The Electron–Phonon Interaction of Low-Dimensional and Multi-Dimensional Materials from He Atom Scattering

Atom scattering is becoming recognized as a sensitive probe of the electron–phonon interaction parameter λ at metal and metal-overlayer surfaces. Here, the theory is developed, linking λ to the thermal attenuation of atom scattering spectra (in particular, the Debye–Waller factor), to conducting materials of different dimensions, from quasi-1D systems such as W(110):H(1 × 1) and Bi(114), to quasi-2D layered chalcogenides, and high-dimensional surfaces such as quasicrystalline 2ML-Ba(0001)/Cu(001) and d-AlNiCo(00001). Values of λ obtained using He atoms compare favorably with known values for the bulk materials. The corresponding analysis indicates in addition, the number of layers contributing to the electron–phonon interaction, which is measured in an atom surface collision.     

On the reliability of Landsat TM for estimating forest variables byregression techniques: a methodological analysis

In order to build models that relate thematic mapper (TM) imagery to field forest variables, several regression techniques, such as the ones based on the Mallows' C_p and the adjusted R² statistics, were applied. Nevertheless, although the best created models had good fittings (R²>0.65) apparently supported by a clear statistical significance (p<0.0001), later trials tested with additional plots showed that these models were, in fact, nonrobust models (models with very low-predictive capabilities). Two factors were pointed out as causes of these inconsistencies between predicted and observed values: a relatively small number of available field plots and a relatively high number of possible independent variables. Actually, different trials suggested much lower fittings for the expected “really” predictive models. Some restrictions of TM satellite data, such as its radiometric, spectral, and spatial limitations, together with restrictions arising from gathering and processing of field data, might have led to these poor relations. This study shows the need for guarantees stronger than the usual ones before concluding that there is a clear possibility of using satellite information to estimate forest parameters by means of regression techniques     

Comparative study of the colorants monascus and cochineal used in the preparation of gels made with various gelling agents

The possibilities of using monascus to colour gels were studied by comparing it with cochineal. Gels were prepared with four gelling agents—carrageenan, gellan, gelatine and xanthan—and their colour was measured with a Hunter Lab colorimeter. The equations relating L^* and h with the concentrations of sugar [SU] and colorant [COL] were deduced, and it was found that [COL] had more influence on colour than [SU]. In general, for these four gelling agents the colour of monascus gels is orange-red and the colour of cochineal gels is purplish red. The gels made with xanthan were always the lightest, whether they were made with cochineal or with monascus.     

Robustness of classification rules that incorporate additional information

The discrimination problem for two normal populations with the same covariance matrix when additional information on the population is available is considered. A study of the robustness properties against training sample contamination of classification rules that incorporate this additional information is performed. These rules have received recently attention where their total misclassification probability (TMP) is proved to be lower than Fisher's linear discriminant rule. The results of a simulation study on the TMP which compares the behaviour of the new rules against Fisher's rule and some of its robustified versions under different types of contamination are presented. These results show that the rules that incorporate the additional information not only have lower TMP, but they also prevent against some types of contamination. In order to achieve prevention from all types of contamination a robustifed version of these rules is recommended.     

Effect-Size Indices for Dichotomized Outcomes in Meta-Analysis.

It is very common to find meta-analyses in which some of the studies compare 2 groups on continuous dependent variables and others compare groups on dichotomized variables. Integrating all of them in a meta-analysis requires an effect-size index in the same metric that can be applied to both types of outcomes. In this article, the performance in terms of bias and sampling variance of 7 different effect-size indices for estimating the population standardized mean difference from a 2 × 2 table is examined by Monte Carlo simulation, assuming normal and nonnormal distributions. The results show good performance for 2 indices, one based on the probit transformation and the other based on the logistic distribution. (PsycINFO Database Record (c) 2010 APA, all rights reserved)