Smart histogram analysis applied to the skull-stripping problem in T1-weighted MRI

In this paper we address the "skull-stripping" problem in 3D MR images. We propose a new method that employs an efficient and unique histogram analysis. A fundamental component of this analysis is an algorithm for partitioning a histogram based on the position of the maximum deviation from a Gaussian fit. In our experiments we use a comprehensive image database, including both synthetic and real MRI. and compare our method with other two well-known methods, namely BSE and BET. For all datasets we achieved superior results. Our method is also highly independent of parameter tuning and very robust across considerable variations of noise ratio.

The Compositional Aesthetic of Rodolfo Coelho de Souza in Paradise Station: an analysis

This article focuses on the compositional aesthetics of Rodolfo Coelho de Souza (1952-), a Brazilian fine art composer and active researcher, whose concerns surpasses the musical composition isolated from the social communication aspect. This is particularly evident in his piece Paradise Station, which, when analyzed, features the structural depth of its compositional process without disregarding the dialog with the listener and the Brazilian character, according to pitch, rhythm, texture, timbre and dynamics. The present analysis reveals a modular structure based on set classes, worked through a transformation network, which follows the David Lewin model.

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.

Automatic aspect discrimination in data clustering

The attributes describing a data set may often be arranged in meaningful subsets, each of which corresponds to a different aspect of the data. An unsupervised algorithm (SCAD) that simultaneously performs fuzzy clustering and aspects weighting was proposed in the literature. However, SCAD may fail and halt given certain conditions. To fix this problem, its steps are modified and then reordered to reduce the number of parameters required to be set by the user. In this paper we prove that each step of the resulting algorithm, named ASCAD, globally minimizes its cost-function with respect to the argument being optimized. The asymptotic analysis of ASCAD leads to a time complexity which is the same as that of fuzzy c-means. A hard version of the algorithm and a novel validity criterion that considers aspect weights in order to estimate the number of clusters are also described. The proposed method is assessed over several artificial and real data sets.

Combinatorial-topological framework for the analysis of global dynamics

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4767672]

Germline mutation analysis of Tpit in Poodle dogs with ACTH-dependent hyperadrenocorticism

There is a high incidence of pituitary-dependent hyperadrenocorticism (PDH) in Poodle dogs, with family members being affected by the disease, suggesting a genetic involvement. Tpit is an obligate transcription factor for the expression of pro-opiomelanocortingene and for corticotroph terminal differentiation. The aim of the present study was to screen the Tpit gene for germline mutations in Poodles with PDH. Fifty Poodle dogs (33 female, 8.71 +/- 2.8 years) with PDH and 50 healthy Poodle dogs (32 females, 9.4241 2.8 years) were studied. Genomic DNA was isolated from peripheral blood, amplified by PCR and submitted to automatic sequence. No mutation in the coding region of Tpit was found, whereas the new single nucleotide polymorphism p.S343G, in heterozygous state, was found in the same frequency in both PDH and control groups. We concluded that Tpit gain-of-function mutations are not involved in the etiology of PDH in Poodle dogs.

Development of a high sensitive automatic setup for screening of microcystins in surface waters by employing a LED-based photometric detector

In this manuscript, an automatic setup for screening of microcystins in surface waters by employing photometric detection is described. Microcystins are toxins delivered by cyanobacteria within an aquatic environment, which have been considered strongly poisonous for humans. For that reason, the World Health Organization (WHO) has proposed a provisional guideline value for drinking water of 1 mu g L-1. In this work, we developed an automated equipment setup, which allows the screening of water for concentration of microcystins below 0.1 mu g V. The photometric method was based on the enzyme-linked immunosorbent assay (ELISA) and the analytical signal was monitored at 458 nm using a homemade LED-based photometer. The proposed system was employed for the detection of microcystins in rivers and lakes waters. Accuracy was assessed by processing samples using a reference method and applying the paired t-test between results. No significant difference at the 95% confidence level was observed. Other useful features including a linear response ranging from 0.05 up to 2.00 mu g L-1 (R-2 =0.999) and a detection limit of 0.03 mu g L-1 microcystins were achieved. (C) 2011 Elsevier B.V. All rights reserved.

A quantitative approach to evolution of music and philosophy

The development of new statistical and computational methods is increasingly making it possible to bridge the gap between hard sciences and humanities. In this study, we propose an approach based on a quantitative evaluation of attributes of objects in fields of humanities, from which concepts such as dialectics and opposition are formally defined mathematically. As case studies, we analyzed the temporal evolution of classical music and philosophy by obtaining data for 8 features characterizing the corresponding fields for 7 well-known composers and philosophers, which were treated with multivariate statistics and pattern recognition methods. A bootstrap method was applied to avoid statistical bias caused by the small sample data set, with which hundreds of artificial composers and philosophers were generated, influenced by the 7 names originally chosen. Upon defining indices for opposition, skewness and counter-dialectics, we confirmed the intuitive analysis of historians in that classical music evolved according to a master apprentice tradition, while in philosophy changes were driven by opposition. Though these case studies were meant only to show the possibility of treating phenomena in humanities quantitatively, including a quantitative measure of concepts such as dialectics and opposition, the results are encouraging for further application of the approach presented here to many other areas, since it is entirely generic.

cDNA-AFLP analysis of Psidium guajava L. cultivars under water stress and mechanical injury: methodological implications

Studies involving amplified fragment length polymorphism (cDNA-AFLP) have often used polyacrylamide gels with radiolabeled primers in order to establish best primer combinations, to analyze, and to recover transcript-derived fragments. Use of automatic sequencer to establish best primer combinations is convenient, because it saves time, reduces costs and risks of contamination with radioactive material and acrylamide, and allows objective band-matching and more precise evaluation of transcript-derived fragments intensities. This study aimed at examining the gene expression of commercial cultivars of P. guajava subjected to water and mechanical injury stresses, combining analyses by automatic sequencer and fluorescent kits for polyacrylamide gel electrophoresis. Firstly, 64 combinations of EcoRI and MseI primers were tested. Ten combinations with higher number of polymorphic fragments were then selected for transcript-derived fragments recovering and cluster analysis, involving 45 saplings of P. guajava. Two groups were obtained, one composed by the control samplings, and another formed by samplings undergoing stress, with no clear distinction between stress treatments. The results revealed the convenience of using a combination of automatic sequencer and fluorescent kits for polyacrylamide gel electrophoreses to examine gene expression profiles. The Unweighted Pair Group Method with Arithmetic Mean analysis using Euclidean distances points out a similar induced response mechanism of P. guajava undergoing water stress and mechanical injury.