WorldWideScience

Sample records for evolutionary models tested

  1. Evolutionary modeling-based approach for model errors correction

    Directory of Open Access Journals (Sweden)

    S. Q. Wan

    2012-08-01

    Full Text Available The inverse problem of using the information of historical data to estimate model errors is one of the science frontier research topics. In this study, we investigate such a problem using the classic Lorenz (1963 equation as a prediction model and the Lorenz equation with a periodic evolutionary function as an accurate representation of reality to generate "observational data."

    On the basis of the intelligent features of evolutionary modeling (EM, including self-organization, self-adaptive and self-learning, the dynamic information contained in the historical data can be identified and extracted by computer automatically. Thereby, a new approach is proposed to estimate model errors based on EM in the present paper. Numerical tests demonstrate the ability of the new approach to correct model structural errors. In fact, it can actualize the combination of the statistics and dynamics to certain extent.

  2. An evolutionary cascade model for sauropod dinosaur gigantism--overview, update and tests.

    Directory of Open Access Journals (Sweden)

    P Martin Sander

    Full Text Available Sauropod dinosaurs are a group of herbivorous dinosaurs which exceeded all other terrestrial vertebrates in mean and maximal body size. Sauropod dinosaurs were also the most successful and long-lived herbivorous tetrapod clade, but no abiological factors such as global environmental parameters conducive to their gigantism can be identified. These facts justify major efforts by evolutionary biologists and paleontologists to understand sauropods as living animals and to explain their evolutionary success and uniquely gigantic body size. Contributions to this research program have come from many fields and can be synthesized into a biological evolutionary cascade model of sauropod dinosaur gigantism (sauropod gigantism ECM. This review focuses on the sauropod gigantism ECM, providing an updated version based on the contributions to the PLoS ONE sauropod gigantism collection and on other very recent published evidence. The model consist of five separate evolutionary cascades ("Reproduction", "Feeding", "Head and neck", "Avian-style lung", and "Metabolism". Each cascade starts with observed or inferred basal traits that either may be plesiomorphic or derived at the level of Sauropoda. Each trait confers hypothetical selective advantages which permit the evolution of the next trait. Feedback loops in the ECM consist of selective advantages originating from traits higher in the cascades but affecting lower traits. All cascades end in the trait "Very high body mass". Each cascade is linked to at least one other cascade. Important plesiomorphic traits of sauropod dinosaurs that entered the model were ovipary as well as no mastication of food. Important evolutionary innovations (derived traits were an avian-style respiratory system and an elevated basal metabolic rate. Comparison with other tetrapod lineages identifies factors limiting body size.

  3. An evolutionary cascade model for sauropod dinosaur gigantism--overview, update and tests.

    Science.gov (United States)

    Sander, P Martin

    2013-01-01

    Sauropod dinosaurs are a group of herbivorous dinosaurs which exceeded all other terrestrial vertebrates in mean and maximal body size. Sauropod dinosaurs were also the most successful and long-lived herbivorous tetrapod clade, but no abiological factors such as global environmental parameters conducive to their gigantism can be identified. These facts justify major efforts by evolutionary biologists and paleontologists to understand sauropods as living animals and to explain their evolutionary success and uniquely gigantic body size. Contributions to this research program have come from many fields and can be synthesized into a biological evolutionary cascade model of sauropod dinosaur gigantism (sauropod gigantism ECM). This review focuses on the sauropod gigantism ECM, providing an updated version based on the contributions to the PLoS ONE sauropod gigantism collection and on other very recent published evidence. The model consist of five separate evolutionary cascades ("Reproduction", "Feeding", "Head and neck", "Avian-style lung", and "Metabolism"). Each cascade starts with observed or inferred basal traits that either may be plesiomorphic or derived at the level of Sauropoda. Each trait confers hypothetical selective advantages which permit the evolution of the next trait. Feedback loops in the ECM consist of selective advantages originating from traits higher in the cascades but affecting lower traits. All cascades end in the trait "Very high body mass". Each cascade is linked to at least one other cascade. Important plesiomorphic traits of sauropod dinosaurs that entered the model were ovipary as well as no mastication of food. Important evolutionary innovations (derived traits) were an avian-style respiratory system and an elevated basal metabolic rate. Comparison with other tetrapod lineages identifies factors limiting body size.

  4. An Evolutionary Cascade Model for Sauropod Dinosaur Gigantism - Overview, Update and Tests

    Science.gov (United States)

    Sander, P. Martin

    2013-01-01

    Sauropod dinosaurs are a group of herbivorous dinosaurs which exceeded all other terrestrial vertebrates in mean and maximal body size. Sauropod dinosaurs were also the most successful and long-lived herbivorous tetrapod clade, but no abiological factors such as global environmental parameters conducive to their gigantism can be identified. These facts justify major efforts by evolutionary biologists and paleontologists to understand sauropods as living animals and to explain their evolutionary success and uniquely gigantic body size. Contributions to this research program have come from many fields and can be synthesized into a biological evolutionary cascade model of sauropod dinosaur gigantism (sauropod gigantism ECM). This review focuses on the sauropod gigantism ECM, providing an updated version based on the contributions to the PLoS ONE sauropod gigantism collection and on other very recent published evidence. The model consist of five separate evolutionary cascades (“Reproduction”, “Feeding”, “Head and neck”, “Avian-style lung”, and “Metabolism”). Each cascade starts with observed or inferred basal traits that either may be plesiomorphic or derived at the level of Sauropoda. Each trait confers hypothetical selective advantages which permit the evolution of the next trait. Feedback loops in the ECM consist of selective advantages originating from traits higher in the cascades but affecting lower traits. All cascades end in the trait “Very high body mass”. Each cascade is linked to at least one other cascade. Important plesiomorphic traits of sauropod dinosaurs that entered the model were ovipary as well as no mastication of food. Important evolutionary innovations (derived traits) were an avian-style respiratory system and an elevated basal metabolic rate. Comparison with other tetrapod lineages identifies factors limiting body size. PMID:24205267

  5. Not just a theory--the utility of mathematical models in evolutionary biology.

    Directory of Open Access Journals (Sweden)

    Maria R Servedio

    2014-12-01

    Full Text Available Progress in science often begins with verbal hypotheses meant to explain why certain biological phenomena exist. An important purpose of mathematical models in evolutionary research, as in many other fields, is to act as “proof-of-concept” tests of the logic in verbal explanations, paralleling the way in which empirical data are used to test hypotheses. Because not all subfields of biology use mathematics for this purpose, misunderstandings of the function of proof-of-concept modeling are common. In the hope of facilitating communication, we discuss the role of proof-of-concept modeling in evolutionary biology.

  6. Testing evolutionary convergence on Europa

    Energy Technology Data Exchange (ETDEWEB)

    Chela-Flores, Julian [Instituto de Estudios Avanzados, Caracas (Venezuela); [Abdus Salam International Centre for Theoretical Physics, Trieste (Italy)

    2002-11-01

    A major objective in solar system exploration is the insertion of appropriate biology-oriented experiments in future missions. We discuss various reasons for suggesting that this type of research be considered a high priority for feasibility studies and, subsequently, for technological development of appropriate melters and submersibles. Based on numerous examples, we argue in favour of the assumption that Darwin's theory is valid for the evolution of life anywhere in the universe. We have suggested how to obtain preliminary insights into the question of the distribution of life in the universe. Universal evolution of intelligent behaviour is at the end of an evolutionary pathway, in which evolution of ion channels in the membrane of microorganisms occurs in its early stages. Further, we have argued that a preliminary test of this conjecture is feasible with experiments on the Europan surface or ocean, involving evolutionary biosignatures (ion channels). This aspect of the exploration for life in the solar system should be viewed as a complement to the astronomical approach for the search of evidence of the later stages of the evolutionary pathways towards intelligent behaviour. (author)

  7. Langley's CSI evolutionary model: Phase O

    Science.gov (United States)

    Belvin, W. Keith; Elliott, Kenny B.; Horta, Lucas G.; Bailey, Jim P.; Bruner, Anne M.; Sulla, Jeffrey L.; Won, John; Ugoletti, Roberto M.

    1991-01-01

    A testbed for the development of Controls Structures Interaction (CSI) technology to improve space science platform pointing is described. The evolutionary nature of the testbed will permit the study of global line-of-sight pointing in phases 0 and 1, whereas, multipayload pointing systems will be studied beginning with phase 2. The design, capabilities, and typical dynamic behavior of the phase 0 version of the CSI evolutionary model (CEM) is documented for investigator both internal and external to NASA. The model description includes line-of-sight pointing measurement, testbed structure, actuators, sensors, and real time computers, as well as finite element and state space models of major components.

  8. An evolutionary model for protein-coding regions with conserved RNA structure

    DEFF Research Database (Denmark)

    Pedersen, Jakob Skou; Forsberg, Roald; Meyer, Irmtraud Margret

    2004-01-01

    in the RNA structure. The overlap of these fundamental dependencies is sufficient to cause "contagious" context dependencies which cascade across many nucleotide sites. Such large-scale dependencies challenge the use of traditional phylogenetic models in evolutionary inference because they explicitly assume...... components of traditional phylogenetic models. We applied this to a data set of full-genome sequences from the hepatitis C virus where five RNA structures are mapped within the coding region. This allowed us to partition the effects of selection on different structural elements and to test various hypotheses......Here we present a model of nucleotide substitution in protein-coding regions that also encode the formation of conserved RNA structures. In such regions, apparent evolutionary context dependencies exist, both between nucleotides occupying the same codon and between nucleotides forming a base pair...

  9. Evolutionary genetics: the Drosophila model

    Indian Academy of Sciences (India)

    Unknown

    Evolutionary genetics straddles the two fundamental processes of life, ... of the genus Drosophila have been used extensively as model systems in experimental ... issue will prove interesting, informative and thought-provoking for both estab-.

  10. An Evolutionary Model of Spatial Competition

    DEFF Research Database (Denmark)

    Knudsen, Thorbjørn; Winter, Sidney G.

      This paper sets forth an evolutionary model in which diverse businesses, with diverse offerings, compete in a stylized physical space.  When a business firm attempts to expand its activity, so as to profit further from the capabilities it has developed, it necessarily does so in a "new location...... as well in the new environment as they did in the old; the firm may respond with effort to locate appropriate environments or by modification of its routines.  Tradeoffs are presented between the complexity of a business model and its replication costs,  as well as issues involving response....... Randomly generated firm policies are tested first by a local market environment, and then, if success leads the firm to grow spatially, in a gradually expanding environment.  In the initial experiments reported here, we show that the model generates configurations that reflect features of the exogenous...

  11. An evolutionary firefly algorithm for the estimation of nonlinear biological model parameters.

    Directory of Open Access Journals (Sweden)

    Afnizanfaizal Abdullah

    Full Text Available The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.

  12. An evolutionary firefly algorithm for the estimation of nonlinear biological model parameters.

    Science.gov (United States)

    Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N V

    2013-01-01

    The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.

  13. Evolutionary modelling of transitions to sustainable development

    International Nuclear Information System (INIS)

    Safarzynska, K.

    2010-01-01

    This thesis has examined how evolutionary economics can contribute to modelling the micromechanisms that underlie transitions towards sustainable development. In general, transitions are fundamental or structural system changes. They involve, or even require, escaping lock-in of dominant, environmentally unsustainable technologies, introducing major technical or social innovations, and changing prevailing social practices and structures. Due to the complexity of socioeconomic interactions, it is not always possible to identify, and thus target with appropriate policy instruments, causes of specific unsustainable patterns of behaviour. Formal modelling exercises can help improve our understanding of the interaction of various transition mechanisms which are otherwise difficult to grasp intuitively. They allow exploring effects of policy interventions in complex systems. However, existing models of transitions focus on social phenomena and seldom address economic problems. As opposed, mainstream (neoclassical) economic models of technological change do not account for social interactions, and changing heterogeneity of users and their perspectives - even though all of these can influence the direction of innovations and patterns of socio-technological development. Evolutionary economics offers an approach that goes beyond neoclassical economics - in the sense of employing more realistic assumptions regarding the behaviour and heterogeneity of consumers, firms and investors. It can complement current transition models by providing them with a better understanding of associated economic dynamics. In this thesis, formal models were proposed to illustrate the usefulness of a range of evolutionary-economic techniques for modelling transitions. Modelling exercises aimed to explain the core properties of socio-economic systems, such as lock-in, path-dependence, coevolution, group selection and recombinant innovation. The studies collected in this dissertation illustrate that

  14. Evaluation of models generated via hybrid evolutionary algorithms ...

    African Journals Online (AJOL)

    2016-04-02

    Apr 2, 2016 ... Evaluation of models generated via hybrid evolutionary algorithms for the prediction of Microcystis ... evolutionary algorithms (HEA) proved to be highly applica- ble to the hypertrophic reservoirs of South Africa. .... discovered and optimised using a large-scale parallel computational device and relevant soft-.

  15. Software testing for evolutionary iterative rapid prototyping

    OpenAIRE

    Davis, Edward V., Jr.

    1990-01-01

    Approved for public release; distribution unlimited. Rapid prototyping is emerging as a promising software development paradigm. It provides a systematic and automatable means of developing a software system under circumstances where initial requirements are not well known or where requirements change frequently during development. To provide high software quality assurance requires sufficient software testing. The unique nature of evolutionary iterative prototyping is not well-suited for ...

  16. Estimating true evolutionary distances under the DCJ model.

    Science.gov (United States)

    Lin, Yu; Moret, Bernard M E

    2008-07-01

    Modern techniques can yield the ordering and strandedness of genes on each chromosome of a genome; such data already exists for hundreds of organisms. The evolutionary mechanisms through which the set of the genes of an organism is altered and reordered are of great interest to systematists, evolutionary biologists, comparative genomicists and biomedical researchers. Perhaps the most basic concept in this area is that of evolutionary distance between two genomes: under a given model of genomic evolution, how many events most likely took place to account for the difference between the two genomes? We present a method to estimate the true evolutionary distance between two genomes under the 'double-cut-and-join' (DCJ) model of genome rearrangement, a model under which a single multichromosomal operation accounts for all genomic rearrangement events: inversion, transposition, translocation, block interchange and chromosomal fusion and fission. Our method relies on a simple structural characterization of a genome pair and is both analytically and computationally tractable. We provide analytical results to describe the asymptotic behavior of genomes under the DCJ model, as well as experimental results on a wide variety of genome structures to exemplify the very high accuracy (and low variance) of our estimator. Our results provide a tool for accurate phylogenetic reconstruction from multichromosomal gene rearrangement data as well as a theoretical basis for refinements of the DCJ model to account for biological constraints. All of our software is available in source form under GPL at http://lcbb.epfl.ch.

  17. Strengths and Weaknesses of McNamara's Evolutionary Psychological Model of Dreaming

    Directory of Open Access Journals (Sweden)

    Sandra Olliges

    2010-10-01

    Full Text Available This article includes a brief overview of McNamara's (2004 evolutionary model of dreaming. The strengths and weaknesses of this model are then evaluated in terms of its consonance with measurable neurological and biological properties of dreaming, its fit within the tenets of evolutionary theories of dreams, and its alignment with evolutionary concepts of cooperation and spirituality. McNamara's model focuses primarily on dreaming that occurs during rapid eye movement (REM sleep; therefore this article also focuses on REM dreaming.

  18. Preference learning with evolutionary Multivariate Adaptive Regression Spline model

    DEFF Research Database (Denmark)

    Abou-Zleikha, Mohamed; Shaker, Noor; Christensen, Mads Græsbøll

    2015-01-01

    This paper introduces a novel approach for pairwise preference learning through combining an evolutionary method with Multivariate Adaptive Regression Spline (MARS). Collecting users' feedback through pairwise preferences is recommended over other ranking approaches as this method is more appealing...... for function approximation as well as being relatively easy to interpret. MARS models are evolved based on their efficiency in learning pairwise data. The method is tested on two datasets that collectively provide pairwise preference data of five cognitive states expressed by users. The method is analysed...

  19. Testing the cranial evolutionary allometric 'rule' in Galliformes.

    Science.gov (United States)

    Linde-Medina, M

    2016-09-01

    Recent comparative studies have indicated the existence of a common cranial evolutionary allometric (CREA) pattern in mammals and birds, in which smaller species have relatively smaller faces and bigger braincases than larger species. In these studies, cranial allometry was tested using a multivariate regression between shape (described using landmarks coordinates) and size (i.e. centroid size), after accounting for phylogenetic relatedness. Alternatively, cranial allometry can be determined by comparing the sizes of two anatomical parts using a bivariate regression analysis. In this analysis, a slope higher or lower than one indicates the existence of positive or negative allometry, respectively. Thus, in those species that support the CREA 'rule', positive allometry is expected for the association between face size and braincase size, which would indicate that larger species have disproportionally larger faces. In this study, I applied these two approaches to explore cranial allometry in 83 Galliformes (Aves, Galloanserae), ranging in mean body weight from 30 g to 2.5 kg. The multivariate regression between shape and centroid size revealed the existence of a significant allometric pattern resembling CREA, whereas the second analysis revealed a negative allometry for beak size and braincase size (i.e. contrary to the CREA 'rule', larger galliform species have disproportionally shorter beaks than smaller galliform species). This study suggests that the presence of CREA may be overestimated when using cranium size as the standard measurement. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

  20. Post-Test Inspection of Nasa's Evolutionary Xenon Thruster Long Duration Test Hardware: Ion Optics

    Science.gov (United States)

    Soulas, George C.; Shastry, Rohit

    2016-01-01

    A Long Duration Test (LDT) was initiated in June 2005 as a part of NASAs Evolutionary Xenon Thruster (NEXT) service life validation approach. Testing was voluntarily terminated in February 2014, with the thruster accumulating 51,184 hours of operation, processing 918 kg of xenon propellant, and delivering 35.5 MN-s of total impulse. This presentation will present the post-test inspection results to date for the thrusters ion optics.

  1. Testing evolutionary hypotheses for phenotypic divergence using landscape genetics.

    Science.gov (United States)

    Funk, W Chris; Murphy, Melanie A

    2010-02-01

    Understanding the evolutionary causes of phenotypic variation among populations has long been a central theme in evolutionary biology. Several factors can influence phenotypic divergence, including geographic isolation, genetic drift, divergent natural or sexual selection, and phenotypic plasticity. But the relative importance of these factors in generating phenotypic divergence in nature is still a tantalizing and unresolved problem in evolutionary biology. The origin and maintenance of phenotypic divergence is also at the root of many ongoing debates in evolutionary biology, such as the extent to which gene flow constrains adaptive divergence (Garant et al. 2007) and the relative importance of genetic drift, natural selection, and sexual selection in initiating reproductive isolation and speciation (Coyne & Orr 2004). In this issue, Wang & Summers (2010) test the causes of one of the most fantastic examples of phenotypic divergence in nature: colour pattern divergence among populations of the strawberry poison frog (Dendrobates pumilio) in Panama and Costa Rica (Fig. 1). This study provides a beautiful example of the use of the emerging field of landscape genetics to differentiate among hypotheses for phenotypic divergence. Using landscape genetic analyses, Wang & Summers were able to reject the hypotheses that colour pattern divergence is due to isolation-by-distance (IBD) or landscape resistance. Instead, the hypothesis left standing is that colour divergence is due to divergent selection, in turn driving reproductive isolation among populations with different colour morphs. More generally, this study provides a wonderful example of how the emerging field of landscape genetics, which has primarily been applied to questions in conservation and ecology, now plays an essential role in evolutionary research.

  2. Individual-based modeling of ecological and evolutionary processes

    Science.gov (United States)

    DeAngelis, Donald L.; Mooij, Wolf M.

    2005-01-01

    Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential-equation and difference-equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis for IBMs by describing five major types of individual variation in IBMs: spatial, ontogenetic, phenotypic, cognitive, and genetic. IBMs are now used in almost all subfields of ecology and evolutionary biology. We map those subfields and look more closely at selected key papers on fish recruitment, forest dynamics, sympatric speciation, metapopulation dynamics, maintenance of diversity, and species conservation. Theorists are currently divided on whether IBMs represent only a practical tool for extending classical theory to more complex situations, or whether individual-based theory represents a radically new research program. We feel that the tension between these two poles of thinking can be a source of creativity in ecology and evolutionary theory.

  3. More efficient evolutionary strategies for model calibration with watershed model for demonstration

    Science.gov (United States)

    Baggett, J. S.; Skahill, B. E.

    2008-12-01

    Evolutionary strategies allow automatic calibration of more complex models than traditional gradient based approaches, but they are more computationally intensive. We present several efficiency enhancements for evolution strategies, many of which are not new, but when combined have been shown to dramatically decrease the number of model runs required for calibration of synthetic problems. To reduce the number of expensive model runs we employ a surrogate objective function for an adaptively determined fraction of the population at each generation (Kern et al., 2006). We demonstrate improvements to the adaptive ranking strategy that increase its efficiency while sacrificing little reliability and further reduce the number of model runs required in densely sampled parts of parameter space. Furthermore, we include a gradient individual in each generation that is usually not selected when the search is in a global phase or when the derivatives are poorly approximated, but when selected near a smooth local minimum can dramatically increase convergence speed (Tahk et al., 2007). Finally, the selection of the gradient individual is used to adapt the size of the population near local minima. We show, by incorporating these enhancements into the Covariance Matrix Adaption Evolution Strategy (CMAES; Hansen, 2006), that their synergetic effect is greater than their individual parts. This hybrid evolutionary strategy exploits smooth structure when it is present but degrades to an ordinary evolutionary strategy, at worst, if smoothness is not present. Calibration of 2D-3D synthetic models with the modified CMAES requires approximately 10%-25% of the model runs of ordinary CMAES. Preliminary demonstration of this hybrid strategy will be shown for watershed model calibration problems. Hansen, N. (2006). The CMA Evolution Strategy: A Comparing Review. In J.A. Lozano, P. Larrañga, I. Inza and E. Bengoetxea (Eds.). Towards a new evolutionary computation. Advances in estimation of

  4. Prediction of stock markets by the evolutionary mix-game model

    Science.gov (United States)

    Chen, Fang; Gou, Chengling; Guo, Xiaoqian; Gao, Jieping

    2008-06-01

    This paper presents the efforts of using the evolutionary mix-game model, which is a modified form of the agent-based mix-game model, to predict financial time series. Here, we have carried out three methods to improve the original mix-game model by adding the abilities of strategy evolution to agents, and then applying the new model referred to as the evolutionary mix-game model to forecast the Shanghai Stock Exchange Composite Index. The results show that these modifications can improve the accuracy of prediction greatly when proper parameters are chosen.

  5. An evolutionary framework for association testing in resequencing studies.

    Directory of Open Access Journals (Sweden)

    C Ryan King

    2010-11-01

    Full Text Available Sequencing technologies are becoming cheap enough to apply to large numbers of study participants and promise to provide new insights into human phenotypes by bringing to light rare and previously unknown genetic variants. We develop a new framework for the analysis of sequence data that incorporates all of the major features of previously proposed approaches, including those focused on allele counts and allele burden, but is both more general and more powerful. We harness population genetic theory to provide prior information on effect sizes and to create a pooling strategy for information from rare variants. Our method, EMMPAT (Evolutionary Mixed Model for Pooled Association Testing, generates a single test per gene (substantially reducing multiple testing concerns, facilitates graphical summaries, and improves the interpretation of results by allowing calculation of attributable variance. Simulations show that, relative to previously used approaches, our method increases the power to detect genes that affect phenotype when natural selection has kept alleles with large effect sizes rare. We demonstrate our approach on a population-based re-sequencing study of association between serum triglycerides and variation in ANGPTL4.

  6. Hidden long evolutionary memory in a model biochemical network

    Science.gov (United States)

    Ali, Md. Zulfikar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

    2018-04-01

    We introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm, and apply the model to study neutral drift in networks that yield oscillatory dynamics. Starting with a functional core module, random evolutionary drift increases network complexity even in the absence of specific selective pressures. Surprisingly, we uncover a hidden order in sequence space that gives rise to long-term evolutionary memory, implying strong constraints on network evolution due to the topology of accessible sequence space.

  7. Yunnan-III models for evolutionary population synthesis

    Science.gov (United States)

    Zhang, F.; Li, L.; Han, Z.; Zhuang, Y.; Kang, X.

    2013-02-01

    We build the Yunnan-III evolutionary population synthesis (EPS) models by using the mesa stellar evolution code, BaSeL stellar spectra library and the initial mass functions (IMFs) of Kroupa and Salpeter, and present colours and integrated spectral energy distributions (ISEDs) of solar-metallicity stellar populations (SPs) in the range of 1 Myr to 15 Gyr. The main characteristic of the Yunnan-III EPS models is the usage of a set of self-consistent solar-metallicity stellar evolutionary tracks (the masses of stars are from 0.1 to 100 M⊙). This set of tracks is obtained by using the state-of-the-art mesa code. mesa code can evolve stellar models through thermally pulsing asymptotic giant branch (TP-AGB) phase for low- and intermediate-mass stars. By comparisons, we confirm that the inclusion of TP-AGB stars makes the V - K, V - J and V - R colours of SPs redder and the infrared flux larger at ages log(t/yr) ≳ 7.6 [the differences reach the maximum at log(t/yr) ˜ 8.6, ˜0.5-0.2 mag for colours, approximately two times for K-band flux]. We also find that the colour-evolution trends of Model with-TPAGB at intermediate and large ages are similar to those from the starburst99 code, which employs the Padova-AGB stellar library, BaSeL spectral library and the Kroupa IMF. At last, we compare the colours with the other EPS models comprising TP-AGB stars (such as CB07, M05, V10 and POPSTAR), and find that the B - V colour agrees with each other but the V-K colour shows a larger discrepancy among these EPS models [˜1 mag when 8 ≲ log(t/yr) ≲ 9]. The stellar evolutionary tracks, isochrones, colours and ISEDs can be obtained on request from the first author or from our website (http://www1.ynao.ac.cn/~zhangfh/). Using the isochrones, you can build your EPS models. Now the format of stellar evolutionary tracks is the same as that in the starburst99 code; you can put them into the starburst99 code and get the SP's results. Moreover, the colours involving other passbands

  8. Evolutionary model of an anonymous consumer durable market

    Science.gov (United States)

    Kaldasch, Joachim

    2011-07-01

    An analytic model is presented that considers the evolution of a market of durable goods. The model suggests that after introduction goods spread always according to a Bass diffusion. However, this phase will be followed by a diffusion process for durable consumer goods governed by a variation-selection-reproduction mechanism and the growth dynamics can be described by a replicator equation. The theory suggests that products play the role of species in biological evolutionary models. It implies that the evolution of man-made products can be arranged into an evolutionary tree. The model suggests that each product can be characterized by its product fitness. The fitness space contains elements of both sites of the market, supply and demand. The unit sales of products with a higher product fitness compared to the mean fitness increase. Durables with a constant fitness advantage replace other goods according to a logistic law. The model predicts in particular that the mean price exhibits an exponential decrease over a long time period for durable goods. The evolutionary diffusion process is directly related to this price decline and is governed by Gompertz equation. Therefore it is denoted as Gompertz diffusion. Describing the aggregate sales as the sum of first, multiple and replacement purchase the product life cycle can be derived. Replacement purchase causes periodic variations of the sales determined by the finite lifetime of the good (Juglar cycles). The model suggests that both, Bass- and Gompertz diffusion may contribute to the product life cycle of a consumer durable. The theory contains the standard equilibrium view of a market as a special case. It depends on the time scale, whether an equilibrium or evolutionary description is more appropriate. The evolutionary framework is used to derive also the size, growth rate and price distribution of manufacturing business units. It predicts that the size distribution of the business units (products) is lognormal

  9. Computational Modeling of Teaching and Learning through Application of Evolutionary Algorithms

    Directory of Open Access Journals (Sweden)

    Richard Lamb

    2015-09-01

    Full Text Available Within the mind, there are a myriad of ideas that make sense within the bounds of everyday experience, but are not reflective of how the world actually exists; this is particularly true in the domain of science. Classroom learning with teacher explanation are a bridge through which these naive understandings can be brought in line with scientific reality. The purpose of this paper is to examine how the application of a Multiobjective Evolutionary Algorithm (MOEA can work in concert with an existing computational-model to effectively model critical-thinking in the science classroom. An evolutionary algorithm is an algorithm that iteratively optimizes machine learning based computational models. The research question is, does the application of an evolutionary algorithm provide a means to optimize the Student Task and Cognition Model (STAC-M and does the optimized model sufficiently represent and predict teaching and learning outcomes in the science classroom? Within this computational study, the authors outline and simulate the effect of teaching on the ability of a “virtual” student to solve a Piagetian task. Using the Student Task and Cognition Model (STAC-M a computational model of student cognitive processing in science class developed in 2013, the authors complete a computational experiment which examines the role of cognitive retraining on student learning. Comparison of the STAC-M and the STAC-M with inclusion of the Multiobjective Evolutionary Algorithm shows greater success in solving the Piagetian science-tasks post cognitive retraining with the Multiobjective Evolutionary Algorithm. This illustrates the potential uses of cognitive and neuropsychological computational modeling in educational research. The authors also outline the limitations and assumptions of computational modeling.

  10. Individual-based modeling of ecological and evolutionary processes

    NARCIS (Netherlands)

    DeAngelis, D.L.; Mooij, W.M.

    2005-01-01

    Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential and difference equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis

  11. Mouse Models as Predictors of Human Responses: Evolutionary Medicine.

    Science.gov (United States)

    Uhl, Elizabeth W; Warner, Natalie J

    Mice offer a number of advantages and are extensively used to model human diseases and drug responses. Selective breeding and genetic manipulation of mice have made many different genotypes and phenotypes available for research. However, in many cases, mouse models have failed to be predictive. Important sources of the prediction problem have been the failure to consider the evolutionary basis for species differences, especially in drug metabolism, and disease definitions that do not reflect the complexity of gene expression underlying disease phenotypes. Incorporating evolutionary insights into mouse models allow for unique opportunities to characterize the effects of diet, different gene expression profiles, and microbiomics underlying human drug responses and disease phenotypes.

  12. Evolutionary model of the growth and size of firms

    Science.gov (United States)

    Kaldasch, Joachim

    2012-07-01

    The key idea of this model is that firms are the result of an evolutionary process. Based on demand and supply considerations the evolutionary model presented here derives explicitly Gibrat's law of proportionate effects as the result of the competition between products. Applying a preferential attachment mechanism for firms, the theory allows to establish the size distribution of products and firms. Also established are the growth rate and price distribution of consumer goods. Taking into account the characteristic property of human activities to occur in bursts, the model allows also an explanation of the size-variance relationship of the growth rate distribution of products and firms. Further the product life cycle, the learning (experience) curve and the market size in terms of the mean number of firms that can survive in a market are derived. The model also suggests the existence of an invariant of a market as the ratio of total profit to total revenue. The relationship between a neo-classic and an evolutionary view of a market is discussed. The comparison with empirical investigations suggests that the theory is able to describe the main stylized facts concerning the size and growth of firms.

  13. On the validity of evolutionary models with site-specific parameters.

    Directory of Open Access Journals (Sweden)

    Konrad Scheffler

    Full Text Available Evolutionary models that make use of site-specific parameters have recently been criticized on the grounds that parameter estimates obtained under such models can be unreliable and lack theoretical guarantees of convergence. We present a simulation study providing empirical evidence that a simple version of the models in question does exhibit sensible convergence behavior and that additional taxa, despite not being independent of each other, lead to improved parameter estimates. Although it would be desirable to have theoretical guarantees of this, we argue that such guarantees would not be sufficient to justify the use of these models in practice. Instead, we emphasize the importance of taking the variance of parameter estimates into account rather than blindly trusting point estimates - this is standardly done by using the models to construct statistical hypothesis tests, which are then validated empirically via simulation studies.

  14. A dynamic parking charge optimal control model under perspective of commuters' evolutionary game behavior

    Science.gov (United States)

    Lin, XuXun; Yuan, PengCheng

    2018-01-01

    In this research we consider commuters' dynamic learning effect by modeling the trip mode choice behavior from a new perspective of dynamic evolutionary game theory. We explore the behavior pattern of different types of commuters and study the evolution path and equilibrium properties under different traffic conditions. We further establish a dynamic parking charge optimal control (referred to as DPCOC) model to alter commuters' trip mode choice while minimizing the total social cost. Numerical tests show. (1) Under fixed parking fee policy, the evolutionary results are completely decided by the travel time and the only method for public transit induction is to increase the parking charge price. (2) Compared with fixed parking fee policy, DPCOC policy proposed in this research has several advantages. Firstly, it can effectively turn the evolutionary path and evolutionary stable strategy to a better situation while minimizing the total social cost. Secondly, it can reduce the sensitivity of trip mode choice behavior to traffic congestion and improve the ability to resist interferences and emergencies. Thirdly, it is able to control the private car proportion to a stable state and make the trip behavior more predictable for the transportation management department. The research results can provide theoretical basis and decision-making references for commuters' mode choice prediction, dynamic setting of urban parking charge prices and public transit induction.

  15. Context dependent DNA evolutionary models

    DEFF Research Database (Denmark)

    Jensen, Jens Ledet

    This paper is about stochastic models for the evolution of DNA. For a set of aligned DNA sequences, connected in a phylogenetic tree, the models should be able to explain - in probabilistic terms - the differences seen in the sequences. From the estimates of the parameters in the model one can...... start to make biologically interpretations and conclusions concerning the evolutionary forces at work. In parallel with the increase in computing power, models have become more complex. Starting with Markov processes on a space with 4 states, and extended to Markov processes with 64 states, we are today...... studying models on spaces with 4n (or 64n) number of states with n well above one hundred, say. For such models it is no longer possible to calculate the transition probability analytically, and often Markov chain Monte Carlo is used in connection with likelihood analysis. This is also the approach taken...

  16. Genome-wide investigation reveals high evolutionary rates in annual model plants.

    Science.gov (United States)

    Yue, Jia-Xing; Li, Jinpeng; Wang, Dan; Araki, Hitoshi; Tian, Dacheng; Yang, Sihai

    2010-11-09

    Rates of molecular evolution vary widely among species. While significant deviations from molecular clock have been found in many taxa, effects of life histories on molecular evolution are not fully understood. In plants, annual/perennial life history traits have long been suspected to influence the evolutionary rates at the molecular level. To date, however, the number of genes investigated on this subject is limited and the conclusions are mixed. To evaluate the possible heterogeneity in evolutionary rates between annual and perennial plants at the genomic level, we investigated 85 nuclear housekeeping genes, 10 non-housekeeping families, and 34 chloroplast genes using the genomic data from model plants including Arabidopsis thaliana and Medicago truncatula for annuals and grape (Vitis vinifera) and popular (Populus trichocarpa) for perennials. According to the cross-comparisons among the four species, 74-82% of the nuclear genes and 71-97% of the chloroplast genes suggested higher rates of molecular evolution in the two annuals than those in the two perennials. The significant heterogeneity in evolutionary rate between annuals and perennials was consistently found both in nonsynonymous sites and synonymous sites. While a linear correlation of evolutionary rates in orthologous genes between species was observed in nonsynonymous sites, the correlation was weak or invisible in synonymous sites. This tendency was clearer in nuclear genes than in chloroplast genes, in which the overall evolutionary rate was small. The slope of the regression line was consistently lower than unity, further confirming the higher evolutionary rate in annuals at the genomic level. The higher evolutionary rate in annuals than in perennials appears to be a universal phenomenon both in nuclear and chloroplast genomes in the four dicot model plants we investigated. Therefore, such heterogeneity in evolutionary rate should result from factors that have genome-wide influence, most likely those

  17. Cash Management Policies By Evolutionary Models: A Comparison Using The MILLER-ORR Model

    Directory of Open Access Journals (Sweden)

    Marcelo Botelho da Costa Moraes

    2013-10-01

    Full Text Available This work aims to apply genetic algorithms (GA and particle swarm optimization (PSO to managing cash balance, comparing performance results between computational models and the Miller-Orr model. Thus, the paper proposes the application of computational evolutionary models to minimize the total cost of cash balance maintenance, obtaining the parameters for a cash management policy, using assumptions presented in the literature, considering the cost of maintenance and opportunity for cost of cash. For such, we developed computational experiments from cash flows simulated to implement the algorithms. For a control purpose, an algorithm has been developed that uses the Miller-Orr model defining the lower bound parameter, which is not obtained by the original model. The results indicate that evolutionary algorithms present better results than the Miller-Orr model, with prevalence for PSO algorithm in results.

  18. Can evolutionary convergence be tested on Europa?

    Energy Technology Data Exchange (ETDEWEB)

    Chela-Flores, Julian [Instituto de Estudios Avanzados, Caracas (Venezuela); [Abdus Salam International Centre for Theoretical Physics, Trieste (Italy)]. E-mail: chelaf@ictp.trieste.it

    2002-09-01

    A major objective in solar system exploration has to be the insertion of appropriate biology-oriented experiments in future missions. We discuss various reasons for suggesting that this type of research be considered a high priority for feasibility studies and, subsequently, for technological development of appropriate melters and submersibles. With the assumption that Darwin's theory is valid for the evolution of life anywhere in the universe, various degrees of convergent phenomena argue in favor of the conjecture that universal evolution of intelligent behavior is just a matter of time and preservation of steady planetary conditions. A preliminary test of this conjecture is feasible with experiments involving evolutionary biosignatures on Europa. (author)

  19. A new ARMAX model based on evolutionary algorithm and particle swarm optimization for short-term load forecasting

    International Nuclear Information System (INIS)

    Wang, Bo; Tai, Neng-ling; Zhai, Hai-qing; Ye, Jian; Zhu, Jia-dong; Qi, Liang-bo

    2008-01-01

    In this paper, a new ARMAX model based on evolutionary algorithm and particle swarm optimization for short-term load forecasting is proposed. Auto-regressive (AR) and moving average (MA) with exogenous variables (ARMAX) has been widely applied in the load forecasting area. Because of the nonlinear characteristics of the power system loads, the forecasting function has many local optimal points. The traditional method based on gradient searching may be trapped in local optimal points and lead to high error. While, the hybrid method based on evolutionary algorithm and particle swarm optimization can solve this problem more efficiently than the traditional ways. It takes advantage of evolutionary strategy to speed up the convergence of particle swarm optimization (PSO), and applies the crossover operation of genetic algorithm to enhance the global search ability. The new ARMAX model for short-term load forecasting has been tested based on the load data of Eastern China location market, and the results indicate that the proposed approach has achieved good accuracy. (author)

  20. Economic modeling using evolutionary algorithms : the effect of binary encoding of strategies

    NARCIS (Netherlands)

    Waltman, L.R.; Eck, van N.J.; Dekker, Rommert; Kaymak, U.

    2011-01-01

    We are concerned with evolutionary algorithms that are employed for economic modeling purposes. We focus in particular on evolutionary algorithms that use a binary encoding of strategies. These algorithms, commonly referred to as genetic algorithms, are popular in agent-based computational economics

  1. Asteroseismology of pulsating DA white dwarfs with fully evolutionary models

    Directory of Open Access Journals (Sweden)

    Althaus L.G.

    2013-03-01

    Full Text Available We present a new approach for asteroseismology of DA white dwarfs that consists in the employment of a large set of non-static, physically sound, fully evolutionary models representative of these stars. We already have applied this approach with success to pulsating PG1159 stars (GW Vir variables. Our white dwarf models, which cover a wide range of stellar masses, effective temperatures, and envelope thicknesses, are the result of fully evolutionary computations that take into account the complete history of the progenitor stars from the ZAMS. In particular, the models are characterized by self-consistent chemical structures from the centre to the surface, a crucial aspect of white dwarf asteroseismology. We apply this approach to an ensemble of 44 bright DAV (ZZ Ceti stars.

  2. Measuring fit of sequence data to phylogenetic model: gain of power using marginal tests.

    Science.gov (United States)

    Waddell, Peter J; Ota, Rissa; Penny, David

    2009-10-01

    Testing fit of data to model is fundamentally important to any science, but publications in the field of phylogenetics rarely do this. Such analyses discard fundamental aspects of science as prescribed by Karl Popper. Indeed, not without cause, Popper (Unended quest: an intellectual autobiography. Fontana, London, 1976) once argued that evolutionary biology was unscientific as its hypotheses were untestable. Here we trace developments in assessing fit from Penny et al. (Nature 297:197-200, 1982) to the present. We compare the general log-likelihood ratio (the G or G (2) statistic) statistic between the evolutionary tree model and the multinomial model with that of marginalized tests applied to an alignment (using placental mammal coding sequence data). It is seen that the most general test does not reject the fit of data to model (P approximately 0.5), but the marginalized tests do. Tests on pairwise frequency (F) matrices, strongly (P < 0.001) reject the most general phylogenetic (GTR) models commonly in use. It is also clear (P < 0.01) that the sequences are not stationary in their nucleotide composition. Deviations from stationarity and homogeneity seem to be unevenly distributed amongst taxa; not necessarily those expected from examining other regions of the genome. By marginalizing the 4( t ) patterns of the i.i.d. model to observed and expected parsimony counts, that is, from constant sites, to singletons, to parsimony informative characters of a minimum possible length, then the likelihood ratio test regains power, and it too rejects the evolutionary model with P < 0.001. Given such behavior over relatively recent evolutionary time, readers in general should maintain a healthy skepticism of results, as the scale of the systematic errors in published trees may really be far larger than the analytical methods (e.g., bootstrap) report.

  3. Building v/s Exploring Models: Comparing Learning of Evolutionary Processes through Agent-based Modeling

    Science.gov (United States)

    Wagh, Aditi

    Two strands of work motivate the three studies in this dissertation. Evolutionary change can be viewed as a computational complex system in which a small set of rules operating at the individual level result in different population level outcomes under different conditions. Extensive research has documented students' difficulties with learning about evolutionary change (Rosengren et al., 2012), particularly in terms of levels slippage (Wilensky & Resnick, 1999). Second, though building and using computational models is becoming increasingly common in K-12 science education, we know little about how these two modalities compare. This dissertation adopts agent-based modeling as a representational system to compare these modalities in the conceptual context of micro-evolutionary processes. Drawing on interviews, Study 1 examines middle-school students' productive ways of reasoning about micro-evolutionary processes to find that the specific framing of traits plays a key role in whether slippage explanations are cued. Study 2, which was conducted in 2 schools with about 150 students, forms the crux of the dissertation. It compares learning processes and outcomes when students build their own models or explore a pre-built model. Analysis of Camtasia videos of student pairs reveals that builders' and explorers' ways of accessing rules, and sense-making of observed trends are of a different character. Builders notice rules through available blocks-based primitives, often bypassing their enactment while explorers attend to rules primarily through the enactment. Moreover, builders' sense-making of observed trends is more rule-driven while explorers' is more enactment-driven. Pre and posttests reveal that builders manifest a greater facility with accessing rules, providing explanations manifesting targeted assembly. Explorers use rules to construct explanations manifesting non-targeted assembly. Interviews reveal varying degrees of shifts away from slippage in both

  4. Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games

    Science.gov (United States)

    Peña, Jorge; Rochat, Yannick

    2012-01-01

    By combining evolutionary game theory and graph theory, “games on graphs” study the evolutionary dynamics of frequency-dependent selection in population structures modeled as geographical or social networks. Networks are usually represented by means of unipartite graphs, and social interactions by two-person games such as the famous prisoner’s dilemma. Unipartite graphs have also been used for modeling interactions going beyond pairwise interactions. In this paper, we argue that bipartite graphs are a better alternative to unipartite graphs for describing population structures in evolutionary multiplayer games. To illustrate this point, we make use of bipartite graphs to investigate, by means of computer simulations, the evolution of cooperation under the conventional and the distributed N-person prisoner’s dilemma. We show that several implicit assumptions arising from the standard approach based on unipartite graphs (such as the definition of replacement neighborhoods, the intertwining of individual and group diversity, and the large overlap of interaction neighborhoods) can have a large impact on the resulting evolutionary dynamics. Our work provides a clear example of the importance of construction procedures in games on graphs, of the suitability of bigraphs and hypergraphs for computational modeling, and of the importance of concepts from social network analysis such as centrality, centralization and bipartite clustering for the understanding of dynamical processes occurring on networked population structures. PMID:22970237

  5. The environmental zero-point problem in evolutionary reaction norm modeling.

    Science.gov (United States)

    Ergon, Rolf

    2018-04-01

    There is a potential problem in present quantitative genetics evolutionary modeling based on reaction norms. Such models are state-space models, where the multivariate breeder's equation in some form is used as the state equation that propagates the population state forward in time. These models use the implicit assumption of a constant reference environment, in many cases set to zero. This zero-point is often the environment a population is adapted to, that is, where the expected geometric mean fitness is maximized. Such environmental reference values follow from the state of the population system, and they are thus population properties. The environment the population is adapted to, is, in other words, an internal population property, independent of the external environment. It is only when the external environment coincides with the internal reference environment, or vice versa, that the population is adapted to the current environment. This is formally a result of state-space modeling theory, which is an important theoretical basis for evolutionary modeling. The potential zero-point problem is present in all types of reaction norm models, parametrized as well as function-valued, and the problem does not disappear when the reference environment is set to zero. As the environmental reference values are population characteristics, they ought to be modeled as such. Whether such characteristics are evolvable is an open question, but considering the complexity of evolutionary processes, such evolvability cannot be excluded without good arguments. As a straightforward solution, I propose to model the reference values as evolvable mean traits in their own right, in addition to other reaction norm traits. However, solutions based on an evolvable G matrix are also possible.

  6. An Evolutionary Cascade Model for Sauropod Dinosaur Gigantism - Overview, Update and Tests

    OpenAIRE

    Sander, P. Martin

    2013-01-01

    Sauropod dinosaurs are a group of herbivorous dinosaurs which exceeded all other terrestrial vertebrates in mean and maximal body size. Sauropod dinosaurs were also the most successful and long-lived herbivorous tetrapod clade, but no abiological factors such as global environmental parameters conducive to their gigantism can be identified. These facts justify major efforts by evolutionary biologists and paleontologists to understand sauropods as living animals and to explain their evolutiona...

  7. Evolutionary molecular medicine.

    Science.gov (United States)

    Nesse, Randolph M; Ganten, Detlev; Gregory, T Ryan; Omenn, Gilbert S

    2012-05-01

    Evolution has long provided a foundation for population genetics, but some major advances in evolutionary biology from the twentieth century that provide foundations for evolutionary medicine are only now being applied in molecular medicine. They include the need for both proximate and evolutionary explanations, kin selection, evolutionary models for cooperation, competition between alleles, co-evolution, and new strategies for tracing phylogenies and identifying signals of selection. Recent advances in genomics are transforming evolutionary biology in ways that create even more opportunities for progress at its interfaces with genetics, medicine, and public health. This article reviews 15 evolutionary principles and their applications in molecular medicine in hopes that readers will use them and related principles to speed the development of evolutionary molecular medicine.

  8. Evolutionary modelling of the macro-economic impacts of catastrophic flood events

    NARCIS (Netherlands)

    Safarzynska, K.E.; Brouwer, R.; Hofkes, M.

    2013-01-01

    This paper examines the possible contribution of evolutionary economics to macro-economic modelling of flood impacts to provide guidance for future economic risk modelling. Most macro-economic models start from a neoclassical economic perspective and focus on equilibrium outcomes, either in a static

  9. Radiation, ecology and the invalid LNT model: the evolutionary imperative.

    Science.gov (United States)

    Parsons, Peter A

    2006-09-27

    Metabolic and energetic efficiency, and hence fitness of organisms to survive, should be maximal in their habitats. This tenet of evolutionary biology invalidates the linear-no threshold (LNT) model for the risk consequences of environmental agents. Hormesis in response to selection for maximum metabolic and energetic efficiency, or minimum metabolic imbalance, to adapt to a stressed world dominated by oxidative stress should therefore be universal. Radiation hormetic zones extending substantially beyond common background levels, can be explained by metabolic interactions among multiple abiotic stresses. Demographic and experimental data are mainly in accord with this expectation. Therefore, non-linearity becomes the primary model for assessing risks from low-dose ionizing radiation. This is the evolutionary imperative upon which risk assessment for radiation should be based.

  10. Dynamic and photometric evolutionary models of tidal tails and ripples

    International Nuclear Information System (INIS)

    Wallin, J.F.

    1989-01-01

    An investigation into the causes of star formation in tidal tails has been conducted using a restricted three-body dynamical model in conjunction with a broad-band photometric evolutionary code. In these models, regions of compression form inside the disk and along the tidal tail and tidal bridge. The effects these density changes have on the colors of the tidal features are examined with a broad-band photometric evolutionary code. A spiral galaxy population is synthesized and the effects of modest changes in the star formation rate are explored. Limits on the density changes needed to make detectable changes in the colors are calculated using a Schmidt (1959) law. These models suggest that the blue colors and knotty features observed in the tidal features of some galaxies result from increased rates of star formation induced by tidally produced density increases. Limitations of this model are discussed along with photometric evolutionary models based on the density evolution in the tails. The Lynds and Toomre (1976) interpretation of ring galaxies as the natural result of a nearly head-on collision between a disk galaxy and a companion galaxy has become widely accepted. Similarly, Quinn's (1984) interpretation of the shells in elliptical galaxies as the aftermath of the cannibalization of a low-mass companion has been quite successful in accounting for the observations. Restricted three-body calculations of high inclination, low impact parameter encounters demonstrate that the shell-like ripples observed in a number of disk galaxies can also be produced as collisional artifacts from internal oscillations much as in ring galaxies

  11. Form of an evolutionary tradeoff affects eco-evolutionary dynamics in a predator-prey system.

    Science.gov (United States)

    Kasada, Minoru; Yamamichi, Masato; Yoshida, Takehito

    2014-11-11

    Evolution on a time scale similar to ecological dynamics has been increasingly recognized for the last three decades. Selection mediated by ecological interactions can change heritable phenotypic variation (i.e., evolution), and evolution of traits, in turn, can affect ecological interactions. Hence, ecological and evolutionary dynamics can be tightly linked and important to predict future dynamics, but our understanding of eco-evolutionary dynamics is still in its infancy and there is a significant gap between theoretical predictions and empirical tests. Empirical studies have demonstrated that the presence of genetic variation can dramatically change ecological dynamics, whereas theoretical studies predict that eco-evolutionary dynamics depend on the details of the genetic variation, such as the form of a tradeoff among genotypes, which can be more important than the presence or absence of the genetic variation. Using a predator-prey (rotifer-algal) experimental system in laboratory microcosms, we studied how different forms of a tradeoff between prey defense and growth affect eco-evolutionary dynamics. Our experimental results show for the first time to our knowledge that different forms of the tradeoff produce remarkably divergent eco-evolutionary dynamics, including near fixation, near extinction, and coexistence of algal genotypes, with quantitatively different population dynamics. A mathematical model, parameterized from completely independent experiments, explains the observed dynamics. The results suggest that knowing the details of heritable trait variation and covariation within a population is essential for understanding how evolution and ecology will interact and what form of eco-evolutionary dynamics will result.

  12. Testing evolutionary theories of discriminative grandparental investment.

    Science.gov (United States)

    Kaptijn, Ralf; Thomese, Fleur; Liefbroer, Aart C; Silverstein, Merril

    2013-05-01

    This study tests two evolutionary hypotheses on grandparental investments differentiated by the child's sex: the paternity uncertainty hypothesis and the Trivers-Willard hypothesis. Data are from two culturally different countries: the Dutch Longitudinal Aging Study Amsterdam (n=2375) and the Chinese Anhui Survey (n=4026). In the Netherlands, grandparental investments are biased towards daughters' children, which is in accordance with the paternity uncertainty hypothesis. But in China, grandparental investments are biased towards sons' children, which is in conflict with the paternity uncertainty hypothesis. This study found no support for the Trivers-Willard hypothesis. These results raise doubts over the relevance of paternity uncertainty as an explanation of a grandparental investment bias towards daughters' children that is often found in Western populations. The results suggest that discriminative grandparental investments are better understood as the outcome of cultural prescriptions and economic motives.

  13. Aggregate meta-models for evolutionary multiobjective and many-objective optimization

    Czech Academy of Sciences Publication Activity Database

    Pilát, Martin; Neruda, Roman

    Roč. 116, 20 September (2013), s. 392-402 ISSN 0925-2312 R&D Projects: GA ČR GAP202/11/1368 Institutional support: RVO:67985807 Keywords : evolutionary algorithms * multiobjective optimization * many-objective optimization * surrogate models * meta-models * memetic algorithm Subject RIV: IN - Informatics, Computer Science Impact factor: 2.005, year: 2013

  14. Linear and evolutionary polynomial regression models to forecast coastal dynamics: Comparison and reliability assessment

    Science.gov (United States)

    Bruno, Delia Evelina; Barca, Emanuele; Goncalves, Rodrigo Mikosz; de Araujo Queiroz, Heithor Alexandre; Berardi, Luigi; Passarella, Giuseppe

    2018-01-01

    In this paper, the Evolutionary Polynomial Regression data modelling strategy has been applied to study small scale, short-term coastal morphodynamics, given its capability for treating a wide database of known information, non-linearly. Simple linear and multilinear regression models were also applied to achieve a balance between the computational load and reliability of estimations of the three models. In fact, even though it is easy to imagine that the more complex the model, the more the prediction improves, sometimes a "slight" worsening of estimations can be accepted in exchange for the time saved in data organization and computational load. The models' outcomes were validated through a detailed statistical, error analysis, which revealed a slightly better estimation of the polynomial model with respect to the multilinear model, as expected. On the other hand, even though the data organization was identical for the two models, the multilinear one required a simpler simulation setting and a faster run time. Finally, the most reliable evolutionary polynomial regression model was used in order to make some conjecture about the uncertainty increase with the extension of extrapolation time of the estimation. The overlapping rate between the confidence band of the mean of the known coast position and the prediction band of the estimated position can be a good index of the weakness in producing reliable estimations when the extrapolation time increases too much. The proposed models and tests have been applied to a coastal sector located nearby Torre Colimena in the Apulia region, south Italy.

  15. A Self-adaptive Dynamic Evaluation Model for Diabetes Mellitus, Based on Evolutionary Strategies

    Directory of Open Access Journals (Sweden)

    An-Jiang Lu

    2016-03-01

    Full Text Available In order to evaluate diabetes mellitus objectively and accurately, this paper builds a self-adaptive dynamic evaluation model for diabetes mellitus, based on evolutionary strategies. First of all, on the basis of a formalized description of the evolutionary process of diabetes syndromes, using a state transition function, it judges whether a disease is evolutionary, through an excitation parameter. It then, provides evidence for the rebuilding of the evaluation index system. After that, by abstracting and rebuilding the composition of evaluation indexes, it makes use of a heuristic algorithm to determine the composition of the evolved evaluation index set of diabetes mellitus, It then, calculates the weight of each index in the evolved evaluation index set of diabetes mellitus by building a dependency matrix and realizes the self-adaptive dynamic evaluation of diabetes mellitus under an evolutionary environment. Using this evaluation model, it is possible to, quantify all kinds of diagnoses and treatment experiences of diabetes and finally to adopt ideal diagnoses and treatment measures for different patients with diabetics.

  16. Direct Test of the Brown Dwarf Evolutionary Models Through Secondary Eclipse Spectroscopy of LHS 6343

    Science.gov (United States)

    Albert, Loic

    2015-10-01

    As the number of field Brown Dwarfs counts in the thousands, interpreting their physical parameters (mass, temperature, radius, luminosity, age, metallicity) relies as heavily as ever on atmosphere and evolutionary models. Fortunately, models are largely successful in explaining observations (colors, spectral types, luminosity), so they appear well calibrated in a relative sense. However, an absolute model-independent calibration is still lacking. Eclipsing BDs systems are a unique laboratory in this respect but until recently only one such system was known, 2M0535-05 - a very young (1 Gyr) - was identified (62.1+/-1.2 MJup, 0.783+/-0.011 RJup) transiting LHS6343 with a 12.7-day period. We propose to use WFC3 in drift scan mode and 5 HST orbits to determine the spectral type (a proxy for temperature) as well as the near-infrared luminosity of this brown dwarf. We conducted simulations that predict a signal-to-noise ratio ranging between 10 and 30 per resolution element in the peaks of the spectrum. These measurements, coupled with existing luminosity measurements with Spitzer at 3.6 and 4.5 microns, will allow us to trace the spectral energy distribution of the Brown Dwarf and directly calculate its blackbody temperature. It will be the first field Brown Dwarfs with simultaneous measurements of its radius, mass, luminosity and temperature all measured independently of models.

  17. SIMULATING AN EVOLUTIONARY MULTI-AGENT BASED MODEL OF THE STOCK MARKET

    Directory of Open Access Journals (Sweden)

    Diana MARICA

    2015-08-01

    Full Text Available The paper focuses on artificial stock market simulations using a multi-agent model incorporating 2,000 heterogeneous agents interacting on the artificial market. The agents interaction is due to trading activity on the market through a call auction trading mechanism. The multi-agent model uses evolutionary techniques such as genetic programming in order to generate an adaptive and evolving population of agents. Each artificial agent is endowed with wealth and a genetic programming induced trading strategy. The trading strategy evolves and adapts to the new market conditions through a process called breeding, which implies that at each simulation step, new agents with better trading strategies are generated by the model, from recombining the best performing trading strategies and replacing the agents which have the worst performing trading strategies. The simulation model was build with the help of the simulation software Altreva Adaptive Modeler which offers a suitable platform for financial market simulations of evolutionary agent based models, the S&P500 composite index being used as a benchmark for the simulation results.

  18. The causal pie model: an epidemiological method applied to evolutionary biology and ecology.

    Science.gov (United States)

    Wensink, Maarten; Westendorp, Rudi G J; Baudisch, Annette

    2014-05-01

    A general concept for thinking about causality facilitates swift comprehension of results, and the vocabulary that belongs to the concept is instrumental in cross-disciplinary communication. The causal pie model has fulfilled this role in epidemiology and could be of similar value in evolutionary biology and ecology. In the causal pie model, outcomes result from sufficient causes. Each sufficient cause is made up of a "causal pie" of "component causes". Several different causal pies may exist for the same outcome. If and only if all component causes of a sufficient cause are present, that is, a causal pie is complete, does the outcome occur. The effect of a component cause hence depends on the presence of the other component causes that constitute some causal pie. Because all component causes are equally and fully causative for the outcome, the sum of causes for some outcome exceeds 100%. The causal pie model provides a way of thinking that maps into a number of recurrent themes in evolutionary biology and ecology: It charts when component causes have an effect and are subject to natural selection, and how component causes affect selection on other component causes; which partitions of outcomes with respect to causes are feasible and useful; and how to view the composition of a(n apparently homogeneous) population. The diversity of specific results that is directly understood from the causal pie model is a test for both the validity and the applicability of the model. The causal pie model provides a common language in which results across disciplines can be communicated and serves as a template along which future causal analyses can be made.

  19. Application of evolutionary games to modeling carcinogenesis.

    Science.gov (United States)

    Swierniak, Andrzej; Krzeslak, Michal

    2013-06-01

    We review a quite large volume of literature concerning mathematical modelling of processes related to carcinogenesis and the growth of cancer cell populations based on the theory of evolutionary games. This review, although partly idiosyncratic, covers such major areas of cancer-related phenomena as production of cytotoxins, avoidance of apoptosis, production of growth factors, motility and invasion, and intra- and extracellular signaling. We discuss the results of other authors and append to them some additional results of our own simulations dealing with the possible dynamics and/or spatial distribution of the processes discussed.

  20. Multiparty Evolutionary Game Model in Coal Mine Safety Management and Its Application

    Directory of Open Access Journals (Sweden)

    Rongwu Lu

    2018-01-01

    Full Text Available Coal mine safety management involves many interested parties and there are complex relationships between them. According to game theory, a multiparty evolutionary game model is established to analyze the selection of strategies. Then, a simplified three-party model is taken as an example to carry out detailed analysis and solution. Based on stability theory of dynamics system and phase diagram analysis, this article studies replicator dynamics of the evolutionary model to make an optimization analysis of the behaviors of those interested parties and the adjustment mechanism of safety management policies and decisions. The results show how the charge of supervision of government department and inspection of coal mine enterprise impact the efficiency of safety management and the effect of constraint measures and incentive and other measures in safety management.

  1. An evolutionary algorithm for model selection

    Energy Technology Data Exchange (ETDEWEB)

    Bicker, Karl [CERN, Geneva (Switzerland); Chung, Suh-Urk; Friedrich, Jan; Grube, Boris; Haas, Florian; Ketzer, Bernhard; Neubert, Sebastian; Paul, Stephan; Ryabchikov, Dimitry [Technische Univ. Muenchen (Germany)

    2013-07-01

    When performing partial-wave analyses of multi-body final states, the choice of the fit model, i.e. the set of waves to be used in the fit, can significantly alter the results of the partial wave fit. Traditionally, the models were chosen based on physical arguments and by observing the changes in log-likelihood of the fits. To reduce possible bias in the model selection process, an evolutionary algorithm was developed based on a Bayesian goodness-of-fit criterion which takes into account the model complexity. Starting from systematically constructed pools of waves which contain significantly more waves than the typical fit model, the algorithm yields a model with an optimal log-likelihood and with a number of partial waves which is appropriate for the number of events in the data. Partial waves with small contributions to the total intensity are penalized and likely to be dropped during the selection process, as are models were excessive correlations between single waves occur. Due to the automated nature of the model selection, a much larger part of the model space can be explored than would be possible in a manual selection. In addition the method allows to assess the dependence of the fit result on the fit model which is an important contribution to the systematic uncertainty.

  2. Evolutionary disarmament in interspecific competition.

    Science.gov (United States)

    Kisdi, E; Geritz, S A

    2001-12-22

    Competitive asymmetry, which is the advantage of having a larger body or stronger weaponry than a contestant, drives spectacular evolutionary arms races in intraspecific competition. Similar asymmetries are well documented in interspecific competition, yet they seldom lead to exaggerated traits. Here we demonstrate that two species with substantially different size may undergo parallel coevolution towards a smaller size under the same ecological conditions where a single species would exhibit an evolutionary arms race. We show that disarmament occurs for a wide range of parameters in an ecologically explicit model of competition for a single shared resource; disarmament also occurs in a simple Lotka-Volterra competition model. A key property of both models is the interplay between evolutionary dynamics and population density. The mechanism does not rely on very specific features of the model. Thus, evolutionary disarmament may be widespread and may help to explain the lack of interspecific arms races.

  3. A Test of Evolutionary Policing Theory with Data from Human Societies

    Science.gov (United States)

    Kümmerli, Rolf

    2011-01-01

    In social groups where relatedness among interacting individuals is low, cooperation can often only be maintained through mechanisms that repress competition among group members. Repression-of-competition mechanisms, such as policing and punishment, seem to be of particular importance in human societies, where cooperative interactions often occur among unrelated individuals. In line with this view, economic games have shown that the ability to punish defectors enforces cooperation among humans. Here, I examine a real-world example of a repression-of-competition system, the police institutions common to modern human societies. Specifically, I test evolutionary policing theory by comparing data on policing effort, per capita crime rate, and similarity (used as a proxy for genetic relatedness) among citizens across the 26 cantons of Switzerland. This comparison revealed full support for all three predictions of evolutionary policing theory. First, when controlling for policing efforts, crime rate correlated negatively with the similarity among citizens. This is in line with the prediction that high similarity results in higher levels of cooperative self-restraint (i.e. lower crime rates) because it aligns the interests of individuals. Second, policing effort correlated negatively with the similarity among citizens, supporting the prediction that more policing is required to enforce cooperation in low-similarity societies, where individuals' interests diverge most. Third, increased policing efforts were associated with reductions in crime rates, indicating that policing indeed enforces cooperation. These analyses strongly indicate that humans respond to cues of their social environment and adjust cheating and policing behaviour as predicted by evolutionary policing theory. PMID:21909429

  4. A test of evolutionary policing theory with data from human societies.

    Science.gov (United States)

    Kümmerli, Rolf

    2011-01-01

    In social groups where relatedness among interacting individuals is low, cooperation can often only be maintained through mechanisms that repress competition among group members. Repression-of-competition mechanisms, such as policing and punishment, seem to be of particular importance in human societies, where cooperative interactions often occur among unrelated individuals. In line with this view, economic games have shown that the ability to punish defectors enforces cooperation among humans. Here, I examine a real-world example of a repression-of-competition system, the police institutions common to modern human societies. Specifically, I test evolutionary policing theory by comparing data on policing effort, per capita crime rate, and similarity (used as a proxy for genetic relatedness) among citizens across the 26 cantons of Switzerland. This comparison revealed full support for all three predictions of evolutionary policing theory. First, when controlling for policing efforts, crime rate correlated negatively with the similarity among citizens. This is in line with the prediction that high similarity results in higher levels of cooperative self-restraint (i.e. lower crime rates) because it aligns the interests of individuals. Second, policing effort correlated negatively with the similarity among citizens, supporting the prediction that more policing is required to enforce cooperation in low-similarity societies, where individuals' interests diverge most. Third, increased policing efforts were associated with reductions in crime rates, indicating that policing indeed enforces cooperation. These analyses strongly indicate that humans respond to cues of their social environment and adjust cheating and policing behaviour as predicted by evolutionary policing theory.

  5. A test of evolutionary policing theory with data from human societies.

    Directory of Open Access Journals (Sweden)

    Rolf Kümmerli

    Full Text Available In social groups where relatedness among interacting individuals is low, cooperation can often only be maintained through mechanisms that repress competition among group members. Repression-of-competition mechanisms, such as policing and punishment, seem to be of particular importance in human societies, where cooperative interactions often occur among unrelated individuals. In line with this view, economic games have shown that the ability to punish defectors enforces cooperation among humans. Here, I examine a real-world example of a repression-of-competition system, the police institutions common to modern human societies. Specifically, I test evolutionary policing theory by comparing data on policing effort, per capita crime rate, and similarity (used as a proxy for genetic relatedness among citizens across the 26 cantons of Switzerland. This comparison revealed full support for all three predictions of evolutionary policing theory. First, when controlling for policing efforts, crime rate correlated negatively with the similarity among citizens. This is in line with the prediction that high similarity results in higher levels of cooperative self-restraint (i.e. lower crime rates because it aligns the interests of individuals. Second, policing effort correlated negatively with the similarity among citizens, supporting the prediction that more policing is required to enforce cooperation in low-similarity societies, where individuals' interests diverge most. Third, increased policing efforts were associated with reductions in crime rates, indicating that policing indeed enforces cooperation. These analyses strongly indicate that humans respond to cues of their social environment and adjust cheating and policing behaviour as predicted by evolutionary policing theory.

  6. Pseudorandom numbers: evolutionary models in image processing, biology, and nonlinear dynamic systems

    Science.gov (United States)

    Yaroslavsky, Leonid P.

    1996-11-01

    We show that one can treat pseudo-random generators, evolutionary models of texture images, iterative local adaptive filters for image restoration and enhancement and growth models in biology and material sciences in a unified way as special cases of dynamic systems with a nonlinear feedback.

  7. Applying Evolutionary Genetics to Developmental Toxicology and Risk Assessment

    Science.gov (United States)

    Leung, Maxwell C. K.; Procter, Andrew C.; Goldstone, Jared V.; Foox, Jonathan; DeSalle, Robert; Mattingly, Carolyn J.; Siddall, Mark E.; Timme-Laragy, Alicia R.

    2018-01-01

    Evolutionary thinking continues to challenge our views on health and disease. Yet, there is a communication gap between evolutionary biologists and toxicologists in recognizing the connections among developmental pathways, high-throughput screening, and birth defects in humans. To increase our capability in identifying potential developmental toxicants in humans, we propose to apply evolutionary genetics to improve the experimental design and data interpretation with various in vitro and whole-organism models. We review five molecular systems of stress response and update 18 consensual cell-cell signaling pathways that are the hallmark for early development, organogenesis, and differentiation; and revisit the principles of teratology in light of recent advances in high-throughput screening, big data techniques, and systems toxicology. Multiscale systems modeling plays an integral role in the evolutionary approach to cross-species extrapolation. Phylogenetic analysis and comparative bioinformatics are both valuable tools in identifying and validating the molecular initiating events that account for adverse developmental outcomes in humans. The discordance of susceptibility between test species and humans (ontogeny) reflects their differences in evolutionary history (phylogeny). This synthesis not only can lead to novel applications in developmental toxicity and risk assessment, but also can pave the way for applying an evo-devo perspective to the study of developmental origins of health and disease. PMID:28267574

  8. Evolutionary thinking in microeconomic models: prestige bias and market bubbles.

    Directory of Open Access Journals (Sweden)

    Adrian Viliami Bell

    Full Text Available Evolutionary models broadly support a number of social learning strategies likely important in economic behavior. Using a simple model of price dynamics, I show how prestige bias, or copying of famed (and likely successful individuals, influences price equilibria and investor disposition in a way that exacerbates or creates market bubbles. I discuss how integrating the social learning and demographic forces important in cultural evolution with economic models provides a fruitful line of inquiry into real-world behavior.

  9. Asymmetric Evolutionary Games

    Science.gov (United States)

    McAvoy, Alex; Hauert, Christoph

    2015-01-01

    Evolutionary game theory is a powerful framework for studying evolution in populations of interacting individuals. A common assumption in evolutionary game theory is that interactions are symmetric, which means that the players are distinguished by only their strategies. In nature, however, the microscopic interactions between players are nearly always asymmetric due to environmental effects, differing baseline characteristics, and other possible sources of heterogeneity. To model these phenomena, we introduce into evolutionary game theory two broad classes of asymmetric interactions: ecological and genotypic. Ecological asymmetry results from variation in the environments of the players, while genotypic asymmetry is a consequence of the players having differing baseline genotypes. We develop a theory of these forms of asymmetry for games in structured populations and use the classical social dilemmas, the Prisoner’s Dilemma and the Snowdrift Game, for illustrations. Interestingly, asymmetric games reveal essential differences between models of genetic evolution based on reproduction and models of cultural evolution based on imitation that are not apparent in symmetric games. PMID:26308326

  10. Some Analytical Properties of the Model for Stochastic Evolutionary Games in Finite Populations with Non-uniform Interaction Rate

    International Nuclear Information System (INIS)

    Quan Ji; Wang Xianjia

    2013-01-01

    Traditional evolutionary games assume uniform interaction rate, which means that the rate at which individuals meet and interact is independent of their strategies. But in some systems, especially biological systems, the players interact with each other discriminately. Taylor and Nowak (2006) were the first to establish the corresponding non-uniform interaction rate model by allowing the interaction rates to depend on strategies. Their model is based on replicator dynamics which assumes an infinite size population. But in reality, the number of individuals in the population is always finite, and there will be some random interference in the individuals' strategy selection process. Therefore, it is more practical to establish the corresponding stochastic evolutionary model in finite populations. In fact, the analysis of evolutionary games in a finite size population is more difficult. Just as Taylor and Nowak said in the outlook section of their paper, ''The analysis of non-uniform interaction rates should be extended to stochastic game dynamics of finite populations''. In this paper, we are exactly doing this work. We extend Taylor and Nowak's model from infinite to finite case, especially focusing on the infiuence of non-uniform connection characteristics on the evolutionary stable state of the system. We model the strategy evolutionary process of the population by a continuous ergodic Markov process. Based on the limit distribution of the process, we can give the evolutionary stable state of the system. We make a complete classification of the symmetric 2 × 2 games. For each case game, the corresponding limit distribution of the Markov-based process is given when noise intensity is small enough. In contrast with most literatures in evolutionary games using the simulation method, all our results obtained are analytical. Especially, in the dominant-case game, coexistence of the two strategies may become evolutionary stable states in our model. This result can be

  11. An Evolutionary Modelling Approach To Understanding The Factors Behind Plant Invasiveness And Community Susceptibility To Invasion

    DEFF Research Database (Denmark)

    Warren, John; Topping, Christopher John; James, Penri

    2011-01-01

    Ecologists have had limited success in understanding which introduced species may become invasive. An evolutionary model is used to investigate which traits are associated with invasiveness. Translocation experiments were simulated in which species were moved into similar but evolutionary younger...

  12. Polymorphic Evolutionary Games.

    Science.gov (United States)

    Fishman, Michael A

    2016-06-07

    In this paper, I present an analytical framework for polymorphic evolutionary games suitable for explicitly modeling evolutionary processes in diploid populations with sexual reproduction. The principal aspect of the proposed approach is adding diploid genetics cum sexual recombination to a traditional evolutionary game, and switching from phenotypes to haplotypes as the new game׳s pure strategies. Here, the relevant pure strategy׳s payoffs derived by summing the payoffs of all the phenotypes capable of producing gametes containing that particular haplotype weighted by the pertinent probabilities. The resulting game is structurally identical to the familiar Evolutionary Games with non-linear pure strategy payoffs (Hofbauer and Sigmund, 1998. Cambridge University Press), and can be analyzed in terms of an established analytical framework for such games. And these results can be translated into the terms of genotypic, and whence, phenotypic evolutionary stability pertinent to the original game. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Mothers Who Kill Their Offspring: Testing Evolutionary Hypothesis in a 110-Case Italian Sample

    Science.gov (United States)

    Camperio Ciani, Andrea S.; Fontanesi, Lilybeth

    2012-01-01

    Objectives: This research aimed to identify incidents of mothers in Italy killing their own children and to test an adaptive evolutionary hypothesis to explain their occurrence. Methods: 110 cases of mothers killing 123 of their own offspring from 1976 to 2010 were analyzed. Each case was classified using 13 dichotomic variables. Descriptive…

  14. EVOLUTIONARY FOUNDATIONS FOR MOLECULAR MEDICINE

    Science.gov (United States)

    Nesse, Randolph M.; Ganten, Detlev; Gregory, T. Ryan; Omenn, Gilbert S.

    2015-01-01

    Evolution has long provided a foundation for population genetics, but many major advances in evolutionary biology from the 20th century are only now being applied in molecular medicine. They include the distinction between proximate and evolutionary explanations, kin selection, evolutionary models for cooperation, and new strategies for tracing phylogenies and identifying signals of selection. Recent advances in genomics are further transforming evolutionary biology and creating yet more opportunities for progress at the interface of evolution with genetics, medicine, and public health. This article reviews 15 evolutionary principles and their applications in molecular medicine in hopes that readers will use them and others to speed the development of evolutionary molecular medicine. PMID:22544168

  15. Assessing variation in life-history tactics within a population using mixture regression models: a practical guide for evolutionary ecologists.

    Science.gov (United States)

    Hamel, Sandra; Yoccoz, Nigel G; Gaillard, Jean-Michel

    2017-05-01

    violated in life-history data. Mixed models were quite robust to this violation in the sense that fixed effects were unbiased at the population level. However, fixed effects at the cluster level and random effects were better estimated using mixture models. Our empirical analyses demonstrated that using mixture models facilitates the identification of the diversity of growth and reproductive tactics occurring within a population. Therefore, using this modelling framework allows testing for the presence of clusters and, when clusters occur, provides reliable estimates of fixed and random effects for each cluster of the population. In the presence or expectation of clusters, using mixture models offers a suitable extension of mixed models, particularly when evolutionary ecologists aim at identifying how ecological and evolutionary processes change within a population. Mixture regression models therefore provide a valuable addition to the statistical toolbox of evolutionary ecologists. As these models are complex and have their own limitations, we provide recommendations to guide future users. © 2016 Cambridge Philosophical Society.

  16. Understanding the mind from an evolutionary perspective: an overview of evolutionary psychology.

    Science.gov (United States)

    Shackelford, Todd K; Liddle, James R

    2014-05-01

    The theory of evolution by natural selection provides the only scientific explanation for the existence of complex adaptations. The design features of the brain, like any organ, are the result of selection pressures operating over deep time. Evolutionary psychology posits that the human brain comprises a multitude of evolved psychological mechanisms, adaptations to specific and recurrent problems of survival and reproduction faced over human evolutionary history. Although some mistakenly view evolutionary psychology as promoting genetic determinism, evolutionary psychologists appreciate and emphasize the interactions between genes and environments. This approach to psychology has led to a richer understanding of a variety of psychological phenomena, and has provided a powerful foundation for generating novel hypotheses. Critics argue that evolutionary psychologists resort to storytelling, but as with any branch of science, empirical testing is a vital component of the field, with hypotheses standing or falling with the weight of the evidence. Evolutionary psychology is uniquely suited to provide a unifying theoretical framework for the disparate subdisciplines of psychology. An evolutionary perspective has provided insights into several subdisciplines of psychology, while simultaneously demonstrating the arbitrary nature of dividing psychological science into such subdisciplines. Evolutionary psychologists have amassed a substantial empirical and theoretical literature, but as a relatively new approach to psychology, many questions remain, with several promising directions for future research. For further resources related to this article, please visit the WIREs website. The authors have declared no conflicts of interest for this article. © 2014 John Wiley & Sons, Ltd.

  17. Citizen science reveals unexpected continental-scale evolutionary change in a model organism.

    Directory of Open Access Journals (Sweden)

    Jonathan Silvertown

    2011-04-01

    Full Text Available Organisms provide some of the most sensitive indicators of climate change and evolutionary responses are becoming apparent in species with short generation times. Large datasets on genetic polymorphism that can provide an historical benchmark against which to test for recent evolutionary responses are very rare, but an exception is found in the brown-lipped banded snail (Cepaea nemoralis. This species is sensitive to its thermal environment and exhibits several polymorphisms of shell colour and banding pattern affecting shell albedo in the majority of populations within its native range in Europe. We tested for evolutionary changes in shell albedo that might have been driven by the warming of the climate in Europe over the last half century by compiling an historical dataset for 6,515 native populations of C. nemoralis and comparing this with new data on nearly 3,000 populations. The new data were sampled mainly in 2009 through the Evolution MegaLab, a citizen science project that engaged thousands of volunteers in 15 countries throughout Europe in the biggest such exercise ever undertaken. A known geographic cline in the frequency of the colour phenotype with the highest albedo (yellow was shown to have persisted and a difference in colour frequency between woodland and more open habitats was confirmed, but there was no general increase in the frequency of yellow shells. This may have been because snails adapted to a warming climate through behavioural thermoregulation. By contrast, we detected an unexpected decrease in the frequency of Unbanded shells and an increase in the Mid-banded morph. Neither of these evolutionary changes appears to be a direct response to climate change, indicating that the influence of other selective agents, possibly related to changing predation pressure and habitat change with effects on micro-climate.

  18. EvoBuild: A Quickstart Toolkit for Programming Agent-Based Models of Evolutionary Processes

    Science.gov (United States)

    Wagh, Aditi; Wilensky, Uri

    2018-04-01

    Extensive research has shown that one of the benefits of programming to learn about scientific phenomena is that it facilitates learning about mechanisms underlying the phenomenon. However, using programming activities in classrooms is associated with costs such as requiring additional time to learn to program or students needing prior experience with programming. This paper presents a class of programming environments that we call quickstart: Environments with a negligible threshold for entry into programming and a modest ceiling. We posit that such environments can provide benefits of programming for learning without incurring associated costs for novice programmers. To make this claim, we present a design-based research study conducted to compare programming models of evolutionary processes with a quickstart toolkit with exploring pre-built models of the same processes. The study was conducted in six seventh grade science classes in two schools. Students in the programming condition used EvoBuild, a quickstart toolkit for programming agent-based models of evolutionary processes, to build their NetLogo models. Students in the exploration condition used pre-built NetLogo models. We demonstrate that although students came from a range of academic backgrounds without prior programming experience, and all students spent the same number of class periods on the activities including the time students took to learn programming in this environment, EvoBuild students showed greater learning about evolutionary mechanisms. We discuss the implications of this work for design research on programming environments in K-12 science education.

  19. An evolutionary-game model of tumour-cell interactions: possible relevance to gene therapy

    DEFF Research Database (Denmark)

    Bach, L.A.; Bentzen, S.M.; Alsner, Jan

    2001-01-01

    Evolutionary games have been applied as simple mathematical models of populations where interactions between individuals control the dynamics. Recently, it has been proposed to use this type of model to describe the evolution of tumour cell populations with interactions between cells. We extent...

  20. GALEV evolutionary synthesis models – I. Code, input physics and web

    NARCIS (Netherlands)

    Kotulla, R.; Fritze, U.; Weilbacher, P.; Anders, P.

    2009-01-01

    GALEV (GALaxy EVolution) evolutionary synthesis models describe the evolution of stellar populations in general, of star clusters as well as of galaxies, both in terms of resolved stellar populations and of integrated light properties over cosmological time-scales of ≥13 Gyr from the onset of star

  1. On economic applications of evolutionary game theory

    OpenAIRE

    Daniel Friedman

    1998-01-01

    Evolutionary games have considerable unrealized potential for modeling substantive economic issues. They promise richer predictions than orthodox game models but often require more extensive specifications. This paper exposits the specification of evolutionary game models and classifies the possible asymptotic behavior for one and two dimensional models.

  2. USING ECO-EVOLUTIONARY INDIVIDUAL-BASED MODELS TO INVESTIGATE SPATIALLY-DEPENDENT PROCESSES IN CONSERVATION GENETICS

    Science.gov (United States)

    Eco-evolutionary population simulation models are powerful new forecasting tools for exploring management strategies for climate change and other dynamic disturbance regimes. Additionally, eco-evo individual-based models (IBMs) are useful for investigating theoretical feedbacks ...

  3. Estimating the ratios of the stationary distribution values for Markov chains modeling evolutionary algorithms.

    Science.gov (United States)

    Mitavskiy, Boris; Cannings, Chris

    2009-01-01

    The evolutionary algorithm stochastic process is well-known to be Markovian. These have been under investigation in much of the theoretical evolutionary computing research. When the mutation rate is positive, the Markov chain modeling of an evolutionary algorithm is irreducible and, therefore, has a unique stationary distribution. Rather little is known about the stationary distribution. In fact, the only quantitative facts established so far tell us that the stationary distributions of Markov chains modeling evolutionary algorithms concentrate on uniform populations (i.e., those populations consisting of a repeated copy of the same individual). At the same time, knowing the stationary distribution may provide some information about the expected time it takes for the algorithm to reach a certain solution, assessment of the biases due to recombination and selection, and is of importance in population genetics to assess what is called a "genetic load" (see the introduction for more details). In the recent joint works of the first author, some bounds have been established on the rates at which the stationary distribution concentrates on the uniform populations. The primary tool used in these papers is the "quotient construction" method. It turns out that the quotient construction method can be exploited to derive much more informative bounds on ratios of the stationary distribution values of various subsets of the state space. In fact, some of the bounds obtained in the current work are expressed in terms of the parameters involved in all the three main stages of an evolutionary algorithm: namely, selection, recombination, and mutation.

  4. Test scheduling optimization for 3D network-on-chip based on cloud evolutionary algorithm of Pareto multi-objective

    Science.gov (United States)

    Xu, Chuanpei; Niu, Junhao; Ling, Jing; Wang, Suyan

    2018-03-01

    In this paper, we present a parallel test strategy for bandwidth division multiplexing under the test access mechanism bandwidth constraint. The Pareto solution set is combined with a cloud evolutionary algorithm to optimize the test time and power consumption of a three-dimensional network-on-chip (3D NoC). In the proposed method, all individuals in the population are sorted in non-dominated order and allocated to the corresponding level. Individuals with extreme and similar characteristics are then removed. To increase the diversity of the population and prevent the algorithm from becoming stuck around local optima, a competition strategy is designed for the individuals. Finally, we adopt an elite reservation strategy and update the individuals according to the cloud model. Experimental results show that the proposed algorithm converges to the optimal Pareto solution set rapidly and accurately. This not only obtains the shortest test time, but also optimizes the power consumption of the 3D NoC.

  5. Evolutionary Agent-based Models to design distributed water management strategies

    Science.gov (United States)

    Giuliani, M.; Castelletti, A.; Reed, P. M.

    2012-12-01

    There is growing awareness in the scientific community that the traditional centralized approach to water resources management, as described in much of the water resources literature, provides an ideal optimal solution, which is certainly useful to quantify the best physically achievable performance, but is generally inapplicable. Most real world water resources management problems are indeed characterized by the presence of multiple, distributed and institutionally-independent decision-makers. Multi-Agent Systems provide a potentially more realistic alternative framework to model multiple and self-interested decision-makers in a credible context. Each decision-maker can be represented by an agent who, being self-interested, acts according to local objective functions and produces negative externalities on system level objectives. Different levels of coordination can potentially be included in the framework by designing coordination mechanisms to drive the current decision-making structure toward the global system efficiency. Yet, the identification of effective coordination strategies can be particularly complex in modern institutional contexts and current practice is dependent on largely ad-hoc coordination strategies. In this work we propose a novel Evolutionary Agent-based Modeling (EAM) framework that enables a mapping of fully uncoordinated and centrally coordinated solutions into their relative "many-objective" tradeoffs using multiobjective evolutionary algorithms. Then, by analysing the conflicts between local individual agent and global system level objectives it is possible to more fully understand the causes, consequences, and potential solution strategies for coordination failures. Game-theoretic criteria have value for identifying the most interesting alternatives from a policy making point of view as well as the coordination mechanisms that can be applied to obtain these interesting solutions. The proposed approach is numerically tested on a

  6. Testing the ecological consequences of evolutionary change using elements.

    Science.gov (United States)

    Jeyasingh, Punidan D; Cothran, Rickey D; Tobler, Michael

    2014-02-01

    Understanding the ecological consequences of evolutionary change is a central challenge in contemporary biology. We propose a framework based on the ˜25 elements represented in biology, which can serve as a conduit for a general exploration of poorly understood evolution-to-ecology links. In this framework, known as ecological stoichiometry, the quantity of elements in the inorganic realm is a fundamental environment, while the flow of elements from the abiotic to the biotic realm is due to the action of genomes, with the unused elements excreted back into the inorganic realm affecting ecological processes at higher levels of organization. Ecological stoichiometry purposefully assumes distinct elemental composition of species, enabling powerful predictions about the ecological functions of species. However, this assumption results in a simplified view of the evolutionary mechanisms underlying diversification in the elemental composition of species. Recent research indicates substantial intraspecific variation in elemental composition and associated ecological functions such as nutrient excretion. We posit that attention to intraspecific variation in elemental composition will facilitate a synthesis of stoichiometric information in light of population genetics theory for a rigorous exploration of the ecological consequences of evolutionary change.

  7. Comparison of evolutionary algorithms in gene regulatory network model inference.

    LENUS (Irish Health Repository)

    2010-01-01

    ABSTRACT: BACKGROUND: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineering of GRNs). However, the nature of these data has made this process very difficult. At the moment, several methods of discovering qualitative causal relationships between genes with high accuracy from microarray data exist, but large scale quantitative analysis on real biological datasets cannot be performed, to date, as existing approaches are not suitable for real microarray data which are noisy and insufficient. RESULTS: This paper performs an analysis of several existing evolutionary algorithms for quantitative gene regulatory network modelling. The aim is to present the techniques used and offer a comprehensive comparison of approaches, under a common framework. Algorithms are applied to both synthetic and real gene expression data from DNA microarrays, and ability to reproduce biological behaviour, scalability and robustness to noise are assessed and compared. CONCLUSIONS: Presented is a comparison framework for assessment of evolutionary algorithms, used to infer gene regulatory networks. Promising methods are identified and a platform for development of appropriate model formalisms is established.

  8. An evolutionary model of cooperation, fairness and altruistic punishment in public good games.

    Directory of Open Access Journals (Sweden)

    Moritz Hetzer

    Full Text Available We identify and explain the mechanisms that account for the emergence of fairness preferences and altruistic punishment in voluntary contribution mechanisms by combining an evolutionary perspective together with an expected utility model. We aim at filling a gap between the literature on the theory of evolution applied to cooperation and punishment, and the empirical findings from experimental economics. The approach is motivated by previous findings on other-regarding behavior, the co-evolution of culture, genes and social norms, as well as bounded rationality. Our first result reveals the emergence of two distinct evolutionary regimes that force agents to converge either to a defection state or to a state of coordination, depending on the predominant set of self- or other-regarding preferences. Our second result indicates that subjects in laboratory experiments of public goods games with punishment coordinate and punish defectors as a result of an aversion against disadvantageous inequitable outcomes. Our third finding identifies disadvantageous inequity aversion as evolutionary dominant and stable in a heterogeneous population of agents endowed initially only with purely self-regarding preferences. We validate our model using previously obtained results from three independently conducted experiments of public goods games with punishment.

  9. An evolutionary model of cooperation, fairness and altruistic punishment in public good games.

    Science.gov (United States)

    Hetzer, Moritz; Sornette, Didier

    2013-01-01

    We identify and explain the mechanisms that account for the emergence of fairness preferences and altruistic punishment in voluntary contribution mechanisms by combining an evolutionary perspective together with an expected utility model. We aim at filling a gap between the literature on the theory of evolution applied to cooperation and punishment, and the empirical findings from experimental economics. The approach is motivated by previous findings on other-regarding behavior, the co-evolution of culture, genes and social norms, as well as bounded rationality. Our first result reveals the emergence of two distinct evolutionary regimes that force agents to converge either to a defection state or to a state of coordination, depending on the predominant set of self- or other-regarding preferences. Our second result indicates that subjects in laboratory experiments of public goods games with punishment coordinate and punish defectors as a result of an aversion against disadvantageous inequitable outcomes. Our third finding identifies disadvantageous inequity aversion as evolutionary dominant and stable in a heterogeneous population of agents endowed initially only with purely self-regarding preferences. We validate our model using previously obtained results from three independently conducted experiments of public goods games with punishment.

  10. Gnarled-trunk evolutionary model of influenza A virus hemagglutinin.

    Directory of Open Access Journals (Sweden)

    Kimihito Ito

    Full Text Available Human influenza A viruses undergo antigenic changes with gradual accumulation of amino acid substitutions on the hemagglutinin (HA molecule. A strong antigenic mismatch between vaccine and epidemic strains often requires the replacement of influenza vaccines worldwide. To establish a practical model enabling us to predict the future direction of the influenza virus evolution, relative distances of amino acid sequences among past epidemic strains were analyzed by multidimensional scaling (MDS. We found that human influenza viruses have evolved along a gnarled evolutionary pathway with an approximately constant curvature in the MDS-constructed 3D space. The gnarled pathway indicated that evolution on the trunk favored multiple substitutions at the same amino acid positions on HA. The constant curvature was reasonably explained by assuming that the rate of amino acid substitutions varied from one position to another according to a gamma distribution. Furthermore, we utilized the estimated parameters of the gamma distribution to predict the amino acid substitutions on HA in subsequent years. Retrospective prediction tests for 12 years from 1997 to 2009 showed that 70% of actual amino acid substitutions were correctly predicted, and that 45% of predicted amino acid substitutions have been actually observed. Although it remains unsolved how to predict the exact timing of antigenic changes, the present results suggest that our model may have the potential to recognize emerging epidemic strains.

  11. An Evolutionary Game Theory Model of Spontaneous Brain Functioning.

    Science.gov (United States)

    Madeo, Dario; Talarico, Agostino; Pascual-Leone, Alvaro; Mocenni, Chiara; Santarnecchi, Emiliano

    2017-11-22

    Our brain is a complex system of interconnected regions spontaneously organized into distinct networks. The integration of information between and within these networks is a continuous process that can be observed even when the brain is at rest, i.e. not engaged in any particular task. Moreover, such spontaneous dynamics show predictive value over individual cognitive profile and constitute a potential marker in neurological and psychiatric conditions, making its understanding of fundamental importance in modern neuroscience. Here we present a theoretical and mathematical model based on an extension of evolutionary game theory on networks (EGN), able to capture brain's interregional dynamics by balancing emulative and non-emulative attitudes among brain regions. This results in the net behavior of nodes composing resting-state networks identified using functional magnetic resonance imaging (fMRI), determining their moment-to-moment level of activation and inhibition as expressed by positive and negative shifts in BOLD fMRI signal. By spontaneously generating low-frequency oscillatory behaviors, the EGN model is able to mimic functional connectivity dynamics, approximate fMRI time series on the basis of initial subset of available data, as well as simulate the impact of network lesions and provide evidence of compensation mechanisms across networks. Results suggest evolutionary game theory on networks as a new potential framework for the understanding of human brain network dynamics.

  12. Invisible hand effect in an evolutionary minority game model

    Science.gov (United States)

    Sysi-Aho, Marko; Saramäki, Jari; Kaski, Kimmo

    2005-03-01

    In this paper, we study the properties of a minority game with evolution realized by using genetic crossover to modify fixed-length decision-making strategies of agents. Although the agents in this evolutionary game act selfishly by trying to maximize their own performances only, it turns out that the whole society will eventually be rewarded optimally. This “invisible hand” effect is what Adam Smith over two centuries ago expected to take place in the context of free market mechanism. However, this behaviour of the society of agents is realized only under idealized conditions, where all agents are utilizing the same efficient evolutionary mechanism. If on the other hand part of the agents are adaptive, but not evolutionary, the system does not reach optimum performance, which is also the case if part of the evolutionary agents form a uniformly acting “cartel”.

  13. Evolutionary Models for Simple Biosystems

    Science.gov (United States)

    Bagnoli, Franco

    The concept of evolutionary development of structures constituted a real revolution in biology: it was possible to understand how the very complex structures of life can arise in an out-of-equilibrium system. The investigation of such systems has shown that indeed, systems under a flux of energy or matter can self-organize into complex patterns, think for instance to Rayleigh-Bernard convection, Liesegang rings, patterns formed by granular systems under shear. Following this line, one could characterize life as a state of matter, characterized by the slow, continuous process that we call evolution. In this paper we try to identify the organizational level of life, that spans several orders of magnitude from the elementary constituents to whole ecosystems. Although similar structures can be found in other contexts like ideas (memes) in neural systems and self-replicating elements (computer viruses, worms, etc.) in computer systems, we shall concentrate on biological evolutionary structure, and try to put into evidence the role and the emergence of network structure in such systems.

  14. Beryllium abundances along the evolutionary sequence of the open cluster IC 4651 - A new test for hydrodynamical stellar models

    Science.gov (United States)

    Smiljanic, R.; Pasquini, L.; Charbonnel, C.; Lagarde, N.

    2010-02-01

    Context. Previous analyses of lithium abundances in main sequence and red giant stars have revealed the action of mixing mechanisms other than convection in stellar interiors. Beryllium abundances in stars with Li abundance determinations can offer valuable complementary information on the nature of these mechanisms. Aims: Our aim is to derive Be abundances along the whole evolutionary sequence of an open cluster. We focus on the well-studied open cluster IC 4651. These Be abundances are used with previously determined Li abundances, in the same sample stars, to investigate the mixing mechanisms in a range of stellar masses and evolutionary stages. Methods: Atmospheric parameters were adopted from a previous abundance analysis by the same authors. New Be abundances have been determined from high-resolution, high signal-to-noise UVES spectra using spectrum synthesis and model atmospheres. The careful synthetic modeling of the Be lines region is used to calculate reliable abundances in rapidly rotating stars. The observed behavior of Be and Li is compared to theoretical predictions from stellar models including rotation-induced mixing, internal gravity waves, atomic diffusion, and thermohaline mixing. Results: Beryllium is detected in all the main sequence and turn-off sample stars, both slow- and fast-rotating stars, including the Li-dip stars, but is not detected in the red giants. Confirming previous results, we find that the Li dip is also a Be dip, although the depletion of Be is more modest than for Li in the corresponding effective temperature range. For post-main-sequence stars, the Be dilution starts earlier within the Hertzsprung gap than expected from classical predictions, as does the Li dilution. A clear dispersion in the Be abundances is also observed. Theoretical stellar models including the hydrodynamical transport processes mentioned above are able to reproduce all the observed features well. These results show a good theoretical understanding of the

  15. Chaotic Multiobjective Evolutionary Algorithm Based on Decomposition for Test Task Scheduling Problem

    Directory of Open Access Journals (Sweden)

    Hui Lu

    2014-01-01

    Full Text Available Test task scheduling problem (TTSP is a complex optimization problem and has many local optima. In this paper, a hybrid chaotic multiobjective evolutionary algorithm based on decomposition (CMOEA/D is presented to avoid becoming trapped in local optima and to obtain high quality solutions. First, we propose an improving integrated encoding scheme (IES to increase the efficiency. Then ten chaotic maps are applied into the multiobjective evolutionary algorithm based on decomposition (MOEA/D in three phases, that is, initial population and crossover and mutation operators. To identify a good approach for hybrid MOEA/D and chaos and indicate the effectiveness of the improving IES several experiments are performed. The Pareto front and the statistical results demonstrate that different chaotic maps in different phases have different effects for solving the TTSP especially the circle map and ICMIC map. The similarity degree of distribution between chaotic maps and the problem is a very essential factor for the application of chaotic maps. In addition, the experiments of comparisons of CMOEA/D and variable neighborhood MOEA/D (VNM indicate that our algorithm has the best performance in solving the TTSP.

  16. Evolutionary theory of ageing and the problem of correlated Gompertz parameters.

    Science.gov (United States)

    Burger, Oskar; Missov, Trifon I

    2016-11-07

    The Gompertz mortality model is often used to evaluate evolutionary theories of ageing, such as the Medawar-Williams' hypothesis that high extrinsic mortality leads to faster ageing. However, fits of the Gompertz mortality model to data often find the opposite result that mortality is negatively correlated with the rate of ageing. This negative correlation has been independently discovered in several taxa and is known in actuarial studies of ageing as the Strehler-Mildvan correlation. We examine the role of mortality selection in determining late-life variation in susceptibility to death, which has been suggested to be the cause of this negative correlation. We demonstrate that fixed-frailty models that account for heterogeneity in frailty do not remove the correlation and that the correlation is an inherent statistical property of the Gompertz distribution. Linking actuarial and biological rates of ageing will continue to be a pressing challenge, but the Strehler-Mildvan correlation itself should not be used to diagnose any biological, physiological, or evolutionary process. These findings resolve some key tensions between theory and data that affect evolutionary and biological studies of ageing and mortality. Tests of evolutionary theories of ageing should include direct measures of physiological performance or condition. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Radiation, Ecology and the Invalid LNT Model: The Evolutionary Imperative

    OpenAIRE

    Parsons, Peter A.

    2006-01-01

    Metabolic and energetic efficiency, and hence fitness of organisms to survive, should be maximal in their habitats. This tenet of evolutionary biology invalidates the linear-nothreshold (LNT) model for the risk consequences of environmental agents. Hormesis in response to selection for maximum metabolic and energetic efficiency, or minimum metabolic imbalance, to adapt to a stressed world dominated by oxidative stress should therefore be universal. Radiation hormetic zones extending substanti...

  18. Key innovations and island colonization as engines of evolutionary diversification: a comparative test with the Australasian diplodactyloid geckos.

    Science.gov (United States)

    Garcia-Porta, J; Ord, T J

    2013-12-01

    The acquisition of key innovations and the invasion of new areas constitute two major processes that facilitate ecological opportunity and subsequent evolutionary diversification. Using a major lizard radiation as a model, the Australasian diplodactyloid geckos, we explored the effects of two key innovations (adhesive toepads and a snake-like phenotype) and the invasion of new environments (island colonization) in promoting the evolution of phenotypic and species diversity. We found no evidence that toepads had significantly increased evolutionary diversification, which challenges the common assumption that the evolution of toepads has been responsible for the extensive radiation of geckos. In contrast, a snakelike phenotype was associated with increased rates of body size evolution and, to a lesser extent, species diversification. However, the clearest impact on evolutionary diversification has been the colonization of New Zealand and New Caledonia, which were associated with increased rates of both body size evolution and species diversification. This highlights that colonizing new environments can drive adaptive diversification in conjunction or independently of the evolution of a key innovation. Studies wishing to confirm the putative link between a key innovation and subsequent evolutionary diversification must therefore show that it has been the acquisition of an innovation specifically, not the colonization of new areas more generally, that has prompted diversification. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

  19. Experimental test of an eco-evolutionary dynamic feedback loop between evolution and population density in the green peach aphid.

    Science.gov (United States)

    Turcotte, Martin M; Reznick, David N; Daniel Hare, J

    2013-05-01

    An eco-evolutionary feedback loop is defined as the reciprocal impacts of ecology on evolutionary dynamics and evolution on ecological dynamics on contemporary timescales. We experimentally tested for an eco-evolutionary feedback loop in the green peach aphid, Myzus persicae, by manipulating initial densities and evolution. We found strong evidence that initial aphid density alters the rate and direction of evolution, as measured by changes in genotype frequencies through time. We also found that evolution of aphids within only 16 days, or approximately three generations, alters the rate of population growth and predicts density compared to nonevolving controls. The impact of evolution on population dynamics also depended on density. In one evolution treatment, evolution accelerated population growth by up to 10.3% at high initial density or reduced it by up to 6.4% at low initial density. The impact of evolution on population growth was as strong as or stronger than that caused by a threefold change in intraspecific density. We found that, taken together, ecological condition, here intraspecific density, alters evolutionary dynamics, which in turn alter concurrent population growth rate (ecological dynamics) in an eco-evolutionary feedback loop. Our results suggest that ignoring evolution in studies predicting population dynamics might lead us to over- or underestimate population density and that we cannot predict the evolutionary outcome within aphid populations without considering population size.

  20. Species packing in eco-evolutionary models of seasonally fluctuating environments.

    Science.gov (United States)

    Kremer, Colin T; Klausmeier, Christopher A

    2017-09-01

    As ecology and evolution become ever more entwined, many areas of ecological theory are being re-examined. Eco-evolutionary analyses of classic coexistence mechanisms are yielding new insights into the structure and stability of communities. We examine fluctuation-dependent coexistence models, identifying communities that are both ecologically and evolutionarily stable. Members of these communities possess distinct environmental preferences, revealing widespread patterns of limiting similarity. This regularity leads to consistent changes in the structure of communities across fluctuation regimes. However, at high amplitudes, subtle differences in the form of fluctuations dramatically affect the collapse of communities. We also show that identical fluctuations can support multiple evolutionarily stable communities - a novel example of alternative stable states within eco-evolutionary systems. Consequently, the configuration of communities will depend on historical contingencies, including details of the adaptive process. Integrating evolution into the study of coexistence offers new insights, while enriching our understanding of ecology. © 2017 John Wiley & Sons Ltd/CNRS.

  1. Basic emotions and adaptation. A computational and evolutionary model.

    Directory of Open Access Journals (Sweden)

    Daniela Pacella

    Full Text Available The core principles of the evolutionary theories of emotions declare that affective states represent crucial drives for action selection in the environment and regulated the behavior and adaptation of natural agents in ancestrally recurrent situations. While many different studies used autonomous artificial agents to simulate emotional responses and the way these patterns can affect decision-making, few are the approaches that tried to analyze the evolutionary emergence of affective behaviors directly from the specific adaptive problems posed by the ancestral environment. A model of the evolution of affective behaviors is presented using simulated artificial agents equipped with neural networks and physically inspired on the architecture of the iCub humanoid robot. We use genetic algorithms to train populations of virtual robots across generations, and investigate the spontaneous emergence of basic emotional behaviors in different experimental conditions. In particular, we focus on studying the emotion of fear, therefore the environment explored by the artificial agents can contain stimuli that are safe or dangerous to pick. The simulated task is based on classical conditioning and the agents are asked to learn a strategy to recognize whether the environment is safe or represents a threat to their lives and select the correct action to perform in absence of any visual cues. The simulated agents have special input units in their neural structure whose activation keep track of their actual "sensations" based on the outcome of past behavior. We train five different neural network architectures and then test the best ranked individuals comparing their performances and analyzing the unit activations in each individual's life cycle. We show that the agents, regardless of the presence of recurrent connections, spontaneously evolved the ability to cope with potentially dangerous environment by collecting information about the environment and then

  2. Basic emotions and adaptation. A computational and evolutionary model.

    Science.gov (United States)

    Pacella, Daniela; Ponticorvo, Michela; Gigliotta, Onofrio; Miglino, Orazio

    2017-01-01

    The core principles of the evolutionary theories of emotions declare that affective states represent crucial drives for action selection in the environment and regulated the behavior and adaptation of natural agents in ancestrally recurrent situations. While many different studies used autonomous artificial agents to simulate emotional responses and the way these patterns can affect decision-making, few are the approaches that tried to analyze the evolutionary emergence of affective behaviors directly from the specific adaptive problems posed by the ancestral environment. A model of the evolution of affective behaviors is presented using simulated artificial agents equipped with neural networks and physically inspired on the architecture of the iCub humanoid robot. We use genetic algorithms to train populations of virtual robots across generations, and investigate the spontaneous emergence of basic emotional behaviors in different experimental conditions. In particular, we focus on studying the emotion of fear, therefore the environment explored by the artificial agents can contain stimuli that are safe or dangerous to pick. The simulated task is based on classical conditioning and the agents are asked to learn a strategy to recognize whether the environment is safe or represents a threat to their lives and select the correct action to perform in absence of any visual cues. The simulated agents have special input units in their neural structure whose activation keep track of their actual "sensations" based on the outcome of past behavior. We train five different neural network architectures and then test the best ranked individuals comparing their performances and analyzing the unit activations in each individual's life cycle. We show that the agents, regardless of the presence of recurrent connections, spontaneously evolved the ability to cope with potentially dangerous environment by collecting information about the environment and then switching their behavior

  3. Industrial Applications of Evolutionary Algorithms

    CERN Document Server

    Sanchez, Ernesto; Tonda, Alberto

    2012-01-01

    This book is intended as a reference both for experienced users of evolutionary algorithms and for researchers that are beginning to approach these fascinating optimization techniques. Experienced users will find interesting details of real-world problems, and advice on solving issues related to fitness computation, modeling and setting appropriate parameters to reach optimal solutions. Beginners will find a thorough introduction to evolutionary computation, and a complete presentation of all evolutionary algorithms exploited to solve different problems. The book could fill the gap between the

  4. Transforming Biology Assessment with Machine Learning: Automated Scoring of Written Evolutionary Explanations

    Science.gov (United States)

    Nehm, Ross H.; Ha, Minsu; Mayfield, Elijah

    2012-02-01

    This study explored the use of machine learning to automatically evaluate the accuracy of students' written explanations of evolutionary change. Performance of the Summarization Integrated Development Environment (SIDE) program was compared to human expert scoring using a corpus of 2,260 evolutionary explanations written by 565 undergraduate students in response to two different evolution instruments (the EGALT-F and EGALT-P) that contained prompts that differed in various surface features (such as species and traits). We tested human-SIDE scoring correspondence under a series of different training and testing conditions, using Kappa inter-rater agreement values of greater than 0.80 as a performance benchmark. In addition, we examined the effects of response length on scoring success; that is, whether SIDE scoring models functioned with comparable success on short and long responses. We found that SIDE performance was most effective when scoring models were built and tested at the individual item level and that performance degraded when suites of items or entire instruments were used to build and test scoring models. Overall, SIDE was found to be a powerful and cost-effective tool for assessing student knowledge and performance in a complex science domain.

  5. Evolutionary Stages of e-Tailors and Retailers: Firm Value Determinants Model

    OpenAIRE

    Jae K. Lee; Heegoo Kang; Hoe K. Lee; Han S. Lee

    2002-01-01

    We have studied the evolutionary stages of pure e-tailers, click & mortar (C&M) and brick & mortar (B&M) retailers for three points of time: June 1999, June 2000, and June 2001. To evaluate the dynamic stages of e-tailing business as an innovative venture, we propose four stages: exploration, breakeven, growth, and maturity. The stages are measured by the impact of revenue and income on the firm value, and a regression model is adopted to formulate the model. To empirically examine the stages...

  6. Prediction of strong earthquake motions on rock surface using evolutionary process models

    International Nuclear Information System (INIS)

    Kameda, H.; Sugito, M.

    1984-01-01

    Stochastic process models are developed for prediction of strong earthquake motions for engineering design purposes. Earthquake motions with nonstationary frequency content are modeled by using the concept of evolutionary processes. Discussion is focused on the earthquake motions on bed rocks which are important for construction of nuclear power plants in seismic regions. On this basis, two earthquake motion prediction models are developed, one (EMP-IB Model) for prediction with given magnitude and epicentral distance, and the other (EMP-IIB Model) to account for the successive fault ruptures and the site location relative to the fault of great earthquakes. (Author) [pt

  7. A Hybrid Chaotic Quantum Evolutionary Algorithm

    DEFF Research Database (Denmark)

    Cai, Y.; Zhang, M.; Cai, H.

    2010-01-01

    A hybrid chaotic quantum evolutionary algorithm is proposed to reduce amount of computation, speed up convergence and restrain premature phenomena of quantum evolutionary algorithm. The proposed algorithm adopts the chaotic initialization method to generate initial population which will form a pe...... tests. The presented algorithm is applied to urban traffic signal timing optimization and the effect is satisfied....

  8. Tables and intercomparisons of evolutionary sequences of models for massive stars

    International Nuclear Information System (INIS)

    Chin, Chaowen; Stothers, R.B.

    1990-01-01

    Tables of evolutionary sequences of models for massive stars have been prepared for a variety of physical input parameters that are normally treated as free. These parameters include the interior convective mixing scheme, the mixing length in the outer convective envelope, the rate of stellar-wind mass loss, the initial stellar mass, and the initial chemical composition. Ranges of specified initial mass and initial chemical composition are M = 10-120 solar masses, Xe = 0.602-0.739, and Ze = 0.021-0.044. The tables cover evolution of the star from the ZAMS to either the end of core H burning or the end of core He burning. Differences among the evolutionary tracks are illustrated primarily in terms of the interior mixing scheme, since the amount and timing of stellar wind mass loss are still very uncertain for initial masses above about 30 solar masses. 52 refs

  9. Understanding herding based on a co-evolutionary model for strategy and game structure

    International Nuclear Information System (INIS)

    Wang, Tao; Huang, Keke; Cheng, Yuan; Zheng, Xiaoping

    2015-01-01

    Highlights: •We model herding effect in emergency from perspective of evolutionary game theory. •Rational subpopulation survives only when the game parameter is significantly large. •Herding effect may arise if the relative rewarding for rational agents is small. •Increasing the relative rewarding for rational agents will prevent herding effect. •The evolution result is unstable if the game parameter approaches critical points. -- Abstract: So far, there has been no conclusion on the mechanism for herding, which is often discussed in the academia. Assuming escaping behavior of individuals in emergency is rational rather than out of panic according to recent findings in social psychology, we investigate the behavioral evolution of large crowds from the perspective of evolutionary game theory. Specifically, evolution of the whole population divided into two subpopulations, namely the co-evolution of strategy and game structure, is numerically simulated based on the game theoretical models built and the evolutionary rule designed, and a series of phenomena including extinction of one subpopulation and herding effect are predicted in the proposed framework. Furthermore, if the rewarding for rational agents becomes significantly larger than that for emotional ones, herding effect will disappear. It is exciting that some phase transition points with interesting properties for the system can be found. In addition, our model framework is able to explain the fact that it is difficult for mavericks to prevail in society. The current results of this work will be helpful in understanding and restraining herding effect in real life

  10. A molecular phylogeny of nephilid spiders: evolutionary history of a model lineage.

    Science.gov (United States)

    Kuntner, Matjaž; Arnedo, Miquel A; Trontelj, Peter; Lokovšek, Tjaša; Agnarsson, Ingi

    2013-12-01

    The pantropical orb web spider family Nephilidae is known for the most extreme sexual size dimorphism among terrestrial animals. Numerous studies have made Nephilidae, particularly Nephila, a model lineage in evolutionary research. However, a poorly understood phylogeny of this lineage, relying only on morphology, has prevented thorough evolutionary syntheses of nephilid biology. We here use three nuclear and five mitochondrial genes for 28 out of 40 nephilid species to provide a more robust nephilid phylogeny and infer clade ages in a fossil-calibrated Bayesian framework. We complement the molecular analyses with total evidence analysis including morphology. All analyses find strong support for nephilid monophyly and exclusivity and the monophyly of the genera Herennia and Clitaetra. The inferred phylogenetic structure within Nephilidae is novel and conflicts with morphological phylogeny and traditional taxonomy. Nephilengys species fall into two clades, one with Australasian species (true Nephilengys) as sister to Herennia, and another with Afrotropical species (Nephilingis Kuntner new genus) as sister to a clade containing Clitaetra plus most currently described Nephila. Surprisingly, Nephila is also diphyletic, with true Nephila containing N. pilipes+N. constricta, and the second clade with all other species sister to Clitaetra; this "Nephila" clade is further split into an Australasian clade that also contains the South American N. sexpunctata and the Eurasian N. clavata, and an African clade that also contains the Panamerican N. clavipes. An approximately unbiased test constraining the monophyly of Nephilengys, Nephila, and Nephilinae (Nephila, Nephilengys, Herennia), respectively, rejected Nephilengys monophyly, but not that of Nephila and Nephilinae. Further data are therefore necessary to robustly test these two new, but inconclusive findings, and also to further test the precise placement of Nephilidae within the Araneoidea. For divergence date estimation

  11. Democratizing evolutionary biology, lessons from insects

    DEFF Research Database (Denmark)

    Dunn, Robert Roberdeau; Beasley, DeAnna E.

    2016-01-01

    The engagement of the public in the scientific process is an old practice. Yet with recent advances in technology, the role of the citizen scientist in studying evolutionary processes has increased. Insects provide ideal models for understanding these evolutionary processes at large scales. This ...

  12. Evolutionary Explanations of Eating Disorders

    Directory of Open Access Journals (Sweden)

    Igor Kardum

    2008-12-01

    Full Text Available This article reviews several most important evolutionary mechanisms that underlie eating disorders. The first part clarifies evolutionary foundations of mental disorders and various mechanisms leading to their development. In the second part selective pressures and evolved adaptations causing contemporary epidemic of obesity as well as differences in dietary regimes and life-style between modern humans and their ancestors are described. Concerning eating disorders, a number of current evolutionary explanations of anorexia nervosa are presented together with their main weaknesses. Evolutionary explanations of eating disorders based on the reproductive suppression hypothesis and its variants derived from kin selection theory and the model of parental manipulation were elaborated. The sexual competition hypothesis of eating disorder, adapted to flee famine hypothesis as well as explanation based on the concept of social attention holding power and the need to belonging were also explained. The importance of evolutionary theory in modern conceptualization and research of eating disorders is emphasized.

  13. Hybrid fitness, adaptation and evolutionary diversification: lessons learned from Louisiana Irises.

    Science.gov (United States)

    Arnold, M L; Ballerini, E S; Brothers, A N

    2012-03-01

    Estimates of hybrid fitness have been used as either a platform for testing the potential role of natural hybridization in the evolution of species and species complexes or, alternatively, as a rationale for dismissing hybridization events as being of any evolutionary significance. From the time of Darwin's publication of The Origin, through the neo-Darwinian synthesis, to the present day, the observation of variability in hybrid fitness has remained a challenge for some models of speciation. Yet, Darwin and others have reported the elevated fitness of hybrid genotypes under certain environmental conditions. In modern scientific terminology, this observation reflects the fact that hybrid genotypes can demonstrate genotype × environment interactions. In the current review, we illustrate the development of one plant species complex, namely the Louisiana Irises, into a 'model system' for investigating hybrid fitness and the role of genetic exchange in adaptive evolution and diversification. In particular, we will argue that a multitude of approaches, involving both experimental and natural environments, and incorporating both manipulative analyses and surveys of natural populations, are necessary to adequately test for the evolutionary significance of introgressive hybridization. An appreciation of the variability of hybrid fitness leads to the conclusion that certain genetic signatures reflect adaptive evolution. Furthermore, tests of the frequency of allopatric versus sympatric/parapatric divergence (that is, divergence with ongoing gene flow) support hybrid genotypes as a mechanism of evolutionary diversification in numerous species complexes.

  14. General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models.

    Science.gov (United States)

    de Villemereuil, Pierre; Schielzeth, Holger; Nakagawa, Shinichi; Morrissey, Michael

    2016-11-01

    Methods for inference and interpretation of evolutionary quantitative genetic parameters, and for prediction of the response to selection, are best developed for traits with normal distributions. Many traits of evolutionary interest, including many life history and behavioral traits, have inherently nonnormal distributions. The generalized linear mixed model (GLMM) framework has become a widely used tool for estimating quantitative genetic parameters for nonnormal traits. However, whereas GLMMs provide inference on a statistically convenient latent scale, it is often desirable to express quantitative genetic parameters on the scale upon which traits are measured. The parameters of fitted GLMMs, despite being on a latent scale, fully determine all quantities of potential interest on the scale on which traits are expressed. We provide expressions for deriving each of such quantities, including population means, phenotypic (co)variances, variance components including additive genetic (co)variances, and parameters such as heritability. We demonstrate that fixed effects have a strong impact on those parameters and show how to deal with this by averaging or integrating over fixed effects. The expressions require integration of quantities determined by the link function, over distributions of latent values. In general cases, the required integrals must be solved numerically, but efficient methods are available and we provide an implementation in an R package, QGglmm. We show that known formulas for quantities such as heritability of traits with binomial and Poisson distributions are special cases of our expressions. Additionally, we show how fitted GLMM can be incorporated into existing methods for predicting evolutionary trajectories. We demonstrate the accuracy of the resulting method for evolutionary prediction by simulation and apply our approach to data from a wild pedigreed vertebrate population. Copyright © 2016 de Villemereuil et al.

  15. Integrating evolutionary game theory into an agent-based model of ductal carcinoma in situ: Role of gap junctions in cancer progression.

    Science.gov (United States)

    Malekian, Negin; Habibi, Jafar; Zangooei, Mohammad Hossein; Aghakhani, Hojjat

    2016-11-01

    There are many cells with various phenotypic behaviors in cancer interacting with each other. For example, an apoptotic cell may induce apoptosis in adjacent cells. A living cell can also protect cells from undergoing apoptosis and necrosis. These survival and death signals are propagated through interaction pathways between adjacent cells called gap junctions. The function of these signals depends on the cellular context of the cell receiving them. For instance, a receiver cell experiencing a low level of oxygen may interpret a received survival signal as an apoptosis signal. In this study, we examine the effect of these signals on tumor growth. We make an evolutionary game theory component in order to model the signal propagation through gap junctions. The game payoffs are defined as a function of cellular context. Then, the game theory component is integrated into an agent-based model of tumor growth. After that, the integrated model is applied to ductal carcinoma in situ, a type of early stage breast cancer. Different scenarios are explored to observe the impact of the gap junction communication and parameters of the game theory component on cancer progression. We compare these scenarios by using the Wilcoxon signed-rank test. The Wilcoxon signed-rank test succeeds in proving a significant difference between the tumor growth of the model before and after considering the gap junction communication. The Wilcoxon signed-rank test also proves that the tumor growth significantly depends on the oxygen threshold of turning survival signals into apoptosis. In this study, the gap junction communication is modeled by using evolutionary game theory to illustrate its role at early stage cancers such as ductal carcinoma in situ. This work indicates that the gap junction communication and the oxygen threshold of turning survival signals into apoptosis can notably affect cancer progression. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  16. BEAST: Bayesian evolutionary analysis by sampling trees

    Directory of Open Access Journals (Sweden)

    Drummond Alexei J

    2007-11-01

    Full Text Available Abstract Background The evolutionary analysis of molecular sequence variation is a statistical enterprise. This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics. Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree. A large number of popular stochastic models of sequence evolution are provided and tree-based models suitable for both within- and between-species sequence data are implemented. Results BEAST version 1.4.6 consists of 81000 lines of Java source code, 779 classes and 81 packages. It provides models for DNA and protein sequence evolution, highly parametric coalescent analysis, relaxed clock phylogenetics, non-contemporaneous sequence data, statistical alignment and a wide range of options for prior distributions. BEAST source code is object-oriented, modular in design and freely available at http://beast-mcmc.googlecode.com/ under the GNU LGPL license. Conclusion BEAST is a powerful and flexible evolutionary analysis package for molecular sequence variation. It also provides a resource for the further development of new models and statistical methods of evolutionary analysis.

  17. Exaptation in human evolution: how to test adaptive vs exaptive evolutionary hypotheses.

    Science.gov (United States)

    Pievani, Telmo; Serrelli, Emanuele

    2011-01-01

    Palaeontologists, Stephen J. Gould and Elisabeth Vrba, introduced the term "ex-aptation" with the aim of improving and enlarging the scientific language available to researchers studying the evolution of any useful character, instead of calling it an "adaptation" by default, coming up with what Gould named an "extended taxonomy of fitness". With the extension to functional co-optations from non-adaptive structures ("spandrels"), the notion of exaptation expanded and revised the neo-Darwinian concept of "pre-adaptation" (which was misleading, for Gould and Vrba, suggesting foreordination). Exaptation is neither a "saltationist" nor an "anti-Darwinian" concept and, since 1982, has been adopted by many researchers in evolutionary and molecular biology, and particularly in human evolution. Exaptation has also been contested. Objections include the "non-operationality objection".We analyze the possible operationalization of this concept in two recent studies, and identify six directions of empirical research, which are necessary to test "adaptive vs. exaptive" evolutionary hypotheses. We then comment on a comprehensive survey of literature (available online), and on the basis of this we make a quantitative and qualitative evaluation of the adoption of the term among scientists who study human evolution. We discuss the epistemic conditions that may have influenced the adoption and appropriate use of exaptation, and comment on the benefits of an "extended taxonomy of fitness" in present and future studies concerning human evolution.

  18. Characterizing Phase Transitions in a Model of Neutral Evolutionary Dynamics

    Science.gov (United States)

    Scott, Adam; King, Dawn; Bahar, Sonya

    2013-03-01

    An evolutionary model was recently introduced for sympatric, phenotypic evolution over a variable fitness landscape with assortative mating (Dees & Bahar 2010). Organisms in the model are described by coordinates in a two-dimensional phenotype space, born at random coordinates with limited variation from their parents as determined by a mutation parameter, mutability. The model has been extended to include both neutral evolution and asexual reproduction in Scott et al (submitted). It has been demonstrated that a second order, non-equilibrium phase transition occurs for the temporal dynamics as the mutability is varied, for both the original model and for neutral conditions. This transition likely belongs to the directed percolation universality class. In contrast, the spatial dynamics of the model shows characteristics of an ordinary percolation phase transition. Here, we characterize the phase transitions exhibited by this model by determining critical exponents for the relaxation times, characteristic lengths, and cluster (species) mass distributions. Missouri Research Board; J.S. McDonnell Foundation

  19. A New DG Multiobjective Optimization Method Based on an Improved Evolutionary Algorithm

    Directory of Open Access Journals (Sweden)

    Wanxing Sheng

    2013-01-01

    Full Text Available A distribution generation (DG multiobjective optimization method based on an improved Pareto evolutionary algorithm is investigated in this paper. The improved Pareto evolutionary algorithm, which introduces a penalty factor in the objective function constraints, uses an adaptive crossover and a mutation operator in the evolutionary process and combines a simulated annealing iterative process. The proposed algorithm is utilized to the optimize DG injection models to maximize DG utilization while minimizing system loss and environmental pollution. A revised IEEE 33-bus system with multiple DG units was used to test the multiobjective optimization algorithm in a distribution power system. The proposed algorithm was implemented and compared with the strength Pareto evolutionary algorithm 2 (SPEA2, a particle swarm optimization (PSO algorithm, and nondominated sorting genetic algorithm II (NGSA-II. The comparison of the results demonstrates the validity and practicality of utilizing DG units in terms of economic dispatch and optimal operation in a distribution power system.

  20. Nash evolutionary algorithms : Testing problem size in reconstruction problems in frame structures

    OpenAIRE

    Greiner, D.; Periaux, Jacques; Emperador, J.M.; Galván, B.; Winter, G.

    2016-01-01

    The use of evolutionary algorithms has been enhanced in recent years for solving real engineering problems, where the requirements of intense computational calculations are needed, especially when computational engineering simulations are involved (use of finite element method, boundary element method, etc). The coupling of game-theory concepts in evolutionary algorithms has been a recent line of research which could enhance the efficiency of the optimum design procedure and th...

  1. A Study On Traditional And Evolutionary Software Development Models

    Directory of Open Access Journals (Sweden)

    Kamran Rasheed

    2017-07-01

    Full Text Available Today Computing technologies are becoming the pioneers of the organizations and helpful in individual functionality i.e. added to computing device we need to add softwares. Set of instruction or computer program is known as software. The development of software is done through some traditional or some new or evolutionary models. Software development is becoming a key and a successful business nowadays. Without software all hardware is useless. Some collective steps that are performed in the development of these are known as Software development life cycle SDLC. There are some adaptive and predictive models for developing software. Predictive mean already known like WATERFALL Spiral Prototype and V-shaped models while Adaptive model include agile Scrum. All methodologies of both adaptive and predictive have their own procedure and steps. Predictive are Static and Adaptive are dynamic mean change cannot be made to the predictive while adaptive have the capability of changing. The purpose of this study is to get familiar with all these and discuss their uses and steps of development. This discussion will be helpful in deciding which model they should use in which circumstance and what are the development step including in each model.

  2. Theoretical Approaches in Evolutionary Ecology: Environmental Feedback as a Unifying Perspective.

    Science.gov (United States)

    Lion, Sébastien

    2018-01-01

    Evolutionary biology and ecology have a strong theoretical underpinning, and this has fostered a variety of modeling approaches. A major challenge of this theoretical work has been to unravel the tangled feedback loop between ecology and evolution. This has prompted the development of two main classes of models. While quantitative genetics models jointly consider the ecological and evolutionary dynamics of a focal population, a separation of timescales between ecology and evolution is assumed by evolutionary game theory, adaptive dynamics, and inclusive fitness theory. As a result, theoretical evolutionary ecology tends to be divided among different schools of thought, with different toolboxes and motivations. My aim in this synthesis is to highlight the connections between these different approaches and clarify the current state of theory in evolutionary ecology. Central to this approach is to make explicit the dependence on environmental dynamics of the population and evolutionary dynamics, thereby materializing the eco-evolutionary feedback loop. This perspective sheds light on the interplay between environmental feedback and the timescales of ecological and evolutionary processes. I conclude by discussing some potential extensions and challenges to our current theoretical understanding of eco-evolutionary dynamics.

  3. THE APPLICATION OF AN EVOLUTIONARY ALGORITHM TO THE OPTIMIZATION OF A MESOSCALE METEOROLOGICAL MODEL

    Energy Technology Data Exchange (ETDEWEB)

    Werth, D.; O' Steen, L.

    2008-02-11

    We show that a simple evolutionary algorithm can optimize a set of mesoscale atmospheric model parameters with respect to agreement between the mesoscale simulation and a limited set of synthetic observations. This is illustrated using the Regional Atmospheric Modeling System (RAMS). A set of 23 RAMS parameters is optimized by minimizing a cost function based on the root mean square (rms) error between the RAMS simulation and synthetic data (observations derived from a separate RAMS simulation). We find that the optimization can be efficient with relatively modest computer resources, thus operational implementation is possible. The optimization efficiency, however, is found to depend strongly on the procedure used to perturb the 'child' parameters relative to their 'parents' within the evolutionary algorithm. In addition, the meteorological variables included in the rms error and their weighting are found to be an important factor with respect to finding the global optimum.

  4. Evolutionary algorithms for mobile ad hoc networks

    CERN Document Server

    Dorronsoro, Bernabé; Danoy, Grégoire; Pigné, Yoann; Bouvry, Pascal

    2014-01-01

    Describes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers in optimization and mobile networking. Mobile ad hoc networks (MANETs), vehicular networks (VANETs), sensor networks (SNs), and hybrid networks—each of these require a designer’s keen sense and knowledge of evolutionary algorithms in order to help with the common issues that plague professionals involved in optimization and mobile networking. This book introduces readers to both mobile ad hoc networks and evolutionary algorithms, presenting basic concepts as well as detailed descriptions of each. It demonstrates how metaheuristics and evolutionary algorithms (EAs) can be used to help provide low-cost operations in the optimization process—allowing designers to put some “intelligence” or sophistication into the design. It also offers efficient and accurate information on dissemination algorithms topology management, and mobility models to address challenges in the ...

  5. Evolutionary dynamics with fluctuating population sizes and strong mutualism

    Science.gov (United States)

    Chotibut, Thiparat; Nelson, David R.

    2015-08-01

    Game theory ideas provide a useful framework for studying evolutionary dynamics in a well-mixed environment. This approach, however, typically enforces a strictly fixed overall population size, deemphasizing natural growth processes. We study a competitive Lotka-Volterra model, with number fluctuations, that accounts for natural population growth and encompasses interaction scenarios typical of evolutionary games. We show that, in an appropriate limit, the model describes standard evolutionary games with both genetic drift and overall population size fluctuations. However, there are also regimes where a varying population size can strongly influence the evolutionary dynamics. We focus on the strong mutualism scenario and demonstrate that standard evolutionary game theory fails to describe our simulation results. We then analytically and numerically determine fixation probabilities as well as mean fixation times using matched asymptotic expansions, taking into account the population size degree of freedom. These results elucidate the interplay between population dynamics and evolutionary dynamics in well-mixed systems.

  6. Evolutionary dynamics with fluctuating population sizes and strong mutualism.

    Science.gov (United States)

    Chotibut, Thiparat; Nelson, David R

    2015-08-01

    Game theory ideas provide a useful framework for studying evolutionary dynamics in a well-mixed environment. This approach, however, typically enforces a strictly fixed overall population size, deemphasizing natural growth processes. We study a competitive Lotka-Volterra model, with number fluctuations, that accounts for natural population growth and encompasses interaction scenarios typical of evolutionary games. We show that, in an appropriate limit, the model describes standard evolutionary games with both genetic drift and overall population size fluctuations. However, there are also regimes where a varying population size can strongly influence the evolutionary dynamics. We focus on the strong mutualism scenario and demonstrate that standard evolutionary game theory fails to describe our simulation results. We then analytically and numerically determine fixation probabilities as well as mean fixation times using matched asymptotic expansions, taking into account the population size degree of freedom. These results elucidate the interplay between population dynamics and evolutionary dynamics in well-mixed systems.

  7. Can manipulations of cognitive load be used to test evolutionary hypotheses?

    Science.gov (United States)

    Barrett, H Clark; Frederick, David A; Haselton, Martie G; Kurzban, Robert

    2006-09-01

    D. DeSteno, M. Y. Bartlett, J. Braverman, and P. Salovey proposed that if sex-differentiated responses to infidelity are evolved, then they should be automatic, and therefore cognitive load should not attenuate them. DeSteno et al. found smaller sex differences in response to sexual versus emotional infidelity among participants under cognitive load, an effect interpreted as evidence against the evolutionary hypothesis. This logic is faulty. Cognitive load probably affects mechanisms involved in simulating infidelity experiences, thus seriously challenging the usefulness of cognitive load manipulations in testing hypotheses involving simulation. The method also entails the assumption that evolved jealousy mechanisms are necessarily automatic, an assumption not supported by theory or evidence. Regardless of how the jealousy debate is eventually settled, cognitive load manipulations cannot rule out the operation of evolved mechanisms. ((c) 2006 APA, all rights reserved).

  8. Evolutionary change in physiological phenotypes along the human lineage.

    Science.gov (United States)

    Vining, Alexander Q; Nunn, Charles L

    2016-01-01

    Research in evolutionary medicine provides many examples of how evolution has shaped human susceptibility to disease. Traits undergoing rapid evolutionary change may result in associated costs or reduce the energy available to other traits. We hypothesize that humans have experienced more such changes than other primates as a result of major evolutionary change along the human lineage. We investigated 41 physiological traits across 50 primate species to identify traits that have undergone marked evolutionary change along the human lineage. We analysed the data using two Bayesian phylogenetic comparative methods. One approach models trait covariation in non-human primates and predicts human phenotypes to identify whether humans are evolutionary outliers. The other approach models adaptive shifts under an Ornstein-Uhlenbeck model of evolution to assess whether inferred shifts are more common on the human branch than on other primate lineages. We identified four traits with strong evidence for an evolutionary increase on the human lineage (amylase, haematocrit, phosphorus and monocytes) and one trait with strong evidence for decrease (neutrophilic bands). Humans exhibited more cases of distinct evolutionary change than other primates. Human physiology has undergone increased evolutionary change compared to other primates. Long distance running may have contributed to increases in haematocrit and mean corpuscular haemoglobin concentration, while dietary changes are likely related to increases in amylase. In accordance with the pathogen load hypothesis, human monocyte levels were increased, but many other immune-related measures were not. Determining the mechanisms underlying conspicuous evolutionary change in these traits may provide new insights into human disease. The Author(s) 2016. Published by Oxford University Press on behalf of the Foundation for Evolution, Medicine, and Public Health.

  9. Numerical Simulation of Entropy Growth for a Nonlinear Evolutionary Model of Random Markets

    Directory of Open Access Journals (Sweden)

    Mahdi Keshtkar

    2016-01-01

    Full Text Available In this communication, the generalized continuous economic model for random markets is revisited. In this model for random markets, agents trade by pairs and exchange their money in a random and conservative way. They display the exponential wealth distribution as asymptotic equilibrium, independently of the effectiveness of the transactions and of the limitation of the total wealth. In the current work, entropy of mentioned model is defined and then some theorems on entropy growth of this evolutionary problem are given. Furthermore, the entropy increasing by simulation on some numerical examples is verified.

  10. Evolutionary sequence of models of planetary nebulae

    International Nuclear Information System (INIS)

    Vil'koviskij, Eh.Ya.; Kondrat'eva, L.N.; Tambovtseva, L.V.

    1983-01-01

    The evolutionary sequences of model planetary nebulae of different masses have been calculated. The computed emission line intensities are compared with the observed ones by means of the parameter ''reduced size of the nebula'', Rsub(n). It is shown that the evolution tracks of Schonberner for the central stars are consistent with the observed data. Part of ionized mass Mi in any nebulae does not not exceed 0.3 b and in the average Msu(i) 3 years at actual values of radius Rsub(i) <0.025 ps. Then the luminosity growth slows down to the maximum temperature which central star reaches and decreases with sharp decrease of the star luminosity. At that, the radius of ionized zone of greater mass nebulae can even decrease, inspite of the constant expansion of the nebula. As a result nebulae of great masses having undergone the evolution can be included in the number of observed compact objects (Rsub(n) < 0.1 ps)

  11. When It’s Good to Feel Bad: An Evolutionary Model of Guilt and Apology

    Directory of Open Access Journals (Sweden)

    Sarita Rosenstock

    2018-03-01

    Full Text Available We use techniques from evolutionary game theory to analyze the conditions under which guilt can provide individual fitness benefits, and so evolve. In particular, we focus on the benefits of guilty apology. We consider models where actors err in an iterated prisoner’s dilemma and have the option to apologize. Guilt either improves the trustworthiness of apology or imposes a cost on actors who apologize. We analyze the stability and likelihood of evolution of such a “guilt-prone” strategy against cooperators, defectors, grim triggers, and individuals who offer fake apologies, but continue to defect. We find that in evolutionary models guilty apology is more likely to evolve in cases where actors interact repeatedly over long periods of time, where the costs of apology are low or moderate, and where guilt is hard to fake. Researchers interested in naturalized ethics, and emotion researchers, can employ these results to assess the plausibility of fuller accounts of the evolution of guilt.

  12. Generator Approach to Evolutionary Optimization of Catalysts and its Integration with Surrogate Modeling

    Czech Academy of Sciences Publication Activity Database

    Holeňa, Martin; Linke, D.; Rodemerck, U.

    2011-01-01

    Roč. 159, č. 1 (2011), s. 84-95 ISSN 0920-5861 R&D Projects: GA ČR GA201/08/0802 Institutional research plan: CEZ:AV0Z10300504 Keywords : optimization of catalytic materials * evolutionary optimization * surrogate modeling * artificial neural networks * multilayer perceptron * regression boosting Subject RIV: IN - Informatics, Computer Science Impact factor: 3.407, year: 2011

  13. Evolutionary Nephrology.

    Science.gov (United States)

    Chevalier, Robert L

    2017-05-01

    Progressive kidney disease follows nephron loss, hyperfiltration, and incomplete repair, a process described as "maladaptive." In the past 20 years, a new discipline has emerged that expands research horizons: evolutionary medicine. In contrast to physiologic (homeostatic) adaptation, evolutionary adaptation is the result of reproductive success that reflects natural selection. Evolutionary explanations for physiologically maladaptive responses can emerge from mismatch of the phenotype with environment or evolutionary tradeoffs. Evolutionary adaptation to a terrestrial environment resulted in a vulnerable energy-consuming renal tubule and a hypoxic, hyperosmolar microenvironment. Natural selection favors successful energy investment strategy: energy is allocated to maintenance of nephron integrity through reproductive years, but this declines with increasing senescence after ~40 years of age. Risk factors for chronic kidney disease include restricted fetal growth or preterm birth (life history tradeoff resulting in fewer nephrons), evolutionary selection for APOL1 mutations (that provide resistance to trypanosome infection, a tradeoff), and modern life experience (Western diet mismatch leading to diabetes and hypertension). Current advances in genomics, epigenetics, and developmental biology have revealed proximate causes of kidney disease, but attempts to slow kidney disease remain elusive. Evolutionary medicine provides a complementary approach by addressing ultimate causes of kidney disease. Marked variation in nephron number at birth, nephron heterogeneity, and changing susceptibility to kidney injury throughout life history are the result of evolutionary processes. Combined application of molecular genetics, evolutionary developmental biology (evo-devo), developmental programming and life history theory may yield new strategies for prevention and treatment of chronic kidney disease.

  14. Evolutionary Nephrology

    Directory of Open Access Journals (Sweden)

    Robert L. Chevalier

    2017-05-01

    Full Text Available Progressive kidney disease follows nephron loss, hyperfiltration, and incomplete repair, a process described as “maladaptive.” In the past 20 years, a new discipline has emerged that expands research horizons: evolutionary medicine. In contrast to physiologic (homeostatic adaptation, evolutionary adaptation is the result of reproductive success that reflects natural selection. Evolutionary explanations for physiologically maladaptive responses can emerge from mismatch of the phenotype with environment or from evolutionary tradeoffs. Evolutionary adaptation to a terrestrial environment resulted in a vulnerable energy-consuming renal tubule and a hypoxic, hyperosmolar microenvironment. Natural selection favors successful energy investment strategy: energy is allocated to maintenance of nephron integrity through reproductive years, but this declines with increasing senescence after ∼40 years of age. Risk factors for chronic kidney disease include restricted fetal growth or preterm birth (life history tradeoff resulting in fewer nephrons, evolutionary selection for APOL1 mutations (which provide resistance to trypanosome infection, a tradeoff, and modern life experience (Western diet mismatch leading to diabetes and hypertension. Current advances in genomics, epigenetics, and developmental biology have revealed proximate causes of kidney disease, but attempts to slow kidney disease remain elusive. Evolutionary medicine provides a complementary approach by addressing ultimate causes of kidney disease. Marked variation in nephron number at birth, nephron heterogeneity, and changing susceptibility to kidney injury throughout the life history are the result of evolutionary processes. Combined application of molecular genetics, evolutionary developmental biology (evo-devo, developmental programming, and life history theory may yield new strategies for prevention and treatment of chronic kidney disease.

  15. [Sex differences in sexual versus emotional jealousy: evolutionary approach and recent discussions].

    Science.gov (United States)

    Demirtaş Madran, H Andaç

    2008-01-01

    Sex differences in jealousy have been reported widely in the social psychological, clinical psychological, psychiatric, and anthropological literature. Many of the studies conducted on jealousy have focused on the sex differences in the level of reported jealousy. Most research has reported that there is no difference between men and women regarding the level of reported jealousy, but there are some sex differences between sexual and emotional jealousy. Evolutionary psychologists divide jealousy into 2 dimensions based on their observations and empirical research findings: Sexual jealousy and emotional jealousy. Sexual jealousy is knowing or suspecting that one's partners has had sexual relationship with a third person, whereas emotional jealousy is triggered by partner's emotional involvement with and/or love for another person. The parental investment model, which extended Darwin's explanations of sexual selection, provides a useful theoretical framework for studying sexual and emotional jealousy. According to this model sexual selection is driven by differential parental investment by men and women; men should experience more sexual jealousy than women and women should experience more emotional jealousy than men. Considerable research has focused on testing this hypothesis and, with a few exceptions, the results are generally consistent with the evolutionary account. In this study, firstly, a brief definition of the sexual and emotional jealousy will be given. Then, sex differences in sexual and emotional jealousy will be explained according to the evolutionary theory. Finally, the results of empirical studies and critiques of the evolutionary model will be given.

  16. Do arms races punctuate evolutionary stasis? Unified insights from phylogeny, phylogeography and microevolutionary processes.

    Science.gov (United States)

    Toju, Hirokazu; Sota, Teiji

    2009-09-01

    One of the major controversies in evolutionary biology concerns the processes underlying macroevolutionary patterns in which prolonged stasis is disrupted by rapid, short-term evolution that leads species to new adaptive zones. Recent advances in the understanding of contemporary evolution have suggested that such rapid evolution can occur in the wild as a result of environmental changes. Here, we examined a novel hypothesis that evolutionary stasis is punctuated by co-evolutionary arms races, which continuously alter adaptive peaks and landscapes. Based on the phylogeny of long-mouthed weevils in the genus Curculio, likelihood ratio tests showed that the macroevolutionary pattern of the weevils coincides with the punctuational evolution model. A coalescent analysis of a species, Curculio camelliae, the mouthpart of which has diverged considerably among populations because of an arms race with its host plant, further suggested that major evolutionary shifts had occurred within 7000 generations. Through a microevolutionary analysis of the species, we also found that natural selection acting through co-evolutionary interactions is potentially strong enough to drive rapid evolutionary shifts between adaptive zones. Overall, we posit that co-evolution is an important factor driving the history of organismal evolution.

  17. Optimality and stability of symmetric evolutionary games with applications in genetic selection.

    Science.gov (United States)

    Huang, Yuanyuan; Hao, Yiping; Wang, Min; Zhou, Wen; Wu, Zhijun

    2015-06-01

    Symmetric evolutionary games, i.e., evolutionary games with symmetric fitness matrices, have important applications in population genetics, where they can be used to model for example the selection and evolution of the genotypes of a given population. In this paper, we review the theory for obtaining optimal and stable strategies for symmetric evolutionary games, and provide some new proofs and computational methods. In particular, we review the relationship between the symmetric evolutionary game and the generalized knapsack problem, and discuss the first and second order necessary and sufficient conditions that can be derived from this relationship for testing the optimality and stability of the strategies. Some of the conditions are given in different forms from those in previous work and can be verified more efficiently. We also derive more efficient computational methods for the evaluation of the conditions than conventional approaches. We demonstrate how these conditions can be applied to justifying the strategies and their stabilities for a special class of genetic selection games including some in the study of genetic disorders.

  18. Exponential Expansion in Evolutionary Economics

    DEFF Research Database (Denmark)

    Frederiksen, Peter; Jagtfelt, Tue

    2013-01-01

    This article attempts to solve current problems of conceptual fragmentation within the field of evolutionary economics. One of the problems, as noted by a number of observers, is that the field suffers from an assemblage of fragmented and scattered concepts (Boschma and Martin 2010). A solution...... to this problem is proposed in the form of a model of exponential expansion. The model outlines the overall structure and function of the economy as exponential expansion. The pictographic model describes four axiomatic concepts and their exponential nature. The interactive, directional, emerging and expanding...... concepts are described in detail. Taken together it provides the rudimentary aspects of an economic system within an analytical perspective. It is argued that the main dynamic processes of the evolutionary perspective can be reduced to these four concepts. The model and concepts are evaluated in the light...

  19. An Examination of the Impact of Harsh Parenting Contexts on Children's Adaptation within an Evolutionary Framework

    Science.gov (United States)

    Sturge-Apple, Melissa L.; Davies, Patrick T.; Martin, Meredith J.; Cicchetti, Dante; Hentges, Rochelle F.

    2012-01-01

    The current study tests whether propositions set forth in an evolutionary model of temperament (Korte, Koolhaas, Wingfield, & McEwen, 2005) may enhance our understanding of children's differential susceptibility to unsupportive and harsh caregiving practices. Guided by this model, we examined whether children's behavioral strategies for coping…

  20. Evolutionary game theory and organizational ecology: The case of resource-partitioning theory

    OpenAIRE

    ZHOU, Chaohong; VAN WITTELOOSTUIJN, Arjen

    2009-01-01

    Abstract: In this paper, we construct a mathematical model that applies tools from evolutionary game theory to issues in organizational ecology. Evolutionary game theory shares the key feature of mathematical rigor with the industrial organization tradition, but is similar to organizational ecology by emphasizing evolutionary dynamics. Evolutionary game theory may well be a complementary modeling tool for the analytical study of organizational ecology issues, next to formal logic, standard ga...

  1. Evolutionary adaptations: theoretical and practical implications for visual ergonomics.

    Science.gov (United States)

    Fostervold, Knut Inge; Watten, Reidulf G; Volden, Frode

    2014-01-01

    The literature discussing visual ergonomics often mention that human vision is adapted to light emitted by the sun. However, theoretical and practical implications of this viewpoint is seldom discussed or taken into account. The paper discusses some of the main theoretical implications of an evolutionary approach to visual ergonomics. Based on interactional theory and ideas from ecological psychology an evolutionary stress model is proposed as a theoretical framework for future research in ergonomics and human factors. The model stresses the importance of developing work environments that fits with our evolutionary adaptations. In accordance with evolutionary psychology, the environment of evolutionary adaptedness (EEA) and evolutionarily-novel environments (EN) are used as key concepts. Using work with visual display units (VDU) as an example, the paper discusses how this knowledge can be utilized in an ergonomic analysis of risk factors in the work environment. The paper emphasises the importance of incorporating evolutionary theory in the field of ergonomics. Further, the paper encourages scientific practices that further our understanding of any phenomena beyond the borders of traditional proximal explanations.

  2. A network growth model based on the evolutionary ultimatum game

    International Nuclear Information System (INIS)

    Deng, L L; Zhou, G G; Cai, J H; Wang, C; Tang, W S

    2012-01-01

    In this paper, we provide a network growth model with incorporation into the ultimatum game dynamics. The network grows on the basis of the payoff-oriented preferential attachment mechanism, where a new node is added into the network and attached preferentially to nodes with higher payoffs. The interplay between the network growth and the game dynamics gives rise to quite interesting dynamical behaviors. Simulation results show the emergence of altruistic behaviors in the ultimatum game, which is affected by the growing network structure. Compared with the static counterpart case, the levels of altruistic behaviors are promoted. The corresponding strategy distributions and wealth distributions are also presented to further demonstrate the strategy evolutionary dynamics. Subsequently, we turn to the topological properties of the evolved network, by virtue of some statistics. The most studied characteristic path length and the clustering coefficient of the network are shown to indicate their small-world effect. Then the degree distributions are analyzed to clarify the interplay of structure and evolutionary dynamics. In particular, the difference between our growth network and the static counterpart is revealed. To explain clearly the evolved networks, the rich-club ordering and the assortative mixing coefficient are exploited to reveal the degree correlation. (paper)

  3. MESA models of the evolutionary state of the interacting binary epsilon Aurigae

    Science.gov (United States)

    Gibson, Justus L.; Stencel, Robert E.

    2018-06-01

    Using MESA code (Modules for Experiments in Stellar Astrophysics, version 9575), an evaluation was made of the evolutionary state of the epsilon Aurigae binary system (HD 31964, F0Iap + disc). We sought to satisfy several observational constraints: (1) requiring evolutionary tracks to pass close to the current temperature and luminosity of the primary star; (2) obtaining a period near the observed value of 27.1 years; (3) matching a mass function of 3.0; (4) concurrent Roche lobe overflow and mass transfer; (5) an isotopic ratio 12C/13C = 5 and, (6) matching the interferometrically determined angular diameter. A MESA model starting with binary masses of 9.85 + 4.5 M⊙, with a 100 d initial period, produces a 1.2 + 10.6 M⊙ result having a 547 d period, and a single digit 12C/13C ratio. These values were reached near an age of 20 Myr, when the donor star comes close to the observed luminosity and temperature for epsilon Aurigae A, as a post-RGB/pre-AGB star. Contemporaneously, the accretor then appears as an upper main-sequence, early B-type star. This benchmark model can provide a basis for further exploration of this interacting binary, and other long-period binary stars.

  4. Sex differences in jealousy in evolutionary and cultural perspective : Tests from the Netherlands, Germany, and the United States

    NARCIS (Netherlands)

    Buunk, BP; Angleitner, A; Oubaid, [No Value; Buss, DM

    1996-01-01

    As predicted by models derived from evolutionary psychology, men within the United States have been shown to exhibit greater psychological and physiological distress to sexual than to emotional infidelity of their partner, and women have been shown to exhibit more distress to emotional than to

  5. Observational and evolutionary aspects of Wolf-Rayet stars

    International Nuclear Information System (INIS)

    Vanbeveren, D.

    1980-01-01

    The author considers (i) the binary status of Wolf-Rayet stars, (ii) the evolutionary status of Wolf-Rayet stars, (iii) the chemical abundances of Wolf-Rayet stars and (iv) evolutionary models for some known Wolf-Rayet systems. (G.T.H.)

  6. Kernel Method Based Human Model for Enhancing Interactive Evolutionary Optimization

    Science.gov (United States)

    Zhao, Qiangfu; Liu, Yong

    2015-01-01

    A fitness landscape presents the relationship between individual and its reproductive success in evolutionary computation (EC). However, discrete and approximate landscape in an original search space may not support enough and accurate information for EC search, especially in interactive EC (IEC). The fitness landscape of human subjective evaluation in IEC is very difficult and impossible to model, even with a hypothesis of what its definition might be. In this paper, we propose a method to establish a human model in projected high dimensional search space by kernel classification for enhancing IEC search. Because bivalent logic is a simplest perceptual paradigm, the human model is established by considering this paradigm principle. In feature space, we design a linear classifier as a human model to obtain user preference knowledge, which cannot be supported linearly in original discrete search space. The human model is established by this method for predicting potential perceptual knowledge of human. With the human model, we design an evolution control method to enhance IEC search. From experimental evaluation results with a pseudo-IEC user, our proposed model and method can enhance IEC search significantly. PMID:25879050

  7. Spatial multiobjective optimization of agricultural conservation practices using a SWAT model and an evolutionary algorithm.

    Science.gov (United States)

    Rabotyagov, Sergey; Campbell, Todd; Valcu, Adriana; Gassman, Philip; Jha, Manoj; Schilling, Keith; Wolter, Calvin; Kling, Catherine

    2012-12-09

    Finding the cost-efficient (i.e., lowest-cost) ways of targeting conservation practice investments for the achievement of specific water quality goals across the landscape is of primary importance in watershed management. Traditional economics methods of finding the lowest-cost solution in the watershed context (e.g.,(5,12,20)) assume that off-site impacts can be accurately described as a proportion of on-site pollution generated. Such approaches are unlikely to be representative of the actual pollution process in a watershed, where the impacts of polluting sources are often determined by complex biophysical processes. The use of modern physically-based, spatially distributed hydrologic simulation models allows for a greater degree of realism in terms of process representation but requires a development of a simulation-optimization framework where the model becomes an integral part of optimization. Evolutionary algorithms appear to be a particularly useful optimization tool, able to deal with the combinatorial nature of a watershed simulation-optimization problem and allowing the use of the full water quality model. Evolutionary algorithms treat a particular spatial allocation of conservation practices in a watershed as a candidate solution and utilize sets (populations) of candidate solutions iteratively applying stochastic operators of selection, recombination, and mutation to find improvements with respect to the optimization objectives. The optimization objectives in this case are to minimize nonpoint-source pollution in the watershed, simultaneously minimizing the cost of conservation practices. A recent and expanding set of research is attempting to use similar methods and integrates water quality models with broadly defined evolutionary optimization methods(3,4,9,10,13-15,17-19,22,23,25). In this application, we demonstrate a program which follows Rabotyagov et al.'s approach and integrates a modern and commonly used SWAT water quality model(7) with a

  8. Bridging the gap between Schumpeterian competition and evolutionary game theory

    DEFF Research Database (Denmark)

    Andersen, Esben Sloth

    This paper suggests that the analysis of Schumpeterian competition within the Nelson-Winter model should be complemented with evolutionary game theory. This model and its limitations for density-dependent Schumpeterian strategies are presented in terms of the equations of evolutionary dynamics. F...

  9. Population and evolutionary dynamics in spatially structured seasonally varying environments.

    Science.gov (United States)

    Reid, Jane M; Travis, Justin M J; Daunt, Francis; Burthe, Sarah J; Wanless, Sarah; Dytham, Calvin

    2018-03-25

    be occupied by different sets of resident and migrant individuals in different seasons, and where locations that can support reproduction can also be linked by dispersal. We outline key forms of within-individual and among-individual variation and structure in migration that could arise within such systems and interact with variation in individual survival, reproduction and dispersal to create complex population dynamics and evolutionary responses across locations, seasons, years and generations. Third, we review approaches by which population dynamic and eco-evolutionary models could be developed to test hypotheses regarding the dynamics and persistence of partially migratory meta-populations given diverse forms of seasonal environmental variation and change, and to forecast system-specific dynamics. To demonstrate one such approach, we use an evolutionary individual-based model to illustrate that multiple forms of partial migration can readily co-exist in a simple spatially structured landscape. Finally, we summarise recent empirical studies that demonstrate key components of demographic structure in partial migration, and demonstrate diverse associations with reproduction and survival. We thereby identify key theoretical and empirical knowledge gaps that remain, and consider multiple complementary approaches by which these gaps can be filled in order to elucidate population dynamic and eco-evolutionary responses to spatio-temporal seasonal environmental variation and change. © 2018 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.

  10. Evolutionary constrained optimization

    CERN Document Server

    Deb, Kalyanmoy

    2015-01-01

    This book makes available a self-contained collection of modern research addressing the general constrained optimization problems using evolutionary algorithms. Broadly the topics covered include constraint handling for single and multi-objective optimizations; penalty function based methodology; multi-objective based methodology; new constraint handling mechanism; hybrid methodology; scaling issues in constrained optimization; design of scalable test problems; parameter adaptation in constrained optimization; handling of integer, discrete and mix variables in addition to continuous variables; application of constraint handling techniques to real-world problems; and constrained optimization in dynamic environment. There is also a separate chapter on hybrid optimization, which is gaining lots of popularity nowadays due to its capability of bridging the gap between evolutionary and classical optimization. The material in the book is useful to researchers, novice, and experts alike. The book will also be useful...

  11. Evolutionary games on graphs

    Science.gov (United States)

    Szabó, György; Fáth, Gábor

    2007-07-01

    Game theory is one of the key paradigms behind many scientific disciplines from biology to behavioral sciences to economics. In its evolutionary form and especially when the interacting agents are linked in a specific social network the underlying solution concepts and methods are very similar to those applied in non-equilibrium statistical physics. This review gives a tutorial-type overview of the field for physicists. The first four sections introduce the necessary background in classical and evolutionary game theory from the basic definitions to the most important results. The fifth section surveys the topological complications implied by non-mean-field-type social network structures in general. The next three sections discuss in detail the dynamic behavior of three prominent classes of models: the Prisoner's Dilemma, the Rock-Scissors-Paper game, and Competing Associations. The major theme of the review is in what sense and how the graph structure of interactions can modify and enrich the picture of long term behavioral patterns emerging in evolutionary games.

  12. How altruism works: An evolutionary model of supply networks

    Science.gov (United States)

    Ge, Zehui; Zhang, Zi-Ke; Lü, Linyuan; Zhou, Tao; Xi, Ning

    2012-02-01

    Recently, supply networks have attracted increasing attention from the scientific community. However, it lacks serious consideration of social preference in Supply Chain Management. In this paper, we develop an evolutionary decision-making model to characterize the effects of suppliers' altruism in supply networks, and find that the performances of both suppliers and supply chains are improved by introducing the role of altruism. Furthermore, an interesting and reasonable phenomenon is discovered that the suppliers' and whole network's profits do not change monotonously with suppliers' altruistic preference, η, but reach the best at η=0.6 and η=0.4, respectively. This work may shed some light on the in-depth understanding of the effects of altruism for both research and commercial applications.

  13. Evolutionary Game Model Study of Construction Green Supply Chain Management under the Government Intervention

    Science.gov (United States)

    Xing, Yuanzhi; Deng, Xiaoyi

    2017-11-01

    The paper first has defined the concepts of green supply chain management and evolution game theory, and pointed out the characteristics of green supply chain management in construction. The main participants and key links of the construction green supply chain management are determined by constructing the organization framework. This paper established the evolutionary game model between construction enterprises and recycling enterprises for the green supply chain closed-loop structure. The waste recycling evolutionary stability equilibrium solution is obtained to explore the principle and effective scope of government policy intervention. This paper put forward the relevant countermeasures to the green supply chain management in construction recycling stage from the government point of view. The conclusion has reference value and guidance to the final product construction enterprises, recycling enterprises and the government during green supply chain.

  14. Evolutionary-Hierarchical Bases of the Formation of Cluster Model of Innovation Economic Development

    Directory of Open Access Journals (Sweden)

    Yuliya Vladimirovna Dubrovskaya

    2016-10-01

    Full Text Available The functioning of a modern economic system is based on the interaction of objects of different hierarchical levels. Thus, the problem of the study of innovation processes taking into account the mutual influence of the activities of these economic actors becomes important. The paper dwells evolutionary basis for the formation of models of innovation development on the basis of micro and macroeconomic analysis. Most of the concepts recognized that despite a big number of diverse models, the coordination of the relations between economic agents is of crucial importance for the successful innovation development. According to the results of the evolutionary-hierarchical analysis, the authors reveal key phases of the development of forms of business cooperation, science and government in the domestic economy. It has become the starting point of the conception of the characteristics of the interaction in the cluster models of innovation development of the economy. Considerable expectancies on improvement of the national innovative system are connected with the development of cluster and network structures. The main objective of government authorities is the formation of mechanisms and institutions that will foster cooperation between members of the clusters. The article explains that the clusters cannot become the factors in the growth of the national economy, not being an effective tool for interaction between the actors of the regional innovative systems.

  15. Multiobjective Multifactorial Optimization in Evolutionary Multitasking.

    Science.gov (United States)

    Gupta, Abhishek; Ong, Yew-Soon; Feng, Liang; Tan, Kay Chen

    2016-05-03

    In recent decades, the field of multiobjective optimization has attracted considerable interest among evolutionary computation researchers. One of the main features that makes evolutionary methods particularly appealing for multiobjective problems is the implicit parallelism offered by a population, which enables simultaneous convergence toward the entire Pareto front. While a plethora of related algorithms have been proposed till date, a common attribute among them is that they focus on efficiently solving only a single optimization problem at a time. Despite the known power of implicit parallelism, seldom has an attempt been made to multitask, i.e., to solve multiple optimization problems simultaneously. It is contended that the notion of evolutionary multitasking leads to the possibility of automated transfer of information across different optimization exercises that may share underlying similarities, thereby facilitating improved convergence characteristics. In particular, the potential for automated transfer is deemed invaluable from the standpoint of engineering design exercises where manual knowledge adaptation and reuse are routine. Accordingly, in this paper, we present a realization of the evolutionary multitasking paradigm within the domain of multiobjective optimization. The efficacy of the associated evolutionary algorithm is demonstrated on some benchmark test functions as well as on a real-world manufacturing process design problem from the composites industry.

  16. Evolutionary heritage influences Amazon tree ecology

    Science.gov (United States)

    Coelho de Souza, Fernanda; Dexter, Kyle G.; Phillips, Oliver L.; Brienen, Roel J. W.; Chave, Jerome; Galbraith, David R.; Lopez Gonzalez, Gabriela; Monteagudo Mendoza, Abel; Pennington, R. Toby; Poorter, Lourens; Alexiades, Miguel; Álvarez-Dávila, Esteban; Andrade, Ana; Aragão, Luis E. O. C.; Araujo-Murakami, Alejandro; Arets, Eric J. M. M.; Aymard C, Gerardo A.; Baraloto, Christopher; Barroso, Jorcely G.; Bonal, Damien; Boot, Rene G. A.; Camargo, José L. C.; Comiskey, James A.; Valverde, Fernando Cornejo; de Camargo, Plínio B.; Di Fiore, Anthony; Erwin, Terry L.; Feldpausch, Ted R.; Ferreira, Leandro; Fyllas, Nikolaos M.; Gloor, Emanuel; Herault, Bruno; Herrera, Rafael; Higuchi, Niro; Honorio Coronado, Eurídice N.; Killeen, Timothy J.; Laurance, William F.; Laurance, Susan; Lloyd, Jon; Lovejoy, Thomas E.; Malhi, Yadvinder; Maracahipes, Leandro; Marimon, Beatriz S.; Marimon-Junior, Ben H.; Mendoza, Casimiro; Morandi, Paulo; Neill, David A.; Vargas, Percy Núñez; Oliveira, Edmar A.; Lenza, Eddie; Palacios, Walter A.; Peñuela-Mora, Maria C.; Pipoly, John J.; Pitman, Nigel C. A.; Prieto, Adriana; Quesada, Carlos A.; Ramirez-Angulo, Hirma; Rudas, Agustin; Ruokolainen, Kalle; Salomão, Rafael P.; Silveira, Marcos; ter Steege, Hans; Thomas-Caesar, Raquel; van der Hout, Peter; van der Heijden, Geertje M. F.; van der Meer, Peter J.; Vasquez, Rodolfo V.; Vieira, Simone A.; Vilanova, Emilio; Vos, Vincent A.; Wang, Ophelia; Young, Kenneth R.; Zagt, Roderick J.; Baker, Timothy R.

    2016-01-01

    Lineages tend to retain ecological characteristics of their ancestors through time. However, for some traits, selection during evolutionary history may have also played a role in determining trait values. To address the relative importance of these processes requires large-scale quantification of traits and evolutionary relationships among species. The Amazonian tree flora comprises a high diversity of angiosperm lineages and species with widely differing life-history characteristics, providing an excellent system to investigate the combined influences of evolutionary heritage and selection in determining trait variation. We used trait data related to the major axes of life-history variation among tropical trees (e.g. growth and mortality rates) from 577 inventory plots in closed-canopy forest, mapped onto a phylogenetic hypothesis spanning more than 300 genera including all major angiosperm clades to test for evolutionary constraints on traits. We found significant phylogenetic signal (PS) for all traits, consistent with evolutionarily related genera having more similar characteristics than expected by chance. Although there is also evidence for repeated evolution of pioneer and shade tolerant life-history strategies within independent lineages, the existence of significant PS allows clearer predictions of the links between evolutionary diversity, ecosystem function and the response of tropical forests to global change. PMID:27974517

  17. Evolutionary heritage influences Amazon tree ecology.

    Science.gov (United States)

    Coelho de Souza, Fernanda; Dexter, Kyle G; Phillips, Oliver L; Brienen, Roel J W; Chave, Jerome; Galbraith, David R; Lopez Gonzalez, Gabriela; Monteagudo Mendoza, Abel; Pennington, R Toby; Poorter, Lourens; Alexiades, Miguel; Álvarez-Dávila, Esteban; Andrade, Ana; Aragão, Luis E O C; Araujo-Murakami, Alejandro; Arets, Eric J M M; Aymard C, Gerardo A; Baraloto, Christopher; Barroso, Jorcely G; Bonal, Damien; Boot, Rene G A; Camargo, José L C; Comiskey, James A; Valverde, Fernando Cornejo; de Camargo, Plínio B; Di Fiore, Anthony; Elias, Fernando; Erwin, Terry L; Feldpausch, Ted R; Ferreira, Leandro; Fyllas, Nikolaos M; Gloor, Emanuel; Herault, Bruno; Herrera, Rafael; Higuchi, Niro; Honorio Coronado, Eurídice N; Killeen, Timothy J; Laurance, William F; Laurance, Susan; Lloyd, Jon; Lovejoy, Thomas E; Malhi, Yadvinder; Maracahipes, Leandro; Marimon, Beatriz S; Marimon-Junior, Ben H; Mendoza, Casimiro; Morandi, Paulo; Neill, David A; Vargas, Percy Núñez; Oliveira, Edmar A; Lenza, Eddie; Palacios, Walter A; Peñuela-Mora, Maria C; Pipoly, John J; Pitman, Nigel C A; Prieto, Adriana; Quesada, Carlos A; Ramirez-Angulo, Hirma; Rudas, Agustin; Ruokolainen, Kalle; Salomão, Rafael P; Silveira, Marcos; Stropp, Juliana; Ter Steege, Hans; Thomas-Caesar, Raquel; van der Hout, Peter; van der Heijden, Geertje M F; van der Meer, Peter J; Vasquez, Rodolfo V; Vieira, Simone A; Vilanova, Emilio; Vos, Vincent A; Wang, Ophelia; Young, Kenneth R; Zagt, Roderick J; Baker, Timothy R

    2016-12-14

    Lineages tend to retain ecological characteristics of their ancestors through time. However, for some traits, selection during evolutionary history may have also played a role in determining trait values. To address the relative importance of these processes requires large-scale quantification of traits and evolutionary relationships among species. The Amazonian tree flora comprises a high diversity of angiosperm lineages and species with widely differing life-history characteristics, providing an excellent system to investigate the combined influences of evolutionary heritage and selection in determining trait variation. We used trait data related to the major axes of life-history variation among tropical trees (e.g. growth and mortality rates) from 577 inventory plots in closed-canopy forest, mapped onto a phylogenetic hypothesis spanning more than 300 genera including all major angiosperm clades to test for evolutionary constraints on traits. We found significant phylogenetic signal (PS) for all traits, consistent with evolutionarily related genera having more similar characteristics than expected by chance. Although there is also evidence for repeated evolution of pioneer and shade tolerant life-history strategies within independent lineages, the existence of significant PS allows clearer predictions of the links between evolutionary diversity, ecosystem function and the response of tropical forests to global change. © 2016 The Authors.

  18. A case study of bats and white-nose syndrome demonstrating how to model population viability with evolutionary effects.

    Science.gov (United States)

    Maslo, Brooke; Fefferman, Nina H

    2015-08-01

    Ecological factors generally affect population viability on rapid time scales. Traditional population viability analyses (PVA) therefore focus on alleviating ecological pressures, discounting potential evolutionary impacts on individual phenotypes. Recent studies of evolutionary rescue (ER) focus on cases in which severe, environmentally induced population bottlenecks trigger a rapid evolutionary response that can potentially reverse demographic threats. ER models have focused on shifting genetics and resulting population recovery, but no one has explored how to incorporate those findings into PVA. We integrated ER into PVA to identify the critical decision interval for evolutionary rescue (DIER) under which targeted conservation action should be applied to buffer populations undergoing ER against extinction from stochastic events and to determine the most appropriate vital rate to target to promote population recovery. We applied this model to little brown bats (Myotis lucifugus) affected by white-nose syndrome (WNS), a fungal disease causing massive declines in several North American bat populations. Under the ER scenario, the model predicted that the DIER period for little brown bats was within 11 years of initial WNS emergence, after which they stabilized at a positive growth rate (λ = 1.05). By comparing our model results with population trajectories of multiple infected hibernacula across the WNS range, we concluded that ER is a potential explanation of observed little brown bat population trajectories across multiple hibernacula within the affected range. Our approach provides a tool that can be used by all managers to provide testable hypotheses regarding the occurrence of ER in declining populations, suggest empirical studies to better parameterize the population genetics and conservation-relevant vital rates, and identify the DIER period during which management strategies will be most effective for species conservation. © 2015 Society for Conservation

  19. Using Evolutionary Theory to Guide Mental Health Research.

    Science.gov (United States)

    Durisko, Zachary; Mulsant, Benoit H; McKenzie, Kwame; Andrews, Paul W

    2016-03-01

    Evolutionary approaches to medicine can shed light on the origins and etiology of disease. Such an approach may be especially useful in psychiatry, which frequently addresses conditions with heterogeneous presentation and unknown causes. We review several previous applications of evolutionary theory that highlight the ways in which psychiatric conditions may persist despite and because of natural selection. One lesson from the evolutionary approach is that some conditions currently classified as disorders (because they cause distress and impairment) may actually be caused by functioning adaptations operating "normally" (as designed by natural selection). Such conditions suggest an alternative illness model that may generate alternative intervention strategies. Thus, the evolutionary approach suggests that psychiatry should sometimes think differently about distress and impairment. The complexity of the human brain, including normal functioning and potential for dysfunctions, has developed over evolutionary time and has been shaped by natural selection. Understanding the evolutionary origins of psychiatric conditions is therefore a crucial component to a complete understanding of etiology. © The Author(s) 2016.

  20. The impact of rapid evolution on population dynamics in the wild: experimental test of eco-evolutionary dynamics.

    Science.gov (United States)

    Turcotte, Martin M; Reznick, David N; Hare, J Daniel

    2011-11-01

    Rapid evolution challenges the assumption that evolution is too slow to impact short-term ecological dynamics. This insight motivates the study of 'Eco-Evolutionary Dynamics' or how evolution and ecological processes reciprocally interact on short time scales. We tested how rapid evolution impacts concurrent population dynamics using an aphid (Myzus persicae) and an undomesticated host (Hirschfeldia incana) in replicated wild populations. We manipulated evolvability by creating non-evolving (single clone) and potentially evolving (two-clone) aphid populations that contained genetic variation in intrinsic growth rate. We observed significant evolution in two-clone populations whether or not they were exposed to predators and competitors. Evolving populations grew up to 42% faster and attained up to 67% higher density, compared with non-evolving control populations but only in treatments exposed to competitors and predators. Increased density also correlates with relative fitness of competing clones suggesting a full eco-evolutionary dynamic cycle defined as reciprocal interactions between evolution and density. © 2011 Blackwell Publishing Ltd/CNRS.

  1. On the evolutionary origins of equity.

    Directory of Open Access Journals (Sweden)

    Stéphane Debove

    Full Text Available Equity, defined as reward according to contribution, is considered a central aspect of human fairness in both philosophical debates and scientific research. Despite large amounts of research on the evolutionary origins of fairness, the evolutionary rationale behind equity is still unknown. Here, we investigate how equity can be understood in the context of the cooperative environment in which humans evolved. We model a population of individuals who cooperate to produce and divide a resource, and choose their cooperative partners based on how they are willing to divide the resource. Agent-based simulations, an analytical model, and extended simulations using neural networks provide converging evidence that equity is the best evolutionary strategy in such an environment: individuals maximize their fitness by dividing benefits in proportion to their own and their partners' relative contribution. The need to be chosen as a cooperative partner thus creates a selection pressure strong enough to explain the evolution of preferences for equity. We discuss the limitations of our model, the discrepancies between its predictions and empirical data, and how interindividual and intercultural variability fit within this framework.

  2. Spatial evolutionary epidemiology of spreading epidemics.

    Science.gov (United States)

    Lion, S; Gandon, S

    2016-10-26

    Most spatial models of host-parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation. © 2016 The Author(s).

  3. Evolutionary accounts of human behavioural diversity

    Science.gov (United States)

    Brown, Gillian R.; Dickins, Thomas E.; Sear, Rebecca; Laland, Kevin N.

    2011-01-01

    Human beings persist in an extraordinary range of ecological settings, in the process exhibiting enormous behavioural diversity, both within and between populations. People vary in their social, mating and parental behaviour and have diverse and elaborate beliefs, traditions, norms and institutions. The aim of this theme issue is to ask whether, and how, evolutionary theory can help us to understand this diversity. In this introductory article, we provide a background to the debate surrounding how best to understand behavioural diversity using evolutionary models of human behaviour. In particular, we examine how diversity has been viewed by the main subdisciplines within the human evolutionary behavioural sciences, focusing in particular on the human behavioural ecology, evolutionary psychology and cultural evolution approaches. In addition to differences in focus and methodology, these subdisciplines have traditionally varied in the emphasis placed on human universals, ecological factors and socially learned behaviour, and on how they have addressed the issue of genetic variation. We reaffirm that evolutionary theory provides an essential framework for understanding behavioural diversity within and between human populations, but argue that greater integration between the subfields is critical to developing a satisfactory understanding of diversity. PMID:21199836

  4. Evolutionary thinking

    Science.gov (United States)

    Hunt, Tam

    2014-01-01

    Evolution as an idea has a lengthy history, even though the idea of evolution is generally associated with Darwin today. Rebecca Stott provides an engaging and thoughtful overview of this history of evolutionary thinking in her 2013 book, Darwin's Ghosts: The Secret History of Evolution. Since Darwin, the debate over evolution—both how it takes place and, in a long war of words with religiously-oriented thinkers, whether it takes place—has been sustained and heated. A growing share of this debate is now devoted to examining how evolutionary thinking affects areas outside of biology. How do our lives change when we recognize that all is in flux? What can we learn about life more generally if we study change instead of stasis? Carter Phipps’ book, Evolutionaries: Unlocking the Spiritual and Cultural Potential of Science's Greatest Idea, delves deep into this relatively new development. Phipps generally takes as a given the validity of the Modern Synthesis of evolutionary biology. His story takes us into, as the subtitle suggests, the spiritual and cultural implications of evolutionary thinking. Can religion and evolution be reconciled? Can evolutionary thinking lead to a new type of spirituality? Is our culture already being changed in ways that we don't realize by evolutionary thinking? These are all important questions and Phipps book is a great introduction to this discussion. Phipps is an author, journalist, and contributor to the emerging “integral” or “evolutionary” cultural movement that combines the insights of Integral Philosophy, evolutionary science, developmental psychology, and the social sciences. He has served as the Executive Editor of EnlightenNext magazine (no longer published) and more recently is the co-founder of the Institute for Cultural Evolution, a public policy think tank addressing the cultural roots of America's political challenges. What follows is an email interview with Phipps. PMID:26478766

  5. An evolutionary-network model reveals stratified interactions in the V3 loop of the HIV-1 envelope.

    Directory of Open Access Journals (Sweden)

    Art F Y Poon

    2007-11-01

    Full Text Available The third variable loop (V3 of the human immunodeficiency virus type 1 (HIV-1 envelope is a principal determinant of antibody neutralization and progression to AIDS. Although it is undoubtedly an important target for vaccine research, extensive genetic variation in V3 remains an obstacle to the development of an effective vaccine. Comparative methods that exploit the abundance of sequence data can detect interactions between residues of rapidly evolving proteins such as the HIV-1 envelope, revealing biological constraints on their variability. However, previous studies have relied implicitly on two biologically unrealistic assumptions: (1 that founder effects in the evolutionary history of the sequences can be ignored, and; (2 that statistical associations between residues occur exclusively in pairs. We show that comparative methods that neglect the evolutionary history of extant sequences are susceptible to a high rate of false positives (20%-40%. Therefore, we propose a new method to detect interactions that relaxes both of these assumptions. First, we reconstruct the evolutionary history of extant sequences by maximum likelihood, shifting focus from extant sequence variation to the underlying substitution events. Second, we analyze the joint distribution of substitution events among positions in the sequence as a Bayesian graphical model, in which each branch in the phylogeny is a unit of observation. We perform extensive validation of our models using both simulations and a control case of known interactions in HIV-1 protease, and apply this method to detect interactions within V3 from a sample of 1,154 HIV-1 envelope sequences. Our method greatly reduces the number of false positives due to founder effects, while capturing several higher-order interactions among V3 residues. By mapping these interactions to a structural model of the V3 loop, we find that the loop is stratified into distinct evolutionary clusters. We extend our model to

  6. Deathly drool: evolutionary and ecological basis of septic bacteria in Komodo dragon mouths.

    Science.gov (United States)

    Bull, J J; Jessop, Tim S; Whiteley, Marvin

    2010-06-21

    Komodo dragons, the world's largest lizard, dispatch their large ungulate prey by biting and tearing flesh. If a prey escapes, oral bacteria inoculated into the wound reputedly induce a sepsis that augments later prey capture by the same or other lizards. However, the ecological and evolutionary basis of sepsis in Komodo prey acquisition is controversial. Two models have been proposed. The "bacteria as venom" model postulates that the oral flora directly benefits the lizard in prey capture irrespective of any benefit to the bacteria. The "passive acquisition" model is that the oral flora of lizards reflects the bacteria found in carrion and sick prey, with no relevance to the ability to induce sepsis in subsequent prey. A third model is proposed and analyzed here, the "lizard-lizard epidemic" model. In this model, bacteria are spread indirectly from one lizard mouth to another. Prey escaping an initial attack act as vectors in infecting new lizards. This model requires specific life history characteristics and ways to refute the model based on these characteristics are proposed and tested. Dragon life histories (some details of which are reported here) prove remarkably consistent with the model, especially that multiple, unrelated lizards feed communally on large carcasses and that escaping, wounded prey are ultimately fed on by other lizards. The identities and evolutionary histories of bacteria in the oral flora may yield the most useful additional insights for further testing the epidemic model and can now be obtained with new technologies.

  7. An affinity-based evolutionary model of the diffusion of knowledge

    Directory of Open Access Journals (Sweden)

    Roberto Luiz Souza Monteiro

    2015-08-01

    Full Text Available In this paper, we present a theoretical model that can simulate the diffusion of knowledge in social networks using an evolutionary approach. We assume that social networks built on processes of collaboration and cooperation among stakeholders (people and companies evolve like living organisms, as described by Charles Darwin in The Origin of Species. We propose an evolutionary model of the diffusion of knowledge, in which stakeholders are knowledge propagators and/or receivers, depending on their customizable attributes. We consider each attribute as a gene that constitutes a chromosome. As in Darwin's theory, the proposed model achieves the processes of crossover and mutation between stakeholders for several generations, until a maximum number of generations is reached. The main contribution of the model is the creation of an environment that is conducive to the study of the dynamics of network cooperation, which uses the stakeholders’ attributes as parameters. Modelo evolutivo de difusión del conocimiento basado en afinidad Resumen En este artículo presentamos un modelo teórico capaz de simular la difusión del conocimiento en redes sociales, usando una aproximación evolutiva. Partimos del presupuesto que redes sociales constituidas por procesos de cooperación entre actores (e.g. personas, empresas, etc. evolucionan de forma semejante a los organismos vivos, como ha sido descrito por Charles Darwin en El Origen de las Especies. Proponemos un modelo evolutivo de difusión del conocimiento, donde los actores son propagadores y/o retenedores de conocimiento, dependiendo de atributos ajustables que cada actor presenta. Consideramos cada atributo un gen que constituye a un cromosoma. Similar a la teoría de Darwin, el modelo propuesto realiza los procesos de crossover y mutación entre los actores por diversas generaciones, hasta que se obtiene un número máximo de generaciones. La principal contribución del modelo es la creación de un

  8. Evolutionary perspectives on ageing.

    Science.gov (United States)

    Reichard, Martin

    2017-10-01

    From an evolutionary perspective, ageing is a decrease in fitness with chronological age - expressed by an increase in mortality risk and/or decline in reproductive success and mediated by deterioration of functional performance. While this makes ageing intuitively paradoxical - detrimental to individual fitness - evolutionary theory offers answers as to why ageing has evolved. In this review, I first briefly examine the classic evolutionary theories of ageing and their empirical tests, and highlight recent findings that have advanced our understanding of the evolution of ageing (condition-dependent survival, positive pleiotropy). I then provide an overview of recent theoretical extensions and modifications that accommodate those new discoveries. I discuss the role of indeterminate (asymptotic) growth for lifetime increases in fecundity and ageing trajectories. I outline alternative views that challenge a universal existence of senescence - namely the lack of a germ-soma distinction and the ability of tissue replacement and retrogression to younger developmental stages in modular organisms. I argue that rejuvenation at the organismal level is plausible, but includes a return to a simple developmental stage. This may exempt a particular genotype from somatic defects but, correspondingly, removes any information acquired during development. A resolution of the question of whether a rejuvenated individual is the same entity is central to the recognition of whether current evolutionary theories of ageing, with their extensions and modifications, can explain the patterns of ageing across the Tree of Life. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Android malware detection based on evolutionary super-network

    Science.gov (United States)

    Yan, Haisheng; Peng, Lingling

    2018-04-01

    In the paper, an android malware detection method based on evolutionary super-network is proposed in order to improve the precision of android malware detection. Chi square statistics method is used for selecting characteristics on the basis of analyzing android authority. Boolean weighting is utilized for calculating characteristic weight. Processed characteristic vector is regarded as the system training set and test set; hyper edge alternative strategy is used for training super-network classification model, thereby classifying test set characteristic vectors, and it is compared with traditional classification algorithm. The results show that the detection method proposed in the paper is close to or better than traditional classification algorithm. The proposed method belongs to an effective Android malware detection means.

  10. Modeling evolutionary games in populations with demographic structure

    DEFF Research Database (Denmark)

    Li, Xiang-Yi; Giaimo, Stefano; Baudisch, Annette

    2015-01-01

    interactions, but usually omits life history and the demographic structure of the population. Here we show how an integration of both aspects can substantially alter the underlying evolutionary dynamics. We study the replicator dynamics of strategy interactions in life stage structured populations. Individuals...

  11. MEGA5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods

    Science.gov (United States)

    Tamura, Koichiro; Peterson, Daniel; Peterson, Nicholas; Stecher, Glen; Nei, Masatoshi; Kumar, Sudhir

    2011-01-01

    Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net. PMID:21546353

  12. Multi-objective mixture-based iterated density estimation evolutionary algorithms

    NARCIS (Netherlands)

    Thierens, D.; Bosman, P.A.N.

    2001-01-01

    We propose an algorithm for multi-objective optimization using a mixture-based iterated density estimation evolutionary algorithm (MIDEA). The MIDEA algorithm is a prob- abilistic model building evolutionary algo- rithm that constructs at each generation a mixture of factorized probability

  13. Comparative Study of Lectin Domains in Model Species: New Insights into Evolutionary Dynamics

    Directory of Open Access Journals (Sweden)

    Sofie Van Holle

    2017-05-01

    Full Text Available Lectins are present throughout the plant kingdom and are reported to be involved in diverse biological processes. In this study, we provide a comparative analysis of the lectin families from model species in a phylogenetic framework. The analysis focuses on the different plant lectin domains identified in five representative core angiosperm genomes (Arabidopsis thaliana, Glycine max, Cucumis sativus, Oryza sativa ssp. japonica and Oryza sativa ssp. indica. The genomes were screened for genes encoding lectin domains using a combination of Basic Local Alignment Search Tool (BLAST, hidden Markov models, and InterProScan analysis. Additionally, phylogenetic relationships were investigated by constructing maximum likelihood phylogenetic trees. The results demonstrate that the majority of the lectin families are present in each of the species under study. Domain organization analysis showed that most identified proteins are multi-domain proteins, owing to the modular rearrangement of protein domains during evolution. Most of these multi-domain proteins are widespread, while others display a lineage-specific distribution. Furthermore, the phylogenetic analyses reveal that some lectin families evolved to be similar to the phylogeny of the plant species, while others share a closer evolutionary history based on the corresponding protein domain architecture. Our results yield insights into the evolutionary relationships and functional divergence of plant lectins.

  14. Evolutionary mysteries in meiosis

    NARCIS (Netherlands)

    Lenormand, Thomas; Engelstädter, Jan; Johnston, Susan E.; Wijnker, Erik; Haag, Christoph R.

    2016-01-01

    Meiosis is a key event of sexual life cycles in eukaryotes. Its mechanistic details have been uncovered in several model organisms, and most of its essential features have received various and often contradictory evolutionary interpretations. In this perspective, we present an overview of these

  15. Evolutionary mysteries in meiosis.

    Science.gov (United States)

    Lenormand, Thomas; Engelstädter, Jan; Johnston, Susan E; Wijnker, Erik; Haag, Christoph R

    2016-10-19

    Meiosis is a key event of sexual life cycles in eukaryotes. Its mechanistic details have been uncovered in several model organisms, and most of its essential features have received various and often contradictory evolutionary interpretations. In this perspective, we present an overview of these often 'weird' features. We discuss the origin of meiosis (origin of ploidy reduction and recombination, two-step meiosis), its secondary modifications (in polyploids or asexuals, inverted meiosis), its importance in punctuating life cycles (meiotic arrests, epigenetic resetting, meiotic asymmetry, meiotic fairness) and features associated with recombination (disjunction constraints, heterochiasmy, crossover interference and hotspots). We present the various evolutionary scenarios and selective pressures that have been proposed to account for these features, and we highlight that their evolutionary significance often remains largely mysterious. Resolving these mysteries will likely provide decisive steps towards understanding why sex and recombination are found in the majority of eukaryotes.This article is part of the themed issue 'Weird sex: the underappreciated diversity of sexual reproduction'. © 2016 The Author(s).

  16. Evolutionary Stable Strategy

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 21; Issue 9. Evolutionary Stable Strategy: Application of Nash Equilibrium in Biology. General Article Volume 21 Issue 9 September 2016 pp 803- ... Keywords. Evolutionary game theory, evolutionary stable state, conflict, cooperation, biological games.

  17. An Efficient Evolutionary Based Method For Image Segmentation

    OpenAIRE

    Aslanzadeh, Roohollah; Qazanfari, Kazem; Rahmati, Mohammad

    2017-01-01

    The goal of this paper is to present a new efficient image segmentation method based on evolutionary computation which is a model inspired from human behavior. Based on this model, a four layer process for image segmentation is proposed using the split/merge approach. In the first layer, an image is split into numerous regions using the watershed algorithm. In the second layer, a co-evolutionary process is applied to form centers of finals segments by merging similar primary regions. In the t...

  18. An Evolutionary Approach to Regional Systems of Innovation

    DEFF Research Database (Denmark)

    Gunnarsson, Jan Sture Gunnar; Wallin, Torsten

    This article examines how the birth and the development of regional systems of innovation are connected with economic selection and points to implications for regional-level policies. The research questions are explored using an evolutionary model, which emphasises geographical spaces and product......This article examines how the birth and the development of regional systems of innovation are connected with economic selection and points to implications for regional-level policies. The research questions are explored using an evolutionary model, which emphasises geographical spaces...

  19. An evolutionary approach to regional systems of innovation

    DEFF Research Database (Denmark)

    Gunnarsson, Jan Sture Gunnar; Wallin, Torsten

    2011-01-01

    This article examines how the birth and the development of regional systems of innovation are connected with economic selection and points to implications for regional-level policies. The research questions are explored using an evolutionary model, which emphasises geographical spaces and product......This article examines how the birth and the development of regional systems of innovation are connected with economic selection and points to implications for regional-level policies. The research questions are explored using an evolutionary model, which emphasises geographical spaces...

  20. Evolutionary Aesthetics and Print Advertising

    Directory of Open Access Journals (Sweden)

    Kamil Luczaj

    2015-06-01

    Full Text Available The article analyzes the extent to which predictions based on the theory of evolutionary aesthetics are utilized by the advertising industry. The purpose of a comprehensive content analysis of print advertising is to determine whether the items indicated by evolutionists such as animals, flowers, certain types of landscapes, beautiful humans, and some colors are part of real advertising strategies. This article has shown that many evolutionary hypotheses (although not all of them are supported by empirical data. Along with these hypotheses, some inferences from Bourdieu’s cultural capital theory were tested. It turned out that advertising uses both biological schemata and cultural patterns to make an image more likable.

  1. Evolutionary computation in zoology and ecology.

    Science.gov (United States)

    Boone, Randall B

    2017-12-01

    Evolutionary computational methods have adopted attributes of natural selection and evolution to solve problems in computer science, engineering, and other fields. The method is growing in use in zoology and ecology. Evolutionary principles may be merged with an agent-based modeling perspective to have individual animals or other agents compete. Four main categories are discussed: genetic algorithms, evolutionary programming, genetic programming, and evolutionary strategies. In evolutionary computation, a population is represented in a way that allows for an objective function to be assessed that is relevant to the problem of interest. The poorest performing members are removed from the population, and remaining members reproduce and may be mutated. The fitness of the members is again assessed, and the cycle continues until a stopping condition is met. Case studies include optimizing: egg shape given different clutch sizes, mate selection, migration of wildebeest, birds, and elk, vulture foraging behavior, algal bloom prediction, and species richness given energy constraints. Other case studies simulate the evolution of species and a means to project shifts in species ranges in response to a changing climate that includes competition and phenotypic plasticity. This introduction concludes by citing other uses of evolutionary computation and a review of the flexibility of the methods. For example, representing species' niche spaces subject to selective pressure allows studies on cladistics, the taxon cycle, neutral versus niche paradigms, fundamental versus realized niches, community structure and order of colonization, invasiveness, and responses to a changing climate.

  2. Evolutionary public health: introducing the concept.

    Science.gov (United States)

    Wells, Jonathan C K; Nesse, Randolph M; Sear, Rebecca; Johnstone, Rufus A; Stearns, Stephen C

    2017-07-29

    The emerging discipline of evolutionary medicine is breaking new ground in understanding why people become ill. However, the value of evolutionary analyses of human physiology and behaviour is only beginning to be recognised in the field of public health. Core principles come from life history theory, which analyses the allocation of finite amounts of energy between four competing functions-maintenance, growth, reproduction, and defence. A central tenet of evolutionary theory is that organisms are selected to allocate energy and time to maximise reproductive success, rather than health or longevity. Ecological interactions that influence mortality risk, nutrient availability, and pathogen burden shape energy allocation strategies throughout the life course, thereby affecting diverse health outcomes. Public health interventions could improve their own effectiveness by incorporating an evolutionary perspective. In particular, evolutionary approaches offer new opportunities to address the complex challenges of global health, in which populations are differentially exposed to the metabolic consequences of poverty, high fertility, infectious diseases, and rapid changes in nutrition and lifestyle. The effect of specific interventions is predicted to depend on broader factors shaping life expectancy. Among the important tools in this approach are mathematical models, which can explore probable benefits and limitations of interventions in silico, before their implementation in human populations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. The evolutionary ecology of molecular replicators.

    Science.gov (United States)

    Nee, Sean

    2016-08-01

    By reasonable criteria, life on the Earth consists mainly of molecular replicators. These include viruses, transposons, transpovirons, coviruses and many more, with continuous new discoveries like Sputnik Virophage. Their study is inherently multidisciplinary, spanning microbiology, genetics, immunology and evolutionary theory, and the current view is that taking a unified approach has great power and promise. We support this with a new, unified, model of their evolutionary ecology, using contemporary evolutionary theory coupling the Price equation with game theory, studying the consequences of the molecular replicators' promiscuous use of each others' gene products for their natural history and evolutionary ecology. Even at this simple expository level, we can make a firm prediction of a new class of replicators exploiting viruses such as lentiviruses like SIVs, a family which includes HIV: these have been explicitly stated in the primary literature to be non-existent. Closely connected to this departure is the view that multicellular organism immunology is more about the management of chronic infections rather than the elimination of acute ones and new understandings emerging are changing our view of the kind of theatre we ourselves provide for the evolutionary play of molecular replicators. This study adds molecular replicators to bacteria in the emerging field of sociomicrobiology.

  4. Evolutionary model of the subdwarf binary system LB3459

    International Nuclear Information System (INIS)

    Paczynski, B.; Dearborn, D.S.

    1980-01-01

    An evolutionary model is proposed for the eclipsing binary system LB 3459 (=CPD-60 0 389 = HDE 269696). The two stars are hot subdwarfs with degenerate helium cores, hydrogen burning shell sources and low mass hydrogen rich envelopes. The system probably evolved through two common envelope phases. After the first such phase it might look like the semi-detached binary AS Eri. Soon after the second common envelope phase the system might look like UU Sge, an eclipsing binary nucleus of a planetary nebula. The present mass of the optical (spectroscopic) primary is probably close to 0.24 solar mass, and the predicted radial velocity amplitude of the primary is about 150 km/s. The optical secondary should be hotter and bolometrically brighter, with a mass of 0.32 solar mass. The primary eclipse is an occultation. (author)

  5. Evolutionary patterns and processes in the radiation of phyllostomid bats

    Directory of Open Access Journals (Sweden)

    Monteiro Leandro R

    2011-05-01

    Full Text Available Abstract Background The phyllostomid bats present the most extensive ecological and phenotypic radiation known among mammal families. This group is an important model system for studies of cranial ecomorphology and functional optimisation because of the constraints imposed by the requirements of flight. A number of studies supporting phyllostomid adaptation have focused on qualitative descriptions or correlating functional variables and diet, but explicit tests of possible evolutionary mechanisms and scenarios for phenotypic diversification have not been performed. We used a combination of morphometric and comparative methods to test hypotheses regarding the evolutionary processes behind the diversification of phenotype (mandible shape and size and diet during the phyllostomid radiation. Results The different phyllostomid lineages radiate in mandible shape space, with each feeding specialisation evolving towards different axes. Size and shape evolve quite independently, as the main directions of shape variation are associated with mandible elongation (nectarivores or the relative size of tooth rows and mandibular processes (sanguivores and frugivores, which are not associated with size changes in the mandible. The early period of phyllostomid diversification is marked by a burst of shape, size, and diet disparity (before 20 Mya, larger than expected by neutral evolution models, settling later to a period of relative phenotypic and ecological stasis. The best fitting evolutionary model for both mandible shape and size divergence was an Ornstein-Uhlenbeck process with five adaptive peaks (insectivory, carnivory, sanguivory, nectarivory and frugivory. Conclusions The radiation of phyllostomid bats presented adaptive and non-adaptive components nested together through the time frame of the family's evolution. The first 10 My of the radiation were marked by strong phenotypic and ecological divergence among ancestors of modern lineages, whereas the

  6. Evolutionary patterns and processes in the radiation of phyllostomid bats

    Science.gov (United States)

    2011-01-01

    Background The phyllostomid bats present the most extensive ecological and phenotypic radiation known among mammal families. This group is an important model system for studies of cranial ecomorphology and functional optimisation because of the constraints imposed by the requirements of flight. A number of studies supporting phyllostomid adaptation have focused on qualitative descriptions or correlating functional variables and diet, but explicit tests of possible evolutionary mechanisms and scenarios for phenotypic diversification have not been performed. We used a combination of morphometric and comparative methods to test hypotheses regarding the evolutionary processes behind the diversification of phenotype (mandible shape and size) and diet during the phyllostomid radiation. Results The different phyllostomid lineages radiate in mandible shape space, with each feeding specialisation evolving towards different axes. Size and shape evolve quite independently, as the main directions of shape variation are associated with mandible elongation (nectarivores) or the relative size of tooth rows and mandibular processes (sanguivores and frugivores), which are not associated with size changes in the mandible. The early period of phyllostomid diversification is marked by a burst of shape, size, and diet disparity (before 20 Mya), larger than expected by neutral evolution models, settling later to a period of relative phenotypic and ecological stasis. The best fitting evolutionary model for both mandible shape and size divergence was an Ornstein-Uhlenbeck process with five adaptive peaks (insectivory, carnivory, sanguivory, nectarivory and frugivory). Conclusions The radiation of phyllostomid bats presented adaptive and non-adaptive components nested together through the time frame of the family's evolution. The first 10 My of the radiation were marked by strong phenotypic and ecological divergence among ancestors of modern lineages, whereas the remaining 20 My were

  7. EvoluCode: Evolutionary Barcodes as a Unifying Framework for Multilevel Evolutionary Data.

    Science.gov (United States)

    Linard, Benjamin; Nguyen, Ngoc Hoan; Prosdocimi, Francisco; Poch, Olivier; Thompson, Julie D

    2012-01-01

    Evolutionary systems biology aims to uncover the general trends and principles governing the evolution of biological networks. An essential part of this process is the reconstruction and analysis of the evolutionary histories of these complex, dynamic networks. Unfortunately, the methodologies for representing and exploiting such complex evolutionary histories in large scale studies are currently limited. Here, we propose a new formalism, called EvoluCode (Evolutionary barCode), which allows the integration of different evolutionary parameters (eg, sequence conservation, orthology, synteny …) in a unifying format and facilitates the multilevel analysis and visualization of complex evolutionary histories at the genome scale. The advantages of the approach are demonstrated by constructing barcodes representing the evolution of the complete human proteome. Two large-scale studies are then described: (i) the mapping and visualization of the barcodes on the human chromosomes and (ii) automatic clustering of the barcodes to highlight protein subsets sharing similar evolutionary histories and their functional analysis. The methodologies developed here open the way to the efficient application of other data mining and knowledge extraction techniques in evolutionary systems biology studies. A database containing all EvoluCode data is available at: http://lbgi.igbmc.fr/barcodes.

  8. Evolutionary stability concepts in a stochastic environment

    Science.gov (United States)

    Zheng, Xiu-Deng; Li, Cong; Lessard, Sabin; Tao, Yi

    2017-09-01

    Over the past 30 years, evolutionary game theory and the concept of an evolutionarily stable strategy have been not only extensively developed and successfully applied to explain the evolution of animal behaviors, but also widely used in economics and social sciences. Nonetheless, the stochastic dynamical properties of evolutionary games in randomly fluctuating environments are still unclear. In this study, we investigate conditions for stochastic local stability of fixation states and constant interior equilibria in a two-phenotype model with random payoffs following pairwise interactions. Based on this model, we develop the concepts of stochastic evolutionary stability (SES) and stochastic convergence stability (SCS). We show that the condition for a pure strategy to be SES and SCS is more stringent than in a constant environment, while the condition for a constant mixed strategy to be SES is less stringent than the condition to be SCS, which is less stringent than the condition in a constant environment.

  9. Phylogenetic inference with weighted codon evolutionary distances.

    Science.gov (United States)

    Criscuolo, Alexis; Michel, Christian J

    2009-04-01

    We develop a new approach to estimate a matrix of pairwise evolutionary distances from a codon-based alignment based on a codon evolutionary model. The method first computes a standard distance matrix for each of the three codon positions. Then these three distance matrices are weighted according to an estimate of the global evolutionary rate of each codon position and averaged into a unique distance matrix. Using a large set of both real and simulated codon-based alignments of nucleotide sequences, we show that this approach leads to distance matrices that have a significantly better treelikeness compared to those obtained by standard nucleotide evolutionary distances. We also propose an alternative weighting to eliminate the part of the noise often associated with some codon positions, particularly the third position, which is known to induce a fast evolutionary rate. Simulation results show that fast distance-based tree reconstruction algorithms on distance matrices based on this codon position weighting can lead to phylogenetic trees that are at least as accurate as, if not better, than those inferred by maximum likelihood. Finally, a well-known multigene dataset composed of eight yeast species and 106 codon-based alignments is reanalyzed and shows that our codon evolutionary distances allow building a phylogenetic tree which is similar to those obtained by non-distance-based methods (e.g., maximum parsimony and maximum likelihood) and also significantly improved compared to standard nucleotide evolutionary distance estimates.

  10. Stimulating Scientific Reasoning with Drawing-Based Modeling

    Science.gov (United States)

    Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

    2018-01-01

    We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each…

  11. Evolutionary neural network modeling for software cumulative failure time prediction

    International Nuclear Information System (INIS)

    Tian Liang; Noore, Afzel

    2005-01-01

    An evolutionary neural network modeling approach for software cumulative failure time prediction based on multiple-delayed-input single-output architecture is proposed. Genetic algorithm is used to globally optimize the number of the delayed input neurons and the number of neurons in the hidden layer of the neural network architecture. Modification of Levenberg-Marquardt algorithm with Bayesian regularization is used to improve the ability to predict software cumulative failure time. The performance of our proposed approach has been compared using real-time control and flight dynamic application data sets. Numerical results show that both the goodness-of-fit and the next-step-predictability of our proposed approach have greater accuracy in predicting software cumulative failure time compared to existing approaches

  12. Passivity and Evolutionary Game Dynamics

    KAUST Repository

    Park, Shinkyu; Shamma, Jeff S.; Martins, Nuno C.

    2018-01-01

    This paper investigates an energy conservation and dissipation -- passivity -- aspect of dynamic models in evolutionary game theory. We define a notion of passivity using the state-space representation of the models, and we devise systematic methods to examine passivity and to identify properties of passive dynamic models. Based on the methods, we describe how passivity is connected to stability in population games and illustrate stability of passive dynamic models using numerical simulations.

  13. Passivity and Evolutionary Game Dynamics

    KAUST Repository

    Park, Shinkyu

    2018-03-21

    This paper investigates an energy conservation and dissipation -- passivity -- aspect of dynamic models in evolutionary game theory. We define a notion of passivity using the state-space representation of the models, and we devise systematic methods to examine passivity and to identify properties of passive dynamic models. Based on the methods, we describe how passivity is connected to stability in population games and illustrate stability of passive dynamic models using numerical simulations.

  14. Deathly drool: evolutionary and ecological basis of septic bacteria in Komodo dragon mouths.

    Directory of Open Access Journals (Sweden)

    J J Bull

    2010-06-01

    Full Text Available Komodo dragons, the world's largest lizard, dispatch their large ungulate prey by biting and tearing flesh. If a prey escapes, oral bacteria inoculated into the wound reputedly induce a sepsis that augments later prey capture by the same or other lizards. However, the ecological and evolutionary basis of sepsis in Komodo prey acquisition is controversial. Two models have been proposed. The "bacteria as venom" model postulates that the oral flora directly benefits the lizard in prey capture irrespective of any benefit to the bacteria. The "passive acquisition" model is that the oral flora of lizards reflects the bacteria found in carrion and sick prey, with no relevance to the ability to induce sepsis in subsequent prey. A third model is proposed and analyzed here, the "lizard-lizard epidemic" model. In this model, bacteria are spread indirectly from one lizard mouth to another. Prey escaping an initial attack act as vectors in infecting new lizards. This model requires specific life history characteristics and ways to refute the model based on these characteristics are proposed and tested. Dragon life histories (some details of which are reported here prove remarkably consistent with the model, especially that multiple, unrelated lizards feed communally on large carcasses and that escaping, wounded prey are ultimately fed on by other lizards. The identities and evolutionary histories of bacteria in the oral flora may yield the most useful additional insights for further testing the epidemic model and can now be obtained with new technologies.

  15. Deathly Drool: Evolutionary and Ecological Basis of Septic Bacteria in Komodo Dragon Mouths

    Science.gov (United States)

    Bull, J. J.; Jessop, Tim S.; Whiteley, Marvin

    2010-01-01

    Komodo dragons, the world's largest lizard, dispatch their large ungulate prey by biting and tearing flesh. If a prey escapes, oral bacteria inoculated into the wound reputedly induce a sepsis that augments later prey capture by the same or other lizards. However, the ecological and evolutionary basis of sepsis in Komodo prey acquisition is controversial. Two models have been proposed. The “bacteria as venom” model postulates that the oral flora directly benefits the lizard in prey capture irrespective of any benefit to the bacteria. The “passive acquisition” model is that the oral flora of lizards reflects the bacteria found in carrion and sick prey, with no relevance to the ability to induce sepsis in subsequent prey. A third model is proposed and analyzed here, the “lizard-lizard epidemic” model. In this model, bacteria are spread indirectly from one lizard mouth to another. Prey escaping an initial attack act as vectors in infecting new lizards. This model requires specific life history characteristics and ways to refute the model based on these characteristics are proposed and tested. Dragon life histories (some details of which are reported here) prove remarkably consistent with the model, especially that multiple, unrelated lizards feed communally on large carcasses and that escaping, wounded prey are ultimately fed on by other lizards. The identities and evolutionary histories of bacteria in the oral flora may yield the most useful additional insights for further testing the epidemic model and can now be obtained with new technologies. PMID:20574514

  16. Face Alignment Using Boosting and Evolutionary Search

    NARCIS (Netherlands)

    Zhang, Hua; Liu, Duanduan; Poel, Mannes; Nijholt, Antinus; Zha, H.; Taniguchi, R.-I.; Maybank, S.

    2010-01-01

    In this paper, we present a face alignment approach using granular features, boosting, and an evolutionary search algorithm. Active Appearance Models (AAM) integrate a shape-texture-combined morphable face model into an efficient fitting strategy, then Boosting Appearance Models (BAM) consider the

  17. A Study on Standard Competition with Network Effect Based on Evolutionary Game Model

    Science.gov (United States)

    Wang, Ye; Wang, Bingdong; Li, Kangning

    Owing to networks widespread in modern society, standard competition with network effect is now endowed with new connotation. This paper aims to study the impact of network effect on standard competition; it is organized in the mode of "introduction-model setup-equilibrium analysis-conclusion". Starting from a well-structured model of evolutionary game, it is then extended to a dynamic analysis. This article proves both theoretically and empirically that whether or not a standard can lead the market trends depends on the utility it would bring, and the author also discusses some advisable strategies revolving around the two factors of initial position and border break.

  18. Multivariate dynamic linear models for estimating the effect of experimental interventions in an evolutionary operations setup in dairy herds

    DEFF Research Database (Denmark)

    Stygar, Anna Helena; Krogh, Mogens Agerbo; Kristensen, Troels

    2017-01-01

    Evolutionary operations is a method to exploit the association of often small changes in process variables, planned during systematic experimentation and occurring during the normal production flow, to production characteristics to find a way to alter the production process to be more efficient....... The objective of this study was to construct a tool to assess the intervention effect on milk production in an evolutionary operations setup. The method used for this purpose was a dynamic linear model (DLM) with Kalman filtering. The DLM consisted of parameters describing milk yield in a herd, individual cows...... bulk tank records. The presented model proved to be a flexible and dynamic tool, and it was successfully applied for systematic experimentation in dairy herds. The model can serve as a decision support tool for on-farm process optimization exploiting planned changes in process variables...

  19. Evolutionary Games with Randomly Changing Payoff Matrices

    Science.gov (United States)

    Yakushkina, Tatiana; Saakian, David B.; Bratus, Alexander; Hu, Chin-Kun

    2015-06-01

    Evolutionary games are used in various fields stretching from economics to biology. In most of these games a constant payoff matrix is assumed, although some works also consider dynamic payoff matrices. In this article we assume a possibility of switching the system between two regimes with different sets of payoff matrices. Potentially such a model can qualitatively describe the development of bacterial or cancer cells with a mutator gene present. A finite population evolutionary game is studied. The model describes the simplest version of annealed disorder in the payoff matrix and is exactly solvable at the large population limit. We analyze the dynamics of the model, and derive the equations for both the maximum and the variance of the distribution using the Hamilton-Jacobi equation formalism.

  20. The First Joke: Exploring the Evolutionary Origins of Humor

    Directory of Open Access Journals (Sweden)

    Joseph Polimeni

    2006-01-01

    Full Text Available Humor is a complex cognitive function which often leads to laughter. Contemporary humor theorists have begun to formulate hypotheses outlining the possible innate cognitive structures underlying humor. Humor's conspicuous presence in the behavioral repertoire of humankind invites adaptive explanations. This article explores the possible adaptive features of humor and ponders its evolutionary path through hominid history. Current humor theories and previous evolutionary ideas on humor are reviewed. In addition, scientific fields germane to the evolutionary study of humor are examined: animal models, genetics, children's humor, humor in pathological conditions, neurobiology, humor in traditional societies and cognitive archeology. Candidate selection pressures and associated evolutionary mechanisms are considered. The authors conclude that several evolutionary-related topics such as the origins of language, cognition underlying spiritual feelings, hominid group size, and primate teasing could have special relevance to the origins of humor.

  1. Genomes, Phylogeny, and Evolutionary Systems Biology

    Energy Technology Data Exchange (ETDEWEB)

    Medina, Monica

    2005-03-25

    With the completion of the human genome and the growing number of diverse genomes being sequenced, a new age of evolutionary research is currently taking shape. The myriad of technological breakthroughs in biology that are leading to the unification of broad scientific fields such as molecular biology, biochemistry, physics, mathematics and computer science are now known as systems biology. Here I present an overview, with an emphasis on eukaryotes, of how the postgenomics era is adopting comparative approaches that go beyond comparisons among model organisms to shape the nascent field of evolutionary systems biology.

  2. Evolutionary algorithm for vehicle driving cycle generation.

    Science.gov (United States)

    Perhinschi, Mario G; Marlowe, Christopher; Tamayo, Sergio; Tu, Jun; Wayne, W Scott

    2011-09-01

    Modeling transit bus emissions and fuel economy requires a large amount of experimental data over wide ranges of operational conditions. Chassis dynamometer tests are typically performed using representative driving cycles defined based on vehicle instantaneous speed as sequences of "microtrips", which are intervals between consecutive vehicle stops. Overall significant parameters of the driving cycle, such as average speed, stops per mile, kinetic intensity, and others, are used as independent variables in the modeling process. Performing tests at all the necessary combinations of parameters is expensive and time consuming. In this paper, a methodology is proposed for building driving cycles at prescribed independent variable values using experimental data through the concatenation of "microtrips" isolated from a limited number of standard chassis dynamometer test cycles. The selection of the adequate "microtrips" is achieved through a customized evolutionary algorithm. The genetic representation uses microtrip definitions as genes. Specific mutation, crossover, and karyotype alteration operators have been defined. The Roulette-Wheel selection technique with elitist strategy drives the optimization process, which consists of minimizing the errors to desired overall cycle parameters. This utility is part of the Integrated Bus Information System developed at West Virginia University.

  3. Ecological and evolutionary consequences of niche construction for its agent.

    Science.gov (United States)

    Kylafis, Grigoris; Loreau, Michel

    2008-10-01

    Niche construction can generate ecological and evolutionary feedbacks that have been underinvestigated so far. We present an eco-evolutionary model that incorporates the process of niche construction to reveal its effects on the ecology and evolution of the niche-constructing agent. We consider a simple plant-soil nutrient ecosystem in which plants have the ability to increase the input of inorganic nutrient as an example of positive niche construction. On an ecological time scale, the model shows that niche construction allows the persistence of plants under infertile soil conditions that would otherwise lead to their extinction. This expansion of plants' niche, however, requires a high enough rate of niche construction and a high enough initial plant biomass to fuel the positive ecological feedback between plants and their soil environment. On an evolutionary time scale, we consider that the rates of niche construction and nutrient uptake coevolve in plants while a trade-off constrains their values. Different evolutionary outcomes are possible depending on the shape of the trade-off. We show that niche construction results in an evolutionary feedback between plants and their soil environment such that plants partially regulate soil nutrient content. The direct benefit accruing to plants, however, plays a crucial role in the evolutionary advantage of niche construction.

  4. Adaptive evolutionary walks require neutral intermediates in RNA fitness landscapes.

    Science.gov (United States)

    Rendel, Mark D

    2011-01-01

    In RNA fitness landscapes with interconnected networks of neutral mutations, neutral precursor mutations can play an important role in facilitating the accessibility of epistatic adaptive mutant combinations. I use an exhaustively surveyed fitness landscape model based on short sequence RNA genotypes (and their secondary structure phenotypes) to calculate the minimum rate at which mutants initially appearing as neutral are incorporated into an adaptive evolutionary walk. I show first, that incorporating neutral mutations significantly increases the number of point mutations in a given evolutionary walk when compared to estimates from previous adaptive walk models. Second, that incorporating neutral mutants into such a walk significantly increases the final fitness encountered on that walk - indeed evolutionary walks including neutral steps often reach the global optimum in this model. Third, and perhaps most importantly, evolutionary paths of this kind are often extremely winding in their nature and have the potential to undergo multiple mutations at a given sequence position within a single walk; the potential of these winding paths to mislead phylogenetic reconstruction is briefly considered. Copyright © 2010 Elsevier Inc. All rights reserved.

  5. The evolutionary implications of epigenetic inheritance.

    Science.gov (United States)

    Jablonka, Eva

    2017-10-06

    The Modern Evolutionary Synthesis (MS) forged in the mid-twentieth century was built on a notion of heredity that excluded soft inheritance, the inheritance of the effects of developmental modifications. However, the discovery of molecular mechanisms that generate random and developmentally induced epigenetic variations is leading to a broadening of the notion of biological heredity that has consequences for ideas about evolution. After presenting some old challenges to the MS that were raised, among others, by Karl Popper, I discuss recent research on epigenetic inheritance, which provides experimental and theoretical support for these challenges. There is now good evidence that epigenetic inheritance is ubiquitous and is involved in adaptive evolution and macroevolution. I argue that the many evolutionary consequences of epigenetic inheritance open up new research areas and require the extension of the evolutionary synthesis beyond the current neo-Darwinian model.

  6. Testing substellar models with dynamical mass measurements

    Directory of Open Access Journals (Sweden)

    Liu M.C.

    2011-07-01

    Full Text Available We have been using Keck laser guide star adaptive optics to monitor the orbits of ultracool binaries, providing dynamical masses at lower luminosities and temperatures than previously available and enabling strong tests of theoretical models. We have identified three specific problems with theory: (1 We find that model color–magnitude diagrams cannot be reliably used to infer masses as they do not accurately reproduce the colors of ultracool dwarfs of known mass. (2 Effective temperatures inferred from evolutionary model radii are typically inconsistent with temperatures derived from fitting atmospheric models to observed spectra by 100–300 K. (3 For the only known pair of field brown dwarfs with a precise mass (3% and age determination (≈25%, the measured luminosities are ~2–3× higher than predicted by model cooling rates (i.e., masses inferred from Lbol and age are 20–30% larger than measured. To make progress in understanding the observed discrepancies, more mass measurements spanning a wide range of luminosity, temperature, and age are needed, along with more accurate age determinations (e.g., via asteroseismology for primary stars with brown dwarf binary companions. Also, resolved optical and infrared spectroscopy are needed to measure lithium depletion and to characterize the atmospheres of binary components in order to better assess model deficiencies.

  7. Evolutionary strategy to develop learning-based decision systems. Application to breast cancer and liver fibrosis stadialization.

    Science.gov (United States)

    Gorunescu, Florin; Belciug, Smaranda

    2014-06-01

    The purpose of this paper is twofold: first, to propose an evolutionary-based method for building a decision model and, second, to assess and validate the model's performance using five different real-world medical datasets (breast cancer and liver fibrosis) by comparing it with state-of-the-art machine learning techniques. The evolutionary-inspired approach has been used to develop the learning-based decision model in the following manner: the hybridization of algorithms has been considered as "crossover", while the development of new variants which can be thought of as "mutation". An appropriate hierarchy of the component algorithms was established based on a statistically built fitness measure. A synergetic decision-making process, based on a weighted voting system, involved the collaboration between the selected algorithms in making the final decision. Well-established statistical performance measures and comparison tests have been extensively used to design and implement the model. Finally, the proposed method has been tested on five medical datasets, out of which four publicly available, and contrasted with state-of-the-art techniques, showing its efficiency in supporting the medical decision-making process. Copyright © 2014 Elsevier Inc. All rights reserved.

  8. The Neural Systems of Forgiveness: An Evolutionary Psychological Perspective

    Directory of Open Access Journals (Sweden)

    Joseph Billingsley

    2017-05-01

    Full Text Available Evolution-minded researchers posit that the suite of human cognitive adaptations may include forgiveness systems. According to these researchers, forgiveness systems regulate interpersonal motivation toward a transgressor in the wake of harm by weighing multiple factors that influence both the potential gains of future interaction with the transgressor and the likelihood of future harm. Although behavioral research generally supports this evolutionary model of forgiveness, the model’s claims have not been examined with available neuroscience specifically in mind, nor has recent neuroscientific research on forgiveness generally considered the evolutionary literature. The current review aims to help bridge this gap by using evolutionary psychology and cognitive neuroscience to mutually inform and interrogate one another. We briefly summarize the evolutionary research on forgiveness, then review recent neuroscientific findings on forgiveness in light of the evolutionary model. We emphasize neuroscientific research that links desire for vengeance to reward-based areas of the brain, that singles out prefrontal areas likely associated with inhibition of vengeful feelings, and that correlates the activity of a theory-of-mind network with assessments of the intentions and blameworthiness of those who commit harm. In addition, we identify gaps in the existing neuroscientific literature, and propose future research directions that might address them, at least in part.

  9. Protein 3D structure computed from evolutionary sequence variation.

    Directory of Open Access Journals (Sweden)

    Debora S Marks

    Full Text Available The evolutionary trajectory of a protein through sequence space is constrained by its function. Collections of sequence homologs record the outcomes of millions of evolutionary experiments in which the protein evolves according to these constraints. Deciphering the evolutionary record held in these sequences and exploiting it for predictive and engineering purposes presents a formidable challenge. The potential benefit of solving this challenge is amplified by the advent of inexpensive high-throughput genomic sequencing.In this paper we ask whether we can infer evolutionary constraints from a set of sequence homologs of a protein. The challenge is to distinguish true co-evolution couplings from the noisy set of observed correlations. We address this challenge using a maximum entropy model of the protein sequence, constrained by the statistics of the multiple sequence alignment, to infer residue pair couplings. Surprisingly, we find that the strength of these inferred couplings is an excellent predictor of residue-residue proximity in folded structures. Indeed, the top-scoring residue couplings are sufficiently accurate and well-distributed to define the 3D protein fold with remarkable accuracy.We quantify this observation by computing, from sequence alone, all-atom 3D structures of fifteen test proteins from different fold classes, ranging in size from 50 to 260 residues, including a G-protein coupled receptor. These blinded inferences are de novo, i.e., they do not use homology modeling or sequence-similar fragments from known structures. The co-evolution signals provide sufficient information to determine accurate 3D protein structure to 2.7-4.8 Å C(α-RMSD error relative to the observed structure, over at least two-thirds of the protein (method called EVfold, details at http://EVfold.org. This discovery provides insight into essential interactions constraining protein evolution and will facilitate a comprehensive survey of the universe of

  10. Evolutionary Computation and Its Applications in Neural and Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Biaobiao Zhang

    2011-01-01

    Full Text Available Neural networks and fuzzy systems are two soft-computing paradigms for system modelling. Adapting a neural or fuzzy system requires to solve two optimization problems: structural optimization and parametric optimization. Structural optimization is a discrete optimization problem which is very hard to solve using conventional optimization techniques. Parametric optimization can be solved using conventional optimization techniques, but the solution may be easily trapped at a bad local optimum. Evolutionary computation is a general-purpose stochastic global optimization approach under the universally accepted neo-Darwinian paradigm, which is a combination of the classical Darwinian evolutionary theory, the selectionism of Weismann, and the genetics of Mendel. Evolutionary algorithms are a major approach to adaptation and optimization. In this paper, we first introduce evolutionary algorithms with emphasis on genetic algorithms and evolutionary strategies. Other evolutionary algorithms such as genetic programming, evolutionary programming, particle swarm optimization, immune algorithm, and ant colony optimization are also described. Some topics pertaining to evolutionary algorithms are also discussed, and a comparison between evolutionary algorithms and simulated annealing is made. Finally, the application of EAs to the learning of neural networks as well as to the structural and parametric adaptations of fuzzy systems is also detailed.

  11. Remembering the evolutionary Freud.

    Science.gov (United States)

    Young, Allan

    2006-03-01

    Throughout his career as a writer, Sigmund Freud maintained an interest in the evolutionary origins of the human mind and its neurotic and psychotic disorders. In common with many writers then and now, he believed that the evolutionary past is conserved in the mind and the brain. Today the "evolutionary Freud" is nearly forgotten. Even among Freudians, he is regarded to be a red herring, relevant only to the extent that he diverts attention from the enduring achievements of the authentic Freud. There are three ways to explain these attitudes. First, the evolutionary Freud's key work is the "Overview of the Transference Neurosis" (1915). But it was published at an inopportune moment, forty years after the author's death, during the so-called "Freud wars." Second, Freud eventually lost interest in the "Overview" and the prospect of a comprehensive evolutionary theory of psychopathology. The publication of The Ego and the Id (1923), introducing Freud's structural theory of the psyche, marked the point of no return. Finally, Freud's evolutionary theory is simply not credible. It is based on just-so stories and a thoroughly discredited evolutionary mechanism, Lamarckian use-inheritance. Explanations one and two are probably correct but also uninteresting. Explanation number three assumes that there is a fundamental difference between Freud's evolutionary narratives (not credible) and the evolutionary accounts of psychopathology that currently circulate in psychiatry and mainstream journals (credible). The assumption is mistaken but worth investigating.

  12. Falsification of matching theory and confirmation of an evolutionary theory of behavior dynamics in a critical experiment.

    Science.gov (United States)

    McDowell, J J; Calvin, Olivia L; Hackett, Ryan; Klapes, Bryan

    2017-07-01

    Two competing predictions of matching theory and an evolutionary theory of behavior dynamics, and one additional prediction of the evolutionary theory, were tested in a critical experiment in which human participants worked on concurrent schedules for money (Dallery et al., 2005). The three predictions concerned the descriptive adequacy of matching theory equations, and of equations describing emergent equilibria of the evolutionary theory. Tests of the predictions falsified matching theory and supported the evolutionary theory. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Improvements in seismic event locations in a deep western U.S. coal mine using tomographic velocity models and an evolutionary search algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Adam Lurka; Peter Swanson [Central Mining Institute, Katowice (Poland)

    2009-09-15

    Methods of improving seismic event locations were investigated as part of a research study aimed at reducing ground control safety hazards. Seismic event waveforms collected with a 23-station three-dimensional sensor array during longwall coal mining provide the data set used in the analyses. A spatially variable seismic velocity model is constructed using seismic event sources in a passive tomographic method. The resulting three-dimensional velocity model is used to relocate seismic event positions. An evolutionary optimization algorithm is implemented and used in both the velocity model development and in seeking improved event location solutions. Results obtained using the different velocity models are compared. The combination of the tomographic velocity model development and evolutionary search algorithm provides improvement to the event locations. 13 refs., 5 figs., 4 tabs.

  14. Multi-objective evolutionary algorithms for fuzzy classification in survival prediction.

    Science.gov (United States)

    Jiménez, Fernando; Sánchez, Gracia; Juárez, José M

    2014-03-01

    This paper presents a novel rule-based fuzzy classification methodology for survival/mortality prediction in severe burnt patients. Due to the ethical aspects involved in this medical scenario, physicians tend not to accept a computer-based evaluation unless they understand why and how such a recommendation is given. Therefore, any fuzzy classifier model must be both accurate and interpretable. The proposed methodology is a three-step process: (1) multi-objective constrained optimization of a patient's data set, using Pareto-based elitist multi-objective evolutionary algorithms to maximize accuracy and minimize the complexity (number of rules) of classifiers, subject to interpretability constraints; this step produces a set of alternative (Pareto) classifiers; (2) linguistic labeling, which assigns a linguistic label to each fuzzy set of the classifiers; this step is essential to the interpretability of the classifiers; (3) decision making, whereby a classifier is chosen, if it is satisfactory, according to the preferences of the decision maker. If no classifier is satisfactory for the decision maker, the process starts again in step (1) with a different input parameter set. The performance of three multi-objective evolutionary algorithms, niched pre-selection multi-objective algorithm, elitist Pareto-based multi-objective evolutionary algorithm for diversity reinforcement (ENORA) and the non-dominated sorting genetic algorithm (NSGA-II), was tested using a patient's data set from an intensive care burn unit and a standard machine learning data set from an standard machine learning repository. The results are compared using the hypervolume multi-objective metric. Besides, the results have been compared with other non-evolutionary techniques and validated with a multi-objective cross-validation technique. Our proposal improves the classification rate obtained by other non-evolutionary techniques (decision trees, artificial neural networks, Naive Bayes, and case

  15. Conversion Rate Optimization through Evolutionary Computation

    OpenAIRE

    Miikkulainen, Risto; Iscoe, Neil; Shagrin, Aaron; Cordell, Ron; Nazari, Sam; Schoolland, Cory; Brundage, Myles; Epstein, Jonathan; Dean, Randy; Lamba, Gurmeet

    2017-01-01

    Conversion optimization means designing a web interface so that as many users as possible take a desired action on it, such as register or purchase. Such design is usually done by hand, testing one change at a time through A/B testing, or a limited number of combinations through multivariate testing, making it possible to evaluate only a small fraction of designs in a vast design space. This paper describes Sentient Ascend, an automatic conversion optimization system that uses evolutionary op...

  16. Evolutionary competition between boundedly rational behavioral rules in oligopoly games

    International Nuclear Information System (INIS)

    Cerboni Baiardi, Lorenzo; Lamantia, Fabio; Radi, Davide

    2015-01-01

    In this paper, we propose an evolutionary model of oligopoly competition where agents can select between different behavioral rules to make decisions on productions. We formalize the model as a general class of evolutionary oligopoly games and then we consider an example with two specific rules, namely Local Monopolistic Approximation and Gradient dynamics. We provide several results on the global dynamic properties of the model, showing that in some cases the attractor of the system may belong to an invariant plane where only one behavioral rule is adopted (monomorphic state). The attractors on the invariant planes can be either strong attractors or weak attractors. However, we also explain why the system can be in a state of Evolutionary Stable Heterogeneity, where it is more profitable for the agents to employ both heuristics in the long term (polymorphic state).

  17. Empirical tests of natural selection-based evolutionary accounts of ADHD: a systematic review.

    Science.gov (United States)

    Thagaard, Marthe S; Faraone, Stephen V; Sonuga-Barke, Edmund J; Østergaard, Søren D

    2016-10-01

    ADHD is a prevalent and highly heritable mental disorder associated with significant impairment, morbidity and increased rates of mortality. This combination of high prevalence and high morbidity/mortality seen in ADHD and other mental disorders presents a challenge to natural selection-based models of human evolution. Several hypotheses have been proposed in an attempt to resolve this apparent paradox. The aim of this study was to review the evidence for these hypotheses. We conducted a systematic review of the literature on empirical investigations of natural selection-based evolutionary accounts for ADHD in adherence with the PRISMA guideline. The PubMed, Embase, and PsycINFO databases were screened for relevant publications, by combining search terms covering evolution/selection with search terms covering ADHD. The search identified 790 records. Of these, 15 full-text articles were assessed for eligibility, and three were included in the review. Two of these reported on the evolution of the seven-repeat allele of the ADHD-associated dopamine receptor D4 gene, and one reported on the results of a simulation study of the effect of suggested ADHD-traits on group survival. The authors of the three studies interpreted their findings as favouring the notion that ADHD-traits may have been associated with increased fitness during human evolution. However, we argue that none of the three studies really tap into the core symptoms of ADHD, and that their conclusions therefore lack validity for the disorder. This review indicates that the natural selection-based accounts of ADHD have not been subjected to empirical test and therefore remain hypothetical.

  18. The Predictive Power of Evolutionary Biology and the Discovery of Eusociality in the Naked Mole-Rat.

    Science.gov (United States)

    Braude, Stanton

    1997-01-01

    Discusses how biologists use evolutionary theory and provides examples of how evolutionary biologists test hypotheses on specific modes of selection and evolution. Presents an example of the successful predictive power of one evolutionary hypothesis. Contains 38 references. (DDR)

  19. [Evolutionary medicine].

    Science.gov (United States)

    Wjst, M

    2013-12-01

    Evolutionary medicine allows new insights into long standing medical problems. Are we "really stoneagers on the fast lane"? This insight might have enormous consequences and will allow new answers that could never been provided by traditional anthropology. Only now this is made possible using data from molecular medicine and systems biology. Thereby evolutionary medicine takes a leap from a merely theoretical discipline to practical fields - reproductive, nutritional and preventive medicine, as well as microbiology, immunology and psychiatry. Evolutionary medicine is not another "just so story" but a serious candidate for the medical curriculum providing a universal understanding of health and disease based on our biological origin. © Georg Thieme Verlag KG Stuttgart · New York.

  20. Core principles of evolutionary medicine

    Science.gov (United States)

    Grunspan, Daniel Z; Nesse, Randolph M; Barnes, M Elizabeth; Brownell, Sara E

    2018-01-01

    Abstract Background and objectives Evolutionary medicine is a rapidly growing field that uses the principles of evolutionary biology to better understand, prevent and treat disease, and that uses studies of disease to advance basic knowledge in evolutionary biology. Over-arching principles of evolutionary medicine have been described in publications, but our study is the first to systematically elicit core principles from a diverse panel of experts in evolutionary medicine. These principles should be useful to advance recent recommendations made by The Association of American Medical Colleges and the Howard Hughes Medical Institute to make evolutionary thinking a core competency for pre-medical education. Methodology The Delphi method was used to elicit and validate a list of core principles for evolutionary medicine. The study included four surveys administered in sequence to 56 expert panelists. The initial open-ended survey created a list of possible core principles; the three subsequent surveys winnowed the list and assessed the accuracy and importance of each principle. Results Fourteen core principles elicited at least 80% of the panelists to agree or strongly agree that they were important core principles for evolutionary medicine. These principles over-lapped with concepts discussed in other articles discussing key concepts in evolutionary medicine. Conclusions and implications This set of core principles will be helpful for researchers and instructors in evolutionary medicine. We recommend that evolutionary medicine instructors use the list of core principles to construct learning goals. Evolutionary medicine is a young field, so this list of core principles will likely change as the field develops further. PMID:29493660

  1. Tools for Accurate and Efficient Analysis of Complex Evolutionary Mechanisms in Microbial Genomes. Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Nakhleh, Luay

    2014-03-12

    I proposed to develop computationally efficient tools for accurate detection and reconstruction of microbes' complex evolutionary mechanisms, thus enabling rapid and accurate annotation, analysis and understanding of their genomes. To achieve this goal, I proposed to address three aspects. (1) Mathematical modeling. A major challenge facing the accurate detection of HGT is that of distinguishing between these two events on the one hand and other events that have similar "effects." I proposed to develop a novel mathematical approach for distinguishing among these events. Further, I proposed to develop a set of novel optimization criteria for the evolutionary analysis of microbial genomes in the presence of these complex evolutionary events. (2) Algorithm design. In this aspect of the project, I proposed to develop an array of e cient and accurate algorithms for analyzing microbial genomes based on the formulated optimization criteria. Further, I proposed to test the viability of the criteria and the accuracy of the algorithms in an experimental setting using both synthetic as well as biological data. (3) Software development. I proposed the nal outcome to be a suite of software tools which implements the mathematical models as well as the algorithms developed.

  2. Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset

    Directory of Open Access Journals (Sweden)

    Gidrol Xavier

    2008-02-01

    Full Text Available Abstract Background Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interactions may be modelled by a Bayesian Network (BN that represents the presence of direct interactions from regulators to regulees by conditional probability distributions. We used enhanced evolutionary algorithms to stochastically evolve a set of candidate BN structures and found the model that best fits data without prior knowledge. Results We proposed various evolutionary strategies suitable for the task and tested our choices using simulated data drawn from a given bio-realistic network of 35 nodes, the so-called insulin network, which has been used in the literature for benchmarking. We assessed the inferred models against this reference to obtain statistical performance results. We then compared performances of evolutionary algorithms using two kinds of recombination operators that operate at different scales in the graphs. We introduced a niching strategy that reinforces diversity through the population and avoided trapping of the algorithm in one local minimum in the early steps of learning. We show the limited effect of the mutation operator when niching is applied. Finally, we compared our best evolutionary approach with various well known learning algorithms (MCMC, K2, greedy search, TPDA, MMHC devoted to BN structure learning. Conclusion We studied the behaviour of an evolutionary approach enhanced by niching for the learning of gene regulatory networks with BN. We show that this approach outperforms classical structure learning methods in elucidating the original model. These results were obtained for the learning of a bio-realistic network and, more importantly, on various small datasets. This is a suitable approach for learning transcriptional regulatory networks from real datasets without prior knowledge.

  3. Misrepresentations of evolutionary psychology in sex and gender textbooks.

    Science.gov (United States)

    Winegard, Benjamin M; Winegard, Bo M; Deaner, Robert O

    2014-05-20

    Evolutionary psychology has provoked controversy, especially when applied to human sex differences. We hypothesize that this is partly due to misunderstandings of evolutionary psychology that are perpetuated by undergraduate sex and gender textbooks. As an initial test of this hypothesis, we develop a catalog of eight types of errors and document their occurrence in 15 widely used sex and gender textbooks. Consistent with our hypothesis, of the 12 textbooks that discussed evolutionary psychology, all contained at least one error, and the median number of errors was five. The most common types of errors were "Straw Man," "Biological Determinism," and "Species Selection." We conclude by suggesting improvements to undergraduate sex and gender textbooks.

  4. Evolutionary optimization of production materials workflow processes

    DEFF Research Database (Denmark)

    Herbert, Luke Thomas; Hansen, Zaza Nadja Lee; Jacobsen, Peter

    2014-01-01

    We present an evolutionary optimisation technique for stochastic production processes, which is able to find improved production materials workflow processes with respect to arbitrary combinations of numerical quantities associated with the production process. Working from a core fragment...... of the BPMN language, we employ an evolutionary algorithm where stochastic model checking is used as a fitness function to determine the degree of improvement of candidate processes derived from the original process through mutation and cross-over operations. We illustrate this technique using a case study...

  5. Development of a population of cancer cells: Observation and modeling by a Mixed Spatial Evolutionary Games approach.

    Science.gov (United States)

    Świerniak, Andrzej; Krześlak, Michał; Student, Sebastian; Rzeszowska-Wolny, Joanna

    2016-09-21

    Living cells, like whole living organisms during evolution, communicate with their neighbors, interact with the environment, divide, change their phenotypes, and eventually die. The development of specific ways of communication (through signaling molecules and receptors) allows some cellular subpopulations to survive better, to coordinate their physiological status, and during embryonal development to create tissues and organs or in some conditions to become tumors. Populations of cells cultured in vitro interact similarly, also competing for space and nutrients and stimulating each other to better survive or to die. The results of these intercellular interactions of different types seem to be good examples of biological evolutionary games, and have been the subjects of simulations by the methods of evolutionary game theory where individual cells are treated as players. Here we present examples of intercellular contacts in a population of living human cancer HeLa cells cultured in vitro and propose an evolutionary game theory approach to model the development of such populations. We propose a new technique termed Mixed Spatial Evolutionary Games (MSEG) which are played on multiple lattices corresponding to the possible cellular phenotypes which gives the possibility of simulating and investigating the effects of heterogeneity at the cellular level in addition to the population level. Analyses performed with MSEG suggested different ways in which cellular populations develop in the case of cells communicating directly and through factors released to the environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Applying evolutionary anthropology.

    Science.gov (United States)

    Gibson, Mhairi A; Lawson, David W

    2015-01-01

    Evolutionary anthropology provides a powerful theoretical framework for understanding how both current environments and legacies of past selection shape human behavioral diversity. This integrative and pluralistic field, combining ethnographic, demographic, and sociological methods, has provided new insights into the ultimate forces and proximate pathways that guide human adaptation and variation. Here, we present the argument that evolutionary anthropological studies of human behavior also hold great, largely untapped, potential to guide the design, implementation, and evaluation of social and public health policy. Focusing on the key anthropological themes of reproduction, production, and distribution we highlight classic and recent research demonstrating the value of an evolutionary perspective to improving human well-being. The challenge now comes in transforming relevance into action and, for that, evolutionary behavioral anthropologists will need to forge deeper connections with other applied social scientists and policy-makers. We are hopeful that these developments are underway and that, with the current tide of enthusiasm for evidence-based approaches to policy, evolutionary anthropology is well positioned to make a strong contribution. © 2015 Wiley Periodicals, Inc.

  7. Applying Evolutionary Anthropology

    Science.gov (United States)

    Gibson, Mhairi A; Lawson, David W

    2015-01-01

    Evolutionary anthropology provides a powerful theoretical framework for understanding how both current environments and legacies of past selection shape human behavioral diversity. This integrative and pluralistic field, combining ethnographic, demographic, and sociological methods, has provided new insights into the ultimate forces and proximate pathways that guide human adaptation and variation. Here, we present the argument that evolutionary anthropological studies of human behavior also hold great, largely untapped, potential to guide the design, implementation, and evaluation of social and public health policy. Focusing on the key anthropological themes of reproduction, production, and distribution we highlight classic and recent research demonstrating the value of an evolutionary perspective to improving human well-being. The challenge now comes in transforming relevance into action and, for that, evolutionary behavioral anthropologists will need to forge deeper connections with other applied social scientists and policy-makers. We are hopeful that these developments are underway and that, with the current tide of enthusiasm for evidence-based approaches to policy, evolutionary anthropology is well positioned to make a strong contribution. PMID:25684561

  8. Evolutionary Computation Methods and their applications in Statistics

    Directory of Open Access Journals (Sweden)

    Francesco Battaglia

    2013-05-01

    Full Text Available A brief discussion of the genesis of evolutionary computation methods, their relationship to artificial intelligence, and the contribution of genetics and Darwin’s theory of natural evolution is provided. Then, the main evolutionary computation methods are illustrated: evolution strategies, genetic algorithms, estimation of distribution algorithms, differential evolution, and a brief description of some evolutionary behavior methods such as ant colony and particle swarm optimization. We also discuss the role of the genetic algorithm for multivariate probability distribution random generation, rather than as a function optimizer. Finally, some relevant applications of genetic algorithm to statistical problems are reviewed: selection of variables in regression, time series model building, outlier identification, cluster analysis, design of experiments.

  9. Studying the evolutionary significance of thermal adaptation in ectotherms: The diversification of amphibians' energetics.

    Science.gov (United States)

    Nespolo, Roberto F; Figueroa, Julio; Solano-Iguaran, Jaiber J

    2017-08-01

    A fundamental problem in evolutionary biology is the understanding of the factors that promote or constrain adaptive evolution, and assessing the role of natural selection in this process. Here, comparative phylogenetics, that is, using phylogenetic information and traits to infer evolutionary processes has been a major paradigm . In this study, we discuss Ornstein-Uhlenbeck models (OU) in the context of thermal adaptation in ectotherms. We specifically applied this approach to study amphibians's evolution and energy metabolism. It has been hypothesized that amphibians exploit adaptive zones characterized by low energy expenditure, which generate specific predictions in terms of the patterns of diversification in standard metabolic rate (SMR). We complied whole-animal metabolic rates for 122 species of amphibians, and adjusted several models of diversification. According to the adaptive zone hypothesis, we expected: (1) to find "accelerated evolution" in SMR (i.e., diversification above Brownian Motion expectations, BM), (2) that a model assuming evolutionary optima (i.e., an OU model) fits better than a white-noise model and (3) that a model assuming multiple optima (according to the three amphibians's orders) fits better than a model assuming a single optimum. As predicted, we found that the diversification of SMR occurred most of the time, above BM expectations. Also, we found that a model assuming an optimum explained the data in a better way than a white-noise model. However, we did not find evidence that an OU model with multiple optima fits the data better, suggesting a single optimum in SMR for Anura, Caudata and Gymnophiona. These results show how comparative phylogenetics could be applied for testing adaptive hypotheses regarding history and physiological performance in ectotherms. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Evolutionary game theory: cells as players.

    Science.gov (United States)

    Hummert, Sabine; Bohl, Katrin; Basanta, David; Deutsch, Andreas; Werner, Sarah; Theissen, Günter; Schroeter, Anja; Schuster, Stefan

    2014-12-01

    In two papers we review game theory applications in biology below the level of cognitive living beings. It can be seen that evolution and natural selection replace the rationality of the actors appropriately. Even in these micro worlds, competing situations and cooperative relationships can be found and modeled by evolutionary game theory. Also those units of the lowest levels of life show different strategies for different environmental situations or different partners. We give a wide overview of evolutionary game theory applications to microscopic units. In this first review situations on the cellular level are tackled. In particular metabolic problems are discussed, such as ATP-producing pathways, secretion of public goods and cross-feeding. Further topics are cyclic competition among more than two partners, intra- and inter-cellular signalling, the struggle between pathogens and the immune system, and the interactions of cancer cells. Moreover, we introduce the theoretical basics to encourage scientists to investigate problems in cell biology and molecular biology by evolutionary game theory.

  11. A system dynamics model based on evolutionary game theory for green supply chain management diffusion among Chinese manufacturers

    DEFF Research Database (Denmark)

    Tian, Yihui; Govindan, Kannan; Zhu, Qinghua

    2014-01-01

    In this study, a system dynamics (SD) model is developed to guide the subsidy policies to promote the diffusion of green supply chain management (GSCM) in China. The relationships of stakeholders such as government, enterprises and consumers are analyzed through evolutionary game theory. Finally...

  12. Parallel Evolutionary Optimization Algorithms for Peptide-Protein Docking

    Science.gov (United States)

    Poluyan, Sergey; Ershov, Nikolay

    2018-02-01

    In this study we examine the possibility of using evolutionary optimization algorithms in protein-peptide docking. We present the main assumptions that reduce the docking problem to a continuous global optimization problem and provide a way of using evolutionary optimization algorithms. The Rosetta all-atom force field was used for structural representation and energy scoring. We describe the parallelization scheme and MPI/OpenMP realization of the considered algorithms. We demonstrate the efficiency and the performance for some algorithms which were applied to a set of benchmark tests.

  13. Evolutionary Expectations

    DEFF Research Database (Denmark)

    Nash, Ulrik William

    2014-01-01

    , they are correlated among people who share environments because these individuals satisfice within their cognitive bounds by using cues in order of validity, as opposed to using cues arbitrarily. Any difference in expectations thereby arise from differences in cognitive ability, because two individuals with identical...... cognitive bounds will perceive business opportunities identically. In addition, because cues provide information about latent causal structures of the environment, changes in causality must be accompanied by changes in cognitive representations if adaptation is to be maintained. The concept of evolutionary......The concept of evolutionary expectations descends from cue learning psychology, synthesizing ideas on rational expectations with ideas on bounded rationality, to provide support for these ideas simultaneously. Evolutionary expectations are rational, but within cognitive bounds. Moreover...

  14. Evolutionary Awareness

    Directory of Open Access Journals (Sweden)

    Gregory Gorelik

    2014-10-01

    Full Text Available In this article, we advance the concept of “evolutionary awareness,” a metacognitive framework that examines human thought and emotion from a naturalistic, evolutionary perspective. We begin by discussing the evolution and current functioning of the moral foundations on which our framework rests. Next, we discuss the possible applications of such an evolutionarily-informed ethical framework to several domains of human behavior, namely: sexual maturation, mate attraction, intrasexual competition, culture, and the separation between various academic disciplines. Finally, we discuss ways in which an evolutionary awareness can inform our cross-generational activities—which we refer to as “intergenerational extended phenotypes”—by helping us to construct a better future for ourselves, for other sentient beings, and for our environment.

  15. Synergistic Coherence of Bifurcation Evolutionary Processes of Mergers and Acquisitions of Enterprises

    Directory of Open Access Journals (Sweden)

    Ivanchenko Hennadii F.

    2016-08-01

    Full Text Available The aim of the article is developing information tools for the economic and mathematical modeling of the dynamics of evolutionary processes concerning trophic relationships of populations of enterprises, which allowed to conduct the phase and bifurcation analysis of possible dynamic regimes of the populations’ evolution, determine the mechanisms of influence of the external environment and the internal structure of the system, identify patterns and limits of stability of M&A processes. In the work the main provisions of the evolutionary concept concerning development of the population of enterprises as an economic system are analyzed, the provisions of the evolutionary concept of population systems’ development are considered, the basis of evolutionary modeling methods allowing to analyze the functioning of populations of enterprises in terms of individual strategies of each enterprise’s behavior is studied. The basic principles of synergy of the life cycle evolution for populations of enterprises are determined. An evolutionary approach to the evaluation of a synergistic effect of M & A is proposed. The evolutionary modeling of the scenario for self-organization of populations of dairy industry enterprises through a combination of statistical and expert data is applied. There also created a model of the population of firms reflecting behavioral and resource and technological characteristics of the studied in the work real population of industrial enterprises, which form the input flows of matter, energy and information to the dairy industry, which allows to combine the reflection of main possible options in terms of the external conditions of the population functioning and its internal structure.

  16. Modelling Evolutionary Algorithms with Stochastic Differential Equations.

    Science.gov (United States)

    Heredia, Jorge Pérez

    2017-11-20

    There has been renewed interest in modelling the behaviour of evolutionary algorithms (EAs) by more traditional mathematical objects, such as ordinary differential equations or Markov chains. The advantage is that the analysis becomes greatly facilitated due to the existence of well established methods. However, this typically comes at the cost of disregarding information about the process. Here, we introduce the use of stochastic differential equations (SDEs) for the study of EAs. SDEs can produce simple analytical results for the dynamics of stochastic processes, unlike Markov chains which can produce rigorous but unwieldy expressions about the dynamics. On the other hand, unlike ordinary differential equations (ODEs), they do not discard information about the stochasticity of the process. We show that these are especially suitable for the analysis of fixed budget scenarios and present analogues of the additive and multiplicative drift theorems from runtime analysis. In addition, we derive a new more general multiplicative drift theorem that also covers non-elitist EAs. This theorem simultaneously allows for positive and negative results, providing information on the algorithm's progress even when the problem cannot be optimised efficiently. Finally, we provide results for some well-known heuristics namely Random Walk (RW), Random Local Search (RLS), the (1+1) EA, the Metropolis Algorithm (MA), and the Strong Selection Weak Mutation (SSWM) algorithm.

  17. Infrastructure system restoration planning using evolutionary algorithms

    Science.gov (United States)

    Corns, Steven; Long, Suzanna K.; Shoberg, Thomas G.

    2016-01-01

    This paper presents an evolutionary algorithm to address restoration issues for supply chain interdependent critical infrastructure. Rapid restoration of infrastructure after a large-scale disaster is necessary to sustaining a nation's economy and security, but such long-term restoration has not been investigated as thoroughly as initial rescue and recovery efforts. A model of the Greater Saint Louis Missouri area was created and a disaster scenario simulated. An evolutionary algorithm is used to determine the order in which the bridges should be repaired based on indirect costs. Solutions were evaluated based on the reduction of indirect costs and the restoration of transportation capacity. When compared to a greedy algorithm, the evolutionary algorithm solution reduced indirect costs by approximately 12.4% by restoring automotive travel routes for workers and re-establishing the flow of commodities across the three rivers in the Saint Louis area.

  18. An evolutionary explanation of the value premium puzzle

    OpenAIRE

    Hens, Thorsten; Lensberg, Terje; Schenk-Hoppé, Klaus Reiner; Wöhrmann, Peter

    2011-01-01

    As early as 1934 Graham and Dodd conjectured that excess returns from value investment originate from a tendency of stock prices to converge towards a fundamental value. This paper confirms their insights within the evolutionary finance model of Evstigneev et al. (Econ Theory 27:449–468, (Evstigneev et al. 2006)). Our empirical results show the predictive power of the evolutionary benchmark valuation for the relative market capitalization and its dynamics in the sample of firms listed in the ...

  19. Economic and evolutionary hypotheses for cross-population variation in parochialism

    OpenAIRE

    Daniel Jacob Hruschka; Joseph eHenrich

    2013-01-01

    Human populations differ reliably in the degree to which people favor family, friends and community members over strangers and outsiders. In the last decade, researchers have begun to propose several economic and evolutionary hypotheses for these cross-population differences in parochialism. In this paper, we outline major current theories and review recent attempts to test them. We also discuss the key methodological challenges in assessing these diverse economic and evolutionary theories...

  20. Electricity demand and spot price forecasting using evolutionary computation combined with chaotic nonlinear dynamic model

    International Nuclear Information System (INIS)

    Unsihuay-Vila, C.; Zambroni de Souza, A.C.; Marangon-Lima, J.W.; Balestrassi, P.P.

    2010-01-01

    This paper proposes a new hybrid approach based on nonlinear chaotic dynamics and evolutionary strategy to forecast electricity loads and prices. The main idea is to develop a new training or identification stage in a nonlinear chaotic dynamic based predictor. In the training stage five optimal parameters for a chaotic based predictor are searched through an optimization model based on evolutionary strategy. The objective function of the optimization model is the mismatch minimization between the multi-step-ahead forecasting of predictor and observed data such as it is done in identification problems. The first contribution of this paper is that the proposed approach is capable of capturing the complex dynamic of demand and price time series considered resulting in a more accuracy forecasting. The second contribution is that the proposed approach run on-line manner, i.e. the optimal set of parameters and prediction is executed automatically which can be used to prediction in real-time, it is an advantage in comparison with other models, where the choice of their input parameters are carried out off-line, following qualitative/experience-based recipes. A case study of load and price forecasting is presented using data from New England, Alberta, and Spain. A comparison with other methods such as autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) is shown. The results show that the proposed approach provides a more accurate and effective forecasting than ARIMA and ANN methods. (author)

  1. Attractive evolutionary equilibria

    NARCIS (Netherlands)

    Joosten, Reinoud A.M.G.; Roorda, Berend

    2011-01-01

    We present attractiveness, a refinement criterion for evolutionary equilibria. Equilibria surviving this criterion are robust to small perturbations of the underlying payoff system or the dynamics at hand. Furthermore, certain attractive equilibria are equivalent to others for certain evolutionary

  2. The Zipf Law revisited: An evolutionary model of emerging classification

    Energy Technology Data Exchange (ETDEWEB)

    Levitin, L.B. [Boston Univ., MA (United States); Schapiro, B. [TINA, Brandenburg (Germany); Perlovsky, L. [NRC, Wakefield, MA (United States)

    1996-12-31

    Zipf`s Law is a remarkable rank-frequency relationship observed in linguistics (the frequencies of the use of words are approximately inversely proportional to their ranks in the decreasing frequency order) as well as in the behavior of many complex systems of surprisingly different nature. We suggest an evolutionary model of emerging classification of objects into classes corresponding to concepts and denoted by words. The evolution of the system is derived from two basic assumptions: first, the probability to recognize an object as belonging to a known class is proportional to the number of objects in this class already recognized, and, second, there exists a small probability to observe an object that requires creation of a new class ({open_quotes}mutation{close_quotes} that gives birth to a new {open_quotes}species{close_quotes}). It is shown that the populations of classes in such a system obey the Zipf Law provided that the rate of emergence of new classes is small. The model leads also to the emergence of a second-tier structure of {open_quotes}super-classes{close_quotes} - groups of classes with almost equal populations.

  3. Open Issues in Evolutionary Robotics.

    Science.gov (United States)

    Silva, Fernando; Duarte, Miguel; Correia, Luís; Oliveira, Sancho Moura; Christensen, Anders Lyhne

    2016-01-01

    One of the long-term goals in evolutionary robotics is to be able to automatically synthesize controllers for real autonomous robots based only on a task specification. While a number of studies have shown the applicability of evolutionary robotics techniques for the synthesis of behavioral control, researchers have consistently been faced with a number of issues preventing the widespread adoption of evolutionary robotics for engineering purposes. In this article, we review and discuss the open issues in evolutionary robotics. First, we analyze the benefits and challenges of simulation-based evolution and subsequent deployment of controllers versus evolution on real robotic hardware. Second, we discuss specific evolutionary computation issues that have plagued evolutionary robotics: (1) the bootstrap problem, (2) deception, and (3) the role of genomic encoding and genotype-phenotype mapping in the evolution of controllers for complex tasks. Finally, we address the absence of standard research practices in the field. We also discuss promising avenues of research. Our underlying motivation is the reduction of the current gap between evolutionary robotics and mainstream robotics, and the establishment of evolutionary robotics as a canonical approach for the engineering of autonomous robots.

  4. Predicting loss of evolutionary history: Where are we?

    Science.gov (United States)

    Veron, Simon; Davies, T Jonathan; Cadotte, Marc W; Clergeau, Philippe; Pavoine, Sandrine

    2017-02-01

    The Earth's evolutionary history is threatened by species loss in the current sixth mass extinction event in Earth's history. Such extinction events not only eliminate species but also their unique evolutionary histories. Here we review the expected loss of Earth's evolutionary history quantified by phylogenetic diversity (PD) and evolutionary distinctiveness (ED) at risk. Due to the general paucity of data, global evolutionary history losses have been predicted for only a few groups, such as mammals, birds, amphibians, plants, corals and fishes. Among these groups, there is now empirical support that extinction threats are clustered on the phylogeny; however this is not always a sufficient condition to cause higher loss of phylogenetic diversity in comparison to a scenario of random extinctions. Extinctions of the most evolutionarily distinct species and the shape of phylogenetic trees are additional factors that can elevate losses of evolutionary history. Consequently, impacts of species extinctions differ among groups and regions, and even if global losses are low within large groups, losses can be high among subgroups or within some regions. Further, we show that PD and ED are poorly protected by current conservation practices. While evolutionary history can be indirectly protected by current conservation schemes, optimizing its preservation requires integrating phylogenetic indices with those that capture rarity and extinction risk. Measures based on PD and ED could bring solutions to conservation issues, however they are still rarely used in practice, probably because the reasons to protect evolutionary history are not clear for practitioners or due to a lack of data. However, important advances have been made in the availability of phylogenetic trees and methods for their construction, as well as assessments of extinction risk. Some challenges remain, and looking forward, research should prioritize the assessment of expected PD and ED loss for more taxonomic

  5. Evolutionary game dynamics in a growing structured population

    Energy Technology Data Exchange (ETDEWEB)

    Poncela, Julia; Gomez-Gardenes, Jesus; Moreno, Yamir [Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, E-50009 Zaragoza (Spain); Traulsen, Arne [Emmy-Noether Group for Evolutionary Dynamics, Department of Evolutionary Ecology, Max Planck Institute for Evolutionary Biology, August-Thienemann-Strasse 2, 24306 Ploen (Germany)], E-mail: traulsen@evolbio.mpg.de

    2009-08-15

    We discuss a model for evolutionary game dynamics in a growing, network-structured population. In our model, new players can either make connections to random preexisting players or preferentially attach to those that have been successful in the past. The latter depends on the dynamics of strategies in the game, which we implement following the so-called Fermi rule such that the limits of weak and strong strategy selection can be explored. Our framework allows to address general evolutionary games. With only two parameters describing the preferential attachment and the intensity of selection, we describe a wide range of network structures and evolutionary scenarios. Our results show that even for moderate payoff preferential attachment, over represented hubs arise. Interestingly, we find that while the networks are growing, high levels of cooperation are attained, but the same network structure does not promote cooperation as a static network. Therefore, the mechanism of payoff preferential attachment is different to those usually invoked to explain the promotion of cooperation in static, already-grown networks.

  6. Evolutionary game dynamics in a growing structured population

    International Nuclear Information System (INIS)

    Poncela, Julia; Gomez-Gardenes, Jesus; Moreno, Yamir; Traulsen, Arne

    2009-01-01

    We discuss a model for evolutionary game dynamics in a growing, network-structured population. In our model, new players can either make connections to random preexisting players or preferentially attach to those that have been successful in the past. The latter depends on the dynamics of strategies in the game, which we implement following the so-called Fermi rule such that the limits of weak and strong strategy selection can be explored. Our framework allows to address general evolutionary games. With only two parameters describing the preferential attachment and the intensity of selection, we describe a wide range of network structures and evolutionary scenarios. Our results show that even for moderate payoff preferential attachment, over represented hubs arise. Interestingly, we find that while the networks are growing, high levels of cooperation are attained, but the same network structure does not promote cooperation as a static network. Therefore, the mechanism of payoff preferential attachment is different to those usually invoked to explain the promotion of cooperation in static, already-grown networks.

  7. Epidemiological, evolutionary and co-evolutionary implications of context-dependent parasitism

    Science.gov (United States)

    Vale, Pedro F.; Wilson, Alastair J.; Best, Alex; Boots, Mike; Little, Tom J.

    2013-01-01

    Victims of infection are expected to suffer increasingly as parasite population growth increases. Yet, under some conditions, faster growing parasites do not appear to cause more damage and infections can be quite tolerable. We studied these conditions by assessing how the relationship between parasite population growth and host health is sensitive to environmental variation. In experimental infections of the crustacean Daphnia magna and its bacterial parasite Pasteuria ramosa we show how easily an interaction can shift from a severe interaction, i.e. when host fitness declines substantially with each unit of parasite growth, to a tolerable relationship by changing only simple environmental variables: temperature and food availability. We explored the evolutionary and epidemiological implications of such a shift by modelling pathogen evolution and disease spread under different levels of infection severity, and find that environmental shifts that promote tolerance ultimately result in populations harbouring more parasitized individuals. We also find that the opportunity for selection, as indicated by the variance around traits, varied considerably with the environmental treatment. Thus our results suggest two mechanisms that could underlie co-evolutionary hot- and coldspots: spatial variation in tolerance and spatial variation in the opportunity for selection. PMID:21460572

  8. Probing evolutionary population synthesis models in the near infrared with early-type galaxies

    Science.gov (United States)

    Dahmer-Hahn, Luis Gabriel; Riffel, Rogério; Rodríguez-Ardila, Alberto; Martins, Lucimara P.; Kehrig, Carolina; Heckman, Timothy M.; Pastoriza, Miriani G.; Dametto, Natacha Z.

    2018-06-01

    We performed a near-infrared (NIR; ˜1.0 -2.4 μm) stellar population study in a sample of early-type galaxies. The synthesis was performed using five different evolutionary population synthesis libraries of models. Our main results can be summarized as follows: low-spectral-resolution libraries are not able to produce reliable results when applied to the NIR alone, with each library finding a different dominant population. The two newest higher resolution models, on the other hand, perform considerably better, finding consistent results to each other and to literature values. We also found that optical results are consistent with each other even for lower resolution models. We also compared optical and NIR results and found out that lower resolution models tend to disagree in the optical and in the NIR, with higher fraction of young populations in the NIR and dust extinction ˜1 mag higher than optical values. For higher resolution models, optical and NIR results tend to agree much better, suggesting that a higher spectral resolution is fundamental to improve the quality of the results.

  9. Marmosets as model species in neuroscience and evolutionary anthropology.

    Science.gov (United States)

    Burkart, Judith M; Finkenwirth, Christa

    2015-04-01

    Marmosets are increasingly used as model species by both neuroscientists and evolutionary anthropologists, but with a different rationale for doing so. Whereas neuroscientists stress that marmosets share many cognitive traits with humans due to common descent, anthropologists stress those traits shared with marmosets - and callitrichid monkeys in general - due to convergent evolution, as a consequence of the cooperative breeding system that characterizes both humans and callitrichids. Similarities in socio-cognitive abilities due to convergence, rather than homology, raise the question whether these similarities also extend to the proximate regulatory mechanisms, which is particularly relevant for neuroscientific investigations. In this review, we first provide an overview of the convergent adaptations to cooperative breeding at the psychological and cognitive level in primates, which bear important implications for our understanding of human cognitive evolution. In the second part, we zoom in on two of these convergent adaptations, proactive prosociality and social learning, and compare their proximate regulation in marmosets and humans with regard to oxytocin and cognitive top down regulation. Our analysis suggests considerable similarity in these regulatory mechanisms presumably because the convergent traits emerged due to small motivational changes that define how pre-existing cognitive mechanisms are quantitatively combined. This finding reconciles the prima facie contradictory rationale for using marmosets as high priority model species in neuroscience and anthropology. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

  10. Competition-colonization trade-offs, competitive uncertainty, and the evolutionary assembly of species.

    Directory of Open Access Journals (Sweden)

    Pradeep Pillai

    Full Text Available We utilize a standard competition-colonization metapopulation model in order to study the evolutionary assembly of species. Based on earlier work showing how models assuming strict competitive hierarchies will likely lead to runaway evolution and self-extinction for all species, we adopt a continuous competition function that allows for levels of uncertainty in the outcome of competition. We then, by extending the standard patch-dynamic metapopulation model in order to include evolutionary dynamics, allow for the coevolution of species into stable communities composed of species with distinct limiting similarities. Runaway evolution towards stochastic extinction then becomes a limiting case controlled by the level of competitive uncertainty. We demonstrate how intermediate competitive uncertainty maximizes the equilibrium species richness as well as maximizes the adaptive radiation and self-assembly of species under adaptive dynamics with mutations of non-negligible size. By reconciling competition-colonization tradeoff theory with co-evolutionary dynamics, our results reveal the importance of intermediate levels of competitive uncertainty for the evolutionary assembly of species.

  11. An Evolutionary Perspective on Toxic Leadership

    Directory of Open Access Journals (Sweden)

    Lucia Ovidia VREJA

    2016-12-01

    Full Text Available Charles Darwin’s prediction from 1859, that future psychology was going to be built on principles derived from evolutionary theory came at last to be fulfilled. Nowadays, there are at least four disciplines that attempt to explain human behaviours as evolutionary adaptations (or maladaptations to the natural and/or social environment: human sociobiology, human behavioural ecology, evolutionary psychology, memetics and gene–culture coevolution theory (in our view, the most adequate of all. According to gene–culture coevolution theory, articulated language was the singular phenomenon that permitted humans to become a cultural species, and from that moment on culture become itself a selection factor. Culture means transmission of information from one generation to the next and learning from other individuals’ experiences, trough language. So, it is of critical importance to have good criteria for the selection of those individuals from whom we should learn. Yet when humans also choose their leaders from among those role-models, according to the same criteria, this mechanism can become a maladaptation and the result can be toxic leadership.

  12. Development of antibiotic regimens using graph based evolutionary algorithms.

    Science.gov (United States)

    Corns, Steven M; Ashlock, Daniel A; Bryden, Kenneth M

    2013-12-01

    This paper examines the use of evolutionary algorithms in the development of antibiotic regimens given to production animals. A model is constructed that combines the lifespan of the animal and the bacteria living in the animal's gastro-intestinal tract from the early finishing stage until the animal reaches market weight. This model is used as the fitness evaluation for a set of graph based evolutionary algorithms to assess the impact of diversity control on the evolving antibiotic regimens. The graph based evolutionary algorithms have two objectives: to find an antibiotic treatment regimen that maintains the weight gain and health benefits of antibiotic use and to reduce the risk of spreading antibiotic resistant bacteria. This study examines different regimens of tylosin phosphate use on bacteria populations divided into Gram positive and Gram negative types, with a focus on Campylobacter spp. Treatment regimens were found that provided decreased antibiotic resistance relative to conventional methods while providing nearly the same benefits as conventional antibiotic regimes. By using a graph to control the information flow in the evolutionary algorithm, a variety of solutions along the Pareto front can be found automatically for this and other multi-objective problems. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  13. Intention recognition, commitment and their roles in the evolution of cooperation from artificial intelligence techniques to evolutionary game theory models

    CERN Document Server

    Han, The Anh

    2013-01-01

    This original and timely monograph describes a unique self-contained excursion that reveals to the readers the roles of two basic cognitive abilities, i.e. intention recognition and arranging commitments, in the evolution of cooperative behavior. This book analyses intention recognition, an important ability that helps agents predict others’ behavior, in its artificial intelligence and evolutionary computational modeling aspects, and proposes a novel intention recognition method. Furthermore, the book presents a new framework for intention-based decision making and illustrates several ways in which an ability to recognize intentions of others can enhance a decision making process. By employing the new intention recognition method and the tools of evolutionary game theory, this book introduces computational models demonstrating that intention recognition promotes the emergence of cooperation within populations of self-regarding agents. Finally, the book describes how commitment provides a pathway to the evol...

  14. The deep subterranean environment as a potential model system in ecological, biogeographical and evolutionary research

    Directory of Open Access Journals (Sweden)

    David Sánchez-Fernández

    2018-01-01

    Full Text Available One of the main challenges in ecology, biogeography and evolution is to understand and predict how species may respond to environmental changes. Here we focus on the deep subterranean environment, a system that minimizes most of the typical uncertainties of studies on epigean (surface environments. Caves are relatively homogeneous habitats with nearly constant environmental conditions and simplified biological communities, allowing to control for biotic interactions. Thus, this particular system could be considered a natural habitat whose environmental conditions are similar to what can be reproduced in a laboratory, being an ideal model system for ecological, biogeographical and evolutionary studies. Subterranean species may potentially be used to assess the capability to persist in situ in a global change scenario, as they cannot accommodate to drastic changing conditions by behavioural plasticity, microhabitat use or by migrating to distant, more suitable areas, something frequent in epigean environments. In order to provide accurate predictions of the response of the subterranean biodiversity to climate change, we encourage evolutionary biologist, biogeographers and conservation biologist to work in this interesting ecosystem.

  15. Upon Accounting for the Impact of Isoenzyme Loss, Gene Deletion Costs Anticorrelate with Their Evolutionary Rates.

    Directory of Open Access Journals (Sweden)

    Christopher Jacobs

    Full Text Available System-level metabolic network models enable the computation of growth and metabolic phenotypes from an organism's genome. In particular, flux balance approaches have been used to estimate the contribution of individual metabolic genes to organismal fitness, offering the opportunity to test whether such contributions carry information about the evolutionary pressure on the corresponding genes. Previous failure to identify the expected negative correlation between such computed gene-loss cost and sequence-derived evolutionary rates in Saccharomyces cerevisiae has been ascribed to a real biological gap between a gene's fitness contribution to an organism "here and now" and the same gene's historical importance as evidenced by its accumulated mutations over millions of years of evolution. Here we show that this negative correlation does exist, and can be exposed by revisiting a broadly employed assumption of flux balance models. In particular, we introduce a new metric that we call "function-loss cost", which estimates the cost of a gene loss event as the total potential functional impairment caused by that loss. This new metric displays significant negative correlation with evolutionary rate, across several thousand minimal environments. We demonstrate that the improvement gained using function-loss cost over gene-loss cost is explained by replacing the base assumption that isoenzymes provide unlimited capacity for backup with the assumption that isoenzymes are completely non-redundant. We further show that this change of the assumption regarding isoenzymes increases the recall of epistatic interactions predicted by the flux balance model at the cost of a reduction in the precision of the predictions. In addition to suggesting that the gene-to-reaction mapping in genome-scale flux balance models should be used with caution, our analysis provides new evidence that evolutionary gene importance captures much more than strict essentiality.

  16. Upon Accounting for the Impact of Isoenzyme Loss, Gene Deletion Costs Anticorrelate with Their Evolutionary Rates.

    Science.gov (United States)

    Jacobs, Christopher; Lambourne, Luke; Xia, Yu; Segrè, Daniel

    2017-01-01

    System-level metabolic network models enable the computation of growth and metabolic phenotypes from an organism's genome. In particular, flux balance approaches have been used to estimate the contribution of individual metabolic genes to organismal fitness, offering the opportunity to test whether such contributions carry information about the evolutionary pressure on the corresponding genes. Previous failure to identify the expected negative correlation between such computed gene-loss cost and sequence-derived evolutionary rates in Saccharomyces cerevisiae has been ascribed to a real biological gap between a gene's fitness contribution to an organism "here and now" and the same gene's historical importance as evidenced by its accumulated mutations over millions of years of evolution. Here we show that this negative correlation does exist, and can be exposed by revisiting a broadly employed assumption of flux balance models. In particular, we introduce a new metric that we call "function-loss cost", which estimates the cost of a gene loss event as the total potential functional impairment caused by that loss. This new metric displays significant negative correlation with evolutionary rate, across several thousand minimal environments. We demonstrate that the improvement gained using function-loss cost over gene-loss cost is explained by replacing the base assumption that isoenzymes provide unlimited capacity for backup with the assumption that isoenzymes are completely non-redundant. We further show that this change of the assumption regarding isoenzymes increases the recall of epistatic interactions predicted by the flux balance model at the cost of a reduction in the precision of the predictions. In addition to suggesting that the gene-to-reaction mapping in genome-scale flux balance models should be used with caution, our analysis provides new evidence that evolutionary gene importance captures much more than strict essentiality.

  17. Testing lowered isothermal models with direct N-body simulations of globular clusters - II. Multimass models

    Science.gov (United States)

    Peuten, M.; Zocchi, A.; Gieles, M.; Hénault-Brunet, V.

    2017-09-01

    Lowered isothermal models, such as the multimass Michie-King models, have been successful in describing observational data of globular clusters. In this study, we assess whether such models are able to describe the phase space properties of evolutionary N-body models. We compare the multimass models as implemented in limepy (Gieles & Zocchi) to N-body models of star clusters with different retention fractions for the black holes and neutron stars evolving in a tidal field. We find that multimass models successfully reproduce the density and velocity dispersion profiles of the different mass components in all evolutionary phases and for different remnants retention. We further use these results to study the evolution of global model parameters. We find that over the lifetime of clusters, radial anisotropy gradually evolves from the low- to the high-mass components and we identify features in the properties of observable stars that are indicative of the presence of stellar-mass black holes. We find that the model velocity scale depends on mass as m-δ, with δ ≃ 0.5 for almost all models, but the dependence of central velocity dispersion on m can be shallower, depending on the dark remnant content, and agrees well with that of the N-body models. The reported model parameters, and correlations amongst them, can be used as theoretical priors when fitting these types of mass models to observational data.

  18. Economic and evolutionary hypotheses for cross-population variation in parochialism.

    Science.gov (United States)

    Hruschka, Daniel J; Henrich, Joseph

    2013-09-11

    Human populations differ reliably in the degree to which people favor family, friends, and community members over strangers and outsiders. In the last decade, researchers have begun to propose several economic and evolutionary hypotheses for these cross-population differences in parochialism. In this paper, we outline major current theories and review recent attempts to test them. We also discuss the key methodological challenges in assessing these diverse economic and evolutionary theories for cross-population differences in parochialism.

  19. Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment.

    Science.gov (United States)

    Lee, Wei-Po; Hsiao, Yu-Ting; Hwang, Wei-Che

    2014-01-16

    To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high

  20. Evolutionary games on multilayer networks: a colloquium

    Science.gov (United States)

    Wang, Zhen; Wang, Lin; Szolnoki, Attila; Perc, Matjaž

    2015-05-01

    Networks form the backbone of many complex systems, ranging from the Internet to human societies. Accordingly, not only is the range of our interactions limited and thus best described and modeled by networks, it is also a fact that the networks that are an integral part of such models are often interdependent or even interconnected. Networks of networks or multilayer networks are therefore a more apt description of social systems. This colloquium is devoted to evolutionary games on multilayer networks, and in particular to the evolution of cooperation as one of the main pillars of modern human societies. We first give an overview of the most significant conceptual differences between single-layer and multilayer networks, and we provide basic definitions and a classification of the most commonly used terms. Subsequently, we review fascinating and counterintuitive evolutionary outcomes that emerge due to different types of interdependencies between otherwise independent populations. The focus is on coupling through the utilities of players, through the flow of information, as well as through the popularity of different strategies on different network layers. The colloquium highlights the importance of pattern formation and collective behavior for the promotion of cooperation under adverse conditions, as well as the synergies between network science and evolutionary game theory.

  1. Evaluation of liquefaction potential of soil based on standard penetration test using multi-gene genetic programming model

    Science.gov (United States)

    Muduli, Pradyut; Das, Sarat

    2014-06-01

    This paper discusses the evaluation of liquefaction potential of soil based on standard penetration test (SPT) dataset using evolutionary artificial intelligence technique, multi-gene genetic programming (MGGP). The liquefaction classification accuracy (94.19%) of the developed liquefaction index (LI) model is found to be better than that of available artificial neural network (ANN) model (88.37%) and at par with the available support vector machine (SVM) model (94.19%) on the basis of the testing data. Further, an empirical equation is presented using MGGP to approximate the unknown limit state function representing the cyclic resistance ratio (CRR) of soil based on developed LI model. Using an independent database of 227 cases, the overall rates of successful prediction of occurrence of liquefaction and non-liquefaction are found to be 87, 86, and 84% by the developed MGGP based model, available ANN and the statistical models, respectively, on the basis of calculated factor of safety (F s) against the liquefaction occurrence.

  2. Evolutionary relationships of Aurora kinases: Implications for model organism studies and the development of anti-cancer drugs

    Directory of Open Access Journals (Sweden)

    Patrick Denis R

    2004-10-01

    Full Text Available Abstract Background As key regulators of mitotic chromosome segregation, the Aurora family of serine/threonine kinases play an important role in cell division. Abnormalities in Aurora kinases have been strongly linked with cancer, which has lead to the recent development of new classes of anti-cancer drugs that specifically target the ATP-binding domain of these kinases. From an evolutionary perspective, the species distribution of the Aurora kinase family is complex. Mammals uniquely have three Aurora kinases, Aurora-A, Aurora-B, and Aurora-C, while for other metazoans, including the frog, fruitfly and nematode, only Aurora-A and Aurora-B kinases are known. The fungi have a single Aurora-like homolog. Based on the tacit assumption of orthology to human counterparts, model organism studies have been central to the functional characterization of Aurora kinases. However, the ortholog and paralog relationships of these kinases across various species have not been rigorously examined. Here, we present comprehensive evolutionary analyses of the Aurora kinase family. Results Phylogenetic trees suggest that all three vertebrate Auroras evolved from a single urochordate ancestor. Specifically, Aurora-A is an orthologous lineage in cold-blooded vertebrates and mammals, while structurally similar Aurora-B and Aurora-C evolved more recently in mammals from a duplication of an ancestral Aurora-B/C gene found in cold-blooded vertebrates. All so-called Aurora-A and Aurora-B kinases of non-chordates are ancestral to the clade of chordate Auroras and, therefore, are not strictly orthologous to vertebrate counterparts. Comparisons of human Aurora-B and Aurora-C sequences to the resolved 3D structure of human Aurora-A lends further support to the evolutionary scenario that vertebrate Aurora-B and Aurora-C are closely related paralogs. Of the 26 residues lining the ATP-binding active site, only three were variant and all were specific to Aurora-A. Conclusions In

  3. EVOLUTIONARY THEORY AND THE MARKET COMPETITION

    Directory of Open Access Journals (Sweden)

    SIRGHI Nicoleta

    2014-12-01

    Full Text Available Evolutionary theory study of processes that transform economy for firms, institutions, industries, employment, production, trade and growth within, through the actions of diverse agents from experience and interactions, using evolutionary methodology. Evolutionary theory analyses the unleashing of a process of technological and institutional innovation by generating and testing a diversity of ideas which discover and accumulate more survival value for the costs incurred than competing alternatives.This paper presents study the behavior of the firms on the market used the evolutionary theory.The paper is to present in full the developments that have led to the re-assessment of theories of firms starting from the criticism on Coase's theory based on the lack of testable hypotheses and on non-operative definition of transaction costs. In the literature in the field studies on firms were allotted a secondary place for a long period of time, to date the new theories of the firm hold a dominant place in the firms’ economic analysis. In an article, published in 1937, Ronald H. Coase identified the main sources of the cost of using the market mechanism. The firms theory represent a issue intensively studied in the literature in the field, regarding the survival, competitiveness and innovation of firm on the market. The research of Nelson and Winter, “An Evolutionary Theory of Economic Change” (1982 is the starting point for a modern literature in the field which considers the approach of the theory of the firm from an evolutionary perspective. Nelson and Winter have shown that the “orthodox” theory, is objectionable primarily by the fact that the hypothesis regarding profit maximization has a normative character and is not valid in any situation. Nelson and Winter reconsidered their microeconomic analysis showing that excessive attention should not be paid to market equilibrium but rather to dynamic processes resulting from irreversible

  4. On Reciprocal Causation in the Evolutionary Process.

    Science.gov (United States)

    Svensson, Erik I

    2018-01-01

    Recent calls for a revision of standard evolutionary theory (SET) are based partly on arguments about the reciprocal causation. Reciprocal causation means that cause-effect relationships are bi-directional, as a cause could later become an effect and vice versa. Such dynamic cause-effect relationships raise questions about the distinction between proximate and ultimate causes, as originally formulated by Ernst Mayr. They have also motivated some biologists and philosophers to argue for an Extended Evolutionary Synthesis (EES). The EES will supposedly expand the scope of the Modern Synthesis (MS) and SET, which has been characterized as gene-centred, relying primarily on natural selection and largely neglecting reciprocal causation. Here, I critically examine these claims, with a special focus on the last conjecture. I conclude that reciprocal causation has long been recognized as important by naturalists, ecologists and evolutionary biologists working in the in the MS tradition, although it it could be explored even further. Numerous empirical examples of reciprocal causation in the form of positive and negative feedback are now well known from both natural and laboratory systems. Reciprocal causation have also been explicitly incorporated in mathematical models of coevolutionary arms races, frequency-dependent selection, eco-evolutionary dynamics and sexual selection. Such dynamic feedback were already recognized by Richard Levins and Richard Lewontin in their bok The Dialectical Biologist . Reciprocal causation and dynamic feedback might also be one of the few contributions of dialectical thinking and Marxist philosophy in evolutionary theory. I discuss some promising empirical and analytical tools to study reciprocal causation and the implications for the EES. Finally, I briefly discuss how quantitative genetics can be adapated to studies of reciprocal causation, constructive inheritance and phenotypic plasticity and suggest that the flexibility of this approach

  5. Evolutionary Demography

    DEFF Research Database (Denmark)

    Levitis, Daniel

    2015-01-01

    of biological and cultural evolution. Demographic variation within and among human populations is influenced by our biology, and therefore by natural selection and our evolutionary background. Demographic methods are necessary for studying populations of other species, and for quantifying evolutionary fitness......Demography is the quantitative study of population processes, while evolution is a population process that influences all aspects of biological organisms, including their demography. Demographic traits common to all human populations are the products of biological evolution or the interaction...

  6. Threat-detection in child development: an evolutionary perspective.

    Science.gov (United States)

    Boyer, Pascal; Bergstrom, Brian

    2011-03-01

    Evidence for developmental aspects of fear-targets and anxiety suggests a complex but stable pattern whereby specific kinds of fears emerge at different periods of development. This developmental schedule seems appropriate to dangers encountered repeatedly during human evolution. Also consistent with evolutionary perspective, the threat-detection systems are domain-specific, comprising different kinds of cues to do with predation, intraspecific violence, contamination-contagion and status loss. Proper evolutionary models may also be relevant to outstanding issues in the domain, notably the connections between typical development and pathology. Copyright © 2010 Elsevier Ltd. All rights reserved.

  7. Proteomics in evolutionary ecology.

    Science.gov (United States)

    Baer, B; Millar, A H

    2016-03-01

    Evolutionary ecologists are traditionally gene-focused, as genes propagate phenotypic traits across generations and mutations and recombination in the DNA generate genetic diversity required for evolutionary processes. As a consequence, the inheritance of changed DNA provides a molecular explanation for the functional changes associated with natural selection. A direct focus on proteins on the other hand, the actual molecular agents responsible for the expression of a phenotypic trait, receives far less interest from ecologists and evolutionary biologists. This is partially due to the central dogma of molecular biology that appears to define proteins as the 'dead-end of molecular information flow' as well as technical limitations in identifying and studying proteins and their diversity in the field and in many of the more exotic genera often favored in ecological studies. Here we provide an overview of a newly forming field of research that we refer to as 'Evolutionary Proteomics'. We point out that the origins of cellular function are related to the properties of polypeptide and RNA and their interactions with the environment, rather than DNA descent, and that the critical role of horizontal gene transfer in evolution is more about coopting new proteins to impact cellular processes than it is about modifying gene function. Furthermore, post-transcriptional and post-translational processes generate a remarkable diversity of mature proteins from a single gene, and the properties of these mature proteins can also influence inheritance through genetic and perhaps epigenetic mechanisms. The influence of post-transcriptional diversification on evolutionary processes could provide a novel mechanistic underpinning for elements of rapid, directed evolutionary changes and adaptations as observed for a variety of evolutionary processes. Modern state-of the art technologies based on mass spectrometry are now available to identify and quantify peptides, proteins, protein

  8. Energy demand forecasting in Iranian metal industry using linear and nonlinear models based on evolutionary algorithms

    International Nuclear Information System (INIS)

    Piltan, Mehdi; Shiri, Hiva; Ghaderi, S.F.

    2012-01-01

    Highlights: ► Investigating different fitness functions for evolutionary algorithms in energy forecasting. ► Energy forecasting of Iranian metal industry by value added, energy prices, investment and employees. ► Using real-coded instead of binary-coded genetic algorithm decreases energy forecasting error. - Abstract: Developing energy-forecasting models is known as one of the most important steps in long-term planning. In order to achieve sustainable energy supply toward economic development and social welfare, it is required to apply precise forecasting model. Applying artificial intelligent models for estimation complex economic and social functions is growing up considerably in many researches recently. In this paper, energy consumption in industrial sector as one of the critical sectors in the consumption of energy has been investigated. Two linear and three nonlinear functions have been used in order to forecast and analyze energy in the Iranian metal industry, Particle Swarm Optimization (PSO) and Genetic Algorithms (GAs) are applied to attain parameters of the models. The Real-Coded Genetic Algorithm (RCGA) has been developed based on real numbers, which is introduced as a new approach in the field of energy forecasting. In the proposed model, electricity consumption has been considered as a function of different variables such as electricity tariff, manufacturing value added, prevailing fuel prices, the number of employees, the investment in equipment and consumption in the previous years. Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Deviation (MAD) and Mean Absolute Percent Error (MAPE) are the four functions which have been used as the fitness function in the evolutionary algorithms. The results show that the logarithmic nonlinear model using PSO algorithm with 1.91 error percentage has the best answer. Furthermore, the prediction of electricity consumption in industrial sector of Turkey and also Turkish industrial sector

  9. Evolutionary inference via the Poisson Indel Process.

    Science.gov (United States)

    Bouchard-Côté, Alexandre; Jordan, Michael I

    2013-01-22

    We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114-124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments.

  10. Applying ecological and evolutionary theory to cancer: a long and winding road.

    Science.gov (United States)

    Thomas, Frédéric; Fisher, Daniel; Fort, Philippe; Marie, Jean-Pierre; Daoust, Simon; Roche, Benjamin; Grunau, Christoph; Cosseau, Céline; Mitta, Guillaume; Baghdiguian, Stephen; Rousset, François; Lassus, Patrice; Assenat, Eric; Grégoire, Damien; Missé, Dorothée; Lorz, Alexander; Billy, Frédérique; Vainchenker, William; Delhommeau, François; Koscielny, Serge; Itzykson, Raphael; Tang, Ruoping; Fava, Fanny; Ballesta, Annabelle; Lepoutre, Thomas; Krasinska, Liliana; Dulic, Vjekoslav; Raynaud, Peggy; Blache, Philippe; Quittau-Prevostel, Corinne; Vignal, Emmanuel; Trauchessec, Hélène; Perthame, Benoit; Clairambault, Jean; Volpert, Vitali; Solary, Eric; Hibner, Urszula; Hochberg, Michael E

    2013-01-01

    Since the mid 1970s, cancer has been described as a process of Darwinian evolution, with somatic cellular selection and evolution being the fundamental processes leading to malignancy and its many manifestations (neoangiogenesis, evasion of the immune system, metastasis, and resistance to therapies). Historically, little attention has been placed on applications of evolutionary biology to understanding and controlling neoplastic progression and to prevent therapeutic failures. This is now beginning to change, and there is a growing international interest in the interface between cancer and evolutionary biology. The objective of this introduction is first to describe the basic ideas and concepts linking evolutionary biology to cancer. We then present four major fronts where the evolutionary perspective is most developed, namely laboratory and clinical models, mathematical models, databases, and techniques and assays. Finally, we discuss several of the most promising challenges and future prospects in this interdisciplinary research direction in the war against cancer.

  11. Economic and evolutionary hypotheses for cross-population variation in parochialism

    Directory of Open Access Journals (Sweden)

    Daniel Jacob Hruschka

    2013-09-01

    Full Text Available Human populations differ reliably in the degree to which people favor family, friends and community members over strangers and outsiders. In the last decade, researchers have begun to propose several economic and evolutionary hypotheses for these cross-population differences in parochialism. In this paper, we outline major current theories and review recent attempts to test them. We also discuss the key methodological challenges in assessing these diverse economic and evolutionary theories for cross-population differences in parochialism.

  12. Function Follows Performance in Evolutionary Computational Processing

    DEFF Research Database (Denmark)

    Pasold, Anke; Foged, Isak Worre

    2011-01-01

    As the title ‘Function Follows Performance in Evolutionary Computational Processing’ suggests, this paper explores the potentials of employing multiple design and evaluation criteria within one processing model in order to account for a number of performative parameters desired within varied...

  13. Multidimensional extended spatial evolutionary games.

    Science.gov (United States)

    Krześlak, Michał; Świerniak, Andrzej

    2016-02-01

    The goal of this paper is to study the classical hawk-dove model using mixed spatial evolutionary games (MSEG). In these games, played on a lattice, an additional spatial layer is introduced for dependence on more complex parameters and simulation of changes in the environment. Furthermore, diverse polymorphic equilibrium points dependent on cell reproduction, model parameters, and their simulation are discussed. Our analysis demonstrates the sensitivity properties of MSEGs and possibilities for further development. We discuss applications of MSEGs, particularly algorithms for modelling cell interactions during the development of tumours. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Wind Farm Layout Optimization through a Crossover-Elitist Evolutionary Algorithm performed over a High Performing Analytical Wake Model

    Science.gov (United States)

    Kirchner-Bossi, Nicolas; Porté-Agel, Fernando

    2017-04-01

    Wind turbine wakes can significantly disrupt the performance of further downstream turbines in a wind farm, thus seriously limiting the overall wind farm power output. Such effect makes the layout design of a wind farm to play a crucial role on the whole performance of the project. An accurate definition of the wake interactions added to a computationally compromised layout optimization strategy can result in an efficient resource when addressing the problem. This work presents a novel soft-computing approach to optimize the wind farm layout by minimizing the overall wake effects that the installed turbines exert on one another. An evolutionary algorithm with an elitist sub-optimization crossover routine and an unconstrained (continuous) turbine positioning set up is developed and tested over an 80-turbine offshore wind farm over the North Sea off Denmark (Horns Rev I). Within every generation of the evolution, the wind power output (cost function) is computed through a recently developed and validated analytical wake model with a Gaussian profile velocity deficit [1], which has shown to outperform the traditionally employed wake models through different LES simulations and wind tunnel experiments. Two schemes with slightly different perimeter constraint conditions (full or partial) are tested. Results show, compared to the baseline, gridded layout, a wind power output increase between 5.5% and 7.7%. In addition, it is observed that the electric cable length at the facilities is reduced by up to 21%. [1] Bastankhah, Majid, and Fernando Porté-Agel. "A new analytical model for wind-turbine wakes." Renewable Energy 70 (2014): 116-123.

  15. Stochastic noncooperative and cooperative evolutionary game strategies of a population of biological networks under natural selection.

    Science.gov (United States)

    Chen, Bor-Sen; Yeh, Chin-Hsun

    2017-12-01

    We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. An Angiotensin II type 1 receptor activation switch patch revealed through Evolutionary Trace analysis

    DEFF Research Database (Denmark)

    Bonde, Marie Mi; Yao, Rong; Ma, Jian-Nong

    2010-01-01

    to be completely resolved. Evolutionary Trace (ET) analysis is a computational method, which identifies clusters of functionally important residues by integrating information on evolutionary important residue variations with receptor structure. Combined with known mutational data, ET predicted a patch of residues......) displayed phenotypes associated with changed activation state, such as increased agonist affinity or basal activity, promiscuous activation, or constitutive internalization highlighting the importance of testing different signaling pathways. We conclude that this evolutionary important patch mediates...

  17. Evolutionary maintenance of filovirus-like genes in bat genomes

    Directory of Open Access Journals (Sweden)

    Taylor Derek J

    2011-11-01

    Full Text Available Abstract Background Little is known of the biological significance and evolutionary maintenance of integrated non-retroviral RNA virus genes in eukaryotic host genomes. Here, we isolated novel filovirus-like genes from bat genomes and tested for evolutionary maintenance. We also estimated the age of filovirus VP35-like gene integrations and tested the phylogenetic hypotheses that there is a eutherian mammal clade and a marsupial/ebolavirus/Marburgvirus dichotomy for filoviruses. Results We detected homologous copies of VP35-like and NP-like gene integrations in both Old World and New World species of Myotis (bats. We also detected previously unknown VP35-like genes in rodents that are positionally homologous. Comprehensive phylogenetic estimates for filovirus NP-like and VP35-like loci support two main clades with a marsupial and a rodent grouping within the ebolavirus/Lloviu virus/Marburgvirus clade. The concordance of VP35-like, NP-like and mitochondrial gene trees with the expected species tree supports the notion that the copies we examined are orthologs that predate the global spread and radiation of the genus Myotis. Parametric simulations were consistent with selective maintenance for the open reading frame (ORF of VP35-like genes in Myotis. The ORF of the filovirus-like VP35 gene has been maintained in bat genomes for an estimated 13. 4 MY. ORFs were disrupted for the NP-like genes in Myotis. Likelihood ratio tests revealed that a model that accommodates positive selection is a significantly better fit to the data than a model that does not allow for positive selection for VP35-like sequences. Moreover, site-by-site analysis of selection using two methods indicated at least 25 sites in the VP35-like alignment are under positive selection in Myotis. Conclusions Our results indicate that filovirus-like elements have significance beyond genomic imprints of prior infection. That is, there appears to be, or have been, functionally maintained

  18. Social traits, social networks and evolutionary biology.

    Science.gov (United States)

    Fisher, D N; McAdam, A G

    2017-12-01

    The social environment is both an important agent of selection for most organisms, and an emergent property of their interactions. As an aggregation of interactions among members of a population, the social environment is a product of many sets of relationships and so can be represented as a network or matrix. Social network analysis in animals has focused on why these networks possess the structure they do, and whether individuals' network traits, representing some aspect of their social phenotype, relate to their fitness. Meanwhile, quantitative geneticists have demonstrated that traits expressed in a social context can depend on the phenotypes and genotypes of interacting partners, leading to influences of the social environment on the traits and fitness of individuals and the evolutionary trajectories of populations. Therefore, both fields are investigating similar topics, yet have arrived at these points relatively independently. We review how these approaches are diverged, and yet how they retain clear parallelism and so strong potential for complementarity. This demonstrates that, despite separate bodies of theory, advances in one might inform the other. Techniques in network analysis for quantifying social phenotypes, and for identifying community structure, should be useful for those studying the relationship between individual behaviour and group-level phenotypes. Entering social association matrices into quantitative genetic models may also reduce bias in heritability estimates, and allow the estimation of the influence of social connectedness on trait expression. Current methods for measuring natural selection in a social context explicitly account for the fact that a trait is not necessarily the property of a single individual, something the network approaches have not yet considered when relating network metrics to individual fitness. Harnessing evolutionary models that consider traits affected by genes in other individuals (i.e. indirect genetic

  19. CDMetaPOP: An individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics

    Science.gov (United States)

    Landguth, Erin L; Bearlin, Andrew; Day, Casey; Dunham, Jason B.

    2016-01-01

    1. Combining landscape demographic and genetics models offers powerful methods for addressing questions for eco-evolutionary applications.2. Using two illustrative examples, we present Cost–Distance Meta-POPulation, a program to simulate changes in neutral and/or selection-driven genotypes through time as a function of individual-based movement, complex spatial population dynamics, and multiple and changing landscape drivers.3. Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.

  20. Design and selection of load control strategies using a multiple objective model and evolutionary algorithms

    International Nuclear Information System (INIS)

    Gomes, Alvaro; Antunes, Carlos Henggeler; Martins, Antonio Gomes

    2005-01-01

    This paper aims at presenting a multiple objective model to evaluate the attractiveness of the use of demand resources (through load management control actions) by different stakeholders and in diverse structure scenarios in electricity systems. For the sake of model flexibility, the multiple (and conflicting) objective functions of technical, economical and quality of service nature are able to capture distinct market scenarios and operating entities that may be interested in promoting load management activities. The computation of compromise solutions is made by resorting to evolutionary algorithms, which are well suited to tackle multiobjective problems of combinatorial nature herein involving the identification and selection of control actions to be applied to groups of loads. (Author)

  1. Ifuzzer : An evolutionary interpreter fuzzer using genetic programming

    NARCIS (Netherlands)

    Veggalam, Spandan; Rawat, Sanjay; Haller, Istvan; Bos, Herbert

    We present an automated evolutionary fuzzing technique to find bugs in JavaScript interpreters. Fuzzing is an automated black box testing technique used for finding security vulnerabilities in the software by providing random data as input. However, in the case of an interpreter, fuzzing is

  2. Spatial effect on stochastic dynamics of bistable evolutionary games

    International Nuclear Information System (INIS)

    So, Kohaku H Z; Ohtsuki, Hisashi; Kato, Takeo

    2014-01-01

    We consider the lifetimes of metastable states in bistable evolutionary games (coordination games), and examine how they are affected by spatial structure. A semiclassical approximation based on a path integral method is applied to stochastic evolutionary game dynamics with and without spatial structure, and the lifetimes of the metastable states are evaluated. It is shown that the population dependence of the lifetimes is qualitatively different in these two models. Our result indicates that spatial structure can accelerate the transitions between metastable states. (paper)

  3. Schroedinger operators and evolutionary strategies

    International Nuclear Information System (INIS)

    Asselmeyer, T.

    1997-01-01

    First we introduce a simple model for the description of evolutionary algorithms, which is based on 2nd order partial differential equations for the distribution function of the individuals. Then we turn to the properties of Boltzmann's and Darwin's strategy. the next chapter is dedicated to the mathematical properties of Schroedinger operators. Both statements on the spectral density and their reproducibility during the simulation are summarized. The remaining of this chapter are dedicated to the analysis of the kernel as well as the dependence of the Schroedinger operator on the potential. As conclusion from the results of this chapter we obtain the classification of the strategies in dependence of the fitness. We obtain the classification of the evolutionary strategies, which are described by a 2nd order partial differential equation, in relation to their solution behaviour. Thereafter we are employed with the variation of the mutation distribution

  4. Attractive evolutionary equilibria

    OpenAIRE

    Roorda, Berend; Joosten, Reinoud

    2011-01-01

    We present attractiveness, a refinement criterion for evolutionary equilibria. Equilibria surviving this criterion are robust to small perturbations of the underlying payoff system or the dynamics at hand. Furthermore, certain attractive equilibria are equivalent to others for certain evolutionary dynamics. For instance, each attractive evolutionarily stable strategy is an attractive evolutionarily stable equilibrium for certain barycentric ray-projection dynamics, and vice versa.

  5. An Evolutionary Approach to the Climate Change Negotiation Game

    Energy Technology Data Exchange (ETDEWEB)

    Courtois, P. [CIRED and University of Paris, Paris (France); Pereau, J.C. [OEP, University of Marne-la-Vallee, Marne-la-Vallee (France); Tazdait, T. [CIRED and OEP, University of Marne-la-Vallee, Marne-la-Vallee (France)

    2001-10-01

    We describe in this paper an evolutionary game theoretic model aiming at representing the climate change negotiation. The model is used to examine the outcome of climate change negotiations in a framework which seeks to closely represent negotiation patterns. Evolutionary setting allows us to consider a decision making structure characterised by agents with bounded knowledge practising mimics and learning from past events and strategies. We show on that framework that a third significant alternative to the binary coordination-defection strategies needs to be considered: a unilateral commitment as precautionary strategy. As a means to widen cooperation, we examine the influence of linking environmental and trade policies via the implementation of a trade penalty on non cooperative behaviours.

  6. An Evolutionary Approach to the Climate Change Negotiation Game

    International Nuclear Information System (INIS)

    Courtois, P.; Pereau, J.C.; Tazdait, T.

    2001-10-01

    We describe in this paper an evolutionary game theoretic model aiming at representing the climate change negotiation. The model is used to examine the outcome of climate change negotiations in a framework which seeks to closely represent negotiation patterns. Evolutionary setting allows us to consider a decision making structure characterised by agents with bounded knowledge practising mimics and learning from past events and strategies. We show on that framework that a third significant alternative to the binary coordination-defection strategies needs to be considered: a unilateral commitment as precautionary strategy. As a means to widen cooperation, we examine the influence of linking environmental and trade policies via the implementation of a trade penalty on non cooperative behaviours

  7. The status of evolutionary medicine education in North American medical schools.

    Science.gov (United States)

    Hidaka, Brandon H; Asghar, Anila; Aktipis, C Athena; Nesse, Randolph M; Wolpaw, Terry M; Skursky, Nicole K; Bennett, Katelyn J; Beyrouty, Matthew W; Schwartz, Mark D

    2015-03-08

    Medical and public health scientists are using evolution to devise new strategies to solve major health problems. But based on a 2003 survey, medical curricula may not adequately prepare physicians to evaluate and extend these advances. This study assessed the change in coverage of evolution in North American medical schools since 2003 and identified opportunities for enriching medical education. In 2013, curriculum deans for all North American medical schools were invited to rate curricular coverage and perceived importance of 12 core principles, the extent of anticipated controversy from adding evolution, and the usefulness of 13 teaching resources. Differences between schools were assessed by Pearson's chi-square test, Student's t-test, and Spearman's correlation. Open-ended questions sought insight into perceived barriers and benefits. Despite repeated follow-up, 60 schools (39%) responded to the survey. There was no evidence of sample bias. The three evolutionary principles rated most important were antibiotic resistance, environmental mismatch, and somatic selection in cancer. While importance and coverage of principles were correlated (r = 0.76, P evolutionary principles were covered by 4 to 74% more schools. Nearly half (48%) of responders anticipated igniting controversy at their medical school if they added evolution to their curriculum. The teaching resources ranked most useful were model test questions and answers, case studies, and model curricula for existing courses/rotations. Limited resources (faculty expertise) were cited as the major barrier to adding more evolution, but benefits included a deeper understanding and improved patient care. North American medical schools have increased the evolution content in their curricula over the past decade. However, coverage is not commensurate with importance. At a few medical schools, anticipated controversy impedes teaching more evolution. Efforts to improve evolution education in medical schools

  8. Evolutionary principles and their practical application.

    Science.gov (United States)

    Hendry, Andrew P; Kinnison, Michael T; Heino, Mikko; Day, Troy; Smith, Thomas B; Fitt, Gary; Bergstrom, Carl T; Oakeshott, John; Jørgensen, Peter S; Zalucki, Myron P; Gilchrist, George; Southerton, Simon; Sih, Andrew; Strauss, Sharon; Denison, Robert F; Carroll, Scott P

    2011-03-01

    Evolutionary principles are now routinely incorporated into medicine and agriculture. Examples include the design of treatments that slow the evolution of resistance by weeds, pests, and pathogens, and the design of breeding programs that maximize crop yield or quality. Evolutionary principles are also increasingly incorporated into conservation biology, natural resource management, and environmental science. Examples include the protection of small and isolated populations from inbreeding depression, the identification of key traits involved in adaptation to climate change, the design of harvesting regimes that minimize unwanted life-history evolution, and the setting of conservation priorities based on populations, species, or communities that harbor the greatest evolutionary diversity and potential. The adoption of evolutionary principles has proceeded somewhat independently in these different fields, even though the underlying fundamental concepts are the same. We explore these fundamental concepts under four main themes: variation, selection, connectivity, and eco-evolutionary dynamics. Within each theme, we present several key evolutionary principles and illustrate their use in addressing applied problems. We hope that the resulting primer of evolutionary concepts and their practical utility helps to advance a unified multidisciplinary field of applied evolutionary biology.

  9. A new stellar spectrum interpolation algorithm and its application to Yunnan-III evolutionary population synthesis models

    Science.gov (United States)

    Cheng, Liantao; Zhang, Fenghui; Kang, Xiaoyu; Wang, Lang

    2018-05-01

    In evolutionary population synthesis (EPS) models, we need to convert stellar evolutionary parameters into spectra via interpolation in a stellar spectral library. For theoretical stellar spectral libraries, the spectrum grid is homogeneous on the effective-temperature and gravity plane for a given metallicity. It is relatively easy to derive stellar spectra. For empirical stellar spectral libraries, stellar parameters are irregularly distributed and the interpolation algorithm is relatively complicated. In those EPS models that use empirical stellar spectral libraries, different algorithms are used and the codes are often not released. Moreover, these algorithms are often complicated. In this work, based on a radial basis function (RBF) network, we present a new spectrum interpolation algorithm and its code. Compared with the other interpolation algorithms that are used in EPS models, it can be easily understood and is highly efficient in terms of computation. The code is written in MATLAB scripts and can be used on any computer system. Using it, we can obtain the interpolated spectra from a library or a combination of libraries. We apply this algorithm to several stellar spectral libraries (such as MILES, ELODIE-3.1 and STELIB-3.2) and give the integrated spectral energy distributions (ISEDs) of stellar populations (with ages from 1 Myr to 14 Gyr) by combining them with Yunnan-III isochrones. Our results show that the differences caused by the adoption of different EPS model components are less than 0.2 dex. All data about the stellar population ISEDs in this work and the RBF spectrum interpolation code can be obtained by request from the first author or downloaded from http://www1.ynao.ac.cn/˜zhangfh.

  10. Self-organized modularization in evolutionary algorithms.

    Science.gov (United States)

    Dauscher, Peter; Uthmann, Thomas

    2005-01-01

    The principle of modularization has proven to be extremely successful in the field of technical applications and particularly for Software Engineering purposes. The question to be answered within the present article is whether mechanisms can also be identified within the framework of Evolutionary Computation that cause a modularization of solutions. We will concentrate on processes, where modularization results only from the typical evolutionary operators, i.e. selection and variation by recombination and mutation (and not, e.g., from special modularization operators). This is what we call Self-Organized Modularization. Based on a combination of two formalizations by Radcliffe and Altenberg, some quantitative measures of modularity are introduced. Particularly, we distinguish Built-in Modularity as an inherent property of a genotype and Effective Modularity, which depends on the rest of the population. These measures can easily be applied to a wide range of present Evolutionary Computation models. It will be shown, both theoretically and by simulation, that under certain conditions, Effective Modularity (as defined within this paper) can be a selection factor. This causes Self-Organized Modularization to take place. The experimental observations emphasize the importance of Effective Modularity in comparison with Built-in Modularity. Although the experimental results have been obtained using a minimalist toy model, they can lead to a number of consequences for existing models as well as for future approaches. Furthermore, the results suggest a complex self-amplification of highly modular equivalence classes in the case of respected relations. Since the well-known Holland schemata are just the equivalence classes of respected relations in most Simple Genetic Algorithms, this observation emphasizes the role of schemata as Building Blocks (in comparison with arbitrary subsets of the search space).

  11. Modeling evolutionary dynamics of epigenetic mutations in hierarchically organized tumors.

    Directory of Open Access Journals (Sweden)

    Andrea Sottoriva

    2011-05-01

    Full Text Available The cancer stem cell (CSC concept is a highly debated topic in cancer research. While experimental evidence in favor of the cancer stem cell theory is apparently abundant, the results are often criticized as being difficult to interpret. An important reason for this is that most experimental data that support this model rely on transplantation studies. In this study we use a novel cellular Potts model to elucidate the dynamics of established malignancies that are driven by a small subset of CSCs. Our results demonstrate that epigenetic mutations that occur during mitosis display highly altered dynamics in CSC-driven malignancies compared to a classical, non-hierarchical model of growth. In particular, the heterogeneity observed in CSC-driven tumors is considerably higher. We speculate that this feature could be used in combination with epigenetic (methylation sequencing studies of human malignancies to prove or refute the CSC hypothesis in established tumors without the need for transplantation. Moreover our tumor growth simulations indicate that CSC-driven tumors display evolutionary features that can be considered beneficial during tumor progression. Besides an increased heterogeneity they also exhibit properties that allow the escape of clones from local fitness peaks. This leads to more aggressive phenotypes in the long run and makes the neoplasm more adaptable to stringent selective forces such as cancer treatment. Indeed when therapy is applied the clone landscape of the regrown tumor is more aggressive with respect to the primary tumor, whereas the classical model demonstrated similar patterns before and after therapy. Understanding these often counter-intuitive fundamental properties of (non-hierarchically organized malignancies is a crucial step in validating the CSC concept as well as providing insight into the therapeutical consequences of this model.

  12. Adaptive Capacity: An Evolutionary Neuroscience Model Linking Exercise, Cognition, and Brain Health.

    Science.gov (United States)

    Raichlen, David A; Alexander, Gene E

    2017-07-01

    The field of cognitive neuroscience was transformed by the discovery that exercise induces neurogenesis in the adult brain, with the potential to improve brain health and stave off the effects of neurodegenerative disease. However, the basic mechanisms underlying exercise-brain connections are not well understood. We use an evolutionary neuroscience approach to develop the adaptive capacity model (ACM), detailing how and why physical activity improves brain function based on an energy-minimizing strategy. Building on studies showing a combined benefit of exercise and cognitive challenge to enhance neuroplasticity, our ACM addresses two fundamental questions: (i) what are the proximate and ultimate mechanisms underlying age-related brain atrophy, and (ii) how do lifestyle changes influence the trajectory of healthy and pathological aging? Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Environmental Policy and Technology Diffusion under Imperfect Competition. An Evolutionary Game Theoretical Approach

    Energy Technology Data Exchange (ETDEWEB)

    De Vries, F.P.

    2003-05-01

    The analysis of the thesis centers around the diffusion incentives of different environmental policy instruments. Emission taxation, subsidies per unit of emission reduction, marketable emission permits and marketable emission credits will be discussed and compared to each other on how they affect the diffusion of an environmentally benign technology. The analysis is conducted within an applied evolutionary game theoretical framework. An extensive discussion of evolutionary game theory can be found in chapter 2. Chapter 3 reviews classical diffusion models: the epidemic, probit and classic game theoretical model. Then we shift our attention to general evolutionary diffusion models, followed by an outline of the use of evolutionary game theory as a tool for analyzing technology diffusion. The purpose of the chapter is to illustrate the main differences between the various models. Relevant parts of economic theory are reviewed in chapters 4 and 5. Chapter 4 contains a survey and interpretive assessment of the current literature dealing with the impact of environmental policy instruments on the adoption and diffusion of a pollution abatement technology. The chapter illustrates and criticizes the static character of the most influential models. In chapter 2 it will become apparent that an evolutionary analysis is quite appealing when markets axe characterized by perfect competition. Enhanced competitiveness forces firms to produce efficiently in order to avoid elimination. However, in imperfect competitive markets competition is limited to only a small number of firms. Since the central market structure in this thesis is that of imperfect competition, chapter 5 examines the literature on evolutionary game models applied to these type of markets. The survey reveals that the literature focuses on determining whether the evolutionary game models generate output equilibria identical to the traditional static Cournot and Bertrand models or to other output levels. Chapter 6

  14. Dynamic Ising model: reconstruction of evolutionary trees

    International Nuclear Information System (INIS)

    De Oliveira, P M C

    2013-01-01

    An evolutionary tree is a cascade of bifurcations starting from a single common root, generating a growing set of daughter species as time goes by. ‘Species’ here is a general denomination for biological species, spoken languages or any other entity which evolves through heredity. From the N currently alive species within a clade, distances are measured through pairwise comparisons made by geneticists, linguists, etc. The larger is such a distance that, for a pair of species, the older is their last common ancestor. The aim is to reconstruct the previously unknown bifurcations, i.e. the whole clade, from knowledge of the N(N − 1)/2 quoted distances, which are taken for granted. A mechanical method is presented and its applicability is discussed. (paper)

  15. Comparative mtDNA phylogeography of neotropical freshwater fishes: testing shared history to infer the evolutionary landscape of lower Central America.

    Science.gov (United States)

    Bermingham, E; Martin, A P

    1998-04-01

    Historical biogeography seeks to explain contemporary distributions of taxa in the context of intrinsic biological and extrinsic geological and climatic factors. To decipher the relative importance of biological characteristics vs. environmental conditions, it is necessary to ask whether groups of taxa with similar distributions share the same history of diversification. Because all of the taxa will have shared the same climatic and geological history, evidence of shared history across multiple species provides an estimate of the role of extrinsic factors in shaping contemporary biogeographic patterns. Similarly, differences in the records of evolutionary history across species will probably be signatures of biological differences. In this study, we focus on inferring the evolutionary history for geographical populations and closely related species representing three genera of primary freshwater fishes that are widely distributed in lower Central America (LCA) and northwestern Colombia. Analysis of mitochondrial gene trees provides the opportunity for robust tests of shared history across taxa. Moreover, because mtDNA permits inference of the temporal scale of diversification we can test hypotheses regarding the chronological development of the Isthmian corridor linking North and South America. We have focused attention on two issues. First, we show that many of the distinct populations of LCA fishes diverged in a relatively brief period of time thus limiting the phylogenetic signal available for tests of shared history. Second, our results provide reduced evidence of shared history when all drainages are included in the analysis because of inferred dispersion events that obscure the evolutionary history among drainage basins. When we restrict the analysis to areas that harbour endemic mitochondrial lineages, there is evidence of shared history across taxa. We hypothesize that there were two to three distinct waves of invasion into LCA from putative source

  16. Towards a Population Dynamics Theory for Evolutionary Computing: Learning from Biological Population Dynamics in Nature

    Science.gov (United States)

    Ma, Zhanshan (Sam)

    In evolutionary computing (EC), population size is one of the critical parameters that a researcher has to deal with. Hence, it was no surprise that the pioneers of EC, such as De Jong (1975) and Holland (1975), had already studied the population sizing from the very beginning of EC. What is perhaps surprising is that more than three decades later, we still largely depend on the experience or ad-hoc trial-and-error approach to set the population size. For example, in a recent monograph, Eiben and Smith (2003) indicated: "In almost all EC applications, the population size is constant and does not change during the evolutionary search." Despite enormous research on this issue in recent years, we still lack a well accepted theory for population sizing. In this paper, I propose to develop a population dynamics theory forEC with the inspiration from the population dynamics theory of biological populations in nature. Essentially, the EC population is considered as a dynamic system over time (generations) and space (search space or fitness landscape), similar to the spatial and temporal dynamics of biological populations in nature. With this conceptual mapping, I propose to 'transplant' the biological population dynamics theory to EC via three steps: (i) experimentally test the feasibility—whether or not emulating natural population dynamics improves the EC performance; (ii) comparatively study the underlying mechanisms—why there are improvements, primarily via statistical modeling analysis; (iii) conduct theoretical analysis with theoretical models such as percolation theory and extended evolutionary game theory that are generally applicable to both EC and natural populations. This article is a summary of a series of studies we have performed to achieve the general goal [27][30]-[32]. In the following, I start with an extremely brief introduction on the theory and models of natural population dynamics (Sections 1 & 2). In Sections 4 to 6, I briefly discuss three

  17. ORBITAL MIGRATION OF LOW-MASS PLANETS IN EVOLUTIONARY RADIATIVE MODELS: AVOIDING CATASTROPHIC INFALL

    International Nuclear Information System (INIS)

    Lyra, Wladimir; Mac Low, Mordecai-Mark; Paardekooper, Sijme-Jan

    2010-01-01

    Outward migration of low-mass planets has recently been shown to be a possibility in non-barotropic disks. We examine the consequences of this result in evolutionary models of protoplanetary disks. Planet migration occurs toward equilibrium radii with zero torque. These radii themselves migrate inwards because of viscous accretion and photoevaporation. We show that as the surface density and temperature fall the planet orbital migration and disk depletion timescales eventually become comparable, with the precise timing depending on the mass of the planet. When this occurs, the planet decouples from the equilibrium radius. At this time, however, the gas surface density is already too low to drive substantial further migration. A higher mass planet, of 10 M + , can open a gap during the late evolution of the disk, and stops migrating. Low-mass planets, with 1 or 0.1 M + , released beyond 1 AU in our models avoid migrating into the star. Our results provide support for the reduced migration rates adopted in recent planet population synthesis models.

  18. Genetic evolutionary taboo search for optimal marker placement in infrared patient setup

    International Nuclear Information System (INIS)

    Riboldi, M; Baroni, G; Spadea, M F; Tagaste, B; Garibaldi, C; Cambria, R; Orecchia, R; Pedotti, A

    2007-01-01

    In infrared patient setup adequate selection of the external fiducial configuration is required for compensating inner target displacements (target registration error, TRE). Genetic algorithms (GA) and taboo search (TS) were applied in a newly designed approach to optimal marker placement: the genetic evolutionary taboo search (GETS) algorithm. In the GETS paradigm, multiple solutions are simultaneously tested in a stochastic evolutionary scheme, where taboo-based decision making and adaptive memory guide the optimization process. The GETS algorithm was tested on a group of ten prostate patients, to be compared to standard optimization and to randomly selected configurations. The changes in the optimal marker configuration, when TRE is minimized for OARs, were specifically examined. Optimal GETS configurations ensured a 26.5% mean decrease in the TRE value, versus 19.4% for conventional quasi-Newton optimization. Common features in GETS marker configurations were highlighted in the dataset of ten patients, even when multiple runs of the stochastic algorithm were performed. Including OARs in TRE minimization did not considerably affect the spatial distribution of GETS marker configurations. In conclusion, the GETS algorithm proved to be highly effective in solving the optimal marker placement problem. Further work is needed to embed site-specific deformation models in the optimization process

  19. Evolutionary Dynamics and Diversity in Microbial Populations

    Science.gov (United States)

    Thompson, Joel; Fisher, Daniel

    2013-03-01

    Diseases such as flu and cancer adapt at an astonishing rate. In large part, viruses and cancers are so difficult to prevent because they are continually evolving. Controlling such ``evolutionary diseases'' requires a better understanding of the underlying evolutionary dynamics. It is conventionally assumed that adaptive mutations are rare and therefore will occur and sweep through the population in succession. Recent experiments using modern sequencing technologies have illuminated the many ways in which real population sequence data does not conform to the predictions of conventional theory. We consider a very simple model of asexual evolution and perform simulations in a range of parameters thought to be relevant for microbes and cancer. Simulation results reveal complex evolutionary dynamics typified by competition between lineages with different sets of adaptive mutations. This dynamical process leads to a distribution of mutant gene frequencies different than expected under the conventional assumption that adaptive mutations are rare. Simulated gene frequencies share several conspicuous features with data collected from laboratory-evolved yeast and the worldwide population of influenza.

  20. Evolutionary dynamics of fluctuating populations with strong mutualism

    Science.gov (United States)

    Chotibut, Thiparat; Nelson, David

    2013-03-01

    Evolutionary game theory with finite interacting populations is receiving increased attention, including subtle phenomena associated with number fluctuations, i.e., ``genetic drift.'' Models of cooperation and competition often utilize a simplified Moran model, with a strictly fixed total population size. We explore a more general evolutionary model with independent fluctuations in the numbers of two distinct species, in a regime characterized by ``strong mutualism.'' The model has two absorbing states, each corresponding to fixation of one of the two species, and allows exploration of the interplay between growth, competition, and mutualism. When mutualism is favored, number fluctuations eventually drive the system away from a stable fixed point, characterized by cooperation, to one of the absorbing states. Well-mixed populations will thus be taken over by a single species in a finite time, despite the bias towards cooperation. We calculate both the fixation probability and the mean fixation time as a function of the initial conditions and carrying capacities in the strong mutualism regime, using the method of matched asymptotic expansions. Our results are compared to computer simulations.

  1. Sixty-Five Million Years of Change in Temperature and Topography Explain Evolutionary History in Eastern North American Plethodontid Salamanders.

    Science.gov (United States)

    Barnes, Richard; Clark, Adam Thomas

    2017-07-01

    For many taxa and systems, species richness peaks at midelevations. One potential explanation for this pattern is that large-scale changes in climate and geography have, over evolutionary time, selected for traits that are favored under conditions found in contemporary midelevation regions. To test this hypothesis, we use records of historical temperature and topographic changes over the past 65 Myr to construct a general simulation model of plethodontid salamander evolution in eastern North America. We then explore possible mechanisms constraining species to midelevation bands by using the model to predict plethodontid evolutionary history and contemporary geographic distributions. Our results show that models that incorporate both temperature and topographic changes are better able to predict these patterns, suggesting that both processes may have played an important role in driving plethodontid evolution in the region. Additionally, our model (whose annotated source code is included as a supplement) represents a proof of concept to encourage future work that takes advantage of recent advances in computing power to combine models of ecology, evolution, and earth history to better explain the abundance and distribution of species over time.

  2. Algorithmic Mechanism Design of Evolutionary Computation.

    Science.gov (United States)

    Pei, Yan

    2015-01-01

    We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm.

  3. BANYAN. IV. Fundamental parameters of low-mass star candidates in nearby young stellar kinematic groups—isochronal age determination using magnetic evolutionary models

    Energy Technology Data Exchange (ETDEWEB)

    Malo, Lison; Doyon, René; Albert, Loïc; Lafrenière, David; Artigau, Étienne; Gagné, Jonathan [Département de physique and Observatoire du Mont-Mégantic, Université de Montréal, Montréal, QC H3C 3J7 (Canada); Feiden, Gregory A. [Department of Physics and Astronomy, Uppsala University, Box 516, SE-751 20 Uppsala (Sweden); Riedel, Adric, E-mail: malo@cfht.hawaii.edu, E-mail: doyon@astro.umontreal.ca [Department of Astrophysics, American Museum of Natural History, Central Park West at 79th Street, New York, NY 10024 (United States)

    2014-09-01

    Based on high-resolution optical spectra obtained with ESPaDOnS at Canada-France-Hawaii Telescope, we determine fundamental parameters (T {sub eff}, R, L {sub bol}, log g, and metallicity) for 59 candidate members of nearby young kinematic groups. The candidates were identified through the BANYAN Bayesian inference method of Malo et al., which takes into account the position, proper motion, magnitude, color, radial velocity, and parallax (when available) to establish a membership probability. The derived parameters are compared to Dartmouth magnetic evolutionary models and field stars with the goal of constraining the age of our candidates. We find that, in general, low-mass stars in our sample are more luminous and have inflated radii compared to older stars, a trend expected for pre-main-sequence stars. The Dartmouth magnetic evolutionary models show a good fit to observations of field K and M stars, assuming a magnetic field strength of a few kG, as typically observed for cool stars. Using the low-mass members of the β Pictoris moving group, we have re-examined the age inconsistency problem between lithium depletion age and isochronal age (Hertzspring-Russell diagram). We find that the inclusion of the magnetic field in evolutionary models increases the isochronal age estimates for the K5V-M5V stars. Using these models and field strengths, we derive an average isochronal age between 15 and 28 Myr and we confirm a clear lithium depletion boundary from which an age of 26 ± 3 Myr is derived, consistent with previous age estimates based on this method.

  4. MESA models for the evolutionary status of the epsilon Aurigae disk-eclipsed binary system

    Science.gov (United States)

    Stencel, Robert E.; Gibson, Justus

    2018-06-01

    The brightest member of the class of disk-eclipsed binary stars is the Algol-like long-period binary, epsilon Aurigae (HD 31964, F0Iap + disk, http://adsabs.harvard.edu/abs/2016SPIE.9907E..17S ). Using MESA (Modules for Experiments in Stellar Astrophysics, version 9575), we have made an evaluation of its evolutionary state. We sought to satisfy several observational constraints, including: (1) requiring evolutionary tracks to pass close to the current temperature and luminosity of the primary star; (2) obtaining a period near the observed value of 27.1 years; (3) matching a mass function of 3.0; (4) concurrent Roche lobe overflow and mass transfer; (5) an isotopic ratio 12C / 13C = 5 and, (6) matching the interferometrically determined angular diameter. A MESA model starting with binary masses of 9.85 + 4.5 solar masses, with a 100 day initial period, produces a 1.2 + 10.6 solar masses result having a 547 day period, plus a single digit 12C / 13C ratio. These values were reached near an age of 20 Myr, when the donor star comes close to the observed luminosity and temperature for epsilon Aurigae A, as a post-RGB/pre-AGB star. Contemporaneously, the accretor then appears as an upper main sequence, early B-type star. This benchmark model can provide a basis for further exploration of this interacting binary, and other long period binary stars. This report has been submitted to MNRAS, along with a parallel investigation of mass transfer stream and disk sub-structure. The authors are grateful to the estate of William Herschel Womble for the support of astronomy at the University of Denver.

  5. Biophysics of protein evolution and evolutionary protein biophysics

    Science.gov (United States)

    Sikosek, Tobias; Chan, Hue Sun

    2014-01-01

    The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence–structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by ‘hidden’ conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution. PMID:25165599

  6. An evolutionary perspective on gradual formation of superego in the primal horde

    Directory of Open Access Journals (Sweden)

    Erdem ePulcu

    2014-01-01

    Full Text Available Freud proposed that the processes which occurred in the primal horde are essential for understanding superego formation and therefore, the successful dissolution of the Oedipus complex. However, Freud theorized superego formation in the primal horde as if it is an instant, all-or-none achievement. The present paper proposes an alternative model aiming to explain gradual development of superego in the primitive man. The proposed model is built on knowledge from evolutionary and neural sciences as well as anthropology, and it particularly focuses on the evolutionary significance of the acquisition of fire by hominids in the Pleistocene period in the light of archaeological findings. Acquisition of fire is discussed as a form of sublimation which might have helped Prehistoric man to maximise the utility of limited evolutionary biological resources, potentially contributing to the rate and extent of bodily evolution. The limitations of both Freud's original conceptualisation and the present model are discussed accordingly in an interdisciplinary framework.

  7. Sensitivity versus accuracy in multiclass problems using memetic Pareto evolutionary neural networks.

    Science.gov (United States)

    Fernández Caballero, Juan Carlos; Martínez, Francisco José; Hervás, César; Gutiérrez, Pedro Antonio

    2010-05-01

    This paper proposes a multiclassification algorithm using multilayer perceptron neural network models. It tries to boost two conflicting main objectives of multiclassifiers: a high correct classification rate level and a high classification rate for each class. This last objective is not usually optimized in classification, but is considered here given the need to obtain high precision in each class in real problems. To solve this machine learning problem, we use a Pareto-based multiobjective optimization methodology based on a memetic evolutionary algorithm. We consider a memetic Pareto evolutionary approach based on the NSGA2 evolutionary algorithm (MPENSGA2). Once the Pareto front is built, two strategies or automatic individual selection are used: the best model in accuracy and the best model in sensitivity (extremes in the Pareto front). These methodologies are applied to solve 17 classification benchmark problems obtained from the University of California at Irvine (UCI) repository and one complex real classification problem. The models obtained show high accuracy and a high classification rate for each class.

  8. Preventive evolutionary medicine of cancers.

    Science.gov (United States)

    Hochberg, Michael E; Thomas, Frédéric; Assenat, Eric; Hibner, Urszula

    2013-01-01

    Evolutionary theory predicts that once an individual reaches an age of sufficiently low Darwinian fitness, (s)he will have reduced chances of keeping cancerous lesions in check. While we clearly need to better understand the emergence of precursor states and early malignancies as well as their mitigation by the microenvironment and tissue architecture, we argue that lifestyle changes and preventive therapies based in an evolutionary framework, applied to identified high-risk populations before incipient neoplasms become clinically detectable and chemoresistant lineages emerge, are currently the most reliable way to control or eliminate early tumours. Specifically, the relatively low levels of (epi)genetic heterogeneity characteristic of many if not most incipient lesions will mean a relatively limited set of possible adaptive traits and associated costs compared to more advanced cancers, and thus a more complete and predictable understanding of treatment options and outcomes. We propose a conceptual model for preventive treatments and discuss the many associated challenges.

  9. Adaptive Topographies and Equilibrium Selection in an Evolutionary Game

    Science.gov (United States)

    Osinga, Hinke M.; Marshall, James A. R.

    2015-01-01

    It has long been known in the field of population genetics that adaptive topographies, in which population equilibria maximise mean population fitness for a trait regardless of its genetic bases, do not exist. Whether one chooses to model selection acting on a single locus or multiple loci does matter. In evolutionary game theory, analysis of a simple and general game involving distinct roles for the two players has shown that whether strategies are modelled using a single ‘locus’ or one ‘locus’ for each role, the stable population equilibria are unchanged and correspond to the fitness-maximising evolutionary stable strategies of the game. This is curious given the aforementioned population genetical results on the importance of the genetic bases of traits. Here we present a dynamical systems analysis of the game with roles detailing how, while the stable equilibria in this game are unchanged by the number of ‘loci’ modelled, equilibrium selection may differ under the two modelling approaches. PMID:25706762

  10. Structure-based Markov random field model for representing evolutionary constraints on functional sites.

    Science.gov (United States)

    Jeong, Chan-Seok; Kim, Dongsup

    2016-02-24

    Elucidating the cooperative mechanism of interconnected residues is an important component toward understanding the biological function of a protein. Coevolution analysis has been developed to model the coevolutionary information reflecting structural and functional constraints. Recently, several methods have been developed based on a probabilistic graphical model called the Markov random field (MRF), which have led to significant improvements for coevolution analysis; however, thus far, the performance of these models has mainly been assessed by focusing on the aspect of protein structure. In this study, we built an MRF model whose graphical topology is determined by the residue proximity in the protein structure, and derived a novel positional coevolution estimate utilizing the node weight of the MRF model. This structure-based MRF method was evaluated for three data sets, each of which annotates catalytic site, allosteric site, and comprehensively determined functional site information. We demonstrate that the structure-based MRF architecture can encode the evolutionary information associated with biological function. Furthermore, we show that the node weight can more accurately represent positional coevolution information compared to the edge weight. Lastly, we demonstrate that the structure-based MRF model can be reliably built with only a few aligned sequences in linear time. The results show that adoption of a structure-based architecture could be an acceptable approximation for coevolution modeling with efficient computation complexity.

  11. Combining Interactive Infrastructure Modeling and Evolutionary Algorithm Optimization for Sustainable Water Resources Design

    Science.gov (United States)

    Smith, R.; Kasprzyk, J. R.; Zagona, E. A.

    2013-12-01

    Population growth and climate change, combined with difficulties in building new infrastructure, motivate portfolio-based solutions to ensuring sufficient water supply. Powerful simulation models with graphical user interfaces (GUI) are often used to evaluate infrastructure portfolios; these GUI based models require manual modification of the system parameters, such as reservoir operation rules, water transfer schemes, or system capacities. Multiobjective evolutionary algorithm (MOEA) based optimization can be employed to balance multiple objectives and automatically suggest designs for infrastructure systems, but MOEA based decision support typically uses a fixed problem formulation (i.e., a single set of objectives, decisions, and constraints). This presentation suggests a dynamic framework for linking GUI-based infrastructure models with MOEA search. The framework begins with an initial formulation which is solved using a MOEA. Then, stakeholders can interact with candidate solutions, viewing their properties in the GUI model. This is followed by changes in the formulation which represent users' evolving understanding of exigent system properties. Our case study is built using RiverWare, an object-oriented, data-centered model that facilitates the representation of a diverse array of water resources systems. Results suggest that assumptions within the initial MOEA search are violated after investigating tradeoffs and reveal how formulations should be modified to better capture stakeholders' preferences.

  12. An integrative model of evolutionary covariance: a symposium on body shape in fishes.

    Science.gov (United States)

    Walker, Jeffrey A

    2010-12-01

    A major direction of current and future biological research is to understand how multiple, interacting functional systems coordinate in producing a body that works. This understanding is complicated by the fact that organisms need to work well in multiple environments, with both predictable and unpredictable environmental perturbations. Furthermore, organismal design reflects a history of past environments and not a plan for future environments. How complex, interacting functional systems evolve, then, is a truly grand challenge. In accepting the challenge, an integrative model of evolutionary covariance is developed. The model combines quantitative genetics, functional morphology/physiology, and functional ecology. The model is used to convene scientists ranging from geneticists, to physiologists, to ecologists, to engineers to facilitate the emergence of body shape in fishes as a model system for understanding how complex, interacting functional systems develop and evolve. Body shape of fish is a complex morphology that (1) results from many developmental paths and (2) functions in many different behaviors. Understanding the coordination and evolution of the many paths from genes to body shape, body shape to function, and function to a working fish body in a dynamic environment is now possible given new technologies from genetics to engineering and new theoretical models that integrate the different levels of biological organization (from genes to ecology).

  13. Evolutionary rate patterns of the Gibberellin pathway genes

    Directory of Open Access Journals (Sweden)

    Zhang Fu-min

    2009-08-01

    Full Text Available Abstract Background Analysis of molecular evolutionary patterns of different genes within metabolic pathways allows us to determine whether these genes are subject to equivalent evolutionary forces and how natural selection shapes the evolution of proteins in an interacting system. Although previous studies found that upstream genes in the pathway evolved more slowly than downstream genes, the correlation between evolutionary rate and position of the genes in metabolic pathways as well as its implications in molecular evolution are still less understood. Results We sequenced and characterized 7 core structural genes of the gibberellin biosynthetic pathway from 8 representative species of the rice tribe (Oryzeae to address alternative hypotheses regarding evolutionary rates and patterns of metabolic pathway genes. We have detected significant rate heterogeneity among 7 GA pathway genes for both synonymous and nonsynonymous sites. Such rate variation is mostly likely attributed to differences of selection intensity rather than differential mutation pressures on the genes. Unlike previous argument that downstream genes in metabolic pathways would evolve more slowly than upstream genes, the downstream genes in the GA pathway did not exhibited the elevated substitution rate and instead, the genes that encode either the enzyme at the branch point (GA20ox or enzymes catalyzing multiple steps (KO, KAO and GA3ox in the pathway had the lowest evolutionary rates due to strong purifying selection. Our branch and codon models failed to detect signature of positive selection for any lineage and codon of the GA pathway genes. Conclusion This study suggests that significant heterogeneity of evolutionary rate of the GA pathway genes is mainly ascribed to differential constraint relaxation rather than the positive selection and supports the pathway flux theory that predicts that natural selection primarily targets enzymes that have the greatest control on fluxes.

  14. The citation field of evolutionary economics

    NARCIS (Netherlands)

    Dolfsma, Wilfred; Leydesdorff, Loet

    2010-01-01

    Evolutionary economics has developed into an academic field of its own, institutionalized around, amongst others, the Journal of Evolutionary Economics (JEE). This paper analyzes the way and extent to which evolutionary economics has become an interdisciplinary journal, as its aim was: a journal

  15. On the evolutionary relationship between chondrocytes and osteoblasts

    Directory of Open Access Journals (Sweden)

    Patsy eGomez-Picos

    2015-09-01

    Full Text Available Vertebrates are the only animals that produce bone, but the molecular genetic basis for this evolutionary novelty remains obscure. Here, we synthesize information from traditional evolutionary and modern molecular genetic studies in order to generate a working hypothesis on the evolution of the gene regulatory network (GRN underlying bone formation. To make this argument, we focus on three skeletal tissues that comprise the majority of the vertebrate skeleton: immature cartilage, mature cartilage, and bone. Immature cartilage is produced during early stages of cartilage differentiation and can persist into adulthood, whereas mature cartilage undergoes additional stages of differentiation, including hypertrophy and mineralization. Functionally, histologically, and embryologically, these three skeletal tissues are very similar, yet unique, suggesting that one might have evolved from another. Traditional studies of the fossil record, comparative anatomy and embryology demonstrate clearly that immature cartilage evolved before mature cartilage or bone. Modern molecular approaches show that the GRNs regulating differentiation of these three skeletal cell fates are similar, yet unique, just like the functional and histological features of the tissues themselves. Intriguingly, the Sox9 GRN driving cartilage formation appears to be dominant to the Runx2 GRN of bone. Emphasizing an embryological and evolutionary transcriptomic view, we hypothesize that the Runx2 GRN underlying bone formation was co-opted from mature cartilage. We discuss how modern molecular genetic experiments, such as comparative transcriptomics, can test this hypothesis directly, meanwhile permitting levels of constraint and adaptation to be evaluated quantitatively. Therefore, comparative transcriptomics may revolutionize understanding of not only the clade-specific evolution of skeletal cells, but also the generation of evolutionary novelties, providing a modern paradigm for the

  16. Towards a mechanistic foundation of evolutionary theory.

    Science.gov (United States)

    Doebeli, Michael; Ispolatov, Yaroslav; Simon, Burt

    2017-02-15

    Most evolutionary thinking is based on the notion of fitness and related ideas such as fitness landscapes and evolutionary optima. Nevertheless, it is often unclear what fitness actually is, and its meaning often depends on the context. Here we argue that fitness should not be a basal ingredient in verbal or mathematical descriptions of evolution. Instead, we propose that evolutionary birth-death processes, in which individuals give birth and die at ever-changing rates, should be the basis of evolutionary theory, because such processes capture the fundamental events that generate evolutionary dynamics. In evolutionary birth-death processes, fitness is at best a derived quantity, and owing to the potential complexity of such processes, there is no guarantee that there is a simple scalar, such as fitness, that would describe long-term evolutionary outcomes. We discuss how evolutionary birth-death processes can provide useful perspectives on a number of central issues in evolution.

  17. Exploring the evolutionary mechanism of complex supply chain systems using evolving hypergraphs

    Science.gov (United States)

    Suo, Qi; Guo, Jin-Li; Sun, Shiwei; Liu, Han

    2018-01-01

    A new evolutionary model is proposed to describe the characteristics and evolution pattern of supply chain systems using evolving hypergraphs, in which nodes represent enterprise entities while hyperedges represent the relationships among diverse trades. The nodes arrive at the system in accordance with a Poisson process, with the evolving process incorporating the addition of new nodes, linking of old nodes, and rewiring of links. Grounded in the Poisson process theory and continuum theory, the stationary average hyperdegree distribution is shown to follow a shifted power law (SPL), and the theoretical predictions are consistent with the results of numerical simulations. Testing the impact of parameters on the model yields a positive correlation between hyperdegree and degree. The model also uncovers macro characteristics of the relationships among enterprises due to the microscopic interactions among individuals.

  18. THE Ep EVOLUTIONARY SLOPE WITHIN THE DECAY PHASE OF 'FAST RISE AND EXPONENTIAL DECAY' GAMMA-RAY BURST PULSES

    International Nuclear Information System (INIS)

    Peng, Z. Y.; Ma, L.; Yin, Y.; Zhao, X. H.; Fang, L. M.; Bao, Y. Y.

    2009-01-01

    Employing two samples containing of 56 and 59 well-separated fast rise and exponential decay gamma-ray burst pulses whose spectra are fitted by the Band spectrum and Compton model, respectively, we have investigated the evolutionary slope of E p (where E p is the peak energy in the νFν spectrum) with time during the pulse decay phase. The bursts in the samples were observed by the Burst and Transient Source Experiment on the Compton Gamma Ray Observatory. We first test the E p evolutionary slope during the pulse decay phase predicted by Lu et al. based on the model of highly symmetric expanding fireballs in which the curvature effect of the expanding fireball surface is the key factor concerned. It is found that the evolutionary slopes are normally distributed for both samples and concentrated around the values of 0.73 and 0.76 for Band and Compton model, respectively, which is in good agreement with the theoretical expectation of Lu et al.. However, the inconsistency with their results is that the intrinsic spectra of most of bursts may bear the Comptonized or thermal synchrotron spectrum, rather than the Band spectrum. The relationships between the evolutionary slope and the spectral parameters are also checked. We show that the slope is correlated with E p of time-integrated spectra as well as the photon flux but anticorrelated with the lower energy index α. In addition, a correlation between the slope and the intrinsic E p derived by using the pseudo-redshift is also identified. The mechanisms of these correlations are unclear currently and the theoretical interpretations are required.

  19. Bi-directional evolutionary structural optimization for strut-and-tie modelling of three-dimensional structural concrete

    Science.gov (United States)

    Shobeiri, Vahid; Ahmadi-Nedushan, Behrouz

    2017-12-01

    This article presents a method for the automatic generation of optimal strut-and-tie models in reinforced concrete structures using a bi-directional evolutionary structural optimization method. The methodology presented is developed for compliance minimization relying on the Abaqus finite element software package. The proposed approach deals with the generation of truss-like designs in a three-dimensional environment, addressing the design of corbels and joints as well as bridge piers and pile caps. Several three-dimensional examples are provided to show the capabilities of the proposed framework in finding optimal strut-and-tie models in reinforced concrete structures and verifying its efficiency to cope with torsional actions. Several issues relating to the use of the topology optimization for strut-and-tie modelling of structural concrete, such as chequerboard patterns, mesh-dependency and multiple load cases, are studied. In the last example, a design procedure for detailing and dimensioning of the strut-and-tie models is given according to the American Concrete Institute (ACI) 318-08 provisions.

  20. An Evolutionary Game Theory Model of Revision-Resistant Motivations and Strategic Reasoning

    National Research Council Canada - National Science Library

    DeLancey, Craig

    2008-01-01

    Strong reciprocity and other forms of cooperation with non-kin in large groups and in one-time social interactions is difficult to explain with traditional economic or with simple evolutionary accounts...

  1. A Novel Multiobjective Evolutionary Algorithm Based on Regression Analysis

    Directory of Open Access Journals (Sweden)

    Zhiming Song

    2015-01-01

    Full Text Available As is known, the Pareto set of a continuous multiobjective optimization problem with m objective functions is a piecewise continuous (m-1-dimensional manifold in the decision space under some mild conditions. However, how to utilize the regularity to design multiobjective optimization algorithms has become the research focus. In this paper, based on this regularity, a model-based multiobjective evolutionary algorithm with regression analysis (MMEA-RA is put forward to solve continuous multiobjective optimization problems with variable linkages. In the algorithm, the optimization problem is modelled as a promising area in the decision space by a probability distribution, and the centroid of the probability distribution is (m-1-dimensional piecewise continuous manifold. The least squares method is used to construct such a model. A selection strategy based on the nondominated sorting is used to choose the individuals to the next generation. The new algorithm is tested and compared with NSGA-II and RM-MEDA. The result shows that MMEA-RA outperforms RM-MEDA and NSGA-II on the test instances with variable linkages. At the same time, MMEA-RA has higher efficiency than the other two algorithms. A few shortcomings of MMEA-RA have also been identified and discussed in this paper.

  2. Evolutionary thinking: "A conversation with Carter Phipps about the role of evolutionary thinking in modern culture".

    Science.gov (United States)

    Hunt, Tam

    2014-12-01

    Evolution as an idea has a lengthy history, even though the idea of evolution is generally associated with Darwin today. Rebecca Stott provides an engaging and thoughtful overview of this history of evolutionary thinking in her 2013 book, Darwin's Ghosts: The Secret History of Evolution. Since Darwin, the debate over evolution-both how it takes place and, in a long war of words with religiously-oriented thinkers, whether it takes place-has been sustained and heated. A growing share of this debate is now devoted to examining how evolutionary thinking affects areas outside of biology. How do our lives change when we recognize that all is in flux? What can we learn about life more generally if we study change instead of stasis? Carter Phipps' book, Evolutionaries: Unlocking the Spiritual and Cultural Potential of Science's Greatest Idea, delves deep into this relatively new development. Phipps generally takes as a given the validity of the Modern Synthesis of evolutionary biology. His story takes us into, as the subtitle suggests, the spiritual and cultural implications of evolutionary thinking. Can religion and evolution be reconciled? Can evolutionary thinking lead to a new type of spirituality? Is our culture already being changed in ways that we don't realize by evolutionary thinking? These are all important questions and Phipps book is a great introduction to this discussion. Phipps is an author, journalist, and contributor to the emerging "integral" or "evolutionary" cultural movement that combines the insights of Integral Philosophy, evolutionary science, developmental psychology, and the social sciences. He has served as the Executive Editor of EnlightenNext magazine (no longer published) and more recently is the co-founder of the Institute for Cultural Evolution, a public policy think tank addressing the cultural roots of America's political challenges. What follows is an email interview with Phipps.

  3. Where Evolutionary Psychology Meets Cognitive Neuroscience: A Précis to Evolutionary Cognitive Neuroscience1

    Directory of Open Access Journals (Sweden)

    Austen L. Krill

    2007-01-01

    Full Text Available Cognitive neuroscience, the study of brain-behavior relationships, has long attempted to map the brain. The discipline is flourishing, with an increasing number of functional neuroimaging studies appearing in the scientific literature daily. Unlike biology and even psychology, the cognitive neurosciences have only recently begun to apply evolutionary meta-theory and methodological guidance. Approaching cognitive neuroscience from an evolutionary perspective allows scientists to apply biologically based theoretical guidance to their investigations and can be conducted in both humans and nonhuman animals. In fact, several investigations of this sort are underway in laboratories around the world. This paper and two new volumes (Platek, Keenan, and Shackelford [Eds.], 2007; Platek and Shackelford [Eds.], under contract represent the first formal attempts to document the burgeoning field of evolutionary cognitive neuroscience. Here, we briefly review the current state of the science of evolutionary cognitive neuroscience, the methods available to the evolutionary cognitive neuroscientist, and what we foresee as the future directions of the discipline.

  4. Constrained Optimization Based on Hybrid Evolutionary Algorithm and Adaptive Constraint-Handling Technique

    DEFF Research Database (Denmark)

    Wang, Yong; Cai, Zixing; Zhou, Yuren

    2009-01-01

    A novel approach to deal with numerical and engineering constrained optimization problems, which incorporates a hybrid evolutionary algorithm and an adaptive constraint-handling technique, is presented in this paper. The hybrid evolutionary algorithm simultaneously uses simplex crossover and two...... mutation operators to generate the offspring population. Additionally, the adaptive constraint-handling technique consists of three main situations. In detail, at each situation, one constraint-handling mechanism is designed based on current population state. Experiments on 13 benchmark test functions...... and four well-known constrained design problems verify the effectiveness and efficiency of the proposed method. The experimental results show that integrating the hybrid evolutionary algorithm with the adaptive constraint-handling technique is beneficial, and the proposed method achieves competitive...

  5. The evolution of different forms of sociality: behavioral mechanisms and eco-evolutionary feedback.

    Directory of Open Access Journals (Sweden)

    Daniel J van der Post

    Full Text Available Different forms of sociality have evolved via unique evolutionary trajectories. However, it remains unknown to what extent trajectories of social evolution depend on the specific characteristics of different species. Our approach to studying such trajectories is to use evolutionary case-studies, so that we can investigate how grouping co-evolves with a multitude of individual characteristics. Here we focus on anti-predator vigilance and foraging. We use an individual-based model, where behavioral mechanisms are specified, and costs and benefits are not predefined. We show that evolutionary changes in grouping alter selection pressures on vigilance, and vice versa. This eco-evolutionary feedback generates an evolutionary progression from "leader-follower" societies to "fission-fusion" societies, where cooperative vigilance in groups is maintained via a balance between within- and between-group selection. Group-level selection is generated from an assortment that arises spontaneously when vigilant and non-vigilant foragers have different grouping tendencies. The evolutionary maintenance of small groups, and cooperative vigilance in those groups, is therefore achieved simultaneously. The evolutionary phases, and the transitions between them, depend strongly on behavioral mechanisms. Thus, integrating behavioral mechanisms and eco-evolutionary feedback is critical for understanding what kinds of intermediate stages are involved during the evolution of particular forms of sociality.

  6. Evolutionary Design of Convolutional Neural Networks for Human Activity Recognition in Sensor-Rich Environments.

    Science.gov (United States)

    Baldominos, Alejandro; Saez, Yago; Isasi, Pedro

    2018-04-23

    Human activity recognition is a challenging problem for context-aware systems and applications. It is gaining interest due to the ubiquity of different sensor sources, wearable smart objects, ambient sensors, etc. This task is usually approached as a supervised machine learning problem, where a label is to be predicted given some input data, such as the signals retrieved from different sensors. For tackling the human activity recognition problem in sensor network environments, in this paper we propose the use of deep learning (convolutional neural networks) to perform activity recognition using the publicly available OPPORTUNITY dataset. Instead of manually choosing a suitable topology, we will let an evolutionary algorithm design the optimal topology in order to maximize the classification F1 score. After that, we will also explore the performance of committees of the models resulting from the evolutionary process. Results analysis indicates that the proposed model was able to perform activity recognition within a heterogeneous sensor network environment, achieving very high accuracies when tested with new sensor data. Based on all conducted experiments, the proposed neuroevolutionary system has proved to be able to systematically find a classification model which is capable of outperforming previous results reported in the state-of-the-art, showing that this approach is useful and improves upon previously manually-designed architectures.

  7. Essays on nonlinear evolutionary game dynamics

    NARCIS (Netherlands)

    Ochea, M.I.

    2010-01-01

    Evolutionary game theory has been viewed as an evolutionary repair of rational actor game theory in the hope that a population of boundedly rational players may attain convergence to classic rational solutions, such as the Nash Equilibrium, via some learning or evolutionary process. In this thesis

  8. Women, behavior, and evolution: understanding the debate between feminist evolutionists and evolutionary psychologists.

    Science.gov (United States)

    Liesen, Laurette T

    2007-03-01

    Often since the early 1990s, feminist evolutionists have criticized evolutionary psychologists, finding fault in their analyses of human male and female reproductive behavior. Feminist evolutionists have criticized various evolutionary psychologists for perpetuating gender stereotypes, using questionable methodology, and exhibiting a chill toward feminism. Though these criticisms have been raised many times, the conflict itself has not been fully analyzed. Therefore, I reconsider this conflict, both in its origins and its implications. I find that the approaches and perspectives of feminist evolutionists and evolutionary psychologists are distinctly different, leading many of the former to work in behavioral ecology, primatology, and evolutionary biology. Invitingly to feminist evolutionists, these three fields emphasize social behavior and the influences of environmental variables; in contrast, evolutionary psychology has come to rely on assumptions deemphasizing the pliability of psychological mechanisms and the flexibility of human behavior. In behavioral ecology, primatology, and evolutionary biology, feminist evolutionists have found old biases easy to correct and new hypotheses practical to test, offering new insights into male and female behavior, explaining the emergence and persistence of patriarchy, and potentially bringing closer a prime feminist goal, sexual equality.

  9. Induction of diploid gynogenesis in an evolutionary model organism, the three-spined stickleback (Gasterosteus aculeatus

    Directory of Open Access Journals (Sweden)

    Scharsack Jörn P

    2011-09-01

    Full Text Available Abstract Background Rapid advances in genomics have provided nearly complete genome sequences for many different species. However, no matter how the sequencing technology has improved, natural genetic polymorphism complicates the production of high quality reference genomes. To address this problem, researchers have tried using artificial modes of genome manipulation such as gynogenesis for fast production of inbred lines. Results Here, we present the first successful induction of diploid gynogenesis in an evolutionary model system, the three-spined sticklebacks (Gasterosteus aculeatus, using a combination of UV-irradiation of the sperm and heat shock (HS of the resulting embryo to inhibit the second meiotic division. Optimal UV irradiation of the sperm was established by exposing stickleback sperm to a UV- light source at various times. Heat shock parameters like temperature, duration, and time of initiation were tested by subjecting eggs fertilized with UV inactivated sperm 5, 10, 15, 20, 25, or 30 minutes post fertilization (mpf to 30°C, 34°C, or 38°C for 2, 4, 6 or 8 minutes. Gynogen yield was highest when stickleback eggs were activated with 2 minutes UV-irradiated sperm and received HS 5 mpf at 34°C for 4 minutes. Conclusions Diploid gynogenesis has been successfully performed in three-spined stickleback. This has been confirmed by microsatellite DNA analysis which revealed exclusively maternal inheritance in all gynogenetic fry tested. Ploidy verification by flow cytometry showed that gynogenetic embryos/larvae exhibiting abnormalities were haploids and those that developed normally were diploids, i.e., double haploids that can be raised until adult size.

  10. Induction of diploid gynogenesis in an evolutionary model organism, the three-spined stickleback (Gasterosteus aculeatus)

    Science.gov (United States)

    2011-01-01

    Background Rapid advances in genomics have provided nearly complete genome sequences for many different species. However, no matter how the sequencing technology has improved, natural genetic polymorphism complicates the production of high quality reference genomes. To address this problem, researchers have tried using artificial modes of genome manipulation such as gynogenesis for fast production of inbred lines. Results Here, we present the first successful induction of diploid gynogenesis in an evolutionary model system, the three-spined sticklebacks (Gasterosteus aculeatus), using a combination of UV-irradiation of the sperm and heat shock (HS) of the resulting embryo to inhibit the second meiotic division. Optimal UV irradiation of the sperm was established by exposing stickleback sperm to a UV- light source at various times. Heat shock parameters like temperature, duration, and time of initiation were tested by subjecting eggs fertilized with UV inactivated sperm 5, 10, 15, 20, 25, or 30 minutes post fertilization (mpf) to 30°C, 34°C, or 38°C for 2, 4, 6 or 8 minutes. Gynogen yield was highest when stickleback eggs were activated with 2 minutes UV-irradiated sperm and received HS 5 mpf at 34°C for 4 minutes. Conclusions Diploid gynogenesis has been successfully performed in three-spined stickleback. This has been confirmed by microsatellite DNA analysis which revealed exclusively maternal inheritance in all gynogenetic fry tested. Ploidy verification by flow cytometry showed that gynogenetic embryos/larvae exhibiting abnormalities were haploids and those that developed normally were diploids, i.e., double haploids that can be raised until adult size. PMID:21910888

  11. Evolutionary process of deep-sea bathymodiolus mussels.

    Science.gov (United States)

    Miyazaki, Jun-Ichi; de Oliveira Martins, Leonardo; Fujita, Yuko; Matsumoto, Hiroto; Fujiwara, Yoshihiro

    2010-04-27

    Since the discovery of deep-sea chemosynthesis-based communities, much work has been done to clarify their organismal and environmental aspects. However, major topics remain to be resolved, including when and how organisms invade and adapt to deep-sea environments; whether strategies for invasion and adaptation are shared by different taxa or unique to each taxon; how organisms extend their distribution and diversity; and how they become isolated to speciate in continuous waters. Deep-sea mussels are one of the dominant organisms in chemosynthesis-based communities, thus investigations of their origin and evolution contribute to resolving questions about life in those communities. We investigated worldwide phylogenetic relationships of deep-sea Bathymodiolus mussels and their mytilid relatives by analyzing nucleotide sequences of the mitochondrial cytochrome c oxidase subunit I (COI) and NADH dehydrogenase subunit 4 (ND4) genes. Phylogenetic analysis of the concatenated sequence data showed that mussels of the subfamily Bathymodiolinae from vents and seeps were divided into four groups, and that mussels of the subfamily Modiolinae from sunken wood and whale carcasses assumed the outgroup position and shallow-water modioline mussels were positioned more distantly to the bathymodioline mussels. We provisionally hypothesized the evolutionary history of Bathymodilolus mussels by estimating evolutionary time under a relaxed molecular clock model. Diversification of bathymodioline mussels was initiated in the early Miocene, and subsequently diversification of the groups occurred in the early to middle Miocene. The phylogenetic relationships support the "Evolutionary stepping stone hypothesis," in which mytilid ancestors exploited sunken wood and whale carcasses in their progressive adaptation to deep-sea environments. This hypothesis is also supported by the evolutionary transition of symbiosis in that nutritional adaptation to the deep sea proceeded from extracellular

  12. Cultural and climatic changes shape the evolutionary history of the Uralic languages.

    Science.gov (United States)

    Honkola, T; Vesakoski, O; Korhonen, K; Lehtinen, J; Syrjänen, K; Wahlberg, N

    2013-06-01

    Quantitative phylogenetic methods have been used to study the evolutionary relationships and divergence times of biological species, and recently, these have also been applied to linguistic data to elucidate the evolutionary history of language families. In biology, the factors driving macroevolutionary processes are assumed to be either mainly biotic (the Red Queen model) or mainly abiotic (the Court Jester model) or a combination of both. The applicability of these models is assumed to depend on the temporal and spatial scale observed as biotic factors act on species divergence faster and in smaller spatial scale than the abiotic factors. Here, we used the Uralic language family to investigate whether both 'biotic' interactions (i.e. cultural interactions) and abiotic changes (i.e. climatic fluctuations) are also connected to language diversification. We estimated the times of divergence using Bayesian phylogenetics with a relaxed-clock method and related our results to climatic, historical and archaeological information. Our timing results paralleled the previous linguistic studies but suggested a later divergence of Finno-Ugric, Finnic and Saami languages. Some of the divergences co-occurred with climatic fluctuation and some with cultural interaction and migrations of populations. Thus, we suggest that both 'biotic' and abiotic factors contribute either directly or indirectly to the diversification of languages and that both models can be applied when studying language evolution. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

  13. How cultural evolutionary theory can inform social psychology and vice versa.

    Science.gov (United States)

    Mesoudi, Alex

    2009-10-01

    Cultural evolutionary theory is an interdisciplinary field in which human culture is viewed as a Darwinian process of variation, competition, and inheritance, and the tools, methods, and theories developed by evolutionary biologists to study genetic evolution are adapted to study cultural change. It is argued here that an integration of the theories and findings of mainstream social psychology and of cultural evolutionary theory can be mutually beneficial. Social psychology provides cultural evolution with a set of empirically verified microevolutionary cultural processes, such as conformity, model-based biases, and content biases, that are responsible for specific patterns of cultural change. Cultural evolutionary theory provides social psychology with ultimate explanations for, and an understanding of the population-level consequences of, many social psychological phenomena, such as social learning, conformity, social comparison, and intergroup processes, as well as linking social psychology with other social science disciplines such as cultural anthropology, archaeology, and sociology.

  14. Modelling and multi-objective optimization of a variable valve-timing spark-ignition engine using polynomial neural networks and evolutionary algorithms

    International Nuclear Information System (INIS)

    Atashkari, K.; Nariman-Zadeh, N.; Goelcue, M.; Khalkhali, A.; Jamali, A.

    2007-01-01

    The main reason for the efficiency decrease at part load conditions for four-stroke spark-ignition (SI) engines is the flow restriction at the cross-sectional area of the intake system. Traditionally, valve-timing has been designed to optimize operation at high engine-speed and wide open throttle conditions. Several investigations have demonstrated that improvements at part load conditions in engine performance can be accomplished if the valve-timing is variable. Controlling valve-timing can be used to improve the torque and power curve as well as to reduce fuel consumption and emissions. In this paper, a group method of data handling (GMDH) type neural network and evolutionary algorithms (EAs) are firstly used for modelling the effects of intake valve-timing (V t ) and engine speed (N) of a spark-ignition engine on both developed engine torque (T) and fuel consumption (Fc) using some experimentally obtained training and test data. Using such obtained polynomial neural network models, a multi-objective EA (non-dominated sorting genetic algorithm, NSGA-II) with a new diversity preserving mechanism are secondly used for Pareto based optimization of the variable valve-timing engine considering two conflicting objectives such as torque (T) and fuel consumption (Fc). The comparison results demonstrate the superiority of the GMDH type models over feedforward neural network models in terms of the statistical measures in the training data, testing data and the number of hidden neurons. Further, it is shown that some interesting and important relationships, as useful optimal design principles, involved in the performance of the variable valve-timing four-stroke spark-ignition engine can be discovered by the Pareto based multi-objective optimization of the polynomial models. Such important optimal principles would not have been obtained without the use of both the GMDH type neural network modelling and the multi-objective Pareto optimization approach

  15. Chemical evolutionary games.

    Science.gov (United States)

    Aristotelous, Andreas C; Durrett, Richard

    2014-05-01

    Inspired by the use of hybrid cellular automata in modeling cancer, we introduce a generalization of evolutionary games in which cells produce and absorb chemicals, and the chemical concentrations dictate the death rates of cells and their fitnesses. Our long term aim is to understand how the details of the interactions in a system with n species and m chemicals translate into the qualitative behavior of the system. Here, we study two simple 2×2 games with two chemicals and revisit the two and three species versions of the one chemical colicin system studied earlier by Durrett and Levin (1997). We find that in the 2×2 examples, the behavior of our new spatial model can be predicted from that of the mean field differential equation using ideas of Durrett and Levin (1994). However, in the three species colicin model, the system with diffusion does not have the coexistence which occurs in the lattices model in which sites interact with only their nearest neighbors. Copyright © 2014 Elsevier Inc. All rights reserved.

  16. Integrating genomics into evolutionary medicine.

    Science.gov (United States)

    Rodríguez, Juan Antonio; Marigorta, Urko M; Navarro, Arcadi

    2014-12-01

    The application of the principles of evolutionary biology into medicine was suggested long ago and is already providing insight into the ultimate causes of disease. However, a full systematic integration of medical genomics and evolutionary medicine is still missing. Here, we briefly review some cases where the combination of the two fields has proven profitable and highlight two of the main issues hindering the development of evolutionary genomic medicine as a mature field, namely the dissociation between fitness and health and the still considerable difficulties in predicting phenotypes from genotypes. We use publicly available data to illustrate both problems and conclude that new approaches are needed for evolutionary genomic medicine to overcome these obstacles. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Gene Coexpression and Evolutionary Conservation Analysis of the Human Preimplantation Embryos

    Directory of Open Access Journals (Sweden)

    Tiancheng Liu

    2015-01-01

    Full Text Available Evolutionary developmental biology (EVO-DEVO tries to decode evolutionary constraints on the stages of embryonic development. Two models—the “funnel-like” model and the “hourglass” model—have been proposed by investigators to illustrate the fluctuation of selective pressure on these stages. However, selective indices of stages corresponding to mammalian preimplantation embryonic development (PED were undetected in previous studies. Based on single cell RNA sequencing of stages during human PED, we used coexpression method to identify gene modules activated in each of these stages. Through measuring the evolutionary indices of gene modules belonging to each stage, we observed change pattern of selective constraints on PED for the first time. The selective pressure decreases from the zygote stage to the 4-cell stage and increases at the 8-cell stage and then decreases again from 8-cell stage to the late blastocyst stages. Previous EVO-DEVO studies concerning the whole embryo development neglected the fluctuation of selective pressure in these earlier stages, and the fluctuation was potentially correlated with events of earlier stages, such as zygote genome activation (ZGA. Such oscillation in an earlier stage would further affect models of the evolutionary constraints on whole embryo development. Therefore, these earlier stages should be measured intensively in future EVO-DEVO studies.

  18. Practical advantages of evolutionary computation

    Science.gov (United States)

    Fogel, David B.

    1997-10-01

    Evolutionary computation is becoming a common technique for solving difficult, real-world problems in industry, medicine, and defense. This paper reviews some of the practical advantages to using evolutionary algorithms as compared with classic methods of optimization or artificial intelligence. Specific advantages include the flexibility of the procedures, as well as their ability to self-adapt the search for optimum solutions on the fly. As desktop computers increase in speed, the application of evolutionary algorithms will become routine.

  19. Evolutionary responses to a constructed niche: ancient Mesoamericans as a model of gene-culture coevolution.

    Directory of Open Access Journals (Sweden)

    Tábita Hünemeier

    Full Text Available Culture and genetics rely on two distinct but not isolated transmission systems. Cultural processes may change the human selective environment and thereby affect which individuals survive and reproduce. Here, we evaluated whether the modes of subsistence in Native American populations and the frequencies of the ABCA1*Arg230Cys polymorphism were correlated. Further, we examined whether the evolutionary consequences of the agriculturally constructed niche in Mesoamerica could be considered as a gene-culture coevolution model. For this purpose, we genotyped 229 individuals affiliated with 19 Native American populations and added data for 41 other Native American groups (n = 1905 to the analysis. In combination with the SNP cluster of a neutral region, this dataset was then used to unravel the scenario involved in 230Cys evolutionary history. The estimated age of 230Cys is compatible with its origin occurring in the American continent. The correlation of its frequencies with the archeological data on Zea pollen in Mesoamerica/Central America, the neutral coalescent simulations, and the F(ST-based natural selection analysis suggest that maize domestication was the driving force in the increase in the frequencies of 230Cys in this region. These results may represent the first example of a gene-culture coevolution involving an autochthonous American allele.

  20. Risk attitudes in a changing environment: An evolutionary model of the fourfold pattern of risk preferences.

    Science.gov (United States)

    Mallpress, Dave E W; Fawcett, Tim W; Houston, Alasdair I; McNamara, John M

    2015-04-01

    A striking feature of human decision making is the fourfold pattern of risk attitudes, involving risk-averse behavior in situations of unlikely losses and likely gains, but risk-seeking behavior in response to likely losses and unlikely gains. Current theories to explain this pattern assume particular psychological processes to reproduce empirical observations, but do not address whether it is adaptive for the decision maker to respond to risk in this way. Here, drawing on insights from behavioral ecology, we build an evolutionary model of risk-sensitive behavior, to investigate whether particular types of environmental conditions could favor a fourfold pattern of risk attitudes. We consider an individual foraging in a changing environment, where energy is needed to prevent starvation and build up reserves for reproduction. The outcome, in terms of reproductive value (a rigorous measure of evolutionary success), of a one-off choice between a risky and a safe gain, or between a risky and a safe loss, determines the risk-sensitive behavior we should expect to see in this environment. Our results show that the fourfold pattern of risk attitudes may be adaptive in an environment in which conditions vary stochastically but are autocorrelated in time. In such an environment the current options provide information about the likely environmental conditions in the future, which affect the optimal pattern of risk sensitivity. Our model predicts that risk preferences should be both path dependent and affected by the decision maker's current state. (c) 2015 APA, all rights reserved).

  1. Divergent evolutionary processes associated with colonization of offshore islands.

    Science.gov (United States)

    Martínková, Natália; Barnett, Ross; Cucchi, Thomas; Struchen, Rahel; Pascal, Marine; Pascal, Michel; Fischer, Martin C; Higham, Thomas; Brace, Selina; Ho, Simon Y W; Quéré, Jean-Pierre; O'Higgins, Paul; Excoffier, Laurent; Heckel, Gerald; Hoelzel, A Rus; Dobney, Keith M; Searle, Jeremy B

    2013-10-01

    Oceanic islands have been a test ground for evolutionary theory, but here, we focus on the possibilities for evolutionary study created by offshore islands. These can be colonized through various means and by a wide range of species, including those with low dispersal capabilities. We use morphology, modern and ancient sequences of cytochrome b (cytb) and microsatellite genotypes to examine colonization history and evolutionary change associated with occupation of the Orkney archipelago by the common vole (Microtus arvalis), a species found in continental Europe but not in Britain. Among possible colonization scenarios, our results are most consistent with human introduction at least 5100 bp (confirmed by radiocarbon dating). We used approximate Bayesian computation of population history to infer the coast of Belgium as the possible source and estimated the evolutionary timescale using a Bayesian coalescent approach. We showed substantial morphological divergence of the island populations, including a size increase presumably driven by selection and reduced microsatellite variation likely reflecting founder events and genetic drift. More surprisingly, our results suggest that a recent and widespread cytb replacement event in the continental source area purged cytb variation there, whereas the ancestral diversity is largely retained in the colonized islands as a genetic 'ark'. The replacement event in the continental M. arvalis was probably triggered by anthropogenic causes (land-use change). Our studies illustrate that small offshore islands can act as field laboratories for studying various evolutionary processes over relatively short timescales, informing about the mainland source area as well as the island. © 2013 John Wiley & Sons Ltd.

  2. Cooperative Evolutionary Game and Applications in Construction Supplier Tendency

    Directory of Open Access Journals (Sweden)

    Qianqian Shi

    2018-01-01

    Full Text Available Major construction projects have a great influence on the national economy and society, wherein cooperative relationship between construction suppliers plays an increasingly significant role in the overall supply chain system. However, the relationships between suppliers are noncontractual, multistage, dynamic, and complicated. To gain a deeper insight into the suppliers’ cooperative relationships, an evolutionary game model is developed to explore the cooperation tendency of multisuppliers. A replicator dynamic system is further formulated to investigate the evolutionary stable strategies of multisuppliers. Then, fourteen “when-then” type scenarios are concluded and classified into six different evolutionary tracks. Meanwhile, the critical influencing factors are identified. The results show that the suppliers’ production capacity, owner-supplier contract, and the owner’s incentive mechanism influence the cooperation tendency of suppliers directly. The managerial implications contribute to insightful references for a more stable cooperative relationship between the owner and suppliers.

  3. Eco-evolutionary dynamics in a coevolving host-virus system.

    Science.gov (United States)

    Frickel, Jens; Sieber, Michael; Becks, Lutz

    2016-04-01

    Eco-evolutionary dynamics have been shown to be important for understanding population and community stability and their adaptive potential. However, coevolution in the framework of eco-evolutionary theory has not been addressed directly. Combining experiments with an algal host and its viral parasite, and mathematical model analyses we show eco-evolutionary dynamics in antagonistic coevolving populations. The interaction between antagonists initially resulted in arms race dynamics (ARD) with selective sweeps, causing oscillating host-virus population dynamics. However, ARD ended and populations stabilised after the evolution of a general resistant host, whereas a trade-off between host resistance and growth then maintained host diversity over time (trade-off driven dynamics). Most importantly, our study shows that the interaction between ecology and evolution had important consequences for the predictability of the mode and tempo of adaptive change and for the stability and adaptive potential of populations. © 2016 John Wiley & Sons Ltd/CNRS.

  4. Evolutionary game theory using agent-based methods.

    Science.gov (United States)

    Adami, Christoph; Schossau, Jory; Hintze, Arend

    2016-12-01

    Evolutionary game theory is a successful mathematical framework geared towards understanding the selective pressures that affect the evolution of the strategies of agents engaged in interactions with potential conflicts. While a mathematical treatment of the costs and benefits of decisions can predict the optimal strategy in simple settings, more realistic settings such as finite populations, non-vanishing mutations rates, stochastic decisions, communication between agents, and spatial interactions, require agent-based methods where each agent is modeled as an individual, carries its own genes that determine its decisions, and where the evolutionary outcome can only be ascertained by evolving the population of agents forward in time. While highlighting standard mathematical results, we compare those to agent-based methods that can go beyond the limitations of equations and simulate the complexity of heterogeneous populations and an ever-changing set of interactors. We conclude that agent-based methods can predict evolutionary outcomes where purely mathematical treatments cannot tread (for example in the weak selection-strong mutation limit), but that mathematics is crucial to validate the computational simulations. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. Toward a general evolutionary theory of oncogenesis.

    Science.gov (United States)

    Ewald, Paul W; Swain Ewald, Holly A

    2013-01-01

    We propose an evolutionary framework, the barrier theory of cancer, which is based on the distinction between barriers to oncogenesis and restraints. Barriers are defined as mechanisms that prevent oncogenesis. Restraints, which are more numerous, inhibit but do not prevent oncogenesis. Processes that compromise barriers are essential causes of cancer; those that interfere with restraints are exacerbating causes. The barrier theory is built upon the three evolutionary processes involved in oncogenesis: natural selection acting on multicellular organisms to mold barriers and restraints, natural selection acting on infectious organisms to abrogate these protective mechanisms, and oncogenic selection which is responsible for the evolution of normal cells into cancerous cells. The barrier theory is presented as a first step toward the development of a general evolutionary theory of cancer. Its attributes and implications for intervention are compared with those of other major conceptual frameworks for understanding cancer: the clonal diversification model, the stem cell theory and the hallmarks of cancer. The barrier theory emphasizes the practical value of distinguishing between essential and exacerbating causes. It also stresses the importance of determining the scope of infectious causation of cancer, because individual pathogens can be responsible for multiple essential causes in infected cells.

  6. A Common, Conceptual Framework for Behavioral Ecology and Evolutionary Psychology

    Directory of Open Access Journals (Sweden)

    Donald W. White

    2007-04-01

    Full Text Available Since evolutionary psychology and behavioral ecology have much in common despite their using different objects for their study, one might expect these disciplines to share a common conceptual framework with associated definitions. Unfortunately, such agreement does not entirely exist. To address the problem, we propose a common, conceptual framework, the Adaptive Behavioral System (ABS, which organizes behavior within an evolutionary framework around an organism's life history tasks. An ABS includes strategies that use decision rules and employs tactics administered by a hypothesized construct, the Evolved Processing Unit (EPU. The ABS also includes observed or predicted behavior which can be tested experimentally – the ultimate test of construct validity. Use of the proposed framework should help the two disciplines focus on their common, core business of behavior and, ultimately, be to the benefit of both.

  7. Evolving cell models for systems and synthetic biology.

    Science.gov (United States)

    Cao, Hongqing; Romero-Campero, Francisco J; Heeb, Stephan; Cámara, Miguel; Krasnogor, Natalio

    2010-03-01

    This paper proposes a new methodology for the automated design of cell models for systems and synthetic biology. Our modelling framework is based on P systems, a discrete, stochastic and modular formal modelling language. The automated design of biological models comprising the optimization of the model structure and its stochastic kinetic constants is performed using an evolutionary algorithm. The evolutionary algorithm evolves model structures by combining different modules taken from a predefined module library and then it fine-tunes the associated stochastic kinetic constants. We investigate four alternative objective functions for the fitness calculation within the evolutionary algorithm: (1) equally weighted sum method, (2) normalization method, (3) randomly weighted sum method, and (4) equally weighted product method. The effectiveness of the methodology is tested on four case studies of increasing complexity including negative and positive autoregulation as well as two gene networks implementing a pulse generator and a bandwidth detector. We provide a systematic analysis of the evolutionary algorithm's results as well as of the resulting evolved cell models.

  8. Grand challenges in evolutionary and population genetics: The importance of integrating epigenetics, genomics, modeling, and experimentation

    Science.gov (United States)

    Samuel A. Cushman

    2014-01-01

    This is a time of explosive growth in the fields of evolutionary and population genetics, with whole genome sequencing and bioinformatics driving a transformative paradigm shift (Morozova and Marra, 2008). At the same time, advances in epigenetics are thoroughly transforming our understanding of evolutionary processes and their implications for populations, species and...

  9. Calculating evolutionary dynamics in structured populations.

    Directory of Open Access Journals (Sweden)

    Charles G Nathanson

    2009-12-01

    Full Text Available Evolution is shaping the world around us. At the core of every evolutionary process is a population of reproducing individuals. The outcome of an evolutionary process depends on population structure. Here we provide a general formula for calculating evolutionary dynamics in a wide class of structured populations. This class includes the recently introduced "games in phenotype space" and "evolutionary set theory." There can be local interactions for determining the relative fitness of individuals, but we require global updating, which means all individuals compete uniformly for reproduction. We study the competition of two strategies in the context of an evolutionary game and determine which strategy is favored in the limit of weak selection. We derive an intuitive formula for the structure coefficient, sigma, and provide a method for efficient numerical calculation.

  10. Impact of CCR5delta32 Host Genetic Background and Disease Progression on HIV-1 Intrahost Evolutionary Processes: Efficient Hypothesis Testing through Hierarchical Phylogenetic Models

    NARCIS (Netherlands)

    Edo-Matas, Diana; Lemey, Philippe; Tom, Jennifer A.; Serna-Bolea, Cèlia; van den Blink, Agnes E.; van 't Wout, Angélique B.; Schuitemaker, Hanneke; Suchard, Marc A.

    2011-01-01

    The interplay between C-C chemokine receptor type 5 (CCR5) host genetic background, disease progression, and intrahost HIV-1 evolutionary dynamics remains unclear because differences in viral evolution between hosts limit the ability to draw conclusions across hosts stratified into clinically

  11. Evolutionary Multiplayer Games

    OpenAIRE

    Gokhale, Chaitanya S.; Traulsen, Arne

    2014-01-01

    Evolutionary game theory has become one of the most diverse and far reaching theories in biology. Applications of this theory range from cell dynamics to social evolution. However, many applications make it clear that inherent non-linearities of natural systems need to be taken into account. One way of introducing such non-linearities into evolutionary games is by the inclusion of multiple players. An example is of social dilemmas, where group benefits could e.g.\\ increase less than linear wi...

  12. THE HCN/HNC ABUNDANCE RATIO TOWARD DIFFERENT EVOLUTIONARY PHASES OF MASSIVE STAR FORMATION

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Mihwa; Lee, Jeong-Eun [School of Space Research, Kyung Hee University, Yongin-Si, Gyeonggi-Do 446-701 (Korea, Republic of); Kim, Kee-Tae, E-mail: mihwajin.sf@gmail.com, E-mail: jeongeun.lee@khu.ac.kr, E-mail: ktkim@kasi.re.kr [Korea Astronomy and Space Science Institute, 776 Daedeokdae-ro, Yuseong-gu, Daejeon 305-348 (Korea, Republic of)

    2015-07-20

    Using the H{sup 13}CN and HN{sup 13}C J = 1–0 line observations, the abundance ratio of HCN/HNC has been estimated for different evolutionary stages of massive star formation: infrared dark clouds (IRDCs), high-mass protostellar objects (HMPOs), and ultracompact H ii regions (UCH iis). IRDCs were divided into “quiescent IRDC cores (qIRDCc)” and “active IRDC cores (aIRDCc),” depending on star formation activity. The HCN/HNC ratio is known to be higher at active and high temperature regions related to ongoing star formation, compared to cold and quiescent regions. Our observations toward 8 qIRDCc, 16 aIRDCc, 23 HMPOs, and 31 UCH iis show consistent results; the ratio is 0.97 (±0.10), 2.65 (±0.88), 4.17 (±1.03), and 8.96 (±3.32) in these respective evolutionary stages, increasing from qIRDCc to UCH iis. The change of the HCN/HNC abundance ratio, therefore, seems directly associated with the evolutionary stages of star formation, which have different temperatures. One suggested explanation for this trend is the conversion of HNC to HCN, which occurs effectively at higher temperatures. To test the explanation, we performed a simple chemical model calculation. In order to fit the observed results, the energy barrier of the conversion must be much lower than the value provided by theoretical calculations.

  13. Application of network methods for understanding evolutionary dynamics in discrete habitats.

    Science.gov (United States)

    Greenbaum, Gili; Fefferman, Nina H

    2017-06-01

    In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene-flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population-genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene-flow patterns. In the last decades, network theory - a branch of discrete mathematics concerned with complex interactions between discrete elements - has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population-genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology. © 2017 John Wiley & Sons Ltd.

  14. Testing gradual and speciational models of evolution in extant taxa: the example of ratites

    NARCIS (Netherlands)

    Laurin, M.; Gussekloo, S.W.S.; Marjanovic, D.; Legendre, L.; Cubo, J.

    2012-01-01

    Ever since Eldredge and Gould proposed their model of punctuated equilibria, evolutionary biologists have debated how often this model is the best description of nature and how important it is compared to the more gradual models of evolution expected from natural selection and the neo-Darwinian

  15. Surface magnetic field strengths: New tests of magnetoconvective models of M dwarfs

    International Nuclear Information System (INIS)

    MacDonald, James; Mullan, D. J.

    2014-01-01

    Precision modeling of M dwarfs has become worthwhile in recent years due to the increasingly precise values of masses and radii which can be obtained from eclipsing binary studies. In a recent paper, Torres has identified four prime M dwarf pairs with the most precise empirical determinations of masses and radii. The measured radii are consistently larger than standard stellar models predict by several percent. These four systems potentially provide the most challenging tests of precision evolutionary models of cool dwarfs at the present time. We have previously modeled M dwarfs in the context of a criterion due to Gough and Tayler in which magnetic fields inhibit the onset of convection according to a physics-based prescription. In the present paper, we apply our magnetoconvective approach to the four prime systems in the Torres list. Going a step beyond what we have already modeled in CM Dra (one of the four Torres systems), we note that new constraints on magnetoconvective models of M dwarfs are now available from empirical estimates of magnetic field strengths on the surfaces of these stars. In the present paper, we consider how well our magnetoconvective models succeed when confronted with this new test of surface magnetic field strengths. Among the systems listed by Torres, we find that plausible magnetic models work well for CM Dra, YY Gem, and CU Cnc. (The fourth system in Torres's list does not yet have enough information to warrant magnetic modeling.) Our magnetoconvection models of CM Dra, YY Gem, and CU Cnc yield predictions of the magnetic fluxes on the stellar surface which are consistent with the observed correlation between magnetic flux and X-ray luminosity.

  16. Surface Magnetic Field Strengths: New Tests of Magnetoconvective Models of M Dwarfs

    Science.gov (United States)

    MacDonald, James; Mullan, D. J.

    2014-05-01

    Precision modeling of M dwarfs has become worthwhile in recent years due to the increasingly precise values of masses and radii which can be obtained from eclipsing binary studies. In a recent paper, Torres has identified four prime M dwarf pairs with the most precise empirical determinations of masses and radii. The measured radii are consistently larger than standard stellar models predict by several percent. These four systems potentially provide the most challenging tests of precision evolutionary models of cool dwarfs at the present time. We have previously modeled M dwarfs in the context of a criterion due to Gough & Tayler in which magnetic fields inhibit the onset of convection according to a physics-based prescription. In the present paper, we apply our magnetoconvective approach to the four prime systems in the Torres list. Going a step beyond what we have already modeled in CM Dra (one of the four Torres systems), we note that new constraints on magnetoconvective models of M dwarfs are now available from empirical estimates of magnetic field strengths on the surfaces of these stars. In the present paper, we consider how well our magnetoconvective models succeed when confronted with this new test of surface magnetic field strengths. Among the systems listed by Torres, we find that plausible magnetic models work well for CM Dra, YY Gem, and CU Cnc. (The fourth system in Torres's list does not yet have enough information to warrant magnetic modeling.) Our magnetoconvection models of CM Dra, YY Gem, and CU Cnc yield predictions of the magnetic fluxes on the stellar surface which are consistent with the observed correlation between magnetic flux and X-ray luminosity.

  17. Statistical physics and computational methods for evolutionary game theory

    CERN Document Server

    Javarone, Marco Alberto

    2018-01-01

    This book presents an introduction to Evolutionary Game Theory (EGT) which is an emerging field in the area of complex systems attracting the attention of researchers from disparate scientific communities. EGT allows one to represent and study several complex phenomena, such as the emergence of cooperation in social systems, the role of conformity in shaping the equilibrium of a population, and the dynamics in biological and ecological systems. Since EGT models belong to the area of complex systems, statistical physics constitutes a fundamental ingredient for investigating their behavior. At the same time, the complexity of some EGT models, such as those realized by means of agent-based methods, often require the implementation of numerical simulations. Therefore, beyond providing an introduction to EGT, this book gives a brief overview of the main statistical physics tools (such as phase transitions and the Ising model) and computational strategies for simulating evolutionary games (such as Monte Carlo algor...

  18. Earthquake likelihood model testing

    Science.gov (United States)

    Schorlemmer, D.; Gerstenberger, M.C.; Wiemer, S.; Jackson, D.D.; Rhoades, D.A.

    2007-01-01

    INTRODUCTIONThe Regional Earthquake Likelihood Models (RELM) project aims to produce and evaluate alternate models of earthquake potential (probability per unit volume, magnitude, and time) for California. Based on differing assumptions, these models are produced to test the validity of their assumptions and to explore which models should be incorporated in seismic hazard and risk evaluation. Tests based on physical and geological criteria are useful but we focus on statistical methods using future earthquake catalog data only. We envision two evaluations: a test of consistency with observed data and a comparison of all pairs of models for relative consistency. Both tests are based on the likelihood method, and both are fully prospective (i.e., the models are not adjusted to fit the test data). To be tested, each model must assign a probability to any possible event within a specified region of space, time, and magnitude. For our tests the models must use a common format: earthquake rates in specified “bins” with location, magnitude, time, and focal mechanism limits.Seismology cannot yet deterministically predict individual earthquakes; however, it should seek the best possible models for forecasting earthquake occurrence. This paper describes the statistical rules of an experiment to examine and test earthquake forecasts. The primary purposes of the tests described below are to evaluate physical models for earthquakes, assure that source models used in seismic hazard and risk studies are consistent with earthquake data, and provide quantitative measures by which models can be assigned weights in a consensus model or be judged as suitable for particular regions.In this paper we develop a statistical method for testing earthquake likelihood models. A companion paper (Schorlemmer and Gerstenberger 2007, this issue) discusses the actual implementation of these tests in the framework of the RELM initiative.Statistical testing of hypotheses is a common task and a

  19. Lack of phenotypic and evolutionary cross-resistance against parasitoids and pathogens in Drosophila melanogaster.

    Directory of Open Access Journals (Sweden)

    Alex R Kraaijeveld

    Full Text Available When organisms are attacked by multiple natural enemies, the evolution of a resistance mechanism to one natural enemy will be influenced by the degree of cross-resistance to another natural enemy. Cross-resistance can be positive, when a resistance mechanism against one natural enemy also offers resistance to another; or negative, in the form of a trade-off, when an increase in resistance against one natural enemy results in a decrease in resistance against another. Using Drosophila melanogaster, an important model system for the evolution of invertebrate immunity, we test for the existence of cross-resistance against parasites and pathogens, at both a phenotypic and evolutionary level.We used a field strain of D. melanogaster to test whether surviving parasitism by the parasitoid Asobara tabida has an effect on the resistance against Beauveria bassiana, an entomopathogenic fungus; and whether infection with the microsporidian Tubulinosema kingi has an effect on the resistance against A. tabida. We used lines selected for increased resistance to A. tabida to test whether increased parasitoid resistance has an effect on resistance against B. bassiana and T. kingi. We used lines selected for increased tolerance against B. bassiana to test whether increased fungal resistance has an effect on resistance against A. tabida.We found no positive cross-resistance or trade-offs in the resistance to parasites and pathogens. This is an important finding, given the use of D. melanogaster as a model system for the evolution of invertebrate immunity. The lack of any cross-resistance to parasites and pathogens, at both the phenotypic and the evolutionary level, suggests that evolution of resistance against one class of natural enemies is largely independent of evolution of resistance against the other.

  20. Evolutionary rescue: linking theory for conservation and medicine.

    Science.gov (United States)

    Alexander, Helen K; Martin, Guillaume; Martin, Oliver Y; Bonhoeffer, Sebastian

    2014-12-01

    Evolutionary responses that rescue populations from extinction when drastic environmental changes occur can be friend or foe. The field of conservation biology is concerned with the survival of species in deteriorating global habitats. In medicine, in contrast, infected patients are treated with chemotherapeutic interventions, but drug resistance can compromise eradication of pathogens. These contrasting biological systems and goals have created two quite separate research communities, despite addressing the same central question of whether populations will decline to extinction or be rescued through evolution. We argue that closer integration of the two fields, especially of theoretical understanding, would yield new insights and accelerate progress on these applied problems. Here, we overview and link mathematical modelling approaches in these fields, suggest specific areas with potential for fruitful exchange, and discuss common ideas and issues for empirical testing and prediction.

  1. Core principles of evolutionary medicine: A Delphi study.

    Science.gov (United States)

    Grunspan, Daniel Z; Nesse, Randolph M; Barnes, M Elizabeth; Brownell, Sara E

    2018-01-01

    Evolutionary medicine is a rapidly growing field that uses the principles of evolutionary biology to better understand, prevent and treat disease, and that uses studies of disease to advance basic knowledge in evolutionary biology. Over-arching principles of evolutionary medicine have been described in publications, but our study is the first to systematically elicit core principles from a diverse panel of experts in evolutionary medicine. These principles should be useful to advance recent recommendations made by The Association of American Medical Colleges and the Howard Hughes Medical Institute to make evolutionary thinking a core competency for pre-medical education. The Delphi method was used to elicit and validate a list of core principles for evolutionary medicine. The study included four surveys administered in sequence to 56 expert panelists. The initial open-ended survey created a list of possible core principles; the three subsequent surveys winnowed the list and assessed the accuracy and importance of each principle. Fourteen core principles elicited at least 80% of the panelists to agree or strongly agree that they were important core principles for evolutionary medicine. These principles over-lapped with concepts discussed in other articles discussing key concepts in evolutionary medicine. This set of core principles will be helpful for researchers and instructors in evolutionary medicine. We recommend that evolutionary medicine instructors use the list of core principles to construct learning goals. Evolutionary medicine is a young field, so this list of core principles will likely change as the field develops further.

  2. Emergence of structured communities through evolutionary dynamics.

    Science.gov (United States)

    Shtilerman, Elad; Kessler, David A; Shnerb, Nadav M

    2015-10-21

    Species-rich communities, in which many competing species coexist in a single trophic level, are quite frequent in nature, but pose a formidable theoretical challenge. In particular, it is known that complex competitive systems become unstable and unfeasible when the number of species is large. Recently, many studies have attributed the stability of natural communities to the structure of the interspecific interaction network, yet the nature of such structures and the underlying mechanisms responsible for them remain open questions. Here we introduce an evolutionary model, based on the generic Lotka-Volterra competitive framework, from which a stable, structured, diverse community emerges spontaneously. The modular structure of the competition matrix reflects the phylogeny of the community, in agreement with the hierarchial taxonomic classification. Closely related species tend to have stronger niche overlap and weaker fitness differences, as opposed to pairs of species from different modules. The competitive-relatedness hypothesis and the idea of emergent neutrality are discussed in the context of this evolutionary model. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. An empirical test of evolutionary theories for reproductive senescence and reproductive effort in the garter snake Thamnophis elegans.

    Science.gov (United States)

    Sparkman, Amanda M; Arnold, Stevan J; Bronikowski, Anne M

    2007-04-07

    Evolutionary theory predicts that differential reproductive effort and rate of reproductive senescence will evolve under different rates of external mortality. We examine the evolutionary divergence of age-specific reproduction in two life-history ecotypes of the western terrestrial garter snake, Thamnophis elegans. We test for the signature of reproductive senescence (decreasing fecundity with age) and increasing reproductive effort with age (increasing reproductive productivity per gram female) in replicate populations of two life-history ecotypes: snakes that grow fast, mature young and have shorter lifespans, and snakes that grow slow, mature late and have long lives. The difference between life-history ecotypes is due to genetic divergence in growth rate. We find (i) reproductive success (live litter mass) increases with age in both ecotypes, but does so more rapidly in the fast-growth ecotype, (ii) reproductive failure increases with age in both ecotypes, but the proportion of reproductive failure to total reproductive output remains invariant, and (iii) reproductive effort remains constant in fast-growth individuals with age, but declines in slow-growth individuals. This illustration of increasing fecundity with age, even at the latest ages, deviates from standard expectations for reproductive senescence, as does the lack of increases in reproductive effort. We discuss our findings in light of recent theories regarding the phenomenon of increased reproduction throughout life in organisms with indeterminate growth and its potential to offset theoretical expectations for the ubiquity of senescence.

  4. Conceptual Barriers to Progress Within Evolutionary Biology.

    Science.gov (United States)

    Laland, Kevin N; Odling-Smee, John; Feldman, Marcus W; Kendal, Jeremy

    2009-08-01

    In spite of its success, Neo-Darwinism is faced with major conceptual barriers to further progress, deriving directly from its metaphysical foundations. Most importantly, neo-Darwinism fails to recognize a fundamental cause of evolutionary change, "niche construction". This failure restricts the generality of evolutionary theory, and introduces inaccuracies. It also hinders the integration of evolutionary biology with neighbouring disciplines, including ecosystem ecology, developmental biology, and the human sciences. Ecology is forced to become a divided discipline, developmental biology is stubbornly difficult to reconcile with evolutionary theory, and the majority of biologists and social scientists are still unhappy with evolutionary accounts of human behaviour. The incorporation of niche construction as both a cause and a product of evolution removes these disciplinary boundaries while greatly generalizing the explanatory power of evolutionary theory.

  5. Evolutionary Statistical Procedures

    CERN Document Server

    Baragona, Roberto; Poli, Irene

    2011-01-01

    This proposed text appears to be a good introduction to evolutionary computation for use in applied statistics research. The authors draw from a vast base of knowledge about the current literature in both the design of evolutionary algorithms and statistical techniques. Modern statistical research is on the threshold of solving increasingly complex problems in high dimensions, and the generalization of its methodology to parameters whose estimators do not follow mathematically simple distributions is underway. Many of these challenges involve optimizing functions for which analytic solutions a

  6. A study of driver's route choice behavior based on evolutionary game theory.

    Science.gov (United States)

    Jiang, Xiaowei; Ji, Yanjie; Du, Muqing; Deng, Wei

    2014-01-01

    This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers' route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver's route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver's route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent.

  7. Analog Circuit Design Optimization Based on Evolutionary Algorithms

    Directory of Open Access Journals (Sweden)

    Mansour Barari

    2014-01-01

    Full Text Available This paper investigates an evolutionary-based designing system for automated sizing of analog integrated circuits (ICs. Two evolutionary algorithms, genetic algorithm and PSO (Parswal particle swarm optimization algorithm, are proposed to design analog ICs with practical user-defined specifications. On the basis of the combination of HSPICE and MATLAB, the system links circuit performances, evaluated through specific electrical simulation, to the optimization system in the MATLAB environment, for the selected topology. The system has been tested by typical and hard-to-design cases, such as complex analog blocks with stringent design requirements. The results show that the design specifications are closely met. Comparisons with available methods like genetic algorithms show that the proposed algorithm offers important advantages in terms of optimization quality and robustness. Moreover, the algorithm is shown to be efficient.

  8. Spatial evolutionary games of interaction among generic cancer cells

    DEFF Research Database (Denmark)

    Bach, L.A.; Sumpter, D.J.T.; Alsner, J.

    2003-01-01

    Evolutionary game models of cellular interactions have shown that heterogeneity in the cellular genotypic composition is maintained through evolution to stable coexistence of growth-promoting and non-promoting cell types. We generalise these mean-field models and relax the assumption of perfect m...... at a cellular level. This study thus points a new direction towards more plausible spatial tumour modelling and the understanding of cancerous growth....

  9. A new evolutionary system for evolving artificial neural networks.

    Science.gov (United States)

    Yao, X; Liu, Y

    1997-01-01

    This paper presents a new evolutionary system, i.e., EPNet, for evolving artificial neural networks (ANNs). The evolutionary algorithm used in EPNet is based on Fogel's evolutionary programming (EP). Unlike most previous studies on evolving ANN's, this paper puts its emphasis on evolving ANN's behaviors. Five mutation operators proposed in EPNet reflect such an emphasis on evolving behaviors. Close behavioral links between parents and their offspring are maintained by various mutations, such as partial training and node splitting. EPNet evolves ANN's architectures and connection weights (including biases) simultaneously in order to reduce the noise in fitness evaluation. The parsimony of evolved ANN's is encouraged by preferring node/connection deletion to addition. EPNet has been tested on a number of benchmark problems in machine learning and ANNs, such as the parity problem, the medical diagnosis problems, the Australian credit card assessment problem, and the Mackey-Glass time series prediction problem. The experimental results show that EPNet can produce very compact ANNs with good generalization ability in comparison with other algorithms.

  10. The Evolutionary Puzzle of Suicide

    Directory of Open Access Journals (Sweden)

    Henri-Jean Aubin

    2013-12-01

    Full Text Available Mechanisms of self-destruction are difficult to reconcile with evolution’s first rule of thumb: survive and reproduce. However, evolutionary success ultimately depends on inclusive fitness. The altruistic suicide hypothesis posits that the presence of low reproductive potential and burdensomeness toward kin can increase the inclusive fitness payoff of self-removal. The bargaining hypothesis assumes that suicide attempts could function as an honest signal of need. The payoff may be positive if the suicidal person has a low reproductive potential. The parasite manipulation hypothesis is founded on the rodent—Toxoplasma gondii host-parasite model, in which the parasite induces a “suicidal” feline attraction that allows the parasite to complete its life cycle. Interestingly, latent infection by T. gondii has been shown to cause behavioral alterations in humans, including increased suicide attempts. Finally, we discuss how suicide risk factors can be understood as nonadaptive byproducts of evolved mechanisms that malfunction. Although most of the mechanisms proposed in this article are largely speculative, the hypotheses that we raise accept self-destructive behavior within the framework of evolutionary theory.

  11. Multiscale structure in eco-evolutionary dynamics

    Science.gov (United States)

    Stacey, Blake C.

    In a complex system, the individual components are neither so tightly coupled or correlated that they can all be treated as a single unit, nor so uncorrelated that they can be approximated as independent entities. Instead, patterns of interdependency lead to structure at multiple scales of organization. Evolution excels at producing such complex structures. In turn, the existence of these complex interrelationships within a biological system affects the evolutionary dynamics of that system. I present a mathematical formalism for multiscale structure, grounded in information theory, which makes these intuitions quantitative, and I show how dynamics defined in terms of population genetics or evolutionary game theory can lead to multiscale organization. For complex systems, "more is different," and I address this from several perspectives. Spatial host--consumer models demonstrate the importance of the structures which can arise due to dynamical pattern formation. Evolutionary game theory reveals the novel effects which can result from multiplayer games, nonlinear payoffs and ecological stochasticity. Replicator dynamics in an environment with mesoscale structure relates to generalized conditionalization rules in probability theory. The idea of natural selection "acting at multiple levels" has been mathematized in a variety of ways, not all of which are equivalent. We will face down the confusion, using the experience developed over the course of this thesis to clarify the situation.

  12. Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

    Science.gov (United States)

    Liu, Qiaoyuan; Wang, Yuru; Yin, Minghao; Ren, Jinchang; Li, Ruizhi

    2017-11-01

    Although various visual tracking algorithms have been proposed in the last 2-3 decades, it remains a challenging problem for effective tracking with fast motion, deformation, occlusion, etc. Under complex tracking conditions, most tracking models are not discriminative and adaptive enough. When the combined feature vectors are inputted to the visual models, this may lead to redundancy causing low efficiency and ambiguity causing poor performance. An effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective of evolution. Every feature vector is compared to a biological individual and then decontaminated via classical evolutionary algorithms. With the optimized subsets of features, the "curse of dimensionality" has been avoided while the accuracy of the visual model has been improved. The proposed algorithm has been tested on several publicly available datasets with various tracking challenges and benchmarked with a number of state-of-the-art approaches. The comprehensive experiments have demonstrated the efficacy of the proposed methodology.

  13. Evolutionary considerations on complex emotions and music-induced emotions. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

    Science.gov (United States)

    Gingras, Bruno; Marin, Manuela M.

    2015-06-01

    Recent efforts to uncover the neural underpinnings of emotional experiences have provided a foundation for novel neurophysiological theories of emotions, adding to the existing body of psychophysiological, motivational, and evolutionary theories. Besides explicitly modeling human-specific emotions and considering the interactions between emotions and language, Koelsch et al.'s original contribution to this challenging endeavor is to identify four brain areas as distinct "affect systems" which differ in terms of emotional qualia and evolutionary pathways [1]. Here, we comment on some features of this promising Quartet Theory of Emotions, focusing particularly on evolutionary and biological aspects related to the four affect systems and their relation to prevailing emotion theories, as well as on the role of music-induced emotions.

  14. Part E: Evolutionary Computation

    DEFF Research Database (Denmark)

    2015-01-01

    of Computational Intelligence. First, comprehensive surveys of genetic algorithms, genetic programming, evolution strategies, parallel evolutionary algorithms are presented, which are readable and constructive so that a large audience might find them useful and – to some extent – ready to use. Some more general...... kinds of evolutionary algorithms, have been prudently analyzed. This analysis was followed by a thorough analysis of various issues involved in stochastic local search algorithms. An interesting survey of various technological and industrial applications in mechanical engineering and design has been...... topics like the estimation of distribution algorithms, indicator-based selection, etc., are also discussed. An important problem, from a theoretical and practical point of view, of learning classifier systems is presented in depth. Multiobjective evolutionary algorithms, which constitute one of the most...

  15. Contemporary issues in evolutionary biology

    Indian Academy of Sciences (India)

    These discussions included, among others, the possible consequences of nonDNA-based inheritance—epigenetics and cultural evolution, niche construction, and developmental mechanisms on our understanding of the evolutionary process, speciation, complexity in biology, and constructing a formal evolutionary theory.

  16. Accelerated evolutionary rates in tropical and oceanic parmelioid lichens (Ascomycota

    Directory of Open Access Journals (Sweden)

    Blanco Oscar

    2008-09-01

    Full Text Available Abstract Background The rate of nucleotide substitutions is not constant across the Tree of Life, and departures from a molecular clock have been commonly reported. Within parmelioid lichens, the largest group of macrolichens, large discrepancies in branch lengths between clades were found in previous studies. Using an extended taxon sampling, we test for presence of significant rate discrepancies within and between these clades and test our a priori hypothesis that such rate discrepancies may be explained by shifts in moisture regime or other environmental conditions. Results In this paper, the first statistical evidence for accelerated evolutionary rate in lichenized ascomycetes is presented. Our results give clear evidence for a faster rate of evolution in two Hypotrachyna clades that includes species occurring in tropical and oceanic habitats in comparison with clades consisting of species occurring in semi-arid and temperate habitats. Further we explore potential links between evolutionary rates and shifts in habitat by comparing alternative Ornstein-Uhlenbeck models. Conclusion Although there was only weak support for a shift at the base of a second tropical clade, where the observed nucleotide substitution rate is high, overall support for a shift in environmental conditions at cladogenesis is very strong. This suggests that speciation in some lichen clades has proceeded by dispersal into a novel environment, followed by radiation within that environment. We found moderate support for a shift in moisture regime at the base of one tropical clade and a clade occurring in semi-arid regions and a shift in minimum temperature at the base of a boreal-temperate clade.

  17. Research traditions and evolutionary explanations in medicine.

    Science.gov (United States)

    Méthot, Pierre-Olivier

    2011-02-01

    In this article, I argue that distinguishing 'evolutionary' from 'Darwinian' medicine will help us assess the variety of roles that evolutionary explanations can play in a number of medical contexts. Because the boundaries of evolutionary and Darwinian medicine overlap to some extent, however, they are best described as distinct 'research traditions' rather than as competing paradigms. But while evolutionary medicine does not stand out as a new scientific field of its own, Darwinian medicine is united by a number of distinctive theoretical and methodological claims. For example, evolutionary medicine and Darwinian medicine can be distinguished with respect to the styles of evolutionary explanations they employ. While the former primarily involves 'forward looking' explanations, the latter depends mostly on 'backward looking' explanations. A forward looking explanation tries to predict the effects of ongoing evolutionary processes on human health and disease in contemporary environments (e.g., hospitals). In contrast, a backward looking explanation typically applies evolutionary principles from the vantage point of humans' distant biological past in order to assess present states of health and disease. Both approaches, however, are concerned with the prevention and control of human diseases. In conclusion, I raise some concerns about the claim that 'nothing in medicine makes sense except in the light of evolution'.

  18. Applications of evolutionary economic geography

    NARCIS (Netherlands)

    Boschma, R.A.; Frenken, K.; Puranam, Krishna Kishore; Ravi Kumar Jain B., xx

    2008-01-01

    This paper is written as the first chapter of an edited volume on evolutionary economics and economic geography (Frenken, K., editor, Applied Evolutionary Economics and Economic Geography, Cheltenham: Edward Elgar, expected publication date February 2007). The paper reviews empirical applications of

  19. THE THEORY OF THE FIRM AND THE EVOLUTIONARY GAMES

    Directory of Open Access Journals (Sweden)

    Sirghi Nicoleta

    2013-07-01

    Full Text Available The neoclassical theory of the firm deals with the pattern of perfect competition, within which the perfect information available to economic agents provides instant allocation of production factors and access to economic goods. The Austrian School (C. Menger, L. von Mises, Hayek, etc. supported the idea of minimal state intervention on the markets, bringing important conceptual developments on the theory of the firm. Hirschleifer (1982 put forward the model of social and institutional functioning, arguing that the game theory is able to predict the outcome of the collective behavior and the human characteristics necessary for building the respective institutions.The evolutionary theory provides the firm and the entrepreneur the recognition of the functions of innovation, of generating and exploiting information and of organizing and coordinating production. The evolutionary perspective of the firm assumes the existence of a body of knowledge that is acquired through and builds up the organizational memory, subsequently found in routines, all choices being made based on these routines (Nelson and Winter, 2002. The evolution of the firm is considered to be similar to natural selection, but unlike the classic market selection, the evolutionists suggest the existence of a plurality of selection media. The present research is structured as follows: a brief introduction into the theories of the firm, the second part of the paper analyzes the theories of the firm from an institutional, neo-institutional and evolutionary perspective. In the third part of the paper the evolutionary games are described and analyzed from the evolutionary perspective of the firm. The last part of the paper represents a study of the “hawk-dove” game dynamic replicator. The final conclusions of the paper show that the evolutionary theory brings valuable contributions to the foundation of explanations regarding economic phenomena, indicating new directions for advanced

  20. Differential Dynamic Evolutionary Model of Emergency Financial Service Supply Chain in Natural Disaster Risk Management

    Directory of Open Access Journals (Sweden)

    Shujian Ma

    2016-01-01

    Full Text Available A government-market-public partnership (GMPP could be a feasible arrangement for providing insurance coverage for natural disaster. Firstly, we put forward GMPP management mode. Secondly, the emergency financial service supply chain for natural disaster risk is built from the view of supply chain. Finally, the objective of this paper is to obtain insights into the cooperative and competitive relationship in GMPP system. We establish the cooperative and competitive differential dynamic evolutionary models and prove the existence of equilibrium solutions in order to solve the coordination problems. In conclusion, the equilibrium solutions can be achieved among the insurers, the operating governments, and the public.

  1. Evolutionary Transitions of MicroRNA-Target Pairs

    KAUST Repository

    Nozawa, Masafumi; Fujimi, Mai; Iwamoto, Chie; Onizuka, Kanako; Fukuda, Nana; Ikeo, Kazuho; Gojobori, Takashi

    2016-01-01

    How newly generated microRNA (miRNA) genes are integrated into gene regulatory networks during evolution is fundamental in understanding the molecular and evolutionary bases of robustness and plasticity in gene regulation. A recent model proposed that after the birth of a miRNA, the miRNA is generally integrated into the network by decreasing the number of target genes during evolution. However, this decreasing model remains to be carefully examined by considering in vivo conditions. In this study, we therefore compared the number of target genes among miRNAs with different ages, combining experiments with bioinformatics predictions. First, we focused on three Drosophila miRNAs with different ages. As a result, we found that an older miRNA has a greater number of target genes than a younger miRNA, suggesting the increasing number of targets for each miRNA during evolution (increasing model). To further confirm our results, we also predicted all target genes for all miRNAs in D. melanogaster, considering co-expression of miRNAs and mRNAs in vivo. The results obtained also do not support the decreasing model but are reasonably consistent with the increasing model of miRNA-target pairs. Furthermore, our large-scale analyses of currently available experimental data of miRNA-target pairs also showed a weak but the same trend in humans. These results indicate that the current decreasing model of miRNA-target pairs should be reconsidered and the increasing model may be more appropriate to explain the evolutionary transitions of miRNA-target pairs in many organisms.

  2. Evolutionary Transitions of MicroRNA-Target Pairs

    KAUST Repository

    Nozawa, Masafumi

    2016-04-27

    How newly generated microRNA (miRNA) genes are integrated into gene regulatory networks during evolution is fundamental in understanding the molecular and evolutionary bases of robustness and plasticity in gene regulation. A recent model proposed that after the birth of a miRNA, the miRNA is generally integrated into the network by decreasing the number of target genes during evolution. However, this decreasing model remains to be carefully examined by considering in vivo conditions. In this study, we therefore compared the number of target genes among miRNAs with different ages, combining experiments with bioinformatics predictions. First, we focused on three Drosophila miRNAs with different ages. As a result, we found that an older miRNA has a greater number of target genes than a younger miRNA, suggesting the increasing number of targets for each miRNA during evolution (increasing model). To further confirm our results, we also predicted all target genes for all miRNAs in D. melanogaster, considering co-expression of miRNAs and mRNAs in vivo. The results obtained also do not support the decreasing model but are reasonably consistent with the increasing model of miRNA-target pairs. Furthermore, our large-scale analyses of currently available experimental data of miRNA-target pairs also showed a weak but the same trend in humans. These results indicate that the current decreasing model of miRNA-target pairs should be reconsidered and the increasing model may be more appropriate to explain the evolutionary transitions of miRNA-target pairs in many organisms.

  3. Commitment in Age-Gap Heterosexual Romantic Relationships: A Test of Evolutionary and Socio-Cultural Predictions

    Science.gov (United States)

    Lehmiller, Justin J.; Agnew, Christopher R.

    2008-01-01

    Little research has addressed age-gap romantic relationships (romantic involvements characterized by substantial age differences between partners). Drawing on evolutionary and socio-cultural perspectives, the present study examined normative beliefs and commitment processes among heterosexual women involved in age-gap and age-concordant…

  4. Cultural evolutionary theory: How culture evolves and why it matters.

    Science.gov (United States)

    Creanza, Nicole; Kolodny, Oren; Feldman, Marcus W

    2017-07-24

    Human cultural traits-behaviors, ideas, and technologies that can be learned from other individuals-can exhibit complex patterns of transmission and evolution, and researchers have developed theoretical models, both verbal and mathematical, to facilitate our understanding of these patterns. Many of the first quantitative models of cultural evolution were modified from existing concepts in theoretical population genetics because cultural evolution has many parallels with, as well as clear differences from, genetic evolution. Furthermore, cultural and genetic evolution can interact with one another and influence both transmission and selection. This interaction requires theoretical treatments of gene-culture coevolution and dual inheritance, in addition to purely cultural evolution. In addition, cultural evolutionary theory is a natural component of studies in demography, human ecology, and many other disciplines. Here, we review the core concepts in cultural evolutionary theory as they pertain to the extension of biology through culture, focusing on cultural evolutionary applications in population genetics, ecology, and demography. For each of these disciplines, we review the theoretical literature and highlight relevant empirical studies. We also discuss the societal implications of the study of cultural evolution and of the interactions of humans with one another and with their environment.

  5. Environmental fluctuations restrict eco-evolutionary dynamics in predator-prey system.

    Science.gov (United States)

    Hiltunen, Teppo; Ayan, Gökçe B; Becks, Lutz

    2015-06-07

    Environmental fluctuations, species interactions and rapid evolution are all predicted to affect community structure and their temporal dynamics. Although the effects of the abiotic environment and prey evolution on ecological community dynamics have been studied separately, these factors can also have interactive effects. Here we used bacteria-ciliate microcosm experiments to test for eco-evolutionary dynamics in fluctuating environments. Specifically, we followed population dynamics and a prey defence trait over time when populations were exposed to regular changes of bottom-up or top-down stressors, or combinations of these. We found that the rate of evolution of a defence trait was significantly lower in fluctuating compared with stable environments, and that the defence trait evolved to lower levels when two environmental stressors changed recurrently. The latter suggests that top-down and bottom-up changes can have additive effects constraining evolutionary response within populations. The differences in evolutionary trajectories are explained by fluctuations in population sizes of the prey and the predator, which continuously alter the supply of mutations in the prey and strength of selection through predation. Thus, it may be necessary to adopt an eco-evolutionary perspective on studies concerning the evolution of traits mediating species interactions. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  6. Incorporating evolutionary insights to improve ecotoxicology for freshwater species

    Science.gov (United States)

    Brady, Steven P.; Richardson, Jonathan L.; Kunz, Bethany K.

    2017-01-01

    Ecotoxicological studies have provided extensive insights into the lethal and sublethal effects of environmental contaminants. These insights are critical for environmental regulatory frameworks, which rely on knowledge of toxicity for developing policies to manage contaminants. While varied approaches have been applied to ecotoxicological questions, perspectives related to the evolutionary history of focal species or populations have received little consideration. Here, we evaluate chloride toxicity from the perspectives of both macroevolution and contemporary evolution. First, by mapping chloride toxicity values derived from the literature onto a phylogeny of macroinvertebrates, fish, and amphibians, we tested whether macroevolutionary relationships across species and taxa are predictive of chloride tolerance. Next, we conducted chloride exposure tests for two amphibian species to assess whether potential contemporary evolutionary change associated with environmental chloride contamination influences chloride tolerance across local populations. We show that explicitly evaluating both macroevolution and contemporary evolution can provide important and even qualitatively different insights from those obtained via traditional ecotoxicological studies. While macroevolutionary perspectives can help forecast toxicological end points for species with untested sensitivities, contemporary evolutionary perspectives demonstrate the need to consider the environmental context of exposed populations when measuring toxicity. Accounting for divergence among populations of interest can provide more accurate and relevant information related to the sensitivity of populations that may be evolving in response to selection from contaminant exposure. Our data show that approaches accounting for and specifically examining variation among natural populations should become standard practice in ecotoxicology.

  7. Evolutionary Perspectives on Genetic and Environmental Risk Factors for Psychiatric Disorders.

    Science.gov (United States)

    Keller, Matthew C

    2018-05-07

    Evolutionary medicine uses evolutionary theory to help elucidate why humans are vulnerable to disease and disorders. I discuss two different types of evolutionary explanations that have been used to help understand human psychiatric disorders. First, a consistent finding is that psychiatric disorders are moderately to highly heritable, and many, such as schizophrenia, are also highly disabling and appear to decrease Darwinian fitness. Models used in evolutionary genetics to understand why genetic variation exists in fitness-related traits can be used to understand why risk alleles for psychiatric disorders persist in the population. The usual explanation for species-typical adaptations-natural selection-is less useful for understanding individual differences in genetic risk to disorders. Rather, two other types of models, mutation-selection-drift and balancing selection, offer frameworks for understanding why genetic variation in risk to psychiatric (and other) disorders exists, and each makes predictions that are now testable using whole-genome data. Second, species-typical capacities to mount reactions to negative events are likely to have been crafted by natural selection to minimize fitness loss. The pain reaction to tissue damage is almost certainly such an example, but it has been argued that the capacity to experience depressive symptoms such as sadness, anhedonia, crying, and fatigue in the face of adverse life situations may have been crafted by natural selection as well. I review the rationale and strength of evidence for this hypothesis. Evolutionary hypotheses of psychiatric disorders are important not only for offering explanations for why psychiatric disorders exist, but also for generating new, testable hypotheses and understanding how best to design studies and analyze data.

  8. Incorporating evolutionary principles into environmental management and policy

    DEFF Research Database (Denmark)

    Lankau, Richard; Jørgensen, Peter Søgaard; Harris, David J.

    2011-01-01

    As policymakers and managers work to mitigate the effects of rapid anthropogenic environmental changes, they need to consider organisms’ responses. In light of recent evidence that evolution can be quite rapid, this now includes evolutionary responses. Evolutionary principles have a long history...... in conservation biology, and the necessary next step for the field is to consider ways in which conservation policy makers and managers can proactively manipulate evolutionary processes to achieve their goals. In this review, we aim to illustrate the potential conservation benefits of an increased understanding...... of evolutionary history and prescriptive manipulation of three basic evolutionary factors: selection, variation, and gene flow. For each, we review and propose ways that policy makers and managers can use evolutionary thinking to preserve threatened species, combat pest species, or reduce undesirable evolutionary...

  9. A conceptual evolutionary aseismic decision support framework for hospitals

    Science.gov (United States)

    Hu, Yufeng; Dargush, Gary F.; Shao, Xiaoyun

    2012-12-01

    In this paper, aconceptual evolutionary framework for aseismic decision support for hospitalsthat attempts to integrate a range of engineering and sociotechnical models is presented. Genetic algorithms are applied to find the optimal decision sets. A case study is completed to demonstrate how the frameworkmay applytoa specific hospital.The simulations show that the proposed evolutionary decision support framework is able to discover robust policy sets in either uncertain or fixed environments. The framework also qualitatively identifies some of the characteristicbehavior of the critical care organization. Thus, by utilizing the proposedframework, the decision makers are able to make more informed decisions, especially toenhance the seismic safety of the hospitals.

  10. From experimental systems to evolutionary biology: an impossible journey?

    Science.gov (United States)

    Morange, Michel

    2013-01-01

    The historical approach to the sciences has undergone a sea change during recent decades. Maybe the major contribution of Hans-Jörg Rheinberger to this movement was his demonstration of the importance of experimental systems, and of their transformations, in the development of the sciences. To describe these transformations, Hans-Jörg borrows metaphors from evolutionary biology. I want to argue that evolutionary biologists can find in these recent historical studies plenty of models and concepts to address unresolved issues in their discipline. At a time when transdisciplinarity is highly praised, it is useful to provide a precise description of the obstacles that have so far prevented this exchange.

  11. Evolutionary Design of Convolutional Neural Networks for Human Activity Recognition in Sensor-Rich Environments

    Directory of Open Access Journals (Sweden)

    Alejandro Baldominos

    2018-04-01

    Full Text Available Human activity recognition is a challenging problem for context-aware systems and applications. It is gaining interest due to the ubiquity of different sensor sources, wearable smart objects, ambient sensors, etc. This task is usually approached as a supervised machine learning problem, where a label is to be predicted given some input data, such as the signals retrieved from different sensors. For tackling the human activity recognition problem in sensor network environments, in this paper we propose the use of deep learning (convolutional neural networks to perform activity recognition using the publicly available OPPORTUNITY dataset. Instead of manually choosing a suitable topology, we will let an evolutionary algorithm design the optimal topology in order to maximize the classification F1 score. After that, we will also explore the performance of committees of the models resulting from the evolutionary process. Results analysis indicates that the proposed model was able to perform activity recognition within a heterogeneous sensor network environment, achieving very high accuracies when tested with new sensor data. Based on all conducted experiments, the proposed neuroevolutionary system has proved to be able to systematically find a classification model which is capable of outperforming previous results reported in the state-of-the-art, showing that this approach is useful and improves upon previously manually-designed architectures.

  12. Evolutionary Design of Convolutional Neural Networks for Human Activity Recognition in Sensor-Rich Environments

    Science.gov (United States)

    2018-01-01

    Human activity recognition is a challenging problem for context-aware systems and applications. It is gaining interest due to the ubiquity of different sensor sources, wearable smart objects, ambient sensors, etc. This task is usually approached as a supervised machine learning problem, where a label is to be predicted given some input data, such as the signals retrieved from different sensors. For tackling the human activity recognition problem in sensor network environments, in this paper we propose the use of deep learning (convolutional neural networks) to perform activity recognition using the publicly available OPPORTUNITY dataset. Instead of manually choosing a suitable topology, we will let an evolutionary algorithm design the optimal topology in order to maximize the classification F1 score. After that, we will also explore the performance of committees of the models resulting from the evolutionary process. Results analysis indicates that the proposed model was able to perform activity recognition within a heterogeneous sensor network environment, achieving very high accuracies when tested with new sensor data. Based on all conducted experiments, the proposed neuroevolutionary system has proved to be able to systematically find a classification model which is capable of outperforming previous results reported in the state-of-the-art, showing that this approach is useful and improves upon previously manually-designed architectures. PMID:29690587

  13. Evolutionary economics and industry location

    NARCIS (Netherlands)

    Boschma, R.A.; Frenken, K.

    2003-01-01

    This paper aims to provide the outlines of an evolutionary economic geography of industry location. We discuss two evolutionary explanations of industry location, that is, one that concentrates on spin-offs, and one that focuses attention on knowledge and agglomeration economies. We claim that both

  14. Evolutionary institutionalism.

    Science.gov (United States)

    Fürstenberg, Dr Kai

    Institutions are hard to define and hard to study. Long prominent in political science have been two theories: Rational Choice Institutionalism (RCI) and Historical Institutionalism (HI). Arising from the life sciences is now a third: Evolutionary Institutionalism (EI). Comparative strengths and weaknesses of these three theories warrant review, and the value-to-be-added by expanding the third beyond Darwinian evolutionary theory deserves consideration. Should evolutionary institutionalism expand to accommodate new understanding in ecology, such as might apply to the emergence of stability, and in genetics, such as might apply to political behavior? Core arguments are reviewed for each theory with more detailed exposition of the third, EI. Particular attention is paid to EI's gene-institution analogy; to variation, selection, and retention of institutional traits; to endogeneity and exogeneity; to agency and structure; and to ecosystem effects, institutional stability, and empirical limitations in behavioral genetics. RCI, HI, and EI are distinct but complementary. Institutional change, while amenable to rational-choice analysis and, retrospectively, to criticaljuncture and path-dependency analysis, is also, and importantly, ecological. Stability, like change, is an emergent property of institutions, which tend to stabilize after change in a manner analogous to allopatric speciation. EI is more than metaphorically biological in that institutional behaviors are driven by human behaviors whose evolution long preceded the appearance of institutions themselves.

  15. Evolutionary process of deep-sea bathymodiolus mussels.

    Directory of Open Access Journals (Sweden)

    Jun-Ichi Miyazaki

    Full Text Available BACKGROUND: Since the discovery of deep-sea chemosynthesis-based communities, much work has been done to clarify their organismal and environmental aspects. However, major topics remain to be resolved, including when and how organisms invade and adapt to deep-sea environments; whether strategies for invasion and adaptation are shared by different taxa or unique to each taxon; how organisms extend their distribution and diversity; and how they become isolated to speciate in continuous waters. Deep-sea mussels are one of the dominant organisms in chemosynthesis-based communities, thus investigations of their origin and evolution contribute to resolving questions about life in those communities. METHODOLOGY/PRINCIPAL FINDING: We investigated worldwide phylogenetic relationships of deep-sea Bathymodiolus mussels and their mytilid relatives by analyzing nucleotide sequences of the mitochondrial cytochrome c oxidase subunit I (COI and NADH dehydrogenase subunit 4 (ND4 genes. Phylogenetic analysis of the concatenated sequence data showed that mussels of the subfamily Bathymodiolinae from vents and seeps were divided into four groups, and that mussels of the subfamily Modiolinae from sunken wood and whale carcasses assumed the outgroup position and shallow-water modioline mussels were positioned more distantly to the bathymodioline mussels. We provisionally hypothesized the evolutionary history of Bathymodilolus mussels by estimating evolutionary time under a relaxed molecular clock model. Diversification of bathymodioline mussels was initiated in the early Miocene, and subsequently diversification of the groups occurred in the early to middle Miocene. CONCLUSIONS/SIGNIFICANCE: The phylogenetic relationships support the "Evolutionary stepping stone hypothesis," in which mytilid ancestors exploited sunken wood and whale carcasses in their progressive adaptation to deep-sea environments. This hypothesis is also supported by the evolutionary transition of

  16. Evolutionary foundations for cancer biology.

    Science.gov (United States)

    Aktipis, C Athena; Nesse, Randolph M

    2013-01-01

    New applications of evolutionary biology are transforming our understanding of cancer. The articles in this special issue provide many specific examples, such as microorganisms inducing cancers, the significance of within-tumor heterogeneity, and the possibility that lower dose chemotherapy may sometimes promote longer survival. Underlying these specific advances is a large-scale transformation, as cancer research incorporates evolutionary methods into its toolkit, and asks new evolutionary questions about why we are vulnerable to cancer. Evolution explains why cancer exists at all, how neoplasms grow, why cancer is remarkably rare, and why it occurs despite powerful cancer suppression mechanisms. Cancer exists because of somatic selection; mutations in somatic cells result in some dividing faster than others, in some cases generating neoplasms. Neoplasms grow, or do not, in complex cellular ecosystems. Cancer is relatively rare because of natural selection; our genomes were derived disproportionally from individuals with effective mechanisms for suppressing cancer. Cancer occurs nonetheless for the same six evolutionary reasons that explain why we remain vulnerable to other diseases. These four principles-cancers evolve by somatic selection, neoplasms grow in complex ecosystems, natural selection has shaped powerful cancer defenses, and the limitations of those defenses have evolutionary explanations-provide a foundation for understanding, preventing, and treating cancer.

  17. Evolution of microgastropods (Ellobioidea, Carychiidae): integrating taxonomic, phylogenetic and evolutionary hypotheses

    Science.gov (United States)

    2013-01-01

    Background Current biodiversity patterns are considered largely the result of past climatic and tectonic changes. In an integrative approach, we combine taxonomic and phylogenetic hypotheses to analyze temporal and geographic diversification of epigean (Carychium) and subterranean (Zospeum) evolutionary lineages in Carychiidae (Eupulmonata, Ellobioidea). We explicitly test three hypotheses: 1) morphospecies encompass unrecognized evolutionary lineages, 2) limited dispersal results in a close genetic relationship of geographical proximally distributed taxa and 3) major climatic and tectonic events had an impact on lineage diversification within Carychiidae. Results Initial morphospecies assignments were investigated by different molecular delimitation approaches (threshold, ABGD, GMYC and SP). Despite a conservative delimitation strategy, carychiid morphospecies comprise a great number of unrecognized evolutionary lineages. We attribute this phenomenon to historic underestimation of morphological stasis and phenotypic variability amongst lineages. The first molecular phylogenetic hypothesis for the Carychiidae (based on COI, 16S and H3) reveals Carychium and Zospeum to be reciprocally monophyletic. Geographical proximally distributed lineages are often closely related. The temporal diversification of Carychiidae is best described by a constant rate model of diversification. The evolution of Carychiidae is characterized by relatively few (long distance) colonization events. We find support for an Asian origin of Carychium. Zospeum may have arrived in Europe before extant members of Carychium. Distantly related Carychium clades inhabit a wide spectrum of the available bioclimatic niche and demonstrate considerable niche overlap. Conclusions Carychiid taxonomy is in dire need of revision. An inferred wide distribution and variable phenotype suggest underestimated diversity in Zospeum. Several Carychium morphospecies are results of past taxonomic lumping. By collecting

  18. Exploring social influence on evolutionary prisoner’s dilemma games in networks

    Science.gov (United States)

    Zong, Hengshan; Jia, Guozhu; Cheng, Yang

    2015-11-01

    Though numerous studies demonstrate the importance of social influence in deciding individual decision-making process in networks, little has been done to explore its impact on players’ behavioral patterns in evolutionary prisoner’s dilemma games (PDGs). This study investigates how social influenced strategy updating rules may affect the final equilibrium of game dynamics. The results show that weak social influence usually inhibits cooperation, while strong social influence has a mediating effect. The impacts of network structure and the existence of rebels in social influence scenarios are also tested. The paper provides a comprehensive interpretation on social influence effects on evolutionary PDGs in networks.

  19. Evolutionary plant physiology: Charles Darwin's forgotten synthesis

    Science.gov (United States)

    Kutschera, Ulrich; Niklas, Karl J.

    2009-11-01

    Charles Darwin dedicated more than 20 years of his life to a variety of investigations on higher plants (angiosperms). It has been implicitly assumed that these studies in the fields of descriptive botany and experimental plant physiology were carried out to corroborate his principle of descent with modification. However, Darwin’s son Francis, who was a professional plant biologist, pointed out that the interests of his father were both of a physiological and an evolutionary nature. In this article, we describe Darwin’s work on the physiology of higher plants from a modern perspective, with reference to the following topics: circumnutations, tropisms and the endogenous oscillator model; the evolutionary patterns of auxin action; the root-brain hypothesis; phloem structure and photosynthesis research; endosymbioses and growth-promoting bacteria; photomorphogenesis and phenotypic plasticity; basal metabolic rate, the Pfeffer-Kleiber relationship and metabolic optimality theory with respect to adaptive evolution; and developmental constraints versus functional equivalence in relationship to directional natural selection. Based on a review of these various fields of inquiry, we deduce the existence of a Darwinian (evolutionary) approach to plant physiology and define this emerging scientific discipline as the experimental study and theoretical analysis of the functions of green, sessile organisms from a phylogenetic perspective.

  20. Evolutionary plant physiology: Charles Darwin's forgotten synthesis.

    Science.gov (United States)

    Kutschera, Ulrich; Niklas, Karl J

    2009-11-01

    Charles Darwin dedicated more than 20 years of his life to a variety of investigations on higher plants (angiosperms). It has been implicitly assumed that these studies in the fields of descriptive botany and experimental plant physiology were carried out to corroborate his principle of descent with modification. However, Darwin's son Francis, who was a professional plant biologist, pointed out that the interests of his father were both of a physiological and an evolutionary nature. In this article, we describe Darwin's work on the physiology of higher plants from a modern perspective, with reference to the following topics: circumnutations, tropisms and the endogenous oscillator model; the evolutionary patterns of auxin action; the root-brain hypothesis; phloem structure and photosynthesis research; endosymbioses and growth-promoting bacteria; photomorphogenesis and phenotypic plasticity; basal metabolic rate, the Pfeffer-Kleiber relationship and metabolic optimality theory with respect to adaptive evolution; and developmental constraints versus functional equivalence in relationship to directional natural selection. Based on a review of these various fields of inquiry, we deduce the existence of a Darwinian (evolutionary) approach to plant physiology and define this emerging scientific discipline as the experimental study and theoretical analysis of the functions of green, sessile organisms from a phylogenetic perspective.

  1. Evolutionary perspectives into placental biology and disease

    Directory of Open Access Journals (Sweden)

    Edward B. Chuong

    2013-12-01

    Full Text Available In all mammals including humans, development takes place within the protective environment of the maternal womb. Throughout gestation, nutrients and waste products are continuously exchanged between mother and fetus through the placenta. Despite the clear importance of the placenta to successful pregnancy and the health of both mother and offspring, relatively little is understood about the biology of the placenta and its role in pregnancy-related diseases. Given that pre- and peri-natal diseases involving the placenta affect millions of women and their newborns worldwide, there is an urgent need to understand placenta biology and development. Here, we suggest that the placenta is an organ under unique selective pressures that have driven its rapid diversification throughout mammalian evolution. The high divergence of the placenta complicates the use of non-human animal models and necessitates an evolutionary perspective when studying its biology and role in disease. We suggest that diversifying evolution of the placenta is primarily driven by intraspecies evolutionary conflict between mother and fetus, and that many pregnancy diseases are a consequence of this evolutionary force. Understanding how maternal–fetal conflict shapes both basic placental and reproductive biology – in all species – will provide key insights into diseases of pregnancy.

  2. Evolutionary rates at codon sites may be used to align sequences and infer protein domain function

    Directory of Open Access Journals (Sweden)

    Hazelhurst Scott

    2010-03-01

    Full Text Available Abstract Background Sequence alignments form part of many investigations in molecular biology, including the determination of phylogenetic relationships, the prediction of protein structure and function, and the measurement of evolutionary rates. However, to obtain meaningful results, a significant degree of sequence similarity is required to ensure that the alignments are accurate and the inferences correct. Limitations arise when sequence similarity is low, which is particularly problematic when working with fast-evolving genes, evolutionary distant taxa, genomes with nucleotide biases, and cases of convergent evolution. Results A novel approach was conceptualized to address the "low sequence similarity" alignment problem. We developed an alignment algorithm termed FIRE (Functional Inference using the Rates of Evolution, which aligns sequences using the evolutionary rate at codon sites, as measured by the dN/dS ratio, rather than nucleotide or amino acid residues. FIRE was used to test the hypotheses that evolutionary rates can be used to align sequences and that the alignments may be used to infer protein domain function. Using a range of test data, we found that aligning domains based on evolutionary rates was possible even when sequence similarity was very low (for example, antibody variable regions. Furthermore, the alignment has the potential to infer protein domain function, indicating that domains with similar functions are subject to similar evolutionary constraints. These data suggest that an evolutionary rate-based approach to sequence analysis (particularly when combined with structural data may be used to study cases of convergent evolution or when sequences have very low similarity. However, when aligning homologous gene sets with sequence similarity, FIRE did not perform as well as the best traditional alignment algorithms indicating that the conventional approach of aligning residues as opposed to evolutionary rates remains the

  3. The relative importance of regional, local, and evolutionary factors structuring cryptobenthic coral-reef assemblages

    Science.gov (United States)

    Ahmadia, Gabby N.; Tornabene, Luke; Smith, David J.; Pezold, Frank L.

    2018-03-01

    Factors shaping coral-reef fish species assemblages can operate over a wide range of spatial scales (local versus regional) and across both proximate and evolutionary time. Niche theory and neutral theory provide frameworks for testing assumptions and generating insights about the importance of local versus regional processes. Niche theory postulates that species assemblages are an outcome of evolutionary processes at regional scales followed by local-scale interactions, whereas neutral theory presumes that species assemblages are formed by largely random processes drawing from regional species pools. Indo-Pacific cryptobenthic coral-reef fishes are highly evolved, ecologically diverse, temporally responsive, and situated on a natural longitudinal diversity gradient, making them an ideal group for testing predictions from niche and neutral theories and effects of regional and local processes on species assemblages. Using a combination of ecological metrics (fish density, diversity, assemblage composition) and evolutionary analyses (testing for phylogenetic niche conservatism), we demonstrate that the structure of cryptobenthic fish assemblages can be explained by a mixture of regional factors, such as the size of regional species pools and broad-scale barriers to gene flow/drivers of speciation, coupled with local-scale factors, such as the relative abundance of specific microhabitat types. Furthermore, species of cryptobenthic fishes have distinct microhabitat associations that drive significant differences in assemblage community structure between microhabitat types, and these distinct microhabitat associations are phylogenetically conserved over evolutionary timescales. The implied differential fitness of cryptobenthic fishes across varied microhabitats and the conserved nature of their ecology are consistent with predictions from niche theory. Neutral theory predictions may still hold true for early life-history stages, where stochastic factors may be more

  4. Defensive traits exhibit an evolutionary trade-off and drive diversification in ants.

    Science.gov (United States)

    Blanchard, Benjamin D; Moreau, Corrie S

    2017-02-01

    Evolutionary biologists have long predicted that evolutionary trade-offs among traits should constrain morphological divergence and species diversification. However, this prediction has yet to be tested in a broad evolutionary context in many diverse clades, including ants. Here, we reconstruct an expanded ant phylogeny representing 82% of ant genera, compile a new family-wide trait database, and conduct various trait-based analyses to show that defensive traits in ants do exhibit an evolutionary trade-off. In particular, the use of a functional sting negatively correlates with a suite of other defensive traits including spines, large eye size, and large colony size. Furthermore, we find that several of the defensive traits that trade off with a sting are also positively correlated with each other and drive increased diversification, further suggesting that these traits form a defensive suite. Our results support the hypothesis that trade-offs in defensive traits significantly constrain trait evolution and influence species diversification in ants. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

  5. A brief introduction to continuous evolutionary optimization

    CERN Document Server

    Kramer, Oliver

    2014-01-01

    Practical optimization problems are often hard to solve, in particular when they are black boxes and no further information about the problem is available except via function evaluations. This work introduces a collection of heuristics and algorithms for black box optimization with evolutionary algorithms in continuous solution spaces. The book gives an introduction to evolution strategies and parameter control. Heuristic extensions are presented that allow optimization in constrained, multimodal, and multi-objective solution spaces. An adaptive penalty function is introduced for constrained optimization. Meta-models reduce the number of fitness and constraint function calls in expensive optimization problems. The hybridization of evolution strategies with local search allows fast optimization in solution spaces with many local optima. A selection operator based on reference lines in objective space is introduced to optimize multiple conflictive objectives. Evolutionary search is employed for learning kernel ...

  6. Evolutionary principles and their practical application

    DEFF Research Database (Denmark)

    Hendry, A. P.; Kinnison, M. T.; Heino, M.

    2011-01-01

    Evolutionary principles are now routinely incorporated into medicine and agriculture. Examples include the design of treatments that slow the evolution of resistance by weeds, pests, and pathogens, and the design of breeding programs that maximize crop yield or quality. Evolutionary principles...... are also increasingly incorporated into conservation biology, natural resource management, and environmental science. Examples include the protection of small and isolated populations from inbreeding depression, the identification of key traits involved in adaptation to climate change, the design...... of harvesting regimes that minimize unwanted life-history evolution, and the setting of conservation priorities based on populations, species, or communities that harbor the greatest evolutionary diversity and potential. The adoption of evolutionary principles has proceeded somewhat independently...

  7. Evolutionary aspects of non-cell-autonomous regulation in vascular plants: structural background and models to study

    Directory of Open Access Journals (Sweden)

    Anastasiia I. Evkaikina

    2014-02-01

    Full Text Available Plasmodesmata (PD serve for the exchange of information in form of miRNA, proteins and mRNA between adjacent cells in the course of plant development. This fundamental role of PD is well established in angiosperms but has not yet been traced back to the evolutionary ancient plant taxa where functional studies lag behind studies of PD structure and ontogenetic origin. There is convincing evidence that the ability to form secondary (post-cytokinesis PD, which can connect any adjacent cells, contrary to primary PD which form during cytokinesis and link only cells of the same lineage, appeared in the evolution of higher plants at least twice: in seed plants and in some representatives of the Lycopodiophyta. The (inability to form secondary PD is manifested in the symplastic organization of the shoot apical meristem (SAM which in most taxa of seedless vascular plants differs dramatically from that in seed plants. Lycopodiophyta appear to be suitable models to analyze the transport of developmental regulators via PD in SAMs with symplastic organization both different from, as well as analogous to, that in angiosperms, and to understand the evolutionary aspects of the role of this transport in the morphogenesis of vascular plant taxa.

  8. Statistical mechanics of spatial evolutionary games

    International Nuclear Information System (INIS)

    Miekisz, Jacek

    2004-01-01

    We discuss the long-run behaviour of stochastic dynamics of many interacting players in spatial evolutionary games. In particular, we investigate the effect of the number of players and the noise level on the stochastic stability of Nash equilibria. We discuss similarities and differences between systems of interacting players maximizing their individual payoffs and particles minimizing their interaction energy. We use concepts and techniques of statistical mechanics to study game-theoretic models. In order to obtain results in the case of the so-called potential games, we analyse the thermodynamic limit of the appropriate models of interacting particles

  9. Gender Inequality in Interaction--An Evolutionary Account

    Science.gov (United States)

    Hopcroft, Rosemary L.

    2009-01-01

    In this article I argue that evolutionary theorizing can help sociologists and feminists better understand gender inequality. Evolutionary theory explains why control of the sexuality of young women is a priority across most human societies both past and present. Evolutionary psychology has extended our understanding of male violence against…

  10. In Darwin's Footsteps: An On and Off-Campus Approach to Teaching Evolutionary Theory and Animal Behavior

    Science.gov (United States)

    Gillie, Lynn; Bizub, Anne L.

    2012-01-01

    The study of evolutionary theory and fieldwork in animal behavior is enriched when students leave the classroom so they may test their abilities to think and act like scientists. This article describes a course on evolutionary theory and animal behavior that blended on campus learning with field experience in the United States and in Ecuador and…

  11. Quantifying the Determinants of Evolutionary Dynamics Leading to Drug Resistance.

    Directory of Open Access Journals (Sweden)

    Guillaume Chevereau

    Full Text Available The emergence of drug resistant pathogens is a serious public health problem. It is a long-standing goal to predict rates of resistance evolution and design optimal treatment strategies accordingly. To this end, it is crucial to reveal the underlying causes of drug-specific differences in the evolutionary dynamics leading to resistance. However, it remains largely unknown why the rates of resistance evolution via spontaneous mutations and the diversity of mutational paths vary substantially between drugs. Here we comprehensively quantify the distribution of fitness effects (DFE of mutations, a key determinant of evolutionary dynamics, in the presence of eight antibiotics representing the main modes of action. Using precise high-throughput fitness measurements for genome-wide Escherichia coli gene deletion strains, we find that the width of the DFE varies dramatically between antibiotics and, contrary to conventional wisdom, for some drugs the DFE width is lower than in the absence of stress. We show that this previously underappreciated divergence in DFE width among antibiotics is largely caused by their distinct drug-specific dose-response characteristics. Unlike the DFE, the magnitude of the changes in tolerated drug concentration resulting from genome-wide mutations is similar for most drugs but exceptionally small for the antibiotic nitrofurantoin, i.e., mutations generally have considerably smaller resistance effects for nitrofurantoin than for other drugs. A population genetics model predicts that resistance evolution for drugs with this property is severely limited and confined to reproducible mutational paths. We tested this prediction in laboratory evolution experiments using the "morbidostat", a device for evolving bacteria in well-controlled drug environments. Nitrofurantoin resistance indeed evolved extremely slowly via reproducible mutations-an almost paradoxical behavior since this drug causes DNA damage and increases the mutation

  12. Evolutionary status of AA Doradus: still an enigma?

    International Nuclear Information System (INIS)

    Sarna, M.J.

    1985-01-01

    The evolutionary scenarios for AA Dor are reconsidered using new contraction times for degenerate red dwarfs. It is found that both types of models considered by Paczynski (1980) with the primary being either an hydrogen shell burning helium white dwarf or a double shell burning carbon-oxygen white dwarf are consistent with the available data. The second model requires a very narrow range of the initial parameters of the binary system. 26 refs. (author)

  13. Making evolutionary biology a basic science for medicine

    Science.gov (United States)

    Nesse, Randolph M.; Bergstrom, Carl T.; Ellison, Peter T.; Flier, Jeffrey S.; Gluckman, Peter; Govindaraju, Diddahally R.; Niethammer, Dietrich; Omenn, Gilbert S.; Perlman, Robert L.; Schwartz, Mark D.; Thomas, Mark G.; Stearns, Stephen C.; Valle, David

    2010-01-01

    New applications of evolutionary biology in medicine are being discovered at an accelerating rate, but few physicians have sufficient educational background to use them fully. This article summarizes suggestions from several groups that have considered how evolutionary biology can be useful in medicine, what physicians should learn about it, and when and how they should learn it. Our general conclusion is that evolutionary biology is a crucial basic science for medicine. In addition to looking at established evolutionary methods and topics, such as population genetics and pathogen evolution, we highlight questions about why natural selection leaves bodies vulnerable to disease. Knowledge about evolution provides physicians with an integrative framework that links otherwise disparate bits of knowledge. It replaces the prevalent view of bodies as machines with a biological view of bodies shaped by evolutionary processes. Like other basic sciences, evolutionary biology needs to be taught both before and during medical school. Most introductory biology courses are insufficient to establish competency in evolutionary biology. Premedical students need evolution courses, possibly ones that emphasize medically relevant aspects. In medical school, evolutionary biology should be taught as one of the basic medical sciences. This will require a course that reviews basic principles and specific medical applications, followed by an integrated presentation of evolutionary aspects that apply to each disease and organ system. Evolutionary biology is not just another topic vying for inclusion in the curriculum; it is an essential foundation for a biological understanding of health and disease. PMID:19918069

  14. A Study of Driver’s Route Choice Behavior Based on Evolutionary Game Theory

    Directory of Open Access Journals (Sweden)

    Xiaowei Jiang

    2014-01-01

    Full Text Available This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers’ route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver’s route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver’s route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent.

  15. Home and away- the evolutionary dynamics of homing endonucleases

    Directory of Open Access Journals (Sweden)

    Barzel Adi

    2011-11-01

    Full Text Available Abstract Background Homing endonucleases (HEases are a large and diverse group of site-specific DNAases. They reside within self-splicing introns and inteins, and promote their horizontal dissemination. In recent years, HEases have been the focus of extensive research due to their promising potential use in gene targeting procedures for the treatment of genetic diseases and for the genetic engineering of crop, animal models and cell lines. Results Using mathematical analysis and computational modeling, we present here a novel account for the evolution and population dynamics of HEase genes (HEGs. We describe HEGs as paradoxical selfish elements whose long-term persistence in a single population relies on low transmission rates and a positive correlation between transmission efficiency and toxicity. Conclusion Plausible conditions allow HEGs to sustain at high frequency through long evolutionary periods, with the endonuclease frequency being either at equilibrium or periodically oscillating. The predictions of our model may prove important not only for evolutionary theory but also for gene therapy and bio-engineering applications of HEases.

  16. Models for Evolutionary Algorithms and Their Applications in System Identification and Control Optimization

    DEFF Research Database (Denmark)

    Ursem, Rasmus Kjær

    population and many generations, which essentially turns the problem into a series of related static problems. To our surprise, the control problem could easily be solved when optimized like this. To further examine this, we compared the EA with a particle swarm and a local search approach, which we...... simulate an evolutionary process where the goal is to evolve solutions by means of crossover, mutation, and selection based on their quality (fitness) with respect to the optimization problem at hand. Evolutionary algorithms (EAs) are highly relevant for industrial applications, because they are capable...... of handling problems with non-linear constraints, multiple objectives, and dynamic components – properties that frequently appear in real-world problems. This thesis presents research in three fundamental areas of EC; fitness function design, methods for parameter control, and techniques for multimodal...

  17. Contemporary issues in evolutionary biology

    Indian Academy of Sciences (India)

    We are delighted to bring to the readers, a set of peer-reviewed papers on evolutionary biology, published as a special issue of the Journal of Genetics. These papers emanated from ruminations upon and discussions at the Foundations of. Evolutionary Theory: the Ongoing Synthesis meeting at Coorg, India, in February ...

  18. BIRDS AS A MODEL TO STUDY ADULT NEUROGENESIS: BRIDGING EVOLUTIONARY, COMPARATIVE AND NEUROETHOLOGICAL APPROCHES

    Science.gov (United States)

    BARNEA, ANAT; PRAVOSUDOV, VLADIMIR

    2011-01-01

    During the last few decades evidence has demonstrated that adult neurogenesis is a well-preserved feature throughout the animal kingdom. In birds, ongoing neuronal addition occurs rather broadly, to a number of brain regions. This review describes adult avian neurogenesis and neuronal recruitment, discusses factors that regulate these processes, and touches upon the question of their genetic control. Several attributes make birds an extremely advantageous model to study neurogenesis. First, song learning exhibits seasonal variation that is associated with seasonal variation in neuronal turnover in some song control brain nuclei, which seems to be regulated via adult neurogenesis. Second, food-caching birds naturally use memory-dependent behavior in learning locations of thousands of food caches scattered over their home ranges. In comparison with other birds, food-caching species have relatively enlarged hippocampi with more neurons and intense neurogenesis, which appears to be related to spatial learning. Finally, migratory behavior and naturally occurring social systems in birds also provide opportunities to investigate neurogenesis. Such diversity of naturally-occurring memory-based behaviors, combined with the fact that birds can be studied both in the wild and in the laboratory, make them ideal for investigation of neural processes underlying learning. This can be done by using various approaches, from evolutionary and comparative to neuroethological and molecular. Finally, we connect the avian arena to a broader view by providing a brief comparative and evolutionary overview of adult neurogenesis and by discussing the possible functional role of the new neurons. We conclude by indicating future directions and possible medical applications. PMID:21929623

  19. Evolutionary dynamics of a smoothed war of attrition game.

    Science.gov (United States)

    Iyer, Swami; Killingback, Timothy

    2016-05-07

    In evolutionary game theory the War of Attrition game is intended to model animal contests which are decided by non-aggressive behavior, such as the length of time that a participant will persist in the contest. The classical War of Attrition game assumes that no errors are made in the implementation of an animal׳s strategy. However, it is inevitable in reality that such errors must sometimes occur. Here we introduce an extension of the classical War of Attrition game which includes the effect of errors in the implementation of an individual׳s strategy. This extension of the classical game has the important feature that the payoff is continuous, and as a consequence admits evolutionary behavior that is fundamentally different from that possible in the original game. We study the evolutionary dynamics of this new game in well-mixed populations both analytically using adaptive dynamics and through individual-based simulations, and show that there are a variety of possible outcomes, including simple monomorphic or dimorphic configurations which are evolutionarily stable and cannot occur in the classical War of Attrition game. In addition, we study the evolutionary dynamics of this extended game in a variety of spatially and socially structured populations, as represented by different complex network topologies, and show that similar outcomes can also occur in these situations. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Study on Cooperative Mechanism of Prefabricated Producers Based on Evolutionary Game Theory

    Directory of Open Access Journals (Sweden)

    Tongyao Feng

    2017-01-01

    Full Text Available Good cooperation mechanism is an important guarantee for the advancement of industrialization construction. To strengthen the partnership between producers, we analyze the behavior evolution trend of both parties using an evolutionary game theory. Based on the original model, the mechanism of coordination and cooperation between prefabricated producers is explained under the condition of punishment and incentive. The results indicate that stable evolutionary strategies exist under both cooperation and noncooperation, and the evolutionary results are influenced by the initial proportion of both decision-making processes. The government can support the production enterprises to establish a solid partnership through effective punishment and incentive mechanisms to reduce the initial cost in the supply chain of prefabricated construction, resulting in a win-win situation.

  1. Evolutionary Developmental Robotics: Improving Morphology and Control of Physical Robots.

    Science.gov (United States)

    Vujovic, Vuk; Rosendo, Andre; Brodbeck, Luzius; Iida, Fumiya

    2017-01-01

    Evolutionary algorithms have previously been applied to the design of morphology and control of robots. The design space for such tasks can be very complex, which can prevent evolution from efficiently discovering fit solutions. In this article we introduce an evolutionary-developmental (evo-devo) experiment with real-world robots. It allows robots to grow their leg size to simulate ontogenetic morphological changes, and this is the first time that such an experiment has been performed in the physical world. To test diverse robot morphologies, robot legs of variable shapes were generated during the evolutionary process and autonomously built using additive fabrication. We present two cases with evo-devo experiments and one with evolution, and we hypothesize that the addition of a developmental stage can be used within robotics to improve performance. Moreover, our results show that a nonlinear system-environment interaction exists, which explains the nontrivial locomotion patterns observed. In the future, robots will be present in our daily lives, and this work introduces for the first time physical robots that evolve and grow while interacting with the environment.

  2. Recovery after mass extinction: evolutionary assembly in large-scale biosphere dynamics.

    Science.gov (United States)

    Solé, Ricard V; Montoya, José M; Erwin, Douglas H

    2002-01-01

    Biotic recoveries following mass extinctions are characterized by a process in which whole ecologies are reconstructed from low-diversity systems, often characterized by opportunistic groups. The recovery process provides an unexpected window to ecosystem dynamics. In many aspects, recovery is very similar to ecological succession, but important differences are also apparently linked to the innovative patterns of niche construction observed in the fossil record. In this paper, we analyse the similarities and differences between ecological succession and evolutionary recovery to provide a preliminary ecological theory of recoveries. A simple evolutionary model with three trophic levels is presented, and its properties (closely resembling those observed in the fossil record) are compared with characteristic patterns of ecological response to disturbances in continuous models of three-level ecosystems. PMID:12079530

  3. Evolutionary robotics simulations help explain why reciprocity is rare in nature.

    Science.gov (United States)

    André, Jean-Baptiste; Nolfi, Stefano

    2016-09-12

    The relative rarity of reciprocity in nature, contrary to theoretical predictions that it should be widespread, is currently one of the major puzzles in social evolution theory. Here we use evolutionary robotics to solve this puzzle. We show that models based on game theory are misleading because they neglect the mechanics of behavior. In a series of experiments with simulated robots controlled by artificial neural networks, we find that reciprocity does not evolve, and show that this results from a general constraint that likely also prevents it from evolving in the wild. Reciprocity can evolve if it requires very few mutations, as is usually assumed in evolutionary game theoretic models, but not if, more realistically, it requires the accumulation of many adaptive mutations.

  4. Evolutionary stability in the asymmetric volunteer's dilemma.

    Directory of Open Access Journals (Sweden)

    Jun-Zhou He

    Full Text Available It is often assumed that in public goods games, contributors are either strong or weak players and each individual has an equal probability of exhibiting cooperation. It is difficult to explain why the public good is produced by strong individuals in some cooperation systems, and by weak individuals in others. Viewing the asymmetric volunteer's dilemma game as an evolutionary game, we find that whether the strong or the weak players produce the public good depends on the initial condition (i.e., phenotype or initial strategy of individuals. These different evolutionarily stable strategies (ESS associated with different initial conditions, can be interpreted as the production modes of public goods of different cooperation systems. A further analysis revealed that the strong player adopts a pure strategy but mixed strategies for the weak players to produce the public good, and that the probability of volunteering by weak players decreases with increasing group size or decreasing cost-benefit ratio. Our model shows that the defection probability of a "strong" player is greater than the "weak" players in the model of Diekmann (1993. This contradicts Selten's (1980 model that public goods can only be produced by a strong player, is not an evolutionarily stable strategy, and will therefore disappear over evolutionary time. Our public good model with ESS has thus extended previous interpretations that the public good can only be produced by strong players in an asymmetric game.

  5. Ancestral state reconstructions require biological evidence to test evolutionary hypotheses: A case study examining the evolution of reproductive mode in squamate reptiles.

    Science.gov (United States)

    Griffith, Oliver W; Blackburn, Daniel G; Brandley, Matthew C; Van Dyke, James U; Whittington, Camilla M; Thompson, Michael B

    2015-09-01

    To understand evolutionary transformations it is necessary to identify the character states of extinct ancestors. Ancestral character state reconstruction is inherently difficult because it requires an accurate phylogeny, character state data, and a statistical model of transition rates and is fundamentally constrained by missing data such as extinct taxa. We argue that model based ancestral character state reconstruction should be used to generate hypotheses but should not be considered an analytical endpoint. Using the evolution of viviparity and reversals to oviparity in squamates as a case study, we show how anatomical, physiological, and ecological data can be used to evaluate hypotheses about evolutionary transitions. The evolution of squamate viviparity requires changes to the timing of reproductive events and the successive loss of features responsible for building an eggshell. A reversal to oviparity requires that those lost traits re-evolve. We argue that the re-evolution of oviparity is inherently more difficult than the reverse. We outline how the inviability of intermediate phenotypes might present physiological barriers to reversals from viviparity to oviparity. Finally, we show that ecological data supports an oviparous ancestral state for squamates and multiple transitions to viviparity. In summary, we conclude that the first squamates were oviparous, that frequent transitions to viviparity have occurred, and that reversals to oviparity in viviparous lineages either have not occurred or are exceedingly rare. As this evidence supports conclusions that differ from previous ancestral state reconstructions, our paper highlights the importance of incorporating biological evidence to evaluate model-generated hypotheses. © 2015 Wiley Periodicals, Inc.

  6. Evolutionary fuzzy ARTMAP neural networks for classification of semiconductor defects.

    Science.gov (United States)

    Tan, Shing Chiang; Watada, Junzo; Ibrahim, Zuwairie; Khalid, Marzuki

    2015-05-01

    Wafer defect detection using an intelligent system is an approach of quality improvement in semiconductor manufacturing that aims to enhance its process stability, increase production capacity, and improve yields. Occasionally, only few records that indicate defective units are available and they are classified as a minority group in a large database. Such a situation leads to an imbalanced data set problem, wherein it engenders a great challenge to deal with by applying machine-learning techniques for obtaining effective solution. In addition, the database may comprise overlapping samples of different classes. This paper introduces two models of evolutionary fuzzy ARTMAP (FAM) neural networks to deal with the imbalanced data set problems in a semiconductor manufacturing operations. In particular, both the FAM models and hybrid genetic algorithms are integrated in the proposed evolutionary artificial neural networks (EANNs) to classify an imbalanced data set. In addition, one of the proposed EANNs incorporates a facility to learn overlapping samples of different classes from the imbalanced data environment. The classification results of the proposed evolutionary FAM neural networks are presented, compared, and analyzed using several classification metrics. The outcomes positively indicate the effectiveness of the proposed networks in handling classification problems with imbalanced data sets.

  7. Archaeogenetics in evolutionary medicine.

    Science.gov (United States)

    Bouwman, Abigail; Rühli, Frank

    2016-09-01

    Archaeogenetics is the study of exploration of ancient DNA (aDNA) of more than 70 years old. It is an important part of the wider studies of many different areas of our past, including animal, plant and pathogen evolution and domestication events. Hereby, we address specifically the impact of research in archaeogenetics in the broader field of evolutionary medicine. Studies on ancient hominid genomes help to understand even modern health patterns. Human genetic microevolution, e.g. related to abilities of post-weaning milk consumption, and specifically genetic adaptation in disease susceptibility, e.g. towards malaria and other infectious diseases, are of the upmost importance in contributions of archeogenetics on the evolutionary understanding of human health and disease. With the increase in both the understanding of modern medical genetics and the ability to deep sequence ancient genetic information, the field of archaeogenetic evolutionary medicine is blossoming.

  8. Complexity in Evolutionary Processes

    International Nuclear Information System (INIS)

    Schuster, P.

    2010-01-01

    Darwin's principle of evolution by natural selection is readily casted into a mathematical formalism. Molecular biology revealed the mechanism of mutation and provides the basis for a kinetic theory of evolution that models correct reproduction and mutation as parallel chemical reaction channels. A result of the kinetic theory is the existence of a phase transition in evolution occurring at a critical mutation rate, which represents a localization threshold for the population in sequence space. Occurrence and nature of such phase transitions depend critically on fitness landscapes. The fitness landscape being tantamount to a mapping from sequence or genotype space into phenotype space is identified as the true source of complexity in evolution. Modeling evolution as a stochastic process is discussed and neutrality with respect to selection is shown to provide a major challenge for understanding evolutionary processes (author)

  9. Genetic hotels for the standard genetic code: evolutionary analysis based upon novel three-dimensional algebraic models.

    Science.gov (United States)

    José, Marco V; Morgado, Eberto R; Govezensky, Tzipe

    2011-07-01

    Herein, we rigorously develop novel 3-dimensional algebraic models called Genetic Hotels of the Standard Genetic Code (SGC). We start by considering the primeval RNA genetic code which consists of the 16 codons of type RNY (purine-any base-pyrimidine). Using simple algebraic operations, we show how the RNA code could have evolved toward the current SGC via two different intermediate evolutionary stages called Extended RNA code type I and II. By rotations or translations of the subset RNY, we arrive at the SGC via the former (type I) or via the latter (type II), respectively. Biologically, the Extended RNA code type I, consists of all codons of the type RNY plus codons obtained by considering the RNA code but in the second (NYR type) and third (YRN type) reading frames. The Extended RNA code type II, comprises all codons of the type RNY plus codons that arise from transversions of the RNA code in the first (YNY type) and third (RNR) nucleotide bases. Since the dimensions of remarkable subsets of the Genetic Hotels are not necessarily integer numbers, we also introduce the concept of algebraic fractal dimension. A general decoding function which maps each codon to its corresponding amino acid or the stop signals is also derived. The Phenotypic Hotel of amino acids is also illustrated. The proposed evolutionary paths are discussed in terms of the existing theories of the evolution of the SGC. The adoption of 3-dimensional models of the Genetic and Phenotypic Hotels will facilitate the understanding of the biological properties of the SGC.

  10. Ant aggression and evolutionary stability in plant-ant and plant-pollinator mutualistic interactions.

    Science.gov (United States)

    Oña, L; Lachmann, M

    2011-03-01

    Mutualistic partners derive a benefit from their interaction, but this benefit can come at a cost. This is the case for plant-ant and plant-pollinator mutualistic associations. In exchange for protection from herbivores provided by the resident ants, plants supply various kinds of resources or nests to the ants. Most ant-myrmecophyte mutualisms are horizontally transmitted, and therefore, partners share an interest in growth but not in reproduction. This lack of alignment in fitness interests between plants and ants drives a conflict between them: ants can attack pollinators that cross-fertilize the host plants. Using a mathematical model, we define a threshold in ant aggressiveness determining pollinator survival or elimination on the host plant. In our model we observed that, all else being equal, facultative interactions result in pollinator extinction for lower levels of ant aggressiveness than obligatory interactions. We propose that the capacity to discriminate pollinators from herbivores should not often evolve in ants, and when it does it will be when the plants exhibit limited dispersal in an environment that is not seed saturated so that each seed produced can effectively generate a new offspring or if ants acquire an extra benefit from pollination (e.g. if ants eat fruit). We suggest specific mutualism examples where these hypotheses can be tested empirically. © 2010 The Authors. Journal of Evolutionary Biology © 2010 European Society For Evolutionary Biology.

  11. Evolutionary relevance facilitates visual information processing.

    Science.gov (United States)

    Jackson, Russell E; Calvillo, Dusti P

    2013-11-03

    Visual search of the environment is a fundamental human behavior that perceptual load affects powerfully. Previously investigated means for overcoming the inhibitions of high perceptual load, however, generalize poorly to real-world human behavior. We hypothesized that humans would process evolutionarily relevant stimuli more efficiently than evolutionarily novel stimuli, and evolutionary relevance would mitigate the repercussions of high perceptual load during visual search. Animacy is a significant component to evolutionary relevance of visual stimuli because perceiving animate entities is time-sensitive in ways that pose significant evolutionary consequences. Participants completing a visual search task located evolutionarily relevant and animate objects fastest and with the least impact of high perceptual load. Evolutionarily novel and inanimate objects were located slowest and with the highest impact of perceptual load. Evolutionary relevance may importantly affect everyday visual information processing.

  12. Mean-Potential Law in Evolutionary Games

    Science.gov (United States)

    Nałecz-Jawecki, Paweł; Miekisz, Jacek

    2018-01-01

    The Letter presents a novel way to connect random walks, stochastic differential equations, and evolutionary game theory. We introduce a new concept of a potential function for discrete-space stochastic systems. It is based on a correspondence between one-dimensional stochastic differential equations and random walks, which may be exact not only in the continuous limit but also in finite-state spaces. Our method is useful for computation of fixation probabilities in discrete stochastic dynamical systems with two absorbing states. We apply it to evolutionary games, formulating two simple and intuitive criteria for evolutionary stability of pure Nash equilibria in finite populations. In particular, we show that the 1 /3 law of evolutionary games, introduced by Nowak et al. [Nature, 2004], follows from a more general mean-potential law.

  13. Evolutionary tradeoffs, Pareto optimality and the morphology of ammonite shells.

    Science.gov (United States)

    Tendler, Avichai; Mayo, Avraham; Alon, Uri

    2015-03-07

    Organisms that need to perform multiple tasks face a fundamental tradeoff: no design can be optimal at all tasks at once. Recent theory based on Pareto optimality showed that such tradeoffs lead to a highly defined range of phenotypes, which lie in low-dimensional polyhedra in the space of traits. The vertices of these polyhedra are called archetypes- the phenotypes that are optimal at a single task. To rigorously test this theory requires measurements of thousands of species over hundreds of millions of years of evolution. Ammonoid fossil shells provide an excellent model system for this purpose. Ammonoids have a well-defined geometry that can be parameterized using three dimensionless features of their logarithmic-spiral-shaped shells. Their evolutionary history includes repeated mass extinctions. We find that ammonoids fill out a pyramid in morphospace, suggesting five specific tasks - one for each vertex of the pyramid. After mass extinctions, surviving species evolve to refill essentially the same pyramid, suggesting that the tasks are unchanging. We infer putative tasks for each archetype, related to economy of shell material, rapid shell growth, hydrodynamics and compactness. These results support Pareto optimality theory as an approach to study evolutionary tradeoffs, and demonstrate how this approach can be used to infer the putative tasks that may shape the natural selection of phenotypes.

  14. Is evolutionary psychology a metatheory for psychology? A discussion of four major issues in psychology from an evolutionary developmental perspective

    NARCIS (Netherlands)

    Ploeger, A.; van der Maas, H.L.J.; Raijmakers, M.E.J.

    2008-01-01

    Evolutionary psychology has been proposed as a metatheoretical framework for psychology. We argue that evolutionary psychology should be expanded if it is to offer new insights regarding the major issues in psychology. Evolutionary developmental biology can provide valuable new insights into issues

  15. MEGA-CC: computing core of molecular evolutionary genetics analysis program for automated and iterative data analysis.

    Science.gov (United States)

    Kumar, Sudhir; Stecher, Glen; Peterson, Daniel; Tamura, Koichiro

    2012-10-15

    There is a growing need in the research community to apply the molecular evolutionary genetics analysis (MEGA) software tool for batch processing a large number of datasets and to integrate it into analysis workflows. Therefore, we now make available the computing core of the MEGA software as a stand-alone executable (MEGA-CC), along with an analysis prototyper (MEGA-Proto). MEGA-CC provides users with access to all the computational analyses available through MEGA's graphical user interface version. This includes methods for multiple sequence alignment, substitution model selection, evolutionary distance estimation, phylogeny inference, substitution rate and pattern estimation, tests of natural selection and ancestral sequence inference. Additionally, we have upgraded the source code for phylogenetic analysis using the maximum likelihood methods for parallel execution on multiple processors and cores. Here, we describe MEGA-CC and outline the steps for using MEGA-CC in tandem with MEGA-Proto for iterative and automated data analysis. http://www.megasoftware.net/.

  16. An Evolutionary Model of the Environmental Conditions that Shape the Development of Prosociality

    Directory of Open Access Journals (Sweden)

    Daniel Tumminelli O'Brien

    2014-04-01

    Full Text Available The current review presents a model for how prosocial development is driven by sociocognitive mechanisms that have been shaped by natural selection to translate critical environmental factors into locally adaptive levels of prosociality. This is done through a synthesis of two existing literatures. Evolutionary developmental psychologists have demonstrated a biological basis for the emergence of prosocial behavior early in youth, and work based on social learning theory has explored how social experiences can influence prosociality across development. The model forwarded organizes this latter literature in a way that is specific to how the biological mechanisms underpinning prosociality have evolved. This consists of two main psychological mechanisms. 1 A domain-specific program that is responsive to environmental factors that determine the relative success of different levels of prosociality. It uses the local prevalence of prosocial others (i.e., support and expectations for prosocial behavior (i.e., structure to guide prosocial development. 2 The domain-general process of cultural learning, by which youth adopt local social norms based on the examples of others. Implications and hypotheses are articulated for both the sociocognitive structure of the individual and the role of social contexts.

  17. Structure versus time in the evolutionary diversification of avian carotenoid metabolic networks.

    Science.gov (United States)

    Morrison, Erin S; Badyaev, Alexander V

    2018-05-01

    Historical associations of genes and proteins are thought to delineate pathways available to subsequent evolution; however, the effects of past functional involvements on contemporary evolution are rarely quantified. Here, we examined the extent to which the structure of a carotenoid enzymatic network persists in avian evolution. Specifically, we tested whether the evolution of carotenoid networks was most concordant with phylogenetically structured expansion from core reactions of common ancestors or with subsampling of biochemical pathway modules from an ancestral network. We compared structural and historical associations in 467 carotenoid networks of extant and ancestral species and uncovered the overwhelming effect of pre-existing metabolic network structure on carotenoid diversification over the last 50 million years of avian evolution. Over evolutionary time, birds repeatedly subsampled and recombined conserved biochemical modules, which likely maintained the overall structure of the carotenoid metabolic network during avian evolution. These findings explain the recurrent convergence of evolutionary distant species in carotenoid metabolism and weak phylogenetic signal in avian carotenoid evolution. Remarkable retention of an ancient metabolic structure throughout extensive and prolonged ecological diversification in avian carotenoid metabolism illustrates a fundamental requirement of organismal evolution - historical continuity of a deterministic network that links past and present functional associations of its components. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

  18. Bioinformatics education dissemination with an evolutionary problem solving perspective.

    Science.gov (United States)

    Jungck, John R; Donovan, Samuel S; Weisstein, Anton E; Khiripet, Noppadon; Everse, Stephen J

    2010-11-01

    Bioinformatics is central to biology education in the 21st century. With the generation of terabytes of data per day, the application of computer-based tools to stored and distributed data is fundamentally changing research and its application to problems in medicine, agriculture, conservation and forensics. In light of this 'information revolution,' undergraduate biology curricula must be redesigned to prepare the next generation of informed citizens as well as those who will pursue careers in the life sciences. The BEDROCK initiative (Bioinformatics Education Dissemination: Reaching Out, Connecting and Knitting together) has fostered an international community of bioinformatics educators. The initiative's goals are to: (i) Identify and support faculty who can take leadership roles in bioinformatics education; (ii) Highlight and distribute innovative approaches to incorporating evolutionary bioinformatics data and techniques throughout undergraduate education; (iii) Establish mechanisms for the broad dissemination of bioinformatics resource materials and teaching models; (iv) Emphasize phylogenetic thinking and problem solving; and (v) Develop and publish new software tools to help students develop and test evolutionary hypotheses. Since 2002, BEDROCK has offered more than 50 faculty workshops around the world, published many resources and supported an environment for developing and sharing bioinformatics education approaches. The BEDROCK initiative builds on the established pedagogical philosophy and academic community of the BioQUEST Curriculum Consortium to assemble the diverse intellectual and human resources required to sustain an international reform effort in undergraduate bioinformatics education.

  19. Comparison of evolutionary computation algorithms for solving bi ...

    Indian Academy of Sciences (India)

    failure probability. Multiobjective Evolutionary Computation algorithms (MOEAs) are well-suited for Multiobjective task scheduling on heterogeneous environment. The two Multi-Objective Evolutionary Algorithms such as Multiobjective Genetic. Algorithm (MOGA) and Multiobjective Evolutionary Programming (MOEP) with.

  20. Species co-evolutionary algorithm: a novel evolutionary algorithm based on the ecology and environments for optimization

    DEFF Research Database (Denmark)

    Li, Wuzhao; Wang, Lei; Cai, Xingjuan

    2015-01-01

    and affect each other in many ways. The relationships include competition, predation, parasitism, mutualism and pythogenesis. In this paper, we consider the five relationships between solutions to propose a co-evolutionary algorithm termed species co-evolutionary algorithm (SCEA). In SCEA, five operators...

  1. Evolutionary and adaptive learning in complex markets: a brief summary

    Science.gov (United States)

    Hommes, Cars H.

    2007-06-01

    We briefly review some work on expectations and learning in complex markets, using the familiar demand-supply cobweb model. We discuss and combine two different approaches on learning. According to the adaptive learning approach, agents behave as econometricians using time series observations to form expectations, and update the parameters as more observations become available. This approach has become popular in macro. The second approach has an evolutionary flavor and is sometimes referred to as reinforcement learning. Agents employ different forecasting strategies and evaluate these strategies based upon a fitness measure, e.g. past realized profits. In this framework, boundedly rational agents switch between different, but fixed behavioral rules. This approach has become popular in finance. We combine evolutionary and adaptive learning to model complex markets and discuss whether this theory can match empirical facts and forecasting behavior in laboratory experiments with human subjects.

  2. Evolutionary Inference across Eukaryotes Identifies Specific Pressures Favoring Mitochondrial Gene Retention.

    Science.gov (United States)

    Johnston, Iain G; Williams, Ben P

    2016-02-24

    Since their endosymbiotic origin, mitochondria have lost most of their genes. Although many selective mechanisms underlying the evolution of mitochondrial genomes have been proposed, a data-driven exploration of these hypotheses is lacking, and a quantitatively supported consensus remains absent. We developed HyperTraPS, a methodology coupling stochastic modeling with Bayesian inference, to identify the ordering of evolutionary events and suggest their causes. Using 2015 complete mitochondrial genomes, we inferred evolutionary trajectories of mtDNA gene loss across the eukaryotic tree of life. We find that proteins comprising the structural cores of the electron transport chain are preferentially encoded within mitochondrial genomes across eukaryotes. A combination of high GC content and high protein hydrophobicity is required to explain patterns of mtDNA gene retention; a model that accounts for these selective pressures can also predict the success of artificial gene transfer experiments in vivo. This work provides a general method for data-driven inference of the ordering of evolutionary and progressive events, here identifying the distinct features shaping mitochondrial genomes of present-day species. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. An evolutionary model of bounded rationality and intelligence.

    Directory of Open Access Journals (Sweden)

    Thomas J Brennan

    Full Text Available BACKGROUND: Most economic theories are based on the premise that individuals maximize their own self-interest and correctly incorporate the structure of their environment into all decisions, thanks to human intelligence. The influence of this paradigm goes far beyond academia-it underlies current macroeconomic and monetary policies, and is also an integral part of existing financial regulations. However, there is mounting empirical and experimental evidence, including the recent financial crisis, suggesting that humans do not always behave rationally, but often make seemingly random and suboptimal decisions. METHODS AND FINDINGS: Here we propose to reconcile these contradictory perspectives by developing a simple binary-choice model that takes evolutionary consequences of decisions into account as well as the role of intelligence, which we define as any ability of an individual to increase its genetic success. If no intelligence is present, our model produces results consistent with prior literature and shows that risks that are independent across individuals in a generation generally lead to risk-neutral behaviors, but that risks that are correlated across a generation can lead to behaviors such as risk aversion, loss aversion, probability matching, and randomization. When intelligence is present the nature of risk also matters, and we show that even when risks are independent, either risk-neutral behavior or probability matching will occur depending upon the cost of intelligence in terms of reproductive success. In the case of correlated risks, we derive an implicit formula that shows how intelligence can emerge via selection, why it may be bounded, and how such bounds typically imply the coexistence of multiple levels and types of intelligence as a reflection of varying environmental conditions. CONCLUSIONS: Rational economic behavior in which individuals maximize their own self interest is only one of many possible types of behavior that

  4. An evolutionary model of bounded rationality and intelligence.

    Science.gov (United States)

    Brennan, Thomas J; Lo, Andrew W

    2012-01-01

    Most economic theories are based on the premise that individuals maximize their own self-interest and correctly incorporate the structure of their environment into all decisions, thanks to human intelligence. The influence of this paradigm goes far beyond academia-it underlies current macroeconomic and monetary policies, and is also an integral part of existing financial regulations. However, there is mounting empirical and experimental evidence, including the recent financial crisis, suggesting that humans do not always behave rationally, but often make seemingly random and suboptimal decisions. Here we propose to reconcile these contradictory perspectives by developing a simple binary-choice model that takes evolutionary consequences of decisions into account as well as the role of intelligence, which we define as any ability of an individual to increase its genetic success. If no intelligence is present, our model produces results consistent with prior literature and shows that risks that are independent across individuals in a generation generally lead to risk-neutral behaviors, but that risks that are correlated across a generation can lead to behaviors such as risk aversion, loss aversion, probability matching, and randomization. When intelligence is present the nature of risk also matters, and we show that even when risks are independent, either risk-neutral behavior or probability matching will occur depending upon the cost of intelligence in terms of reproductive success. In the case of correlated risks, we derive an implicit formula that shows how intelligence can emerge via selection, why it may be bounded, and how such bounds typically imply the coexistence of multiple levels and types of intelligence as a reflection of varying environmental conditions. Rational economic behavior in which individuals maximize their own self interest is only one of many possible types of behavior that arise from natural selection. The key to understanding which types of

  5. Model-Based Security Testing

    Directory of Open Access Journals (Sweden)

    Ina Schieferdecker

    2012-02-01

    Full Text Available Security testing aims at validating software system requirements related to security properties like confidentiality, integrity, authentication, authorization, availability, and non-repudiation. Although security testing techniques are available for many years, there has been little approaches that allow for specification of test cases at a higher level of abstraction, for enabling guidance on test identification and specification as well as for automated test generation. Model-based security testing (MBST is a relatively new field and especially dedicated to the systematic and efficient specification and documentation of security test objectives, security test cases and test suites, as well as to their automated or semi-automated generation. In particular, the combination of security modelling and test generation approaches is still a challenge in research and of high interest for industrial applications. MBST includes e.g. security functional testing, model-based fuzzing, risk- and threat-oriented testing, and the usage of security test patterns. This paper provides a survey on MBST techniques and the related models as well as samples of new methods and tools that are under development in the European ITEA2-project DIAMONDS.

  6. Fixation Time for Evolutionary Graphs

    Science.gov (United States)

    Nie, Pu-Yan; Zhang, Pei-Ai

    Evolutionary graph theory (EGT) is recently proposed by Lieberman et al. in 2005. EGT is successful for explaining biological evolution and some social phenomena. It is extremely important to consider the time of fixation for EGT in many practical problems, including evolutionary theory and the evolution of cooperation. This study characterizes the time to asymptotically reach fixation.

  7. The evolutionary reserve cell concept and model of cellular response induced by low doses of radiation

    International Nuclear Information System (INIS)

    Spitkovsky, D.M.; Talyzina, T.A.

    1995-01-01

    The model is based on the concept of programmed initiation of genetic damage in sub-populations of specific evolutionary reserve cells (ERC). The model quantitatively predicts a dose response of genetic lesions at low dose range and furnishes an explanation of the minimum observed in the dose-response curve at doses corresponding to one (on the average) event of energy deposition per ERC. The complex shape of the dose-response curve is demonstrated to result from superposition of processes in different sub-populations within the exposed cell population (at low doses mainly in ERC). Programmed initiation of genetic lesions in ERC requires two hits to cell membrane and probably, at the same time, to the cell nucleus. The equation for dicentric yield in human lymphocytes as a function of dose describes the experimental observations rather well. (Author)

  8. Selective modes determine evolutionary rates, gene compactness and expression patterns in Brassica.

    Science.gov (United States)

    Guo, Yue; Liu, Jing; Zhang, Jiefu; Liu, Shengyi; Du, Jianchang

    2017-07-01

    It has been well documented that most nuclear protein-coding genes in organisms can be classified into two categories: positively selected genes (PSGs) and negatively selected genes (NSGs). The characteristics and evolutionary fates of different types of genes, however, have been poorly understood. In this study, the rates of nonsynonymous substitution (K a ) and the rates of synonymous substitution (K s ) were investigated by comparing the orthologs between the two sequenced Brassica species, Brassica rapa and Brassica oleracea, and the evolutionary rates, gene structures, expression patterns, and codon bias were compared between PSGs and NSGs. The resulting data show that PSGs have higher protein evolutionary rates, lower synonymous substitution rates, shorter gene length, fewer exons, higher functional specificity, lower expression level, higher tissue-specific expression and stronger codon bias than NSGs. Although the quantities and values are different, the relative features of PSGs and NSGs have been largely verified in the model species Arabidopsis. These data suggest that PSGs and NSGs differ not only under selective pressure (K a /K s ), but also in their evolutionary, structural and functional properties, indicating that selective modes may serve as a determinant factor for measuring evolutionary rates, gene compactness and expression patterns in Brassica. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

  9. Evolutionary Relevance Facilitates Visual Information Processing

    Directory of Open Access Journals (Sweden)

    Russell E. Jackson

    2013-07-01

    Full Text Available Visual search of the environment is a fundamental human behavior that perceptual load affects powerfully. Previously investigated means for overcoming the inhibitions of high perceptual load, however, generalize poorly to real-world human behavior. We hypothesized that humans would process evolutionarily relevant stimuli more efficiently than evolutionarily novel stimuli, and evolutionary relevance would mitigate the repercussions of high perceptual load during visual search. Animacy is a significant component to evolutionary relevance of visual stimuli because perceiving animate entities is time-sensitive in ways that pose significant evolutionary consequences. Participants completing a visual search task located evolutionarily relevant and animate objects fastest and with the least impact of high perceptual load. Evolutionarily novel and inanimate objects were located slowest and with the highest impact of perceptual load. Evolutionary relevance may importantly affect everyday visual information processing.

  10. Multi-objective evolutionary optimisation for product design and manufacturing

    CERN Document Server

    2011-01-01

    Presents state-of-the-art research in the area of multi-objective evolutionary optimisation for integrated product design and manufacturing Provides a comprehensive review of the literature Gives in-depth descriptions of recently developed innovative and novel methodologies, algorithms and systems in the area of modelling, simulation and optimisation

  11. A Note on Evolutionary Algorithms and Its Applications

    Science.gov (United States)

    Bhargava, Shifali

    2013-01-01

    This paper introduces evolutionary algorithms with its applications in multi-objective optimization. Here elitist and non-elitist multiobjective evolutionary algorithms are discussed with their advantages and disadvantages. We also discuss constrained multiobjective evolutionary algorithms and their applications in various areas.

  12. Tracing evolutionary relicts of positive selection on eight malaria-related immune genes in mammals.

    Science.gov (United States)

    Huang, Bing-Hong; Liao, Pei-Chun

    2015-07-01

    Plasmodium-induced malaria widely infects primates and other mammals. Multiple past studies have revealed that positive selection could be the main evolutionary force triggering the genetic diversity of anti-malaria resistance-associated genes in human or primates. However, researchers focused most of their attention on the infra-generic and intra-specific genome evolution rather than analyzing the complete evolutionary history of mammals. Here we extend previous research by testing the evolutionary link of natural selection on eight candidate genes associated with malaria resistance in mammals. Three of the eight genes were detected to be affected by recombination, including TNF-α, iNOS and DARC. Positive selection was detected in the rest five immunogenes multiple times in different ancestral lineages of extant species throughout the mammalian evolution. Signals of positive selection were exposed in four malaria-related immunogenes in primates: CCL2, IL-10, HO1 and CD36. However, selection signals of G6PD have only been detected in non-primate eutherians. Significantly higher evolutionary rates and more radical amino acid replacement were also detected in primate CD36, suggesting its functional divergence from other eutherians. Prevalent positive selection throughout the evolutionary trajectory of mammalian malaria-related genes supports the arms race evolutionary hypothesis of host genetic response of mammalian immunogenes to infectious pathogens. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  13. Evolutionary optimization methods for accelerator design

    Science.gov (United States)

    Poklonskiy, Alexey A.

    Many problems from the fields of accelerator physics and beam theory can be formulated as optimization problems and, as such, solved using optimization methods. Despite growing efficiency of the optimization methods, the adoption of modern optimization techniques in these fields is rather limited. Evolutionary Algorithms (EAs) form a relatively new and actively developed optimization methods family. They possess many attractive features such as: ease of the implementation, modest requirements on the objective function, a good tolerance to noise, robustness, and the ability to perform a global search efficiently. In this work we study the application of EAs to problems from accelerator physics and beam theory. We review the most commonly used methods of unconstrained optimization and describe the GATool, evolutionary algorithm and the software package, used in this work, in detail. Then we use a set of test problems to assess its performance in terms of computational resources, quality of the obtained result, and the tradeoff between them. We justify the choice of GATool as a heuristic method to generate cutoff values for the COSY-GO rigorous global optimization package for the COSY Infinity scientific computing package. We design the model of their mutual interaction and demonstrate that the quality of the result obtained by GATool increases as the information about the search domain is refined, which supports the usefulness of this model. We Giscuss GATool's performance on the problems suffering from static and dynamic noise and study useful strategies of GATool parameter tuning for these and other difficult problems. We review the challenges of constrained optimization with EAs and methods commonly used to overcome them. We describe REPA, a new constrained optimization method based on repairing, in exquisite detail, including the properties of its two repairing techniques: REFIND and REPROPT. We assess REPROPT's performance on the standard constrained

  14. Evolutionary Computing Methods for Spectral Retrieval

    Science.gov (United States)

    Terrile, Richard; Fink, Wolfgang; Huntsberger, Terrance; Lee, Seugwon; Tisdale, Edwin; VonAllmen, Paul; Tinetti, Geivanna

    2009-01-01

    A methodology for processing spectral images to retrieve information on underlying physical, chemical, and/or biological phenomena is based on evolutionary and related computational methods implemented in software. In a typical case, the solution (the information that one seeks to retrieve) consists of parameters of a mathematical model that represents one or more of the phenomena of interest. The methodology was developed for the initial purpose of retrieving the desired information from spectral image data acquired by remote-sensing instruments aimed at planets (including the Earth). Examples of information desired in such applications include trace gas concentrations, temperature profiles, surface types, day/night fractions, cloud/aerosol fractions, seasons, and viewing angles. The methodology is also potentially useful for retrieving information on chemical and/or biological hazards in terrestrial settings. In this methodology, one utilizes an iterative process that minimizes a fitness function indicative of the degree of dissimilarity between observed and synthetic spectral and angular data. The evolutionary computing methods that lie at the heart of this process yield a population of solutions (sets of the desired parameters) within an accuracy represented by a fitness-function value specified by the user. The evolutionary computing methods (ECM) used in this methodology are Genetic Algorithms and Simulated Annealing, both of which are well-established optimization techniques and have also been described in previous NASA Tech Briefs articles. These are embedded in a conceptual framework, represented in the architecture of the implementing software, that enables automatic retrieval of spectral and angular data and analysis of the retrieved solutions for uniqueness.

  15. Applied evolutionary economics and economic geography

    NARCIS (Netherlands)

    Frenken, K.

    2007-01-01

    Applied Evolutionary Economics and Economic Geography" aims to further advance empirical methodologies in evolutionary economics, with a special emphasis on geography and firm location. It does so by bringing together a select group of leading scholars including economists, geographers and

  16. Diversity-Guided Evolutionary Algorithms

    DEFF Research Database (Denmark)

    Ursem, Rasmus Kjær

    2002-01-01

    Population diversity is undoubtably a key issue in the performance of evolutionary algorithms. A common hypothesis is that high diversity is important to avoid premature convergence and to escape local optima. Various diversity measures have been used to analyze algorithms, but so far few...... algorithms have used a measure to guide the search. The diversity-guided evolutionary algorithm (DGEA) uses the wellknown distance-to-average-point measure to alternate between phases of exploration (mutation) and phases of exploitation (recombination and selection). The DGEA showed remarkable results...

  17. Stars with shell energy sources. Part 1. Special evolutionary code

    International Nuclear Information System (INIS)

    Rozyczka, M.

    1977-01-01

    A new version of the Henyey-type stellar evolution code is described and tested. It is shown, as a by-product of the tests, that the thermal time scale of the core of a red giant approaching the helium flash is of the order of the evolutionary time scale. The code itself appears to be a very efficient tool for investigations of the helium flash, carbon flash and the evolution of a white dwarf accreting mass. (author)

  18. Do Test Design and Uses Influence Test Preparation? Testing a Model of Washback with Structural Equation Modeling

    Science.gov (United States)

    Xie, Qin; Andrews, Stephen

    2013-01-01

    This study introduces Expectancy-value motivation theory to explain the paths of influences from perceptions of test design and uses to test preparation as a special case of washback on learning. Based on this theory, two conceptual models were proposed and tested via Structural Equation Modeling. Data collection involved over 870 test takers of…

  19. Evolutionary analyses of non-genealogical bonds produced by introgressive descent.

    Science.gov (United States)

    Bapteste, Eric; Lopez, Philippe; Bouchard, Frédéric; Baquero, Fernando; McInerney, James O; Burian, Richard M

    2012-11-06

    All evolutionary biologists are familiar with evolutionary units that evolve by vertical descent in a tree-like fashion in single lineages. However, many other kinds of processes contribute to evolutionary diversity. In vertical descent, the genetic material of a particular evolutionary unit is propagated by replication inside its own lineage. In what we call introgressive descent, the genetic material of a particular evolutionary unit propagates into different host structures and is replicated within these host structures. Thus, introgressive descent generates a variety of evolutionary units and leaves recognizable patterns in resemblance networks. We characterize six kinds of evolutionary units, of which five involve mosaic lineages generated by introgressive descent. To facilitate detection of these units in resemblance networks, we introduce terminology based on two notions, P3s (subgraphs of three nodes: A, B, and C) and mosaic P3s, and suggest an apparatus for systematic detection of introgressive descent. Mosaic P3s correspond to a distinct type of evolutionary bond that is orthogonal to the bonds of kinship and genealogy usually examined by evolutionary biologists. We argue that recognition of these evolutionary bonds stimulates radical rethinking of key questions in evolutionary biology (e.g., the relations among evolutionary players in very early phases of evolutionary history, the origin and emergence of novelties, and the production of new lineages). This line of research will expand the study of biological complexity beyond the usual genealogical bonds, revealing additional sources of biodiversity. It provides an important step to a more realistic pluralist treatment of evolutionary complexity.

  20. A new chronostratigraphical and evolutionary model for La Gomera: Implications for the overall evolution of the Canarian Archipelago

    OpenAIRE

    Ancochea Soto, Eumenio; Hernán, F.; Huertas Coronel, María José; Brandle, J.L.; Herrera, R.

    2006-01-01

    A review of the general volcano-stratigraphy and geochronology of La Gomera, one of the lesser known Canary Islands, has led to the establishment of a new evolutionary model. The oldest edifice corresponds to the submarine stage built up between 20 and 15 Ma. The construction of the Submarine Edifice was followed by an important break in the activity (about 4 Ma) and deep erosion of the edifice. About 10.5 Ma ago, the main present-day edifice (the Old Edifice 10.5–6.4 Ma) emerged, which was a...

  1. Convergence of Residential Gateway technology: analysis of evolutionary paths

    NARCIS (Netherlands)

    Hartog, den F.T.H.; Balm, M.; Jong, de C.M.; Kwaaitaal, J.J.B.

    2004-01-01

    A new OSI (Open Systems Interconnection)-based model is described that can be used for the classification of residential gateways (RG). It is applied to analyze current gateway solutions and to draw evolutionary paths for the mid-to-long term. It is concluded that set-top boxes and broadband modems

  2. An Evolutionary Algorithm for Multiobjective Fuzzy Portfolio Selection Models with Transaction Cost and Liquidity

    Directory of Open Access Journals (Sweden)

    Wei Yue

    2015-01-01

    Full Text Available The major issues for mean-variance-skewness models are the errors in estimations that cause corner solutions and low diversity in the portfolio. In this paper, a multiobjective fuzzy portfolio selection model with transaction cost and liquidity is proposed to maintain the diversity of portfolio. In addition, we have designed a multiobjective evolutionary algorithm based on decomposition of the objective space to maintain the diversity of obtained solutions. The algorithm is used to obtain a set of Pareto-optimal portfolios with good diversity and convergence. To demonstrate the effectiveness of the proposed model and algorithm, the performance of the proposed algorithm is compared with the classic MOEA/D and NSGA-II through some numerical examples based on the data of the Shanghai Stock Exchange Market. Simulation results show that our proposed algorithm is able to obtain better diversity and more evenly distributed Pareto front than the other two algorithms and the proposed model can maintain quite well the diversity of portfolio. The purpose of this paper is to deal with portfolio problems in the weighted possibilistic mean-variance-skewness (MVS and possibilistic mean-variance-skewness-entropy (MVS-E frameworks with transaction cost and liquidity and to provide different Pareto-optimal investment strategies as diversified as possible for investors at a time, rather than one strategy for investors at a time.

  3. Interpreting Evolutionary Diagrams: When Topology and Process Conflict

    Science.gov (United States)

    Catley, Kefyn M.; Novick, Laura R.; Shade, Courtney K.

    2010-01-01

    The authors argue that some diagrams in biology textbooks and the popular press presented as depicting evolutionary relationships suggest an inappropriate (anagenic) conception of evolutionary history. The goal of this research was to provide baseline data that begin to document how college students conceptualize the evolutionary relationships…

  4. Evolutionary signals of symbiotic persistence in the legume-rhizobia mutualism.

    Science.gov (United States)

    Werner, Gijsbert D A; Cornwell, William K; Cornelissen, Johannes H C; Kiers, E Toby

    2015-08-18

    Understanding the origins and evolutionary trajectories of symbiotic partnerships remains a major challenge. Why are some symbioses lost over evolutionary time whereas others become crucial for survival? Here, we use a quantitative trait reconstruction method to characterize different evolutionary stages in the ancient symbiosis between legumes (Fabaceae) and nitrogen-fixing bacteria, asking how labile is symbiosis across different host clades. We find that more than half of the 1,195 extant nodulating legumes analyzed have a high likelihood (>95%) of being in a state of high symbiotic persistence, meaning that they show a continued capacity to form the symbiosis over evolutionary time, even though the partnership has remained facultative and is not obligate. To explore patterns associated with the likelihood of loss and retention of the N2-fixing symbiosis, we tested for correlations between symbiotic persistence and legume distribution, climate, soil and trait data. We found a strong latitudinal effect and demonstrated that low mean annual temperatures are associated with high symbiotic persistence in legumes. Although no significant correlations between soil variables and symbiotic persistence were found, nitrogen and phosphorus leaf contents were positively correlated with legumes in a state of high symbiotic persistence. This pattern suggests that highly demanding nutrient lifestyles are associated with more stable partnerships, potentially because they "lock" the hosts into symbiotic dependency. Quantitative reconstruction methods are emerging as a powerful comparative tool to study broad patterns of symbiont loss and retention across diverse partnerships.

  5. Evolutionary signals of symbiotic persistence in the legume–rhizobia mutualism

    Science.gov (United States)

    Werner, Gijsbert D. A.; Cornwell, William K.; Cornelissen, Johannes H. C.; Kiers, E. Toby

    2015-01-01

    Understanding the origins and evolutionary trajectories of symbiotic partnerships remains a major challenge. Why are some symbioses lost over evolutionary time whereas others become crucial for survival? Here, we use a quantitative trait reconstruction method to characterize different evolutionary stages in the ancient symbiosis between legumes (Fabaceae) and nitrogen-fixing bacteria, asking how labile is symbiosis across different host clades. We find that more than half of the 1,195 extant nodulating legumes analyzed have a high likelihood (>95%) of being in a state of high symbiotic persistence, meaning that they show a continued capacity to form the symbiosis over evolutionary time, even though the partnership has remained facultative and is not obligate. To explore patterns associated with the likelihood of loss and retention of the N2-fixing symbiosis, we tested for correlations between symbiotic persistence and legume distribution, climate, soil and trait data. We found a strong latitudinal effect and demonstrated that low mean annual temperatures are associated with high symbiotic persistence in legumes. Although no significant correlations between soil variables and symbiotic persistence were found, nitrogen and phosphorus leaf contents were positively correlated with legumes in a state of high symbiotic persistence. This pattern suggests that highly demanding nutrient lifestyles are associated with more stable partnerships, potentially because they “lock” the hosts into symbiotic dependency. Quantitative reconstruction methods are emerging as a powerful comparative tool to study broad patterns of symbiont loss and retention across diverse partnerships. PMID:26041807

  6. Evolutionary engineering of industrial microorganisms-strategies and applications.

    Science.gov (United States)

    Zhu, Zhengming; Zhang, Juan; Ji, Xiaomei; Fang, Zhen; Wu, Zhimeng; Chen, Jian; Du, Guocheng

    2018-06-01

    Microbial cells have been widely used in the industry to obtain various biochemical products, and evolutionary engineering is a common method in biological research to improve their traits, such as high environmental tolerance and improvement of product yield. To obtain better integrate functions of microbial cells, evolutionary engineering combined with other biotechnologies have attracted more attention in recent years. Classical laboratory evolution has been proven effective to letting more beneficial mutations occur in different genes but also has some inherent limitations such as a long evolutionary period and uncontrolled mutation frequencies. However, recent studies showed that some new strategies may gradually overcome these limitations. In this review, we summarize the evolutionary strategies commonly used in industrial microorganisms and discuss the combination of evolutionary engineering with other biotechnologies such as systems biology and inverse metabolic engineering. Finally, we prospect the importance and application prospect of evolutionary engineering as a powerful tool especially in optimization of industrial microbial cell factories.

  7. Use of multiple objective evolutionary algorithms in optimizing surveillance requirements

    International Nuclear Information System (INIS)

    Martorell, S.; Carlos, S.; Villanueva, J.F.; Sanchez, A.I; Galvan, B.; Salazar, D.; Cepin, M.

    2006-01-01

    This paper presents the development and application of a double-loop Multiple Objective Evolutionary Algorithm that uses a Multiple Objective Genetic Algorithm to perform the simultaneous optimization of periodic Test Intervals (TI) and Test Planning (TP). It takes into account the time-dependent effect of TP performed on stand-by safety-related equipment. TI and TP are part of the Surveillance Requirements within Technical Specifications at Nuclear Power Plants. It addresses the problem of multi-objective optimization in the space of dependable variables, i.e. TI and TP, using a novel flexible structure of the optimization algorithm. Lessons learnt from the cases of application of the methodology to optimize TI and TP for the High-Pressure Injection System are given. The results show that the double-loop Multiple Objective Evolutionary Algorithm is able to find the Pareto set of solutions that represents a surface of non-dominated solutions that satisfy all the constraints imposed on the objective functions and decision variables. Decision makers can adopt then the best solution found depending on their particular preference, e.g. minimum cost, minimum unavailability

  8. Markov Networks in Evolutionary Computation

    CERN Document Server

    Shakya, Siddhartha

    2012-01-01

    Markov networks and other probabilistic graphical modes have recently received an upsurge in attention from Evolutionary computation community, particularly in the area of Estimation of distribution algorithms (EDAs).  EDAs have arisen as one of the most successful experiences in the application of machine learning methods in optimization, mainly due to their efficiency to solve complex real-world optimization problems and their suitability for theoretical analysis. This book focuses on the different steps involved in the conception, implementation and application of EDAs that use Markov networks, and undirected models in general. It can serve as a general introduction to EDAs but covers also an important current void in the study of these algorithms by explaining the specificities and benefits of modeling optimization problems by means of undirected probabilistic models. All major developments to date in the progressive introduction of Markov networks based EDAs are reviewed in the book. Hot current researc...

  9. Evolutionary theory and the naturalist fallacy

    DEFF Research Database (Denmark)

    Grodal, Torben Kragh

    2008-01-01

    that great work of art are also automatically fitness-enhancing in the present day environment, at that there are simple correllations between whether a work of art has a high aesthetic value and whether it is fitness-enhancing or not.  Keywords :  Evolutionary aesthetics, film theory, literary theory......The article is an invited response to a target article by Joseph Carroll entitled "An evolutionary paradigm for literary study". It argues that the target article  misuse the fact that works of art are based on adaptations that were fitness-enhancing in the era of evolutionary adaptations to claim...

  10. A teleofunctional account of evolutionary mismatch.

    Science.gov (United States)

    Cofnas, Nathan

    When the environment in which an organism lives deviates in some essential way from that to which it is adapted, this is described as "evolutionary mismatch," or "evolutionary novelty." The notion of mismatch plays an important role, explicitly or implicitly, in evolution-informed cognitive psychology, clinical psychology, and medicine. The evolutionary novelty of our contemporary environment is thought to have significant implications for our health and well-being. However, scientists have generally been working without a clear definition of mismatch. This paper defines mismatch as deviations in the environment that render biological traits unable, or impaired in their ability, to produce their selected effects (i.e., to perform their proper functions in Neander's sense). The machinery developed by Millikan in connection with her account of proper function, and with her related teleosemantic account of representation, is used to identify four major types, and several subtypes, of evolutionary mismatch. While the taxonomy offered here does not in itself resolve any scientific debates, the hope is that it can be used to better formulate empirical hypotheses concerning the effects of mismatch. To illustrate, it is used to show that the controversial hypothesis that general intelligence evolved as an adaptation to handle evolutionary novelty can, contra some critics, be formulated in a conceptually coherent way.

  11. Evolutionary cell biology: two origins, one objective.

    Science.gov (United States)

    Lynch, Michael; Field, Mark C; Goodson, Holly V; Malik, Harmit S; Pereira-Leal, José B; Roos, David S; Turkewitz, Aaron P; Sazer, Shelley

    2014-12-02

    All aspects of biological diversification ultimately trace to evolutionary modifications at the cellular level. This central role of cells frames the basic questions as to how cells work and how cells come to be the way they are. Although these two lines of inquiry lie respectively within the traditional provenance of cell biology and evolutionary biology, a comprehensive synthesis of evolutionary and cell-biological thinking is lacking. We define evolutionary cell biology as the fusion of these two eponymous fields with the theoretical and quantitative branches of biochemistry, biophysics, and population genetics. The key goals are to develop a mechanistic understanding of general evolutionary processes, while specifically infusing cell biology with an evolutionary perspective. The full development of this interdisciplinary field has the potential to solve numerous problems in diverse areas of biology, including the degree to which selection, effectively neutral processes, historical contingencies, and/or constraints at the chemical and biophysical levels dictate patterns of variation for intracellular features. These problems can now be examined at both the within- and among-species levels, with single-cell methodologies even allowing quantification of variation within genotypes. Some results from this emerging field have already had a substantial impact on cell biology, and future findings will significantly influence applications in agriculture, medicine, environmental science, and synthetic biology.

  12. An evolutionary perspective on drug discovery in the plant genus Euphorbia L. (Euphorbiaceae)

    DEFF Research Database (Denmark)

    Ernst, Madeleine

    herbivory and physical stresses or to attract pollinators. Consequently, specializedmetabolites, as well as plants used in traditional medicine, are not randomly distributed across phylogenetictrees. Evolutionary approaches to plant-based drug discovery suggest that this informationcan be used to guide...... healthcarethreats, urge for systematic and time-efficient approaches in finding new drug candidates. Manydrugs are derived from plant specialized metabolites, chemical compounds, which are synthesizedby the plants in response to evolutionary adaptation to environmental and ecological factors, for example,to combat...... evolution and diversification. Also, Euphorbia species producean often chemically highly diverse latex exhibiting an exceptional number of biological activities withpharmaceutical interest. In this PhD project, the genus Euphorbia was chosen as a model group forstudying evolutionary approaches to plant...

  13. How to Identify and Interpret Evolutionary Tree Diagrams

    Science.gov (United States)

    Kong, Yi; Anderson, Trevor; Pelaez, Nancy

    2016-01-01

    Evolutionary trees are key tools for modern biology and are commonly portrayed in textbooks to promote learning about biological evolution. However, many people have difficulty in understanding what evolutionary trees are meant to portray. In fact, some ideas that current professional biologists depict with evolutionary trees are neither clearly…

  14. An evolutionary perspective on anti-tumor immunity

    Directory of Open Access Journals (Sweden)

    David John Klinke

    2013-01-01

    Full Text Available The challenges associated with demonstrating a durable response using molecular targeted therapies in cancer has sparked a renewed interest in viewing cancer from an evolutionary perspective. Evolutionary processes have three common traits: heterogeneity, dynamics, and a selective fitness landscape. Mutagens randomly alter the genome of host cells creating a population of cells that contain different somatic mutations. This genomic rearrangement perturbs cellular homeostasis through changing how cells interact with their tissue microenvironment. To counterbalance the ability of mutated cells to outcompete for limited resources, control structures are encoded within the cell and within the organ system, such as innate and adaptive immunity, to restore cellular homeostasis. These control structures shape the selective fitness landscape and determine whether a cell that harbors particular somatic mutations is retained or eliminated from a cell population. While next-generation sequencing has revealed the complexity and heterogeneity of oncogenic transformation, understanding the dynamics of oncogenesis and how cancer cells alter the selective fitness landscape remain unclear. In this technology review, we will summarize how recent advances in technology have impacted our understanding of these three attributes of cancer as an evolutionary process. In particular, we will focus on how advances in genome sequencing have enabled quantifying cellular heterogeneity, advances in computational power have enabled explicit testing of postulated intra- and intercellular control structures against the available data using simulation, and advances in proteomics have enabled identifying novel mechanisms of cellular cross-talk that cancer cells use to alter the fitness landscape.

  15. Evolutionary potential games on lattices

    Energy Technology Data Exchange (ETDEWEB)

    Szabó, György, E-mail: szabo@mfa.kfki.hu; Borsos, István, E-mail: borsos@mfa.kfki.hu

    2016-04-05

    Game theory provides a general mathematical background to study the effect of pair interactions and evolutionary rules on the macroscopic behavior of multi-player games where players with a finite number of strategies may represent a wide scale of biological objects, human individuals, or even their associations. In these systems the interactions are characterized by matrices that can be decomposed into elementary matrices (games) and classified into four types. The concept of decomposition helps the identification of potential games and also the evaluation of the potential that plays a crucial role in the determination of the preferred Nash equilibrium, and defines the Boltzmann distribution towards which these systems evolve for suitable types of dynamical rules. This survey draws parallel between the potential games and the kinetic Ising type models which are investigated for a wide scale of connectivity structures. We discuss briefly the applicability of the tools and concepts of statistical physics and thermodynamics. Additionally the general features of ordering phenomena, phase transitions and slow relaxations are outlined and applied to evolutionary games. The discussion extends to games with three or more strategies. Finally we discuss what happens when the system is weakly driven out of the “equilibrium state” by adding non-potential components representing games of cyclic dominance.

  16. Evolutionary potential games on lattices

    International Nuclear Information System (INIS)

    Szabó, György; Borsos, István

    2016-01-01

    Game theory provides a general mathematical background to study the effect of pair interactions and evolutionary rules on the macroscopic behavior of multi-player games where players with a finite number of strategies may represent a wide scale of biological objects, human individuals, or even their associations. In these systems the interactions are characterized by matrices that can be decomposed into elementary matrices (games) and classified into four types. The concept of decomposition helps the identification of potential games and also the evaluation of the potential that plays a crucial role in the determination of the preferred Nash equilibrium, and defines the Boltzmann distribution towards which these systems evolve for suitable types of dynamical rules. This survey draws parallel between the potential games and the kinetic Ising type models which are investigated for a wide scale of connectivity structures. We discuss briefly the applicability of the tools and concepts of statistical physics and thermodynamics. Additionally the general features of ordering phenomena, phase transitions and slow relaxations are outlined and applied to evolutionary games. The discussion extends to games with three or more strategies. Finally we discuss what happens when the system is weakly driven out of the “equilibrium state” by adding non-potential components representing games of cyclic dominance.

  17. Evolutionary potential games on lattices

    Science.gov (United States)

    Szabó, György; Borsos, István

    2016-04-01

    Game theory provides a general mathematical background to study the effect of pair interactions and evolutionary rules on the macroscopic behavior of multi-player games where players with a finite number of strategies may represent a wide scale of biological objects, human individuals, or even their associations. In these systems the interactions are characterized by matrices that can be decomposed into elementary matrices (games) and classified into four types. The concept of decomposition helps the identification of potential games and also the evaluation of the potential that plays a crucial role in the determination of the preferred Nash equilibrium, and defines the Boltzmann distribution towards which these systems evolve for suitable types of dynamical rules. This survey draws parallel between the potential games and the kinetic Ising type models which are investigated for a wide scale of connectivity structures. We discuss briefly the applicability of the tools and concepts of statistical physics and thermodynamics. Additionally the general features of ordering phenomena, phase transitions and slow relaxations are outlined and applied to evolutionary games. The discussion extends to games with three or more strategies. Finally we discuss what happens when the system is weakly driven out of the "equilibrium state" by adding non-potential components representing games of cyclic dominance.

  18. Evolutionary biology of bacterial and fungal pathogens

    National Research Council Canada - National Science Library

    Baquero, F

    2008-01-01

    ... and Evolutionary Dynamics of Pathogens * 21 Keith A. Crandall and Marcos Pérez-Losada II. Evolutionary Genetics of Microbial Pathogens 4. Environmental and Social Influences on Infectious Disea...

  19. An evolutionary framework for the Jovian and Saturnian satellites

    International Nuclear Information System (INIS)

    Stevenson, R.J.

    1987-01-01

    The position of the satellite within the protonebula, the influence of the parent planet, particularly the relative effects of tidal (gravitational) as opposed to radiogenic (internal) heat generating processes, as well as the type of ice, exert a control on the evolutionary histories of the Jovian and Saturnian satellites. The landscapes of the moons are modified by surface deformational processes (tectonic activity derived from within the body) and externally derived cratering. The geological history of the Galilean satellites is deduced from surface stratigraphic successions of geological units. Io and Europa, with crater-free surfaces, are tectonically more advanced than crater-saturated Callisto. Two thermal-drive models are proposed based on: an expression for externally derived gravitational influences between two bodies; and internal heat generation via radiogenic decay (expressed by surface area/volume ratio). Both parameters, for the Galilean satellites, are plotted against an inferred product of tectonic processes - the age of the surface terrain. From these diagrams, the tectonic evolutionary state of the more distant Saturnian system are predicted. These moons are fitted into an evolutionary framework for the Solar System. 34 refs.; 4 figs.; 2 tabs

  20. Regional systems of innovation: an evolutionary perspective

    OpenAIRE

    P Cooke; M G Uranga; G Etxebarria

    1998-01-01

    The authors develop the concept of regional systems of innovation and relate it to preexisting research on national systems of innovation. They argue that work conducted in the 'new regional science' field is complementary to systems of innovation approaches. They seek to link new regional work to evolutionary economics, and argue for the development of evolutionary regional science. Common elements of interest to evolutionary innovation research and new regional science are important in unde...

  1. Research on Information Sharing Mechanism of Network Organization Based on Evolutionary Game

    Science.gov (United States)

    Wang, Lin; Liu, Gaozhi

    2018-02-01

    This article first elaborates the concept and effect of network organization, and the ability to share information is analyzed, secondly introduces the evolutionary game theory, network organization for information sharing all kinds of limitations, establishes the evolutionary game model, analyzes the dynamic evolution of network organization of information sharing, through reasoning and evolution. The network information sharing by the initial state and two sides of the game payoff matrix of excess profits and information is the information sharing of cost and risk sharing are the influence of network organization node information sharing decision.

  2. Evolutionary tracks of the terrestrial planets

    International Nuclear Information System (INIS)

    Matsui, Takafumi; Abe, Yutaka

    1987-01-01

    On the basis of the model proposed by Matsui and Abe, the authors show that two major factors - distance from the Sun and the efficiency of retention of accretional energy - control the early evolution of the terrestrial planets. A diagram of accretional energy versus the optical depth of a proto-atmosphere provides a means to follow the evolutionary track of surface temperature of the terrestrial planets and an explanation for why the third planet in our solar system is an 'aqua'-planet. 15 refs; 3 figs

  3. Evolutionary robotics

    Indian Academy of Sciences (India)

    In evolutionary robotics, a suitable robot control system is developed automatically through evolution due to the interactions between the robot and its environment. It is a complicated task, as the robot and the environment constitute a highly dynamical system. Several methods have been tried by various investigators to ...

  4. Connecting proximate mechanisms and evolutionary patterns: pituitary gland size and mammalian life history.

    Science.gov (United States)

    Kamilar, J M; Tecot, S R

    2015-11-01

    At the proximate level, hormones are known to play a critical role in influencing the life history of mammals, including humans. The pituitary gland is directly responsible for producing several hormones, including those related to growth and reproduction. Although we have a basic understanding of how hormones affect life history characteristics, we still have little knowledge of this relationship in an evolutionary context. We used data from 129 mammal species representing 14 orders to investigate the relationship between pituitary gland size and life history variation. Because pituitary gland size should be related to hormone production and action, we predicted that species with relatively large pituitaries should be associated with fast life histories, especially increased foetal and post-natal growth rates. Phylogenetic analyses revealed that total pituitary size and the size of the anterior lobe of the pituitary significantly predicted a life history axis that was correlated with several traits including body mass, and foetal and post-natal growth rates. Additional models directly examining the association between relative pituitary size and growth rates produced concordant results. We also found that relative pituitary size variation across mammals was best explained by an Ornstein-Uhlenbeck model of evolution, suggesting an important role of stabilizing selection. Our results support the idea that the size of the pituitary is linked to life history variation through evolutionary time. This pattern is likely due to mediating hormone levels but additional work is needed. We suggest that future investigations incorporating endocrine gland size may be critical for understanding life history evolution. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

  5. Tracing the evolutionary origin of vertebrate skeletal tissues: insights from cephalochordate amphioxus.

    Science.gov (United States)

    Yong, Luok Wen; Yu, Jr-Kai

    2016-08-01

    Vertebrate mineralized skeletal tissues are widely considered as an evolutionary novelty. Despite the importance of these tissues to the adaptation and radiation of vertebrate animals, the evolutionary origin of vertebrate skeletal tissues remains largely unclear. Cephalochordates (Amphioxus) occupy a key phylogenetic position and can serve as a valuable model for studying the evolution of vertebrate skeletal tissues. Here we summarize recent advances in amphioxus developmental biology and comparative genomics that can help to elucidate the evolutionary origins of the vertebrate skeletal tissues and their underlying developmental gene regulatory networks (GRN). By making comparisons to the developmental studies in vertebrate models and recent discoveries in paleontology and genomics, it becomes evident that the collagen matrix-based connective tissues secreted by the somite-derived cells in amphioxus likely represent the rudimentary skeletal tissues in chordates. We propose that upon the foundation of this collagenous precursor, novel tissue mineralization genes that arose from gene duplications were incorporated into an ancestral mesodermal GRN that makes connective and supporting tissues, leading to the emergence of highly-mineralized skeletal tissues in early vertebrates. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Loglinear Rasch model tests

    NARCIS (Netherlands)

    Kelderman, Hendrikus

    1984-01-01

    Existing statistical tests for the fit of the Rasch model have been criticized, because they are only sensitive to specific violations of its assumptions. Contingency table methods using loglinear models have been used to test various psychometric models. In this paper, the assumptions of the Rasch

  7. Mismatch between ectotherm thermal preferenda and optima for swimming: a test of the evolutionary pace hypothesis

    Czech Academy of Sciences Publication Activity Database

    Gvoždík, Lumír

    2015-01-01

    Roč. 42, č. 2 (2015), s. 137-145 ISSN 0071-3260 R&D Projects: GA ČR GAP506/10/2170 Institutional support: RVO:68081766 Keywords : Amphibia * Coadaptation * Evolutionary rates * Newts * Preferred body temperatures * Thermal performance curves * Thermal sensitivity Subject RIV: EG - Zoology Impact factor: 2.267, year: 2015

  8. Evolutionary impact assessment: accounting for evolutionary consequences of fishing in an ecosystem approach to fisheries management.

    Science.gov (United States)

    Laugen, Ane T; Engelhard, Georg H; Whitlock, Rebecca; Arlinghaus, Robert; Dankel, Dorothy J; Dunlop, Erin S; Eikeset, Anne M; Enberg, Katja; Jørgensen, Christian; Matsumura, Shuichi; Nusslé, Sébastien; Urbach, Davnah; Baulier, Loїc; Boukal, David S; Ernande, Bruno; Johnston, Fiona D; Mollet, Fabian; Pardoe, Heidi; Therkildsen, Nina O; Uusi-Heikkilä, Silva; Vainikka, Anssi; Heino, Mikko; Rijnsdorp, Adriaan D; Dieckmann, Ulf

    2014-03-01

    Managing fisheries resources to maintain healthy ecosystems is one of the main goals of the ecosystem approach to fisheries (EAF). While a number of international treaties call for the implementation of EAF, there are still gaps in the underlying methodology. One aspect that has received substantial scientific attention recently is fisheries-induced evolution (FIE). Increasing evidence indicates that intensive fishing has the potential to exert strong directional selection on life-history traits, behaviour, physiology, and morphology of exploited fish. Of particular concern is that reversing evolutionary responses to fishing can be much more difficult than reversing demographic or phenotypically plastic responses. Furthermore, like climate change, multiple agents cause FIE, with effects accumulating over time. Consequently, FIE may alter the utility derived from fish stocks, which in turn can modify the monetary value living aquatic resources provide to society. Quantifying and predicting the evolutionary effects of fishing is therefore important for both ecological and economic reasons. An important reason this is not happening is the lack of an appropriate assessment framework. We therefore describe the evolutionary impact assessment (EvoIA) as a structured approach for assessing the evolutionary consequences of fishing and evaluating the predicted evolutionary outcomes of alternative management options. EvoIA can contribute to EAF by clarifying how evolution may alter stock properties and ecological relations, support the precautionary approach to fisheries management by addressing a previously overlooked source of uncertainty and risk, and thus contribute to sustainable fisheries.

  9. Integrating Evolutionary Game Theory into Mechanistic Genotype-Phenotype Mapping.

    Science.gov (United States)

    Zhu, Xuli; Jiang, Libo; Ye, Meixia; Sun, Lidan; Gragnoli, Claudia; Wu, Rongling

    2016-05-01

    Natural selection has shaped the evolution of organisms toward optimizing their structural and functional design. However, how this universal principle can enhance genotype-phenotype mapping of quantitative traits has remained unexplored. Here we show that the integration of this principle and functional mapping through evolutionary game theory gains new insight into the genetic architecture of complex traits. By viewing phenotype formation as an evolutionary system, we formulate mathematical equations to model the ecological mechanisms that drive the interaction and coordination of its constituent components toward population dynamics and stability. Functional mapping provides a procedure for estimating the genetic parameters that specify the dynamic relationship of competition and cooperation and predicting how genes mediate the evolution of this relationship during trait formation. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Evolution of Cooperation in Evolutionary Games for Heterogeneous Interactions

    International Nuclear Information System (INIS)

    Qian Xiaolan; Yang Junzhong

    2012-01-01

    When a population structure is modelled as a square lattice, the cooperation may be improved for an evolutionary prisoner dilemma game or be inhibited for an evolutionary snowdrift game. In this work, we investigate cooperation in a population on a square lattice where the interaction among players contains both prisoner dilemma game and snowdrift game. The heterogeneity in interaction is introduced to the population in two different ways: the heterogenous character of interaction assigned to every player (HCP) or the heterogenous character of interaction assigned to every link between any two players (HCL). The resonant enhancement of cooperation in the case of HCP is observed while the resonant inhibition of cooperation in the case of HCL is prominent. The explanations on the enhancement or inhibition of cooperation are presented for these two cases. (general)

  11. Co-existence of multiple trade-off currencies shapes evolutionary outcomes.

    Directory of Open Access Journals (Sweden)

    Alan A Cohen

    Full Text Available Evolutionary studies often assume that energy is the primary resource (i.e. "currency" at the heart of the survival-reproduction trade-off, despite recent evidence to the contrary. The evolutionary consequences of having a single trade-off currency versus multiple competing currencies are unknown. Using simulations, we modeled the evolution of either a single physiological currency between reproduction and survival, or of multiple such currencies. For a wide array of model specifications varying functional forms and strengths of the trade-offs, we show that the presence of multiple currencies (e.g. nutrients, time generally results in the evolution of higher lifetime reproductive success through partial circumvention of such trade-offs. Evolution of the underlying physiology is also more highly contingent with multiple currencies. These results challenge the paradigm of a single survival-reproduction trade-off as central to life history evolution, suggesting greater roles for physiological constraints and contingency, and implying potential selection for evolution of multiple trade-off currencies.

  12. Co-existence of multiple trade-off currencies shapes evolutionary outcomes

    Science.gov (United States)

    Isaksson, Caroline; Salguero-Gómez, Roberto

    2017-01-01

    Evolutionary studies often assume that energy is the primary resource (i.e. “currency”) at the heart of the survival-reproduction trade-off, despite recent evidence to the contrary. The evolutionary consequences of having a single trade-off currency versus multiple competing currencies are unknown. Using simulations, we modeled the evolution of either a single physiological currency between reproduction and survival, or of multiple such currencies. For a wide array of model specifications varying functional forms and strengths of the trade-offs, we show that the presence of multiple currencies (e.g. nutrients, time) generally results in the evolution of higher lifetime reproductive success through partial circumvention of such trade-offs. Evolution of the underlying physiology is also more highly contingent with multiple currencies. These results challenge the paradigm of a single survival-reproduction trade-off as central to life history evolution, suggesting greater roles for physiological constraints and contingency, and implying potential selection for evolution of multiple trade-off currencies. PMID:29216275

  13. Freud: the first evolutionary psychologist?

    Science.gov (United States)

    LeCroy, D

    2000-04-01

    An evolutionary perspective on attachment theory and psychoanalytic theory brings these two fields together in interesting ways. Application of the evolutionary principle of parent-offspring conflict to attachment theory suggests that attachment styles represent context-sensitive, evolved (adaptive) behaviors. In addition, an emphasis on offspring counter-strategies to adult reproductive strategies leads to consideration of attachment styles as overt manifestations of psychodynamic mediating processes, including the defense mechanisms of repression and reaction formation.

  14. Evolutionary origin of Ceratonova shasta and phylogeny of the marine myxosporean lineage

    Czech Academy of Sciences Publication Activity Database

    Fiala, Ivan; Hlavničková, M.; Kodádková, Alena; Freeman, M. A.; Bartošová-Sojková, Pavla; Atkinson, S.D.

    2015-01-01

    Roč. 86, MAY 2015 (2015), s. 75-89 ISSN 1055-7903 R&D Projects: GA ČR GBP505/12/G112 Institutional support: RVO:60077344 Keywords : Myxozoa * Ceratomyxa * topology test * evolutionary trends * taxonomy Subject RIV: EG - Zoology Impact factor: 3.792, year: 2015

  15. Traceability in Model-Based Testing

    Directory of Open Access Journals (Sweden)

    Mathew George

    2012-11-01

    Full Text Available The growing complexities of software and the demand for shorter time to market are two important challenges that face today’s IT industry. These challenges demand the increase of both productivity and quality of software. Model-based testing is a promising technique for meeting these challenges. Traceability modeling is a key issue and challenge in model-based testing. Relationships between the different models will help to navigate from one model to another, and trace back to the respective requirements and the design model when the test fails. In this paper, we present an approach for bridging the gaps between the different models in model-based testing. We propose relation definition markup language (RDML for defining the relationships between models.

  16. Performance comparison of some evolutionary algorithms on job shop scheduling problems

    Science.gov (United States)

    Mishra, S. K.; Rao, C. S. P.

    2016-09-01

    Job Shop Scheduling as a state space search problem belonging to NP-hard category due to its complexity and combinational explosion of states. Several naturally inspire evolutionary methods have been developed to solve Job Shop Scheduling Problems. In this paper the evolutionary methods namely Particles Swarm Optimization, Artificial Intelligence, Invasive Weed Optimization, Bacterial Foraging Optimization, Music Based Harmony Search Algorithms are applied and find tuned to model and solve Job Shop Scheduling Problems. To compare about 250 Bench Mark instances have been used to evaluate the performance of these algorithms. The capabilities of each these algorithms in solving Job Shop Scheduling Problems are outlined.

  17. Evolutionary Rate Heterogeneity of Primary and Secondary Metabolic Pathway Genes in Arabidopsis thaliana.

    Science.gov (United States)

    Mukherjee, Dola; Mukherjee, Ashutosh; Ghosh, Tapash Chandra

    2015-11-10

    Primary metabolism is essential to plants for growth and development, and secondary metabolism helps plants to interact with the environment. Many plant metabolites are industrially important. These metabolites are produced by plants through complex metabolic pathways. Lack of knowledge about these pathways is hindering the successful breeding practices for these metabolites. For a better knowledge of the metabolism in plants as a whole, evolutionary rate variation of primary and secondary metabolic pathway genes is a prerequisite. In this study, evolutionary rate variation of primary and secondary metabolic pathway genes has been analyzed in the model plant Arabidopsis thaliana. Primary metabolic pathway genes were found to be more conserved than secondary metabolic pathway genes. Several factors such as gene structure, expression level, tissue specificity, multifunctionality, and domain number are the key factors behind this evolutionary rate variation. This study will help to better understand the evolutionary dynamics of plant metabolism. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  18. Protecting the larger fish: an ecological, economical and evolutionary analysis using a demographic model

    DEFF Research Database (Denmark)

    Verdiell, Nuria Calduch

    . Recently, there is increasing evidence that this size-selective fishing reduces the chances of maintaining populations at levels sufficient to produce maximum sustainable yields, the chances of recovery/rebuilding populations that have been depleted/collapsed and may causes rapid evolutionary changes...... and the consequent changes in yield. We attempt to evaluate the capability of the larger fish to mitigate the evolutionary change on life-history traits caused by fishing, while also maintaining a sustainable annual yield. This is achieved by calculating the expected selection response on three life-history traits......Many marine fish stocks are reported as overfished on a global scale. This overfishing not only removes fish biomass, but also causes dramatic changes in the age and size structure of fish stocks. In particular, targeting of the larger individuals truncates the age and size structure of stocks...

  19. Application of evolutionary algorithms for multi-objective optimization in VLSI and embedded systems

    CERN Document Server

    2015-01-01

    This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design. Many complex engineering optimization problems can be modelled as multi-objective formulations. This book provides an introduction to multi-objective optimization using meta-heuristic algorithms, GA and PSO, and how they can be applied to problems like hardware/software partitioning in embedded systems, circuit partitioning in VLSI, design of operational amplifiers in analog VLSI, design space exploration in high-level synthesis, delay fault testing in VLSI testing, and scheduling in heterogeneous distributed systems. It is shown how, in each case, the various aspects of the EA, namely its representation, and operators like crossover, mutation, etc. can be separately formulated to solve these problems. This book is intended for design engineers and researchers in the field ...

  20. [Evolutionary medicine: an introduction. Evolutionary biology, a missing element in medical teaching].

    Science.gov (United States)

    Swynghedauw, Bernard

    2009-05-01

    The aim of this brief review article is to help to reconcile medicine with evolutionary biology, a subject that should be taught in medical school. Evolutionary medicine takes the view that contemporary ills are related to an incompatibility between the environment in which humans currently live and their genomes, which have been shaped by diferent environmental conditions during biological evolution. Human activity has recently induced acute environmental modifications that have profoundly changed the medical landscape. Evolutionary biology is an irreversible, ongoing and discontinuous process characterized by periods of stasis followed by accelerations. Evolutionary biology is determined by genetic mutations, which are selected either by Darwinian selective pressure or randomly by genetic drift. Most medical events result from a genome/environment conflict. Some may be purely genetic, as in monogenic diseases, and others purely environmental, such as traffic accidents. Nevertheless, in most common diseases the clinical landscape is determined by the conflict between these two factors, the genetic elements of which are gradually being unraveled Three examples are examined in depth:--The medical consequences of the greenhouse effect. The absence of excess mortality during recent heat waves suggests that the main determinant of mortality in the 2003 heatwave was heatstroke and old age. The projected long-term effects of global warming call for research on thermolysis, a forgotten branch of physiology.--The hygiene hypothesis postulates that the exponential rise in autoimmune and allergic diseases is linked to lesser exposure to infectious agents, possibly involving counter-regulatory factors such as IL-10.--The recent rise in the incidence of obesity and type 2 diabetes in rich countries can be considered to result from a conflict between a calorie-rich environment and gene variants that control appetite. These variants are currently being identified by genome