Conspicuous males suffer higher predation risk: visual modelling and experimental evidence from lizards

Colour pattern variation is a striking and widespread phenomenon. Differential predation risk between individuals is often invoked to explain colour variation, but empirical support for this hypothesis is equivocal. We investigated differential conspicuousness and predation risk in two species of Australian rock dragons, Ctenophorus decresii and C. vadnappa. To humans, the coloration of males of these species varies between 'bright' and 'dull'. Visual modelling based on objective colour measurements and the spectral sensitivities of avian visual pigments showed that dragon colour variants are differentially conspicuous to the visual system of avian predators when viewed against the natural background. We conducted field experiments to test for differential predation risk, using plaster models of 'bright' and 'dull' males. 'Bright' models were attacked significantly more often than 'dull' models suggesting that differential conspicuousness translates to differential predation risk in the wild. We also examined the influence of natural geographical range on predation risk. Results from 22 localities suggest that predation rates vary according to whether predators are familiar with the prey species. This study is among the first to demonstrate both differential conspicuousness and differential predation risk in the wild using an experimental protocol. (C) 2003 Published by Elsevier Ltd on behalf of The Association for the Study of Animal Behaviour.

Adaptive mutations in bacteria: high rate and small effects

Evolution by natural selection is driven by the continuous generation of adaptive mutations. We measured the genomic mutation rate that generates beneficial mutations and their effects on fitness in Escherichia coli under conditions in which the effect of competition between lineages carrying different beneficial mutations is minimized. We found a rate on the order of 10–5 per genome per generation, which is 1000 times as high as previous estimates, and a mean selective advantage of 1%. Such a high rate of adaptive evolution has implications for the evolution of antibiotic resistance and pathogenicity.

Mutation accumulation in Tetrahymena

Background - The rate and fitness effects of mutations are key in understanding the evolution of every species. Traditionally, these parameters are estimated in mutation accumulation experiments where replicate lines are propagated in conditions that allow mutations to randomly accumulate without the purging effect of natural selection. These experiments have been performed with many model organisms but we still lack empirical estimates of the rate and effects of mutation in the protists. Results - We performed a mutation accumulation (MA) experiment in Tetrahymena thermophila, a species that can reproduce sexually and asexually in nature, and measured both the mean decline and variance increase in fitness of 20 lines. The results obtained with T. thermophila were compared with T. pyriformis that is an obligate asexual species. We show that MA lines of T. thermophila go to extinction at a rate of 1.25 clonal extinctions per bottleneck. In contrast, populations of T. pyriformis show a much higher resistance to extinction. Variation in gene copy number is likely to be a key factor in explaining these results, and indeed we show that T. pyriformis has a higher mean copy number per cell than T. thermophila. From fitness measurements during the MA experiment, we infer a rate of mutation to copy number variation of 0.0333 per haploid MAC genome of T. thermophila and a mean effect against copy number variation of 0.16. A strong effect of population size in the rate of fitness decline was also found, consistent with the increased power of natural selection. Conclusions - The rate of clonal extinction measured for T. thermophila is characteristic of a mutational degradation and suggests that this species must undergo sexual reproduction to avoid the deleterious effects detected in the laboratory experiments. We also suggest that an increase in chromosomal copy number associated with the phenotypic assortment of amitotic divisions can provide an alternative mechanism to escape the deleterious effect of random chromosomal copy number variation in species like T. pyriformis that lack the resetting mechanism of sexual reproduction. Our results are relevant to the understanding of cell line longevity and senescence in ciliates.

A fuzzified systematic adjustment of the robotic Darwinian PSO

The Darwinian Particle Swarm Optimization (DPSO) is an evolutionary algorithm that extends the Particle Swarm Optimization using natural selection to enhance the ability to escape from sub-optimal solutions. An extension of the DPSO to multi-robot applications has been recently proposed and denoted as Robotic Darwinian PSO (RDPSO), benefiting from the dynamical partitioning of the whole population of robots, hence decreasing the amount of required information exchange among robots. This paper further extends the previously proposed algorithm adapting the behavior of robots based on a set of context-based evaluation metrics. Those metrics are then used as inputs of a fuzzy system so as to systematically adjust the RDPSO parameters (i.e., outputs of the fuzzy system), thus improving its convergence rate, susceptibility to obstacles and communication constraints. The adapted RDPSO is evaluated in groups of physical robots, being further explored using larger populations of simulated mobile robots within a larger scenario.

Introducing the fractional-order Darwinian PSO

One of the most well-known bio-inspired algorithms used in optimization problems is the particle swarm optimization (PSO), which basically consists on a machinelearning technique loosely inspired by birds flocking in search of food. More specifically, it consists of a number of particles that collectively move on the search space in search of the global optimum. The Darwinian particle swarm optimization (DPSO) is an evolutionary algorithm that extends the PSO using natural selection, or survival of the fittest, to enhance the ability to escape from local optima. This paper firstly presents a survey on PSO algorithms mainly focusing on the DPSO. Afterward, a method for controlling the convergence rate of the DPSO using fractional calculus (FC) concepts is proposed. The fractional-order optimization algorithm, denoted as FO-DPSO, is tested using several well-known functions, and the relationship between the fractional-order velocity and the convergence of the algorithm is observed. Moreover, experimental results show that the FO-DPSO significantly outperforms the previously presented FO-PSO.

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.

Introdução ao estudo da paralelização de algoritmos de planeamentooperacional com metodos genéticos

Dissertação de Mestrado

HLA and malaria in four colombian ethnic groups

HLA antigens and their relationship with malaria infection were studied in four different ethnic groups in Colombia (South America): two groups of indians (Kunas and Katios), one of negroes and a group of mixed ancestry. A total of 965 persons were studied, 415 with malaria and 550 as controls. HLA-A,B, and C antigen frequencies in the four groups are reported. The association of each HLA antigen with malaria infection due to P. vivax and to P. falciparum was evaluated. Negroes, Kunas and Katios indians variously lack from 6 to 9 of the HLA antigens found in the mixed group. In the designated ethnic groups, antigens B5, B13, B15, Cw2 and Cw4 showed borderline association with malaria infection. However, in the mixed ethnic group, statistically significant associations were found with malaria infection and the presence of A9, Aw19, B17, B35, and Z98 (a B21-B45: crossreacting determinant) with few differences when P. vivax infection and P. falciparum infection were considered individually. This finding may represent a lack of general resistance to malaria in the group that harbors antigens of Caucasian origin. These individuals have been in direct and permanent contact with malaria only in the past 65 years. In contrast, indians, both Kunas and Katios, and Negroes have lived for centuries in malaria endemic areas, and it is possible that a natural selection system has developed through which only those individuals able to initiate an acute immune response to malaria have survived.

Exportação e impacto nos resultados: o caso de um grupo de empresas portuguesas

Com a crescente preocupação em dinamizar as exportações e potenciar os seus efeitos na economia, muitos trabalhos têm tentado encontrar fatores potenciadores do sucesso das empresas no mercado internacional (dimensão, produtividade pré exportadora, idade, fase do ciclo de produção, relacionamento prévio com o exterior, etc.). Temas como a seleção natural do mercado e a aprendizagem pela exportação, são transversais e incontornáveis nos trabalhos empíricos que abordam o estudo das exportações ao nível das empresas. No entanto, não nos devemos esquecer que uma das principais motivações das empresas, é a maximização do lucro. Com efeito, uma nova onda de trabalhos tem-se voltado para a o impacto que as exportações têm sobre a rentabilidade das empresas. Utilizando um modelo de efeitos fixos com dados em painel, aplicado a uma base de dados de empresas portuguesas, com espetro temporal entre 2008 e 2012, este trabalho encontra evidências e que as exportações são um fraco potenciador da rentabilidade das empresas. Do ponto de vista da organização do presente trabalho, no primeiro capítulo será apresentada uma breve revisão de literatura enquadradora do tema; no segundo capítulo será apresentada a base de dados, tratamento e a abordagem econométrica; por último será apresentada uma conclusão, com os resultados principais do trabalho e com algumas questões que poderão ser abordadas no futuro.

Adaptation from standing genetic variation and from mutation

Dissertation presented to obtain the Ph.D degree in Evolutionary Biology

Intention recognition, commitment and their roles in the evolution of cooperation

Dissertação para obtenção do Grau de Doutor em Informática

Impact of chromossomal structure on the evolution of Schizosaccharomyces pombe undergoing Mutation Accumulation

Large chromosomal rearrangements are common in natural populations and thought to be involved in speciation events. In this project, we used experimental evolution to determine how the speed of evolution and the type of accumulated mutations depend on the ancestral chromosomal structure and genotype. We utilized two Wild Type strains and a set of genetically engineered Schizosaccharomyces pombe strains, different solely in the presence of a certain type of chromosomal variant (inversions or translocations), along with respective controls. Previous research has shown that these chromosomal variants have different fitness levels in several environments, probably due to changes in the gene expression along the genome. These strains were propagated in the laboratory at very low population sizes, in which we expect natural selection to be less efficient at purging deleterious mutations. We then measured these strains’ changes in fitness throughout this accumulation of deleterious mutations, comparing the evolutionary trajectories in the different rearrangements to understand if the chromosomal structure affected the speed of evolution. We also tested these mutations for possible epistatic effects and estimated their parameters: the number of arising deleterious mutations per generation (Ud) and each one’s mean effect (sd).

MOEA/VAN: Multiobjective Evolutionary Algorithm based on Vector Angle Neighborhood

Natural selection favors the survival and reproduction of organisms that are best adapted to their environment. Selection mechanism in evolutionary algorithms mimics this process, aiming to create environmental conditions in which artificial organisms could evolve solving the problem at hand. This paper proposes a new selection scheme for evolutionary multiobjective optimization. The similarity measure that defines the concept of the neighborhood is a key feature of the proposed selection. Contrary to commonly used approaches, usually defined on the basis of distances between either individuals or weight vectors, it is suggested to consider the similarity and neighborhood based on the angle between individuals in the objective space. The smaller the angle, the more similar individuals. This notion is exploited during the mating and environmental selections. The convergence is ensured by minimizing distances from individuals to a reference point, whereas the diversity is preserved by maximizing angles between neighboring individuals. Experimental results reveal a highly competitive performance and useful characteristics of the proposed selection. Its strong diversity preserving ability allows to produce a significantly better performance on some problems when compared with stat-of-the-art algorithms.

Desenvolvimento de materiais para isolamento térmico com base em biomimética

Dissertação de mestrado Internacional em Sustentabilidade do Ambiente Construído