Efficient Forest Data Structure for Evolutionary Algorithms Applied to Network Design

The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.

Collaborative fuzzy clustering algorithms: some refinements and design guidelines

There are some variants of the widely used Fuzzy C-Means (FCM) algorithm that support clustering data distributed across different sites. Those methods have been studied under different names, like collaborative and parallel fuzzy clustering. In this study, we offer some augmentation of the two FCM-based clustering algorithms used to cluster distributed data by arriving at some constructive ways of determining essential parameters of the algorithms (including the number of clusters) and forming a set of systematically structured guidelines such as a selection of the specific algorithm depending on the nature of the data environment and the assumptions being made about the number of clusters. A thorough complexity analysis, including space, time, and communication aspects, is reported. A series of detailed numeric experiments is used to illustrate the main ideas discussed in the study.

Litterfall and leaf decomposition in forest fragments under different successional phases on the Atlantic Plateau of the state of Sao Paulo, Brazil

Litterfall and litter decomposition are vital processes in tropical forests because they regulate nutrient cycling. Nutrient cycling can be altered by forest fragmentation. The Atlantic Forest is one of the most threatened biomes in the world due to human occupation over the last 500 years. This scenario has resulted in fragments of different size, age and regeneration phase. To investigate differences in litterfall and leaf decomposition between forest successional phases, we compared six forest fragments at three different successional phases and an area of mature forest on the Atlantic Plateau of Sao Paulo, Brazil. We sampled litter monthly from November 2008 to October 2009. We used litterbags to calculate leaf decomposition rate of an exotic species, Tipuana tipu (Fabaceae), over the same period litter sampling was performed. Litterfall was higher in the earliest successional area. This pattern may be related to the structural properties of the forest fragments, especially the higher abundance of pioneer species, which have higher productivity and are typical of early successional areas. However, we have not found significant differences in the decomposition rates between the studied areas, which may be caused by rapid stabilization of the decomposition environment (combined effect of microclimatic conditions and the decomposers activities). This result indicates that the leaf decomposition process have already been restored to levels observed in mature forests after a few decades of regeneration, although litterfall has not been entirely restored. This study emphasizes the importance of secondary forests for restoration of ecosystem processes on a regional scale.

Characterization of depolymerized residues from extremely low acid hydrolysis (ELA) of sugarcane bagasse cellulose: Effects of degree of polymerization, crystallinity and crystallite size on thermal decomposition

Sugarcane bagasse cellulose was subjected to the extremely low acid (ELA) hydrolysis in 0.07% H2SO4 at 190, 210 and 225 degrees C for various times. The cellulose residues from this process were characterized by TGA, XRD, GPC, FIR and SEM. A kinetic study of thermal decomposition of the residues was also carried out, using the ASTM and Kissinger methods. The thermal studies revealed that residues of cellulose hydrolyzed at 190, 210 and 225 degrees C for 80,40 and 8 min have initial decomposition temperature and activation energy for the main decomposition step similar to those of Avicel PH-101. XRD studies confirmed this finding by showing that these cellulose residues are similar to Avicel in crystallinity index and crystallite size in relation to the 110 and 200 planes. FTIR spectra revealed no significant changes in the cellulose chemical structure and analysis of SEM micrographs demonstrated that the particle size of the cellulose residues hydrolyzed at 190 and 210 degrees C were similar to that of Avicel. (C) 2011 Elsevier B.V. All rights reserved.

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.

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.

The sigma-isotypic decomposition and the sigma-index of reversible-equivariant systems

This work is concerned with dynamical systems in presence of symmetries and reversing symmetries. We describe a construction process of subspaces that are invariant by linear Gamma-reversible-equivariant mappings, where Gamma is the compact Lie group of all the symmetries and reversing symmetries of such systems. These subspaces are the sigma-isotypic components, first introduced by Lamb and Roberts in (1999) [10] and that correspond to the isotypic components for purely equivariant systems. In addition, by representation theory methods derived from the topological structure of the group Gamma, two algebraic formulae are established for the computation of the sigma-index of a closed subgroup of Gamma. The results obtained here are to be applied to general reversible-equivariant systems, but are of particular interest for the more subtle of the two possible cases, namely the non-self-dual case. Some examples are presented. (C) 2011 Elsevier BM. All rights reserved.

LITTER DEVOLUTION AND DECOMPOSITION IN A PERIODICALLY FLOODED FOREST IN RESTINGA DA MARAMBAIA, RIO DE JANEIRO

Restinga (sandbank) areas are fragile environments, which have been subjected to anthropogenic pressures since the country colonization. So that mitigate actions can be taken, it must be developed studies to better understand the ecological processes in these environments. Thus, this study aims to quantify litter and nutrients devolution and litter decomposition in a periodically flooded forest in 'Restinga da Marambaia', Rio de Janeiro. In the study area 10 conic collectors and 30 litter bags were installed. The annual litter devolution was 7.64 Mg.ha(-1), and September was the highest contribution month. Nitrogen was the element returned to the soil to a higher amount (71.9 kg ha(-1) yr(-1)), followed by potassium (41.1 kg ha(-1) yr(-1)). Litter decomposition rate 0.0015 g g(-1) day(-1) and the half-life were 462 days. Potassium was the element that showed the highest losses in comparison to the others. Cellulose appeared as a major participant in the structure of leaf litter, followed by lignin, the latter being associated with the leathery texture of the leaves in this formation.

The contribution of HGAL/GCET2 in immunohistological algorithms: a comparative study in 424 cases of nodal diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma can be subclassified into at least two molecular subgroups by gene expression profiling: germinal center B-cell like and activated B-cell like diffuse large B-cell lymphoma. Several immunohistological algorithms have been proposed as surrogates to gene expression profiling at the level of protein expression, but their reliability has been an issue of controversy. Furthermore, the proportion of misclassified cases of germinal center B-cell subgroup by immunohistochemistry, in all reported algorithms, is higher compared with germinal center B-cell cases defined by gene expression profiling. We analyzed 424 cases of nodal diffuse large B-cell lymphoma with the panel of markers included in the three previously described algorithms: Hans, Choi, and Tally. To test whether the sensitivity of detecting germinal center B-cell cases could be improved, the germinal center B-cell marker HGAL/GCET2 was also added to all three algorithms. Our results show that the inclusion of HGAL/GCET2 significantly increased the detection of germinal center B-cell cases in all three algorithms (P<0.001). The proportions of germinal center B-cell cases in the original algorithms were 27%, 34%, and 19% for Hans, Choi, and Tally, respectively. In the modified algorithms, with the inclusion of HGAL/GCET2, the frequencies of germinal center B-cell cases were increased to 38%, 48%, and 35%, respectively. Therefore, HGAL/GCET2 protein expression may function as a marker for germinal center B-cell type diffuse large B-cell lymphoma. Consideration should be given to the inclusion of HGAL/GCET2 analysis in algorithms to better predict the cell of origin. These findings bear further validation, from comparison to gene expression profiles and from clinical/therapeutic data. Modern Pathology (2012) 25, 1439-1445; doi: 10.1038/modpathol.2012.119; published online 29 June 2012

Long-term decomposition of sugarcane harvest residues in Sao Paulo state, Brazil

Crop residues returned to the soil are important to preserve fertility and sustainability. This research addressed the long-term decomposition of sugarcane post-harvest residues (trash) under reduced tillage, therefore field renewal was performed with herbicide followed by subsoiling and ratoons were deprived of interrow scarification. The trial was conducted in the northern Sao Paulo State, Brazil during four consecutive crops (2005-2008) where litter bags containing N-15-labeled trash were disposed in the field attempting to simulate two distinct situations: the previous crop trash (PCT) or residues incorporated in the field after tillage, and post-harvest trash (PHT) or the remains of plant-cane harvest. Decomposition rates regarding dry matter (DM), carbon (C), root growth, plant nutrients (N, P, K, Ca, Mg and S), lignin (LIG) cellulose (CEL) and hemicellulose (HCEL) contents were assessed for PCT (2005 ndash;2008) and for PHT (2006-2008). There were significant reductions on DM and C:N ratio due to C losses and root growth within the litter bags over time. The DM from PCT and PHT decreased 96% and 73% after four and three crops, respectively, and the higher nutrients release were found for K, Ca and N. The LIG, CEL and HCEL concentrations in PCT decreased 60%, 29%, 70% after four crops and 47%, 35%, 70% from PHT after three crops, respectively. Trash decomposition was driven mainly by residues biochemical composition, root growth within the trash blanket and the climatic conditions during the crop cycles. (C) 2012 Elsevier Ltd. All rights reserved.

Revision of Singlet Quantum Yields in the Catalyzed Decomposition of Cyclic Peroxides

The chemiluminescence of cyclic peroxides activated by oxidizable fluorescent dyes is an example of chemically initiated electron exchange luminescence (CIEEL), which has been used also to explain the efficient bioluminescence of fireflies. Diphenoyl peroxide and dimethyl-1,2-dioxetanone were used as model compounds for the development of this CIEEL mechanism. However, the chemiexcitation efficiency of diphenoyl peroxide was found to be much lower than originally described. In this work, we redetermine the chemiexcitation quantum efficiency of dimethyl-1,2-dioxetanone, a more adequate model for firefly bioluminescence, and found a singlet quantum yield (Phi(s)) of 0.1%, a value at least 2 orders of magnitude lower than previously reported. Furthermore, we synthesized two other 1,2-dioxetanone derivatives and confirm the low chemiexcitation efficiency (Phi(s) < 0.1%) of the intermolecular CIEEL-activated decomposition of this class of cyclic. peroxides. These results are compared with other chemiluminescent reactions, supporting the general trend that intermolecular CIEEL systems are much less efficient in generating singlet excited states than analogous intramolecular processes (Phi(s) approximate to 50%), with the notable exception of the peroxyoxalate reaction (Phi(s) approximate to 60%).

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.

Kinetics of thermal decomposition of niobium hydride

High-purity niobium powders can be obtained from the well-known hydride-dehydride (HDH) process. The aim of this work was the investigation of the structural phase transition of the niobium hydride to niobium metal as function of temperature, heating rate and time. The niobium powder used in this work was obtained by high-temperature hydriding of niobium machining chips followed by conventional ball milling and sieving. X-ray diffraction measurements were carried out in vacuum using a high-temperature chamber coupled to an X-ray diffractometer. During the dehydriding process, it is possible to follow the phase transition from niobium hydride to niobium metal starting at about 380 degrees C for a heating rate of 20 degrees C/min. The heating rate was found to be an important parameter, since complete dehydriding was obtained at 490 degrees C for a heating rate of 20 degrees C/min. The higher dehydriding rate was found at 500 degrees C. Results contribute to a better understanding of the kinetics of thermal decomposition of niobium hydride to niobium metal. (C) 2011 Elsevier Ltd. All rights reserved.

A novel method for power quality multiple disturbance decomposition based on Independent Component Analysis

In this paper, a novel method for power quality signal decomposition is proposed based on Independent Component Analysis (ICA). This method aims to decompose the power system signal (voltage or current) into components that can provide more specific information about the different disturbances which are occurring simultaneously during a multiple disturbance situation. The ICA is originally a multichannel technique. However, the method proposes its use to blindly separate out disturbances existing in a single measured signal (single channel). Therefore, a preprocessing step for the ICA is proposed using a filter bank. The proposed method was applied to synthetic data, simulated data, as well as actual power system signals, showing a very good performance. A comparison with the decomposition provided by the Discrete Wavelet Transform shows that the proposed method presented better decoupling for the analyzed data. (C) 2012 Elsevier Ltd. All rights reserved.

Development of Plurimetallic Electrocatalysts Prepared by Decomposition of Polymeric Precursors for EtOH/O-2 Fuel Cell

This work aimed to develop plurimetallic electrocatalysts composed of Pt, Ru, Ni, and Sn supported on C by decomposition of polymeric precursors (DPP), at a constant metal: carbon ratio of 40:60 wt.%, for application in direct ethanol fuel cell (DEFC). The obtained nanoparticles were physico-chemically characterized by X-ray diffraction (XRD) and energy dispersive X-ray spectroscopy (EDX). XRD results revealed a face-centered cubic crystalline Pt with evidence that Ni, Ru, and Sn atoms were incorporated into the Pt structure. Electrochemical characterization of the nanoparticles was accomplished by cyclic voltammetry (CV) and chronoamperometry (CA) in slightly acidic medium (0.05 mol L-1 H2SO4), in the absence and presence of ethanol. Addition of Sn to PtRuNi/C catalysts significantly shifted the ethanol and CO onset potentials toward lower values, thus increasing the catalytic activity, especially for the quaternary composition Pt64Sn15Ru13Ni8/C. Electrolysis of ethanol solutions at 0.4 V vs. RHE allowed determination of acetaldehyde and acetic acid as the main reaction products. The presence of Ru in alloys promoted formation of acetic acid as the main product of ethanol oxidation. The Pt64Sn15Ru13Ni8/C catalyst displayed the best performance for DEFC.