Algorithmic Trading with Developmental and Linear Genetic Programming

NASA Astrophysics Data System (ADS)

Wilson, Garnett; Banzhaf, Wolfgang

A developmental co-evolutionary genetic programming approach (PAM DGP) and a standard linear genetic programming (LGP) stock trading systemare applied to a number of stocks across market sectors. Both GP techniques were found to be robust to market fluctuations and reactive to opportunities associated with stock price rise and fall, with PAMDGP generating notably greater profit in some stock trend scenarios. Both algorithms were very accurate at buying to achieve profit and selling to protect assets, while exhibiting bothmoderate trading activity and the ability to maximize or minimize investment as appropriate. The content of the trading rules produced by both algorithms are also examined in relation to stock price trend scenarios.

Scheduling Earth Observing Satellites with Evolutionary Algorithms

NASA Technical Reports Server (NTRS)

Globus, Al; Crawford, James; Lohn, Jason; Pryor, Anna

2003-01-01

We hypothesize that evolutionary algorithms can effectively schedule coordinated fleets of Earth observing satellites. The constraints are complex and the bottlenecks are not well understood, a condition where evolutionary algorithms are often effective. This is, in part, because evolutionary algorithms require only that one can represent solutions, modify solutions, and evaluate solution fitness. To test the hypothesis we have developed a representative set of problems, produced optimization software (in Java) to solve them, and run experiments comparing techniques. This paper presents initial results of a comparison of several evolutionary and other optimization techniques; namely the genetic algorithm, simulated annealing, squeaky wheel optimization, and stochastic hill climbing. We also compare separate satellite vs. integrated scheduling of a two satellite constellation. While the results are not definitive, tests to date suggest that simulated annealing is the best search technique and integrated scheduling is superior.

Hybrid Genetic Agorithms and Line Search Method for Industrial Production Planning with Non-Linear Fitness Function

NASA Astrophysics Data System (ADS)

Vasant, Pandian; Barsoum, Nader

2008-10-01

Many engineering, science, information technology and management optimization problems can be considered as non linear programming real world problems where the all or some of the parameters and variables involved are uncertain in nature. These can only be quantified using intelligent computational techniques such as evolutionary computation and fuzzy logic. The main objective of this research paper is to solve non linear fuzzy optimization problem where the technological coefficient in the constraints involved are fuzzy numbers which was represented by logistic membership functions by using hybrid evolutionary optimization approach. To explore the applicability of the present study a numerical example is considered to determine the production planning for the decision variables and profit of the company.

Genetic programming based ensemble system for microarray data classification.

PubMed

Liu, Kun-Hong; Tong, Muchenxuan; Xie, Shu-Tong; Yee Ng, Vincent To

2015-01-01

Recently, more and more machine learning techniques have been applied to microarray data analysis. The aim of this study is to propose a genetic programming (GP) based new ensemble system (named GPES), which can be used to effectively classify different types of cancers. Decision trees are deployed as base classifiers in this ensemble framework with three operators: Min, Max, and Average. Each individual of the GP is an ensemble system, and they become more and more accurate in the evolutionary process. The feature selection technique and balanced subsampling technique are applied to increase the diversity in each ensemble system. The final ensemble committee is selected by a forward search algorithm, which is shown to be capable of fitting data automatically. The performance of GPES is evaluated using five binary class and six multiclass microarray datasets, and results show that the algorithm can achieve better results in most cases compared with some other ensemble systems. By using elaborate base classifiers or applying other sampling techniques, the performance of GPES may be further improved.

Genetic Programming Based Ensemble System for Microarray Data Classification

PubMed Central

Liu, Kun-Hong; Tong, Muchenxuan; Xie, Shu-Tong; Yee Ng, Vincent To

2015-01-01

Recently, more and more machine learning techniques have been applied to microarray data analysis. The aim of this study is to propose a genetic programming (GP) based new ensemble system (named GPES), which can be used to effectively classify different types of cancers. Decision trees are deployed as base classifiers in this ensemble framework with three operators: Min, Max, and Average. Each individual of the GP is an ensemble system, and they become more and more accurate in the evolutionary process. The feature selection technique and balanced subsampling technique are applied to increase the diversity in each ensemble system. The final ensemble committee is selected by a forward search algorithm, which is shown to be capable of fitting data automatically. The performance of GPES is evaluated using five binary class and six multiclass microarray datasets, and results show that the algorithm can achieve better results in most cases compared with some other ensemble systems. By using elaborate base classifiers or applying other sampling techniques, the performance of GPES may be further improved. PMID:25810748

Forecasting Caspian Sea level changes using satellite altimetry data (June 1992-December 2013) based on evolutionary support vector regression algorithms and gene expression programming

NASA Astrophysics Data System (ADS)

Imani, Moslem; You, Rey-Jer; Kuo, Chung-Yen

2014-10-01

Sea level forecasting at various time intervals is of great importance in water supply management. Evolutionary artificial intelligence (AI) approaches have been accepted as an appropriate tool for modeling complex nonlinear phenomena in water bodies. In the study, we investigated the ability of two AI techniques: support vector machine (SVM), which is mathematically well-founded and provides new insights into function approximation, and gene expression programming (GEP), which is used to forecast Caspian Sea level anomalies using satellite altimetry observations from June 1992 to December 2013. SVM demonstrates the best performance in predicting Caspian Sea level anomalies, given the minimum root mean square error (RMSE = 0.035) and maximum coefficient of determination (R2 = 0.96) during the prediction periods. A comparison between the proposed AI approaches and the cascade correlation neural network (CCNN) model also shows the superiority of the GEP and SVM models over the CCNN.

Optimal GENCO bidding strategy

NASA Astrophysics Data System (ADS)

Gao, Feng

Electricity industries worldwide are undergoing a period of profound upheaval. The conventional vertically integrated mechanism is being replaced by a competitive market environment. Generation companies have incentives to apply novel technologies to lower production costs, for example: Combined Cycle units. Economic dispatch with Combined Cycle units becomes a non-convex optimization problem, which is difficult if not impossible to solve by conventional methods. Several techniques are proposed here: Mixed Integer Linear Programming, a hybrid method, as well as Evolutionary Algorithms. Evolutionary Algorithms share a common mechanism, stochastic searching per generation. The stochastic property makes evolutionary algorithms robust and adaptive enough to solve a non-convex optimization problem. This research implements GA, EP, and PS algorithms for economic dispatch with Combined Cycle units, and makes a comparison with classical Mixed Integer Linear Programming. The electricity market equilibrium model not only helps Independent System Operator/Regulator analyze market performance and market power, but also provides Market Participants the ability to build optimal bidding strategies based on Microeconomics analysis. Supply Function Equilibrium (SFE) is attractive compared to traditional models. This research identifies a proper SFE model, which can be applied to a multiple period situation. The equilibrium condition using discrete time optimal control is then developed for fuel resource constraints. Finally, the research discusses the issues of multiple equilibria and mixed strategies, which are caused by the transmission network. Additionally, an advantage of the proposed model for merchant transmission planning is discussed. A market simulator is a valuable training and evaluation tool to assist sellers, buyers, and regulators to understand market performance and make better decisions. A traditional optimization model may not be enough to consider the distributed, large-scale, and complex energy market. This research compares the performance and searching paths of different artificial life techniques such as Genetic Algorithm (GA), Evolutionary Programming (EP), and Particle Swarm (PS), and look for a proper method to emulate Generation Companies' (GENCOs) bidding strategies. After deregulation, GENCOs face risk and uncertainty associated with the fast-changing market environment. A profit-based bidding decision support system is critical for GENCOs to keep a competitive position in the new environment. Most past research do not pay special attention to the piecewise staircase characteristic of generator offer curves. This research proposes an optimal bidding strategy based on Parametric Linear Programming. The proposed algorithm is able to handle actual piecewise staircase energy offer curves. The proposed method is then extended to incorporate incomplete information based on Decision Analysis. Finally, the author develops an optimal bidding tool (GenBidding) and applies it to the RTS96 test system.

The Simulation and Analysis of an Evolutionary Model of Deoxyribonucleic Acid (DNA).

DTIC Science & Technology

1983-09-01

current interest in evolutionary biology . This section identifies the organization of the remainder of the paper. The second chapter reports the...the field of evolutionary biology . 77 APPENDIX 78 APPENDIX A PROGRAM SOURCE LISTING -79 PROGRAM SOURCE LISTING 00005 PROGRAM (COMPUTERANDOM MUTATIONS...34Some Theoretical Aspects of the Problem of Life Origin," Journal 2f Theoreical Biology : 13-23, 1975. 27. Chirpich, Thomas P. "Rates of Protein

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation.

PubMed

Cornuet, Jean-Marie; Santos, Filipe; Beaumont, Mark A; Robert, Christian P; Marin, Jean-Michel; Balding, David J; Guillemaud, Thomas; Estoup, Arnaud

2008-12-01

Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. The software DIY ABC is freely available at http://www.montpellier.inra.fr/CBGP/diyabc.

Neuro-evolutionary computing paradigm for Painlevé equation-II in nonlinear optics

NASA Astrophysics Data System (ADS)

Ahmad, Iftikhar; Ahmad, Sufyan; Awais, Muhammad; Ul Islam Ahmad, Siraj; Asif Zahoor Raja, Muhammad

2018-05-01

The aim of this study is to investigate the numerical treatment of the Painlevé equation-II arising in physical models of nonlinear optics through artificial intelligence procedures by incorporating a single layer structure of neural networks optimized with genetic algorithms, sequential quadratic programming and active set techniques. We constructed a mathematical model for the nonlinear Painlevé equation-II with the help of networks by defining an error-based cost function in mean square sense. The performance of the proposed technique is validated through statistical analyses by means of the one-way ANOVA test conducted on a dataset generated by a large number of independent runs.

Speeding Up Ecological and Evolutionary Computations in R; Essentials of High Performance Computing for Biologists

PubMed Central

Visser, Marco D.; McMahon, Sean M.; Merow, Cory; Dixon, Philip M.; Record, Sydne; Jongejans, Eelke

2015-01-01

Computation has become a critical component of research in biology. A risk has emerged that computational and programming challenges may limit research scope, depth, and quality. We review various solutions to common computational efficiency problems in ecological and evolutionary research. Our review pulls together material that is currently scattered across many sources and emphasizes those techniques that are especially effective for typical ecological and environmental problems. We demonstrate how straightforward it can be to write efficient code and implement techniques such as profiling or parallel computing. We supply a newly developed R package (aprof) that helps to identify computational bottlenecks in R code and determine whether optimization can be effective. Our review is complemented by a practical set of examples and detailed Supporting Information material (S1–S3 Texts) that demonstrate large improvements in computational speed (ranging from 10.5 times to 14,000 times faster). By improving computational efficiency, biologists can feasibly solve more complex tasks, ask more ambitious questions, and include more sophisticated analyses in their research. PMID:25811842

Synthesis of concentric circular antenna arrays using dragonfly algorithm

NASA Astrophysics Data System (ADS)

Babayigit, B.

2018-05-01

Due to the strong non-linear relationship between the array factor and the array elements, concentric circular antenna array (CCAA) synthesis problem is challenging. Nature-inspired optimisation techniques have been playing an important role in solving array synthesis problems. Dragonfly algorithm (DA) is a novel nature-inspired optimisation technique which is based on the static and dynamic swarming behaviours of dragonflies in nature. This paper presents the design of CCAAs to get low sidelobes using DA. The effectiveness of the proposed DA is investigated in two different (with and without centre element) cases of two three-ring (having 4-, 6-, 8-element or 8-, 10-, 12-element) CCAA design. The radiation pattern of each design cases is obtained by finding optimal excitation weights of the array elements using DA. Simulation results show that the proposed algorithm outperforms the other state-of-the-art techniques (symbiotic organisms search, biogeography-based optimisation, sequential quadratic programming, opposition-based gravitational search algorithm, cat swarm optimisation, firefly algorithm, evolutionary programming) for all design cases. DA can be a promising technique for electromagnetic problems.

Stochastic Evolutionary Algorithms for Planning Robot Paths

NASA Technical Reports Server (NTRS)

Fink, Wolfgang; Aghazarian, Hrand; Huntsberger, Terrance; Terrile, Richard

2006-01-01

A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.

Cooperative combinatorial optimization: evolutionary computation case study.

PubMed

Burgin, Mark; Eberbach, Eugene

2008-01-01

This paper presents a formalization of the notion of cooperation and competition of multiple systems that work toward a common optimization goal of the population using evolutionary computation techniques. It is proved that evolutionary algorithms are more expressive than conventional recursive algorithms, such as Turing machines. Three classes of evolutionary computations are introduced and studied: bounded finite, unbounded finite, and infinite computations. Universal evolutionary algorithms are constructed. Such properties of evolutionary algorithms as completeness, optimality, and search decidability are examined. A natural extension of evolutionary Turing machine (ETM) model is proposed to properly reflect phenomena of cooperation and competition in the whole population.

Comparing Evolutionary Programs and Evolutionary Pattern Search Algorithms: A Drug Docking Application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, W.E.

1999-02-10

Evolutionary programs (EPs) and evolutionary pattern search algorithms (EPSAS) are two general classes of evolutionary methods for optimizing on continuous domains. The relative performance of these methods has been evaluated on standard global optimization test functions, and these results suggest that EPSAs more robustly converge to near-optimal solutions than EPs. In this paper we evaluate the relative performance of EPSAs and EPs on a real-world application: flexible ligand binding in the Autodock docking software. We compare the performance of these methods on a suite of docking test problems. Our results confirm that EPSAs and EPs have comparable performance, and theymore » suggest that EPSAs may be more robust on larger, more complex problems.« less

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation

PubMed Central

Cornuet, Jean-Marie; Santos, Filipe; Beaumont, Mark A.; Robert, Christian P.; Marin, Jean-Michel; Balding, David J.; Guillemaud, Thomas; Estoup, Arnaud

2008-01-01

Summary: Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. Availability: The software DIY ABC is freely available at http://www.montpellier.inra.fr/CBGP/diyabc. Contact: j.cornuet@imperial.ac.uk Supplementary information: Supplementary data are also available at http://www.montpellier.inra.fr/CBGP/diyabc PMID:18842597

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

NASA Astrophysics Data System (ADS)

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.

Why evolutionary biologists should get seriously involved in ecological monitoring and applied biodiversity assessment programs

PubMed Central

Brodersen, Jakob; Seehausen, Ole

2014-01-01

While ecological monitoring and biodiversity assessment programs are widely implemented and relatively well developed to survey and monitor the structure and dynamics of populations and communities in many ecosystems, quantitative assessment and monitoring of genetic and phenotypic diversity that is important to understand evolutionary dynamics is only rarely integrated. As a consequence, monitoring programs often fail to detect changes in these key components of biodiversity until after major loss of diversity has occurred. The extensive efforts in ecological monitoring have generated large data sets of unique value to macro-scale and long-term ecological research, but the insights gained from such data sets could be multiplied by the inclusion of evolutionary biological approaches. We argue that the lack of process-based evolutionary thinking in ecological monitoring means a significant loss of opportunity for research and conservation. Assessment of genetic and phenotypic variation within and between species needs to be fully integrated to safeguard biodiversity and the ecological and evolutionary dynamics in natural ecosystems. We illustrate our case with examples from fishes and conclude with examples of ongoing monitoring programs and provide suggestions on how to improve future quantitative diversity surveys. PMID:25553061

DE and NLP Based QPLS Algorithm

NASA Astrophysics Data System (ADS)

Yu, Xiaodong; Huang, Dexian; Wang, Xiong; Liu, Bo

As a novel evolutionary computing technique, Differential Evolution (DE) has been considered to be an effective optimization method for complex optimization problems, and achieved many successful applications in engineering. In this paper, a new algorithm of Quadratic Partial Least Squares (QPLS) based on Nonlinear Programming (NLP) is presented. And DE is used to solve the NLP so as to calculate the optimal input weights and the parameters of inner relationship. The simulation results based on the soft measurement of diesel oil solidifying point on a real crude distillation unit demonstrate that the superiority of the proposed algorithm to linear PLS and QPLS which is based on Sequential Quadratic Programming (SQP) in terms of fitting accuracy and computational costs.

Evolutionary game theory for physical and biological scientists. I. Training and validating population dynamics equations.

PubMed

Liao, David; Tlsty, Thea D

2014-08-06

Failure to understand evolutionary dynamics has been hypothesized as limiting our ability to control biological systems. An increasing awareness of similarities between macroscopic ecosystems and cellular tissues has inspired optimism that game theory will provide insights into the progression and control of cancer. To realize this potential, the ability to compare game theoretic models and experimental measurements of population dynamics should be broadly disseminated. In this tutorial, we present an analysis method that can be used to train parameters in game theoretic dynamics equations, used to validate the resulting equations, and used to make predictions to challenge these equations and to design treatment strategies. The data analysis techniques in this tutorial are adapted from the analysis of reaction kinetics using the method of initial rates taught in undergraduate general chemistry courses. Reliance on computer programming is avoided to encourage the adoption of these methods as routine bench activities.

Practical advantages of evolutionary computation

NASA Astrophysics Data System (ADS)

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.

Life sciences biomedical research planning for Space Station

NASA Technical Reports Server (NTRS)

Primeaux, Gary R.; Michaud, Roger; Miller, Ladonna; Searcy, Jim; Dickey, Bernistine

1987-01-01

The Biomedical Research Project (BmRP), a major component of the NASA Life Sciences Space Station Program, incorporates a laboratory for the study of the effects of microgravity on the human body, and the development of techniques capable of modifying or counteracting these effects. Attention is presently given to a representative scenario of BmRP investigations and associated engineering analyses, together with an account of the evolutionary process by which the scenarios and the Space Station design requirements they entail are identified. Attention is given to a tether-implemented 'variable gravity centrifuge'.

An evolutionary algorithm that constructs recurrent neural networks.

PubMed

Angeline, P J; Saunders, G M; Pollack, J B

1994-01-01

Standard methods for simultaneously inducing the structure and weights of recurrent neural networks limit every task to an assumed class of architectures. Such a simplification is necessary since the interactions between network structure and function are not well understood. Evolutionary computations, which include genetic algorithms and evolutionary programming, are population-based search methods that have shown promise in many similarly complex tasks. This paper argues that genetic algorithms are inappropriate for network acquisition and describes an evolutionary program, called GNARL, that simultaneously acquires both the structure and weights for recurrent networks. GNARL's empirical acquisition method allows for the emergence of complex behaviors and topologies that are potentially excluded by the artificial architectural constraints imposed in standard network induction methods.

Evolutionary effects of alternative artificial propagation programs: implications for viability of endangered anadromous salmonids

PubMed Central

McClure, Michelle M; Utter, Fred M; Baldwin, Casey; Carmichael, Richard W; Hassemer, Peter F; Howell, Philip J; Spruell, Paul; Cooney, Thomas D; Schaller, Howard A; Petrosky, Charles E

2008-01-01

Most hatchery programs for anadromous salmonids have been initiated to increase the numbers of fish for harvest, to mitigate for habitat losses, or to increase abundance in populations at low abundance. However, the manner in which these programs are implemented can have significant impacts on the evolutionary trajectory and long-term viability of populations. In this paper, we review the potential benefits and risks of hatchery programs relative to the conservation of species listed under the US Endangered Species Act. To illustrate, we present the range of potential effects within a population as well as among populations of Chinook salmon (Oncorhynchus tshawytscha) where changes to major hatchery programs are being considered. We apply evolutionary considerations emerging from these examples to suggest broader principles for hatchery uses that are consistent with conservation goals. We conclude that because of the evolutionary risks posed by artificial propagation programs, they should not be viewed as a substitute for addressing other limiting factors that prevent achieving viability. At the population level, artificial propagation programs that are implemented as a short-term approach to avoid imminent extinction are more likely to achieve long-term population viability than approaches that rely on long-term supplementation. In addition, artificial propagation programs can have out-of-population impacts that should be considered in conservation planning. PMID:25567637

Product Mix Selection Using AN Evolutionary Technique

NASA Astrophysics Data System (ADS)

Tsoulos, Ioannis G.; Vasant, Pandian

2009-08-01

This paper proposes an evolutionary technique for the solution of a real—life industrial problem and particular for the product mix selection problem. The evolutionary technique is a combination of a genetic algorithm that preserves the feasibility of the trial solutions with penalties and some local optimization method. The goal of this paper has been achieved in finding the best near optimal solution for the profit fitness function respect to vagueness factor and level of satisfaction. The findings of the profit values will be very useful for the decision makers in the industrial engineering sector for the implementation purpose. It's possible to improve the solutions obtained in this study by employing other meta-heuristic methods such as simulated annealing, tabu Search, ant colony optimization, particle swarm optimization and artificial immune systems.

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

PubMed

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

2014-03-01

This paper presents a novel rule-based fuzzy classification methodology for survival/mortality prediction in severe burnt patients. Due to the ethical aspects involved in this medical scenario, physicians tend not to accept a computer-based evaluation unless they understand why and how such a recommendation is given. Therefore, any fuzzy classifier model must be both accurate and interpretable. The proposed methodology is a three-step process: (1) multi-objective constrained optimization of a patient's data set, using Pareto-based elitist multi-objective evolutionary algorithms to maximize accuracy and minimize the complexity (number of rules) of classifiers, subject to interpretability constraints; this step produces a set of alternative (Pareto) classifiers; (2) linguistic labeling, which assigns a linguistic label to each fuzzy set of the classifiers; this step is essential to the interpretability of the classifiers; (3) decision making, whereby a classifier is chosen, if it is satisfactory, according to the preferences of the decision maker. If no classifier is satisfactory for the decision maker, the process starts again in step (1) with a different input parameter set. The performance of three multi-objective evolutionary algorithms, niched pre-selection multi-objective algorithm, elitist Pareto-based multi-objective evolutionary algorithm for diversity reinforcement (ENORA) and the non-dominated sorting genetic algorithm (NSGA-II), was tested using a patient's data set from an intensive care burn unit and a standard machine learning data set from an standard machine learning repository. The results are compared using the hypervolume multi-objective metric. Besides, the results have been compared with other non-evolutionary techniques and validated with a multi-objective cross-validation technique. Our proposal improves the classification rate obtained by other non-evolutionary techniques (decision trees, artificial neural networks, Naive Bayes, and case-based reasoning) obtaining with ENORA a classification rate of 0.9298, specificity of 0.9385, and sensitivity of 0.9364, with 14.2 interpretable fuzzy rules on average. Our proposal improves the accuracy and interpretability of the classifiers, compared with other non-evolutionary techniques. We also conclude that ENORA outperforms niched pre-selection and NSGA-II algorithms. Moreover, given that our multi-objective evolutionary methodology is non-combinational based on real parameter optimization, the time cost is significantly reduced compared with other evolutionary approaches existing in literature based on combinational optimization. Copyright © 2014 Elsevier B.V. All rights reserved.

AI-BL1.0: a program for automatic on-line beamline optimization using the evolutionary algorithm.

PubMed

Xi, Shibo; Borgna, Lucas Santiago; Zheng, Lirong; Du, Yonghua; Hu, Tiandou

2017-01-01

In this report, AI-BL1.0, an open-source Labview-based program for automatic on-line beamline optimization, is presented. The optimization algorithms used in the program are Genetic Algorithm and Differential Evolution. Efficiency was improved by use of a strategy known as Observer Mode for Evolutionary Algorithm. The program was constructed and validated at the XAFCA beamline of the Singapore Synchrotron Light Source and 1W1B beamline of the Beijing Synchrotron Radiation Facility.

Modelling formulations using gene expression programming--a comparative analysis with artificial neural networks.

PubMed

Colbourn, E A; Roskilly, S J; Rowe, R C; York, P

2011-10-09

This study has investigated the utility and potential advantages of gene expression programming (GEP)--a new development in evolutionary computing for modelling data and automatically generating equations that describe the cause-and-effect relationships in a system--to four types of pharmaceutical formulation and compared the models with those generated by neural networks, a technique now widely used in the formulation development. Both methods were capable of discovering subtle and non-linear relationships within the data, with no requirement from the user to specify the functional forms that should be used. Although the neural networks rapidly developed models with higher values for the ANOVA R(2) these were black box and provided little insight into the key relationships. However, GEP, although significantly slower at developing models, generated relatively simple equations describing the relationships that could be interpreted directly. The results indicate that GEP can be considered an effective and efficient modelling technique for formulation data. Copyright © 2011 Elsevier B.V. All rights reserved.

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

ERIC Educational Resources Information Center

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…

A review of estimation of distribution algorithms in bioinformatics

PubMed Central

Armañanzas, Rubén; Inza, Iñaki; Santana, Roberto; Saeys, Yvan; Flores, Jose Luis; Lozano, Jose Antonio; Peer, Yves Van de; Blanco, Rosa; Robles, Víctor; Bielza, Concha; Larrañaga, Pedro

2008-01-01

Evolutionary search algorithms have become an essential asset in the algorithmic toolbox for solving high-dimensional optimization problems in across a broad range of bioinformatics problems. Genetic algorithms, the most well-known and representative evolutionary search technique, have been the subject of the major part of such applications. Estimation of distribution algorithms (EDAs) offer a novel evolutionary paradigm that constitutes a natural and attractive alternative to genetic algorithms. They make use of a probabilistic model, learnt from the promising solutions, to guide the search process. In this paper, we set out a basic taxonomy of EDA techniques, underlining the nature and complexity of the probabilistic model of each EDA variant. We review a set of innovative works that make use of EDA techniques to solve challenging bioinformatics problems, emphasizing the EDA paradigm's potential for further research in this domain. PMID:18822112

Evolutionary Theory in Undergraduate Biology Programs at Lebanese Universities: A Comparative Study

ERIC Educational Resources Information Center

Vlaardingerbroek, Barend; Hachem-El-Masri, Yasmine

2006-01-01

The purpose of this study was to gauge the profile of evolutionary theory in Lebanese undergraduate biology programs. The research focused mainly on the views of university biology department heads, given that they are the people who exercise the most direct influence over their departments' ethos. An Australasian sample was chosen as a reference…

Evolutionary trade-offs in kidney injury and repair.

PubMed

Lei, Yutian; Anders, Hans-Joachim

2017-11-01

Evolutionary medicine has proven helpful to understand the origin of human disease, e.g. in identifying causal roles of recent environmental changes impacting on human physiology (environment-phenotype mismatch). In contrast, diseases affecting only a limited number of members of a species often originate from evolutionary trade-offs for usually physiologic adaptations assuring reproductive success in the context of extrinsic threats. For example, the G1 and G2 variants of the APOL1 gene supporting control of Trypanosoma infection come with the trade-off that they promote the progression of kidney disease. In this review we extend the concept of evolutionary nephrology by discussing how the physiologic adaptations (danger responses) to tissue injury create evolutionary trade-offs that drive histopathological changes underlying acute and chronic kidney diseases. The evolution of multicellular organisms positively selected a number of danger response programs for their overwhelming benefits in assuring survival such as clotting, inflammation, epithelial healing and mesenchymal healing, i.e. fibrosis and sclerosis. Upon kidney injury these danger programs often present as pathomechanisms driving persistent nephron loss and renal failure. We explore how classic kidney disease entities involve insufficient or overshooting activation of these danger response programs for which the underlying genetic basis remains largely to be defined. Dissecting the causative and hierarchical relationships between danger programs should help to identify molecular targets to control kidney injury and to improve disease outcomes.

Multidimensional scaling for evolutionary algorithms--visualization of the path through search space and solution space using Sammon mapping.

PubMed

Pohlheim, Hartmut

2006-01-01

Multidimensional scaling as a technique for the presentation of high-dimensional data with standard visualization techniques is presented. The technique used is often known as Sammon mapping. We explain the mathematical foundations of multidimensional scaling and its robust calculation. We also demonstrate the use of this technique in the area of evolutionary algorithms. First, we present the visualization of the path through the search space of the best individuals during an optimization run. We then apply multidimensional scaling to the comparison of multiple runs regarding the variables of individuals and multi-criteria objective values (path through the solution space).

Analysis of convergence of an evolutionary algorithm with self-adaptation using a stochastic Lyapunov function.

PubMed

Semenov, Mikhail A; Terkel, Dmitri A

2003-01-01

This paper analyses the convergence of evolutionary algorithms using a technique which is based on a stochastic Lyapunov function and developed within the martingale theory. This technique is used to investigate the convergence of a simple evolutionary algorithm with self-adaptation, which contains two types of parameters: fitness parameters, belonging to the domain of the objective function; and control parameters, responsible for the variation of fitness parameters. Although both parameters mutate randomly and independently, they converge to the "optimum" due to the direct (for fitness parameters) and indirect (for control parameters) selection. We show that the convergence velocity of the evolutionary algorithm with self-adaptation is asymptotically exponential, similar to the velocity of the optimal deterministic algorithm on the class of unimodal functions. Although some martingale inequalities have not be proved analytically, they have been numerically validated with 0.999 confidence using Monte-Carlo simulations.

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

PubMed

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.

A Bell-Curved Based Algorithm for Mixed Continuous and Discrete Structural Optimization

NASA Technical Reports Server (NTRS)

Kincaid, Rex K.; Weber, Michael; Sobieszczanski-Sobieski, Jaroslaw

2001-01-01

An evolutionary based strategy utilizing two normal distributions to generate children is developed to solve mixed integer nonlinear programming problems. This Bell-Curve Based (BCB) evolutionary algorithm is similar in spirit to (mu + mu) evolutionary strategies and evolutionary programs but with fewer parameters to adjust and no mechanism for self adaptation. First, a new version of BCB to solve purely discrete optimization problems is described and its performance tested against a tabu search code for an actuator placement problem. Next, the performance of a combined version of discrete and continuous BCB is tested on 2-dimensional shape problems and on a minimum weight hub design problem. In the latter case the discrete portion is the choice of the underlying beam shape (I, triangular, circular, rectangular, or U).

Development of an evolutionary simulator and an overall control system for intelligent wheelchair

NASA Astrophysics Data System (ADS)

Imai, Makoto; Kawato, Koji; Hamagami, Tomoki; Hirata, Hironori

The goal of this research is to develop an intelligent wheelchair (IWC) system which aids an indoor safe mobility for elderly and disabled people with a new conceptual architecture which realizes autonomy, cooperativeness, and a collaboration behavior. In order to develop the IWC system in real environment, we need design-tools and flexible architecture. In particular, as more significant ones, this paper describes two key techniques which are an evolutionary simulation and an overall control mechanism. The evolutionary simulation technique corrects the error between the virtual environment in a simulator and real one in during the learning of an IWC agent, and coevolves with the agent. The overall control mechanism is implemented with subsumption architecture which is employed in an autonomous robot controller. By using these techniques in both simulations and experiments, we confirm that our IWC system acquires autonomy, cooperativeness, and a collaboration behavior efficiently.

Integrating instance selection, instance weighting, and feature weighting for nearest neighbor classifiers by coevolutionary algorithms.

PubMed

Derrac, Joaquín; Triguero, Isaac; Garcia, Salvador; Herrera, Francisco

2012-10-01

Cooperative coevolution is a successful trend of evolutionary computation which allows us to define partitions of the domain of a given problem, or to integrate several related techniques into one, by the use of evolutionary algorithms. It is possible to apply it to the development of advanced classification methods, which integrate several machine learning techniques into a single proposal. A novel approach integrating instance selection, instance weighting, and feature weighting into the framework of a coevolutionary model is presented in this paper. We compare it with a wide range of evolutionary and nonevolutionary related methods, in order to show the benefits of the employment of coevolution to apply the techniques considered simultaneously. The results obtained, contrasted through nonparametric statistical tests, show that our proposal outperforms other methods in the comparison, thus becoming a suitable tool in the task of enhancing the nearest neighbor classifier.

Non-Evolutionary Algorithms for Scheduling Dependent Tasks in Distributed Heterogeneous Computing Environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wayne F. Boyer; Gurdeep S. Hura

2005-09-01

The Problem of obtaining an optimal matching and scheduling of interdependent tasks in distributed heterogeneous computing (DHC) environments is well known to be an NP-hard problem. In a DHC system, task execution time is dependent on the machine to which it is assigned and task precedence constraints are represented by a directed acyclic graph. Recent research in evolutionary techniques has shown that genetic algorithms usually obtain more efficient schedules that other known algorithms. We propose a non-evolutionary random scheduling (RS) algorithm for efficient matching and scheduling of inter-dependent tasks in a DHC system. RS is a succession of randomized taskmore » orderings and a heuristic mapping from task order to schedule. Randomized task ordering is effectively a topological sort where the outcome may be any possible task order for which the task precedent constraints are maintained. A detailed comparison to existing evolutionary techniques (GA and PSGA) shows the proposed algorithm is less complex than evolutionary techniques, computes schedules in less time, requires less memory and fewer tuning parameters. Simulation results show that the average schedules produced by RS are approximately as efficient as PSGA schedules for all cases studied and clearly more efficient than PSGA for certain cases. The standard formulation for the scheduling problem addressed in this paper is Rm|prec|Cmax.,« less

On the path to genetic novelties: insights from programmed DNA elimination and RNA splicing.

PubMed

Catania, Francesco; Schmitz, Jürgen

2015-01-01

Understanding how genetic novelties arise is a central goal of evolutionary biology. To this end, programmed DNA elimination and RNA splicing deserve special consideration. While programmed DNA elimination reshapes genomes by eliminating chromatin during organismal development, RNA splicing rearranges genetic messages by removing intronic regions during transcription. Small RNAs help to mediate this class of sequence reorganization, which is not error-free. It is this imperfection that makes programmed DNA elimination and RNA splicing excellent candidates for generating evolutionary novelties. Leveraging a number of these two processes' mechanistic and evolutionary properties, which have been uncovered over the past years, we present recently proposed models and empirical evidence for how splicing can shape the structure of protein-coding genes in eukaryotes. We also chronicle a number of intriguing similarities between the processes of programmed DNA elimination and RNA splicing, and highlight the role that the variation in the population-genetic environment may play in shaping their target sequences. © 2015 Wiley Periodicals, Inc.

Quality Assurance Program for Molecular Medicine Laboratories

PubMed Central

Hajia, M; Safadel, N; Samiee, S Mirab; Dahim, P; Anjarani, S; Nafisi, N; Sohrabi, A; Rafiee, M; Sabzavi, F; Entekhabi, B

2013-01-01

Background: Molecular diagnostic methods have played and continuing to have a critical role in clinical laboratories in recent years. Therefore, standardization is an evolutionary process that needs to be upgrade with increasing scientific knowledge, improvement of the instruments and techniques. The aim of this study was to design a quality assurance program in order to have similar conditions for all medical laboratories engaging with molecular tests. Methods: We had to design a plan for all four elements; required space conditions, equipments, training, and basic guidelines. Necessary guidelines was prepared and confirmed by the launched specific committee at the Health Reference Laboratory. Results: Several workshops were also held for medical laboratories directors and staffs, quality control manager of molecular companies, directors and nominees from universities. Accreditation of equipments and molecular material was followed parallel with rest of program. Now we are going to accredit medical laboratories and to evaluate the success of the program. Conclusion: Accreditation of medical laboratory will be succeeding if its basic elements are provided in advance. Professional practice guidelines, holding training and performing accreditation the molecular materials and equipments ensured us that laboratories are aware of best practices, proper interpretation, limitations of techniques, and technical issues. Now, active external auditing can improve the applied laboratory conditions toward the defined standard level. PMID:23865028

Quality assurance program for molecular medicine laboratories.

PubMed

Hajia, M; Safadel, N; Samiee, S Mirab; Dahim, P; Anjarani, S; Nafisi, N; Sohrabi, A; Rafiee, M; Sabzavi, F; Entekhabi, B

2013-01-01

Molecular diagnostic methods have played and continuing to have a critical role in clinical laboratories in recent years. Therefore, standardization is an evolutionary process that needs to be upgrade with increasing scientific knowledge, improvement of the instruments and techniques. The aim of this study was to design a quality assurance program in order to have similar conditions for all medical laboratories engaging with molecular tests. We had to design a plan for all four elements; required space conditions, equipments, training, and basic guidelines. Necessary guidelines was prepared and confirmed by the launched specific committee at the Health Reference Laboratory. Several workshops were also held for medical laboratories directors and staffs, quality control manager of molecular companies, directors and nominees from universities. Accreditation of equipments and molecular material was followed parallel with rest of program. Now we are going to accredit medical laboratories and to evaluate the success of the program. Accreditation of medical laboratory will be succeeding if its basic elements are provided in advance. Professional practice guidelines, holding training and performing accreditation the molecular materials and equipments ensured us that laboratories are aware of best practices, proper interpretation, limitations of techniques, and technical issues. Now, active external auditing can improve the applied laboratory conditions toward the defined standard level.

A sense of life: computational and experimental investigations with models of biochemical and evolutionary processes.

PubMed

Mishra, Bud; Daruwala, Raoul-Sam; Zhou, Yi; Ugel, Nadia; Policriti, Alberto; Antoniotti, Marco; Paxia, Salvatore; Rejali, Marc; Rudra, Archisman; Cherepinsky, Vera; Silver, Naomi; Casey, William; Piazza, Carla; Simeoni, Marta; Barbano, Paolo; Spivak, Marina; Feng, Jiawu; Gill, Ofer; Venkatesh, Mysore; Cheng, Fang; Sun, Bing; Ioniata, Iuliana; Anantharaman, Thomas; Hubbard, E Jane Albert; Pnueli, Amir; Harel, David; Chandru, Vijay; Hariharan, Ramesh; Wigler, Michael; Park, Frank; Lin, Shih-Chieh; Lazebnik, Yuri; Winkler, Franz; Cantor, Charles R; Carbone, Alessandra; Gromov, Mikhael

2003-01-01

We collaborate in a research program aimed at creating a rigorous framework, experimental infrastructure, and computational environment for understanding, experimenting with, manipulating, and modifying a diverse set of fundamental biological processes at multiple scales and spatio-temporal modes. The novelty of our research is based on an approach that (i) requires coevolution of experimental science and theoretical techniques and (ii) exploits a certain universality in biology guided by a parsimonious model of evolutionary mechanisms operating at the genomic level and manifesting at the proteomic, transcriptomic, phylogenic, and other higher levels. Our current program in "systems biology" endeavors to marry large-scale biological experiments with the tools to ponder and reason about large, complex, and subtle natural systems. To achieve this ambitious goal, ideas and concepts are combined from many different fields: biological experimentation, applied mathematical modeling, computational reasoning schemes, and large-scale numerical and symbolic simulations. From a biological viewpoint, the basic issues are many: (i) understanding common and shared structural motifs among biological processes; (ii) modeling biological noise due to interactions among a small number of key molecules or loss of synchrony; (iii) explaining the robustness of these systems in spite of such noise; and (iv) cataloging multistatic behavior and adaptation exhibited by many biological processes.

The Molecular Ecophysiology of Programmed Cell Death in Marine Phytoplankton

NASA Astrophysics Data System (ADS)

Bidle, Kay D.

2015-01-01

Planktonic, prokaryotic, and eukaryotic photoautotrophs (phytoplankton) share a diverse and ancient evolutionary history, during which time they have played key roles in regulating marine food webs, biogeochemical cycles, and Earth's climate. Because phytoplankton represent the basis of marine ecosystems, the manner in which they die critically determines the flow and fate of photosynthetically fixed organic matter (and associated elements), ultimately constraining upper-ocean biogeochemistry. Programmed cell death (PCD) and associated pathway genes, which are triggered by a variety of nutrient stressors and are employed by parasitic viruses, play an integral role in determining the cell fate of diverse photoautotrophs in the modern ocean. Indeed, these multifaceted death pathways continue to shape the success and evolutionary trajectory of diverse phytoplankton lineages at sea. Research over the past two decades has employed physiological, biochemical, and genetic techniques to provide a novel, comprehensive, mechanistic understanding of the factors controlling this key process. Here, I discuss the current understanding of the genetics, activation, and regulation of PCD pathways in marine model systems; how PCD evolved in unicellular photoautotrophs; how it mechanistically interfaces with viral infection pathways; how stress signals are sensed and transduced into cellular responses; and how novel molecular and biochemical tools are revealing the impact of PCD genes on the fate of natural phytoplankton assemblages.

Evolutionary and Comparative Genomics to Drive Rational Drug Design, with Particular Focus on Neuropeptide Seven-Transmembrane Receptors.

PubMed

Furlong, Michael; Seong, Jae Young

2017-01-01

Seven transmembrane receptors (7TMRs), also known as G protein-coupled receptors, are popular targets of drug development, particularly 7TMR systems that are activated by peptide ligands. Although many pharmaceutical drugs have been discovered via conventional bulk analysis techniques the increasing availability of structural and evolutionary data are facilitating change to rational, targeted drug design. This article discusses the appeal of neuropeptide-7TMR systems as drug targets and provides an overview of concepts in the evolution of vertebrate genomes and gene families. Subsequently, methods that use evolutionary concepts and comparative analysis techniques to aid in gene discovery, gene function identification, and novel drug design are provided along with case study examples.

Evolutionary and Comparative Genomics to Drive Rational Drug Design, with Particular Focus on Neuropeptide Seven-Transmembrane Receptors

PubMed Central

Furlong, Michael; Seong, Jae Young

2017-01-01

Seven transmembrane receptors (7TMRs), also known as G protein-coupled receptors, are popular targets of drug development, particularly 7TMR systems that are activated by peptide ligands. Although many pharmaceutical drugs have been discovered via conventional bulk analysis techniques the increasing availability of structural and evolutionary data are facilitating change to rational, targeted drug design. This article discusses the appeal of neuropeptide-7TMR systems as drug targets and provides an overview of concepts in the evolution of vertebrate genomes and gene families. Subsequently, methods that use evolutionary concepts and comparative analysis techniques to aid in gene discovery, gene function identification, and novel drug design are provided along with case study examples. PMID:28035082

Scalability issues in evolutionary synthesis of electronic circuits: lessons learned and challenges ahead

NASA Technical Reports Server (NTRS)

Stoica, A.; Keymeulen, D.; Zebulum, R. S.; Ferguson, M. I.

2003-01-01

This paper describes scalability issues of evolutionary-driven automatic synthesis of electronic circuits. The article begins by reviewing the concepts of circuit evolution and discussing the limitations of this technique when trying to achieve more complex systems.

Development of X-TOOLSS: Preliminary Design of Space Systems Using Evolutionary Computation

NASA Technical Reports Server (NTRS)

Schnell, Andrew R.; Hull, Patrick V.; Turner, Mike L.; Dozier, Gerry; Alverson, Lauren; Garrett, Aaron; Reneau, Jarred

2008-01-01

Evolutionary computational (EC) techniques such as genetic algorithms (GA) have been identified as promising methods to explore the design space of mechanical and electrical systems at the earliest stages of design. In this paper the authors summarize their research in the use of evolutionary computation to develop preliminary designs for various space systems. An evolutionary computational solver developed over the course of the research, X-TOOLSS (Exploration Toolset for the Optimization of Launch and Space Systems) is discussed. With the success of early, low-fidelity example problems, an outline of work involving more computationally complex models is discussed.

Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation.

PubMed

Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A

2015-09-01

This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach. © 2015 Society for Risk Analysis.

Training the Millennial learner through experiential evolutionary scaffolding: implications for clinical supervision in graduate education programs.

PubMed

Venne, Vickie L; Coleman, Darrell

2010-12-01

They are the Millennials--Generation Y. Over the next few decades, they will be entering genetic counseling graduate training programs and the workforce. As a group, they are unlike previous youth generations in many ways, including the way they learn. Therefore, genetic counselors who teach and supervise need to understand the Millennials and explore new ways of teaching to ensure that the next cohort of genetic counselors has both skills and knowledge to represent our profession well. This paper will summarize the distinguishing traits of the Millennial generation as well as authentic learning and evolutionary scaffolding theories of learning that can enhance teaching and supervision. We will then use specific aspects of case preparation during clinical rotations to demonstrate how incorporating authentic learning theory into evolutionary scaffolding results in experiential evolutionary scaffolding, a method that potentially offers a more effective approach when teaching Millennials. We conclude with suggestions for future research.

Bell-Curve Based Evolutionary Strategies for Structural Optimization

NASA Technical Reports Server (NTRS)

Kincaid, Rex K.

2001-01-01

Evolutionary methods are exceedingly popular with practitioners of many fields; more so than perhaps any optimization tool in existence. Historically Genetic Algorithms (GAs) led the way in practitioner popularity. However, in the last ten years Evolutionary Strategies (ESs) and Evolutionary Programs (EPS) have gained a significant foothold. One partial explanation for this shift is the interest in using GAs to solve continuous optimization problems. The typical GA relies upon a cumbersome binary representation of the design variables. An ES or EP, however, works directly with the real-valued design variables. For detailed references on evolutionary methods in general and ES or EP in specific see Back and Dasgupta and Michalesicz. We call our evolutionary algorithm BCB (bell curve based) since it is based upon two normal distributions.

Open Issues in Evolutionary Robotics.

PubMed

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.

Applications of Evolutionary Technology to Manufacturing and Logistics Systems : State-of-the Art Survey

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Lin, Lin

Many combinatorial optimization problems from industrial engineering and operations research in real-world are very complex in nature and quite hard to solve them by conventional techniques. Since the 1960s, there has been an increasing interest in imitating living beings to solve such kinds of hard combinatorial optimization problems. Simulating the natural evolutionary process of human beings results in stochastic optimization techniques called evolutionary algorithms (EAs), which can often outperform conventional optimization methods when applied to difficult real-world problems. In this survey paper, we provide a comprehensive survey of the current state-of-the-art in the use of EA in manufacturing and logistics systems. In order to demonstrate the EAs which are powerful and broadly applicable stochastic search and optimization techniques, we deal with the following engineering design problems: transportation planning models, layout design models and two-stage logistics models in logistics systems; job-shop scheduling, resource constrained project scheduling in manufacturing system.

Big cat phylogenies, consensus trees, and computational thinking.

PubMed

Sul, Seung-Jin; Williams, Tiffani L

2011-07-01

Phylogenetics seeks to deduce the pattern of relatedness between organisms by using a phylogeny or evolutionary tree. For a given set of organisms or taxa, there may be many evolutionary trees depicting how these organisms evolved from a common ancestor. As a result, consensus trees are a popular approach for summarizing the shared evolutionary relationships in a group of trees. We examine these consensus techniques by studying how the pantherine lineage of cats (clouded leopard, jaguar, leopard, lion, snow leopard, and tiger) evolved, which is hotly debated. While there are many phylogenetic resources that describe consensus trees, there is very little information, written for biologists, regarding the underlying computational techniques for building them. The pantherine cats provide us with a small, relevant example to explore the computational techniques (such as sorting numbers, hashing functions, and traversing trees) for constructing consensus trees. Our hope is that life scientists enjoy peeking under the computational hood of consensus tree construction and share their positive experiences with others in their community.

Evolutionary Based Techniques for Fault Tolerant Field Programmable Gate Arrays

NASA Technical Reports Server (NTRS)

Larchev, Gregory V.; Lohn, Jason D.

2006-01-01

The use of SRAM-based Field Programmable Gate Arrays (FPGAs) is becoming more and more prevalent in space applications. Commercial-grade FPGAs are potentially susceptible to permanently debilitating Single-Event Latchups (SELs). Repair methods based on Evolutionary Algorithms may be applied to FPGA circuits to enable successful fault recovery. This paper presents the experimental results of applying such methods to repair four commonly used circuits (quadrature decoder, 3-by-3-bit multiplier, 3-by-3-bit adder, 440-7 decoder) into which a number of simulated faults have been introduced. The results suggest that evolutionary repair techniques can improve the process of fault recovery when used instead of or as a supplement to Triple Modular Redundancy (TMR), which is currently the predominant method for mitigating FPGA faults.

Fuzzy Controller Design Using Evolutionary Techniques for Twin Rotor MIMO System: A Comparative Study.

PubMed

Hashim, H A; Abido, M A

2015-01-01

This paper presents a comparative study of fuzzy controller design for the twin rotor multi-input multioutput (MIMO) system (TRMS) considering most promising evolutionary techniques. These are gravitational search algorithm (GSA), particle swarm optimization (PSO), artificial bee colony (ABC), and differential evolution (DE). In this study, the gains of four fuzzy proportional derivative (PD) controllers for TRMS have been optimized using the considered techniques. The optimization techniques are developed to identify the optimal control parameters for system stability enhancement, to cancel high nonlinearities in the model, to reduce the coupling effect, and to drive TRMS pitch and yaw angles into the desired tracking trajectory efficiently and accurately. The most effective technique in terms of system response due to different disturbances has been investigated. In this work, it is observed that GSA is the most effective technique in terms of solution quality and convergence speed.

Fuzzy Controller Design Using Evolutionary Techniques for Twin Rotor MIMO System: A Comparative Study

PubMed Central

Hashim, H. A.; Abido, M. A.

2015-01-01

This paper presents a comparative study of fuzzy controller design for the twin rotor multi-input multioutput (MIMO) system (TRMS) considering most promising evolutionary techniques. These are gravitational search algorithm (GSA), particle swarm optimization (PSO), artificial bee colony (ABC), and differential evolution (DE). In this study, the gains of four fuzzy proportional derivative (PD) controllers for TRMS have been optimized using the considered techniques. The optimization techniques are developed to identify the optimal control parameters for system stability enhancement, to cancel high nonlinearities in the model, to reduce the coupling effect, and to drive TRMS pitch and yaw angles into the desired tracking trajectory efficiently and accurately. The most effective technique in terms of system response due to different disturbances has been investigated. In this work, it is observed that GSA is the most effective technique in terms of solution quality and convergence speed. PMID:25960738

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

PubMed

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.

Advanced fitness landscape analysis and the performance of memetic algorithms.

PubMed

Merz, Peter

2004-01-01

Memetic algorithms (MAs) have demonstrated very effective in combinatorial optimization. This paper offers explanations as to why this is so by investigating the performance of MAs in terms of efficiency and effectiveness. A special class of MAs is used to discuss efficiency and effectiveness for local search and evolutionary meta-search. It is shown that the efficiency of MAs can be increased drastically with the use of domain knowledge. However, effectiveness highly depends on the structure of the problem. As is well-known, identifying this structure is made easier with the notion of fitness landscapes: the local properties of the fitness landscape strongly influence the effectiveness of the local search while the global properties strongly influence the effectiveness of the evolutionary meta-search. This paper also introduces new techniques for analyzing the fitness landscapes of combinatorial problems; these techniques focus on the investigation of random walks in the fitness landscape starting at locally optimal solutions as well as on the escape from the basins of attractions of current local optima. It is shown for NK-landscapes and landscapes of the unconstrained binary quadratic programming problem (BQP) that a random walk to another local optimum can be used to explain the efficiency of recombination in comparison to mutation. Moreover, the paper shows that other aspects like the size of the basins of attractions of local optima are important for the efficiency of MAs and a local search escape analysis is proposed. These simple analysis techniques have several advantages over previously proposed statistical measures and provide valuable insight into the behaviour of MAs on different kinds of landscapes.

Adaptive Fuzzy Systems in Computational Intelligence

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1996-01-01

In recent years, the interest in computational intelligence techniques, which currently includes neural networks, fuzzy systems, and evolutionary programming, has grown significantly and a number of their applications have been developed in the government and industry. In future, an essential element in these systems will be fuzzy systems that can learn from experience by using neural network in refining their performances. The GARIC architecture, introduced earlier, is an example of a fuzzy reinforcement learning system which has been applied in several control domains such as cart-pole balancing, simulation of to Space Shuttle orbital operations, and tether control. A number of examples from GARIC's applications in these domains will be demonstrated.

Automated design of spacecraft systems power subsystems

NASA Technical Reports Server (NTRS)

Terrile, Richard J.; Kordon, Mark; Mandutianu, Dan; Salcedo, Jose; Wood, Eric; Hashemi, Mona

2006-01-01

This paper discusses the application of evolutionary computing to a dynamic space vehicle power subsystem resource and performance simulation in a parallel processing environment. Our objective is to demonstrate the feasibility, application and advantage of using evolutionary computation techniques for the early design search and optimization of space systems.

Testing Evolutionary Hypotheses in the Classroom with MacClade Software.

ERIC Educational Resources Information Center

Codella, Sylvio G.

2002-01-01

Introduces MacClade which is a Macintosh-based software package that uses the techniques of cladistic analysis to explore evolutionary patterns. Describes a novel and effective exercise that allows undergraduate biology majors to test a hypothesis about behavioral evolution in insects. (Contains 13 references.) (Author/YDS)

Optimal Wavelengths Selection Using Hierarchical Evolutionary Algorithm for Prediction of Firmness and Soluble Solids Content in Apples

USDA-ARS?s Scientific Manuscript database

Hyperspectral scattering is a promising technique for rapid and noninvasive measurement of multiple quality attributes of apple fruit. A hierarchical evolutionary algorithm (HEA) approach, in combination with subspace decomposition and partial least squares (PLS) regression, was proposed to select o...

Bistability of Evolutionary Stable Vaccination Strategies in the Reinfection SIRI Model.

PubMed

Martins, José; Pinto, Alberto

2017-04-01

We use the reinfection SIRI epidemiological model to analyze the impact of education programs and vaccine scares on individuals decisions to vaccinate or not. The presence of the reinfection provokes the novelty of the existence of three Nash equilibria for the same level of the morbidity relative risk instead of a single Nash equilibrium as occurs in the SIR model studied by Bauch and Earn (PNAS 101:13391-13394, 2004). The existence of three Nash equilibria, with two of them being evolutionary stable, introduces two scenarios with relevant and opposite features for the same level of the morbidity relative risk: the low-vaccination scenario corresponding to the evolutionary stable vaccination strategy, where individuals will vaccinate with a low probability; and the high-vaccination scenario corresponding to the evolutionary stable vaccination strategy, where individuals will vaccinate with a high probability. We introduce the evolutionary vaccination dynamics for the SIRI model and we prove that it is bistable. The bistability of the evolutionary dynamics indicates that the damage provoked by false scares on the vaccination perceived morbidity risks can be much higher and much more persistent than in the SIR model. Furthermore, the vaccination education programs to be efficient they need to implement a mechanism to suddenly increase the vaccination coverage level.

Bell-Curve Based Evolutionary Strategies for Structural Optimization

NASA Technical Reports Server (NTRS)

Kincaid, Rex K.

2000-01-01

Evolutionary methods are exceedingly popular with practitioners of many fields; more so than perhaps any optimization tool in existence. Historically Genetic Algorithms (GAs) led the way in practitioner popularity (Reeves 1997). However, in the last ten years Evolutionary Strategies (ESs) and Evolutionary Programs (EPS) have gained a significant foothold (Glover 1998). One partial explanation for this shift is the interest in using GAs to solve continuous optimization problems. The typical GA relies upon a cumber-some binary representation of the design variables. An ES or EP, however, works directly with the real-valued design variables. For detailed references on evolutionary methods in general and ES or EP in specific see Back (1996) and Dasgupta and Michalesicz (1997). We call our evolutionary algorithm BCB (bell curve based) since it is based upon two normal distributions.

Evolutionary Multiobjective Design Targeting a Field Programmable Transistor Array

NASA Technical Reports Server (NTRS)

Aguirre, Arturo Hernandez; Zebulum, Ricardo S.; Coello, Carlos Coello

2004-01-01

This paper introduces the ISPAES algorithm for circuit design targeting a Field Programmable Transistor Array (FPTA). The use of evolutionary algorithms is common in circuit design problems, where a single fitness function drives the evolution process. Frequently, the design problem is subject to several goals or operating constraints, thus, designing a suitable fitness function catching all requirements becomes an issue. Such a problem is amenable for multi-objective optimization, however, evolutionary algorithms lack an inherent mechanism for constraint handling. This paper introduces ISPAES, an evolutionary optimization algorithm enhanced with a constraint handling technique. Several design problems targeting a FPTA show the potential of our approach.

A theoretical comparison of evolutionary algorithms and simulated annealing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, W.E.

1995-08-28

This paper theoretically compares the performance of simulated annealing and evolutionary algorithms. Our main result is that under mild conditions a wide variety of evolutionary algorithms can be shown to have greater performance than simulated annealing after a sufficiently large number of function evaluations. This class of EAs includes variants of evolutionary strategie and evolutionary programming, the canonical genetic algorithm, as well as a variety of genetic algorithms that have been applied to combinatorial optimization problems. The proof of this result is based on a performance analysis of a very general class of stochastic optimization algorithms, which has implications formore » the performance of a variety of other optimization algorithm.« less

Evolutionary perspectives on wildlife disease: concepts and applications

PubMed Central

Vander Wal, Eric; Garant, Dany; Pelletier, Fanie

2014-01-01

Wildlife disease has the potential to cause significant ecological, socioeconomic, and health impacts. As a result, all tools available need to be employed when host–pathogen dynamics merit conservation or management interventions. Evolutionary principles, such as evolutionary history, phenotypic and genetic variation, and selection, have the potential to unravel many of the complex ecological realities of infectious disease in the wild. Despite this, their application to wildlife disease ecology and management remains in its infancy. In this article, we outline the impetus behind applying evolutionary principles to disease ecology and management issues in the wild. We then introduce articles from this special issue on Evolutionary Perspectives on Wildlife Disease: Concepts and Applications, outlining how each is exemplar of a practical wildlife disease challenge that can be enlightened by applied evolution. Ultimately, we aim to bring new insights to wildlife disease ecology and its management using tools and techniques commonly employed in evolutionary ecology. PMID:25469154

An Analysis on a Negotiation Model Based on Multiagent Systems with Symbiotic Learning and Evolution

NASA Astrophysics Data System (ADS)

Hossain, Md. Tofazzal

This study explores an evolutionary analysis on a negotiation model based on Masbiole (Multiagent Systems with Symbiotic Learning and Evolution) which has been proposed as a new methodology of Multiagent Systems (MAS) based on symbiosis in the ecosystem. In Masbiole, agents evolve in consideration of not only their own benefits and losses, but also the benefits and losses of opponent agents. To aid effective application of Masbiole, we develop a competitive negotiation model where rigorous and advanced intelligent decision-making mechanisms are required for agents to achieve solutions. A Negotiation Protocol is devised aiming at developing a set of rules for agents' behavior during evolution. Simulations use a newly developed evolutionary computing technique, called Genetic Network Programming (GNP) which has the directed graph-type gene structure that can develop and design the required intelligent mechanisms for agents. In a typical scenario, competitive negotiation solutions are reached by concessions that are usually predetermined in the conventional MAS. In this model, however, not only concession is determined automatically by symbiotic evolution (making the system intelligent, automated, and efficient) but the solution also achieves Pareto optimal automatically.

Adaptive elastic segmentation of brain MRI via shape-model-guided evolutionary programming.

PubMed

Pitiot, Alain; Toga, Arthur W; Thompson, Paul M

2002-08-01

This paper presents a fully automated segmentation method for medical images. The goal is to localize and parameterize a variety of types of structure in these images for subsequent quantitative analysis. We propose a new hybrid strategy that combines a general elastic template matching approach and an evolutionary heuristic. The evolutionary algorithm uses prior statistical information about the shape of the target structure to control the behavior of a number of deformable templates. Each template, modeled in the form of a B-spline, is warped in a potential field which is itself dynamically adapted. Such a hybrid scheme proves to be promising: by maintaining a population of templates, we cover a large domain of the solution space under the global guidance of the evolutionary heuristic, and thoroughly explore interesting areas. We address key issues of automated image segmentation systems. The potential fields are initially designed based on the spatial features of the edges in the input image, and are subjected to spatially adaptive diffusion to guarantee the deformation of the template. This also improves its global consistency and convergence speed. The deformation algorithm can modify the internal structure of the templates to allow a better match. We investigate in detail the preprocessing phase that the images undergo before they can be used more effectively in the iterative elastic matching procedure: a texture classifier, trained via linear discriminant analysis of a learning set, is used to enhance the contrast of the target structure with respect to surrounding tissues. We show how these techniques interact within a statistically driven evolutionary scheme to achieve a better tradeoff between template flexibility and sensitivity to noise and outliers. We focus on understanding the features of template matching that are most beneficial in terms of the achieved match. Examples from simulated and real image data are discussed, with considerations of algorithmic efficiency.

Evolutionary computation in zoology and ecology.

PubMed

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 computation in zoology and ecology

PubMed Central

2017-01-01

Abstract 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. PMID:29492029

Evolutionary principles and their practical application

PubMed Central

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

2011-01-01

Evolutionary principles are now routinely incorporated into medicine and agriculture. Examples include the design of treatments that slow the evolution of resistance by weeds, pests, and pathogens, and the design of breeding programs that maximize crop yield or quality. Evolutionary principles are also increasingly incorporated into conservation biology, natural resource management, and environmental science. Examples include the protection of small and isolated populations from inbreeding depression, the identification of key traits involved in adaptation to climate change, the design of harvesting regimes that minimize unwanted life-history evolution, and the setting of conservation priorities based on populations, species, or communities that harbor the greatest evolutionary diversity and potential. The adoption of evolutionary principles has proceeded somewhat independently 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. PMID:25567966

Evolutionary principles and their practical application.

PubMed

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.

Evolutionary computing for the design search and optimization of space vehicle power subsystems

NASA Technical Reports Server (NTRS)

Kordon, M.; Klimeck, G.; Hanks, D.

2004-01-01

Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment.

Vibration attenuation of the NASA Langley evolutionary structure experiment using H(sub infinity) and structured singular value (micron) robust multivariable control techniques

NASA Technical Reports Server (NTRS)

Balas, Gary J.

1992-01-01

The use is studied of active control to attenuate structural vibrations of the NASA Langley Phase Zero Evolutionary Structure due to external disturbance excitations. H sub infinity and structured singular value (mu) based control techniques are used to analyze and synthesize control laws for the NASA Langley Controls Structures Interaction (CSI) Evolutionary Model (CEM). The CEM structure experiment provides an excellent test bed to address control design issues for large space structures. Specifically, control design for structures with numerous lightly damped, coupled flexible modes, collocated and noncollocated sensors and actuators and stringent performance specifications. The performance objectives are to attenuate the vibration of the structure due to external disturbances, and minimize the actuator control force. The control design problem formulation for the CEM Structure uses a mathematical model developed with finite element techniques. A reduced order state space model for the control design is formulated from the finite element model. It is noted that there are significant variations between the design model and the experimentally derived transfer function data.

An efficient and accurate solution methodology for bilevel multi-objective programming problems using a hybrid evolutionary-local-search algorithm.

PubMed

Deb, Kalyanmoy; Sinha, Ankur

2010-01-01

Bilevel optimization problems involve two optimization tasks (upper and lower level), in which every feasible upper level solution must correspond to an optimal solution to a lower level optimization problem. These problems commonly appear in many practical problem solving tasks including optimal control, process optimization, game-playing strategy developments, transportation problems, and others. However, they are commonly converted into a single level optimization problem by using an approximate solution procedure to replace the lower level optimization task. Although there exist a number of theoretical, numerical, and evolutionary optimization studies involving single-objective bilevel programming problems, not many studies look at the context of multiple conflicting objectives in each level of a bilevel programming problem. In this paper, we address certain intricate issues related to solving multi-objective bilevel programming problems, present challenging test problems, and propose a viable and hybrid evolutionary-cum-local-search based algorithm as a solution methodology. The hybrid approach performs better than a number of existing methodologies and scales well up to 40-variable difficult test problems used in this study. The population sizing and termination criteria are made self-adaptive, so that no additional parameters need to be supplied by the user. The study indicates a clear niche of evolutionary algorithms in solving such difficult problems of practical importance compared to their usual solution by a computationally expensive nested procedure. The study opens up many issues related to multi-objective bilevel programming and hopefully this study will motivate EMO and other researchers to pay more attention to this important and difficult problem solving activity.

Space industrialization. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

1978-01-01

Potential goals for space industrialization were identified, and evolutionary program options for the realization of those goals were developed and assessed. Program support demands were defined, and recommendations were made in relation to program implementation.

The ABCs of an evolutionary education science: The academic, behavioral, and cultural implications of an evolutionary approach to education theory and practice

NASA Astrophysics Data System (ADS)

Kauffman, Rick, Jr.

Calls for improving research-informed policy in education are everywhere. Yet, while there is an increasing trend towards science-based practice, there remains little agreement over which of the sciences to consult and how to organize a collective effort between them. What Education lacks is a general theoretical framework through which policies can be constructed, implemented, and assessed. This dissertation submits that evolutionary theory can provide a suitable framework for coordinating educational policies and practice, and can provide the entire field of education with a clearer sense of how to better manage the learning environment. This dissertation explores two broad paths that outline the conceptual foundations for an Evolutionary Education Science: "Teaching Evolution" and "Using Evolution to Teach." Chapter 1 introduces both of these themes. After describing why evolutionary science is best suited for organizing education research and practice, Chapter 1 proceeds to "teach" an overview of the "evolutionary toolkit"---the mechanisms and principles that underlie the modern evolutionary perspective. The chapter then employs the "toolkit" in examining education from an evolutionary perspective, outlining the evolutionary precepts that can guide theorizing and research in education, describing how educators can "use evolution to teach.". Chapters 2-4 expand on this second theme. Chapters 2 and 3 describe an education program for at-risk 9th and 10th grade students, the Regents Academy, designed entirely with evolutionary principles in mind. The program was rigorously assessed in a randomized control design and has demonstrated success at improving students' academic performance (Chapter 2) and social & behavioral development (Chapter 3). Chapter 4 examines current teaching strategies that underlie effective curriculum-instruction-assessment practices and proposes a framework for organizing successful, evidence-based strategies for neural-/cognitive-focused learning goals. Chapter 5 explores the cognitive effects that "teaching evolution" has on the learner. This chapter examines the effects that a course on evolutionary theory has on university undergraduate students in understanding and applying evolution and how learning the evolutionary toolkit affects critical thinking skills and domain transfer of knowledge. The results demonstrate that a single course on evolutionary theory increases students' acceptance and understanding of evolution and science, and, in effect, increases critical thinking performance.

Understanding Evolutionary Change within the Framework of Geological Time

ERIC Educational Resources Information Center

Dodick, Jeff

2007-01-01

This paper focuses on a learning strategy designed to overcome students' difficulty in understanding evolutionary change within the framework of geological time. Incorporated into the learning program "From Dinosaurs to Darwin: Evolution from the Perspective of Time," this strategy consists of four scaffolded investigations in which…

On Using Surrogates with Genetic Programming.

PubMed

Hildebrandt, Torsten; Branke, Jürgen

2015-01-01

One way to accelerate evolutionary algorithms with expensive fitness evaluations is to combine them with surrogate models. Surrogate models are efficiently computable approximations of the fitness function, derived by means of statistical or machine learning techniques from samples of fully evaluated solutions. But these models usually require a numerical representation, and therefore cannot be used with the tree representation of genetic programming (GP). In this paper, we present a new way to use surrogate models with GP. Rather than using the genotype directly as input to the surrogate model, we propose using a phenotypic characterization. This phenotypic characterization can be computed efficiently and allows us to define approximate measures of equivalence and similarity. Using a stochastic, dynamic job shop scenario as an example of simulation-based GP with an expensive fitness evaluation, we show how these ideas can be used to construct surrogate models and improve the convergence speed and solution quality of GP.

How mutation affects evolutionary games on graphs

PubMed Central

Allen, Benjamin; Traulsen, Arne; Tarnita, Corina E.; Nowak, Martin A.

2011-01-01

Evolutionary dynamics are affected by population structure, mutation rates and update rules. Spatial or network structure facilitates the clustering of strategies, which represents a mechanism for the evolution of cooperation. Mutation dilutes this effect. Here we analyze how mutation influences evolutionary clustering on graphs. We introduce new mathematical methods to evolutionary game theory, specifically the analysis of coalescing random walks via generating functions. These techniques allow us to derive exact identity-by-descent (IBD) probabilities, which characterize spatial assortment on lattices and Cayley trees. From these IBD probabilities we obtain exact conditions for the evolution of cooperation and other game strategies, showing the dual effects of graph topology and mutation rate. High mutation rates diminish the clustering of cooperators, hindering their evolutionary success. Our model can represent either genetic evolution with mutation, or social imitation processes with random strategy exploration. PMID:21473871

The role of selection on evolutionary rescue

NASA Astrophysics Data System (ADS)

Amirjanov, Adil

The paper investigates the role of selection on evolutionary rescue of population. The statistical mechanics technique is used to model dynamics of a population experiencing a natural selection and an abrupt change in the environment. The paper assesses the selective pressure produced by two different mechanisms: by strength of resistance and by strength of selection (by intraspecific competition). It is shown that both mechanisms are capable of providing an evolutionary rescue of population in particular conditions. However, for a small level of an extinction rate, the population cannot be rescued without intraspecific competition.

Communications and Tracking Distributed Systems Evolution Study

NASA Technical Reports Server (NTRS)

Culpepper, William

1990-01-01

The Communications and Tracking (C & T) techniques and equipment to support evolutionary space station concepts are being analyzed. Evolutionary space station configurations and operational concepts are used to derive the results to date. A description of the C & T system based on future capability needs is presented. Included are the hooks and scars currently identified to support future growth.

Evolutionary Computation for the Identification of Emergent Behavior in Autonomous Systems

NASA Technical Reports Server (NTRS)

Terrile, Richard J.; Guillaume, Alexandre

2009-01-01

Over the past several years the Center for Evolutionary Computation and Automated Design at the Jet Propulsion Laboratory has developed a technique based on Evolutionary Computational Methods (ECM) that allows for the automated optimization of complex computationally modeled systems. An important application of this technique is for the identification of emergent behaviors in autonomous systems. Mobility platforms such as rovers or airborne vehicles are now being designed with autonomous mission controllers that can find trajectories over a solution space that is larger than can reasonably be tested. It is critical to identify control behaviors that are not predicted and can have surprising results (both good and bad). These emergent behaviors need to be identified, characterized and either incorporated into or isolated from the acceptable range of control characteristics. We use cluster analysis of automatically retrieved solutions to identify isolated populations of solutions with divergent behaviors.

Wildlife monitoring program plan

NASA Technical Reports Server (NTRS)

Sebesta, P.; Arno, R.

1979-01-01

A plan for integrating the various requirements for wildlife monitoring with modern aerospace technology is presented. This plan is responsive to user needs, recognizes legal requirements, and is based on an evolutionary growth from domestic animals and larger animals to smaller, more scarce and remote species. The basis for animal study selection was made from the 1973 Santa Cruz Summer Study on Wildlife Monitoring. As techniques are developed the monitoring and management tasks will be interfaced with and eventually operated by the user agencies. Field efforts, aircraft and satellites, will be supplemented by laboratory investigations. Sixty percent of the effort will be in hardware research and development (satellite technology, microminiaturization) and the rest for gathering and interpreting data.

Literary study and evolutionary theory : A review essay.

PubMed

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.

A novel approach for supercapacitors degradation characterization

NASA Astrophysics Data System (ADS)

Oz, Alon; Gelman, Danny; Goren, Emanuelle; Shomrat, Neta; Baltianski, Sioma; Tsur, Yoed

2017-07-01

A novel approach to analyze electrochemical impedance spectroscopy (EIS), based on evolutionary programming, has been utilized to characterize supercapacitors operation mechanism and degradation processes. This approach poses the ability of achieving a comprehensive study of supercapacitors via solely AC measurements. Commercial supercapacitors were examined during accelerated degradation. The microstructure of the electrode-electrolyte interface changes upon degradation; electrolyte parasitic reactions yield the formation of precipitates on the porous surface, which limit the access of the electrolyte ions to the active area and thus reduces performance. EIS analysis using Impedance Spectroscopy Genetic Programming (ISGP) technique enables identifying how the changing microstructure is affecting the operation mechanism of supercapacitors, in terms of each process effective capacitance and time constant. The most affected process is the transport of electrolyte ions at the porous electrode. Their access to the whole active area is hindered, which is shown in our analysis by the decrease of the capacitance gained in the transport and the longer time it takes to penetrate the entire pores depth. Early failure detection is also demonstrated, in a way not readily possible via conventional indicators. ISGP advanced analysis method has been verified using conventional and proven techniques: cyclic voltammetry and post mortem measurements.

Evaluation of Generation Alternation Models in Evolutionary Robotics

NASA Astrophysics Data System (ADS)

Oiso, Masashi; Matsumura, Yoshiyuki; Yasuda, Toshiyuki; Ohkura, Kazuhiro

For efficient implementation of Evolutionary Algorithms (EA) to a desktop grid computing environment, we propose a new generation alternation model called Grid-Oriented-Deletion (GOD) based on comparison with the conventional techniques. In previous research, generation alternation models are generally evaluated by using test functions. However, their exploration performance on the real problems such as Evolutionary Robotics (ER) has not been made very clear yet. Therefore we investigate the relationship between the exploration performance of EA on an ER problem and its generation alternation model. We applied four generation alternation models to the Evolutionary Multi-Robotics (EMR), which is the package-pushing problem to investigate their exploration performance. The results show that GOD is more effective than the other conventional models.

Scheduling Earth Observing Fleets Using Evolutionary Algorithms: Problem Description and Approach

NASA Technical Reports Server (NTRS)

Globus, Al; Crawford, James; Lohn, Jason; Morris, Robert; Clancy, Daniel (Technical Monitor)

2002-01-01

We describe work in progress concerning multi-instrument, multi-satellite scheduling. Most, although not all, Earth observing instruments currently in orbit are unique. In the relatively near future, however, we expect to see fleets of Earth observing spacecraft, many carrying nearly identical instruments. This presents a substantially new scheduling challenge. Inspired by successful commercial applications of evolutionary algorithms in scheduling domains, this paper presents work in progress regarding the use of evolutionary algorithms to solve a set of Earth observing related model problems. Both the model problems and the software are described. Since the larger problems will require substantial computation and evolutionary algorithms are embarrassingly parallel, we discuss our parallelization techniques using dedicated and cycle-scavenged workstations.

Multi-objective optimization of an arch dam shape under static loads using an evolutionary game method

NASA Astrophysics Data System (ADS)

Meng, Rui; Cheong, Kang Hao; Bao, Wei; Wong, Kelvin Kian Loong; Wang, Lu; Xie, Neng-gang

2018-06-01

This article attempts to evaluate the safety and economic performance of an arch dam under the action of static loads. The geometric description of a crown cantilever section and the horizontal arch ring is presented. A three-objective optimization model of arch dam shape is established based on the arch dam volume, maximum principal tensile stress and total strain energy. The evolutionary game method is then applied to obtain the optimal solution. In the evolutionary game technique, a novel and more efficient exploration method of the game players' strategy space, named the 'sorting partition method under the threshold limit', is presented, with the game profit functions constructed according to both competitive and cooperative behaviour. By way of example, three optimization goals have all shown improvements over the initial solutions. In particular, the evolutionary game method has potentially faster convergence. This demonstrates the preliminary proof of principle of the evolutionary game method.

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

PubMed

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.

Universality and predictability in molecular quantitative genetics.

PubMed

Nourmohammad, Armita; Held, Torsten; Lässig, Michael

2013-12-01

Molecular traits, such as gene expression levels or protein binding affinities, are increasingly accessible to quantitative measurement by modern high-throughput techniques. Such traits measure molecular functions and, from an evolutionary point of view, are important as targets of natural selection. We review recent developments in evolutionary theory and experiments that are expected to become building blocks of a quantitative genetics of molecular traits. We focus on universal evolutionary characteristics: these are largely independent of a trait's genetic basis, which is often at least partially unknown. We show that universal measurements can be used to infer selection on a quantitative trait, which determines its evolutionary mode of conservation or adaptation. Furthermore, universality is closely linked to predictability of trait evolution across lineages. We argue that universal trait statistics extends over a range of cellular scales and opens new avenues of quantitative evolutionary systems biology. Copyright © 2013. Published by Elsevier Ltd.

Effective Technology Insertion: The Key to Evolutionary Acquisition Program

DTIC Science & Technology

2004-05-03

Army War College, 7 April 2003. 47Orazia A. Di Marca ; Rejto, Stephen B. Rejto and Thomas Gomez, “ Open System Design and Evolutionary Acquisition...to Military Applications-Report No. D-2002-107. 14 June 2002. Di Marca , Orazia A.; Rejto, StephenB., and Gomez, Thomas, “ Open System Design and

Machine-assisted discovery of relationships in astronomy

NASA Astrophysics Data System (ADS)

Graham, Matthew J.; Djorgovski, S. G.; Mahabal, Ashish A.; Donalek, Ciro; Drake, Andrew J.

2013-05-01

High-volume feature-rich data sets are becoming the bread-and-butter of 21st century astronomy but present significant challenges to scientific discovery. In particular, identifying scientifically significant relationships between sets of parameters is non-trivial. Similar problems in biological and geosciences have led to the development of systems which can explore large parameter spaces and identify potentially interesting sets of associations. In this paper, we describe the application of automated discovery systems of relationships to astronomical data sets, focusing on an evolutionary programming technique and an information-theory technique. We demonstrate their use with classical astronomical relationships - the Hertzsprung-Russell diagram and the Fundamental Plane of elliptical galaxies. We also show how they work with the issue of binary classification which is relevant to the next generation of large synoptic sky surveys, such as the Large Synoptic Survey Telescope (LSST). We find that comparable results to more familiar techniques, such as decision trees, are achievable. Finally, we consider the reality of the relationships discovered and how this can be used for feature selection and extraction.

Applications of genetic programming in cancer research.

PubMed

Worzel, William P; Yu, Jianjun; Almal, Arpit A; Chinnaiyan, Arul M

2009-02-01

The theory of Darwinian evolution is the fundamental keystones of modern biology. Late in the last century, computer scientists began adapting its principles, in particular natural selection, to complex computational challenges, leading to the emergence of evolutionary algorithms. The conceptual model of selective pressure and recombination in evolutionary algorithms allow scientists to efficiently search high dimensional space for solutions to complex problems. In the last decade, genetic programming has been developed and extensively applied for analysis of molecular data to classify cancer subtypes and characterize the mechanisms of cancer pathogenesis and development. This article reviews current successes using genetic programming and discusses its potential impact in cancer research and treatment in the near future.

Development of Collaborative Research Initiatives to Advance the Aerospace Sciences-via the Communications, Electronics, Information Systems Focus Group

NASA Technical Reports Server (NTRS)

Knasel, T. Michael

1996-01-01

The primary goal of the Adaptive Vision Laboratory Research project was to develop advanced computer vision systems for automatic target recognition. The approach used in this effort combined several machine learning paradigms including evolutionary learning algorithms, neural networks, and adaptive clustering techniques to develop the E-MOR.PH system. This system is capable of generating pattern recognition systems to solve a wide variety of complex recognition tasks. A series of simulation experiments were conducted using E-MORPH to solve problems in OCR, military target recognition, industrial inspection, and medical image analysis. The bulk of the funds provided through this grant were used to purchase computer hardware and software to support these computationally intensive simulations. The payoff from this effort is the reduced need for human involvement in the design and implementation of recognition systems. We have shown that the techniques used in E-MORPH are generic and readily transition to other problem domains. Specifically, E-MORPH is multi-phase evolutionary leaming system that evolves cooperative sets of features detectors and combines their response using an adaptive classifier to form a complete pattern recognition system. The system can operate on binary or grayscale images. In our most recent experiments, we used multi-resolution images that are formed by applying a Gabor wavelet transform to a set of grayscale input images. To begin the leaming process, candidate chips are extracted from the multi-resolution images to form a training set and a test set. A population of detector sets is randomly initialized to start the evolutionary process. Using a combination of evolutionary programming and genetic algorithms, the feature detectors are enhanced to solve a recognition problem. The design of E-MORPH and recognition results for a complex problem in medical image analysis are described at the end of this report. The specific task involves the identification of vertebrae in x-ray images of human spinal columns. This problem is extremely challenging because the individual vertebra exhibit variation in shape, scale, orientation, and contrast. E-MORPH generated several accurate recognition systems to solve this task. This dual use of this ATR technology clearly demonstrates the flexibility and power of our approach.

Variations on a Theme.

ERIC Educational Resources Information Center

Vitali, Julius

1990-01-01

Explains an experimental photographic technique starting with a realistic photograph. Using various media (oil painting, video/computer photography, and multiprint imagery) the artist changes the photograph's compositional elements. Outlines the phases of this evolutionary process. Illustrates four images created by the technique. (DB)

Understanding Evolutionary Potential in Virtual CPU Instruction Set Architectures

PubMed Central

Bryson, David M.; Ofria, Charles

2013-01-01

We investigate fundamental decisions in the design of instruction set architectures for linear genetic programs that are used as both model systems in evolutionary biology and underlying solution representations in evolutionary computation. We subjected digital organisms with each tested architecture to seven different computational environments designed to present a range of evolutionary challenges. Our goal was to engineer a general purpose architecture that would be effective under a broad range of evolutionary conditions. We evaluated six different types of architectural features for the virtual CPUs: (1) genetic flexibility: we allowed digital organisms to more precisely modify the function of genetic instructions, (2) memory: we provided an increased number of registers in the virtual CPUs, (3) decoupled sensors and actuators: we separated input and output operations to enable greater control over data flow. We also tested a variety of methods to regulate expression: (4) explicit labels that allow programs to dynamically refer to specific genome positions, (5) position-relative search instructions, and (6) multiple new flow control instructions, including conditionals and jumps. Each of these features also adds complication to the instruction set and risks slowing evolution due to epistatic interactions. Two features (multiple argument specification and separated I/O) demonstrated substantial improvements in the majority of test environments, along with versions of each of the remaining architecture modifications that show significant improvements in multiple environments. However, some tested modifications were detrimental, though most exhibit no systematic effects on evolutionary potential, highlighting the robustness of digital evolution. Combined, these observations enhance our understanding of how instruction architecture impacts evolutionary potential, enabling the creation of architectures that support more rapid evolution of complex solutions to a broad range of challenges. PMID:24376669

DiscML: an R package for estimating evolutionary rates of discrete characters using maximum likelihood.

PubMed

Kim, Tane; Hao, Weilong

2014-09-27

The study of discrete characters is crucial for the understanding of evolutionary processes. Even though great advances have been made in the analysis of nucleotide sequences, computer programs for non-DNA discrete characters are often dedicated to specific analyses and lack flexibility. Discrete characters often have different transition rate matrices, variable rates among sites and sometimes contain unobservable states. To obtain the ability to accurately estimate a variety of discrete characters, programs with sophisticated methodologies and flexible settings are desired. DiscML performs maximum likelihood estimation for evolutionary rates of discrete characters on a provided phylogeny with the options that correct for unobservable data, rate variations, and unknown prior root probabilities from the empirical data. It gives users options to customize the instantaneous transition rate matrices, or to choose pre-determined matrices from models such as birth-and-death (BD), birth-death-and-innovation (BDI), equal rates (ER), symmetric (SYM), general time-reversible (GTR) and all rates different (ARD). Moreover, we show application examples of DiscML on gene family data and on intron presence/absence data. DiscML was developed as a unified R program for estimating evolutionary rates of discrete characters with no restriction on the number of character states, and with flexibility to use different transition models. DiscML is ideal for the analyses of binary (1s/0s) patterns, multi-gene families, and multistate discrete morphological characteristics.

Preserving the tree of life.

PubMed

Mace, Georgina M; Gittleman, John L; Purvis, Andy

2003-06-13

Phylogenies provide new ways to measure biodiversity, to assess conservation priorities, and to quantify the evolutionary history in any set of species. Methodological problems and a lack of knowledge about most species have so far hampered their use. In the future, as techniques improve and more data become accessible, we will have an expanded set of conservation options, including ways to prioritize outcomes from evolutionary and ecological processes.

Comparison of multiobjective evolutionary algorithms: empirical results.

PubMed

Zitzler, E; Deb, K; Thiele, L

2000-01-01

In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly in converging to the Pareto-optimal front (e.g., multimodality and deception). By investigating these different problem features separately, it is possible to predict the kind of problems to which a certain technique is or is not well suited. However, in contrast to what was suspected beforehand, the experimental results indicate a hierarchy of the algorithms under consideration. Furthermore, the emerging effects are evidence that the suggested test functions provide sufficient complexity to compare multiobjective optimizers. Finally, elitism is shown to be an important factor for improving evolutionary multiobjective search.

Structural technology challenges for evolutionary growth of Space Station Freedom

NASA Technical Reports Server (NTRS)

Doiron, Harold H.

1990-01-01

A proposed evolutionary growth scenario for Space Station Freedom was defined recently by a NASA task force created to study requirements for a Human Exploration Initiative. The study was an initial response to President Bush's July 20, 1989 proposal to begin a long range program of human exploration of space including a permanently manned lunar base and a manned mission to Mars. This growth scenario evolves Freedom into a critical transportation node to support lunar and Mars missions. The growth scenario begins with the Assembly Complete configuration and adds structure, power, and facilities to support a Lunar Transfer Vehicle (LTV) verification flight. Evolutionary growth continues to support expendable, then reusable LTV operations, and finally, LTV and Mars Transfer Vehicle (MTV) operations. The significant structural growth and additional operations creating new loading conditions will present new technological and structural design challenges in addition to the considerable technology requirements of the baseline Space Station Freedom program. Several structural design and technology issues of the baseline program are reviewed and related technology development required by the growth scenario is identified.

The Meaningful Roles Intervention: An Evolutionary Approach to Reducing Bullying and Increasing Prosocial Behavior.

PubMed

Ellis, Bruce J; Volk, Anthony A; Gonzalez, Jose-Michael; Embry, Dennis D

2016-12-01

Bullying is a problem that affects adolescents worldwide. Efforts to prevent bullying have been moderately successful at best, or iatrogenic at worst. We offer an explanation for this limited success by employing an evolutionary-psychological perspective to analyze antibullying interventions. We argue that bullying is a goal-directed behavior that is sensitive to benefits as well as costs, and that interventions must address these benefits. This perspective led us to develop a novel antibullying intervention, Meaningful Roles, which offers bullies prosocial alternatives-meaningful roles and responsibilities implemented through a school jobs program and reinforced through peer-to-peer praise notes-that effectively meet the same status goals as bullying behavior. We describe this new intervention and how its theoretical evolutionary roots may be applicable to other intervention programs. © 2015 The Authors. Journal of Research on Adolescence © 2015 Society for Research on Adolescence.

Efficient fractal-based mutation in evolutionary algorithms from iterated function systems

NASA Astrophysics Data System (ADS)

Salcedo-Sanz, S.; Aybar-Ruíz, A.; Camacho-Gómez, C.; Pereira, E.

2018-03-01

In this paper we present a new mutation procedure for Evolutionary Programming (EP) approaches, based on Iterated Function Systems (IFSs). The new mutation procedure proposed consists of considering a set of IFS which are able to generate fractal structures in a two-dimensional phase space, and use them to modify a current individual of the EP algorithm, instead of using random numbers from different probability density functions. We test this new proposal in a set of benchmark functions for continuous optimization problems. In this case, we compare the proposed mutation against classical Evolutionary Programming approaches, with mutations based on Gaussian, Cauchy and chaotic maps. We also include a discussion on the IFS-based mutation in a real application of Tuned Mass Dumper (TMD) location and optimization for vibration cancellation in buildings. In both practical cases, the proposed EP with the IFS-based mutation obtained extremely competitive results compared to alternative classical mutation operators.

Artificial intelligence in peer review: How can evolutionary computation support journal editors?

PubMed

Mrowinski, Maciej J; Fronczak, Piotr; Fronczak, Agata; Ausloos, Marcel; Nedic, Olgica

2017-01-01

With the volume of manuscripts submitted for publication growing every year, the deficiencies of peer review (e.g. long review times) are becoming more apparent. Editorial strategies, sets of guidelines designed to speed up the process and reduce editors' workloads, are treated as trade secrets by publishing houses and are not shared publicly. To improve the effectiveness of their strategies, editors in small publishing groups are faced with undertaking an iterative trial-and-error approach. We show that Cartesian Genetic Programming, a nature-inspired evolutionary algorithm, can dramatically improve editorial strategies. The artificially evolved strategy reduced the duration of the peer review process by 30%, without increasing the pool of reviewers (in comparison to a typical human-developed strategy). Evolutionary computation has typically been used in technological processes or biological ecosystems. Our results demonstrate that genetic programs can improve real-world social systems that are usually much harder to understand and control than physical systems.

Evolution of the INMARSAT aeronautical system: Service, system, and business considerations

NASA Technical Reports Server (NTRS)

Sengupta, Jay R.

1995-01-01

A market-driven approach was adopted to develop enhancements to the Inmarsat-Aeronautical system, to address the requirements of potential new market segments. An evolutionary approach and well differentiated product/service portfolio was required, to minimize system upgrade costs and market penetration, respectively. The evolved system definition serves to minimize equipment cost/size/mass for short/medium range aircraft, by reducing the antenna gain requirement and relaxing the performance requirements for non safety-related communications. A validation program involving simulation, laboratory tests, over-satellite tests and flight trials is being conducted to confirm the system definition. Extensive market research has been conducted to determine user requirements and to quantify market demand for future Inmarsat Aero-1 AES, using sophisticated computer assisted survey techniques.

Optimization of antibacterial activity by Gold-Thread (Coptidis Rhizoma Franch) against Streptococcus mutans using evolutionary operation-factorial design technique.

PubMed

Choi, Ung-Kyu; Kim, Mi-Hyang; Lee, Nan-Hee

2007-11-01

This study was conducted to find the optimum extraction condition of Gold-Thread for antibacterial activity against Streptococcus mutans using The evolutionary operation-factorial design technique. Higher antibacterial activity was achieved in a higher extraction temperature (R2 = -0.79) and in a longer extraction time (R2 = -0.71). Antibacterial activity was not affected by differentiation of the ethanol concentration in the extraction solvent (R2 = -0.12). The maximum antibacterial activity of clove against S. mutans determined by the EVOP-factorial technique was obtained at 80 degrees C extraction temperature, 26 h extraction time, and 50% ethanol concentration. The population of S. mutans decreased from 6.110 logCFU/ml in the initial set to 4.125 logCFU/ml in the third set.

Achieving sustainable plant disease management through evolutionary principles.

PubMed

Zhan, Jiasui; Thrall, Peter H; Burdon, Jeremy J

2014-09-01

Plants and their pathogens are engaged in continuous evolutionary battles and sustainable disease management requires novel systems to create environments conducive for short-term and long-term disease control. In this opinion article, we argue that knowledge of the fundamental factors that drive host-pathogen coevolution in wild systems can provide new insights into disease development in agriculture. Such evolutionary principles can be used to guide the formulation of sustainable disease management strategies which can minimize disease epidemics while simultaneously reducing pressure on pathogens to evolve increased infectivity and aggressiveness. To ensure agricultural sustainability, disease management programs that reflect the dynamism of pathogen population structure are essential and evolutionary biologists should play an increasing role in their design. Copyright © 2014 Elsevier Ltd. All rights reserved.

Ignoring heterozygous sites biases phylogenomic estimates of divergence times: implications for the evolutionary history of microtus voles.

PubMed

Lischer, Heidi E L; Excoffier, Laurent; Heckel, Gerald

2014-04-01

Phylogenetic reconstruction of the evolutionary history of closely related organisms may be difficult because of the presence of unsorted lineages and of a relatively high proportion of heterozygous sites that are usually not handled well by phylogenetic programs. Genomic data may provide enough fixed polymorphisms to resolve phylogenetic trees, but the diploid nature of sequence data remains analytically challenging. Here, we performed a phylogenomic reconstruction of the evolutionary history of the common vole (Microtus arvalis) with a focus on the influence of heterozygosity on the estimation of intraspecific divergence times. We used genome-wide sequence information from 15 voles distributed across the European range. We provide a novel approach to integrate heterozygous information in existing phylogenetic programs by repeated random haplotype sampling from sequences with multiple unphased heterozygous sites. We evaluated the impact of the use of full, partial, or no heterozygous information for tree reconstructions on divergence time estimates. All results consistently showed four deep and strongly supported evolutionary lineages in the vole data. These lineages undergoing divergence processes split only at the end or after the last glacial maximum based on calibration with radiocarbon-dated paleontological material. However, the incorporation of information from heterozygous sites had a significant impact on absolute and relative branch length estimations. Ignoring heterozygous information led to an overestimation of divergence times between the evolutionary lineages of M. arvalis. We conclude that the exclusion of heterozygous sites from evolutionary analyses may cause biased and misleading divergence time estimates in closely related taxa.

Multi-Objective and Multidisciplinary Design Optimisation (MDO) of UAV Systems using Hierarchical Asynchronous Parallel Evolutionary Algorithms

DTIC Science & Technology

2007-09-17

been proposed; these include a combination of variable fidelity models, parallelisation strategies and hybridisation techniques (Coello, Veldhuizen et...Coello et al (Coello, Veldhuizen et al. 2002). 4.4.2 HIERARCHICAL POPULATION TOPOLOGY A hierarchical population topology, when integrated into...to hybrid parallel Multi-Objective Evolutionary Algorithms (pMOEA) (Cantu-Paz 2000; Veldhuizen , Zydallis et al. 2003); it uses a master slave

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

ERIC Educational Resources Information Center

Wagh, Aditi; Wilensky, Uri

2018-01-01

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…

Manager’s Guide to Technology Transition in an Evolutionary Acquisition Environment

DTIC Science & Technology

2005-06-01

program managers, product managers, staffs, and organizations that manage the development , procurement, production, and fielding of systems...rapidly advancing technologies. Technology transitions can occur during the development of systems, or even after a system has been in the field ...Documentation Evolutionary acquisition is an acquisition strategy that defines, develops , produces or acquires, and fields an initial hardware or software

PAQ: Partition Analysis of Quasispecies.

PubMed

Baccam, P; Thompson, R J; Fedrigo, O; Carpenter, S; Cornette, J L

2001-01-01

The complexities of genetic data may not be accurately described by any single analytical tool. Phylogenetic analysis is often used to study the genetic relationship among different sequences. Evolutionary models and assumptions are invoked to reconstruct trees that describe the phylogenetic relationship among sequences. Genetic databases are rapidly accumulating large amounts of sequences. Newly acquired sequences, which have not yet been characterized, may require preliminary genetic exploration in order to build models describing the evolutionary relationship among sequences. There are clustering techniques that rely less on models of evolution, and thus may provide nice exploratory tools for identifying genetic similarities. Some of the more commonly used clustering methods perform better when data can be grouped into mutually exclusive groups. Genetic data from viral quasispecies, which consist of closely related variants that differ by small changes, however, may best be partitioned by overlapping groups. We have developed an intuitive exploratory program, Partition Analysis of Quasispecies (PAQ), which utilizes a non-hierarchical technique to partition sequences that are genetically similar. PAQ was used to analyze a data set of human immunodeficiency virus type 1 (HIV-1) envelope sequences isolated from different regions of the brain and another data set consisting of the equine infectious anemia virus (EIAV) regulatory gene rev. Analysis of the HIV-1 data set by PAQ was consistent with phylogenetic analysis of the same data, and the EIAV rev variants were partitioned into two overlapping groups. PAQ provides an additional tool which can be used to glean information from genetic data and can be used in conjunction with other tools to study genetic similarities and genetic evolution of viral quasispecies.

Automated Antenna Design with Evolutionary Algorithms

NASA Technical Reports Server (NTRS)

Hornby, Gregory S.; Globus, Al; Linden, Derek S.; Lohn, Jason D.

2006-01-01

Current methods of designing and optimizing antennas by hand are time and labor intensive, and limit complexity. Evolutionary design techniques can overcome these limitations by searching the design space and automatically finding effective solutions. In recent years, evolutionary algorithms have shown great promise in finding practical solutions in large, poorly understood design spaces. In particular, spacecraft antenna design has proven tractable to evolutionary design techniques. Researchers have been investigating evolutionary antenna design and optimization since the early 1990s, and the field has grown in recent years as computer speed has increased and electromagnetic simulators have improved. Two requirements-compliant antennas, one for ST5 and another for TDRS-C, have been automatically designed by evolutionary algorithms. The ST5 antenna is slated to fly this year, and a TDRS-C phased array element has been fabricated and tested. Such automated evolutionary design is enabled by medium-to-high quality simulators and fast modern computers to evaluate computer-generated designs. Evolutionary algorithms automate cut-and-try engineering, substituting automated search though millions of potential designs for intelligent search by engineers through a much smaller number of designs. For evolutionary design, the engineer chooses the evolutionary technique, parameters and the basic form of the antenna, e.g., single wire for ST5 and crossed-element Yagi for TDRS-C. Evolutionary algorithms then search for optimal configurations in the space defined by the engineer. NASA's Space Technology 5 (ST5) mission will launch three small spacecraft to test innovative concepts and technologies. Advanced evolutionary algorithms were used to automatically design antennas for ST5. The combination of wide beamwidth for a circularly-polarized wave and wide impedance bandwidth made for a challenging antenna design problem. From past experience in designing wire antennas, we chose to constrain the evolutionary design to a monopole wire antenna. The results of the runs produced requirements-compliant antennas that were subsequently fabricated and tested. The evolved antenna has a number of advantages with regard to power consumption, fabrication time and complexity, and performance. Lower power requirements result from achieving high gain across a wider range of elevation angles, thus allowing a broader range of angles over which maximum data throughput can be achieved. Since the evolved antenna does not require a phasing circuit, less design and fabrication work is required. In terms of overall work, the evolved antenna required approximately three person-months to design and fabricate whereas the conventional antenna required about five. Furthermore, when the mission was modified and new orbital parameters selected, a redesign of the antenna to new requirements was required. The evolutionary system was rapidly modified and a new antenna evolved in a few weeks. The evolved antenna was shown to be compliant to the ST5 mission requirements. It has an unusual organic looking structure, one that expert antenna designers would not likely produce. This antenna has been tested, baselined and is scheduled to fly this year. In addition to the ST5 antenna, our laboratory has evolved an S-band phased array antenna element design that meets the requirements for NASA's TDRS-C communications satellite scheduled for launch early next decade. A combination of fairly broad bandwidth, high efficiency and circular polarization at high gain made for another challenging design problem. We chose to constrain the evolutionary design to a crossed-element Yagi antenna. The specification called for two types of elements, one for receive only and one for transmit/receive. We were able to evolve a single element design that meets both specifications thereby simplifying the antenna and reducing testing and integration costs. The highest performance antenna found using a getic algorithm and stochastic hill-climbing has been fabricated and tested. Laboratory results correspond well with simulation. Aerospace component design is an expensive and important step in space development. Evolutionary design can make a significant contribution wherever sufficiently fast, accurate and capable software simulators are available. We have demonstrated successful real-world design in the spacecraft antenna domain; and there is good reason to believe that these results could be replicated in other design spaces.

Evolutionary Nephrology.

PubMed

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.

The evolutionary psychology of hunger.

PubMed

Al-Shawaf, Laith

2016-10-01

An evolutionary psychological perspective suggests that emotions can be understood as coordinating mechanisms whose job is to regulate various psychological and physiological programs in the service of solving an adaptive problem. This paper suggests that it may also be fruitful to approach hunger from this coordinating mechanism perspective. To this end, I put forward an evolutionary task analysis of hunger, generating novel a priori hypotheses about the coordinating effects of hunger on psychological processes such as perception, attention, categorization, and memory. This approach appears empirically fruitful in that it yields a bounty of testable new hypotheses. Copyright © 2016 Elsevier Ltd. All rights reserved.

Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods.

PubMed

Hidalgo, J Ignacio; Colmenar, J Manuel; Kronberger, Gabriel; Winkler, Stephan M; Garnica, Oscar; Lanchares, Juan

2017-08-08

Predicting glucose values on the basis of insulin and food intakes is a difficult task that people with diabetes need to do daily. This is necessary as it is important to maintain glucose levels at appropriate values to avoid not only short-term, but also long-term complications of the illness. Artificial intelligence in general and machine learning techniques in particular have already lead to promising results in modeling and predicting glucose concentrations. In this work, several machine learning techniques are used for the modeling and prediction of glucose concentrations using as inputs the values measured by a continuous monitoring glucose system as well as also previous and estimated future carbohydrate intakes and insulin injections. In particular, we use the following four techniques: genetic programming, random forests, k-nearest neighbors, and grammatical evolution. We propose two new enhanced modeling algorithms for glucose prediction, namely (i) a variant of grammatical evolution which uses an optimized grammar, and (ii) a variant of tree-based genetic programming which uses a three-compartment model for carbohydrate and insulin dynamics. The predictors were trained and tested using data of ten patients from a public hospital in Spain. We analyze our experimental results using the Clarke error grid metric and see that 90% of the forecasts are correct (i.e., Clarke error categories A and B), but still even the best methods produce 5 to 10% of serious errors (category D) and approximately 0.5% of very serious errors (category E). We also propose an enhanced genetic programming algorithm that incorporates a three-compartment model into symbolic regression models to create smoothed time series of the original carbohydrate and insulin time series.

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

NASA Astrophysics Data System (ADS)

Muduli, Pradyut; Das, Sarat

2014-06-01

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

Multi-objective optimisation and decision-making of space station logistics strategies

NASA Astrophysics Data System (ADS)

Zhu, Yue-he; Luo, Ya-zhong

2016-10-01

Space station logistics strategy optimisation is a complex engineering problem with multiple objectives. Finding a decision-maker-preferred compromise solution becomes more significant when solving such a problem. However, the designer-preferred solution is not easy to determine using the traditional method. Thus, a hybrid approach that combines the multi-objective evolutionary algorithm, physical programming, and differential evolution (DE) algorithm is proposed to deal with the optimisation and decision-making of space station logistics strategies. A multi-objective evolutionary algorithm is used to acquire a Pareto frontier and help determine the range parameters of the physical programming. Physical programming is employed to convert the four-objective problem into a single-objective problem, and a DE algorithm is applied to solve the resulting physical programming-based optimisation problem. Five kinds of objective preference are simulated and compared. The simulation results indicate that the proposed approach can produce good compromise solutions corresponding to different decision-makers' preferences.

Evolutionary Technologies: Fundamentals and Applications to Information/Communication Systems and Manufacturing/Logistics Systems

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Kawakami, Hiroshi; Tsujimura, Yasuhiro; Handa, Hisashi; Lin, Lin; Okamoto, Azuma

As efficient utilization of computational resources is increasing, evolutionary technology based on the Genetic Algorithm (GA), Genetic Programming (GP), Evolution Strategy (ES) and other Evolutionary Computations (ECs) is making rapid progress, and its social recognition and the need as applied technology are increasing. This is explained by the facts that EC offers higher robustness for knowledge information processing systems, intelligent production and logistics systems, most advanced production scheduling and other various real-world problems compared to the approaches based on conventional theories, and EC ensures flexible applicability and usefulness for any unknown system environment even in a case where accurate mathematical modeling fails in the formulation. In this paper, we provide a comprehensive survey of the current state-of-the-art in the fundamentals and applications of evolutionary technologies.

The Evolution of Cartography Graduate Programs and the Development of New Graduate Programs in Cartography: An Assessment of Models.

ERIC Educational Resources Information Center

Steinke, Theodore R.

This paper traces the historical development of cartography graduate programs, establishes an evolutionary model, and evaluates the model to determine if it has some utility today for the development of programs capable of producing highly skilled cartographers. Cartography is defined to include traditional cartography, computer cartography,…

Unraveling the Tangled Skein: The Evolution of Transcriptional Regulatory Networks in Development.

PubMed

Rebeiz, Mark; Patel, Nipam H; Hinman, Veronica F

2015-01-01

The molecular and genetic basis for the evolution of anatomical diversity is a major question that has inspired evolutionary and developmental biologists for decades. Because morphology takes form during development, a true comprehension of how anatomical structures evolve requires an understanding of the evolutionary events that alter developmental genetic programs. Vast gene regulatory networks (GRNs) that connect transcription factors to their target regulatory sequences control gene expression in time and space and therefore determine the tissue-specific genetic programs that shape morphological structures. In recent years, many new examples have greatly advanced our understanding of the genetic alterations that modify GRNs to generate newly evolved morphologies. Here, we review several aspects of GRN evolution, including their deep preservation, their mechanisms of alteration, and how they originate to generate novel developmental programs.

Nemo: an evolutionary and population genetics programming framework.

PubMed

Guillaume, Frédéric; Rougemont, Jacques

2006-10-15

Nemo is an individual-based, genetically explicit and stochastic population computer program for the simulation of population genetics and life-history trait evolution in a metapopulation context. It comes as both a C++ programming framework and an executable program file. Its object-oriented programming design gives it the flexibility and extensibility needed to implement a large variety of forward-time evolutionary models. It provides developers with abstract models allowing them to implement their own life-history traits and life-cycle events. Nemo offers a large panel of population models, from the Island model to lattice models with demographic or environmental stochasticity and a variety of already implemented traits (deleterious mutations, neutral markers and more), life-cycle events (mating, dispersal, aging, selection, etc.) and output operators for saving data and statistics. It runs on all major computer platforms including parallel computing environments. The source code, binaries and documentation are available under the GNU General Public License at http://nemo2.sourceforge.net.

Clinical software development for the Web: lessons learned from the BOADICEA project

PubMed Central

2012-01-01

Background In the past 20 years, society has witnessed the following landmark scientific advances: (i) the sequencing of the human genome, (ii) the distribution of software by the open source movement, and (iii) the invention of the World Wide Web. Together, these advances have provided a new impetus for clinical software development: developers now translate the products of human genomic research into clinical software tools; they use open-source programs to build them; and they use the Web to deliver them. Whilst this open-source component-based approach has undoubtedly made clinical software development easier, clinical software projects are still hampered by problems that traditionally accompany the software process. This study describes the development of the BOADICEA Web Application, a computer program used by clinical geneticists to assess risks to patients with a family history of breast and ovarian cancer. The key challenge of the BOADICEA Web Application project was to deliver a program that was safe, secure and easy for healthcare professionals to use. We focus on the software process, problems faced, and lessons learned. Our key objectives are: (i) to highlight key clinical software development issues; (ii) to demonstrate how software engineering tools and techniques can facilitate clinical software development for the benefit of individuals who lack software engineering expertise; and (iii) to provide a clinical software development case report that can be used as a basis for discussion at the start of future projects. Results We developed the BOADICEA Web Application using an evolutionary software process. Our approach to Web implementation was conservative and we used conventional software engineering tools and techniques. The principal software development activities were: requirements, design, implementation, testing, documentation and maintenance. The BOADICEA Web Application has now been widely adopted by clinical geneticists and researchers. BOADICEA Web Application version 1 was released for general use in November 2007. By May 2010, we had > 1200 registered users based in the UK, USA, Canada, South America, Europe, Africa, Middle East, SE Asia, Australia and New Zealand. Conclusions We found that an evolutionary software process was effective when we developed the BOADICEA Web Application. The key clinical software development issues identified during the BOADICEA Web Application project were: software reliability, Web security, clinical data protection and user feedback. PMID:22490389

Clinical software development for the Web: lessons learned from the BOADICEA project.

PubMed

Cunningham, Alex P; Antoniou, Antonis C; Easton, Douglas F

2012-04-10

In the past 20 years, society has witnessed the following landmark scientific advances: (i) the sequencing of the human genome, (ii) the distribution of software by the open source movement, and (iii) the invention of the World Wide Web. Together, these advances have provided a new impetus for clinical software development: developers now translate the products of human genomic research into clinical software tools; they use open-source programs to build them; and they use the Web to deliver them. Whilst this open-source component-based approach has undoubtedly made clinical software development easier, clinical software projects are still hampered by problems that traditionally accompany the software process. This study describes the development of the BOADICEA Web Application, a computer program used by clinical geneticists to assess risks to patients with a family history of breast and ovarian cancer. The key challenge of the BOADICEA Web Application project was to deliver a program that was safe, secure and easy for healthcare professionals to use. We focus on the software process, problems faced, and lessons learned. Our key objectives are: (i) to highlight key clinical software development issues; (ii) to demonstrate how software engineering tools and techniques can facilitate clinical software development for the benefit of individuals who lack software engineering expertise; and (iii) to provide a clinical software development case report that can be used as a basis for discussion at the start of future projects. We developed the BOADICEA Web Application using an evolutionary software process. Our approach to Web implementation was conservative and we used conventional software engineering tools and techniques. The principal software development activities were: requirements, design, implementation, testing, documentation and maintenance. The BOADICEA Web Application has now been widely adopted by clinical geneticists and researchers. BOADICEA Web Application version 1 was released for general use in November 2007. By May 2010, we had > 1200 registered users based in the UK, USA, Canada, South America, Europe, Africa, Middle East, SE Asia, Australia and New Zealand. We found that an evolutionary software process was effective when we developed the BOADICEA Web Application. The key clinical software development issues identified during the BOADICEA Web Application project were: software reliability, Web security, clinical data protection and user feedback.

Evolutionary engineering for industrial microbiology.

PubMed

Vanee, Niti; Fisher, Adam B; Fong, Stephen S

2012-01-01

Superficially, evolutionary engineering is a paradoxical field that balances competing interests. In natural settings, evolution iteratively selects and enriches subpopulations that are best adapted to a particular ecological niche using random processes such as genetic mutation. In engineering desired approaches utilize rational prospective design to address targeted problems. When considering details of evolutionary and engineering processes, more commonality can be found. Engineering relies on detailed knowledge of the problem parameters and design properties in order to predict design outcomes that would be an optimized solution. When detailed knowledge of a system is lacking, engineers often employ algorithmic search strategies to identify empirical solutions. Evolution epitomizes this iterative optimization by continuously diversifying design options from a parental design, and then selecting the progeny designs that represent satisfactory solutions. In this chapter, the technique of applying the natural principles of evolution to engineer microbes for industrial applications is discussed to highlight the challenges and principles of evolutionary engineering.

Evolutionary Optimization of a Geometrically Refined Truss

NASA Technical Reports Server (NTRS)

Hull, P. V.; Tinker, M. L.; Dozier, G. V.

2007-01-01

Structural optimization is a field of research that has experienced noteworthy growth for many years. Researchers in this area have developed optimization tools to successfully design and model structures, typically minimizing mass while maintaining certain deflection and stress constraints. Numerous optimization studies have been performed to minimize mass, deflection, and stress on a benchmark cantilever truss problem. Predominantly traditional optimization theory is applied to this problem. The cross-sectional area of each member is optimized to minimize the aforementioned objectives. This Technical Publication (TP) presents a structural optimization technique that has been previously applied to compliant mechanism design. This technique demonstrates a method that combines topology optimization, geometric refinement, finite element analysis, and two forms of evolutionary computation: genetic algorithms and differential evolution to successfully optimize a benchmark structural optimization problem. A nontraditional solution to the benchmark problem is presented in this TP, specifically a geometrically refined topological solution. The design process begins with an alternate control mesh formulation, multilevel geometric smoothing operation, and an elastostatic structural analysis. The design process is wrapped in an evolutionary computing optimization toolset.

Real-time maritime scene simulation for ladar sensors

NASA Astrophysics Data System (ADS)

Christie, Chad L.; Gouthas, Efthimios; Swierkowski, Leszek; Williams, Owen M.

2011-06-01

Continuing interest exists in the development of cost-effective synthetic environments for testing Laser Detection and Ranging (ladar) sensors. In this paper we describe a PC-based system for real-time ladar scene simulation of ships and small boats in a dynamic maritime environment. In particular, we describe the techniques employed to generate range imagery accompanied by passive radiance imagery. Our ladar scene generation system is an evolutionary extension of the VIRSuite infrared scene simulation program and includes all previous features such as ocean wave simulation, the physically-realistic representation of boat and ship dynamics, wake generation and simulation of whitecaps, spray, wake trails and foam. A terrain simulation extension is also under development. In this paper we outline the development, capabilities and limitations of the VIRSuite extensions.

Artificial intelligence in peer review: How can evolutionary computation support journal editors?

PubMed Central

Fronczak, Piotr; Fronczak, Agata; Ausloos, Marcel; Nedic, Olgica

2017-01-01

With the volume of manuscripts submitted for publication growing every year, the deficiencies of peer review (e.g. long review times) are becoming more apparent. Editorial strategies, sets of guidelines designed to speed up the process and reduce editors’ workloads, are treated as trade secrets by publishing houses and are not shared publicly. To improve the effectiveness of their strategies, editors in small publishing groups are faced with undertaking an iterative trial-and-error approach. We show that Cartesian Genetic Programming, a nature-inspired evolutionary algorithm, can dramatically improve editorial strategies. The artificially evolved strategy reduced the duration of the peer review process by 30%, without increasing the pool of reviewers (in comparison to a typical human-developed strategy). Evolutionary computation has typically been used in technological processes or biological ecosystems. Our results demonstrate that genetic programs can improve real-world social systems that are usually much harder to understand and control than physical systems. PMID:28931033

Evolutionary pattern search algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, W.E.

1995-09-19

This paper defines a class of evolutionary algorithms called evolutionary pattern search algorithms (EPSAs) and analyzes their convergence properties. This class of algorithms is closely related to evolutionary programming, evolutionary strategie and real-coded genetic algorithms. EPSAs are self-adapting systems that modify the step size of the mutation operator in response to the success of previous optimization steps. The rule used to adapt the step size can be used to provide a stationary point convergence theory for EPSAs on any continuous function. This convergence theory is based on an extension of the convergence theory for generalized pattern search methods. An experimentalmore » analysis of the performance of EPSAs demonstrates that these algorithms can perform a level of global search that is comparable to that of canonical EAs. We also describe a stopping rule for EPSAs, which reliably terminated near stationary points in our experiments. This is the first stopping rule for any class of EAs that can terminate at a given distance from stationary points.« less

Predicting patchy particle crystals: variable box shape simulations and evolutionary algorithms.

PubMed

Bianchi, Emanuela; Doppelbauer, Günther; Filion, Laura; Dijkstra, Marjolein; Kahl, Gerhard

2012-06-07

We consider several patchy particle models that have been proposed in literature and we investigate their candidate crystal structures in a systematic way. We compare two different algorithms for predicting crystal structures: (i) an approach based on Monte Carlo simulations in the isobaric-isothermal ensemble and (ii) an optimization technique based on ideas of evolutionary algorithms. We show that the two methods are equally successful and provide consistent results on crystalline phases of patchy particle systems.

Influences on Understanding and Belief About the Origin of Species in Chinese and American Adolescents

NASA Astrophysics Data System (ADS)

Smith, Erin Irene

Although beliefs about origins and evolutionary knowledge have been considered independent, research has suggested that both are influenced by cognitive constraints of psychological essentialism and teleology. Most research supporting these claims has been conducted with children from Western cultures; little is known about the psychological processes underpinning beliefs and knowledge about the natural world outside Western contexts or during adolescence. Claims about the universality of beliefs, knowledge, and the possible relationship between should be made after examining samples that differ in theoretically relevant ways from a typical Western sample, such as a Chinese sample in which religious explanations are rare or an adolescent sample in which brain development promotes the coordination of conflicting information. To examine how belief and knowledge are related in Western- and non-Western samples, as well as the factors that predict both independently, 238 Chinese (M = 15.85 years old, SD = .85 years; 36.6% male) and 277 American adolescents (M = 15.80 years, SD = 1.34 years; 51.6% male) were recruited from their high schools to participate. Adolescents completed a survey measuring beliefs about the origin of living and non-living exemplars, evolutionary knowledge, and variables that were likely to influence belief and knowledge such as science preference, epistemology, psychological essentialism, teleological reasoning, and religious beliefs. American adolescents were more creationist than Chinese adolescents. Chinese adolescents displayed more sophisticated evolutionary knowledge than American adolescents although overall performance was low. Finally, there was no relationship between belief and knowledge for American adolescents yet there was a small, positive relationship for Chinese adolescents such that adolescents who believed in creation also tended to demonstrate more evolutionary knowledge. Additional analyses employed mediation techniques to explain why cultural differences in creation belief and evolutionary knowledge exist. Age was unrelated to belief and to knowledge. The discussion focuses on the aspects of cultural membership that contribute to belief and evolutionary knowledge. Additional discussion highlights the role of classroom curriculum, curriculum testing, and focusing on uncovering variables and techniques that promote evolutionary learning.

Evolutionary Losses? The Growth of Graduate Programs at Undergraduate Colleges.

ERIC Educational Resources Information Center

McCormick, Alexander C.; Staklis, Sandra

This study examined the addition and expansion of graduate programs at primarily undergraduate colleges. The primary approach of the study was quantitative, consisting of descriptive and multivariate analysis of master's degree programs at colleges that were classified in 1994 as Baccalaureate Colleges. Data came from the 1994 and 2000 Carnegie…

Conservation and canalization of gene expression during angiosperm diversification accompany the origin and evolution of the flower

PubMed Central

Chanderbali, André S.; Yoo, Mi-Jeong; Zahn, Laura M.; Brockington, Samuel F.; Wall, P. Kerr; Gitzendanner, Matthew A.; Albert, Victor A.; Leebens-Mack, James; Altman, Naomi S.; Ma, Hong; dePamphilis, Claude W.; Soltis, Douglas E.; Soltis, Pamela S.

2010-01-01

The origin and rapid diversification of the angiosperms (Darwin's “Abominable Mystery”) has engaged generations of researchers. Here, we examine the floral genetic programs of phylogenetically pivotal angiosperms (water lily, avocado, California poppy, and Arabidopsis) and a nonflowering seed plant (a cycad) to obtain insight into the origin and subsequent evolution of the flower. Transcriptional cascades with broadly overlapping spatial domains, resembling the hypothesized ancestral gymnosperm program, are deployed across morphologically intergrading organs in water lily and avocado flowers. In contrast, spatially discrete transcriptional programs in distinct floral organs characterize the more recently derived angiosperm lineages represented by California poppy and Arabidopsis. Deep evolutionary conservation in the genetic programs of putatively homologous floral organs traces to those operating in gymnosperm reproductive cones. Female gymnosperm cones and angiosperm carpels share conserved genetic features, which may be associated with the ovule developmental program common to both organs. However, male gymnosperm cones share genetic features with both perianth (sterile attractive and protective) organs and stamens, supporting the evolutionary origin of the floral perianth from the male genetic program of seed plants. PMID:21149731

Conservation and canalization of gene expression during angiosperm diversification accompany the origin and evolution of the flower.

PubMed

Chanderbali, André S; Yoo, Mi-Jeong; Zahn, Laura M; Brockington, Samuel F; Wall, P Kerr; Gitzendanner, Matthew A; Albert, Victor A; Leebens-Mack, James; Altman, Naomi S; Ma, Hong; dePamphilis, Claude W; Soltis, Douglas E; Soltis, Pamela S

2010-12-28

The origin and rapid diversification of the angiosperms (Darwin's "Abominable Mystery") has engaged generations of researchers. Here, we examine the floral genetic programs of phylogenetically pivotal angiosperms (water lily, avocado, California poppy, and Arabidopsis) and a nonflowering seed plant (a cycad) to obtain insight into the origin and subsequent evolution of the flower. Transcriptional cascades with broadly overlapping spatial domains, resembling the hypothesized ancestral gymnosperm program, are deployed across morphologically intergrading organs in water lily and avocado flowers. In contrast, spatially discrete transcriptional programs in distinct floral organs characterize the more recently derived angiosperm lineages represented by California poppy and Arabidopsis. Deep evolutionary conservation in the genetic programs of putatively homologous floral organs traces to those operating in gymnosperm reproductive cones. Female gymnosperm cones and angiosperm carpels share conserved genetic features, which may be associated with the ovule developmental program common to both organs. However, male gymnosperm cones share genetic features with both perianth (sterile attractive and protective) organs and stamens, supporting the evolutionary origin of the floral perianth from the male genetic program of seed plants.

Assembling networks of microbial genomes using linear programming.

PubMed

Holloway, Catherine; Beiko, Robert G

2010-11-20

Microbial genomes exhibit complex sets of genetic affinities due to lateral genetic transfer. Assessing the relative contributions of parent-to-offspring inheritance and gene sharing is a vital step in understanding the evolutionary origins and modern-day function of an organism, but recovering and showing these relationships is a challenging problem. We have developed a new approach that uses linear programming to find between-genome relationships, by treating tables of genetic affinities (here, represented by transformed BLAST e-values) as an optimization problem. Validation trials on simulated data demonstrate the effectiveness of the approach in recovering and representing vertical and lateral relationships among genomes. Application of the technique to a set comprising Aquifex aeolicus and 75 other thermophiles showed an important role for large genomes as 'hubs' in the gene sharing network, and suggested that genes are preferentially shared between organisms with similar optimal growth temperatures. We were also able to discover distinct and common genetic contributors to each sequenced representative of genus Pseudomonas. The linear programming approach we have developed can serve as an effective inference tool in its own right, and can be an efficient first step in a more-intensive phylogenomic analysis.

Possible steps in the evolutionary development of bird navigation

NASA Technical Reports Server (NTRS)

Bellrose, F. C.

1972-01-01

Hypotheses are presented to explain the evolutionary development of navigational ability in migratory birds. Areas of discussion to describe the possible techniques are: (1) sun compass, (2) bicoordinate navigation, (3) star compass, (4) wind cues, (5) earth magnetic field, and (6) landscape features. It is concluded that landscape is the single most important cue for orientation of nonmigratory birds. The long range migratory birds appear to use a combination of cues with the relative importance of the cue dependent upon the species of the bird involved.

From the "Modern Synthesis" to cybernetics: Ivan Ivanovich Schmalhausen (1884-1963) and his research program for a synthesis of evolutionary and developmental biology.

PubMed

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

2006-03-15

Ivan I. Schmalhausen was one of the central figures in the Russian development of the "Modern Synthesis" in evolutionary biology. He is widely cited internationally even today. Schmalhausen developed the main principles of his theory facing the danger of death in the totalitarian Soviet Union. His great services to evolutionary and theoretical biology are indisputable. However, the received view of Schmalhausen's contributions to evolutionary biology makes an unbiased reading of his texts difficult. Here we show that taking all of his works into consideration (including those only available in Russian) paints a much more dynamic and exciting picture of what he tried to achieve. Schmalhausen pioneered the integration of a developmental perspective into evolutionary thinking. A main tool for achieving this was his approach to living objects as complex multi-level self-regulating systems. Schmalhausen put enormous effort into bringing this idea into fruition during the final stages of his career by combining evolutionary theory with cybernetics. His results and ideas remain thought-provoking, and his texts are of more than just historical interest. Copyright 2006 Wiley-Liss, Inc.

Applying Evolutionary Genetics to Developmental Toxicology and Risk Assessment

PubMed Central

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

Evolutionary perspectives on learning: conceptual and methodological issues in the study of adaptive specializations.

PubMed

Krause, Mark A

2015-07-01

Inquiry into evolutionary adaptations has flourished since the modern synthesis of evolutionary biology. Comparative methods, genetic techniques, and various experimental and modeling approaches are used to test adaptive hypotheses. In psychology, the concept of adaptation is broadly applied and is central to comparative psychology and cognition. The concept of an adaptive specialization of learning is a proposed account for exceptions to general learning processes, as seen in studies of Pavlovian conditioning of taste aversions, sexual responses, and fear. The evidence generally consists of selective associations forming between biologically relevant conditioned and unconditioned stimuli, with conditioned responses differing in magnitude, persistence, or other measures relative to non-biologically relevant stimuli. Selective associations for biologically relevant stimuli may suggest adaptive specializations of learning, but do not necessarily confirm adaptive hypotheses as conceived of in evolutionary biology. Exceptions to general learning processes do not necessarily default to an adaptive specialization explanation, even if experimental results "make biological sense". This paper examines the degree to which hypotheses of adaptive specializations of learning in sexual and fear response systems have been tested using methodologies developed in evolutionary biology (e.g., comparative methods, quantitative and molecular genetics, survival experiments). A broader aim is to offer perspectives from evolutionary biology for testing adaptive hypotheses in psychological science.

Evolution of apoptosis-like programmed cell death in unicellular protozoan parasites.

PubMed

Kaczanowski, Szymon; Sajid, Mohammed; Reece, Sarah E

2011-03-25

Apoptosis-like programmed cell death (PCD) has recently been described in multiple taxa of unicellular protists, including the protozoan parasites Plasmodium, Trypanosoma and Leishmania. Apoptosis-like PCD in protozoan parasites shares a number of morphological features with programmed cell death in multicellular organisms. However, both the evolutionary explanations and mechanisms involved in parasite PCD are poorly understood. Explaining why unicellular organisms appear to undergo 'suicide' is a challenge for evolutionary biology and uncovering death executors and pathways is a challenge for molecular and cell biology. Bioinformatics has the potential to integrate these approaches by revealing homologies in the PCD machinery of diverse taxa and evaluating their evolutionary trajectories. As the molecular mechanisms of apoptosis in model organisms are well characterised, and recent data suggest similar mechanisms operate in protozoan parasites, key questions can now be addressed. These questions include: which elements of apoptosis machinery appear to be shared between protozoan parasites and multicellular taxa and, have these mechanisms arisen through convergent or divergent evolution? We use bioinformatics to address these questions and our analyses suggest that apoptosis mechanisms in protozoan parasites and other taxa have diverged during their evolution, that some apoptosis factors are shared across taxa whilst others have been replaced by proteins with similar biochemical activities.

Evolution of apoptosis-like programmed cell death in unicellular protozoan parasites

PubMed Central

2011-01-01

Apoptosis-like programmed cell death (PCD) has recently been described in multiple taxa of unicellular protists, including the protozoan parasites Plasmodium, Trypanosoma and Leishmania. Apoptosis-like PCD in protozoan parasites shares a number of morphological features with programmed cell death in multicellular organisms. However, both the evolutionary explanations and mechanisms involved in parasite PCD are poorly understood. Explaining why unicellular organisms appear to undergo 'suicide' is a challenge for evolutionary biology and uncovering death executors and pathways is a challenge for molecular and cell biology. Bioinformatics has the potential to integrate these approaches by revealing homologies in the PCD machinery of diverse taxa and evaluating their evolutionary trajectories. As the molecular mechanisms of apoptosis in model organisms are well characterised, and recent data suggest similar mechanisms operate in protozoan parasites, key questions can now be addressed. These questions include: which elements of apoptosis machinery appear to be shared between protozoan parasites and multicellular taxa and, have these mechanisms arisen through convergent or divergent evolution? We use bioinformatics to address these questions and our analyses suggest that apoptosis mechanisms in protozoan parasites and other taxa have diverged during their evolution, that some apoptosis factors are shared across taxa whilst others have been replaced by proteins with similar biochemical activities. PMID:21439063

Application of time series discretization using evolutionary programming for classification of precancerous cervical lesions.

PubMed

Acosta-Mesa, Héctor-Gabriel; Rechy-Ramírez, Fernando; Mezura-Montes, Efrén; Cruz-Ramírez, Nicandro; Hernández Jiménez, Rodolfo

2014-06-01

In this work, we present a novel application of time series discretization using evolutionary programming for the classification of precancerous cervical lesions. The approach optimizes the number of intervals in which the length and amplitude of the time series should be compressed, preserving the important information for classification purposes. Using evolutionary programming, the search for a good discretization scheme is guided by a cost function which considers three criteria: the entropy regarding the classification, the complexity measured as the number of different strings needed to represent the complete data set, and the compression rate assessed as the length of the discrete representation. This discretization approach is evaluated using a time series data based on temporal patterns observed during a classical test used in cervical cancer detection; the classification accuracy reached by our method is compared with the well-known times series discretization algorithm SAX and the dimensionality reduction method PCA. Statistical analysis of the classification accuracy shows that the discrete representation is as efficient as the complete raw representation for the present application, reducing the dimensionality of the time series length by 97%. This representation is also very competitive in terms of classification accuracy when compared with similar approaches. Copyright © 2014 Elsevier Inc. All rights reserved.

Individual-based modeling of ecological and evolutionary processes

USGS Publications Warehouse

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.

Breast tumor malignancy modelling using evolutionary neural logic networks.

PubMed

Tsakonas, Athanasios; Dounias, Georgios; Panagi, Georgia; Panourgias, Evangelia

2006-01-01

The present work proposes a computer assisted methodology for the effective modelling of the diagnostic decision for breast tumor malignancy. The suggested approach is based on innovative hybrid computational intelligence algorithms properly applied in related cytological data contained in past medical records. The experimental data used in this study were gathered in the early 1990s in the University of Wisconsin, based in post diagnostic cytological observations performed by expert medical staff. Data were properly encoded in a computer database and accordingly, various alternative modelling techniques were applied on them, in an attempt to form diagnostic models. Previous methods included standard optimisation techniques, as well as artificial intelligence approaches, in a way that a variety of related publications exists in modern literature on the subject. In this report, a hybrid computational intelligence approach is suggested, which effectively combines modern mathematical logic principles, neural computation and genetic programming in an effective manner. The approach proves promising either in terms of diagnostic accuracy and generalization capabilities, or in terms of comprehensibility and practical importance for the related medical staff.

A Program for At-Risk High School Students Informed by Evolutionary Science

PubMed Central

Wilson, David Sloan; Kauffman, Richard A.; Purdy, Miriam S.

2011-01-01

Improving the academic performance of at-risk high school students has proven difficult, often calling for an extended day, extended school year, and other expensive measures. Here we report the results of a program for at-risk 9th and 10th graders in Binghamton, New York, called the Regents Academy that takes place during the normal school day and year. The design of the program is informed by the evolutionary dynamics of cooperation and learning, in general and for our species as a unique product of biocultural evolution. Not only did the Regents Academy students outperform their comparison group in a randomized control design, but they performed on a par with the average high school student in Binghamton on state-mandated exams. All students can benefit from the social environment provided for at-risk students at the Regents Academy, which is within the reach of most public school districts. PMID:22114703

The protein-protein interface evolution acts in a similar way to antibody affinity maturation.

PubMed

Li, Bohua; Zhao, Lei; Wang, Chong; Guo, Huaizu; Wu, Lan; Zhang, Xunming; Qian, Weizhu; Wang, Hao; Guo, Yajun

2010-02-05

Understanding the evolutionary mechanism that acts at the interfaces of protein-protein complexes is a fundamental issue with high interest for delineating the macromolecular complexes and networks responsible for regulation and complexity in biological systems. To investigate whether the evolution of protein-protein interface acts in a similar way as antibody affinity maturation, we incorporated evolutionary information derived from antibody affinity maturation with common simulation techniques to evaluate prediction success rates of the computational method in affinity improvement in four different systems: antibody-receptor, antibody-peptide, receptor-membrane ligand, and receptor-soluble ligand. It was interesting to find that the same evolutionary information could improve the prediction success rates in all the four protein-protein complexes with an exceptional high accuracy (>57%). One of the most striking findings in our present study is that not only in the antibody-combining site but in other protein-protein interfaces almost all of the affinity-enhancing mutations are located at the germline hotspot sequences (RGYW or WA), indicating that DNA hot spot mechanisms may be widely used in the evolution of protein-protein interfaces. Our data suggest that the evolution of distinct protein-protein interfaces may use the same basic strategy under selection pressure to maintain interactions. Additionally, our data indicate that classical simulation techniques incorporating the evolutionary information derived from in vivo antibody affinity maturation can be utilized as a powerful tool to improve the binding affinity of protein-protein complex with a high accuracy.

The Evolutionary Development of Echocardiography

PubMed Central

Maleki, Majid; Esmaeilzadeh, Maryam

2012-01-01

Echocardiography is a non-invasive diagnostic technique which provides information on cardiac morphology, function, and hemodynamics. It is the most frequently used cardiovascular diagnostic test only after electrocardiography. In less than five decades, the evolution in this technique has made it the basic part of cardiovascular medicine. Herein, the evolution of various forms of echocardiography is briefly described. PMID:23390327

Strategies for converting to a DBMS environment

NASA Technical Reports Server (NTRS)

Durban, D. M.

1984-01-01

The conversion to data base management systems processing techniques consists of three different strategies - one for each of the major stages in the development process. Each strategy was chosen for its approach in bringing about a smooth evolutionary type transition from one mode of operation to the next. The initial strategy of the indoctrination stage consisted of: (1) providing maximum access to current administrative data as soon as possible; (2) select and developing small prototype systems; (3) establishing a user information center as a central focal point for user training and assistance; and (4) developing a training program for programmers, management and ad hoc users in DBMS application and utilization. Security, the rate of the data dictionary, and data base tuning and capacity planning, and the development of a change of attitude in an automated office are issues meriting consideration.

Space and transatmospheric propulsion technology

NASA Technical Reports Server (NTRS)

Merkle, Charles; Stangeland, Maynard L.; Brown, James R.; Mccarty, John P.; Povinelli, Louis A.; Northam, G. Burton; Zukoski, Edward E.

1994-01-01

This report focuses primarily on Japan's programs in liquid rocket propulsion and propulsion for spaceplane and related transatmospheric areas. It refers briefly to Japan's solid rocket programs and to new supersonic air-breathing propulsion efforts. The panel observed that the Japanese had a carefully thought-out plan, a broad-based program, and an ambitious but achievable schedule for propulsion activity. Japan's overall propulsion program is behind that of the United States at the time of this study, but the Japanese are gaining rapidly. The Japanese are at the forefront in such key areas as advanced materials, enjoying a high level of project continuity and funding. Japan's space program has been evolutionary in nature, while the U.S. program has emphasized revolutionary advances. Projects have typically been smaller in Japan than in the United States, focusing on incremental advances in technology, with an excellent record of applying proven technology to new projects. This evolutionary approach, coupled with an ability to take technology off the shelf from other countries, has resulted in relatively low development costs, rapid progress, and enhanced reliability. Clearly Japan is positioned to be a world leader in space and transatmospheric propulsion technology by the year 2000.

Prediction of Layer Thickness in Molten Borax Bath with Genetic Evolutionary Programming

NASA Astrophysics Data System (ADS)

Taylan, Fatih

2011-04-01

In this study, the vanadium carbide coating in molten borax bath process is modeled by evolutionary genetic programming (GEP) with bath composition (borax percentage, ferro vanadium (Fe-V) percentage, boric acid percentage), bath temperature, immersion time, and layer thickness data. Five inputs and one output data exist in the model. The percentage of borax, Fe-V, and boric acid, temperature, and immersion time parameters are used as input data and the layer thickness value is used as output data. For selected bath components, immersion time, and temperature variables, the layer thicknesses are derived from the mathematical expression. The results of the mathematical expressions are compared to that of experimental data; it is determined that the derived mathematical expression has an accuracy of 89%.

New paradigms in clonal evolution: punctuated equilibrium in cancer.

PubMed

Cross, William Ch; Graham, Trevor A; Wright, Nicholas A

2016-10-01

Evolutionary theories are themselves subject to evolution. Clonal evolution - the model that describes the initiation and progression of cancer - is entering a period of profound change, brought about largely by technological developments in genome analysis. A flurry of recent publications, using modern mathematical and bioinformatics techniques, have revealed both punctuated and neutral evolution phenomena that are poorly explained by the conventional graduated perspectives. In this review, we propose that a hybrid model, inspired by the evolutionary model of punctuated equilibrium, could better explain these recent observations. We also discuss the conceptual changes and clinical implications of variable evolutionary tempos. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Knowing the natural world: The construction of knowledge about evolution in and out of the classroom

NASA Astrophysics Data System (ADS)

Perkins, Alison Emily Havard

Evolution is a central underlying concept to a significant number of discourses in civilized society, but the complexity of understanding basic tenets of this important theory is just now coming to light. Knowledge about evolution is constructed from both formal and "free-choice" opportunities, like television. Nature programs are commonly considered "educational" by definition, but research indicates the narratives often promote creationist ideas about this important process in biology. I explored how nature programs influenced knowledge construction about evolutionary theory using a combination of qualitative and quantitative approaches. Because misconceptions about evolution are common, I examined how students' conceptual ecologies changed in response to information presented in an example of a particularly poor nature film narrative. Students' held a diversity of misconceptions, proximate conceptions, and evolutionary conceptions simultaneously, and many of their responses were direct reflections of the nature program. As a result, I incorporated the same nature program into an experiment designed to examine the effects of narrative and imagery on evolution understanding. After completing an extensive pre-assessment that addressed attitudes and beliefs about science knowledge, students viewed one of four versions of the nature program that varied in the quality of science and imagery presented. The effect of watching different versions was only vaguely apparent in students with a moderate understanding of evolution. The relationship was much more complex among students with a poor understanding of evolution but suggested a negative effect that was more influenced by public discourses about this "controversial" subject than conceptual understanding. The relationships warranted examining learning from the perspective of the consumers of these programs. I surveyed audience beliefs about the educational value of nature programs and found that an overwhelming majority believed the programs were "educational" and designed to teach about nature. The results were particularly alarming because beliefs about the educational value may strongly impact learning outcomes. An informal survey of nature programs aired during a "sweeps" month indicated that poor presentation of science, and specifically evolutionary theory, was indeed the norm. Indeed, nature programs may be contributing to the "deconstruction" of knowledge about evolution both in and out of the classroom.

Constraints in Genetic Programming

NASA Technical Reports Server (NTRS)

Janikow, Cezary Z.

1996-01-01

Genetic programming refers to a class of genetic algorithms utilizing generic representation in the form of program trees. For a particular application, one needs to provide the set of functions, whose compositions determine the space of program structures being evolved, and the set of terminals, which determine the space of specific instances of those programs. The algorithm searches the space for the best program for a given problem, applying evolutionary mechanisms borrowed from nature. Genetic algorithms have shown great capabilities in approximately solving optimization problems which could not be approximated or solved with other methods. Genetic programming extends their capabilities to deal with a broader variety of problems. However, it also extends the size of the search space, which often becomes too large to be effectively searched even by evolutionary methods. Therefore, our objective is to utilize problem constraints, if such can be identified, to restrict this space. In this publication, we propose a generic constraint specification language, powerful enough for a broad class of problem constraints. This language has two elements -- one reduces only the number of program instances, the other reduces both the space of program structures as well as their instances. With this language, we define the minimal set of complete constraints, and a set of operators guaranteeing offspring validity from valid parents. We also show that these operators are not less efficient than the standard genetic programming operators if one preprocesses the constraints - the necessary mechanisms are identified.

Evolutionary Scheduler for the Deep Space Network

NASA Technical Reports Server (NTRS)

Guillaume, Alexandre; Lee, Seungwon; Wang, Yeou-Fang; Zheng, Hua; Chau, Savio; Tung, Yu-Wen; Terrile, Richard J.; Hovden, Robert

2010-01-01

A computer program assists human schedulers in satisfying, to the maximum extent possible, competing demands from multiple spacecraft missions for utilization of the transmitting/receiving Earth stations of NASA s Deep Space Network. The program embodies a concept of optimal scheduling to attain multiple objectives in the presence of multiple constraints.

Irrigation water allocation optimization using multi-objective evolutionary algorithm (MOEA) - a review

NASA Astrophysics Data System (ADS)

Fanuel, Ibrahim Mwita; Mushi, Allen; Kajunguri, Damian

2018-03-01

This paper analyzes more than 40 papers with a restricted area of application of Multi-Objective Genetic Algorithm, Non-Dominated Sorting Genetic Algorithm-II and Multi-Objective Differential Evolution (MODE) to solve the multi-objective problem in agricultural water management. The paper focused on different application aspects which include water allocation, irrigation planning, crop pattern and allocation of available land. The performance and results of these techniques are discussed. The review finds that there is a potential to use MODE to analyzed the multi-objective problem, the application is more significance due to its advantage of being simple and powerful technique than any Evolutionary Algorithm. The paper concludes with the hopeful new trend of research that demand effective use of MODE; inclusion of benefits derived from farm byproducts and production costs into the model.

The Comet Cometh: Evolving Developmental Systems.

PubMed

Jaeger, Johannes; Laubichler, Manfred; Callebaut, Werner

In a recent opinion piece, Denis Duboule has claimed that the increasing shift towards systems biology is driving evolutionary and developmental biology apart, and that a true reunification of these two disciplines within the framework of evolutionary developmental biology (EvoDevo) may easily take another 100 years. He identifies methodological, epistemological, and social differences as causes for this supposed separation. Our article provides a contrasting view. We argue that Duboule's prediction is based on a one-sided understanding of systems biology as a science that is only interested in functional, not evolutionary, aspects of biological processes. Instead, we propose a research program for an evolutionary systems biology, which is based on local exploration of the configuration space in evolving developmental systems. We call this approach-which is based on reverse engineering, simulation, and mathematical analysis-the natural history of configuration space. We discuss a number of illustrative examples that demonstrate the past success of local exploration, as opposed to global mapping, in different biological contexts. We argue that this pragmatic mode of inquiry can be extended and applied to the mathematical analysis of the developmental repertoire and evolutionary potential of evolving developmental mechanisms and that evolutionary systems biology so conceived provides a pragmatic epistemological framework for the EvoDevo synthesis.

Creating ensembles of oblique decision trees with evolutionary algorithms and sampling

DOEpatents

Cantu-Paz, Erick [Oakland, CA; Kamath, Chandrika [Tracy, CA

2006-06-13

A decision tree system that is part of a parallel object-oriented pattern recognition system, which in turn is part of an object oriented data mining system. A decision tree process includes the step of reading the data. If necessary, the data is sorted. A potential split of the data is evaluated according to some criterion. An initial split of the data is determined. The final split of the data is determined using evolutionary algorithms and statistical sampling techniques. The data is split. Multiple decision trees are combined in ensembles.

Evolution and diversification of the Toxicofera reptile venom system.

PubMed

Fry, Bryan G; Vidal, Nicolas; van der Weerd, Louise; Kochva, Elazar; Renjifo, Camila

2009-03-06

The diversification of the reptile venom system has been an area of major research but of great controversy. In this review we examine the historical and modern-day efforts of all aspects of the venom system including dentition, glands and secreted toxins and highlight areas of future research opportunities. We use multidisciplinary techniques, including magnetic resonance imaging of venom glands through to molecular phylogenetic reconstruction of toxin evolutionary history, to illustrate the diversity within this integrated weapons system and map the timing of toxin recruitment events over the toxicoferan organismal evolutionary tree.

Evolutionary algorithm for optimization of nonimaging Fresnel lens geometry.

PubMed

Yamada, N; Nishikawa, T

2010-06-21

In this study, an evolutionary algorithm (EA), which consists of genetic and immune algorithms, is introduced to design the optical geometry of a nonimaging Fresnel lens; this lens generates the uniform flux concentration required for a photovoltaic cell. Herein, a design procedure that incorporates a ray-tracing technique in the EA is described, and the validity of the design is demonstrated. The results show that the EA automatically generated a unique geometry of the Fresnel lens; the use of this geometry resulted in better uniform flux concentration with high optical efficiency.

Phylomemetics—Evolutionary Analysis beyond the Gene

PubMed Central

Howe, Christopher J.; Windram, Heather F.

2011-01-01

Genes are propagated by error-prone copying, and the resulting variation provides the basis for phylogenetic reconstruction of evolutionary relationships. Horizontal gene transfer may be superimposed on a tree-like evolutionary pattern, with some relationships better depicted as networks. The copying of manuscripts by scribes is very similar to the replication of genes, and phylogenetic inference programs can be used directly for reconstructing the copying history of different versions of a manuscript text. Phylogenetic methods have also been used for some time to analyse the evolution of languages and the development of physical cultural artefacts. These studies can help to answer a range of anthropological questions. We propose the adoption of the term “phylomemetics” for phylogenetic analysis of reproducing non-genetic elements. PMID:21655311

Vibration Attenuation of the NASA Langley Evolutionary Structure Experiment Using H(infinity) and Structured Singular Value (mu) Robust Multivariable Control Techniques

NASA Technical Reports Server (NTRS)

Balas, Gary J.

1996-01-01

This final report summarizes the research results under NASA Contract NAG-1-1254 from May, 1991 - April, 1995. The main contribution of this research are in the areas of control of flexible structures, model validation, optimal control analysis and synthesis techniques, and use of shape memory alloys for structural damping.

Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation

PubMed Central

2018-01-01

Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site. PMID:29370230

Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation.

PubMed

Illias, Hazlee Azil; Zhao Liang, Wee

2018-01-01

Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site.

Comparative modeling of coevolution in communities of unicellular organisms: adaptability and biodiversity.

PubMed

Lashin, Sergey A; Suslov, Valentin V; Matushkin, Yuri G

2010-06-01

We propose an original program "Evolutionary constructor" that is capable of computationally efficient modeling of both population-genetic and ecological problems, combining these directions in one model of required detail level. We also present results of comparative modeling of stability, adaptability and biodiversity dynamics in populations of unicellular haploid organisms which form symbiotic ecosystems. The advantages and disadvantages of two evolutionary strategies of biota formation--a few generalists' taxa-based biota formation and biodiversity-based biota formation--are discussed.

Generative Representations for Automated Design of Robots

NASA Technical Reports Server (NTRS)

Homby, Gregory S.; Lipson, Hod; Pollack, Jordan B.

2007-01-01

A method of automated design of complex, modular robots involves an evolutionary process in which generative representations of designs are used. The term generative representations as used here signifies, loosely, representations that consist of or include algorithms, computer programs, and the like, wherein encoded designs can reuse elements of their encoding and thereby evolve toward greater complexity. Automated design of robots through synthetic evolutionary processes has already been demonstrated, but it is not clear whether genetically inspired search algorithms can yield designs that are sufficiently complex for practical engineering. The ultimate success of such algorithms as tools for automation of design depends on the scaling properties of representations of designs. A nongenerative representation (one in which each element of the encoded design is used at most once in translating to the design) scales linearly with the number of elements. Search algorithms that use nongenerative representations quickly become intractable (search times vary approximately exponentially with numbers of design elements), and thus are not amenable to scaling to complex designs. Generative representations are compact representations and were devised as means to circumvent the above-mentioned fundamental restriction on scalability. In the present method, a robot is defined by a compact programmatic form (its generative representation) and the evolutionary variation takes place on this form. The evolutionary process is an iterative one, wherein each cycle consists of the following steps: 1. Generative representations are generated in an evolutionary subprocess. 2. Each generative representation is a program that, when compiled, produces an assembly procedure. 3. In a computational simulation, a constructor executes an assembly procedure to generate a robot. 4. A physical-simulation program tests the performance of a simulated constructed robot, evaluating the performance according to a fitness criterion to yield a figure of merit that is fed back into the evolutionary subprocess of the next iteration. In comparison with prior approaches to automated evolutionary design of robots, the use of generative representations offers two advantages: First, a generative representation enables the reuse of components in regular and hierarchical ways and thereby serves a systematic means of creating more complex modules out of simpler ones. Second, the evolved generative representation may capture intrinsic properties of the design problem, so that variations in the representations move through the design space more effectively than do equivalent variations in a nongenerative representation. This method has been demonstrated by using it to design some robots that move, variously, by walking, rolling, or sliding. Some of the robots were built (see figure). Although these robots are very simple, in comparison with robots designed by humans, their structures are more regular, modular, hierarchical, and complex than are those of evolved designs of comparable functionality synthesized by use of nongenerative representations.

How hardwired is human behavior?

PubMed

Nicholson, N

1998-01-01

Time and time again managers have tried to eliminate hierarchies, politics, and interorganizational rivalry--but to no avail. Why? Evolutionary psychologists would say that they are working against nature--emotional and behavioral "hardwiring" that is the legacy of our Stone Age ancestors. In this evolutionary psychology primer for executives, Nigel Nicholson explores many of the Science's central tenets. Of course, evolutionary psychology is still an emerging discipline, and its strong connection with the theory of natural selection has sparked significant controversy. But, as Nicholson suggests, evolutionary psychology is now well established enough that its insights into human instinct will prove illuminating to anyone seeking to understand why people act the way they do in organizational settings. Take gossip. According to evolutionary psychology, our Stone Age ancestors needed this skill to survive the socially unpredictable conditions of the Savannah Plain. Thus, over time, the propensity to gossip became part of our mental programming. Executives trying to eradicate gossip at work might as well try to change their employees' musical tastes. Better to put one's energy into making sure the "rumor mill" avoids dishonesty or unkindness as much as possible. Evolutionary psychology also explores the dynamics of the human group. Clans on the Savannah Plain, for example, appear to have had no more than 150 members. The message for managers? People will likely be most effective in small organizational units. As every executive knows, it pays to be an insightful student of human nature. Evolutionary psychology adds another important chapter to consider.

Assessment of Creep Capability of HSR-EPM Turbine Airfoil Alloys

NASA Technical Reports Server (NTRS)

MacKay, Rebecca A.; Garg, Anita; Ritzert, Frank J.; Locci, Ivan E.

2007-01-01

The High Speed Civil Transport (HSCT) mission of the High Speed Research-Enabling Propulsion Materials (HSR-EPM) Program represented a unique challenge for turbine airfoil materials because the highest operating temperatures occur during climb and supersonic cruise. The accumulated hot time of an HSCT engine before overhaul is many thousands of hours. This is significantly different from subsonic engines, where the maximum operating temperatures occur during takeoff and thrust reverse after landing, and the accumulated hot time before overhaul is about 300 hr. The goal of airfoil alloy development under the HSR-EPM Program was to develop an alloy with a 75 F increase in creep rupture capability over the average Rene N5/PWA 1484 baseline. Airfoil alloy development under the HSR-EPM Program pursued a path that led to evolutionary mechanical behavior improvements, resulting from increased amounts of high density, refractory metals. The purpose of the present paper is to describe the experimental work that was performed at NASA Glenn Research Center after the HSR-EPM Program ended. Emphasis will be placed on the creep behavior of coated specimens, as well as on the development and progression of phase instabilities during creep deformation. Mitigation techniques that were used to reduce phase instabilities are also discussed. Most of the work described in this report was performed at NASA Glenn during the years 2000 and 2001.

Evolution of proliferation and the angiogenic switch in tumors with high clonal diversity.

PubMed

Bickel, Scott T; Juliano, Joseph D; Nagy, John D

2014-01-01

Natural selection among tumor cell clones is thought to produce hallmark properties of malignancy. Efforts to understand evolution of one such hallmark--the angiogenic switch--has suggested that selection for angiogenesis can "run away" and generate a hypertumor, a form of evolutionary suicide by extreme vascular hypo- or hyperplasia. This phenomenon is predicted by models of tumor angiogenesis studied with the techniques of adaptive dynamics. These techniques also predict that selection drives tumor proliferative potential towards an evolutionarily stable strategy (ESS) that is also convergence-stable. However, adaptive dynamics are predicated on two key assumptions: (i) no more than two distinct clones or evolutionary strategies can exist in the tumor at any given time; and (ii) mutations cause small phenotypic changes. Here we show, using a stochastic simulation, that relaxation of these assumptions has no effect on the predictions of adaptive dynamics in this case. In particular, selection drives proliferative potential towards, and angiogenic potential away from, their respective ESSs. However, these simulations also show that tumor behavior is highly contingent on mutational history, particularly for angiogenesis. Individual tumors frequently grow to lethal size before the evolutionary endpoint is approached. In fact, most tumor dynamics are predicted to be in the evolutionarily transient regime throughout their natural history, so that clinically, the ESS is often largely irrelevant. In addition, we show that clonal diversity as measured by the Shannon Information Index correlates with the speed of approach to the evolutionary endpoint. This observation dovetails with results showing that clonal diversity in Barrett's esophagus predicts progression to malignancy.

Combining analysis with optimization at Langley Research Center. An evolutionary process

NASA Technical Reports Server (NTRS)

Rogers, J. L., Jr.

1982-01-01

The evolutionary process of combining analysis and optimization codes was traced with a view toward providing insight into the long term goal of developing the methodology for an integrated, multidisciplinary software system for the concurrent analysis and optimization of aerospace structures. It was traced along the lines of strength sizing, concurrent strength and flutter sizing, and general optimization to define a near-term goal for combining analysis and optimization codes. Development of a modular software system combining general-purpose, state-of-the-art, production-level analysis computer programs for structures, aerodynamics, and aeroelasticity with a state-of-the-art optimization program is required. Incorporation of a modular and flexible structural optimization software system into a state-of-the-art finite element analysis computer program will facilitate this effort. This effort results in the software system used that is controlled with a special-purpose language, communicates with a data management system, and is easily modified for adding new programs and capabilities. A 337 degree-of-freedom finite element model is used in verifying the accuracy of this system.

A program to compute the soft Robinson-Foulds distance between phylogenetic networks.

PubMed

Lu, Bingxin; Zhang, Louxin; Leong, Hon Wai

2017-03-14

Over the past two decades, phylogenetic networks have been studied to model reticulate evolutionary events. The relationships among phylogenetic networks, phylogenetic trees and clusters serve as the basis for reconstruction and comparison of phylogenetic networks. To understand these relationships, two problems are raised: the tree containment problem, which asks whether a phylogenetic tree is displayed in a phylogenetic network, and the cluster containment problem, which asks whether a cluster is represented at a node in a phylogenetic network. Both the problems are NP-complete. A fast exponential-time algorithm for the cluster containment problem on arbitrary networks is developed and implemented in C. The resulting program is further extended into a computer program for fast computation of the Soft Robinson-Foulds distance between phylogenetic networks. Two computer programs are developed for facilitating reconstruction and validation of phylogenetic network models in evolutionary and comparative genomics. Our simulation tests indicated that they are fast enough for use in practice. Additionally, the distribution of the Soft Robinson-Foulds distance between phylogenetic networks is demonstrated to be unlikely normal by our simulation data.

Assessing the determinants of evolutionary rates in the presence of noise.

PubMed

Plotkin, Joshua B; Fraser, Hunter B

2007-05-01

Although protein sequences are known to evolve at vastly different rates, little is known about what determines their rate of evolution. However, a recent study using principal component regression (PCR) has concluded that evolutionary rates in yeast are primarily governed by a single determinant related to translation frequency. Here, we demonstrate that noise in biological data can confound PCRs, leading to spurious conclusions. When equalizing noise levels across 7 predictor variables used in previous studies, we find no evidence that protein evolution is dominated by a single determinant. Our results indicate that a variety of factors--including expression level, gene dispensability, and protein-protein interactions--may independently affect evolutionary rates in yeast. More accurate measurements or more sophisticated statistical techniques will be required to determine which one, if any, of these factors dominates protein evolution.

Evolutionary synthesis of simple stellar populations. Colours and indices

NASA Astrophysics Data System (ADS)

Kurth, O. M.; Fritze-v. Alvensleben, U.; Fricke, K. J.

1999-07-01

We construct evolutionary synthesis models for simple stellar populations using the evolutionary tracks from the Padova group (1993, 1994), theoretical colour calibrations from \\cite[Lejeune et al. (1997, 1998)]{lejeune} and fit functions for stellar atmospheric indices from \\cite[Worthey et al. (1994)]{worthey}. A Monte-Carlo technique allows us to obtain a smooth time evolution of both broad band colours in UBVRIK and a series of stellar absorption features for Single Burst Stellar Populations (SSPs). We present colours and indices for SSPs with ages from 1 \\ 10(9) yrs to 1.6 \\ 10(10) yrs and metallicities [M/H]=-2.3, -1.7, -0.7, -0.4, 0.0 and 0.4. Model colours and indices at an age of about a Hubble time are in good agreement with observed colours and indices of the Galactic and M 31 GCs.

An Effective Hybrid Evolutionary Algorithm for Solving the Numerical Optimization Problems

NASA Astrophysics Data System (ADS)

Qian, Xiaohong; Wang, Xumei; Su, Yonghong; He, Liu

2018-04-01

There are many different algorithms for solving complex optimization problems. Each algorithm has been applied successfully in solving some optimization problems, but not efficiently in other problems. In this paper the Cauchy mutation and the multi-parent hybrid operator are combined to propose a hybrid evolutionary algorithm based on the communication (Mixed Evolutionary Algorithm based on Communication), hereinafter referred to as CMEA. The basic idea of the CMEA algorithm is that the initial population is divided into two subpopulations. Cauchy mutation operators and multiple paternal crossover operators are used to perform two subpopulations parallelly to evolve recursively until the downtime conditions are met. While subpopulation is reorganized, the individual is exchanged together with information. The algorithm flow is given and the performance of the algorithm is compared using a number of standard test functions. Simulation results have shown that this algorithm converges significantly faster than FEP (Fast Evolutionary Programming) algorithm, has good performance in global convergence and stability and is superior to other compared algorithms.

The Growth of Developmental Thought: Implications for a New Evolutionary Psychology

PubMed Central

Lickliter, Robert

2009-01-01

Evolution has come to be increasingly discussed in terms of changes in developmental processes rather than simply in terms of changes in gene frequencies. This shift is based in large part on the recognition that since all phenotypic traits arise during ontogeny as products of individual development, a primary basis for evolutionary change must be variations in the patterns and processes of development. Further, the products of development are epigenetic, not just genetic, and this is the case even when considering the evolutionary process. These insights have led investigators to reconsider the established notion of genes as the primary cause of development, opening the door to research programs focused on identifying how genetic and non-genetic factors coact to guide and constrain the process of development and its outcomes. I explore this growth of developmental thought and its implications for the achievement of a unified theory of heredity, development, and evolution and consider its implications for the realization of a new, developmentally-based evolutionary psychology. PMID:19956346

Evolutionary Algorithms for Boolean Functions in Diverse Domains of Cryptography.

PubMed

Picek, Stjepan; Carlet, Claude; Guilley, Sylvain; Miller, Julian F; Jakobovic, Domagoj

2016-01-01

The role of Boolean functions is prominent in several areas including cryptography, sequences, and coding theory. Therefore, various methods for the construction of Boolean functions with desired properties are of direct interest. New motivations on the role of Boolean functions in cryptography with attendant new properties have emerged over the years. There are still many combinations of design criteria left unexplored and in this matter evolutionary computation can play a distinct role. This article concentrates on two scenarios for the use of Boolean functions in cryptography. The first uses Boolean functions as the source of the nonlinearity in filter and combiner generators. Although relatively well explored using evolutionary algorithms, it still presents an interesting goal in terms of the practical sizes of Boolean functions. The second scenario appeared rather recently where the objective is to find Boolean functions that have various orders of the correlation immunity and minimal Hamming weight. In both these scenarios we see that evolutionary algorithms are able to find high-quality solutions where genetic programming performs the best.

Evolutionary Design and Simulation of a Tube Crawling Inspection Robot

NASA Technical Reports Server (NTRS)

Craft, Michael; Howsman, Tom; ONeil, Daniel; Howell, Joe T. (Technical Monitor)

2002-01-01

The Space Robotics Assembly Team Simulation (SpaceRATS) is an expansive concept that will hopefully lead to a space flight demonstration of a robotic team cooperatively assembling a system from its constitutive parts. A primary objective of the SpaceRATS project is to develop a generalized evolutionary design approach for multiple classes of robots. The portion of the overall SpaceRats program associated with the evolutionary design and simulation of an inspection robot's morphology is the subject of this paper. The vast majority of this effort has concentrated on the use and modification of Darwin2K, a robotic design and simulation software package, to analyze the design of a tube crawling robot. This robot is designed for carrying out inspection duties in relatively inaccessible locations within a liquid rocket engine similar to the SSME. A preliminary design of the tube crawler robot was completed, and the mechanical dynamics of the system were simulated. An evolutionary approach to optimizing a few parameters of the system was utilized, resulting in a more optimum design.

A new evolutionary system for evolving artificial neural networks.

PubMed

Yao, X; Liu, Y

1997-01-01

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

Mission building blocks for outer solar system exploration.

NASA Technical Reports Server (NTRS)

Herman, D.; Tarver, P.; Moore, J.

1973-01-01

Description of the technological building blocks required for exploring the outer planets with maximum scientific yields under stringent resource constraints. Two generic spacecraft types are considered: the Mariner and the Pioneer. Following a discussion of the outer planet mission constraints, the evolutionary development of spacecraft, probes, and propulsion building blocks is presented. Then, program genealogies are shown for Pioneer and Mariner missions and advanced propulsion systems to illustrate the soundness of a program based on spacecraft modification rather than on the development of new spacecraft for each mission. It is argued that, for minimum costs, technological advancement should occur in an evolutionary manner from mission to mission. While this strategy is likely to result in compromises on specific missions, the realization of the overall objectives calls for an advance commitment to the entire mission series.

Modeling Open Architecture and Evolutionary Acquisition: Implementation Lessons from the ARCI Program for the Rapid Capability Insertion Process

DTIC Science & Technology

2009-04-22

Implementation Issues Another RCIP implementation risk is program management burnout . The ACRI program manager specifically identified the potential...of burnout in his program management team due to the repeated, intense Integration phases. To investigate the possibility and severity of this risk to...the ACRI simulation. This suggests that the burnout risk will be larger for RCIP than it was for ACRI. Successfully implementing a sustainable RCIP

Crossover versus mutation: a comparative analysis of the evolutionary strategy of genetic algorithms applied to combinatorial optimization problems.

PubMed

Osaba, E; Carballedo, R; Diaz, F; Onieva, E; de la Iglesia, I; Perallos, A

2014-01-01

Since their first formulation, genetic algorithms (GAs) have been one of the most widely used techniques to solve combinatorial optimization problems. The basic structure of the GAs is known by the scientific community, and thanks to their easy application and good performance, GAs are the focus of a lot of research works annually. Although throughout history there have been many studies analyzing various concepts of GAs, in the literature there are few studies that analyze objectively the influence of using blind crossover operators for combinatorial optimization problems. For this reason, in this paper a deep study on the influence of using them is conducted. The study is based on a comparison of nine techniques applied to four well-known combinatorial optimization problems. Six of the techniques are GAs with different configurations, and the remaining three are evolutionary algorithms that focus exclusively on the mutation process. Finally, to perform a reliable comparison of these results, a statistical study of them is made, performing the normal distribution z-test.

Crossover versus Mutation: A Comparative Analysis of the Evolutionary Strategy of Genetic Algorithms Applied to Combinatorial Optimization Problems

PubMed Central

Osaba, E.; Carballedo, R.; Diaz, F.; Onieva, E.; de la Iglesia, I.; Perallos, A.

2014-01-01

Since their first formulation, genetic algorithms (GAs) have been one of the most widely used techniques to solve combinatorial optimization problems. The basic structure of the GAs is known by the scientific community, and thanks to their easy application and good performance, GAs are the focus of a lot of research works annually. Although throughout history there have been many studies analyzing various concepts of GAs, in the literature there are few studies that analyze objectively the influence of using blind crossover operators for combinatorial optimization problems. For this reason, in this paper a deep study on the influence of using them is conducted. The study is based on a comparison of nine techniques applied to four well-known combinatorial optimization problems. Six of the techniques are GAs with different configurations, and the remaining three are evolutionary algorithms that focus exclusively on the mutation process. Finally, to perform a reliable comparison of these results, a statistical study of them is made, performing the normal distribution z-test. PMID:25165731

Robust image registration for multiple exposure high dynamic range image synthesis

NASA Astrophysics Data System (ADS)

Yao, Susu

2011-03-01

Image registration is an important preprocessing technique in high dynamic range (HDR) image synthesis. This paper proposed a robust image registration method for aligning a group of low dynamic range images (LDR) that are captured with different exposure times. Illumination change and photometric distortion between two images would result in inaccurate registration. We propose to transform intensity image data into phase congruency to eliminate the effect of the changes in image brightness and use phase cross correlation in the Fourier transform domain to perform image registration. Considering the presence of non-overlapped regions due to photometric distortion, evolutionary programming is applied to search for the accurate translation parameters so that the accuracy of registration is able to be achieved at a hundredth of a pixel level. The proposed algorithm works well for under and over-exposed image registration. It has been applied to align LDR images for synthesizing high quality HDR images..

Influence of TCSC Devices on Congestion Management in a Deregulated Power System Using Evolutionary Programming Technique

NASA Astrophysics Data System (ADS)

Ananthichristy, A., Dr.; Elanthirayan, R.; Brindha, R., Dr.; Siddhiq, M. S.; Venkatesh, N.; Harshit, M. V.; Nikhilreddy, M.

2018-04-01

Congestion management is one of the technical challenges in power system deregulation. In deregulated electricity market it may always not be possible to dispatch all of the contracted power transactions due to congestion of the transmission corridors. Transmission congestion occurs when there is insufficient transmission capacity to simultaneously accommodate all constraints for transmission of a line. Flexible Alternative Current Transmission System (FACTS) devices can be an alternative to reduce the flows in the heavily loaded lines, resulting in an increased loadability, low system loss, improved stability of the network, reduced cost of production and fulfilled contractual requirement by controlling the power flow in the network. A method to determine the optimal location of FACTS has been suggested based on reduction of total system VAR power losses. The simulation was done on IEEE 14 bus system and results were obtained.

Archeological insights into hominin cognitive evolution.

PubMed

Wynn, Thomas; Coolidge, Frederick L

2016-07-01

How did the human mind evolve? How and when did we come to think in the ways we do? The last thirty years have seen an explosion in research related to the brain and cognition. This research has encompassed a range of biological and social sciences, from epigenetics and cognitive neuroscience to social and developmental psychology. Following naturally on this efflorescence has been a heightened interest in the evolution of the brain and cognition. Evolutionary scholars, including paleoanthropologists, have deployed the standard array of evolutionary methods. Ethological and experimental evidence has added significantly to our understanding of nonhuman brains and cognition, especially those of nonhuman primates. Studies of fossil brains through endocasts and sophisticated imaging techniques have revealed evolutionary changes in gross neural anatomy. Psychologists have also gotten into the game through application of reverse engineering to experimentally based descriptions of cognitive functions. For hominin evolution, there is another rich source of evidence of cognition, the archeological record. Using the methods of Paleolithic archeology and the theories and models of cognitive science, evolutionary cognitive archeology documents developments in the hominin mind that would otherwise be inaccessible. © 2016 Wiley Periodicals, Inc.

Decentralized diagnostics based on a distributed micro-genetic algorithm for transducer networks monitoring large experimental systems.

PubMed

Arpaia, P; Cimmino, P; Girone, M; La Commara, G; Maisto, D; Manna, C; Pezzetti, M

2014-09-01

Evolutionary approach to centralized multiple-faults diagnostics is extended to distributed transducer networks monitoring large experimental systems. Given a set of anomalies detected by the transducers, each instance of the multiple-fault problem is formulated as several parallel communicating sub-tasks running on different transducers, and thus solved one-by-one on spatially separated parallel processes. A micro-genetic algorithm merges evaluation time efficiency, arising from a small-size population distributed on parallel-synchronized processors, with the effectiveness of centralized evolutionary techniques due to optimal mix of exploitation and exploration. In this way, holistic view and effectiveness advantages of evolutionary global diagnostics are combined with reliability and efficiency benefits of distributed parallel architectures. The proposed approach was validated both (i) by simulation at CERN, on a case study of a cold box for enhancing the cryogeny diagnostics of the Large Hadron Collider, and (ii) by experiments, under the framework of the industrial research project MONDIEVOB (Building Remote Monitoring and Evolutionary Diagnostics), co-funded by EU and the company Del Bo srl, Napoli, Italy.

An Evolutionary Algorithm for Fast Intensity Based Image Matching Between Optical and SAR Satellite Imagery

NASA Astrophysics Data System (ADS)

Fischer, Peter; Schuegraf, Philipp; Merkle, Nina; Storch, Tobias

2018-04-01

This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR) optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search) and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.

The extended evolutionary synthesis: its structure, assumptions and predictions

PubMed Central

Laland, Kevin N.; Uller, Tobias; Feldman, Marcus W.; Sterelny, Kim; Müller, Gerd B.; Moczek, Armin; Jablonka, Eva; Odling-Smee, John

2015-01-01

Scientific activities take place within the structured sets of ideas and assumptions that define a field and its practices. The conceptual framework of evolutionary biology emerged with the Modern Synthesis in the early twentieth century and has since expanded into a highly successful research program to explore the processes of diversification and adaptation. Nonetheless, the ability of that framework satisfactorily to accommodate the rapid advances in developmental biology, genomics and ecology has been questioned. We review some of these arguments, focusing on literatures (evo-devo, developmental plasticity, inclusive inheritance and niche construction) whose implications for evolution can be interpreted in two ways—one that preserves the internal structure of contemporary evolutionary theory and one that points towards an alternative conceptual framework. The latter, which we label the ‘extended evolutionary synthesis' (EES), retains the fundaments of evolutionary theory, but differs in its emphasis on the role of constructive processes in development and evolution, and reciprocal portrayals of causation. In the EES, developmental processes, operating through developmental bias, inclusive inheritance and niche construction, share responsibility for the direction and rate of evolution, the origin of character variation and organism–environment complementarity. We spell out the structure, core assumptions and novel predictions of the EES, and show how it can be deployed to stimulate and advance research in those fields that study or use evolutionary biology. PMID:26246559

Marr's levels and the minimalist program.

PubMed

Johnson, Mark

2017-02-01

A simple change to a cognitive system at Marr's computational level may entail complex changes at the other levels of description of the system. The implementational level complexity of a change, rather than its computational level complexity, may be more closely related to the plausibility of a discrete evolutionary event causing that change. Thus the formal complexity of a change at the computational level may not be a good guide to the plausibility of an evolutionary event introducing that change. For example, while the Minimalist Program's Merge is a simple formal operation (Berwick & Chomsky, 2016), the computational mechanisms required to implement the language it generates (e.g., to parse the language) may be considerably more complex. This has implications for the theory of grammar: theories of grammar which involve several kinds of syntactic operations may be no less evolutionarily plausible than a theory of grammar that involves only one. A deeper understanding of human language at the algorithmic and implementational levels could strengthen Minimalist Program's account of the evolution of language.

Empirical verification of evolutionary theories of aging.

PubMed

Kyryakov, Pavlo; Gomez-Perez, Alejandra; Glebov, Anastasia; Asbah, Nimara; Bruno, Luigi; Meunier, Carolynne; Iouk, Tatiana; Titorenko, Vladimir I

2016-10-25

We recently selected 3 long-lived mutant strains of Saccharomyces cerevisiae by a lasting exposure to exogenous lithocholic acid. Each mutant strain can maintain the extended chronological lifespan after numerous passages in medium without lithocholic acid. In this study, we used these long-lived yeast mutants for empirical verification of evolutionary theories of aging. We provide evidence that the dominant polygenic trait extending longevity of each of these mutants 1) does not affect such key features of early-life fitness as the exponential growth rate, efficacy of post-exponential growth and fecundity; and 2) enhances such features of early-life fitness as susceptibility to chronic exogenous stresses, and the resistance to apoptotic and liponecrotic forms of programmed cell death. These findings validate evolutionary theories of programmed aging. We also demonstrate that under laboratory conditions that imitate the process of natural selection within an ecosystem, each of these long-lived mutant strains is forced out of the ecosystem by the parental wild-type strain exhibiting shorter lifespan. We therefore concluded that yeast cells have evolved some mechanisms for limiting their lifespan upon reaching a certain chronological age. These mechanisms drive the evolution of yeast longevity towards maintaining a finite yeast chronological lifespan within ecosystems.

Atmospheric lidar multi-user instrument system definition study

NASA Technical Reports Server (NTRS)

Greco, R. V. (Editor)

1980-01-01

A spaceborne lidar system for atmospheric studies was defined. The primary input was the Science Objectives Experiment Description and Evolutionary Flow Document. The first task of the study was to perform an experiment evolutionary analysis of the SEED. The second task was the system definition effort of the instrument system. The third task was the generation of a program plan for the hardware phase. The fourth task was the supporting studies which included a Shuttle deficiency analysis, a preliminary safety hazard analysis, the identification of long lead items, and development studies required. As a result of the study an evolutionary Lidar Multi-User Instrument System (MUIS) was defined. The MUIS occupies a full Spacelab pallet and has a weight of 1300 kg. The Lidar MUIS laser provides a 2 joule frequency doubled Nd:YAG laser that can also pump a tuneable dye laser wide frequency range and bandwidth. The MUIS includes a 1.25 meter diameter aperture Cassegrain receiver, with a moveable secondary mirror to provide precise alignment with the laser. The receiver can transmit the return signal to three single and multiple photomultiple tube detectors by use of a rotating fold mirror. It is concluded that the Lidar MUIS proceed to program implementation.

Punctuated equilibrium in the large-scale evolution of programming languages†

PubMed Central

Valverde, Sergi; Solé, Ricard V.

2015-01-01

The analogies and differences between biological and cultural evolution have been explored by evolutionary biologists, historians, engineers and linguists alike. Two well-known domains of cultural change are language and technology. Both share some traits relating the evolution of species, but technological change is very difficult to study. A major challenge in our way towards a scientific theory of technological evolution is how to properly define evolutionary trees or clades and how to weight the role played by horizontal transfer of information. Here, we study the large-scale historical development of programming languages, which have deeply marked social and technological advances in the last half century. We analyse their historical connections using network theory and reconstructed phylogenetic networks. Using both data analysis and network modelling, it is shown that their evolution is highly uneven, marked by innovation events where new languages are created out of improved combinations of different structural components belonging to previous languages. These radiation events occur in a bursty pattern and are tied to novel technological and social niches. The method can be extrapolated to other systems and consistently captures the major classes of languages and the widespread horizontal design exchanges, revealing a punctuated evolutionary path. PMID:25994298

Restart Operator Meta-heuristics for a Problem-Oriented Evolutionary Strategies Algorithm in Inverse Mathematical MISO Modelling Problem Solving

NASA Astrophysics Data System (ADS)

Ryzhikov, I. S.; Semenkin, E. S.

2017-02-01

This study is focused on solving an inverse mathematical modelling problem for dynamical systems based on observation data and control inputs. The mathematical model is being searched in the form of a linear differential equation, which determines the system with multiple inputs and a single output, and a vector of the initial point coordinates. The described problem is complex and multimodal and for this reason the proposed evolutionary-based optimization technique, which is oriented on a dynamical system identification problem, was applied. To improve its performance an algorithm restart operator was implemented.

Evolutionary computing for the design search and optimization of space vehicle power subsystems

NASA Technical Reports Server (NTRS)

Kordon, Mark; Klimeck, Gerhard; Hanks, David; Hua, Hook

2004-01-01

Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment. Out preliminary results demonstrate that this approach has the potential to improve the space system trade study process by allowing engineers to statistically weight subsystem goals of mass, cost and performance then automatically size power elements based on anticipated performance of the subsystem rather than on worst-case estimates.

On the design of neuro-controllers for individual and social learning behaviour in autonomous robots: an evolutionary approach

NASA Astrophysics Data System (ADS)

Pini, Giovanni; Tuci, Elio

2008-06-01

In biology/psychology, the capability of natural organisms to learn from the observation/interaction with conspecifics is referred to as social learning. Roboticists have recently developed an interest in social learning, since it might represent an effective strategy to enhance the adaptivity of a team of autonomous robots. In this study, we show that a methodological approach based on artifcial neural networks shaped by evolutionary computation techniques can be successfully employed to synthesise the individual and social learning mechanisms for robots required to learn a desired action (i.e. phototaxis or antiphototaxis).

Evolution of Aging Theories: Why Modern Programmed Aging Concepts Are Transforming Medical Research.

PubMed

Goldsmith, Theodore C

2016-12-01

Programmed aging refers to the idea that senescence in humans and other organisms is purposely caused by evolved biological mechanisms to obtain an evolutionary advantage. Until recently, programmed aging was considered theoretically impossible because of the mechanics of the evolution process, and medical research was based on the idea that aging was not programmed. Theorists struggled for more than a century in efforts to develop non-programmed theories that fit observations, without obtaining a consensus supporting any non-programmed theory. Empirical evidence of programmed lifespan limitations continued to accumulate. More recently, developments, especially in our understanding of biological inheritance, have exposed major issues and complexities regarding the process of evolution, some of which explicitly enable programmed aging of mammals. Consequently, science-based opposition to programmed aging has dramatically declined. This progression has major implications for medical research, because the theories suggest that very different biological mechanisms are ultimately responsible for highly age-related diseases that now represent most research efforts and health costs. Most particularly, programmed theories suggest that aging per se is a treatable condition and suggest a second path toward treating and preventing age-related diseases that can be exploited in addition to the traditional disease-specific approaches. The theories also make predictions regarding the nature of biological aging mechanisms and therefore suggest research directions. This article discusses developments of evolutionary mechanics, the consequent programmed aging theories, and logical inferences concerning biological aging mechanisms. It concludes that major medical research organizations cannot afford to ignore programmed aging concepts in assigning research resources and directions.

How evolutionary crystal structure prediction works--and why.

PubMed

Oganov, Artem R; Lyakhov, Andriy O; Valle, Mario

2011-03-15

Once the crystal structure of a chemical substance is known, many properties can be predicted reliably and routinely. Therefore if researchers could predict the crystal structure of a material before it is synthesized, they could significantly accelerate the discovery of new materials. In addition, the ability to predict crystal structures at arbitrary conditions of pressure and temperature is invaluable for the study of matter at extreme conditions, where experiments are difficult. Crystal structure prediction (CSP), the problem of finding the most stable arrangement of atoms given only the chemical composition, has long remained a major unsolved scientific problem. Two problems are entangled here: search, the efficient exploration of the multidimensional energy landscape, and ranking, the correct calculation of relative energies. For organic crystals, which contain a few molecules in the unit cell, search can be quite simple as long as a researcher does not need to include many possible isomers or conformations of the molecules; therefore ranking becomes the main challenge. For inorganic crystals, quantum mechanical methods often provide correct relative energies, making search the most critical problem. Recent developments provide useful practical methods for solving the search problem to a considerable extent. One can use simulated annealing, metadynamics, random sampling, basin hopping, minima hopping, and data mining. Genetic algorithms have been applied to crystals since 1995, but with limited success, which necessitated the development of a very different evolutionary algorithm. This Account reviews CSP using one of the major techniques, the hybrid evolutionary algorithm USPEX (Universal Structure Predictor: Evolutionary Xtallography). Using recent developments in the theory of energy landscapes, we unravel the reasons evolutionary techniques work for CSP and point out their limitations. We demonstrate that the energy landscapes of chemical systems have an overall shape and explore their intrinsic dimensionalities. Because of the inverse relationships between order and energy and between the dimensionality and diversity of an ensemble of crystal structures, the chances that a random search will find the ground state decrease exponentially with increasing system size. A well-designed evolutionary algorithm allows for much greater computational efficiency. We illustrate the power of evolutionary CSP through applications that examine matter at high pressure, where new, unexpected phenomena take place. Evolutionary CSP has allowed researchers to make unexpected discoveries such as a transparent phase of sodium, a partially ionic form of boron, complex superconducting forms of calcium, a novel superhard allotrope of carbon, polymeric modifications of nitrogen, and a new class of compounds, perhydrides. These methods have also led to the discovery of novel hydride superconductors including the "impossible" LiH(n) (n=2, 6, 8) compounds, and CaLi(2). We discuss extensions of the method to molecular crystals, systems of variable composition, and the targeted optimization of specific physical properties. © 2011 American Chemical Society

Introducing Evolution to Non-Biology Majors via the Fossil Record: A Case Study from the Israeli High School System.

ERIC Educational Resources Information Center

Dodick, Jeff; Orion, Nir

2003-01-01

Discusses challenges faced in the teaching and learning of evolution. Presents a curricular program and a case study on evolutionary biology. Investigates students' conceptual knowledge after exposure to the program "From Dinosaurs to Darwin," which focuses on fossil records as evidence of evolution. (Contains 32 references.) (YDS)

EEG/ERP adaptive noise canceller design with controlled search space (CSS) approach in cuckoo and other optimization algorithms.

PubMed

Ahirwal, M K; Kumar, Anil; Singh, G K

2013-01-01

This paper explores the migration of adaptive filtering with swarm intelligence/evolutionary techniques employed in the field of electroencephalogram/event-related potential noise cancellation or extraction. A new approach is proposed in the form of controlled search space to stabilize the randomness of swarm intelligence techniques especially for the EEG signal. Swarm-based algorithms such as Particles Swarm Optimization, Artificial Bee Colony, and Cuckoo Optimization Algorithm with their variants are implemented to design optimized adaptive noise canceler. The proposed controlled search space technique is tested on each of the swarm intelligence techniques and is found to be more accurate and powerful. Adaptive noise canceler with traditional algorithms such as least-mean-square, normalized least-mean-square, and recursive least-mean-square algorithms are also implemented to compare the results. ERP signals such as simulated visual evoked potential, real visual evoked potential, and real sensorimotor evoked potential are used, due to their physiological importance in various EEG studies. Average computational time and shape measures of evolutionary techniques are observed 8.21E-01 sec and 1.73E-01, respectively. Though, traditional algorithms take negligible time consumption, but are unable to offer good shape preservation of ERP, noticed as average computational time and shape measure difference, 1.41E-02 sec and 2.60E+00, respectively.

Genetic Regulatory Networks in Embryogenesis and Evolution

NASA Technical Reports Server (NTRS)

1998-01-01

The article introduces a series of papers that were originally presented at a workshop titled Genetic Regulatory Network in Embryogenesis and Evaluation. Contents include the following: evolution of cleavage programs in relationship to axial specification and body plan evolution, changes in cell lineage specification elucidate evolutionary relations in spiralia, axial patterning in the leech: developmental mechanisms and evolutionary implications, hox genes in arthropod development and evolution, heterochronic genes in development and evolution, a common theme for LIM homeobox gene function across phylogeny, and mechanisms of specification in ascidian embryos.

An evolutionary solution to anesthesia automated record keeping.

PubMed

Bicker, A A; Gage, J S; Poppers, P J

1998-08-01

In the course of five years the development of an automated anesthesia record keeper has evolved through nearly a dozen stages, each marked by new features and sophistication. Commodity PC hardware and software minimized development costs. Object oriented analysis, programming and design supported the process of change. In addition, we developed an evolutionary strategy that optimized motivation, risk management, and maximized return on investment. Besides providing record keeping services, the system supports educational and research activities and through a flexible plotting paradigm, supports each anesthesiologist's focus on physiological data during and after anesthesia.

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

USGS Publications Warehouse

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.

Landscaping plant epigenetics.

PubMed

McKeown, Peter C; Spillane, Charles

2014-01-01

The understanding of epigenetic mechanisms is necessary for assessing the potential impacts of epigenetics on plant growth, development and reproduction, and ultimately for the response of these factors to evolutionary pressures and crop breeding programs. This volume highlights the latest in laboratory and bioinformatic techniques used for the investigation of epigenetic phenomena in plants. Such techniques now allow genome-wide analyses of epigenetic regulation and help to advance our understanding of how epigenetic regulatory mechanisms affect cellular and genome function. To set the scene, we begin with a short background of how the field of epigenetics has evolved, with a particular focus on plant epigenetics. We consider what has historically been understood by the term "epigenetics" before turning to the advances in biochemistry, molecular biology, and genetics which have led to current-day definitions of the term. Following this, we pay attention to key discoveries in the field of epigenetics that have emerged from the study of unusual and enigmatic phenomena in plants. Many of these phenomena have involved cases of non-Mendelian inheritance and have often been dismissed as mere curiosities prior to the elucidation of their molecular mechanisms. In the penultimate section, consideration is given to how advances in molecular techniques are opening the doors to a more comprehensive understanding of epigenetic phenomena in plants. We conclude by assessing some opportunities, challenges, and techniques for epigenetic research in both model and non-model plants, in particular for advancing understanding of the regulation of genome function by epigenetic mechanisms.

Regulatory RNA design through evolutionary computation and strand displacement.

PubMed

Rostain, William; Landrain, Thomas E; Rodrigo, Guillermo; Jaramillo, Alfonso

2015-01-01

The discovery and study of a vast number of regulatory RNAs in all kingdoms of life over the past decades has allowed the design of new synthetic RNAs that can regulate gene expression in vivo. Riboregulators, in particular, have been used to activate or repress gene expression. However, to accelerate and scale up the design process, synthetic biologists require computer-assisted design tools, without which riboregulator engineering will remain a case-by-case design process requiring expert attention. Recently, the design of RNA circuits by evolutionary computation and adapting strand displacement techniques from nanotechnology has proven to be suited to the automated generation of DNA sequences implementing regulatory RNA systems in bacteria. Herein, we present our method to carry out such evolutionary design and how to use it to create various types of riboregulators, allowing the systematic de novo design of genetic control systems in synthetic biology.

Genomic investigations of evolutionary dynamics and epistasis in microbial evolution experiments.

PubMed

Jerison, Elizabeth R; Desai, Michael M

2015-12-01

Microbial evolution experiments enable us to watch adaptation in real time, and to quantify the repeatability and predictability of evolution by comparing identical replicate populations. Further, we can resurrect ancestral types to examine changes over evolutionary time. Until recently, experimental evolution has been limited to measuring phenotypic changes, or to tracking a few genetic markers over time. However, recent advances in sequencing technology now make it possible to extensively sequence clones or whole-population samples from microbial evolution experiments. Here, we review recent work exploiting these techniques to understand the genomic basis of evolutionary change in experimental systems. We first focus on studies that analyze the dynamics of genome evolution in microbial systems. We then survey work that uses observations of sequence evolution to infer aspects of the underlying fitness landscape, concentrating on the epistatic interactions between mutations and the constraints these interactions impose on adaptation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evolutionary fuzzy modeling human diagnostic decisions.

PubMed

Peña-Reyes, Carlos Andrés

2004-05-01

Fuzzy CoCo is a methodology, combining fuzzy logic and evolutionary computation, for constructing systems able to accurately predict the outcome of a human decision-making process, while providing an understandable explanation of the underlying reasoning. Fuzzy logic provides a formal framework for constructing systems exhibiting both good numeric performance (accuracy) and linguistic representation (interpretability). However, fuzzy modeling--meaning the construction of fuzzy systems--is an arduous task, demanding the identification of many parameters. To solve it, we use evolutionary computation techniques (specifically cooperative coevolution), which are widely used to search for adequate solutions in complex spaces. We have successfully applied the algorithm to model the decision processes involved in two breast cancer diagnostic problems, the WBCD problem and the Catalonia mammography interpretation problem, obtaining systems both of high performance and high interpretability. For the Catalonia problem, an evolved system was embedded within a Web-based tool-called COBRA-for aiding radiologists in mammography interpretation.

A survey on evolutionary algorithm based hybrid intelligence in bioinformatics.

PubMed

Li, Shan; Kang, Liying; Zhao, Xing-Ming

2014-01-01

With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs) are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks.

A combined NLP-differential evolution algorithm approach for the optimization of looped water distribution systems

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.

2011-08-01

This paper proposes a novel optimization approach for the least cost design of looped water distribution systems (WDSs). Three distinct steps are involved in the proposed optimization approach. In the first step, the shortest-distance tree within the looped network is identified using the Dijkstra graph theory algorithm, for which an extension is proposed to find the shortest-distance tree for multisource WDSs. In the second step, a nonlinear programming (NLP) solver is employed to optimize the pipe diameters for the shortest-distance tree (chords of the shortest-distance tree are allocated the minimum allowable pipe sizes). Finally, in the third step, the original looped water network is optimized using a differential evolution (DE) algorithm seeded with diameters in the proximity of the continuous pipe sizes obtained in step two. As such, the proposed optimization approach combines the traditional deterministic optimization technique of NLP with the emerging evolutionary algorithm DE via the proposed network decomposition. The proposed methodology has been tested on four looped WDSs with the number of decision variables ranging from 21 to 454. Results obtained show the proposed approach is able to find optimal solutions with significantly less computational effort than other optimization techniques.

Affective Neuronal Selection: The Nature of the Primordial Emotion Systems

PubMed Central

Toronchuk, Judith A.; Ellis, George F. R.

2013-01-01

Based on studies in affective neuroscience and evolutionary psychiatry, a tentative new proposal is made here as to the nature and identification of primordial emotional systems. Our model stresses phylogenetic origins of emotional systems, which we believe is necessary for a full understanding of the functions of emotions and additionally suggests that emotional organizing systems play a role in sculpting the brain during ontogeny. Nascent emotional systems thus affect cognitive development. A second proposal concerns two additions to the affective systems identified by Panksepp. We suggest there is substantial evidence for a primary emotional organizing program dealing with power, rank, dominance, and subordination which instantiates competitive and territorial behavior and is an evolutionary contributor to self-esteem in humans. A program underlying disgust reactions which originally functioned in ancient vertebrates to protect against infection and toxins is also suggested. PMID:23316177

Can An Evolutionary Process Create English Text?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bailey, David H.

Critics of the conventional theory of biological evolution have asserted that while natural processes might result in some limited diversity, nothing fundamentally new can arise from 'random' evolution. In response, biologists such as Richard Dawkins have demonstrated that a computer program can generate a specific short phrase via evolution-like iterations starting with random gibberish. While such demonstrations are intriguing, they are flawed in that they have a fixed, pre-specified future target, whereas in real biological evolution there is no fixed future target, but only a complicated 'fitness landscape'. In this study, a significantly more sophisticated evolutionary scheme is employed tomore » produce text segments reminiscent of a Charles Dickens novel. The aggregate size of these segments is larger than the computer program and the input Dickens text, even when comparing compressed data (as a measure of information content).« less

MySSP: Non-stationary evolutionary sequence simulation, including indels

PubMed Central

Rosenberg, Michael S.

2007-01-01

MySSP is a new program for the simulation of DNA sequence evolution across a phylogenetic tree. Although many programs are available for sequence simulation, MySSP is unique in its inclusion of indels, flexibility in allowing for non-stationary patterns, and output of ancestral sequences. Some of these features can individually be found in existing programs, but have not all have been previously available in a single package. PMID:19325855

The 25 kW power module evolution study. Part 3: Conceptual designs for power module evolution. Volume 2: Program plans

NASA Technical Reports Server (NTRS)

1979-01-01

A plan is presented for the evolutionary development and deployment of the power module system with performance capabilities required to support the 1983 to 1990 user requirements. Aspects summarized include program functional, operational, and hardware elements; program work breakdown and specification items; development plans and schedules for developmental and technology milestones; test concepts and timeliness; and ground and orbit operations concepts.

Detecting and Analyzing Genetic Recombination Using RDP4.

PubMed

Martin, Darren P; Murrell, Ben; Khoosal, Arjun; Muhire, Brejnev

2017-01-01

Recombination between nucleotide sequences is a major process influencing the evolution of most species on Earth. The evolutionary value of recombination has been widely debated and so too has its influence on evolutionary analysis methods that assume nucleotide sequences replicate without recombining. When nucleic acids recombine, the evolution of the daughter or recombinant molecule cannot be accurately described by a single phylogeny. This simple fact can seriously undermine the accuracy of any phylogenetics-based analytical approach which assumes that the evolutionary history of a set of recombining sequences can be adequately described by a single phylogenetic tree. There are presently a large number of available methods and associated computer programs for analyzing and characterizing recombination in various classes of nucleotide sequence datasets. Here we examine the use of some of these methods to derive and test recombination hypotheses using multiple sequence alignments.

IDEA: Interactive Display for Evolutionary Analyses.

PubMed

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.

IDEA: Interactive Display for Evolutionary Analyses

PubMed Central

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

2008-01-01

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. PMID:19061522

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

PubMed

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 quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks.

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

PubMed Central

2014-01-01

Background 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. Results 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. Conclusions 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 quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks. PMID:24428926

Heat Transfer Search Algorithm for Non-convex Economic Dispatch Problems

NASA Astrophysics Data System (ADS)

Hazra, Abhik; Das, Saborni; Basu, Mousumi

2018-06-01

This paper presents Heat Transfer Search (HTS) algorithm for the non-linear economic dispatch problem. HTS algorithm is based on the law of thermodynamics and heat transfer. The proficiency of the suggested technique has been disclosed on three dissimilar complicated economic dispatch problems with valve point effect; prohibited operating zone; and multiple fuels with valve point effect. Test results acquired from the suggested technique for the economic dispatch problem have been fitted to that acquired from other stated evolutionary techniques. It has been observed that the suggested HTS carry out superior solutions.

Heat Transfer Search Algorithm for Non-convex Economic Dispatch Problems

NASA Astrophysics Data System (ADS)

Hazra, Abhik; Das, Saborni; Basu, Mousumi

2018-03-01

This paper presents Heat Transfer Search (HTS) algorithm for the non-linear economic dispatch problem. HTS algorithm is based on the law of thermodynamics and heat transfer. The proficiency of the suggested technique has been disclosed on three dissimilar complicated economic dispatch problems with valve point effect; prohibited operating zone; and multiple fuels with valve point effect. Test results acquired from the suggested technique for the economic dispatch problem have been fitted to that acquired from other stated evolutionary techniques. It has been observed that the suggested HTS carry out superior solutions.

Divergent Evolutionary Patterns of NAC Transcription Factors Are Associated with Diversification and Gene Duplications in Angiosperm

PubMed Central

Jin, Xiaoli; Ren, Jing; Nevo, Eviatar; Yin, Xuegui; Sun, Dongfa; Peng, Junhua

2017-01-01

NAC (NAM/ATAF/CUC) proteins constitute one of the biggest plant-specific transcription factor (TF) families and have crucial roles in diverse developmental programs during plant growth. Phylogenetic analyses have revealed both conserved and lineage-specific NAC subfamilies, among which various origins and distinct features were observed. It is reasonable to hypothesize that there should be divergent evolutionary patterns of NAC TFs both between dicots and monocots, and among NAC subfamilies. In this study, we compared the gene duplication and loss, evolutionary rate, and selective pattern among non-lineage specific NAC subfamilies, as well as those between dicots and monocots, through genome-wide analyses of sequence and functional data in six dicot and five grass lineages. The number of genes gained in the dicot lineages was much larger than that in the grass lineages, while fewer gene losses were observed in the grass than that in the dicots. We revealed (1) uneven constitution of Clusters of Orthologous Groups (COGs) and contrasting birth/death rates among subfamilies, and (2) two distinct evolutionary scenarios of NAC TFs between dicots and grasses. Our results demonstrated that relaxed selection, resulting from concerted gene duplications, may have permitted substitutions responsible for functional divergence of NAC genes into new lineages. The underlying mechanism of distinct evolutionary fates of NAC TFs shed lights on how evolutionary divergence contributes to differences in establishing NAC gene subfamilies and thus impacts the distinct features between dicots and grasses. PMID:28713414

Observing Clonal Dynamics across Spatiotemporal Axes: A Prelude to Quantitative Fitness Models for Cancer.

PubMed

McPherson, Andrew W; Chan, Fong Chun; Shah, Sohrab P

2018-02-01

The ability to accurately model evolutionary dynamics in cancer would allow for prediction of progression and response to therapy. As a prelude to quantitative understanding of evolutionary dynamics, researchers must gather observations of in vivo tumor evolution. High-throughput genome sequencing now provides the means to profile the mutational content of evolving tumor clones from patient biopsies. Together with the development of models of tumor evolution, reconstructing evolutionary histories of individual tumors generates hypotheses about the dynamics of evolution that produced the observed clones. In this review, we provide a brief overview of the concepts involved in predicting evolutionary histories, and provide a workflow based on bulk and targeted-genome sequencing. We then describe the application of this workflow to time series data obtained for transformed and progressed follicular lymphomas (FL), and contrast the observed evolutionary dynamics between these two subtypes. We next describe results from a spatial sampling study of high-grade serous (HGS) ovarian cancer, propose mechanisms of disease spread based on the observed clonal mixtures, and provide examples of diversification through subclonal acquisition of driver mutations and convergent evolution. Finally, we state implications of the techniques discussed in this review as a necessary but insufficient step on the path to predictive modelling of disease dynamics. Copyright © 2018 Cold Spring Harbor Laboratory Press; all rights reserved.

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

NASA Astrophysics Data System (ADS)

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.

Improving Search Properties in Genetic Programming

NASA Technical Reports Server (NTRS)

Janikow, Cezary Z.; DeWeese, Scott

1997-01-01

With the advancing computer processing capabilities, practical computer applications are mostly limited by the amount of human programming required to accomplish a specific task. This necessary human participation creates many problems, such as dramatically increased cost. To alleviate the problem, computers must become more autonomous. In other words, computers must be capable to program/reprogram themselves to adapt to changing environments/tasks/demands/domains. Evolutionary computation offers potential means, but it must be advanced beyond its current practical limitations. Evolutionary algorithms model nature. They maintain a population of structures representing potential solutions to the problem at hand. These structures undergo a simulated evolution by means of mutation, crossover, and a Darwinian selective pressure. Genetic programming (GP) is the most promising example of an evolutionary algorithm. In GP, the structures that evolve are trees, which is a dramatic departure from previously used representations such as strings in genetic algorithms. The space of potential trees is defined by means of their elements: functions, which label internal nodes, and terminals, which label leaves. By attaching semantic interpretation to those elements, trees can be interpreted as computer programs (given an interpreter), evolved architectures, etc. JSC has begun exploring GP as a potential tool for its long-term project on evolving dextrous robotic capabilities. Last year we identified representation redundancies as the primary source of inefficiency in GP. Subsequently, we proposed a method to use problem constraints to reduce those redundancies, effectively reducing GP complexity. This method was implemented afterwards at the University of Missouri. This summer, we have evaluated the payoff from using problem constraints to reduce search complexity on two classes of problems: learning boolean functions and solving the forward kinematics problem. We have also developed and implemented methods to use additional problem heuristics to fine-tune the searchable space, and to use typing information to further reduce the search space. Additional improvements have been proposed, but they are yet to be explored and implemented.

Evolutionary Optimization of a Quadrifilar Helical Antenna

NASA Technical Reports Server (NTRS)

Lohn, Jason D.; Kraus, William F.; Linden, Derek S.; Clancy, Daniel (Technical Monitor)

2002-01-01

Automated antenna synthesis via evolutionary design has recently garnered much attention in the research literature. Evolutionary algorithms show promise because, among search algorithms, they are able to effectively search large, unknown design spaces. NASA's Mars Odyssey spacecraft is due to reach final Martian orbit insertion in January, 2002. Onboard the spacecraft is a quadrifilar helical antenna that provides telecommunications in the UHF band with landed assets, such as robotic rovers. Each helix is driven by the same signal which is phase-delayed in 90 deg increments. A small ground plane is provided at the base. It is designed to operate in the frequency band of 400-438 MHz. Based on encouraging previous results in automated antenna design using evolutionary search, we wanted to see whether such techniques could improve upon Mars Odyssey antenna design. Specifically, a co-evolutionary genetic algorithm is applied to optimize the gain and size of the quadrifilar helical antenna. The optimization was performed in-situ in the presence of a neighboring spacecraft structure. On the spacecraft, a large aluminum fuel tank is adjacent to the antenna. Since this fuel tank can dramatically affect the antenna's performance, we leave it to the evolutionary process to see if it can exploit the fuel tank's properties advantageously. Optimizing in the presence of surrounding structures would be quite difficult for human antenna designers, and thus the actual antenna was designed for free space (with a small ground plane). In fact, when flying on the spacecraft, surrounding structures that are moveable (e.g., solar panels) may be moved during the mission in order to improve the antenna's performance.

NASA information sciences and human factors program

NASA Technical Reports Server (NTRS)

1991-01-01

The Data Systems Program consists of research and technology devoted to controlling, processing, storing, manipulating, and analyzing space-derived data. The objectives of the program are to provide the technology advancements needed to enable affordable utilization of space-derived data, to increase substantially the capability for future missions of on-board processing and recording and to provide high-speed, high-volume computational systems that are anticipated for missions such as the evolutionary Space Station and Earth Observing System.

How does cognition evolve? Phylogenetic comparative psychology

PubMed Central

Matthews, Luke J.; Hare, Brian A.; Nunn, Charles L.; Anderson, Rindy C.; Aureli, Filippo; Brannon, Elizabeth M.; Call, Josep; Drea, Christine M.; Emery, Nathan J.; Haun, Daniel B. M.; Herrmann, Esther; Jacobs, Lucia F.; Platt, Michael L.; Rosati, Alexandra G.; Sandel, Aaron A.; Schroepfer, Kara K.; Seed, Amanda M.; Tan, Jingzhi; van Schaik, Carel P.; Wobber, Victoria

2014-01-01

Now more than ever animal studies have the potential to test hypotheses regarding how cognition evolves. Comparative psychologists have developed new techniques to probe the cognitive mechanisms underlying animal behavior, and they have become increasingly skillful at adapting methodologies to test multiple species. Meanwhile, evolutionary biologists have generated quantitative approaches to investigate the phylogenetic distribution and function of phenotypic traits, including cognition. In particular, phylogenetic methods can quantitatively (1) test whether specific cognitive abilities are correlated with life history (e.g., lifespan), morphology (e.g., brain size), or socio-ecological variables (e.g., social system), (2) measure how strongly phylogenetic relatedness predicts the distribution of cognitive skills across species, and (3) estimate the ancestral state of a given cognitive trait using measures of cognitive performance from extant species. Phylogenetic methods can also be used to guide the selection of species comparisons that offer the strongest tests of a priori predictions of cognitive evolutionary hypotheses (i.e., phylogenetic targeting). Here, we explain how an integration of comparative psychology and evolutionary biology will answer a host of questions regarding the phylogenetic distribution and history of cognitive traits, as well as the evolutionary processes that drove their evolution. PMID:21927850

Evolution of egg coats: linking molecular biology and ecology.

PubMed

Shu, Longfei; Suter, Marc J-F; Räsänen, Katja

2015-08-01

One central goal of evolutionary biology is to explain how biological diversity emerges and is maintained in nature. Given the complexity of the phenotype and the multifaceted nature of inheritance, modern evolutionary ecological studies rely heavily on the use of molecular tools. Here, we show how molecular tools help to gain insight into the role of egg coats (i.e. the extracellular structures surrounding eggs and embryos) in evolutionary diversification. Egg coats are maternally derived structures that have many biological functions from mediating fertilization to protecting the embryo from environmental hazards. They show great molecular, structural and functional diversity across species, but intraspecific variability and the role of ecology in egg coat evolution have largely been overlooked. Given that much of the variation that influences egg coat function is ultimately determined by their molecular phenotype, cutting-edge molecular tools (e.g. proteomics, glycomics and transcriptomics), combined with functional assays, are needed for rigorous inferences on their evolutionary ecology. Here, we identify key research areas and highlight emerging molecular techniques that can increase our understanding of the role of egg coats in the evolution of biological diversity, from adaptation to speciation. © 2015 John Wiley & Sons Ltd.

Gender approaches to evolutionary multi-objective optimization using pre-selection of criteria

NASA Astrophysics Data System (ADS)

Kowalczuk, Zdzisław; Białaszewski, Tomasz

2018-01-01

A novel idea to perform evolutionary computations (ECs) for solving highly dimensional multi-objective optimization (MOO) problems is proposed. Following the general idea of evolution, it is proposed that information about gender is used to distinguish between various groups of objectives and identify the (aggregate) nature of optimality of individuals (solutions). This identification is drawn out of the fitness of individuals and applied during parental crossover in the processes of evolutionary multi-objective optimization (EMOO). The article introduces the principles of the genetic-gender approach (GGA) and virtual gender approach (VGA), which are not just evolutionary techniques, but constitute a completely new rule (philosophy) for use in solving MOO tasks. The proposed approaches are validated against principal representatives of the EMOO algorithms of the state of the art in solving benchmark problems in the light of recognized EC performance criteria. The research shows the superiority of the gender approach in terms of effectiveness, reliability, transparency, intelligibility and MOO problem simplification, resulting in the great usefulness and practicability of GGA and VGA. Moreover, an important feature of GGA and VGA is that they alleviate the 'curse' of dimensionality typical of many engineering designs.

Evolutionary fuzzy ARTMAP neural networks for classification of semiconductor defects.

PubMed

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.

Mode and tempo in the evolution of socio-political organization: reconciling 'Darwinian' and 'Spencerian' evolutionary approaches in anthropology.

PubMed

Currie, Thomas E; Mace, Ruth

2011-04-12

Traditional investigations of the evolution of human social and political institutions trace their ancestry back to nineteenth century social scientists such as Herbert Spencer, and have concentrated on the increase in socio-political complexity over time. More recent studies of cultural evolution have been explicitly informed by Darwinian evolutionary theory and focus on the transmission of cultural traits between individuals. These two approaches to investigating cultural change are often seen as incompatible. However, we argue that many of the defining features and assumptions of 'Spencerian' cultural evolutionary theory represent testable hypotheses that can and should be tackled within a broader 'Darwinian' framework. In this paper we apply phylogenetic comparative techniques to data from Austronesian-speaking societies of Island South-East Asia and the Pacific to test hypotheses about the mode and tempo of human socio-political evolution. We find support for three ideas often associated with Spencerian cultural evolutionary theory: (i) political organization has evolved through a regular sequence of forms, (ii) increases in hierarchical political complexity have been more common than decreases, and (iii) political organization has co-evolved with the wider presence of hereditary social stratification.

Mode and tempo in the evolution of socio-political organization: reconciling ‘Darwinian’ and ‘Spencerian’ evolutionary approaches in anthropology

PubMed Central

Currie, Thomas E.; Mace, Ruth

2011-01-01

Traditional investigations of the evolution of human social and political institutions trace their ancestry back to nineteenth century social scientists such as Herbert Spencer, and have concentrated on the increase in socio-political complexity over time. More recent studies of cultural evolution have been explicitly informed by Darwinian evolutionary theory and focus on the transmission of cultural traits between individuals. These two approaches to investigating cultural change are often seen as incompatible. However, we argue that many of the defining features and assumptions of ‘Spencerian’ cultural evolutionary theory represent testable hypotheses that can and should be tackled within a broader ‘Darwinian’ framework. In this paper we apply phylogenetic comparative techniques to data from Austronesian-speaking societies of Island South-East Asia and the Pacific to test hypotheses about the mode and tempo of human socio-political evolution. We find support for three ideas often associated with Spencerian cultural evolutionary theory: (i) political organization has evolved through a regular sequence of forms, (ii) increases in hierarchical political complexity have been more common than decreases, and (iii) political organization has co-evolved with the wider presence of hereditary social stratification. PMID:21357233

How does cognition evolve? Phylogenetic comparative psychology.

PubMed

MacLean, Evan L; Matthews, Luke J; Hare, Brian A; Nunn, Charles L; Anderson, Rindy C; Aureli, Filippo; Brannon, Elizabeth M; Call, Josep; Drea, Christine M; Emery, Nathan J; Haun, Daniel B M; Herrmann, Esther; Jacobs, Lucia F; Platt, Michael L; Rosati, Alexandra G; Sandel, Aaron A; Schroepfer, Kara K; Seed, Amanda M; Tan, Jingzhi; van Schaik, Carel P; Wobber, Victoria

2012-03-01

Now more than ever animal studies have the potential to test hypotheses regarding how cognition evolves. Comparative psychologists have developed new techniques to probe the cognitive mechanisms underlying animal behavior, and they have become increasingly skillful at adapting methodologies to test multiple species. Meanwhile, evolutionary biologists have generated quantitative approaches to investigate the phylogenetic distribution and function of phenotypic traits, including cognition. In particular, phylogenetic methods can quantitatively (1) test whether specific cognitive abilities are correlated with life history (e.g., lifespan), morphology (e.g., brain size), or socio-ecological variables (e.g., social system), (2) measure how strongly phylogenetic relatedness predicts the distribution of cognitive skills across species, and (3) estimate the ancestral state of a given cognitive trait using measures of cognitive performance from extant species. Phylogenetic methods can also be used to guide the selection of species comparisons that offer the strongest tests of a priori predictions of cognitive evolutionary hypotheses (i.e., phylogenetic targeting). Here, we explain how an integration of comparative psychology and evolutionary biology will answer a host of questions regarding the phylogenetic distribution and history of cognitive traits, as well as the evolutionary processes that drove their evolution.

Towards unbiased benchmarking of evolutionary and hybrid algorithms for real-valued optimisation

NASA Astrophysics Data System (ADS)

MacNish, Cara

2007-12-01

Randomised population-based algorithms, such as evolutionary, genetic and swarm-based algorithms, and their hybrids with traditional search techniques, have proven successful and robust on many difficult real-valued optimisation problems. This success, along with the readily applicable nature of these techniques, has led to an explosion in the number of algorithms and variants proposed. In order for the field to advance it is necessary to carry out effective comparative evaluations of these algorithms, and thereby better identify and understand those properties that lead to better performance. This paper discusses the difficulties of providing benchmarking of evolutionary and allied algorithms that is both meaningful and logistically viable. To be meaningful the benchmarking test must give a fair comparison that is free, as far as possible, from biases that favour one style of algorithm over another. To be logistically viable it must overcome the need for pairwise comparison between all the proposed algorithms. To address the first problem, we begin by attempting to identify the biases that are inherent in commonly used benchmarking functions. We then describe a suite of test problems, generated recursively as self-similar or fractal landscapes, designed to overcome these biases. For the second, we describe a server that uses web services to allow researchers to 'plug in' their algorithms, running on their local machines, to a central benchmarking repository.

Adaptations to sexual selection and sexual conflict: insights from experimental evolution and artificial selection.

PubMed

Edward, Dominic A; Fricke, Claudia; Chapman, Tracey

2010-08-27

Artificial selection and experimental evolution document natural selection under controlled conditions. Collectively, these techniques are continuing to provide fresh and important insights into the genetic basis of evolutionary change, and are now being employed to investigate mating behaviour. Here, we focus on how selection techniques can reveal the genetic basis of post-mating adaptations to sexual selection and sexual conflict. Alteration of the operational sex ratio of adult Drosophila over just a few tens of generations can lead to altered ejaculate allocation patterns and the evolution of resistance in females to the costly effects of elevated mating rates. We provide new data to show how male responses to the presence of rivals can evolve. For several traits, the way in which males responded to rivals was opposite in lines selected for male-biased, as opposed to female-biased, adult sex ratio. This shows that the manipulation of the relative intensity of intra- and inter-sexual selection can lead to replicable and repeatable effects on mating systems, and reveals the potential for significant contemporary evolutionary change. Such studies, with important safeguards, have potential utility for understanding sexual selection and sexual conflict across many taxa. We discuss how artificial selection studies combined with genomics will continue to deepen our knowledge of the evolutionary principles first laid down by Darwin 150 years ago.

Hybrid Disease Diagnosis Using Multiobjective Optimization with Evolutionary Parameter Optimization

PubMed Central

Nalluri, MadhuSudana Rao; K., Kannan; M., Manisha

2017-01-01

With the widespread adoption of e-Healthcare and telemedicine applications, accurate, intelligent disease diagnosis systems have been profoundly coveted. In recent years, numerous individual machine learning-based classifiers have been proposed and tested, and the fact that a single classifier cannot effectively classify and diagnose all diseases has been almost accorded with. This has seen a number of recent research attempts to arrive at a consensus using ensemble classification techniques. In this paper, a hybrid system is proposed to diagnose ailments using optimizing individual classifier parameters for two classifier techniques, namely, support vector machine (SVM) and multilayer perceptron (MLP) technique. We employ three recent evolutionary algorithms to optimize the parameters of the classifiers above, leading to six alternative hybrid disease diagnosis systems, also referred to as hybrid intelligent systems (HISs). Multiple objectives, namely, prediction accuracy, sensitivity, and specificity, have been considered to assess the efficacy of the proposed hybrid systems with existing ones. The proposed model is evaluated on 11 benchmark datasets, and the obtained results demonstrate that our proposed hybrid diagnosis systems perform better in terms of disease prediction accuracy, sensitivity, and specificity. Pertinent statistical tests were carried out to substantiate the efficacy of the obtained results. PMID:29065626

Task-level robot programming: Integral part of evolution from teleoperation to autonomy

NASA Technical Reports Server (NTRS)

Reynolds, James C.

1987-01-01

An explanation is presented of task-level robot programming and of how it differs from the usual interpretation of task planning for robotics. Most importantly, it is argued that the physical and mathematical basis of task-level robot programming provides inherently greater reliability than efforts to apply better known concepts from artificial intelligence (AI) to autonomous robotics. Finally, an architecture is presented that allows the integration of task-level robot programming within an evolutionary, redundant, and multi-modal framework that spans teleoperation to autonomy.

Punctuated equilibrium in the large-scale evolution of programming languages.

PubMed

Valverde, Sergi; Solé, Ricard V

2015-06-06

The analogies and differences between biological and cultural evolution have been explored by evolutionary biologists, historians, engineers and linguists alike. Two well-known domains of cultural change are language and technology. Both share some traits relating the evolution of species, but technological change is very difficult to study. A major challenge in our way towards a scientific theory of technological evolution is how to properly define evolutionary trees or clades and how to weight the role played by horizontal transfer of information. Here, we study the large-scale historical development of programming languages, which have deeply marked social and technological advances in the last half century. We analyse their historical connections using network theory and reconstructed phylogenetic networks. Using both data analysis and network modelling, it is shown that their evolution is highly uneven, marked by innovation events where new languages are created out of improved combinations of different structural components belonging to previous languages. These radiation events occur in a bursty pattern and are tied to novel technological and social niches. The method can be extrapolated to other systems and consistently captures the major classes of languages and the widespread horizontal design exchanges, revealing a punctuated evolutionary path. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Predicting protein contact map using evolutionary and physical constraints by integer programming.

PubMed

Wang, Zhiyong; Xu, Jinbo

2013-07-01

Protein contact map describes the pairwise spatial and functional relationship of residues in a protein and contains key information for protein 3D structure prediction. Although studied extensively, it remains challenging to predict contact map using only sequence information. Most existing methods predict the contact map matrix element-by-element, ignoring correlation among contacts and physical feasibility of the whole-contact map. A couple of recent methods predict contact map by using mutual information, taking into consideration contact correlation and enforcing a sparsity restraint, but these methods demand for a very large number of sequence homologs for the protein under consideration and the resultant contact map may be still physically infeasible. This article presents a novel method PhyCMAP for contact map prediction, integrating both evolutionary and physical restraints by machine learning and integer linear programming. The evolutionary restraints are much more informative than mutual information, and the physical restraints specify more concrete relationship among contacts than the sparsity restraint. As such, our method greatly reduces the solution space of the contact map matrix and, thus, significantly improves prediction accuracy. Experimental results confirm that PhyCMAP outperforms currently popular methods no matter how many sequence homologs are available for the protein under consideration. http://raptorx.uchicago.edu.

Peptide Signaling in Plant Development

PubMed Central

Katsir, Leron; Davies, Kelli A.; Bergmann, Dominique C.; Laux, Thomas

2011-01-01

Cell-to-cell communication is integral to the evolution of multicellularity. In plant development, peptide signals relay information coordinating cell proliferation and differentiation. These peptides are often encoded by gene families and bind to corresponding families of receptors. The precise spatiotemporal expression of signals and their cognate receptors underlies developmental patterning, and expressional and biochemical changes over evolutionary time have likely contributed to the refinement and complexity of developmental programs. Here, we discuss two major plant peptide families which have central roles in plant development: the CLAVATA3/ENDOSPERM SURROUNDING REGION (CLE) peptide family and the EPIDERMAL PATTERNING FACTOR (EPF) family. We discuss how specialization has enabled the CLE peptides to modulate stem cell differentiation in various tissue types, and how differing activities of EPF peptides precisely regulate the stomatal developmental program, and we examine the contributions of these peptide families to plant development from an evolutionary perspective. PMID:21549958

Re-writing Popper's philosophy of science for systematics.

PubMed

Rieppel, Olivier

2008-01-01

This paper explores the use of Popper's philosophy of science by cladists in their battle against evolutionary and numerical taxonomy. Three schools of biological systematics fiercely debated each other from the late 1960s: evolutionary taxonomy, phenetics or numerical taxonomy, and phylogenetic systematics or cladistics. The outcome of that debate was the victory of phylogenetic systematics/cladistics over the competing schools of thought. To bring about this "cladistic turn" in systematics, the cladists drew heavily on the philosopher K.R. Popper in order to dress up phylogenetic systematics as a hypothetico-deductivist, indeed falsificationist, research program that would put an end to authoritarianism. As the case of the "cladistic revolution" demonstrates, scientists who turn to philosophy in defense of a research program read philosophers with an agenda in mind. That agenda is likely to distort the philosophical picture, as happened to Popper's philosophy of science at the hands of cladists.

Toward understanding the evolution of vertebrate gene regulatory networks: comparative genomics and epigenomic approaches.

PubMed

Martinez-Morales, Juan R

2016-07-01

Vertebrates, as most animal phyla, originated >500 million years ago during the Cambrian explosion, and progressively radiated into the extant classes. Inferring the evolutionary history of the group requires understanding the architecture of the developmental programs that constrain the vertebrate anatomy. Here, I review recent comparative genomic and epigenomic studies, based on ChIP-seq and chromatin accessibility, which focus on the identification of functionally equivalent cis-regulatory modules among species. This pioneer work, primarily centered in the mammalian lineage, has set the groundwork for further studies in representative vertebrate and chordate species. Mapping of active regulatory regions across lineages will shed new light on the evolutionary forces stabilizing ancestral developmental programs, as well as allowing their variation to sustain morphological adaptations on the inherited vertebrate body plan. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Potential applications of skip SMV with thrust engine

NASA Astrophysics Data System (ADS)

Wang, Weilin; Savvaris, Al

2016-11-01

This paper investigates the potential applications of Space Maneuver Vehicles (SMV) with skip trajectory. Due to soaring space operations over the past decades, the risk of space debris has considerably increased such as collision risks with space asset, human property on ground and even aviation. Many active debris removal methods have been investigated and in this paper, a debris remediation method is first proposed based on skip SMV. The key point is to perform controlled re-entry. These vehicles are expected to achieve a trans-atmospheric maneuver with thrust engine. If debris is released at altitude below 80 km, debris could be captured by the atmosphere drag force and re-entry interface prediction accuracy is improved. Moreover if the debris is released in a cargo at a much lower altitude, this technique protects high value space asset from break up by the atmosphere and improves landing accuracy. To demonstrate the feasibility of this concept, the present paper presents the simulation results for two specific mission profiles: (1) descent to predetermined altitude; (2) descent to predetermined point (altitude, longitude and latitude). The evolutionary collocation method is adopted for skip trajectory optimization due to its global optimality and high-accuracy. This method is actually a two-step optimization approach based on the heuristic algorithm and the collocation method. The optimal-control problem is transformed into a nonlinear programming problem (NLP) which can be efficiently and accurately solved by the sequential quadratic programming (SQP) procedure. However, such a method is sensitive to initial values. To reduce the sensitivity problem, genetic algorithm (GA) is adopted to refine the grids and provide near optimum initial values. By comparing the simulation data from different scenarios, it is found that skip SMV is feasible in active debris removal and the evolutionary collocation method gives a truthful re-entry trajectory that satisfies the path and boundary constraints.

SCARF: maximizing next-generation EST assemblies for evolutionary and population genomic analyses.

PubMed

Barker, Michael S; Dlugosch, Katrina M; Reddy, A Chaitanya C; Amyotte, Sarah N; Rieseberg, Loren H

2009-02-15

Scaffolded and Corrected Assembly of Roche 454 (SCARF) is a next-generation sequence assembly tool for evolutionary genomics that is designed especially for assembling 454 EST sequences against high-quality reference sequences from related species. The program was created to knit together 454 contigs that do not assemble during traditional de novo assembly, using a reference sequence library to orient the 454 sequences. SCARF is freely available at http://msbarker.com/software.htm, and is released under the open source GPLv3 license (http://www.opensource.org/licenses/gpl-3.0.html.

Toward an integrative approach of cognitive neuroscientific and evolutionary psychological studies of art.

PubMed

De Smedt, Johan; De Cruz, Helen

2010-11-28

This paper examines explanations for human artistic behavior in two reductionist research programs, cognitive neuroscience and evolutionary psychology. Despite their different methodological outlooks, both approaches converge on an explanation of art production and appreciation as byproducts of normal perceptual and motivational cognitive skills that evolved in response to problems originally not related to art, such as the discrimination of salient visual stimuli and speech sounds. The explanatory power of this reductionist framework does not obviate the need for higher-level accounts of art from the humanities, such as aesthetics, art history or anthropology of art.

A data mining approach to dinoflagellate clustering according to sterol composition: Correlations with evolutionary history.

USDA-ARS?s Scientific Manuscript database

This study examined the sterol compositions of 102 dinoflagellates (including several previously unexamined species) using clustering techniques as a means of determining the relatedness of the organisms. In addition, dinoflagellate sterol-based relationships were compared statistically to dinoflag...

Protein self-marking by ectoparasites: a case study using bed bugs

USDA-ARS?s Scientific Manuscript database

1. The ability to mark individuals is a critical feature of many ecological and evolutionary investigations, including dispersal studies. Insect dispersal is generally investigated using mark-release-recapture techniques, whereby marked individuals are released at a known location and then captured ...

Evolutionary medicine and bone loss in chronic inflammatory diseases--A theory of inflammation-related osteopenia.

PubMed

Straub, Rainer H; Cutolo, Maurizio; Pacifici, Roberto

2015-10-01

Bone loss is typical in chronic inflammatory diseases such as rheumatoid arthritis, psoriasis, ankylosing spondylitis, systemic lupus erythematosus, multiple sclerosis, inflammatory bowel diseases, pemphigus vulgaris, and others. It is also typical in transplantation-related inflammation and during the process of aging. While we recognized that bone loss is tightly linked to immune system activation or inflamm-aging in the form of acute, chronic active, or chronic smoldering inflammation, bone loss is typically discussed to be an "accident of inflammation." Extensive literature search in PubMed central. Using elements of evolutionary medicine, energy regulation, and neuroendocrine regulation of homeostasis and immune function, we work out that bone waste is an adaptive, evolutionarily positively selected program that is absolutely necessary during acute inflammation. However, when acute inflammation enters a chronic state due to the inability to terminate inflammation (e.g., in autoimmunity or in continuous immunity against microbes), the acute program of bone loss is a misguided adaptive program. The article highlights the complexity of interwoven pathways of osteopenia. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Evolutionary medicine and bone loss in chronic inflammatory diseases – a theory of inflammation-related osteopenia

PubMed Central

Straub, Rainer H.; Cutolo, Maurizio; Pacifici, Roberto

2015-01-01

Objective Bone loss is typical in chronic inflammatory diseases such as rheumatoid arthritis, psoriasis, ankylosing spondylitis, systemic lupus erythematosus, multiple sclerosis, inflammatory bowel diseases, pemphigus vulgaris, and others. It is also typical in transplantation-related inflammation and during the process of aging. While we recognized that bone loss is tightly linked to immune system activation or inflammaging in the form of acute, chronic active, or chronic smoldering inflammation, bone loss is typically discussed to be an “accident of inflammation”. Methods Extensive literature search in PubMed central. Results Using elements of evolutionary medicine, energy regulation, and neuroendocrine regulation of homeostasis and immune function, we work out that bone waste is an adaptive, evolutionarily positively selected program that is absolutely necessary during acute inflammation. However, when acute inflammation enters a chronic state due to the inability to terminate inflammation (e.g., in autoimmunity or in continuous immunity against microbes), the acute program of bone loss is a misguided adaptive program. Conclusions The article highlights the complexity of interwoven pathways of osteopenia. PMID:26044543

Evaluation of an Agricultural Meteorological Disaster Based on Multiple Criterion Decision Making and Evolutionary Algorithm

PubMed Central

Yu, Xiaobing; Yu, Xianrui; Lu, Yiqun

2018-01-01

The evaluation of a meteorological disaster can be regarded as a multiple-criteria decision making problem because it involves many indexes. Firstly, a comprehensive indexing system for an agricultural meteorological disaster is proposed, which includes the disaster rate, the inundated rate, and the complete loss rate. Following this, the relative weights of the three criteria are acquired using a novel proposed evolutionary algorithm. The proposed algorithm consists of a differential evolution algorithm and an evolution strategy. Finally, a novel evaluation model, based on the proposed algorithm and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), is presented to estimate the agricultural meteorological disaster of 2008 in China. The geographic information system (GIS) technique is employed to depict the disaster. The experimental results demonstrated that the agricultural meteorological disaster of 2008 was very serious, especially in Hunan and Hubei provinces. Some useful suggestions are provided to relieve agriculture meteorological disasters. PMID:29597243

Regularization techniques for backward--in--time evolutionary PDE problems

NASA Astrophysics Data System (ADS)

Gustafsson, Jonathan; Protas, Bartosz

2007-11-01

Backward--in--time evolutionary PDE problems have applications in the recently--proposed retrograde data assimilation. We consider the terminal value problem for the Kuramoto--Sivashinsky equation (KSE) in a 1D periodic domain as our model system. The KSE, proposed as a model for interfacial and combustion phenomena, is also often adopted as a toy model for hydrodynamic turbulence because of its multiscale and chaotic dynamics. Backward--in--time problems are typical examples of ill-posed problem, where disturbances are amplified exponentially during the backward march. Regularization is required to solve such problems efficiently and we consider approaches in which the original ill--posed problem is approximated with a less ill--posed problem obtained by adding a regularization term to the original equation. While such techniques are relatively well--understood for linear problems, they less understood in the present nonlinear setting. We consider regularization terms with fixed magnitudes and also explore a novel approach in which these magnitudes are adapted dynamically using simple concepts from the Control Theory.

Identifying irregularly shaped crime hot-spots using a multiobjective evolutionary algorithm

NASA Astrophysics Data System (ADS)

Wu, Xiaolan; Grubesic, Tony H.

2010-12-01

Spatial cluster detection techniques are widely used in criminology, geography, epidemiology, and other fields. In particular, spatial scan statistics are popular and efficient techniques for detecting areas of elevated crime or disease events. The majority of spatial scan approaches attempt to delineate geographic zones by evaluating the significance of clusters using likelihood ratio statistics tested with the Poisson distribution. While this can be effective, many scan statistics give preference to circular clusters, diminishing their ability to identify elongated and/or irregular shaped clusters. Although adjusting the shape of the scan window can mitigate some of these problems, both the significance of irregular clusters and their spatial structure must be accounted for in a meaningful way. This paper utilizes a multiobjective evolutionary algorithm to find clusters with maximum significance while quantitatively tracking their geographic structure. Crime data for the city of Cincinnati are utilized to demonstrate the advantages of the new approach and highlight its benefits versus more traditional scan statistics.

Using Fossil Shark Teeth to Illustrate Evolution and Introduce Basic Geologic Concepts in a High School Biology Classroom

NASA Astrophysics Data System (ADS)

Agnew, J. G.; Nunn, J. A.

2007-12-01

Shell Foundation sponsors a program at Louisiana State University called Shell Undergraduate Recruitment and Geoscience Education (SURGE). The purpose of SURGE is to help local high school science teachers incorporate geology into their classrooms by providing resources and training. As part of this program, a workshop for high school biology teachers was held at Louisiana State University in Baton Rouge on June 3-5, 2007. We had the teachers do a series of activities on fossil shark teeth to illustrate evolution and introduce basic earth science concepts such as geologic time, superposition, and faunal succession and provided the teachers with lesson plans and materials. As an example, one of our exercises explores the evolution of the megatoothed shark lineage leading to Carcharocles megalodon, the largest predatory shark in history with teeth up to 17 cm long. Megatoothed shark teeth make excellent evolutionary subjects because they have a good fossil record and show continuous transitions in morphology from the Eocene to Pliocene. Our activity follows the learning cycle model. We take advantage of the curiosity of sharks shared by most people, and allow students to explore the variations among different shark teeth and explain the causes of those variations. The objectives of this exercise are to have the students: 1) sort fossil shark teeth into biologically reasonable species; 2) form hypotheses about evolutionary relationships among fossil shark teeth; and 3) describe and interpret evolutionary trends in the fossil Megatoothed lineage. To do the activity, students are divided into groups of 2-3 and given a shuffled set of 72 shark tooth cards with different images of megatoothed shark teeth. They are instructed to group the shark tooth cards into separate species of sharks. After sorting the cards, students are asked to consider the evolutionary relationships among their species and arrange their species chronologically according to the species first appearance in the fossil record. This is followed by a group discussion of each group's predictions. Next students are given photographs of teeth from different megatoothed sharks, and a geologic time scale with the sharks stratigraphic ranges. Students are asked to describe evolutionary trends in the fossil megatoothed lineage and formulate several hypotheses to explain the observed evolutionary trends. The exercise is concluded with a discussion of the environmental and biotic events occurring between the Eocene and Miocene epochs that may have caused the evolutionary changes in the megatoothed shark's teeth.

Fear and Loving in Las Vegas: Evolution, Emotion, and Persuasion.

PubMed

Griskevicius, Vladas; Goldstein, Noah J; Mortensen, Chad R; Sundie, Jill M; Cialdini, Robert B; Kenrick, Douglas T

2009-06-01

How do arousal-inducing contexts, such as frightening or romantic television programs, influence the effectiveness of basic persuasion heuristics? Different predictions are made by three theoretical models: A general arousal model predicts that arousal should increase effectiveness of heuristics; an affective valence model predicts that effectiveness should depend on whether the context elicits positive or negative affect; an evolutionary model predicts that persuasiveness should depend on both the specific emotion that is elicited and the content of the particular heuristic. Three experiments examined how fear-inducing versus romantic contexts influenced the effectiveness of two widely used heuristics-social proof (e.g., "most popular") and scarcity (e.g., "limited edition"). Results supported predictions from an evolutionary model, showing that fear can lead scarcity appeals to be counter-persuasive, and that romantic desire can lead social proof appeals to be counter-persuasive. The findings highlight how an evolutionary theoretical approach can lead to novel theoretical and practical marketing insights.

The 1999 Crafoord Prize lectures. Neo-Lamarckian experimentalism in America: origins and consequences.

PubMed

Cook, G M

1999-12-01

The 1890s and the first decades of the twentieth century saw a vigorous debate about the mechanisms of evolutionary change. On one side, August Weismann defended the selectionist hypothesis; on the other, Herbert Spencer defended neo-Lamarckian theory. Supporters of Spencer, notably the American paleontologist and evolutionary theorist Henry Fairfield Osborn, recognized that the questions raised by Weismann and Spencer could only be settled experimentally. They called for the application of experimental methods, and the establishment of a new institution for the purpose of confirming the inheritance of acquired characters. To a great extent, the experimental program championed by Osborn and others was implemented and, although it failed to reveal soft inheritance and was soon eclipsed by Mendelian and chromosomal genetics, it did make significant and lasting contributions to evolutionary biology. Thus the importance of methodological and institutional innovation and theoretical pluralism to the progress of science is illustrated and underscored.

Available Transfer Capability Determination Using Hybrid Evolutionary Algorithm

NASA Astrophysics Data System (ADS)

Jirapong, Peeraool; Ongsakul, Weerakorn

2008-10-01

This paper proposes a new hybrid evolutionary algorithm (HEA) based on evolutionary programming (EP), tabu search (TS), and simulated annealing (SA) to determine the available transfer capability (ATC) of power transactions between different control areas in deregulated power systems. The optimal power flow (OPF)-based ATC determination is used to evaluate the feasible maximum ATC value within real and reactive power generation limits, line thermal limits, voltage limits, and voltage and angle stability limits. The HEA approach simultaneously searches for real power generations except slack bus in a source area, real power loads in a sink area, and generation bus voltages to solve the OPF-based ATC problem. Test results on the modified IEEE 24-bus reliability test system (RTS) indicate that ATC determination by the HEA could enhance ATC far more than those from EP, TS, hybrid TS/SA, and improved EP (IEP) algorithms, leading to an efficient utilization of the existing transmission system.

An Analytical Framework for Runtime of a Class of Continuous Evolutionary Algorithms.

PubMed

Zhang, Yushan; Hu, Guiwu

2015-01-01

Although there have been many studies on the runtime of evolutionary algorithms in discrete optimization, relatively few theoretical results have been proposed on continuous optimization, such as evolutionary programming (EP). This paper proposes an analysis of the runtime of two EP algorithms based on Gaussian and Cauchy mutations, using an absorbing Markov chain. Given a constant variation, we calculate the runtime upper bound of special Gaussian mutation EP and Cauchy mutation EP. Our analysis reveals that the upper bounds are impacted by individual number, problem dimension number n, searching range, and the Lebesgue measure of the optimal neighborhood. Furthermore, we provide conditions whereby the average runtime of the considered EP can be no more than a polynomial of n. The condition is that the Lebesgue measure of the optimal neighborhood is larger than a combinatorial calculation of an exponential and the given polynomial of n.

Turbopump Performance Improved by Evolutionary Algorithms

NASA Technical Reports Server (NTRS)

Oyama, Akira; Liou, Meng-Sing

2002-01-01

The development of design optimization technology for turbomachinery has been initiated using the multiobjective evolutionary algorithm under NASA's Intelligent Synthesis Environment and Revolutionary Aeropropulsion Concepts programs. As an alternative to the traditional gradient-based methods, evolutionary algorithms (EA's) are emergent design-optimization algorithms modeled after the mechanisms found in natural evolution. EA's search from multiple points, instead of moving from a single point. In addition, they require no derivatives or gradients of the objective function, leading to robustness and simplicity in coupling any evaluation codes. Parallel efficiency also becomes very high by using a simple master-slave concept for function evaluations, since such evaluations often consume the most CPU time, such as computational fluid dynamics. Application of EA's to multiobjective design problems is also straightforward because EA's maintain a population of design candidates in parallel. Because of these advantages, EA's are a unique and attractive approach to real-world design optimization problems.

Air Force Flight Screening: Evolutionary Changes, 1917-2003

DTIC Science & Technology

2004-12-01

US), FFA (Switzerland), Siai Marchetti (Italy), SAAB (Sweden), Slingsby (United Kingdom), Glassair (US), Piper (US), American General (US), and...Jumper, USAF/CC, [Academy Flight Screening program], 10 Apr 03, 3) BBP , 557 FTS/CC, “USAF 66 As the...Academy Flight Screening (AFS) Program,” 4 Feb 03, 4) BBP , 557 FTS/CC, “AFS Funding,” 22 Jan 03, 5) Position Paper, 557 FTS/CC

Near earth tracking/data exploration

NASA Technical Reports Server (NTRS)

Spearing, Robert

1990-01-01

The future challenges facing NASA's data acquisition program are examined, with emphasis on the near-earth exploration activity and the associated data systems. It is noted that the process that is being followed is an evolutionary one: new technologies are being gradually integrated into currently operating systems. For example, advanced handling is already being introduced into such programs as the Space Telescope and the Gamma Ray Source Observatory System.

An Agent-based Model for Groundwater Allocation and Management at the Bakken Shale in Western North Dakota

NASA Astrophysics Data System (ADS)

Lin, T.; Lin, Z.; Lim, S.

2017-12-01

We present an integrated modeling framework to simulate groundwater level change under the dramatic increase of hydraulic fracturing water use in the Bakken Shale oil production area. The framework combines the agent-based model (ABM) with the Fox Hills-Hell Creek (FH-HC) groundwater model. In development of the ABM, institution theory is used to model the regulation policies from the North Dakota State Water Commission, while evolutionary programming and cognitive maps are used to model the social structure that emerges from the behavior of competing individual water businesses. Evolutionary programming allows individuals to select an appropriate strategy when annually applying for potential water use permits; whereas cognitive maps endow agent's ability and willingness to compete for more water sales. All agents have their own influence boundaries that inhibit their competitive behavior toward their neighbors but not to non-neighbors. The decision-making process is constructed and parameterized with both quantitative and qualitative information, i.e., empirical water use data and knowledge gained from surveys with stakeholders. By linking institution theory, evolutionary programming, and cognitive maps, our approach addresses a higher complexity of the real decision making process. Furthermore, this approach is a new exploration for modeling the dynamics of Coupled Human and Natural System. After integrating ABM with the FH-HC model, drought and limited water accessibility scenarios are simulated to predict FH-HC ground water level changes in the future. The integrated modeling framework of ABM and FH-HC model can be used to support making scientifically sound policies in water allocation and management.

A Review of Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Jain, N. K.; Nangia, Uma; Jain, Jyoti

2018-03-01

This paper presents an overview of the research progress in Particle Swarm Optimization (PSO) during 1995-2017. Fifty two papers have been reviewed. They have been categorized into nine categories based on various aspects. This technique has attracted many researchers because of its simplicity which led to many improvements and modifications of the basic PSO. Some researchers carried out the hybridization of PSO with other evolutionary techniques. This paper discusses the progress of PSO, its improvements, modifications and applications.

EGenBio: A Data Management System for Evolutionary Genomics and Biodiversity

PubMed Central

Nahum, Laila A; Reynolds, Matthew T; Wang, Zhengyuan O; Faith, Jeremiah J; Jonna, Rahul; Jiang, Zhi J; Meyer, Thomas J; Pollock, David D

2006-01-01

Background Evolutionary genomics requires management and filtering of large numbers of diverse genomic sequences for accurate analysis and inference on evolutionary processes of genomic and functional change. We developed Evolutionary Genomics and Biodiversity (EGenBio; ) to begin to address this. Description EGenBio is a system for manipulation and filtering of large numbers of sequences, integrating curated sequence alignments and phylogenetic trees, managing evolutionary analyses, and visualizing their output. EGenBio is organized into three conceptual divisions, Evolution, Genomics, and Biodiversity. The Genomics division includes tools for selecting pre-aligned sequences from different genes and species, and for modifying and filtering these alignments for further analysis. Species searches are handled through queries that can be modified based on a tree-based navigation system and saved. The Biodiversity division contains tools for analyzing individual sequences or sequence alignments, whereas the Evolution division contains tools involving phylogenetic trees. Alignments are annotated with analytical results and modification history using our PRAED format. A miscellaneous Tools section and Help framework are also available. EGenBio was developed around our comparative genomic research and a prototype database of mtDNA genomes. It utilizes MySQL-relational databases and dynamic page generation, and calls numerous custom programs. Conclusion EGenBio was designed to serve as a platform for tools and resources to ease combined analysis in evolution, genomics, and biodiversity. PMID:17118150

Structural dynamic interaction with solar tracking control for evolutionary Space Station concepts

NASA Technical Reports Server (NTRS)

Lim, Tae W.; Cooper, Paul A.; Ayers, J. Kirk

1992-01-01

The sun tracking control system design of the Solar Alpha Rotary Joint (SARJ) and the interaction of the control system with the flexible structure of Space Station Freedom (SSF) evolutionary concepts are addressed. The significant components of the space station pertaining to the SARJ control are described and the tracking control system design is presented. Finite element models representing two evolutionary concepts, enhanced operations capability (EOC) and extended operations capability (XOC), are employed to evaluate the influence of low frequency flexible structure on the control system design and performance. The design variables of the control system are synthesized using a constrained optimization technique to meet design requirements, to provide a given level of control system stability margin, and to achieve the most responsive tracking performance. The resulting SARJ control system design and performance of the EOC and XOC configurations are presented and compared to those of the SSF configuration. Performance limitations caused by the low frequency of the dominant flexible mode are discussed.

Industrial Relevance of Chromosomal Copy Number Variation in Saccharomyces Yeasts.

PubMed

Gorter de Vries, Arthur R; Pronk, Jack T; Daran, Jean-Marc G

2017-06-01

Chromosomal copy number variation (CCNV) plays a key role in evolution and health of eukaryotes. The unicellular yeast Saccharomyces cerevisiae is an important model for studying the generation, physiological impact, and evolutionary significance of CCNV. Fundamental studies of this yeast have contributed to an extensive set of methods for analyzing and introducing CCNV. Moreover, these studies provided insight into the balance between negative and positive impacts of CCNV in evolutionary contexts. A growing body of evidence indicates that CCNV not only frequently occurs in industrial strains of Saccharomyces yeasts but also is a key contributor to the diversity of industrially relevant traits. This notion is further supported by the frequent involvement of CCNV in industrially relevant traits acquired during evolutionary engineering. This review describes recent developments in genome sequencing and genome editing techniques and discusses how these offer opportunities to unravel contributions of CCNV in industrial Saccharomyce s strains as well as to rationally engineer yeast chromosomal copy numbers and karyotypes. Copyright © 2017 Gorter de Vries et al.

Quantifying evolutionary dynamics from variant-frequency time series

NASA Astrophysics Data System (ADS)

Khatri, Bhavin S.

2016-09-01

From Kimura’s neutral theory of protein evolution to Hubbell’s neutral theory of biodiversity, quantifying the relative importance of neutrality versus selection has long been a basic question in evolutionary biology and ecology. With deep sequencing technologies, this question is taking on a new form: given a time-series of the frequency of different variants in a population, what is the likelihood that the observation has arisen due to selection or neutrality? To tackle the 2-variant case, we exploit Fisher’s angular transformation, which despite being discovered by Ronald Fisher a century ago, has remained an intellectual curiosity. We show together with a heuristic approach it provides a simple solution for the transition probability density at short times, including drift, selection and mutation. Our results show under that under strong selection and sufficiently frequent sampling these evolutionary parameters can be accurately determined from simulation data and so they provide a theoretical basis for techniques to detect selection from variant or polymorphism frequency time-series.

Quantifying evolutionary dynamics from variant-frequency time series.

PubMed

Khatri, Bhavin S

2016-09-12

From Kimura's neutral theory of protein evolution to Hubbell's neutral theory of biodiversity, quantifying the relative importance of neutrality versus selection has long been a basic question in evolutionary biology and ecology. With deep sequencing technologies, this question is taking on a new form: given a time-series of the frequency of different variants in a population, what is the likelihood that the observation has arisen due to selection or neutrality? To tackle the 2-variant case, we exploit Fisher's angular transformation, which despite being discovered by Ronald Fisher a century ago, has remained an intellectual curiosity. We show together with a heuristic approach it provides a simple solution for the transition probability density at short times, including drift, selection and mutation. Our results show under that under strong selection and sufficiently frequent sampling these evolutionary parameters can be accurately determined from simulation data and so they provide a theoretical basis for techniques to detect selection from variant or polymorphism frequency time-series.

Phylogenomics reveals extensive reticulate evolution in Xiphophorus fishes.

PubMed

Cui, Rongfeng; Schumer, Molly; Kruesi, Karla; Walter, Ronald; Andolfatto, Peter; Rosenthal, Gil G

2013-08-01

Hybridization is increasingly being recognized as a widespread process, even between ecologically and behaviorally divergent animal species. Determining phylogenetic relationships in the presence of hybridization remains a major challenge for evolutionary biologists, but advances in sequencing technology and phylogenetic techniques are beginning to address these challenges. Here we reconstruct evolutionary relationships among swordtails and platyfishes (Xiphophorus: Poeciliidae), a group of species characterized by remarkable morphological diversity and behavioral barriers to interspecific mating. Past attempts to reconstruct phylogenetic relationships within Xiphophorus have produced conflicting results. Because many of the 26 species in the genus are interfertile, these conflicts are likely due to hybridization. Using genomic data, we resolve a high-confidence species tree of Xiphophorus that accounts for both incomplete lineage sorting and hybridization. Our results allow us to reexamine a long-standing controversy about the evolution of the sexually selected sword in Xiphophorus, and demonstrate that hybridization has been strikingly widespread in the evolutionary history of this genus. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Multi Sensor Fusion Using Fitness Adaptive Differential Evolution

NASA Astrophysics Data System (ADS)

Giri, Ritwik; Ghosh, Arnob; Chowdhury, Aritra; Das, Swagatam

The rising popularity of multi-source, multi-sensor networks supports real-life applications calls for an efficient and intelligent approach to information fusion. Traditional optimization techniques often fail to meet the demands. The evolutionary approach provides a valuable alternative due to its inherent parallel nature and its ability to deal with difficult problems. We present a new evolutionary approach based on a modified version of Differential Evolution (DE), called Fitness Adaptive Differential Evolution (FiADE). FiADE treats sensors in the network as distributed intelligent agents with various degrees of autonomy. Existing approaches based on intelligent agents cannot completely answer the question of how their agents could coordinate their decisions in a complex environment. The proposed approach is formulated to produce good result for the problems that are high-dimensional, highly nonlinear, and random. The proposed approach gives better result in case of optimal allocation of sensors. The performance of the proposed approach is compared with an evolutionary algorithm coordination generalized particle model (C-GPM).

Science, precaution, and the politics of technological risk: converging implications in evolutionary and social scientific perspectives.

PubMed

Stirling, Andy

2008-04-01

This paper examines apparent tensions between "science-based," "precautionary," and "participatory" approaches to decision making on risk. Partly by reference to insights currently emerging in evolutionary studies, the present paper looks for ways to reconcile some of the contradictions. First, I argue that technological evolution is a much more plural and open-ended process than is conventionally supposed. Risk politics is thus implicitly as much about social choice of technological pathways as narrow issues of safety. Second, it is shown how conventional "science-based" risk assessment techniques address only limited aspects of incomplete knowledge in complex, dynamic, evolutionary processes. Together, these understandings open the door to more sophisticated, comprehensive, rational, and robust decision-making processes. Despite their own limitations, it is found that precautionary and participatory approaches help to address these needs. A concrete framework is outlined through which the synergies can be more effectively harnessed. By this means, we can hope simultaneously to improve scientific rigor and democratic legitimacy in risk governance.

Industrial Relevance of Chromosomal Copy Number Variation in Saccharomyces Yeasts

PubMed Central

Gorter de Vries, Arthur R.; Pronk, Jack T.

2017-01-01

ABSTRACT Chromosomal copy number variation (CCNV) plays a key role in evolution and health of eukaryotes. The unicellular yeast Saccharomyces cerevisiae is an important model for studying the generation, physiological impact, and evolutionary significance of CCNV. Fundamental studies of this yeast have contributed to an extensive set of methods for analyzing and introducing CCNV. Moreover, these studies provided insight into the balance between negative and positive impacts of CCNV in evolutionary contexts. A growing body of evidence indicates that CCNV not only frequently occurs in industrial strains of Saccharomyces yeasts but also is a key contributor to the diversity of industrially relevant traits. This notion is further supported by the frequent involvement of CCNV in industrially relevant traits acquired during evolutionary engineering. This review describes recent developments in genome sequencing and genome editing techniques and discusses how these offer opportunities to unravel contributions of CCNV in industrial Saccharomyces strains as well as to rationally engineer yeast chromosomal copy numbers and karyotypes. PMID:28341679

A systematic mapping study of process mining

NASA Astrophysics Data System (ADS)

Maita, Ana Rocío Cárdenas; Martins, Lucas Corrêa; López Paz, Carlos Ramón; Rafferty, Laura; Hung, Patrick C. K.; Peres, Sarajane Marques; Fantinato, Marcelo

2018-05-01

This study systematically assesses the process mining scenario from 2005 to 2014. The analysis of 705 papers evidenced 'discovery' (71%) as the main type of process mining addressed and 'categorical prediction' (25%) as the main mining task solved. The most applied traditional technique is the 'graph structure-based' ones (38%). Specifically concerning computational intelligence and machine learning techniques, we concluded that little relevance has been given to them. The most applied are 'evolutionary computation' (9%) and 'decision tree' (6%), respectively. Process mining challenges, such as balancing among robustness, simplicity, accuracy and generalization, could benefit from a larger use of such techniques.

Estimating true evolutionary distances under the DCJ model.

PubMed

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.

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

PubMed

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.

The VLT-FLAMES Tarantula Survey. XXVI. Properties of the O-dwarf population in 30 Doradus

NASA Astrophysics Data System (ADS)

Sabín-Sanjulián, C.; Simón-Díaz, S.; Herrero, A.; Puls, J.; Schneider, F. R. N.; Evans, C. J.; Garcia, M.; Najarro, F.; Brott, I.; Castro, N.; Crowther, P. A.; de Koter, A.; de Mink, S. E.; Gräfener, G.; Grin, N. J.; Holgado, G.; Langer, N.; Lennon, D. J.; Maíz Apellániz, J.; Ramírez-Agudelo, O. H.; Sana, H.; Taylor, W. D.; Vink, J. S.; Walborn, N. R.

2017-05-01

Context. The VLT-FLAMES Tarantula Survey has observed hundreds of O-type stars in the 30 Doradus region of the Large Magellanic Cloud (LMC). Aims: We study the properties of a statistically significant sample of O-type dwarfs in the same star-forming region and test the latest atmospheric and evolutionary models of the early main-sequence phase of massive stars. Methods: We performed quantitative spectroscopic analysis of 105 apparently single O-type dwarfs. To determine stellar and wind parameters, we used the iacob-gbat package, an automatic procedure based on a large grid of atmospheric models that are calculated with the fastwind code. This package was developed for the analysis of optical spectra of O-type stars. In addition to classical techniques, we applied the Bayesian bonnsai tool to estimate evolutionary masses. Results: We provide a new calibration of effective temperature vs. spectral type for O-type dwarfs in the LMC, based on our homogeneous analysis of the largest sample of such objects to date and including all spectral subtypes. Good agreement with previous results is found, although the sampling at the earliest subtypes could be improved. Rotation rates and helium abundances are studied in an evolutionary context. We find that most of the rapid rotators (v sin I > 300 km s-1) in our sample have masses below 25 M⊙ and intermediate rotation-corrected gravities (3.9 < log gc < 4.1). Such rapid rotators are scarce at higher gravities (I.e. younger ages) and absent at lower gravities (larger ages). This is not expected from theoretical evolutionary models, and does not appear to be due to a selection bias in our sample. We compare the estimated evolutionary and spectroscopic masses, finding a trend that the former is higher for masses below 20 M⊙. This can be explained as a consequence of limiting our sample to the O-type stars, and we see no compelling evidence for a systematic mass discrepancy. For most of the stars in the sample we were unable to estimate the wind-strength parameter (hence mass-loss rates) reliably, particularly for objects with lower luminosity (log L/L⊙ ≲ 5.1). Only with ultraviolet spectroscopy will we be able to undertake a detailed investigation of the wind properties of these dwarfs. Based on observations at the European Southern Observatory Very Large Telescope in program 182.D-0222.Tables A.1 to B.2 are also available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/601/A79

TOmographic Remote Observer of Ionospheric Disturbances

DTIC Science & Technology

2007-11-15

ionosphere . The proposed spacecraft was an evolutionary design from the USUSat, Combat Sentinel, and USUSat II programs whose histories are shown in...Figure 1. The primary science instrument, TOROID for TOmographic Remote Observer of Ionospheric Disturbances, is a photometer for measuring the

Design Mining Interacting Wind Turbines.

PubMed

Preen, Richard J; Bull, Larry

2016-01-01

An initial study has recently been presented of surrogate-assisted evolutionary algorithms used to design vertical-axis wind turbines wherein candidate prototypes are evaluated under fan-generated wind conditions after being physically instantiated by a 3D printer. Unlike other approaches, such as computational fluid dynamics simulations, no mathematical formulations were used and no model assumptions were made. This paper extends that work by exploring alternative surrogate modelling and evolutionary techniques. The accuracy of various modelling algorithms used to estimate the fitness of evaluated individuals from the initial experiments is compared. The effect of temporally windowing surrogate model training samples is explored. A surrogate-assisted approach based on an enhanced local search is introduced; and alternative coevolution collaboration schemes are examined.

Evolutionary Patterns and Processes: Lessons from Ancient DNA.

PubMed

Leonardi, Michela; Librado, Pablo; Der Sarkissian, Clio; Schubert, Mikkel; Alfarhan, Ahmed H; Alquraishi, Saleh A; Al-Rasheid, Khaled A S; Gamba, Cristina; Willerslev, Eske; Orlando, Ludovic

2017-01-01

Ever since its emergence in 1984, the field of ancient DNA has struggled to overcome the challenges related to the decay of DNA molecules in the fossil record. With the recent development of high-throughput DNA sequencing technologies and molecular techniques tailored to ultra-damaged templates, it has now come of age, merging together approaches in phylogenomics, population genomics, epigenomics, and metagenomics. Leveraging on complete temporal sample series, ancient DNA provides direct access to the most important dimension in evolution—time, allowing a wealth of fundamental evolutionary processes to be addressed at unprecedented resolution. This review taps into the most recent findings in ancient DNA research to present analyses of ancient genomic and metagenomic data.

Evolutionary Patterns and Processes: Lessons from Ancient DNA

PubMed Central

Leonardi, Michela; Librado, Pablo; Der Sarkissian, Clio; Schubert, Mikkel; Alfarhan, Ahmed H.; Alquraishi, Saleh A.; Al-Rasheid, Khaled A. S.; Gamba, Cristina; Willerslev, Eske

2017-01-01

Abstract Ever since its emergence in 1984, the field of ancient DNA has struggled to overcome the challenges related to the decay of DNA molecules in the fossil record. With the recent development of high-throughput DNA sequencing technologies and molecular techniques tailored to ultra-damaged templates, it has now come of age, merging together approaches in phylogenomics, population genomics, epigenomics, and metagenomics. Leveraging on complete temporal sample series, ancient DNA provides direct access to the most important dimension in evolution—time, allowing a wealth of fundamental evolutionary processes to be addressed at unprecedented resolution. This review taps into the most recent findings in ancient DNA research to present analyses of ancient genomic and metagenomic data. PMID:28173586

Evolutionary learning processes as the foundation for behaviour change.

PubMed

Crutzen, Rik; Peters, Gjalt-Jorn Ygram

2018-03-01

We argue that the active ingredients of behaviour change interventions, often called behaviour change methods (BCMs) or techniques (BCTs), can usefully be placed on a dimension of psychological aggregation. We introduce evolutionary learning processes (ELPs) as fundamental building blocks that are on a lower level of psychological aggregation than BCMs/BCTs. A better understanding of ELPs is useful to select the appropriate BCMs/BCTs to target determinants of behaviour, or vice versa, to identify potential determinants targeted by a given BCM/BCT, and to optimally translate them into practical applications. Using these insights during intervention development may increase the likelihood of developing effective interventions - both in terms of behaviour change as well as maintenance of behaviour change.

Proposal of Evolutionary Simplex Method for Global Optimization Problem

NASA Astrophysics Data System (ADS)

Shimizu, Yoshiaki

To make an agile decision in a rational manner, role of optimization engineering has been notified increasingly under diversified customer demand. With this point of view, in this paper, we have proposed a new evolutionary method serving as an optimization technique in the paradigm of optimization engineering. The developed method has prospects to solve globally various complicated problem appearing in real world applications. It is evolved from the conventional method known as Nelder and Mead’s Simplex method by virtue of idea borrowed from recent meta-heuristic method such as PSO. Mentioning an algorithm to handle linear inequality constraints effectively, we have validated effectiveness of the proposed method through comparison with other methods using several benchmark problems.

Co-evolutionary data mining for fuzzy rules: automatic fitness function creation phase space, and experiments

NASA Astrophysics Data System (ADS)

Smith, James F., III; Blank, Joseph A.

2003-03-01

An approach is being explored that involves embedding a fuzzy logic based resource manager in an electronic game environment. Game agents can function under their own autonomous logic or human control. This approach automates the data mining problem. The game automatically creates a cleansed database reflecting the domain expert's knowledge, it calls a data mining function, a genetic algorithm, for data mining of the data base as required and allows easy evaluation of the information extracted. The co-evolutionary fitness functions, chromosomes and stopping criteria for ending the game are discussed. Genetic algorithm and genetic program based data mining procedures are discussed that automatically discover new fuzzy rules and strategies. The strategy tree concept and its relationship to co-evolutionary data mining are examined as well as the associated phase space representation of fuzzy concepts. The overlap of fuzzy concepts in phase space reduces the effective strategies available to adversaries. Co-evolutionary data mining alters the geometric properties of the overlap region known as the admissible region of phase space significantly enhancing the performance of the resource manager. Procedures for validation of the information data mined are discussed and significant experimental results provided.

Designing a Pedagogical Model for Web Engineering Education: An Evolutionary Perspective

ERIC Educational Resources Information Center

Hadjerrouit, Said

2005-01-01

In contrast to software engineering, which relies on relatively well established development approaches, there is a lack of a proven methodology that guides Web engineers in building reliable and effective Web-based systems. Currently, Web engineering lacks process models, architectures, suitable techniques and methods, quality assurance, and a…

The Dynamics of Information Transfer

ERIC Educational Resources Information Center

Wagner, Elliott

2012-01-01

Philosophers and scientists have long debated how communication can arise in circumstances in which it is not already present. This dissertation uses the techniques of evolutionary game theory to address this puzzle. Following David Lewis (1969), communication is envisioned as occurring between players in a game. One player, who has private…

Anticipatory Mechanisms in Evolutionary Living Systems

NASA Astrophysics Data System (ADS)

Dubois, Daniel M.; Holmberg, Stig C.

2010-11-01

This paper deals firstly with a revisiting of Darwin's theory of Natural Selection. Darwin in his book never uses the word "evolution", but shows a clear position about mutability of species. Darwin's Natural Selection was mainly inspired by the anticipatory Artificial Selection by humans in domestication, and the Malthus struggle for existence. Darwin showed that the struggle for existence leads to the preservation of the most divergent offspring of any one species. He cited several times the canon of "Natura non facit saltum". He spoke about the origin of life from some one primordial form, into which life was first breathed. Finally, Darwin made anticipation about the future researches in psychology. This paper cites the work of Ernst Mayr who was the first, after 90 years of an intense scientific debate, to present a new and stable Darwinian paradigm as the "Evolutionary Synthesis" in 1942. To explain what is life, the Living Systems Theory (LST) by J. G. Miller is presented. It is showed that the Autopoietic Systems Theory of Varela et al is also a fundamental component of living systems. In agreement with Darwin, the natural selection is a necessary condition for transformation of biological systems, but is not a sufficient condition. Thus, in this paper we conjecture that an anticipatory evolutionary mechanism exists with the genetic code that is a self-replicating and self-modifying anticipatory program. As demonstrated by Nobel laureate McClintock, evolution in genomes is programmed. The word "program" comes from "pro-gram" meaning to write before, by anticipation, and means a plan for the programming of a mechanism, or a sequence of coded instructions that can be inserted into a mechanism, or a sequence of coded instructions, as genes of behavioural responses, that is part of an organism. For example, cell death may be programmed by what is called the apoptosis. This definitively is a great breakthrough in our understanding of biological evolution. Hence, it is possible to formulate a new principle of evolution, i.e. the principle of Double Anticipatory Loop (DAL) of evolution: Biological evolution is driven by interaction between a mindless environment that is passively selecting the fittest inhabitants and purposeful anticipatory living systems, which are actively selecting and creating their own environment. Evolution on the genome level is trigged by environmental stress but guided by an inherent program.

Evolving binary classifiers through parallel computation of multiple fitness cases.

PubMed

Cagnoni, Stefano; Bergenti, Federico; Mordonini, Monica; Adorni, Giovanni

2005-06-01

This paper describes two versions of a novel approach to developing binary classifiers, based on two evolutionary computation paradigms: cellular programming and genetic programming. Such an approach achieves high computation efficiency both during evolution and at runtime. Evolution speed is optimized by allowing multiple solutions to be computed in parallel. Runtime performance is optimized explicitly using parallel computation in the case of cellular programming or implicitly taking advantage of the intrinsic parallelism of bitwise operators on standard sequential architectures in the case of genetic programming. The approach was tested on a digit recognition problem and compared with a reference classifier.

Earth to Moon Transfer: Direct vs Via Libration Points (L1, L2)

NASA Technical Reports Server (NTRS)

Condon, Gerald L.; Wilson, Samuel W.

2004-01-01

For some three decades, the Apollo-style mission has served as a proven baseline technique for transporting flight crews to the Moon and back with expendable hardware. This approach provides an optimal design for expeditionary missions, emphasizing operational flexibility in terms of safely returning the crew in the event of a hardware failure. However, its application is limited essentially to low-latitude lunar sites, and it leaves much to be desired as a model for exploratory and evolutionary programs that employ reusable space-based hardware. This study compares the performance requirements for a lunar orbit rendezvous mission type with one using the cislunar libration point (L1) as a stopover and staging point for access to arbitrary sites on the lunar surface. For selected constraints and mission objectives, it contrasts the relative uniformity of performance cost when the L1 staging point is used with the wide variation of cost for the Apollo-style lunar orbit rendezvous.

libSRES: a C library for stochastic ranking evolution strategy for parameter estimation.

PubMed

Ji, Xinglai; Xu, Ying

2006-01-01

Estimation of kinetic parameters in a biochemical pathway or network represents a common problem in systems studies of biological processes. We have implemented a C library, named libSRES, to facilitate a fast implementation of computer software for study of non-linear biochemical pathways. This library implements a (mu, lambda)-ES evolutionary optimization algorithm that uses stochastic ranking as the constraint handling technique. Considering the amount of computing time it might require to solve a parameter-estimation problem, an MPI version of libSRES is provided for parallel implementation, as well as a simple user interface. libSRES is freely available and could be used directly in any C program as a library function. We have extensively tested the performance of libSRES on various pathway parameter-estimation problems and found its performance to be satisfactory. The source code (in C) is free for academic users at http://csbl.bmb.uga.edu/~jix/science/libSRES/

Evolutionary use of nuclear electric propulsion

NASA Technical Reports Server (NTRS)

Hack, K. J.; George, J. A.; Riehl, J. P.; Gilland, J. H.

1990-01-01

Evolving new propulsion technologies through a rational and conscious effort to minimize development costs and program risks while maximizing the performance benefits is intuitively practical. A phased approach to the evolution of nuclear electric propulsion from use on planetary probes, to lunar cargo vehicles, and finally to manned Mars missions with a concomitant growth in technology is considered. Technology levels and system component makeup are discussed for nuclear power systems and both ion and magnetoplasmadynamic thrusters. Mission scenarios are described, which include analysis of a probe to Pluto, a lunar cargo mission, Martian split, all-up, and quick-trip mission options. Evolutionary progression of the use of NEP in such missions is discussed.

Evolutionary Development of the Simulation by Logical Modeling System (SIBYL)

NASA Technical Reports Server (NTRS)

Wu, Helen

1995-01-01

Through the evolutionary development of the Simulation by Logical Modeling System (SIBYL) we have re-engineered the expensive and complex IBM mainframe based Long-term Hardware Projection Model (LHPM) to a robust cost-effective computer based mode that is easy to use. We achieved significant cost reductions and improved productivity in preparing long-term forecasts of Space Shuttle Main Engine (SSME) hardware. The LHPM for the SSME is a stochastic simulation model that projects the hardware requirements over 10 years. SIBYL is now the primary modeling tool for developing SSME logistics proposals and Program Operating Plan (POP) for NASA and divisional marketing studies.

HBC-Evo: predicting human breast cancer by exploiting amino acid sequence-based feature spaces and evolutionary ensemble system.

PubMed

Majid, Abdul; Ali, Safdar

2015-01-01

We developed genetic programming (GP)-based evolutionary ensemble system for the early diagnosis, prognosis and prediction of human breast cancer. This system has effectively exploited the diversity in feature and decision spaces. First, individual learners are trained in different feature spaces using physicochemical properties of protein amino acids. Their predictions are then stacked to develop the best solution during GP evolution process. Finally, results for HBC-Evo system are obtained with optimal threshold, which is computed using particle swarm optimization. Our novel approach has demonstrated promising results compared to state of the art approaches.

From molecules to mating: Rapid evolution and biochemical studies of reproductive proteins

PubMed Central

Wilburn, Damien B.; Swanson, Willie J.

2015-01-01

Sexual reproduction and the exchange of genetic information are essential biological processes for species across all branches of the tree of life. Over the last four decades, biochemists have continued to identify many of the factors that facilitate reproduction, but the molecular mechanisms that mediate this process continue to elude us. However, a recurring observation in this research has been the rapid evolution of reproductive proteins. In animals, the competing interests of males and females often result in arms race dynamics between pairs of interacting proteins. This phenomenon has been observed in all stages of reproduction, including pheromones, seminal fluid components, and gamete recognition proteins. In this article, we review how the integration of evolutionary theory with biochemical experiments can be used to study interacting reproductive proteins. Examples are included from both model and non-model organisms, and recent studies are highlighted for their use of state-of-the-art genomic and proteomic techniques. Significance Despite decades of research, our understanding of the molecular mechanisms that mediate fertilization remain poorly characterized. To date, molecular evolutionary studies on both model and non-model organisms have provided some of the best inferences to elucidating the molecular underpinnings of animal reproduction. This review article details how biochemical and evolutionary experiments have jointly enhanced the field for 40 years, and how recent work using high-throughput genomic and proteomic techniques have shed additional insights into this crucial biological process. PMID:26074353

Inferring explicit weighted consensus networks to represent alternative evolutionary histories

PubMed Central

2013-01-01

Background The advent of molecular biology techniques and constant increase in availability of genetic material have triggered the development of many phylogenetic tree inference methods. However, several reticulate evolution processes, such as horizontal gene transfer and hybridization, have been shown to blur the species evolutionary history by causing discordance among phylogenies inferred from different genes. Methods To tackle this problem, we hereby describe a new method for inferring and representing alternative (reticulate) evolutionary histories of species as an explicit weighted consensus network which can be constructed from a collection of gene trees with or without prior knowledge of the species phylogeny. Results We provide a way of building a weighted phylogenetic network for each of the following reticulation mechanisms: diploid hybridization, intragenic recombination and complete or partial horizontal gene transfer. We successfully tested our method on some synthetic and real datasets to infer the above-mentioned evolutionary events which may have influenced the evolution of many species. Conclusions Our weighted consensus network inference method allows one to infer, visualize and validate statistically major conflicting signals induced by the mechanisms of reticulate evolution. The results provided by the new method can be used to represent the inferred conflicting signals by means of explicit and easy-to-interpret phylogenetic networks. PMID:24359207

Linking micro- and macro-evolution at the cell type level: a view from the lophotrochozoan Platynereis dumerilii.

PubMed

Simakov, Oleg; Larsson, Tomas A; Arendt, Detlev

2013-09-01

Ever since the origin of the first metazoans over 600 million years ago, cell type diversification has been driven by micro-evolutionary processes at population level, leading to macro-evolution changes above species level. In this review, we introduce the marine annelid Platynereis dumerilii, a member of the lophotrochozoan clade (a key yet most understudied superphylum of bilaterians), as a suitable model system for the simultaneous study, at cellular resolution, of macro-evolutionary processes across phyla and of micro-evolutionary processes across highly polymorphic populations collected worldwide. Recent advances in molecular and experimental techniques, easy maintenance and breeding, and the fast, synchronous and stereotypical development have facilitated the establishment of Platynereis as one of the leading model species in the eco-evo-devo field. Most importantly, Platynereis allows the combination of expression profiling, morphological and physiological characterization at the single cell level. Here, we discuss recent advances in the collection of -omics data for the lab strain and for natural populations collected world-wide that can be integrated with population-specific cellular analyses to result in a cellular atlas integrating genetic, phenotypic and ecological variation. This makes Platynereis a tractable system to begin understanding the interplay between macro- and micro-evolutionary processes and cell type diversity.

A piecewise smooth model of evolutionary game for residential mobility and segregation

NASA Astrophysics Data System (ADS)

Radi, D.; Gardini, L.

2018-05-01

The paper proposes an evolutionary version of a Schelling-type dynamic system to model the patterns of residential segregation when two groups of people are involved. The payoff functions of agents are the individual preferences for integration which are empirically grounded. Differently from Schelling's model, where the limited levels of tolerance are the driving force of segregation, in the current setup agents benefit from integration. Despite the differences, the evolutionary model shows a dynamics of segregation that is qualitatively similar to the one of the classical Schelling's model: segregation is always a stable equilibrium, while equilibria of integration exist only for peculiar configurations of the payoff functions and their asymptotic stability is highly sensitive to parameter variations. Moreover, a rich variety of integrated dynamic behaviors can be observed. In particular, the dynamics of the evolutionary game is regulated by a one-dimensional piecewise smooth map with two kink points that is rigorously analyzed using techniques recently developed for piecewise smooth dynamical systems. The investigation reveals that when a stable internal equilibrium exists, the bimodal shape of the map leads to several different kinds of bifurcations, smooth, and border collision, in a complicated interplay. Our global analysis can give intuitions to be used by a social planner to maximize integration through social policies that manipulate people's preferences for integration.

Climate change and timing of avian breeding and migration: evolutionary versus plastic changes

PubMed Central

Charmantier, Anne; Gienapp, Phillip

2014-01-01

There are multiple observations around the globe showing that in many avian species, both the timing of migration and breeding have advanced, due to warmer springs. Here, we review the literature to disentangle the actions of evolutionary changes in response to selection induced by climate change versus changes due to individual plasticity, that is, the capacity of an individual to adjust its phenology to environmental variables. Within the abundant literature on climate change effects on bird phenology, only a small fraction of studies are based on individual data, yet individual data are required to quantify the relative importance of plastic versus evolutionary responses. While plasticity seems common and often adaptive, no study so far has provided direct evidence for an evolutionary response of bird phenology to current climate change. This assessment leads us to notice the alarming lack of tests for microevolutionary changes in bird phenology in response to climate change, in contrast with the abundant claims on this issue. In short, at present we cannot draw reliable conclusions on the processes underlying the observed patterns of advanced phenology in birds. Rapid improvements in techniques for gathering and analysing individual data offer exciting possibilities that should encourage research activity to fill this knowledge gap. PMID:24454545

Evolution of the Plant Reproduction Master Regulators LFY and the MADS Transcription Factors: The Role of Protein Structure in the Evolutionary Development of the Flower.

PubMed

Silva, Catarina S; Puranik, Sriharsha; Round, Adam; Brennich, Martha; Jourdain, Agnès; Parcy, François; Hugouvieux, Veronique; Zubieta, Chloe

2015-01-01

Understanding the evolutionary leap from non-flowering (gymnosperms) to flowering (angiosperms) plants and the origin and vast diversification of the floral form has been one of the focuses of plant evolutionary developmental biology. The evolving diversity and increasing complexity of organisms is often due to relatively small changes in genes that direct development. These "developmental control genes" and the transcription factors (TFs) they encode, are at the origin of most morphological changes. TFs such as LEAFY (LFY) and the MADS-domain TFs act as central regulators in key developmental processes of plant reproduction including the floral transition in angiosperms and the specification of the male and female organs in both gymnosperms and angiosperms. In addition to advances in genome wide profiling and forward and reverse genetic screening, structural techniques are becoming important tools in unraveling TF function by providing atomic and molecular level information that was lacking in purely genetic approaches. Here, we summarize previous structural work and present additional biophysical and biochemical studies of the key master regulators of plant reproduction - LEAFY and the MADS-domain TFs SEPALLATA3 and AGAMOUS. We discuss the impact of structural biology on our understanding of the complex evolutionary process leading to the development of the bisexual flower.

Graphing evolutionary pattern and process: a history of techniques in archaeology and paleobiology.

PubMed

Lyman, R Lee

2009-02-01

Graphs displaying evolutionary patterns are common in paleontology and in United States archaeology. Both disciplines subscribed to a transformational theory of evolution and graphed evolution as a sequence of archetypes in the late nineteenth and early twentieth centuries. U.S. archaeologists in the second decade of the twentieth century, and paleontologists shortly thereafter, developed distinct graphic styles that reflected the Darwinian variational model of evolution. Paleobiologists adopted the view of a species as a set of phenotypically variant individuals and graphed those variations either as central tendencies or as histograms of frequencies of variants. Archaeologists presumed their artifact types reflected cultural norms of prehistoric artisans and the frequency of specimens in each type reflected human choice and type popularity. They graphed cultural evolution as shifts in frequencies of specimens representing each of several artifact types. Confusion of pattern and process is exemplified by a paleobiologist misinterpreting the process illustrated by an archaeological graph, and an archaeologist misinterpreting the process illustrated by a paleobiological graph. Each style of graph displays particular evolutionary patterns and implies particular evolutionary processes. Graphs of a multistratum collection of prehistoric mammal remains and a multistratum collection of artifacts demonstrate that many graph styles can be used for both kinds of collections.

Evolutionary game based control for biological systems with applications in drug delivery.

PubMed

Li, Xiaobo; Lenaghan, Scott C; Zhang, Mingjun

2013-06-07

Control engineering and analysis of biological systems have become increasingly important for systems and synthetic biology. Unfortunately, no widely accepted control framework is currently available for these systems, especially at the cell and molecular levels. This is partially due to the lack of appropriate mathematical models to describe the unique dynamics of biological systems, and the lack of implementation techniques, such as ultra-fast and ultra-small devices and corresponding control algorithms. This paper proposes a control framework for biological systems subject to dynamics that exhibit adaptive behavior under evolutionary pressures. The control framework was formulated based on evolutionary game based modeling, which integrates both the internal dynamics and the population dynamics. In the proposed control framework, the adaptive behavior was characterized as an internal dynamic, and the external environment was regarded as an external control input. The proposed open-interface control framework can be integrated with additional control algorithms for control of biological systems. To demonstrate the effectiveness of the proposed framework, an optimal control strategy was developed and validated for drug delivery using the pathogen Giardia lamblia as a test case. In principle, the proposed control framework can be applied to any biological system exhibiting adaptive behavior under evolutionary pressures. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Saturn management concept

NASA Technical Reports Server (NTRS)

Bilstein, R. E.

1974-01-01

Management of the Saturn launch vehicles was an evolutionary process, requiring constant interaction between NASA Headquarters, the Marshall Space Flight Center (particularly the Saturn 5 Program Office), and the various prime contractors. Successful Saturn management was a blend of the decades of experience of the von Braun team, management concepts from the Army, Navy, Air Force, and Government, and private industry. The Saturn 5 Program Office shared a unique relationship with the Apollo Program Office at NASA Headquarters. Much of the success of the Saturn 5 Program Office was based on its painstaking attention to detail, emphasis on individual responsibilities (backed up by comprehensive program element plans and management matrices), and a high degree of visibility as embodied in the Program Control Center.

Recent advances in bird sperm morphometric analysis and its role in male gamete characterization and reproduction technologies

PubMed Central

Santiago-Moreno, Julian; Esteso, Milagros Cristina; Villaverde-Morcillo, Silvia; Toledano-Díaz, Adolfo; Castaño, Cristina; Velázquez, Rosario; López-Sebastián, Antonio; Goya, Agustín López; Martínez, Javier Gimeno

2016-01-01

Postcopulatory sexual selection through sperm competition may be an important evolutionary force affecting many reproductive traits, including sperm morphometrics. Environmental factors such as pollutants, pesticides, and climate change may affect different sperm traits, and thus reproduction, in sensitive bird species. Many sperm-handling processes used in assisted reproductive techniques may also affect the size of sperm cells. The accurately measured dimensions of sperm cell structures (especially the head) can thus be used as indicators of environmental influences, in improving our understanding of reproductive and evolutionary strategies, and for optimizing assisted reproductive techniques (e.g., sperm cryopreservation) for use with birds. Computer-assisted sperm morphometry analysis (CASA-Morph) provides an accurate and reliable method for assessing sperm morphometry, reducing the problem of subjectivity associated with human visual assessment. Computerized systems have been standardized for use with semen from different mammalian species. Avian spermatozoa, however, are filiform, limiting their analysis with such systems, which were developed to examine the approximately spherical heads of mammalian sperm cells. To help overcome this, the standardization of staining techniques to be used in computer-assessed light microscopical methods is a priority. The present review discusses these points and describes the sperm morphometric characteristics of several wild and domestic bird species. PMID:27678467

A phylogenomic analysis of Marek's disease virus reveals independent paths to virulence in Eurasia and North America.

PubMed

Trimpert, Jakob; Groenke, Nicole; Jenckel, Maria; He, Shulin; Kunec, Dusan; Szpara, Moriah L; Spatz, Stephen J; Osterrieder, Nikolaus; McMahon, Dino P

2017-12-01

Virulence determines the impact a pathogen has on the fitness of its host, yet current understanding of the evolutionary origins and causes of virulence of many pathogens is surprisingly incomplete. Here, we explore the evolution of Marek's disease virus (MDV), a herpesvirus commonly afflicting chickens and rarely other avian species. The history of MDV in the 20th century represents an important case study in the evolution of virulence. The severity of MDV infection in chickens has been rising steadily since the adoption of intensive farming techniques and vaccination programs in the 1950s and 1970s, respectively. It has remained uncertain, however, which of these factors is causally more responsible for the observed increase in virulence of circulating viruses. We conducted a phylogenomic study to understand the evolution of MDV in the context of dramatic changes to poultry farming and disease control. Our analysis reveals evidence of geographical structuring of MDV strains, with reconstructions supporting the emergence of virulent viruses independently in North America and Eurasia. Of note, the emergence of virulent viruses appears to coincide approximately with the introduction of comprehensive vaccination on both continents. The time-dated phylogeny also indicated that MDV has a mean evolutionary rate of ~1.6 × 10 -5 substitutions per site per year. An examination of gene-linked mutations did not identify a strong association between mutational variation and virulence phenotypes, indicating that MDV may evolve readily and rapidly under strong selective pressures and that multiple genotypic pathways may underlie virulence adaptation in MDV.

Molluscan Evolutionary Genomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simison, W. Brian; Boore, Jeffrey L.

2005-12-01

In the last 20 years there have been dramatic advances in techniques of high-throughput DNA sequencing, most recently accelerated by the Human Genome Project, a program that has determined the three billion base pair code on which we are based. Now this tremendous capability is being directed at other genome targets that are being sampled across the broad range of life. This opens up opportunities as never before for evolutionary and organismal biologists to address questions of both processes and patterns of organismal change. We stand at the dawn of a new 'modern synthesis' period, paralleling that of the earlymore » 20th century when the fledgling field of genetics first identified the underlying basis for Darwin's theory. We must now unite the efforts of systematists, paleontologists, mathematicians, computer programmers, molecular biologists, developmental biologists, and others in the pursuit of discovering what genomics can teach us about the diversity of life. Genome-level sampling for mollusks to date has mostly been limited to mitochondrial genomes and it is likely that these will continue to provide the best targets for broad phylogenetic sampling in the near future. However, we are just beginning to see an inroad into complete nuclear genome sequencing, with several mollusks and other eutrochozoans having been selected for work about to begin. Here, we provide an overview of the state of molluscan mitochondrial genomics, highlight a few of the discoveries from this research, outline the promise of broadening this dataset, describe upcoming projects to sequence whole mollusk nuclear genomes, and challenge the community to prepare for making the best use of these data.« less

NetpathXL - An Excel Interface to the Program NETPATH

USGS Publications Warehouse

Parkhurst, David L.; Charlton, Scott R.

2008-01-01

NetpathXL is a revised version of NETPATH that runs under Windows? operating systems. NETPATH is a computer program that uses inverse geochemical modeling techniques to calculate net geochemical reactions that can account for changes in water composition between initial and final evolutionary waters in hydrologic systems. The inverse models also can account for the isotopic composition of waters and can be used to estimate radiocarbon ages of dissolved carbon in ground water. NETPATH relies on an auxiliary, database program, DB, to enter the chemical analyses and to perform speciation calculations that define total concentrations of elements, charge balance, and redox state of aqueous solutions that are then used in inverse modeling. Instead of DB, NetpathXL relies on Microsoft Excel? to enter the chemical analyses. The speciation calculation formerly included in DB is implemented within the program NetpathXL. A program DBXL can be used to translate files from the old DB format (.lon files) to NetpathXL spreadsheets, or to create new NetpathXL spreadsheets. Once users have a NetpathXL spreadsheet with the proper format, new spreadsheets can be generated by copying or saving NetpathXL spreadsheets. In addition, DBXL can convert NetpathXL spreadsheets to PHREEQC input files. New capabilities in PHREEQC (version 2.15) allow solution compositions to be written to a .lon file, and inverse models developed in PHREEQC to be written as NetpathXL .pat and model files. NetpathXL can open NetpathXL spreadsheets, NETPATH-format path files (.pat files), and NetpathXL-format path files (.pat files). Once the speciation calculations have been performed on a spreadsheet file or a .pat file has been opened, the NetpathXL calculation engine is identical to the original NETPATH. Development of models and viewing results in NetpathXL rely on keyboard entry as in NETPATH.

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

PubMed Central

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

Identifying Evolutionary Patterns of SMBHS Using Characteristic Variables of the Quasar AGNs of eBOSS

NASA Astrophysics Data System (ADS)

Martens, Sarah Katherine; Wilcots, Eric M.

2017-01-01

We investigate the redshift distribution and environmental conditions of quasar AGNs. The importance of studying these relationships is to use the evolutionary patterns of QSOs (features with many quantifiable characteristics) to gain insight into the evolutionary paths and environmental dependencies of their host super massive black holes (SMBHs), which are more difficult to study directly. We employ specific redshift bins within Data Release 13 of the Sloan Digital Sky Survey's (SDSS) Extended Baryonic Oscillation Spectroscopic Survey (eBOSS) and begin with a sample of 595,025 QSOs. We then incorporate overlapping data sets: The Very Large Array Faint Images of the Radio Sky at Twenty-Centimeters (FIRST) which provides the HI detected QSOs in our sample, along with the galaxy group and cluster sample from Tempel, Tago, Liivamägi 2012 which we cross referenced with our QSO sample to see which of them exist in group environments. The addition of these data sets allows us to create a more holistic view of the processes at work within our sample of QSOs. Understanding the HI presence in different evolutionary phases will allow us to draw conclusions on potential star formation rates or quenching, and by understanding the populations of QSOs in galaxy groups we can determine if QSOs exist overwhelmingly in one particular environment and how environmental conditions effect the other characteristics of QSOs. Overall we provide a multi-faceted analysis of some of the evolutionary patterns and cycles of the eBOSS Data Release 13 QSOs and their implications on the evolutionary paths of SMBHs. This work was supported by the SDSS Research Experience for Undergraduates program, which is funded by a grant from Sloan Foundation to the Astrophysical Research Consortium.

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

PubMed

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.

A Generic multi-dimensional feature extraction method using multiobjective genetic programming.

PubMed

Zhang, Yang; Rockett, Peter I

2009-01-01

In this paper, we present a generic feature extraction method for pattern classification using multiobjective genetic programming. This not only evolves the (near-)optimal set of mappings from a pattern space to a multi-dimensional decision space, but also simultaneously optimizes the dimensionality of that decision space. The presented framework evolves vector-to-vector feature extractors that maximize class separability. We demonstrate the efficacy of our approach by making statistically-founded comparisons with a wide variety of established classifier paradigms over a range of datasets and find that for most of the pairwise comparisons, our evolutionary method delivers statistically smaller misclassification errors. At very worst, our method displays no statistical difference in a few pairwise comparisons with established classifier/dataset combinations; crucially, none of the misclassification results produced by our method is worse than any comparator classifier. Although principally focused on feature extraction, feature selection is also performed as an implicit side effect; we show that both feature extraction and selection are important to the success of our technique. The presented method has the practical consequence of obviating the need to exhaustively evaluate a large family of conventional classifiers when faced with a new pattern recognition problem in order to attain a good classification accuracy.

Evolutionary Data Mining Approach to Creating Digital Logic

DTIC Science & Technology

2010-01-01

To deal with this problem a genetic program (GP) based data mining ( DM ) procedure has been invented (Smith 2005). A genetic program is an algorithm...that can operate on the variables. When a GP was used as a DM function in the past to automatically create fuzzy decision trees, the Report...rules represents an approach to the determining the effect of linguistic imprecision, i.e., the inability of experts to provide crisp rules. The

Blockmodeling and the Estimation of Evolutionary Architectural Growth in Major Defense Acquisition Programs

DTIC Science & Technology

2016-04-30

Dabkowski, and Dixit (2015), we demonstrate that the DoDAF models required pre–MS A map to 14 of the 18 parameters of the Constructive Systems...engineering effort in complex systems. Saarbrücken, Germany: VDM Verlag. Valerdi, R., Dabkowski, M., & Dixit , I. (2015). Reliability improvement of...R., Dabkowski, M., & Dixit , I. (2015). Reliability Improvement of Major Defense Acquisition Program Cost Estimates – Mapping DoDAF to COSYSMO

Evolutionary construction by staying together and coming together.

PubMed

Tarnita, Corina E; Taubes, Clifford H; Nowak, Martin A

2013-03-07

The evolutionary trajectory of life on earth is one of increasing size and complexity. Yet the standard equations of evolutionary dynamics describe mutation and selection among similar organisms that compete on the same level of organization. Here we begin to outline a mathematical theory that might help to explore how evolution can be constructive, how natural selection can lead from lower to higher levels of organization. We distinguish two fundamental operations, which we call 'staying together' and 'coming together'. Staying together means that individuals form larger units by not separating after reproduction, while coming together means that independent individuals form aggregates. Staying together can lead to specialization and division of labor, but the developmental program must evolve in the basic unit. Coming together can be creative by combining units with different properties. Both operations have been identified in the context of multicellularity, but they have been treated very similarly. Here we point out that staying together and coming together can be found at every level of biological construction and moreover that they face different evolutionary problems. The distinction is particularly clear in the context of cooperation and defection. For staying together the stability of cooperation takes the form of a developmental error threshold, while coming together leads to evolutionary games and requires a mechanism for the evolution of cooperation. We use our models to discuss simple aspects of the evolution of protocells, eukarya, multi-cellularity and animal societies. Copyright © 2012 Elsevier Ltd. All rights reserved.

Artificial intelligence in sports biomechanics: new dawn or false hope?

PubMed

Bartlett, Roger

2006-12-15

This article reviews developments in the use of Artificial Intelligence (AI) in sports biomechanics over the last decade. It outlines possible uses of Expert Systems as diagnostic tools for evaluating faults in sports movements ('techniques') and presents some example knowledge rules for such an expert system. It then compares the analysis of sports techniques, in which Expert Systems have found little place to date, with gait analysis, in which they are routinely used. Consideration is then given to the use of Artificial Neural Networks (ANNs) in sports biomechanics, focusing on Kohonen self-organizing maps, which have been the most widely used in technique analysis, and multi-layer networks, which have been far more widely used in biomechanics in general. Examples of the use of ANNs in sports biomechanics are presented for javelin and discus throwing, shot putting and football kicking. I also present an example of the use of Evolutionary Computation in movement optimization in the soccer throw in, which predicted an optimal technique close to that in the coaching literature. After briefly overviewing the use of AI in both sports science and biomechanics in general, the article concludes with some speculations about future uses of AI in sports biomechanics. Key PointsExpert Systems remain almost unused in sports biomechanics, unlike in the similar discipline of gait analysis.Artificial Neural Networks, particularly Kohonen Maps, have been used, although their full value remains unclear.Other AI applications, including Evolutionary Computation, have received little attention.

Applications of Genetic Methods to NASA Design and Operations Problems

NASA Technical Reports Server (NTRS)

Laird, Philip D.

1996-01-01

We review four recent NASA-funded applications in which evolutionary/genetic methods are important. In the process we survey: the kinds of problems being solved today with these methods; techniques and tools used; problems encountered; and areas where research is needed. The presentation slides are annotated briefly at the top of each page.

Changing Staffing Patterns in Technical Services since the 1970s: A Study in Change.

ERIC Educational Resources Information Center

Andrews, Virgina Lee; Kelley, Carol Marie

1988-01-01

Describes the impact of automation on the responsibilities of both support and professional staff as well as evolutionary role of library assistants at Texas Tech University. Workflows for retrospective conversion of monographs and serials, current processing techniques, and the organization of the processing units are discussed. (Author/CLB)

Statistical methods for convergence detection of multi-objective evolutionary algorithms.

PubMed

Trautmann, H; Wagner, T; Naujoks, B; Preuss, M; Mehnen, J

2009-01-01

In this paper, two approaches for estimating the generation in which a multi-objective evolutionary algorithm (MOEA) shows statistically significant signs of convergence are introduced. A set-based perspective is taken where convergence is measured by performance indicators. The proposed techniques fulfill the requirements of proper statistical assessment on the one hand and efficient optimisation for real-world problems on the other hand. The first approach accounts for the stochastic nature of the MOEA by repeating the optimisation runs for increasing generation numbers and analysing the performance indicators using statistical tools. This technique results in a very robust offline procedure. Moreover, an online convergence detection method is introduced as well. This method automatically stops the MOEA when either the variance of the performance indicators falls below a specified threshold or a stagnation of their overall trend is detected. Both methods are analysed and compared for two MOEA and on different classes of benchmark functions. It is shown that the methods successfully operate on all stated problems needing less function evaluations while preserving good approximation quality at the same time.

Evolving a Behavioral Repertoire for a Walking Robot.

PubMed

Cully, A; Mouret, J-B

2016-01-01

Numerous algorithms have been proposed to allow legged robots to learn to walk. However, most of these algorithms are devised to learn walking in a straight line, which is not sufficient to accomplish any real-world mission. Here we introduce the Transferability-based Behavioral Repertoire Evolution algorithm (TBR-Evolution), a novel evolutionary algorithm that simultaneously discovers several hundreds of simple walking controllers, one for each possible direction. By taking advantage of solutions that are usually discarded by evolutionary processes, TBR-Evolution is substantially faster than independently evolving each controller. Our technique relies on two methods: (1) novelty search with local competition, which searches for both high-performing and diverse solutions, and (2) the transferability approach, which combines simulations and real tests to evolve controllers for a physical robot. We evaluate this new technique on a hexapod robot. Results show that with only a few dozen short experiments performed on the robot, the algorithm learns a repertoire of controllers that allows the robot to reach every point in its reachable space. Overall, TBR-Evolution introduced a new kind of learning algorithm that simultaneously optimizes all the achievable behaviors of a robot.

Using evolutionary computations to understand the design and evolution of gene and cell regulatory networks.

PubMed

Spirov, Alexander; Holloway, David

2013-07-15

This paper surveys modeling approaches for studying the evolution of gene regulatory networks (GRNs). Modeling of the design or 'wiring' of GRNs has become increasingly common in developmental and medical biology, as a means of quantifying gene-gene interactions, the response to perturbations, and the overall dynamic motifs of networks. Drawing from developments in GRN 'design' modeling, a number of groups are now using simulations to study how GRNs evolve, both for comparative genomics and to uncover general principles of evolutionary processes. Such work can generally be termed evolution in silico. Complementary to these biologically-focused approaches, a now well-established field of computer science is Evolutionary Computations (ECs), in which highly efficient optimization techniques are inspired from evolutionary principles. In surveying biological simulation approaches, we discuss the considerations that must be taken with respect to: (a) the precision and completeness of the data (e.g. are the simulations for very close matches to anatomical data, or are they for more general exploration of evolutionary principles); (b) the level of detail to model (we proceed from 'coarse-grained' evolution of simple gene-gene interactions to 'fine-grained' evolution at the DNA sequence level); (c) to what degree is it important to include the genome's cellular context; and (d) the efficiency of computation. With respect to the latter, we argue that developments in computer science EC offer the means to perform more complete simulation searches, and will lead to more comprehensive biological predictions. Copyright © 2013 Elsevier Inc. All rights reserved.

Spatial Structure of Evolutionary Models of Dialects in Contact

PubMed Central

Murawaki, Yugo

2015-01-01

Phylogenetic models, originally developed to demonstrate evolutionary biology, have been applied to a wide range of cultural data including natural language lexicons, manuscripts, folktales, material cultures, and religions. A fundamental question regarding the application of phylogenetic inference is whether trees are an appropriate approximation of cultural evolutionary history. Their validity in cultural applications has been scrutinized, particularly with respect to the lexicons of dialects in contact. Phylogenetic models organize evolutionary data into a series of branching events through time. However, branching events are typically not included in dialectological studies to interpret the distributions of lexical terms. Instead, dialectologists have offered spatial interpretations to represent lexical data. For example, new lexical items that emerge in a politico-cultural center are likely to spread to peripheries, but not vice versa. To explore the question of the tree model’s validity, we present a simple simulation model in which dialects form a spatial network and share lexical items through contact rather than through common ancestors. We input several network topologies to the model to generate synthetic data. We then analyze the synthesized data using conventional phylogenetic techniques. We found that a group of dialects can be considered tree-like even if it has not evolved in a temporally tree-like manner but has a temporally invariant, spatially tree-like structure. In addition, the simulation experiments appear to reproduce unnatural results observed in reconstructed trees for real data. These results motivate further investigation into the spatial structure of the evolutionary history of dialect lexicons as well as other cultural characteristics. PMID:26221958

Automated discovery of local search heuristics for satisfiability testing.

PubMed

Fukunaga, Alex S

2008-01-01

The development of successful metaheuristic algorithms such as local search for a difficult problem such as satisfiability testing (SAT) is a challenging task. We investigate an evolutionary approach to automating the discovery of new local search heuristics for SAT. We show that several well-known SAT local search algorithms such as Walksat and Novelty are composite heuristics that are derived from novel combinations of a set of building blocks. Based on this observation, we developed CLASS, a genetic programming system that uses a simple composition operator to automatically discover SAT local search heuristics. New heuristics discovered by CLASS are shown to be competitive with the best Walksat variants, including Novelty+. Evolutionary algorithms have previously been applied to directly evolve a solution for a particular SAT instance. We show that the heuristics discovered by CLASS are also competitive with these previous, direct evolutionary approaches for SAT. We also analyze the local search behavior of the learned heuristics using the depth, mobility, and coverage metrics proposed by Schuurmans and Southey.

Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures.

PubMed

Arana-Daniel, Nancy; Gallegos, Alberto A; López-Franco, Carlos; Alanís, Alma Y; Morales, Jacob; López-Franco, Adriana

2016-01-01

With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classification, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classification problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.

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

PubMed

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/.

Fear and Loving in Las Vegas: Evolution, Emotion, and Persuasion

PubMed Central

Griskevicius, Vladas; Goldstein, Noah J.; Mortensen, Chad R.; Sundie, Jill M.; Cialdini, Robert B.; Kenrick, Douglas T.

2009-01-01

How do arousal-inducing contexts, such as frightening or romantic television programs, influence the effectiveness of basic persuasion heuristics? Different predictions are made by three theoretical models: A general arousal model predicts that arousal should increase effectiveness of heuristics; an affective valence model predicts that effectiveness should depend on whether the context elicits positive or negative affect; an evolutionary model predicts that persuasiveness should depend on both the specific emotion that is elicited and the content of the particular heuristic. Three experiments examined how fear-inducing versus romantic contexts influenced the effectiveness of two widely used heuristics—social proof (e.g., “most popular”) and scarcity (e.g., “limited edition”). Results supported predictions from an evolutionary model, showing that fear can lead scarcity appeals to be counter-persuasive, and that romantic desire can lead social proof appeals to be counter-persuasive. The findings highlight how an evolutionary theoretical approach can lead to novel theoretical and practical marketing insights. PMID:19727416

First principles prediction of amorphous phases using evolutionary algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nahas, Suhas, E-mail: shsnhs@iitk.ac.in; Gaur, Anshu, E-mail: agaur@iitk.ac.in; Bhowmick, Somnath, E-mail: bsomnath@iitk.ac.in

2016-07-07

We discuss the efficacy of evolutionary method for the purpose of structural analysis of amorphous solids. At present, ab initio molecular dynamics (MD) based melt-quench technique is used and this deterministic approach has proven to be successful to study amorphous materials. We show that a stochastic approach motivated by Darwinian evolution can also be used to simulate amorphous structures. Applying this method, in conjunction with density functional theory based electronic, ionic and cell relaxation, we re-investigate two well known amorphous semiconductors, namely silicon and indium gallium zinc oxide. We find that characteristic structural parameters like average bond length and bondmore » angle are within ∼2% of those reported by ab initio MD calculations and experimental studies.« less

Applying Evolutionary Terminology Auditing to SNOMED CT

PubMed Central

Ceusters, Werner

2010-01-01

Evolutionary Terminology Auditing is a technique designed to measure quality improvements of terminologies over successive versions. It uses the most recent version of a terminology as a benchmark and assumes that changes in the underlying ontology correspond to changes in either that part of reality that is covered by the terminology, or the authors’ understanding – if not the ‘state of the art’ in general – thereof. Applied to SNOMED CT over 18 versions, it reveals that at the level of the concepts minimal improvements are obtained and that the second assumption holds for far less changes than one would expect. It is recommended that future versions of SNOMED CT provide more explicit documentation for each introduced change. PMID:21346948

Comparison of multiobjective evolutionary algorithms for operations scheduling under machine availability constraints.

PubMed

Frutos, M; Méndez, M; Tohmé, F; Broz, D

2013-01-01

Many of the problems that arise in production systems can be handled with multiobjective techniques. One of those problems is that of scheduling operations subject to constraints on the availability of machines and buffer capacity. In this paper we analyze different Evolutionary multiobjective Algorithms (MOEAs) for this kind of problems. We consider an experimental framework in which we schedule production operations for four real world Job-Shop contexts using three algorithms, NSGAII, SPEA2, and IBEA. Using two performance indexes, Hypervolume and R2, we found that SPEA2 and IBEA are the most efficient for the tasks at hand. On the other hand IBEA seems to be a better choice of tool since it yields more solutions in the approximate Pareto frontier.

Application of resequencing to rice genomics, functional genomics and evolutionary analysis

PubMed Central

2014-01-01

Rice is a model system used for crop genomics studies. The completion of the rice genome draft sequences in 2002 not only accelerated functional genome studies, but also initiated a new era of resequencing rice genomes. Based on the reference genome in rice, next-generation sequencing (NGS) using the high-throughput sequencing system can efficiently accomplish whole genome resequencing of various genetic populations and diverse germplasm resources. Resequencing technology has been effectively utilized in evolutionary analysis, rice genomics and functional genomics studies. This technique is beneficial for both bridging the knowledge gap between genotype and phenotype and facilitating molecular breeding via gene design in rice. Here, we also discuss the limitation, application and future prospects of rice resequencing. PMID:25006357

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

NASA Astrophysics Data System (ADS)

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 requirements specifications. Utilizing the draft NAVAIR SE guideline handbook and the ANSI/EIA-632 standard: Processes for Engineering a System, a systems engineering tailored process approach was adopted for the accelerated SHARP EMD prgram. Tailoring SE processes in this accelerated product delivery environment provided unique opportunities to be technically creative in the establishment of a product performance baseline. This paper provides an historical overview of the systems engineering activities spanning the prototype phase through the EMD SHARP program phase, the performance requirement capture activities and refinement process challenges, and what SE process improvements can be applied to future SHARP-like programs adopting a compressed, evolutionary spiral development acquisition paradigm.

Unweaving misconceptions: Guided learning, simulations, and misconceptions in learning principles of natural selection

NASA Astrophysics Data System (ADS)

Weeks, Brian E.

College students often come to the study of evolutionary biology with many misconceptions of how the processes of natural selection and speciation occur. How to relinquish these misconceptions with learners is a question that many educators face in introductory biology courses. Constructivism as a theoretical framework has become an accepted and promoted model within the epistemology of science instruction. However, constructivism is not without its skeptics who see some problems of its application in lacking necessary guidance for novice learners. This study within a quantitative, quasi-experimental format tested whether guided online instruction in a video format of common misconceptions in evolutionary biology produced higher performance on a survey of knowledge of natural selection versus more constructivist style learning in the form of student exploration of computer simulations of the evolutionary process. Performances on surveys were also explored for a combination of constructivist and guided techniques to determine if a consolidation of approaches produced higher test scores. Out of the 94 participants 95% displayed at least one misconception of natural selection in the pre-test while the study treatments produced no statistically significant improvements in post-test scores except within the video (guided learning treatment). These overall results demonstrated the stubbornness of misconceptions involving natural selection for adult learners and the difficulty of helping them overcome them. It also bolsters the idea that some misconceptions of natural selection and evolution may be hardwired in a neurological sense and that new, more long-term teaching techniques may be warranted. Such long-term strategies may not be best implemented with constructivist techniques alone, and it is likely that some level of guidance may be necessary for novice adult learners. A more substantial, nuanced approach for undergraduates is needed that consolidates successful teaching strategies to adult students that is based on current research.

Modeling of biological intelligence for SCM system optimization.

PubMed

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

XTALOPT version r11: An open-source evolutionary algorithm for crystal structure prediction

NASA Astrophysics Data System (ADS)

Avery, Patrick; Falls, Zackary; Zurek, Eva

2018-01-01

Version 11 of XTALOPT, an evolutionary algorithm for crystal structure prediction, has now been made available for download from the CPC library or the XTALOPT website, http://xtalopt.github.io. Whereas the previous versions of XTALOPT were published under the Gnu Public License (GPL), the current version is made available under the 3-Clause BSD License, which is an open source license that is recognized by the Open Source Initiative. Importantly, the new version can be executed via a command line interface (i.e., it does not require the use of a Graphical User Interface). Moreover, the new version is written as a stand-alone program, rather than an extension to AVOGADRO.

Modeling of Biological Intelligence for SCM System Optimization

PubMed Central

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

The QTN program and the alleles that matter for evolution: all that's gold does not glitter.

PubMed

Rockman, Matthew V

2012-01-01

The search for the alleles that matter, the quantitative trait nucleotides (QTNs) that underlie heritable variation within populations and divergence among them, is a popular pursuit. But what is the question to which QTNs are the answer? Although their pursuit is often invoked as a means of addressing the molecular basis of phenotypic evolution or of estimating the roles of evolutionary forces, the QTNs that are accessible to experimentalists, QTNs of relatively large effect, may be uninformative about these issues if large-effect variants are unrepresentative of the alleles that matter. Although 20th century evolutionary biology generally viewed large-effect variants as atypical, the field has recently undergone a quiet realignment toward a view of readily discoverable large-effect alleles as the primary molecular substrates for evolution. I argue that neither theory nor data justify this realignment. Models and experimental findings covering broad swaths of evolutionary phenomena suggest that evolution often acts via large numbers of small-effect polygenes, individually undetectable. Moreover, these small-effect variants are different in kind, at the molecular level, from the large-effect alleles accessible to experimentalists. Although discoverable QTNs address some fundamental evolutionary questions, they are essentially misleading about many others. © 2011 The Author(s). Evolution © 2011 The Society for the Study of Evolution.

Conciliation biology: the eco-evolutionary management of permanently invaded biotic systems

PubMed Central

Carroll, Scott P

2011-01-01

Biotic invaders and similar anthropogenic novelties such as domesticates, transgenics, and cancers can alter ecology and evolution in environmental, agricultural, natural resource, public health, and medical systems. The resulting biological changes may either hinder or serve management objectives. For example, biological control and eradication programs are often defeated by unanticipated resistance evolution and by irreversibility of invader impacts. Moreover, eradication may be ill-advised when nonnatives introduce beneficial functions. Thus, contexts that appear to call for eradication may instead demand managed coexistence of natives with nonnatives, and yet applied biologists have not generally considered the need to manage the eco-evolutionary dynamics that commonly result from interactions of natives with nonnatives. Here, I advocate a conciliatory approach to managing systems where novel organisms cannot or should not be eradicated. Conciliatory strategies incorporate benefits of nonnatives to address many practical needs including slowing rates of resistance evolution, promoting evolution of indigenous biological control, cultivating replacement services and novel functions, and managing native–nonnative coevolution. Evolutionary links across disciplines foster cohesion essential for managing the broad impacts of novel biotic systems. Rather than signaling defeat, conciliation biology thus utilizes the predictive power of evolutionary theory to offer diverse and flexible pathways to more sustainable outcomes. PMID:25567967

Discovering new materials and new phenomena with evolutionary algorithms

NASA Astrophysics Data System (ADS)

Oganov, Artem

Thanks to powerful evolutionary algorithms, in particular the USPEX method, it is now possible to predict both the stable compounds and their crystal structures at arbitrary conditions, given just the set of chemical elements. Recent developments include major increases of efficiency and extensions to low-dimensional systems and molecular crystals (which allowed large structures to be handled easily, e.g. Mg(BH4)2 and H2O-H2) and new techniques called evolutionary metadynamics and Mendelevian search. Some of the results that I will discuss include: 1. Theoretical and experimental evidence for a new partially ionic phase of boron, γ-B and an insulating and optically transparent form of sodium. 2. Predicted stability of ``impossible'' chemical compounds that become stable under pressure - e.g. Na3Cl, Na2Cl, Na3Cl2, NaCl3, NaCl7, Mg3O2 and MgO2. 3. Novel surface phases (e.g. boron surface reconstructions). 4. Novel dielectric polymers, and novel permanent magnets confirmed by experiment and ready for applications. 5. Prediction of new ultrahard materials and computational proof that diamond is the hardest possible material.

An improved shuffled frog leaping algorithm based evolutionary framework for currency exchange rate prediction

NASA Astrophysics Data System (ADS)

Dash, Rajashree

2017-11-01

Forecasting purchasing power of one currency with respect to another currency is always an interesting topic in the field of financial time series prediction. Despite the existence of several traditional and computational models for currency exchange rate forecasting, there is always a need for developing simpler and more efficient model, which will produce better prediction capability. In this paper, an evolutionary framework is proposed by using an improved shuffled frog leaping (ISFL) algorithm with a computationally efficient functional link artificial neural network (CEFLANN) for prediction of currency exchange rate. The model is validated by observing the monthly prediction measures obtained for three currency exchange data sets such as USD/CAD, USD/CHF, and USD/JPY accumulated within same period of time. The model performance is also compared with two other evolutionary learning techniques such as Shuffled frog leaping algorithm and Particle Swarm optimization algorithm. Practical analysis of results suggest that, the proposed model developed using the ISFL algorithm with CEFLANN network is a promising predictor model for currency exchange rate prediction compared to other models included in the study.

Evolutionary Bi-objective Optimization for Bulldozer and Its Blade in Soil Cutting

NASA Astrophysics Data System (ADS)

Sharma, Deepak; Barakat, Nada

2018-02-01

An evolutionary optimization approach is adopted in this paper for simultaneously achieving the economic and productive soil cutting. The economic aspect is defined by minimizing the power requirement from the bulldozer, and the soil cutting is made productive by minimizing the time of soil cutting. For determining the power requirement, two force models are adopted from the literature to quantify the cutting force on the blade. Three domain-specific constraints are also proposed, which are limiting the power from the bulldozer, limiting the maximum force on the bulldozer blade and achieving the desired production rate. The bi-objective optimization problem is solved using five benchmark multi-objective evolutionary algorithms and one classical optimization technique using the ɛ-constraint method. The Pareto-optimal solutions are obtained with the knee-region. Further, the post-optimal analysis is performed on the obtained solutions to decipher relationships among the objectives and decision variables. Such relationships are later used for making guidelines for selecting the optimal set of input parameters. The obtained results are then compared with the experiment results from the literature that show a close agreement among them.

Evolutionary Optimization of Quadrifilar Helical and Yagi-Uda Antennas

NASA Technical Reports Server (NTRS)

Lohn, Jason D.; Kraus, William F.; Linden, Derek S.; Stoica, Adrian; Clancy, Daniel (Technical Monitor)

2002-01-01

We present optimization results obtained for two type of antennas using evolutionary algorithms. A quadrifilar helical UHF antenna is currently flying aboard NASA's Mars Odyssey spacecraft and is due to reach final Martian orbit insertion in January, 2002. Using this antenna as a benchmark, we ran experiments employing a coevolutionary genetic algorithm to evolve a quadrifilar helical design in-situ - i.e., in the presence of a surrounding structure. Results show a 93% improvement at 400 MHz and a 48% improvement at 438 MHz in the average gain. The evolved antenna is also one-fourth the size. Yagi-Uda antennas are known to be difficult to design and optimize due to their sensitivity at high gain and the inclusion of numerous parasitic elements. Our fitness calculation allows the implicit relationship between power gain and sidelobe/backlobe loss to emerge naturally, a technique that is less complex than previous approaches. Our results include Yagi-Uda antennas that have excellent bandwidth and gain properties with very good impedance characteristics. Results exceeded previous Yagi-Uda antennas produced via evolutionary algorithms by at least 7.8% in mainlobe gain.

Detection of timescales in evolving complex systems

PubMed Central

Darst, Richard K.; Granell, Clara; Arenas, Alex; Gómez, Sergio; Saramäki, Jari; Fortunato, Santo

2016-01-01

Most complex systems are intrinsically dynamic in nature. The evolution of a dynamic complex system is typically represented as a sequence of snapshots, where each snapshot describes the configuration of the system at a particular instant of time. This is often done by using constant intervals but a better approach would be to define dynamic intervals that match the evolution of the system’s configuration. To this end, we propose a method that aims at detecting evolutionary changes in the configuration of a complex system, and generates intervals accordingly. We show that evolutionary timescales can be identified by looking for peaks in the similarity between the sets of events on consecutive time intervals of data. Tests on simple toy models reveal that the technique is able to detect evolutionary timescales of time-varying data both when the evolution is smooth as well as when it changes sharply. This is further corroborated by analyses of several real datasets. Our method is scalable to extremely large datasets and is computationally efficient. This allows a quick, parameter-free detection of multiple timescales in the evolution of a complex system. PMID:28004820

Physical properties of high-mass star-forming clumps in different evolutionary stages from the Bolocam Galactic Plane Survey

NASA Astrophysics Data System (ADS)

Svoboda, Brian; Shirley, Yancy; Rosolowsky, Erik; Dunham, Miranda; Ellsworth-Bowers, Timothy; Ginsburg, Adam

2013-07-01

High mass stars play a key role in the physical and chemical evolution of the interstellar medium, yet the evolutionary sequence for high mass star forming regions is poorly understood. Recent Galactic plane surveys are providing the first systematic view of high-mass star-forming regions in all evolutionary phases across the Milky Way. We present observations of the 22.23 GHz H2O maser transition J(Ka,Kc) = 6(1,6)→5(2,3) transition toward 1398 clumps identified in the Bolocam Galactic Plane Survey using the 100m Green Bank Telescope (GBT). We detect 392 H2O masers, 279 (71%) newly discovered. We show that H2O masers can identify the presence of protostars which were not previously identified by Spitzer/MSX Galactic plane IR surveys: 25% of IR-dark clumps have an H2O maser. We compare the physical properties of the clumps in the Bolocam Galactic Plane Survey (BGPS) with observations of diagnostics of star formation activity: 8 and 24 um YSO candidates, H2O and CH3OH masers, shocked H2, EGOs, and UCHII regions. We identify a sub-sample of 400 clumps with no star formation indicators representing the largest and most robust sample of pre-protocluster candidates from an unbiased survey to date. The different evolutionary stages show strong separations in HCO+ linewidth and integrated intensity, surface mass density, and kinetic temperature. Monte Carlo techniques are applied to distance probability distribution functions (DPDFs) in order to marginalize over the kinematic distance ambiguity and calculate the distribution of derived quantities for clumps in different evolutionary stages. Surface area and dust mass show weak separations above > 2 pc^2 and > 3x10^3 solar masses. An observed breakdown occurs in the size-linewidth relationship with no differentiation by evolutionary stage. Future work includes adding evolutionary indicators (MIPSGAL, HiGal, MMB) and expanding DPDF priors (HI self-absorption, Galactic structure) for more well-resolved KDAs.

Assessment of traffic noise levels in urban areas using different soft computing techniques.

PubMed

Tomić, J; Bogojević, N; Pljakić, M; Šumarac-Pavlović, D

2016-10-01

Available traffic noise prediction models are usually based on regression analysis of experimental data, and this paper presents the application of soft computing techniques in traffic noise prediction. Two mathematical models are proposed and their predictions are compared to data collected by traffic noise monitoring in urban areas, as well as to predictions of commonly used traffic noise models. The results show that application of evolutionary algorithms and neural networks may improve process of development, as well as accuracy of traffic noise prediction.

Evolution of the Plant Reproduction Master Regulators LFY and the MADS Transcription Factors: The Role of Protein Structure in the Evolutionary Development of the Flower

PubMed Central

Silva, Catarina S.; Puranik, Sriharsha; Round, Adam; Brennich, Martha; Jourdain, Agnès; Parcy, François; Hugouvieux, Veronique; Zubieta, Chloe

2016-01-01

Understanding the evolutionary leap from non-flowering (gymnosperms) to flowering (angiosperms) plants and the origin and vast diversification of the floral form has been one of the focuses of plant evolutionary developmental biology. The evolving diversity and increasing complexity of organisms is often due to relatively small changes in genes that direct development. These “developmental control genes” and the transcription factors (TFs) they encode, are at the origin of most morphological changes. TFs such as LEAFY (LFY) and the MADS-domain TFs act as central regulators in key developmental processes of plant reproduction including the floral transition in angiosperms and the specification of the male and female organs in both gymnosperms and angiosperms. In addition to advances in genome wide profiling and forward and reverse genetic screening, structural techniques are becoming important tools in unraveling TF function by providing atomic and molecular level information that was lacking in purely genetic approaches. Here, we summarize previous structural work and present additional biophysical and biochemical studies of the key master regulators of plant reproduction – LEAFY and the MADS-domain TFs SEPALLATA3 and AGAMOUS. We discuss the impact of structural biology on our understanding of the complex evolutionary process leading to the development of the bisexual flower. PMID:26779227

Evolutionary versatility of eukaryotic protein domains revealed by their bigram networks

PubMed Central

2011-01-01

Background Protein domains are globular structures of independently folded polypeptides that exert catalytic or binding activities. Their sequences are recognized as evolutionary units that, through genome recombination, constitute protein repertoires of linkage patterns. Via mutations, domains acquire modified functions that contribute to the fitness of cells and organisms. Recent studies have addressed the evolutionary selection that may have shaped the functions of individual domains and the emergence of particular domain combinations, which led to new cellular functions in multi-cellular animals. This study focuses on modeling domain linkage globally and investigates evolutionary implications that may be revealed by novel computational analysis. Results A survey of 77 completely sequenced eukaryotic genomes implies a potential hierarchical and modular organization of biological functions in most living organisms. Domains in a genome or multiple genomes are modeled as a network of hetero-duplex covalent linkages, termed bigrams. A novel computational technique is introduced to decompose such networks, whereby the notion of domain "networking versatility" is derived and measured. The most and least "versatile" domains (termed "core domains" and "peripheral domains" respectively) are examined both computationally via sequence conservation measures and experimentally using selected domains. Our study suggests that such a versatility measure extracted from the bigram networks correlates with the adaptivity of domains during evolution, where the network core domains are highly adaptive, significantly contrasting the network peripheral domains. Conclusions Domain recombination has played a major part in the evolution of eukaryotes attributing to genome complexity. From a system point of view, as the results of selection and constant refinement, networks of domain linkage are structured in a hierarchical modular fashion. Domains with high degree of networking versatility appear to be evolutionary adaptive, potentially through functional innovations. Domain bigram networks are informative as a model of biological functions. The networking versatility indices extracted from such networks for individual domains reflect the strength of evolutionary selection that the domains have experienced. PMID:21849086

Evolutionary versatility of eukaryotic protein domains revealed by their bigram networks.

PubMed

Xie, Xueying; Jin, Jing; Mao, Yongyi

2011-08-18

Protein domains are globular structures of independently folded polypeptides that exert catalytic or binding activities. Their sequences are recognized as evolutionary units that, through genome recombination, constitute protein repertoires of linkage patterns. Via mutations, domains acquire modified functions that contribute to the fitness of cells and organisms. Recent studies have addressed the evolutionary selection that may have shaped the functions of individual domains and the emergence of particular domain combinations, which led to new cellular functions in multi-cellular animals. This study focuses on modeling domain linkage globally and investigates evolutionary implications that may be revealed by novel computational analysis. A survey of 77 completely sequenced eukaryotic genomes implies a potential hierarchical and modular organization of biological functions in most living organisms. Domains in a genome or multiple genomes are modeled as a network of hetero-duplex covalent linkages, termed bigrams. A novel computational technique is introduced to decompose such networks, whereby the notion of domain "networking versatility" is derived and measured. The most and least "versatile" domains (termed "core domains" and "peripheral domains" respectively) are examined both computationally via sequence conservation measures and experimentally using selected domains. Our study suggests that such a versatility measure extracted from the bigram networks correlates with the adaptivity of domains during evolution, where the network core domains are highly adaptive, significantly contrasting the network peripheral domains. Domain recombination has played a major part in the evolution of eukaryotes attributing to genome complexity. From a system point of view, as the results of selection and constant refinement, networks of domain linkage are structured in a hierarchical modular fashion. Domains with high degree of networking versatility appear to be evolutionary adaptive, potentially through functional innovations. Domain bigram networks are informative as a model of biological functions. The networking versatility indices extracted from such networks for individual domains reflect the strength of evolutionary selection that the domains have experienced.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

A Many-Objective Approach to Developing Adaptive Water Supply Portfolios in the 'Research Triangle' Region of North Carolina

NASA Astrophysics Data System (ADS)

Zeff, H. B.; Kasprzyk, J. R.; Reed, P. M.; Characklis, G. W.

2012-12-01

This study uses many-objective evolutionary optimization to quantify the tradeoffs water utilities face when developing flexible water shortage response plans. Alternatives to infrastructure development, such as temporary demand management programs and inter-utility water transfer agreements, allow local water providers to develop portfolios of water supply options capable of adapting to changing hydrologic conditions and growing water demand. The extent to which these options are implemented will be determined by a number of conflicting operational and financial considerations. An integrated reservoir simulation model including four large water utilities in the 'Research Triangle' region of North Carolina is used to evaluate the potential tradeoffs resulting from regional demands on shared infrastructure, customer concerns, and the financial uncertainty caused by the intermittent and irregular nature of drought. Instead of providing one optimal solution, multi-objective evolutionary algorithms (MOEAs) use the concept of non-dominations to discover a set of portfolio options in which no solution is inferior to any other solution in all objectives. Interactive visual analytics enable water providers to explore these tradeoffs and develop water shortage response plans tailored to their individual circumstances. The simulation model is evaluated under a number of different formulations to help identify and visualize the impacts of water efficiency, revenue/cost variability, consumer effects, and inter-utility cooperation. The different problems are formulated by adding portfolio options and objectives in such a way that the lower dimensional problem formulations are sub-sets of the full formulation. The full formulation considers reservoir reliability, water use restriction frequency, total water transfer allotment, total costs, revenue/cost variability, and additional consumer losses during restrictions. The simulation results highlight the inadequacy of lower order, cost-benefit type analyses to evaluate water management techniques as they move beyond the construction of large storage infrastructure. This work can help water providers develop the analytical tools to evaluate complex, adaptive techniques that are becoming more attractive in an era of growing municipal demand, risking infrastructure costs, and uncertain hydrology.

Hyper-heuristic Evolution of Dispatching Rules: A Comparison of Rule Representations.

PubMed

Branke, Jürgen; Hildebrandt, Torsten; Scholz-Reiter, Bernd

2015-01-01

Dispatching rules are frequently used for real-time, online scheduling in complex manufacturing systems. Design of such rules is usually done by experts in a time consuming trial-and-error process. Recently, evolutionary algorithms have been proposed to automate the design process. There are several possibilities to represent rules for this hyper-heuristic search. Because the representation determines the search neighborhood and the complexity of the rules that can be evolved, a suitable choice of representation is key for a successful evolutionary algorithm. In this paper we empirically compare three different representations, both numeric and symbolic, for automated rule design: A linear combination of attributes, a representation based on artificial neural networks, and a tree representation. Using appropriate evolutionary algorithms (CMA-ES for the neural network and linear representations, genetic programming for the tree representation), we empirically investigate the suitability of each representation in a dynamic stochastic job shop scenario. We also examine the robustness of the evolved dispatching rules against variations in the underlying job shop scenario, and visualize what the rules do, in order to get an intuitive understanding of their inner workings. Results indicate that the tree representation using an improved version of genetic programming gives the best results if many candidate rules can be evaluated, closely followed by the neural network representation that already leads to good results for small to moderate computational budgets. The linear representation is found to be competitive only for extremely small computational budgets.

Evolution in an Afternoon: Rapid Natural Selection and Adaptation of Bacterial Populations

ERIC Educational Resources Information Center

Delpech, Roger

2009-01-01

This paper describes a simple, rapid and low-cost technique for growing bacteria (or other microbes) in an environmental gradient, in order to determine the tolerance of the microbial population to varying concentrations of sodium chloride ions, and suggests how the evolutionary response of a microbial population to the selection pressure of the…

Aerospace Safety Advisory Panel report to the NASA acting administrator

NASA Technical Reports Server (NTRS)

1986-01-01

The level of activity of the Aerospace Safety Advisory Panel was increased smewhat during 1985 in concert with the increased mission rate of the National Space Transportation System, the evolutionary changes in management and operation of that program, and the preparation of the Vandenberg Launch Site; the implementation of the Program Definition Phase of the Space Station Program; and the actual flight testing of the X-29 research aircraft. Impending payload STS missions and NASA's overall aircraft operations are reviewed. The safety aspects of the LEASAT salvage mission were assessed. The findings and recommendation of the committee are summerized.

Application study of evolutionary operation methods in optimization of process parameters for mosquito coils industry

NASA Astrophysics Data System (ADS)

Ginting, E.; Tambunanand, M. M.; Syahputri, K.

2018-02-01

Evolutionary Operation Methods (EVOP) is a method that is designed used in the process of running or operating routinely in the company to enables high productivity. Quality is one of the critical factors for a company to win the competition. Because of these conditions, the research for products quality has been done by gathering the production data of the company and make a direct observation to the factory floor especially the drying department to identify the problem which is the high water content in the mosquito incense coil. PT.X which is producing mosquito coils attempted to reduce product defects caused by the inaccuracy of operating conditions. One of the parameters of good quality insect repellent that is water content, that if the moisture content is too high then the product easy to mold and broken, and vice versa if it is too low the products are easily broken and burn shorter hours. Three factors that affect the value of the optimal water content, the stirring time, drying temperature and drying time. To obtain the required conditions Evolutionary Operation (EVOP) methods is used. Evolutionary Operation (EVOP) is used as an efficient technique for optimization of two or three variable experimental parameters using two-level factorial designs with center point. Optimal operating conditions in the experiment are stirring time performed for 20 minutes, drying temperature at 65°C, and drying time for 130 minutes. The results of the analysis based on the method of Evolutionary Operation (EVOP) value is the optimum water content of 6.90%, which indicates the value has approached the optimal in a production plant that is 7%.

Antibody Epitope Analysis to Investigate Folded Structure, Allosteric Conformation, and Evolutionary Lineage of Proteins.

PubMed

Wong, Sienna; Jin, J-P

2017-01-01

Study of folded structure of proteins provides insights into their biological functions, conformational dynamics and molecular evolution. Current methods of elucidating folded structure of proteins are laborious, low-throughput, and constrained by various limitations. Arising from these methods is the need for a sensitive, quantitative, rapid and high-throughput method not only analysing the folded structure of proteins, but also to monitor dynamic changes under physiological or experimental conditions. In this focused review, we outline the foundation and limitations of current protein structure-determination methods prior to discussing the advantages of an emerging antibody epitope analysis for applications in structural, conformational and evolutionary studies of proteins. We discuss the application of this method using representative examples in monitoring allosteric conformation of regulatory proteins and the determination of the evolutionary lineage of related proteins and protein isoforms. The versatility of the method described herein is validated by the ability to modulate a variety of assay parameters to meet the needs of the user in order to monitor protein conformation. Furthermore, the assay has been used to clarify the lineage of troponin isoforms beyond what has been depicted by sequence homology alone, demonstrating the nonlinear evolutionary relationship between primary structure and tertiary structure of proteins. The antibody epitope analysis method is a highly adaptable technique of protein conformation elucidation, which can be easily applied without the need for specialized equipment or technical expertise. When applied in a systematic and strategic manner, this method has the potential to reveal novel and biomedically meaningful information for structure-function relationship and evolutionary lineage of proteins. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Revisiting the age, evolutionary history and species level diversity of the genus Hydra (Cnidaria: Hydrozoa).

PubMed

Schwentner, Martin; Bosch, Thomas C G

2015-10-01

The genus Hydra has long served as a model system in comparative immunology, developmental and evolutionary biology. Despite its relevance for fundamental research, Hydra's evolutionary origins and species level diversity are not well understood. Detailed previous studies using molecular techniques identified several clades within Hydra, but how these are related to described species remained largely an open question. In the present study, we compiled all published sequence data for three mitochondrial and nuclear genes (COI, 16S and ITS), complemented these with some new sequence data and delimited main genetic lineages (=hypothetical species) objectively by employing two DNA barcoding approaches. Conclusions on the species status of these main lineages were based on inferences of reproductive isolation. Relevant divergence times within Hydra were estimated based on relaxed molecular clock analyses with four genes (COI, 16S, EF1α and 28S) and four cnidarians fossil calibration points All in all, 28 main lineages could be delimited, many more than anticipated from earlier studies. Because allopatric distributions were common, inferences of reproductive isolation often remained ambiguous but reproductive isolation was rarely refuted. Our results support three major conclusions which are central for Hydra research: (1) species level diversity was underestimated by molecular studies; (2) species affiliations of several crucial 'workhorses' of Hydra evolutionary research were wrong and (3) crown group Hydra originated ∼200mya. Our results demonstrate that the taxonomy of Hydra requires a thorough revision and that evolutionary studies need to take this into account when interspecific comparisons are made. Hydra originated on Pangea. Three of four extant groups evolved ∼70mya ago, possibly on the northern landmass of Laurasia. Consequently, Hydra's cosmopolitan distribution is the result of transcontinental and transoceanic dispersal. Copyright © 2015 Elsevier Inc. All rights reserved.

Innovations in Undergraduate Science Education: Going Viral.

PubMed

Hatfull, Graham F

2015-08-01

Bacteriophage discovery and genomics provides a powerful and effective platform for integrating missions in research and education. Implementation of the Science Education Alliance Phage Hunters Advancing Genomics and Evolutionary Science (SEA-PHAGES) program facilitates a broad impact by including a diverse array of schools, faculty, and students. The program generates new insights into the diversity and evolution of the bacteriophage population and presents a model for introducing first-year undergraduate students to discovery-based research experiences. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Satellite Power Systems (SPS) concept definition study (Exhibit D). Volume 5: Systems engineering/integration research and technology

NASA Technical Reports Server (NTRS)

Hanley, G. M.

1981-01-01

Guidelines and ground rules followed in the development of requirements for the SPS are presented. Development planning objectives are specified in each of these areas, and evolutionary SPS program scenarios are described for the various concepts studied during the past one year contract. Program descriptions are presented as planning packages of technical tasks, and schedule phasing. Each package identifies the ground based technology effort that will facilitate SPS definitions, designs, development, and operations.

Evolutionary Optimization of Yagi-Uda Antennas

NASA Technical Reports Server (NTRS)

Lohn, Jason D.; Kraus, William F.; Linden, Derek S.; Colombano, Silvano P.

2001-01-01

Yagi-Uda antennas are known to be difficult to design and optimize due to their sensitivity at high gain, and the inclusion of numerous parasitic elements. We present a genetic algorithm-based automated antenna optimization system that uses a fixed Yagi-Uda topology and a byte-encoded antenna representation. The fitness calculation allows the implicit relationship between power gain and sidelobe/backlobe loss to emerge naturally, a technique that is less complex than previous approaches. The genetic operators used are also simpler. Our results include Yagi-Uda antennas that have excellent bandwidth and gain properties with very good impedance characteristics. Results exceeded previous Yagi-Uda antennas produced via evolutionary algorithms by at least 7.8% in mainlobe gain. We also present encouraging preliminary results where a coevolutionary genetic algorithm is used.

Comparison of Multiobjective Evolutionary Algorithms for Operations Scheduling under Machine Availability Constraints

PubMed Central

Frutos, M.; Méndez, M.; Tohmé, F.; Broz, D.

2013-01-01

Many of the problems that arise in production systems can be handled with multiobjective techniques. One of those problems is that of scheduling operations subject to constraints on the availability of machines and buffer capacity. In this paper we analyze different Evolutionary multiobjective Algorithms (MOEAs) for this kind of problems. We consider an experimental framework in which we schedule production operations for four real world Job-Shop contexts using three algorithms, NSGAII, SPEA2, and IBEA. Using two performance indexes, Hypervolume and R2, we found that SPEA2 and IBEA are the most efficient for the tasks at hand. On the other hand IBEA seems to be a better choice of tool since it yields more solutions in the approximate Pareto frontier. PMID:24489502

Recent developments of axial flow compressors under transonic flow conditions

NASA Astrophysics Data System (ADS)

Srinivas, G.; Raghunandana, K.; Satish Shenoy, B.

2017-05-01

The objective of this paper is to give a holistic view of the most advanced technology and procedures that are practiced in the field of turbomachinery design. Compressor flow solver is the turbulence model used in the CFD to solve viscous problems. The popular techniques like Jameson’s rotated difference scheme was used to solve potential flow equation in transonic condition for two dimensional aero foils and later three dimensional wings. The gradient base method is also a popular method especially for compressor blade shape optimization. Various other types of optimization techniques available are Evolutionary algorithms (EAs) and Response surface methodology (RSM). It is observed that in order to improve compressor flow solver and to get agreeable results careful attention need to be paid towards viscous relations, grid resolution, turbulent modeling and artificial viscosity, in CFD. The advanced techniques like Jameson’s rotated difference had most substantial impact on wing design and aero foil. For compressor blade shape optimization, Evolutionary algorithm is quite simple than gradient based technique because it can solve the parameters simultaneously by searching from multiple points in the given design space. Response surface methodology (RSM) is a method basically used to design empirical models of the response that were observed and to study systematically the experimental data. This methodology analyses the correct relationship between expected responses (output) and design variables (input). RSM solves the function systematically in a series of mathematical and statistical processes. For turbomachinery blade optimization recently RSM has been implemented successfully. The well-designed high performance axial flow compressors finds its application in any air-breathing jet engines.

A graph-based evolutionary algorithm: Genetic Network Programming (GNP) and its extension using reinforcement learning.

PubMed

Mabu, Shingo; Hirasawa, Kotaro; Hu, Jinglu

2007-01-01

This paper proposes a graph-based evolutionary algorithm called Genetic Network Programming (GNP). Our goal is to develop GNP, which can deal with dynamic environments efficiently and effectively, based on the distinguished expression ability of the graph (network) structure. The characteristics of GNP are as follows. 1) GNP programs are composed of a number of nodes which execute simple judgment/processing, and these nodes are connected by directed links to each other. 2) The graph structure enables GNP to re-use nodes, thus the structure can be very compact. 3) The node transition of GNP is executed according to its node connections without any terminal nodes, thus the past history of the node transition affects the current node to be used and this characteristic works as an implicit memory function. These structural characteristics are useful for dealing with dynamic environments. Furthermore, we propose an extended algorithm, "GNP with Reinforcement Learning (GNPRL)" which combines evolution and reinforcement learning in order to create effective graph structures and obtain better results in dynamic environments. In this paper, we applied GNP to the problem of determining agents' behavior to evaluate its effectiveness. Tileworld was used as the simulation environment. The results show some advantages for GNP over conventional methods.

Can-Evo-Ens: Classifier stacking based evolutionary ensemble system for prediction of human breast cancer using amino acid sequences.

PubMed

Ali, Safdar; Majid, Abdul

2015-04-01

The diagnostic of human breast cancer is an intricate process and specific indicators may produce negative results. In order to avoid misleading results, accurate and reliable diagnostic system for breast cancer is indispensable. Recently, several interesting machine-learning (ML) approaches are proposed for prediction of breast cancer. To this end, we developed a novel classifier stacking based evolutionary ensemble system "Can-Evo-Ens" for predicting amino acid sequences associated with breast cancer. In this paper, first, we selected four diverse-type of ML algorithms of Naïve Bayes, K-Nearest Neighbor, Support Vector Machines, and Random Forest as base-level classifiers. These classifiers are trained individually in different feature spaces using physicochemical properties of amino acids. In order to exploit the decision spaces, the preliminary predictions of base-level classifiers are stacked. Genetic programming (GP) is then employed to develop a meta-classifier that optimal combine the predictions of the base classifiers. The most suitable threshold value of the best-evolved predictor is computed using Particle Swarm Optimization technique. Our experiments have demonstrated the robustness of Can-Evo-Ens system for independent validation dataset. The proposed system has achieved the highest value of Area Under Curve (AUC) of ROC Curve of 99.95% for cancer prediction. The comparative results revealed that proposed approach is better than individual ML approaches and conventional ensemble approaches of AdaBoostM1, Bagging, GentleBoost, and Random Subspace. It is expected that the proposed novel system would have a major impact on the fields of Biomedical, Genomics, Proteomics, Bioinformatics, and Drug Development. Copyright © 2015 Elsevier Inc. All rights reserved.

A field ornithologist’s guide to genomics: Practical considerations for ecology and conservation

USGS Publications Warehouse

Oyler-McCance, Sara J.; Oh, Kevin; Langin, Kathryn; Aldridge, Cameron L.

2016-01-01

Vast improvements in sequencing technology have made it practical to simultaneously sequence millions of nucleotides distributed across the genome, opening the door for genomic studies in virtually any species. Ornithological research stands to benefit in three substantial ways. First, genomic methods enhance our ability to parse and simultaneously analyze both neutral and non-neutral genomic regions, thus providing insight into adaptive evolution and divergence. Second, the sheer quantity of sequence data generated by current sequencing platforms allows increased precision and resolution in analyses. Third, high-throughput sequencing can benefit applications that focus on a small number of loci that are otherwise prohibitively expensive, time-consuming, and technically difficult using traditional sequencing methods. These advances have improved our ability to understand evolutionary processes like speciation and local adaptation, but they also offer many practical applications in the fields of population ecology, migration tracking, conservation planning, diet analyses, and disease ecology. This review provides a guide for field ornithologists interested in incorporating genomic approaches into their research program, with an emphasis on techniques related to ecology and conservation. We present a general overview of contemporary genomic approaches and methods, as well as important considerations when selecting a genomic technique. We also discuss research questions that are likely to benefit from utilizing high-throughput sequencing instruments, highlighting select examples from recent avian studies.

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

PubMed

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 multiobjective evolutionary algorithm SPEA2(26), and user-specified set of conservation practices and their costs to search for the complete tradeoff frontiers between costs of conservation practices and user-specified water quality objectives. The frontiers quantify the tradeoffs faced by the watershed managers by presenting the full range of costs associated with various water quality improvement goals. The program allows for a selection of watershed configurations achieving specified water quality improvement goals and a production of maps of optimized placement of conservation practices.

NEXT Ion Propulsion System Development Status and Capabilities

NASA Technical Reports Server (NTRS)

Patterson, Michael J.; Benson, Scott W.

2008-01-01

NASA s Evolutionary Xenon Thruster (NEXT) project is developing next generation ion propulsion technologies to provide future NASA science missions with enhanced mission performance benefit at a low total development cost. The objective of the NEXT project is to advance next generation ion propulsion technology by producing engineering model system components, validating these through qualification-level and integrated system testing, and ensuring preparedness for transitioning to flight system development. As NASA s Evolutionary Xenon Thruster technology program completes advanced development activities, it is advantageous to review the existing technology capabilities of the system under development. This paper describes the NEXT ion propulsion system development status, characteristics and performance. A review of mission analyses results conducted to date using the NEXT system is also provided.

Cloning and characterization of new bioluminescent proteins

NASA Astrophysics Data System (ADS)

Szent-Gyorgyi, Christopher; Ballou, Byron T.; Dagnal, Erich; Bryan, Bruce

1999-07-01

Over the past two years Prolume has undertaken a comprehensive program to clone luciferases and associated 'green fluorescent proteins' (GFPs) from marine animals that use coelenterazine as the luciferin. To data we have cloned several bioluminescent proteins, including two novel copepod luciferases and two anthozoan GFPs. These four proteins have sequences that differ greatly form previously cloned analogous proteins; the sequence diversity apparently is due to independent evolutionary origins and unusual evolutionary constraints. Thus coelenterazine-based bioluminescent systems may also manifest a variety of useful properties. We discuss form this taxonomic perspective the initial biochemical and spectral characterization of our cloned proteins. Emphasis is placed on the anthozoan luciferase-GFP systems, whose efficient resonance energy transfer has elicited much current interest.

Darwinian Theory, Functionalism, and the First American Psychological Revolution

ERIC Educational Resources Information Center

Green, Christopher D.

2009-01-01

American functionalist psychology constituted an effort to model scientific psychology on the successes of English evolutionary theory. In part it was a response to the stagnation of Wundt's psychological research program, which had been grounded in German experimental physiology. In part it was an attempt to make psychology more appealing within…

A Review of the Foundational Processes that Influence Beliefs in Climate Change: Opportunities for Environmental Education Research

ERIC Educational Resources Information Center

Brownlee, Matthew T.J.; Powell, Robert B.; Hallo, Jeffery C.

2013-01-01

Recently, many organizations involved in environmental education have initiated programs that aim to educate visitors or other publics who interact with nature-based resources about the impacts and landscape transformations occurring because of climatic changes. However, many psychological, human-evolutionary, and social-ecological processes that…

PBTE (Performance-Based Teacher Education); Vol 2, No, 2, May 1973.

ERIC Educational Resources Information Center

Andrews, Theodore E., Ed.

This issue of the Multi-State Consortium for Performance-Based Teacher Education (PBTE) newsletter discusses (1) the evolutionary approach adopted by the state of Minnesota toward the implementation of PBTE, which includes discussion of what is known about PBTE, whether Minnesota ought (or wishes) to adopt the program, and state participation in…

Mexico's Federal Education Law of 1973; Its Implications for Nonformal Education.

ERIC Educational Resources Information Center

Dobson-Ingram, John R. A.

An evolutionary step in Mexico's nonformal educational development, the Federal Education Law of 1973 was ratified by the President in December 1973. This law covers the purpose of education in Mexico, the national system of education, distribution of responsibilities for education, programs of study, rights and obligations of institutions,…

The Historical Evolutionary Process, by Organization and Function, of the Office of Strategic Services’ Assessment and Selection Program.

DTIC Science & Technology

1999-06-04

This study examines the historical evolution, by organization and functional process, of the Office of Strategic Services (OSS) Assessment and...the organizational evolution is traced through examination of America’s first central intelligence agency, the Office of the Coordinator of Information

Evolutionary Genomics of Defense Systems in Archaea and Bacteria*

PubMed Central

Koonin, Eugene V.; Makarova, Kira S.; Wolf, Yuri I.

2018-01-01

Evolution of bacteria and archaea involves an incessant arms race against an enormous diversity of genetic parasites. Accordingly, a substantial fraction of the genes in most bacteria and archaea are dedicated to antiparasite defense. The functions of these defense systems follow several distinct strategies, including innate immunity; adaptive immunity; and dormancy induction, or programmed cell death. Recent comparative genomic studies taking advantage of the expanding database of microbial genomes and metagenomes, combined with direct experiments, resulted in the discovery of several previously unknown defense systems, including innate immunity centered on Argonaute proteins, bacteriophage exclusion, and new types of CRISPR-Cas systems of adaptive immunity. Some general principles of function and evolution of defense systems are starting to crystallize, in particular, extensive gain and loss of defense genes during the evolution of prokaryotes; formation of genomic defense islands; evolutionary connections between mobile genetic elements and defense, whereby genes of mobile elements are repeatedly recruited for defense functions; the partially selfish and addictive behavior of the defense systems; and coupling between immunity and dormancy induction/programmed cell death. PMID:28657885

CJ concept for advanced aircraft wiring

NASA Technical Reports Server (NTRS)

Redslob, J.

1972-01-01

The techniques and hardware are described which were developed for facilitating the use of flexible flat conductor cable (FFCC) in commercial air transports. The system was designed as an evolutionary transition from the current round wire harnessing to the use of FFCC harnesses. The equipment discussed includes the pressure crimp barrel designed for terminating FFCC, reel-fed applicator, cable connectors and adaptors, and equipment racks.

Feature Selection for Evolutionary Commercial-off-the-Shelf Software: Studies Focusing on Time-to-Market, Innovation and Hedonic-Utilitarian Trade-Offs

ERIC Educational Resources Information Center

Kakar, Adarsh Kumar

2013-01-01

Feature selection is one of the most important decisions made by product managers. This three article study investigates the concepts, tools and techniques for making trade-off decisions of introducing new features in evolving Commercial-Off-The-Shelf (COTS) software products. The first article investigates the efficacy of various feature…

Software Engineering Guidebook

NASA Technical Reports Server (NTRS)

Connell, John; Wenneson, Greg

1993-01-01

The Software Engineering Guidebook describes SEPG (Software Engineering Process Group) supported processes and techniques for engineering quality software in NASA environments. Three process models are supported: structured, object-oriented, and evolutionary rapid-prototyping. The guidebook covers software life-cycles, engineering, assurance, and configuration management. The guidebook is written for managers and engineers who manage, develop, enhance, and/or maintain software under the Computer Software Services Contract.

Germline transformation of the butterfly Bicyclus anynana.

PubMed

Marcus, Jeffrey M; Ramos, Diane M; Monteiro, Antónia

2004-08-07

Ecological and evolutionary theory has frequently been inspired by the diversity of colour patterns on the wings of butterflies. More recently, these varied patterns have also become model systems for studying the evolution of developmental mechanisms. A technique that will facilitate our understanding of butterfly colour-pattern development is germline transformation. Germline transformation permits functional tests of candidate gene products and of cis-regulatory regions, and provides a means of generating new colour-pattern mutants by insertional mutagenesis. We report the successful transformation of the African satyrid butterfly Bicyclus anynana with two different transposable element vectors, Hermes and piggyBac, each carrying EGFP coding sequences driven by the 3XP3 synthetic enhancer that drives gene expression in the eyes. Candidate lines identified by screening for EGFP in adult eyes were later confirmed by PCR amplification of a fragment of the EGFP coding sequence from genomic DNA. Flanking DNA surrounding the insertions was amplified by inverse PCR and sequenced. Transformation rates were 5% for piggyBac and 10.2% for Hermes. Ultimately, the new data generated by these techniques may permit an integrated understanding of the developmental genetics of colour-pattern formation and of the ecological and evolutionary processes in which these patterns play a role.

Evolutionary Optimization of Centrifugal Nozzles for Organic Vapours

NASA Astrophysics Data System (ADS)

Persico, Giacomo

2017-03-01

This paper discusses the shape-optimization of non-conventional centrifugal turbine nozzles for Organic Rankine Cycle applications. The optimal aerodynamic design is supported by the use of a non-intrusive, gradient-free technique specifically developed for shape optimization of turbomachinery profiles. The method is constructed as a combination of a geometrical parametrization technique based on B-Splines, a high-fidelity and experimentally validated Computational Fluid Dynamic solver, and a surrogate-based evolutionary algorithm. The non-ideal gas behaviour featuring the flow of organic fluids in the cascades of interest is introduced via a look-up-table approach, which is rigorously applied throughout the whole optimization process. Two transonic centrifugal nozzles are considered, featuring very different loading and radial extension. The use of a systematic and automatic design method to such a non-conventional configuration highlights the character of centrifugal cascades; the blades require a specific and non-trivial definition of the shape, especially in the rear part, to avoid the onset of shock waves. It is shown that the optimization acts in similar way for the two cascades, identifying an optimal curvature of the blade that both provides a relevant increase of cascade performance and a reduction of downstream gradients.

InterEvDock: a docking server to predict the structure of protein–protein interactions using evolutionary information

PubMed Central

Yu, Jinchao; Vavrusa, Marek; Andreani, Jessica; Rey, Julien; Tufféry, Pierre; Guerois, Raphaël

2016-01-01

The structural modeling of protein–protein interactions is key in understanding how cell machineries cross-talk with each other. Molecular docking simulations provide efficient means to explore how two unbound protein structures interact. InterEvDock is a server for protein docking based on a free rigid-body docking strategy. A systematic rigid-body docking search is performed using the FRODOCK program and the resulting models are re-scored with InterEvScore and SOAP-PP statistical potentials. The InterEvScore potential was specifically designed to integrate co-evolutionary information in the docking process. InterEvDock server is thus particularly well suited in case homologous sequences are available for both binding partners. The server returns 10 structures of the most likely consensus models together with 10 predicted residues most likely involved in the interface. In 91% of all complexes tested in the benchmark, at least one residue out of the 10 predicted is involved in the interface, providing useful guidelines for mutagenesis. InterEvDock is able to identify a correct model among the top10 models for 49% of the rigid-body cases with evolutionary information, making it a unique and efficient tool to explore structural interactomes under an evolutionary perspective. The InterEvDock web interface is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/InterEvDock/. PMID:27131368

Natural language processing, pragmatics, and verbal behavior

PubMed Central

Cherpas, Chris

1992-01-01

Natural Language Processing (NLP) is that part of Artificial Intelligence (AI) concerned with endowing computers with verbal and listener repertoires, so that people can interact with them more easily. Most attention has been given to accurately parsing and generating syntactic structures, although NLP researchers are finding ways of handling the semantic content of language as well. It is increasingly apparent that understanding the pragmatic (contextual and consequential) dimension of natural language is critical for producing effective NLP systems. While there are some techniques for applying pragmatics in computer systems, they are piecemeal, crude, and lack an integrated theoretical foundation. Unfortunately, there is little awareness that Skinner's (1957) Verbal Behavior provides an extensive, principled pragmatic analysis of language. The implications of Skinner's functional analysis for NLP and for verbal aspects of epistemology lead to a proposal for a “user expert”—a computer system whose area of expertise is the long-term computer user. The evolutionary nature of behavior suggests an AI technology known as genetic algorithms/programming for implementing such a system. ImagesFig. 1 PMID:22477052

MONSS: A multi-objective nonlinear simplex search approach

NASA Astrophysics Data System (ADS)

Zapotecas-Martínez, Saúl; Coello Coello, Carlos A.

2016-01-01

This article presents a novel methodology for dealing with continuous box-constrained multi-objective optimization problems (MOPs). The proposed algorithm adopts a nonlinear simplex search scheme in order to obtain multiple elements of the Pareto optimal set. The search is directed by a well-distributed set of weight vectors, each of which defines a scalarization problem that is solved by deforming a simplex according to the movements described by Nelder and Mead's method. Considering an MOP with n decision variables, the simplex is constructed using n+1 solutions which minimize different scalarization problems defined by n+1 neighbor weight vectors. All solutions found in the search are used to update a set of solutions considered to be the minima for each separate problem. In this way, the proposed algorithm collectively obtains multiple trade-offs among the different conflicting objectives, while maintaining a proper representation of the Pareto optimal front. In this article, it is shown that a well-designed strategy using just mathematical programming techniques can be competitive with respect to the state-of-the-art multi-objective evolutionary algorithms against which it was compared.

An efficient model for auxiliary diagnosis of hepatocellular carcinoma based on gene expression programming.

PubMed

Zhang, Li; Chen, Jiasheng; Gao, Chunming; Liu, Chuanmiao; Xu, Kuihua

2018-03-16

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. The early diagnosis of HCC is greatly helpful to achieve long-term disease-free survival. However, HCC is usually difficult to be diagnosed at an early stage. The aim of this study was to create the prediction model to diagnose HCC based on gene expression programming (GEP). GEP is an evolutionary algorithm and a domain-independent problem-solving technique. Clinical data show that six serum biomarkers, including gamma-glutamyl transferase, C-reaction protein, carcinoembryonic antigen, alpha-fetoprotein, carbohydrate antigen 153, and carbohydrate antigen 199, are related to HCC characteristics. In this study, the prediction of HCC was made based on these six biomarkers (195 HCC patients and 215 non-HCC controls) by setting up optimal joint models with GEP. The GEP model discriminated 353 out of 410 subjects, representing a determination coefficient of 86.28% (283/328) and 85.37% (70/82) for training and test sets, respectively. Compared to the results from the support vector machine, the artificial neural network, and the multilayer perceptron, GEP showed a better outcome. The results suggested that GEP modeling was a promising and excellent tool in diagnosis of hepatocellular carcinoma, and it could be widely used in HCC auxiliary diagnosis. Graphical abstract The process to establish an efficient model for auxiliary diagnosis of hepatocellular carcinoma.

Ostracod (Ostracoda, Crustacea) genomics - Promises and challenges.

PubMed

Schön, Isa; Martens, Koen

2016-10-01

Ostracods are well-suited model organisms for evolutionary research. Classic genetic techniques have mostly been used for phylogenetic studies on Ostracoda and were somewhat affected by the lack of large numbers of suitable markers. Genomic methods with their huge potential have so far rarely been applied to this group of crustaceans. We provide relevant examples of genomic studies on other organisms to propose future avenues of genomic ostracod research. At the same time, we suggest solutions to the potential problems in ostracods that the application of genomic techniques might present. Copyright © 2016 Elsevier B.V. All rights reserved.

Divergent gene expression in the conserved dauer stage of the nematodes Pristionchus pacificus and Caenorhabditis elegans.

PubMed

Sinha, Amit; Sommer, Ralf J; Dieterich, Christoph

2012-06-19

An organism can respond to changing environmental conditions by adjusting gene regulation and by forming alternative phenotypes. In nematodes, these mechanisms are coupled because many species will form dauer larvae, a stress-resistant and non-aging developmental stage, when exposed to unfavorable environmental conditions, and execute gene expression programs that have been selected for the survival of the animal in the wild. These dauer larvae represent an environmentally induced, homologous developmental stage across many nematode species, sharing conserved morphological and physiological properties. Hence it can be expected that some core components of the associated transcriptional program would be conserved across species, while others might diverge over the course of evolution. However, transcriptional and metabolic analysis of dauer development has been largely restricted to Caenorhabditis elegans. Here, we use a transcriptomic approach to compare the dauer stage in the evolutionary model system Pristionchus pacificus with the dauer stage in C. elegans. We have employed Agilent microarrays, which represent 20,446 P. pacificus and 20,143 C. elegans genes to show an unexpected divergence in the expression profiles of these two nematodes in dauer and dauer exit samples. P. pacificus and C. elegans differ in the dynamics and function of genes that are differentially expressed. We find that only a small number of orthologous gene pairs show similar expression pattern in the dauers of the two species, while the non-orthologous fraction of genes is a major contributor to the active transcriptome in dauers. Interestingly, many of the genes acquired by horizontal gene transfer and orphan genes in P. pacificus, are differentially expressed suggesting that these genes are of evolutionary and functional importance. Our data set provides a catalog for future functional investigations and indicates novel insight into evolutionary mechanisms. We discuss the limited conservation of core developmental and transcriptional programs as a common aspect of animal evolution.

Divergent gene expression in the conserved dauer stage of the nematodes Pristionchus pacificus and Caenorhabditis elegans

PubMed Central

2012-01-01

Background An organism can respond to changing environmental conditions by adjusting gene regulation and by forming alternative phenotypes. In nematodes, these mechanisms are coupled because many species will form dauer larvae, a stress-resistant and non-aging developmental stage, when exposed to unfavorable environmental conditions, and execute gene expression programs that have been selected for the survival of the animal in the wild. These dauer larvae represent an environmentally induced, homologous developmental stage across many nematode species, sharing conserved morphological and physiological properties. Hence it can be expected that some core components of the associated transcriptional program would be conserved across species, while others might diverge over the course of evolution. However, transcriptional and metabolic analysis of dauer development has been largely restricted to Caenorhabditis elegans. Here, we use a transcriptomic approach to compare the dauer stage in the evolutionary model system Pristionchus pacificus with the dauer stage in C. elegans. Results We have employed Agilent microarrays, which represent 20,446 P. pacificus and 20,143 C. elegans genes to show an unexpected divergence in the expression profiles of these two nematodes in dauer and dauer exit samples. P. pacificus and C. elegans differ in the dynamics and function of genes that are differentially expressed. We find that only a small number of orthologous gene pairs show similar expression pattern in the dauers of the two species, while the non-orthologous fraction of genes is a major contributor to the active transcriptome in dauers. Interestingly, many of the genes acquired by horizontal gene transfer and orphan genes in P. pacificus, are differentially expressed suggesting that these genes are of evolutionary and functional importance. Conclusion Our data set provides a catalog for future functional investigations and indicates novel insight into evolutionary mechanisms. We discuss the limited conservation of core developmental and transcriptional programs as a common aspect of animal evolution. PMID:22712530

Mining protein database using machine learning techniques.

PubMed

Camargo, Renata da Silva; Niranjan, Mahesan

2008-08-25

With a large amount of information relating to proteins accumulating in databases widely available online, it is of interest to apply machine learning techniques that, by extracting underlying statistical regularities in the data, make predictions about the functional and evolutionary characteristics of unseen proteins. Such predictions can help in achieving a reduction in the space over which experiment designers need to search in order to improve our understanding of the biochemical properties. Previously it has been suggested that an integration of features computable by comparing a pair of proteins can be achieved by an artificial neural network, hence predicting the degree to which they may be evolutionary related and homologous.
We compiled two datasets of pairs of proteins, each pair being characterised by seven distinct features. We performed an exhaustive search through all possible combinations of features, for the problem of separating remote homologous from analogous pairs, we note that significant performance gain was obtained by the inclusion of sequence and structure information. We find that the use of a linear classifier was enough to discriminate a protein pair at the family level. However, at the superfamily level, to detect remote homologous pairs was a relatively harder problem. We find that the use of nonlinear classifiers achieve significantly higher accuracies.
In this paper, we compare three different pattern classification methods on two problems formulated as detecting evolutionary and functional relationships between pairs of proteins, and from extensive cross validation and feature selection based studies quantify the average limits and uncertainties with which such predictions may be made. Feature selection points to a \\"knowledge gap\\" in currently available functional annotations. We demonstrate how the scheme may be employed in a framework to associate an individual protein with an existing family of evolutionarily related proteins.

Evolutionary Computing Methods for Spectral Retrieval

NASA Technical Reports Server (NTRS)

Terrile, Richard; Fink, Wolfgang; Huntsberger, Terrance; Lee, Seugwon; Tisdale, Edwin; VonAllmen, Paul; Tinetti, Geivanna

2009-01-01

A methodology for processing spectral images to retrieve information on underlying physical, chemical, and/or biological phenomena is based on evolutionary and related computational methods implemented in software. In a typical case, the solution (the information that one seeks to retrieve) consists of parameters of a mathematical model that represents one or more of the phenomena of interest. The methodology was developed for the initial purpose of retrieving the desired information from spectral image data acquired by remote-sensing instruments aimed at planets (including the Earth). Examples of information desired in such applications include trace gas concentrations, temperature profiles, surface types, day/night fractions, cloud/aerosol fractions, seasons, and viewing angles. The methodology is also potentially useful for retrieving information on chemical and/or biological hazards in terrestrial settings. In this methodology, one utilizes an iterative process that minimizes a fitness function indicative of the degree of dissimilarity between observed and synthetic spectral and angular data. The evolutionary computing methods that lie at the heart of this process yield a population of solutions (sets of the desired parameters) within an accuracy represented by a fitness-function value specified by the user. The evolutionary computing methods (ECM) used in this methodology are Genetic Algorithms and Simulated Annealing, both of which are well-established optimization techniques and have also been described in previous NASA Tech Briefs articles. These are embedded in a conceptual framework, represented in the architecture of the implementing software, that enables automatic retrieval of spectral and angular data and analysis of the retrieved solutions for uniqueness.

A priori and a posteriori approaches for finding genes of evolutionary interest in non-model species: osmoregulatory genes in the kidney transcriptome of the desert rodent Dipodomys spectabilis (banner-tailed kangaroo rat).

PubMed

Marra, Nicholas J; Eo, Soo Hyung; Hale, Matthew C; Waser, Peter M; DeWoody, J Andrew

2012-12-01

One common goal in evolutionary biology is the identification of genes underlying adaptive traits of evolutionary interest. Recently next-generation sequencing techniques have greatly facilitated such evolutionary studies in species otherwise depauperate of genomic resources. Kangaroo rats (Dipodomys sp.) serve as exemplars of adaptation in that they inhabit extremely arid environments, yet require no drinking water because of ultra-efficient kidney function and osmoregulation. As a basis for identifying water conservation genes in kangaroo rats, we conducted a priori bioinformatics searches in model rodents (Mus musculus and Rattus norvegicus) to identify candidate genes with known or suspected osmoregulatory function. We then obtained 446,758 reads via 454 pyrosequencing to characterize genes expressed in the kidney of banner-tailed kangaroo rats (Dipodomys spectabilis). We also determined candidates a posteriori by identifying genes that were overexpressed in the kidney. The kangaroo rat sequences revealed nine different a priori candidate genes predicted from our Mus and Rattus searches, as well as 32 a posteriori candidate genes that were overexpressed in kidney. Mutations in two of these genes, Slc12a1 and Slc12a3, cause human renal diseases that result in the inability to concentrate urine. These genes are likely key determinants of physiological water conservation in desert rodents. Copyright © 2012 Elsevier Inc. All rights reserved.

Programmed cell death as a defence against infection

PubMed Central

Jorgensen, Ine; Rayamajhi, Manira; Miao, Edward A.

2017-01-01

Eukaryotic cells can die from physical trauma, resulting in necrosis. Alternately, they can die via programmed cell death upon stimulation of specific signalling pathways. Here we discuss the utility of four cell death pathways in innate immune defence against bacterial and viral infection: apoptosis, necroptosis, pyroptosis and NETosis. We describe the interactions that interweave different programmed cell death pathways, which create complex signalling networks that cross-guard each other in the evolutionary arms race with pathogens. Finally, we describe how the resulting cell corpses — apoptotic bodies, pore-induced intracellular traps (PITs) and neutrophil extracellular traps (NETs) — promote clearance of infection. PMID:28138137

Pareto-optimal phylogenetic tree reconciliation

PubMed Central

Libeskind-Hadas, Ran; Wu, Yi-Chieh; Bansal, Mukul S.; Kellis, Manolis

2014-01-01

Motivation: Phylogenetic tree reconciliation is a widely used method for reconstructing the evolutionary histories of gene families and species, hosts and parasites and other dependent pairs of entities. Reconciliation is typically performed using maximum parsimony, in which each evolutionary event type is assigned a cost and the objective is to find a reconciliation of minimum total cost. It is generally understood that reconciliations are sensitive to event costs, but little is understood about the relationship between event costs and solutions. Moreover, choosing appropriate event costs is a notoriously difficult problem. Results: We address this problem by giving an efficient algorithm for computing Pareto-optimal sets of reconciliations, thus providing the first systematic method for understanding the relationship between event costs and reconciliations. This, in turn, results in new techniques for computing event support values and, for cophylogenetic analyses, performing robust statistical tests. We provide new software tools and demonstrate their use on a number of datasets from evolutionary genomic and cophylogenetic studies. Availability and implementation: Our Python tools are freely available at www.cs.hmc.edu/∼hadas/xscape. Contact: mukul@engr.uconn.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24932009

Phylogenetic Quantification of Intra-tumour Heterogeneity

PubMed Central

Schwarz, Roland F.; Trinh, Anne; Sipos, Botond; Brenton, James D.; Goldman, Nick; Markowetz, Florian

2014-01-01

Intra-tumour genetic heterogeneity is the result of ongoing evolutionary change within each cancer. The expansion of genetically distinct sub-clonal populations may explain the emergence of drug resistance, and if so, would have prognostic and predictive utility. However, methods for objectively quantifying tumour heterogeneity have been missing and are particularly difficult to establish in cancers where predominant copy number variation prevents accurate phylogenetic reconstruction owing to horizontal dependencies caused by long and cascading genomic rearrangements. To address these challenges, we present MEDICC, a method for phylogenetic reconstruction and heterogeneity quantification based on a Minimum Event Distance for Intra-tumour Copy-number Comparisons. Using a transducer-based pairwise comparison function, we determine optimal phasing of major and minor alleles, as well as evolutionary distances between samples, and are able to reconstruct ancestral genomes. Rigorous simulations and an extensive clinical study show the power of our method, which outperforms state-of-the-art competitors in reconstruction accuracy, and additionally allows unbiased numerical quantification of tumour heterogeneity. Accurate quantification and evolutionary inference are essential to understand the functional consequences of tumour heterogeneity. The MEDICC algorithms are independent of the experimental techniques used and are applicable to both next-generation sequencing and array CGH data. PMID:24743184

Genetic drift and selection in many-allele range expansions.

PubMed

Weinstein, Bryan T; Lavrentovich, Maxim O; Möbius, Wolfram; Murray, Andrew W; Nelson, David R

2017-12-01

We experimentally and numerically investigate the evolutionary dynamics of four competing strains of E. coli with differing expansion velocities in radially expanding colonies. We compare experimental measurements of the average fraction, correlation functions between strains, and the relative rates of genetic domain wall annihilations and coalescences to simulations modeling the population as a one-dimensional ring of annihilating and coalescing random walkers with deterministic biases due to selection. The simulations reveal that the evolutionary dynamics can be collapsed onto master curves governed by three essential parameters: (1) an expansion length beyond which selection dominates over genetic drift; (2) a characteristic angular correlation describing the size of genetic domains; and (3) a dimensionless constant quantifying the interplay between a colony's curvature at the frontier and its selection length scale. We measure these parameters with a new technique that precisely measures small selective differences between spatially competing strains and show that our simulations accurately predict the dynamics without additional fitting. Our results suggest that the random walk model can act as a useful predictive tool for describing the evolutionary dynamics of range expansions composed of an arbitrary number of genotypes with different fitnesses.

From head to tail: new models and approaches in primate functional anatomy and biomechanics.

PubMed

Organ, Jason M; Deleon, Valerie B; Wang, Qian; Smith, Timothy D

2010-04-01

This special issue of The Anatomical Record (AR) is based on interest generated by a symposium at the 2008 annual meeting of the American Association of Anatomists (AAA) at Experimental Biology, entitled "An Evolutionary Perspective on Human Anatomy." The development of this volume in turn provided impetus for a Biological Anthropology Mini-Meeting, organized by members of the AAA for the 2010 Experimental Biology meeting in Anaheim, California. The research presented in these pages reflects the themes of these symposia and provides a snapshot of the current state of primate functional anatomy and biomechanics research. The 17 articles in this special issue utilize new models and/or approaches to study long-standing questions about the evolution of our closest relatives, including soft-tissue dissection and microanatomical techniques, experimental approaches to morphology, kinematic and kinetic biomechanics, high-resolution computed tomography, and Finite Element Analysis (FEA). This volume continues a close historical association between the disciplines of anatomy and biological anthropology: anatomists benefit from an understanding of the evolutionary history of our modern form, and biological anthropologists rely on anatomical principles to make informed evolutionary inferences about our closest relatives. (c) 2010 Wiley-Liss, Inc.

Molecular evolution and phylodynamics of hepatitis B virus infection circulating in Iran.

PubMed

Mozhgani, Sayed-Hamidreza; Malekpour, Seyed Amir; Norouzi, Mehdi; Ramezani, Fatemeh; Rezaee, Seyed Abdolrahim; Poortahmasebi, Vahdat; Sadeghi, Mehdi; Alavian, Seyed Moayed; Zarei-Ghobadi, Mohadeseh; Ghaziasadi, Azam; Karimzadeh, Hadi; Malekzadeh, Reza; Ziaee, Masood; Abedi, Farshid; Ataei, Behrooz; Yaran, Majid; Sayad, Babak; Jahantigh, Hamid Reza; Somi, Mohammad Hossein; Sarizadeh, Gholamreza; Sanei-Moghaddam, Ismail; Mansour-Ghanaei, Fariborz; Keyvani, Hossein; Kalantari, Ebrahim; Fakhari, Zahra; Geravand, Babak; Jazayeri, Seyed Mohammad

2018-06-01

Previous local and national Iranian publications indicate that all Iranian hepatitis B virus (HBV) strains belong to HBV genotype D. The aim of this study was to analyze the evolutionary history of HBV infection in Iran for the first time, based on an intensive phylodynamic study. The evolutionary parameters, time to most recent common ancestor (tMRCA), and the population dynamics of infections were investigated using the Bayesian Monte Carlo Markov chain (BMCMC). The effective sample size (ESS) and sampling convergence were then monitored. After sampling from the posterior distribution of the nucleotide substitution rate and other evolutionary parameters, the point estimations (median) of these parameters were obtained. All Iranian HBV isolates were of genotype D, sub-type ayw2. The origin of HBV is regarded as having evolved first on the eastern border, before moving westward, where Isfahan province then hosted the virus. Afterwards, the virus moved to the south and west of the country. The tMRCA of HBV in Iran was estimated to be around 1894, with a 95% credible interval between the years 1701 and 1957. The effective number of infections increased exponentially from around 1925 to 1960. Conversely, from around 1992 onwards, the effective number of HBV infections has decreased at a very high rate. Phylodynamic inference clearly demonstrates a unique homogenous pattern of HBV genotype D compatible with a steady configuration of the decreased effective number of infections in the population in recent years, possibly due to the implementation of blood donation screening and vaccination programs. Adequate molecular epidemiology databases for HBV are crucial for infection prevention and treatment programs.

Developmental studies of the lamprey and hierarchical evolutionary steps towards the acquisition of the jaw

PubMed Central

Kuratani, Shigeru

2005-01-01

The evolution of animal morphology can be understood as a series of changes in developmental programs. Among vertebrates, some developmental stages are conserved across species, representing particular developmental constraints. One of the most conserved stages is the vertebrate pharyngula, in which similar embryonic morphology is observed and the Hox code is clearly expressed. The oral developmental program also appears to be constrained to some extent, as both its morphology and the the Hox-code-default state of the oropharyngeal region are well conserved between the lamprey and gnathostome embryos. These features do not by themselves explain the evolution of jaws, but should be regarded as a prerequisite for evolutionary diversification of the mandibular arch. By comparing the pharyngula morphology of the lamprey and gnathostomes, it has become clear that the oral pattern is not entirely identical; in particular, the positional differentiation of the rostral ectomesenchyme is shifted between these animals. Therefore, the jaw seems to have arisen as an evolutionary novelty by overriding ancestral constraints, a process in which morphological homologies are partially lost. This change involves the heterotopic shift of tissue interaction, which appears to have been preceded by the transition from monorhiny to diplorhiny, as well as separation of the hypophysis. When gene expression patterns are compared between the lamprey and gnathostomes, cell-autonomously functioning genes tend to be associated with identical cell types or equivalent anatomical domains, whereas growth-factor-encoding genes have changed their expression domains during evolution. Thus, the heterotopic evolution may be based on changes in the regulation of signalling-molecule-encoding genes. PMID:16313390

The Evolution of Biological Complexity in Digital Organisms

NASA Astrophysics Data System (ADS)

Ofria, Charles

2013-03-01

When Darwin first proposed his theory of evolution by natural selection, he realized that it had a problem explaining the origins of traits of ``extreme perfection and complication'' such as the vertebrate eye. Critics of Darwin's theory have latched onto this perceived flaw as a proof that Darwinian evolution is impossible. In anticipation of this issue, Darwin described the perfect data needed to understand this process, but lamented that such data are ``scarcely ever possible'' to obtain. In this talk, I will discuss research where we use populations of digital organisms (self-replicating and evolving computer programs) to elucidate the genetic and evolutionary processes by which new, highly-complex traits arise, drawing inspiration directly from Darwin's wistful thinking and hypotheses. During the process of evolution in these fully-transparent computational environments we can measure the incorporation of new information into the genome, a process akin to a natural Maxwell's Demon, and identify the original source of any such information. We show that, as Darwin predicted, much of the information used to encode a complex trait was already in the genome as part of simpler evolved traits, and that many routes must be possible for a new complex trait to have a high probability of successfully evolving. In even more extreme examples of the evolution of complexity, we are now using these same principles to examine the evolutionary dynamics the drive major transitions in evolution; that is transitions to higher-levels of organization, which are some of the most complex evolutionary events to occur in nature. Finally, I will explore some of the implications of this research to other aspects of evolutionary biology and as well as ways that these evolutionary principles can be applied toward solving computational and engineering problems.

Deuterium and 15N fractionation in N2H+ during the formation of a Sun-like star

NASA Astrophysics Data System (ADS)

De Simone, M.; Fontani, F.; Codella, C.; Ceccarelli, C.; Lefloch, B.; Bachiller, R.; López-Sepulcre, A.; Caux, E.; Vastel, C.; Soldateschi, J.

2018-05-01

Although chemical models predict that the deuterium fractionation in N2H+ is a good evolutionary tracer in the star formation process, the fractionation of nitrogen is still a poorly understood process. Recent models have questioned the similar evolutionary trend expected for the two fractionation mechanisms in N2H+, based on a classical scenario in which ion-neutral reactions occurring in cold gas should have caused an enhancement of the abundance of N2D+, 15NNH+, and N15NH+. In the framework of the ASAI IRAM-30m large program, we have investigated the fractionation of deuterium and 15N in N2H+ in the best known representatives of the different evolutionary stages of the Sun-like star formation process. The goal is to ultimately confirm (or deny) the classical `ion-neutral reactions' scenario that predicts a similar trend for D and 15N fractionation. We do not find any evolutionary trend of the 14N/15N ratio from both the 15NNH+ and N15NH+ isotopologues. Therefore, our findings confirm that, during the formation of a Sun-like star, the core evolution is irrelevant in the fractionation of 15N. The independence of the 14N/15N ratio with time, found also in high-mass star-forming cores, indicates that the enrichment in 15N revealed in comets and protoplanetary discs is unlikely to happen at core scales. Nevertheless, we have firmly confirmed the evolutionary trend expected for the H/D ratio, with the N2H+/N2D+ ratio decreasing before the pre-stellar core phase, and increasing monotonically during the protostellar phase. We have also confirmed clearly that the two fractionation mechanisms are not related.

Use of gene-expression programming to estimate Manning’s roughness coefficient for high gradient streams

USGS Publications Warehouse

Azamathulla, H. Md.; Jarrett, Robert D.

2013-01-01

Manning’s roughness coefficient (n) has been widely used in the estimation of flood discharges or depths of flow in natural channels. Therefore, the selection of appropriate Manning’s nvalues is of paramount importance for hydraulic engineers and hydrologists and requires considerable experience, although extensive guidelines are available. Generally, the largest source of error in post-flood estimates (termed indirect measurements) is due to estimates of Manning’s n values, particularly when there has been minimal field verification of flow resistance. This emphasizes the need to improve methods for estimating n values. The objective of this study was to develop a soft computing model in the estimation of the Manning’s n values using 75 discharge measurements on 21 high gradient streams in Colorado, USA. The data are from high gradient (S > 0.002 m/m), cobble- and boulder-bed streams for within bank flows. This study presents Gene-Expression Programming (GEP), an extension of Genetic Programming (GP), as an improved approach to estimate Manning’s roughness coefficient for high gradient streams. This study uses field data and assessed the potential of gene-expression programming (GEP) to estimate Manning’s n values. GEP is a search technique that automatically simplifies genetic programs during an evolutionary processes (or evolves) to obtain the most robust computer program (e.g., simplify mathematical expressions, decision trees, polynomial constructs, and logical expressions). Field measurements collected by Jarrett (J Hydraulic Eng ASCE 110: 1519–1539, 1984) were used to train the GEP network and evolve programs. The developed network and evolved programs were validated by using observations that were not involved in training. GEP and ANN-RBF (artificial neural network-radial basis function) models were found to be substantially more effective (e.g., R2 for testing/validation of GEP and RBF-ANN is 0.745 and 0.65, respectively) than Jarrett’s (J Hydraulic Eng ASCE 110: 1519–1539, 1984) equation (R2 for testing/validation equals 0.58) in predicting the Manning’s n.

Social traits, social networks and evolutionary biology.

PubMed

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 effects) provides the potential to understand how entire networks of social interactions in populations influence phenotypes and predict how these traits may evolve. By theoretical integration of social network analysis and quantitative genetics, we hope to identify areas of compatibility and incompatibility and to direct research efforts towards the most promising areas. Continuing this synthesis could provide important insights into the evolution of traits expressed in a social context and the evolutionary consequences of complex and nuanced social phenotypes. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Back to the Future - Part 2. Post-mortem assessment and evolutionary role of the bio-medicolegal sciences.

PubMed

Ferrara, Santo Davide; Cecchetto, Giovanni; Cecchi, Rossana; Favretto, Donata; Grabherr, Silke; Ishikawa, Takaki; Kondo, Toshikazu; Montisci, Massimo; Pfeiffer, Heidi; Bonati, Maurizio Rippa; Shokry, Dina; Vennemann, Marielle; Bajanowski, Thomas

2017-07-01

Part 2 of the review "Back to the Future" is dedicated to the evolutionary role of the bio-medicolegal sciences, reporting the historical profiles, the state of the art, and prospects for future development of the main related techniques and methods of the ancillary disciplines that have risen to the role of "autonomous" sciences, namely, Genetics and Genomics, Toxicology, Radiology, and Imaging, involved in historic synergy in the "post-mortem assessment," together with the mother discipline Legal Medicine, by way of its primary fundament, universally denominated as Forensic Pathology. The evolution of the scientific research and the increased accuracy of the various disciplines will be oriented towards the elaboration of an "algorithm," able to weigh the value of "evidence" placed at the disposal of the "justice system" as real truth and proof.

Evolutionary approaches to cultural and linguistic diversity.

PubMed

Steele, James; Jordan, Peter; Cochrane, Ethan

2010-12-12

Evolutionary approaches to cultural change are increasingly influential, and many scientists believe that a 'grand synthesis' is now in sight. The papers in this Theme Issue, which derives from a symposium held by the AHRC Centre for the Evolution of Cultural Diversity (University College London) in December 2008, focus on how the phylogenetic tree-building and network-based techniques used to estimate descent relationships in biology can be adapted to reconstruct cultural histories, where some degree of inter-societal diffusion will almost inevitably be superimposed on any deeper signal of a historical branching process. The disciplines represented include the three most purely 'cultural' fields from the four-field model of anthropology (cultural anthropology, archaeology and linguistic anthropology). In this short introduction, some context is provided from the history of anthropology, and key issues raised by the papers are highlighted.

Evolutionary approaches to cultural and linguistic diversity

PubMed Central

Steele, James; Jordan, Peter; Cochrane, Ethan

2010-01-01

Evolutionary approaches to cultural change are increasingly influential, and many scientists believe that a ‘grand synthesis’ is now in sight. The papers in this Theme Issue, which derives from a symposium held by the AHRC Centre for the Evolution of Cultural Diversity (University College London) in December 2008, focus on how the phylogenetic tree-building and network-based techniques used to estimate descent relationships in biology can be adapted to reconstruct cultural histories, where some degree of inter-societal diffusion will almost inevitably be superimposed on any deeper signal of a historical branching process. The disciplines represented include the three most purely ‘cultural’ fields from the four-field model of anthropology (cultural anthropology, archaeology and linguistic anthropology). In this short introduction, some context is provided from the history of anthropology, and key issues raised by the papers are highlighted. PMID:21041203

Hybrid soft computing systems for electromyographic signals analysis: a review.

PubMed

Xie, Hong-Bo; Guo, Tianruo; Bai, Siwei; Dokos, Socrates

2014-02-03

Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis.

Hybrid soft computing systems for electromyographic signals analysis: a review

PubMed Central

2014-01-01

Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis. PMID:24490979

Artificial Intelligence in Sports Biomechanics: New Dawn or False Hope?

PubMed Central

Bartlett, Roger

2006-01-01

This article reviews developments in the use of Artificial Intelligence (AI) in sports biomechanics over the last decade. It outlines possible uses of Expert Systems as diagnostic tools for evaluating faults in sports movements (‘techniques’) and presents some example knowledge rules for such an expert system. It then compares the analysis of sports techniques, in which Expert Systems have found little place to date, with gait analysis, in which they are routinely used. Consideration is then given to the use of Artificial Neural Networks (ANNs) in sports biomechanics, focusing on Kohonen self-organizing maps, which have been the most widely used in technique analysis, and multi-layer networks, which have been far more widely used in biomechanics in general. Examples of the use of ANNs in sports biomechanics are presented for javelin and discus throwing, shot putting and football kicking. I also present an example of the use of Evolutionary Computation in movement optimization in the soccer throw in, which predicted an optimal technique close to that in the coaching literature. After briefly overviewing the use of AI in both sports science and biomechanics in general, the article concludes with some speculations about future uses of AI in sports biomechanics. Key Points Expert Systems remain almost unused in sports biomechanics, unlike in the similar discipline of gait analysis. Artificial Neural Networks, particularly Kohonen Maps, have been used, although their full value remains unclear. Other AI applications, including Evolutionary Computation, have received little attention. PMID:24357939

Analysis of Effects of Organizational Behavior on Evolving System of Systems Acquisition Programs Through Agent Based Modeling

DTIC Science & Technology

2013-03-01

function is based on how individualistic or collectivistic a system is. Low individualism values mean the system is more collective and is less likely...Hofstede’s cultural dimensions, integrated with a modified version of the Bak- Sneppen biological evolutionary model, this research highlights which set...14 Hofstede’s Cultural Dimensions

Evolutionary Developmental Linguistics: Naturalization of the Faculty of Language

ERIC Educational Resources Information Center

Locke, John L.

2009-01-01

Since language is a biological trait, it is necessary to investigate its evolution, development, and functions, along with the mechanisms that have been set aside, and are now recruited, for its acquisition and use. It is argued here that progress toward each of these goals can be facilitated by new programs of research, carried out within a new…

A phase one AR/C system design

NASA Technical Reports Server (NTRS)

Kachmar, Peter M.; Polutchko, Robert J.; Matusky, Martin; Chu, William; Jackson, William; Montez, Moises

1991-01-01

The Phase One AR&C System Design integrates an evolutionary design based on the legacy of previous mission successes, flight tested components from manned Rendezvous and Proximity Operations (RPO) space programs, and additional AR&C components validated using proven methods. The Phase One system has a modular, open architecture with the standardized interfaces proposed for Space Station Freedom system architecture.

Digital Learning and Teaching: Evaluation of Developments for Students in Higher Education.

ERIC Educational Resources Information Center

McClelland, Bob

2001-01-01

Focuses on an undergraduate module which served to provide a rationale for a web-based teaching, learning, and a support environment for academic staff and students. Explores module/program support development possibilities on the web from academic, quality, and commercial perspectives as well as the cybernetic and evolutionary nature of learning.…

Saving seeds: Optimally planning our Ex Situ conservation collections to ensure species' evolutionary potential

Treesearch

Sean M. Hoban

2017-01-01

In the face of ongoing environmental change, conservation and natural resource agencies are initiating or expanding ex situ seed collections from natural plant populations. Seed collections have many uses, including in provenance trials, breeding programs, seed orchards, gene banks for long-term conservation (live plants or seeds), restoration, reforestation, and...

National Dam Safety Program. West Millpond Dam (NY 01060), Mohawk River Basin, City of Gloversville, Fulton County, New York. Phase I Inspection Report,

DTIC Science & Technology

1981-09-02

numerous and constantly changing internal and external con- ditions, and is evolutionary in nature. It would be incorrect to assume that the present...to seepage and piping ( internal erosion) problems if a tree blows over and pulls out its roots or if a tree dies and its roots rot. The roots of...for the actual size of the drainage area (same for 10 square miles or less) were inputted to the program as percentages of the index PKF in

Power-Aware Intrusion Detection in Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Şen, Sevil; Clark, John A.; Tapiador, Juan E.

Mobile ad hoc networks (MANETs) are a highly promising new form of networking. However they are more vulnerable to attacks than wired networks. In addition, conventional intrusion detection systems (IDS) are ineffective and inefficient for highly dynamic and resource-constrained environments. Achieving an effective operational MANET requires tradeoffs to be made between functional and non-functional criteria. In this paper we show how Genetic Programming (GP) together with a Multi-Objective Evolutionary Algorithm (MOEA) can be used to synthesise intrusion detection programs that make optimal tradeoffs between security criteria and the power they consume.

Using parallel evolutionary development for a biologically-inspired computer vision system for mobile robots.

PubMed

Wright, Cameron H G; Barrett, Steven F; Pack, Daniel J

2005-01-01

We describe a new approach to attacking the problem of robust computer vision for mobile robots. The overall strategy is to mimic the biological evolution of animal vision systems. Our basic imaging sensor is based upon the eye of the common house fly, Musca domestica. The computational algorithms are a mix of traditional image processing, subspace techniques, and multilayer neural networks.

Strategic Decision Games: Improving Strategic Intuition

DTIC Science & Technology

2007-04-23

this is useful and enlightening , the truly powerful method of learning mathematical techniques is to work through many and various problems using...about, and approaches to, that new world. - General Tony Zinni, The Battle for Peace In 1972, evolutionary scientists Stephen Jay Gould and Niles... neurology and cognitive science, has identified a phenomenon similar to intuition that he calls “Intelligent Memory.” Dr. Gordon describes

Traffic Dimensioning and Performance Modeling of 4G LTE Networks

ERIC Educational Resources Information Center

Ouyang, Ye

2011-01-01

Rapid changes in mobile techniques have always been evolutionary, and the deployment of 4G Long Term Evolution (LTE) networks will be the same. It will be another transition from Third Generation (3G) to Fourth Generation (4G) over a period of several years, as is the case still with the transition from Second Generation (2G) to 3G. As a result,…

UAV Swarm Mission Planning Development Using Evolutionary Algorithms - Part I

DTIC Science & Technology

2008-05-01

desired behaviors in autonomous vehicles is a difficult problem at best and in general prob- ably impossible to completely resolve in complex dynamic...associated behaviors. Various techniques inspired by biological self-organized systems as found in forging insects and flocking birds, revolve around...swarms of heterogeneous vehicles in a distributed simulation system with animated graphics. Statistical measurements and observations indicate that bio

Evolutionary helium and CNO anomalies in the atmospheres and winds of massive hot stars

NASA Technical Reports Server (NTRS)

Walborn, Nolan R.

1987-01-01

The ubiquitous evidence for processed materials in the atmospheres, winds, and circumstellar ejecta of massive stars is reviewed. A broad array of normal and peculiar evolutionary stages is considered, up to and including Type II supernova progenitors. The quantitative analysis of these spectra is difficult, and until recently for the most part only qualitative or approximate results have been available. However, several important current programs promise reliable abundance calculations. A significant emerging result is that the morphologically normal majority of both hot and cold supergiants may already display an admixture of CNO-cycle products in their atmospheres. It may become possible in this way to identify blue supergiants returning from the red supergiant region, as appears to have been the case for the SN 1987A progenitor.

Hunting for swinging millisecond pulsars with XMM-Newton

NASA Astrophysics Data System (ADS)

Papitto, Alessandro

2013-10-01

The recent XMM discovery of a millisecond pulsar swinging between an accretion- powered (X-ray) and a rotation-powered (radio) pulsar state provided the final evidence of the evolutionary link between these two classes, demonstrating that transitions between the two states can be observed over of a few weeks. We propose a ToO program (made of 3 triggers of 60 ks, over a 3years timescale) aimed at detecting X-ray accretion powered pulsations in sources already known as ms radio pulsars. Candidates are restricted to black widows and redbacks, systems in an evolutionary phase that allows state transitions. Enlarging the number of systems in this transitional phase is crucial to test binary evolution theories, and to study the disk-field interaction over a large range of mass accretion rates.

Ancient Wings: animating the evolution of butterfly wing patterns.

PubMed

Arbesman, Samuel; Enthoven, Leo; Monteiro, Antónia

2003-10-01

Character optimization methods can be used to reconstruct ancestral states at the internal nodes of phylogenetic trees. However, seldom are these ancestral states visualized collectively. Ancient Wings is a computer program that provides a novel method of visualizing the evolution of several morphological traits simultaneously. It allows users to visualize how the ventral hindwing pattern of 54 butterflies in the genus Bicyclus may have changed over time. By clicking on each of the nodes within the evolutionary tree, the user can see an animation of how wing size, eyespot size, and eyespot position relative the wing margin, have putatively evolved as a collective whole. Ancient Wings may be used as a pedagogical device as well as a research tool for hypothesis-generation in the fields of evolutionary, ecological, and developmental biology.

iACP-GAEnsC: Evolutionary genetic algorithm based ensemble classification of anticancer peptides by utilizing hybrid feature space.

PubMed

Akbar, Shahid; Hayat, Maqsood; Iqbal, Muhammad; Jan, Mian Ahmad

2017-06-01

Cancer is a fatal disease, responsible for one-quarter of all deaths in developed countries. Traditional anticancer therapies such as, chemotherapy and radiation, are highly expensive, susceptible to errors and ineffective techniques. These conventional techniques induce severe side-effects on human cells. Due to perilous impact of cancer, the development of an accurate and highly efficient intelligent computational model is desirable for identification of anticancer peptides. In this paper, evolutionary intelligent genetic algorithm-based ensemble model, 'iACP-GAEnsC', is proposed for the identification of anticancer peptides. In this model, the protein sequences are formulated, using three different discrete feature representation methods, i.e., amphiphilic Pseudo amino acid composition, g-Gap dipeptide composition, and Reduce amino acid alphabet composition. The performance of the extracted feature spaces are investigated separately and then merged to exhibit the significance of hybridization. In addition, the predicted results of individual classifiers are combined together, using optimized genetic algorithm and simple majority technique in order to enhance the true classification rate. It is observed that genetic algorithm-based ensemble classification outperforms than individual classifiers as well as simple majority voting base ensemble. The performance of genetic algorithm-based ensemble classification is highly reported on hybrid feature space, with an accuracy of 96.45%. In comparison to the existing techniques, 'iACP-GAEnsC' model has achieved remarkable improvement in terms of various performance metrics. Based on the simulation results, it is observed that 'iACP-GAEnsC' model might be a leading tool in the field of drug design and proteomics for researchers. Copyright © 2017 Elsevier B.V. All rights reserved.

Office of Nuclear Energy Knowledge Management Program Situational Analysis Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kimberlyn C. Mousseau

2011-12-01

Knowledge management (KM) has been a high priority for the Department of Energy (DOE) Office of Nuclear Energy (NE) for the past several years. NE Programs are moving toward well-established knowledge management practices and a formal knowledge management program has been established. Knowledge management is being practiced to some level within each of the NE programs. Although it continues to evolve as NE programs evolve, a formal strategic plan that guides the implementation of KM has been developed. Despite the acceptance of KM within DOE NE, more work is necessary before the NE KM program can be considered fully successful.more » Per Dr. David J. Skyrme[1], an organization typically moves through the following evolutionary phases: (1) Ad-hoc - KM is being practiced to some level in some parts of the organization; (2) Formal - KM is established as a formal project or program; (3) Expanding - the use of KM as a discipline grows in practice across different parts of the organization; (4) Cohesive - there is a degree of coordination of KM; (5) Integrated - there are formal standards and approaches that give every individual access to most organizational knowledge through common interfaces; and (6) Embedded - KM is part-and-parcel of everyday tasks; it blends seamlessly into the background. According to the evolutionary phases, the NE KM program is operating at the two lower levels, Ad-hoc and Formal. Although KM is being practiced to some level, it is not being practiced in a consistent manner across the NE programs. To be fully successful, more emphasis must be placed on establishing KM standards and processes for collecting, organizing, sharing and accessing NE knowledge. Existing knowledge needs to be prioritized and gathered on a routine basis, its existence formally recorded in a knowledge inventory. Governance to ensure the quality of the knowledge being used must also be considered. For easy retrieval, knowledge must be organized according to a taxonomy that mimics nuclear energy programs. Technologies need to be established to make accessing the knowledge easier for the user. Finally, knowledge needs to be used as part of a well defined work process.« less

Genetic Network Programming with Reconstructed Individuals

NASA Astrophysics Data System (ADS)

Ye, Fengming; Mabu, Shingo; Wang, Lutao; Eto, Shinji; Hirasawa, Kotaro

A lot of research on evolutionary computation has been done and some significant classical methods such as Genetic Algorithm (GA), Genetic Programming (GP), Evolutionary Programming (EP), and Evolution Strategies (ES) have been studied. Recently, a new approach named Genetic Network Programming (GNP) has been proposed. GNP can evolve itself and find the optimal solution. It is based on the idea of Genetic Algorithm and uses the data structure of directed graphs. Many papers have demonstrated that GNP can deal with complex problems in the dynamic environments very efficiently and effectively. As a result, recently, GNP is getting more and more attentions and is used in many different areas such as data mining, extracting trading rules of stock markets, elevator supervised control systems, etc., and GNP has obtained some outstanding results. Focusing on the GNP's distinguished expression ability of the graph structure, this paper proposes a method named Genetic Network Programming with Reconstructed Individuals (GNP-RI). The aim of GNP-RI is to balance the exploitation and exploration of GNP, that is, to strengthen the exploitation ability by using the exploited information extensively during the evolution process of GNP and finally obtain better performances than that of GNP. In the proposed method, the worse individuals are reconstructed and enhanced by the elite information before undergoing genetic operations (mutation and crossover). The enhancement of worse individuals mimics the maturing phenomenon in nature, where bad individuals can become smarter after receiving a good education. In this paper, GNP-RI is applied to the tile-world problem which is an excellent bench mark for evaluating the proposed architecture. The performance of GNP-RI is compared with that of the conventional GNP. The simulation results show some advantages of GNP-RI demonstrating its superiority over the conventional GNPs.

Top down, bottom up structured programming and program structuring

NASA Technical Reports Server (NTRS)

Hamilton, M.; Zeldin, S.

1972-01-01

New design and programming techniques for shuttle software. Based on previous Apollo experience, recommendations are made to apply top-down structured programming techniques to shuttle software. New software verification techniques for large software systems are recommended. HAL, the higher order language selected for the shuttle flight code, is discussed and found to be adequate for implementing these techniques. Recommendations are made to apply the workable combination of top-down, bottom-up methods in the management of shuttle software. Program structuring is discussed relevant to both programming and management techniques.

Some programming techniques for increasing program versatility and efficiency on CDC equipment

NASA Technical Reports Server (NTRS)

Tiffany, S. H.; Newsom, J. R.

1978-01-01

Five programming techniques used to decrease core and increase program versatility and efficiency are explained. The techniques are: (1) dynamic storage allocation, (2) automatic core-sizing and core-resizing, (3) matrix partitioning, (4) free field alphanumeric reads, and (5) incorporation of a data complex. The advantages of these techniques and the basic methods for employing them are explained and illustrated. Several actual program applications which utilize these techniques are described as examples.

Houston Operations Predictor/Estimator (HOPE) programming manual, volume 1. [Apollo orbit determination

NASA Technical Reports Server (NTRS)

Daly, J. K.

1974-01-01

The programming techniques used to implement the equations and mathematical techniques of the Houston Operations Predictor/Estimator (HOPE) orbit determination program on the UNIVAC 1108 computer are described. Detailed descriptions are given of the program structure, the internal program structure, the internal program tables and program COMMON, modification and maintainence techniques, and individual subroutine documentation.

Using traveling salesman problem algorithms for evolutionary tree construction.

PubMed

Korostensky, C; Gonnet, G H

2000-07-01

The construction of evolutionary trees is one of the major problems in computational biology, mainly due to its complexity. We present a new tree construction method that constructs a tree with minimum score for a given set of sequences, where the score is the amount of evolution measured in PAM distances. To do this, the problem of tree construction is reduced to the Traveling Salesman Problem (TSP). The input for the TSP algorithm are the pairwise distances of the sequences and the output is a circular tour through the optimal, unknown tree plus the minimum score of the tree. The circular order and the score can be used to construct the topology of the optimal tree. Our method can be used for any scoring function that correlates to the amount of changes along the branches of an evolutionary tree, for instance it could also be used for parsimony scores, but it cannot be used for least squares fit of distances. A TSP solution reduces the space of all possible trees to 2n. Using this order, we can guarantee that we reconstruct a correct evolutionary tree if the absolute value of the error for each distance measurement is smaller than f2.gif" BORDER="0">, where f3.gif" BORDER="0">is the length of the shortest edge in the tree. For data sets with large errors, a dynamic programming approach is used to reconstruct the tree. Finally simulations and experiments with real data are shown.

Assessing the evolutionary rate of positional orthologous genes in prokaryotes using synteny data

PubMed Central

Lemoine, Frédéric; Lespinet, Olivier; Labedan, Bernard

2007-01-01

Background Comparison of completely sequenced microbial genomes has revealed how fluid these genomes are. Detecting synteny blocks requires reliable methods to determining the orthologs among the whole set of homologs detected by exhaustive comparisons between each pair of completely sequenced genomes. This is a complex and difficult problem in the field of comparative genomics but will help to better understand the way prokaryotic genomes are evolving. Results We have developed a suite of programs that automate three essential steps to study conservation of gene order, and validated them with a set of 107 bacteria and archaea that cover the majority of the prokaryotic taxonomic space. We identified the whole set of shared homologs between two or more species and computed the evolutionary distance separating each pair of homologs. We applied two strategies to extract from the set of homologs a collection of valid orthologs shared by at least two genomes. The first computes the Reciprocal Smallest Distance (RSD) using the PAM distances separating pairs of homologs. The second method groups homologs in families and reconstructs each family's evolutionary tree, distinguishing bona fide orthologs as well as paralogs created after the last speciation event. Although the phylogenetic tree method often succeeds where RSD fails, the reverse could occasionally be true. Accordingly, we used the data obtained with either methods or their intersection to number the orthologs that are adjacent in for each pair of genomes, the Positional Orthologous Genes (POGs), and to further study their properties. Once all these synteny blocks have been detected, we showed that POGs are subject to more evolutionary constraints than orthologs outside synteny groups, whichever the taxonomic distance separating the compared organisms. Conclusion The suite of programs described in this paper allows a reliable detection of orthologs and is useful for evaluating gene order conservation in prokaryotes whichever their taxonomic distance. Thus, our approach will make easy the rapid identification of POGS in the next few years as we are expecting to be inundated with thousands of completely sequenced microbial genomes. PMID:18047665

A polycomb repressive complex 2 gene regulates apogamy and gives evolutionary insights into early land plant evolution.

PubMed

Okano, Yosuke; Aono, Naoki; Hiwatashi, Yuji; Murata, Takashi; Nishiyama, Tomoaki; Ishikawa, Takaaki; Kubo, Minoru; Hasebe, Mitsuyasu

2009-09-22

Land plants have distinct developmental programs in haploid (gametophyte) and diploid (sporophyte) generations. Although usually the two programs strictly alternate at fertilization and meiosis, one program can be induced during the other program. In a process called apogamy, cells of the gametophyte other than the egg cell initiate sporophyte development. Here, we report for the moss Physcomitrella patens that apogamy resulted from deletion of the gene orthologous to the Arabidopsis thaliana CURLY LEAF (PpCLF), which encodes a component of polycomb repressive complex 2 (PRC2). In the deletion lines, a gametophytic vegetative cell frequently gave rise to a sporophyte-like body. This body grew indeterminately from an apical cell with the character of a sporophytic pluripotent stem cell but did not form a sporangium. Furthermore, with continued culture, the sporophyte-like body branched. Sporophyte branching is almost unknown among extant bryophytes. When PpCLF was expressed in the deletion lines once the sporophyte-like bodies had formed, pluripotent stem cell activity was arrested and a sporangium-like organ formed. Supported by the observed pattern of PpCLF expression, these results demonstrate that, in the gametophyte, PpCLF represses initiation of a sporophytic pluripotent stem cell and, in the sporophyte, represses that stem cell activity and induces reproductive organ development. In land plants, branching, along with indeterminate apical growth and delayed initiation of spore-bearing reproductive organs, were conspicuous innovations for the evolution of a dominant sporophyte plant body. Our study provides insights into the role of PRC2 gene regulation for sustaining evolutionary innovation in land plants.

Rapid wide-field Mueller matrix polarimetry imaging based on four photoelastic modulators with no moving parts.

PubMed

Alali, Sanaz; Gribble, Adam; Vitkin, I Alex

2016-03-01

A new polarimetry method is demonstrated to image the entire Mueller matrix of a turbid sample using four photoelastic modulators (PEMs) and a charge coupled device (CCD) camera, with no moving parts. Accurate wide-field imaging is enabled with a field-programmable gate array (FPGA) optical gating technique and an evolutionary algorithm (EA) that optimizes imaging times. This technique accurately and rapidly measured the Mueller matrices of air, polarization elements, and turbid phantoms. The system should prove advantageous for Mueller matrix analysis of turbid samples (e.g., biological tissues) over large fields of view, in less than a second.

Properties of Starless Clumps through Protoclusters from the Bolocam Galactic Plane Survey

NASA Astrophysics Data System (ADS)

Svoboda, Brian E.; Shirley, Yancy

2014-07-01

High mass stars play a key role in the physical and chemical evolution of the interstellar medium, yet the evolution of physical properties for high-mass star-forming regions remains unclear. We sort a sample of ~4668 molecular cloud clumps from the Bolocam Galactic Plane Survey (BGPS) into different evolutionary stages by combining the BGPS 1.1 mm continuum and observational diagnostics of star-formation activity from a variety of Galactic plane surveys: 70 um compact sources, mid-IR color-selected YSOs, H2O and CH3OH masers, EGOs, and UCHII regions. We apply Monte Carlo techniques to distance probability distribution functions (DPDFs) in order to marginalize over the kinematic distance ambiguity and calculate distributions for derived quantities of clumps in different evolutionary stages. We also present a combined NH3 and H2O maser catalog for ~1590 clumps from the literature and our own GBT 100m observations. We identify a sub-sample of 440 dense clumps with no star-formation indicators, representing the largest and most robust sample of pre-protocluster candidates from a blind survey to date. Distributions of I(HCO+), I(N2H+), dv(HCO+), dv(N2H+), mass surface density, and kinetic temperature show strong progressions when separated by evolutionary stage. No progressions are found in size or dust mass; however, weak progressions are observed in area > 2 pc^2 and dust mass > 3 10^3 Msun. An observed breakdown occurs in the size-linewidth relationship and we find no improvement when sampling by evolutionary stage.

A Panchromatic View of Star-Forming Regions in the Magellanic Clouds: Characterizing Physical and Evolutionary Parameters of 1,000 Young Stellar Objects

NASA Astrophysics Data System (ADS)

Carlson, Lynn R.

2010-01-01

I discuss newly discovered Young Stellar Objects (YSOs) in several star-forming regions in the Magellanic Clouds. I exploit the synergy between infrared photometry from the Spitzer SAGE (Surveying the Agents of Galaxy Evolution) legacy programs, near-infrared and optical photometry from ground-based surveys, and HST imaging to characterize young stellar populations. This reveals a variety of Main Sequence Stars and Proto-Stars over a wide range of evolutionary stages. Through SED fitting, I characterize the youngest, embedded, infrared-bright YSOs. Complementary color-Magnitude analysis and isochrone fitting of optical data allows a statistical description of more evolved, unembedded stellar and protostellar populations within these same regions. I examine the early evolution of Magellanic star clusters, including propagating and triggered star formation, and take a step toward characterizing evolutionary timescales for YSOs. In this talk, I present an overview of the project and exemplify the analysis by focusing on NGC 602 in the SMC and Henize 206 in the LMC as examples. The SAGE Project is supported by NASA/Spitzer grant 1275598 and NASA NAG5-12595.

Evolution Under Environmental Stress at Macro- and Microscales

PubMed Central

Nevo, Eviatar

2011-01-01

Environmental stress has played a major role in the evolution of living organisms (Hoffman AA, Parsons PA. 1991. Evolutionary genetics and environmental stress. Oxford: Oxford University Press; Parsons PA. 2005. Environments and evolution: interactions between stress, resource inadequacy, and energetic efficiency. Biol Rev Camb Philos Soc. 80:589–610). This is reflected by the massive and background extinctions in evolutionary time (Nevo E. 1995a. Evolution and extinction. Encyclopedia of Environmental Biology. New York: Academic Press, Inc. 1:717–745). The interaction between organism and environment is central in evolution. Extinction ensues when organisms fail to change and adapt to the constantly altering abiotic and biotic stressful environmental changes as documented in the fossil record. Extreme environmental stress causes extinction but also leads to evolutionary change and the origination of new species adapted to new environments. I will discuss a few of these global, regional, and local stresses based primarily on my own research programs. These examples will include the 1) global regional and local experiment of subterranean mammals; 2) regional experiment of fungal life in the Dead Sea; 3) evolution of wild cereals; 4) “Evolution Canyon”; 5) human brain evolution, and 6) global warming. PMID:21979157

Expert-guided evolutionary algorithm for layout design of complex space stations

NASA Astrophysics Data System (ADS)

Qian, Zhiqin; Bi, Zhuming; Cao, Qun; Ju, Weiguo; Teng, Hongfei; Zheng, Yang; Zheng, Siyu

2017-08-01

The layout of a space station should be designed in such a way that different equipment and instruments are placed for the station as a whole to achieve the best overall performance. The station layout design is a typical nondeterministic polynomial problem. In particular, how to manage the design complexity to achieve an acceptable solution within a reasonable timeframe poses a great challenge. In this article, a new evolutionary algorithm has been proposed to meet such a challenge. It is called as the expert-guided evolutionary algorithm with a tree-like structure decomposition (EGEA-TSD). Two innovations in EGEA-TSD are (i) to deal with the design complexity, the entire design space is divided into subspaces with a tree-like structure; it reduces the computation and facilitates experts' involvement in the solving process. (ii) A human-intervention interface is developed to allow experts' involvement in avoiding local optimums and accelerating convergence. To validate the proposed algorithm, the layout design of one-space station is formulated as a multi-disciplinary design problem, the developed algorithm is programmed and executed, and the result is compared with those from other two algorithms; it has illustrated the superior performance of the proposed EGEA-TSD.

Multiobjective optimisation design for enterprise system operation in the case of scheduling problem with deteriorating jobs

NASA Astrophysics Data System (ADS)

Wang, Hongfeng; Fu, Yaping; Huang, Min; Wang, Junwei

2016-03-01

The operation process design is one of the key issues in the manufacturing and service sectors. As a typical operation process, the scheduling with consideration of the deteriorating effect has been widely studied; however, the current literature only studied single function requirement and rarely considered the multiple function requirements which are critical for a real-world scheduling process. In this article, two function requirements are involved in the design of a scheduling process with consideration of the deteriorating effect and then formulated into two objectives of a mathematical programming model. A novel multiobjective evolutionary algorithm is proposed to solve this model with combination of three strategies, i.e. a multiple population scheme, a rule-based local search method and an elitist preserve strategy. To validate the proposed model and algorithm, a series of randomly-generated instances are tested and the experimental results indicate that the model is effective and the proposed algorithm can achieve the satisfactory performance which outperforms the other state-of-the-art multiobjective evolutionary algorithms, such as nondominated sorting genetic algorithm II and multiobjective evolutionary algorithm based on decomposition, on all the test instances.

Quantification of complex modular architecture in plants.

PubMed

Reeb, Catherine; Kaandorp, Jaap; Jansson, Fredrik; Puillandre, Nicolas; Dubuisson, Jean-Yves; Cornette, Raphaël; Jabbour, Florian; Coudert, Yoan; Patiño, Jairo; Flot, Jean-François; Vanderpoorten, Alain

2018-04-01

Morphometrics, the assignment of quantities to biological shapes, is a powerful tool to address taxonomic, evolutionary, functional and developmental questions. We propose a novel method for shape quantification of complex modular architecture in thalloid plants, whose extremely reduced morphologies, combined with the lack of a formal framework for thallus description, have long rendered taxonomic and evolutionary studies extremely challenging. Using graph theory, thalli are described as hierarchical series of nodes and edges, allowing for accurate, homologous and repeatable measurements of widths, lengths and angles. The computer program MorphoSnake was developed to extract the skeleton and contours of a thallus and automatically acquire, at each level of organization, width, length, angle and sinuosity measurements. Through the quantification of leaf architecture in Hymenophyllum ferns (Polypodiopsida) and a fully worked example of integrative taxonomy in the taxonomically challenging thalloid liverwort genus Riccardia, we show that MorphoSnake is applicable to all ramified plants. This new possibility of acquiring large numbers of quantitative traits in plants with complex modular architectures opens new perspectives of applications, from the development of rapid species identification tools to evolutionary analyses of adaptive plasticity. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Evolution under environmental stress at macro- and microscales.

PubMed

Nevo, Eviatar

2011-01-01

Environmental stress has played a major role in the evolution of living organisms (Hoffman AA, Parsons PA. 1991. Evolutionary genetics and environmental stress. Oxford: Oxford University Press; Parsons PA. 2005. Environments and evolution: interactions between stress, resource inadequacy, and energetic efficiency. Biol Rev Camb Philos Soc. 80:589-610). This is reflected by the massive and background extinctions in evolutionary time (Nevo E. 1995a. Evolution and extinction. Encyclopedia of Environmental Biology. New York: Academic Press, Inc. 1:717-745). The interaction between organism and environment is central in evolution. Extinction ensues when organisms fail to change and adapt to the constantly altering abiotic and biotic stressful environmental changes as documented in the fossil record. Extreme environmental stress causes extinction but also leads to evolutionary change and the origination of new species adapted to new environments. I will discuss a few of these global, regional, and local stresses based primarily on my own research programs. These examples will include the 1) global regional and local experiment of subterranean mammals; 2) regional experiment of fungal life in the Dead Sea; 3) evolution of wild cereals; 4) "Evolution Canyon"; 5) human brain evolution, and 6) global warming.

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

NASA Astrophysics Data System (ADS)

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.

Phylogenetic Factor Analysis.

PubMed

Tolkoff, Max R; Alfaro, Michael E; Baele, Guy; Lemey, Philippe; Suchard, Marc A

2018-05-01

Phylogenetic comparative methods explore the relationships between quantitative traits adjusting for shared evolutionary history. This adjustment often occurs through a Brownian diffusion process along the branches of the phylogeny that generates model residuals or the traits themselves. For high-dimensional traits, inferring all pair-wise correlations within the multivariate diffusion is limiting. To circumvent this problem, we propose phylogenetic factor analysis (PFA) that assumes a small unknown number of independent evolutionary factors arise along the phylogeny and these factors generate clusters of dependent traits. Set in a Bayesian framework, PFA provides measures of uncertainty on the factor number and groupings, combines both continuous and discrete traits, integrates over missing measurements and incorporates phylogenetic uncertainty with the help of molecular sequences. We develop Gibbs samplers based on dynamic programming to estimate the PFA posterior distribution, over 3-fold faster than for multivariate diffusion and a further order-of-magnitude more efficiently in the presence of latent traits. We further propose a novel marginal likelihood estimator for previously impractical models with discrete data and find that PFA also provides a better fit than multivariate diffusion in evolutionary questions in columbine flower development, placental reproduction transitions and triggerfish fin morphometry.

Method for identifying known materials within a mixture of unknowns

DOEpatents

Wagner, John S.

2000-01-01

One or both of two methods and systems are used to determine concentration of a known material in an unknown mixture on the basis of the measured interaction of electromagnetic waves upon the mixture. One technique is to utilize a multivariate analysis patch technique to develop a library of optimized patches of spectral signatures of known materials containing only those pixels most descriptive of the known materials by an evolutionary algorithm. Identity and concentration of the known materials within the unknown mixture is then determined by minimizing the residuals between the measurements from the library of optimized patches and the measurements from the same pixels from the unknown mixture. Another technique is to train a neural network by the genetic algorithm to determine the identity and concentration of known materials in the unknown mixture. The two techniques may be combined into an expert system providing cross checks for accuracy.

System for identifying known materials within a mixture of unknowns

DOEpatents

Wagner, John S.

1999-01-01

One or both of two methods and systems are used to determine concentration of a known material in an unknown mixture on the basis of the measured interaction of electromagnetic waves upon the mixture. One technique is to utilize a multivariate analysis patch technique to develop a library of optimized patches of spectral signatures of known materials containing only those pixels most descriptive of the known materials by an evolutionary algorithm. Identity and concentration of the known materials within the unknown mixture is then determined by minimizing the residuals between the measurements from the library of optimized patches and the measurements from the same pixels from the unknown mixture. Another technique is to train a neural network by the genetic algorithm to determine the identity and concentration of known materials in the unknown mixture. The two techniques may be combined into an expert system providing cross checks for accuracy.

System for identifying known materials within a mixture of unknowns

DOEpatents

Wagner, J.S.

1999-07-20

One or both of two methods and systems are used to determine concentration of a known material in an unknown mixture on the basis of the measured interaction of electromagnetic waves upon the mixture. One technique is to utilize a multivariate analysis patch technique to develop a library of optimized patches of spectral signatures of known materials containing only those pixels most descriptive of the known materials by an evolutionary algorithm. Identity and concentration of the known materials within the unknown mixture is then determined by minimizing the residuals between the measurements from the library of optimized patches and the measurements from the same pixels from the unknown mixture. Another technique is to train a neural network by the genetic algorithm to determine the identity and concentration of known materials in the unknown mixture. The two techniques may be combined into an expert system providing cross checks for accuracy. 37 figs.

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been provEn effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. Several approaches that have proven effective for other evolutionary algorithms are modified and implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for standard test optimization problems and for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

Evolutionary ecology of specialization: insights from phylogenetic analysis

PubMed Central

Vamosi, Jana C.; Armbruster, W. Scott; Renner, Susanne S.

2014-01-01

In this Special feature, we assemble studies that illustrate phylogenetic approaches to studying salient questions regarding the effect of specialization on lineage diversification. The studies use an array of techniques involving a wide-ranging collection of biological systems (plants, butterflies, fish and amphibians are all represented). Their results reveal that macroevolutionary examination of specialization provides insight into the patterns of trade-offs in specialized systems; in particular, the genetic mechanisms of trade-offs appear to extend to very different aspects of life history in different groups. In turn, because a species may be a specialist from one perspective and a generalist in others, these trade-offs influence whether we perceive specialization to have effects on the evolutionary success of a lineage when we examine specialization only along a single axis. Finally, how geographical range influences speciation and extinction of specialist lineages remains a question offering much potential for further insight. PMID:25274367

Collaboration Networks in the Brazilian Scientific Output in Evolutionary Biology: 2000-2012.

PubMed

Santin, Dirce M; Vanz, Samile A S; Stumpf, Ida R C

2016-03-01

This article analyzes the existing collaboration networks in the Brazilian scientific output in Evolutionary Biology, considering articles published during the period from 2000 to 2012 in journals indexed by Web of Science. The methodology integrates bibliometric techniques and Social Network Analysis resources to describe the growth of Brazilian scientific output and understand the levels, dynamics and structure of collaboration between authors, institutions and countries. The results unveil an enhancement and consolidation of collaborative relationships over time and suggest the existence of key institutions and authors, whose influence on research is expressed by the variety and intensity of the relationships established in the co-authorship of articles. International collaboration, present in more than half of the publications, is highly significant and unusual in Brazilian science. The situation indicates the internationalization of scientific output and the ability of the field to take part in the science produced by the international scientific community.

Paleo-tribology: development of wear measurement techniques and a three-dimensional model revealing how grinding dentitions self-wear to enable functionality

NASA Astrophysics Data System (ADS)

Erickson, Gregory M.; Sidebottom, Mark A.; Curry, John F.; Kay, David Ian; Kuhn-Hendricks, Stephen; Norell, Mark A.; Sawyer, W. Gregory; Krick, Brandon A.

2016-06-01

In most mammals and a rare few reptilian lineages the evolution of precise dental occlusion led to the capacity to form functional chewing surfaces due to pressures generated while feeding. The complex dental architectures of such teeth and the biomechanics of their self-wearing nature are poorly understood. Our research team composed of paleontologists, evolutionary biologists, and engineers have developed a protocol to: (1) determine the histological make-up of grinding dentitions in extant and fossil taxa; (2) ascertain wear-relevant material properties of the tissues; (3) determine how those properties relate to inter-tissue-biomechanics leading the dental functionality using a three-dimensional Archard’s wear model developed specifically for dental applications; (4) analyze those data in phylogenetic contexts to infer evolutionary patterns as they relate to feeding. Finally we discuss industrial applications that are emerging from our paleontologically-inspired research.

Efficient hybrid evolutionary algorithm for optimization of a strip coiling process

NASA Astrophysics Data System (ADS)

Pholdee, Nantiwat; Park, Won-Woong; Kim, Dong-Kyu; Im, Yong-Taek; Bureerat, Sujin; Kwon, Hyuck-Cheol; Chun, Myung-Sik

2015-04-01

This article proposes an efficient metaheuristic based on hybridization of teaching-learning-based optimization and differential evolution for optimization to improve the flatness of a strip during a strip coiling process. Differential evolution operators were integrated into the teaching-learning-based optimization with a Latin hypercube sampling technique for generation of an initial population. The objective function was introduced to reduce axial inhomogeneity of the stress distribution and the maximum compressive stress calculated by Love's elastic solution within the thin strip, which may cause an irregular surface profile of the strip during the strip coiling process. The hybrid optimizer and several well-established evolutionary algorithms (EAs) were used to solve the optimization problem. The comparative studies show that the proposed hybrid algorithm outperformed other EAs in terms of convergence rate and consistency. It was found that the proposed hybrid approach was powerful for process optimization, especially with a large-scale design problem.

Mind, brain, and teaching: Some directions for future research.

PubMed

Pasquinelli, Elena; Zalla, Tiziana; Gvodzic, Katarina; Potier-Watkins, Cassandra; Piazza, Manuela

2015-01-01

In line with Kline's taxonomy, highlighting teaching as an array of behaviors with different cognitive underpinnings, we advocate the expansion of a specific line of research on mind, brain, and teaching. This research program is devoted to the understanding of the neurocognitive mechanisms and the evolutionary determinants of teaching skills, with the ultimate goal of helping teachers improve teaching quality.

2003 IDA Cost Research Symposium: Cost of Evolutionary Acquisition/Spiral Development

DTIC Science & Technology

2003-08-01

Louis, Missouri”, IDA Paper P-3548 “Econometric Modeling of Acquisition Category I Systems at the Lockheed- Martin Plant in Marietta , Georgia”, IDA...Systems Command (NAVSEA)..................................................... B- 71 Naval Surface Warfare Center, Dahlgren Division (NSWCDD...cost estimates and reports on life-cycle costs of major defense acquisition programs (MDAPs) in Acquisition Category ID (see Reference [1]). Cost

A Parallel Genetic Algorithm for Automated Electronic Circuit Design

NASA Technical Reports Server (NTRS)

Lohn, Jason D.; Colombano, Silvano P.; Haith, Gary L.; Stassinopoulos, Dimitris; Norvig, Peter (Technical Monitor)

2000-01-01

We describe a parallel genetic algorithm (GA) that automatically generates circuit designs using evolutionary search. A circuit-construction programming language is introduced and we show how evolution can generate practical analog circuit designs. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. We present experimental results as applied to analog filter and amplifier design tasks.

Social insects: from selfish genes to self organisation and beyond.

PubMed

Boomsma, Jacobus J; Franks, Nigel R

2006-06-01

Selfish gene and self-organisation approaches have revolutionised the study of social insects and have provided unparalleled insights into the highly sophisticated nature of insect social evolution. Here, we briefly review the core programs and interfaces with communication and recognition studies that characterise these fields today, and offer an interdisciplinary future perspective for the study of social insect evolutionary biology.

Arizona State's Origins Project Starts with a Big Bang

ERIC Educational Resources Information Center

Mangan, Katherine

2009-01-01

For 12 hours at Arizona State University, a sold-out crowd of 3,000 people gave a group of famous scientists a pop-star welcome, cheering their remarks and lining up for autographs after a day full of discussion about black holes, string theory, and evolutionary biology. At a time when program cuts and faculty layoffs dominate the headlines of…

Modeling and measurements of XRD spectra of extended solids under high pressure

NASA Astrophysics Data System (ADS)

Batyrev, I. G.; Coleman, S. P.; Stavrou, E.; Zaug, J. M.; Ciezak-Jenkins, J. A.

2017-06-01

We present results of evolutionary simulations based on density functional calculations of various extended solids: N-Si and N-H using variable and fixed concentration methods of USPEX. Predicted from the evolutionary simulations structures were analyzed in terms of thermo-dynamical stability and agreement with experimental X-ray diffraction spectra. Stability of the predicted system was estimated from convex-hull plots. X-ray diffraction spectra were calculated using a virtual diffraction algorithm which computes kinematic diffraction intensity in three-dimensional reciprocal space before being reduced to a two-theta line profile. Calculations of thousands of XRD spectra were used to search for a structure of extended solids at certain pressures with best fits to experimental data according to experimental XRD peak position, peak intensity and theoretically calculated enthalpy. Comparison of Raman and IR spectra calculated for best fitted structures with available experimental data shows reasonable agreement for certain vibration modes. Part of this work was performed by LLNL, Contract DE-AC52-07NA27344. We thank the Joint DoD / DOE Munitions Technology Development Program, the HE C-II research program at LLNL and Advanced Light Source, supported by BES DOE, Contract No. DE-AC02-05CH112.

Three-week inpatient Cognitive Evolutionary Therapy (CET) for patients with personality disorders: evidence of effectiveness in symptoms reduction and improved treatment adherence.

PubMed

Prunetti, Elena; Bosio, Valentina; Bateni, Marco; Liotti, Giovanni

2013-09-01

The aim of this study was to evaluate the efficacy of Cognitive Evolutionary Therapy (CET) in an intensive short residential treatment of a wide range of severe personality disorders (PDs) that resulted in a reduction of social functioning and significant personal distress. Each patient was assessed at admission, discharge, and 3 months later in order to determine if there was a reduction in symptoms and an improved adherence to former outpatient programs and to check if patients were undergoing new treatment after discharge. Fifty-one patients participated in this study. The 20-hr weekly program consisted of two individual sessions and various group modules. Outcome measures included: self-reported measures of depression, anxiety, general symptoms, number and duration of inpatient admissions after the programme, and continuation in an outpatient treatment programme. The results show an overall improvement in general psychopathology after the release and in follow-up sessions, a decrease in the number of further hospital admissions, and an increased level of attendance of outpatient therapy. This study shows that intensive short residential treatment is an effective treatment for patients with a wide range of PDs. © 2012 The British Psychological Society.

Cancer: shift of the paradigm.

PubMed

Lichtenstein, Anatoly V

2008-12-01

Cancer is usually considered to be a by-product of design limitations of a multicellular organism and its intrinsic fallibility. However, recent data prompt a revision of some established notions about carcinogenesis and form a new paradigm of carcinogenesis as a highly conserved biological phenomenon - a programmed death of an organism. This altruistic program, which is unleashed when mutagenesis surpasses a certain critical threshold, gives a population the important benefit acting as a guardian of the gene pool against the spread of certain mutant genes. A growing body of evidence supports this point of view: (i) epigenetic changes leading to cancer arise early, simultaneously in many cells and look like deterministic regulation; (ii) concept of cancer stem cell suggests a view of carcinogenesis not as vague transformation but as well known differentiation; (iii) tumor/host relations usually perceived as antagonistic are, in reality, synergistic; (iv) death of an individual from cancer is predetermined and results apparently from a specific activity (killer function) of cancer cell and (v) evolutionary conservation indicates that cancer comes with a general advantage that explains its evolutionary success. A holistic approach to carcinogenesis suggests new avenues of research and new therapeutic strategy.

Study of an evolutionary interim earth orbit program

NASA Technical Reports Server (NTRS)

Anderson, J. L.; Alton, L. R.; Arno, R. D.; Deerwester, J. M.; Edsinger, L. E.; Sinclair, K. F.; Tindle, E. L.; Wood, R. D.

1971-01-01

An evolutionary, gradual, and step-wise spacecraft systems technology development from those used on the Apollos and Skylab 1 to that required for the space station was considered. The four mission spacecraft were dry workshop versions of the Saturn 4-B stage, and each individually configured, outfitted and launched by INT-21 vehicles. These spacecraft were evaluated for crews of three, six and nine men and for mission lifetimes of one year. Two versions of the Apollo CSM, a three man and a four man crew, were considered as the logistic vehicle. The solar cell electrical power system of the first mission evolves into a light weight panel system supplemented by an operating isotope-Brayton system on the later missions. The open life support system of the first mission evolves to a system which recovers both water and oxygen on the last mission. The data handling, communications, radiation shielding, micrometeoroid protection, and orbit keeping systems were determined. The program costs were estimated and, excluding operational costs, the cost for each mission would average about $2 billion of which one-sixth would be for development, one-fourth for experiments, and the balance for vehicle acquisition.

Hybridization of Strength Pareto Multiobjective Optimization with Modified Cuckoo Search Algorithm for Rectangular Array

NASA Astrophysics Data System (ADS)

Abdul Rani, Khairul Najmy; Abdulmalek, Mohamedfareq; A. Rahim, Hasliza; Siew Chin, Neoh; Abd Wahab, Alawiyah

2017-04-01

This research proposes the various versions of modified cuckoo search (MCS) metaheuristic algorithm deploying the strength Pareto evolutionary algorithm (SPEA) multiobjective (MO) optimization technique in rectangular array geometry synthesis. Precisely, the MCS algorithm is proposed by incorporating the Roulette wheel selection operator to choose the initial host nests (individuals) that give better results, adaptive inertia weight to control the positions exploration of the potential best host nests (solutions), and dynamic discovery rate to manage the fraction probability of finding the best host nests in 3-dimensional search space. In addition, the MCS algorithm is hybridized with the particle swarm optimization (PSO) and hill climbing (HC) stochastic techniques along with the standard strength Pareto evolutionary algorithm (SPEA) forming the MCSPSOSPEA and MCSHCSPEA, respectively. All the proposed MCS-based algorithms are examined to perform MO optimization on Zitzler-Deb-Thiele’s (ZDT’s) test functions. Pareto optimum trade-offs are done to generate a set of three non-dominated solutions, which are locations, excitation amplitudes, and excitation phases of array elements, respectively. Overall, simulations demonstrates that the proposed MCSPSOSPEA outperforms other compatible competitors, in gaining a high antenna directivity, small half-power beamwidth (HPBW), low average side lobe level (SLL) suppression, and/or significant predefined nulls mitigation, simultaneously.

Evolutionary optimization of radial basis function classifiers for data mining applications.

PubMed

Buchtala, Oliver; Klimek, Manuel; Sick, Bernhard

2005-10-01

In many data mining applications that address classification problems, feature and model selection are considered as key tasks. That is, appropriate input features of the classifier must be selected from a given (and often large) set of possible features and structure parameters of the classifier must be adapted with respect to these features and a given data set. This paper describes an evolutionary algorithm (EA) that performs feature and model selection simultaneously for radial basis function (RBF) classifiers. In order to reduce the optimization effort, various techniques are integrated that accelerate and improve the EA significantly: hybrid training of RBF networks, lazy evaluation, consideration of soft constraints by means of penalty terms, and temperature-based adaptive control of the EA. The feasibility and the benefits of the approach are demonstrated by means of four data mining problems: intrusion detection in computer networks, biometric signature verification, customer acquisition with direct marketing methods, and optimization of chemical production processes. It is shown that, compared to earlier EA-based RBF optimization techniques, the runtime is reduced by up to 99% while error rates are lowered by up to 86%, depending on the application. The algorithm is independent of specific applications so that many ideas and solutions can be transferred to other classifier paradigms.

A new adaptive mesh refinement strategy for numerically solving evolutionary PDE's

NASA Astrophysics Data System (ADS)

Burgarelli, Denise; Kischinhevsky, Mauricio; Biezuner, Rodney Josue

2006-11-01

A graph-based implementation of quadtree meshes for dealing with adaptive mesh refinement (AMR) in the numerical solution of evolutionary partial differential equations is discussed using finite volume methods. The technique displays a plug-in feature that allows replacement of a group of cells in any region of interest for another one with arbitrary refinement, and with only local changes occurring in the data structure. The data structure is also specially designed to minimize the number of operations needed in the AMR. Implementation of the new scheme allows flexibility in the levels of refinement of adjacent regions. Moreover, storage requirements and computational cost compare competitively with mesh refinement schemes based on hierarchical trees. Low storage is achieved for only the children nodes are stored when a refinement takes place. These nodes become part of a graph structure, thus motivating the denomination autonomous leaves graph (ALG) for the new scheme. Neighbors can then be reached without accessing their parent nodes. Additionally, linear-system solvers based on the minimization of functionals can be easily employed. ALG was not conceived with any particular problem or geometry in mind and can thus be applied to the study of several phenomena. Some test problems are used to illustrate the effectiveness of the technique.

On Polymorphic Circuits and Their Design Using Evolutionary Algorithms

NASA Technical Reports Server (NTRS)

Stoica, Adrian; Zebulum, Ricardo; Keymeulen, Didier; Lohn, Jason; Clancy, Daniel (Technical Monitor)

2002-01-01

This paper introduces the concept of polymorphic electronics (polytronics) - referring to electronics with superimposed built-in functionality. A function change does not require switches/reconfiguration as in traditional approaches. Instead the change comes from modifications in the characteristics of devices involved in the circuit, in response to controls such as temperature, power supply voltage (VDD), control signals, light, etc. The paper illustrates polytronic circuits in which the control is done by temperature, morphing signals, and VDD respectively. Polytronic circuits are obtained by evolutionary design/evolvable hardware techniques. These techniques are ideal for the polytronics design, a new area that lacks design guidelines, know-how,- yet the requirements/objectives are easy to specify and test. The circuits are evolved/synthesized in two different modes. The first mode explores an unstructured space, in which transistors can be interconnected freely in any arrangement (in simulations only). The second mode uses a Field Programmable Transistor Array (FPTA) model, and the circuit topology is sought as a mapping onto a programmable architecture (these experiments are performed both in simulations and on FPTA chips). The experiments demonstrated the synthesis. of polytronic circuits by evolution. The capacity of storing/hiding "extra" functions provides for watermark/invisible functionality, thus polytronics may find uses in intelligence/security applications.

Suboptimal evolutionary novel environments promote singular altered gravity responses of transcriptome during Drosophila metamorphosis

PubMed Central

2013-01-01

Background Previous experiments have shown that the reduced gravity aboard the International Space Station (ISS) causes important alterations in Drosophila gene expression. These changes were shown to be intimately linked to environmental space-flight related constraints. Results Here, we use an array of different techniques for ground-based simulation of microgravity effects to assess the effect of suboptimal environmental conditions on the gene expression of Drosophila in reduced gravity. A global and integrative analysis, using “gene expression dynamics inspector” (GEDI) self-organizing maps, reveals different degrees in the responses of the transcriptome when using different environmental conditions or microgravity/hypergravity simulation devices. Although the genes that are affected are different in each simulation technique, we find that the same gene ontology groups, including at least one large multigene family related with behavior, stress response or organogenesis, are over represented in each case. Conclusions These results suggest that the transcriptome as a whole can be finely tuned to gravity force. In optimum environmental conditions, the alteration of gravity has only mild effects on gene expression but when environmental conditions are far from optimal, the gene expression must be tuned greatly and effects become more robust, probably linked to the lack of experience of organisms exposed to evolutionary novel environments such as a gravitational free one. PMID:23806134

Options for the human settlement of the moon and Mars

NASA Technical Reports Server (NTRS)

Fairchild, Kyle O.; Roberts, Barney B.

1989-01-01

The evolutionary approach to space development is discussed in the framework of three overall strategies encompassing four case studies. The first strategy, human expeditions, places emphasis on highly visible, near-term manned missions to Mars or to one of the two moons of Mars. These expeditions are similar in scope and objectives to the Apollo program, with infrastructure development only conducted to the degree necessary to support one or two short-duration trips. Two such expeditionary scenarios, one to Phobus and the other to the Mars surface, are discussed. The second strategy involves the construction of science outposts, and emphasizes scientific exploration as well as investigation of technologies and operations needed for permanent habitation. A third strategy, evolutionary expansion, would explore and settle the inner solar system in a series of steps, with continued development of technologies, experience, and infrastructure.

Knowledge discovery with classification rules in a cardiovascular dataset.

PubMed

Podgorelec, Vili; Kokol, Peter; Stiglic, Milojka Molan; Hericko, Marjan; Rozman, Ivan

2005-12-01

In this paper we study an evolutionary machine learning approach to data mining and knowledge discovery based on the induction of classification rules. A method for automatic rules induction called AREX using evolutionary induction of decision trees and automatic programming is introduced. The proposed algorithm is applied to a cardiovascular dataset consisting of different groups of attributes which should possibly reveal the presence of some specific cardiovascular problems in young patients. A case study is presented that shows the use of AREX for the classification of patients and for discovering possible new medical knowledge from the dataset. The defined knowledge discovery loop comprises a medical expert's assessment of induced rules to drive the evolution of rule sets towards more appropriate solutions. The final result is the discovery of a possible new medical knowledge in the field of pediatric cardiology.

Properties of LEGUS Clusters Obtained with Different Massive-Star Evolutionary Tracks

NASA Astrophysics Data System (ADS)

Wofford, A.; Charlot, S.; Eldridge, J. J.

We compute spectral libraries for populations of coeval stars using state-of-the-art massive-star evolutionary tracks that account for different astrophysics including rotation and close-binarity. Our synthetic spectra account for stellar and nebular contributions. We use our models to obtain E(B - V ), age, and mass for six clusters in spiral galaxy NGC 1566, which have ages of < 50 Myr and masses of > 5 x 104M⊙ according to standard models. NGC 1566 was observed from the NUV to the I-band as part of the imaging Treasury HST program LEGUS: Legacy Extragalactic UV Survey. We aim to establish i) if the models provide reasonable fits to the data, ii) how well the models and photometry are able to constrain the cluster properties, and iii) how different the properties obtained with different models are.

Role of Genomic Typing in Taxonomy, Evolutionary Genetics, and Microbial Epidemiology

PubMed Central

van Belkum, Alex; Struelens, Marc; de Visser, Arjan; Verbrugh, Henri; Tibayrenc, Michel

2001-01-01

Currently, genetic typing of microorganisms is widely used in several major fields of microbiological research. Taxonomy, research aimed at elucidation of evolutionary dynamics or phylogenetic relationships, population genetics of microorganisms, and microbial epidemiology all rely on genetic typing data for discrimination between genotypes. Apart from being an essential component of these fundamental sciences, microbial typing clearly affects several areas of applied microbiogical research. The epidemiological investigation of outbreaks of infectious diseases and the measurement of genetic diversity in relation to relevant biological properties such as pathogenicity, drug resistance, and biodegradation capacities are obvious examples. The diversity among nucleic acid molecules provides the basic information for all fields described above. However, researchers in various disciplines tend to use different vocabularies, a wide variety of different experimental methods to monitor genetic variation, and sometimes widely differing modes of data processing and interpretation. The aim of the present review is to summarize the technological and fundamental concepts used in microbial taxonomy, evolutionary genetics, and epidemiology. Information on the nomenclature used in the different fields of research is provided, descriptions of the diverse genetic typing procedures are presented, and examples of both conceptual and technological research developments for Escherichia coli are included. Recommendations for unification of the different fields through standardization of laboratory techniques are made. PMID:11432813

A Gaze-Driven Evolutionary Algorithm to Study Aesthetic Evaluation of Visual Symmetry

PubMed Central

Bertamini, Marco; Jones, Andrew; Holmes, Tim; Zanker, Johannes M.

2016-01-01

Empirical work has shown that people like visual symmetry. We used a gaze-driven evolutionary algorithm technique to answer three questions about symmetry preference. First, do people automatically evaluate symmetry without explicit instruction? Second, is perfect symmetry the best stimulus, or do people prefer a degree of imperfection? Third, does initial preference for symmetry diminish after familiarity sets in? Stimuli were generated as phenotypes from an algorithmic genotype, with genes for symmetry (coded as deviation from a symmetrical template, deviation–symmetry, DS gene) and orientation (0° to 90°, orientation, ORI gene). An eye tracker identified phenotypes that were good at attracting and retaining the gaze of the observer. Resulting fitness scores determined the genotypes that passed to the next generation. We recorded changes to the distribution of DS and ORI genes over 20 generations. When participants looked for symmetry, there was an increase in high-symmetry genes. When participants looked for the patterns they preferred, there was a smaller increase in symmetry, indicating that people tolerated some imperfection. Conversely, there was no increase in symmetry during free viewing, and no effect of familiarity or orientation. This work demonstrates the viability of the evolutionary algorithm approach as a quantitative measure of aesthetic preference. PMID:27433324

The evolution of a key character, or how to evolve a slipper lobster.

PubMed

Haug, Joachim T; Audo, Denis; Charbonnier, Sylvain; Palero, Ferran; Petit, Gilles; Abi Saad, Pierre; Haug, Carolin

2016-03-01

A new fossil lobster from the Cretaceous of Lebanon, Charbelicaris maronites gen. et sp. nov., is presented here, while the former species 'Cancrinos' libanensis is re-described as Paracancrinos libanensis comb. nov. P. libanensis is shown to be closer related to the contemporary slipper lobsters than to Cancrinos claviger (lithographic limestones, Jurassic, southern Germany). A finely-graded evolutionary scenario for the slipper-lobster morphotype is reconstructed based on these fossil species and extant forms. The evolutionary changes that gave rise to the current plate-like antennae of Scyllaridae, a key apomorphy of this group, are traced back through time. The antenna of what is considered the oldest slipper lobster became petaloid and consisted of about 20 fully articulated elements. For this group the name Scyllarida sensu lato tax. nov. is introduced. In a next evolutionary step, the proximal articles became conjoined and a lateral extension appeared on peduncle element 3. The entire distal petaloid region is conjoined already at the node of Verscyllarida tax. nov. In modern slipper lobsters, Neoscyllarida tax nov., the distal region is no longer petaloid in shape but asymmetrical. The study also emphasizes that exceptionally preserved fossils need to be documented with optimal documentation techniques to obtain all available information. Copyright © 2015 Elsevier Ltd. All rights reserved.

Enhancing hydrologic data assimilation by evolutionary Particle Filter and Markov Chain Monte Carlo

NASA Astrophysics Data System (ADS)

Abbaszadeh, Peyman; Moradkhani, Hamid; Yan, Hongxiang

2018-01-01

Particle Filters (PFs) have received increasing attention by researchers from different disciplines including the hydro-geosciences, as an effective tool to improve model predictions in nonlinear and non-Gaussian dynamical systems. The implication of dual state and parameter estimation using the PFs in hydrology has evolved since 2005 from the PF-SIR (sampling importance resampling) to PF-MCMC (Markov Chain Monte Carlo), and now to the most effective and robust framework through evolutionary PF approach based on Genetic Algorithm (GA) and MCMC, the so-called EPFM. In this framework, the prior distribution undergoes an evolutionary process based on the designed mutation and crossover operators of GA. The merit of this approach is that the particles move to an appropriate position by using the GA optimization and then the number of effective particles is increased by means of MCMC, whereby the particle degeneracy is avoided and the particle diversity is improved. In this study, the usefulness and effectiveness of the proposed EPFM is investigated by applying the technique on a conceptual and highly nonlinear hydrologic model over four river basins located in different climate and geographical regions of the United States. Both synthetic and real case studies demonstrate that the EPFM improves both the state and parameter estimation more effectively and reliably as compared with the PF-MCMC.

Evolutionary Strategies for Protein Folding

NASA Astrophysics Data System (ADS)

Murthy Gopal, Srinivasa; Wenzel, Wolfgang

2006-03-01

The free energy approach for predicting the protein tertiary structure describes the native state of a protein as the global minimum of an appropriate free-energy forcefield. The low-energy region of the free-energy landscape of a protein is extremely rugged. Efficient optimization methods must therefore speed up the search for the global optimum by avoiding high energy transition states, adapt large scale moves or accept unphysical intermediates. Here we investigate an evolutionary strategies(ES) for optimizing a protein conformation in our all-atom free-energy force field([1],[2]). A set of random conformations is evolved using an ES to get a diverse population containing low energy structure. The ES is shown to balance energy improvement and yet maintain diversity in structures. The ES is implemented as a master-client model for distributed computing. Starting from random structures and by using this optimization technique, we were able to fold a 20 amino-acid helical protein and 16 amino-acid beta hairpin[3]. We compare ES to basin hopping method. [1]T. Herges and W. Wenzel,Biophys.J. 87,3100(2004) [2] A. Verma and W. Wenzel Stabilization and folding of beta-sheet and alpha-helical proteins in an all-atom free energy model(submitted)(2005) [3] S. M. Gopal and W. Wenzel Evolutionary Strategies for Protein Folding (in preparation)

The Boring Billion, a slingshot for Complex Life on Earth.

PubMed

Mukherjee, Indrani; Large, Ross R; Corkrey, Ross; Danyushevsky, Leonid V

2018-03-13

The period 1800 to 800 Ma ("Boring Billion") is believed to mark a delay in the evolution of complex life, primarily due to low levels of oxygen in the atmosphere. Earlier studies highlight the remarkably flat C, Cr isotopes and low trace element trends during the so-called stasis, caused by prolonged nutrient, climatic, atmospheric and tectonic stability. In contrast, we suggest a first-order variability of bio-essential trace element availability in the oceans by combining systematic sampling of the Proterozoic rock record with sensitive geochemical analyses of marine pyrite by LA-ICP-MS technique. We also recall that several critical biological evolutionary events, such as the appearance of eukaryotes, origin of multicellularity & sexual reproduction, and the first major diversification of eukaryotes (crown group) occurred during this period. Therefore, it appears possible that the period of low nutrient trace elements (1800-1400 Ma) caused evolutionary pressures which became an essential trigger for promoting biological innovations in the eukaryotic domain. Later periods of stress-free conditions, with relatively high nutrient trace element concentration, facilitated diversification. We propose that the "Boring Billion" was a period of sequential stepwise evolution and diversification of complex eukaryotes, triggering evolutionary pathways that made possible the later rise of micro-metazoans and their macroscopic counterparts.

BAYESIAN PROTEIN STRUCTURE ALIGNMENT.

PubMed

Rodriguez, Abel; Schmidler, Scott C

The analysis of the three-dimensional structure of proteins is an important topic in molecular biochemistry. Structure plays a critical role in defining the function of proteins and is more strongly conserved than amino acid sequence over evolutionary timescales. A key challenge is the identification and evaluation of structural similarity between proteins; such analysis can aid in understanding the role of newly discovered proteins and help elucidate evolutionary relationships between organisms. Computational biologists have developed many clever algorithmic techniques for comparing protein structures, however, all are based on heuristic optimization criteria, making statistical interpretation somewhat difficult. Here we present a fully probabilistic framework for pairwise structural alignment of proteins. Our approach has several advantages, including the ability to capture alignment uncertainty and to estimate key "gap" parameters which critically affect the quality of the alignment. We show that several existing alignment methods arise as maximum a posteriori estimates under specific choices of prior distributions and error models. Our probabilistic framework is also easily extended to incorporate additional information, which we demonstrate by including primary sequence information to generate simultaneous sequence-structure alignments that can resolve ambiguities obtained using structure alone. This combined model also provides a natural approach for the difficult task of estimating evolutionary distance based on structural alignments. The model is illustrated by comparison with well-established methods on several challenging protein alignment examples.

Wavelet evolutionary network for complex-constrained portfolio rebalancing

NASA Astrophysics Data System (ADS)

Suganya, N. C.; Vijayalakshmi Pai, G. A.

2012-07-01

Portfolio rebalancing problem deals with resetting the proportion of different assets in a portfolio with respect to changing market conditions. The constraints included in the portfolio rebalancing problem are basic, cardinality, bounding, class and proportional transaction cost. In this study, a new heuristic algorithm named wavelet evolutionary network (WEN) is proposed for the solution of complex-constrained portfolio rebalancing problem. Initially, the empirical covariance matrix, one of the key inputs to the problem, is estimated using the wavelet shrinkage denoising technique to obtain better optimal portfolios. Secondly, the complex cardinality constraint is eliminated using k-means cluster analysis. Finally, WEN strategy with logical procedures is employed to find the initial proportion of investment in portfolio of assets and also rebalance them after certain period. Experimental studies of WEN are undertaken on Bombay Stock Exchange, India (BSE200 index, period: July 2001-July 2006) and Tokyo Stock Exchange, Japan (Nikkei225 index, period: March 2002-March 2007) data sets. The result obtained using WEN is compared with the only existing counterpart named Hopfield evolutionary network (HEN) strategy and also verifies that WEN performs better than HEN. In addition, different performance metrics and data envelopment analysis are carried out to prove the robustness and efficiency of WEN over HEN strategy.

Eco-evolutionary feedbacks, adaptive dynamics and evolutionary rescue theory

PubMed Central

Ferriere, Regis; Legendre, Stéphane

2013-01-01

Adaptive dynamics theory has been devised to account for feedbacks between ecological and evolutionary processes. Doing so opens new dimensions to and raises new challenges about evolutionary rescue. Adaptive dynamics theory predicts that successive trait substitutions driven by eco-evolutionary feedbacks can gradually erode population size or growth rate, thus potentially raising the extinction risk. Even a single trait substitution can suffice to degrade population viability drastically at once and cause ‘evolutionary suicide’. In a changing environment, a population may track a viable evolutionary attractor that leads to evolutionary suicide, a phenomenon called ‘evolutionary trapping’. Evolutionary trapping and suicide are commonly observed in adaptive dynamics models in which the smooth variation of traits causes catastrophic changes in ecological state. In the face of trapping and suicide, evolutionary rescue requires that the population overcome evolutionary threats generated by the adaptive process itself. Evolutionary repellors play an important role in determining how variation in environmental conditions correlates with the occurrence of evolutionary trapping and suicide, and what evolutionary pathways rescue may follow. In contrast with standard predictions of evolutionary rescue theory, low genetic variation may attenuate the threat of evolutionary suicide and small population sizes may facilitate escape from evolutionary traps. PMID:23209163

Artificial intelligence in medicine.

PubMed Central

Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

2004-01-01

INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. RESULTS: The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. DISCUSSION: Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting. PMID:15333167

Artificial intelligence in medicine.

PubMed

Ramesh, A N; Kambhampati, C; Monson, J R T; Drew, P J

2004-09-01

Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting.

Toward autonomous spacecraft

NASA Technical Reports Server (NTRS)

Fogel, L. J.; Calabrese, P. G.; Walsh, M. J.; Owens, A. J.

1982-01-01

Ways in which autonomous behavior of spacecraft can be extended to treat situations wherein a closed loop control by a human may not be appropriate or even possible are explored. Predictive models that minimize mean least squared error and arbitrary cost functions are discussed. A methodology for extracting cyclic components for an arbitrary environment with respect to usual and arbitrary criteria is developed. An approach to prediction and control based on evolutionary programming is outlined. A computer program capable of predicting time series is presented. A design of a control system for a robotic dense with partially unknown physical properties is presented.

Lunar base as a precursor to Mars exploration and settlement

NASA Technical Reports Server (NTRS)

Mendell, Wendell W.

1991-01-01

A well planned program of human exploration of the moon is suggested which would provide a base for increasing human capabilities and experience to levels required for Mars exploration. A strategy intended for immediate Mars exploration and settlement is considered to incur serious programmatic risks from current lack of knowledge on human performance on long-duration deep space missions and lack of experience in designing human space systems. The lunar program provides an opportunity to build up space capability in an evolutionary way and to broaden the participation of the educational system in the space exploration.

The Benchmark Ultracool Subdwarf HD 114762B: A Test of Low-metallicity Atmospheric and Evolutionary Models

NASA Astrophysics Data System (ADS)

Bowler, Brendan P.; Liu, Michael C.; Cushing, Michael C.

2009-12-01

We present a near-infrared spectroscopic study of HD 114762B, the latest-type metal-poor companion discovered to date and the only ultracool subdwarf with a known metallicity, inferred from the primary star to be [Fe/H] = -0.7. We obtained a medium-resolution (R ~ 3800) Keck/OSIRIS 1.18-1.40 μm spectrum and a low-resolution (R ~ 150) Infrared Telescope Facility/SpeX 0.8-2.4 μm spectrum of HD 114762B to test atmospheric and evolutionary models for the first time in this mass-metallicity regime. HD 114762B exhibits spectral features common to both late-type dwarfs and subdwarfs, and we assign it a spectral type of d/sdM9 ± 1. We use a Monte Carlo technique to fit PHOENIX/GAIA synthetic spectra to the observations, accounting for the coarsely gridded nature of the models. Fits to the entire OSIRIS J-band and to the metal-sensitive J-band atomic absorption features (Fe I, K I, and Al I lines) yield model parameters that are most consistent with the metallicity of the primary star and the high surface gravity expected of old late-type objects. The effective temperatures and radii inferred from the model atmosphere fitting broadly agree with those predicted by the evolutionary models of Chabrier & Baraffe, and the model color-absolute magnitude relations accurately predict the metallicity of HD 114762B. We conclude that current low-mass, mildly metal-poor atmospheric and evolutionary models are mutually consistent for spectral fits to medium-resolution J-band spectra of HD 114762B, but are inconsistent for fits to low-resolution near-infrared spectra of mild subdwarfs. Finally, we develop a technique for estimating distances to ultracool subdwarfs based on a single near-infrared spectrum. We show that this "spectroscopic parallax" method enables distance estimates accurate to lsim10% of parallactic distances for ultracool subdwarfs near the hydrogen burning minimum mass. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

Retention and application of Skylab experiences to future programs. [a postflight review of technical programs.

NASA Technical Reports Server (NTRS)

Gillespie, V. G.; Kelly, R. O.

1974-01-01

The problems encountered and special techniques and procedures developed on the Skylab program are described along with the experiences and practical benefits obtained for dissemination and use on future programs. Three major topics are discussed: electrical problems, mechanical problems, and special techniques. Special techniques and procedures are identified that were either developed or refined during the Skylab program. These techniques and procedures came from all manufacturing and test phases of the Skylab program and include both flight and GSE items from component level to sophisticated spaceflight systems.

The astrophysics program at the National Aeronautics and Space Administration (NASA)

NASA Technical Reports Server (NTRS)

Pellerin, C. J.

1990-01-01

Three broad themes characterize the goals of the Astrophysics Division at NASA. These are obtaining an understanding of the origin and evolution of the universe, the fundamental laws of physics, and the birth and evolutionary cycle of galaxies, stars, planets and life. These goals are pursued through contemporaneous observations across the electromagnetic spectrum with high sensitivity and resolution. The strategy to accomplish these goals is fourfold: the establishment of long term space based observatories implemented through the Great Observatories program; attainment of crucial bridging and supporting measurements visa missions of intermediate and small scope conducted within the Explorer, Spacelab, and Space Station Attached Payload Programs; enhancement of scientific access to results of space based research activities through an integrated data system; and development and maintenance of the scientific/technical base for space astrophysics programs through the research and analysis and suborbital programs. The near term activities supporting the first two objectives are discussed.

Foot-and-Mouth Disease in the Middle East Caused by an A/ASIA/G-VII Virus Lineage, 2015-2016.

PubMed

Bachanek-Bankowska, Katarzyna; Di Nardo, Antonello; Wadsworth, Jemma; Henry, Elisabeth K M; Parlak, Ünal; Timina, Anna; Mischenko, Alexey; Qasim, Ibrahim Ahmad; Abdollahi, Darab; Sultana, Munawar; Hossain, M Anwar; King, Donald P; Knowles, Nick J

2018-06-01

Phylogenetic analyses of foot-and-mouth disease type A viruses in the Middle East during 2015-2016 identified viruses belonging to the A/ASIA/G-VII lineage, which originated in the Indian subcontinent. Changes in a critical antigenic site within capsid viral protein 1 suggest possible evolutionary pressure caused by an intensive vaccination program.

Blending ecology and evolution using emerging technologies to determine species distributions with a non-native pathogen in a changing climate

Treesearch

K. Waring; S. Cushman; A. Eckert; L. Flores-Renteria; H. Lintz; R. Sniezko; C. Still; C. Wehenkel; A. Whipple; M. Wing

2017-01-01

A collaborative team of researchers from the United States and Mexico has begun an exciting new research project funded by The National Science Foundation’s Macrosystems Biology program. The project will study ecological and evolutionary processes affecting the distribution of southwestern white pine (Pinus strobiformis), an important tree species of mixed conifer...

CVX Damage Control Information Technology Evolutionary Model

DTIC Science & Technology

1999-03-01

technology -based learning generally) may be exciting technically, it does not automatically lead to better educational programs. Good instructional design...expected to act on the first Aircraft Carrier to attempt substantial manning reductions if nothing is learned from Smart Ship. Beyond the technologies ... technology of the day. Many of the lessons learned then are in use today. However, technology breakthroughs we are now experiencing invite us to

An evolutionary perspective on the history of flap reconstruction in the upper extremity.

PubMed

Fang, Frank; Chung, Kevin C

2014-05-01

Examining the evolution of flap reconstruction of the upper extremity is similar to studying the evolution of biological species. This analogy provides a perspective to appreciate the contributing factors that led to the development of the current arsenal of techniques. It shows the trajectory for the future and provides a glimpse of the factors that that will be influential in the future. Copyright © 2014 Elsevier Inc. All rights reserved.

In-air and pressurized water reactor environment fatigue experiments of 316 stainless steel to study the effect of environment on cyclic hardening

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mohanty, Subhasish; Soppet, William K.; Majumdar, Saurindranath

Argonne National Laboratory (ANL), under the sponsorship of Department of Energy’s Light Water Reactor Sustainability (LWRS) program, is trying to develop a mechanistic approach for more accurate life estimation of LWR components. In this context, ANL has conducted many fatigue experiments under different test and environment conditions on type 316 stainless steel (316SS) material which is widely used in the US reactors. Contrary to the conventional S~N curve based empirical fatigue life estimation approach, the aim of the present DOE sponsored work is to develop an understanding of the material ageing issues more mechanistically (e.g. time dependent hardening and softening)more » under different test and environmental conditions. Better mechanistic understanding will help develop computer-based advanced modeling tools to better extrapolate stress-strain evolution of reactor components under multi-axial stress states and hence help predict their fatigue life more accurately. In this paper (part-I) the fatigue experiments under different test and environment conditions and related stress-strain results for 316 SS are discussed. In a second paper (part-II) the related evolutionary cyclic plasticity material modeling techniques and results are discussed.« less

Dynamics of genetic variability in Anastrepha fraterculus (Diptera: Tephritidae) during adaptation to laboratory rearing conditions.

PubMed

Parreño, María A; Scannapieco, Alejandra C; Remis, María I; Juri, Marianela; Vera, María T; Segura, Diego F; Cladera, Jorge L; Lanzavecchia, Silvia B

2014-01-01

Anastrepha fraterculus is one of the most important fruit fly plagues in the American continent and only chemical control is applied in the field to diminish its population densities. A better understanding of the genetic variability during the introduction and adaptation of wild A. fraterculus populations to laboratory conditions is required for the development of stable and vigorous experimental colonies and mass-reared strains in support of successful Sterile Insect Technique (SIT) efforts. The present study aims to analyze the dynamics of changes in genetic variability during the first six generations under artificial rearing conditions in two populations: a) a wild population recently introduced to laboratory culture, named TW and, b) a long-established control line, named CL. Results showed a declining tendency of genetic variability in TW. In CL, the relatively high values of genetic variability appear to be maintained across generations and could denote an intrinsic capacity to avoid the loss of genetic diversity in time. The impact of evolutionary forces on this species during the adaptation process as well as the best approach to choose strategies to introduce experimental and mass-reared A. fraterculus strains for SIT programs are discussed.