Statistical-based monitoring of multivariate non-Gaussian systems

The monitoring of multivariate systems that exhibit non-Gaussian behavior is addressed. Existing work advocates the use of independent component analysis (ICA) to extract the underlying non-Gaussian data structure. Since some of the source signals may be Gaussian, the use of principal component analysis (PCA) is proposed to capture the Gaussian and non-Gaussian source signals. A subsequent application of ICA then allows the extraction of non-Gaussian components from the retained principal components (PCs). A further contribution is the utilization of a support vector data description to determine a confidence limit for the non-Gaussian components. Finally, a statistical test is developed for determining how many non-Gaussian components are encapsulated within the retained PCs, and associated monitoring statistics are defined. The utility of the proposed scheme is demonstrated by a simulation example, and the analysis of recorded data from an industrial melter.

Statistical theory of finite Fermi systems with chaotic excited eigenstates

A theory of strongly interacting Fermi systems of a few particles is developed. At high excit at ion energies (a few times the single-parti cle level spacing) these systems are characterized by an extreme degree of complexity due to strong mixing of the shell-model-based many-part icle basis st at es by the residual two- body interaction. This regime can be described as many-body quantum chaos. Practically, it occurs when the excitation energy of the system is greater than a few single-particle level spacings near the Fermi energy. Physical examples of such systems are compound nuclei, heavy open shell atoms (e.g. rare earths) and multicharged ions, molecules, clusters and quantum dots in solids. The main quantity of the theory is the strength function which describes spreading of the eigenstates over many-part icle basis states (determinants) constructed using the shell-model orbital basis. A nonlinear equation for the strength function is derived, which enables one to describe the eigenstates without diagonalization of the Hamiltonian matrix. We show how to use this approach to calculate mean orbital occupation numbers and matrix elements between chaotic eigenstates and introduce typically statistical variable s such as t emperature in an isolated microscopic Fermi system of a few particles.

On Entropy-Based Molecular Descriptors: Statistical Analysis of Real and Synthetic Chemical Structures

This paper presents an analysis of entropy-based molecular descriptors. Specifically, we use real chemical structures, as well as synthetic isomeric structures, and investigate properties of and among descriptors with respect to the used data set by a statistical analysis. Our numerical results provide evidence that synthetic chemical structures are notably different to real chemical structures and, hence, should not be used to investigate molecular descriptors. Instead, an analysis based on real chemical structures is favorable. Further, we find strong hints that molecular descriptors can be partitioned into distinct classes capturing complementary information.

A Multicenter Blinded Study to Evaluate KRAS Mutation Testing Methodologies in the Clinical Setting

Evidence that activating mutations of the KRAS oncogene abolish the response to anti-epidermal growth factor receptor therapy has revolutionized the treatment of advanced colorectal cancer. This has resulted in the urgent demand for KRAS mutation testing in the clinical setting to aid choice of therapy. The Am of this study was to evaluate six different KRAS mutation detection methodologies on two series of primary colorectal cancer samples. Two series of 80 frozen and 74 formalin-fixed paraffin-embedded tissue samples were sourced and DNA was extracted at a central site before distribution to seven different testing sites. KRAS mutations in codons 12 and 13 were assessed by using single strand conformation polymorphism analysis, pyrosequencing, high resolution melting analysis, dideoxy sequencing, or the commercially available TIB Molbiol (Berlin, Germany) or DxS Diagnostic innovations (Manchester, UK) kits. in frozen tissue samples, concordance in KRAS status (defined as consensus in at least five assays) was observed in 66/80 (83%) cases. In par-affin tissue, concordance was 46/74 (63%) if all assays were considered or 71/74 (96%) using the five best performing assays. These results demonstrate that a variety of detection methodologies are suitable and provide comparable results for KRAS mutation analysis of clinical samples. (J Mol Diagn 2009, 11:543-552; DOI: 10.2353/jmoldx.2009.090057)