990 resultados para Application pseudo-holomorphe


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Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

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This paper examines the repercussion effects on the production cost of industries in Asian countries when some countries eliminate tariffs and import commodity taxes on all imports. This kind of analysis is related in some sense to that measuring the effects of FTAs on economies, and thus may be considered as an analysis of “pseudo FTAs.” Examining a number of combinations of “pseudo FTAs” between China, Japan, and ASEAN, it is found that the case of China plus Japan plus ASEAN is the most effective “pseudo FTA” of the combinations in terms of production cost reduction. The method is a form of price model based on the Asian International Input-Output Table. Almost no studies on price models related to multilateral I/O tables have been implemented thus far.

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This article introduces a “pseudo classical” notion of modelling non-separability. This form of non-separability can be viewed as lying between separability and quantum-like non-separability. Non-separability is formalized in terms of the non-factorizabilty of the underlying joint probability distribution. A decision criterium for determining the non-factorizability of the joint distribution is related to determining the rank of a matrix as well as another approach based on the chi-square-goodness-of-fit test. This pseudo-classical notion of non-separability is discussed in terms of quantum games and concept combinations in human cognition.

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The structure of the pseudo-merohedrally twinned crystal of the 1:1 proton-transfer compound of 5-sulfosalicylic acid (3-carboxy-4-hydroxybenzenesulfonic acid) with 4-aminopyridine: 4-aminopyridinium 3-carboxy-4-hydroxybenzenesulfonate sesquihydrate has been determined at 180 K and the hydrogen-bonding pattern is described. Crystals of the compound are monoclinic with space group P21/c, with unit cell dimensions a = 35.2589(8), b = 7.1948(1), c = 24.5851(5) Å, β = 110.373(2)o, and Z = 16. The monoclinic asymmetric unit comprises four cation-anion pairs and six water molecules of solvation with only the pyridinium cations having pseudo-symmetry as a result of inter-cation aromatic ring π-π stacking effects. Extensive hydrogen bonding gives a three-dimensional framework structure.

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The emergence of pseudo-marginal algorithms has led to improved computational efficiency for dealing with complex Bayesian models with latent variables. Here an unbiased estimator of the likelihood replaces the true likelihood in order to produce a Bayesian algorithm that remains on the marginal space of the model parameter (with latent variables integrated out), with a target distribution that is still the correct posterior distribution. Very efficient proposal distributions can be developed on the marginal space relative to the joint space of model parameter and latent variables. Thus psuedo-marginal algorithms tend to have substantially better mixing properties. However, for pseudo-marginal approaches to perform well, the likelihood has to be estimated rather precisely. This can be difficult to achieve in complex applications. In this paper we propose to take advantage of multiple central processing units (CPUs), that are readily available on most standard desktop computers. Here the likelihood is estimated independently on the multiple CPUs, with the ultimate estimate of the likelihood being the average of the estimates obtained from the multiple CPUs. The estimate remains unbiased, but the variability is reduced. We compare and contrast two different technologies that allow the implementation of this idea, both of which require a negligible amount of extra programming effort. The superior performance of this idea over the standard approach is demonstrated on simulated data from a stochastic volatility model.

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Application of `advanced analysis' methods suitable for non-linear analysis and design of steel frame structures permits direct and accurate determination of ultimate system strengths, without resort to simplified elastic methods of analysis and semi-empirical specification equations. However, the application of advanced analysis methods has previously been restricted to steel frames comprising only compact sections that are not influenced by the effects of local buckling. A concentrated plasticity method suitable for practical advanced analysis of steel frame structures comprising non-compact sections is presented in this paper. The pseudo plastic zone method implicitly accounts for the effects of gradual cross-sectional yielding, longitudinal spread of plasticity, initial geometric imperfections, residual stresses, and local buckling. The accuracy and precision of the method for the analysis of steel frames comprising non-compact sections is established by comparison with a comprehensive range of analytical benchmark frame solutions. The pseudo plastic zone method is shown to be more accurate and precise than the conventional individual member design methods based on elastic analysis and specification equations.

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Monitoring stream networks through time provides important ecological information. The sampling design problem is to choose locations where measurements are taken so as to maximise information gathered about physicochemical and biological variables on the stream network. This paper uses a pseudo-Bayesian approach, averaging a utility function over a prior distribution, in finding a design which maximizes the average utility. We use models for correlations of observations on the stream network that are based on stream network distances and described by moving average error models. Utility functions used reflect the needs of the experimenter, such as prediction of location values or estimation of parameters. We propose an algorithmic approach to design with the mean utility of a design estimated using Monte Carlo techniques and an exchange algorithm to search for optimal sampling designs. In particular we focus on the problem of finding an optimal design from a set of fixed designs and finding an optimal subset of a given set of sampling locations. As there are many different variables to measure, such as chemical, physical and biological measurements at each location, designs are derived from models based on different types of response variables: continuous, counts and proportions. We apply the methodology to a synthetic example and the Lake Eacham stream network on the Atherton Tablelands in Queensland, Australia. We show that the optimal designs depend very much on the choice of utility function, varying from space filling to clustered designs and mixtures of these, but given the utility function, designs are relatively robust to the type of response variable.

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A computationally efficient sequential Monte Carlo algorithm is proposed for the sequential design of experiments for the collection of block data described by mixed effects models. The difficulty in applying a sequential Monte Carlo algorithm in such settings is the need to evaluate the observed data likelihood, which is typically intractable for all but linear Gaussian models. To overcome this difficulty, we propose to unbiasedly estimate the likelihood, and perform inference and make decisions based on an exact-approximate algorithm. Two estimates are proposed: using Quasi Monte Carlo methods and using the Laplace approximation with importance sampling. Both of these approaches can be computationally expensive, so we propose exploiting parallel computational architectures to ensure designs can be derived in a timely manner. We also extend our approach to allow for model uncertainty. This research is motivated by important pharmacological studies related to the treatment of critically ill patients.

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The surfaces of natural beidellite were modified with cationic surfactant octadecyl trimethylammonium bromide at different concentrations. The organo-beidellite adsorbent materials were then used for the removal of atrazine with the goal of investigating the mechanism for the adsorption of organic triazine herbicide from contaminated water. Changes on the surfaces and structure of beidellite were characterised by X-ray diffraction (XRD), thermogravimetric analysis (TGA), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM) and BET surface analysis. Kinetics of the adsorption studies were also carried out which show that the adsorption capacity of the organoclays increases with increasing surfactant concentration up until 1.0 CEC surfactant loading, after which the adsorption capacity greatly decreases. TG analysis reveals that although the 2.0 CEC sample has the greatest percentage of surfactant by mass, most of it is present on external sites. The 0.5 CEC sample has the highest proportion of surfactant exchanged into the internal active sites and the 1.0 CEC sample accounts for the highest adsorption capacity. The goodness of fit of the pseudo-second order kinetic confirms that chemical adsorption, rather than physical adsorption, controls the adsorption rate of atrazine.

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A pseudo-dynamical approach for a class of inverse problems involving static measurements is proposed and explored. Following linearization of the minimizing functional associated with the underlying optimization problem, the new strategy results in a system of linearized ordinary differential equations (ODEs) whose steady-state solutions yield the desired reconstruction. We consider some explicit and implicit schemes for integrating the ODEs and thus establish a deterministic reconstruction strategy without an explicit use of regularization. A stochastic reconstruction strategy is then developed making use of an ensemble Kalman filter wherein these ODEs serve as the measurement model. Finally, we assess the numerical efficacy of the developed tools against a few linear and nonlinear inverse problems of engineering interest.

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Arylalkylcyclopropenethiones undergo highly regioselective photochemical a-cleavage via thioketene carbene intermediates, giving rise to products derived from the less stabilized carbene. UHF MIND0/3 calculations provide an insight into this unexpected regioselectivity. The nx* triplet of cyclopropenethione is calculated to have a highly unsymmetrical geometry with an elongated C-C bond, a delocalized thiaaUyl fragment, and a pyramidal radicaloid carbon (which eventually becomes the carbene center). From this molecular electronic structure, aryl group stabilization is expected to be more effective at the thiaallyl group rather than at the pyramidal radical center. Thus, the stability of the substituted triplet thione rather than that of the thioketene carbene determines the preferred regiochemistry of cleavage. The unusual structure of the cyclopropenethione triplet is suggested to be related to one of the Jahn-Teller distorted forms of the cyclopropenyl radical. An alternative symmetrical structure is adopted by the corresponding triplet of cyclopropenone, partly accounting for its differing photobehavior. A similar structural dichotomy is demonstrated for the corresponding radical anions as well.

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Pseudo-marginal methods such as the grouped independence Metropolis-Hastings (GIMH) and Markov chain within Metropolis (MCWM) algorithms have been introduced in the literature as an approach to perform Bayesian inference in latent variable models. These methods replace intractable likelihood calculations with unbiased estimates within Markov chain Monte Carlo algorithms. The GIMH method has the posterior of interest as its limiting distribution, but suffers from poor mixing if it is too computationally intensive to obtain high-precision likelihood estimates. The MCWM algorithm has better mixing properties, but less theoretical support. In this paper we propose to use Gaussian processes (GP) to accelerate the GIMH method, whilst using a short pilot run of MCWM to train the GP. Our new method, GP-GIMH, is illustrated on simulated data from a stochastic volatility and a gene network model.

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A pair of Latin squares, A and B, of order n, is said to be pseudo-orthogonal if each symbol in A is paired with every symbol in B precisely once, except for one symbol with which it is paired twice and one symbol with which it is not paired at all. A set of t Latin squares, of order n, are said to be mutually pseudo-orthogonal if they are pairwise pseudo-orthogonal. A special class of pseudo-orthogonal Latin squares are the mutually nearly orthogonal Latin squares (MNOLS) first discussed in 2002, with general constructions given in 2007. In this paper we develop row complete MNOLS from difference covering arrays. We will use this connection to settle the spectrum question for sets of 3 mutually pseudo-orthogonal Latin squares of even order, for all but the order 146.

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The paper presents a method for the evaluation of external stability of reinforced soil walls subjected to earthquakes in the framework of the pseudo-dynamic method. The seismic reliability of the wall is evaluated by considering the different possible failure modes such as sliding along the base, overturning about the toe point of the wall, bearing capacity and the eccentricity of the resultant force. The analysis is performed considering properties of the reinforced backfill, foundation soil below the base of the wall, length of the geosynthetic reinforcement and characteristics of earthquake ground motions such as shear wave and primary wave velocity as random variables. The optimum length of reinforcement needed to maintain stability against four modes of failure by targeting various component reliability indices is obtained. Differences between pseudo-static and pseudo-dynamic methods are clearly highlighted in the paper. A complete analysis of pseudo-static and pseudo-dynamic methodologies shows that the pseudodynamic method results in realistic design values for the length of geosynthetic reinforcement under earthquake conditions.

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Extensive molecular dynamics (MD) simulations have been performed in a B2-NiAl nanowire using an embedded atom method (EAM) potential. We show a stress induced B2 -> body-centered-tetragonal (BCT) phase transformation and a novel temperature and cross-section dependent pseudo-elastic/pseudo-plastic recovery from such an unstable BCT phase with a recoverable strain of similar to 30% as compared to 5-8% in polycrystalline materials. Such a temperature and cross-section dependent pseudo-elastic/pseudo-plastic strain recovery can be useful in various interesting applications of shape memory and strain sensing in nanoscale devices. Effects of size, temperature, and strain rate on the structural and mechanical properties have also been analyzed in detail. For a given size of the nanowire the yield stress of both the B2 and the BCT phases is found to decrease with increasing temperature, whereas for a given temperature and strain rate the yield stress of both the B2 and the BCT phase is found to increase with increase in the cross-sectional dimensions of the nanowire. A constant elastic modulus of similar to 80 GPa of the B2 phase is observed in the temperature range of 200-500 K for nanowires of cross-sectional dimensions in the range of 17.22-28.712 angstrom, whereas the elastic modulus of the BCT phase shows a decreasing trend with an increase in the temperature.