Copper(II) aza-bis(oxazoline) complex immobilized onto ITQ-2 and MCM-22 based materials as heterogeneous catalysts for the cyclopropanation of styrene

A copper(II) chiral aza-bis(oxazoline) homogeneous catalyst (CuazaBox) was anchored onto the external surface of MCM-22 and ITQ-2 structures, as well as encapsulated into hierarchical MCM-22. The transition metal complex loading onto the porous solids was determined by ICP-AES and the materials were also characterized by elemental analysis (C, N, H, S), FTIR, XPS, TG and low temperature N-2 adsorption isotherms. The materials were tested as heterogeneous catalysts in the benchmark reaction of cyclopropanation of styrene to check the effect of the immobilization procedure on the catalytic parameters, as well as on their reutilization in several catalytic cycles. Catalyst CuazaBox anchored onto the external surface of MCM-22 and ITQ-2 materials were more active and enantioselective in the cyclopropanation of styrene than the corresponding homogeneous phase reaction run under similar experimental conditions. This is due to the propylation of the acidic aza-Box nitrogen. HMCM-22 was nevertheless the best heterogeneous catalyst. Encapsulation of CuazaBox on post-synthesis modified MCM-22 materials led to low activities and enantioselectivities. But reversal on the stereochemical course of the reaction was observed, probably due to confinement effect. (C) 2013 Elsevier Inc. All rights reserved.

Risk-factors for antepartum fetal deaths in the city of São Paulo, Brazil

OBJECTIVE: To assess risk factors for antepartum fetal deaths. METHODS: A population-based case-control study was carried out in the city of São Paulo from August 2000 to January 2001. Subjects were selected from a birth cohort from a linked birth and death certificate database. Cases were 164 antepartum fetal deaths and controls were drawn from a random sample of 313 births surviving at least 28 days. Information was collected from birth and death certificates, hospital records and home interviews. A hierarchical conceptual framework guided the logistic regression analysis. RESULTS: Statistically significant factors associated with antepartum fetal death were: mother without or recent marital union; mother's education under four years; mothers with previous low birth weight infant; mothers with hypertension, diabetes, bleeding during pregnancy; no or inadequate prenatal care; congenital malformation and intrauterine growth restriction. The highest population attributable fractions were for inadequacy of prenatal care (40%), hypertension (27%), intrauterine growth restriction (30%) and absence of a long-standing union (26%). CONCLUSIONS: Proximal biological risk factors are most important in antepartum fetal deaths. However, distal factors - mother's low education and marital status - are also significant. Improving access to and quality of prenatal care could have a large impact on fetal mortality.

An ultrasound based computer-aided diagnosis tool for steatosis detection

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool, to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.

Global and local detection of liver steatosis from ultrasound

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. Steatosis is usually a diffuse liver disease, since it is globally affected. However, steatosis can also be focal affecting only some foci difficult to discriminate. In both cases, steatosis is detected by laboratorial analysis and visual inspection of ultrasound images of the hepatic parenchyma. Liver biopsy is the most accurate diagnostic method but its invasive nature suggest the use of other non-invasive methods, while visual inspection of the ultrasound images is subjective and prone to error. In this paper a new Computer Aided Diagnosis (CAD) system for steatosis classification and analysis is presented, where the Bayes Factor, obatined from objective intensity and textural features extracted from US images of the liver, is computed in a local or global basis. The main goal is to provide the physician with an application to make it faster and accurate the diagnosis and quantification of steatosis, namely in a screening approach. The results showed an overall accuracy of 93.54% with a sensibility of 95.83% and 85.71% for normal and steatosis class, respectively. The proposed CAD system seemed suitable as a graphical display for steatosis classification and comparison with some of the most recent works in the literature is also presented.

Fatty liver characterization and classification by ultrasound

Steatosis, also known as fatty liver, corresponds to an abnormal retention of lipids within the hepatic cells and reflects an impairment of the normal processes of synthesis and elimination of fat. Several causes may lead to this condition, namely obesity, diabetes, or alcoholism. In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis from ultrasound images. The features are selected in order to catch the same characteristics used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The algorithm, designed in a Bayesian framework, computes two images: i) a despeckled one, containing the anatomic and echogenic information of the liver, and ii) an image containing only the speckle used to compute the textural features. These images are computed from the estimated RF signal generated by the ultrasound probe where the dynamic range compression performed by the equipment is taken into account. A Bayes classifier, trained with data manually classified by expert clinicians and used as ground truth, reaches an overall accuracy of 95% and a 100% of sensitivity. The main novelties of the method are the estimations of the RF and speckle images which make it possible to accurately compute textural features of the liver parenchyma relevant for the diagnosis.

Machine Learning Algorithms at Myocardial Perfusion Imaging - a Preliminary Study

Introduction: A major focus of data mining process - especially machine learning researches - is to automatically learn to recognize complex patterns and help to take the adequate decisions strictly based on the acquired data. Since imaging techniques like MPI – Myocardial Perfusion Imaging on Nuclear Cardiology, can implicate a huge part of the daily workflow and generate gigabytes of data, there could be advantages on Computerized Analysis of data over Human Analysis: shorter time, homogeneity and consistency, automatic recording of analysis results, relatively inexpensive, etc.Objectives: The aim of this study relates with the evaluation of the efficacy of this methodology on the evaluation of MPI Stress studies and the process of decision taking concerning the continuation – or not – of the evaluation of each patient. It has been pursued has an objective to automatically classify a patient test in one of three groups: “Positive”, “Negative” and “Indeterminate”. “Positive” would directly follow to the Rest test part of the exam, the “Negative” would be directly exempted from continuation and only the “Indeterminate” group would deserve the clinician analysis, so allowing economy of clinician’s effort, increasing workflow fluidity at the technologist’s level and probably sparing time to patients. Methods: WEKA v3.6.2 open source software was used to make a comparative analysis of three WEKA algorithms (“OneR”, “J48” and “Naïve Bayes”) - on a retrospective study using the comparison with correspondent clinical results as reference, signed by nuclear cardiologist experts - on “SPECT Heart Dataset”, available on University of California – Irvine, at the Machine Learning Repository. For evaluation purposes, criteria as “Precision”, “Incorrectly Classified Instances” and “Receiver Operating Characteristics (ROC) Areas” were considered. Results: The interpretation of the data suggests that the Naïve Bayes algorithm has the best performance among the three previously selected algorithms. Conclusions: It is believed - and apparently supported by the findings - that machine learning algorithms could significantly assist, at an intermediary level, on the analysis of scintigraphic data obtained on MPI, namely after Stress acquisition, so eventually increasing efficiency of the entire system and potentially easing both roles of Technologists and Nuclear Cardiologists. In the actual continuation of this study, it is planned to use more patient information and significantly increase the population under study, in order to allow improving system accuracy.

Towards a complex model of cooperative learning

Este artigo é uma introdução à teoria do paradigma desconstrutivo de aprendizagem cooperativa. Centenas de estudos provam com evidências o facto de que as estruturas e os processos de aprendizagem cooperativa aumentam o desempenho académico, reforçam as competências de aprendizagem ao longo da vida e desenvolvem competências sociais, pessoais de cada aluno de uma forma mais eficaz e usta, comparativamente às estruturas tradicionais de aprendizagem nas escolas. Enfrentando os desafios dos nossos sistemas educativos, seria interessante elaborar o quadro teórico do discurso da aprendizagem cooperativa, dos últimos 40 anos, a partir de um aspeto prático dentro do contexto teórico e metodológico. Nas últimas décadas, o discurso cooperativo elaborou os elementos práticos e teóricos de estruturas e processos de aprendizagem cooperativa. Gostaríamos de fazer um resumo desses elementos com o objetivo de compreender que tipo de mudanças estruturais podem fazer diferenças reais na prática de ensino e aprendizagem. Os princípios básicos de estruturas cooperativas, os papéis de cooperação e as atitudes cooperativas são os principais elementos que podemos brevemente descrever aqui, de modo a criar um quadro para a compreensão teórica e prática de como podemos sugerir os elementos de aprendizagem cooperativa na nossa prática em sala de aula. Na minha perspetiva, esta complexa teoria da aprendizagem cooperativa pode ser entendida como um paradigma desconstrutivo que fornece algumas respostas pragmáticas para as questões da nossa prática educativa quotidiana, a partir do nível da sala de aula para o nível de sistema educativo, com foco na destruição de estruturas hierárquicas e antidemocráticas de aprendizagem e, criando, ao mesmo tempo, as estruturas cooperativas.

Modelo de data mining para detecção de tumores em exames de rastreio

Dissertação para obtenção do grau de Mestre em Engenharia Informática

On clustering interval data with different scales of measures : experimental results

This article is is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Attribution-NonCommercial (CC BY-NC) license lets others remix, tweak, and build upon work non-commercially, and although the new works must also acknowledge & be non-commercial.

Cluster analysis using affinity aoefficient in order to identify religious beliefs profiles

International Scientific Forum, ISF 2013, ISF 2013, 12-14 December 2013, Tirana.

Probabilistic approach for comparing partitions

3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon, Portugal.

On cluster analysis of complex and heterogeneous data

3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.

Clustering of variables with a three-way approach for health sciences

TPM Vol. 21, No. 4, December 2014, 435-447 – Special Issue © 2014 Cises.

Modelagem Bayesiana do risco de infecção tuberculosa para estudos com perdas de seguimento

OBJETIVO: Desenvolver um modelo estatístico baseado em métodos Bayesianos para estimar o risco de infecção tuberculosa em estudos com perdas de seguimento, comparando-o com um modelo clássico determinístico. MÉTODOS: O modelo estocástico proposto é baseado em um algoritmo de amostradores de Gibbs, utilizando as informações de perdas de seguimento ao final de um estudo longitudinal. Para simular o número desconhecido de indivíduos reatores ao final do estudo e perdas de seguimento, mas não reatores no tempo inicial, uma variável latente foi introduzida no novo modelo. Apresenta-se um exercício de aplicação de ambos os modelos para comparação das estimativas geradas. RESULTADOS: As estimativas pontuais fornecidas por ambos os modelos são próximas, mas o modelo Bayesiano apresentou a vantagem de trazer os intervalos de credibilidade como medidas da variabilidade amostral dos parâmetros estimados. CONCLUSÕES: O modelo Bayesiano pode ser útil em estudos longitudinais com baixa adesão ao seguimento.

Factors related to inadequate cervical cancer screening in two Brazilian state capitals

OBJECTIVE:To analyze factors associated with cervical cancer screening failure. METHODS:Population-based cross-sectional study with self-weighted two-stage cluster sampling conducted in the cities of Fortaleza (Northeastern Brazil) and Rio de Janeiro (Southeastern Brazil) in 2002. Subjects were women aged 25-59 years in the last three years prior to the study. Data were analyzed through Poisson regression using a hierarchical model. RESULTS: The proportion of women who did not undergo the Pap smear test in Fortaleza and Rio de Janeiro was 19.1% (95% CI: 16.1;22.1) and 16.5% (95% CI: 14.1;18.9), respectively. Higher prevalence ratios of cervical cancer screening failure in both cities were seen among women with low education and low per capita income, old age, unmarried, who never underwent mammography, clinical breast examination, and blood glucose and cholesterol level testing. Smokers also had lower screening rates compared to non-smoker women and this difference was only statistically significant in Rio de Janeiro. CONCLUSIONS:The study findings point to the need of intervention focusing particularly women in worse socioeconomic conditions and access to healthcare, old-aged and unmarried. Education activities must prioritize screening of asymptomatic women and early diagnosis for symptomatic women and access to adequate diagnostic methods and treatment should be provided.