Azorean Agriculture Efficiency by PAR

Copyright © 2013 Springer Netherlands.

A new frontier in biodiversity inventory: a proposal for estimators of phylogenetic and functional diversity

Copyright © 2014 The Authors. Methods in Ecology and Evolution © 2014 British Ecological Society.

Determinants of salivary cotinine level: a population-based study in Brazil

OBJECTIVE: A cross-sectional population-based study was conducted to assess, in active smokers, the relationship of number of cigarettes smoked and other characteristics to salivary cotinine concentrations. METHODS: A random sample of active smokers aged 15 years or older was selected using a stepwise cluster sample strategy, in the year 2000 in Rio de Janeiro, Brazil. The study included 401 subjects. Salivary cotinine concentration was determined using gas chromatography with nitrogen-phosphorus detection. A standard questionnaire was used to collect demographic and smoking behavioral data. The relation between the number of cigarettes smoked in the last 24h and cotinine level was examined by means of a nonparametric fitting technique of robust locally weighted regression. RESULTS: Significantly (p<0.05) higher adjusted mean cotinine levels were found in subjects smoking their first cigarette within five minutes after waking up, and in those smoking 1-20 cigarettes in the last 24h who reported inhaling more than ½ the time. In those smoking 1-20 cigarettes, the slope was significantly higher for those subjects waiting for more than five minutes before smoking their first cigarette after waking up, and those smoking "light" cigarettes when compared with their counterparts. These heterogeneities became negligible and non-significant when subjects with cotinine >40 ng/mL per cigarette were excluded. CONCLUSIONS: There was found a positive association between self-reporting smoking five minutes after waking up, and inhaling more than ½ the time are consistent and higher cotinine levels. These can be markers of dependence and higher nicotine intake. Salivary cotinine proved to be a useful biomarker of recent smoking and can be used in epidemiological studies and smoking cessation programs.

Influência do peróxido e do uso de diferentes substâncias de combate à dor na inflamação e na expressão de neuropeptídeos pró-inflamatórios após o tratamento clareador

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

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.

Classification and staging of chronic liver disease from multimodal data

Chronic liver disease (CLD) is most of the time an asymptomatic, progressive, and ultimately potentially fatal disease. In this study, an automatic hierarchical procedure to stage CLD using ultrasound images, laboratory tests, and clinical records are described. The first stage of the proposed method, called clinical based classifier (CBC), discriminates healthy from pathologic conditions. When nonhealthy conditions are detected, the method refines the results in three exclusive pathologies in a hierarchical basis: 1) chronic hepatitis; 2) compensated cirrhosis; and 3) decompensated cirrhosis. The features used as well as the classifiers (Bayes, Parzen, support vector machine, and k-nearest neighbor) are optimally selected for each stage. A large multimodal feature database was specifically built for this study containing 30 chronic hepatitis cases, 34 compensated cirrhosis cases, and 36 decompensated cirrhosis cases, all validated after histopathologic analysis by liver biopsy. The CBC classification scheme outperformed the nonhierachical one against all scheme, achieving an overall accuracy of 98.67% for the normal detector, 87.45% for the chronic hepatitis detector, and 95.71% for the cirrhosis detector.

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.

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

Dissertação para obtenção do grau de Mestre em Engenharia Informática

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.

O reconhecimento e a divulgação dos impostos diferidos em Portugal: Análise às entidades cotadas no PSI geral durante os anos de 2009 a 2011

Mestrado em Fiscalidade

Surveillance of mother-to-child HIV transmission: socioeconomic and health care coverage indicators

OBJECTIVE: To identify clustering areas of infants exposed to HIV during pregnancy and their association with indicators of primary care coverage and socioeconomic condition. METHODS: Ecological study where the unit of analysis was primary care coverage areas in the city of Porto Alegre, Southern Brazil, in 2003. Geographical Information System and spatial analysis tools were used to describe indicators of primary care coverage areas and socioeconomic condition, and estimate the prevalence of liveborn infants exposed to HIV during pregnancy and delivery. Data was obtained from Brazilian national databases. The association between different indicators was assessed using Spearman's nonparametric test. RESULTS: There was found an association between HIV infection and high birth rates (r=0.22, p<0.01) and lack of prenatal care (r=0.15, p<0.05). The highest HIV infection rates were seen in areas with poor socioeconomic conditions and difficult access to health services (r=0.28, p<0.01). The association found between higher rate of prenatal care among HIV-infected women and adequate immunization coverage (r=0.35, p<0.01) indicates that early detection of HIV infection is effective in those areas with better primary care services. CONCLUSIONS: Urban poverty is a strong determinant of mother-to-child HIV transmission but this trend can be fought with health surveillance at the primary care level.

Qualidade do chocolate: estudo de alguns parâmetros

O chocolate é considerado uma emulsão complexa e um alimento de luxo, que durante o seu consumo provoca estímulos que activam os centros de prazer do cérebro Humano. Tendo em conta a importância deste alimento torna-se necessário estudar e avaliar a melhor forma de melhorar a qualidade do chocolate. Este trabalho teve como objectivo verificar e analisar a qualidade do processo de fabrico da massa de chocolate, no que respeita (i) a rastreabilidade das matérias-primas e do produto acabado e, por outro lado, (ii) determinar e estudar o efeito de alguns parâmetros do processo nas características da massa, através das variáveis viscosidade, tensão de corte, tensão de corte crítica (“yield value”) e granulometria. Estas variáveis foram medidas em massas de chocolate de leite com o nome de formulação CAI e provenientes das duas unidades fabris da empresa (UF1 e UF2). Os parâmetros estudados na UF1 foram a influência das conchas e dos ingredientes. Na UF2 estudou-se a influência dos inutilizados de fabrico e a influência dos inutilizados de fabrico juntamente com o efeito de um ingrediente que foi o açúcar. Os resultados da viscosidade, tensão de corte e tensão de corte crítica (“yield value”) foram analisados estatisticamente por análise de variância (ANOVA), recorrendo aos testes de Komolgorov-Smirnov, Shapiro-Wilk e de Levene para verificar as condições de aplicabilidade desta análise. Os resultados da granulometria como não aderiram a uma distribuição normal foram analisados pelo método não paramétrico de Kruskal-Wallis. Estas análises foram executadas no programa “Statistical Package for the Social Sciences” (SPSS). Pelos resultados obtidos, conclui-se que, para a UF1, a concha afecta a tensão de corte, viscosidade e a tensão de corte crítica do chocolate produzido, na medida em que existem diferenças entre as conchas estudadas. Para esta unidade conclui-se que os ingredientes também influenciam a granulometria da massa. No caso da UF2, conclui-se que a tensão de corte é afectada apenas pelo lote de açúcar, a viscosidade é afectada tanto pelo lote de açúcar como pela presença de inutilizados de fabrico e a tensão de corte crítica não é afectada por nenhum destes efeitos. A granulometria, nesta unidade é afectada pelos lotes de açúcar estudados.

Automatic diagnosis of liver steatosis by ultrasound using autoregressive tissue characterization

Liver steatosis is mainly a textural abnormality of the hepatic parenchyma due to fat accumulation on the hepatic vesicles. Today, the assessment is subjectively performed by visual inspection. Here a classifier based on features extracted from ultrasound (US) images is described for the automatic diagnostic of this phatology. The proposed algorithm estimates the original ultrasound radio-frequency (RF) envelope signal from which the noiseless anatomic information and the textural information encoded in the speckle noise is extracted. The features characterizing the textural information are the coefficients of the first order autoregressive model that describes the speckle field. A binary Bayesian classifier was implemented and the Bayes factor was calculated. The classification has revealed an overall accuracy of 100%. The Bayes factor could be helpful in the graphical display of the quantitative results for diagnosis purposes.