GOOAL: A routine based on Genetic Algorithms to track harmonics in electric power systems

Voltage and current waveforms of a distribution or transmission power system are not pure sinusoids. There are distortions in these waveforms that can be represented as a combination of the fundamental frequency, harmonics and high frequency transients. This paper presents a novel approach to identifying harmonics in power system distorted waveforms. The proposed method is based on Genetic Algorithms, which is an optimization technique inspired by genetics and natural evolution. GOOAL, a specially designed intelligent algorithm for optimization problems, was successfully implemented and tested. Two kinds of representations concerning chromosomes are utilized: binary and real. The results show that the proposed method is more precise than the traditional Fourier Transform, especially considering the real representation of the chromosomes.

Reconfiguration of distribution networks to minimize loss and disruption costs using genetic algorithms

In this paper a computational implementation of an evolutionary algorithm (EA) is shown in order to tackle the problem of reconfiguring radial distribution systems. The developed module considers power quality indices such as long duration interruptions and customer process disruptions due to voltage sags, by using the Monte Carlo simulation method. Power quality costs are modeled into the mathematical problem formulation, which are added to the cost of network losses. As for the EA codification proposed, a decimal representation is used. The EA operators, namely selection, recombination and mutation, which are considered for the reconfiguration algorithm, are herein analyzed. A number of selection procedures are analyzed, namely tournament, elitism and a mixed technique using both elitism and tournament. The recombination operator was developed by considering a chromosome structure representation that maps the network branches and system radiality, and another structure that takes into account the network topology and feasibility of network operation to exchange genetic material. The topologies regarding the initial population are randomly produced so as radial configurations are produced through the Prim and Kruskal algorithms that rapidly build minimum spanning trees. (C) 2009 Elsevier B.V. All rights reserved.

Distributed power control algorithm for multiple access systems based on Verhulst model

In this paper the continuous Verhulst dynamic model is used to synthesize a new distributed power control algorithm (DPCA) for use in direct sequence code division multiple access (DS-CDMA) systems. The Verhulst model was initially designed to describe the population growth of biological species under food and physical space restrictions. The discretization of the corresponding differential equation is accomplished via the Euler numeric integration (ENI) method. Analytical convergence conditions for the proposed DPCA are also established. Several properties of the proposed recursive algorithm, such as Euclidean distance from optimum vector after convergence, convergence speed, normalized mean squared error (NSE), average power consumption per user, performance under dynamics channels, and implementation complexity aspects, are analyzed through simulations. The simulation results are compared with two other DPCAs: the classic algorithm derived by Foschini and Miljanic and the sigmoidal of Uykan and Koivo. Under estimated errors conditions, the proposed DPCA exhibits smaller discrepancy from the optimum power vector solution and better convergence (under fixed and adaptive convergence factor) than the classic and sigmoidal DPCAs. (C) 2010 Elsevier GmbH. All rights reserved.

Evaluation of algorithms used to order markers on genetic maps

When building genetic maps, it is necessary to choose from several marker ordering algorithms and criteria, and the choice is not always simple. In this study, we evaluate the efficiency of algorithms try (TRY), seriation (SER), rapid chain delineation (RCD), recombination counting and ordering (RECORD) and unidirectional growth (UG), as well as the criteria PARF (product of adjacent recombination fractions), SARF (sum of adjacent recombination fractions), SALOD (sum of adjacent LOD scores) and LHMC (likelihood through hidden Markov chains), used with the RIPPLE algorithm for error verification, in the construction of genetic linkage maps. A linkage map of a hypothetical diploid and monoecious plant species was simulated containing one linkage group and 21 markers with fixed distance of 3 cM between them. In all, 700 F(2) populations were randomly simulated with and 400 individuals with different combinations of dominant and co-dominant markers, as well as 10 and 20% of missing data. The simulations showed that, in the presence of co-dominant markers only, any combination of algorithm and criteria may be used, even for a reduced population size. In the case of a smaller proportion of dominant markers, any of the algorithms and criteria (except SALOD) investigated may be used. In the presence of high proportions of dominant markers and smaller samples (around 100), the probability of repulsion linkage increases between them and, in this case, use of the algorithms TRY and SER associated to RIPPLE with criterion LHMC would provide better results. Heredity (2009) 103, 494-502; doi:10.1038/hdy.2009.96; published online 29 July 2009

Quantitative Trait Loci Mapping and The Genetic Basis of Heterosis in Maize and Rice

Despite its importance to agriculture, the genetic basis of heterosis is still not well understood. The main competing hypotheses include dominance, overdominance, and epistasis. NC design III is an experimental design that. has been used for estimating the average degree of dominance of quantitative trait 106 (QTL) and also for studying heterosis. In this study, we first develop a multiple-interval mapping (MIM) model for design III that provides a platform to estimate the number, genomic positions, augmented additive and dominance effects, and epistatic interactions of QTL. The model can be used for parents with any generation of selling. We apply the method to two data sets, one for maize and one for rice. Our results show that heterosis in maize is mainly due to dominant gene action, although overdominance of individual QTL could not completely be ruled out due to the mapping resolution and limitations of NC design III. For rice, the estimated QTL dominant effects could not explain the observed heterosis. There is evidence that additive X additive epistatic effects of QTL could be the main cause for the heterosis in rice. The difference in the genetic basis of heterosis seems to be related to open or self pollination of the two species. The MIM model for NC design III is implemented in Windows QTL Cartographer, a freely distributed software.

Murine cytomegalovirus homologues of cellular immunomodulatory genes

The study of 'molecular mimicry' or 'genetic piracy', with respect to the utilisation of cellular genes captured and modified during the course of virus evolution, has been an area of increasing research with the expansion in virus genome sequencing. Examples of cellular immunomodulatory genes which have been captured from hosts have been identified in a number of viruses. This review concentrates upon studies of murine cytomegalovirus (MCMV), investigating the functions of viral genes homologous to G protein-coupled receptors, MHC class I and chemokines, The study of recombinant MCMV engineered with specific disruptions of these genes has revealed their significance during virus replication and dissemination within the host, In the case of the latter two classes of genes, evidence suggests they interfere with cellular immune responses, although the detailed mechanisms underlying this interference have yet to be delineated. Copyright (C) 2000 S. Karger AG, Basel.

Genetic algorithms for continuous optimization problems - a concept of parameter-space size adjustment

The concept of parameter-space size adjustment is pn,posed in order to enable successful application of genetic algorithms to continuous optimization problems. Performance of genetic algorithms with six different combinations of selection and reproduction mechanisms, with and without parameter-space size adjustment, were severely tested on eleven multiminima test functions. An algorithm with the best performance was employed for the determination of the model parameters of the optical constants of Pt, Ni and Cr.

Rhipicephalus (Boophilus) microplus: Distinct acute phase proteins vary during infestations according to the genetic composition of the bovine hosts, Bos taurus and Bos indicus

Tick bites may trigger acute phase responses. Positive and negative acute phase proteins were measured in infested cattle genetically resistant and susceptible to ticks. During heavier infestations levels of haptoglobin increased significantly in susceptible bovines; levels of serum amyloid A increased in resistant bovines; levels of alpha-l-acid glycoprotein decreased significantly in resistant bovines; levels of transferrin decreased significantly in susceptible bovines. In conclusion, tick infestations trigger acute phase responses and enhancement of specific acute phase proteins differs according to the genetic composition of hosts. Acute phase proteins may constitute useful biological signatures for monitoring the stress induced by tick infestations. (c) 2007 Elsevier Inc. All rights reserved.

Molecular and cellular biology of pre-malignancy in the gastrointestinal tract

Important pathogenic alterations within established cancers are acquired during the premalignant stage. These genetic alterations can be grouped into specific neoplastic pathways that differ within and between anatomical sites. By understanding the mechanisms that determine the initiation and progression of each pathway, it will be possible to develop novel approaches to the diagnosis, prevention and treatment of cancer. This chapter outlines the principles underlying the molecular characterization of pre-malignant lesions, taking colorectal neoplasia as the main model.

ATM, a central controller of cellular responses to DNA damage

Mutations in the ATM gene lead to the genetic disorder ataxia-telangiectasia. ATM encodes a protein kinase that is mainly distributed in the nucleus of proliferating cells. Recent studies reveal that ATM regulates multiple cell cycle checkpoints by phosphorylating different targets at different stages of the cell cycle. ATM also functions in the regulation of DNA repair and apoptosis, suggesting that it is a central regulator of responses to DNA double-strand breaks.

Movement through slits: cellular migration via the Slit family

First isolated in the fly and now characterised in vertebrates, the Slit proteins have emerged as pivotal components controlling the guidance of axonal growth cones and the directional migration of neuronal precursors. As well as extensive expression during development of the central nervous system (CNS), the Slit proteins exhibit a striking array of expression sites in non-neuronal tissues, including the urogenital system, limb primordia and developing eye. Zebrafish Slit has been shown to mediate mesodermal migration during gastrulation, while Drosophila slit guides the migration of mesodermal cells during myogenesis. This suggests that the actions of these secreted molecules are not simply confined to the sphere of CNS development, but rather act in a more general fashion during development and throughout the lifetime of an organism. This review focuses on the non-neuronal activities of Slit proteins, highlighting a common role for the Slit family in cellular migration.

The influence of genetic polymorphisms in XRCC3 and ADH5 genes on the frequency of genotoxicity biomarkers in workers exposed to formaldehyde

The International Agency for Research on Cancer classified formaldehyde as carcinogenic to humans because there is “sufficient epidemiological evidence that it causes nasopharyngeal cancer in humans”. Genes involved in DNA repair and maintenance of genome integrity are critically involved in protecting against mutations that lead to cancer and/or inherited genetic disease. Association studies have recently provided evidence for a link between DNA repair polymorphisms and micronucleus (MN) induction. We used the cytokinesis-block micronucleus (CBMN assay) in peripheral lymphocytes and MN test in buccal cells to investigate the effects of XRCC3 Thr241Met, ADH5 Val309Ile, and Asp353Glu polymorphisms on the frequency of genotoxicity biomarkers in individuals occupationally exposed to formaldehyde (n = 54) and unexposed workers (n = 82). XRCC3 participates in DNA double-strand break/recombination repair, while ADH5 is an important component of cellular metabolism for the elimination of formaldehyde. Exposed workers had significantly higher frequencies (P < 0.01) than controls for all genotoxicity biomarkers evaluated in this study. Moreover, there were significant associations between XRCC3 genotypes and nuclear buds, namely XRCC3 Met/Met (OR = 3.975, CI 1.053–14.998, P = 0.042) and XRCC3 Thr/Met (OR = 5.632, CI 1.673–18.961, P = 0.005) in comparison with XRCC3 Thr/Thr. ADH5 polymorphisms did not show significant effects. This study highlights the importance of integrating genotoxicity biomarkers and genetic polymorphisms in human biomonitoring studies.

Crossing genetic and swarm intelligence algorithms to generate logic circuits

Genetic Algorithms (GAs) are adaptive heuristic search algorithm based on the evolutionary ideas of natural selection and genetic. The basic concept of GAs is designed to simulate processes in natural system necessary for evolution, specifically those that follow the principles first laid down by Charles Darwin of survival of the fittest. On the other hand, Particle swarm optimization (PSO) is a population based stochastic optimization technique inspired by social behavior of bird flocking or fish schooling. PSO shares many similarities with evolutionary computation techniques such as GAs. The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. PSO is attractive because there are few parameters to adjust. This paper presents hybridization between a GA algorithm and a PSO algorithm (crossing the two algorithms). The resulting algorithm is applied to the synthesis of combinational logic circuits. With this combination is possible to take advantage of the best features of each particular algorithm.

Genetic diversity of arginine catabolic mobile element in Staphylococcus epidermidis

PLos One, 4(11): ARTe7722

Genetic diversity and primary resistance among HIV-1-positive patients from Maringá, Paraná, Brazil

The objective of this study is to identify subtypes of Human Immunodeficiency Virus type 1 (HIV-1) and to analyze the presence of mutations associated to antiretroviral resistance in the protease (PR) and reverse transcriptase (RT) regions from 48 HIV-1 positive treatment naïve patients from an outpatient clinic in Maringá, Paraná, Brazil. Sequencing was conducted using PR, partial RT and group-specific antigen gene (gag) nested PCR products from retrotranscribed RNA. Transmitted resistance was determined according to the Surveillance Drug Resistance Mutation List (SDRM) algorithm. Phylogenetic and SimPlot analysis of concatenated genetic segments classified sequences as subtype B 19/48 (39.6%), subtype C 12/48 (25%), subtype F 4/48 (8.3%), with 13/48 (27.1%) recombinant forms. Most recombinant forms were B mosaics (B/F 12.5%, B/C 10.4%), with one C/F (2.1%) and one complex B/C/F mosaic (2.1%). Low levels of transmitted resistance were found in this study, 2/48 (2.1% to NRTIs and 2.1% for PI). This preliminary data may subsidize the monitoring of the HIV evolution in the region.