89 resultados para LEED STRUCTURE-ANALYSIS

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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A family of scaling corrections aimed to improve the chi-square approximation of goodness-of-fit test statistics in small samples, large models, and nonnormal data was proposed in Satorra and Bentler (1994). For structural equations models, Satorra-Bentler's (SB) scaling corrections are available in standard computer software. Often, however, the interest is not on the overall fit of a model, but on a test of the restrictions that a null model say ${\cal M}_0$ implies on a less restricted one ${\cal M}_1$. If $T_0$ and $T_1$ denote the goodness-of-fit test statistics associated to ${\cal M}_0$ and ${\cal M}_1$, respectively, then typically the difference $T_d = T_0 - T_1$ is used as a chi-square test statistic with degrees of freedom equal to the difference on the number of independent parameters estimated under the models ${\cal M}_0$ and ${\cal M}_1$. As in the case of the goodness-of-fit test, it is of interest to scale the statistic $T_d$ in order to improve its chi-square approximation in realistic, i.e., nonasymptotic and nonnormal, applications. In a recent paper, Satorra (1999) shows that the difference between two Satorra-Bentler scaled test statistics for overall model fit does not yield the correct SB scaled difference test statistic. Satorra developed an expression that permits scaling the difference test statistic, but his formula has some practical limitations, since it requires heavy computations that are notavailable in standard computer software. The purpose of the present paper is to provide an easy way to compute the scaled difference chi-square statistic from the scaled goodness-of-fit test statistics of models ${\cal M}_0$ and ${\cal M}_1$. A Monte Carlo study is provided to illustrate the performance of the competing statistics.

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Standard methods for the analysis of linear latent variable models oftenrely on the assumption that the vector of observed variables is normallydistributed. This normality assumption (NA) plays a crucial role inassessingoptimality of estimates, in computing standard errors, and in designinganasymptotic chi-square goodness-of-fit test. The asymptotic validity of NAinferences when the data deviates from normality has been calledasymptoticrobustness. In the present paper we extend previous work on asymptoticrobustnessto a general context of multi-sample analysis of linear latent variablemodels,with a latent component of the model allowed to be fixed across(hypothetical)sample replications, and with the asymptotic covariance matrix of thesamplemoments not necessarily finite. We will show that, under certainconditions,the matrix $\Gamma$ of asymptotic variances of the analyzed samplemomentscan be substituted by a matrix $\Omega$ that is a function only of thecross-product moments of the observed variables. The main advantage of thisis thatinferences based on $\Omega$ are readily available in standard softwareforcovariance structure analysis, and do not require to compute samplefourth-order moments. An illustration with simulated data in the context ofregressionwith errors in variables will be presented.

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In moment structure analysis with nonnormal data, asymptotic valid inferences require the computation of a consistent (under general distributional assumptions) estimate of the matrix $\Gamma$ of asymptotic variances of sample second--order moments. Such a consistent estimate involves the fourth--order sample moments of the data. In practice, the use of fourth--order moments leads to computational burden and lack of robustness against small samples. In this paper we show that, under certain assumptions, correct asymptotic inferences can be attained when $\Gamma$ is replaced by a matrix $\Omega$ that involves only the second--order moments of the data. The present paper extends to the context of multi--sample analysis of second--order moment structures, results derived in the context of (simple--sample) covariance structure analysis (Satorra and Bentler, 1990). The results apply to a variety of estimation methods and general type of statistics. An example involving a test of equality of means under covariance restrictions illustrates theoretical aspects of the paper.

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El Symptom Checklist-90-R (SCL-90-R) es uno de los instrumentos más ampliamente utilizados en la medición de la sintomatología psicopatológica en población clínica y en población general. Ya que gran parte de la investigación en psicopatología se realiza con estudiantes universitarios, este estudio instrumental pretende proporcionar datos de referencia para esta población. Analizamos las propiedades psicométricas de esta escala en una muestra representativa de 1.277 estudiantes de la Universidad de Girona. Las dimensiones con puntuaciones más elevadas para el total de la muestra son Obsesividad-compulsividad, Depresión y Sensibilidad interpersonal. Los resultados muestran diferencias significativas entre hombres y mujeres. La fiabilidad de la escala resulta muy aceptable, con unos coeficientes de consistencia interna de las nueve dimensiones primarias y del GSI, que oscilan entre 0,69 y 0,97. El análisis de la estructura factorial y la fuerte interdependencia entre las escalas primarias cuestionan la multidimensionalidad del SCL-90-R y refuerzan la idea de que el instrumento proporciona una medida de distrés general, es decir, es un indicador unidimensional de malestar psicológico más que una medida de dimensiones psicopatológicas diferenciadas

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El objetivo de este estudio fue replicar las estructuras de 5 y 6 factores de segundo orden del 16PF-5. Para la estructura de 5 factores se toma como referencia teórica la estructura obtenida por Russell y Karol (1995), y para la estructura de 6 factores (incluyendo un factor adicional de Razonamiento) la obtenida en muestras americanas por Cattell y Cattell (1995). Se utilizan tres procedimientos para el estudio de la replicabilidad, a) análisis factorial exploratorio, b) análisis de la estructura ortogonal Procrustes, y c) análisis de los índices de congruencia entre las tres matrices factoriales. Las matrices factoriales obtenidas en el presente estudio son similares a las informadas en los estudios de referencia, aunque la solución Procrustes se revela ligeramente más parecida. Los índices de congruencia en ge- neral son aceptables por lo que se concluye que el 16PF-5 demuestra buena replicabilidad.

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In this study, (011)-highly oriented Sr, Nb co-doped BiFeO3 (BFO) thin films were successfully grown on SrRuO3/Si substrates by rf-magnetron sputtering. The presence of parasite magnetic phases was ruled out based on the high resolution x-ray diffraction data. BFO films exhibited a columnar-like grain growth with rms surface roughness values of 5.3 nm and average grain sizes of 65-70 nm for samples with different thicknesses. Remanent polarization values (2Pr) of 54 lC cm 2 at room temperature were found for the BFO films with a ferroelectric behavior characteristic of an asymmetric device structure. Analysis of the leakage mechanisms for this structure in negative bias suggests Schottky injection and a dominant Poole-Frenkel trap-limited conduction at room temperature. Oxygen vacancies and Fe3þ/Fe2þ trap centers are consistent with the surface chemical bonding states analysis from x-ray photoelectron spectroscopy data. The (011)-BFO/ SrRuO3/Si film structure exhibits a strong magnetic interaction at the interface between the multiferroic film and the substrate layer where an enhanced ferromagnetic response at 5 K was observed. Zero-field cooled (ZFC) and field cooled (FC) magnetization curves of this film system revealed a possible spin glass behavior at spin freezing temperatures below 30 K depending on the BFO film thickness.

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Report for the scientific sojourn at the University of Reading, United Kingdom, from January until May 2008. The main objectives have been firstly to infer population structure and parameters in demographic models using a total of 13 microsatellite loci for genotyping approximately 30 individuals per population in 10 Palinurus elephas populations both from Mediterranean and Atlantic waters. Secondly, developing statistical methods to identify discrepant loci, possibly under selection and implement those methods using the R software environment. It is important to consider that the calculation of the probability distribution of the demographic and mutational parameters for a full genetic data set is numerically difficult for complex demographic history (Stephens 2003). The Approximate Bayesian Computation (ABC), based on summary statistics to infer posterior distributions of variable parameters without explicit likelihood calculations, can surmount this difficulty. This would allow to gather information on different demographic prior values (i.e. effective population sizes, migration rate, microsatellite mutation rate, mutational processes) and assay the sensitivity of inferences to demographic priors by assuming different priors.

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This paper conducts an empirical analysis of the relationship between wage inequality, employment structure, and returns to education in urban areas of Mexico during the past two decades (1987-2008). Applying Melly’s (2005) quantile regression based decomposition, we find that changes in wage inequality have been driven mainly by variations in educational wage premia. Additionally, we find that changes in employment structure, including occupation and firm size, have played a vital role. This evidence seems to suggest that the changes in wage inequality in urban Mexico cannot be interpreted in terms of a skill-biased change, but rather they are the result of an increasing demand for skills during that period.

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This paper identifies the key sectors in greenhouse gas emissions of the Uruguayan economy through input-output analysis. This allows to precisely determine the role played by the different productive sectors and their relationship with other sectors in the relation between the Uruguayan productive structure and atmospheric pollution. In order to guide policy design for GHG reduction, we decompose sectors liability between the pollution generated through their own production processes and the pollution indirectly generated in the production processes of other sectors. The results show that all the key polluting sectors for the different contaminants considered are relevant because of their own emissions, except for the sector Motor vehicles and oil retail trade, which is relevant in CO2 emissions because of its pure, both backward and forward, linkages. Finally, the best policy channels for controlling and reducing GHGs emissions are identified, and compared with the National Climate Change Response Plan (NCCRP) lines of action.

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Studies of large sets of SNP data have proven to be a powerful tool in the analysis of the genetic structure of human populations. In this work, we analyze genotyping data for 2,841 SNPs in 12 Sub-Saharan African populations, including a previously unsampled region of south-eastern Africa (Mozambique). We show that robust results in a world-wide perspective can be obtained when analyzing only 1,000 SNPs. Our main results both confirm the results of previous studies, and show new and interesting features in Sub-Saharan African genetic complexity. There is a strong differentiation of Nilo-Saharans, much beyond what would be expected by geography. Hunter-gatherer populations (Khoisan and Pygmies) show a clear distinctiveness with very intrinsic Pygmy (and not only Khoisan) genetic features. Populations of the West Africa present an unexpected similarity among them, possibly the result of a population expansion. Finally, we find a strong differentiation of the south-eastern Bantu population from Mozambique, which suggests an assimilation of a pre-Bantu substrate by Bantu speakers in the region.

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Amplified ribosomal DNA restriction analysis (ARDRA) is a simple method based on restriction endonuclease digestion of the amplified bacterial 16S rDNA. In this study we have evaluated the suitability of this method to detect differences in activated sludge bacterial communities fed on domestic or industrial wastewater, and subject to different operational conditions. The ability of ARDRA to detect these differences has been tested in modified Ludzack-Ettinger (MLE) configurations. Samples from three activated sludge wastewater treatment plants (WWTPs) with the MLE configuration were collected for both oxic and anoxic reactors, and ARDRA patterns using double enzyme digestions AluI+MspI were obtained. A matrix of Dice similarity coefficients was calculated and used to compare these restriction patterns. Differences in the community structure due to influent characteristics and temperature could be observed, but not between the oxic and anoxic reactors of each of the three MLE configurations. Other possible applications of ARDRA for detecting and monitoring changes in activated sludge systems are also discussed

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The recently measured inclusive electron-proton cross section in the nucleon resonance region, performed with the CLAS detector at the Thomas Jefferson Laboratory, has provided new data for the nucleon structure function F2 with previously unavailable precision. In this paper we propose a description of these experimental data based on a Regge-dual model for F2. The basic inputs in the model are nonlinear complex Regge trajectories producing both isobar resonances and a smooth background. The model is tested against the experimental data, and the Q2 dependence of the moments is calculated. The fitted model for the structure function (inclusive cross section) is a limiting case of the more general scattering amplitude equally applicable to deeply virtual Compton scattering. The connection between the two is discussed.

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Comparative analysis of gene fragments of six housekeeping loci, distributed around the two chromosomes of Vibrio cholerae, has been carried out for a collection of 29 V. cholerae O139 Bengal strains isolated from India during the first epidemic period (1992 to 1993). A toxigenic O1 ElTor strain from the seventh pandemic and an environmental non-O1/non-O139 strain were also included in this study. All loci studied were polymorphic, with a small number of polymorphic sites in the sequenced fragments. The genetic diversity determined for our O139 population is concordant with a previous multilocus enzyme electrophoresis study in which we analyzed the same V. cholerae O139 strains. In both studies we have found a higher genetic diversity than reported previously in other molecular studies. The results of the present work showed that O139 strains clustered in several lineages of the dendrogram generated from the matrix of allelic mismatches between the different genotypes, a finding which does not support the hypothesis previously reported that the O139 serogroup is a unique clone. The statistical analysis performed in the V. cholerae O139 isolates suggested a clonal population structure. Moreover, the application of the Sawyer's test and split decomposition to detect intragenic recombination in the sequenced gene fragments did not indicate the existence of recombination in our O139 population.

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In general terms key sectors analysis aims at identifying the role, or impact, that the existence of a productive sector has in the economy. Quite a few measures, indicators and methodologies of varied complexity have been proposed in the literature, from multiplier sums to extraction methods, but not without debate about their properties and their information content. All of them, to our knowledge, focus exclusively on the interdependence effects that result from the input-output structure of the economy. By so doing the simple input-output approach misses critical links beyond the interindustry ones. A productive sector’s role is that of producing but also that of generating and distributing income among primary factors as a result of production. Thus when measuring a sector’s role, the income generating process cannot and should not be omitted if we want to better elucidate the sector’ economic role. A simple way to make the missing income link explicit is to use the SAM (Soci

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We use experiments to study the efficiency effects for a market as a whole of adding the possibility of forward contracting to a pre-existing spot market. We deal separately with the cases where spot market competition is in quantities and where it is in supply functions. In both cases we compare the effect of adding a contract market with the introduction of an additional competitor, changing the market structure from a triopoly to a quadropoly. We find that, as theory suggests, for both types of competition the introduction of a forward market significantly lowers prices. The combination of supply function competition with a forward market leads to high efficiency levels.