38 resultados para DISTRIBUTION MODELS

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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The theoretical E-curve for the laminar flow of non-Newtonian fluids in circular tubes may not be accurate for real tubular systems with diffusion, mechanical vibration, wall roughness, pipe fittings, curves, coils, or corrugated walls. Deviations from the idealized laminar flow reactor (LFR) cannot be well represented using the axial dispersion or the tanks-in-series models of residence time distribution (RTD). In this work, four RTD models derived from non-ideal velocity profiles in segregated tube flow are proposed. They were used to represent the RTD of three tubular systems working with Newtonian and pseudoplastic fluids. Other RTD models were considered for comparison. The proposed models provided good adjustments, and it was possible to determine the active volumes. It is expected that these models can be useful for the analysis of LFR or for the evaluation of continuous thermal processing of viscous foods.

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Species distribution models (SDMs) can be useful for different conservation purposes. We discuss the importance of fitting spatial scale and using current records and relevant predictors aiming conservation. We choose jaguar (Panthera onca) as a target species and Brazil and Atlantic Forest biome as study areas. We tested two different extents (continent and biome) and resolutions (similar to 4 Km and similar to 1 Km) in Maxent with 186 records and 11 predictors (bioclimatic, elevation, land-use and landscape structure). All models presented satisfactory AUC values (>0.70) and low omission errors (<23%). SDMs were scale-sensitive as the use of reduced extent implied in significant gains to model performance generating more constrained and real predictive distribution maps. Continental-scale models performed poorly in predicting potential current jaguar distribution, but they reached the historic distribution. Specificity increased significantly from coarse to finer-scale models due to the reduction of overprediction. The variability of environmental space (E-space) differed for most of climatic variables between continental and biome-scale and the representation of the E-space by predictors differed significantly (t = 2.42, g.I. = 9, P < 0.05). Refining spatial scale, incorporating landscape variables and improving the quality of biological data are essential for improving model prediction for conservation purposes.

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Historical climatic refugia predict genetic diversity in lowland endemics of the Brazilian Atlantic rainforest. Yet, available data reveal distinct biological responses to the Last Glacial Maximum (LGM) conditions across species of different altitudinal ranges. We show that species occupying Brazil's montane forests were significantly less affected by LGM conditions relative to lowland specialists, but that pre-Pleistocene tectonics greatly influenced their geographic variation. Our conclusions are based on palaeoclimatic distribution models, molecular sequences of the cytochrome b, 16S, and RAG-1 genes, and karyotype data for the endemic frog Proceratophrys boiei. DNA and chromosomal data identify in P. boiei at least two broadly divergent phylogroups, which have not been distinguished morphologically. Cytogenetic results also indicate an area of hybridization in southern Sao Paulo. The location of the phylogeographic break broadly matches the location of a NW-SE fault, which underwent reactivation in the Neogene and led to remarkable landscape changes in southeastern Brazil. Our results point to different mechanisms underpinning diversity patterns in lowland versus montane tropical taxa, and help us to understand the processes responsible for the large number of narrow endemics currently observed in montane areas of the southern Atlantic forest hotspot. (C) 2011 Elsevier Inc. All rights reserved.

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Assessment of the suitability of anthropogenic landscapes for wildlife species is crucial for setting priorities for biodiversity conservation. This study aimed to analyse the environmental suitability of a highly fragmented region of the Brazilian Atlantic Forest, one of the world's 25 recognized biodiversity hotspots, for forest bird species. Eight forest bird species were selected for the analyses, based on point counts (n = 122) conducted in April-September 2006 and January-March 2009. Six additional variables (landscape diversity, distance from forest and streams, aspect, elevation and slope) were modelled in Maxent for (1) actual and (2) simulated land cover, based on the forest expansion required by existing Brazilian forest legislation. Models were evaluated by bootstrap or jackknife methods and their performance was assessed by AUC, omission error, binomial probability or p value. All predictive models were statistically significant, with high AUC values and low omission errors. A small proportion of the actual landscape (24.41 +/- 6.31%) was suitable for forest bird species. The simulated landscapes lead to an increase of c. 30% in total suitable areas. In average, models predicted a small increase (23.69 +/- 6.95%) in the area of suitable native forest for bird species. Being close to forest increased the environmental suitability of landscapes for all bird species; landscape diversity was also a significant factor for some species. In conclusion, this study demonstrates that species distribution modelling (SDM) successfully predicted bird distribution across a heterogeneous landscape at fine spatial resolution, as all models were biologically relevant and statistically significant. The use of landscape variables as predictors contributed significantly to the results, particularly for species distributions over small extents and at fine scales. This is the first study to evaluate the environmental suitability of the remaining Brazilian Atlantic Forest for bird species in an agricultural landscape, and provides important additional data for regional environmental planning.

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Native bees are important providers of pollination services, but there are cumulative evidences of their decline. Global changes such as habitat losses, invasions of exotic species and climate change have been suggested as the main causes of the decline of pollinators. In this study, the influence of climate change on the distribution of 10 species of Brazilian bees was estimated with species distribution modelling. We used Maxent algorithm (maximum entropy) and two different scenarios, an optimistic and a pessimistic, to the years 2050 and 2080. We also evaluated the percentage reduction of species habitat based on the future scenarios of climate change through Geographic Information System (GIS). Results showed that the total area of suitable habitats decreased for all species but one under the different future scenarios. The greatest reductions in habitat area were found for Melipona bicolor bicolor and Melipona scutellaris, which occur predominantly in areas related originally to Atlantic Moist Forest. The species analysed have been reported to be pollinators of some regional crops and the consequence of their decrease for these crops needs further clarification. (C) 2012 Elsevier B.V. All rights reserved.

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Overhead distribution lines are often exposed to lightning overvoltages, whose waveforms vary widely and can differ substantially from the standard impulse voltage waveform (1,2 - 50). Different models have been proposed for predicting the strength of insulation subjected to impulses of non-standard waveforms. One of the most commonly used is the disruptive effect model, for which there are different methods for the estimation of the parameters required for its application. This paper aims at evaluating the dielectric behavior of medium voltage insulators subjected to impulses of non-standard waveforms, as well as at evaluating two methods for predicting their dielectric strength against such impulses. The test results relative to the critical lightning impulse flashover voltage (U50) and the volt-time characteristics obtained for the positive and negative polarities of different voltage waveforms are presented and discussed.

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This paper establishes the spawning habitat of the Brazilian sardine Sardinella brasiliensis and investigates the spatial variability of egg density and its relation with oceanographic conditions in the shelf of the south-east Brazil Bight (SBB). The spawning habitats of S. brasiliensis have been defined in terms of spatial models of egg density, temperature-salinity plots, quotient (Q) analysis and remote sensing data. Quotient curves (Q(C)) were constructed using the geographic distribution of egg density, temperature and salinity from samples collected during nine survey cruises between 1976 and 1993. The interannual sea surface temperature (SST) variability was determined using principal component analysis on the SST anomalies (SSTA) estimated from remote sensing data over the period between 1985 and 2007. The spatial pattern of egg occurrences in the SBB indicated that the largest concentration occurred between Paranagua and Sao Sebastiao. Spawning habitat expanded and contracted during the years, fluctuating around Paranagua. In January 1978 and January 1993, eggs were found nearly everywhere along the inner shelf of the SBB, while in January 1988 and 1991 spawning had contracted to their southernmost position. The SSTA maps for the spawning periods showed that in the case of habitat expansion (1993 only) anomalies over the SBB were zero or slightly negative, whereas for the contraction period anomalies were all positive. Sardinella brasiliensis is capable of exploring suitable spawning sites provided by the entrainment of the colder and less-saline South Atlantic Central Water onto the shelf by means of both coastal wind-driven (to the north-east of the SBB) and meander-induced (to the south-west of the SBB) upwelling.

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The Conway-Maxwell Poisson (COMP) distribution as an extension of the Poisson distribution is a popular model for analyzing counting data. For the first time, we introduce a new three parameter distribution, so-called the exponential-Conway-Maxwell Poisson (ECOMP) distribution, that contains as sub-models the exponential-geometric and exponential-Poisson distributions proposed by Adamidis and Loukas (Stat Probab Lett 39:35-42, 1998) and KuAY (Comput Stat Data Anal 51:4497-4509, 2007), respectively. The new density function can be expressed as a mixture of exponential density functions. Expansions for moments, moment generating function and some statistical measures are provided. The density function of the order statistics can also be expressed as a mixture of exponential densities. We derive two formulae for the moments of order statistics. The elements of the observed information matrix are provided. Two applications illustrate the usefulness of the new distribution to analyze positive data.

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In this paper we use Markov chain Monte Carlo (MCMC) methods in order to estimate and compare GARCH models from a Bayesian perspective. We allow for possibly heavy tailed and asymmetric distributions in the error term. We use a general method proposed in the literature to introduce skewness into a continuous unimodal and symmetric distribution. For each model we compute an approximation to the marginal likelihood, based on the MCMC output. From these approximations we compute Bayes factors and posterior model probabilities. (C) 2012 IMACS. Published by Elsevier B.V. All rights reserved.

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In this paper we obtain asymptotic expansions, up to order n(-1/2) and under a sequence of Pitman alternatives, for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the class of symmetric linear regression models. This is a wide class of models which encompasses the t model and several other symmetric distributions with longer-than normal tails. The asymptotic distributions of all four statistics are obtained for testing a subset of regression parameters. Furthermore, in order to compare the finite-sample performance of these tests in this class of models, Monte Carlo simulations are presented. An empirical application to a real data set is considered for illustrative purposes. (C) 2011 Elsevier B.V. All rights reserved.

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In this paper, an alternative skew Student-t family of distributions is studied. It is obtained as an extension of the generalized Student-t (GS-t) family introduced by McDonald and Newey [10]. The extension that is obtained can be seen as a reparametrization of the skewed GS-t distribution considered by Theodossiou [14]. A key element in the construction of such an extension is that it can be stochastically represented as a mixture of an epsilon-skew-power-exponential distribution [1] and a generalized-gamma distribution. From this representation, we can readily derive theoretical properties and easy-to-implement simulation schemes. Furthermore, we study some of its main properties including stochastic representation, moments and asymmetry and kurtosis coefficients. We also derive the Fisher information matrix, which is shown to be nonsingular for some special cases such as when the asymmetry parameter is null, that is, at the vicinity of symmetry, and discuss maximum-likelihood estimation. Simulation studies for some particular cases and real data analysis are also reported, illustrating the usefulness of the extension considered.

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The impact of biogeographical ancestry, self-reported 'race/color' and geographical origin on the frequency distribution of 10 CYP2C functional polymorphisms (CYP2C8*2, *3, *4, CYP2C9*2, *3, *5, *11, CYP2C19*2, *3 and *17) and their haplotypes was assessed in a representative cohort of the Brazilian population (n = 1034). TaqMan assays were used for allele discrimination at each CYP2C locus investigated. Individual proportions of European, African and Amerindian biogeographical ancestry were estimated using a panel of insertion-deletion polymorphisms. Multinomial log-linear models were applied to infer the statistical association between the CYP2C alleles and haplotypes (response variables), and biogeographical ancestry, self-reported Color and geographical origin (explanatory variables). The results showed that CYP2C19*3, CYP2C9*5 and CYP2C9*11 were rare alleles (<1%), the frequency of other variants ranged from 3.4% (CYP2C8*4) to 17.3% (CYP2C19*17). Two distinct haplotype blocks were identified: block 1 consists of three single nucleotide polymorphisms (SNPs) (CYP2C19*17, CYP2C19*2 and CYP2C9*2) and block 2 of six SNPs (CYP2C9*11, CYP2C9*3, CYP2C9*5, CYP2C8*2, CYP2C8*4 and CYP2C8*3). Diplotype analysis generated 41 haplotypes, of which eight had frequencies greater than 1% and together accounted for 96.4% of the overall genetic diversity. The distribution of CYP2C8 and CYP2C9 (but not CYP2C19) alleles, and of CYP2C haplotypes was significantly associated with self-reported Color and with the individual proportions of European and African genetic ancestry, irrespective of Color self-identification. The individual odds of having alleles CYP2C8*2, CYP2C8*3, CYP2C9*2 and CYP2C9*3, and haplotypes including these alleles, varied continuously as the proportion of European ancestry increased. Collectively, these data strongly suggest that the intrinsic heterogeneity of the Brazilian population must be acknowledged in the design and interpretation of pharmacogenomic studies of the CYP2C cluster in order to avoid spurious conclusions based on improper matching of study cohorts. This conclusion extends to other polymorphic pharmacogenes among Brazilians, and most likely to other admixed populations of the Americas. The Pharmacogenomics Journal (2012) 12, 267-276; doi: 10.1038/tpj.2010.89; published online 21 December 2010

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This finite element analysis (FEA) compared stress distribution on different bony ridges rehabilitated with different lengths of morse taper implants, varying dimensions of metal-ceramic crowns to maintain the occlusal alignment. Three-dimensional FE models were designed representing a posterior left side segment of the mandible: group control, 3 implants of 11 mm length; group 1, implants of 13 mm, 11 mm and 5 mm length; group 2, 1 implant of 11 mm and 2 implants of 5 mm length; and group 3, 3 implants of 5 mm length. The abutments heights were 3.5 mm for 13- and 11-mm implants (regular), and 0.8 mm for 5-mm implants (short). Evaluation was performed on Ansys software, oblique loads of 365N for molars and 200N for premolars. There was 50% higher stress on cortical bone for the short implants than regular implants. There was 80% higher stress on trabecular bone for the short implants than regular implants. There was higher stress concentration on the bone region of the short implants neck. However, these implants were capable of dissipating the stress to the bones, given the applied loads, but achieving near the threshold between elastic and plastic deformation to the trabecular bone. Distal implants and/or with biggest occlusal table generated greatest stress regions on the surrounding bone. It was concluded that patients requiring short implants associated with increased proportions implant prostheses need careful evaluation and occlusal adjustment, as a possible overload in these short implants, and even in regular ones, can generate stress beyond the physiological threshold of the surrounding bone, compromising the whole system.

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In this paper, we proposed a new three-parameter long-term lifetime distribution induced by a latent complementary risk framework with decreasing, increasing and unimodal hazard function, the long-term complementary exponential geometric distribution. The new distribution arises from latent competing risk scenarios, where the lifetime associated scenario, with a particular risk, is not observable, rather we observe only the maximum lifetime value among all risks, and the presence of long-term survival. The properties of the proposed distribution are discussed, including its probability density function and explicit algebraic formulas for its reliability, hazard and quantile functions and order statistics. The parameter estimation is based on the usual maximum-likelihood approach. A simulation study assesses the performance of the estimation procedure. We compare the new distribution with its particular cases, as well as with the long-term Weibull distribution on three real data sets, observing its potential and competitiveness in comparison with some usual long-term lifetime distributions.

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Two structural properties in mixed alkali metal phosphate glasses that seem to be crucial to the development of the mixed ion effect in dc conductivity were systematically analyzed in Na mixed metaphosphates: the local order around the mobile species, and their distribution and mixing in the glass network. The set of glasses considered here, Na1-xMxPO3 with M = Li, Ag, K, Rb, and Cs and 0 <= x <= 1, encompass a broad degree of size mismatch between the mixed cation species. A comprehensive solid-state nuclear magnetic resonance study was carried out using P-31 MAS, Na-23 triple quantum MAS, Rb-87 QCPMG, P-31-Na-23 REDOR, Na-23-Li-7 and Li-7-Li-6 SEDOR, and Na-23 spin echo decay. It was observed that the arrangement of P atoms around Na in the mixed glasses was indistinguishable from that observed in the NaPO3 glass. However, systematic distortions in the local structure of the 0 environments around Na were observed, related to the presence of the second cation. The average Na-O distances show an expansion/compression When Na+ ions are replaced by cations with respectively smaller/bigger radii. The behavior of the nuclear electric quadrupole coupling. constants indicates that this expansion reduces the local symmetry, while the compression produces the opposite effect These effects become marginally small when the site mismatch between the cations is small, as in Na-Ag mixed glasses. The present study confirms the intimate mixing of cation species at the atomic scale, but clear deviations from random mixing were detected in systems with larger alkali metal ions (Cs-Na, K-Na, Rb-Na). In contrast, no deviations from the statistical ion mixture were found in the systems Ag-Na and Li-Na, where mixed cations are either of radii comparable to (Ag+) or smaller than (Li+) Na+. The set of results supports two fundamental structural features of the models proposed to explain the mixed ion effect: the. structural specificity of the sites occupied by each cation species and their mixing at the atomic scale.