6 resultados para adaptation evolution


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Tracking the evolution of research in waste recycling science (WRS) can be valuable for environmental agencies, as well as for recycling businesses. Maps of science are visual, easily readable representations of the cognitive structure of a branch of science, a particular area of research or the global spectrum of scientific production. They are generally built upon evidence collected from reliable sources of information, such as patent and scientific publication databases. This study uses the methodology developed by Rafols et al. (2010) to make a “double overlay map” of WRS upon a basemap reflecting the cognitive structure of all journal-published science, for the years 2005 and 2010. The analysis has taken into account the cognitive areas where WRS articles are published and the areas from where it takes its intellectual nourishing, paying special attention to the growing trends of the key areas. Interpretation of results lead to the conclusion that extraction of energy from waste will probably be an important research topic in the future, along with developments in general chemistry and chemical engineering oriented to the recovery of valuable materials from waste. Agricultural and material sciences, together with the combined economics, politics and geography field, are areas with which WRS shows a relevant and ever increasing cognitive relationship.

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Differently from previous studies of tag-based cooperation, we assume that individuals fail to recognize their own tag. Due to such incomplete information, the action taken against the opponent cannot be based on similarity, although it is still motivated by the tag displayed by the opponent. We present stability conditions for the case when individuals play unconditional cooperation, unconditional defection or conditional cooperation. We then consider the removal of one or two strategies. Results show that conditional cooperators are the most resilient agents against extinction and that the removal of unconditional cooperators may lead to the extinction of unconditional defectors.

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Eguíluz, Federico; Merino, Raquel; Olsen, Vickie; Pajares, Eterio; Santamaría, José Miguel (eds.)

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Papillomaviruses (PVs) are widespread pathogens. However, the extent of PV infections in bats remains largely unknown. This work represents the first comprehensive study of PVs in Iberian bats. We identified four novel PVs in the mucosa of free-ranging Eptesicus serotinus (EserPV1, EserPV2, and EserPV3) and Rhinolophus ferrumequinum (RferPV1) individuals and analyzed their phylogenetic relationships within the viral family. We further assessed their prevalence in different populations of E. serotinus and its close relative E. isabellinus. Although it is frequent to read that PVs co-evolve with their host, that PVs are highly species-specific, and that PVs do not usually recombine, our results suggest otherwise. First, strict virus-host co-evolution is rejected by the existence of five, distantly related bat PV lineages and by the lack of congruence between bats and bat PVs phylogenies. Second, the ability of EserPV2 and EserPV3 to infect two different bat species (E. serotinus and E. isabellinus) argues against strict host specificity. Finally, the description of a second noncoding region in the RferPV1 genome reinforces the view of an increased susceptibility to recombination in the E2-L2 genomic region. These findings prompt the question of whether the prevailing paradigms regarding PVs evolution should be reconsidered.

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Computer vision algorithms that use color information require color constant images to operate correctly. Color constancy of the images is usually achieved in two steps: first the illuminant is detected and then image is transformed with the chromatic adaptation transform ( CAT). Existing CAT methods use a single transformation matrix for all the colors of the input image. The method proposed in this paper requires multiple corresponding color pairs between source and target illuminants given by patches of the Macbeth color checker. It uses Delaunay triangulation to divide the color gamut of the input image into small triangles. Each color of the input image is associated with the triangle containing the color point and transformed with a full linear model associated with the triangle. Full linear model is used because diagonal models are known to be inaccurate if channel color matching functions do not have narrow peaks. Objective evaluation showed that the proposed method outperforms existing CAT methods by more than 21%; that is, it performs statistically significantly better than other existing methods.