Espectroscopía de emisión de rayos x. Aplicación a la caracterización de materiales. X-ray emission spectroscopy. Application to materials characterization

La idea principal del proyecto abarca el estudio de parámetros y fenómenos físicos. Los avances logrados se aplicarán al desarrollo de software y metodologías para cuantificación de materiales mediante microanálisis con sonda de electrones y microscopía electrónica de barrido. El microanálisis no es una técnica absoluta, sino que requiere de estándares de referencia, para obviar el uso de ciertos parámetros geométricos y atómicos difíciles de conocer con una precisión adecuada. Para contar con un método sin estándares debe abordarse la determinación de parámetros atómicos e instrumentales, que es uno de los aspectos que se desea encarar en este proyecto. Por otro lado, también se pretende incluir los parámetros estudiados en un software de cuantificación desarrollado por integrantes del proyecto. Otro de los propósitos del plan de trabajo es estudiar la potencialidad de la resolución espacial de una microsonda de electrones con el fin de desarrollar una metodología para caracterizar interfases, bordes de granos e inclusiones, con resolución submicrométrica, ya que los métodos tradicionales de cuantificación se restringen al caso de muestras planas y homogéneas dentro del volumen de interacción, pero la caracterización de inhomogeneidades a nivel micrométrico no ha sido desarrollada todavía, salvo algunas excepciones. The main idea of this project involves the study of physical parameters and phenomena. The concretion of the different goals will permit the elaboration of softeare and methodologies for materials characterization by means of electron probe microanalysis and scanning microscopy. Electron probe microanalysis is not an absolute technique, but requires reference standards in order not to involve certain geometrical and atomic parameters for which high uncertainties cannot be avoided. In order to have standardless method, the determination of atomic and instrumental parameters must be accomplished, as will be faced through this project. Complementary, the parameters studied will be included in a quantification software developed in our research group of FaMAF. Another objective of this activity plan is to study the spatial resolution potentiality of a focalized electron beam, with the aim of characterizing interphases, grain boundaries and inclusions with submicron sensitivity, since the traditional quantification procedures are restricted to flat homogeneous samples, whereas the characterization of inhomogeneities has not been developed yet.

Study of human brain metabolites using magnetic resonance spectroscopy methods at 7 TESLA

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2012

Difference sets from projective planes

Magdeburg, Univ., Fak. für Mathematik, Diss., 2013

The investigation of glutamine and glutamate in the human brain using MR spectroscopy at 7 Tesla

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2014

Human capital in growth regressions: how much difference does data quality make? An update and further results

We construct estimates of educational attainment for a sample of OECD countries using previously unexploited sources. We follow a heuristic approach to obtain plausible time profiles for attainment levels by removing sharp breaks in the data that seem to reflect changes in classification criteria. We then construct indicators of the information content of our series and a number of previously available data sets and examine their performance in several growth specifications. We find a clear positive correlation between data quality and the size and significance of human capital coefficients in growth regressions. Using an extension of the classical errors in variables model, we construct a set of meta-estimates of the coefficient of years of schooling in an aggregate Cobb-Douglas production function. Our results suggest that, after correcting for measurement error bias, the value of this parameter is well above 0.50.

Normal forms for rational difference equations with applications to the global periodicity problem

We propose a classification and derive the associated normal forms for rational difference equations with complex coefficients. As an application, we study the global periodicity problem for second order rational difference equations with complex coefficients. We find new necessary conditions as well as some new examples of globally periodic equations.

Reduction of periodic difference systems to linear or autonomous ones

We extend Floquet theory for reducing nonlinear periodic difference systems to autonomous ones (actually linear) by using normal form theory.

Dynamics of the third order Lyness' difference equation

"Vegeu el resum a l'inici del document del fitxer adjunt"

The Discrimination of Colored Acrylic, Cotton, and Wool Textile Fibers Using Micro-Raman Spectroscopy. Part 1 : In Situ Detection and Characterization of Dyes

Raman spectroscopy has been applied to characterize fiber dyes and determine the discriminating ability of the method. Black, blue, and red acrylic, cotton, and wool samples were analyzed. Four excitation sources were used to obtain complementary responses in the case of fluorescent samples. Fibers that did not provide informative spectra using a given laser were usually detected using another wavelength. For any colored acrylic, the 633-nm laser did not provide Raman information. The 514-nm laser provided the highest discrimination for blue and black cotton, but half of the blue cottons produced noninformative spectra. The 830-nm laser exhibited the highest discrimination for red cotton. Both visible lasers provided the highest discrimination for black and blue wool, and NIR lasers produced remarkable separation for red and black wool. This study shows that the discriminating ability of Raman spectroscopy depends on the fiber type, color, and the laser wavelength.

Compartmentalized Cerebral Metabolism of [1,6-(13)C]Glucose Determined by in vivo (13)C NMR Spectroscopy at 14.1 T.

Cerebral metabolism is compartmentalized between neurons and glia. Although glial glycolysis is thought to largely sustain the energetic requirements of neurotransmission while oxidative metabolism takes place mainly in neurons, this hypothesis is matter of debate. The compartmentalization of cerebral metabolic fluxes can be determined by (13)C nuclear magnetic resonance (NMR) spectroscopy upon infusion of (13)C-enriched compounds, especially glucose. Rats under light α-chloralose anesthesia were infused with [1,6-(13)C]glucose and (13)C enrichment in the brain metabolites was measured by (13)C NMR spectroscopy with high sensitivity and spectral resolution at 14.1 T. This allowed determining (13)C enrichment curves of amino acid carbons with high reproducibility and to reliably estimate cerebral metabolic fluxes (mean error of 8%). We further found that TCA cycle intermediates are not required for flux determination in mathematical models of brain metabolism. Neuronal tricarboxylic acid cycle rate (V(TCA)) and neurotransmission rate (V(NT)) were 0.45 ± 0.01 and 0.11 ± 0.01 μmol/g/min, respectively. Glial V(TCA) was found to be 38 ± 3% of total cerebral oxidative metabolism, accounting for more than half of neuronal oxidative metabolism. Furthermore, glial anaplerotic pyruvate carboxylation rate (V(PC)) was 0.069 ± 0.004 μmol/g/min, i.e., 25 ± 1% of the glial TCA cycle rate. These results support a role of glial cells as active partners of neurons during synaptic transmission beyond glycolytic metabolism.

Sex difference and the role of leptin in the association between high-sensitivity C-reactive protein and adiposity in two different populations.

Elevated high-sensitivity C-reactive protein (hs-CRP) concentration is associated with an increased risk of cardiovascular disease but this association seems to be largely mediated via conventional cardiovascular risk factors. In particular, the association between hs-CRP and obesity has been extensively demonstrated and correlations are stronger in women than men. We used fractional polynomials-a method that allows flexible modeling of non linear relations-to investigate the dose/response mathematical relationship between hs-CRP and several indicators of adiposity in Caucasians (Switzerland) and Africans (Seychelles) surveyed in two population-based studies. This relationship was non-linear exhibiting a steeper slope for low levels of hs-CRP and a higher level in women. The observed sex difference in the relationship between hs-CRP and adiposity almost disappeared upon adjustment for leptin, suggesting that these sex differences might be partially mediated, by leptin. All these relationship were similar in Caucasians and Africans. This is the first report on a non-linear relation, stratified by gender, between hs-CRP and adiposity.

Investment and financing constraints in China: does working capital management make a difference?

We use a panel of over 120,000 Chinese firms of different ownership types over the period 2000-2007 to analyze the linkages between investment in fixed and working capital and financing constraints. We find that those firms characterized by high working capital display high sensitivities of investment in working capital to cash flow (WKS) and low sensitivities of investment in fixed capital to cash flow (FKS). We then construct and analyze firm-level FKS and WKS measures and find that, despite severe external financing constraints, those firms with low FKS and high WKS exhibit the highest fixed investment rates. This suggests that good working capital management may help firms to alleviate the effects of financing constraints on fixed investment.

The Difference, System and ‘Double-D’ GMM Panel Estimators in the Presence of Structural Breaks

The effects of structural breaks in dynamic panels are more complicated than in time series models as the bias can be either negative or positive. This paper focuses on the effects of mean shifts in otherwise stationary processes within an instrumental variable panel estimation framework. We show the sources of the bias and a Monte Carlo analysis calibrated on United States bank lending data demonstrates the size of the bias for a range of auto-regressive parameters. We also propose additional moment conditions that can be used to reduce the biases caused by shifts in the mean of the data.