Non-linear modal analysis for beams subjected to axial loads: Analytical and finite-element solutions

A rigorous derivation of non-linear equations governing the dynamics of an axially loaded beam is given with a clear focus to develop robust low-dimensional models. Two important loading scenarios were considered, where a structure is subjected to a uniformly distributed axial and a thrust force. These loads are to mimic the main forces acting on an offshore riser, for which an analytical methodology has been developed and applied. In particular, non-linear normal modes (NNMs) and non-linear multi-modes (NMMs) have been constructed by using the method of multiple scales. This is to effectively analyse the transversal vibration responses by monitoring the modal responses and mode interactions. The developed analytical models have been crosschecked against the results from FEM simulation. The FEM model having 26 elements and 77 degrees-of-freedom gave similar results as the low-dimensional (one degree-of-freedom) non-linear oscillator, which was developed by constructing a so-called invariant manifold. The comparisons of the dynamical responses were made in terms of time histories, phase portraits and mode shapes. (C) 2008 Elsevier Ltd. All rights reserved.

Fatores associados à qualidade de vida de cuidadores de idosos em assistência domiciliária

O objetivo do presente estudo foi investigar se o comportamento da qualidade de vida (QV) de cuidadores de idosos em assistência domiciliária pode ser influenciado por características sociodemográficas, pela rede de suporte oferecida ao cuidador e por variáveis relacionadas ao ato de cuidar. Foram entrevistados 40 cuidadores de idosos de um Programa de Assistência Domiciliária da cidade de São Paulo. A QV foi mensurada utilizando-se a versão brasileira do Medical Outcomes Study 36 - Item Short-Form Health Survey (SF-36). Características sociodemográficas, as variáveis relacionadas à rede de suporte oferecida ao cuidador e ao ato de cuidar foram obtidas por meio de questionário complementar. A análise de regressão linear mostrou relação independente entre três domínios do SF-36 e o maior número de horas dedicadas ao cuidado: domínios capacidade funcional, aspecto físico e aspecto emocional. Possuir mais de oito anos de escolaridade implicou em melhor pontuação no domínio estado geral de saúde e pior pontuação no domínio aspecto social. Os cuidadores com mais de 60 anos de idade apresentaram pior pontuação no domínio aspecto físico e as mulheres pior pontuação no domínio dor. Os filhos ou cônjuges que prestam cuidado aos seus pais ou parceiros apresentaram pior pontuação no domínio aspecto emocional. Os cuidadores que modificaram sua rotina para prestar os cuidados apresentaram pior pontuação no domínio saúde mental. Tanto fatores sociodemográficos como a rede de suporte oferecida ao cuidador e os fatores relacionados à dinâmica do cuidado são capazes de influenciar negativamente a QV de cuidadores principais de idosos em atendimento domiciliário.

Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

Musical genres: beating to the rhythms of different drums

Online music databases have increased significantly as a consequence of the rapid growth of the Internet and digital audio, requiring the development of faster and more efficient tools for music content analysis. Musical genres are widely used to organize music collections. In this paper, the problem of automatic single and multi-label music genre classification is addressed by exploring rhythm-based features obtained from a respective complex network representation. A Markov model is built in order to analyse the temporal sequence of rhythmic notation events. Feature analysis is performed by using two multi-variate statistical approaches: principal components analysis (unsupervised) and linear discriminant analysis (supervised). Similarly, two classifiers are applied in order to identify the category of rhythms: parametric Bayesian classifier under the Gaussian hypothesis (supervised) and agglomerative hierarchical clustering (unsupervised). Qualitative results obtained by using the kappa coefficient and the obtained clusters corroborated the effectiveness of the proposed method.

Exploring the knowledge contained in neuroimages: Statistical discriminant analysis and automatic segmentation of the most significant changes

Objective: The aim of this article is to propose an integrated framework for extracting and describing patterns of disorders from medical images using a combination of linear discriminant analysis and active contour models. Methods: A multivariate statistical methodology was first used to identify the most discriminating hyperplane separating two groups of images (from healthy controls and patients with schizophrenia) contained in the input data. After this, the present work makes explicit the differences found by the multivariate statistical method by subtracting the discriminant models of controls and patients, weighted by the pooled variance between the two groups. A variational level-set technique was used to segment clusters of these differences. We obtain a label of each anatomical change using the Talairach atlas. Results: In this work all the data was analysed simultaneously rather than assuming a priori regions of interest. As a consequence of this, by using active contour models, we were able to obtain regions of interest that were emergent from the data. The results were evaluated using, as gold standard, well-known facts about the neuroanatomical changes related to schizophrenia. Most of the items in the gold standard was covered in our result set. Conclusions: We argue that such investigation provides a suitable framework for characterising the high complexity of magnetic resonance images in schizophrenia as the results obtained indicate a high sensitivity rate with respect to the gold standard. (C) 2010 Elsevier B.V. All rights reserved.

A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.

ENHANCING MULTISCALE FRACTAL DESCRIPTORS USING FUNCTIONAL DATA ANALYSIS

This work presents a novel approach in order to increase the recognition power of Multiscale Fractal Dimension (MFD) techniques, when applied to image classification. The proposal uses Functional Data Analysis (FDA) with the aim of enhancing the MFD technique precision achieving a more representative descriptors vector, capable of recognizing and characterizing more precisely objects in an image. FDA is applied to signatures extracted by using the Bouligand-Minkowsky MFD technique in the generation of a descriptors vector from them. For the evaluation of the obtained improvement, an experiment using two datasets of objects was carried out. A dataset was used of characters shapes (26 characters of the Latin alphabet) carrying different levels of controlled noise and a dataset of fish images contours. A comparison with the use of the well-known methods of Fourier and wavelets descriptors was performed with the aim of verifying the performance of FDA method. The descriptor vectors were submitted to Linear Discriminant Analysis (LDA) classification method and we compared the correctness rate in the classification process among the descriptors methods. The results demonstrate that FDA overcomes the literature methods (Fourier and wavelets) in the processing of information extracted from the MFD signature. In this way, the proposed method can be considered as an interesting choice for pattern recognition and image classification using fractal analysis.

Fluoride release profile of a nanofilled resin-modified glass ionomer cement

The present study aimed to compare the fluoride (F-) release pattern of a nanofilled resin-modified glass ionomer cement (GIC) (Ketac N100 - KN) with available GICs used in dental practice (resin-modified GIC - Vitremer - V; conventional GIC - Ketac Molar - KM) and a nanofilled resin composite (Filtek Supreme - RC). Discs of each material (n=6) were placed into 4 mL of deionized water in sealed polyethylene vials and shaken, for 15 days. F- release (μg F-/cm²) was measured each day using a fluoride-ion specific electrode. Cumulative F- release means were statistically analyzed by linear regression analysis. In order to analyze the differences among materials and the influence of time in the daily F- release, 2-way ANOVA test was performed (α=0.05). The linear fits between the cumulative F- release profiles of RC and KM and time were weak. KN and V presented a strong relationship between cumulative F- release and time. There were significant differences between the daily F- release overtime up to the third day only for GICs materials. The daily F- release means for RC were similar overtime. The results indicate that the F- release profile of the nanofilled resin-modified GIC is comparable to the resin-modified GIC.

Allometric models for estimating the phytomass of a secondary Atlantic Forest area of southeastern Brazil

The purpose of this study was to develop and validate equations to estimate the aboveground phytomass of a 30 years old plot of Atlantic Forest. In two plots of 100 m², a total of 82 trees were cut down at ground level. For each tree, height and diameter were measured. Leaves and woody material were separated in order to determine their fresh weights in field conditions. Samples of each fraction were oven dried at 80 °C to constant weight to determine their dry weight. Tree data were divided into two random samples. One sample was used for the development of the regression equations, and the other for validation. The models were developed using single linear regression analysis, where the dependent variable was the dry mass, and the independent variables were height (h), diameter (d) and d²h. The validation was carried out using Pearson correlation coefficient, paired t-Student test and standard error of estimation. The best equations to estimate aboveground phytomass were: lnDW = -3.068+2.522lnd (r² = 0.91; s y/x = 0.67) and lnDW = -3.676+0.951ln d²h (r² = 0.94; s y/x = 0.56).

Modelos preditores da fitomassa aérea da Floresta Baixa de Restinga

Este estudo teve como objetivo desenvolver modelos preditores de fitomassa epigéa da vegetação arbórea da Floresta Baixa de Restinga. Foram selecionadas 102 árvores de 29 espécies ocorrentes na área de estudo e 102 indivíduos de jerivá (Syagrus romanzoffiana (Cham.) Glassman), distribuídos proporcionalmente entre as classes de diâmetro da vegetação arbórea. As árvores foram cortadas, ao nível do solo e foram medidos a altura total e o diâmetro à altura do peito (DAP) de cada árvore. As folhas foram separadas do lenho e a massa fresca da porção lenhosa e foliar medidas separadamente. Amostras de cada fração foram secas a 70 °C, até peso constante, para determinação da massa seca das árvores. Os modelos foram desenvolvidos através de análise de regressão linear, sendo a variável dependente a massa seca (MS) das árvores e as variáveis independentes a altura (h), o diâmetro a altura do peito (d) e as relações d² h e d² h multiplicada pela densidade da madeira (ρ d² h). Os modelos desenvolvidos indicam que o diâmetro explica grande parte da variabilidade da fitomassa das árvores da restinga e a altura é a variável explanatória da equação específica para o jerivá. Os modelos selecionados foram: ln MS (kg) = -1,352 + 2,009 ln d (R² = 0,96; s yx = 0,34) para a comunidade vegetal sem jerivá, ln MS (kg) = -2,052 + 0,801 ln d² h (R² = 0,94; s yx = 0,38) para a comunidade incluindo o jerivá, e ln MS (kg) = -0,884 + 2,40 ln h (R² = 0,92; s yx = 0,49) para o jerivá.

Hidrocarbonetos policíclicos aromáticos (HPAS) em cachaça, rum, uísque e álcool combustível

The concentration of 15 polycyclic aromatic hydrocarbons (PAHs) in 57 samples of distillates (cachaça, rum, whiskey, and alcohol fuel) has been determined by HPLC-Fluorescence detection. The quantitative analytical profile of PAHs treated by Partial Least Square - Discriminant Analysis (PLS-DA) provided a good classification of the studied spirits based on their PAHs content. Additionally, the classification of the sugar cane derivatives according to the harvest practice was obtained treating the analytical data by Linear Discriminant Analysis (LDA), using naphthalene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, benz[a]anthracene, benz[b]fluoranthene, and benz[g,h,i]perylene, as a chemical descriptors.

Fatores associados à qualidade da dieta de adultos residentes na Região Metropolitana de São Paulo, Brasil, 2002

Objetivou-se avaliar os fatores demográficos, sócio-econômicos e de estilo de vida associados à qualidade da dieta de adultos residentes na Região Metropolitana de São Paulo, Brasil. Estudo transversal, por meio de inquérito domiciliar, de base populacional, foi realizado no Distrito do Butantã e nos municípios de Itapecerica da Serra, Embu e Taboão da Serra. Utilizaram-se dados de um questionário e um recordatório de 24 horas de 1.840 adultos de 20 anos ou mais, de ambos os sexos, incluídos em um inquérito de saúde (ISA-SP). A qualidade da dieta foi avaliada através do índice de qualidade da dieta (IQD) adaptado para a realidade local. Utilizou-se análise de regressão linear para avaliar a associação entre o IQD e as demais variáveis. A maioria da população (75%) apresentou dieta que necessita de melhora. Observaram-se médias baixas para os componentes: frutas, verduras e legumes, leite e derivados. Número de bens de consumo duráveis, escolaridade do chefe da família e ter 60 anos ou mais se associaram ao IQD em homens. Para as mulheres, a faixa etária se associou ao IQD. Em ambos os modelos, o consumo de calorias se manteve como variável de ajuste.

Presença de mosquitos (Diptera: Culicidae) em piscinões na zona leste de São Paulo

INTRODUÇÃO: Alterações no ambiente vêm contribuindo com mudanças climáticas, como o aumento do volume de chuvas, que acarreta as inundações. Medidas estão sendo tomadas no enfrentamento das inundações, como a implantação dos reservatórios de contenção de cheias (piscinões). Neste trabalho, foi avaliada a fauna de culicídeos, de importância epidemiológica, nos piscinões Caguaçu e Inhumas. MÉTODOS: Foram realizadas coletas mensais nos piscinões Caguaçu e Inhumas, situados na região leste de São Paulo, de março de 2006 a fevereiro de 2007, empregando-se os métodos de concha entomológica e aspirador. Para análise dos dados, foram realizadas análises estatísticas descritivas e a regressão linear simples. RESULTADOS: Foram coletados 8.917 culicídeos, destacando-se Culex (Culex) quinquefasciatus, que representou 98,9% dos espécimes no Inhumas e 95,2% no Caguaçu. No Caguaçu, a maior frequência de imaturos foi observada no vertedouro (61%) e no Inhumas na canaleta (42,6%). A precipitação prediz 87% da abundância numérica de larvas de terceiro e de quarto estágio no Caguaçu e 60% do número de pupas coletadas. No Inhumas, a precipitação explicou 36% da abundância numérica de larvas e 18% do número de pupas. CONCLUSÕES: Culex quinquefasciatus, vetor de agentes da filariose, arboviroses e fator de incômodo à população, foi a espécie mais frequente nos dois ambientes. Medidas de controle da espécie nos piscinões estudados se fazem necessárias tendo em vista seu potencial epidemiológico.

Influência do consumo alimentar na gestação sobre a retenção de peso pós-parto

OBJETIVO: Avaliar a influência da alimentação durante a gestação sobre a retenção de peso pós-parto. MÉTODOS: Foram acompanhadas 82 gestantes adultas e saudáveis que iniciaram o pré-natal em serviço público de saúde no Município de São Paulo, SP, entre abril e junho de 2005. As medidas de peso e estatura foram aferidas na primeira entrevista (até 16 semanas de gestação) e a medida de peso foi repetida em visita domiciliar 15 dias após o parto. O Recordatório de 24 horas foi usado para avaliar o consumo alimentar e foi aplicado nos três trimestres da gestação. Foi calculado o consumo médio de gordura saturada, fibras, açúcar adicionado, refrigerantes, alimentos processados, frutas, verduras e legumes, e a densidade energética da dieta. A retenção de peso foi obtida pela diferença entre a medida de peso pós-parto e a primeira medida realizada. A influência da alimentação sobre a retenção de peso pós-parto foi avaliada por meio de análise de regressão linear múltipla e foi realizado o teste para tendência linear. As variáveis utilizadas para ajuste do modelo foram: índice de massa corporal no início da gestação, estatura, renda familiar per capita, tabagismo, idade e escolaridade. RESULTADOS: O índice de massa corporal inicial médio foi de 24 kg/m² e a retenção média de peso foi de 1,9 kg. O aumento do consumo de gordura saturada (p = 0,005) e alimentos processados (p = 0,014) elevou de forma significativa a retenção de peso pós-parto, após ajuste pelas variáveis de controle. As demais variáveis de consumo alimentar não apresentaram relação significativa com a variável desfecho. CONCLUSÕES: O maior consumo de alimentos não saudáveis, como alimentos processados, e de gordura saturada influencia a elevação da retenção de peso pós-parto.

Calibration of the dietary data obtained from the Brazilian center of the Natural History of HPV Infection in Men study: the HIM Study

The objective of this study was to estimate the regressions calibration for the dietary data that were measured using the quantitative food frequency questionnaire (QFFQ) in the Natural History of HPV Infection in Men: the HIM Study in Brazil. A sample of 98 individuals from the HIM study answered one QFFQ and three 24-hour recalls (24HR) at interviews. The calibration was performed using linear regression analysis in which the 24HR was the dependent variable and the QFFQ was the independent variable. Age, body mass index, physical activity, income and schooling were used as adjustment variables in the models. The geometric means between the 24HR and the calibration-corrected QFFQ were statistically equal. The dispersion graphs between the instruments demonstrate increased correlation after making the correction, although there is greater dispersion of the points with worse explanatory power of the models. Identification of the regressions calibration for the dietary data of the HIM study will make it possible to estimate the effect of the diet on HPV infection, corrected for the measurement error of the QFFQ.