Robust Autocorrelation Estimation

In this article, we introduce a new class of robust autocorrelation estimators based on interpreting the sample autocorrelation function as a linear regression. We investigate the efficiency and robustness properties of the estimators that result from employing three common robust regression techniques. We discuss the construction of robust autocovariance and positive definite autocorrelation estimates, and their application to AR model fitting. We perform simulation studies with various outlier configurations to compare the different estimators.     

Radial clustergrams: visualizing the aggregate properties of hierarchical clusters

A new radial space-filling method for visualizing cluster hierarchies is presented. The method, referred to as a radial clustergram, arranges the clusters into a series of layers, each representing a different level of the tree. It uses adjacency of nodes instead of links to represent parent-child relationships and allocates sufficient screen real estate to each node to allow effective visualization of cluster properties through color-coding. Radial clustergrams combine the most appealing features of other cluster visualization techniques but avoid their pitfalls. Compared to classical dendrograms and hyperbolic trees, they make much more efficient use of space; compared to treemaps, they are more effective in conveying hierarchical structure and displaying properties of nodes higher in the tree. A fisheye lens is used to focus on areas of interest, without losing sight of the global context. The utility of the method is demonstrated using examples from the fields of molecular diversity and conformational analysis.     

Investigation of the local composition enhancement and related dynamics in supercritical CO2-cosolvent mixtures via computer simulation: the case of ethanol in CO2

The supercritical mixture ethanol-carbon dioxide (EtOH-CO2) with mole fraction of ethanol X(EtOH) congruent with 0.1 was investigated at 348 K, by employing the molecular dynamics simulation technique in the canonical ensemble. The local intermolecular structure of the fluid was studied in terms of the calculated appropriate pair radial distribution functions. The estimated average local coordination numbers and mole fractions around the species in the mixture reveal the existence of local composition enhancement of ethanol around the ethanol molecules. This finding indicates the nonideal mixing behavior of the mixture due to the existence of aggregation between the ethanol molecules. Furthermore, the local environment redistribution dynamics have been explored by analyzing the time correlation functions (TCFs) of the total local coordination number (solvent, cosolvent) around the cosolvent molecules in appropriate parts. The analysis of these total TCFs in the auto-(solvent-solvent, cosolvent-cosolvent) and cross-(solvent-cosolvent, cosolvent-solvent) TCFs has shown that the time dependent redistribution process of the first solvation shell of ethanol is mainly determined by the redistribution of the CO2 solvent molecules. These results might be explained on the basis of the CO2-CO2 and EtOH-CO2 intermolecular forces, which are sufficiently weaker in comparison to the EtOH-EtOH hydrogen bonding interactions, creating in this way a significantly faster redistribution of the CO2 molecules in comparison with EtOH. Finally, the self-diffusion coefficients and the single reorientational dynamics of both the cosolvent and solvent species in the mixture have been predicted and discussed in relationship with the local environment around the species, which in the case of the EtOH molecules seem to be strongly affected.     

Copper inverse-9-metallacrown-3 compounds showing antisymmetric magnetic behaviour

The use of phenyl 2-pyridyl ketoxime (PhPyCNO)/X(-)"blends" (X(-) = OH(-), Cl(-), ClO(4)(-)) in copper chemistry has yielded trinuclear clusters that have been characterized as inverse-9-metallacrown-3 accommodating one or two anions. The magnetic behaviour has shown a large antiferromagnetic interaction. The discrepancy between the Brillouin curve and the experiment has been assigned to the influence of the antisymmetric interaction. By introducing in the magnetization formula the antisymmetric terms derived from the fitting of the susceptibility data the simulated curve become almost superimposable to the experimental one. From the EPR findings it has been shown that the compound [Cu(3)(PhPyCNO)(3)(OCH(3))(Cl)(ClO(4))] () having isosceles magnetic symmetry or lower (delta not equal 0), the antisymmetric exchange is important (G not equal 0) and DeltaE > hv. The structures of the two complexes have been determined by single-crystal X-ray crystallography.     

On Testing for the Number of Components in a Mixed Poisson Model

Poisson mixtures are usually used to describe overdispersed data. Finite Poisson mixtures are used in many practical situations where often it is of interest to determine the number of components in the mixture. Identifying how many components comprise a mixture remains a difficult problem. The likelihood ratio test (LRT) is a general statistical procedure to use. Unfortunately, a number of specific problems arise and the classical theory fails to hold. In this paper a new procedure is proposed that is based on testing whether a new component can be added to a finite Poisson mixture which eventually leads to the number of components in the mixture. It is a sequential testing procedure based on the well known LRT that utilises a resampling technique to construct the distribution of the test statistic. The application of the procedure to real data reveals some interesting features of the distribution of the test statistic.     

Structural rearrangements in hairy-rod polymer solutions undergoing shear

 We report on a rheooptical investigation of hairy-rod poly(p-phenylene) solutions at different concentrations and temperatures. These polymers have a reasonably high persistence length (about 28 nm) and behave as worm-like chains in dilute solutions, whereas they form nearly spherical fractal aggregates with internal anisotropy at higher concentrations. By exposing these systems to time-dependent simple shear and following the evolution of birefringence in start-up and its subsequent relaxation upon the cessation of shear, we find a substantial broadening of the cluster size distribution, resulting from flow-induced cluster deformation and break-up. In contrast to the very dilute solutions, where polymers align in the flow direction, the deformed clusters main axes are aligned in the vorticity direction, presumably due to their strong steric local pretransitional type of ordering, with the constituent polymers following the velocity vector. At the highest concentration, which corresponds to a weak gel, shear is shown to break-up the gel and the steady-state response of a broad-size aggregate suspension is eventually recovered. Received: 18 February 1999/Accepted: 6 July 1999     

A Sharp Threshold for k‐Colorability

Let k be a fixed integer and f_k(n, p) denote the probability that the random graph G(n, p) is k‐colorable. We show that for k≥3, there exists d_k(n) such that for any ϵ>0, (1) As a result we conclude that for sufficiently large n the chromatic number of G(n, d/n) is concentrated in one value for all but a small fraction of d>1. ©1999 John Wiley & Sons, Inc. Random Struct. Alg., 14, 63–70, 1999     

Pattern recognition system for the discrimination of multiple sclerosis from cerebral microangiopathy lesions based on texture analysis of magnetic resonance images

In this study, a pattern recognition system has been developed for the discrimination of multiple sclerosis (MS) from cerebral microangiopathy (CM) lesions based on computer-assisted texture analysis of magnetic resonance images. Twenty-three textural features were calculated from MS and CM regions of interest, delineated by experienced radiologists on fluid attenuated inversion recovery images and obtained from 11 patients diagnosed with clinically definite MS and from 18 patients diagnosed with clinically definite CM. The probabilistic neural network classifier was used to construct the proposed pattern recognition system and the generalization of the system to unseen data was evaluated using an external cross validation process. According to the findings of the present study, statistically significant differences exist in the values of the textural features between CM and MS: MS regions were darker, of higher contrast, less homogeneous and rougher as compared to CM.     

Enhancing the discrimination accuracy between metastases, gliomas and meningiomas on brain MRI by volumetric textural features and ensemble pattern recognition methods

Three-dimensional (3D) texture analysis of volumetric brain magnetic resonance (MR) images has been identified as an important indicator for discriminating among different brain pathologies. The purpose of this study was to evaluate the efficiency of 3D textural features using a pattern recognition system in the task of discriminating benign, malignant and metastatic brain tissues on T1 postcontrast MR imaging (MRI) series. The dataset consisted of 67 brain MRI series obtained from patients with verified and untreated intracranial tumors. The pattern recognition system was designed as an ensemble classification scheme employing a support vector machine classifier, specially modified in order to integrate the least squares features transformation logic in its kernel function. The latter, in conjunction with using 3D textural features, enabled boosting up the performance of the system in discriminating metastatic, malignant and benign brain tumors with 77.14%, 89.19% and 93.33% accuracy, respectively. The method was evaluated using an external cross-validation process; thus, results might be considered indicative of the generalization performance of the system to "unseen" cases. The proposed system might be used as an assisting tool for brain tumor characterization on volumetric MRI series.