920 resultados para diffusive viscoelastic model, global weak solution, error estimate
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Three novel mixed bridged trinuclear and one tetranuclear copper(II) complexes of tridentate NNO donor Schiff base ligands [Cu-3(L-1)(2)(mu(LI)-N-3)(2)(CH3OH)(2)(BF2)(2)] (1), [Cu-3(L-1)(2)(mu(LI)-NO3-I kappa O.2 kappa O')(2)] (2), [Cu-3(L-2)(2)(mu(LI)-N-3)(2)(mu-NOI-I kappa O 2 kappa O')(2)] (3) and [Cu-4(L-3)(2)(mu(LI)-N-3)(4)(mu-CH3COO-I kappa O 2 kappa O')(2)] (4) have been synthesized by reaction of the respective tridentate ligands (L-1 = 2[1-(2-dimethylamino-ethylimino)-ethyl]-phenol, L-2 = 2[1-(2-diethylamino-ethylimino)-ethyl]-phenol, L-3 = 2-[1-(2-dimethylamino-ethylimino)-methyl]-phenol) with the corresponding copper(II) salts in the presence of NaN3 The complexes are characterized by single-crystal X-ray diffraction analyses and variable-temperature magnetic measurements Complex 1 is composed of two terminal [Cu(L-1)(mu(LI)-N-3)] units connected by a central [Cu(BF4)(2)] unit through nitrogen atoms of end-on azido ligands and a phenoxo oxygen atom of the tridentate ligand The structures of 2 and 3 are very similar, the only difference is that the central unit is [Cu(NO1)(2)] and the nitrate group forms an additional mu-NO3-I kappa O 2 kappa O' bridge between the terminal and central copper atoms In complex 4, the central unit is a di-mu(L1)-N-3 bridged dicopper entity, [Cu-2(mu(L1)-N-3)(2)(CH3COO)(2)] that connects two terminal [Cu(L-3)(mu(L1)-N-3)] units through end-on azido; phenoxo oxygen and mu-CH3COO-1 kappa O center dot 2 kappa O' triple bridges to result in a tetranuclear unit Analyses of variable-temperature magnetic susceptibility data indicates that there is a global weak antiferromagnetic interaction between the copper(II) ions in complexes 1-3, with the exchange parameter J of -9 86, -11 6 and -19 98 cm(-1) for 1-3, respectively In complex 4 theoretical calculations show the presence of an antiferromagnetic coupling in the triple bridging ligands (acetato, phenoxo and azido) while the interaction through the double end-on azido bridging ligand is strongly ferromagnetic.
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Four new nickel(II) complexes, [Ni2L2(NO2)2]·CH2Cl2·C2H5OH, 2H2O (1), [Ni2L2(DMF)2(m-NO2)]ClO4·DMF (2a), [Ni2L2(DMF)2(m-NO2)]ClO4 (2b) and [Ni3L¢2(m3-NO2)2(CH2Cl2)]n·1.5H2O (3) where HL = 2-[(3-amino-propylimino)-methyl]-phenol, H2L¢ = 2-({3-[(2-hydroxy-benzylidene)-amino]-propylimino}-methyl)-phenol and DMF = N,N-dimethylformamide, have been synthesized starting with the precursor complex [NiL2]·2H2O, nickel(II) perchlorate and sodium nitrite and characterized structurally and magnetically. The structural analyses reveal that in all the complexes, NiII ions possess a distorted octahedral geometry. Complex 1 is a dinuclear di-m2-phenoxo bridged species in which nitrite ion acts as chelating co-ligand. Complexes 2a and 2b also consist of dinuclear entities, but in these two compounds a cis-(m-nitrito-1kO:2kN) bridge is present in addition to the di-m2-phenoxo bridge. The molecular structures of 2a and 2b are equivalent; they differ only in that 2a contains an additional solvated DMF molecule. Complex 3 is formed by ligand rearrangement and is a one-dimensional polymer in which double phenoxo as well as m-nitrito-1kO:2kN bridged trinuclear units are linked through a very rare m3-nitrito-1kO:2kN:3kO¢ bridge. Analysis of variable-temperature magnetic susceptibility data indicates that there is a global weak antiferromagnetic interaction between the nickel(II) ions in four complexes, with exchange parameters J of -5.26, -11.45, -10.66 and -5.99 cm-1 for 1, 2a, 2b and 3, respectively
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Motivated by accounts of concept use in autistic spectrum disorder (ASD), and a computational model of weak central coherence (O’Loughlin & Thagard, 2000) we examined comprehension and production vocabulary in typically-developing children, and those with ASD and Down syndrome (DS). Controlling for frequency, familiarity, length, and imageability, Colorado Meaningfulness played a hitherto unremarked role in the vocabularies of children with ASD. High Colorado Meaningful words were underrepresented in the comprehension vocabularies of 2- to 12-year-olds with ASD. The Colorado Meaningfulness of a word is a measure of how many words can be associated with it. Situations in which high Colorado Meaningfulness words are encountered are typically highly variable, and words with High Colorado Meaningfulness often involve extensive use of context. Our data suggest that the number of contexts in which a particular word can appear has a role in determining vocabulary in ASD. This suggestion is consistent with the weak central coherence theory of autism.
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In public goods experiments, stochastic choice, censoring and motivational heterogeneity give scope for disagreement over the extent of unselfishness, and whether it is reciprocal or altruistic. We show that these problems can be addressed econometrically, by estimating a finite mixture model to isolate types, incorporating double censoring and a tremble term. Most subjects act selfishly, but a substantial proportion are reciprocal with altruism playing only a marginal role. Isolating reciprocators enables a test of Sugden’s model of voluntary contributions. We estimate that reciprocators display a self-serving bias relative to the model.
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To optimise the placement of small wind turbines in urban areas a detailed understanding of the spatial variability of the wind resource is required. At present, due to a lack of observations, the NOABL wind speed database is frequently used to estimate the wind resource at a potential site. However, recent work has shown that this tends to overestimate the wind speed in urban areas. This paper suggests a method for adjusting the predictions of the NOABL in urban areas by considering the impact of the underlying surface on a neighbourhood scale. In which, the nature of the surface is characterised on a 1 km2 resolution using an urban morphology database. The model was then used to estimate the variability of the annual mean wind speed across Greater London at a height typical of current small wind turbine installations. Initial validation of the results suggests that the predicted wind speeds are considerably more accurate than the NOABL values. The derived wind map therefore currently provides the best opportunity to identify the neighbourhoods in Greater London at which small wind turbines yield their highest energy production. The model does not consider street scale processes, however previously derived scaling factors can be applied to relate the neighbourhood wind speed to a value at a specific rooftop site. The results showed that the wind speed predicted across London is relatively low, exceeding 4 ms-1 at only 27% of the neighbourhoods in the city. Of these sites less than 10% are within 10 km of the city centre, with the majority over 20 km from the city centre. Consequently, it is predicted that small wind turbines tend to perform better towards the outskirts of the city, therefore for cities which fit the Burgess concentric ring model, such as Greater London, ‘distance from city centre’ is a useful parameter for siting small wind turbines. However, there are a number of neighbourhoods close to the city centre at which the wind speed is relatively high and these sites can only been identified with a detailed representation of the urban surface, such as that developed in this study.
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This paper examines the lead–lag relationship between the FTSE 100 index and index futures price employing a number of time series models. Using 10-min observations from June 1996–1997, it is found that lagged changes in the futures price can help to predict changes in the spot price. The best forecasting model is of the error correction type, allowing for the theoretical difference between spot and futures prices according to the cost of carry relationship. This predictive ability is in turn utilised to derive a trading strategy which is tested under real-world conditions to search for systematic profitable trading opportunities. It is revealed that although the model forecasts produce significantly higher returns than a passive benchmark, the model was unable to outperform the benchmark after allowing for transaction costs.
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[1] Iron is hypothesized to be an important micronutrient for ocean biota, thus modulating carbon dioxide uptake by the ocean biological pump. Studies have assumed that atmospheric deposition of iron to the open ocean is predominantly from mineral aerosols. For the first time we model the source, transport, and deposition of iron from combustion sources. Iron is produced in small quantities during fossil fuel burning, incinerator use, and biomass burning. The sources of combustion iron are concentrated in the industrialized regions and biomass burning regions, largely in the tropics. Model results suggest that combustion iron can represent up to 50% of the total iron deposited, but over open ocean regions it is usually less than 5% of the total iron, with the highest values (< 30%) close to the East Asian continent in the North Pacific. For ocean biogeochemistry the bioavailability of the iron is important, and this is often estimated by the fraction which is soluble ( Fe(II)). Previous studies have argued that atmospheric processing of the relatively insoluble Fe(III) occurs to make it more soluble ( Fe( II)). Modeled estimates of soluble iron amounts based solely on atmospheric processing as simulated here cannot match the variability in daily averaged in situ concentration measurements in Korea, which is located close to both combustion and dust sources. The best match to the observations is that there are substantial direct emissions of soluble iron from combustion processes. If we assume observed soluble Fe/black carbon ratios in Korea are representative of the whole globe, we obtain the result that deposition of soluble iron from combustion contributes 20-100% of the soluble iron deposition over many ocean regions. This implies that more work should be done refining the emissions and deposition of combustion sources of soluble iron globally.
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This study develops a simplified model describing the evolutionary dynamics of a population composed of obligate sexually and asexually reproducing, unicellular organisms. The model assumes that the organisms have diploid genomes consisting of two chromosomes, and that the sexual organisms replicate by first dividing into haploid intermediates, which then combine with other haploids, followed by the normal mitotic division of the resulting diploid into two new daughter cells. We assume that the fitness landscape of the diploids is analogous to the single-fitness-peak approach often used in single-chromosome studies. That is, we assume a master chromosome that becomes defective with just one point mutation. The diploid fitness then depends on whether the genome has zero, one, or two copies of the master chromosome. We also assume that only pairs of haploids with a master chromosome are capable of combining so as to produce sexual diploid cells, and that this process is described by second-order kinetics. We find that, in a range of intermediate values of the replication fidelity, sexually reproducing cells can outcompete asexual ones, provided the initial abundance of sexual cells is above some threshold value. The range of values where sexual reproduction outcompetes asexual reproduction increases with decreasing replication rate and increasing population density. We critically evaluate a common approach, based on a group selection perspective, used to study the competition between populations and show its flaws in addressing the evolution of sex problem.
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A mixed integer continuous nonlinear model and a solution method for the problem of orthogonally packing identical rectangles within an arbitrary convex region are introduced in the present work. The convex region is assumed to be made of an isotropic material in such a way that arbitrary rotations of the items, preserving the orthogonality constraint, are allowed. The solution method is based on a combination of branch and bound and active-set strategies for bound-constrained minimization of smooth functions. Numerical results show the reliability of the presented approach. (C) 2010 Elsevier Ltd. All rights reserved.
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Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Neste trabalho é analisada a aplicação de algoritmos heurísticos para o Modelo Híbrido Linear - Hybrid Linear Model (HLM) - no problema de planejamento da expansão de sistemas de transmissão. O HLM é um modelo relaxado que ainda não foi suficientemente explorado. Assim, é realizada uma análise das características do modelo matemático e das técnicas de solução que podem ser usadas para resolver este tipo de modelo. O trabalho analisa em detalhes um algoritmo heurístico construtivo para o HLM e faz uma extensão da modelagem e da técnica de solução para o planejamento multi-estágio da expansão de sistemas de transmissão. Dentro deste contexto, também é realizada uma avaliação da qualidade das soluções encontradas pelo HLM e as possibilidades de aplicação deste modelo em planejamento de sistemas de transmissão. Finalmente, são apresentados testes com sistemas conhecidos na literatura especializada.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Substitutions of Ti and Cu in ZrO2.MgO (Z), cause transformation from monoclinic (m) to cubic (c) and tetragonal (t). According to the vacancy model and solid Solution formation models, neither CuO nor TiO2 cause zirconia stabilization, which derives front other phenomena. Data analysis by TMA using the CRH (constant rate of heating) method shows a solid state reaction of ZrO2.MgO.TiO2 (Z.TiO2) demonstrating a dominant mechanism of volume diffusion (n = 1). However, the sintering of ZrO2.MgO.CuO (Z.CuO) shows a viscous flow mechanism (n = 0), a similar phenomena to that of by sintering of glass. Transformations, such as: CuO to Cu2O at 1000 degreesC, ZrO2 (m) to ZrO2 (t) at 1100 degreesC and Cu2O (s) to Cu2O (l) at 1230 degreesC cause successive rearrangements of microstructure inside of region I (sintering process) and lead to interpretation errors when the Bannister equation is used. (C) 2003 Elsevier Ltd and Techna Group S.r.l. All rights reserved.