Detecting an abnormality in a recovery boiler using dynamic multivariate data analysis with parallel coordinate plots

Data visualization techniques are powerful in the handling and analysis of multivariate systems. One such technique known as parallel coordinates was used to support the diagnosis of an event, detected by a neural network-based monitoring system, in a boiler at a Brazilian Kraft pulp mill. Its attractiveness is the possibility of the visualization of several variables simultaneously. The diagnostic procedure was carried out step-by-step going through exploratory, explanatory, confirmatory, and communicative goals. This tool allowed the visualization of the boiler dynamics in an easier way, compared to commonly used univariate trend plots. In addition it facilitated analysis of other aspects, namely relationships among process variables, distinct modes of operation and discrepant data. The whole analysis revealed firstly that the period involving the detected event was associated with a transition between two distinct normal modes of operation, and secondly the presence of unusual changes in process variables at this time.

A Chaotic Approach of Differential Evolution Optimization Applied to Loudspeaker Design Problem

Over the past few years, the field of global optimization has been very active, producing different kinds of deterministic and stochastic algorithms for optimization in the continuous domain. These days, the use of evolutionary algorithms (EAs) to solve optimization problems is a common practice due to their competitive performance on complex search spaces. EAs are well known for their ability to deal with nonlinear and complex optimization problems. Differential evolution (DE) algorithms are a family of evolutionary optimization techniques that use a rather greedy and less stochastic approach to problem solving, when compared to classical evolutionary algorithms. The main idea is to construct, at each generation, for each element of the population a mutant vector, which is constructed through a specific mutation operation based on adding differences between randomly selected elements of the population to another element. Due to its simple implementation, minimum mathematical processing and good optimization capability, DE has attracted attention. This paper proposes a new approach to solve electromagnetic design problems that combines the DE algorithm with a generator of chaos sequences. This approach is tested on the design of a loudspeaker model with 17 degrees of freedom, for showing its applicability to electromagnetic problems. The results show that the DE algorithm with chaotic sequences presents better, or at least similar, results when compared to the standard DE algorithm and other evolutionary algorithms available in the literature.

Low dynamic muscle strength and its associations with fatigue, functional performance, and quality of life in premenopausal patients with systemic lupus erythematosus and low disease activity: a case–control study

Abstract Background The purpose of the present study was to compare dynamic muscle strength, functional performance, fatigue, and quality of life in premenopausal systemic lupus erythematosus (SLE) patients with low disease activity versus matched-healthy controls and to determine the association of dynamic muscle strength with fatigue, functional performance, and quality of life in SLE patients. Methods We evaluated premenopausal (18–45 years) SLE patients with low disease activity (Systemic lupus erythematosus disease activity index [SLEDAI]: mean 1.5 ± 1.2). The control (n = 25) and patient (n = 25) groups were matched by age, physical characteristics, and the level of physical activities in daily life (International Physical Activity Questionnaire IPAQ). Both groups had not participated in regular exercise programs for at least six months prior to the study. Dynamic muscle strength was assessed by one-repetition maximum (1-RM) tests. Functional performance was assessed by the Timed Up and Go (TUG), in 30-s test a chair stand and arm curl using a 2-kg dumbbell and balance test, handgrip strength and a sit-and-reach flexibility test. Quality of life (SF-36) and fatigue were also measured. Results The SLE patients showed significantly lower dynamic muscle strength in all exercises (leg press 25.63%, leg extension 11.19%, leg curl 15.71%, chest press 18.33%, lat pulldown 13.56%, 1-RM total load 18.12%, P < 0.001-0.02) compared to the controls. The SLE patients also had lower functional performance, greater fatigue and poorer quality of life. In addition, fatigue, SF-36 and functional performance accounted for 52% of the variance in dynamic muscle strength in the SLE patients. Conclusions Premenopausal SLE patients with low disease activity showed lower dynamic muscle strength, along with increased fatigue, reduced functional performance, and poorer quality of life when compared to matched controls.

DETERMINATION OF THE E/G RATIO OF WOOD LOGS USING TRANSVERSE VIBRATION

The Bernoulli's model for vibration of beams is often used to make predictions of bending modulus of elasticity when using dynamic tests. However this model ignores the rotary inertia and shear. Such effects can be added to the solution of Bernoulli's equation by means of the correction proposed by Goens (1931) or by Timoshenko (1953). But to apply these corrections it is necessary to know the E/G ratio of the material. The objective of this paper is the determination of the E/G ratio of wood logs by adjusting the analytical solution of the Timoshenko beam model to the dynamic testing data of 20 Eucalyptus citriodora logs. The dynamic testing was performed with the logs in free-free suspension. To find the stiffness properties of the logs, the residue minimization was carried out using the Genetic Algorithm (GA). From the result analysis one can reasonably assume E/G = 20 for wood logs.

Use of recent geoid models to estimate mean dynamic topography and geostrophic currents in South Atlantic and Brazil Malvinas confluence

The use of geoid models to estimate the Mean Dynamic Topography was stimulated with the launching of the GRACE satellite system, since its models present unprecedented precision and space-time resolution. In the present study, besides the DNSC08 mean sea level model, the following geoid models were used with the objective of computing the MDTs: EGM96, EIGEN-5C and EGM2008. In the method adopted, geostrophic currents for the South Atlantic were computed based on the MDTs. In this study it was found that the degree and order of the geoid models affect the determination of TDM and currents directly. The presence of noise in the MDT requires the use of efficient filtering techniques, such as the filter based on Singular Spectrum Analysis, which presents significant advantages in relation to conventional filters. Geostrophic currents resulting from geoid models were compared with the HYCOM hydrodynamic numerical model. In conclusion, results show that MDTs and respective geostrophic currents calculated with EIGEN-5C and EGM2008 models are similar to the results of the numerical model, especially regarding the main large scale features such as boundary currents and the retroflection at the Brazil-Malvinas Confluence.

Planetary transit candidates in the CoRoT LRa01 field

Context. CoRoT is a pioneering space mission whose primary goals are stellar seismology and extrasolar planets search. Its surveys of large stellar fields generate numerous planetary candidates whose lightcurves have transit-like features. An extensive analytical and observational follow-up effort is undertaken to classify these candidates. Aims. We present the list of planetary transit candidates from the CoRoT LRa01 star field in the Monoceros constellation toward the Galactic anti-center direction. The CoRoT observations of LRa01 lasted from 24 October 2007 to 3 March 2008. Methods. We acquired and analyzed 7470 chromatic and 3938 monochromatic lightcurves. Instrumental noise and stellar variability were treated with several filtering tools by different teams from the CoRoT community. Different transit search algorithms were applied to the lightcurves. Results. Fifty-one stars were classified as planetary transit candidates in LRa01. Thirty-seven (i.e., 73% of all candidates) are "good" planetary candidates based on photometric analysis only. Thirty-two (i.e., 87% of the "good" candidates) have been followed-up. At the time of writing twenty-two cases were solved and five planets were discovered: three transiting hot-Jupiters (CoRoT-5b, CoRoT-12b, and CoRoT-21b), the first terrestrial transiting planet (CoRoT-7b), and another planet in the same system (CoRoT-7c, detected by radial velocity survey only). Evidence of another non-transiting planet in the CoRoT-7 system, namely CoRoT-7d, was recently found as well.

MR-Radix: a multi-relational data mining algorithm

Abstract Background Once multi-relational approach has emerged as an alternative for analyzing structured data such as relational databases, since they allow applying data mining in multiple tables directly, thus avoiding expensive joining operations and semantic losses, this work proposes an algorithm with multi-relational approach. Methods Aiming to compare traditional approach performance and multi-relational for mining association rules, this paper discusses an empirical study between PatriciaMine - an traditional algorithm - and its corresponding multi-relational proposed, MR-Radix. Results This work showed advantages of the multi-relational approach in performance over several tables, which avoids the high cost for joining operations from multiple tables and semantic losses. The performance provided by the algorithm MR-Radix shows faster than PatriciaMine, despite handling complex multi-relational patterns. The utilized memory indicates a more conservative growth curve for MR-Radix than PatriciaMine, which shows the increase in demand of frequent items in MR-Radix does not result in a significant growth of utilized memory like in PatriciaMine. Conclusion The comparative study between PatriciaMine and MR-Radix confirmed efficacy of the multi-relational approach in data mining process both in terms of execution time and in relation to memory usage. Besides that, the multi-relational proposed algorithm, unlike other algorithms of this approach, is efficient for use in large relational databases.

Use of recent geoid models to estimate mean dynamic topography and geostrophic currents in South Atlantic and Brazil Malvinas confluence

The use of geoid models to estimate the Mean Dynamic Topography was stimulated with the launching of the GRACE satellite system, since its models present unprecedented precision and space-time resolution. In the present study, besides the DNSC08 mean sea level model, the following geoid models were used with the objective of computing the MDTs: EGM96, EIGEN-5C and EGM2008. In the method adopted, geostrophic currents for the South Atlantic were computed based on the MDTs. In this study it was found that the degree and order of the geoid models affect the determination of TDM and currents directly. The presence of noise in the MDT requires the use of efficient filtering techniques, such as the filter based on Singular Spectrum Analysis, which presents significant advantages in relation to conventional filters. Geostrophic currents resulting from geoid models were compared with the HYCOM hydrodynamic numerical model. In conclusion, results show that MDTs and respective geostrophic currents calculated with EIGEN-5C and EGM2008 models are similar to the results of the numerical model, especially regarding the main large scale features such as boundary currents and the retroflection at the Brazil-Malvinas Confluence.

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

Background: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

Thermal decomposition kinetics of Brazilian limestones: effect of CO2 partial pressure

The influence of the partial pressure of carbon dioxide (CO2) on the thermal decomposition process of a calcite (CI) and a dolomite (DP) is investigated in this paper using a thermogravimetric analyser. The tests were non-isothermal at five different heating rates in dynamic atmosphere of air with 0% and 15% carbon dioxide (CO2). In the atmosphere without CO2, the average activation energies (E-alpha) were 197.4 kJ mol(-1) and 188.1 kJ mol(-1) for CI and DP, respectively. For the DP with 15% CO2, two decomposition steps were observed, indicating a change of mechanism. The values of E-alpha for 15% CO2 were 378.7 kJ mol(-1) for the CI, and 299.8 kJ mol(-1) (first decomposition) and 453.4 kJ mol(-1) (second decomposition) for the DP, showing that the determination of E-alpha for DP should in this case be considered separately in those two distinct regions. The results obtained in this study are relevant to understanding the behaviour changes in the thermal decomposition of limestones with CO2 partial pressure when applied to technologies, such as carbon capture and storage (CCS), in which carbon dioxide is present in high concentrations.

Equilíbrio estático e dinâmico no indivíduo com espondilite anquilosante: revisão da literatura

Com o objetivo de analisar as alterações musculoesqueléticas dos indivíduos com espondilite anquilosante (EA) e suas repercussões sobre o controle postural, realizou-se uma revisão bibliográfica nas bases de dados da BIREME e EBSCO HOTS e no site Pubmed com as palavras-chave: "ankylosing spondylitis", "postural balance" e "posture". Foram selecionados artigos envolvendo seres humanos e que analisavam o controle postural e a biomecânica dos indivíduos com EA, nos idiomas inglês e português, publicados no período entre 1999 e 2010. Do total de artigos encontrados, apenas quatro preencheram os requisitos. Desses, três compararam os resultados de pacientes com EA com os dados obtidos de indivíduos saudáveis, e um analisou apenas indivíduos com EA. Nenhum artigo continha o mesmo método de análise postural. Para avaliação do equilíbrio foram utilizadas a Escala de Equilíbrio de Berg, a Plataforma de Força e a Magnometria. Os principais desvios posturais encontrados foram aumento da cifose torácica e flexão do quadril, que levam a uma anteriorização do centro de gravidade corporal, apresentando flexão do joelho e plantiflexão do tornozelo como compensação para manter o equilíbrio. Apenas um autor encontrou piora do equilíbrio funcional nos sujeitos com EA. Todos os métodos de avaliação utilizados foram considerados capazes de mensurar o equilíbrio, não havendo uma escala específica para pacientes com EA.

Psychometric properties of the Beck Depression Inventory-II: a comprehensive review

OBJECTIVE: To review the psychometric properties of the Beck Depression Inventory-II (BDI-II) as a self-report measure of depression in a variety of settings and populations. METHODS: Relevant studies of the BDI-II were retrieved through a search of electronic databases, a hand search, and contact with authors. Retained studies (k = 118) were allocated into three groups: non-clinical, psychiatric/institutionalized, and medical samples. RESULTS: The internal consistency was described as around 0.9 and the retest reliability ranged from 0.73 to 0.96. The correlation between BDI-II and the Beck Depression Inventory (BDI-I) was high and substantial overlap with measures of depression and anxiety was reported. The criterion-based validity showed good sensitivity and specificity for detecting depression in comparison to the adopted gold standard. However, the cutoff score to screen for depression varied according to the type of sample. Factor analysis showed a robust dimension of general depression composed by two constructs: cognitive-affective and somatic-vegetative. CONCLUSIONS: The BDI-II is a relevant psychometric instrument, showing high reliability, capacity to discriminate between depressed and non-depressed subjects, and improved concurrent, content, and structural validity. Based on available psychometric evidence, the BDI-II can be viewed as a cost-effective questionnaire for measuring the severity of depression, with broad applicability for research and clinical practice worldwide.

A system for classification of time-series data from industrial non-destructive device

This work proposes a system for classification of industrial steel pieces by means of magnetic nondestructive device. The proposed classification system presents two main stages, online system stage and off-line system stage. In online stage, the system classifies inputs and saves misclassification information in order to perform posterior analyses. In the off-line optimization stage, the topology of a Probabilistic Neural Network is optimized by a Feature Selection algorithm combined with the Probabilistic Neural Network to increase the classification rate. The proposed Feature Selection algorithm searches for the signal spectrogram by combining three basic elements: a Sequential Forward Selection algorithm, a Feature Cluster Grow algorithm with classification rate gradient analysis and a Sequential Backward Selection. Also, a trash-data recycling algorithm is proposed to obtain the optimal feedback samples selected from the misclassified ones.