970 resultados para Algorithmic patterns (Skeletons)


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Flight activity of foragers of four colonies of Plebeia remota (Holmberg, 1903) was registered from December 1998 to December 1999, using an automated system (photocells and PLC system). The colonies originated from two different regions: Cunha, state of São Paulo, and Prudentópolis, state of Paraná, Brazil. Flight activity was influenced by different climatic factors in each season. In the summer, the intensity of the correlations between flight activity and climatic factors was smaller than in the other seasons. During the autumn and winter, solar radiation was the factor that most influenced flight activity, while in the spring, this activity was influenced mainly by temperature. Except in the summer, the various climatic factors similarly influenced flight activity of all of the colonies. Flight activity was not affected by geographic origin of the colonies. Information concerning seasonal differences in flight activity of P. remota will be useful for prediction of geographic distribution scenarios under climatic changes.

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A nymph of Thaumamannia Drake & Davis, 1960, a rare vianaidine genus known only from adults, is described by the first time. The specimens were collected in the soil and walls of caves located in the state of Pará, Brazil. This is the first record of Vianaidinae for Brazil. The T. vanderdrifti fifth instar is compared with the same stadium of Anommatocoris coleopteratus (Kormilev, 1955), the only other vianaidine nymph described so far, and patterns between them and within the family are also discussed.

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ABSTRACT The present study encompasses the species composition and ecological characteristics of the snake community in a Cerrado-Amazon transition zone in Midwest of Brazil (state of Mato Grosso). The data were collected during six excursions to the "Tanguro" (study area) by visual encounter survey, pitfall traps with drift fences and non-systematic sampling. We collected 194 specimens, distributed in 34 species, 26 genera, and eight families. The most abundant species were Crotalus durissus Linnaeus, 1758 (n = 50), Philodryas olfersii (Lichtenstein, 1823) (n = 15), Philodryas nattereri Steindachner, 1870 (n = 13), Xenodon rabdocephalus (Wied, 1824) (n = 12), Lachesis muta (Linnaeus, 1766) (n = 10) and Erythrolamprus almadensis (Wagler, 1824) (n = 10). The composition of species found here represents a combination of Cerrado and Amazonian savanna fauna.

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ABSTRACT Quantitative evaluations of species distributional congruence allow evaluating previously proposed biogeographic regionalization and even identify undetected areas of endemism. The geographic scenery of Northwestern Argentina offers ideal conditions for the study of distributional patterns of species since the boundaries of a diverse group of biomes converge in a relatively small region, which also includes a diverse fauna of mammals. In this paper we applied a grid-based explicit method in order to recognize Patterns of Distributional Congruence (PDCs) and Areas of Endemism (AEs), and the species (native but non-endemic and endemic, respectively) that determine them. Also, we relate these distributional patterns to traditional biogeographic divisions of the study region and with a very recent phytogeographic study and we reconsider what previously rejected as 'spurious' areas. Finally, we assessed the generality of the patterns found. The analysis resulted in 165 consensus areas, characterized by seven species of marsupials, 28 species of bats, and 63 species of rodents, which represents a large percentage of the total species (10, 41, and 73, respectively). Twenty-five percent of the species that characterize consensus areas are endemic to the study region and define six AEs in strict sense while 12 PDCs are mainly defined by widely distributed species. While detailed quantitative analyses of plant species distribution data made by other authors does not result in units that correspond to Cabrera's phytogeographic divisions at this spatial scale, analyses of animal species distribution data does. We were able to identify previously unknown meaningful faunal patterns and more accurately define those already identified. We identify PDCs and AEs that conform Eastern Andean Slopes Patterns, Western High Andes Patterns, and Merged Eastern and Western Andean Slopes Patterns, some of which are re-interpreted at the light of known patterns of the endemic vascular flora. Endemism do not declines towards the south, but do declines towards the west of the study region. Peaks of endemism are found in the eastern Andean slopes in Jujuy and Tucumán/Catamarca, and in the western Andean biomes in Tucumán/Catamarca. The principal habitat types for endemic small mammal species are the eastern humid Andean slopes. Notwithstanding, arid/semi-arid biomes and humid landscapes are represented by the same number of AEs. Rodent species define 15 of the 18 General Patterns, and only in one they have no participation at all. Clearly, at this spatial scale, non-flying mammals, particularly rodents, are biogeographically more valuable species than flying mammals (bat species).

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We construct generating trees with with one, two, and three labels for some classes of permutations avoiding generalized patterns of length 3 and 4. These trees are built by adding at each level an entry to the right end of the permutation, which allows us to incorporate the adjacency condition about some entries in an occurrence of a generalized pattern. We use these trees to find functional equations for the generating functions enumerating these classes of permutations with respect to different parameters. In several cases we solve them using the kernel method and some ideas of Bousquet-Mélou [2]. We obtain refinements of known enumerative results and find new ones.

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"Es tracta d'un projecte dividit en dues parts independents però complementàries, realitzades per autors diferents. Aquest document conté originàriament altre material i/o programari només consultable a la Biblioteca de Ciència i Tecnologia"

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A simple and rapid method for differentialing the sibling species Biomphalaria tenagophila and Biomphalaria occidentalis by agarose gel electrophoresis (AGE) is described. Snail hemolymph is used as the test sample and the red colaration of the hemoglobin fraction permits visualization of the migration patterns without resorting to specific stains. Moreover, hemolymph samples may be obtained without killing the snail, thus permitting its use for other studies for breeding.

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Oxygen uptake was studied during the establishment of cephalocaudal polarity in the very early chick embryo, i.e., 10 hr before (stage VI) and at laying (stage X). Oxygen fluxes in minute regions of the intact blastoderms were measured in vitro by scanning microspectrophotometry in the presence or absence of glucose. The oxygen consumption of the whole blastoderm remained constant (6 nmol O2 X hr-1) throughout the period studied, although the number of cells increased more than twofold. The regional oxygen fluxes varied from 0.41 to 1.13 nmol O2 X hr-1 X mm-2 at stage VI and from 0.42 to 0.70 nmol O2 X hr-1 X mm-2 at stage X. At stage VI, the oxygen flux in the center of the blastoderm was significantly higher than that in its periphery. This pattern remained evident when the values were corrected for cell number or for cytoplasmic volume. At stage X, there was a tendency for the oxygen fluxes to decrease from the posterior to the anterior regions of the area pellucida. Thus the pattern of oxidative metabolism in the late uterine embryos seems to change from radial to bilateral. This change of symmetry probably reflects the process of formation of the embryonic axis. In addition, the fact that the oxygen uptake was similar in the presence or absence of glucose suggests that early chick embryos metabolize essentially intracellular stores.

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The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.