Location and characteristics of the reconnection X line deduced from low-altitude satellite and ground-based observations: 1. Theory

A method for estimating both the Alfvén speed and the field-aligned flow of the magnetosheath at the magnetopause reconnection site is presented. The method employs low-altitude cusp ion observations and requires the identification of a feature in the cusp ion spectra near the low-energy cutoff which will often be present for a low-latitude dayside reconnection site. The appearance of these features in data of limited temporal, energy, and pitch angle resolution is illustrated by using model calculations of cusp ion distribution functions. These are based on the theory of ion acceleration at the dayside magnetopause and allow for the effects on the spectrum of flight times of ions precipitating down newly opened field lines. In addition, the variation of the reconnection rate can be evaluated, and comparison with ground-based observations of the corresponding sequence of transient events allows the field-aligned distance from the ionosphere to the reconnection site to be estimated.

Road Sign Recognition based onInvariant Features using SupportVector Machine

Since last two decades researches have been working on developing systems that can assistsdrivers in the best way possible and make driving safe. Computer vision has played a crucialpart in design of these systems. With the introduction of vision techniques variousautonomous and robust real-time traffic automation systems have been designed such asTraffic monitoring, Traffic related parameter estimation and intelligent vehicles. Among theseautomatic detection and recognition of road signs has became an interesting research topic.The system can assist drivers about signs they don’t recognize before passing them.Aim of this research project is to present an Intelligent Road Sign Recognition System basedon state-of-the-art technique, the Support Vector Machine. The project is an extension to thework done at ITS research Platform at Dalarna University [25]. Focus of this research work ison the recognition of road signs under analysis. When classifying an image its location, sizeand orientation in the image plane are its irrelevant features and one way to get rid of thisambiguity is to extract those features which are invariant under the above mentionedtransformation. These invariant features are then used in Support Vector Machine forclassification. Support Vector Machine is a supervised learning machine that solves problemin higher dimension with the help of Kernel functions and is best know for classificationproblems.

Residual-based Inference for Common Nonlinear Features

This paper investigates common nonlinear features in multivariate nonlinear autore-gressive models via testing the estimated residuals. A Wald-type test is proposed and itis asymptotically Chi-squared distributed. Simulation studies are given to examine thefinite-sample properties of the proposed test.

Follicular diameter range based on morphological features in Synbranchus marmoratus (Bloch, 1795) (Teleostei, Synbranchiformes, Synbranchidae) from the South-central region of Brazil

The morphological characteristics of Synbranchus marmoratus female germ cells in various development stages were described in details; then measurements of ovarian follicle diameters were taken from primary and secondary growth as during these development stages the oocyte size varied considerably along the fish growth. The results were correlated to total fish length, using the individuals division in six size classes. It was possible to group oocytes by stages according to histological characteristics but not according to morphometric diameter, as there was a wide variation in diameter in each stage and overlap between different maturation stages. These data make available new information on the reproductive biology of Synbranchidae. (c) 2004 Published by Elsevier Ltd.

Thermal conductivity features of ZnO-based varistors using the laser-pulse method

The thermal conductivity of several commercial ZnO-based varistor systems was determined based on the laser-pulse method, a technique that proved extremely useful and easy to apply. Using this technique, the thermal conductivity was found to be dependent on the microstructural features of the devices, involving the mean grain size and phase composition. Among the phases existing in commercial ZnO-based varistors, ZniSb2O12 and Bi2O3 were found to contribute strongly to the thermal conductivity of the devices. (C) 2003 Elsevier B.V. All rights reserved.

How Cr2O3 influences the microstructure and nonohmic features of the SnO2(COx, Mn1-x)O-based varistor system

An investigation was made to discover how the addition of Cr2O3 affects the microstructural heterogeneity and nonohmic features of the SnO2(Co-x, Mn1-x)O-based varistor system, with x varying from 0 to 1. The presence of Cr2O3 was found to strongly increase the nonohmic features when x = 1. However, the nonohmic features of the system decrease when x drops from 1 to 0, a behavior explained by the increase of the junction heterogeneity within the system's microstructure. accompanied by ail excess of precipitates at the triple point in the grain boundary region due to modified MnO sintering. The presence of these precipitates causes the leakage current to increase in response to the creation of ail ineffective barrier. The effect produced by heat-treating these systems in oxygen- and nitrogen-rich atmospheres suggests that, according to mechanisms previously discussed in the literature, Cr2O3 is more susceptible to oxygen, so that increasing the amount of oxygen in the grain boundary region may improve the system's nonohmic properties. (c) 2005 Elsevier Ltd. All rights reserved.

Local structure and near-infrared emission features of neodymium-based amine functionalized organic/inorganic hybrids

Nd3+-based organic/inorganic hybrids have potential application in the field of integrated optics. Attractive sol-gel derived di-urea and di-urethane cross-linked poly (oxyethylene) (POE)/siloxane hybrids (di-ureasils and di-urethanesils, respectively) doped with neodymium triflate (Nd(CF3SO3)(3)) were examined by Fourier transform mid-infrared (FT-IR), Raman (FT-Raman), Si-29 magic-angle spinning (MAS) nuclear magnetic resonance (NMR) and photoluminescence spectroscopies, and small-angle X-ray scattering (SAXS). The goals of this work were to determine which cation coordinating site of the host matrix (ether oxygen atoms or carbonyl oxygen atoms) is active in each of the materials analyzed, its influence on the nanostructure of the samples and its relation with the photoluminescence properties. The main conclusion derived from this study is that the hydrogen-bonded associations formed throughout the materials play a major role in the hybrids nanostructure and photoluminescence properties.

Semiautomatic dental recognition using a graph-based segmentation algorithm and teeth shapes features

Dental recognition is very important for forensic human identification, mainly regarding the mass disasters, which have frequently happened due to tsunamis, airplanes crashes, etc. Algorithms for automatic, precise, and robust teeth segmentation from radiograph images are crucial for dental recognition. In this work we propose the use of a graph-based algorithm to extract the teeth contours from panoramic dental radiographs that are used as dental features. In order to assess our proposal, we have carried out experiments using a database of 1126 tooth images, obtained from 40 panoramic dental radiograph images from 20 individuals. The results of the graph-based algorithm was qualitatively assessed by a human expert who reported excellent scores. For dental recognition we propose the use of the teeth shapes as biometric features, by the means of BAS (Bean Angle Statistics) and Shape Context descriptors. The BAS descriptors showed, on the same database, a better performance (EER 14%) than the Shape Context (EER 20%). © 2012 IEEE.

Immunohistochemical features of multifocal melanoacanthoma in the hard palate: A case report

Background: Melanoacanthoma (MA) has been described in the oral mucosa as a solitary lesion or, occasionally, as multiple lesions. MA mainly affects dark skinned patients and grows rapidly, showing a plane or slightly raised appearance and a brown to black color. The differential diagnosis includes oral nevi, amalgam tattoos, and melanomas. We report here the case of a 58-year-old black woman who presented multiple pigmented lesions on the hard palate. Case presentation. Based on the differential diagnosis of melanoma, a punch biopsy (4 mm in diameter) was performed. The material was fixed in 10% formalin, embedded in paraffin, and stained with hematoxylin-eosin or submitted to immunohistochemical analysis. Immunohistochemistry using antibodies against protein S-100, melan-A, HMB-45, MCM-2, MCM-5, Ki-67 and geminin was performed. Immunohistochemical analysis revealed strong cytoplasmic immunoreactivity of dendritic melanocytes for proteinS-100, HMB-45 and melan-A.Positive staining for proliferative markers (MCM-2, MCM-5, Ki-67) was only observed in basal and suprabasal epithelial cells, confirming the reactive etiology of the lesion. The diagnosis was oral Melanoacanthoma (MA). Conclusion: The patient has been followed up for 30 months and shows no clinical alterations. MA should be included in the differential diagnosis of pigmented lesions of the oral cavity. © 2013 das Chagas e Silva de Carvalho et al.; licensee BioMed Central Ltd.

Ureasil-polyether hybrid blend with tuneable hydrophilic/hydrophobic features based on U-PEO1900 and U-PPO400 mixtures

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Mesh-based vs. Image-based Statistical Appearance Model of the Human Femur: a Preliminary Comparison Study for the Creation of Finite Element Meshes

Statistical models have been recently introduced in computational orthopaedics to investigate the bone mechanical properties across several populations. A fundamental aspect for the construction of statistical models concerns the establishment of accurate anatomical correspondences among the objects of the training dataset. Various methods have been proposed to solve this problem such as mesh morphing or image registration algorithms. The objective of this study is to compare a mesh-based and an image-based statistical appearance model approaches for the creation of nite element(FE) meshes. A computer tomography (CT) dataset of 157 human left femurs was used for the comparison. For each approach, 30 finite element meshes were generated with the models. The quality of the obtained FE meshes was evaluated in terms of volume, size and shape of the elements. Results showed that the quality of the meshes obtained with the image-based approach was higher than the quality of the mesh-based approach. Future studies are required to evaluate the impact of this finding on the final mechanical simulations.

Comprehensive analysis of CpG island methylator phenotype (CIMP)-high, -low, and -negative colorectal cancers based on protein marker expression and molecular features

CpG island methylator phenotype (CIMP) is being investigated for its role in the molecular and prognostic classification of colorectal cancer patients but is also emerging as a factor with the potential to influence clinical decision-making. We report a comprehensive analysis of clinico-pathological and molecular features (KRAS, BRAF and microsatellite instability, MSI) as well as of selected tumour- and host-related protein markers characterizing CIMP-high (CIMP-H), -low, and -negative colorectal cancers. Immunohistochemical analysis for 48 protein markers and molecular analysis of CIMP (CIMP-H: ? 4/5 methylated genes), MSI (MSI-H: ? 2 instable genes), KRAS, and BRAF were performed on 337 colorectal cancers. Simple and multiple regression analysis and receiver operating characteristic (ROC) curve analysis were performed. CIMP-H was found in 24 cases (7.1%) and linked (p < 0.0001) to more proximal tumour location, BRAF mutation, MSI-H, MGMT methylation (p = 0.022), advanced pT classification (p = 0.03), mucinous histology (p = 0.069), and less frequent KRAS mutation (p = 0.067) compared to CIMP-low or -negative cases. Of the 48 protein markers, decreased levels of RKIP (p = 0.0056), EphB2 (p = 0.0045), CK20 (p = 0.002), and Cdx2 (p < 0.0001) and increased numbers of CD8+ intra-epithelial lymphocytes (p < 0.0001) were related to CIMP-H, independently of MSI status. In addition to the expected clinico-pathological and molecular associations, CIMP-H colorectal cancers are characterized by a loss of protein markers associated with differentiation, and metastasis suppression, and have increased CD8+ T-lymphocytes regardless of MSI status. In particular, Cdx2 loss seems to strongly predict CIMP-H in both microsatellite-stable (MSS) and MSI-H colorectal cancers. Cdx2 is proposed as a surrogate marker for CIMP-H.