New Rigorous Decomposition Methods for Mixed-integer Linear and Nonlinear Programming

Process systems design, operation and synthesis problems under uncertainty can readily be formulated as two-stage stochastic mixed-integer linear and nonlinear (nonconvex) programming (MILP and MINLP) problems. These problems, with a scenario based formulation, lead to large-scale MILPs/MINLPs that are well structured. The first part of the thesis proposes a new finitely convergent cross decomposition method (CD), where Benders decomposition (BD) and Dantzig-Wolfe decomposition (DWD) are combined in a unified framework to improve the solution of scenario based two-stage stochastic MILPs. This method alternates between DWD iterations and BD iterations, where DWD restricted master problems and BD primal problems yield a sequence of upper bounds, and BD relaxed master problems yield a sequence of lower bounds. A variant of CD, which includes multiple columns per iteration of DW restricted master problem and multiple cuts per iteration of BD relaxed master problem, called multicolumn-multicut CD is then developed to improve solution time. Finally, an extended cross decomposition method (ECD) for solving two-stage stochastic programs with risk constraints is proposed. In this approach, a CD approach at the first level and DWD at a second level is used to solve the original problem to optimality. ECD has a computational advantage over a bilevel decomposition strategy or solving the monolith problem using an MILP solver. The second part of the thesis develops a joint decomposition approach combining Lagrangian decomposition (LD) and generalized Benders decomposition (GBD), to efficiently solve stochastic mixed-integer nonlinear nonconvex programming problems to global optimality, without the need for explicit branch and bound search. In this approach, LD subproblems and GBD subproblems are systematically solved in a single framework. The relaxed master problem obtained from the reformulation of the original problem, is solved only when necessary. A convexification of the relaxed master problem and a domain reduction procedure are integrated into the decomposition framework to improve solution efficiency. Using case studies taken from renewable resource and fossil-fuel based application in process systems engineering, it can be seen that these novel decomposition approaches have significant benefit over classical decomposition methods and state-of-the-art MILP/MINLP global optimization solvers.

Geometrical Methods in Multivariate Risk Management: Algorithms and Applications

This thesis builds a framework for evaluating downside risk from multivariate data via a special class of risk measures (RM). The peculiarity of the analysis lies in getting rid of strong data distributional assumptions and in orientation towards the most critical data in risk management: those with asymmetries and heavy tails. At the same time, under typical assumptions, such as the ellipticity of the data probability distribution, the conformity with classical methods is shown. The constructed class of RM is a multivariate generalization of the coherent distortion RM, which possess valuable properties for a risk manager. The design of the framework is twofold. The first part contains new computational geometry methods for the high-dimensional data. The developed algorithms demonstrate computability of geometrical concepts used for constructing the RM. These concepts bring visuality and simplify interpretation of the RM. The second part develops models for applying the framework to actual problems. The spectrum of applications varies from robust portfolio selection up to broader spheres, such as stochastic conic optimization with risk constraints or supervised machine learning.

Robotic Sensing and Manipulation of Deformable Linear Objects with Learning-based methods

Nowadays robotic applications are widespread and most of the manipulation tasks are efficiently solved. However, Deformable-Objects (DOs) still represent a huge limitation for robots. The main difficulty in DOs manipulation is dealing with the shape and dynamics uncertainties, which prevents the use of model-based approaches (since they are excessively computationally complex) and makes sensory data difficult to interpret. This thesis reports the research activities aimed to address some applications in robotic manipulation and sensing of Deformable-Linear-Objects (DLOs), with particular focus to electric wires. In all the works, a significant effort was made in the study of an effective strategy for analyzing sensory signals with various machine learning algorithms. In the former part of the document, the main focus concerns the wire terminals, i.e. detection, grasping, and insertion. First, a pipeline that integrates vision and tactile sensing is developed, then further improvements are proposed for each module. A novel procedure is proposed to gather and label massive amounts of training images for object detection with minimal human intervention. Together with this strategy, we extend a generic object detector based on Convolutional-Neural-Networks for orientation prediction. The insertion task is also extended by developing a closed-loop control capable to guide the insertion of a longer and curved segment of wire through a hole, where the contact forces are estimated by means of a Recurrent-Neural-Network. In the latter part of the thesis, the interest shifts to the DLO shape. Robotic reshaping of a DLO is addressed by means of a sequence of pick-and-place primitives, while a decision making process driven by visual data learns the optimal grasping locations exploiting Deep Q-learning and finds the best releasing point. The success of the solution leverages on a reliable interpretation of the DLO shape. For this reason, further developments are made on the visual segmentation.

Computational methods applied to undeciphered scripts from the Aegean and Cyprus: Linear A and Cypro-Minoan

The study of ancient, undeciphered scripts presents unique challenges, that depend both on the nature of the problem and on the peculiarities of each writing system. In this thesis, I present two computational approaches that are tailored to two different tasks and writing systems. The first of these methods is aimed at the decipherment of the Linear A afraction signs, in order to discover their numerical values. This is achieved with a combination of constraint programming, ad-hoc metrics and paleographic considerations. The second main contribution of this thesis regards the creation of an unsupervised deep learning model which uses drawings of signs from ancient writing system to learn to distinguish different graphemes in the vector space. This system, which is based on techniques used in the field of computer vision, is adapted to the study of ancient writing systems by incorporating information about sequences in the model, mirroring what is often done in natural language processing. In order to develop this model, the Cypriot Greek Syllabary is used as a target, since this is a deciphered writing system. Finally, this unsupervised model is adapted to the undeciphered Cypro-Minoan and it is used to answer open questions about this script. In particular, by reconstructing multiple allographs that are not agreed upon by paleographers, it supports the idea that Cypro-Minoan is a single script and not a collection of three script like it was proposed in the literature. These results on two different tasks shows that computational methods can be applied to undeciphered scripts, despite the relatively low amount of available data, paving the way for further advancement in paleography using these methods.

Classification Of Frankfurters By Ft-raman Spectroscopy And Chemometric Methods.

Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews's correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%-100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.

Mechanical And Photoelastic Analysis Of Four Different Fixation Methods For Mandibular Body Fractures.

The aim of the present study was to compare four methods of fixation in mandibular body fractures. Mechanical and photoelastic tests were performed using polyurethane and photoelastic resin mandibles, respectively. The study groups contained the following: (I), two miniplates of 2.0 mm; (II) one 2.0 mm plate and an Erich arch bar; (III) one 2.4 mm plate and an Erich arch bar, and (IV) one 2.0 mm plate and one 2.4 mm plate. The differences between the mean values were analyzed using Tukey's test, the Mann-Whitney test and the Bonferroni correction. Group II recorded the lowest resistance, followed by groups I, IV and III. The photoelastic test confirmed the increase of tension in group II. The 2.4 mm system board in linear mandibular body fractures provided more resistance and the use of only one 2.0 mm plate in the central area of the mandible created higher tension.

Estatística aplicada à química: dez dúvidas comuns

Ten common doubts of chemistry students and professionals about their statistical applications are discussed. The use of the N-1 denominator instead of N is described for the standard deviation. The statistical meaning of the denominators of the root mean square error of calibration (RMSEC) and root mean square error of validation (RMSEV) are given for researchers using multivariate calibration methods. The reason why scientists and engineers use the average instead of the median is explained. Several problematic aspects about regression and correlation are treated. The popular use of triplicate experiments in teaching and research laboratories is seen to have its origin in statistical confidence intervals. Nonparametric statistics and bootstrapping methods round out the discussion.

Influência da idade no comportamento da frequência cardíaca na transição repouso-exercício: uma análise por deltas e regressão linear

BACKGROUND: Changes in heart rate during rest-exercise transition can be characterized by the application of mathematical calculations, such as deltas 0-10 and 0-30 seconds to infer on the parasympathetic nervous system and linear regression and delta applied to data range from 60 to 240 seconds to infer on the sympathetic nervous system. The objective of this study was to test the hypothesis that young and middle-aged subjects have different heart rate responses in exercise of moderate and intense intensity, with different mathematical calculations. METHODS: Seven middle-aged men and ten young men apparently healthy were subject to constant load tests (intense and moderate) in cycle ergometer. The heart rate data were submitted to analysis of deltas (0-10, 0-30 and 60-240 seconds) and simple linear regression (60-240 seconds). The parameters obtained from simple linear regression analysis were: intercept and slope angle. We used the Shapiro-Wilk test to check the distribution of data and the t test for unpaired comparisons between groups. The level of statistical significance was 5%. RESULTS: The value of the intercept and delta 0-10 seconds was lower in middle age in two loads tested and the inclination angle was lower in moderate exercise in middle age. CONCLUSION: The young subjects present greater magnitude of vagal withdrawal in the initial stage of the HR response during constant load exercise and higher speed of adjustment of sympathetic response in moderate exercise.

The relationship between cortisol concentrations in pregnancy and systemic vascular resistance in childhood

Objective. To assess the relationship between cortisol concentrations in the last trimester of pregnancy and systemic vascular resistance — SVR in childhood. Materials and methods. This study is part of a cohort involving 130 Brazilian pregnant women and their children, ages 5 to 7 years. Maternal cortisol was determined in saliva by an enzyme immunoassay utilizing the mean concentration of 9 samples of saliva (3 in each different day), collected at the same time, early in the morning. SVR was assessed by the HDI/PulseWave CR-2000 Cardiovascular Profiling System®. Socioeconomic and demographic characteristics and life style factors were determined by a questionnaire. The nutritional status of the women and children was assessed by the body mass index — BMI. The association between maternal cortisol and SVR in childhood was calculated by multivariate linear regression analysis. Results.There were statistically significant associations between maternal cortisol and SVR (p = 0.043) and BMI-z score of the children (p = 0.027), controlling for maternal BMI, birth weight, age, and gender of the children. Conclusion. As far as we know this is the first study in the literature assessing the association between cortisol concentrations in pregnancy and SVR in childhood. Overall, the data suggest that exposure to excess glucocorticoid in the prenatal period is associated to vascular complications in childhood, predisposing to cardiovascular diseases in later life

Fatores associados ao consumo de frutas, legumes e verduras em adultos da cidade de São Paulo

OBJETIVO: Descrever a freqüência de consumo de frutas, legumes e verduras por adultos e analisar os fatores associados ao seu consumo. MÉTODOS: Estudo transversal realizado entre outubro e dezembro de 2003 no município de São Paulo (SP). Foram realizadas entrevistas telefônicas em amostra probabilística da população adulta (>18 anos) residente em domicílios servidos por linhas fixas de telefone, totalizando 1.267 mulheres e 855 homens. A freqüência do consumo de frutas, legumes e verduras foi medida por meio de um roteiro com perguntas curtas e simples. Na avaliação dos fatores associados ao consumo, realizou-se análise de regressão linear multivariada e hierarquizada, com variáveis sociodemográficas no primeiro nível hierárquico, comportamentais no segundo e relacionadas ao padrão alimentar no terceiro nível. RESULTADOS: A freqüência de consumo de frutas, legumes e verduras foi maior entre as mulheres. Para ambos os sexos, verificou-se que a freqüência desse consumo aumentava de acordo com a idade e a escolaridade do indivíduo. Entre mulheres que relataram ter realizado dieta no ano anterior houve maior consumo de frutas, legumes e verduras. O consumo de alimentos que indicam um padrão de consumo não saudável como açúcares e gorduras se mostrou inversamente associado ao consumo de frutas, legumes e verduras em ambos os sexos. CONCLUSÕES: O consumo de frutas, legumes e verduras da população adulta residente em São Paulo foi maior entre as mulheres, sendo influenciado pela idade, escolaridade e dieta

Opportunity for catch-up HPV vaccination in young women after first delivery

Background Early age at first delivery has been identified as a risk factor for high-risk HPV-type infection and cervical cancer development. Methods A cross-sectional study was carried out in a large public maternity hospital in Sao Paulo, Brazil. During June 2006 to February 2007, 301 women aged 15-24 years who gave birth to their first child were recruited between 43 and 60 days after delivery. Detection of HPV DNA in cervical specimens was performed using a standardised PCR protocol with PGMY09/11 primers. The association of selected factors with HPV infection was assessed by using a Generalised Linear Model. Results HPV DNA was detected in 58.5% (95% CI 52.7% to 64.0%) of the enrolled young women. The most common types of HPV found were: HPV16, HPV51, HPV52, HPV58 and HPV71. The overall prevalence of HPV types targeted by the HPV prophylactic vaccines was: HPV 16-12.0%, HPV 18-2.3% and HPV 6 and 11 4.3%. In the multivariate analysis, only age (inversely, p for trend=0.02) and smoking habits were independently associated with HPV infection. Conclusions The findings show that these young primiparous women had high cervical HPV prevalence, suggesting that this is a high-risk group for cervical cancer development. Nevertheless, 17.3% were positive for any of the four HPV types included in HPV vaccines (HPV6, 11, 16 or 18), with 13.3% positive for HPV 16 or 18 and only 1.0% having both vaccine related-oncogenic HPV types. Thus, young primiparous women could benefit from catch-up HPV vaccination programmes.

Comparison of univariate and multivariate calibration for the determination of micronutrients in pellets of plant materials by laser induced breakdown spectrometry

The application of laser induced breakdown spectrometry (LIBS) aiming the direct analysis of plant materials is a great challenge that still needs efforts for its development and validation. In this way, a series of experimental approaches has been carried out in order to show that LIBS can be used as an alternative method to wet acid digestions based methods for analysis of agricultural and environmental samples. The large amount of information provided by LIBS spectra for these complex samples increases the difficulties for selecting the most appropriated wavelengths for each analyte. Some applications have suggested that improvements in both accuracy and precision can be achieved by the application of multivariate calibration in LIBS data when compared to the univariate regression developed with line emission intensities. In the present work, the performance of univariate and multivariate calibration, based on partial least squares regression (PLSR), was compared for analysis of pellets of plant materials made from an appropriate mixture of cryogenically ground samples with cellulose as the binding agent. The development of a specific PLSR model for each analyte and the selection of spectral regions containing only lines of the analyte of interest were the best conditions for the analysis. In this particular application, these models showed a similar performance. but PLSR seemed to be more robust due to a lower occurrence of outliers in comparison to the univariate method. Data suggests that efforts dealing with sample presentation and fitness of standards for LIBS analysis must be done in order to fulfill the boundary conditions for matrix independent development and validation. (C) 2009 Elsevier B.V. All rights reserved.

Total carbon measurement in whole tropical soil sample

Soils are an important component in the biogeochemical cycle of carbon, storing about four times more carbon than biomass plants and nearly three times more than the atmosphere. Moreover, the carbon content is directly related on the capacity of water retention, fertility. among other properties. Thus, soil carbon quantification in field conditions is an important challenge related to carbon cycle and global climatic changes. Nowadays. Laser Induced Breakdown Spectroscopy (LIBS) can be used for qualitative elemental analyses without previous treatment of samples and the results are obtained quickly. New optical technologies made possible the portable LIBS systems and now, the great expectation is the development of methods that make possible quantitative measurements with LIBS. The goal of this work is to calibrate a portable LIBS system to carry out quantitative measures of carbon in whole tropical soil sample. For this, six samples from the Brazilian Cerrado region (Argisoil) were used. Tropical soils have large amounts of iron in their compositions, so the carbon line at 247.86 nm presents strong interference of this element (iron lines at 247.86 and 247.95). For this reason, in this work the carbon line at 193.03 nm was used. Using methods of statistical analysis as a simple linear regression, multivariate linear regression and cross-validation were possible to obtain correlation coefficients higher than 0.91. These results show the great potential of using portable LIBS systems for quantitative carbon measurements in tropical soils. (C) 2008 Elsevier B.V. All rights reserved.

Prevalence, magnitude, and methods of rapid weight loss among judo competitors

ARTIOLI, G. G., B. GUALANO, E. FRANCHINI, F. B. SCAGLIUSI, M. TAKESIAN, M. FUCHS, and A. H. LANCHA. Prevalence, Magnitude, and Methods of Rapid Weight Loss among Judo Competitors. Med. Sci. Sports Exerc., Vol. 42, No. 3, pp. 436-442, 2010. Purpose: To identify the prevalence, magnitude, and methods of rapid weight loss among judo competitors. Methods: Athletes (607 males and 215 females; age = 19.3 +/- 5.3 yr, weight = 70 +/- 7.5 kg, height = 170.6 +/- 9.8 cm) completed a previously validated questionnaire developed to evaluate rapid weight loss in judo athletes, which provides a score. The higher the score obtained, the more aggressive the weight loss behaviors. Data were analyzed using descriptive statistics and frequency analyses. Mean scores obtained in the questionnaire were used to compare specific groups of athletes using, when appropriate, Mann-Whitney U-test or general linear model one-way ANOVA followed by Tamhane post hoc test. Results: Eighty-six percent of athletes reported that have already lost weight to compete. When heavyweights are excluded, this percentage rises to 89%. Most athletes reported reductions of up to 5% of body weight (mean +/- SD: 2.5 +/- 2.3%). The most weight ever lost was 2%-5%, whereas a great part of athletes reported reductions of 5%-10% (mean +/- SD: 6 +/- 4%). The number of reductions underwent in a season was 3 +/- 5. The reductions usually occurred within 7 +/- 7 d. Athletes began cutting weight at 12.6 +/- 6.1 yr. No significant differences were found in the score obtained by male versus female athletes as well as by athletes from different weight classes. Elite athletes scored significantly higher in the questionnaire than nonelite. Athletes who began cutting weight earlier also scored higher than those who began later. Conclusions: Rapid weight loss is highly prevalent in judo competitors. The level of aggressiveness in weight management behaviors seems to not be influenced by the gender or by the weight class, but it seems to be influenced by competitive level and by the age at which athletes began cutting weight.

Estimation of hexenuronic acids and kappa number in kraft pulps of Eucalyptus globulus by Fourier transform near infrared spectroscopy and multivariate analysis

Fourier transform near infrared (FT-NIR) spectroscopy was evaluated as an analytical too[ for monitoring residual Lignin, kappa number and hexenuronic acids (HexA) content in kraft pulps of Eucalyptus globulus. Sets of pulp samples were prepared under different cooking conditions to obtain a wide range of compound concentrations that were characterised by conventional wet chemistry analytical methods. The sample group was also analysed using FT-NIR spectroscopy in order to establish prediction models for the pulp characteristics. Several models were applied to correlate chemical composition in samples with the NIR spectral data by means of PCR or PLS algorithms. Calibration curves were built by using all the spectral data or selected regions. Best calibration models for the quantification of lignin, kappa and HexA were proposed presenting R-2 values of 0.99. Calibration models were used to predict pulp titers of 20 external samples in a validation set. The lignin concentration and kappa number in the range of 1.4-18% and 8-62, respectively, were predicted fairly accurately (standard error of prediction, SEP 1.1% for lignin and 2.9 for kappa). The HexA concentration (range of 5-71 mmol kg(-1) pulp) was more difficult to predict and the SEP was 7.0 mmol kg(-1) pulp in a model of HexA quantified by an ultraviolet (UV) technique and 6.1 mmol kg(-1) pulp in a model of HexA quantified by anion-exchange chromatography (AEC). Even in wet chemical procedures used for HexA determination, there is no good agreement between methods as demonstrated by the UV and AEC methods described in the present work. NIR spectroscopy did provide a rapid estimate of HexA content in kraft pulps prepared in routine cooking experiments.