Food Competition in a Semi-Free-Ranging Cebus apella Group

The competitive regime faced by individuals is fundamental to modelling the evolution of social organization. In this paper, we assess the relative importance of contest and scramble food competition on the social dynamics of a provisioned semi-free-ranging Cebus apella group (n=18). Individuals competed directly for provisioned and clumped foods. Effects of indirect competition were apparent with individuals foraging in different areas and with increased group dispersion during periods of low food abundance. We suggest that both forms of competition can act simultaneously and to some extent synergistically in their influence on social dynamics; the combination of social and ecological opportunities for competition and how those opportunities are exploited both influence the nature of the relationships within social groups of primates and underlie the evolved social structure. Copyright (c) 2008 S. Karger AG, Basel

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.

CONTEXT TREE SELECTION AND LINGUISTIC RHYTHM RETRIEVAL FROM WRITTEN TEXTS

The starting point of this article is the question "How to retrieve fingerprints of rhythm in written texts?" We address this problem in the case of Brazilian and European Portuguese. These two dialects of Modern Portuguese share the same lexicon and most of the sentences they produce are superficially identical. Yet they are conjectured, on linguistic grounds, to implement different rhythms. We show that this linguistic question can be formulated as a problem of model selection in the class of variable length Markov chains. To carry on this approach, we compare texts from European and Brazilian Portuguese. These texts are previously encoded according to some basic rhythmic features of the sentences which can be automatically retrieved. This is an entirely new approach from the linguistic point of view. Our statistical contribution is the introduction of the smallest maximizer criterion which is a constant free procedure for model selection. As a by-product, this provides a solution for the problem of optimal choice of the penalty constant when using the BIC to select a variable length Markov chain. Besides proving the consistency of the smallest maximizer criterion when the sample size diverges, we also make a simulation study comparing our approach with both the standard BIC selection and the Peres-Shields order estimation. Applied to the linguistic sample constituted for our case study, the smallest maximizer criterion assigns different context-tree models to the two dialects of Portuguese. The features of the selected models are compatible with current conjectures discussed in the linguistic literature.

A survey of evolutionary algorithms for decision-tree induction

This paper presents a survey of evolutionary algorithms that are designed for decision-tree induction. In this context, most of the paper focuses on approaches that evolve decision trees as an alternate heuristics to the traditional top-down divide-and-conquer approach. Additionally, we present some alternative methods that make use of evolutionary algorithms to improve particular components of decision-tree classifiers. The paper's original contributions are the following. First, it provides an up-to-date overview that is fully focused on evolutionary algorithms and decision trees and does not concentrate on any specific evolutionary approach. Second, it provides a taxonomy, which addresses works that evolve decision trees and works that design decision-tree components by the use of evolutionary algorithms. Finally, a number of references are provided that describe applications of evolutionary algorithms for decision-tree induction in different domains. At the end of this paper, we address some important issues and open questions that can be the subject of future research.

A marker-and-cell approach to free surface 2-D multiphase flows

This work describes a methodology to simulate free surface incompressible multiphase flows. This novel methodology allows the simulation of multiphase flows with an arbitrary number of phases, each of them having different densities and viscosities. Surface and interfacial tension effects are also included. The numerical technique is based on the GENSMAC front-tracking method. The velocity field is computed using a finite-difference discretization of a modification of the NavierStokes equations. These equations together with the continuity equation are solved for the two-dimensional multiphase flows, with different densities and viscosities in the different phases. The governing equations are solved on a regular Eulerian grid, and a Lagrangian mesh is employed to track free surfaces and interfaces. The method is validated by comparing numerical with analytic results for a number of simple problems; it was also employed to simulate complex problems for which no analytic solutions are available. The method presented in this paper has been shown to be robust and computationally efficient. Copyright (c) 2012 John Wiley & Sons, Ltd.

A novel XML document structure comparison framework based-on sub-tree commonalities and label semantics

XML similarity evaluation has become a central issue in the database and information communities, its applications ranging over document clustering, version control, data integration and ranked retrieval. Various algorithms for comparing hierarchically structured data, XML documents in particular, have been proposed in the literature. Most of them make use of techniques for finding the edit distance between tree structures, XML documents being commonly modeled as Ordered Labeled Trees. Yet, a thorough investigation of current approaches led us to identify several similarity aspects, i.e., sub-tree related structural and semantic similarities, which are not sufficiently addressed while comparing XML documents. In this paper, we provide an integrated and fine-grained comparison framework to deal with both structural and semantic similarities in XML documents (detecting the occurrences and repetitions of structurally and semantically similar sub-trees), and to allow the end-user to adjust the comparison process according to her requirements. Our framework consists of four main modules for (i) discovering the structural commonalities between sub-trees, (ii) identifying sub-tree semantic resemblances, (iii) computing tree-based edit operations costs, and (iv) computing tree edit distance. Experimental results demonstrate higher comparison accuracy with respect to alternative methods, while timing experiments reflect the impact of semantic similarity on overall system performance.

Production of a xylose-stimulated beta-glucosidase and a cellulase-free thermostable xylanase by the thermophilic fungus Humicola brevis var. thermoidea under solid state fermentation

Humicola brevis var. thermoidea cultivated under solid state fermentation in wheat bran and water (1:2 w/v) was a good producer of beta-glucosidase and xylanase. After optimization using response surface methodology the level of xylanase reached 5,791.2 +/- A 411.2 U g(-1), while beta-glucosidase production was increased about 2.6-fold, reaching 20.7 +/- A 1.5 U g(-1). Cellulase levels were negligible. Biochemical characterization of H. brevis beta-glucosidase and xylanase activities showed that they were stable in a wide pH range. Optimum pH for beta-glucosidase and xylanase activities were 5.0 and 5.5, respectively, but the xylanase showed 80 % of maximal activity when assayed at pH 8.0. Both enzymes presented high thermal stability. The beta-glucosidase maintained about 95 % of its activity after 26 h in water at 55 A degrees C, with half-lives of 15.7 h at 60 A degrees C and 5.1 h at 65 A degrees C. The presence of xylose during heat treatment at 65 A degrees C protected beta-glucosidase against thermal inactivation. Xylanase maintained about 80 % of its activity after 200 h in water at 60 A degrees C. Xylose stimulated beta-glucosidase activity up to 1.7-fold, at 200 mmol L-1. The notable features of both xylanase and beta-glucosidase suggest that H. brevis crude culture extract may be useful to compose efficient enzymatic cocktails for lignocellulosic materials treatment or paper pulp biobleaching.

An electrochemical gas sensor based on paper supported room temperature ionic liquids

A sensitive and fast-responding membrane-free amperometric gas sensor is described, consisting of a small filter paper foil soaked with a room temperature ionic liquid (RTIL), upon which three electrodes are screen printed with carbon ink, using a suitable mask. It takes advantage of the high electrical conductivity and negligible vapour pressure of RTILs as well as their easy immobilization into a porous and inexpensive supporting material such as paper. Moreover, thanks to a careful control of the preparation procedure, a very close contact between the RTIL and electrode material can be achieved so as to allow gaseous analytes to undergo charge transfer just as soon as they reach the three-phase sites where the electrode material, paper supported RTIL and gas phase meet. Thus, the adverse effect on recorded currents of slow steps such as analyte diffusion and dissolution in a solvent is avoided. To evaluate the performance of this device, it was used as a wall-jet amperometric detector for flow injection analysis of 1-butanethiol vapours, adopted as the model gaseous analyte, present in headspace samples in equilibrium with aqueous solutions at controlled concentrations. With this purpose, the RTIL soaked paper electrochemical detector (RTIL-PED) was assembled by using 1-butyl-3-methylimidazolium bis(trifluoromethanesulfonyl) imide as the wicking RTIL and printing the working electrode with carbon ink doped with cobalt(II) phthalocyanine, to profit from its ability to electrocatalyze thiol oxidation. The results obtained were quite satisfactory (detection limit: 0.5 mu M; dynamic range: 2-200 mu M, both referring to solution concentrations; correlation coefficient: 0.998; repeatability: +/- 7% RSD; long-term stability: 9%), thus suggesting the possible use of this device for manifold applications.

Determination of the critical coupling of explosive synchronization transitions in scale-free networks by mean-field approximations

An explosive synchronization can be observed in scale-free networks when Kuramoto oscillators have natural frequencies equal to their number of connections. The present paper reports on mean-field approximations to determine the critical coupling of such explosive synchronization. It has been verified that the equation obtained for the critical coupling has an inverse dependence on the network average degree. This expression differs from those whose frequency distributions are unimodal and even. In this case, the critical coupling depends on the ratio between the first and second statistical moments of the degree distribution. Numerical simulations were also conducted to verify our analytical results.