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.

Reconfiguração de sistemas de distribuição utilizando metaheurísticas e critérios de confiabilidade

In an ever more competitive environment, power distribution companies must satisfy two conflicting objectives: minimizing investment costs and the satisfaction of reliability targets. The network reconfiguration of a distribution system is a technique that well adapts to this new deregulated environment for it allows improvement of reliability indices only opening and closing switches, without the onus involved in acquiring new equipment. Due to combinatorial explosion problem characteristic, in the solution are employed metaheuristics methods, which converge to optimal or quasi-optimal solutions, but with a high computational effort. As the main objective of this work is to find the best configuration(s) of the distribution system with the best levels of reliability, the objective function used in the metaheuristics is to minimize the LOLC - Loss Of Load Cost, which is associated with both, number and duration of electric power interruptions. Several metaheuristics techniques are tested, and the tabu search has proven to be most appropriate to solve the proposed problem. To characterize computationally the problem of the switches reconfiguring was developed a vector model (with integers) of the representation of the switches, where each normally open switch is associated with a group of normally closed switches. In this model simplifications have been introduced to reduce computational time and restrictions were made to exclude solutions that do not supply energy to any load point of the system. To check violation of the voltage and loading criteria a study of power flow for the ten best solutions is performed. Also for the ten best solutions a reliability evaluation using Monte Carlo sequential simulation is performed, where it is possible to obtain the probability distributions of the indices and thus calculate the risk of paying penalty due to not meeting the goals. Finally, the methodology is applied in a real Brazilian distribution network, and the results are discussed.

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)

Temporal and Spatial Scaling of the Genetic Structure of a Vector-Borne Plant Pathogen

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Seasonal genetic partitioning in the neotropical malaria vector, Anopheles darlingi

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

Entoepidemiology of Chagas disease in northwest Sao Paulo and cytogenetic analysis of its main vector, Triatoma sordida (Hemiptera: Triatominae)

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

Semliki Forest Virus as a Vector: Pros and Cons for Its Use in Biopharmaceuticals Production

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

Genetic Variability and Geographical Diversity of the Main Chagas' Disease Vector Panstrongylus megistus (Hemiptera: Triatominae) in Brazil Based on Ribosomal DNA Intergenic Sequences

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Wide vector solitons in systems with time- and space-modulated nonlinearities

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Scattering and bound states of fermions in a mixed vector-scalar smooth step potential

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Stationary states of fermions in a sign potential with a mixed vector-scalar coupling

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multi-scale lacunarity as an alternative to quantify and diagnose the behavior of prostate cancer

Prostate cancer is a serious public health problem accounting for up to 30% of clinical tumors in men. The diagnosis of this disease is made with clinical, laboratorial and radiological exams, which may indicate the need for transrectal biopsy. Prostate biopsies are discerningly evaluated by pathologists in an attempt to determine the most appropriate conduct. This paper presents a set of techniques for identifying and quantifying regions of interest in prostatic images. Analyses were performed using multi-scale lacunarity and distinct classification methods: decision tree, support vector machine and polynomial classifier. The performance evaluation measures were based on area under the receiver operating characteristic curve (AUC). The most appropriate region for distinguishing the different tissues (normal, hyperplastic and neoplasic) was defined: the corresponding lacunarity values and a rule's model were obtained considering combinations commonly explored by specialists in clinical practice. The best discriminative values (AUC) were 0.906, 0.891 and 0.859 between neoplasic versus normal, neoplasic versus hyperplastic and hyperplastic versus normal groups, respectively. The proposed protocol offers the advantage of making the findings comprehensible to pathologists. (C) 2014 Elsevier Ltd. All rights reserved.