50 resultados para Asymptote


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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How stable are individual differences in self-esteem? We examined the time-dependent decay of rank-order stability of self-esteem and tested whether stability asymptotically approaches zero or a nonzero value across long test–retest intervals. Analyses were based on 6 assessments across a 29-year period of a sample of 3,180 individuals aged 14 to 102 years. The results indicated that, as test–retest intervals increased, stability exponentially decayed and asymptotically approached a nonzero value (estimated as .43). The exponential decay function explained a large proportion of variance in observed stability coefficients, provided a better fit than alternative functions, and held across gender and for all age groups from adolescence to old age. Moreover, structural equation modeling of the individual-level data suggested that a perfectly stable trait component underlies stability of self-esteem. The findings suggest that the stability of self-esteem is relatively large, even across very long periods, and that self-esteem is a trait-like characteristic.

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In the analysis of tagging data, it has been found that the least-squares method, based on the increment function known as the Fabens method, produces biased estimates because individual variability in growth is not allowed for. This paper modifies the Fabens method to account for individual variability in the length asymptote. Significance tests using t-statistics or log-likelihood ratio statistics may be applied to show the level of individual variability. Simulation results indicate that the modified method reduces the biases in the estimates to negligible proportions. Tagging data from tiger prawns (Penaeus esculentus and Penaeus semisulcatus) and rock lobster (Panulirus ornatus) are analysed as an illustration.

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Seed persistence is poorly quantified for invasive plants of subtropical and tropical environments and Lantana camara, one of the world's worst weeds, is no exception. We investigated germination, seedling emergence, and seed survival of two lantana biotypes (Pink and pink-edged red [PER]) in southeastern Queensland, Australia. Controlled experiments were undertaken in 2002 and repeated in 2004, with treatments comprising two differing environmental regimes (irrigated and natural rainfall) and sowing depths (0 and 2 cm). Seed survival and seedling emergence were significantly affected by all factors (time, biotype, environment, sowing depth, and cohort) (P < 0.001). Seed dormancy varied with treatment (environment, sowing depth, biotype, and cohort) (P < 0.001), but declined rapidly after 6 mo. Significant differential responses by the two biotypes to sowing depth and environment were detected for both seed survival and seedling emergence (P < 0.001). Seed mass was consistently lower in the PER biotype at the population level (P < 0.001), but this variation did not adequately explain the differential responses. Moreover, under natural rainfall the magnitude of the biotype effect was unlikely to result in ecologically significant differences. Seed survival after 36 mo under natural rainfall ranged from 6.8 to 21.3%. Best fit regression analysis of the decline in seed survival over time yielded a five-parameter exponential decay model with a lower asymptote approaching −0.38 (% seed survival = [( 55 − (−0.38)) • e (k • t)] + −0.38; R2 = 88.5%; 9 df). Environmental conditions and burial affected the slope parameter or k value significantly (P < 0.01). Seed survival projections from the model were greatest for buried seeds under natural rainfall (11 yr) and least under irrigation (3 yr). Experimental data and model projections suggest that lantana has a persistent seed bank and this should be considered in management programs, particularly those aimed at eradication.

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The variation in the bulk modulus of semiconductor nanoparticles has been studied within first-principles electronic-structure calculations using the local density approximation (LDA) for the exchange correlation. Quantum Monte Carlo calculations carried out for a silicon nanocrystal Si87H76 provided reasonable agreement with the LDA results. An enhancement was observed in the bulk modulus as the size of the nanoparticle was decreased, with modest enhancements being predicted for the largest nanoparticles studied here, a size just accessible in experiments. To access larger sizes, we fit our calculated bulk moduli to the same empirical law for all materials, the asymptote of which is the bulk value of the modulus. This was found to be within 2-10% of the independently calculated value. The origin of the enhancement has been discussed in terms of Cohen's empirical law M.L. Cohen, Phys. Rev. B 32, 7988 (1985)] as well as other possible scenarios.

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Film flows on inclined surfaces are often assumed to be of constant thickness, which ensures that the velocity profile is half-Poiseuille. It is shown here that by shallow water theory, only flows in a portion of Reynolds number-Froude number (Re-Fr) plane can asymptotically attain constant film thickness. In another portion on the plane, the constant thickness solution appears as an unstable fixed point, while in other regions the film thickness seems to asymptote to a positive slope. Our simulations of the Navier-Stokes equations confirm the predictions of shallow water theory at higher Froude numbers, but disagree with them at lower Froude numbers. We show that different regimes of film flow show completely different stability behaviour from that predicted earlier. Supercritical decelerating flows are shown to be always unstable, whereas accelerating flows become unstable below a certain Reynolds number for a given Froude number. Subcritical flows on the other hand are shown to be unstable above a certain Reynolds number. In some range of parameters, two solutions for the base flowexist, and the attached profile is found to be more stable. All flows except those with separation become more stable as they proceed downstream. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4758299]

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This thesis is divided into two parts: interacting dark matter and fluctuations in cosmology. There is an incongruence between the properties that dark matter is expected to possess between the early universe and the late universe. Weakly-interacting dark matter yields the observed dark matter relic density and is consistent with large-scale structure formation; however, there is strong astrophysical evidence in favor of the idea that dark matter has large self-interactions. The first part of this thesis presents two models in which the nature of dark matter fundamentally changes as the universe evolves. In the first model, the dark matter mass and couplings depend on the value of a chameleonic scalar field that changes as the universe expands. In the second model, dark matter is charged under a hidden SU(N) gauge group and eventually undergoes confinement. These models introduce very different mechanisms to explain the separation between the physics relevant for freezeout and for small-scale dynamics.

As the universe continues to evolve, it will asymptote to a de Sitter vacuum phase. Since there is a finite temperature associated with de Sitter space, the universe is typically treated as a thermal system, subject to rare thermal fluctuations, such as Boltzmann brains. The second part of this thesis begins by attempting to escape this unacceptable situation within the context of known physics: vacuum instability induced by the Higgs field. The vacuum decay rate competes with the production rate of Boltzmann brains, and the cosmological measures that have a sufficiently low occurrence of Boltzmann brains are given more credence. Upon further investigation, however, there are certain situations in which de Sitter space settles into a quiescent vacuum with no fluctuations. This reasoning not only provides an escape from the Boltzmann brain problem, but it also implies that vacuum states do not uptunnel to higher-energy vacua and that perturbations do not decohere during slow-roll inflation, suggesting that eternal inflation is much less common than often supposed. Instead, decoherence occurs during reheating, so this analysis does not alter the conventional understanding of the origin of density fluctuations from primordial inflation.

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This paper reviews the development of computational fluid dynamics (CFD) specifically for turbomachinery simulations and with a particular focus on application to problems with complex geometry. The review is structured by considering this development as a series of paradigm shifts, followed by asymptotes. The original S1-S2 blade-blade-throughflow model is briefly described, followed by the development of two-dimensional then three-dimensional blade-blade analysis. This in turn evolved from inviscid to viscous analysis and then from steady to unsteady flow simulations. This development trajectory led over a surprisingly small number of years to an accepted approach-a 'CFD orthodoxy'. A very important current area of intense interest and activity in turbomachinery simulation is in accounting for real geometry effects, not just in the secondary air and turbine cooling systems but also associated with the primary path. The requirements here are threefold: capturing and representing these geometries in a computer model; making rapid design changes to these complex geometries; and managing the very large associated computational models on PC clusters. Accordingly, the challenges in the application of the current CFD orthodoxy to complex geometries are described in some detail. The main aim of this paper is to argue that the current CFD orthodoxy is on a new asymptote and is not in fact suited for application to complex geometries and that a paradigm shift must be sought. In particular, the new paradigm must be geometry centric and inherently parallel without serial bottlenecks. The main contribution of this paper is to describe such a potential paradigm shift, inspired by the animation industry, based on a fundamental shift in perspective from explicit to implicit geometry and then illustrate this with a number of applications to turbomachinery.

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We studied social organization, behavior, and range use of the Yunnan snub-nosed monkey (Rhinopithecus bieti) at Wuyapiya (99 degrees 12'E, 28 degrees 30'N, the People's Republic of China) over 12 months between May 1992 and June 1994. The Wuyapiya band contained greater than or equal to 175 members and had two levels of social organization. At one level, the monkeys formed multifemale, one-male units (OMUs) similar to those of many other colobines. At another level, 15 to 18 OMUs traveled together in a cohesive band. Unlike the bands of other species of Rhinopithecus, the Wuyapiya band of R. bieti did not show seasonal fission-fusion, although some social behavior, such as male-male aggression, was seasonal. With regard to range use, the Wuyapiya band had a large home range and long daily travel distances compared with other colobines. Minimum range size in 1 year at Wuyapiya is 16.25 km(2), although there is no asymptote for range size as a function of observation time. Range size for the Wuyapiya band is 25.25 km(2) over the 2-year study and appeared to cover 100 km(2) between 1985 and 1994. The primary food of R. bieti at Wuyapiya is lichens, which are ubiquitous in fir frees. The multitiered social organization of R. bieti appears to result from the interaction of food resource characters with the forces of mate competition, with band sizes based on female responses to the spatial and temporal characteristics of lichens and subdivisions within bands based on male competition for mates.

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This article introduces a new neural network architecture, called ARTMAP, that autonomously learns to classify arbitrarily many, arbitrarily ordered vectors into recognition categories based on predictive success. This supervised learning system is built up from a pair of Adaptive Resonance Theory modules (ARTa and ARTb) that are capable of self-organizing stable recognition categories in response to arbitrary sequences of input patterns. During training trials, the ARTa module receives a stream {a^(p)} of input patterns, and ARTb receives a stream {b^(p)} of input patterns, where b^(p) is the correct prediction given a^(p). These ART modules are linked by an associative learning network and an internal controller that ensures autonomous system operation in real time. During test trials, the remaining patterns a^(p) are presented without b^(p), and their predictions at ARTb are compared with b^(p). Tested on a benchmark machine learning database in both on-line and off-line simulations, the ARTMAP system learns orders of magnitude more quickly, efficiently, and accurately than alternative algorithms, and achieves 100% accuracy after training on less than half the input patterns in the database. It achieves these properties by using an internal controller that conjointly maximizes predictive generalization and minimizes predictive error by linking predictive success to category size on a trial-by-trial basis, using only local operations. This computation increases the vigilance parameter ρa of ARTa by the minimal amount needed to correct a predictive error at ARTb· Parameter ρa calibrates the minimum confidence that ARTa must have in a category, or hypothesis, activated by an input a^(p) in order for ARTa to accept that category, rather than search for a better one through an automatically controlled process of hypothesis testing. Parameter ρa is compared with the degree of match between a^(p) and the top-down learned expectation, or prototype, that is read-out subsequent to activation of an ARTa category. Search occurs if the degree of match is less than ρa. ARTMAP is hereby a type of self-organizing expert system that calibrates the selectivity of its hypotheses based upon predictive success. As a result, rare but important events can be quickly and sharply distinguished even if they are similar to frequent events with different consequences. Between input trials ρa relaxes to a baseline vigilance pa When ρa is large, the system runs in a conservative mode, wherein predictions are made only if the system is confident of the outcome. Very few false-alarm errors then occur at any stage of learning, yet the system reaches asymptote with no loss of speed. Because ARTMAP learning is self stabilizing, it can continue learning one or more databases, without degrading its corpus of memories, until its full memory capacity is utilized.

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The main interest in the assessment of forest species diversity for conservation purposes is in the rare species. The main problem in the tropical rain forests is that most of the species are rare. Assessment of species diversity in the tropical rain forests is therefore often concerned with estimating that which is not observed in recorded samples. Statistical methodology is therefore required to try to estimate the truncated tail of the species frequency distribution, or to estimate the asymptote of species/diversity-area curves. A Horvitz-Thompson estimator of the number of unobserved (“virtual”) species in each species intensity class is proposed. The approach allows a definition of an extended definition of diversity, ( or generalised Renyi entropy). The paper presents a case study from data collected in Jambi, Sumatra, and the “extended diversity measure” is used on the species data.

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Published ab-initio and pseudopotential calculations for the dialkali halide systems suggest that the preferred co-linear geometry is for the metal to approach the metal end of the alkali halide. Here, ab-initio calculations on the Li2F system reveal that the well depth on the halide side in this radical is much deeper and is a local saddle-point associated with the ionic non-linear global minima. Although many features of the pseudopotential surfaces are confirmed, significant differences are apparent including the existence of a linear excited state instead of a triangular one, a considerably deeper global minimum some 50% lower in energy and a close approach between the X2A1 and the states, with the minimum 87 kJ mol-1 below the ground state asymptote. All the results can be rationalised as the avoided crossings between a long range, covalent potential dominant within the LiLiF geometry and an ionic state that forms the global minimum. Calculations on the 3rd 2A' potential indicate that even for Li + LiF collisions at ultracold temperatures the collision dynamics could involve as many as three electronic states.

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Invasive species can have profound impacts on communities and it is increasingly recognized that such effects may be mediated by parasitism. The 'enemy release' hypothesis posits that invaders may be successful and have high impacts owing to escape from parasitism. Alternatively, we hypothesize that parasites may increase host feeding rates and hence parasitized invaders may have increased community impacts. Here, we investigate the influence of parasitism on the predatory impact of the invasive freshwater amphipod Gammarus pulex. Up to 70 per cent of individuals are infected with the acanthoce- phalan parasite Echinorhynchus truttae, but parasitized individuals were no different in body condition to those unparasitized. Parasitized individuals consumed significantly more prey (Asellus aquaticus; Isopoda) than did unparasitized individuals. Both parasitized and unparasitized individuals displayed Type-II functional responses (FRs), with the FR for parasitized individuals rising more steeply, with a higher asymptote, compared with unparasi- tized individuals. While the parasite reduced the fitness of individual females, we predict a minor effect on population recruitment because of low parasite prevalence in the peak reproductive period. The parasite thus has a large per capita effect on predatory rate but a low population fitness effect, and thus may enhance rather than reduce the impact of this invader.

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The spatial location of microorganisms in the soil three-dimensional structure with respect to their substrates plays an important role in the persistence and turnover of natural and xenobiotic organic compounds. To study the effect of spatial location on the mineralisation of 14C-2,4-dichlorophenol (2,4-DCP, 0.15 or 0.31 μmol g-1) and 14C-glucose (2.77 μmol g-1), columns packed with autoclaved soil aggregates (2-5 mm) were used. Using a chloride tracer of water movement, the existence of 'immobile' water, which was by-passed by preferentially flowing 'mobile' water, was demonstrated. By manipulation of the soil moisture content, the substrates were putatively placed to these conceptual hydrological domains (immobile and mobile water). Leaching studies revealed that approximately 1.7 (glucose) and 3.4 (2.4-DCP) times the amount of substrate placed in mobile water was recovered in the first 4 fractions of leachate when compared to substrate placed in immobile water. The marked difference in the breakthrough curves was taken as evidence of successful substrate placement. The 2,4-DCP degrading bacterium, Burkholderia sp. RASCc2, was inoculated in mobile water (1.8-5.2 × 107 cells g-1 soil) and parameters (asymptote, time at maximum rate, calculated maximum rate) describing the mineralisation kinetics of 2,4-DCP and glucose previously added to immobile or mobile water domains were compared, For glucose, there was no significant effect (P > 0.1) of substrate placement on any of the mineralisation parameters. However, substrate placement had a significant effect (P < 0.05) on parameters describing 2,4-DCP mineralisation. In particular, 2,4-DCP added in mobile water was mineralised with a greater maximum rate and with a reduced time at maximum rate when compared to 2,4-DCP added to immobile water. The difference in response between the two test substrates may reflect the importance of sorption in controlling the spatial bioavailability of compounds in soil. © 2002 Elsevier Science Ltd. All rights reserved.

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Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal