Presence and distribution of the endosymbiont Wolbachia among Solenopsis spp. (Hymenoptera: Formicidae) from Brazil and its evolutionary history

Wolbachia are intracellular bacteria that commonly infect arthropods. Its prevalence among ants of the genus Solenopsis is high. In the present study, the presence and distribution of these endosymbionts was examined among populations of Solenopsis spp. from Brazil. A phylogenetic analysis based on the wsp gene was conducted to infer the evolutionary history of Wolbachia infections within the populations surveyed. A high frequency of Wolbachia bacteria was observed among the genus Solenopsis, 51% of the colonies examined were infected. Incidence was higher in populations from southern Brazil. However, little genetic variability was found among different Wolbachia strains within supergroups A and B. Our findings also suggest that horizontal transmission events can occur through the social parasite S. daguerrei. © 2012 Elsevier Inc..

Supply Chain Management practices in the electro-electronics sector in Brazil: Evolutionary approach, information technology adoption and management actions

This paper examines the current level of adoption of Supply Chain Management (SCM) practices in the electro-electronic sector in Brazil and aims to identify the management and Information Technology (IT) actions that have been implemented to support the adoption of those practices. An e-mail survey was conducted. Descriptive statistics techniques were employed for data analysis. This study makes contributions to the electro-electronics sector and to the topics related to SCM, such as identifi cation and level of adoption of SCM practices. Another contribution of this research is the investigation of whether approaches such as Enterprise Resources Planning (ERP), Workshop with Customers, Electronic Data Interchange (EDI), Workshop with Suppliers and electronic Kanban are commonly used to support SCM practices. So far, this is the fi rst research on SCM practices in the electro-electronics sector in Brazil. Copyright © 2012 Inderscience Enterprises Ltd.

Application of an iterative method and an evolutionary algorithm in fuzzy optimization

This work develops two approaches based on the fuzzy set theory to solve a class of fuzzy mathematical optimization problems with uncertainties in the objective function and in the set of constraints. The first approach is an adaptation of an iterative method that obtains cut levels and later maximizes the membership function of fuzzy decision making using the bound search method. The second one is a metaheuristic approach that adapts a standard genetic algorithm to use fuzzy numbers. Both approaches use a decision criterion called satisfaction level that reaches the best solution in the uncertain environment. Selected examples from the literature are presented to compare and to validate the efficiency of the methods addressed, emphasizing the fuzzy optimization problem in some import-export companies in the south of Spain. © 2012 Brazilian Operations Research Society.

Fast robot voice interface through optimum-path forest

Voice-based user interfaces have been actively pursued aiming to help individuals with motor impairments, providing natural interfaces to communicate with machines. In this work, we have introduced a recent machine learning technique named Optimum-Path Forest (OPF) for voice-based robot interface, which has been demonstrated to be similar to the state-of-the-art pattern recognition techniques, but much faster. Experiments were conducted against Support Vector Machines, Neural Networks and a Bayesian classifier to show the OPF robustness. The proposed architecture provides high accuracy rates allied with low computational times. © 2012 IEEE.

Fast fault diagnosis in power transformers using optimum-path forest

In this paper we propose a fast and an accurate method for fault diagnosis in power transformers by means of Optimum-Path Forest (OPF) classifier. Since we applied Dissolved Gas Analysis (DGA), the samples have been labeled by IEEE/IEC standard, which was further analyzed by OPF and several other well known supervised pattern recognition techniques. The experiments have showed that OPF can achieve high recognition rates with low computational cost. © 2012 IEEE.

Boosting optimum-path forest clustering through harmony Search and its applications for intrusion detection in computer networks

In this paper we propose a nature-inspired approach that can boost the Optimum-Path Forest (OPF) clustering algorithm by optimizing its parameters in a discrete lattice. The experiments in two public datasets have shown that the proposed algorithm can achieve similar parameters' values compared to the exhaustive search. Although, the proposed technique is faster than the traditional one, being interesting for intrusion detection in large scale traffic networks. © 2012 IEEE.

Productivity, technology and domestic efforts in research and development (the growth-path of a Rayon plant)

Includes bibliography

Automatic visual dictionary generation through Optimum-Path Forest clustering

Image categorization by means of bag of visual words has received increasing attention by the image processing and vision communities in the last years. In these approaches, each image is represented by invariant points of interest which are mapped to a Hilbert Space representing a visual dictionary which aims at comprising the most discriminative features in a set of images. Notwithstanding, the main problem of such approaches is to find a compact and representative dictionary. Finding such representative dictionary automatically with no user intervention is an even more difficult task. In this paper, we propose a method to automatically find such dictionary by employing a recent developed graph-based clustering algorithm called Optimum-Path Forest, which does not make any assumption about the visual dictionary's size and is more efficient and effective than the state-of-the-art techniques used for dictionary generation. © 2012 IEEE.

Automatic landslide recognition through Optimum-Path Forest

In this paper we shed light over the problem of landslide automatic recognition using supervised classification, and we also introduced the OPF classifier in this context. We employed two images acquired from Geoeye-MS satellite at March-2010 in the northwest (high steep areas) and north sides (pipeline area) covering the area of Duque de Caxias city, Rio de Janeiro State, Brazil. The landslide recognition rate has been assessed through a cross-validation with 10 runnings. In regard to the classifiers, we have used OPF against SVM with Radial Basis Function for kernel mapping and a Bayesian classifier. We can conclude that OPF, Bayes and SVM achieved high recognition rates, being OPF the fastest approach. © 2012 IEEE.

Intrusion detection in computer networks using optimum-path forest clustering

Nowadays, organizations face the problem of keeping their information protected, available and trustworthy. In this context, machine learning techniques have also been extensively applied to this task. Since manual labeling is very expensive, several works attempt to handle intrusion detection with traditional clustering algorithms. In this paper, we introduce a new pattern recognition technique called Optimum-Path Forest (OPF) clustering to this task. Experiments on three public datasets have showed that OPF classifier may be a suitable tool to detect intrusions on computer networks, since it outperformed some state-of-the-art unsupervised techniques. © 2012 IEEE.

Improving image classification through descriptor combination

The efficiency in image classification tasks can be improved using combined information provided by several sources, such as shape, color, and texture visual properties. Although many works proposed to combine different feature vectors, we model the descriptor combination as an optimization problem to be addressed by evolutionary-based techniques, which compute distances between samples that maximize their separability in the feature space. The robustness of the proposed technique is assessed by the Optimum-Path Forest classifier. Experiments showed that the proposed methodology can outperform individual information provided by single descriptors in well-known public datasets. © 2012 IEEE.

Karyotypic diversity and evolutionary trends in the neotropical catfish genus Hypostomus lacépède, 1803 (Teleostei, Siluriformes, Loricariidae)

The family Loricariidae with 813 nominal species is one of the largest fish families of the world. Hypostominae, its more complex subfamily, was recently divided into five tribes. The tribe Hypostomini is composed of a single genus, Hypostomus Lacépède, 1803, which exhibits the largest karyotypic diversity in the family Loricariidae. With the main objective of contributing to a better understanding of the relationship and the patterns of evolution among the karyotypes of Hypostomus species, cytogenetic studies were conducted in six species of the genus from Brazil and Venezuela. The results show a great chromosome variety with diploid numbers ranging from 2n=68 to 2n=76, with a clear predominance of acrocentric chromosomes. The Ag-NORs are located in terminal position in all species analyzed. Three species have single Ag-NORs (Hypostomus albopunctatus (Regan, 1908), H. prope plecostomus (Linnaeus, 1758), and H. prope paulinus (Ihering, 1905)) and three have multiple Ag-NORs (H. ancistroides (Ihering, 1911), H. prope iheringi (Regan, 1908), and H. strigaticeps (Regan, 1908)). In the process of karyotype evolution of the group, the main type of chromosome rearrangements was possibly centric fissions, which may have been facilitated by the putative tetraploid origin of Hypostomus species. The relationship between the karyotype changes and the evolution in the genus is discussed. © Anderson Luis Alves et al.

Speeding up optimum-path forest training by path-cost propagation

In this paper we present an optimization of the Optimum-Path Forest classifier training procedure, which is based on a theoretical relationship between minimum spanning forest and optimum-path forest for a specific path-cost function. Experiments on public datasets have shown that the proposed approach can obtain similar accuracy to the traditional one but with faster data training. © 2012 ICPR Org Committee.

Análisis de trayectoria (path analysis): aplicación en la demografía social con un ejemplo que emplea un programa disponible en CELADE

Incluye Bibliografía

Functional extinction of birds drives rapid evolutionary changes in seed size

Local extinctions have cascading effects on ecosystem functions, yet little is known about the potential for the rapid evolutionary change of species in human-modified scenarios. We show that the functional extinction of large-gape seed dispersers in the Brazilian Atlantic forest is associated with the consistent reduction of the seed size of a keystone palm species. Among 22 palm populations, areas deprived of large avian frugivores for several decades present smaller seeds than nondefaunated forests, with negative consequences for palm regeneration. Coalescence and phenotypic selection models indicate that seed size reduction most likely occurred within the past 100 years, associated with human-driven fragmentation. The fast-paced defaunation of large vertebrates is most likely causing unprecedented changes in the evolutionary trajectories and community composition of tropical forests.