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

Estimating true evolutionary distances under the DCJ model.

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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.

An Evolutionary Game Theory Model of Spontaneous Brain Functioning.

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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.

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

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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.

Integrating EMDR into an evolutionary-based therapy for depression: a case study

OpenAIRE

Krupnik, Valery

2015-01-01

Key Clinical Message We present an intervention in a case of major depression, where eye movement desensitization and reprocessing (EMDR) therapy was integrated into an evolutionary-based psychotherapy for depression. At the end of the treatment and at follow up assessment we observed a more accepting disposition and decreased depressive but not anxiety symptoms.

Integrating EMDR into an evolutionary-based therapy for depression: a case study

Science.gov (United States)

Krupnik, Valery

2015-01-01

Key Clinical Message We present an intervention in a case of major depression, where eye movement desensitization and reprocessing (EMDR) therapy was integrated into an evolutionary-based psychotherapy for depression. At the end of the treatment and at follow up assessment we observed a more accepting disposition and decreased depressive but not anxiety symptoms. PMID:25984310

The evolutionary role of modularity and integration in the hominoid cranium.

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Mitteroecker, Philipp; Bookstein, Fred

2008-04-01

Patterns of morphological integration and modularity among shape features emerge from genetic and developmental factors with varying pleiotropic effects. Factors or processes affecting morphology only locally may respond to selection more easily than common factors that may lead to deleterious side effects and hence are expected to be more conserved. We briefly review evidence for such global factors in primate cranial development as well as for local factors constrained to either the face or the neurocranium. In a sample comprising 157 crania of Homo sapiens, Pan troglodytes, and Gorilla gorilla, we statistically estimated common and local factors of shape variation from Procrustes coordinates of 347 landmarks and semilandmarks. Common factors with pleiotropic effects on both the face and the neurocranium account for a large amount of shape variation, but mainly by extension or truncation of otherwise conserved developmental pathways. Local factors (modular shape characteristics) have more degrees of freedom for evolutionary change than mere ontogenetic scaling. Cranial shape is similarly integrated during development in all three species, but human evolution involves dissociation among several characteristics. The dissociation has probably been achieved by evolutionary alterations and by the novel emergence of local factors affecting characteristics that are controlled at the same time by the common factors.

Individual-based modeling of ecological and evolutionary processes

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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.

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

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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

Prediction of stock markets by the evolutionary mix-game model

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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.

Hidden long evolutionary memory in a model biochemical network

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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.

Evolutionary model of an anonymous consumer durable market

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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

Computational Modeling of Teaching and Learning through Application of Evolutionary Algorithms

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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.

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

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.

Evolutionary model of the growth and size of firms

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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.

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...

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

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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...

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

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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

Evolutionary accounts of human behavioural diversity

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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

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

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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.

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.

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.

Enhanced lipase recovery through RSM integrated differential evolutionary approach from the fermented biomass

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Vijay Kumar Garlapati

2013-10-01

Full Text Available The aim of this work was to apply a modeling integrated optimisation approach for a complex, highly nonlinear system for an extracellular lipase extraction process. The model was developed using mutation, crossover and selection variables of Differential Evolution (DE based on central composite design of Response Surface Methodology. The experimentally validated model was optimized by DE, a robust evolutionary optimization tool. A maximum lipase activity of 134.13 U/gds (more than 36.28 U/gds compared to one variable at a time approach was observed with the DE-stated optimum values of 25.01% dimethyl sulfoxide concentration, 40 mM buffer, 128.52 min soaking time and 35ºC with the DE control parameters, namely number of population, generations, crossover operator and scaling factor as 20, 50, 0.5 and 0.25, respectively. The use of DE approach improved the optimization capability and decision speed, resulting in an improved yield of 36.28 U/gds compared to the one variable at a time approach for the extracellular lipase activity under the non-optimized conditions. The developed mathematical model and optimization were generic in nature, which seemed to be useful for the scale-up studies of maximum recovery of lipase from the fermented biomass.

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)

Introduction: integrating genetic and cultural evolutionary approaches to language.

Science.gov (United States)

Mesoudi, Alex; McElligott, Alan G; Adger, David

2011-04-01

The papers in this special issue of Human Biology address recent research in the field of language evolution, both the genetic evolution of the language faculty and the cultural evolution of specific languages. While both of these areas have received increasing interest in recent years, there is also a need to integrate these somewhat separate efforts and explore the relevant gene-culture coevolutionary interactions. Here we summarize the individual contributions, set them in the context of the wider literature, and identify outstanding future research questions. The first set of papers concerns the comparative study of nonhuman communication in primates and birds from both a behavioral and neurobiological perspective, revealing evidence for several common language-related traits in various nonhuman species and providing clues as to the evolutionary origin and function of the human language faculty. The second set of papers discusses the consequences of viewing language as a culturally evolving system in its own right, including claims that this removes the need for strong genetic biases for language acquisition, and that phylogenetic evolutionary methods can be used to reconstruct language histories. We conclude by highlighting outstanding areas for future research, including identifying the precise selection pressures that gave rise to the language faculty in ancestral hominin species, and determining the strength, domain specificity, and origin of the cultural transmission biases that shape languages as they pass along successive generations of language learners.

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.

Modelling nutritional mutualisms: challenges and opportunities for data integration.

Science.gov (United States)

Clark, Teresa J; Friel, Colleen A; Grman, Emily; Shachar-Hill, Yair; Friesen, Maren L

2017-09-01

Nutritional mutualisms are ancient, widespread, and profoundly influential in biological communities and ecosystems. Although much is known about these interactions, comprehensive answers to fundamental questions, such as how resource availability and structured interactions influence mutualism persistence, are still lacking. Mathematical modelling of nutritional mutualisms has great potential to facilitate the search for comprehensive answers to these and other fundamental questions by connecting the physiological and genomic underpinnings of mutualisms with ecological and evolutionary processes. In particular, when integrated with empirical data, models enable understanding of underlying mechanisms and generalisation of principles beyond the particulars of a given system. Here, we demonstrate how mathematical models can be integrated with data to address questions of mutualism persistence at four biological scales: cell, individual, population, and community. We highlight select studies where data has been or could be integrated with models to either inform model structure or test model predictions. We also point out opportunities to increase model rigour through tighter integration with data, and describe areas in which data is urgently needed. We focus on plant-microbe systems, for which a wealth of empirical data is available, but the principles and approaches can be generally applied to any nutritional mutualism. © 2017 John Wiley & Sons Ltd/CNRS.

The fossil record of phenotypic integration and modularity: A deep-time perspective on developmental and evolutionary dynamics.

Science.gov (United States)

Goswami, Anjali; Binder, Wendy J; Meachen, Julie; O'Keefe, F Robin

2015-04-21

Variation is the raw material for natural selection, but the factors shaping variation are still poorly understood. Genetic and developmental interactions can direct variation, but there has been little synthesis of these effects with the extrinsic factors that can shape biodiversity over large scales. The study of phenotypic integration and modularity has the capacity to unify these aspects of evolutionary study by estimating genetic and developmental interactions through the quantitative analysis of morphology, allowing for combined assessment of intrinsic and extrinsic effects. Data from the fossil record in particular are central to our understanding of phenotypic integration and modularity because they provide the only information on deep-time developmental and evolutionary dynamics, including trends in trait relationships and their role in shaping organismal diversity. Here, we demonstrate the important perspective on phenotypic integration provided by the fossil record with a study of Smilodon fatalis (saber-toothed cats) and Canis dirus (dire wolves). We quantified temporal trends in size, variance, phenotypic integration, and direct developmental integration (fluctuating asymmetry) through 27,000 y of Late Pleistocene climate change. Both S. fatalis and C. dirus showed a gradual decrease in magnitude of phenotypic integration and an increase in variance and the correlation between fluctuating asymmetry and overall integration through time, suggesting that developmental integration mediated morphological response to environmental change in the later populations of these species. These results are consistent with experimental studies and represent, to our knowledge, the first deep-time validation of the importance of developmental integration in stabilizing morphological evolution through periods of environmental change.

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

Asteroseismology of pulsating DA white dwarfs with fully evolutionary models

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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.

Dimensions of integration in interdisciplinary explanations of the origin of evolutionary novelty.

Science.gov (United States)

Love, Alan C; Lugar, Gary L

2013-12-01

Many philosophers of biology have embraced a version of pluralism in response to the failure of theory reduction but overlook how concepts, methods, and explanatory resources are in fact coordinated, such as in interdisciplinary research where the aim is to integrate different strands into an articulated whole. This is observable for the origin of evolutionary novelty-a complex problem that requires a synthesis of intellectual resources from different fields to arrive at robust answers to multiple allied questions. It is an apt locus for exploring new dimensions of explanatory integration because it necessitates coordination among historical and experimental disciplines (e.g., geology and molecular biology). These coordination issues are widespread for the origin of novel morphologies observed in the Cambrian Explosion. Despite an explicit commitment to an integrated, interdisciplinary explanation, some potential disciplinary contributors are excluded. Notable among these exclusions is the physics of ontogeny. We argue that two different dimensions of integration-data and standards-have been insufficiently distinguished. This distinction accounts for why physics-based explanatory contributions to the origin of novelty have been resisted: they do not integrate certain types of data and differ in how they conceptualize the standard of uniformitarianism in historical, causal explanations. Our analysis of these different dimensions of integration contributes to the development of more adequate and integrated explanatory frameworks. Copyright © 2013 Elsevier Ltd. All rights reserved.

Data-driven modelling of structured populations a practical guide to the integral projection model

CERN Document Server

Ellner, Stephen P; Rees, Mark

2016-01-01

This book is a “How To” guide for modeling population dynamics using Integral Projection Models (IPM) starting from observational data. It is written by a leading research team in this area and includes code in the R language (in the text and online) to carry out all computations. The intended audience are ecologists, evolutionary biologists, and mathematical biologists interested in developing data-driven models for animal and plant populations. IPMs may seem hard as they involve integrals. The aim of this book is to demystify IPMs, so they become the model of choice for populations structured by size or other continuously varying traits. The book uses real examples of increasing complexity to show how the life-cycle of the study organism naturally leads to the appropriate statistical analysis, which leads directly to the IPM itself. A wide range of model types and analyses are presented, including model construction, computational methods, and the underlying theory, with the more technical material in B...

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

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.

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

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

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

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

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.

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

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

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.

Integrative Assessment of Evolutionary Theory Acceptance and Knowledge Levels of Biology Undergraduate Students from a Brazilian University

Science.gov (United States)

Tavares, Gustavo Medina; Bobrowski, Vera Lucia

2018-01-01

The integrative role that Evolutionary theory plays within Biology is recognised by most scientific authors, as well as in governmental education policies, including Brazilian policies. However, teaching and learning evolution seems problematic in many countries, and Brazil is among those. Many factors may affect teachers' and students'…

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.

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

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.

An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing.

Science.gov (United States)

Wu, Zujian; Pang, Wei; Coghill, George M

2015-01-01

Both qualitative and quantitative model learning frameworks for biochemical systems have been studied in computational systems biology. In this research, after introducing two forms of pre-defined component patterns to represent biochemical models, we propose an integrative qualitative and quantitative modelling framework for inferring biochemical systems. In the proposed framework, interactions between reactants in the candidate models for a target biochemical system are evolved and eventually identified by the application of a qualitative model learning approach with an evolution strategy. Kinetic rates of the models generated from qualitative model learning are then further optimised by employing a quantitative approach with simulated annealing. Experimental results indicate that our proposed integrative framework is feasible to learn the relationships between biochemical reactants qualitatively and to make the model replicate the behaviours of the target system by optimising the kinetic rates quantitatively. Moreover, potential reactants of a target biochemical system can be discovered by hypothesising complex reactants in the synthetic models. Based on the biochemical models learned from the proposed framework, biologists can further perform experimental study in wet laboratory. In this way, natural biochemical systems can be better understood.

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.

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

Odonata (dragonflies and damselflies) as a bridge between ecology and evolutionary genomics.

Science.gov (United States)

Bybee, Seth; Córdoba-Aguilar, Alex; Duryea, M Catherine; Futahashi, Ryo; Hansson, Bengt; Lorenzo-Carballa, M Olalla; Schilder, Ruud; Stoks, Robby; Suvorov, Anton; Svensson, Erik I; Swaegers, Janne; Takahashi, Yuma; Watts, Phillip C; Wellenreuther, Maren

2016-01-01

Odonata (dragonflies and damselflies) present an unparalleled insect model to integrate evolutionary genomics with ecology for the study of insect evolution. Key features of Odonata include their ancient phylogenetic position, extensive phenotypic and ecological diversity, several unique evolutionary innovations, ease of study in the wild and usefulness as bioindicators for freshwater ecosystems worldwide. In this review, we synthesize studies on the evolution, ecology and physiology of odonates, highlighting those areas where the integration of ecology with genomics would yield significant insights into the evolutionary processes that would not be gained easily by working on other animal groups. We argue that the unique features of this group combined with their complex life cycle, flight behaviour, diversity in ecological niches and their sensitivity to anthropogenic change make odonates a promising and fruitful taxon for genomics focused research. Future areas of research that deserve increased attention are also briefly outlined.

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.

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.

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.

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.

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

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

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...

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...

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.

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

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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.

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

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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

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)

Evolutionary games on multilayer networks: a colloquium

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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.

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

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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.

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

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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.

Conceptual Barriers to Progress Within Evolutionary Biology.

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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.

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.

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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.

Integrative assessment of Evolutionary theory acceptance and knowledge levels of Biology undergraduate students from a Brazilian university

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Tavares, Gustavo Medina; Bobrowski, Vera Lucia

2018-03-01

The integrative role that Evolutionary theory plays within Biology is recognised by most scientific authors, as well as in governmental education policies, including Brazilian policies. However, teaching and learning evolution seems problematic in many countries, and Brazil is among those. Many factors may affect teachers' and students' perceptions towards evolution, and studies can help to reveal those factors. We used a conceptual questionnaire, the Measure of Acceptance of the Theory of Evolution (MATE) instrument, and a Knowledge test to assess (1) the level of acceptance and understanding of 23 undergraduate Biology students nearing the end of their course, (2) other factors that could affect these levels, including course structure, and (3) the most difficult topics regarding evolutionary biology. The results of this study showed that the students, on average, had a 'Very High Acceptance' (89.91) and a 'Very Low Knowledge' (59.42%) of Evolutionary theory, and also indicated a moderate positive correlation between the two (r = 0.66, p = .001). The most difficult topics were related to the definition of evolution and dating techniques. We believe that the present study provides evidence for policymakers to reformulate current school and university curricula in order to improve the teachers' acceptance and understanding of evolution and other biological concepts, consequently, helping students reduce their misconceptions related to evolutionary biology.

The integration of Darwinism and evolutionary morphology: Alexej Nikolajevich Sewertzoff (1866-1936) and the developmental basis of evolutionary change.

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Levit, George S; Hossfeld, Uwe; Olsson, Lennart

2004-07-15

The growth of evolutionary morphology in the late 19th and early 20th centuries was inspired by the work of Carl Gegenbaur (1826-1903) and his protégé and friend Ernst Haeckel (1834-1919). However, neither of them succeeded in creating and applying a strictly Darwinian (selectionist) methodology. This task was left to the next generation of evolutionary morphologists. In this paper we present a relatively unknown researcher, Alexej Nikolajevich Sewertzoff (1866-1936) who made important contributions towards a synthesis of Darwinism and evolutionary morphology. Copyright 2004 Wiley-Liss, Inc.

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.

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.

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.

Evolutionary disarmament in interspecific competition.

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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.

Outrun or Outmaneuver: Predator-Prey Interactions as a Model System for Integrating Biomechanical Studies in a Broader Ecological and Evolutionary Context.

Science.gov (United States)

Moore, Talia Y; Biewener, Andrew A

2015-12-01

Behavioral studies performed in natural habitats provide a context for the development of hypotheses and the design of experiments relevant both to biomechanics and to evolution. In particular, predator-prey interactions are a model system for integrative study because success or failure of predation has a direct effect on fitness and drives the evolution of specialized performance in both predator and prey. Although all predators share the goal of capturing prey, and all prey share the goal of survival, the behavior of predators and prey are diverse in nature. This article presents studies of some predator-prey interactions sharing common predation strategies that reveal general principles governing the behaviors of predator and prey, even in distantly related taxa. Studies of predator-prey interactions also reveal that maximal performance observed in a laboratory setting is not necessarily the performance that determines fitness. Thus, considering locomotion in the context of predation ecology can aid in evolutionarily relevant experimental design. Classification by strategy reveals that displaying unpredictable trajectories is a relevant anti-predator behavior in response to multiple predation strategies. A predator's perception and pursuit of prey can be affected indirectly by divergent locomotion of similar animals that share an ecosystem. Variation in speed and direction of locomotion that directly increases the unpredictability of a prey's trajectory can be increased through genetic mutation that affects locomotor patterns, musculoskeletal changes that affect maneuverability, and physical interactions between an animal and the environment. By considering the interconnectedness of ecology, physical constraints, and the evolutionary history of behavior, studies in biomechanics can be designed to inform each of these fields. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights

Paleontological Studies Integrated into a New Evolutionary Zoology.

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Kuratani, Shigeru; Fukatsu, Takema

2017-02-01

Zoological Letters, an open access online journal launched in 2015 is entering its third year of publication, and now seeks to drive new insights in evolutionary and comparative zoology by the inclusion of paleontological studies into its scope.

Eco-Evo-Devo: developmental symbiosis and developmental plasticity as evolutionary agents.

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Gilbert, Scott F; Bosch, Thomas C G; Ledón-Rettig, Cristina

2015-10-01

The integration of research from developmental biology and ecology into evolutionary theory has given rise to a relatively new field, ecological evolutionary developmental biology (Eco-Evo-Devo). This field integrates and organizes concepts such as developmental symbiosis, developmental plasticity, genetic accommodation, extragenic inheritance and niche construction. This Review highlights the roles that developmental symbiosis and developmental plasticity have in evolution. Developmental symbiosis can generate particular organs, can produce selectable genetic variation for the entire animal, can provide mechanisms for reproductive isolation, and may have facilitated evolutionary transitions. Developmental plasticity is crucial for generating novel phenotypes, facilitating evolutionary transitions and altered ecosystem dynamics, and promoting adaptive variation through genetic accommodation and niche construction. In emphasizing such non-genomic mechanisms of selectable and heritable variation, Eco-Evo-Devo presents a new layer of evolutionary synthesis.

Evolutionary approaches to autism: an overview and integration

NARCIS (Netherlands)

Ploeger, A.; Galis, F.

2011-01-01

Autism is a highly heritable neurodevelopmental disorder, which greatly reduces reproductive success. The combination of high heritability and low reproductive success raises an evolutionary question: why was autism not eliminated by natural selection? We review different perspectives on the

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.

Modeling fabrication of nuclear components: An integrative approach

Energy Technology Data Exchange (ETDEWEB)

Hench, K.W.

1996-08-01

Reduction of the nuclear weapons stockpile and the general downsizing of the nuclear weapons complex has presented challenges for Los Alamos. One is to design an optimized fabrication facility to manufacture nuclear weapon primary components in an environment of intense regulation and shrinking budgets. This dissertation presents an integrative two-stage approach to modeling the casting operation for fabrication of nuclear weapon primary components. The first stage optimizes personnel radiation exposure for the casting operation layout by modeling the operation as a facility layout problem formulated as a quadratic assignment problem. The solution procedure uses an evolutionary heuristic technique. The best solutions to the layout problem are used as input to the second stage - a simulation model that assesses the impact of competing layouts on operational performance. The focus of the simulation model is to determine the layout that minimizes personnel radiation exposures and nuclear material movement, and maximizes the utilization of capacity for finished units.

Asymmetric Evolutionary Games

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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

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.

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

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...

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.

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

Uniqueness of human running coordination: The integration of modern and ancient evolutionary innovations

Directory of Open Access Journals (Sweden)

John eKiely

2016-04-01

Full Text Available Running is a pervasive activity across human cultures and a cornerstone of contemporary health, fitness and sporting activities. Yet for the overwhelming predominance of human existence running was an essential prerequisite for survival. A means to hunt, and a means to escape when hunted. In a very real sense humans have evolved to run. Yet curiously, perhaps due to running’s cultural ubiquity and the natural ease with which we learn to run, we rarely consider the uniqueness of human bipedal running within the animal kingdom. Our unique upright, single stance, bouncing running gait imposes a unique set of coordinative difficulties. Challenges demanding we precariously balance our fragile brains in the very position where they are most vulnerable to falling injury while simultaneously retaining stability, steering direction of travel, and powering the upcoming stride: all within the abbreviated time-frames afforded by short, violent ground contacts separated by long flight times. These running coordination challenges are solved through the tightly-integrated blending of primitive evolutionary legacies, conserved from reptilian and vertebrate lineages, and comparatively modern, more exclusively human, innovations. The integrated unification of these top-down and bottom-up control processes bestows humans with an agile control system, enabling us to readily modulate speeds, change direction, negotiate varied terrains and to instantaneously adapt to changing surface conditions. The seamless integration of these evolutionary processes is facilitated by pervasive, neural and biological, activity-dependent adaptive plasticity. Over time, and with progressive exposure, this adaptive plasticity shapes neural and biological structures to best cope with regularly imposed movement challenges. This pervasive plasticity enables the gradual construction of a robust system of distributed coordinated control, comprised of processes that are so deeply

A Semiotic Analysis of the Interface between Evolutionary and Developmental Processes

Directory of Open Access Journals (Sweden)

Eugenio Andrade

2008-07-01

Full Text Available This work proposes the notion of organisms as Evolving Developing Agents (EDA in order to ground an internalist model in which evolution and development are conceived as aspects of a general transformative tendency driven by organism's need to cope with environmental uncertainty. It is shown how the integration Evo/Devo contributes to an expanded evolutionary synthesis that accounts for divergent evolution in terms of development, without disregarding the role of genes and natural selection. However this integration has to be seen as a specific case that contributes to the contextualization of C.S.Peirce's evolutionary ontology founded on three universal categories and six space/time/function relations, as described by Taborsky. The role played by the EDA is characterized by the Secondness as firstness relation for it merges the internal/ external, and individual/population and present/past/ progressive cuts that permeate the discourse of biology.

Evolutionary Process for Integrating COTS-Based Systems (EPIC): An Overview. Key Elements in Building, Fielding, and Supporting Commercial-off-the-Shelf (COTS) Based Solutions

National Research Council Canada - National Science Library

Albert, Cecilia

2002-01-01

.... The Evolutionary Process for Integrating COTS-based systems (EPIC) redefines acquisition, management, and engineering practices to more effectively leverage the COTS marketplace and other sources of pre-existing components...

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.

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.

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...

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.

Integrative structure modeling with the Integrative Modeling Platform.

Science.gov (United States)

Webb, Benjamin; Viswanath, Shruthi; Bonomi, Massimiliano; Pellarin, Riccardo; Greenberg, Charles H; Saltzberg, Daniel; Sali, Andrej

2018-01-01

Building models of a biological system that are consistent with the myriad data available is one of the key challenges in biology. Modeling the structure and dynamics of macromolecular assemblies, for example, can give insights into how biological systems work, evolved, might be controlled, and even designed. Integrative structure modeling casts the building of structural models as a computational optimization problem, for which information about the assembly is encoded into a scoring function that evaluates candidate models. Here, we describe our open source software suite for integrative structure modeling, Integrative Modeling Platform (https://integrativemodeling.org), and demonstrate its use. © 2017 The Protein Society.

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.

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.

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.

Integrating Ecological and Evolutionary Context in the Study of Maternal Stress.

Science.gov (United States)

Sheriff, Michael J; Bell, Alison; Boonstra, Rudy; Dantzer, Ben; Lavergne, Sophia G; McGhee, Katie E; MacLeod, Kirsty J; Winandy, Laurane; Zimmer, Cedric; Love, Oliver P

2017-09-01

Maternal stress can prenatally influence offspring phenotypes and there are an increasing number of ecological studies that are bringing to bear biomedical findings to natural systems. This is resulting in a shift from the perspective that maternal stress is unanimously costly, to one in which maternal stress may be beneficial to offspring. However, this adaptive perspective is in its infancy with much progress to still be made in understanding the role of maternal stress in natural systems. Our aim is to emphasize the importance of the ecological and evolutionary context within which adaptive hypotheses of maternal stress can be evaluated. We present five primary research areas where we think future research can make substantial progress: (1) understanding maternal and offspring control mechanisms that modulate exposure between maternal stress and subsequent offspring phenotype response; (2) understanding the dynamic nature of the interaction between mothers and their environment; (3) integrating offspring phenotypic responses and measuring both maternal and offspring fitness outcomes under real-life (either free-living or semi-natural) conditions; (4) empirically testing these fitness outcomes across relevant spatial and temporal environmental contexts (both pre- and post-natal environments); (5) examining the role of maternal stress effects in human-altered environments-i.e., do they limit or enhance fitness. To make progress, it is critical to understand the role of maternal stress in an ecological context and to do that, we must integrate across physiology, behavior, genetics, and evolution. © The Author 2017. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

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

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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 ...

Incorporating Development Into Evolutionary Psychology

Directory of Open Access Journals (Sweden)

David F. Bjorklund

2016-09-01

Full Text Available Developmental thinking is gradually becoming integrated within mainstream evolutionary psychology. This is most apparent with respect to the role of parenting, with proponents of life history theory arguing that cognitive and behavioral plasticity early in life permits children to select different life history strategies, with such strategies being adaptive solutions to different fitness trade-offs. I argue that adaptations develop and are based on the highly plastic nature of infants’ and children’s behavior/cognition/brains. The concept of evolved probabilistic cognitive mechanisms is introduced, defined as information processing mechanisms evolved to solve recurrent problems faced by ancestral populations that are expressed in a probabilistic fashion in each individual in a generation and are based on the continuous and bidirectional interaction over time at all levels of organization, from the genetic through the cultural. Early perceptual/cognitive biases result in behavior that, when occurring in a species-typical environment, produce continuous adaptive changes in behavior (and cognition, yielding adaptive outcomes. Examples from social learning and tool use are provided, illustrating the development of adaptations via evolved probabilistic cognitive mechanisms. The integration of developmental concepts into mainstream evolutionary psychology (and evolutionary concepts into mainstream developmental psychology will provide a clearer picture of what it means to be human.

Evolutionary and differential psychology: conceptual conflicts and the path to integration

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Marsh, Tim; Boag, Simon

2013-01-01

Evolutionary psychology has seen the majority of its success exploring adaptive features of the mind believed to be ubiquitous across our species. This has given rise to the belief that the adaptationist approach has little to offer the field of differential psychology, which concerns itself exclusively with the ways in which individuals systematically differ. By framing the historical origins of both disciplines, and exploring the means through which they each address the unique challenges of psychological description and explanation, the present article identifies the conceptual and theoretical problems that have kept differential psychology isolated not only from evolutionary psychology, but from explanatory approaches in general. Paying special attention to these conceptual problems, the authors review how these difficulties are being overcome by contemporary evolutionary research, and offer instructive suggestions concerning how differential researchers (and others) can best build upon these innovations. PMID:24065949

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.

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.

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.

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.

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.

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”.

[Charles Darwin and the problem of evolutionary progress].

Science.gov (United States)

Iordanskiĭ, N N

2010-01-01

According to Ch. Darwin's evolutionary theory, evolutionary progress (interpreted as morpho-physiological progress or arogenesis in recent terminology) is one of logical results of natural selection. At the same time, natural selection does not hold any factors especially promoting evolutionary progress. Darwin emphasized that the pattern of evolutionary changes depends on organism nature more than on the pattern of environment changes. Arogenesis specificity is determined by organization of rigorous biological systems - integral organisms. Onward progressive development is determined by fundamental features of living organisms: metabolism and homeostasis. The concept of social Darwinism differs fundamentally from Darwin's ideas about the most important role of social instincts in progress of mankind. Competition and selection play secondary role in socio-cultural progress of human society.

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.

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.

Genome-wide detection of selection and other evolutionary forces

DEFF Research Database (Denmark)

Xu, Zhuofei; Zhou, Rui

2015-01-01

As is well known, pathogenic microbes evolve rapidly to escape from the host immune system and antibiotics. Genetic variations among microbial populations occur frequently during the long-term pathogen–host evolutionary arms race, and individual mutation beneficial for the fitness can be fixed...... to scan genome-wide alignments for evidence of positive Darwinian selection, recombination, and other evolutionary forces operating on the coding regions. In this chapter, we describe an integrative analysis pipeline and its application to tracking featured evolutionary trajectories on the genome...

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.

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...

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

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...

Psychoanalysis and cognitive-evolutionary psychology: an attempt at integration.

Science.gov (United States)

Migone, P; Liotti, G

1998-12-01

The authors argue that the abandonment of the theory of trauma in 1897 was a trauma for Freud himself, who was led to 'despair', and possibly reacted with an overemphasis on inner fantasies and drive discharge. They suggest that today we are facing a second trauma in the history of psychoanalysis that we might call the 'abandonment of drive theory', i.e. the notion that human beings strive not primarily to reduce sexual and aggressive drives but rather seek objects, assign meanings, test previous beliefs and assimilate new schemes. Our task is to recover as Freud was able to do, giving a new impetus to psychoanalysis. The current challenge is, on the one hand, a revision of the psychoanalytic conception of inherited information, and, on the other, a theory of motivation based on converging evidence from cognitive science, ethology, infant research and psychotherapy research. Many clinical models are current in contemporary psychoanalysis. Only as one example among these models, some concepts used in Weiss & Sampson's 'Control-Mastery Theory' will be discussed in light of cognitive science and evolutionary epistemology within the framework of (a) the 1960 classic, 'Plans and Structure of Behavior' by Miller, Galanter and Pribram (b) Edelman's neurobiological theory and (c) Bowlby's attachment theory.

Islamic medicine and evolutionary medicine: a comparative analysis.

Science.gov (United States)

Saniotis, Arthur

2012-01-01

The advent of evolutionary medicine in the last two decades has provided new insights into the causes of human disease and possible preventative strategies. One of the strengths of evolutionary medicine is that it follows a multi-disciplinary approach. Such an approach is vital to future biomedicine as it enables for the infiltration of new ideas. Although evolutionary medicine uses Darwinian evolution as a heuristic for understanding human beings' susceptibility to disease, this is not necessarily in conflict with Islamic medicine. It should be noted that current evolutionary theory was first expounded by various Muslim scientists such as al-Jāḥiẓ, al-Ṭūsī, Ibn Khaldūn and Ibn Maskawayh centuries before Darwin and Wallace. In this way, evolution should not be viewed as being totally antithetical to Islam. This article provides a comparative overview of Islamic medicine and Evolutionary medicine as well as drawing points of comparison between the two approaches which enables their possible future integration.

Literary study and evolutionary theory : A review essay.

Science.gov (United States)

Carroll, J

1998-09-01

Several recent books have claimed to integrate literary study with evolutionary biology. All of the books here considered, except Robert Storey's, adopt conceptions of evolutionary theory that are in some way marginal to the Darwinian adaptationist program. All the works attempt to connect evolutionary study with various other disciplines or methodologies: for example, with cultural anthropology, cognitive psychology, the psychology of emotion, neurobiology, chaos theory, or structuralist linguistics. No empirical paradigm has yet been established for this field, but important steps have been taken, especially by Storey, in formulating basic principles, identifying appropriate disciplinary connections, and marking out lines of inquiry. Reciprocal efforts are needed from biologists and social scientists.

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

SHARP's systems engineering challenge: rectifying integrated product team requirements with performance issues in an evolutionary spiral development acquisition

Science.gov (United States)

Kuehl, C. Stephen

2003-08-01

Completing its final development and early deployment on the Navy's multi-role aircraft, the F/A-18 E/F Super Hornet, the SHAred Reconnaissance Pod (SHARP) provides the war fighter with the latest digital tactical reconnaissance (TAC Recce) Electro-Optical/Infrared (EO/IR) sensor system. The SHARP program is an evolutionary acquisition that used a spiral development process across a prototype development phase tightly coupled into overlapping Engineering and Manufacturing Development (EMD) and Low Rate Initial Production (LRIP) phases. Under a tight budget environment with a highly compressed schedule, SHARP challenged traditional acquisition strategies and systems engineering (SE) processes. Adopting tailored state-of-the-art systems engineering process models allowd the SHARP program to overcome the technical knowledge transition challenges imposed by a compressed program schedule. The program's original goal was the deployment of digital TAC Recce mission capabilities to the fleet customer by summer of 2003. Hardware and software integration technical challenges resulted from requirements definition and analysis activities performed across a government-industry led Integrated Product Team (IPT) involving Navy engineering and test sites, Boeing, and RTSC-EPS (with its subcontracted hardware and government furnished equipment vendors). Requirements development from a bottoms-up approach was adopted using an electronic requirements capture environment to clarify and establish the SHARP EMD product baseline specifications as relevant technical data became available. Applying Earned-Value Management (EVM) against an Integrated Master Schedule (IMS) resulted in efficiently managing SE task assignments and product deliveries in a dynamically evolving customer requirements environment. Application of Six Sigma improvement methodologies resulted in the uncovering of root causes of errors in wiring interconnectivity drawings, pod manufacturing processes, and avionics

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...

Grand Theories of Personality Cannot Be Integrated

Science.gov (United States)

Wood, Alex; Joseph, Stephen

2007-01-01

Comments on the original article "A New Big Five: Fundamental Principles for an Integrative Science of Personality," by Dan P. McAdams and Jennifer L. Pals (see record 2006-03947-002). McAdams and Pals (April 2006) presented a new model to integrate the field of personality psychology. Cultural and evolutionary factors interact with an…

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

Model integration and a theory of models

OpenAIRE

Dolk, Daniel R.; Kottemann, Jeffrey E.

1993-01-01

Model integration extends the scope of model management to include the dimension of manipulation as well. This invariably leads to comparisons with database theory. Model integration is viewed from four perspectives: Organizational, definitional, procedural, and implementational. Strategic modeling is discussed as the organizational motivation for model integration. Schema and process integration are examined as the logical and manipulation counterparts of model integr...

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

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

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.

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 ...

Transmutability, generalised Darwinism and the limits to conceptual integration

OpenAIRE

Christopher Brown

2013-01-01

This article explores the limits to conceptual integration between evolutionary biology, cognitive neuroscience and economics. The new learning in the natural sciences supplies material to update and enrich the microfoundations of institutional economics—specifically, the instinct–habit psychology. The framing of social reality with evolutionary concepts is, however, misguided in important respects. Metaphorical modelling is the transfer of concepts developed for the understanding of one doma...

Evolutionary Explanations of Eating Disorders

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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.

BEAST: Bayesian evolutionary analysis by sampling trees

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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.

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

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

2012-01-01

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…

Characterizing Phase Transitions in a Model of Neutral Evolutionary Dynamics

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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

How evolutionary principles improve the understanding of human health and disease.

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Gluckman, Peter D; Low, Felicia M; Buklijas, Tatjana; Hanson, Mark A; Beedle, Alan S

2011-03-01

An appreciation of the fundamental principles of evolutionary biology provides new insights into major diseases and enables an integrated understanding of human biology and medicine. However, there is a lack of awareness of their importance amongst physicians, medical researchers, and educators, all of whom tend to focus on the mechanistic (proximate) basis for disease, excluding consideration of evolutionary (ultimate) reasons. The key principles of evolutionary medicine are that selection acts on fitness, not health or longevity; that our evolutionary history does not cause disease, but rather impacts on our risk of disease in particular environments; and that we are now living in novel environments compared to those in which we evolved. We consider these evolutionary principles in conjunction with population genetics and describe several pathways by which evolutionary processes can affect disease risk. These perspectives provide a more cohesive framework for gaining insights into the determinants of health and disease. Coupled with complementary insights offered by advances in genomic, epigenetic, and developmental biology research, evolutionary perspectives offer an important addition to understanding disease. Further, there are a number of aspects of evolutionary medicine that can add considerably to studies in other domains of contemporary evolutionary studies.

Bridging developmental systems theory and evolutionary psychology using dynamic optimization.

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Frankenhuis, Willem E; Panchanathan, Karthik; Clark Barrett, H

2013-07-01

Interactions between evolutionary psychologists and developmental systems theorists have been largely antagonistic. This is unfortunate because potential synergies between the two approaches remain unexplored. This article presents a method that may help to bridge the divide, and that has proven fruitful in biology: dynamic optimization. Dynamic optimization integrates developmental systems theorists' focus on dynamics and contingency with the 'design stance' of evolutionary psychology. It provides a theoretical framework as well as a set of tools for exploring the properties of developmental systems that natural selection might favor, given particular evolutionary ecologies. We also discuss limitations of the approach. © 2013 Blackwell Publishing Ltd.

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)

A Study On Traditional And Evolutionary Software Development Models

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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.

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

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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.

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

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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.

Evolutionary development of the neurocranium in Dissorophoidea (Tetrapoda: Temnospondyli), an integrative approach.

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Maddin, Hillary C; Reisz, Robert R; Anderson, Jason S

2010-01-01

Ontogenetic data can play a prominent role in addressing questions in tetrapod evolution, but such evidence from the fossil record is often incompletely considered because it is limited to initiation of ossification, or allometric changes with increasing size. In the present study, specimens of a new species of an archaic amphibian (280 Myr old), Acheloma n. sp., a member of the temnospondyl superfamily Dissorophoidea and the sister group to Amphibamidae, which is thought to include at least two of our modern amphibian clades, anurans and caudatans (Batrachia), provides us with new developmental data. We identify five ontogenetic events, enabling us to construct a partial ontogenetic trajectory (integration of developmental and transformation sequence data) related to the relative timing of completion of neurocranial structures. Comparison of the adult amphibamid morphology with this partial ontogeny identifies a heterochronic event that occurred within the neurocranium at some point in time between the two taxa, which is consistent with the predictions of miniaturization in amphibamids, providing the first insights into the influence of miniaturization on the neurocranium in a fossil tetrapod group. This study refines hypotheses of large-scale evolutionary trends within Dissorophoidea that may have facilitated the radiation of amphibamids and, projected forward, the origin of the generalized batrachian skull. Most importantly, this study highlights the importance of integrating developmental and transformation sequence data, instead of onset of ossification alone, into investigations of major events in tetrapod evolution using evidence provided by the fossil record, and highlights the value of even highly incomplete growth series comprised of relatively late-stage individuals.

Evolution in health and medicine Sackler colloquium: Making evolutionary biology a basic science for medicine.

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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

2010-01-26

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.

Integrating evo-devo with ecology for a better understanding of phenotypic evolution.

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Santos, M Emília; Berger, Chloé S; Refki, Peter N; Khila, Abderrahman

2015-11-01

Evolutionary developmental biology (evo-devo) has provided invaluable contributions to our understanding of the mechanistic relationship between genotypic and phenotypic change. Similarly, evolutionary ecology has greatly advanced our understanding of the relationship between the phenotype and the environment. To fully understand the evolution of organismal diversity, a thorough integration of these two fields is required. This integration remains highly challenging because model systems offering a rich ecological and evolutionary background, together with the availability of developmental genetic tools and genomic resources, are scarce. In this review, we introduce the semi-aquatic bugs (Gerromorpha, Heteroptera) as original models well suited to study why and how organisms diversify. The Gerromorpha invaded water surfaces over 200 mya and diversified into a range of remarkable new forms within this new ecological habitat. We summarize the biology and evolutionary history of this group of insects and highlight a set of characters associated with the habitat change and the diversification that followed. We further discuss the morphological, behavioral, molecular and genomic tools available that together make semi-aquatic bugs a prime model for integration across disciplines. We present case studies showing how the implementation and combination of these approaches can advance our understanding of how the interaction between genotypes, phenotypes and the environment drives the evolution of distinct morphologies. Finally, we explain how the same set of experimental designs can be applied in other systems to address similar biological questions. © The Author 2015. Published by Oxford University Press.

Evolutionary algorithms for mobile ad hoc networks

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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 ...

Evolutionary dynamics with fluctuating population sizes and strong mutualism

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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.

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.

The curiously long absence of cooking in evolutionary thought.

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Wrangham, R

2016-06-01

Beran et al. (2015, p. 1) characterized the idea that "cooked food was integral in human evolution" as a "long-held hypothesis" favored by Darwin and Engels. In fact, however, although Darwin and Engels considered the use of cooked food to be an important influence on behavior and society, neither of them suggested that its effects were evolutionary in the sense of affecting biology. Explicit discussion of the possible evolutionary impacts of cooking did not begin until the twentieth century.

Evolutionary change in physiological phenotypes along the human lineage.

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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.

Network-level architecture and the evolutionary potential of underground metabolism.

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Notebaart, Richard A; Szappanos, Balázs; Kintses, Bálint; Pál, Ferenc; Györkei, Ádám; Bogos, Balázs; Lázár, Viktória; Spohn, Réka; Csörgő, Bálint; Wagner, Allon; Ruppin, Eytan; Pál, Csaba; Papp, Balázs

2014-08-12

A central unresolved issue in evolutionary biology is how metabolic innovations emerge. Low-level enzymatic side activities are frequent and can potentially be recruited for new biochemical functions. However, the role of such underground reactions in adaptation toward novel environments has remained largely unknown and out of reach of computational predictions, not least because these issues demand analyses at the level of the entire metabolic network. Here, we provide a comprehensive computational model of the underground metabolism in Escherichia coli. Most underground reactions are not isolated and 45% of them can be fully wired into the existing network and form novel pathways that produce key precursors for cell growth. This observation allowed us to conduct an integrated genome-wide in silico and experimental survey to characterize the evolutionary potential of E. coli to adapt to hundreds of nutrient conditions. We revealed that underground reactions allow growth in new environments when their activity is increased. We estimate that at least ∼20% of the underground reactions that can be connected to the existing network confer a fitness advantage under specific environments. Moreover, our results demonstrate that the genetic basis of evolutionary adaptations via underground metabolism is computationally predictable. The approach used here has potential for various application areas from bioengineering to medical genetics.

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

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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.

An evolutionary model of bounded rationality and intelligence.

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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

An evolutionary model of bounded rationality and intelligence.

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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

Modeling energy-economy interactions using integrated models

International Nuclear Information System (INIS)

Uyterlinde, M.A.

1994-06-01

Integrated models are defined as economic energy models that consist of several submodels, either coupled by an interface module, or embedded in one large model. These models can be used for energy policy analysis. Using integrated models yields the following benefits. They provide a framework in which energy-economy interactions can be better analyzed than in stand-alone models. Integrated models can represent both energy sector technological details, as well as the behaviour of the market and the role of prices. Furthermore, the combination of modeling methodologies in one model can compensate weaknesses of one approach with strengths of another. These advantages motivated this survey of the class of integrated models. The purpose of this literature survey therefore was to collect and to present information on integrated models. To carry out this task, several goals were identified. The first goal was to give an overview of what is reported on these models in general. The second one was to find and describe examples of such models. Other goals were to find out what kinds of models were used as component models, and to examine the linkage methodology. Solution methods and their convergence properties were also a subject of interest. The report has the following structure. In chapter 2, a 'conceptual framework' is given. In chapter 3 a number of integrated models is described. In a table, a complete overview is presented of all described models. Finally, in chapter 4, the report is summarized, and conclusions are drawn regarding the advantages and drawbacks of integrated models. 8 figs., 29 refs

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)

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

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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.

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

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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.

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...

The Importance of Multi-level Theoretical Integration in Biopsychosocial Research

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Daniel J. Kruger

2007-12-01

Full Text Available There is a growing interest in the unification of health research in a biopsychosocial framework. However, increasing specialization and advancement in instrumentation makes it more difficult to bridge understanding across areas. It would be very useful to ground biopsychosocial research in the most powerful explanatory framework in the life sciences, evolution by natural and sexual selection. This would require and explanation of the functional significance of the phenomena related to the area of study, in addition to descriptions of the mechanism. The application of an integrative evolutionary framework will be illustrated with the example of sex differences in human mortality rates, which are related to endocrine, psychological, and socio-environmental factors. The integrative evolutionary model will be contrasted with a theoretical model that acknowledges physiological and social influences, but artificially separates them.

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.

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...

Evolutionary adaptations: theoretical and practical implications for visual ergonomics.

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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.

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)

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

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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.

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

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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.

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.)

Kernel Method Based Human Model for Enhancing Interactive Evolutionary Optimization

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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

Evolutionary conceptual analysis: faith community nursing.

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Ziebarth, Deborah

2014-12-01

The aim of the study was to report an evolutionary concept analysis of faith community nursing (FCN). FCN is a source of healthcare delivery in the USA which has grown in comprehensiveness and complexity. With increasing healthcare cost and a focus on access and prevention, FCN has extended beyond the physical walls of the faith community building. Faith communities and healthcare organizations invest in FCN and standardized training programs exist. Using Rodgers' evolutionary analysis, the literature was examined for antecedents, attributes, and consequences of the concept. This design allows for understanding the historical and social nature of the concept and how it changes over time. A search of databases using the keywords FCN, faith community nurse, parish nursing, and parish nurse was done. The concept of FCN was explored using research and theoretical literature. A theoretical definition and model were developed with relevant implications. The search results netted a sample of 124 reports of research and theoretical articles from multiple disciplines: medicine, education, religion and philosophy, international health, and nursing. Theoretical definition: FCN is a method of healthcare delivery that is centered in a relationship between the nurse and client (client as person, family, group, or community). The relationship occurs in an iterative motion over time when the client seeks or is targeted for wholistic health care with the goal of optimal wholistic health functioning. Faith integrating is a continuous occurring attribute. Health promoting, disease managing, coordinating, empowering and accessing health care are other essential attributes. All essential attributes occur with intentionality in a faith community, home, health institution and other community settings with fluidity as part of a community, national, or global health initiative. A new theoretical definition and corresponding conceptual model of FCN provides a basis for future nursing

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

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

2017-05-01

Mixed models are now well-established methods in ecology and evolution because they allow accounting for and quantifying within- and between-individual variation. However, the required normal distribution of the random effects can often be violated by the presence of clusters among subjects, which leads to multi-modal distributions. In such cases, using what is known as mixture regression models might offer a more appropriate approach. These models are widely used in psychology, sociology, and medicine to describe the diversity of trajectories occurring within a population over time (e.g. psychological development, growth). In ecology and evolution, however, these models are seldom used even though understanding changes in individual trajectories is an active area of research in life-history studies. Our aim is to demonstrate the value of using mixture models to describe variation in individual life-history tactics within a population, and hence to promote the use of these models by ecologists and evolutionary ecologists. We first ran a set of simulations to determine whether and when a mixture model allows teasing apart latent clustering, and to contrast the precision and accuracy of estimates obtained from mixture models versus mixed models under a wide range of ecological contexts. We then used empirical data from long-term studies of large mammals to illustrate the potential of using mixture models for assessing within-population variation in life-history tactics. Mixture models performed well in most cases, except for variables following a Bernoulli distribution and when sample size was small. The four selection criteria we evaluated [Akaike information criterion (AIC), Bayesian information criterion (BIC), and two bootstrap methods] performed similarly well, selecting the right number of clusters in most ecological situations. We then showed that the normality of random effects implicitly assumed by evolutionary ecologists when using mixed models was often

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...

Evolutionary maintenance of filovirus-like genes in bat genomes

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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

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.

How altruism works: An evolutionary model of supply networks

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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.

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...

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.

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

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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.

Design measures in evolutionary water cooled reactors to optimize for economic viability

International Nuclear Information System (INIS)

Oh, S.J.; Yu, S.K.W.; Appell, B.

1999-01-01

Since the mid 1980s, there have been various efforts to develop evolutionary water cooled reactors based on the current operating plant experience. To sustain and improve the economic viability, particular attention has been paid to the following aspects in developing evolutionary water cooled reactors: design simplification and increased operating margins, standardization in design as well as construction and operation, integration of operating plant insights, and consideration of safety, operability and constructability during the design stage. This paper reviews each item and discusses several examples from some of the evolutionary water cooled reactors being developed. (author)

The role of evolutionary biology in research and control of liver flukes in Southeast Asia.

Science.gov (United States)

Echaubard, Pierre; Sripa, Banchob; Mallory, Frank F; Wilcox, Bruce A

2016-09-01

Stimulated largely by the availability of new technology, biomedical research at the molecular-level and chemical-based control approaches arguably dominate the field of infectious diseases. Along with this, the proximate view of disease etiology predominates to the exclusion of the ultimate, evolutionary biology-based, causation perspective. Yet, historically and up to today, research in evolutionary biology has provided much of the foundation for understanding the mechanisms underlying disease transmission dynamics, virulence, and the design of effective integrated control strategies. Here we review the state of knowledge regarding the biology of Asian liver Fluke-host relationship, parasitology, phylodynamics, drug-based interventions and liver Fluke-related cancer etiology from an evolutionary biology perspective. We consider how evolutionary principles, mechanisms and research methods could help refine our understanding of clinical disease associated with infection by Liver Flukes as well as their transmission dynamics. We identify a series of questions for an evolutionary biology research agenda for the liver Fluke that should contribute to an increased understanding of liver Fluke-associated diseases. Finally, we describe an integrative evolutionary medicine approach to liver Fluke prevention and control highlighting the need to better contextualize interventions within a broader human health and sustainable development framework. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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.

On the evolutionary origins of equity.

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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.

Spatial evolutionary epidemiology of spreading epidemics.

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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).

[Narcissism in the world of Facebook. An evolutionary psychopathological interpretation].

Science.gov (United States)

Szekeres, Adám; Tisljár, Roland

2013-01-01

In the last few decades there has been a considerable increase in the levels of narcissism among the population of individualistic, western cultures. The phenomena of narcissism induced a large number of psychological researches, some of which approaches the issue from changes in environmental factors. The modern environment of these days is substantially different from the one to which our ancestors have adapted over millions of years of evolution. The research results of narcissism from the perspective of evolutionary psychopathology approach have yet to integrate.The present review focuses on two studies and empirical findings induced by them in which an attempt is made to explore the evolutionary origins of narcissism. Relating to these studies we present the main mechanisms by which evolution may have played a role in the development and maintenance of narcissism. One of the significant elements of the current, changing social environment allowing virtual contacts is the social networking site called Facebook. Following the presentation of the main features of the site we discuss research results in connection with narcissistic traits and Facebook usage. Finally an attempt is made to integrate these findings into an evolutionary psychopathological framework.

Completely integrable operator evolutionary equations

International Nuclear Information System (INIS)

Chudnovsky, D.V.

1979-01-01

The authors present natural generalizations of classical completely integrable equations where the functions are replaced by arbitrary operators. Among these equations are the non-linear Schroedinger, the Korteweg-de Vries, and the modified KdV equations. The Lax representation and the Baecklund transformations are presented. (Auth.)

Sport science integration: An evolutionary synthesis.

Science.gov (United States)

Balagué, N; Torrents, C; Hristovski, R; Kelso, J A S

2017-02-01

The aim of the paper is to point out one way of integrating the supposedly incommensurate disciplines investigated in sports science. General, common principles can be found among apparently unrelated disciplines when the focus is put on the dynamics of sports-related phenomena. Dynamical systems approaches that have recently changed research in biological and social sciences among others, offer key concepts to create a common pluricontextual language in sport science. This common language, far from being homogenising, offers key synthesis between diverse fields, respecting and enabling the theoretical and experimental pluralism. It forms a softly integrated sports science characterised by a basic dynamic explanatory backbone as well as context-dependent theoretical flexibility. After defining the dynamic integration in living systems, unable to be captured by structural static approaches, we show the commonalities between the diversity of processes existing on different levels and time scales in biological and social entities. We justify our interpretation by drawing on some recent scientific contributions that use the same general principles and concepts, and diverse methods and techniques of data analysis, to study different types of phenomena in diverse disciplines. We show how the introduction of the dynamic framework in sport science has started to blur the boundaries between physiology, biomechanics, psychology, phenomenology and sociology. The advantages and difficulties of sport science integration and its consequences in research are also discussed.

On the Existence of Evolutionary Learning Equilibriums

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Masudul Alam Choudhury

2011-12-01

Full Text Available The usual kinds of Fixed-Point Theorems formalized on the existence of competitive equilibrium that explain much of economic theory at the core of economics can operate only on bounded and closed sets with convex mappings. But these conditions are hardly true of the real world of economic and financial complexities and perturbations. The category of learning sets explained by continuous fields of interactive, integrative and evolutionary behaviour caused by dynamic preferences at the individual and institutional and social levels cannot maintain the assumption of closed, bounded and convex sets. Thus learning sets and multi-system inter-temporal relations explained by pervasive complementarities and  participation between variables and entities, and evolution by learning, have evolutionary equilibriums. Such a study requires a new methodological approach. This paper formalizes such a methodology for evolutionary equilibriums in learning spaces. It briefly points out the universality of learning equilibriums in all mathematical structures. For a particular case though, the inter-systemic interdependence between sustainable development and ethics and economics in the specific understanding of learning domain is pointed out.

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

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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

An affinity-based evolutionary model of the diffusion of knowledge

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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

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

Diverse methods for integrable models

NARCIS (Netherlands)

Fehér, G.

2017-01-01

This thesis is centered around three topics, sharing integrability as a common theme. This thesis explores different methods in the field of integrable models. The first two chapters are about integrable lattice models in statistical physics. The last chapter describes an integrable quantum chain.

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

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.

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

Cancer treatment as a game: integrating evolutionary game theory into the optimal control of chemotherapy

International Nuclear Information System (INIS)

Orlando, Paul A; Gatenby, Robert A; Brown, Joel S

2012-01-01

Chemotherapy for metastatic cancer commonly fails due to evolution of drug resistance in tumor cells. Here, we view cancer treatment as a game in which the oncologists choose a therapy and tumors ‘choose’ an adaptive strategy. We propose the oncologist can gain an upper hand in the game by choosing treatment strategies that anticipate the adaptations of the tumor. In particular, we examine the potential benefit of exploiting evolutionary tradeoffs in tumor adaptations to therapy. We analyze a math model where cancer cells face tradeoffs in allocation of resistance to two drugs. The tumor ‘chooses’ its strategy by natural selection and the oncologist chooses her strategy by solving a control problem. We find that when tumor cells perform best by investing resources to maximize response to one drug the optimal therapy is a time-invariant delivery of both drugs simultaneously. However, if cancer cells perform better using a generalist strategy allowing resistance to both drugs simultaneously, then the optimal protocol is a time varying solution in which the two drug concentrations negatively covary. However, drug interactions can significantly alter these results. We conclude that knowledge of both evolutionary tradeoffs and drug interactions is crucial in planning optimal chemotherapy schedules for individual patients. (paper)

Cancer treatment as a game: integrating evolutionary game theory into the optimal control of chemotherapy

Science.gov (United States)

Orlando, Paul A.; Gatenby, Robert A.; Brown, Joel S.

2012-12-01

Chemotherapy for metastatic cancer commonly fails due to evolution of drug resistance in tumor cells. Here, we view cancer treatment as a game in which the oncologists choose a therapy and tumors ‘choose’ an adaptive strategy. We propose the oncologist can gain an upper hand in the game by choosing treatment strategies that anticipate the adaptations of the tumor. In particular, we examine the potential benefit of exploiting evolutionary tradeoffs in tumor adaptations to therapy. We analyze a math model where cancer cells face tradeoffs in allocation of resistance to two drugs. The tumor ‘chooses’ its strategy by natural selection and the oncologist chooses her strategy by solving a control problem. We find that when tumor cells perform best by investing resources to maximize response to one drug the optimal therapy is a time-invariant delivery of both drugs simultaneously. However, if cancer cells perform better using a generalist strategy allowing resistance to both drugs simultaneously, then the optimal protocol is a time varying solution in which the two drug concentrations negatively covary. However, drug interactions can significantly alter these results. We conclude that knowledge of both evolutionary tradeoffs and drug interactions is crucial in planning optimal chemotherapy schedules for individual patients.

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

Optimum dispatching by using evolutionary programming; Despacho optimo utilizando programacao evolucionaria

Energy Technology Data Exchange (ETDEWEB)

Proenca, Luis Miguel; Pinto, Joao Luis; Matos, Manuel Antonio [Instituto de Engenharia de Sistemas e Computadores (INESC), Porto (Portugal). E-mail: lproenca@inescn.pt; jpinto@duque.inescn.pt; mmatos@inescn.pt

1999-07-01

This paper presents a methodology for solving the problem of the optimum dispatching based on the Evolutionary Programming. Also, a software module is described which is based on this integrated approach, integrated in a real system for power systems control and having a high contribution from renewable resources, in the framework of the CARE European project.

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).

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.

Developing Integrated Care: Towards a development model for integrated care

NARCIS (Netherlands)

M.M.N. Minkman (Mirella)

2012-01-01

textabstractThe thesis adresses the phenomenon of integrated care. The implementation of integrated care for patients with a stroke or dementia is studied. Because a generic quality management model for integrated care is lacking, the study works towards building a development model for integrated

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...

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...

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...

Integrated approach for sinkhole evaluation and evolution prediction in the Central Ebro Basin (NE Spain

Directory of Open Access Journals (Sweden)

Oscar Pueyo Anchuela

2017-06-01

Full Text Available Evaluation of karst hazards benefits from the integration of different techniques, methodologies and approaches. Each one presents a different signature and is sensitive to certain indicators related to karst hazards. In some cases, detailed analysis permits the evaluation of representativeness either from isolated approaches or by means of integrated analyses. In this study, we present the evaluation of an area with high density of karstic collapses at different evolutionary stages through the integration of surficial, historical, geomorphological and geophysical data in order to finally define the evolutionary model for karst activity development. The obtained dataset permits to identify different steps in sinkhole evolution: (i cavities and open sinkholes, (ii filling of these cavities, with materials having different signatures, (iii the progression from collapses to subsidence sinkholes and (iv enlargement through collapses in marginal areas of previous sinkholes. The presence of different stages of this evolutionary model permits to determine their own signatures that can be of application in contexts where analysis cannot be so systematic and also to evaluate the definition of the marginal areas of previous sinkholes as the most hazardous sectors.

Social Integration and Sleep Disturbance: A Gene-Environment Interaction Study

Directory of Open Access Journals (Sweden)

David A. Sbarra

2016-03-01

Full Text Available Objective: Low levels of perceived social integration, or loneliness, are associated with increased risk for a range of poor health outcomes. Sleep disturbance plays a central role in the evolutionary theory of loneliness, which provides a mechanistic account of how low levels of social integration may negatively impact health. No studies, however, have examined whether the association between social integration and sleep disturbance is consistent with a causal effect after accounting for genes that are common to both variables.  Method: Using twin data ('N' = 905 twin pairs from the nationally-representative Midlife in the United States (MIDUS survey, I evaluated a series of bivariate twin models exploring whether the phenotypic association between low social integration and sleep disturbance can be explained by shared genetics. In addition, the current study specified a series of quantitative models for studying gene x environment (G X E interactions to determine whether the genetic and environmental influences on sleep disturbance differ as a function of social integration. Results: The phenotypic association between social integration and sleep disturbance was fully accounted for by genes that are common between the two variables, suggesting that within-twin pair differences in social integration do not exert a causal influence on sleep disturbance. Social integration, however, moderated the non-shared environmental influence on sleep disturbances, with the greatest environmental influences observed at the lowest levels of social integration. Conclusions: The results of this study suggest that an essential feature of the evolutionary model of loneliness may need refinement or elaboration. The moderation findings are discussed in terms of the fit with a stress-buffering model of social support in which environmental influences on sleep disturbance are strongest when social resources are low.

Evolution and development: some insights from evolutionary theory

Directory of Open Access Journals (Sweden)

DAVID JEAN R.

2001-01-01

Full Text Available Developmental biology and evolutionary biology are both mature integrative disciplines which started in the 19th century and then followed parallel and independent scientific pathways. Recently, a genetical component has stepped into both disciplines (developmental genetics and evolutionary genetics pointing out the need for future convergent maturation. Indeed, the Evo-Devo approach is becoming popular among developmental biologists, based on the facts that distant groups share a common ancestry, that precise phylogenies can be worked out and that homologous genes often play similar roles during the development of very different organisms. In this essay, I try to show that the real future of Evo-Devo thinking is still broader. The evolutionary theory is a set of diverse concepts which can and should be used in any biological field. Evolutionary thinking trains to ask « why » questions and to provide logical and plausible answers. It can shed some light on a diversity of general problems such as how to distinguish homologies from analogies, the costs and benefits of multicellularity, the origin of novel structures (e.g. the head, or the evolution of sexual reproduction. In the next decade, we may expect a progressive convergence between developmental genetics and quantitative genetics.

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.

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.

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.

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)

Tumor evolutionary directed graphs and the history of chronic lymphocytic leukemia.

Science.gov (United States)

Wang, Jiguang; Khiabanian, Hossein; Rossi, Davide; Fabbri, Giulia; Gattei, Valter; Forconi, Francesco; Laurenti, Luca; Marasca, Roberto; Del Poeta, Giovanni; Foà, Robin; Pasqualucci, Laura; Gaidano, Gianluca; Rabadan, Raul

2014-12-11

Cancer is a clonal evolutionary process, caused by successive accumulation of genetic alterations providing milestones of tumor initiation, progression, dissemination, and/or resistance to certain therapeutic regimes. To unravel these milestones we propose a framework, tumor evolutionary directed graphs (TEDG), which is able to characterize the history of genetic alterations by integrating longitudinal and cross-sectional genomic data. We applied TEDG to a chronic lymphocytic leukemia (CLL) cohort of 70 patients spanning 12 years and show that: (a) the evolution of CLL follows a time-ordered process represented as a global flow in TEDG that proceeds from initiating events to late events; (b) there are two distinct and mutually exclusive evolutionary paths of CLL evolution; (c) higher fitness clones are present in later stages of the disease, indicating a progressive clonal replacement with more aggressive clones. Our results suggest that TEDG may constitute an effective framework to recapitulate the evolutionary history of tumors.

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

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.

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.

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

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.

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.

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...

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.

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

Integrating Traditional and Evolutionary Knowledge in Biodiversity Conservation: a Population Level Case Study

Directory of Open Access Journals (Sweden)

Dylan J. Fraser

2006-12-01

Full Text Available Despite their dual importance in the assessment of endangered/threatened species, there have been few attempts to integrate traditional ecological knowledge (TEK and evolutionary biology knowledge (EBK at the population level. We contrasted long-term aboriginal TEK with previously obtained EBK in the context of seasonal migratory habits and population biology of a salmonid fish, brook charr, (Salvelinus fontinalis inhabiting a large, remote postglacial lake. Compilation of TEK spanning four decades involved analytical workshops, semidirective interviews, and collaborative fieldwork with local aboriginal informants and fishing guides. We found that TEK complemented EBK of brook charr by providing concordant and additional information about (1 population viability; (2 breeding areas and migration patterns of divergent populations; and (3 the behavioral ecology of populations within feeding areas; all of which may ultimately affect the maintenance of population diversity. Aboriginal concerns related to human pressures on this species, not revealed by EBK, also help to focus future conservation initiatives for divergent populations and to encourage restoration of traditional fishing practices. However, relative to EBK, the relevance of TEK to salmonid biodiversity conservation was evident mainly at a smaller spatial scale, for example, that of individual rivers occupied by populations or certain lake sectors. Nevertheless, EBK was only collected over a 4-yr period, so TEK provided an essential long-term temporal window to evaluate population differences and persistence. We concluded that, despite different conceptual underpinnings, spatially and temporally varying TEK and EBK both contribute to the knowledge base required to achieve sustainability and effective biodiversity conservation planning for a given species. Such integration may be particularly relevant in many isolated regions, where intraspecific diversity can go unrecognized due to sparse

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...

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.

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.

Ancient Biomolecules and Evolutionary Inference.

Science.gov (United States)

Cappellini, Enrico; Prohaska, Ana; Racimo, Fernando; Welker, Frido; Pedersen, Mikkel Winther; Allentoft, Morten E; de Barros Damgaard, Peter; Gutenbrunner, Petra; Dunne, Julie; Hammann, Simon; Roffet-Salque, Mélanie; Ilardo, Melissa; Moreno-Mayar, J Víctor; Wang, Yucheng; Sikora, Martin; Vinner, Lasse; Cox, Jürgen; Evershed, Richard P; Willerslev, Eske

2018-04-25

Over the last decade, studies of ancient biomolecules-particularly ancient DNA, proteins, and lipids-have revolutionized our understanding of evolutionary history. Though initially fraught with many challenges, the field now stands on firm foundations. Researchers now successfully retrieve nucleotide and amino acid sequences, as well as lipid signatures, from progressively older samples, originating from geographic areas and depositional environments that, until recently, were regarded as hostile to long-term preservation of biomolecules. Sampling frequencies and the spatial and temporal scope of studies have also increased markedly, and with them the size and quality of the data sets generated. This progress has been made possible by continuous technical innovations in analytical methods, enhanced criteria for the selection of ancient samples, integrated experimental methods, and advanced computational approaches. Here, we discuss the history and current state of ancient biomolecule research, its applications to evolutionary inference, and future directions for this young and exciting field. Expected final online publication date for the Annual Review of Biochemistry Volume 87 is June 20, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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.

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.

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.

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.

An Evolutionary Complex Systems Decision-Support Tool for the Management of Operations

International Nuclear Information System (INIS)

Baldwin, J S; Allen, P M; Ridgway, K

2011-01-01

This research aimed to add both to the development of complex systems thinking in the subject area of Operations and Production Management and to the limited number of applications of computational models and simulations from the science of complex systems. The latter potentially offer helpful decision-support tools for operations and production managers. A mechanical engineering firm was used as a case study where a combined qualitative and quantitative methodological approach was employed to extract the required data from four senior managers. Company performance measures as well as firm technologies, practices and policies, and their relation and interaction with one another, were elicited. The data were subjected to an evolutionary complex systems model resulting in a series of simulations. The findings included both reassuring and some unexpected results. The simulation based on the CEO's opinions led the most cohesive and synergistic collection of practices describing the firm, closely followed by the Marketing and R and D Managers. The Manufacturing Manager's responses led to the most extreme evolutionary trajectory where the integrity of the entire firm came into question particularly when considering how employees were utilised. By drawing directly from the opinions and views of managers rather than from logical 'if-then' rules and averaged mathematical representations of agents that characterise agent-based and other self-organisational models, this work builds on previous applications by capturing a micro-level description of diversity and a learning effect that has been problematical not only in terms of theory but also in application. This approach can be used as a decision-support tool for operations and other managers providing a forum with which to explore a) the strengths, weaknesses and consequences of different decision-making capacities within the firm; b) the introduction of new manufacturing technologies, practices and policies; and, c) the

An Evolutionary Complex Systems Decision-Support Tool for the Management of Operations

Science.gov (United States)

Baldwin, J. S.; Allen, P. M.; Ridgway, K.

2011-12-01

This research aimed to add both to the development of complex systems thinking in the subject area of Operations and Production Management and to the limited number of applications of computational models and simulations from the science of complex systems. The latter potentially offer helpful decision-support tools for operations and production managers. A mechanical engineering firm was used as a case study where a combined qualitative and quantitative methodological approach was employed to extract the required data from four senior managers. Company performance measures as well as firm technologies, practices and policies, and their relation and interaction with one another, were elicited. The data were subjected to an evolutionary complex systems model resulting in a series of simulations. The findings included both reassuring and some unexpected results. The simulation based on the CEO's opinions led the most cohesive and synergistic collection of practices describing the firm, closely followed by the Marketing and R&D Managers. The Manufacturing Manager's responses led to the most extreme evolutionary trajectory where the integrity of the entire firm came into question particularly when considering how employees were utilised. By drawing directly from the opinions and views of managers rather than from logical 'if-then' rules and averaged mathematical representations of agents that characterise agent-based and other self-organisational models, this work builds on previous applications by capturing a micro-level description of diversity and a learning effect that has been problematical not only in terms of theory but also in application. This approach can be used as a decision-support tool for operations and other managers providing a forum with which to explore a) the strengths, weaknesses and consequences of different decision-making capacities within the firm; b) the introduction of new manufacturing technologies, practices and policies; and, c) the

Compassion: An Evolutionary Analysis and Empirical Review

OpenAIRE

Goetz, Jennifer L.; Keltner, Dacher; Simon-Thomas, Emiliana

2010-01-01

What is compassion? And how did it evolve? In this review, we integrate three evolutionary arguments that converge on the hypothesis that compassion evolved as a distinct affective experience whose primary function is to facilitate cooperation and protection of the weak and those who suffer. Our empirical review reveals compassion to have distinct appraisal processes attuned to undeserved suffering, distinct signaling behavior related to caregiving patterns of touch, posture, and vocalization...

Qualitative Analysis of Integration Adapter Modeling

OpenAIRE

Ritter, Daniel; Holzleitner, Manuel

2015-01-01

Integration Adapters are a fundamental part of an integration system, since they provide (business) applications access to its messaging channel. However, their modeling and configuration remain under-represented. In previous work, the integration control and data flow syntax and semantics have been expressed in the Business Process Model and Notation (BPMN) as a semantic model for message-based integration, while adapter and the related quality of service modeling were left for further studi...

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.

Integrability of the Rabi Model

International Nuclear Information System (INIS)

Braak, D.

2011-01-01

The Rabi model is a paradigm for interacting quantum systems. It couples a bosonic mode to the smallest possible quantum model, a two-level system. I present the analytical solution which allows us to consider the question of integrability for quantum systems that do not possess a classical limit. A criterion for quantum integrability is proposed which shows that the Rabi model is integrable due to the presence of a discrete symmetry. Moreover, I introduce a generalization with no symmetries; the generalized Rabi model is the first example of a nonintegrable but exactly solvable system.

On the numerical treatment of selected oscillatory evolutionary problems

Science.gov (United States)

Cardone, Angelamaria; Conte, Dajana; D'Ambrosio, Raffaele; Paternoster, Beatrice

2017-07-01

We focus on evolutionary problems whose qualitative behaviour is known a-priori and exploited in order to provide efficient and accurate numerical schemes. For classical numerical methods, depending on constant coefficients, the required computational effort could be quite heavy, due to the necessary employ of very small stepsizes needed to accurately reproduce the qualitative behaviour of the solution. In these situations, it may be convenient to use special purpose formulae, i.e. non-polynomially fitted formulae on basis functions adapted to the problem (see [16, 17] and references therein). We show examples of special purpose strategies to solve two families of evolutionary problems exhibiting periodic solutions, i.e. partial differential equations and Volterra integral equations.

First insights into the evolutionary history of the Davallia repens complex

NARCIS (Netherlands)

Chen, C.-W.; Ngan, L.T.; Hidayat, A.; Evangelista, L.; Nooteboom, H.P.; Chiou, W.-L.

2014-01-01

Davallia repens and its close relatives have been identified as a species complex in this study because of the existence of continuously morphological variation. To decipher its evolutionary history, integrated methodologies were applied in this study including morphology, cytology, reproductive

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.

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.

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.

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.

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.

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.

Understanding the function of bacterial and eukaryotic thiolases II by integrating evolutionary and functional approaches.

Science.gov (United States)

Fox, Ana Romina; Soto, Gabriela; Mozzicafreddo, Matteo; Garcia, Araceli Nora; Cuccioloni, Massimiliano; Angeletti, Mauro; Salerno, Juan Carlos; Ayub, Nicolás Daniel

2014-01-01

Acetoacetyl-CoA thiolase (EC 2.3.1.9), commonly named thiolase II, condenses two molecules of acetyl-CoA to give acetoacetyl-CoA and CoA. This enzyme acts in anabolic processes as the first step in the biosynthesis of isoprenoids and polyhydroxybutyrate in eukaryotes and bacteria, respectively. We have recently reported the evolutionary and functional equivalence of these enzymes, suggesting that thiolase II could be the rate limiting enzyme in these pathways and presented evidence indicating that this enzyme modulates the availability of reducing equivalents during abiotic stress adaptation in bacteria and plants. However, these results are not sufficient to clarify why thiolase II was evolutionary selected as a critical enzyme in the production of antioxidant compounds. Regarding this intriguing topic, we propose that thiolase II could sense changes in the acetyl-CoA/CoA ratio induced by the inhibition of the tricarboxylic acid cycle under abiotic stress. Thus, the high level of evolutionary and functional constraint of thiolase II may be due to the connection of this enzyme with an ancient and conserved metabolic route. © 2013.

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).

Topological quantum theories and integrable models

International Nuclear Information System (INIS)

Keski-Vakkuri, E.; Niemi, A.J.; Semenoff, G.; Tirkkonen, O.

1991-01-01

The path-integral generalization of the Duistermaat-Heckman integration formula is investigated for integrable models. It is shown that for models with periodic classical trajectories the path integral reduces to a form similar to the finite-dimensional Duistermaat-Heckman integration formula. This provides a relation between exactness of the stationary-phase approximation and Morse theory. It is also argued that certain integrable models can be related to topological quantum theories. Finally, it is found that in general the stationary-phase approximation presumes that the initial and final configurations are in different polarizations. This is exemplified by the quantization of the SU(2) coadjoint orbit

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.

Corporate Social Responsibility Agreements Model for Community ...

African Journals Online (AJOL)

Corporate Social Responsibility Agreements Model for Community ... their host communities with concomitant adverse effect on mining operations. ... sustainable community development an integral part of the mining business. This paper presents the evolutionary strategic models, with differing principles and action plans, ...

[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.

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

Business and technology integrated model

OpenAIRE

Noce, Irapuan; Carvalho, João Álvaro

2011-01-01

There is a growing interest in business modeling and architecture in the areas of management and information systems. One of the issues in the area is the lack of integration between the modeling techniques that are employed to support business development and those used for technology modeling. This paper proposes a modeling approach that is capable of integrating the modeling of the business and of the technology. By depicting the business model, the organization structure and the technolog...

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...

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.

An open future for ecological and evolutionary data?

Science.gov (United States)

Kenall, Amye; Harold, Simon; Foote, Christopher

2014-04-02

As part of BioMed Central's open science mission, we are pleased to announce that two of our journals have integrated with the open data repository Dryad. Authors submitting their research to either BMC Ecology or BMC Evolutionary Biology will now have the opportunity to deposit their data directly into the Dryad archive and will receive a permanent, citable link to their dataset. Although this does not affect any of our current data deposition policies at these journals, we hope to encourage a more widespread adoption of open data sharing in the fields of ecology and evolutionary biology by facilitating this process for our authors. We also take this opportunity to discuss some of the wider issues that may concern researchers when making their data openly available. Although we offer a number of positive examples from different fields of biology, we also recognise that reticence to data sharing still exists, and that change must be driven from within research communities in order to create future science that is fit for purpose in the digital age. This editorial was published jointly in both BMC Ecology and BMC Evolutionary Biology.

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.

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.

INTEGRATED CORPORATE STRATEGY MODEL

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CATALINA SORIANA SITNIKOV

2014-02-01

Full Text Available Corporations are at present operating in demanding and highly unsure periods, facing a mixture of increased macroeconomic need, competitive and capital market dangers, and in many cases, the prospect for significant technical and regulative gap. Throughout these demanding and highly unsure times, the corporations must pay particular attention to corporate strategy. In present times, corporate strategy must be perceived and used as a function of various fields, covers, and characters as well as a highly interactive system. For the corporation's strategy to become a competitive advantage is necessary to understand and also to integrate it in a holistic model to ensure sustainable progress of corporation activities under the optimum conditions of profitability. The model proposed in this paper is aimed at integrating the two strategic models, Hoshin Kanri and Integrated Strategy Model, as well as their consolidation with the principles of sound corporate governance set out by the OECD.

The evolution of ecosystem ascendency in a complex systems based model.

Science.gov (United States)

Brinck, Katharina; Jensen, Henrik Jeldtoft

2017-09-07

General patterns in ecosystem development can shed light on driving forces behind ecosystem formation and recovery and have been of long interest. In recent years, the need for integrative and process oriented approaches to capture ecosystem growth, development and organisation, as well as the scope of information theory as a descriptive tool has been addressed from various sides. However data collection of ecological network flows is difficult and tedious and comprehensive models are lacking. We use a hierarchical version of the Tangled Nature Model of evolutionary ecology to study the relationship between structure, flow and organisation in model ecosystems, their development over evolutionary time scales and their relation to ecosystem stability. Our findings support the validity of ecosystem ascendency as a meaningful measure of ecosystem organisation, which increases over evolutionary time scales and significantly drops during periods of disturbance. The results suggest a general trend towards both higher integrity and increased stability driven by functional and structural ecosystem coadaptation. Copyright © 2017 Elsevier Ltd. All rights reserved.

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...

Cooperation and conflict in cancer: An evolutionary perspective

Directory of Open Access Journals (Sweden)

Jonathan Featherston

2012-09-01

Full Text Available Evolutionary approaches to carcinogenesis have gained prominence in the literature and enhanced our understanding of cancer. However, an appreciation of neoplasia in the context of evolutionary transitions, particularly the transition from independent genes to a fullyintegrated genome, is largely absent. In the gene–genome evolutionary transition, mobile genetic elements (MGEs can be studied as the extant exemplars of selfish autonomous lowerlevel units that cooperated to form a higher-level, functionally integrated genome. Here,we discuss levels of selection in cancer cells. In particular, we examine the tension between gene and genome units of selection by examining the expression profiles of MGE domains in an array of human cancers. Overall, across diverse cancers, there is an aberrant expression of several families of mobile elements, including the most common MGE in the human genome, retrotransposon LINE 1. These results indicate an alternative life-history strategy for MGEs in the cancers studied. Whether the aberrant expression is the cause or effect oftumourigenesis is unknown, although some evidence suggests that dysregulation of MGEs can play a role in cancer origin and progression. These data are interpreted in combination with phylostratigraphic reports correlating the origin of cancer genes with multicellularity and other potential increases in complexity in cancer cell populations. Cooperation and conflict between individuals at the gene, genome and cell level provide an evolutionary medicineperspective of cancer that enhances our understanding of disease pathogenesis and treatment.

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...

Evolutionary Awareness

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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.

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.

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.

The origins of pedagogy: developmental and evolutionary perspectives.

Science.gov (United States)

Skerry, Amy E; Lambert, Enoch; Powell, Lindsey J; McAuliffe, Katherine

2013-07-18

The question of whether and how information is actively transferred from knowledgeable to ignorant individuals has received much attention in psychology and evolutionary biology. Research in these fields has proceeded largely independently, with studies of nonhuman animals focusing on knowledgeable individuals and whether or not they meet a functional definition of teaching, while studies of children focus on the learner's assumptions and inferences. We argue that a comprehensive theory of teaching will benefit from integrating perspectives and empirical phenomena from evolutionary and developmental disciplines. In this review, we identify cases of seemingly purposeful information transfer (i.e. teaching) in human and nonhuman animals, discuss what is known about the cognitive processes that support teaching in different species, and highlight ways in which each discipline might be informed by extant theories and empirical tools from the other.

Separations and safeguards model integration.

Energy Technology Data Exchange (ETDEWEB)

Cipiti, Benjamin B.; Zinaman, Owen

2010-09-01

Research and development of advanced reprocessing plant designs can greatly benefit from the development of a reprocessing plant model capable of transient solvent extraction chemistry. This type of model can be used to optimize the operations of a plant as well as the designs for safeguards, security, and safety. Previous work has integrated a transient solvent extraction simulation module, based on the Solvent Extraction Process Having Interaction Solutes (SEPHIS) code developed at Oak Ridge National Laboratory, with the Separations and Safeguards Performance Model (SSPM) developed at Sandia National Laboratory, as a first step toward creating a more versatile design and evaluation tool. The goal of this work was to strengthen the integration by linking more variables between the two codes. The results from this integrated model show expected operational performance through plant transients. Additionally, ORIGEN source term files were integrated into the SSPM to provide concentrations, radioactivity, neutron emission rate, and thermal power data for various spent fuels. This data was used to generate measurement blocks that can determine the radioactivity, neutron emission rate, or thermal power of any stream or vessel in the plant model. This work examined how the code could be expanded to integrate other separation steps and benchmark the results to other data. Recommendations for future work will be presented.

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.

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 ...

Basic emotions and adaptation. A computational and evolutionary model.

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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

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

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.

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

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.

Evolutionary design assistants for architecture

Directory of Open Access Journals (Sweden)

N. Onur Sönmez

2015-04-01

existing literature and the proposals and applications of the thesis; secondly, proposals for descriptive and prescriptive models, mappings, summary illustrations, task structures, decomposition schemes, and integratory frameworks; and finally, experimental applications of these proposals. This tripartite progression allows an evaluation of each proposal both conceptually and practically; thereby, enabling a progressive improvement of the understanding regarding the research question, while producing concrete outputs on the way. Besides theoretical and interpretative examinations, the thesis investigates its subject through a set of practical and speculative proposals, which function as both research instruments and the outputs of the study. The first main output of the study is the “design_proxy” approach (d_p, which is an integrated approach for draft making design assistants. It is an outcome of both theoretical examinations and experimental applications, and proposes an integration of, (1 flexible and relaxed task definitions and representations (instead of strict formalisms, (2 intuitive interfaces that make use of usual design media, (3 evaluation of solution proposals through their similarity to given examples, and (4 a dynamic evolutionary approach for solution generation. The design_proxy approach may be useful for AD researchers that aim at developing practical design assistants, as has been examined and demonstrated with the two applications, i.e., design_proxy.graphics and design_proxy.layout. The second main output, the “Interleaved Evolutionary Algorithm” (IEA, or Interleaved EA is a novel evolutionary algorithm proposed and used as the underlying generative mechanism of design_proxybased design assistants. The Interleaved EA is a dynamic, adaptive, and multi-objective EA, in which one of the objectives leads the evolution until its fitness progression stagnates; in the sense that the settings and fitness values of this objective is used for most

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.

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.

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.

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

Integrated Inflammatory Stress (ITIS) Model

DEFF Research Database (Denmark)

Bangsgaard, Elisabeth O.; Hjorth, Poul G.; Olufsen, Mette S.

2017-01-01

maintains a long-term level of the stress hormone cortisol which is also anti-inflammatory. A new integrated model of the interaction between these two subsystems of the inflammatory system is proposed and coined the integrated inflammatory stress (ITIS) model. The coupling mechanisms describing....... A constant activation results in elevated levels of the variables in the model while a prolonged change of the oscillations in ACTH and cortisol concentrations is the most pronounced result of different LPS doses predicted by the model....

Non-integrable quantum field theories as perturbations of certain integrable models

International Nuclear Information System (INIS)

Delfino, G.; Simonetti, P.

1996-03-01

We approach the study of non-integrable models of two-dimensional quantum field theory as perturbations of the integrable ones. By exploiting the knowledge of the exact S-matrix and Form Factors of the integrable field theories we obtain the first order corrections to the mass ratios, the vacuum energy density and the S-matrix of the non-integrable theories. As interesting applications of the formalism, we study the scaling region of the Ising model in an external magnetic field at T ∼ T c and the scaling region around the minimal model M 2 , τ . For these models, a remarkable agreement is observed between the theoretical predictions and the data extracted by a numerical diagonalization of their Hamiltonian. (author). 41 refs, 9 figs, 1 tab

An architecture for integration of multidisciplinary models

DEFF Research Database (Denmark)

Belete, Getachew F.; Voinov, Alexey; Holst, Niels

2014-01-01

Integrating multidisciplinary models requires linking models: that may operate at different temporal and spatial scales; developed using different methodologies, tools and techniques; different levels of complexity; calibrated for different ranges of inputs and outputs, etc. On the other hand......, Enterprise Application Integration, and Integration Design Patterns. We developed an architecture of a multidisciplinary model integration framework that brings these three aspects of integration together. Service-oriented-based platform independent architecture that enables to establish loosely coupled...

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.

Evolutionary conservation and changes in insect TRP channels

OpenAIRE

Tominaga Makoto; Kohno Keigo; Sokabe Takaaki; Matsuura Hironori; Kadowaki Tatsuhiko

2009-01-01

Abstract Background TRP (Transient Receptor Potential) channels respond to diverse stimuli and thus function as the primary integrators of varied sensory information. They are also activated by various compounds and secondary messengers to mediate cell-cell interactions as well as to detect changes in the local environment. Their physiological roles have been primarily characterized only in mice and fruit flies, and evolutionary studies are limited. To understand the evolution of insect TRP c...

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.

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.

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.

Data assimilation in integrated hydrological modelling

DEFF Research Database (Denmark)

Rasmussen, Jørn

Integrated hydrological models are useful tools for water resource management and research, and advances in computational power and the advent of new observation types has resulted in the models generally becoming more complex and distributed. However, the models are often characterized by a high...... degree of parameterization which results in significant model uncertainty which cannot be reduced much due to observations often being scarce and often taking the form of point measurements. Data assimilation shows great promise for use in integrated hydrological models , as it allows for observations...... to be efficiently combined with models to improve model predictions, reduce uncertainty and estimate model parameters. In this thesis, a framework for assimilating multiple observation types and updating multiple components and parameters of a catchment scale integrated hydrological model is developed and tested...

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.

Development of antibiotic regimens using graph based evolutionary algorithms.

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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.

MEGA-CC: computing core of molecular evolutionary genetics analysis program for automated and iterative data analysis.

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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/.

Enabling model customization and integration

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Park, Minho; Fishwick, Paul A.

2003-09-01

Until fairly recently, the idea of dynamic model content and presentation were treated synonymously. For example, if one was to take a data flow network, which captures the dynamics of a target system in terms of the flow of data through nodal operators, then one would often standardize on rectangles and arrows for the model display. The increasing web emphasis on XML, however, suggests that the network model can have its content specified in an XML language, and then the model can be represented in a number of ways depending on the chosen style. We have developed a formal method, based on styles, that permits a model to be specified in XML and presented in 1D (text), 2D, and 3D. This method allows for customization and personalization to exert their benefits beyond e-commerce, to the area of model structures used in computer simulation. This customization leads naturally to solving the bigger problem of model integration - the act of taking models of a scene and integrating them with that scene so that there is only one unified modeling interface. This work focuses mostly on customization, but we address the integration issue in the future work section.

Integrated modelling in materials and process technology

DEFF Research Database (Denmark)

Hattel, Jesper Henri

2008-01-01

Integrated modelling of entire process sequences and the subsequent in-service conditions, and multiphysics modelling of the single process steps are areas that increasingly support optimisation of manufactured parts. In the present paper, three different examples of modelling manufacturing...... processes from the viewpoint of combined materials and process modelling are presented: solidification of thin walled ductile cast iron, integrated modelling of spray forming and multiphysics modelling of friction stir welding. The fourth example describes integrated modelling applied to a failure analysis...

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...

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

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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.

An integrated development environment for PMESII model authoring, integration, validation, and debugging

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Pioch, Nicholas J.; Lofdahl, Corey; Sao Pedro, Michael; Krikeles, Basil; Morley, Liam

2007-04-01

To foster shared battlespace awareness in Air Operations Centers supporting the Joint Forces Commander and Joint Force Air Component Commander, BAE Systems is developing a Commander's Model Integration and Simulation Toolkit (CMIST), an Integrated Development Environment (IDE) for model authoring, integration, validation, and debugging. CMIST is built on the versatile Eclipse framework, a widely used open development platform comprised of extensible frameworks that enable development of tools for building, deploying, and managing software. CMIST provides two distinct layers: 1) a Commander's IDE for supporting staff to author models spanning the Political, Military, Economic, Social, Infrastructure, Information (PMESII) taxonomy; integrate multiple native (third-party) models; validate model interfaces and outputs; and debug the integrated models via intuitive controls and time series visualization, and 2) a PMESII IDE for modeling and simulation developers to rapidly incorporate new native simulation tools and models to make them available for use in the Commander's IDE. The PMESII IDE provides shared ontologies and repositories for world state, modeling concepts, and native tool characterization. CMIST includes extensible libraries for 1) reusable data transforms for semantic alignment of native data with the shared ontology, and 2) interaction patterns to synchronize multiple native simulations with disparate modeling paradigms, such as continuous-time system dynamics, agent-based discrete event simulation, and aggregate solution methods such as Monte Carlo sampling over dynamic Bayesian networks. This paper describes the CMIST system architecture, our technical approach to addressing these semantic alignment and synchronization problems, and initial results from integrating Political-Military-Economic models of post-war Iraq spanning multiple modeling paradigms.

Open source integrated modeling environment Delta Shell

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Donchyts, G.; Baart, F.; Jagers, B.; van Putten, H.

2012-04-01

In the last decade, integrated modelling has become a very popular topic in environmental modelling since it helps solving problems, which is difficult to model using a single model. However, managing complexity of integrated models and minimizing time required for their setup remains a challenging task. The integrated modelling environment Delta Shell simplifies this task. The software components of Delta Shell are easy to reuse separately from each other as well as a part of integrated environment that can run in a command-line or a graphical user interface mode. The most components of the Delta Shell are developed using C# programming language and include libraries used to define, save and visualize various scientific data structures as well as coupled model configurations. Here we present two examples showing how Delta Shell simplifies process of setting up integrated models from the end user and developer perspectives. The first example shows coupling of a rainfall-runoff, a river flow and a run-time control models. The second example shows how coastal morphological database integrates with the coastal morphological model (XBeach) and a custom nourishment designer. Delta Shell is also available as open-source software released under LGPL license and accessible via http://oss.deltares.nl.

IDEA: Interactive Display for Evolutionary Analyses.

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Egan, Amy; Mahurkar, Anup; Crabtree, Jonathan; Badger, Jonathan H; Carlton, Jane M; Silva, Joana C

2008-12-08

The availability of complete genomic sequences for hundreds of organisms promises to make obtaining genome-wide estimates of substitution rates, selective constraints and other molecular evolution variables of interest an increasingly important approach to addressing broad evolutionary questions. Two of the programs most widely used for this purpose are codeml and baseml, parts of the PAML (Phylogenetic Analysis by Maximum Likelihood) suite. A significant drawback of these programs is their lack of a graphical user interface, which can limit their user base and considerably reduce their efficiency. We have developed IDEA (Interactive Display for Evolutionary Analyses), an intuitive graphical input and output interface which interacts with PHYLIP for phylogeny reconstruction and with codeml and baseml for molecular evolution analyses. IDEA's graphical input and visualization interfaces eliminate the need to edit and parse text input and output files, reducing the likelihood of errors and improving processing time. Further, its interactive output display gives the user immediate access to results. Finally, IDEA can process data in parallel on a local machine or computing grid, allowing genome-wide analyses to be completed quickly. IDEA provides a graphical user interface that allows the user to follow a codeml or baseml analysis from parameter input through to the exploration of results. Novel options streamline the analysis process, and post-analysis visualization of phylogenies, evolutionary rates and selective constraint along protein sequences simplifies the interpretation of results. The integration of these functions into a single tool eliminates the need for lengthy data handling and parsing, significantly expediting access to global patterns in the data.

Evolutionary conservation and changes in insect TRP channels.

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Matsuura, Hironori; Sokabe, Takaaki; Kohno, Keigo; Tominaga, Makoto; Kadowaki, Tatsuhiko

2009-09-10

TRP (Transient Receptor Potential) channels respond to diverse stimuli and thus function as the primary integrators of varied sensory information. They are also activated by various compounds and secondary messengers to mediate cell-cell interactions as well as to detect changes in the local environment. Their physiological roles have been primarily characterized only in mice and fruit flies, and evolutionary studies are limited. To understand the evolution of insect TRP channels and the mechanisms of integrating sensory inputs in insects, we have identified and compared TRP channel genes in Drosophila melanogaster, Bombyx mori, Tribolium castaneum, Apis mellifera, Nasonia vitripennis, and Pediculus humanus genomes as part of genome sequencing efforts. All the insects examined have 2 TRPV, 1 TRPN, 1 TRPM, 3 TRPC, and 1 TRPML subfamily members, demonstrating that these channels have the ancient origins in insects. The common pattern also suggests that the mechanisms for detecting mechanical and visual stimuli and maintaining lysosomal functions may be evolutionarily well conserved in insects. However, a TRPP channel, the most ancient TRP channel, is missing in B. mori, A. mellifera, and N. vitripennis. Although P. humanus and D. melanogaster contain 4 TRPA subfamily members, the other insects have 5 TRPA subfamily members. T. castaneum, A. mellifera, and N. vitripennis contain TRPA5 channels, which have been specifically retained or gained in Coleoptera and Hymenoptera. Furthermore, TRPA1, which functions for thermotaxis in Drosophila, is missing in A. mellifera and N. vitripennis; however, they have other Hymenoptera-specific TRPA channels (AmHsTRPA and NvHsTRPA). NvHsTRPA expressed in HEK293 cells is activated by temperature increase, demonstrating that HsTRPAs function as novel thermal sensors in Hymenoptera. The total number of insect TRP family members is 13-14, approximately half that of mammalian TRP family members. As shown for mammalian TRP channels, this

Evolutionary conservation and changes in insect TRP channels

Directory of Open Access Journals (Sweden)

Tominaga Makoto

2009-09-01

Full Text Available Abstract Background TRP (Transient Receptor Potential channels respond to diverse stimuli and thus function as the primary integrators of varied sensory information. They are also activated by various compounds and secondary messengers to mediate cell-cell interactions as well as to detect changes in the local environment. Their physiological roles have been primarily characterized only in mice and fruit flies, and evolutionary studies are limited. To understand the evolution of insect TRP channels and the mechanisms of integrating sensory inputs in insects, we have identified and compared TRP channel genes in Drosophila melanogaster, Bombyx mori, Tribolium castaneum, Apis mellifera, Nasonia vitripennis, and Pediculus humanus genomes as part of genome sequencing efforts. Results All the insects examined have 2 TRPV, 1 TRPN, 1 TRPM, 3 TRPC, and 1 TRPML subfamily members, demonstrating that these channels have the ancient origins in insects. The common pattern also suggests that the mechanisms for detecting mechanical and visual stimuli and maintaining lysosomal functions may be evolutionarily well conserved in insects. However, a TRPP channel, the most ancient TRP channel, is missing in B. mori, A. mellifera, and N. vitripennis. Although P. humanus and D. melanogaster contain 4 TRPA subfamily members, the other insects have 5 TRPA subfamily members. T. castaneum, A. mellifera, and N. vitripennis contain TRPA5 channels, which have been specifically retained or gained in Coleoptera and Hymenoptera. Furthermore, TRPA1, which functions for thermotaxis in Drosophila, is missing in A. mellifera and N. vitripennis; however, they have other Hymenoptera-specific TRPA channels (AmHsTRPA and NvHsTRPA. NvHsTRPA expressed in HEK293 cells is activated by temperature increase, demonstrating that HsTRPAs function as novel thermal sensors in Hymenoptera. Conclusion The total number of insect TRP family members is 13-14, approximately half that of mammalian TRP

Packets Distributing Evolutionary Algorithm Based on PSO for Ad Hoc Network

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Xu, Xiao-Feng

2018-03-01

Wireless communication network has such features as limited bandwidth, changeful channel and dynamic topology, etc. Ad hoc network has lots of difficulties in accessing control, bandwidth distribution, resource assign and congestion control. Therefore, a wireless packets distributing Evolutionary algorithm based on PSO (DPSO)for Ad Hoc Network is proposed. Firstly, parameters impact on performance of network are analyzed and researched to obtain network performance effective function. Secondly, the improved PSO Evolutionary Algorithm is used to solve the optimization problem from local to global in the process of network packets distributing. The simulation results show that the algorithm can ensure fairness and timeliness of network transmission, as well as improve ad hoc network resource integrated utilization efficiency.

Evolutionary algorithms approach for integrated bioenergy supply chains optimization

International Nuclear Information System (INIS)

Ayoub, Nasser; Elmoshi, Elsayed; Seki, Hiroya; Naka, Yuji

2009-01-01

In this paper, we propose an optimization model and solution approach for designing and evaluating integrated system of bioenergy production supply chains, SC, at the local level. Designing SC that simultaneously utilize a set of bio-resources together is a complicated task, considered here. The complication arises from the different nature and sources of bio-resources used in bioenergy production i.e., wet, dry or agriculture, industrial etc. Moreover, the different concerns that decision makers should take into account, to overcome the tradeoff anxieties of the socialists and investors, i.e., social, environmental and economical factors, was considered through the options of multi-criteria optimization. A first part of this research was introduced in earlier research work explaining the general Bioenergy Decision System gBEDS [Ayoub N, Martins R, Wang K, Seki H, Naka Y. Two levels decision system for efficient planning and implementation of bioenergy production. Energy Convers Manage 2007;48:709-23]. In this paper, brief introduction and emphasize on gBEDS are given; the optimization model is presented and followed by a case study on designing a supply chain of nine bio-resources at Iida city in the middle part of Japan.

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

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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

On Reciprocal Causation in the Evolutionary Process.

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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

Is the political animal politically ignorant? Applying evolutionary psychology to the study of political attitudes.

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Petersen, Michael Bang; Aarøe, Lene

2012-12-20

As evidenced by research in evolutionary psychology, humans have evolved sophisticated psychological mechanisms tailored to solve enduring adaptive problems of social life. Many of these social problems are political in nature and relate to the distribution of costs and benefits within and between groups. In that sense, evolutionary psychology suggests that humans are, by nature, political animals. By implication, a straightforward application of evolutionary psychology to the study of public opinion seems to entail that modern individuals find politics intrinsically interesting. Yet, as documented by more than fifty years of research in political science, people lack knowledge of basic features of the political process and the ability to form consistent political attitudes. By reviewing and integrating research in evolutionary psychology and public opinion, we describe (1) why modern mass politics often fail to activate evolved mechanisms and (2) the conditions in which these mechanisms are in fact triggered.

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...

Threat-detection in child development: an evolutionary perspective.

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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.

Proteomics in evolutionary ecology.

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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

On discourse space modeling

OpenAIRE

Казыдуб, Надежда

2013-01-01

Discourse space is a complex structure that incorporates different levels and dimensions. The paper focuses on developing a multidisciplinary approach that is congruent to the complex character of the modern discourse. Two models of discourse space are proposed here. The Integrated Model reveals the interaction of different categorical mechanisms in the construction of the discourse space. The Evolutionary Model describes the historical roots of the modern discourse. It also reveals historica...

High Efficiency Computation of the Variances of Structural Evolutionary Random Responses

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J.H. Lin

2000-01-01

Full Text Available For structures subjected to stationary or evolutionary white/colored random noise, their various response variances satisfy algebraic or differential Lyapunov equations. The solution of these Lyapunov equations used to be very difficult. A precise integration method is proposed in the present paper, which solves such Lyapunov equations accurately and very efficiently.

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

Evolutionary inference via the Poisson Indel Process.

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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.

Integrated Debugging of Modelica Models

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Adrian Pop

2014-04-01

Full Text Available The high abstraction level of equation-based object-oriented (EOO languages such as Modelica has the drawback that programming and modeling errors are often hard to find. In this paper we present integrated static and dynamic debugging methods for Modelica models and a debugger prototype that addresses several of those problems. The goal is an integrated debugging framework that combines classical debugging techniques with special techniques for equation-based languages partly based on graph visualization and interaction. To our knowledge, this is the first Modelica debugger that supports both equation-based transformational and algorithmic code debugging in an integrated fashion.

Evolutionary systems biology: historical and philosophical perspectives on an emerging synthesis.

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O'Malley, Maureen A

2012-01-01

Systems biology (SB) is at least a decade old now and maturing rapidly. A more recent field, evolutionary systems biology (ESB), is in the process of further developing system-level approaches through the expansion of their explanatory and potentially predictive scope. This chapter will outline the varieties of ESB existing today by tracing the diverse roots and fusions that make up this integrative project. My approach is philosophical and historical. As well as examining the recent origins of ESB, I will reflect on its central features and the different clusters of research it comprises. In its broadest interpretation, ESB consists of five overlapping approaches: comparative and correlational ESB; network architecture ESB; network property ESB; population genetics ESB; and finally, standard evolutionary questions answered with SB methods. After outlining each approach with examples, I will examine some strong general claims about ESB, particularly that it can be viewed as the next step toward a fuller modern synthesis of evolutionary biology (EB), and that it is also the way forward for evolutionary and systems medicine. I will conclude with a discussion of whether the emerging field of ESB has the capacity to combine an even broader scope of research aims and efforts than it presently does.

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

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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.

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

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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.

Bacterial Actins? An Evolutionary Perspective

Science.gov (United States)

Doolittle, Russell F.; York, Amanda L.

2003-01-01

According to the conventional wisdom, the existence of a cytoskeleton in eukaryotes and its absence in prokaryotes constitute a fundamental divide between the two domains of life. An integral part of the dogma is that a cytoskeleton enabled an early eukaryote to feed upon prokaryotes, a consequence of which was the occasional endosymbiosis and the eventual evolution of organelles. Two recent papers present compelling evidence that actin, one of the principal components of a cytoskeleton, has a homolog in Bacteria that behaves in many ways like eukaryotic actin. Sequence comparisons reveml that eukaryotic actin and the bacterial homolog (mreB protein), unlike many other proteins common to eukaryotes and Bacteria, have very different and more highly extended evolutionary histories.

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...

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.

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.

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.

Yonsei Evolutionary Population Synthesis (YEPS). II. Spectro-photometric Evolution of Helium-enhanced Stellar Populations

Energy Technology Data Exchange (ETDEWEB)

Chung, Chul; Yoon, Suk-Jin; Lee, Young-Wook, E-mail: chulchung@yonsei.ac.kr, E-mail: sjyoon0691@yonsei.ac.kr [Center for Galaxy Evolution Research, Yonsei University, Seoul 03722 (Korea, Republic of)

2017-06-20

The discovery of multiple stellar populations in Milky Way globular clusters (GCs) has stimulated various follow-up studies on helium-enhanced stellar populations. Here we present the evolutionary population synthesis models for the spectro-photometric evolution of simple stellar populations (SSPs) with varying initial helium abundance ( Y {sub ini}). We show that Y {sub ini} brings about dramatic changes in spectro-photometric properties of SSPs. Like the normal-helium SSPs, the integrated spectro-photometric evolution of helium-enhanced SSPs is also dependent on metallicity and age for a given Y {sub ini}. We discuss the implications and prospects for the helium-enhanced populations in relation to the second-generation populations found in the Milky Way GCs. All of the models are available at http://web.yonsei.ac.kr/cosmic/data/YEPS.htm.

Yonsei Evolutionary Population Synthesis (YEPS). II. Spectro-photometric Evolution of Helium-enhanced Stellar Populations

International Nuclear Information System (INIS)

Chung, Chul; Yoon, Suk-Jin; Lee, Young-Wook

2017-01-01

The discovery of multiple stellar populations in Milky Way globular clusters (GCs) has stimulated various follow-up studies on helium-enhanced stellar populations. Here we present the evolutionary population synthesis models for the spectro-photometric evolution of simple stellar populations (SSPs) with varying initial helium abundance ( Y ini ). We show that Y ini brings about dramatic changes in spectro-photometric properties of SSPs. Like the normal-helium SSPs, the integrated spectro-photometric evolution of helium-enhanced SSPs is also dependent on metallicity and age for a given Y ini . We discuss the implications and prospects for the helium-enhanced populations in relation to the second-generation populations found in the Milky Way GCs. All of the models are available at http://web.yonsei.ac.kr/cosmic/data/YEPS.htm.

Culture belief based multi-objective hybrid differential evolutionary algorithm in short term hydrothermal scheduling

International Nuclear Information System (INIS)

Zhang Huifeng; Zhou Jianzhong; Zhang Yongchuan; Lu Youlin; Wang Yongqiang

2013-01-01

Highlights: ► Culture belief is integrated into multi-objective differential evolution. ► Chaotic sequence is imported to improve evolutionary population diversity. ► The priority of convergence rate is proved in solving hydrothermal problem. ► The results show the quality and potential of proposed algorithm. - Abstract: A culture belief based multi-objective hybrid differential evolution (CB-MOHDE) is presented to solve short term hydrothermal optimal scheduling with economic emission (SHOSEE) problem. This problem is formulated for compromising thermal cost and emission issue while considering its complicated non-linear constraints with non-smooth and non-convex characteristics. The proposed algorithm integrates a modified multi-objective differential evolutionary algorithm into the computation model of culture algorithm (CA) as well as some communication protocols between population space and belief space, three knowledge structures in belief space are redefined according to these problem-solving characteristics, and in the differential evolution a chaotic factor is embedded into mutation operator for avoiding the premature convergence by enlarging the search scale when the search trajectory reaches local optima. Furthermore, a new heuristic constraint-handling technique is utilized to handle those complex equality and inequality constraints of SHOSEE problem. After the application on hydrothermal scheduling system, the efficiency and stability of the proposed CB-MOHDE is verified by its more desirable results in comparison to other method established recently, and the simulation results also reveal that CB-MOHDE can be a promising alternative for solving SHOSEE.

Can evolutionary design of social networks make it easier to be 'green'?

Science.gov (United States)

Dickinson, Janis L; Crain, Rhiannon L; Reeve, H Kern; Schuldt, Jonathon P

2013-09-01

The social Web is swiftly becoming a living laboratory for understanding human cooperation on massive scales. It has changed how we organize, socialize, and tackle problems that benefit from the efforts of a large crowd. A new, applied, behavioral ecology has begun to build on theoretical and empirical studies of cooperation, integrating research in the fields of evolutionary biology, social psychology, social networking, and citizen science. Here, we review the ways in which these disciplines inform the design of Internet environments to support collective pro-environmental behavior, tapping into proximate prosocial mechanisms and models of social evolution, as well as generating opportunities for 'field studies' to discover how we can support massive collective action and shift environmental social norms. Copyright © 2013 Elsevier Ltd. All rights reserved.

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)

An open future for ecological and evolutionary data?

OpenAIRE

Kenall, Amye; Harold, Simon; Foote, Christopher

2014-01-01

As part of BioMed Central’s open science mission, we are pleased to announce that two of our journals have integrated with the open data repository Dryad. Authors submitting their research to either BMC Ecology or BMC Evolutionary Biology will now have the opportunity to deposit their data directly into the Dryad archive and will receive a permanent, citable link to their dataset. Although this does not affect any of our current data deposition policies at these journals, we hope to encourage...

Long-term greenhouse gas emission and petroleum reduction goals: Evolutionary pathways for the light-duty vehicle sector

International Nuclear Information System (INIS)

Kromer, Matthew A.; Bandivadekar, Anup; Evans, Christopher

2010-01-01

To meet long-term environmental and energy security goals, the United States must reduce petroleum use in the light-duty vehicle fleet by 70% and greenhouse gas emissions by a factor of ten compared to business-as-usual growth projections for the year 2050. A wedge-based approach was used to quantify the scope of the problem in real terms, and to develop options for meeting mid-century targets. Four mitigation mechanisms were considered: (1) improvements in near-term vehicle technologies; (2) emphasis on low-carbon biofuels; (3) de-carbonization of the electric grid; and (4) demand-side travel-reduction initiatives. Projections from previous studies were used to characterize the potential of individual mitigation mechanisms, which were then integrated into a light-duty vehicle fleet model; particular emphasis was given to systemic constraints on scale and rates of change. Based on these projections, two different greenhouse gas (GHG) mitigation implementation plans were considered ('evolutionary' and 'aggressive'). Fleet model projections indicate that both the evolutionary and aggressive approaches can effectively end US dependence on foreign oil, but achieving an 80% GHG reduction requires changes that extend significantly beyond even the aggressive case, which was projected to achieve a 65% reduction.

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

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.

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.

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

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

Increasingly imperative objectives in ecology are to understand and forecast population dynamic and evolutionary responses to seasonal environmental variation and change. Such population and evolutionary dynamics result from immediate and lagged responses of all key life-history traits, and resulting demographic rates that affect population growth rate, to seasonal environmental conditions and population density. However, existing population dynamic and eco-evolutionary theory and models have not yet fully encompassed within-individual and among-individual variation, covariation, structure and heterogeneity, and ongoing evolution, in a critical life-history trait that allows individuals to respond to seasonal environmental conditions: seasonal migration. Meanwhile, empirical studies aided by new animal-tracking technologies are increasingly demonstrating substantial within-population variation in the occurrence and form of migration versus year-round residence, generating diverse forms of 'partial migration' spanning diverse species, habitats and spatial scales. Such partially migratory systems form a continuum between the extreme scenarios of full migration and full year-round residence, and are commonplace in nature. Here, we first review basic scenarios of partial migration and associated models designed to identify conditions that facilitate the maintenance of migratory polymorphism. We highlight that such models have been fundamental to the development of partial migration theory, but are spatially and demographically simplistic compared to the rich bodies of population dynamic theory and models that consider spatially structured populations with dispersal but no migration, or consider populations experiencing strong seasonality and full obligate migration. Second, to provide an overarching conceptual framework for spatio-temporal population dynamics, we define a 'partially migratory meta-population' system as a spatially structured set of locations that can

IDEA: Interactive Display for Evolutionary Analyses

Directory of Open Access Journals (Sweden)

Carlton Jane M

2008-12-01

Full Text Available Abstract Background The availability of complete genomic sequences for hundreds of organisms promises to make obtaining genome-wide estimates of substitution rates, selective constraints and other molecular evolution variables of interest an increasingly important approach to addressing broad evolutionary questions. Two of the programs most widely used for this purpose are codeml and baseml, parts of the PAML (Phylogenetic Analysis by Maximum Likelihood suite. A significant drawback of these programs is their lack of a graphical user interface, which can limit their user base and considerably reduce their efficiency. Results We have developed IDEA (Interactive Display for Evolutionary Analyses, an intuitive graphical input and output interface which interacts with PHYLIP for phylogeny reconstruction and with codeml and baseml for molecular evolution analyses. IDEA's graphical input and visualization interfaces eliminate the need to edit and parse text input and output files, reducing the likelihood of errors and improving processing time. Further, its interactive output display gives the user immediate access to results. Finally, IDEA can process data in parallel on a local machine or computing grid, allowing genome-wide analyses to be completed quickly. Conclusion IDEA provides a graphical user interface that allows the user to follow a codeml or baseml analysis from parameter input through to the exploration of results. Novel options streamline the analysis process, and post-analysis visualization of phylogenies, evolutionary rates and selective constraint along protein sequences simplifies the interpretation of results. The integration of these functions into a single tool eliminates the need for lengthy data handling and parsing, significantly expediting access to global patterns in the data.

Genomicus 2018: karyotype evolutionary trees and on-the-fly synteny computing.

Science.gov (United States)

Nguyen, Nga Thi Thuy; Vincens, Pierre; Roest Crollius, Hugues; Louis, Alexandra

2018-01-04

Since 2010, the Genomicus web server is available online at http://genomicus.biologie.ens.fr/genomicus. This graphical browser provides access to comparative genomic analyses in four different phyla (Vertebrate, Plants, Fungi, and non vertebrate Metazoans). Users can analyse genomic information from extant species, as well as ancestral gene content and gene order for vertebrates and flowering plants, in an integrated evolutionary context. New analyses and visualization tools have recently been implemented in Genomicus Vertebrate. Karyotype structures from several genomes can now be compared along an evolutionary pathway (Multi-KaryotypeView), and synteny blocks can be computed and visualized between any two genomes (PhylDiagView). © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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.

Deciphering the evolutionary history of open and closed mitosis.

Science.gov (United States)

Sazer, Shelley; Lynch, Michael; Needleman, Daniel

2014-11-17

The origin of the nucleus at the prokaryote-to-eukaryote transition represents one of the most important events in the evolution of cellular organization. The nuclear envelope encircles the chromosomes in interphase and is a selectively permeable barrier between the nucleoplasm and cytoplasm and an organizational scaffold for the nucleus. It remains intact in the 'closed' mitosis of some yeasts, but loses its integrity in the 'open' mitosis of mammals. Instances of both types of mitosis within two evolutionary clades indicate multiple evolutionary transitions between open and closed mitosis, although the underlying genetic changes that influenced these transitions remain unknown. A survey of the diversity of mitotic nuclei that fall between these extremes is the starting point from which to determine the physiologically relevant characteristics distinguishing open from closed mitosis and to understand how they evolved and why they are retained in present-day organisms. The field is now poised to begin addressing these issues by defining and documenting patterns of mitotic nuclear variation within and among species and mapping them onto a phylogenic tree. Deciphering the evolutionary history of open and closed mitosis will complement cell biological and genetic approaches aimed at deciphering the fundamental organizational principles of the nucleus. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evolution of microbes and viruses: A paradigm shift in evolutionary biology?

Directory of Open Access Journals (Sweden)

Eugene V. Koonin

2012-09-01

Full Text Available When Charles Darwin formulated the central principles of evolutionary biology in the Origin of Species in 1859 and the architects of the Modern Synthesis integrated these principles with population genetics almost a century later, the principal if not the sole objects of evolutionary biology were multicellular eukaryotes, primarily animals and plants. Before the advent of efficient gene sequencing, all attempts to extend evolutionary studies to bacteria have been futile. Sequencing of the rRNA genes in thousands of microbes allowed the construction of the three- domain ‘ribosomal Tree of Life’ that was widely thought to have resolved the evolutionary relationships between the cellular life forms. However, subsequent massive sequencing of numerous, complete microbial genomes revealed novel evolutionary phenomena, the most fundamental of these being: i pervasive horizontal gene transfer (HGT, in large part mediated by viruses and plasmids, that shapes the genomes of archaea and bacteria and call for a radical revision (if not abandonment of the Tree of Life concept, ii Lamarckian-type inheritance that appears to be critical for antivirus defense and other forms of adaptation in prokaryotes, and iii evolution of evolvability, i.e. dedicated mechanisms for evolution such as vehicles for HGT and stress-induced mutagenesis systems. In the non-cellular part of the microbial world, phylogenomics and metagenomics of viruses and related selfish genetic elements revealed enormous genetic and molecular diversity and extremely high abundance of viruses that come across as the dominant biological entities on earth. Furthermore, the perennial arms race between viruses and their hosts is one of the defining factors of evolution. Thus, microbial phylogenomics adds new dimensions to the fundamental picture of evolution even as the principle of descent with modification discovered by Darwin and the laws of population genetics remain at the core of evolutionary

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).

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.

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.

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.

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

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)

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.

The role of rules in the evolution of the market system: Hayek’s concept of evolutionary epistemology

Directory of Open Access Journals (Sweden)

Krstić Miloš

2012-01-01

Full Text Available Starting from the concept of the Darwinian paradigm that, by using Darwin’s principles of variation, selection, and retention, all domains from biology to economic systems can be explained, the advocates of modern evolutionary epistemology have analyzed the role of thoughtful institutional design in the process of cultural evolution. In light of the issue of how human intention and evolutionary forces interact in socioeconomic processes, this paper examines the views of F. A. Hayek, the most famous follower of evolutionary epistemology, on the evolution of the market economy system. In this paper special attention will be devoted to Hayek’s concept of rational liberalism and his evolutionary epistemology. [Ministarstva nauke Republike Srbije, br. 179066: Improving the Competitiveness of the Public and Private Sectors by Networking Competences in the European Integration Process of Serbia

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.

Toward an Integrative Model of Global Business Strategy

DEFF Research Database (Denmark)

Li, Xin

fragmentation-integration-fragmentation-integration upward spiral. In response to the call for integrative approach to strategic management research, we propose an integrative model of global business strategy that aims at integrating not only strategy and IB but also the different paradigms within the strategy...... field. We also discuss the merit and limitation of our model....

Model integration and the economics of nuclear power

International Nuclear Information System (INIS)

Lundgren, S.

1985-01-01

The author proposes and applies a specific approach to model integration, i.e. the merger of two or several independently developed models. The approach is intended for integrations of activity analysis sector models and applied general equilibrium models. Model integration makes it possible to extend the range of applicability of applied general equilibrium models by exploiting the information contained in sector models. It also makes it possible to evaluate the validity of the partial equilibrium analyses in which sector models often are employed. The proposed approach is used to integrate a sector model of electricity and heat production with a general equilibrium model of the Swedish economy. Both models have been constructed within the research programme. The author uses the integrated model to look at two issues concerning the role of nuclear power on the Swedish electricity market: What are the likely consequences of a nuclear power discontinuation and how does the nuclear power investment programme of the 1970's and the early 1980's compare with a socially efficient one. (Author)

Evolutionary dynamics of fluctuating populations with strong mutualism

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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.

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.

Modern model of integrated corporate communication

Directory of Open Access Journals (Sweden)

Milica Slijepčević

2018-03-01

Full Text Available The main purpose of this paper is to present the modern model of integrated corporate communication. Beside this, the authors will describe the changes occurring in the corporate environment and importance of changing the model of corporate communication. This paper also discusses the importance of implementation of the suggested model, the use of new media and effects of these changes on corporations. The approach used in this paper is the literature review. The authors explore the importance of implementation of the suggested model and the new media in corporate communication, both internal and external, addressing all the stakeholders and communication contents. The paper recommends implementation of a modern model of integrated corporate communication as a response to constant development of the new media and generation changes taking place. Practical implications: the modern model of integrated corporate communication can be used as an upgrade of the conventional communication models. This modern model empowers companies to sustain and build up the existing relationships with stakeholders, and to find out and create new relationships with stakeholders who were previously inaccessible and invisible.

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.

Integration of design applications with building models

DEFF Research Database (Denmark)

Eastman, C. M.; Jeng, T. S.; Chowdbury, R.

1997-01-01

This paper reviews various issues in the integration of applications with a building model... (Truncated.)......This paper reviews various issues in the integration of applications with a building model... (Truncated.)...

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

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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.

Biophysics of protein evolution and evolutionary protein biophysics

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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

A CO-EVOLUTIONARY PERSPECTIVE AND ITS APPLICATION TO THE THEORY OF ORGANIZATIONS

Directory of Open Access Journals (Sweden)

Flavia Luciane Scherer

2012-11-01

Full Text Available This article pointed out the reasons and possibilities of co-evolutionary studies, requirements and problems to develop such studies, as well as discuss some of the central theoretical frameworks to the theory of organizations, from the perspective of coevolution (lewin and volberda , 1999. From this, we identify the possible links that can be established between different lenses of study, when integrated into a co-evolutionary study. Such links are drawn by taking the analysis of institutional theory (dimaggio and powell, 1991; meyer and rowan, 1991; scott, 1995, the transaction costs theory (williamson, 1981 and the theory of social relations in economic action (granovetter, 1992. Thus, it is expected to contribute to the discussion about the possibilities for greater integration in organizational studies, when calling attention to the importance of moving toward a more inclusive, taking into account the macro economic and social dynamics and their impact on the level the firm (in terms of effect size, identity, culture and learning processes and its inverse relationships - from the firm to the macro environment.

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

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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.

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.

Historical change and evolutionary theory.

Science.gov (United States)

Masters, Roger D

2007-09-01

systems are constantly transformed by human technology and social behavior, multilevel evolutionary processes can explain two central features of human history: the rise, transformations, and ultimate fall of centralized governments (the "stuff" of history); and the biological uniqueness of Homo sapiens as the mammalian species that colonized--and became top carnivore--in virtually every habitable environment on the earth's surface. Once scholars admit the necessity of linking processes of natural selection with human transformations of the natural world, it will seem anomalous that it has taken so long to integrate Darwinian biology and the social sciences.

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.

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

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.

Under pressure: evolutionary engineering of yeast strains for improved performance in fuels and chemicals production

NARCIS (Netherlands)

Mans, R.; Daran, J.G.; Pronk, J.T.

2018-01-01

Evolutionary engineering, which uses laboratory evolution to select for industrially relevant traits, is a popular strategy in the development of high-performing yeast strains for industrial production of fuels and chemicals. By integrating whole-genome sequencing, bioinformatics, classical

Nanoscopical dissection of ancestral nucleoli in Archaea: a case of study in Evolutionary Cell Biology

KAUST Repository

Islas Morales, Parsifal

2018-04-01

Is the nucleolus a sine qua non condition of eukaryotes? The present project starts from this central question to contribute to our knowledge about the origin and the evolution of the cells. The nucleolus is a cryptic organelle that plays a central role in cell function. It is responsible for the orchestration of ribosomal RNA expression, maturation and modification in the regulatory context of cellular homeostasis. Ribosomal expression is undoubtedly the greatest transcriptional and regulatory activity of any cell. The nucleolus is not just a conventional organelle –membrane-limited-, but a magnificent transcriptional puff: a dichotomy between structure and process, form and function. What is the minimum nucleolus? Evolution should bring some light into these questions. Evolutionary cell biology (ECB) has raised increasing attention in the last decades. Is this a new discipline and an historical opportunity to combine functional and evolutionary biology towards the insight that cell evolution underlies organismic complexity? In the post-genomic era, we have developed the potential of combining high throughput acquisition of data with functional in situ and in sillico approaches: integration understood as omics approaches. Can this provide a real consilience between evolutionary and functional approaches? The reduced number of model organisms and cultivation techniques still excludes the majority of the extant diversity of cells from the scope of experimental inquiry. Furthermore, at the conceptual level, the simplification of evolutionary processes in biosciences still limits the conformation of a successful disciplinary link between functional and evolutionary biology. This limits the formulation of questions and experiments that properly address the mechanistic nature of cellular events that underlie microbial and organismic diversity and evolution. Here we provide a critical and comparative review to the historical background of ECB. This project takes the

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.

Model-integrating software components engineering flexible software systems

CERN Document Server

Derakhshanmanesh, Mahdi

2015-01-01

In his study, Mahdi Derakhshanmanesh builds on the state of the art in modeling by proposing to integrate models into running software on the component-level without translating them to code. Such so-called model-integrating software exploits all advantages of models: models implicitly support a good separation of concerns, they are self-documenting and thus improve understandability and maintainability and in contrast to model-driven approaches there is no synchronization problem anymore between the models and the code generated from them. Using model-integrating components, software will be

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.

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

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.

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.

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...

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.

Integrable models in classical and quantum mechanics

International Nuclear Information System (INIS)

Jurco, B.

1991-01-01

Integrable systems are investigated, especially the rational and trigonometric Gaudin models. The Gaudin models are diagonalized for the case of classical Lie algebras. Their relation to the other integrable models and to the quantum inverse scattering method is investigated. Applications in quantum optics and plasma physics are discussed. (author). 94 refs

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

MEASURING INFORMATION INTEGR-ATION MODEL FOR CAD/CMM

Institute of Scientific and Technical Information of China (English)

无

2003-01-01

A CAD/CMM workpiece modeling system based on IGES file is proposed. The modeling system is implemented by using a new method for labelling the tolerance items of 3D workpiece. The concept-"feature face" is used in the method. First the CAD data of workpiece are extracted and recognized automatically. Then a workpiece model is generated, which is the integration of pure 3D geometry form with its corresponding inspection items. The principle of workpiece modeling is also presented. At last, the experiment results are shown and correctness of the model is certified.

Integrated Site Model Process Model Report

International Nuclear Information System (INIS)

Booth, T.

2000-01-01

The Integrated Site Model (ISM) provides a framework for discussing the geologic features and properties of Yucca Mountain, which is being evaluated as a potential site for a geologic repository for the disposal of nuclear waste. The ISM is important to the evaluation of the site because it provides 3-D portrayals of site geologic, rock property, and mineralogic characteristics and their spatial variabilities. The ISM is not a single discrete model; rather, it is a set of static representations that provide three-dimensional (3-D), computer representations of site geology, selected hydrologic and rock properties, and mineralogic-characteristics data. These representations are manifested in three separate model components of the ISM: the Geologic Framework Model (GFM), the Rock Properties Model (RPM), and the Mineralogic Model (MM). The GFM provides a representation of the 3-D stratigraphy and geologic structure. Based on the framework provided by the GFM, the RPM and MM provide spatial simulations of the rock and hydrologic properties, and mineralogy, respectively. Functional summaries of the component models and their respective output are provided in Section 1.4. Each of the component models of the ISM considers different specific aspects of the site geologic setting. Each model was developed using unique methodologies and inputs, and the determination of the modeled units for each of the components is dependent on the requirements of that component. Therefore, while the ISM represents the integration of the rock properties and mineralogy into a geologic framework, the discussion of ISM construction and results is most appropriately presented in terms of the three separate components. This Process Model Report (PMR) summarizes the individual component models of the ISM (the GFM, RPM, and MM) and describes how the three components are constructed and combined to form the ISM

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

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.

Development of a generalized integral jet model

DEFF Research Database (Denmark)

Duijm, Nijs Jan; Kessler, A.; Markert, Frank

2017-01-01

Integral type models to describe stationary plumes and jets in cross-flows (wind) have been developed since about 1970. These models are widely used for risk analysis, to describe the consequences of many different scenarios. Alternatively, CFD codes are being applied, but computational requireme......Integral type models to describe stationary plumes and jets in cross-flows (wind) have been developed since about 1970. These models are widely used for risk analysis, to describe the consequences of many different scenarios. Alternatively, CFD codes are being applied, but computational...... requirements still limit the number of scenarios that can be dealt with using CFD only. The integral models, however, are not suited to handle transient releases, such as releases from pressurized equipment, where the initially high release rate decreases rapidly with time. Further, on gas ignition, a second...... model is needed to describe the rapid combustion of the flammable part of the plume (flash fire) and a third model has to be applied for the remaining jet fire. The objective of this paper is to describe the first steps of the development of an integral-type model describing the transient development...

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.

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.

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.

Model-Based Integration and Interpretation of Data

DEFF Research Database (Denmark)

Petersen, Johannes

2004-01-01

Data integration and interpretation plays a crucial role in supervisory control. The paper defines a set of generic inference steps for the data integration and interpretation process based on a three-layer model of system representations. The three-layer model is used to clarify the combination...... of constraint and object-centered representations of the work domain throwing new light on the basic principles underlying the data integration and interpretation process of Rasmussen's abstraction hierarchy as well as other model-based approaches combining constraint and object-centered representations. Based...

Modular Architecture for Integrated Model-Based Decision Support.

Science.gov (United States)

Gaebel, Jan; Schreiber, Erik; Oeser, Alexander; Oeltze-Jafra, Steffen

2018-01-01

Model-based decision support systems promise to be a valuable addition to oncological treatments and the implementation of personalized therapies. For the integration and sharing of decision models, the involved systems must be able to communicate with each other. In this paper, we propose a modularized architecture of dedicated systems for the integration of probabilistic decision models into existing hospital environments. These systems interconnect via web services and provide model sharing and processing capabilities for clinical information systems. Along the lines of IHE integration profiles from other disciplines and the meaningful reuse of routinely recorded patient data, our approach aims for the seamless integration of decision models into hospital infrastructure and the physicians' daily work.

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.

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

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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).

Evolutionary relationships of ATP-Binding Cassette (ABC) uptake porters.

Science.gov (United States)

Zheng, Wei Hao; Västermark, Åke; Shlykov, Maksim A; Reddy, Vamsee; Sun, Eric I; Saier, Milton H

2013-05-06

The ATP-Binding Cassette (ABC) functional superfamily includes integral transmembrane exporters that have evolved three times independently, forming three families termed ABC1, ABC2 and ABC3, upon which monophyletic ATPases have been superimposed for energy-coupling purposes [e.g., J Membr Biol 231(1):1-10, 2009]. The goal of the work reported in this communication was to understand how the integral membrane constituents of ABC uptake transporters with different numbers of predicted or established transmembrane segments (TMSs) evolved. In a few cases, high resolution 3-dimensional structures were available, and in these cases, their structures plus primary sequence analyses allowed us to predict evolutionary pathways of origin. All of the 35 currently recognized families of ABC uptake proteins except for one (family 21) were shown to be homologous using quantitative statistical methods. These methods involved using established programs that compare native protein sequences with each other, after having compared each sequence with thousands of its own shuffled sequences, to gain evidence for homology. Topological analyses suggested that these porters contain numbers of TMSs ranging from four or five to twenty. Intragenic duplication events occurred multiple times during the evolution of these porters. They originated from a simple primordial protein containing 3 TMSs which duplicated to 6 TMSs, and then produced porters of the various topologies via insertions, deletions and further duplications. Except for family 21 which proved to be related to ABC1 exporters, they are all related to members of the previously identified ABC2 exporter family. Duplications that occurred in addition to the primordial 3 → 6 duplication included 5 → 10, 6 → 12 and 10 → 20 TMSs. In one case, protein topologies were uncertain as different programs gave discrepant predictions. It could not be concluded with certainty whether a 4 TMS ancestral protein or a 5 TMS ancestral protein

Modeling integrated biomass gasification business concepts

Science.gov (United States)

Peter J. Ince; Ted Bilek; Mark A. Dietenberger

2011-01-01

Biomass gasification is an approach to producing energy and/or biofuels that could be integrated into existing forest product production facilities, particularly at pulp mills. Existing process heat and power loads tend to favor integration at existing pulp mills. This paper describes a generic modeling system for evaluating integrated biomass gasification business...

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.

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.

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.

Toward a general evolutionary theory of oncogenesis.

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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.

Integrated Medical Model – Chest Injury Model

Data.gov (United States)

National Aeronautics and Space Administration — The Exploration Medical Capability (ExMC) Element of NASA's Human Research Program (HRP) developed the Integrated Medical Model (IMM) to forecast the resources...

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.

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...

Challenges in horizontal model integration.

Science.gov (United States)

Kolczyk, Katrin; Conradi, Carsten

2016-03-11

Systems Biology has motivated dynamic models of important intracellular processes at the pathway level, for example, in signal transduction and cell cycle control. To answer important biomedical questions, however, one has to go beyond the study of isolated pathways towards the joint study of interacting signaling pathways or the joint study of signal transduction and cell cycle control. Thereby the reuse of established models is preferable, as it will generally reduce the modeling effort and increase the acceptance of the combined model in the field. Obtaining a combined model can be challenging, especially if the submodels are large and/or come from different working groups (as is generally the case, when models stored in established repositories are used). To support this task, we describe a semi-automatic workflow based on established software tools. In particular, two frequent challenges are described: identification of the overlap and subsequent (re)parameterization of the integrated model. The reparameterization step is crucial, if the goal is to obtain a model that can reproduce the data explained by the individual models. For demonstration purposes we apply our workflow to integrate two signaling pathways (EGF and NGF) from the BioModels Database.

The macroevolutionary consequences of phenotypic integration: from development to deep time.

Science.gov (United States)

Goswami, A; Smaers, J B; Soligo, C; Polly, P D

2014-08-19

Phenotypic integration is a pervasive characteristic of organisms. Numerous analyses have demonstrated that patterns of phenotypic integration are conserved across large clades, but that significant variation also exists. For example, heterochronic shifts related to different mammalian reproductive strategies are reflected in postcranial skeletal integration and in coordination of bone ossification. Phenotypic integration and modularity have been hypothesized to shape morphological evolution, and we extended simulations to confirm that trait integration can influence both the trajectory and magnitude of response to selection. We further demonstrate that phenotypic integration can produce both more and less disparate organisms than would be expected under random walk models by repartitioning variance in preferred directions. This effect can also be expected to favour homoplasy and convergent evolution. New empirical analyses of the carnivoran cranium show that rates of evolution, in contrast, are not strongly influenced by phenotypic integration and show little relationship to morphological disparity, suggesting that phenotypic integration may shape the direction of evolutionary change, but not necessarily the speed of it. Nonetheless, phenotypic integration is problematic for morphological clocks and should be incorporated more widely into models that seek to accurately reconstruct both trait and organismal evolution.

Gravitational interactions of integrable models

International Nuclear Information System (INIS)

Abdalla, E.; Abdalla, M.C.B.

1995-10-01

We couple non-linear σ-models to Liouville gravity, showing that integrability properties of symmetric space models still hold for the matter sector. Using similar arguments for the fermionic counterpart, namely Gross-Neveu-type models, we verify that such conclusions must also hold for them, as recently suggested. (author). 18 refs

Ontogenetic ritualization of primate gesture as a case study in dyadic brain modeling.

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Gasser, Brad; Cartmill, Erica A; Arbib, Michael A

2014-01-01

This paper introduces dyadic brain modeling - the simultaneous, computational modeling of the brains of two interacting agents - to explore ways in which our understanding of macaque brain circuitry can ground new models of brain mechanisms involved in ape interaction. Specifically, we assess a range of data on gestural communication of great apes as the basis for developing an account of the interactions of two primates engaged in ontogenetic ritualization, a proposed learning mechanism through which a functional action may become a communicative gesture over repeated interactions between two individuals (the 'dyad'). The integration of behavioral, neural, and computational data in dyadic (or, more generally, social) brain modeling has broad application to comparative and evolutionary questions, particularly for the evolutionary origins of cognition and language in the human lineage. We relate this work to the neuroinformatics challenges of integrating and sharing data to support collaboration between primatologists, neuroscientists and modelers that will help speed the emergence of what may be called comparative neuro-primatology.

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...

Economic chances and problems of the peaceful uses of nuclear energy in an evolutionary context

International Nuclear Information System (INIS)

Hohn, B.

1992-01-01

To organize and ensure energy supply is of pivotal importance for social development. Therefore, the paper focuses on the issue of nuclear energy within the stress field of society, technology, energy and evolution. Nuclear energy use is studied with regard to its evolutionary fit, on the basis of an integrating analysis overriding economic considerations. So the criterion of customary economics is expanded by the evaluation criterion of evolutionary principles. After considering the theoretical structure of environment and resource economy and its limits, the evolutionary background of energy and energy use is examined. Evolution strategies are outlined to show how structures and orders are formed in the course of evolution and how energy resources are exploited. In view of the global ecological crisis, solution strategies require a solid concept of an evolutionary fitting energy system the requirement profile of which can be obtained, by means of fitting criteria, from a synthesis of economic theory and the outlined evolution strategies. In order to sound the evolutionary fit of nuclear energy use on the basis of the theoretical foundations of economics and evolution and of the fitting criteria obtained from their synthesis, the status of the problem and its multifacetted interconnections are structured. Critical analysis of the peaceful use of nuclear energy is performed by means of a systematics which is to ensure that the mental order gradually approaches the evaluation of the evolutionary fit of nuclear power. (orig./HSCH) [de

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.

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.

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

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.

Renewed mer model of integral management

Directory of Open Access Journals (Sweden)

Janko Belak

2015-12-01

Full Text Available Background: The research work on entrepreneurship, enterprise's policy and management, which started in 1992, successfully continued in the following years. Between 1992 and 2011, more than 400 academics and other researchers have participated in research work (MER research program whose main orientation has been the creation of their own model of integral management. Results: In past years, academics (researchers and authors of published papers from Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Byelorussia, Canada, the Czech Republic, Croatia, Estonia, France, Germany, Hungary, Italy, Poland, Romania, Russia, the Slovak Republic, Slovenia, Switzerland, Ukraine, and the US have cooperated in MER programs, coming from more than fifty institutions. Thus, scientific doctrines of different universities influenced the development of the MER model which is based on both horizontal and vertical integration of the enterprises' governance and management processes, instruments and institutions into a consistently operating unit. Conclusions: The presented MER model is based on the multi-layer integration of governance and management with an enterprise and its environment, considering the fundamental desires for the enterprises' existence and, thus, their quantitative as well as qualitative changes. The process, instrumental, and institutional integrity of the governance and management is also the initial condition for the implementation of all other integration factors.

A Course in Evolutionary Biology: Engaging Students in the "Practice" of Evolution. Research Report.

Science.gov (United States)

Passmore, Cynthia; Stewart, James

Recent education reform documents emphasize the need for students to develop a rich understanding of evolution's power to integrate knowledge of the natural world. This paper describes a nine-week high school course designed to help students understand evolutionary biology by engaging them in developing, elaborating, and using Charles Darwin's…

Integrated Modelling - the next steps (Invited)

Science.gov (United States)

Moore, R. V.

2010-12-01

Integrated modelling (IM) has made considerable advances over the past decade but it has not yet been taken up as an operational tool in the way that its proponents had hoped. The reasons why will be discussed in Session U17. This talk will propose topics for a research and development programme and suggest an institutional structure which, together, could overcome the present obstacles. Their combined aim would be first to make IM into an operational tool useable by competent public authorities and commercial companies and, in time, to see it evolve into the modelling equivalent of Google Maps, something accessible and useable by anyone with a PC or an iphone and an internet connection. In a recent study, a number of government agencies, water authorities and utilities applied integrated modelling to operational problems. While the project demonstrated that IM could be used in an operational setting and had benefit, it also highlighted the advances that would be required for its widespread uptake. These were: greatly improving the ease with which models could be a) made linkable, b) linked and c) run; developing a methodology for applying integrated modelling; developing practical options for calibrating and validating linked models; addressing the science issues that arise when models are linked; extending the range of modelling concepts that can be linked; enabling interface standards to pass uncertainty information; making the interface standards platform independent; extending the range of platforms to include those for high performance computing; developing the concept of modelling components as web services; separating simulation code from the model’s GUI, so that all the results from the linked models can be viewed through a single GUI; developing scenario management systems so that that there is an audit trail of the version of each model and dataset used in each linked model run. In addition to the above, there is a need to build a set of integrated

Comparison of three models predicting developmental milestones given environmental and individual variation

Science.gov (United States)

Estella Gilbert; James A. Powell; Jesse A. Logan; Barbara J. Bentz

2004-01-01

In all organisms, phenotypic variability is an evolutionary stipulation. Because the development of poikilothermic organisms depends directly on the temperature of their habitat, environmental variability is also an integral factor in models of their phenology. In this paper we present two existing phenology models, the distributed delay model and the Sharpe and...

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....

Design Principles as a Guide for Constraint Based and Dynamic Modeling: Towards an Integrative Workflow

Directory of Open Access Journals (Sweden)

Christiana Sehr

2015-10-01

Full Text Available During the last 10 years, systems biology has matured from a fuzzy concept combining omics, mathematical modeling and computers into a scientific field on its own right. In spite of its incredible potential, the multilevel complexity of its objects of study makes it very difficult to establish a reliable connection between data and models. The great number of degrees of freedom often results in situations, where many different models can explain/fit all available datasets. This has resulted in a shift of paradigm from the initially dominant, maybe naive, idea of inferring the system out of a number of datasets to the application of different techniques that reduce the degrees of freedom before any data set is analyzed. There is a wide variety of techniques available, each of them can contribute a piece of the puzzle and include different kinds of experimental information. But the challenge that remains is their meaningful integration. Here we show some theoretical results that enable some of the main modeling approaches to be applied sequentially in a complementary manner, and how this workflow can benefit from evolutionary reasoning to keep the complexity of the problem in check. As a proof of concept, we show how the synergies between these modeling techniques can provide insight into some well studied problems: Ammonia assimilation in bacteria and an unbranched linear pathway with end-product inhibition.

Design Principles as a Guide for Constraint Based and Dynamic Modeling: Towards an Integrative Workflow.

Science.gov (United States)

Sehr, Christiana; Kremling, Andreas; Marin-Sanguino, Alberto

2015-10-16

During the last 10 years, systems biology has matured from a fuzzy concept combining omics, mathematical modeling and computers into a scientific field on its own right. In spite of its incredible potential, the multilevel complexity of its objects of study makes it very difficult to establish a reliable connection between data and models. The great number of degrees of freedom often results in situations, where many different models can explain/fit all available datasets. This has resulted in a shift of paradigm from the initially dominant, maybe naive, idea of inferring the system out of a number of datasets to the application of different techniques that reduce the degrees of freedom before any data set is analyzed. There is a wide variety of techniques available, each of them can contribute a piece of the puzzle and include different kinds of experimental information. But the challenge that remains is their meaningful integration. Here we show some theoretical results that enable some of the main modeling approaches to be applied sequentially in a complementary manner, and how this workflow can benefit from evolutionary reasoning to keep the complexity of the problem in check. As a proof of concept, we show how the synergies between these modeling techniques can provide insight into some well studied problems: Ammonia assimilation in bacteria and an unbranched linear pathway with end-product inhibition.

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.

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.

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...

Cognition and Culture in Evolutionary Context.

Science.gov (United States)

Colmenares, Fernando; Hernández-Lloreda, María Victoria

2017-01-09

In humans and other animals, the individuals' ability to adapt efficiently and effectively to the niches they have actively contributed to construct relies heavily on an evolved psychology which has been shaped by biological, social, and cultural processes over evolutionary time. As expected, although many of the behavioral and cognitive components of this evolved psychology are widely shared across species, many others are species-unique. Although many animal species are known to acquire group-specific traditions (or cultures) via social learning, human culture is unique in terms of its contents and characteristics (observable and unobservable products, cumulative effects, norm conformity, and norm enforcement) and of its cognitive underpinnings (imitation, instructed teaching, and language). Here we provide a brief overview of some of the issues that are currently tackled in the field. We also highlight some of the strengths of a biological, comparative, non-anthropocentric and evolutionarily grounded approach to the study of culture. The main contributions of this approach to the science of culture are its emphasis (a) on the integration of information on mechanisms, function, and evolution, and on mechanistic factors located at different levels of the biological hierarchy, and (b) on the search for general principles that account for commonalities and differences between species, both in the cultural products and in the processes of innovation, dissemination, and accumulation involved that operate during developmental and evolutionary timespans.

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.

Data requirements for integrated near field models

International Nuclear Information System (INIS)

Wilems, R.E.; Pearson, F.J. Jr.; Faust, C.R.; Brecher, A.

1981-01-01

The coupled nature of the various processes in the near field require that integrated models be employed to assess long term performance of the waste package and repository. The nature of the integrated near field models being compiled under the SCEPTER program are discussed. The interfaces between these near field models and far field models are described. Finally, near field data requirements are outlined in sufficient detail to indicate overall programmatic guidance for data gathering activities

On the origins of anticipation as an evolutionary framework: functional systems perspective

Science.gov (United States)

Kurismaa, Andres

2015-08-01

This paper discusses the problem of anticipation from an evolutionary and systems-theoretical perspective, developed in the context of Russian/Soviet evolutionary biological and neurophysiological schools in the early and mid-twentieth century. On this background, an outline is given of the epigenetic interpretation of anticipatory capacities formulated and substantiated by the eminent Russian neurophysiologist academician Peter K. Anokhin in the framework of functional systems theory. It is considered that several key positions of this theory are well confirmed by recent evidence on anticipation as an evolutionarily basic adaptive capacity, possibly inherent to the organization of life. In the field of neuroscience, the theory of functional systems may potentially facilitate future studies at the intersection of learning, development and evolution by representing an integrative approach to the problem of anticipation.

Under pressure: evolutionary engineering of yeast strains for improved performance in fuels and chemicals production.

Science.gov (United States)

Mans, Robert; Daran, Jean-Marc G; Pronk, Jack T

2018-04-01

Evolutionary engineering, which uses laboratory evolution to select for industrially relevant traits, is a popular strategy in the development of high-performing yeast strains for industrial production of fuels and chemicals. By integrating whole-genome sequencing, bioinformatics, classical genetics and genome-editing techniques, evolutionary engineering has also become a powerful approach for identification and reverse engineering of molecular mechanisms that underlie industrially relevant traits. New techniques enable acceleration of in vivo mutation rates, both across yeast genomes and at specific loci. Recent studies indicate that phenotypic trade-offs, which are often observed after evolution under constant conditions, can be mitigated by using dynamic cultivation regimes. Advances in research on synthetic regulatory circuits offer exciting possibilities to extend the applicability of evolutionary engineering to products of yeasts whose synthesis requires a net input of cellular energy. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Research traditions and evolutionary explanations in medicine.

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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'.

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