National Scientific and Technical Research Council

About: National Scientific and Technical Research Council is a government organization based out in Buenos Aires, Argentina. It is known for research contribution in the topics: Population & Catalysis. The organization has 36143 authors who have published 62683 publications receiving 1013255 citations. The organization is also known as: CONICET.

Coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regression

Abstract: A major focus of geographical ecology and macroecology is to understand the causes of spatially structured ecological patterns. However, achieving this understanding can be complicated when using multiple regression, because the relative importance of explanatory variables, as measured by regression coefficients, can shift depending on whether spatially explicit or non-spatial modeling is used. However, the extent to which coefficients may shift and why shifts occur are unclear. Here, we analyze the relationship between environmental predictors and the geographical distribution of species richness, body size, range size and abundance in 97 multi-factorial data sets. Our goal was to compare standardized partial regression coefficients of non-spatial ordinary least squares regressions (i.e. models fitted using ordinary least squares without taking autocorrelation into account; "OLS models" hereafter) and eight spatial methods to evaluate the frequency of coefficient shifts and identify characteristics of data that might predict when shifts are likely. We generated three metrics of coefficient shifts and eight characteristics of the data sets as predictors of shifts. Typical of ecological data, spatial autocorrelation in the residuals of OLS models was found in most data sets. The spatial models varied in the extent to which they minimized residual spatial autocorrelation. Patterns of coefficient shifts also varied among methods and datasets, although the magnitudes of shifts tended to be small in all cases. We were unable to identify strong predictors of shifts, including the levels of autocorrelation in either explanatory variables or model residuals. Thus, changes in coefficients between spatial and non-spatial methods depend on the method used and are largely idiosyncratic, making it difficult to predict when or why shifts occur. We conclude that the ecological importance of regression coefficients cannot be evaluated with confidence irrespective of whether spatially explicit modelling is used or not. Researchers may have little choice but to be more explicit about the uncertainty of models and more cautious in their interpretation.

Texture evolution during large-strain hot rolling of the Mg AZ61 alloy

Abstract: Grain refinement in a Mg-based AZ61 alloy of initially coarse, recrystallized microstructure was successfully achieved by thermomechanical processing (TMP) consisting of two to three hot-rolling steps with large reductions per pass. Reductions as large as 85% (equivalent to a true strain of ≈1) were achieved without surface cracking. The underlying microscopic mechanisms operative during the TMP that allowed this hcp material to accommodate such large strains per pass were investigated by macro- and microtexture analysis. A significant decrease in the intensity of the initial basal texture was observed after the first pass. This was attributed to rotational dynamic recrystallization, a mechanism by which new recrystallized grains develop, with orientations favourable for basal slip. Upon subsequent passes, basal slip becomes the main deformation mechanism. Simultaneously, grain refinement takes place by continuous dynamic recrystallization. The fine-grained microstructure thus developed showed improved superplastic behaviour in comparison with that of similar alloys processed by more elaborate methods.

Dynamical mean-field theory within an augmented plane-wave framework: Assessing electronic correlations in the iron pnictide LaFeAsO

Abstract: We present an approach that combines the local-density approximation (LDA) and the dynamical mean-field theory (DMFT) in the framework of the full-potential linear augmented plane-wave method. Wannier-type functions for the correlated shell are constructed by projecting local orbitals onto a set of Bloch eigenstates located within a certain energy window. The screened Coulomb interaction and Hund's coupling are calculated from a first-principles constrained random-phase approximation scheme. We apply this $\text{LDA}+\text{DMFT}$ implementation, in conjunction with a continuous-time quantum Monte Carlo algorithm, to the study of electronic correlations in LaFeAsO. Our findings support the physical picture of a metal with intermediate correlations. The average value of the mass renormalization of the $\text{Fe}\text{ }3d$ bands is about 1.6, in reasonable agreement with the picture inferred from photoemission experiments. The discrepancies between different $\text{LDA}+\text{DMFT}$ calculations (all technically correct) which have been reported in the literature are shown to have two causes: (i) the specific value of the interaction parameters used in these calculations and (ii) the degree of localization of the Wannier orbitals chosen to represent the $\text{Fe}\text{ }3d$ states, to which many-body terms are applied. The latter is a fundamental issue in the application of many-body calculations, such as DMFT, in a realistic setting. We provide strong evidence that the DMFT approximation is more accurate and more straightforward to implement when well-localized orbitals are constructed from a large energy window encompassing $\text{Fe-}3d$, $\text{As-}4p$, and $\text{O-}2p$ and point out several difficulties associated with the use of extended Wannier functions associated with the low-energy iron bands. Some of these issues have important physical consequences regarding, in particular, the sensitivity to the Hund's coupling.