245 resultados para structural change

em University of Queensland eSpace - Australia


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We demonstrate that the process of generating smooth transitions Call be viewed as a natural result of the filtering operations implied in the generation of discrete-time series observations from the sampling of data from an underlying continuous time process that has undergone a process of structural change. In order to focus discussion, we utilize the problem of estimating the location of abrupt shifts in some simple time series models. This approach will permit its to address salient issues relating to distortions induced by the inherent aggregation associated with discrete-time sampling of continuous time processes experiencing structural change, We also address the issue of how time irreversible structures may be generated within the smooth transition processes. (c) 2005 Elsevier Inc. All rights reserved.

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The relationship between the ordering characteristic of the pyrochlore structure type and that characteristic of the defect fluorite structure type (immediately on either side of two phase regions separating the two structure types) in a range of rare eath sesquioxide stabilized cubic zirconias is investigated via electron diffraction and imaging. Systematic structural change as a function of composition and relative size of the constituent metal ions is highlighted and a multi-q to single-q = 1/2 [111]* model proposed for the observed pyrochlore to defect fluorite phase transition. Strain introduced into the close-packed {111} metal ion planes of the defect fluorite average structure by the local cation and oxygen vacancy distribution is pointed to as the likely origin of the observed behavior. (C) 2001 Academic Press

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Applied econometricians often fail to impose economic regularity constraints in the exact form economic theory prescribes. We show how the Singular Value Decomposition (SVD) Theorem and Markov Chain Monte Carlo (MCMC) methods can be used to rigorously impose time- and firm-varying equality and inequality constraints. To illustrate the technique we estimate a system of translog input demand functions subject to all the constraints implied by economic theory, including observation-varying symmetry and concavity constraints. Results are presented in the form of characteristics of the estimated posterior distributions of functions of the parameters. Copyright (C) 2001 John Wiley Sons, Ltd.

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In modeling expectation formation, economic agents are usually viewed as forming expectations adaptively or in accordance with some rationality postulate. We offer an alternative nonlinear model where agents exchange their opinions and information with each other. Such a model yields multiple equilibria, or attracting distributions, that are persistent but subject to sudden large jumps. Using German Federal Statistical Office economic indicators and German IFO Poll expectational data, we show that this kind of model performs well in simulation experiments. Focusing upon producers' expectations in the consumption goods sector, we also discover evidence that structural change in the interactive process occurred over the period of investigation (1970-1998). Specifically, interactions in expectation formation seem to have become less important over time.

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This paper develops an evolutionary theory of adaptive growth, understood as a product of structural change and economic self-transformation, based upon processes that are closely connected with but not reducible to the growth of knowledge. The dominant connecting theme is enterprise, the innovative variations it generates and the multiple connections between investment, innovation, demand and structural transformation in the market process. The paper explores the dependence of macroeconomic productivity growth on the diversity of technical progress functions and income elasticities of demand at the industry level, and the resolution of this diversity into patterns of economic change through market processes. It is shown how industry growth rates are constrained by higher-order processes of emergence that convert an ensemble of industry growth rates into an aggregate rate of growth. The growth of productivity, output and employment are determined mutually and endogenously, and their values depend on the variation in the primary causal influences in the system.

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Mesoporous Mobil catalytic materials of number 41 (MCM-41) silica was chemically modified using both inorganic and organic precursors and characterized using the techniques, XRD, XPS, MAS NMR, FTIR, W-Vis, and physical adsorption of nitrogen, hydrocarbons (hexane, benzene, acetone, and methanol) and water vapor. Modification using organic reagents was found to result in a significant loss in porosity and a shape change of surface properties (increased hydrophobicity and decreased acidity). With inorganic modifying reagents, the decrease in porosity was also observed while the surface properties were not significantly altered as reflected by the adsorption isotherms of organics and water vapors. Chemical modifications can greatly improve the hydrothermal stability of MCM-41 material because of the enhanced surface hydrophobicity (with organic modifiers) or increased pore wall thickness (with inorganic modifiers). (C) 2000 Elsevier Science B.V. All rights reserved.

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Exponential and sigmoidal functions have been suggested to describe the bulk density profiles of crusts. The present work aims to evaluate these conceptual models using high resolution X-radiography. Repacked seedbeds from two soil materials, air-dried or prewetted by capillary rise, were subjected to simulated rain, which resulted in three types of structural crusts, namely, slaking, infilling, and coalescing. Bulk density distributions with depth were generated using high-resolution (70 mum), calibrated X-ray images of slices from the resin-impregnated crusted seedbeds. The bulk density decreased progressively with depth, which supports the suggestion that a crust should be considered as a nonuniform layer. For the slaking and the coalescing crusts, the exponential function underestimated the strong change in bulk density across the morphologically defined transition between the crust and the underlying material; the sigmoidal function provided a better description. Neither of these crust models effectively described the shape of the bulk density profiles through the whole seedbed. Below the infilling and slaking crusts, bulk density increased linearly with depth as a result of slumping. In the coalescing crusted seedbed, the whole seedbed uniformly collapsed and most of the bulk density change within the crust could be ascribed to slumping (0.33 g cm(-3)) rather than to crusting (0.12 g cm(-3)). Finally, (i) X-radiography appears as a unique tool to generate high resolution bulk density profiles and (ii) in structural crusts, bulk density profiles could be modeled using the existing exponential and sigmoidal crusting models, provided a slumping model would be coupled.

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This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimer's disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhood and adult-onset schizophrenia, bipolar disorder, attention-deficit/ hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages. (C) 2004 Published by Elsevier Inc.

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The extended X-ray absorption fine structure spectroscopy (EXAFS) of (ND4)(2)[CU(D2O)(6)](SO4)(2) at 5, 14,100, 200, and 298 K is reported. This indicates that the Cu-O bond lengths of the Cu(D2O)(6)(2+) ion do not change significantly within this temperature range, which contrasts with EPR results and X-ray and neutron diffraction experiments, which imply that two of the Cu-(D2O) bonds converge in length as the temperature is raised. The EXAFS measurements thus confirm that the bond distances yielded by the diffraction experiments refer to the average positions of ligands involved in a dynamic equilibrium in which the directions of the long and intermediate bonds of the Jahn-Teller distorted Cu(D2O)(6)(2+) ion are interchanged in the crystal lattice. Analysis of the displacement parameters is consistent with this interpretation, as are the wave functions calculated using a model involving Jahn-Teller vibronic coupling and the influence of lattice strain interactions.

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Australia's rangelands are experiencing a post-productivist transition at a tempo comparable to Western Europe's, but in contexts that ensure marked divergence in impulses, actors, processes and outcomes. In Australia's most marginal lands, a flimsy mode of pastoral occupance is being displaced by renewed indigenous occupance, conservation and tourism, with significant changes in land ownership, property rights, investment sources and power relations, but also with structural problems arising from fugitive income streams. The sharp delineation between structurally coherent commodity-oriented regions and emerging amenity-oriented regions can provisionally be mapped at a national scale. A comparison of Australia with Western Europe indicates that three distinct but interconnected driving forces are propelling the rural transition, namely: agricultural overcapacity; the emergence of amenity-oriented uses; and changing societal values.

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The effect of heat treatment on the structure of an Australian semi-anthracite char was studied in detail in the 850-1150degreesC temperature range using XRD, HRTEM, and electrical resistivity techniques. It was found that the carbon crystallite size in the char does not change significantly during heat treatment in the temperature range studied, for both the raw coal and its ash-free derivative obtained by acid treatment. However, the fraction of the organized carbon in the raw coal chars, determined by XRD, increased with increase of heat treatment time and temperature, while that for the ash-free coal chars remained almost unchanged. This suggests the occurrence of catalytic ordering during heat treatment, supported by the observation that the electrical resistivity of the raw coal chars decreased with heat treatment, while that of the ash-free coal chars did not vary significantly. Further confirmatory evidence was provided by high resolution transmission electron micrographs depicting well-organized carbon layers surrounding iron particles. It is also found that the fraction of organized carbon does not reach unity, but attains an apparent equilibrium value that increases with increase in temperature, providing an apparent heat of ordering of 71.7 kJ mol(-1) in the temperature range studied. Good temperature-independent correlation was found between the electrical resistivity and the organized carbon fraction, indicating that electrical resistivity is indeed structure sensitive. Good correlation was also found between the electrical resistivity and the reactivity of coal char. All these results strongly suggest that the thermal deactivation is the result of a crystallite-perfecting process, which is effectively catalyzed by the inorganic matter in the coal char. Based on kinetic interpretation of the data it is concluded that the process is diffusion controlled, most likely involving transport of iron in the inter-crystallite nanospaces in the temperature range studied. The activation energy of this transport process is found to be very low, at about 11.8 kJ mol(-1), which is corroborated by model-free correlation of the temporal variation of organized carbon fraction as well as electrical resistivity data using the superposition method, and is suggestive of surface transport of iron. (C) 2002 Elsevier Science Ltd. All rights reserved.

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A detailed analysis procedure is described for evaluating rates of volumetric change in brain structures based on structural magnetic resonance (MR) images. In this procedure, a series of image processing tools have been employed to address the problems encountered in measuring rates of change based on structural MR images. These tools include an algorithm for intensity non-uniforniity correction, a robust algorithm for three-dimensional image registration with sub-voxel precision and an algorithm for brain tissue segmentation. However, a unique feature in the procedure is the use of a fractional volume model that has been developed to provide a quantitative measure for the partial volume effect. With this model, the fractional constituent tissue volumes are evaluated for voxels at the tissue boundary that manifest partial volume effect, thus allowing tissue boundaries be defined at a sub-voxel level and in an automated fashion. Validation studies are presented on key algorithms including segmentation and registration. An overall assessment of the method is provided through the evaluation of the rates of brain atrophy in a group of normal elderly subjects for which the rate of brain atrophy due to normal aging is predictably small. An application of the method is given in Part 11 where the rates of brain atrophy in various brain regions are studied in relation to normal aging and Alzheimer's disease. (C) 2002 Elsevier Science Inc. All rights reserved.