Influence of ceria addition on thermal properties and local structure of bismuth germanate glasses

Bismuth germanate glasses are interesting materials due to their physical properties and their unique structural characteristics caused by the coordination changes of bismuth and germanium atoms. Glasses of the bismuth germanate system were prepared by melting/molding method and were investigated concerning their thermal and structural properties. The structural analysis of the samples was carried out by micro-Raman and Fourier transform infrared spectroscopes. It was observed that the glass structure is formed basically by GeO(4) tetrahedral units also having the formation of the GeO(6) octahedral units. BiO(2) was considered a network former by observing the presence of octahedral BiO(6) and pyramidal BiO(3) groups in the local structure of the samples. An absorption band observed at 1103 cm(-1) in the IR spectrum of the undoped glass was attributed to the Bi-O-Ge and/or Bi-O-Bi linkage vibration. The said band shifted to lower wavenumbers after the CeO(2) addition thus reflecting changes in the glass network. Cerium oxide was an efficient oxidant agent to prevent the darkening of the glasses which was probably associated to the reduction of Bi ions. However, CeO(2) was incorporated as a local network modifier in the glass structure even at concentrations of 0.2 mol%. (C) 2010 Elsevier B.V. All rights reserved.

Generating segmented meshes from textured color images

This paper presents a new framework for generating triangular meshes from textured color images. The proposed framework combines a texture classification technique, called W-operator, with Imesh, a method originally conceived to generate simplicial meshes from gray scale images. An extension of W-operators to handle textured color images is proposed, which employs a combination of RGB and HSV channels and Sequential Floating Forward Search guided by mean conditional entropy criterion to extract features from the training data. The W-operator is built into the local error estimation used by Imesh to choose the mesh vertices. Furthermore, the W-operator also enables to assign a label to the triangles during the mesh construction, thus allowing to obtain a segmented mesh at the end of the process. The presented results show that the combination of W-operators with Imesh gives rise to a texture classification-based triangle mesh generation framework that outperforms pixel based methods. Crown Copyright (C) 2009 Published by Elsevier Inc. All rights reserved.

A non-parametric vessel detection method for complex vascular structures

Modern medical imaging techniques enable the acquisition of in vivo high resolution images of the vascular system. Most common methods for the detection of vessels in these images, such as multiscale Hessian-based operators and matched filters, rely on the assumption that at each voxel there is a single cylinder. Such an assumption is clearly violated at the multitude of branching points that are easily observed in all, but the Most focused vascular image studies. In this paper, we propose a novel method for detecting vessels in medical images that relaxes this single cylinder assumption. We directly exploit local neighborhood intensities and extract characteristics of the local intensity profile (in a spherical polar coordinate system) which we term as the polar neighborhood intensity profile. We present a new method to capture the common properties shared by polar neighborhood intensity profiles for all the types of vascular points belonging to the vascular system. The new method enables us to detect vessels even near complex extreme points, including branching points. Our method demonstrates improved performance over standard methods on both 2D synthetic images and 3D animal and clinical vascular images, particularly close to vessel branching regions. (C) 2008 Elsevier B.V. All rights reserved.

Identification of genes associated with local aggressiveness and metastatic behavior in soft tissue tumors

Soft tissue tumors represent a group of neoplasia with different histologic and biological presentations varying from benign, locally confined to very aggressive and metastatic tumors. The molecular mechanisms responsible for such differences are still unknown. The understanding of these molecular alterations mechanism will be critical to discriminate patients who need systemic treatment from those that can be treated only locally and could also guide the development of new drugs` against this tumors. Using 102 tumor samples representing a large spectrum of these tumors, we performed expression profiling and defined differentially expression genes that are likely to be involved in tumors that are locally aggressive and in tumors with metastatic potential. We described a set of 12 genes (SNRPD3, MEGF9, SPTAN-1, AFAP1L2, ENDOD1, SERPIN5, ZWINTAS, TOP2A, UBE2C, ABCF1, MCM2, and ARL6IP5) showing opposite expression when these two conditions were compared. These genes are mainly related to cell-cell and cell-extracellular matrix interactions and cell proliferation and might represent helpful tools for a more precise classification and diagnosis as well as potential drug targets.