Screening Brazilian commercial gasoline quality by hydrogen nuclear magnetic resonance spectroscopic fingerprintings and pattern-recognition multivariate chemometric analysis

The identification of gasoline adulteration by organic solvents is not an easy task, because compounds that constitute the solvents are already in gasoline composition. In this work, the combination of Hydrogen Nuclear Magnetic Resonance ((1)H NMR) spectroscopic fingerprintings with pattern-recognition multivariate Soft Independent Modeling of Class Analogy (SIMCA) chemometric analysis provides an original and alternative approach to screening Brazilian commercial gasoline quality in a Monitoring Program for Quality Control of Automotive Fuels. SIMCA was performed on spectroscopic fingerprints to classify the quality of representative commercial gasoline samples selected by Hierarchical Cluster Analysis (HCA) and collected over a 6-month period from different gas stations in the São Paulo state, Brazil. Following optimized the (1)H NMR-SIMCA algorithm, it was possible to correctly classify 92.0% of commercial gasoline samples, which is considered acceptable. The chemometric method is recommended for routine applications in Quality-Control Monitoring Programs, since its measurements are fast and can be easily automated. Also, police laboratories could employ this method for rapid screening analysis to discourage adulteration practices. (C) 2010 Elsevier B.V. All rights reserved.

DIAGNOSIS of REGIONAL CEREBRAL BLOOD FLOW ABNORMALITIES USING SPECT: AGREEMENT BETWEEN INDIVIDUALIZED STATISTICAL PARAMETRIC MAPS and VISUAL INSPECTION BY NUCLEAR MEDICINE PHYSICIANS WITH DIFFERENT LEVELS of EXPERTISE IN NUCLEAR NEUROLOGY

INTRODUCTION: Visual analysis is widely used to interpret regional cerebral blood flow (rCBF) SPECT images in clinical practice despite its limitations. Automated methods are employed to investigate between-group rCBF differences in research Studies but have rarely been explored in individual analyses.OBJECTIVES: To compare visual inspection by nuclear physicians with the automated statistical parametric mapping program using a SPECT dataset of patients with neurological disorders and normal control images.METHODS: Using statistical parametric mapping, 14 SPECT images from patients with various neurological disorders were compared individually with a databank of 32 normal images using a statistical threshold of p<0.05 (corrected for multiple comparisons at the level of individual voxels or clusters). Statistical parametric mapping results were compared with Visual analyses by a nuclear physician highly experienced in neurology (A) as well as a nuclear physician with a general background of experience (B) who independently classified images as normal or altered, and determined the location of changes and the severity.RESULTS: of the 32 images of the normal databank, 4 generated maps showing rCBF abnormalities (p<0.05, corrected). Among the 14 images from patients with neurological disorders, 13 showed rCBF alterations. Statistical parametric mapping and physician A completely agreed on 84.37% and 64.28% of cases from the normal databank and neurological disorders, respectively. The agreement between statistical parametric mapping and ratings of physician B were lower (71.18% and 35.71%, respectively).CONCLUSION: Statistical parametric mapping replicated the findings described by the more experienced nuclear physician. This finding suggests that automated methods for individually analyzing rCBF SPECT images may be a valuable resource to complement visual inspection in clinical practice.

Nuclear data for proton beam radiotherapy

The need for a program of work focused on the nuclear data evaluation of chargedparticle reactions has arisen recently due to their increasing use in cancer therapy. This project, as part of that program, has as its main goal the selection and comparison of nuclear data for nuclear reactions induced by protons at low to intermediate energies (E < 250 MeV). The methodology of selection was based on the data base EXFOR and the compilations of radionuclide production cross sections of N. Sobolevsky. For the purpose of comparison and evaluation, theoretical calculations with the reaction model code EMPIRE-II are being used. © 2009 American Institute of Physics.

A educação escolar e a relação entre o desenvolvimento do pensamento e a apropriação da cultura: a psicologia de A. N. Leontiev como referência nuclear de análise

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estudo teórico da contribuição do espalhamento nuclear não elástico na trajetória de prótons de energias entre 50 e 250 MeV em materiais de interesse em radiologia: aplicação em tomografia com prótons

The goal of this work is to study the process of interaction of protons with matter through Monte Carlo simulation. For this purpose, it was employed the SRIM program (Stopping and Range of Ions in Matter ) and MCNPX (Monte Carlo N-Particle eXtended) v2.50. This work is going to support the development of a tomography system with protons. It was studied the interaction of proton with the follow materials: Polimethyl Mehacralate (PMMA), MS20 Tissue Substitute and water. This work employed energies in range of 50 MeV and 250 MeV, that is the range of clinical interest. The energy loss of proton after cross a material layer, the decreasing of its intensity, the angular and lateral de ection of incident beam, including and excluding nuclear interactions. This work is related with Medical Physics and Material Physics, like interaction of radiation with matter, particle transport phenomena, and the experimental methods in Nuclear Physics like simulation and computational by Monte Carlo method

Análise da relação filogenética entre Triatoma carcavalloi Jurberg, Rocha; Lent, 1998; Triatoma circummaculata Stal, 1859; Triatoma klugi Carcavallo, Jurberg, Lent; Galvão, 2001 e Triatoma rubrovaria Blanchard, 1843 (Hemiptera, Reduviidae) baseada no sequenciamento de genes do DNA mitocondrial e nuclear

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)