in the limits of large N and H, which coincides with the result of the classical occupancy problem of randomly assigning N objects to H words.