A single chart with supplementary runs rules for monitoring the mean vector and the covariance matrix of multivariate processes

The MRMAX chart is a single chart based on the standardized sample means and sample ranges for monitoring the mean vector and the covariance matrix of multivariate processes. User's familiarity with the computation of these statistics is a point in favor of the MRMAX chart. As a single chart, the recently proposed MRMAX chart is very appropriate for supplementary runs rules. In this article, we compare the supplemented MRMAX chart and the synthetic MRMAX chart with the standard MRMAX chart. The supplementary and the synthetic runs rules enhance the performance of the MRMAX chart. © 2013 Elsevier Ltd.

Binary Bat Algorithm for Feature Selection

Feature selection aims to find the most important information to save computational efforts and data storage. We formulated this task as a combinatorial optimization problem since the exponential growth of possible solutions makes an exhaustive search infeasible. In this work, we propose a new nature-inspired feature selection technique based on bats behavior, namely, binary bat algorithm The wrapper approach combines the power of exploration of the bats together with the speed of the optimum-path forest classifier to find a better data representation. Experiments in public datasets have shown that the proposed technique can indeed improve the effectiveness of the optimum-path forest and outperform some well-known swarm-based techniques. © 2013 Copyright © 2013 Elsevier Inc. All rights reserved.

Peixoto's Theorem for vector fields on S2 with impasse points

The structural stability of vector fields with impasse regular curves on S2 is studied and a version of Peixoto's Theorem is established. Moreover a global analysis of normal forms of the constrained systems. A(x).ẋ=F(x),x∈R3,A∈M(3),F:R3→R3 in the Poincaré ball (i.e. in the compactification of R3 with the sphere S2 of the infinity) is made. © 2013 Elsevier Masson SAS.

A decoding method of an n length binary BCH code through (n + 1)n length binary cyclic code

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

BCS: A Binary Cuckoo Search algorithm for feature selection

Feature selection has been actively pursued in the last years, since to find the most discriminative set of features can enhance the recognition rates and also to make feature extraction faster. In this paper, the propose a new feature selection called Binary Cuckoo Search, which is based on the behavior of cuckoo birds. The experiments were carried out in the context of theft detection in power distribution systems in two datasets obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others nature-inspired optimization techniques. © 2013 IEEE.

Asymptomatic dogs are highly competent to transmit Leishmania (Leishmania) infantum chagasi to the natural vector

We evaluated the ability of dogs naturally infected with Leishmania (Leishmania) infantum chagasi to transfer the parasite to the vector and the factors associated with transmission. Thirty-eight infected dogs were confirmed to be infected by direct observation of Leishmania in lymph node smears. Dogs were grouped according to external clinical signs and laboratory data into symptomatic (n= 24) and asymptomatic (n= 14) animals. All dogs were sedated and submitted to xenodiagnosis with F1-laboratory-reared Lutzomyia longipalpis. After blood digestion, sand flies were dissected and examined for the presence of promastigotes. Following canine euthanasia, fragments of skin, lymph nodes, and spleen were collected and processed using immunohistochemistry to evaluate tissue parasitism. Specific antibodies were detected using an enzyme-linked immunosorbent assay. Antibody levels were found to be higher in symptomatic dogs compared to asymptomatic dogs (p= 0.0396). Both groups presented amastigotes in lymph nodes, while skin parasitism was observed in only 58.3% of symptomatic and in 35.7% of asymptomatic dogs. Parasites were visualized in the spleens of 66.7% and 71.4% of symptomatic and asymptomatic dogs, respectively. Parasite load varied from mild to intense, and was not significantly different between groups. All asymptomatic dogs except for one (93%) were competent to transmit Leishmania to the vector, including eight (61.5%) without skin parasitism. Sixteen symptomatic animals (67%) infected sand flies; six (37.5%) showed no amastigotes in the skin. Skin parasitism was not crucial for the ability to infect Lutzomyia longipalpis but the presence of Leishmania in lymph nodes was significantly related to a positive xenodiagnosis. Additionally, a higher proportion of infected vectors that fed on asymptomatic dogs was observed (p= 0.0494). Clinical severity was inversely correlated with the infection rate of sand flies (p= 0.027) and was directly correlated with antibody levels (p= 0.0379). Age and gender did not influence the transmissibility. Our data show that asymptomatic dogs are highly infective and competent for establishing sand fly infection, indicating their role in maintaining L. (L.) infantum chagasi cycle as well as their involvement in VL spreading in endemic areas. © 2013 Elsevier B.V.

Optimizing feature selection through binary charged system search

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques. © 2013 Springer-Verlag.

Stability and collapse of fermions in a binary dipolar boson-fermion 164Dy-161Dy mixture

We suggest a time-dependent mean-field hydrodynamic model for a binary dipolar boson-fermion mixture to study the stability and collapse of fermions in the 164Dy-161Dy mixture. The condition of stability of the dipolar mixture is illustrated in terms of phase diagrams. A collapse is induced in a disk-shaped stable binary mixture by jumping the interspecies contact interaction from repulsive to attractive by the Feshbach resonance technique. The subsequent dynamics is studied by solving the time-dependent mean-field model including three-body loss due to molecule formation in boson-fermion and boson-boson channels. Collapse and fragmentation in the fermions after subsequent explosions are illustrated. The anisotropic dipolar interaction leads to anisotropic fermionic density distribution during collapse. This study is carried out in three-dimensional space using realistic values of dipolar and contact interactions. © 2013 American Physical Society.

Improving face recognition with multispectral fusion and support vector machines

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Exotic Bose-Einstein condensates: binary mixtures and dipolar gases

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Process for genetically engineering acidophilic bacteria and constructing a transformation vector

The present invention describes a method for transforming chemolithotrophic acidophilic bacteria using electroporation technology. The proposed method allows transforming a bacterial line using a transformation vector, the pAF vector, which contains an origin of vegetative replication that allows the vector to replicate inside the bacteria without altering the natural physiological functions of the latter. Also disclosed is the use of the bacteria modified according to the invention in bioleaching processes of sulphated copper, gold, uranium, nickel, zinc and cobalt ore, inter alia.

Aedes aegypti on Madeira Island (Portugal): genetic variation of a recently introduced dengue vector

The increasing population of Aedes aegypti mosquitoes on Madeira Island (Portugal) resulted in the first autochthonous dengue outbreak, which occurred in October 2012. Our study establishes the first genetic evaluation based on the mitochondrial DNA (mtDNA) genes [cytochrome oxidase subunit I (COI) and NADH dehydrogenase subunit 4 (ND4)] and knockdown resistance ( kdr ) mutations exploring the colonisation history and the genetic diversity of this insular vector population. We included mosquito populations from Brazil and Venezuela in the analysis as putative geographic sources. The Ae. aegyptipopulation from Madeira showed extremely low mtDNA genetic variability, with a single haplotype for COI and ND4. We also detected the presence of two important kdr mutations and the quasi-fixation of one of these mutations (F1534C). These results are consistent with a unique recent founder event that occurred on the island of Ae. aegyptimosquitoes that carry kdr mutations associated with insecticide resistance. Finally, we also report the presence of the F1534C kdr mutation in the Brazil and Venezuela populations. To our knowledge, this is the first time this mutation has been found in South American Ae. aegypti mosquitoes. Given the present risk of Ae. aegypti re-invading continental Europe from Madeira and the recent dengue outbreaks on the island, this information is important to plan surveillance and control measures.

Comparing support vector machines and artificial neural networks in the recognition of steering angle for driving of mobile robots through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by pre-processing them to extract image features. Such features are then submitted to a support vector machine and an artificial neural network in order to find out the most appropriate route. A comparison of the two approaches was performed to ascertain the one presenting the best outcome. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine and of an artificial neural network, which so far presented respectively around 93% and 90% accuracy in predicting the appropriate route. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science

Inclusive search for a vector-like T quark with charge 2/3 in pp collisions at root s=8 TeV

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Fractional fermion charges induced by axial-vector and vector gauge potentials and parity anomaly in planar graphenelike structures

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)