Attention, memory and verbal learning and their relation to schizotypal traits in unaffected parents of schizophrenic patients

The main objective of this ex post facto study is to compare the differences in cognitive functions and their relation to schizotypal personality traits between a group of unaffected parents of schizophrenic patients and a control group. A total of 52 unaffected biological parents of schizophrenic patients and 52 unaffected parents of unaffected subjects were assessed in measures of attention (Continuous Performance Test- Identical Pairs Version, CPT-IP), memory and verbal learning (California Verbal Learning Test, CVLT) as well as schizotypal personality traits (Oxford-Liverpool Inventory of Feelings and Experiences, O-LIFE). The parents of the patients with schizophrenia differ from the parents of the control group in omission errors on the Continuous Performance Test- Identical Pairs, on a measure of recall and on two contrast measures of the California Verbal Learning Test. The associations between neuropsychological variables and schizotpyal traits are of a low magnitude. There is no defined pattern of the relationship between cognitive measures and schizotypal traits

An R Library for Compositional Data Analysis in Archaeometry

Compositional data naturally arises from the scientific analysis of the chemical composition of archaeological material such as ceramic and glass artefacts. Data of this type can be explored using a variety of techniques, from standard multivariate methods such as principal components analysis and cluster analysis, to methods based upon the use of log-ratios. The general aim is to identify groups of chemically similar artefacts that could potentially be used to answer questions of provenance. This paper will demonstrate work in progress on the development of a documented library of methods, implemented using the statistical package R, for the analysis of compositional data. R is an open source package that makes available very powerful statistical facilities at no cost. We aim to show how, with the aid of statistical software such as R, traditional exploratory multivariate analysis can easily be used alongside, or in combination with, specialist techniques of compositional data analysis. The library has been developed from a core of basic R functionality, together with purpose-written routines arising from our own research (for example that reported at CoDaWork'03). In addition, we have included other appropriate publicly available techniques and libraries that have been implemented in R by other authors. Available functions range from standard multivariate techniques through to various approaches to log-ratio analysis and zero replacement. We also discuss and demonstrate a small selection of relatively new techniques that have hitherto been little-used in archaeometric applications involving compositional data. The application of the library to the analysis of data arising in archaeometry will be demonstrated; results from different analyses will be compared; and the utility of the various methods discussed

Analysis of chemical bonding and aromaticity from electronic delocalization descriptors

Interactions between electrons determine the structure and properties of matter from molecules to solids. Therefore, the understanding of the electronic structure of molecules will enable us to extract relevant chemical information. In the first part of this thesis, we focus our attention on the analysis of chemical bonding by means of the Electron Localization Function (ELF) and the Domain-Averaged Fermi Hole analysis (DAFH). In the second part, we assess the performance of some indicators of aromaticity by analyzing their advantages and drawbacks. We propose a series of tests based on well-known aromaticity trends that can be applied to evaluate the aromaticity of current and future indicators of aromaticity in both organic and inorganic species. Moreover, we investigate the nature of electron delocalization in both aromatic and antiaromatic systems in the light of Hückel’s (4n + 2) rule. Finally, we analyze the phenomenon of multiple aromaticity in all-metal clusters.