Drift compensation of gas sensor array data by common principal component analysis

A new drift compensation method based on Common Principal Component Analysis (CPCA) is proposed. The drift variance in data is found as the principal components computed by CPCA. This method finds components that are common for all gasses in feature space. The method is compared in classification task with respect to the other approaches published where the drift direction is estimated through a Principal Component Analysis (PCA) of a reference gas. The proposed new method ¿ employing no specific reference gas, but information from all gases ¿has shown the same performance as the traditional approach with the best-fitted reference gas. Results are shown with data lasting 7-months including three gases at different concentrations for an array of 17 polymeric sensors.

Quantum critical effects in mean-field glassy systems

We consider the effects of quantum fluctuations in mean-field quantum spin-glass models with pairwise interactions. We examine the nature of the quantum glass transition at zero temperature in a transverse field. In models (such as the random orthogonal model) where the classical phase transition is discontinuous an analysis using the static approximation reveals that the transition becomes continuous at zero temperature.

A fully-automatic caudate nucleus segmentation of brain MRI: application in volumetric analysis of pediatric attention-deficit/hyperactivity disorder

Background Accurate automatic segmentation of the caudate nucleus in magnetic resonance images (MRI) of the brain is of great interest in the analysis of developmental disorders. Segmentation methods based on a single atlas or on multiple atlases have been shown to suitably localize caudate structure. However, the atlas prior information may not represent the structure of interest correctly. It may therefore be useful to introduce a more flexible technique for accurate segmentations. Method We present Cau-dateCut: a new fully-automatic method of segmenting the caudate nucleus in MRI. CaudateCut combines an atlas-based segmentation strategy with the Graph Cut energy-minimization framework. We adapt the Graph Cut model to make it suitable for segmenting small, low-contrast structures, such as the caudate nucleus, by defining new energy function data and boundary potentials. In particular, we exploit information concerning the intensity and geometry, and we add supervised energies based on contextual brain structures. Furthermore, we reinforce boundary detection using a new multi-scale edgeness measure. Results We apply the novel CaudateCut method to the segmentation of the caudate nucleus to a new set of 39 pediatric attention-deficit/hyperactivity disorder (ADHD) patients and 40 control children, as well as to a public database of 18 subjects. We evaluate the quality of the segmentation using several volumetric and voxel by voxel measures. Our results show improved performance in terms of segmentation compared to state-of-the-art approaches, obtaining a mean overlap of 80.75%. Moreover, we present a quantitative volumetric analysis of caudate abnormalities in pediatric ADHD, the results of which show strong correlation with expert manual analysis. Conclusion CaudateCut generates segmentation results that are comparable to gold-standard segmentations and which are reliable in the analysis of differentiating neuroanatomical abnormalities between healthy controls and pediatric ADHD.

Hepatitis G virus infection in primary Sjögren's syndrome: analysis in a series of 100 patients.

OBJECTIVE To determine the prevalence and clinical significance of hepatitis G virus (HGV) infection in a large cohort of patients with primary Sjögren¿s syndrome (SS). PATIENTS AND METHODS The study included 100 consecutive patients (92 female and eight male), with a mean age of 62 years (range 31¿80) that were prospectively visited in our unit. All patients fulfilled the European Community criteria for SS and underwent a complete history, physical examination, as well as biochemical and immunological evaluation for liver disease. Two hundred volunteer blood donors were also studied. The presence of HGV-RNA was investigated in the serum of all patients and donors. Aditionally, HBsAg and antibodies to hepatitis C virus were determined. RESULTS Four patients (4%) and six volunteer blood donors (3%) presented HGV-RNA sequences in serum. HGV infection was associated with biochemical signs of liver involvement in two (50%) patients. When compared with primary SS patients without HGV infection, no significant differences were found in terms of clinical or immunological features. HCV coinfection occurs in one (25%) of the four patients with HGV infection. CONCLUSION The prevalence of HGV infection in patients with primary SS is low in the geographical area of the study and HCV coinfection is very uncommon. HGV infection alone does not seen to be an important cause of chronic liver injury in the patients with primary SS in this area.