911 resultados para Structural change


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Commentators have predicted bureaucratic organisations would undergo substantial change as a result of social and economic pressures. We ask whether reforms to the Australian public service over the 1983–93 period exemplify this process. We use the methods of organisational analysis to characterise the direction of change, basing our assessment on the standard structural variables of complexity, formalisation and centralisation, together with a cultural variable. We find evidence that, overall, departments of state in the APS were becoming less bureaucratic in their structure, culture and internal function in the 1983–93 period. However, the effect was not uniform across departments, or unambiguous — formalisation, for example, increased in some respects and decreased in others. Centralisation increased overall, despite devolution of some decision-making.

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Many diseases are believed to be related to abnormal protein folding. In the first step of such pathogenic structural changes, misfolding occurs in regions important for the stability of the native structure. This destabilizes the normal protein conformation, while exposing the previously hidden aggregation-prone regions, leading to subsequent errors in the folding pathway. Sites involved in this first stage can be deemed switch regions of the protein, and can represent perfect binding targets for drugs to block the abnormal folding pathway and prevent pathogenic conformational changes. In this study, a prediction algorithm for the switch regions responsible for the start of pathogenic structural changes is introduced. With an accuracy of 94%, this algorithm can successfully find short segments covering sites significant in triggering conformational diseases (CDs) and is the first that can predict switch regions for various CDs. To illustrate its effectiveness in dealing with urgent public health problems, the reason of the increased pathogenicity of H5N1 influenza virus is analyzed; the mechanisms of the pandemic swine-origin 2009 A(H1N1) influenza virus in overcoming species barriers and in infecting large number of potential patients are also suggested. It is shown that the algorithm is a potential tool useful in the study of the pathology of CDs because: (1) it can identify the origin of pathogenic structural conversion with high sensitivity and specificity, and (2) it provides an ideal target for clinical treatment.

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Sheet resistance of laser-irradiated Ge2Sb2Te5 thin films prepared by magnetron sputtering was measured by the four-point probe method. With increasing laser power the sheet resistance undergoes an abrupt drop from 10(7) to 10(3) Omega/square at about 580 mW. The abrupt drop in resistance is due to the structural change from amorphous to crystalline state as revealed by X-ray diffraction (XRD) study of the samples around the abrupt change point. Crystallized dots were also formed in the amorphous Ge2Sb2Te5 films by focused short pulse laser-irradiated, the resistivities at the crystallized dots and the non-crystallized area are 3.375 x 10(-3) and 2.725 Omega m, sheet resistance is 3.37 x 10(4) and 2.725 x 10(7) Omega/square respectively, deduced from the I-V Curves that is obtained by conductive atomic force microscope (C-AFM). (C) 2008 Elsevier B.V. All rights reserved.

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We study the typical entanglement properties of a system comprising two independent qubit environments interacting via a shuttling ancilla. The initial preparation of the environments is modeled using random matrix techniques. The entanglement measure used in our study is then averaged over many histories of randomly prepared environmental states. Under a Heisenberg interaction model, the average entanglement between the ancilla and one of the environments remains constant, regardless of the preparation of the latter and the details of the interaction. We also show that, upon suitable kinematic and dynamical changes in the ancillaenvironment subsystems, the entanglement-sharing structure undergoes abrupt modifications associated with a change in the multipartite entanglement class of the overall system's state. These results are invariant with respect to the randomized initial state of the environments.

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We study the changes in the spatial distribution of vortices in a rotating Bose-Einstein condensate due to an increasing eccentricity of the trapping potential. By breaking the rotational symmetry, the vortex system undergoes a rich variety of structural changes, including the formation of zigzag and linear configurations. These spatial rearrangements are well signaled by the change in the behavior of the vortex-pattern eigenmodes against the eccentricity parameter. This behavior allows to actively control the distribution of vorticity in many-body systems and opens the possibility of studying interactions between quantum vortices over a large range of parameters.

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Small angle neutron scattering (SANS) has been applied to examine the effect of high pressure CO2 on the structure of Wyodak coal. Significant decrease in the scattering intensities upon exposure of the coal to high pressure CO2 showed that high pressure CO2 rapidly adsorbs on the coal and reaches to all pores in the structure. This is confirmed by strong and steep exothermic peaks observed on DSC scans during coal/ CO2 interactions. In situ small angle neutron scattering on coal at high pressure CO2 atmosphere showed an increase in scattering intensities with time suggesting that after adsorption, high pressure CO2 immediately begins to diffuse into the coal matrix, changes the macromolecular structure of the coal, swells the matrix and probably creates microporosity in coal structure by extraction of volatile components from coal. Significant decrease in the glass transition temperature of coal caused by high pressure CO2 also confirms that CO2 at elevated pressures dissolve in the coal matrix, results in significant plasticization and physical rearrangement of the coal’s macromolecular structure.

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Previous research on the prediction of fiscal aggregates has shown evidence that simple autoregressive models often provide better forecasts of fiscal variables than multivariate specifications. We argue that the multivariate models considered by previous studies are small-scale, probably burdened by overparameterization, and not robust to structural changes. Bayesian Vector Autoregressions (BVARs), on the other hand, allow the information contained in a large data set to be summarized efficiently, and can also allow for time variation in both the coefficients and the volatilities. In this paper we explore the performance of BVARs with constant and drifting coefficients for forecasting key fiscal variables such as government revenues, expenditures, and interest payments on the outstanding debt. We focus on both point and density forecasting, as assessments of a country’s fiscal stability and overall credit risk should typically be based on the specification of a whole probability distribution for the future state of the economy. Using data from the US and the largest European countries, we show that both the adoption of a large system and the introduction of time variation help in forecasting, with the former playing a relatively more important role in point forecasting, and the latter being more important for density forecasting.

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In a recent paper, Bai and Perron (1998) considered theoretical issues related to the limiting distribution of estimators and test statistics in the linear model with multiple structural changes. In this companion paper, we consider practical issues for the empirical applications of the procedures. We first address the problem of estimation of the break dates and present an efficient algorithm to obtain global minimizers of the sum of squared residuals. This algorithm is based on the principle of dynamic programming and requires at most least-squares operations of order O(T 2) for any number of breaks. Our method can be applied to both pure and partial structural-change models. Secondly, we consider the problem of forming confidence intervals for the break dates under various hypotheses about the structure of the data and the errors across segments. Third, we address the issue of testing for structural changes under very general conditions on the data and the errors. Fourth, we address the issue of estimating the number of breaks. We present simulation results pertaining to the behavior of the estimators and tests in finite samples. Finally, a few empirical applications are presented to illustrate the usefulness of the procedures. All methods discussed are implemented in a GAUSS program available upon request for non-profit academic use.

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We extend the class of M-tests for a unit root analyzed by Perron and Ng (1996) and Ng and Perron (1997) to the case where a change in the trend function is allowed to occur at an unknown time. These tests M(GLS) adopt the GLS detrending approach of Dufour and King (1991) and Elliott, Rothenberg and Stock (1996) (ERS). Following Perron (1989), we consider two models : one allowing for a change in slope and the other for both a change in intercept and slope. We derive the asymptotic distribution of the tests as well as that of the feasible point optimal tests PT(GLS) suggested by ERS. The asymptotic critical values of the tests are tabulated. Also, we compute the non-centrality parameter used for the local GLS detrending that permits the tests to have 50% asymptotic power at that value. We show that the M(GLS) and PT(GLS) tests have an asymptotic power function close to the power envelope. An extensive simulation study analyzes the size and power in finite samples under various methods to select the truncation lag for the autoregressive spectral density estimator. An empirical application is also provided.