Evolutionary design optimization of traffic signals applied to Quito city

PubMed Central

2017-01-01

This work applies evolutionary computation and machine learning methods to study the transportation system of Quito from a design optimization perspective. It couples an evolutionary algorithm with a microscopic transport simulator and uses the outcome of the optimization process to deepen our understanding of the problem and gain knowledge about the system. The work focuses on the optimization of a large number of traffic lights deployed on a wide area of the city and studies their impact on travel time, emissions and fuel consumption. An evolutionary algorithm with specialized mutation operators is proposed to search effectively in large decision spaces, evolving small populations for a short number of generations. The effects of the operators combined with a varying mutation schedule are studied, and an analysis of the parameters of the algorithm is also included. In addition, hierarchical clustering is performed on the best solutions found in several runs of the algorithm. An analysis of signal clusters and their geolocation, estimation of fuel consumption, spatial analysis of emissions, and an analysis of signal coordination provide an overall picture of the systemic effects of the optimization process. PMID:29236733

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 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.

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.

A performance-oriented power transformer design methodology using multi-objective evolutionary optimization

PubMed Central

Adly, Amr A.; Abd-El-Hafiz, Salwa K.

2014-01-01

Transformers are regarded as crucial components in power systems. Due to market globalization, power transformer manufacturers are facing an increasingly competitive environment that mandates the adoption of design strategies yielding better performance at lower costs. In this paper, a power transformer design methodology using multi-objective evolutionary optimization is proposed. Using this methodology, which is tailored to be target performance design-oriented, quick rough estimation of transformer design specifics may be inferred. Testing of the suggested approach revealed significant qualitative and quantitative match with measured design and performance values. Details of the proposed methodology as well as sample design results are reported in the paper. PMID:26257939

A performance-oriented power transformer design methodology using multi-objective evolutionary optimization.

PubMed

Adly, Amr A; Abd-El-Hafiz, Salwa K

2015-05-01

Transformers are regarded as crucial components in power systems. Due to market globalization, power transformer manufacturers are facing an increasingly competitive environment that mandates the adoption of design strategies yielding better performance at lower costs. In this paper, a power transformer design methodology using multi-objective evolutionary optimization is proposed. Using this methodology, which is tailored to be target performance design-oriented, quick rough estimation of transformer design specifics may be inferred. Testing of the suggested approach revealed significant qualitative and quantitative match with measured design and performance values. Details of the proposed methodology as well as sample design results are reported in the paper.

Evolvable Hardware for Space Applications

NASA Technical Reports Server (NTRS)

Lohn, Jason; Globus, Al; Hornby, Gregory; Larchev, Gregory; Kraus, William

2004-01-01

This article surveys the research of the Evolvable Systems Group at NASA Ames Research Center. Over the past few years, our group has developed the ability to use evolutionary algorithms in a variety of NASA applications ranging from spacecraft antenna design, fault tolerance for programmable logic chips, atomic force field parameter fitting, analog circuit design, and earth observing satellite scheduling. In some of these applications, evolutionary algorithms match or improve on human performance.

Designing synthetic networks in silico: a generalised evolutionary algorithm approach.

PubMed

Smith, Robert W; van Sluijs, Bob; Fleck, Christian

2017-12-02

Evolution has led to the development of biological networks that are shaped by environmental signals. Elucidating, understanding and then reconstructing important network motifs is one of the principal aims of Systems & Synthetic Biology. Consequently, previous research has focused on finding optimal network structures and reaction rates that respond to pulses or produce stable oscillations. In this work we present a generalised in silico evolutionary algorithm that simultaneously finds network structures and reaction rates (genotypes) that can satisfy multiple defined objectives (phenotypes). The key step to our approach is to translate a schema/binary-based description of biological networks into systems of ordinary differential equations (ODEs). The ODEs can then be solved numerically to provide dynamic information about an evolved networks functionality. Initially we benchmark algorithm performance by finding optimal networks that can recapitulate concentration time-series data and perform parameter optimisation on oscillatory dynamics of the Repressilator. We go on to show the utility of our algorithm by finding new designs for robust synthetic oscillators, and by performing multi-objective optimisation to find a set of oscillators and feed-forward loops that are optimal at balancing different system properties. In sum, our results not only confirm and build on previous observations but we also provide new designs of synthetic oscillators for experimental construction. In this work we have presented and tested an evolutionary algorithm that can design a biological network to produce desired output. Given that previous designs of synthetic networks have been limited to subregions of network- and parameter-space, the use of our evolutionary optimisation algorithm will enable Synthetic Biologists to construct new systems with the potential to display a wider range of complex responses.

Using Generative Representations to Evolve Robots. Chapter 1

NASA Technical Reports Server (NTRS)

Hornby, Gregory S.

2004-01-01

Recent research has demonstrated the ability of evolutionary algorithms to automatically design both the physical structure and software controller of real physical robots. One of the challenges for these automated design systems is to improve their ability to scale to the high complexities found in real-world problems. Here we claim that for automated design systems to scale in complexity they must use a representation which allows for the hierarchical creation and reuse of modules, which we call a generative representation. Not only is the ability to reuse modules necessary for functional scalability, but it is also valuable for improving efficiency in testing and construction. We then describe an evolutionary design system with a generative representation capable of hierarchical modularity and demonstrate it for the design of locomoting robots in simulation. Finally, results from our experiments show that evolution with our generative representation produces better robots than those evolved with a non-generative representation.

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.

The kW power module evolution study: Executive summary

NASA Technical Reports Server (NTRS)

1979-01-01

Using the Marshall Space Flight Center 25 kW Power Module (PM) reference design as a point of departure, the study defined evolutionary growth paths to 100 kW and above. A recommended development approach and initial configurations were described. Specific hardware changes from the reference design are recommended for the initial PM configuration to ensure evolutionary growth, improved replicability, and reduced cost. Certain functional changes are also recommended to enhance system capabilities.

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.

Sum-of-squares-based fuzzy controller design using quantum-inspired evolutionary algorithm

NASA Astrophysics Data System (ADS)

Yu, Gwo-Ruey; Huang, Yu-Chia; Cheng, Chih-Yung

2016-07-01

In the field of fuzzy control, control gains are obtained by solving stabilisation conditions in linear-matrix-inequality-based Takagi-Sugeno fuzzy control method and sum-of-squares-based polynomial fuzzy control method. However, the optimal performance requirements are not considered under those stabilisation conditions. In order to handle specific performance problems, this paper proposes a novel design procedure with regard to polynomial fuzzy controllers using quantum-inspired evolutionary algorithms. The first contribution of this paper is a combination of polynomial fuzzy control and quantum-inspired evolutionary algorithms to undertake an optimal performance controller design. The second contribution is the proposed stability condition derived from the polynomial Lyapunov function. The proposed design approach is dissimilar to the traditional approach, in which control gains are obtained by solving the stabilisation conditions. The first step of the controller design uses the quantum-inspired evolutionary algorithms to determine the control gains with the best performance. Then, the stability of the closed-loop system is analysed under the proposed stability conditions. To illustrate effectiveness and validity, the problem of balancing and the up-swing of an inverted pendulum on a cart is used.

From evolutionary computation to the evolution of things.

PubMed

Eiben, Agoston E; Smith, Jim

2015-05-28

Evolution has provided a source of inspiration for algorithm designers since the birth of computers. The resulting field, evolutionary computation, has been successful in solving engineering tasks ranging in outlook from the molecular to the astronomical. Today, the field is entering a new phase as evolutionary algorithms that take place in hardware are developed, opening up new avenues towards autonomous machines that can adapt to their environment. We discuss how evolutionary computation compares with natural evolution and what its benefits are relative to other computing approaches, and we introduce the emerging area of artificial evolution in physical systems.

A framework for evolutionary systems biology

PubMed Central

Loewe, Laurence

2009-01-01

Background Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects. Results Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions in silico. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism. Conclusion EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications. PMID:19239699

Algorithmic Mechanism Design of Evolutionary Computation.

PubMed

Pei, Yan

2015-01-01

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

Algorithmic Mechanism Design of Evolutionary Computation

PubMed Central

2015-01-01

We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm. PMID:26257777

Learning Evolution and the Nature of Science Using Evolutionary Computing and Artificial Life

ERIC Educational Resources Information Center

Pennock, Robert T.

2007-01-01

Because evolution in natural systems happens so slowly, it is difficult to design inquiry-based labs where students can experiment and observe evolution in the way they can when studying other phenomena. New research in evolutionary computation and artificial life provides a solution to this problem. This paper describes a new A-Life software…

Vehicle management and mission planning systems with shuttle applications

NASA Technical Reports Server (NTRS)

1972-01-01

A preliminary definition of a concept for an automated system is presented that will support the effective management and planning of space shuttle operations. It is called the Vehicle Management and Mission Planning System (VMMPS). In addition to defining the system and its functions, some of the software requirements of the system are identified and a phased and evolutionary method is recommended for software design, development, and implementation. The concept is composed of eight software subsystems supervised by an executive system. These subsystems are mission design and analysis, flight scheduler, launch operations, vehicle operations, payload support operations, crew support, information management, and flight operations support. In addition to presenting the proposed system, a discussion of the evolutionary software development philosophy that the Mission Planning and Analysis Division (MPAD) would propose to use in developing the required supporting software is included. A preliminary software development schedule is also included.

Advanced Targeting Cost Function Design for Evolutionary Optimization of Control of Logistic Equation

NASA Astrophysics Data System (ADS)

Senkerik, Roman; Zelinka, Ivan; Davendra, Donald; Oplatkova, Zuzana

2010-06-01

This research deals with the optimization of the control of chaos by means of evolutionary algorithms. This work is aimed on an explanation of how to use evolutionary algorithms (EAs) and how to properly define the advanced targeting cost function (CF) securing very fast and precise stabilization of desired state for any initial conditions. As a model of deterministic chaotic system, the one dimensional Logistic equation was used. The evolutionary algorithm Self-Organizing Migrating Algorithm (SOMA) was used in four versions. For each version, repeated simulations were conducted to outline the effectiveness and robustness of used method and targeting CF.

Ecological perspectives on synthetic biology: insights from microbial population biology

PubMed Central

Escalante, Ana E.; Rebolleda-Gómez, María; Benítez, Mariana; Travisano, Michael

2015-01-01

The metabolic capabilities of microbes are the basis for many major biotechnological advances, exploiting microbial diversity by selection or engineering of single strains. However, there are limits to the advances that can be achieved with single strains, and attention has turned toward the metabolic potential of consortia and the field of synthetic ecology. The main challenge for the synthetic ecology is that consortia are frequently unstable, largely because evolution by constituent members affects their interactions, which are the basis of collective metabolic functionality. Current practices in modeling consortia largely consider interactions as fixed circuits of chemical reactions, which greatly increases their tractability. This simplification comes at the cost of essential biological realism, stripping out the ecological context in which the metabolic actions occur and the potential for evolutionary change. In other words, evolutionary stability is not engineered into the system. This realization highlights the necessity to better identify the key components that influence the stable coexistence of microorganisms. Inclusion of ecological and evolutionary principles, in addition to biophysical variables and stoichiometric modeling of metabolism, is critical for microbial consortia design. This review aims to bring ecological and evolutionary concepts to the discussion on the stability of microbial consortia. In particular, we focus on the combined effect of spatial structure (connectivity of molecules and cells within the system) and ecological interactions (reciprocal and non-reciprocal) on the persistence of microbial consortia. We discuss exemplary cases to illustrate these ideas from published studies in evolutionary biology and biotechnology. We conclude by making clear the relevance of incorporating evolutionary and ecological principles to the design of microbial consortia, as a way of achieving evolutionarily stable and sustainable systems. PMID:25767468

Automatic Evolution of Molecular Nanotechnology Designs

NASA Technical Reports Server (NTRS)

Globus, Al; Lawton, John; Wipke, Todd; Saini, Subhash (Technical Monitor)

1998-01-01

This paper describes strategies for automatically generating designs for analog circuits at the molecular level. Software maps out the edges and vertices of potential nanotechnology systems on graphs, then selects appropriate ones through evolutionary or genetic paradigms.

Performance optimization of the power user electric energy data acquire system based on MOEA/D evolutionary algorithm

NASA Astrophysics Data System (ADS)

Ding, Zhongan; Gao, Chen; Yan, Shengteng; Yang, Canrong

2017-10-01

The power user electric energy data acquire system (PUEEDAS) is an important part of smart grid. This paper builds a multi-objective optimization model for the performance of the PUEEADS from the point of view of the combination of the comprehensive benefits and cost. Meanwhile, the Chebyshev decomposition approach is used to decompose the multi-objective optimization problem. We design a MOEA/D evolutionary algorithm to solve the problem. By analyzing the Pareto optimal solution set of multi-objective optimization problem and comparing it with the monitoring value to grasp the direction of optimizing the performance of the PUEEDAS. Finally, an example is designed for specific analysis.

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

What have humans done for evolutionary biology? Contributions from genes to populations.

PubMed

Briga, Michael; Griffin, Robert M; Berger, Vérane; Pettay, Jenni E; Lummaa, Virpi

2017-11-15

Many fundamental concepts in evolutionary biology were discovered using non-human study systems. Humans are poorly suited to key study designs used to advance this field, and are subject to cultural, technological, and medical influences often considered to restrict the pertinence of human studies to other species and general contexts. Whether studies using current and recent human populations provide insights that have broader biological relevance in evolutionary biology is, therefore, frequently questioned. We first surveyed researchers in evolutionary biology and related fields on their opinions regarding whether studies on contemporary humans can advance evolutionary biology. Almost all 442 participants agreed that humans still evolve, but fewer agreed that this occurs through natural selection. Most agreed that human studies made valuable contributions to evolutionary biology, although those less exposed to human studies expressed more negative views. With a series of examples, we discuss strengths and limitations of evolutionary studies on contemporary humans. These show that human studies provide fundamental insights into evolutionary processes, improve understanding of the biology of many other species, and will make valuable contributions to evolutionary biology in the future. © 2017 The Author(s).

What have humans done for evolutionary biology? Contributions from genes to populations

PubMed Central

Briga, Michael; Griffin, Robert M.; Berger, Vérane; Pettay, Jenni E.

2017-01-01

Many fundamental concepts in evolutionary biology were discovered using non-human study systems. Humans are poorly suited to key study designs used to advance this field, and are subject to cultural, technological, and medical influences often considered to restrict the pertinence of human studies to other species and general contexts. Whether studies using current and recent human populations provide insights that have broader biological relevance in evolutionary biology is, therefore, frequently questioned. We first surveyed researchers in evolutionary biology and related fields on their opinions regarding whether studies on contemporary humans can advance evolutionary biology. Almost all 442 participants agreed that humans still evolve, but fewer agreed that this occurs through natural selection. Most agreed that human studies made valuable contributions to evolutionary biology, although those less exposed to human studies expressed more negative views. With a series of examples, we discuss strengths and limitations of evolutionary studies on contemporary humans. These show that human studies provide fundamental insights into evolutionary processes, improve understanding of the biology of many other species, and will make valuable contributions to evolutionary biology in the future. PMID:29118130

Energy and time determine scaling in biological and computer designs

PubMed Central

Bezerra, George; Edwards, Benjamin; Brown, James; Forrest, Stephanie

2016-01-01

Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy–time minimization principle may govern the design of many complex systems that process energy, materials and information. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID:27431524

Energy and time determine scaling in biological and computer designs.

PubMed

Moses, Melanie; Bezerra, George; Edwards, Benjamin; Brown, James; Forrest, Stephanie

2016-08-19

Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy-time minimization principle may govern the design of many complex systems that process energy, materials and information.This article is part of the themed issue 'The major synthetic evolutionary transitions'. © 2016 The Author(s).

Toward Optimal Transport Networks

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia; Kincaid, Rex K.; Vargo, Erik P.

2008-01-01

Strictly evolutionary approaches to improving the air transport system a highly complex network of interacting systems no longer suffice in the face of demand that is projected to double or triple in the near future. Thus evolutionary approaches should be augmented with active design methods. The ability to actively design, optimize and control a system presupposes the existence of predictive modeling and reasonably well-defined functional dependences between the controllable variables of the system and objective and constraint functions for optimization. Following recent advances in the studies of the effects of network topology structure on dynamics, we investigate the performance of dynamic processes on transport networks as a function of the first nontrivial eigenvalue of the network's Laplacian, which, in turn, is a function of the network s connectivity and modularity. The last two characteristics can be controlled and tuned via optimization. We consider design optimization problem formulations. We have developed a flexible simulation of network topology coupled with flows on the network for use as a platform for computational experiments.

Extended evolution: A conceptual framework for integrating regulatory networks and niche construction

PubMed Central

Renn, Jürgen

2015-01-01

ABSTRACT This paper introduces a conceptual framework for the evolution of complex systems based on the integration of regulatory network and niche construction theories. It is designed to apply equally to cases of biological, social and cultural evolution. Within the conceptual framework we focus especially on the transformation of complex networks through the linked processes of externalization and internalization of causal factors between regulatory networks and their corresponding niches and argue that these are an important part of evolutionary explanations. This conceptual framework extends previous evolutionary models and focuses on several challenges, such as the path‐dependent nature of evolutionary change, the dynamics of evolutionary innovation and the expansion of inheritance systems. J. Exp. Zool. (Mol. Dev. Evol.) 324B: 565–577, 2015. © 2015 The Authors. Journal of Experimental Zoology Part B: Molecular and Developmental Evolution published by Wiley Periodicals, Inc. PMID:26097188

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.

Learning Biology by Designing

ERIC Educational Resources Information Center

Janssen, Fred; Waarlo, Arend Jan

2010-01-01

According to a century-old tradition in biological thinking, organisms can be considered as being optimally designed. In modern biology this idea still has great heuristic value. In evolutionary biology a so-called design heuristic has been formulated which provides guidance to researchers in the generation of knowledge about biological systems.…

Can evolutionary theory explain the slow development of knowledge about the level of safety built into roads?

PubMed

Elvik, Rune

2017-09-01

In several papers, Hauer (1988, 1989, 2000a, 2000b, 2016) has argued that the level of safety built into roads is unpremeditated, i.e. not the result of decisions based on knowledge of the safety impacts of design standards. Hauer has pointed out that the development of knowledge about the level of safety built into roads has been slow and remains incomplete even today. Based on these observations, this paper asks whether evolutionary theory can contribute to explaining the slow development of knowledge. A key proposition of evolutionary theory is that knowledge is discovered through a process of learning-by-doing; it is not necessarily produced intentionally by means of research or development. An unintentional discovery of knowledge is treacherous as far as road safety is concerned, since an apparently effective safety treatment may simply be the result of regression-to-the-mean. The importance of regression-to-the-mean was not fully understood until about 1980, and a substantial part of what was regarded as known at that time may have been based on studies not controlling for regression-to-the-mean. An attempt to provide an axiomatic foundation for designing a safe road system was made by Gunnarsson and Lindström (1970). This had the ambition of providing universal guidelines that would facilitate a preventive approach, rather than the reactive approach based on accident history (i.e. designing a system known to be safe, rather than reacting to events in a system of unknown safety). Three facts are notable about these principles. First, they are stated in very general terms and do not address many of the details of road design or traffic control. Second, they are not based on experience showing their effectiveness. Third, they are partial and do not address the interaction between elements of the road traffic system, in particular road user adaptation to system design. Another notable fact consistent with evolutionary theory, is that the safety margins built into various design elements have been continuously eroded by the development of bigger and faster motor vehicles, that can only be operated safely if roads are wider and straighter than they needed to be when motor vehicles were smaller and moved slower. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modelling and strategy optimisation for a kind of networked evolutionary games with memories under the bankruptcy mechanism

NASA Astrophysics Data System (ADS)

Fu, Shihua; Li, Haitao; Zhao, Guodong

2018-05-01

This paper investigates the evolutionary dynamic and strategy optimisation for a kind of networked evolutionary games whose strategy updating rules incorporate 'bankruptcy' mechanism, and the situation that each player's bankruptcy is due to the previous continuous low profits gaining from the game is considered. First, by using semi-tensor product of matrices method, the evolutionary dynamic of this kind of games is expressed as a higher order logical dynamic system and then converted into its algebraic form, based on which, the evolutionary dynamic of the given games can be discussed. Second, the strategy optimisation problem is investigated, and some free-type control sequences are designed to maximise the total payoff of the whole game. Finally, an illustrative example is given to show that our new results are very effective.

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

Intelligent monitoring and diagnosis systems for the Space Station Freedom ECLSS

NASA Technical Reports Server (NTRS)

Dewberry, Brandon S.; Carnes, James R.

1991-01-01

Specific activities in NASA's environmental control and life support system (ECLSS) advanced automation project that is designed to minimize the crew and ground manpower needed for operations are discussed. Various analyses and the development of intelligent software for the initial and evolutionary Space Station Freedom (SSF) ECLSS are described. The following are also discussed: (1) intelligent monitoring and diagnostics applications under development for the ECLSS domain; (2) integration into the MSFC ECLSS hardware testbed; and (3) an evolutionary path from the baseline ECLSS automation to the more advanced ECLSS automation processes.

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.

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.

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

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

Measuring, Enabling and Comparing Modularity, Regularity and Hierarchy in Evolutionary Design

NASA Technical Reports Server (NTRS)

Hornby, Gregory S.

2005-01-01

For computer-automated design systems to scale to complex designs they must be able to produce designs that exhibit the characteristics of modularity, regularity and hierarchy - characteristics that are found both in man-made and natural designs. Here we claim that these characteristics are enabled by implementing the attributes of combination, control-flow and abstraction in the representation. To support this claim we use an evolutionary algorithm to evolve solutions to different sizes of a table design problem using five different representations, each with different combinations of modularity, regularity and hierarchy enabled and show that the best performance happens when all three of these attributes are enabled. We also define metrics for modularity, regularity and hierarchy in design encodings and demonstrate that high fitness values are achieved with high values of modularity, regularity and hierarchy and that there is a positive correlation between increases in fitness and increases in modularity. regularity and hierarchy.

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.

Turbomachinery Airfoil Design Optimization Using Differential Evolution

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.; Biegel, Bryan A. (Technical Monitor)

2002-01-01

An aerodynamic design optimization procedure that is based on a evolutionary algorithm known at Differential Evolution is described. Differential Evolution is a simple, fast, and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems, including highly nonlinear systems with discontinuities and multiple local optima. The method is combined with a Navier-Stokes solver that evaluates the various intermediate designs and provides inputs to the optimization procedure. An efficient constraint handling mechanism is also incorporated. Results are presented for the inverse design of a turbine airfoil from a modern jet engine. The capability of the method to search large design spaces and obtain the optimal airfoils in an automatic fashion is demonstrated. Substantial reductions in the overall computing time requirements are achieved by using the algorithm in conjunction with neural networks.

Space station WP-04 power system. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

Hallinan, G. J.

1987-01-01

Major study activities and results of the phase B study contract for the preliminary design of the space station Electrical Power System (EPS) are summarized. The areas addressed include the general system design, man-tended option, automation and robotics, evolutionary growth, software development environment, advanced development, customer accommodations, operations planning, product assurance, and design and development phase planning. The EPS consists of a combination photovoltaic and solar dynamic power generation subsystem and a power management and distribution (PMAD) subsystem. System trade studies and costing activities are also summarized.

Design and implementation of EP-based PID controller for chaos synchronization of Rikitake circuit systems.

PubMed

Hou, Yi-You

2017-09-01

This article addresses an evolutionary programming (EP) algorithm technique-based and proportional-integral-derivative (PID) control methods are established to guarantee synchronization of the master and slave Rikitake chaotic systems. For PID synchronous control, the evolutionary programming (EP) algorithm is used to find the optimal PID controller parameters k p , k i , k d by integrated absolute error (IAE) method for the convergence conditions. In order to verify the system performance, the basic electronic components containing operational amplifiers (OPAs), resistors, and capacitors are used to implement the proposed chaotic Rikitake systems. Finally, the experimental results validate the proposed Rikitake chaotic synchronization approach. Copyright © 2017. Published by Elsevier Ltd.

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.

Langley's CSI evolutionary model: Phase O

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

Evolutionary Developmental Robotics: Improving Morphology and Control of Physical Robots.

PubMed

Vujovic, Vuk; Rosendo, Andre; Brodbeck, Luzius; Iida, Fumiya

2017-01-01

Evolutionary algorithms have previously been applied to the design of morphology and control of robots. The design space for such tasks can be very complex, which can prevent evolution from efficiently discovering fit solutions. In this article we introduce an evolutionary-developmental (evo-devo) experiment with real-world robots. It allows robots to grow their leg size to simulate ontogenetic morphological changes, and this is the first time that such an experiment has been performed in the physical world. To test diverse robot morphologies, robot legs of variable shapes were generated during the evolutionary process and autonomously built using additive fabrication. We present two cases with evo-devo experiments and one with evolution, and we hypothesize that the addition of a developmental stage can be used within robotics to improve performance. Moreover, our results show that a nonlinear system-environment interaction exists, which explains the nontrivial locomotion patterns observed. In the future, robots will be present in our daily lives, and this work introduces for the first time physical robots that evolve and grow while interacting with the environment.

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

PubMed

Baldominos, Alejandro; Saez, Yago; Isasi, Pedro

2018-04-23

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

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

PubMed Central

2018-01-01

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

Eyes Wide Shut: the impact of dim-light vision on neural investment in marine teleosts.

PubMed

Iglesias, Teresa L; Dornburg, Alex; Warren, Dan L; Wainwright, Peter C; Schmitz, Lars; Economo, Evan P

2018-05-28

Understanding how organismal design evolves in response to environmental challenges is a central goal of evolutionary biology. In particular, assessing the extent to which environmental requirements drive general design features among distantly related groups is a major research question. The visual system is a critical sensory apparatus that evolves in response to changing light regimes. In vertebrates, the optic tectum is the primary visual processing centre of the brain and yet it is unclear how or whether this structure evolves while lineages adapt to changes in photic environment. On one hand, dim-light adaptation is associated with larger eyes and enhanced light-gathering power that could require larger information processing capacity. On the other hand, dim-light vision may evolve to maximize light sensitivity at the cost of acuity and colour sensitivity, which could require less processing power. Here, we use X-ray microtomography and phylogenetic comparative methods to examine the relationships between diel activity pattern, optic morphology, trophic guild and investment in the optic tectum across the largest radiation of vertebrates-teleost fishes. We find that despite driving the evolution of larger eyes, enhancement of the capacity for dim-light vision generally is accompanied by a decrease in investment in the optic tectum. These findings underscore the importance of considering diel activity patterns in comparative studies and demonstrate how vision plays a role in brain evolution, illuminating common design principles of the vertebrate visual system. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Human Factors in Automated and Robotic Space Systems: Proceedings of a Symposium (Washington, D.C., January 29-30, 1987).

ERIC Educational Resources Information Center

Sheridan, Thomas B., Ed.; And Others

This document attempts to identify and promote human factors research that would likely produce results applicable to the evolutionary design of a National Aeronautics and Space Administration (NASA) national space station to be launched in the 1990s. It reports on a symposium designed to yield information applicable to future space systems. The…

The Environmental Control and Life Support System (ECLSS) advanced automation project

NASA Technical Reports Server (NTRS)

Dewberry, Brandon S.; Carnes, Ray

1990-01-01

The objective of the environmental control and life support system (ECLSS) Advanced Automation Project is to influence the design of the initial and evolutionary Space Station Freedom Program (SSFP) ECLSS toward a man-made closed environment in which minimal flight and ground manpower is needed. Another objective includes capturing ECLSS design and development knowledge future missions. Our approach has been to (1) analyze the SSFP ECLSS, (2) envision as our goal a fully automated evolutionary environmental control system - an augmentation of the baseline, and (3) document the advanced software systems, hooks, and scars which will be necessary to achieve this goal. From this analysis, prototype software is being developed, and will be tested using air and water recovery simulations and hardware subsystems. In addition, the advanced software is being designed, developed, and tested using automation software management plan and lifecycle tools. Automated knowledge acquisition, engineering, verification and testing tools are being used to develop the software. In this way, we can capture ECLSS development knowledge for future use develop more robust and complex software, provide feedback to the knowledge based system tool community, and ensure proper visibility of our efforts.

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.

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

Designing and Securing an Event Processing System for Smart Spaces

ERIC Educational Resources Information Center

Li, Zang

2011-01-01

Smart spaces, or smart environments, represent the next evolutionary development in buildings, banking, homes, hospitals, transportation systems, industries, cities, and government automation. By riding the tide of sensor and event processing technologies, the smart environment captures and processes information about its surroundings as well as…

Environmental Controls and Life Support System Design for a Space Exploration Vehicle

NASA Technical Reports Server (NTRS)

Stambaugh, Imelda C.; Rodriguez, Branelle; Vonau, Walt, Jr.; Borrego, Melissa

2012-01-01

Engineers at Johnson Space Center (JSC) are developing an Environmental Control and Life Support System (ECLSS) design for the Space Exploration Vehicle (SEV). The SEV will aid to expand the human exploration envelope for Geostationary Transfer Orbit (GEO), Near Earth Object (NEO), or planetary missions by using pressurized surface exploration vehicles. The SEV, formerly known as the Lunar Electric Rover (LER), will be an evolutionary design starting as a ground test prototype where technologies for various systems will be tested and evolve into a flight vehicle. This paper will discuss the current SEV ECLSS design, any work contributed toward the development of the ECLSS design, and the plan to advance the ECLSS design based on the SEV vehicle and system needs.

Environmental Controls and Life Support System (ECLSS) Design for a Space Exploration Vehicle (SEV)

NASA Technical Reports Server (NTRS)

Stambaugh, Imelda; Sankaran, Subra

2010-01-01

Engineers at Johnson Space Center (JSC) are developing an Environmental Control and Life Support System (ECLSS) design for the Space Exploration Vehicle (SEV). The SEV will aid to expand the human exploration envelope for Geostationary Transfer Orbit (GEO), Near Earth Object (NEO), or planetary missions by using pressurized surface exploration vehicles. The SEV, formerly known as the Lunar Electric Rover (LER), will be an evolutionary design starting as a ground test prototype where technologies for various systems will be tested and evolve into a flight vehicle. This paper will discuss the current SEV ECLSS design, any work contributed toward the development of the ECLSS design, and the plan to advance the ECLSS design based on the SEV vehicle and system needs.

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.

Applying Evolutionary Prototyping In Developing LMIS: A Spatial Web-Based System For Land Management

NASA Astrophysics Data System (ADS)

Agustiono, W.

2018-01-01

Software development project is a difficult task. Especially for software designed to comply with regulations that are constantly being introduced or changed, it is almost impossible to make just one change during the development process. Even if it is possible, nonetheless, the developers may take bulk of works to fix the design to meet specified needs. This iterative work also means that it takes additional time and potentially leads to failing to meet the original schedule and budget. In such inevitable changes, it is essential for developers to carefully consider and use an appropriate method which will help them carry out software project development. This research aims to examine the implementation of a software development method called evolutionary prototyping for developing software for complying regulation. It investigates the development of Land Management Information System (pseudonym), initiated by the Australian government, for use by farmers to meet regulatory demand requested by Soil and Land Conservation Act. By doing so, it sought to provide understanding the efficacy of evolutionary prototyping in helping developers address frequent changing requirements and iterative works but still within schedule. The findings also offer useful practical insights for other developers who seek to build similar regulatory compliance software.

Conceptual spacecraft systems design and synthesis

NASA Technical Reports Server (NTRS)

Wright, R. L.; Deryder, D. D.; Ferebee, M. J., Jr.

1984-01-01

An interactive systems design and synthesis is performed on future spacecraft concepts using the Interactive Design and Evaluation of Advanced Systems (IDEAS) computer-aided design and analysis system. The capabilities and advantages of the systems-oriented interactive computer-aided design and analysis system are described. The synthesis of both large antenna and space station concepts, and space station evolutionary growth designs is demonstrated. The IDEAS program provides the user with both an interactive graphics and an interactive computing capability which consists of over 40 multidisciplinary synthesis and analysis modules. Thus, the user can create, analyze, and conduct parametric studies and modify earth-orbiting spacecraft designs (space stations, large antennas or platforms, and technologically advanced spacecraft) at an interactive terminal with relative ease. The IDEAS approach is useful during the conceptual design phase of advanced space missions when a multiplicity of parameters and concepts must be analyzed and evaluated in a cost-effective and timely manner.

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

Different Evolutionary Modifications as a Guide to Rewire Two-Component Systems

PubMed Central

Krueger, Beate; Friedrich, Torben; Förster, Frank; Bernhardt, Jörg; Gross, Roy; Dandekar, Thomas

2012-01-01

Two-component systems (TCS) are short signalling pathways generally occurring in prokaryotes. They frequently regulate prokaryotic stimulus responses and thus are also of interest for engineering in biotechnology and synthetic biology. The aim of this study is to better understand and describe rewiring of TCS while investigating different evolutionary scenarios. Based on large-scale screens of TCS in different organisms, this study gives detailed data, concrete alignments, and structure analysis on three general modification scenarios, where TCS were rewired for new responses and functions: (i) exchanges in the sequence within single TCS domains, (ii) exchange of whole TCS domains; (iii) addition of new components modulating TCS function. As a result, the replacement of stimulus and promotor cassettes to rewire TCS is well defined exploiting the alignments given here. The diverged TCS examples are non-trivial and the design is challenging. Designed connector proteins may also be useful to modify TCS in selected cases. PMID:22586357

Evolutionary Design of Controlled Structures

NASA Technical Reports Server (NTRS)

Masters, Brett P.; Crawley, Edward F.

1997-01-01

Basic physical concepts of structural delay and transmissibility are provided for simple rod and beam structures. Investigations show the sensitivity of these concepts to differing controlled-structures variables, and to rational system modeling effects. An evolutionary controls/structures design method is developed. The basis of the method is an accurate model formulation for dynamic compensator optimization and Genetic Algorithm based updating of sensor/actuator placement and structural attributes. One and three dimensional examples from the literature are used to validate the method. Frequency domain interpretation of these controlled structure systems provide physical insight as to how the objective is optimized and consequently what is important in the objective. Several disturbance rejection type controls-structures systems are optimized for a stellar interferometer spacecraft application. The interferometric designs include closed loop tracking optics. Designs are generated for differing structural aspect ratios, differing disturbance attributes, and differing sensor selections. Physical limitations in achieving performance are given in terms of average system transfer function gains and system phase loss. A spacecraft-like optical interferometry system is investigated experimentally over several different optimized controlled structures configurations. Configurations represent common and not-so-common approaches to mitigating pathlength errors induced by disturbances of two different spectra. Results show that an optimized controlled structure for low frequency broadband disturbances achieves modest performance gains over a mass equivalent regular structure, while an optimized structure for high frequency narrow band disturbances is four times better in terms of root-mean-square pathlength. These results are predictable given the nature of the physical system and the optimization design variables. Fundamental limits on controlled performance are discussed based on the measured and fit average system transfer function gains and system phase loss.

Gramene database: navigating plant comparative genomics resources

USDA-ARS?s Scientific Manuscript database

Gramene (http://www.gramene.org) is an online, open source, curated resource for plant comparative genomics and pathway analysis designed to support researchers working in plant genomics, breeding, evolutionary biology, system biology, and metabolic engineering. It exploits phylogenetic relationship...

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.

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.

Generative Representations for the Automated Design of Modular Physical Robots

NASA Technical Reports Server (NTRS)

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

2003-01-01

We will begin with a brief background of evolutionary robotics and related work, and demonstrate the scaling problem with our own prior results. Next we propose the use of an evolved generative representation as opposed to a non-generative representation. We describe this representation in detail as well as the evolutionary process that uses it. We then compare progress of evolved robots with and without the use of the grammar, and quantify the obtained advantage. Working two- dimensional and three-dimensional physical robots produced by the system are shown.

Design trends for Army/Air Force airplanes in the United States

NASA Technical Reports Server (NTRS)

Spearman, M. Leroy

1990-01-01

Some design trends in Army/Air Force airplane systems in the U.S. are traced from the pre-World War 2 era to the present time. Various types of aircraft systems are reviewed with a view toward noting design features that were used. Some observations concerning the design trends indicate that some may be driven by advanced technology and some by a need for new mission requirements. In addition, it is noted that some design trends are evolutionary and result in an extension of service life or utility of existing systems. In other cases the design trends may be more revolutionary with the intent of creating a system with a new capability. Some examples are included of designs that did not proceed to production for reasons that sometimes were technical and sometimes were not.

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.

Interactive systems design and synthesis of future spacecraft concepts

NASA Technical Reports Server (NTRS)

Wright, R. L.; Deryder, D. D.; Ferebee, M. J., Jr.

1984-01-01

An interactive systems design and synthesis is performed on future spacecraft concepts using the Interactive Design and Evaluation of Advanced spacecraft (IDEAS) computer-aided design and analysis system. The capabilities and advantages of the systems-oriented interactive computer-aided design and analysis system are described. The synthesis of both large antenna and space station concepts, and space station evolutionary growth is demonstrated. The IDEAS program provides the user with both an interactive graphics and an interactive computing capability which consists of over 40 multidisciplinary synthesis and analysis modules. Thus, the user can create, analyze and conduct parametric studies and modify Earth-orbiting spacecraft designs (space stations, large antennas or platforms, and technologically advanced spacecraft) at an interactive terminal with relative ease. The IDEAS approach is useful during the conceptual design phase of advanced space missions when a multiplicity of parameters and concepts must be analyzed and evaluated in a cost-effective and timely manner.

Generative Representations for Computer-Automated Design Systems

NASA Technical Reports Server (NTRS)

Hornby, Gregory S.

2004-01-01

With the increasing computational power of Computers, software design systems are progressing from being tools for architects and designers to express their ideas to tools capable of creating designs under human guidance. One of the main limitations for these computer-automated design programs is the representation with which they encode designs. If the representation cannot encode a certain design, then the design program cannot produce it. Similarly, a poor representation makes some types of designs extremely unlikely to be created. Here we define generative representations as those representations which can create and reuse organizational units within a design and argue that reuse is necessary for design systems to scale to more complex and interesting designs. To support our argument we describe GENRE, an evolutionary design program that uses both a generative and a non-generative representation, and compare the results of evolving designs with both types of representations.

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.

Optimal Solution for an Engineering Applications Using Modified Artificial Immune System

NASA Astrophysics Data System (ADS)

Padmanabhan, S.; Chandrasekaran, M.; Ganesan, S.; patan, Mahamed Naveed Khan; Navakanth, Polina

2017-03-01

An Engineering optimization leads a essential role in several engineering application areas like process design, product design, re-engineering and new product development, etc. In engineering, an awfully best answer is achieved by comparison to some completely different solutions by utilization previous downside information. An optimization algorithms provide systematic associate degreed economical ways that within which of constructing and comparison new design solutions so on understand at best vogue, thus on best solution efficiency and acquire the foremost wonderful design impact. In this paper, a new evolutionary based Modified Artificial Immune System (MAIS) algorithm used to optimize an engineering application of gear drive design. The results are compared with existing design.

The Design and Transformation of Biofundamentals: A Nonsurvey Introductory Evolutionary and Molecular Biology Course

PubMed Central

Klymkowsky, Michael W.; Rentsch, Jeremy D.; Begovic, Emina; Cooper, Melanie M.

2016-01-01

Many introductory biology courses amount to superficial surveys of disconnected topics. Often, foundational observations and the concepts derived from them and students’ ability to use these ideas appropriately are overlooked, leading to unrealistic expectations and unrecognized learning obstacles. The result can be a focus on memorization at the expense of the development of a meaningful framework within which to consider biological phenomena. About a decade ago, we began a reconsideration of what an introductory course should present to students and the skills they need to master. The original Web-based course’s design presaged many of the recommendations of the Vision and Change report; in particular, a focus on social evolutionary mechanisms, stochastic (evolutionary and molecular) processes, and core ideas (cellular continuity, evolutionary homology, molecular interactions, coupled chemical reactions, and molecular machines). Inspired by insights from the Chemistry, Life, the Universe & Everything general chemistry project, we transformed the original Web version into a (freely available) book with a more unified narrative flow and a set of formative assessments delivered through the beSocratic system. We outline how student responses to course materials are guiding future course modifications, in particular a more concerted effort at helping students to construct logical, empirically based arguments, explanations, and models. PMID:27909020

Organically Grown Architectures: Creating Decentralized, Autonomous Systems by Embryomorphic Engineering

NASA Astrophysics Data System (ADS)

Doursat, René

Exploding growth growth in computational systems forces us to gradually replace rigid design and control with decentralization and autonomy. Information technologies will progress, instead, by"meta-designing" mechanisms of system self-assembly, self-regulation and evolution. Nature offers a great variety of efficient complex systems, in which numerous small elements form large-scale, adaptive patterns. The new engineering challenge is to recreate this self-organization and let it freely generate innovative designs under guidance. This article presents an original model of artificial system growth inspired by embryogenesis. A virtual organism is a lattice of cells that proliferate, migrate and self-pattern into differentiated domains. Each cell's fate is controlled by an internal gene regulatory network network. Embryomorphic engineering emphasizes hyperdistributed architectures, and their development as a prerequisite of evolutionary design.

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.

The Evolutionary Development of CAI Hardware.

ERIC Educational Resources Information Center

Stifle, John E.

After six years of research in computer assisted instruction (CAI) using PLATO III, a decision was made at the University of Illinois to develop a larger system as a national CAI resource. This document describes the design specifications and problems in the development of PLATO IV, a system which is capable of accomodating up to 4,000 terminals…

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

Integrating Evolutionary Game Theory into Mechanistic Genotype-Phenotype Mapping.

PubMed

Zhu, Xuli; Jiang, Libo; Ye, Meixia; Sun, Lidan; Gragnoli, Claudia; Wu, Rongling

2016-05-01

Natural selection has shaped the evolution of organisms toward optimizing their structural and functional design. However, how this universal principle can enhance genotype-phenotype mapping of quantitative traits has remained unexplored. Here we show that the integration of this principle and functional mapping through evolutionary game theory gains new insight into the genetic architecture of complex traits. By viewing phenotype formation as an evolutionary system, we formulate mathematical equations to model the ecological mechanisms that drive the interaction and coordination of its constituent components toward population dynamics and stability. Functional mapping provides a procedure for estimating the genetic parameters that specify the dynamic relationship of competition and cooperation and predicting how genes mediate the evolution of this relationship during trait formation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Towards Evolving Electronic Circuits for Autonomous Space Applications

NASA Technical Reports Server (NTRS)

Lohn, Jason D.; Haith, Gary L.; Colombano, Silvano P.; Stassinopoulos, Dimitris

2000-01-01

The relatively new field of Evolvable Hardware studies how simulated evolution can reconfigure, adapt, and design hardware structures in an automated manner. Space applications, especially those requiring autonomy, are potential beneficiaries of evolvable hardware. For example, robotic drilling from a mobile platform requires high-bandwidth controller circuits that are difficult to design. In this paper, we present automated design techniques based on evolutionary search that could potentially be used in such applications. First, we present a method of automatically generating analog circuit designs using evolutionary search and a circuit construction language. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. Using a parallel genetic algorithm, we present experimental results for five design tasks. Second, we investigate the use of coevolution in automated circuit design. We examine fitness evaluation by comparing the effectiveness of four fitness schedules. The results indicate that solution quality is highest with static and co-evolving fitness schedules as compared to the other two dynamic schedules. We discuss these results and offer two possible explanations for the observed behavior: retention of useful information, and alignment of problem difficulty with circuit proficiency.

Modular space station phase B extension preliminary system design. Volume 5: configuration analyses

NASA Technical Reports Server (NTRS)

Stefan, A. J.; Goble, G. J.

1972-01-01

The initial and growth modular space station configurations are described, and the evolutionary steps arriving at the final configuration are outlined. Supporting tradeoff studies and analyses such as stress, radiation dosage, and micrometeoroid and thermal protection are included.

Multidisciplinary Multiobjective Optimal Design for Turbomachinery Using Evolutionary Algorithm

NASA Technical Reports Server (NTRS)

2005-01-01

This report summarizes Dr. Lian s efforts toward developing a robust and efficient tool for multidisciplinary and multi-objective optimal design for turbomachinery using evolutionary algorithms. This work consisted of two stages. The first stage (from July 2003 to June 2004) Dr. Lian focused on building essential capabilities required for the project. More specifically, Dr. Lian worked on two subjects: an enhanced genetic algorithm (GA) and an integrated optimization system with a GA and a surrogate model. The second stage (from July 2004 to February 2005) Dr. Lian formulated aerodynamic optimization and structural optimization into a multi-objective optimization problem and performed multidisciplinary and multi-objective optimizations on a transonic compressor blade based on the proposed model. Dr. Lian s numerical results showed that the proposed approach can effectively reduce the blade weight and increase the stage pressure ratio in an efficient manner. In addition, the new design was structurally safer than the original design. Five conference papers and three journal papers were published on this topic by Dr. Lian.

The Langley Research Center CSI phase-0 evolutionary model testbed-design and experimental results

NASA Technical Reports Server (NTRS)

Belvin, W. K.; Horta, Lucas G.; Elliott, K. B.

1991-01-01

A testbed for the development of Controls Structures Interaction (CSI) technology is described. The design philosophy, capabilities, and early experimental results are presented to introduce some of the ongoing CSI research at NASA-Langley. The testbed, referred to as the Phase 0 version of the CSI Evolutionary model (CEM), is the first stage of model complexity designed to show the benefits of CSI technology and to identify weaknesses in current capabilities. Early closed loop test results have shown non-model based controllers can provide an order of magnitude increase in damping in the first few flexible vibration modes. Model based controllers for higher performance will need to be robust to model uncertainty as verified by System ID tests. Data are presented that show finite element model predictions of frequency differ from those obtained from tests. Plans are also presented for evolution of the CEM to study integrated controller and structure design as well as multiple payload dynamics.

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.

Participatory design of a collaborative clinical trial protocol writing system.

PubMed

Weng, Chunhua; McDonald, David W; Sparks, Dana; McCoy, Jason; Gennari, John H

2007-06-01

To explore concrete approaches to socio-technical design of collaborative healthcare information systems and to design a groupware technology for collaborative clinical trial protocol writing. We conducted "quick and dirty ethnography" through semi-structured interviews, observational studies, and work artifacts analysis to understand the group work for protocol development. We used participatory design through evolutionary prototyping to explore the feature space of a collaborative writing system. Our design strategies include role-based user advocacy, formative evaluation, and change management. Quick and dirty ethnography helped us efficiently understand relevant work practice, and participatory design helped us engage users into design and bring out their tacit work knowledge. Our approach that intertwined both techniques helped achieve a "work-informed and user-oriented" design. This research leads to a collaborative writing system that supports in situ communication, group awareness, and effective work progress tracking. The usability evaluation results have been satisfactory. The system design is being transferred to an organizational tool for daily use.

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.

Using concepts from biology to improve problem-solving methods

NASA Astrophysics Data System (ADS)

Goodman, Erik D.; Rothwell, Edward J.; Averill, Ronald C.

2011-06-01

Observing nature has been a cornerstone of engineering design. Today, engineers look not only at finished products, but imitate the evolutionary process by which highly optimized artifacts have appeared in nature. Evolutionary computation began by capturing only the simplest ideas of evolution, but today, researchers study natural evolution and incorporate an increasing number of concepts in order to evolve solutions to complex engineering problems. At the new BEACON Center for the Study of Evolution in Action, studies in the lab and field and in silico are laying the groundwork for new tools for evolutionary engineering design. This paper, which accompanies a keynote address, describes various steps in development and application of evolutionary computation, particularly as regards sensor design, and sets the stage for future advances.

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

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

NASA Astrophysics Data System (ADS)

Wagh, Aditi

Two strands of work motivate the three studies in this dissertation. Evolutionary change can be viewed as a computational complex system in which a small set of rules operating at the individual level result in different population level outcomes under different conditions. Extensive research has documented students' difficulties with learning about evolutionary change (Rosengren et al., 2012), particularly in terms of levels slippage (Wilensky & Resnick, 1999). Second, though building and using computational models is becoming increasingly common in K-12 science education, we know little about how these two modalities compare. This dissertation adopts agent-based modeling as a representational system to compare these modalities in the conceptual context of micro-evolutionary processes. Drawing on interviews, Study 1 examines middle-school students' productive ways of reasoning about micro-evolutionary processes to find that the specific framing of traits plays a key role in whether slippage explanations are cued. Study 2, which was conducted in 2 schools with about 150 students, forms the crux of the dissertation. It compares learning processes and outcomes when students build their own models or explore a pre-built model. Analysis of Camtasia videos of student pairs reveals that builders' and explorers' ways of accessing rules, and sense-making of observed trends are of a different character. Builders notice rules through available blocks-based primitives, often bypassing their enactment while explorers attend to rules primarily through the enactment. Moreover, builders' sense-making of observed trends is more rule-driven while explorers' is more enactment-driven. Pre and posttests reveal that builders manifest a greater facility with accessing rules, providing explanations manifesting targeted assembly. Explorers use rules to construct explanations manifesting non-targeted assembly. Interviews reveal varying degrees of shifts away from slippage in both modalities, with students who built models not incorporating slippage explanations in responses. Study 3 compares these modalities with a control using traditional activities. Pre and posttests reveal that the two modalities manifested greater facility with accessing and assembling rules than the control. The dissertation offers implications for the design of learning environments for evolutionary change, design of the two modalities based on their strengths and weaknesses, and teacher training for the same.

Modeling evolution of crosstalk in noisy signal transduction networks

NASA Astrophysics Data System (ADS)

Tareen, Ammar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

2018-02-01

Signal transduction networks can form highly interconnected systems within cells due to crosstalk between constituent pathways. To better understand the evolutionary design principles underlying such networks, we study the evolution of crosstalk for two parallel signaling pathways that arise via gene duplication. We use a sequence-based evolutionary algorithm and evolve the network based on two physically motivated fitness functions related to information transmission. We find that one fitness function leads to a high degree of crosstalk while the other leads to pathway specificity. Our results offer insights on the relationship between network architecture and information transmission for noisy biomolecular networks.

Navigating the Perfect Storm: Research Strategies for Socialecological Systems in a Rapidly Evolving World

NASA Astrophysics Data System (ADS)

Dearing, John A.; Bullock, Seth; Costanza, Robert; Dawson, Terry P.; Edwards, Mary E.; Poppy, Guy M.; Smith, Graham M.

2012-04-01

The `Perfect Storm' metaphor describes a combination of events that causes a surprising or dramatic impact. It lends an evolutionary perspective to how social-ecological interactions change. Thus, we argue that an improved understanding of how social-ecological systems have evolved up to the present is necessary for the modelling, understanding and anticipation of current and future social-ecological systems. Here we consider the implications of an evolutionary perspective for designing research approaches. One desirable approach is the creation of multi-decadal records produced by integrating palaeoenvironmental, instrument and documentary sources at multiple spatial scales. We also consider the potential for improved analytical and modelling approaches by developing system dynamical, cellular and agent-based models, observing complex behaviour in social-ecological systems against which to test systems dynamical theory, and drawing better lessons from history. Alongside these is the need to find more appropriate ways to communicate complex systems, risk and uncertainty to the public and to policy-makers.

Evolutionary Design of a Robotic Material Defect Detection System

NASA Technical Reports Server (NTRS)

Ballard, Gary; Howsman, Tom; Craft, Mike; ONeil, Daniel; Steincamp, Jim; Howell, Joe T. (Technical Monitor)

2002-01-01

During the post-flight inspection of SSME engines, several inaccessible regions must be disassembled to inspect for defects such as cracks, scratches, gouges, etc. An improvement to the inspection process would be the design and development of very small robots capable of penetrating these inaccessible regions and detecting the defects. The goal of this research was to utilize an evolutionary design approach for the robotic detection of these types of defects. A simulation and visualization tool was developed prior to receiving the hardware as a development test bed. A small, commercial off-the-shelf (COTS) robot was selected from several candidates as the proof of concept robot. The basic approach to detect the defects was to utilize Cadmium Sulfide (CdS) sensors to detect changes in contrast of an illuminated surface. A neural network, optimally designed utilizing a genetic algorithm, was employed to detect the presence of the defects (cracks). By utilization of the COTS robot and US sensors, the research successfully demonstrated that an evolutionarily designed neural network can detect the presence of surface defects.

Preliminary design of mesoscale turbocompressor and rotordynamics tests of rotor bearing system

NASA Astrophysics Data System (ADS)

Hossain, Md Saddam

2011-12-01

A mesoscale turbocompressor spinning above 500,000 RPM is evolutionary technology for micro turbochargers, turbo blowers, turbo compressors, micro-gas turbines, auxiliary power units, etc for automotive, aerospace, and fuel cell industries. Objectives of this work are: (1) to evaluate different air foil bearings designed for the intended applications, and (2) to design & perform CFD analysis of a micro-compressor. CFD analysis of shrouded 3-D micro compressor was conducted using Ansys Bladegen as blade generation tool, ICEM CFD as mesh generation tool, and CFX as main solver for different design and off design cases and also for different number of blades. Comprehensive experimental facilities for testing the turbocompressor system have been also designed and proposed for future work.

Diversification and enrichment of clinical biomaterials inspired by Darwinian evolution.

PubMed

Green, D W; Watson, G S; Watson, J A; Lee, D-J; Lee, J-M; Jung, H-S

2016-09-15

Regenerative medicine and biomaterials design are driven by biomimicry. There is the essential requirement to emulate human cell, tissue, organ and physiological complexity to ensure long-lasting clinical success. Biomimicry projects for biomaterials innovation can be re-invigorated with evolutionary insights and perspectives, since Darwinian evolution is the original dynamic process for biological organisation and complexity. Many existing human inspired regenerative biomaterials (defined as a nature generated, nature derived and nature mimicking structure, produced within a biological system, which can deputise for, or replace human tissues for which it closely matches) are without important elements of biological complexity such as, hierarchy and autonomous actions. It is possible to engineer these essential elements into clinical biomaterials via bioinspired implementation of concepts, processes and mechanisms played out during Darwinian evolution; mechanisms such as, directed, computational, accelerated evolutions and artificial selection contrived in the laboratory. These dynamos for innovation can be used during biomaterials fabrication, but also to choose optimal designs in the regeneration process. Further evolutionary information can help at the design stage; gleaned from the historical evolution of material adaptations compared across phylogenies to changes in their environment and habitats. Taken together, harnessing evolutionary mechanisms and evolutionary pathways, leading to ideal adaptations, will eventually provide a new class of Darwinian and evolutionary biomaterials. This will provide bioengineers with a more diversified and more efficient innovation tool for biomaterial design, synthesis and function than currently achieved with synthetic materials chemistry programmes and rational based materials design approach, which require reasoned logic. It will also inject further creativity, diversity and richness into the biomedical technologies that we make. All of which are based on biological principles. Such evolution-inspired biomaterials have the potential to generate innovative solutions, which match with existing bioengineering problems, in vital areas of clinical materials translation that include tissue engineering, gene delivery, drug delivery, immunity modulation, and scar-less wound healing. Evolution by natural selection is a powerful generator of innovations in molecular, materials and structures. Man has influenced evolution for thousands of years, to create new breeds of farm animals and crop plants, but now molecular and materials can be molded in the same way. Biological molecules and simple structures can be evolved, literally in the laboratory. Furthermore, they are re-designed via lessons learnt from evolutionary history. Through a 3-step process to (1) create variants in material building blocks, (2) screen the variants with beneficial traits/properties and (3) select and support their self-assembly into usable materials, improvements in design and performance can emerge. By introducing biological molecules and small organisms into this process, it is possible to make increasingly diversified, sophisticated and clinically relevant materials for multiple roles in biomedicine. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Circuit Design Optimization Using Genetic Algorithm with Parameterized Uniform Crossover

NASA Astrophysics Data System (ADS)

Bao, Zhiguo; Watanabe, Takahiro

Evolvable hardware (EHW) is a new research field about the use of Evolutionary Algorithms (EAs) to construct electronic systems. EHW refers in a narrow sense to use evolutionary mechanisms as the algorithmic drivers for system design, while in a general sense to the capability of the hardware system to develop and to improve itself. Genetic Algorithm (GA) is one of typical EAs. We propose optimal circuit design by using GA with parameterized uniform crossover (GApuc) and with fitness function composed of circuit complexity, power, and signal delay. Parameterized uniform crossover is much more likely to distribute its disruptive trials in an unbiased manner over larger portions of the space, then it has more exploratory power than one and two-point crossover, so we have more chances of finding better solutions. Its effectiveness is shown by experiments. From the results, we can see that the best elite fitness, the average value of fitness of the correct circuits and the number of the correct circuits of GApuc are better than that of GA with one-point crossover or two-point crossover. The best case of optimal circuits generated by GApuc is 10.18% and 6.08% better in evaluating value than that by GA with one-point crossover and two-point crossover, respectively.

A master-slave parallel hybrid multi-objective evolutionary algorithm for groundwater remediation design under general hydrogeological conditions

NASA Astrophysics Data System (ADS)

Wu, J.; Yang, Y.; Luo, Q.; Wu, J.

2012-12-01

This study presents a new hybrid multi-objective evolutionary algorithm, the niched Pareto tabu search combined with a genetic algorithm (NPTSGA), whereby the global search ability of niched Pareto tabu search (NPTS) is improved by the diversification of candidate solutions arose from the evolving nondominated sorting genetic algorithm II (NSGA-II) population. Also, the NPTSGA coupled with the commonly used groundwater flow and transport codes, MODFLOW and MT3DMS, is developed for multi-objective optimal design of groundwater remediation systems. The proposed methodology is then applied to a large-scale field groundwater remediation system for cleanup of large trichloroethylene (TCE) plume at the Massachusetts Military Reservation (MMR) in Cape Cod, Massachusetts. Furthermore, a master-slave (MS) parallelization scheme based on the Message Passing Interface (MPI) is incorporated into the NPTSGA to implement objective function evaluations in distributed processor environment, which can greatly improve the efficiency of the NPTSGA in finding Pareto-optimal solutions to the real-world application. This study shows that the MS parallel NPTSGA in comparison with the original NPTS and NSGA-II can balance the tradeoff between diversity and optimality of solutions during the search process and is an efficient and effective tool for optimizing the multi-objective design of groundwater remediation systems under complicated hydrogeologic conditions.

The Systems Autonomy Demonstration Project - Catalyst for Space Station advanced automation

NASA Technical Reports Server (NTRS)

Healey, Kathleen J.

1988-01-01

The Systems Autonomy Demonstration Project (SADP) was initiated by NASA to address the advanced automation needs for the Space Station program. The application of advanced automation to the Space Station's operations management system (OMS) is discussed. The SADP's future goals and objectives are discussed with respect to OMS functional requirements, design, and desired evolutionary capabilities. Major technical challenges facing the designers, developers, and users of the OMS are identified in order to guide the definition of objectives, plans, and scenarios for future SADP demonstrations, and to focus the efforts on the supporting research.

Pathways to cognitive design.

PubMed

Wertz, Annie E; Moya, Cristina

2018-05-30

Despite a shared recognition that the design of the human mind and the design of human culture are tightly linked, researchers in the evolutionary social sciences tend to specialize in understanding one at the expense of the other. The disciplinary boundaries roughly correspond to research traditions that focus more on natural selection and those that focus more on cultural evolution. In this paper, we articulate how two research traditions within the evolutionary social sciences-evolutionary psychology and cultural evolution-approach the study of design. We focus our analysis on the design of cognitive mechanisms that are the result of the interplay of genetic and cultural evolution. We aim to show how the approaches of these two research traditions can complement each other, and provide a framework for developing a wider range of testable hypotheses about cognitive design. To do so, we provide concrete illustrations of how this integrated approach can be used to interrogate cognitive design using examples from our own work on plant and symbolic group boundary cognition. We hope this recognition of different pathways to design will broaden the hypothesis space in the evolutionary social sciences and encourage methodological pluralism in the investigation of the mind. Copyright © 2018 Elsevier B.V. All rights reserved.

Propulsion requirements for reusable single-stage-to-orbit rocket vehicles

NASA Astrophysics Data System (ADS)

Stanley, Douglas O.; Engelund, Walter C.; Lepsch, Roger

1994-05-01

The conceptual design of a single-stage-to-orbit (SSTO) vehicle using a wide variety of evolutionary technologies has recently been completed as a part of NASA's Advanced Manned Launch System (AMLS) study. The employment of new propulsion system technologies is critical to the design of a reasonably sized, operationally efficient SSTO vehicle. This paper presents the propulsion system requirements identified for this near-term AMLS SSTO vehicle. Sensitivities of the vehicle to changes in specific impulse and sea-level thrust-to-weight ratio are examined. The results of a variety of vehicle/propulsion system trades performed on the near-term AMLS SSTO vehicle are also presented.

Evolutionary and biological metaphors for engineering design

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

Jakiela, M.

1994-12-31

Since computing became generally available, there has been strong interest in using computers to assist and automate engineering design processes. Specifically, for design optimization and automation, nonlinear programming and artificial intelligence techniques have been extensively studied. New computational techniques, based upon the natural processes of evolution, adaptation, and learing, are showing promise because of their generality and robustness. This presentation will describe the use of two such techniques, genetic algorithms and classifier systems, for a variety of engineering design problems. Structural topology optimization, meshing, and general engineering optimization are shown as example applications.

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…

Representing and Reasoning With Design Records for Evolutionary Systems

DTIC Science & Technology

2002-08-01

Product Innovation Management , (15...43-59, 1996. Mullins and Sutherland, "New Product Development in Rapidly changing Markets: An exploratory Study", Journal of Product Innovation Management , (15...Really New versus Incremental Products", Journal of Product Innovation Management , 15 124-135, 1998. Techart, "Digital prepress book for

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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.

Optimal active vibration absorber: Design and experimental results

NASA Technical Reports Server (NTRS)

Lee-Glauser, Gina; Juang, Jer-Nan; Sulla, Jeffrey L.

1992-01-01

An optimal active vibration absorber can provide guaranteed closed-loop stability and control for large flexible space structures with collocated sensors/actuators. The active vibration absorber is a second-order dynamic system which is designed to suppress any unwanted structural vibration. This can be designed with minimum knowledge of the controlled system. Two methods for optimizing the active vibration absorber parameters are illustrated: minimum resonant amplitude and frequency matched active controllers. The Controls-Structures Interaction Phase-1 Evolutionary Model at NASA LaRC is used to demonstrate the effectiveness of the active vibration absorber for vibration suppression. Performance is compared numerically and experimentally using acceleration feedback.

Linking species habitat and past palaeoclimatic events to evolution of the teleost innate immune system.

PubMed

Solbakken, Monica Hongrø; Voje, Kjetil Lysne; Jakobsen, Kjetill Sigurd; Jentoft, Sissel

2017-04-26

Host-intrinsic factors as well as environmental changes are known to be strong evolutionary drivers defining the genetic foundation of immunity. Using a novel set of teleost genomes and a time-calibrated phylogeny, we here investigate the family of Toll-like receptor ( TLR ) genes and address the underlying evolutionary processes shaping the diversity of the first-line defence. Our findings reveal remarkable flexibility within the evolutionary design of teleost innate immunity characterized by prominent TLR gene losses and expansions. In the order of Gadiformes, expansions correlate with the loss of major histocompatibility complex class II ( MHCII ) and diversifying selection analyses support that this has fostered new immunological innovations in TLR s within this lineage. In teleosts overall, TLRs expansions correlate with species latitudinal distributions and maximum depth. By contrast, lineage-specific gene losses overlap with well-described changes in palaeoclimate (global ocean anoxia) and past Atlantic Ocean geography. In conclusion, we suggest that the evolvability of the teleost immune system has most likely played a prominent role in the survival and successful radiation of this lineage. © 2017 The Authors.

Toward A New Evolutionary Synthesis.

PubMed

Flannery, Michael A

2017-01-01

This essay responds to Peter T. Saunders's call to go Beyond the neo-Darwinist Paradigm. While there is much to commend in his analysis, especially his suggestion that the extended evolutionary synthesis (EES) may not go far enough, he leaves the question of whether this should involve mere revision or total replacement open. A historiographical review reveals significant problems stemming from certain positivist assumptions and commitments within neo-Darwinian orthodoxy and the EES over and above any scientific considerations. As such, mere tweaking of the existing paradigm or its extension will do little to remedy the intellectual prejudices currently plaguing it. A complete overhaul is suggested by applying the López Ontological Demarcation Design (LODD) principle with biology in a multidisciplinary, non-reductionist philosophical framework. Building on the concept of Organismic-Systems Biology (OSB), a component of General Systems Theory (GTS) associated with polymathic biologist Ludwig von Bertalanffy (1901-1972), and cosmic evolution (CE) proposed by UCLA philosopher John Elof Boodin (1869-1950), the outline of a new evolutionary synthesis is offered as a prolegomenon to further study and evaluation. Copyright: © 2016 by Fabrizio Serra editore, Pisa · Roma.

Design for robustness of unique, multi-component engineering systems

NASA Astrophysics Data System (ADS)

Shelton, Kenneth A.

2007-12-01

The purpose of this research is to advance the science of conceptual designing for robustness in unique, multi-component engineering systems. Robustness is herein defined as the ability of an engineering system to operate within a desired performance range even if the actual configuration has differences from specifications within specified tolerances. These differences are caused by three sources, namely manufacturing errors, system degradation (operational wear and tear), and parts availability. Unique, multi-component engineering systems are defined as systems produced in unique or very small production numbers. They typically have design and manufacturing costs on the order of billions of dollars, and have multiple, competing performance objectives. Design time for these systems must be minimized due to competition, high manpower costs, long manufacturing times, technology obsolescence, and limited available manpower expertise. Most importantly, design mistakes cannot be easily corrected after the systems are operational. For all these reasons, robustness of these systems is absolutely critical. This research examines the space satellite industry in particular. Although inherent robustness assurance is absolutely critical, it is difficult to achieve in practice. The current state of the art for robustness in the industry is to overdesign components and subsystems with redundancy and margin. The shortfall is that it is not known if the added margins were either necessary or sufficient given the risk management preferences of the designer or engineering system customer. To address this shortcoming, new assessment criteria to evaluate robustness in design concepts have been developed. The criteria are comprised of the "Value Distance", addressing manufacturing errors and system degradation, and "Component Distance", addressing parts availability. They are based on an evolutionary computation format that uses a string of alleles to describe the components in the design concept. These allele values are unitless themselves, but map to both configuration descriptions and attribute values. The Value Distance and Component Distance are metrics that measure the relative differences between two design concepts using the allele values, and all differences in a population of design concepts are calculated relative to a reference design, called the "base design". The base design is the top-ranked member of the population in weighted terms of robustness and performance. Robustness is determined based on the change in multi-objective performance as Value Distance and Component Distance (and thus differences in design) increases. It is assessed as acceptable if differences in design configurations up to specified tolerances result in performance changes that remain within a specified performance range. The design configuration difference tolerances and performance range together define the designer's risk management preferences for the final design concepts. Additionally, a complementary visualization capability was developed, called the "Design Solution Topography". This concept allows the visualization of a population of design concepts, and is a 3-axis plot where each point represents an entire design concept. The axes are the Value Distance, Component Distance and Performance Objective. The key benefit of the Design Solution Topography is that it allows the designer to visually identify and interpret the overall robustness of the current population of design concepts for a particular performance objective. In a multi-objective problem, each performance objective has its own Design Solution Topography view. These new concepts are implemented in an evolutionary computation-based conceptual designing method called the "Design for Robustness Method" that produces robust design concepts. The design procedures associated with this method enable designers to evaluate and ensure robustness in selected designs that also perform within a desired performance range. The method uses an evolutionary computation-based procedure to generate populations of large numbers of alternative design concepts, which are assessed for robustness using the Value Distance, Component Distance and Design Solution Topography procedures. The Design for Robustness Method provides a working conceptual designing structure in which to implement and gain the benefits of these new concepts. In the included experiments, the method was used on several mathematical examples to demonstrate feasibility, which showed favorable results as compared to existing known methods. Furthermore, it was tested on a real-world satellite conceptual designing problem to illustrate the applicability and benefits to industry. Risk management insights were demonstrated for the robustness-related issues of manufacturing errors, operational degradation, parts availability, and impacts based on selections of particular types of components.

Deep Space Mission Applications for NEXT: NASA's Evolutionary Xenon Thruster

NASA Technical Reports Server (NTRS)

Oh, David; Benson, Scott; Witzberger, Kevin; Cupples, Michael

2004-01-01

NASA's Evolutionary Xenon Thruster (NEXT) is designed to address a need for advanced ion propulsion systems on certain future NASA deep space missions. This paper surveys seven potential missions that have been identified as being able to take advantage of the unique capabilities of NEXT. Two conceptual missions to Titan and Neptune are analyzed, and it is shown that ion thrusters could decrease launch mass and shorten trip time, to Titan compared to chemical propulsion. A potential Mars Sample return mission is described, and compassion made between a chemical mission and a NEXT based mission. Four possible near term applications to New Frontiers and Discovery class missions are described, and comparisons are made to chemical systems or existing NSTAR ion propulsion system performance. The results show that NEXT has potential performance and cost benefits for missions in the Discovery, New Frontiers, and larger mission classes.

Maximizing ecological and evolutionary insight in bisulfite sequencing data sets

PubMed Central

Lea, Amanda J.; Vilgalys, Tauras P.; Durst, Paul A.P.; Tung, Jenny

2017-01-01

Preface Genome-scale bisulfite sequencing approaches have opened the door to ecological and evolutionary studies of DNA methylation in many organisms. These approaches can be powerful. However, they introduce new methodological and statistical considerations, some of which are particularly relevant to non-model systems. Here, we highlight how these considerations influence a study’s power to link methylation variation with a predictor variable of interest. Relative to current practice, we argue that sample sizes will need to increase to provide robust insights. We also provide recommendations for overcoming common challenges and an R Shiny app to aid in study design. PMID:29046582

Expanding Evolutionary Theory beyond Darwinism with Elaborating, Self-Organizing, and Fractionating Complex Evolutionary Systems

ERIC Educational Resources Information Center

Fichter, Lynn S.; Pyle, E. J.; Whitmeyer, S. J.

2010-01-01

Earth systems increase in complexity, diversity, and interconnectedness with time, driven by tectonic/solar energy that keeps the systems far from equilibrium. The evolution of Earth systems is facilitated by three evolutionary mechanisms: "elaboration," "fractionation," and "self-organization," that share…

A new bio-inspired, population-level approach to the socioeconomic evolution of dynamic spectrum access services

NASA Astrophysics Data System (ADS)

Horvath, Denis; Gazda, Juraj; Brutovsky, Branislav

Evolutionary species and quasispecies models provide the universal and flexible basis for a large-scale description of the dynamics of evolutionary systems, which can be built conceived as a constraint satisfaction dynamics. It represents a general framework to design and study many novel, technologically contemporary models and their variants. Here, we apply the classical quasispecies concept to model the emerging dynamic spectrum access (DSA) markets. The theory describes the mechanisms of mimetic transfer, competitive interactions between socioeconomic strata of the end-users, their perception of the utility and inter-operator switching in the variable technological environments of the operators offering the wireless spectrum services. The algorithmization and numerical modeling demonstrate the long-term evolutionary socioeconomic changes which reflect the end-user preferences and results of the majorization of their irrational decisions in the same manner as the prevailing tendencies which are embodied in the efficient market hypothesis.

Biological engineering applications of feedforward neural networks designed and parameterized by genetic algorithms.

PubMed

Ferentinos, Konstantinos P

2005-09-01

Two neural network (NN) applications in the field of biological engineering are developed, designed and parameterized by an evolutionary method based on the evolutionary process of genetic algorithms. The developed systems are a fault detection NN model and a predictive modeling NN system. An indirect or 'weak specification' representation was used for the encoding of NN topologies and training parameters into genes of the genetic algorithm (GA). Some a priori knowledge of the demands in network topology for specific application cases is required by this approach, so that the infinite search space of the problem is limited to some reasonable degree. Both one-hidden-layer and two-hidden-layer network architectures were explored by the GA. Except for the network architecture, each gene of the GA also encoded the type of activation functions in both hidden and output nodes of the NN and the type of minimization algorithm that was used by the backpropagation algorithm for the training of the NN. Both models achieved satisfactory performance, while the GA system proved to be a powerful tool that can successfully replace the problematic trial-and-error approach that is usually used for these tasks.

Biosequence Similarity Search on the Mercury System

PubMed Central

Krishnamurthy, Praveen; Buhler, Jeremy; Chamberlain, Roger; Franklin, Mark; Gyang, Kwame; Jacob, Arpith; Lancaster, Joseph

2007-01-01

Biosequence similarity search is an important application in modern molecular biology. Search algorithms aim to identify sets of sequences whose extensional similarity suggests a common evolutionary origin or function. The most widely used similarity search tool for biosequences is BLAST, a program designed to compare query sequences to a database. Here, we present the design of BLASTN, the version of BLAST that searches DNA sequences, on the Mercury system, an architecture that supports high-volume, high-throughput data movement off a data store and into reconfigurable hardware. An important component of application deployment on the Mercury system is the functional decomposition of the application onto both the reconfigurable hardware and the traditional processor. Both the Mercury BLASTN application design and its performance analysis are described. PMID:18846267

Climate change and evolutionary adaptation.

PubMed

Hoffmann, Ary A; Sgrò, Carla M

2011-02-24

Evolutionary adaptation can be rapid and potentially help species counter stressful conditions or realize ecological opportunities arising from climate change. The challenges are to understand when evolution will occur and to identify potential evolutionary winners as well as losers, such as species lacking adaptive capacity living near physiological limits. Evolutionary processes also need to be incorporated into management programmes designed to minimize biodiversity loss under rapid climate change. These challenges can be met through realistic models of evolutionary change linked to experimental data across a range of taxa.

A Bright Future for Evolutionary Methods in Drug Design.

PubMed

Le, Tu C; Winkler, David A

2015-08-01

Most medicinal chemists understand that chemical space is extremely large, essentially infinite. Although high-throughput experimental methods allow exploration of drug-like space more rapidly, they are still insufficient to fully exploit the opportunities that such large chemical space offers. Evolutionary methods can synergistically blend automated synthesis and characterization methods with computational design to identify promising regions of chemical space more efficiently. We describe how evolutionary methods are implemented, and provide examples of published drug development research in which these methods have generated molecules with increased efficacy. We anticipate that evolutionary methods will play an important role in future drug discovery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Effects of topology on network evolution

NASA Astrophysics Data System (ADS)

Oikonomou, Panos; Cluzel, Philippe

2006-08-01

The ubiquity of scale-free topology in nature raises the question of whether this particular network design confers an evolutionary advantage. A series of studies has identified key principles controlling the growth and the dynamics of scale-free networks. Here, we use neuron-based networks of boolean components as a framework for modelling a large class of dynamical behaviours in both natural and artificial systems. Applying a training algorithm, we characterize how networks with distinct topologies evolve towards a pre-established target function through a process of random mutations and selection. We find that homogeneous random networks and scale-free networks exhibit drastically different evolutionary paths. Whereas homogeneous random networks accumulate neutral mutations and evolve by sparse punctuated steps, scale-free networks evolve rapidly and continuously. Remarkably, this latter property is robust to variations of the degree exponent. In contrast, homogeneous random networks require a specific tuning of their connectivity to optimize their ability to evolve. These results highlight an organizing principle that governs the evolution of complex networks and that can improve the design of engineered systems.

CamOptimus: a tool for exploiting complex adaptive evolution to optimize experiments and processes in biotechnology.

PubMed

Cankorur-Cetinkaya, Ayca; Dias, Joao M L; Kludas, Jana; Slater, Nigel K H; Rousu, Juho; Oliver, Stephen G; Dikicioglu, Duygu

2017-06-01

Multiple interacting factors affect the performance of engineered biological systems in synthetic biology projects. The complexity of these biological systems means that experimental design should often be treated as a multiparametric optimization problem. However, the available methodologies are either impractical, due to a combinatorial explosion in the number of experiments to be performed, or are inaccessible to most experimentalists due to the lack of publicly available, user-friendly software. Although evolutionary algorithms may be employed as alternative approaches to optimize experimental design, the lack of simple-to-use software again restricts their use to specialist practitioners. In addition, the lack of subsidiary approaches to further investigate critical factors and their interactions prevents the full analysis and exploitation of the biotechnological system. We have addressed these problems and, here, provide a simple-to-use and freely available graphical user interface to empower a broad range of experimental biologists to employ complex evolutionary algorithms to optimize their experimental designs. Our approach exploits a Genetic Algorithm to discover the subspace containing the optimal combination of parameters, and Symbolic Regression to construct a model to evaluate the sensitivity of the experiment to each parameter under investigation. We demonstrate the utility of this method using an example in which the culture conditions for the microbial production of a bioactive human protein are optimized. CamOptimus is available through: (https://doi.org/10.17863/CAM.10257).

Testing for a genetic response to sexual selection in a wild Drosophila population.

PubMed

Gosden, T P; Thomson, J R; Blows, M W; Schaul, A; Chenoweth, S F

2016-06-01

In accordance with the consensus that sexual selection is responsible for the rapid evolution of display traits on macroevolutionary scales, microevolutionary studies suggest sexual selection is a widespread and often strong form of directional selection in nature. However, empirical evidence for the contemporary evolution of sexually selected traits via sexual rather than natural selection remains weak. In this study, we used a novel application of quantitative genetic breeding designs to test for a genetic response to sexual selection on eight chemical display traits from a field population of the fly, Drosophila serrata. Using our quantitative genetic approach, we were able to detect a genetically based difference in means between groups of males descended from fathers who had either successfully sired offspring or were randomly collected from the same wild population for one of these display traits, the diene (Z,Z)-5,9-C27 : 2 . Our experimental results, in combination with previous laboratory studies on this system, suggest that both natural and sexual selection may be influencing the evolutionary trajectories of these traits in nature, limiting the capacity for a contemporary evolutionary response. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Direct methanol fuel cells: A database-driven design procedure

NASA Astrophysics Data System (ADS)

Flipsen, S. F. J.; Spitas, C.

2011-10-01

To test the feasibility of DMFC systems in preliminary stages of the design process the design engineer can make use of heuristic models identifying the opportunity of DMFC systems in a specific application. In general these models are to generic and have a low accuracy. To improve the accuracy a second-order model is proposed in this paper. The second-order model consists of an evolutionary algorithm written in Mathematica, which selects a component-set satisfying the fuel-cell systems' performance requirements, places the components in 3D space and optimizes for volume. The results are presented as a 3D draft proposal together with a feasibility metric. To test the algorithm the design of DMFC system applied in the MP3 player is evaluated. The results show that volume and costs are an issue for the feasibility of the fuel-cell power-system applied in the MP3 player. The generated designs and the algorithm are evaluated and recommendations are given.

Adaptive design lessons from professional architects

NASA Astrophysics Data System (ADS)

Geiger, Ray W.; Snell, J. T.

1993-09-01

Psychocybernetic systems engineering design conceptualization is mimicking the evolutionary path of habitable environmental design and the professional practice of building architecture, construction, and facilities management. In pursuing better ways to design cellular automata and qualification classifiers in a design process, we have found surprising success in exploring certain more esoteric approaches, e.g., the vision of interdisciplinary artistic discovery in and around creative problem solving. Our evaluation in research into vision and hybrid sensory systems associated with environmental design and human factors has led us to discover very specific connections between the human spirit and quality design. We would like to share those very qualitative and quantitative parameters of engineering design, particularly as it relates to multi-faceted and future oriented design practice. Discussion covers areas of case- based techniques of cognitive ergonomics, natural modeling sources, and an open architectural process of means/goal satisfaction, qualified by natural repetition, gradation, rhythm, contrast, balance, and integrity of process.

Quantitative evolutionary design

PubMed Central

Diamond, Jared

2002-01-01

The field of quantitative evolutionary design uses evolutionary reasoning (in terms of natural selection and ultimate causation) to understand the magnitudes of biological reserve capacities, i.e. excesses of capacities over natural loads. Ratios of capacities to loads, defined as safety factors, fall in the range 1.2-10 for most engineered and biological components, even though engineered safety factors are specified intentionally by humans while biological safety factors arise through natural selection. Familiar examples of engineered safety factors include those of buildings, bridges and elevators (lifts), while biological examples include factors of bones and other structural elements, of enzymes and transporters, and of organ metabolic performances. Safety factors serve to minimize the overlap zone (resulting in performance failure) between the low tail of capacity distributions and the high tail of load distributions. Safety factors increase with coefficients of variation of load and capacity, with capacity deterioration with time, and with cost of failure, and decrease with costs of initial construction, maintenance, operation, and opportunity. Adaptive regulation of many biological systems involves capacity increases with increasing load; several quantitative examples suggest sublinear increases, such that safety factors decrease towards 1.0. Unsolved questions include safety factors of series systems, parallel or branched pathways, elements with multiple functions, enzyme reaction chains, and equilibrium enzymes. The modest sizes of safety factors imply the existence of costs that penalize excess capacities. Those costs are likely to involve wasted energy or space for large or expensive components, but opportunity costs of wasted space at the molecular level for minor components. PMID:12122135

A VHDL Core for Intrinsic Evolution of Discrete Time Filters with Signal Feedback

NASA Technical Reports Server (NTRS)

Gwaltney, David A.; Dutton, Kenneth

2005-01-01

The design of an Evolvable Machine VHDL Core is presented, representing a discrete-time processing structure capable of supporting control system applications. This VHDL Core is implemented in an FPGA and is interfaced with an evolutionary algorithm implemented in firmware on a Digital Signal Processor (DSP) to create an evolvable system platform. The salient features of this architecture are presented. The capability to implement IIR filter structures is presented along with the results of the intrinsic evolution of a filter. The robustness of the evolved filter design is tested and its unique characteristics are described.

Precision Attitude Determination System (PADS) system design and analysis: Single-axis gimbal star tracker

NASA Technical Reports Server (NTRS)

1974-01-01

The feasibility is evaluated of an evolutionary development for use of a single-axis gimbal star tracker from prior two-axis gimbal star tracker based system applications. Detailed evaluation of the star tracker gimbal encoder is considered. A brief system description is given including the aspects of tracker evolution and encoder evaluation. System analysis includes evaluation of star availability and mounting constraints for the geosynchronous orbit application, and a covariance simulation analysis to evaluate performance potential. Star availability and covariance analysis digital computer programs are included.

Electrical power systems for Space Station

NASA Technical Reports Server (NTRS)

Simon, W. E.

1984-01-01

Major challenges in power system development are described. Evolutionary growth, operational lifetime, and other design requirements are discussed. A pictorial view of weight-optimized power system applications shows which systems are best for missions of various lengths and required power level. Following definition of the major elements of the electrical power system, an overview of element options and a brief technology assessment are presented. Selected trade-study results show end-to-end system efficiencies, required photovoltaic power capability as a function of energy storage system efficiency, and comparisons with other systems such as a solar dynamic power system.

Evolutionary dynamics from a variational principle.

PubMed

Klimek, Peter; Thurner, Stefan; Hanel, Rudolf

2010-07-01

We demonstrate with a thought experiment that fitness-based population dynamical approaches to evolution are not able to make quantitative, falsifiable predictions about the long-term behavior of some evolutionary systems. A key characteristic of evolutionary systems is the ongoing endogenous production of new species. These novel entities change the conditions for already existing species. Even Darwin's Demon, a hypothetical entity with exact knowledge of the abundance of all species and their fitness functions at a given time, could not prestate the impact of these novelties on established populations. We argue that fitness is always a posteriori knowledge--it measures but does not explain why a species has reproductive success or not. To overcome these conceptual limitations, a variational principle is proposed in a spin-model-like setup of evolutionary systems. We derive a functional which is minimized under the most general evolutionary formulation of a dynamical system, i.e., evolutionary trajectories causally emerge as a minimization of a functional. This functional allows the derivation of analytic solutions of the asymptotic diversity for stochastic evolutionary systems within a mean-field approximation. We test these approximations by numerical simulations of the corresponding model and find good agreement in the position of phase transitions in diversity curves. The model is further able to reproduce stylized facts of timeseries from several man-made and natural evolutionary systems. Light will be thrown on how species and their fitness landscapes dynamically coevolve.

Classifier-Guided Sampling for Complex Energy System Optimization

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

Backlund, Peter B.; Eddy, John P.

2015-09-01

This report documents the results of a Laboratory Directed Research and Development (LDRD) effort enti tled "Classifier - Guided Sampling for Complex Energy System Optimization" that was conducted during FY 2014 and FY 2015. The goal of this proj ect was to develop, implement, and test major improvements to the classifier - guided sampling (CGS) algorithm. CGS is type of evolutionary algorithm for perform ing search and optimization over a set of discrete design variables in the face of one or more objective functions. E xisting evolutionary algorithms, such as genetic algorithms , may require a large number of omore » bjecti ve function evaluations to identify optimal or near - optimal solutions . Reducing the number of evaluations can result in significant time savings, especially if the objective function is computationally expensive. CGS reduce s the evaluation count by us ing a Bayesian network classifier to filter out non - promising candidate designs , prior to evaluation, based on their posterior probabilit ies . In this project, b oth the single - objective and multi - objective version s of the CGS are developed and tested on a set of benchm ark problems. As a domain - specific case study, CGS is used to design a microgrid for use in islanded mode during an extended bulk power grid outage.« less

Autonomous Weapon Systems: A Brief Survey of Developmental, Operational, Legal, and Ethical Issues

DTIC Science & Technology

2015-12-01

aspects of the early days of these ground- based AWS.14 Gage’s account characterizes the efforts as largely focused on research and development in...human judg- ment, but this responsibility also extends to those who design and develop the systems.27 The next section ad- dresses some of the key... develop - ment (R&D) efforts.”31 Further, the report argues that recent development of unmanned systems was large- ly evolutionary, moving forward based on

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.

Ranking Mammal Species for Conservation and the Loss of Both Phylogenetic and Trait Diversity.

PubMed

Redding, David W; Mooers, Arne O

2015-01-01

The 'edge of existence' (EDGE) prioritisation scheme is a new approach to rank species for conservation attention that aims to identify species that are both isolated on the tree of life and at imminent risk of extinction as defined by the World Conservation Union (IUCN). The self-stated benefit of the EDGE system is that it effectively captures unusual 'unique' species, and doing so will preserve the total evolutionary history of a group into the future. Given the EDGE metric was not designed to capture total evolutionary history, we tested this claim. Our analyses show that the total evolutionary history of mammals preserved is indeed much higher if EDGE species are protected than if at-risk species are chosen randomly. More of the total tree is also protected by EDGE species than if solely threat status or solely evolutionary distinctiveness were used for prioritisation. When considering how much trait diversity is captured by IUCN and EDGE prioritisation rankings, interestingly, preserving the highest-ranked EDGE species, or indeed just the most threatened species, captures more total trait diversity compared to sets of randomly-selected at-risk species. These results suggest that, as advertised, EDGE mammal species contribute evolutionary history to the evolutionary tree of mammals non-randomly, and EDGE-style rankings among endangered species can also capture important trait diversity. If this pattern holds for other groups, the EDGE prioritisation scheme has greater potential to be an efficient method to allocate scarce conservation effort.

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.

God, the Devil, and Darwin - A Critique of Intelligent Design Theory

NASA Astrophysics Data System (ADS)

Shanks, Niall

2007-03-01

In the last fifteen years a controversial new theory of the origins of biological complexity and the nature of the universe has been fomenting bitter debates in education and science policy across North America, Europe, and Australia. Backed by intellectuals at respectable universities, Intelligent Design theory (ID) proposes an alternative to accepted accounts of evolutionary theory: that life is so complex, and that the universe is so fine-tuned for the appearance of life, that the only plausible explanation is the existence of an intelligent designer. For many ID theorists, the designer is taken to be the god of Christianity. Niall Shanks has written the first accessible introduction to, and critique of, this controversial new intellectual movement. Shanks locates the growth of ID in the last two decades of the twentieth century in the growing influence of the American religious right. But as he shows, its roots go back beyond Aquinas to Ancient Greece. After looking at the historical roots of ID, Shanks takes a hard look at its intellectual underpinnings, discussing modern understandings of thermodynamics, and how self-organizing processes lead to complex physical, chemical, and biological systems. He considers cosmological arguments for ID rooted in so-called "anthropic coincidences" and also tackles new biochemical arguments for ID based on "irreducible biological complexity." Throughout he shows how arguments for ID lack cohesion, rest on errors and unfounded suppositions, and generally are grossly inferior to evolutionary explanations. While ID has been proposed as a scientific alternative to evolutionary biology, Shanks argues that ID is in fact "old creationist wine in new designer label bottles" and moreover is a serious threat to the scientific and democratic values that are our cultural and intellectual inheritance from the Enlightenment.

Human Inspired Self-developmental Model of Neural Network (HIM): Introducing Content/Form Computing

NASA Astrophysics Data System (ADS)

Krajíček, Jiří

This paper presents cross-disciplinary research between medical/psychological evidence on human abilities and informatics needs to update current models in computer science to support alternative methods for computation and communication. In [10] we have already proposed hypothesis introducing concept of human information model (HIM) as cooperative system. Here we continue on HIM design in detail. In our design, first we introduce Content/Form computing system which is new principle of present methods in evolutionary computing (genetic algorithms, genetic programming). Then we apply this system on HIM (type of artificial neural network) model as basic network self-developmental paradigm. Main inspiration of our natural/human design comes from well known concept of artificial neural networks, medical/psychological evidence and Sheldrake theory of "Nature as Alive" [22].

An Integrated Framework for Modeling Air Carrier Behavior, Policy, and Impacts in the U.S. Air Transportation System

NASA Technical Reports Server (NTRS)

Horio, Brant M.; Kumar, Vivek; DeCicco, Anthony H.; Hasan, Shahab; Stouffer, Virginia L.; Smith, Jeremy C.; Guerreiro, Nelson M.

2015-01-01

The implementation of the Next Generation Air Transportation System (NextGen) in the United States is an ongoing challenge for policymakers due to the complexity of the air transportation system (ATS) with its broad array of stakeholders and dynamic interdependencies between them. The successful implementation of NextGen has a hard dependency on the active participation of U.S. commercial airlines. To assist policymakers in identifying potential policy designs that facilitate the implementation of NextGen, the National Aeronautics and Space Administration (NASA) and LMI developed a research framework called the Air Transportation System Evolutionary Simulation (ATS-EVOS). This framework integrates large empirical data sets with multiple specialized models to simulate the evolution of the airline response to potential future policies and explore consequential impacts on ATS performance and market dynamics. In the ATS-EVOS configuration presented here, we leverage the Transportation Systems Analysis Model (TSAM), the Airline Evolutionary Simulation (AIRLINE-EVOS), the Airspace Concept Evaluation System (ACES), and the Aviation Environmental Design Tool (AEDT), all of which enable this research to comprehensively represent the complex facets of the ATS and its participants. We validated this baseline configuration of ATS-EVOS against Airline Origin and Destination Survey (DB1B) data and subject matter expert opinion, and we verified the ATS-EVOS framework and agent behavior logic through scenario-based experiments that explored potential implementations of a carbon tax, congestion pricing policy, and the dynamics for equipage of new technology by airlines. These experiments demonstrated ATS-EVOS's capabilities in responding to a wide range of potential NextGen-related policies and utility for decision makers to gain insights for effective policy design.

Cooperation in microbial communities and their biotechnological applications

PubMed Central

Cavaliere, Matteo; Feng, Song; Soyer, Orkun S.

2017-01-01

Summary Microbial communities are increasingly utilized in biotechnology. Efficiency and productivity in many of these applications depends on the presence of cooperative interactions between members of the community. Two key processes underlying these interactions are the production of public goods and metabolic cross‐feeding, which can be understood in the general framework of ecological and evolutionary (eco‐evo) dynamics. In this review, we illustrate the relevance of cooperative interactions in microbial biotechnological processes, discuss their mechanistic origins and analyse their evolutionary resilience. Cooperative behaviours can be damaged by the emergence of ‘cheating’ cells that benefit from the cooperative interactions but do not contribute to them. Despite this, cooperative interactions can be stabilized by spatial segregation, by the presence of feedbacks between the evolutionary dynamics and the ecology of the community, by the role of regulatory systems coupled to the environmental conditions and by the action of horizontal gene transfer. Cooperative interactions enrich microbial communities with a higher degree of robustness against environmental stress and can facilitate the evolution of more complex traits. Therefore, the evolutionary resilience of microbial communities and their ability to constraint detrimental mutants should be considered to design robust biotechnological applications. PMID:28447371

De novo design of molecular architectures by evolutionary assembly of drug-derived building blocks.

PubMed

Schneider, G; Lee, M L; Stahl, M; Schneider, P

2000-07-01

An evolutionary algorithm was developed for fragment-based de novo design of molecules (TOPAS, TOPology-Assigning System). This stochastic method aims at generating a novel molecular structure mimicking a template structure. A set of approximately 25,000 fragment structures serves as the building block supply, which were obtained by a straightforward fragmentation procedure applied to 36,000 known drugs. Eleven reaction schemes were implemented for both fragmentation and building block assembly. This combination of drug-derived building blocks and a restricted set of reaction schemes proved to be a key for the automatic development of novel, synthetically tractable structures. In a cyclic optimization process, molecular architectures were generated from a parent structure by virtual synthesis, and the best structure of a generation was selected as the parent for the subsequent TOPAS cycle. Similarity measures were used to define 'fitness', based on 2D-structural similarity or topological pharmacophore distance between the template molecule and the variants. The concept of varying library 'diversity' during a design process was consequently implemented by using adaptive variant distributions. The efficiency of the design algorithm was demonstrated for the de novo construction of potential thrombin inhibitors mimicking peptide and non-peptide template structures.

Comparison of evolutionary algorithms for LPDA antenna optimization

NASA Astrophysics Data System (ADS)

Lazaridis, Pavlos I.; Tziris, Emmanouil N.; Zaharis, Zaharias D.; Xenos, Thomas D.; Cosmas, John P.; Gallion, Philippe B.; Holmes, Violeta; Glover, Ian A.

2016-08-01

A novel approach to broadband log-periodic antenna design is presented, where some of the most powerful evolutionary algorithms are applied and compared for the optimal design of wire log-periodic dipole arrays (LPDA) using Numerical Electromagnetics Code. The target is to achieve an optimal antenna design with respect to maximum gain, gain flatness, front-to-rear ratio (F/R) and standing wave ratio. The parameters of the LPDA optimized are the dipole lengths, the spacing between the dipoles, and the dipole wire diameters. The evolutionary algorithms compared are the Differential Evolution (DE), Particle Swarm (PSO), Taguchi, Invasive Weed (IWO), and Adaptive Invasive Weed Optimization (ADIWO). Superior performance is achieved by the IWO (best results) and PSO (fast convergence) algorithms.

Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics.

PubMed

Trianni, Vito; López-Ibáñez, Manuel

2015-01-01

The application of multi-objective optimisation to evolutionary robotics is receiving increasing attention. A survey of the literature reveals the different possibilities it offers to improve the automatic design of efficient and adaptive robotic systems, and points to the successful demonstrations available for both task-specific and task-agnostic approaches (i.e., with or without reference to the specific design problem to be tackled). However, the advantages of multi-objective approaches over single-objective ones have not been clearly spelled out and experimentally demonstrated. This paper fills this gap for task-specific approaches: starting from well-known results in multi-objective optimisation, we discuss how to tackle commonly recognised problems in evolutionary robotics. In particular, we show that multi-objective optimisation (i) allows evolving a more varied set of behaviours by exploring multiple trade-offs of the objectives to optimise, (ii) supports the evolution of the desired behaviour through the introduction of objectives as proxies, (iii) avoids the premature convergence to local optima possibly introduced by multi-component fitness functions, and (iv) solves the bootstrap problem exploiting ancillary objectives to guide evolution in the early phases. We present an experimental demonstration of these benefits in three different case studies: maze navigation in a single robot domain, flocking in a swarm robotics context, and a strictly collaborative task in collective robotics.

Capturing planar shapes by approximating their outlines

NASA Astrophysics Data System (ADS)

Sarfraz, M.; Riyazuddin, M.; Baig, M. H.

2006-05-01

A non-deterministic evolutionary approach for approximating the outlines of planar shapes has been developed. Non-uniform Rational B-splines (NURBS) have been utilized as an underlying approximation curve scheme. Simulated Annealing heuristic is used as an evolutionary methodology. In addition to independent studies of the optimization of weight and knot parameters of the NURBS, a separate scheme has also been developed for the optimization of weights and knots simultaneously. The optimized NURBS models have been fitted over the contour data of the planar shapes for the ultimate and automatic output. The output results are visually pleasing with respect to the threshold provided by the user. A web-based system has also been developed for the effective and worldwide utilization. The objective of this system is to provide the facility to visualize the output to the whole world through internet by providing the freedom to the user for various desired input parameters setting in the algorithm designed.

Improving the sampling efficiency of Monte Carlo molecular simulations: an evolutionary approach

NASA Astrophysics Data System (ADS)

Leblanc, Benoit; Braunschweig, Bertrand; Toulhoat, Hervé; Lutton, Evelyne

We present a new approach in order to improve the convergence of Monte Carlo (MC) simulations of molecular systems belonging to complex energetic landscapes: the problem is redefined in terms of the dynamic allocation of MC move frequencies depending on their past efficiency, measured with respect to a relevant sampling criterion. We introduce various empirical criteria with the aim of accounting for the proper convergence in phase space sampling. The dynamic allocation is performed over parallel simulations by means of a new evolutionary algorithm involving 'immortal' individuals. The method is bench marked with respect to conventional procedures on a model for melt linear polyethylene. We record significant improvement in sampling efficiencies, thus in computational load, while the optimal sets of move frequencies are liable to allow interesting physical insights into the particular systems simulated. This last aspect should provide a new tool for designing more efficient new MC moves.

Recent Development Activities and Future Mission Applications of NASA's Evolutionary Xenon Thruster (NEXT)

NASA Technical Reports Server (NTRS)

Patterson, Michael J.; Pencil, Eric J.

2014-01-01

NASAs Evolutionary Xenon Thruster (NEXT) project is developing next generation ion propulsion technologies to enhance the performance and lower the costs of future NASA space science missions. This is being accomplished by producing Engineering Model (EM) and Prototype Model (PM) components, validating these via qualification-level and integrated system testing, and preparing the transition of NEXT technologies to flight system development. This presentation is a follow-up to the NEXT project overviews presented in 2009-2010. It reviews the status of the NEXT project, presents the current system performance characteristics, and describes planned activities in continuing the transition of NEXT technology to a first flight. In 2013 a voluntary decision was made to terminate the long duration test of the NEXT thruster, given the thruster design has exceeded all expectations by accumulating over 50,000 hours of operation to demonstrate around 900 kg of xenon throughput. Besides its promise for upcoming NASA science missions, NEXT has excellent potential for future commercial and international spacecraft applications.

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.

Automating software design system DESTA

NASA Technical Reports Server (NTRS)

Lovitsky, Vladimir A.; Pearce, Patricia D.

1992-01-01

'DESTA' is the acronym for the Dialogue Evolutionary Synthesizer of Turnkey Algorithms by means of a natural language (Russian or English) functional specification of algorithms or software being developed. DESTA represents the computer-aided and/or automatic artificial intelligence 'forgiving' system which provides users with software tools support for algorithm and/or structured program development. The DESTA system is intended to provide support for the higher levels and earlier stages of engineering design of software in contrast to conventional Computer Aided Design (CAD) systems which provide low level tools for use at a stage when the major planning and structuring decisions have already been taken. DESTA is a knowledge-intensive system. The main features of the knowledge are procedures, functions, modules, operating system commands, batch files, their natural language specifications, and their interlinks. The specific domain for the DESTA system is a high level programming language like Turbo Pascal 6.0. The DESTA system is operational and runs on an IBM PC computer.

CamOptimus: a tool for exploiting complex adaptive evolution to optimize experiments and processes in biotechnology

PubMed Central

Cankorur-Cetinkaya, Ayca; Dias, Joao M. L.; Kludas, Jana; Slater, Nigel K. H.; Rousu, Juho; Dikicioglu, Duygu

2017-01-01

Multiple interacting factors affect the performance of engineered biological systems in synthetic biology projects. The complexity of these biological systems means that experimental design should often be treated as a multiparametric optimization problem. However, the available methodologies are either impractical, due to a combinatorial explosion in the number of experiments to be performed, or are inaccessible to most experimentalists due to the lack of publicly available, user-friendly software. Although evolutionary algorithms may be employed as alternative approaches to optimize experimental design, the lack of simple-to-use software again restricts their use to specialist practitioners. In addition, the lack of subsidiary approaches to further investigate critical factors and their interactions prevents the full analysis and exploitation of the biotechnological system. We have addressed these problems and, here, provide a simple‐to‐use and freely available graphical user interface to empower a broad range of experimental biologists to employ complex evolutionary algorithms to optimize their experimental designs. Our approach exploits a Genetic Algorithm to discover the subspace containing the optimal combination of parameters, and Symbolic Regression to construct a model to evaluate the sensitivity of the experiment to each parameter under investigation. We demonstrate the utility of this method using an example in which the culture conditions for the microbial production of a bioactive human protein are optimized. CamOptimus is available through: (https://doi.org/10.17863/CAM.10257). PMID:28635591

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

PubMed Central

Emília Santos, M.; Berger, Chloé S.; Refki, Peter N.

2015-01-01

Evolutionary developmental biology (evo-devo) has provided invaluable contributions to our understanding of the mechanistic relationship between genotypic and phenotypic change. Similarly, evolutionary ecology has greatly advanced our understanding of the relationship between the phenotype and the environment. To fully understand the evolution of organismal diversity, a thorough integration of these two fields is required. This integration remains highly challenging because model systems offering a rich ecological and evolutionary background, together with the availability of developmental genetic tools and genomic resources, are scarce. In this review, we introduce the semi-aquatic bugs (Gerromorpha, Heteroptera) as original models well suited to study why and how organisms diversify. The Gerromorpha invaded water surfaces over 200 mya and diversified into a range of remarkable new forms within this new ecological habitat. We summarize the biology and evolutionary history of this group of insects and highlight a set of characters associated with the habitat change and the diversification that followed. We further discuss the morphological, behavioral, molecular and genomic tools available that together make semi-aquatic bugs a prime model for integration across disciplines. We present case studies showing how the implementation and combination of these approaches can advance our understanding of how the interaction between genotypes, phenotypes and the environment drives the evolution of distinct morphologies. Finally, we explain how the same set of experimental designs can be applied in other systems to address similar biological questions. PMID:25750411

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

PubMed

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

2015-11-01

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

A Multi Agent System for Flow-Based Intrusion Detection Using Reputation and Evolutionary Computation

DTIC Science & Technology

2011-03-01

the actions of malicious and benign users of the Internet, as well as the engi- neering decisions giving rise to observed network topologies. Say and...with resilience, which is particularly important in the domain of quickly-evolving cyber threats. “Self-organization,” says Meadows, “is basically the...system design paradigm is to leverage the advantages of a distributed approach? What is meant by saying the witness conceptually rates the target

Evolutionary multiobjective design of a flexible caudal fin for robotic fish.

PubMed

Clark, Anthony J; Tan, Xiaobo; McKinley, Philip K

2015-11-25

Robotic fish accomplish swimming by deforming their bodies or other fin-like appendages. As an emerging class of embedded computing system, robotic fish are anticipated to play an important role in environmental monitoring, inspection of underwater structures, tracking of hazardous wastes and oil spills, and the study of live fish behaviors. While integration of flexible materials (into the fins and/or body) holds the promise of improved swimming performance (in terms of both speed and maneuverability) for these robots, such components also introduce significant design challenges due to the complex material mechanics and hydrodynamic interactions. The problem is further exacerbated by the need for the robots to meet multiple objectives (e.g., both speed and energy efficiency). In this paper, we propose an evolutionary multiobjective optimization approach to the design and control of a robotic fish with a flexible caudal fin. Specifically, we use the NSGA-II algorithm to investigate morphological and control parameter values that optimize swimming speed and power usage. Several evolved fin designs are validated experimentally with a small robotic fish, where fins of different stiffness values and sizes are printed with a multi-material 3D printer. Experimental results confirm the effectiveness of the proposed design approach in balancing the two competing objectives.

Biological differences between the evolutionary lineages within Phytophthora ramorum and Phytophthora lateralis: Should the lineages be formally taxonomically designated?

Treesearch

Clive Brasier

2017-01-01

It is now generally accepted that the four evolutionary lineages of Phytophthora ramorum (informally designated NA1, NA2, EU1, and EU2) are relatively anciently divergent populations, recently introduced into Europe and North America from different, unknown geographic locations; that recombinants between them are genetically unstable and probably...

Space station experiment definition: Advanced power system test bed

NASA Technical Reports Server (NTRS)

Pollard, H. E.; Neff, R. E.

1986-01-01

A conceptual design for an advanced photovoltaic power system test bed was provided and the requirements for advanced photovoltaic power system experiments better defined. Results of this study will be used in the design efforts conducted in phase B and phase C/D of the space station program so that the test bed capabilities will be responsive to user needs. Critical PV and energy storage technologies were identified and inputs were received from the idustry (government and commercial, U.S. and international) which identified experimental requirements. These inputs were used to develop a number of different conceptual designs. Pros and cons of each were discussed and a strawman candidate identified. A preliminary evolutionary plan, which included necessary precursor activities, was established and cost estimates presented which would allow for a successful implementation to the space station in the 1994 time frame.

Hardware platforms for MEMS gyroscope tuning based on evolutionary computation using open-loop and closed -loop frequency response

NASA Technical Reports Server (NTRS)

Keymeulen, Didier; Ferguson, Michael I.; Fink, Wolfgang; Oks, Boris; Peay, Chris; Terrile, Richard; Cheng, Yen; Kim, Dennis; MacDonald, Eric; Foor, David

2005-01-01

We propose a tuning method for MEMS gyroscopes based on evolutionary computation to efficiently increase the sensitivity of MEMS gyroscopes through tuning. The tuning method was tested for the second generation JPL/Boeing Post-resonator MEMS gyroscope using the measurement of the frequency response of the MEMS device in open-loop operation. We also report on the development of a hardware platform for integrated tuning and closed loop operation of MEMS gyroscopes. The control of this device is implemented through a digital design on a Field Programmable Gate Array (FPGA). The hardware platform easily transitions to an embedded solution that allows for the miniaturization of the system to a single chip.

A comparative study of corrugated horn design by evolutionary techniques

NASA Technical Reports Server (NTRS)

Hoorfar, A.

2003-01-01

Here an evolutionary programming algorithm is used to optimize the pattern of a corrugated circular horn subject to various constraints on return loss, antenna beamwidth, pattern circularity, and low cross polarization.

Multiobjective Multifactorial Optimization in Evolutionary Multitasking.

PubMed

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

2016-05-03

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

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.

Evolutionary Connectionism: Algorithmic Principles Underlying the Evolution of Biological Organisation in Evo-Devo, Evo-Eco and Evolutionary Transitions.

PubMed

Watson, Richard A; Mills, Rob; Buckley, C L; Kouvaris, Kostas; Jackson, Adam; Powers, Simon T; Cox, Chris; Tudge, Simon; Davies, Adam; Kounios, Loizos; Power, Daniel

2016-01-01

The mechanisms of variation, selection and inheritance, on which evolution by natural selection depends, are not fixed over evolutionary time. Current evolutionary biology is increasingly focussed on understanding how the evolution of developmental organisations modifies the distribution of phenotypic variation, the evolution of ecological relationships modifies the selective environment, and the evolution of reproductive relationships modifies the heritability of the evolutionary unit. The major transitions in evolution, in particular, involve radical changes in developmental, ecological and reproductive organisations that instantiate variation, selection and inheritance at a higher level of biological organisation. However, current evolutionary theory is poorly equipped to describe how these organisations change over evolutionary time and especially how that results in adaptive complexes at successive scales of organisation (the key problem is that evolution is self-referential, i.e. the products of evolution change the parameters of the evolutionary process). Here we first reinterpret the central open questions in these domains from a perspective that emphasises the common underlying themes. We then synthesise the findings from a developing body of work that is building a new theoretical approach to these questions by converting well-understood theory and results from models of cognitive learning. Specifically, connectionist models of memory and learning demonstrate how simple incremental mechanisms, adjusting the relationships between individually-simple components, can produce organisations that exhibit complex system-level behaviours and improve the adaptive capabilities of the system. We use the term "evolutionary connectionism" to recognise that, by functionally equivalent processes, natural selection acting on the relationships within and between evolutionary entities can result in organisations that produce complex system-level behaviours in evolutionary systems and modify the adaptive capabilities of natural selection over time. We review the evidence supporting the functional equivalences between the domains of learning and of evolution, and discuss the potential for this to resolve conceptual problems in our understanding of the evolution of developmental, ecological and reproductive organisations and, in particular, the major evolutionary transitions.

The optimal design support system for shell components of vehicles using the methods of artificial intelligence

NASA Astrophysics Data System (ADS)

Szczepanik, M.; Poteralski, A.

2016-11-01

The paper is devoted to an application of the evolutionary methods and the finite element method to the optimization of shell structures. Optimization of thickness of a car wheel (shell) by minimization of stress functional is considered. A car wheel geometry is built from three surfaces of revolution: the central surface with the holes destined for the fastening bolts, the surface of the ring of the wheel and the surface connecting the two mentioned earlier. The last one is subjected to the optimization process. The structures are discretized by triangular finite elements and subjected to the volume constraints. Using proposed method, material properties or thickness of finite elements are changing evolutionally and some of them are eliminated. As a result the optimal shape, topology and material or thickness of the structures are obtained. The numerical examples demonstrate that the method based on evolutionary computation is an effective technique for solving computer aided optimal design.

The Carnegie Mellon University Insert Project

DTIC Science & Technology

1997-02-01

Real - Time Systems (INSERT) project under the DARPA Evolutionary Design for Complex Software (EDCS) Program. The INSERT team has completed an initial API definition and ported the existing real-time publication subscription group communication software to LynxOS 2.4, a POSIX.1b compliant OS. The distributed real-time publisher/subscriber communication model is now supported by a processor membership protocol which allows a node in the system to fail, or to rejoin the system later. When a node fails, all the publishers and subscribers on that node have to be

A New Automated Design Method Based on Machine Learning for CMOS Analog Circuits

NASA Astrophysics Data System (ADS)

Moradi, Behzad; Mirzaei, Abdolreza

2016-11-01

A new simulation based automated CMOS analog circuit design method which applies a multi-objective non-Darwinian-type evolutionary algorithm based on Learnable Evolution Model (LEM) is proposed in this article. The multi-objective property of this automated design of CMOS analog circuits is governed by a modified Strength Pareto Evolutionary Algorithm (SPEA) incorporated in the LEM algorithm presented here. LEM includes a machine learning method such as the decision trees that makes a distinction between high- and low-fitness areas in the design space. The learning process can detect the right directions of the evolution and lead to high steps in the evolution of the individuals. The learning phase shortens the evolution process and makes remarkable reduction in the number of individual evaluations. The expert designer's knowledge on circuit is applied in the design process in order to reduce the design space as well as the design time. The circuit evaluation is made by HSPICE simulator. In order to improve the design accuracy, bsim3v3 CMOS transistor model is adopted in this proposed design method. This proposed design method is tested on three different operational amplifier circuits. The performance of this proposed design method is verified by comparing it with the evolutionary strategy algorithm and other similar methods.

Design and Optimization Method of a Two-Disk Rotor System

NASA Astrophysics Data System (ADS)

Huang, Jingjing; Zheng, Longxi; Mei, Qing

2016-04-01

An integrated analytical method based on multidisciplinary optimization software Isight and general finite element software ANSYS was proposed in this paper. Firstly, a two-disk rotor system was established and the mode, humorous response and transient response at acceleration condition were analyzed with ANSYS. The dynamic characteristics of the two-disk rotor system were achieved. On this basis, the two-disk rotor model was integrated to the multidisciplinary design optimization software Isight. According to the design of experiment (DOE) and the dynamic characteristics, the optimization variables, optimization objectives and constraints were confirmed. After that, the multi-objective design optimization of the transient process was carried out with three different global optimization algorithms including Evolutionary Optimization Algorithm, Multi-Island Genetic Algorithm and Pointer Automatic Optimizer. The optimum position of the two-disk rotor system was obtained at the specified constraints. Meanwhile, the accuracy and calculation numbers of different optimization algorithms were compared. The optimization results indicated that the rotor vibration reached the minimum value and the design efficiency and quality were improved by the multidisciplinary design optimization in the case of meeting the design requirements, which provided the reference to improve the design efficiency and reliability of the aero-engine rotor.

A Philosophical Perspective on Evolutionary Systems Biology

PubMed Central

Soyer, Orkun S.; Siegal, Mark L.

2015-01-01

Evolutionary systems biology (ESB) is an emerging hybrid approach that integrates methods, models, and data from evolutionary and systems biology. Drawing on themes that arose at a cross-disciplinary meeting on ESB in 2013, we discuss in detail some of the explanatory friction that arises in the interaction between evolutionary and systems biology. These tensions appear because of different modeling approaches, diverse explanatory aims and strategies, and divergent views about the scope of the evolutionary synthesis. We locate these discussions in the context of long-running philosophical deliberations on explanation, modeling, and theoretical synthesis. We show how many of the issues central to ESB’s progress can be understood as general philosophical problems. The benefits of addressing these philosophical issues feed back into philosophy too, because ESB provides excellent examples of scientific practice for the development of philosophy of science and philosophy of biology. PMID:26085823

The great opportunity: Evolutionary applications to medicine and public health.

PubMed

Nesse, Randolph M; Stearns, Stephen C

2008-02-01

Evolutionary biology is an essential basic science for medicine, but few doctors and medical researchers are familiar with its most relevant principles. Most medical schools have geneticists who understand evolution, but few have even one evolutionary biologist to suggest other possible applications. The canyon between evolutionary biology and medicine is wide. The question is whether they offer each other enough to make bridge building worthwhile. What benefits could be expected if evolution were brought fully to bear on the problems of medicine? How would studying medical problems advance evolutionary research? Do doctors need to learn evolution, or is it valuable mainly for researchers? What practical steps will promote the application of evolutionary biology in the areas of medicine where it offers the most? To address these questions, we review current and potential applications of evolutionary biology to medicine and public health. Some evolutionary technologies, such as population genetics, serial transfer production of live vaccines, and phylogenetic analysis, have been widely applied. Other areas, such as infectious disease and aging research, illustrate the dramatic recent progress made possible by evolutionary insights. In still other areas, such as epidemiology, psychiatry, and understanding the regulation of bodily defenses, applying evolutionary principles remains an open opportunity. In addition to the utility of specific applications, an evolutionary perspective fundamentally challenges the prevalent but fundamentally incorrect metaphor of the body as a machine designed by an engineer. Bodies are vulnerable to disease - and remarkably resilient - precisely because they are not machines built from a plan. They are, instead, bundles of compromises shaped by natural selection in small increments to maximize reproduction, not health. Understanding the body as a product of natural selection, not design, offers new research questions and a framework for making medical education more coherent. We conclude with recommendations for actions that would better connect evolutionary biology and medicine in ways that will benefit public health. It is our hope that faculty and students will send this article to their undergraduate and medical school Deans, and that this will initiate discussions about the gap, the great opportunity, and action plans to bring the full power of evolutionary biology to bear on human health problems.

Next-generation laser retroreflectors for GNSS, solar system exploration, geodesy, gravitational physics and earth observation

NASA Astrophysics Data System (ADS)

Dell'Agnello, S.; Boni, A.; Cantone, C.; Ciocci, E.; Martini, M.; Patrizi, G.; Tibuzzi, M.; Delle Monache, G.; Vittori, R.; Bianco, G.; Currie, D.; Intaglietta, N.; Salvatori, L.; Lops, C.; Contessa, S.; Porcelli, L.; Mondaini, C.; Tuscano, P.; Maiello, M.

2017-11-01

The SCF_Lab (Satellite/lunar/gnss laser ranging and altimetry Characterization Facility Laboratory) of INFNLNF is designed to cover virtually LRAs (Laser Retroreflector Arrays) of CCRs (Cube Corner Retroreflectors) for missions in the whole solar system, with a modular organization of its instrumentation, two redundant SCF (SCF_Lab Characterization Facilities), and an evolutionary measurement approach, including customization and potentially upgrade on-demand. See http://www.lnf.infn.it/esperimenti/etrusco/ for a general description.

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.

Rapid Preliminary Design of Interplanetary Trajectories Using the Evolutionary Mission Trajectory Generator

NASA Technical Reports Server (NTRS)

Englander, Jacob

2016-01-01

This set of tutorial slides is an introduction to the Evolutionary Mission Trajectory Generator (EMTG), NASA Goddard Space Flight Center's autonomous tool for preliminary design of interplanetary missions. This slide set covers the basics of creating and post-processing simple interplanetary missions in EMTG using both high-thrust chemical and low-thrust electric propulsion along with a variety of operational constraints.

Are hotspots of evolutionary potential adequately protected in southern California?

USGS Publications Warehouse

Vandergast, A.G.; Bohonak, A.J.; Hathaway, S.A.; Boys, J.; Fisher, R.N.

2008-01-01

Reserves are often designed to protect rare habitats, or "typical" exemplars of ecoregions and geomorphic provinces. This approach focuses on current patterns of organismal and ecosystem-level biodiversity, but typically ignores the evolutionary processes that control the gain and loss of biodiversity at these and other levels (e.g., genetic, ecological). In order to include evolutionary processes in conservation planning efforts, their spatial components must first be identified and mapped. We describe a GIS-based approach for explicitly mapping patterns of genetic divergence and diversity for multiple species (a "multi-species genetic landscape"). Using this approach, we analyzed mitochondrial DNA datasets from 21 vertebrate and invertebrate species in southern California to identify areas with common phylogeographic breaks and high intrapopulation diversity. The result is an evolutionary framework for southern California within which patterns of genetic diversity can be analyzed in the context of historical processes, future evolutionary potential and current reserve design. Our multi-species genetic landscapes pinpoint six hotspots where interpopulation genetic divergence is consistently high, five evolutionary hotspots within which genetic connectivity is high, and three hotspots where intrapopulation genetic diversity is high. These 14 hotspots can be grouped into eight geographic areas, of which five largely are unprotected at this time. The multi-species genetic landscape approach may provide an avenue to readily incorporate measures of evolutionary process into GIS-based systematic conservation assessment and land-use planning.

Computer-Automated Evolution of Spacecraft X-Band Antennas

NASA Technical Reports Server (NTRS)

Lohn, Jason D.; Homby, Gregory S.; Linden, Derek S.

2010-01-01

A document discusses the use of computer- aided evolution in arriving at a design for X-band communication antennas for NASA s three Space Technology 5 (ST5) satellites, which were launched on March 22, 2006. Two evolutionary algorithms, incorporating different representations of the antenna design and different fitness functions, were used to automatically design and optimize an X-band antenna design. A set of antenna designs satisfying initial ST5 mission requirements was evolved by use these algorithms. The two best antennas - one from each evolutionary algorithm - were built. During flight-qualification testing of these antennas, the mission requirements were changed. After minimal changes in the evolutionary algorithms - mostly in the fitness functions - new antenna designs satisfying the changed mission requirements were evolved and within one month of this change, two new antennas were designed and prototypes of the antennas were built and tested. One of these newly evolved antennas was approved for deployment on the ST5 mission, and flight-qualified versions of this design were built and installed on the spacecraft. At the time of writing the document, these antennas were the first computer-evolved hardware in outer space.

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.

Hybrid Co-Evolutionary Motion Planning via Visibility-Based Repair

NASA Technical Reports Server (NTRS)

Dozier, Gerry; McCullough, Shaun; Brown, Edward, Jr.; Homaifar, Abdollah; Bikdash, Mar-wan

1997-01-01

This paper introduces a hybrid co-evolutionary system for global motion planning within unstructured environments. This system combines the concept of co-evolutionary search along with a concept that we refer to as the visibility-based repair to form a hybrid which quickly transforms infeasible motions into feasible ones. Also, this system makes use of a novel representation scheme for the obstacles within an environment. Our hybrid evolutionary system differs from other evolutionary motion planners in that (1) more emphasis is placed on repairing infeasible motions to develop feasible motions rather than using simulated evolution exclusively as a means of discovering feasible motions, (2) a continuous map of the environment is used rather than a discretized map, and (3) it develops global motion plans for multiple mobile destinations by co-evolving populations of sub-global motion plans. In this paper, we demonstrate the effectiveness of this system by using it to solve two challenging motion planning problems where multiple targets try to move away from a point robot.

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.

Rapid evolution of hosts begets species diversity at the cost of intraspecific diversity.

PubMed

Frickel, Jens; Theodosiou, Loukas; Becks, Lutz

2017-10-17

Ecosystems are complex food webs in which multiple species interact and ecological and evolutionary processes continuously shape populations and communities. Previous studies on eco-evolutionary dynamics have shown that the presence of intraspecific diversity affects community structure and function, and that eco-evolutionary feedback dynamics can be an important driver for its maintenance. Within communities, feedbacks are, however, often indirect, and they can feed back over many generations. Here, we studied eco-evolutionary feedbacks in evolving communities over many generations and compared two-species systems (virus-host and prey-predator) with a more complex three-species system (virus-host-predator). Both indirect density- and trait-mediated effects drove the dynamics in the complex system, where host-virus coevolution facilitated coexistence of predator and virus, and where coexistence, in return, lowered intraspecific diversity of the host population. Furthermore, ecological and evolutionary dynamics were significantly altered in the three-species system compared with the two-species systems. We found that the predator slowed host-virus coevolution in the complex system and that the virus' effect on the overall population dynamics was negligible when the three species coexisted. Overall, we show that a detailed understanding of the mechanism driving eco-evolutionary feedback dynamics is necessary for explaining trait and species diversity in communities, even in communities with only three species.

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.

Some assembly required: evolutionary and systems perspectives on the mammalian reproductive system.

PubMed

Mordhorst, Bethany R; Wilson, Miranda L; Conant, Gavin C

2016-01-01

In this review, we discuss the way that insights from evolutionary theory and systems biology shed light on form and function in mammalian reproductive systems. In the first part of the review, we contrast the rapid evolution seen in some reproductive genes with the generally conservative nature of development. We discuss directional selection and coevolution as potential drivers of rapid evolution in sperm and egg proteins. Such rapid change is very different from the highly conservative nature of later embryo development. However, it is not unique, as some regions of the sex chromosomes also show elevated rates of evolutionary change. To explain these contradictory trends, we argue that it is not reproductive functions per se that induce rapid evolution. Rather, it is the fact that biotic interactions, such as speciation events and sexual conflict, have no evolutionary endpoint and hence can drive continuous evolutionary changes. Returning to the question of sex chromosome evolution, we discuss the way that recent advances in evolutionary genomics and systems biology and, in particular, the development of a theory of gene balance provide a better understanding of the evolutionary patterns seen on these chromosomes. We end the review with a discussion of a surprising and incompletely understood phenomenon observed in early embryos: namely the Warburg effect, whereby glucose is fermented to lactate and alanine rather than respired to carbon dioxide. We argue that evolutionary insights, from both yeasts and tumor cells, help to explain the Warburg effect, and that new metabolic modeling approaches are useful in assessing the potential sources of the effect.

An intelligent control and virtual display system for evolutionary space station workstation design

NASA Technical Reports Server (NTRS)

Feng, Xin; Niederjohn, Russell J.; Mcgreevy, Michael W.

1992-01-01

Research and development of the Advanced Display and Computer Augmented Control System (ADCACS) for the space station Body-Ported Cupola Virtual Workstation (BP/VCWS) were pursued. The potential applications were explored of body ported virtual display and intelligent control technology for the human-system interfacing applications is space station environment. The new system is designed to enable crew members to control and monitor a variety of space operations with greater flexibility and efficiency than existing fixed consoles. The technologies being studied include helmet mounted virtual displays, voice and special command input devices, and microprocessor based intelligent controllers. Several research topics, such as human factors, decision support expert systems, and wide field of view, color displays are being addressed. The study showed the significant advantages of this uniquely integrated display and control system, and its feasibility for human-system interfacing applications in the space station command and control environment.

Reconstructing Networks from Profit Sequences in Evolutionary Games via a Multiobjective Optimization Approach with Lasso Initialization

PubMed Central

Wu, Kai; Liu, Jing; Wang, Shuai

2016-01-01

Evolutionary games (EG) model a common type of interactions in various complex, networked, natural and social systems. Given such a system with only profit sequences being available, reconstructing the interacting structure of EG networks is fundamental to understand and control its collective dynamics. Existing approaches used to handle this problem, such as the lasso, a convex optimization method, need a user-defined constant to control the tradeoff between the natural sparsity of networks and measurement error (the difference between observed data and simulated data). However, a shortcoming of these approaches is that it is not easy to determine these key parameters which can maximize the performance. In contrast to these approaches, we first model the EG network reconstruction problem as a multiobjective optimization problem (MOP), and then develop a framework which involves multiobjective evolutionary algorithm (MOEA), followed by solution selection based on knee regions, termed as MOEANet, to solve this MOP. We also design an effective initialization operator based on the lasso for MOEA. We apply the proposed method to reconstruct various types of synthetic and real-world networks, and the results show that our approach is effective to avoid the above parameter selecting problem and can reconstruct EG networks with high accuracy. PMID:27886244

Neutral forces acting on intragenomic variability shape the Escherichia coli regulatory network topology.

PubMed

Ruths, Troy; Nakhleh, Luay

2013-05-07

Cis-regulatory networks (CRNs) play a central role in cellular decision making. Like every other biological system, CRNs undergo evolution, which shapes their properties by a combination of adaptive and nonadaptive evolutionary forces. Teasing apart these forces is an important step toward functional analyses of the different components of CRNs, designing regulatory perturbation experiments, and constructing synthetic networks. Although tests of neutrality and selection based on molecular sequence data exist, no such tests are currently available based on CRNs. In this work, we present a unique genotype model of CRNs that is grounded in a genomic context and demonstrate its use in identifying portions of the CRN with properties explainable by neutral evolutionary forces at the system, subsystem, and operon levels. We leverage our model against experimentally derived data from Escherichia coli. The results of this analysis show statistically significant and substantial neutral trends in properties previously identified as adaptive in origin--degree distribution, clustering coefficient, and motifs--within the E. coli CRN. Our model captures the tightly coupled genome-interactome of an organism and enables analyses of how evolutionary events acting at the genome level, such as mutation, and at the population level, such as genetic drift, give rise to neutral patterns that we can quantify in CRNs.

Reconstructing Networks from Profit Sequences in Evolutionary Games via a Multiobjective Optimization Approach with Lasso Initialization

NASA Astrophysics Data System (ADS)

Wu, Kai; Liu, Jing; Wang, Shuai

2016-11-01

Evolutionary games (EG) model a common type of interactions in various complex, networked, natural and social systems. Given such a system with only profit sequences being available, reconstructing the interacting structure of EG networks is fundamental to understand and control its collective dynamics. Existing approaches used to handle this problem, such as the lasso, a convex optimization method, need a user-defined constant to control the tradeoff between the natural sparsity of networks and measurement error (the difference between observed data and simulated data). However, a shortcoming of these approaches is that it is not easy to determine these key parameters which can maximize the performance. In contrast to these approaches, we first model the EG network reconstruction problem as a multiobjective optimization problem (MOP), and then develop a framework which involves multiobjective evolutionary algorithm (MOEA), followed by solution selection based on knee regions, termed as MOEANet, to solve this MOP. We also design an effective initialization operator based on the lasso for MOEA. We apply the proposed method to reconstruct various types of synthetic and real-world networks, and the results show that our approach is effective to avoid the above parameter selecting problem and can reconstruct EG networks with high accuracy.

Space power reactor in-core thermionic multicell evolutionary (S-prime) design

NASA Astrophysics Data System (ADS)

Determan, William R.; Van Hagan, Tom H.

1993-01-01

A 5- to 40-kWe moderated in-core thermionic space nuclear power system (TI-SNPS) concept was developed to address the TI-SNPS program requirements. The 40-kWe baseline design uses multicell Thermionic Fuel Elements (TFEs) in a zirconium hydride moderated reactor to achieve a specific mass of 18.2 We/kg and a net end-of-mission (EOM) efficiency of 8.2%. The reactor is cooled with a single NaK-78 pumped loop, which rejects the heat through a 24 m2 heat pipe space radiator.

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

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.

SP-100 power system conceptual design for lunar base applications

NASA Technical Reports Server (NTRS)

Mason, Lee S.; Bloomfield, Harvey S.; Hainley, Donald C.

1989-01-01

A conceptual design is presented for a nuclear power system utilizing an SP-100 reactor and multiple Stirling cycle engines for operation on the lunar surface. Based on the results of this study, it was concluded that this power plant could be a viable option for an evolutionary lunar base. The design concept consists of a 2500 kWt (kilowatt thermal) SP-100 reactor coupled to eight free-piston Stirling engines. Two of the engines are held in reserve to provide conversion system redundancy. The remaining engines operate at 91.7 percent of their rated capacity of 150 kWe. The design power level for this system is 825 kWe. Each engine has a pumped heat-rejection loop connected to a heat pipe radiator. Power system performance, sizing, layout configurations, shielding options, and transmission line characteristics are described. System components and integration options are compared for safety, high performance, low mass, and ease of assembly. The power plant was integrated with a proposed human lunar base concept to ensure mission compatibility. This study should be considered a preliminary investigation; further studies are planned to investigate the effect of different technologies on this baseline design.

Virtual workstations and telepresence interfaces: Design accommodations and prototypes for Space Station Freedom evolution

NASA Technical Reports Server (NTRS)

Mcgreevy, Michael W.

1990-01-01

An advanced human-system interface is being developed for evolutionary Space Station Freedom as part of the NASA Office of Space Station (OSS) Advanced Development Program. The human-system interface is based on body-pointed display and control devices. The project will identify and document the design accommodations ('hooks and scars') required to support virtual workstations and telepresence interfaces, and prototype interface systems will be built, evaluated, and refined. The project is a joint enterprise of Marquette University, Astronautics Corporation of America (ACA), and NASA's ARC. The project team is working with NASA's JSC and McDonnell Douglas Astronautics Company (the Work Package contractor) to ensure that the project is consistent with space station user requirements and program constraints. Documentation describing design accommodations and tradeoffs will be provided to OSS, JSC, and McDonnell Douglas, and prototype interface devices will be delivered to ARC and JSC. ACA intends to commercialize derivatives of the interface for use with computer systems developed for scientific visualization and system simulation.

Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics

PubMed Central

Trianni, Vito; López-Ibáñez, Manuel

2015-01-01

The application of multi-objective optimisation to evolutionary robotics is receiving increasing attention. A survey of the literature reveals the different possibilities it offers to improve the automatic design of efficient and adaptive robotic systems, and points to the successful demonstrations available for both task-specific and task-agnostic approaches (i.e., with or without reference to the specific design problem to be tackled). However, the advantages of multi-objective approaches over single-objective ones have not been clearly spelled out and experimentally demonstrated. This paper fills this gap for task-specific approaches: starting from well-known results in multi-objective optimisation, we discuss how to tackle commonly recognised problems in evolutionary robotics. In particular, we show that multi-objective optimisation (i) allows evolving a more varied set of behaviours by exploring multiple trade-offs of the objectives to optimise, (ii) supports the evolution of the desired behaviour through the introduction of objectives as proxies, (iii) avoids the premature convergence to local optima possibly introduced by multi-component fitness functions, and (iv) solves the bootstrap problem exploiting ancillary objectives to guide evolution in the early phases. We present an experimental demonstration of these benefits in three different case studies: maze navigation in a single robot domain, flocking in a swarm robotics context, and a strictly collaborative task in collective robotics. PMID:26295151

The Design and Transformation of Biofundamentals: A Nonsurvey Introductory Evolutionary and Molecular Biology Course.

PubMed

Klymkowsky, Michael W; Rentsch, Jeremy D; Begovic, Emina; Cooper, Melanie M

2016-01-01

Many introductory biology courses amount to superficial surveys of disconnected topics. Often, foundational observations and the concepts derived from them and students' ability to use these ideas appropriately are overlooked, leading to unrealistic expectations and unrecognized learning obstacles. The result can be a focus on memorization at the expense of the development of a meaningful framework within which to consider biological phenomena. About a decade ago, we began a reconsideration of what an introductory course should present to students and the skills they need to master. The original Web-based course's design presaged many of the recommendations of the Vision and Change report; in particular, a focus on social evolutionary mechanisms, stochastic (evolutionary and molecular) processes, and core ideas (cellular continuity, evolutionary homology, molecular interactions, coupled chemical reactions, and molecular machines). Inspired by insights from the Chemistry, Life, the Universe & Everything general chemistry project, we transformed the original Web version into a (freely available) book with a more unified narrative flow and a set of formative assessments delivered through the beSocratic system. We outline how student responses to course materials are guiding future course modifications, in particular a more concerted effort at helping students to construct logical, empirically based arguments, explanations, and models. © 2016 M. W. Klymkowsky et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Liquid rocket booster study. Volume 2, book 5, appendix 9: LRB alternate applications and evolutionary growth

NASA Technical Reports Server (NTRS)

1989-01-01

The analyses performed in assessing the merit of the Liquid Rocket Booster concept for use in alternate applications such as for Shuttle C, for Standalone Expendable Launch Vehicles, and possibly for use with the Air Force's Advanced Launch System are presented. A comparison is also presented of the three LRB candidate designs, namely: (1) the LO2/LH2 pump fed, (2) the LO2/RP-1 pump fed, and (3) the LO2/RP-1 pressure fed propellant systems in terms of evolution along with design and cost factors, and other qualitative considerations. A further description is also presented of the recommended LRB standalone, core-to-orbit launch vehicle concept.

LinkFinder: An expert system that constructs phylogenic trees

NASA Technical Reports Server (NTRS)

Inglehart, James; Nelson, Peter C.

1991-01-01

An expert system has been developed using the C Language Integrated Production System (CLIPS) that automates the process of constructing DNA sequence based phylogenies (trees or lineages) that indicate evolutionary relationships. LinkFinder takes as input homologous DNA sequences from distinct individual organisms. It measures variations between the sequences, selects appropriate proportionality constants, and estimates the time that has passed since each pair of organisms diverged from a common ancestor. It then designs and outputs a phylogenic map summarizing these results. LinkFinder can find genetic relationships between different species, and between individuals of the same species, including humans. It was designed to take advantage of the vast amount of sequence data being produced by the Genome Project, and should be of value to evolution theorists who wish to utilize this data, but who have no formal training in molecular genetics. Evolutionary theory holds that distinct organisms carrying a common gene inherited that gene from a common ancestor. Homologous genes vary from individual to individual and species to species, and the amount of variation is now believed to be directly proportional to the time that has passed since divergence from a common ancestor. The proportionality constant must be determined experimentally; it varies considerably with the types of organisms and DNA molecules under study. Given an appropriate constant, and the variation between two DNA sequences, a simple linear equation gives the divergence time.

Evolution of Autonomous Self-Righting Behaviors for Articulated Nanorovers

NASA Technical Reports Server (NTRS)

Tunstel, Edward

1999-01-01

Miniature rovers with articulated mobility mechanisms are being developed for planetary surface exploration on Mars and small solar system bodies. These vehicles are designed to be capable of autonomous recovery from overturning during surface operations. This paper describes a computational means of developing motion behaviors that achieve the autonomous recovery function. It proposes a control software design approach aimed at reducing the effort involved in developing self-righting behaviors. The approach is based on the integration of evolutionary computing with a dynamics simulation environment for evolving and evaluating motion behaviors. The automated behavior design approach is outlined and its underlying genetic programming infrastructure is described.

Inspection planning development: An evolutionary approach using reliability engineering as a tool

NASA Technical Reports Server (NTRS)

Graf, David A.; Huang, Zhaofeng

1994-01-01

This paper proposes an evolutionary approach for inspection planning which introduces various reliability engineering tools into the process and assess system trade-offs among reliability, engineering requirement, manufacturing capability and inspection cost to establish an optimal inspection plan. The examples presented in the paper illustrate some advantages and benefits of the new approach. Through the analysis, reliability and engineering impacts due to manufacturing process capability and inspection uncertainty are clearly understood; the most cost effective and efficient inspection plan can be established and associated risks are well controlled; some inspection reductions and relaxations are well justified; and design feedbacks and changes may be initiated from the analysis conclusion to further enhance reliability and reduce cost. The approach is particularly promising as global competitions and customer quality improvement expectations are rapidly increasing.

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.

Intelligent systems/software engineering methodology - A process to manage cost and risk

NASA Technical Reports Server (NTRS)

Friedlander, Carl; Lehrer, Nancy

1991-01-01

A systems development methodology is discussed that has been successfully applied to the construction of a number of intelligent systems. This methodology is a refinement of both evolutionary and spiral development methodologies. It is appropriate for development of intelligent systems. The application of advanced engineering methodology to the development of software products and intelligent systems is an important step toward supporting the transition of AI technology into aerospace applications. A description of the methodology and the process model from which it derives is given. Associated documents and tools are described which are used to manage the development process and record and report the emerging design.

Growing Up of Autonomous Agents: an Emergent Phenomenon

NASA Astrophysics Data System (ADS)

Morgavi, Giovanna; Marconi, Lucia

2008-10-01

A fundamental research challenge is the design of robust artifacts that are capable of operating under changing environments and noisy input, and yet exhibit the desired behavior and response time. These systems should be able to adapt and learn how to react to unforeseen scenarios as well as to display properties comparable to biological entities. The turn to nature has brought us many unforeseen great concepts. Biological systems are able to handle many of these challenges with an elegance and efficiency still far beyond current human artifacts. A living artifact grows up when its capabilities, abilities/knowledge, shift to a further level of complexity, i.e. the complexity rank of its internal capabilities performs a step forward. In the attempt to define an architecture for autonomous growing up agents [1]. We conducted an experiment on the abstraction process in children as natural parts of a cognitive system. We found that linguistic growing up involve a number of different trial processes. We identified a fixed number of distinct paths that were crossed by children. Once a given interpretation paths was discovered useless, they tried to follow another path, until the new meaning was emerging. This study generates suggestion about the evolutionary conditions conducive to the emergence of growing up in robots and provides guidelines for designing artificial evolutionary systems displaying spontaneous adaptation abilities. The importance of multi-sensor perception, motivation and emotional drives are underlined and, above all, the growing up insights shows similarities to emergent self-organized behaviors.

Modeling Tumor Clonal Evolution for Drug Combinations Design.

PubMed

Zhao, Boyang; Hemann, Michael T; Lauffenburger, Douglas A

2016-03-01

Cancer is a clonal evolutionary process. This presents challenges for effective therapeutic intervention, given the constant selective pressure towards drug resistance. Mathematical modeling from population genetics, evolutionary dynamics, and engineering perspectives are being increasingly employed to study tumor progression, intratumoral heterogeneity, drug resistance, and rational drug scheduling and combinations design. In this review, we discuss promising opportunities these inter-disciplinary approaches hold for advances in cancer biology and treatment. We propose that quantitative modeling perspectives can complement emerging experimental technologies to facilitate enhanced understanding of disease progression and improved capabilities for therapeutic drug regimen designs.

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.

Incorporating Eco-Evolutionary Processes into Population Models:Design and Applications

EPA Science Inventory

Eco-evolutionary population models are powerful new tools for exploring howevolutionary processes influence plant and animal population dynamics andvice-versa. The need to manage for climate change and other dynamicdisturbance regimes is creating a demand for the incorporation of...

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.

Rapid evolution of hosts begets species diversity at the cost of intraspecific diversity

PubMed Central

Frickel, Jens; Theodosiou, Loukas

2017-01-01

Ecosystems are complex food webs in which multiple species interact and ecological and evolutionary processes continuously shape populations and communities. Previous studies on eco-evolutionary dynamics have shown that the presence of intraspecific diversity affects community structure and function, and that eco-evolutionary feedback dynamics can be an important driver for its maintenance. Within communities, feedbacks are, however, often indirect, and they can feed back over many generations. Here, we studied eco-evolutionary feedbacks in evolving communities over many generations and compared two-species systems (virus–host and prey–predator) with a more complex three-species system (virus–host–predator). Both indirect density- and trait-mediated effects drove the dynamics in the complex system, where host–virus coevolution facilitated coexistence of predator and virus, and where coexistence, in return, lowered intraspecific diversity of the host population. Furthermore, ecological and evolutionary dynamics were significantly altered in the three-species system compared with the two-species systems. We found that the predator slowed host–virus coevolution in the complex system and that the virus’ effect on the overall population dynamics was negligible when the three species coexisted. Overall, we show that a detailed understanding of the mechanism driving eco-evolutionary feedback dynamics is necessary for explaining trait and species diversity in communities, even in communities with only three species. PMID:28973943

Genetic architecture of hybrid male sterility in Drosophila: analysis of intraspecies variation for interspecies isolation.

PubMed

Reed, Laura K; LaFlamme, Brooke A; Markow, Therese A

2008-08-27

The genetic basis of postzygotic isolation is a central puzzle in evolutionary biology. Evolutionary forces causing hybrid sterility or inviability act on the responsible genes while they still are polymorphic, thus we have to study these traits as they arise, before isolation is complete. Isofemale strains of D. mojavensis vary significantly in their production of sterile F(1) sons when females are crossed to D. arizonae males. We took advantage of the intraspecific polymorphism, in a novel design, to perform quantitative trait locus (QTL) mapping analyses directly on F(1) hybrid male sterility itself. We found that the genetic architecture of the polymorphism for hybrid male sterility (HMS) in the F(1) is complex, involving multiple QTL, epistasis, and cytoplasmic effects. The role of extensive intraspecific polymorphism, multiple QTL, and epistatic interactions in HMS in this young species pair shows that HMS is arising as a complex trait in this system. Directional selection alone would be unlikely to maintain polymorphism at multiple loci, thus we hypothesize that directional selection is unlikely to be the only evolutionary force influencing postzygotic isolation.

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.

A molecular signaling approach to linking intraspecific variation and macro-evolutionary patterns.

PubMed

Swanson, Eli M; Snell-Rood, Emilie C

2014-11-01

Macro-evolutionary comparisons are a valued tool in evolutionary biology. Nevertheless, our understanding of how systems involved in molecular signaling change in concert with phenotypic diversification has lagged. We argue that integrating our understanding of the evolution of molecular signaling systems with phylogenetic comparative methods is an important step toward understanding the processes linking variation among individuals with variation among species. Focusing mostly on the endocrine system, we discuss how the complexity and mechanistic nature of molecular signaling systems may influence the application and interpretation of macro-evolutionary comparisons. We also detail five hypotheses concerning the role that physiological mechanisms can play in shaping macro-evolutionary patterns, and discuss ways in which these hypotheses could influence phenotypic diversification. Finally, we review a series of tools able to analyze the complexity of physiological systems and the way they change in concert with the phenotypes for which they coordinate development. © The Author 2014. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Biomimetic design processes in architecture: morphogenetic and evolutionary computational design.

PubMed

Menges, Achim

2012-03-01

Design computation has profound impact on architectural design methods. This paper explains how computational design enables the development of biomimetic design processes specific to architecture, and how they need to be significantly different from established biomimetic processes in engineering disciplines. The paper first explains the fundamental difference between computer-aided and computational design in architecture, as the understanding of this distinction is of critical importance for the research presented. Thereafter, the conceptual relation and possible transfer of principles from natural morphogenesis to design computation are introduced and the related developments of generative, feature-based, constraint-based, process-based and feedback-based computational design methods are presented. This morphogenetic design research is then related to exploratory evolutionary computation, followed by the presentation of two case studies focusing on the exemplary development of spatial envelope morphologies and urban block morphologies.

Multiobjective Optimization of Rocket Engine Pumps Using Evolutionary Algorithm

NASA Technical Reports Server (NTRS)

Oyama, Akira; Liou, Meng-Sing

2001-01-01

A design optimization method for turbopumps of cryogenic rocket engines has been developed. Multiobjective Evolutionary Algorithm (MOEA) is used for multiobjective pump design optimizations. Performances of design candidates are evaluated by using the meanline pump flow modeling method based on the Euler turbine equation coupled with empirical correlations for rotor efficiency. To demonstrate the feasibility of the present approach, a single stage centrifugal pump design and multistage pump design optimizations are presented. In both cases, the present method obtains very reasonable Pareto-optimal solutions that include some designs outperforming the original design in total head while reducing input power by one percent. Detailed observation of the design results also reveals some important design criteria for turbopumps in cryogenic rocket engines. These results demonstrate the feasibility of the EA-based design optimization method in this field.

Artificial gravity Mars spaceship

NASA Technical Reports Server (NTRS)

Clark, Benton C.

1989-01-01

Experience gained in the study of artificial gravity for a manned trip to Mars is reviewed, and a snowflake-configured interplanetary vehicle cluster of habitat modules, descent vehicles, and propulsion systems is presented. An evolutionary design is described which permits sequential upgrading from five to nine crew members, an increase of landers from one to as many a three per mission, and an orderly, phased incorporation of advanced technologies as they become available.

Evolutionary Systems Design: Recognizing Changes in Security and Survivability Risks

DTIC Science & Technology

2006-09-01

Unlimited distribution subject to the copyright. Technical Note CMU/SEI-2006-TN-027 The Software Engineering Institute is a federally...CARNEGIE MELLON UNIVERSITY AND SOFTWARE ENGINEERING INSTITUTE MATERIAL IS FURNISHED ON AN “AS-IS” BASIS. CARNEGIE MELLON UNIVERSITY MAKES NO WARRANTIES OF...created in the performance of Federal Government Contract Number FA8721-05-C-0003 with Carnegie Mellon University for the operation of the Software

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.

Perspective: Evolutionary design of granular media and block copolymer patterns

NASA Astrophysics Data System (ADS)

Jaeger, Heinrich M.; de Pablo, Juan J.

2016-05-01

The creation of new materials "by design" is a process that starts from desired materials properties and proceeds to identify requirements for the constituent components. Such process is challenging because it inverts the typical modeling approach, which starts from given micro-level components to predict macro-level properties. We describe how to tackle this inverse problem using concepts from evolutionary computation. These concepts have widespread applicability and open up new opportunities for design as well as discovery. Here we apply them to design tasks involving two very different classes of soft materials, shape-optimized granular media and nanopatterned block copolymer thin films.

An overview of ecological and evolutionary research on disease in natural systems: an annotated reference list

Treesearch

Helen M. Alexander

2012-01-01

The Fourth International Workshop on the Genetics of Host-Parasite Interactions in Forestry (July 31-August 5, 2011) included a session on “Ecology and Evolutionary Biology of Resistance and Tolerance, Natural Systems.” Within this session, I gave a talk entitled “An overview of ecological and evolutionary research on disease in ‘natural’ systems” that reviewed...

Boeing electronic flight bag

NASA Astrophysics Data System (ADS)

Trujillo, Eddie J.; Ellersick, Steven D.

2006-05-01

The Boeing Electronic Flight Bag (EFB) is a key element in the evolutionary process of an "e-enabled" flight deck. The EFB is designed to improve the overall safety, efficiency, and operation of the flight deck and corresponding airline operations by providing the flight crew with better information and enhanced functionality in a user-friendly digital format. The EFB is intended to increase the pilots' situational awareness of the airplane and systems, as well as improve the efficiency of information management. The system will replace documents and forms that are currently stored or carried onto the flight deck and put them, in digital format, at the crew's fingertips. This paper describes what the Boeing EFB is and the significant human factors and interface design issues, trade-offs, and decisions made during development of the display system. In addition, EFB formats, graphics, input control methods, challenges using COTS (commercial-off-the-shelf)-leveraged glass and formatting technology are discussed. The optical design requirements, display technology utilized, brightness control system, reflection challenge, and the resulting optical performance are presented.

The constructal law and the evolution of design in nature.

PubMed

Bejan, Adrian; Lorente, Sylvie

2011-10-01

The constructal law accounts for the universal phenomenon of generation and evolution of design (configuration, shape, structure, pattern, rhythm). This phenomenon is observed across the board, in animate, inanimate and human systems. The constructal law states the time direction of the evolutionary design phenomenon. It defines the concept of design evolution in physics. Along with the first and second law, the constructal law elevates thermodynamics to a science of systems with configuration. In this article we review the more recent work of our group, with emphasis on the advances made with the constructal law in the natural sciences. Highlighted are the oneness of animate and inanimate designs, the origin of finite-size organs on animals and vehicles, the flow of stresses as the generator of design in solid structures (skeletons, vegetation), the universality and rigidity of hierarchy in all flow systems, and the global design of human flows. Noteworthy is the tapestry of distributed energy systems, which balances nodes of production with networks of distribution on the landscape, and serves as key to energy sustainability and empowerment. At the global level, the constructal law accounts for the geography and design of human movement, wealth and communications. Copyright © 2011 Elsevier B.V. All rights reserved.

Mean-Potential Law in Evolutionary Games

NASA Astrophysics Data System (ADS)

Nałecz-Jawecki, Paweł; Miekisz, Jacek

2018-01-01

The Letter presents a novel way to connect random walks, stochastic differential equations, and evolutionary game theory. We introduce a new concept of a potential function for discrete-space stochastic systems. It is based on a correspondence between one-dimensional stochastic differential equations and random walks, which may be exact not only in the continuous limit but also in finite-state spaces. Our method is useful for computation of fixation probabilities in discrete stochastic dynamical systems with two absorbing states. We apply it to evolutionary games, formulating two simple and intuitive criteria for evolutionary stability of pure Nash equilibria in finite populations. In particular, we show that the 1 /3 law of evolutionary games, introduced by Nowak et al. [Nature, 2004], follows from a more general mean-potential law.

Moglichkeiten und Grenzen eines evolutionaren Paradigmas in der Erziehungswissenschaft (Possibilities and Limits of an Evolutionary Paradigm in Educational Science).

ERIC Educational Resources Information Center

Nipkow, Karl Ernst

2002-01-01

Describes a sectoral and paradigmatic approach to evolutionary research. Argues that an evolutionary paradigm does not exist. Examines the socio-biological approach and that of a system-theoretical oriented general evolutionary theory. Utilizes the topics of cooperation, delimitation, and indoctrination to explain more promising ways of adoption.…

Using Evolutionary Theory to Guide Mental Health Research.

PubMed

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

2016-03-01

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

Using Evolutionary Theory to Guide Mental Health Research

PubMed Central

Mulsant, Benoit H.; McKenzie, Kwame; Andrews, Paul W.

2016-01-01

Evolutionary approaches to medicine can shed light on the origins and etiology of disease. Such an approach may be especially useful in psychiatry, which frequently addresses conditions with heterogeneous presentation and unknown causes. We review several previous applications of evolutionary theory that highlight the ways in which psychiatric conditions may persist despite and because of natural selection. One lesson from the evolutionary approach is that some conditions currently classified as disorders (because they cause distress and impairment) may actually be caused by functioning adaptations operating “normally” (as designed by natural selection). Such conditions suggest an alternative illness model that may generate alternative intervention strategies. Thus, the evolutionary approach suggests that psychiatry should sometimes think differently about distress and impairment. The complexity of the human brain, including normal functioning and potential for dysfunctions, has developed over evolutionary time and has been shaped by natural selection. Understanding the evolutionary origins of psychiatric conditions is therefore a crucial component to a complete understanding of etiology. PMID:27254091

Towards Engineering Biological Systems in a Broader Context.

PubMed

Venturelli, Ophelia S; Egbert, Robert G; Arkin, Adam P

2016-02-27

Significant advances have been made in synthetic biology to program information processing capabilities in cells. While these designs can function predictably in controlled laboratory environments, the reliability of these devices in complex, temporally changing environments has not yet been characterized. As human society faces global challenges in agriculture, human health and energy, synthetic biology should develop predictive design principles for biological systems operating in complex environments. Natural biological systems have evolved mechanisms to overcome innumerable and diverse environmental challenges. Evolutionary design rules should be extracted and adapted to engineer stable and predictable ecological function. We highlight examples of natural biological responses spanning the cellular, population and microbial community levels that show promise in synthetic biology contexts. We argue that synthetic circuits embedded in host organisms or designed ecologies informed by suitable measurement of biotic and abiotic environmental parameters could be used as engineering substrates to achieve target functions in complex environments. Successful implementation of these methods will broaden the context in which synthetic biological systems can be applied to solve important problems. Copyright © 2015 Elsevier Ltd. All rights reserved.

Space Station Freedom extravehicular activity systems evolution study

NASA Technical Reports Server (NTRS)

Rouen, Michael

1990-01-01

Evaluation of Space Station Freedom (SSF) support of manned exploration is in progress to identify SSF extravehicular activity (EVA) system evolution requirements and capabilities. The output from these studies will provide data to support the preliminary design process to ensure that Space Station EVA system requirements for future missions (including the transportation node) are adequately considered and reflected in the baseline design. The study considers SSF support of future missions and the EVA system baseline to determine adequacy of EVA requirements and capabilities and to identify additional requirements, capabilities, and necessary technology upgrades. The EVA demands levied by formal requirements and indicated by evolutionary mission scenarios are high for the out-years of Space Station Freedom. An EVA system designed to meet the baseline requirements can easily evolve to meet evolution demands with few exceptions. Results to date indicate that upgrades or modifications to the EVA system may be necessary to meet the full range of EVA thermal environments associated with the transportation node. Work continues to quantify the EVA capability in this regard. Evolution mission scenarios with EVA and ground unshielded nuclear propulsion engines are inconsistent with anthropomorphic EVA capabilities.

Common evolutionary trends underlie the four-bar linkage systems of sunfish and mantis shrimp.

PubMed

Hu, Yinan; Nelson-Maney, Nathan; Anderson, Philip S L

2017-05-01

Comparative biomechanics offers an opportunity to explore the evolution of disparate biological systems that share common underlying mechanics. Four-bar linkage modeling has been applied to various biological systems such as fish jaws and crustacean appendages to explore the relationship between biomechanics and evolutionary diversification. Mechanical sensitivity states that the functional output of a mechanical system will show differential sensitivity to changes in specific morphological components. We document similar patterns of mechanical sensitivity in two disparate four-bar systems from different phyla: the opercular four-bar system in centrarchid fishes and the raptorial appendage of stomatopods. We built dynamic linkage models of 19 centrarchid and 36 stomatopod species and used phylogenetic generalized least squares regression (PGLS) to compare evolutionary shifts in linkage morphology and mechanical outputs derived from the models. In both systems, the kinematics of the four-bar mechanism show significant evolutionary correlation with the output link, while travel distance of the output arm is correlated with the coupler link. This common evolutionary pattern seen in both fish and crustacean taxa is a potential consequence of the mechanical principles underlying four-bar systems. Our results illustrate the potential influence of physical principles on morphological evolution across biological systems with different structures, behaviors, and ecologies. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Mesoscopic structure conditions the emergence of cooperation on social networks

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

Lozano, S.; Arenas, A.; Sanchez, A.

We study the evolutionary Prisoner's Dilemma on two social networks substrates obtained from actual relational data. We find very different cooperation levels on each of them that cannot be easily understood in terms of global statistical properties of both networks. We claim that the result can be understood at the mesoscopic scale, by studying the community structure of the networks. We explain the dependence of the cooperation level on the temptation parameter in terms of the internal structure of the communities and their interconnections. We then test our results on community-structured, specifically designed artificial networks, finding a good agreement withmore » the observations in both real substrates. Our results support the conclusion that studies of evolutionary games on model networks and their interpretation in terms of global properties may not be sufficient to study specific, real social systems. Further, the study allows us to define new quantitative parameters that summarize the mesoscopic structure of any network. In addition, the community perspective may be helpful to interpret the origin and behavior of existing networks as well as to design structures that show resilient cooperative behavior.« less

Evolutionary orbital period change in BH Virginis

NASA Astrophysics Data System (ADS)

Gebrehiwot, Y. M.; Tessema, S. B.; Berdnikov, L. N.

2017-04-01

The study of orbital period change of close binaries, such as BH Virginis (BH Vir), using very long time baseline is vital to understand evolutionary processes of the system. In this paper, we use photometric data to analyze the evolutionary orbital period change of the short period RS CVn-type binary system, BH Vir, with a time baseline spanning 123 years. We used the software version of the Hertzsprung method to describe the O-C curve of the system, and we found that the orbital period secularly decreases at a rate of dp/dt=-(0.0013000 ± 0.0000863) s yr^{-1}. Because BH Vir is a typical detached binary system and both components are late type (G0 V + G2 V) stars, the evolutionary period change could be caused by the angular momentum loss due to tides coupled with magnetic breaking.

Modeling Tumor Clonal Evolution for Drug Combinations Design

PubMed Central

Zhao, Boyang; Hemann, Michael T.; Lauffenburger, Douglas A.

2016-01-01

Cancer is a clonal evolutionary process. This presents challenges for effective therapeutic intervention, given the constant selective pressure towards drug resistance. Mathematical modeling from population genetics, evolutionary dynamics, and engineering perspectives are being increasingly employed to study tumor progression, intratumoral heterogeneity, drug resistance, and rational drug scheduling and combinations design. In this review, we discuss promising opportunities these inter-disciplinary approaches hold for advances in cancer biology and treatment. We propose that quantitative modeling perspectives can complement emerging experimental technologies to facilitate enhanced understanding of disease progression and improved capabilities for therapeutic drug regimen designs. PMID:28435907

MSAT-X: A technical introduction and status report

NASA Technical Reports Server (NTRS)

Dessouky, Khaled; Sue, Miles

1988-01-01

A technical introduction and status report for the Mobile Satellite Experiment (MSAT-X) program is presented. The concepts of a Mobile Satellite System (MSS) and its unique challenges are introduced. MSAT-X's role and objectives are delineated with focus on its achievements. An outline of MSS design philosophy is followed by a presentation and analysis of the MSAT-X results, which are cast in a broader context of an MSS. The current phase of MSAT-X has focused notably on the ground segment of MSS. The accomplishments in the four critical technology areas of vehicle antennas, modem and mobile terminal design, speech coding, and networking are presented. A concise evolutionary trace is incorporated in each area to elucidate the rationale leading to the current design choices. The findings in the area of propagation channel modeling are also summarized and their impact on system design discussed. To facilitate the assessment of the MSAT-X results, technology and subsystem recommendations are also included and integrated with a quantitative first-generation MSS design.

Stochastic dynamics and stable equilibrium of evolutionary optional public goods game in finite populations

NASA Astrophysics Data System (ADS)

Quan, Ji; Liu, Wei; Chu, Yuqing; Wang, Xianjia

2018-07-01

Continuous noise caused by mutation is widely present in evolutionary systems. Considering the noise effects and under the optional participation mechanism, a stochastic model for evolutionary public goods game in a finite size population is established. The evolutionary process of strategies in the population is described as a multidimensional ergodic and continuous time Markov process. The stochastic stable state of the system is analyzed by the limit distribution of the stochastic process. By numerical experiments, the influences of the fixed income coefficient for non-participants and the investment income coefficient of the public goods on the stochastic stable equilibrium of the system are analyzed. Through the numerical calculation results, we found that the optional participation mechanism can change the evolutionary dynamics and the equilibrium of the public goods game, and there is a range of parameters which can effectively promote the evolution of cooperation. Further, we obtain the accurate quantitative relationship between the parameters and the probabilities for the system to choose different stable equilibriums, which can be used to realize the control of cooperation.

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…

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

PubMed

O'Malley, Maureen A

2012-01-01

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

Comparison of Evolutionary (Genetic) Algorithm and Adjoint Methods for Multi-Objective Viscous Airfoil Optimizations

NASA Technical Reports Server (NTRS)

Pulliam, T. H.; Nemec, M.; Holst, T.; Zingg, D. W.; Kwak, Dochan (Technical Monitor)

2002-01-01

A comparison between an Evolutionary Algorithm (EA) and an Adjoint-Gradient (AG) Method applied to a two-dimensional Navier-Stokes code for airfoil design is presented. Both approaches use a common function evaluation code, the steady-state explicit part of the code,ARC2D. The parameterization of the design space is a common B-spline approach for an airfoil surface, which together with a common griding approach, restricts the AG and EA to the same design space. Results are presented for a class of viscous transonic airfoils in which the optimization tradeoff between drag minimization as one objective and lift maximization as another, produces the multi-objective design space. Comparisons are made for efficiency, accuracy and design consistency.

Are there ergodic limits to evolution? Ergodic exploration of genome space and convergence

PubMed Central

McLeish, Tom C. B.

2015-01-01

We examine the analogy between evolutionary dynamics and statistical mechanics to include the fundamental question of ergodicity—the representative exploration of the space of possible states (in the case of evolution this is genome space). Several properties of evolutionary dynamics are identified that allow a generalization of the ergodic dynamics, familiar in dynamical systems theory, to evolution. Two classes of evolved biological structure then arise, differentiated by the qualitative duration of their evolutionary time scales. The first class has an ergodicity time scale (the time required for representative genome exploration) longer than available evolutionary time, and has incompletely explored the genotypic and phenotypic space of its possibilities. This case generates no expectation of convergence to an optimal phenotype or possibility of its prediction. The second, more interesting, class exhibits an evolutionary form of ergodicity—essentially all of the structural space within the constraints of slower evolutionary variables have been sampled; the ergodicity time scale for the system evolution is less than the evolutionary time. In this case, some convergence towards similar optima may be expected for equivalent systems in different species where both possess ergodic evolutionary dynamics. When the fitness maximum is set by physical, rather than co-evolved, constraints, it is additionally possible to make predictions of some properties of the evolved structures and systems. We propose four structures that emerge from evolution within genotypes whose fitness is induced from their phenotypes. Together, these result in an exponential speeding up of evolution, when compared with complete exploration of genomic space. We illustrate a possible case of application and a prediction of convergence together with attaining a physical fitness optimum in the case of invertebrate compound eye resolution. PMID:26640648

Are there ergodic limits to evolution? Ergodic exploration of genome space and convergence.

PubMed

McLeish, Tom C B

2015-12-06

We examine the analogy between evolutionary dynamics and statistical mechanics to include the fundamental question of ergodicity-the representative exploration of the space of possible states (in the case of evolution this is genome space). Several properties of evolutionary dynamics are identified that allow a generalization of the ergodic dynamics, familiar in dynamical systems theory, to evolution. Two classes of evolved biological structure then arise, differentiated by the qualitative duration of their evolutionary time scales. The first class has an ergodicity time scale (the time required for representative genome exploration) longer than available evolutionary time, and has incompletely explored the genotypic and phenotypic space of its possibilities. This case generates no expectation of convergence to an optimal phenotype or possibility of its prediction. The second, more interesting, class exhibits an evolutionary form of ergodicity-essentially all of the structural space within the constraints of slower evolutionary variables have been sampled; the ergodicity time scale for the system evolution is less than the evolutionary time. In this case, some convergence towards similar optima may be expected for equivalent systems in different species where both possess ergodic evolutionary dynamics. When the fitness maximum is set by physical, rather than co-evolved, constraints, it is additionally possible to make predictions of some properties of the evolved structures and systems. We propose four structures that emerge from evolution within genotypes whose fitness is induced from their phenotypes. Together, these result in an exponential speeding up of evolution, when compared with complete exploration of genomic space. We illustrate a possible case of application and a prediction of convergence together with attaining a physical fitness optimum in the case of invertebrate compound eye resolution.

Mean-Potential Law in Evolutionary Games.

PubMed

Nałęcz-Jawecki, Paweł; Miękisz, Jacek

2018-01-12

The Letter presents a novel way to connect random walks, stochastic differential equations, and evolutionary game theory. We introduce a new concept of a potential function for discrete-space stochastic systems. It is based on a correspondence between one-dimensional stochastic differential equations and random walks, which may be exact not only in the continuous limit but also in finite-state spaces. Our method is useful for computation of fixation probabilities in discrete stochastic dynamical systems with two absorbing states. We apply it to evolutionary games, formulating two simple and intuitive criteria for evolutionary stability of pure Nash equilibria in finite populations. In particular, we show that the 1/3 law of evolutionary games, introduced by Nowak et al. [Nature, 2004], follows from a more general mean-potential law.

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.

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.

Adaptive evolution of body size subject to indirect effect in trophic cascade system.

PubMed

Wang, Xin; Fan, Meng; Hao, Lina

2017-09-01

Trophic cascades represent a classic example of indirect effect and are wide-spread in nature. Their ecological impact are well established, but the evolutionary consequences have received even less theoretical attention. We theoretically and numerically investigate the trait (i.e., body size of consumer) evolution in response to indirect effect in a trophic cascade system. By applying the quantitative trait evolutionary theory and the adaptive dynamic theory, we formulate and explore two different types of eco-evolutionary resource-consumer-predator trophic cascade model. First, an eco-evolutionary model incorporating the rapid evolution is formulated to investigate the effect of rapid evolution of the consumer's body size, and to explore the impact of density-mediate indirect effect on the population dynamics and trait dynamics. Next, by employing the adaptive dynamic theory, a long-term evolutionary model of consumer body size is formulated to evaluate the effect of long-term evolution on the population dynamics and the effect of trait-mediate indirect effect. Those models admit rich dynamics that has not been observed yet in empirical studies. It is found that, both in the trait-mediated and density-mediated system, the body size of consumer in predator-consumer-resource interaction (indirect effect) evolves smaller than that in consumer-resource and predator-consumer interaction (direct effect). Moreover, in the density-mediated system, we found that the evolution of consumer body size contributes to avoiding consumer extinction (i.e., evolutionary rescue). The trait-mediate and density-mediate effects may produce opposite evolutionary response. This study suggests that the trophic cascade indirect effect affects consumer evolution, highlights a more comprehensive mechanistic understanding of the intricate interplay between ecological and evolutionary force. The modeling approaches provide avenue for study on indirect effects from an evolutionary perspective. Copyright © 2017 Elsevier B.V. All rights reserved.

J.A. Schumpeter and T.B. Veblen on economic evolution: the dichotomy between statics and dynamics

PubMed Central

Schütz, Marlies; Rainer, Andreas

2016-01-01

Abstract At present, the discussion on the dichotomy between statics and dynamics is resolved by concentrating on its mathematical meaning. Yet, a simple formalisation masks the underlying methodological discussion. Overcoming this limitation, the paper discusses Schumpeter's and Veblen's viewpoint on dynamic economic systems as systems generating change from within. It contributes to an understanding on their ideas of how economics could become an evolutionary science and on their contributions to elaborate an evolutionary economics. It confronts Schumpeter's with Veblen's perspective on evolutionary economics and provides insight into their evolutionary economic theorising by discussing their ideas on the evolution of capitalism. PMID:28057981

Magnetic fusion commercial power plants

NASA Astrophysics Data System (ADS)

Sheffield, J.

Toroidal magnetic systems present the best opportunity to make a commercial fusion power plant. They offer potential solutions to the main requirements that confront a power plant designer. An ideal system may be postulated in which the coils are a very small part of the cost, and the cost stems primarily from the inescapable components: minimal plasma heating (and sustaining system), tritium breeding blanket, shield, particle input, removal and treatment system, heat transfer system, generators, buildings, and balance of plant. No present system meets the ideal standards; however, toroidal systems contain among them the elements required. Consequently, a logical program may be based upon an evolutionary development, building on the contributions of the tokamak, which has been the mainline of research for a number of years.

The future orientation of constructive memory: an evolutionary perspective on therapeutic hypnosis and brief psychotherapy.

PubMed

Rossi, Ernest; Erickson-Klein, Roxanna; Rossi, Kathryn

2008-04-01

We explore a new distinction between the future, prospective memory system being investigated in current neuroscience and the past, retrospective memory system, which was the original theoretical foundation of therapeutic hypnosis, classical psychoanalysis, and psychotherapy. We then generalize a current evolutionary theory of sleep and dreaming, which focuses on the future, prospective memory system, to conceptualize a new evolutionary perspective on therapeutic hypnosis and brief psychotherapy. The implication of current neuroscience research is that activity-dependent gene expression and brain plasticity are the psychobiological basis of adaptive behavior, consciousness, and creativity in everyday life as well as psychotherapy. We summarize a case illustrating how this evolutionary perspective can be used to quickly resolve problems with past obstructive procrastination in school to facilitate current and future academic success.

Why an extended evolutionary synthesis is necessary

PubMed Central

2017-01-01

Since the last major theoretical integration in evolutionary biology—the modern synthesis (MS) of the 1940s—the biosciences have made significant advances. The rise of molecular biology and evolutionary developmental biology, the recognition of ecological development, niche construction and multiple inheritance systems, the ‘-omics’ revolution and the science of systems biology, among other developments, have provided a wealth of new knowledge about the factors responsible for evolutionary change. Some of these results are in agreement with the standard theory and others reveal different properties of the evolutionary process. A renewed and extended theoretical synthesis, advocated by several authors in this issue, aims to unite pertinent concepts that emerge from the novel fields with elements of the standard theory. The resulting theoretical framework differs from the latter in its core logic and predictive capacities. Whereas the MS theory and its various amendments concentrate on genetic and adaptive variation in populations, the extended framework emphasizes the role of constructive processes, ecological interactions and systems dynamics in the evolution of organismal complexity as well as its social and cultural conditions. Single-level and unilinear causation is replaced by multilevel and reciprocal causation. Among other consequences, the extended framework overcomes many of the limitations of traditional gene-centric explanation and entails a revised understanding of the role of natural selection in the evolutionary process. All these features stimulate research into new areas of evolutionary biology. PMID:28839929

Evolutionary Science as a Method to Facilitate Higher Level Thinking and Reasoning in Medical Training.

PubMed

Graves, Joseph L; Reiber, Chris; Thanukos, Anna; Hurtado, Magdalena; Wolpaw, Terry

2016-10-15

Evolutionary science is indispensable for understanding biological processes. Effective medical treatment must be anchored in sound biology. However, currently the insights available from evolutionary science are not adequately incorporated in either pre-medical or medical school curricula. To illuminate how evolution may be helpful in these areas, examples in which the insights of evolutionary science are already improving medical treatment and ways in which evolutionary reasoning can be practiced in the context of medicine are provided. In order to facilitate the learning of evolutionary principles, concepts derived from evolutionary science that medical students and professionals should understand are outlined. These concepts are designed to be authoritative and at the same time easily accessible for anyone with the general biological knowledge of a first-year medical student. Thus we conclude that medical practice informed by evolutionary principles will be more effective and lead to better patient outcomes.Furthermore, it is argued that evolutionary medicine complements general medical training because it provides an additional means by which medical students can practice the critical thinking skills that will be important in their future practice. We argue that core concepts from evolutionary science have the potential to improve critical thinking and facilitate more effective learning in medical training. © The Author(s) 2016. Published by Oxford University Press on behalf of the Foundation for Evolution, Medicine, and Public Health.

NASA research in aircraft propulsion

NASA Technical Reports Server (NTRS)

Beheim, M. A.

1982-01-01

A broad overview of the scope of research presently being supported by NASA in aircraft propulsion is presented with emphasis on Lewis Research Center activities related to civil air transports, CTOL and V/STOL systems. Aircraft systems work is performed to identify the requirements for the propulsion system that enhance the mission capabilities of the aircraft. This important source of innovation and creativity drives the direction of propulsion research. In a companion effort, component research of a generic nature is performed to provide a better basis for design and provides an evolutionary process for technological growth that increases the capabilities of all types of aircraft. Both are important.

Reconstructing evolutionary trees in parallel for massive sequences.

PubMed

Zou, Quan; Wan, Shixiang; Zeng, Xiangxiang; Ma, Zhanshan Sam

2017-12-14

Building the evolutionary trees for massive unaligned DNA sequences is challenging and crucial. However, reconstructing evolutionary tree for ultra-large sequences is hard. Massive multiple sequence alignment is also challenging and time/space consuming. Hadoop and Spark are developed recently, which bring spring light for the classical computational biology problems. In this paper, we tried to solve the multiple sequence alignment and evolutionary reconstruction in parallel. HPTree, which is developed in this paper, can deal with big DNA sequence files quickly. It works well on the >1GB files, and gets better performance than other evolutionary reconstruction tools. Users could use HPTree for reonstructing evolutioanry trees on the computer clusters or cloud platform (eg. Amazon Cloud). HPTree could help on population evolution research and metagenomics analysis. In this paper, we employ the Hadoop and Spark platform and design an evolutionary tree reconstruction software tool for unaligned massive DNA sequences. Clustering and multiple sequence alignment are done in parallel. Neighbour-joining model was employed for the evolutionary tree building. We opened our software together with source codes via http://lab.malab.cn/soft/HPtree/ .

An evolutionary perspective on health psychology: new approaches and applications.

PubMed

Tybur, Joshua M; Bryan, Angela D; Hooper, Ann E Caldwell

2012-12-20

Although health psychologists' efforts to understand and promote health are most effective when guided by theory, health psychology has not taken full advantage of theoretical insights provided by evolutionary psychology. Here, we argue that evolutionary perspectives can fruitfully inform strategies for addressing some of the challenges facing health psychologists. Evolutionary psychology's emphasis on modular, functionally specialized psychological systems can inform approaches to understanding the myriad behaviors grouped under the umbrella of "health," as can theoretical perspectives used by evolutionary anthropologists, biologists, and psychologists (e.g., Life History Theory). We detail some early investigations into evolutionary health psychology, and we provide suggestions for directions for future research.

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.

Systems metabolic engineering for chemicals and materials.

PubMed

Lee, Jeong Wook; Kim, Tae Yong; Jang, Yu-Sin; Choi, Sol; Lee, Sang Yup

2011-08-01

Metabolic engineering has contributed significantly to the enhanced production of various value-added and commodity chemicals and materials from renewable resources in the past two decades. Recently, metabolic engineering has been upgraded to the systems level (thus, systems metabolic engineering) by the integrated use of global technologies of systems biology, fine design capabilities of synthetic biology, and rational-random mutagenesis through evolutionary engineering. By systems metabolic engineering, production of natural and unnatural chemicals and materials can be better optimized in a multiplexed way on a genome scale, with reduced time and effort. Here, we review the recent trends in systems metabolic engineering for the production of chemicals and materials by presenting general strategies and showcasing representative examples. Copyright © 2011 Elsevier Ltd. All rights reserved.

Reticulate evolution and the human past: an anthropological perspective.

PubMed

Winder, Isabelle C; Winder, Nick P

2014-01-01

The evidence is mounting that reticulate (web-like) evolution has shaped the biological histories of many macroscopic plants and animals, including non-human primates closely related to Homo sapiens, but the implications of this non-hierarchical evolution for anthropological enquiry are not yet fully understood. When they are understood, the result may be a paradigm shift in evolutionary anthropology. This paper reviews the evidence for reticulated evolution in the non-human primates and human lineage. Then it makes the case for extrapolating this sort of patterning to Homo sapiens and other hominins and explores the implications this would have for research design, method and understandings of evolution in anthropology. Reticulation was significant in human evolutionary history and continues to influence societies today. Anthropologists and human scientists-whether working on ancient or modern populations-thus need to consider the implications of non-hierarchic evolution, particularly where molecular clocks, mathematical models and simplifying assumptions about evolutionary processes are used. This is not just a problem for palaeoanthropology. The simple fact of different mating systems among modern human groups, for example, may demand that more attention is paid to the potential for complexity in human genetic and cultural histories.

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

Genetic Architecture of Hybrid Male Sterility in Drosophila: Analysis of Intraspecies Variation for Interspecies Isolation

PubMed Central

Reed, Laura K.; LaFlamme, Brooke A.; Markow, Therese A.

2008-01-01

Background The genetic basis of postzygotic isolation is a central puzzle in evolutionary biology. Evolutionary forces causing hybrid sterility or inviability act on the responsible genes while they still are polymorphic, thus we have to study these traits as they arise, before isolation is complete. Methodology/Principal Findings Isofemale strains of D. mojavensis vary significantly in their production of sterile F1 sons when females are crossed to D. arizonae males. We took advantage of the intraspecific polymorphism, in a novel design, to perform quantitative trait locus (QTL) mapping analyses directly on F1 hybrid male sterility itself. We found that the genetic architecture of the polymorphism for hybrid male sterility (HMS) in the F1 is complex, involving multiple QTL, epistasis, and cytoplasmic effects. Conclusions/Significance The role of extensive intraspecific polymorphism, multiple QTL, and epistatic interactions in HMS in this young species pair shows that HMS is arising as a complex trait in this system. Directional selection alone would be unlikely to maintain polymorphism at multiple loci, thus we hypothesize that directional selection is unlikely to be the only evolutionary force influencing postzygotic isolation. PMID:18728782

Fitness landscapes, heuristics and technological paradigms: A critique on random search models in evolutionary economics

NASA Astrophysics Data System (ADS)

Frenken, Koen

2001-06-01

The biological evolution of complex organisms, in which the functioning of genes is interdependent, has been analyzed as "hill-climbing" on NK fitness landscapes through random mutation and natural selection. In evolutionary economics, NK fitness landscapes have been used to simulate the evolution of complex technological systems containing elements that are interdependent in their functioning. In these models, economic agents randomly search for new technological design by trial-and-error and run the risk of ending up in sub-optimal solutions due to interdependencies between the elements in a complex system. These models of random search are legitimate for reasons of modeling simplicity, but remain limited as these models ignore the fact that agents can apply heuristics. A specific heuristic is one that sequentially optimises functions according to their ranking by users of the system. To model this heuristic, a generalized NK-model is developed. In this model, core elements that influence many functions can be distinguished from peripheral elements that affect few functions. The concept of paradigmatic search can then be analytically defined as search that leaves core elements in tact while concentrating on improving functions by mutation of peripheral elements.

Population genetics inside a cell: Mutations and mitochondrial genome maintenance

NASA Astrophysics Data System (ADS)

Goyal, Sidhartha; Shraiman, Boris; Gottschling, Dan

2012-02-01

In realistic ecological and evolutionary systems natural selection acts on multiple levels, i.e. it acts on individuals as well as on collection of individuals. An understanding of evolutionary dynamics of such systems is limited in large part due to the lack of experimental systems that can challenge theoretical models. Mitochondrial genomes (mtDNA) are subjected to selection acting on cellular as well as organelle levels. It is well accepted that mtDNA in yeast Saccharomyces cerevisiae is unstable and can degrade over time scales comparable to yeast cell division time. We utilize a recent technology designed in Gottschling lab to extract DNA from populations of aged yeast cells and deep sequencing to characterize mtDNA variation in a population of young and old cells. In tandem, we developed a stochastic model that includes the essential features of mitochondrial biology that provides a null model for expected mtDNA variation. Overall, we find approximately 2% of the polymorphic loci that show significant increase in frequency as cells age providing direct evidence for organelle level selection. Such quantitative study of mtDNA dynamics is absolutely essential to understand the propagation of mtDNA mutations linked to a spectrum of age-related diseases in humans.

Computer-automated evolution of an X-band antenna for NASA's Space Technology 5 mission.

PubMed

Hornby, Gregory S; Lohn, Jason D; Linden, Derek S

2011-01-01

Whereas the current practice of designing antennas by hand is severely limited because it is both time and labor intensive and requires a significant amount of domain knowledge, evolutionary algorithms can be used to search the design space and automatically find novel antenna designs that are more effective than would otherwise be developed. Here we present our work in using evolutionary algorithms to automatically design an X-band antenna for NASA's Space Technology 5 (ST5) spacecraft. Two evolutionary algorithms were used: the first uses a vector of real-valued parameters and the second uses a tree-structured generative representation for constructing the antenna. The highest-performance antennas from both algorithms were fabricated and tested and both outperformed a hand-designed antenna produced by the antenna contractor for the mission. Subsequent changes to the spacecraft orbit resulted in a change in requirements for the spacecraft antenna. By adjusting our fitness function we were able to rapidly evolve a new set of antennas for this mission in less than a month. One of these new antenna designs was built, tested, and approved for deployment on the three ST5 spacecraft, which were successfully launched into space on March 22, 2006. This evolved antenna design is the first computer-evolved antenna to be deployed for any application and is the first computer-evolved hardware in space.

Applying Evolutionary Anthropology

PubMed Central

Gibson, Mhairi A; Lawson, David W

2015-01-01

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

Applying evolutionary anthropology.

PubMed

Gibson, Mhairi A; Lawson, David W

2015-01-01

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

Comparing marine and terrestrial ecosystems: Implications for the design of coastal marine reserves

USGS Publications Warehouse

Carr, M.H.; Neigel, J.E.; Estes, J.A.; Andelman, S.; Warner, R.R.; Largier, J. L.

2003-01-01

Concepts and theory for the design and application of terrestrial reserves is based on our understanding of environmental, ecological, and evolutionary processes responsible for biological diversity and sustainability of terrestrial ecosystems and how humans have influenced these processes. How well this terrestrial-based theory can be applied toward the design and application of reserves in the coastal marine environment depends, in part, on the degree of similarity between these systems. Several marked differences in ecological and evolutionary processes exist between marine and terrestrial ecosystems as ramifications of fundamental differences in their physical environments (i.e., the relative prevalence of air and water) and contemporary patterns of human impacts. Most notably, the great extent and rate of dispersal of nutrients, materials, holoplanktonic organisms, and reproductive propagules of benthic organisms expand scales of connectivity among near-shore communities and ecosystems. Consequently, the "openness" of marine populations, communities, and ecosystems probably has marked influences on their spatial, genetic, and trophic structures and dynamics in ways experienced by only some terrestrial species. Such differences appear to be particularly significant for the kinds of organisms most exploited and targeted for protection in coastal marine ecosystems (fishes and macroinvertebrates). These and other differences imply some unique design criteria and application of reserves in the marine environment. In explaining the implications of these differences for marine reserve design and application, we identify many of the environmental and ecological processes and design criteria necessary for consideration in the development of the analytical approaches developed elsewhere in this Special Issue.

Modeling the stylized facts in finance through simple nonlinear adaptive systems

PubMed Central

Hommes, Cars H.

2002-01-01

Recent work on adaptive systems for modeling financial markets is discussed. Financial markets are viewed as evolutionary systems between different, competing trading strategies. Agents are boundedly rational in the sense that they tend to follow strategies that have performed well, according to realized profits or accumulated wealth, in the recent past. Simple technical trading rules may survive evolutionary competition in a heterogeneous world where prices and beliefs co-evolve over time. Evolutionary models can explain important stylized facts, such as fat tails, clustered volatility, and long memory, of real financial series. PMID:12011401

Signatures of selection acting on the innate immunity gene Toll-like receptor 2 (TLR2) during the evolutionary history of rodents.

PubMed

Tschirren, B; Råberg, L; Westerdahl, H

2011-06-01

Patterns of selection acting on immune defence genes have recently been the focus of considerable interest. Yet, when it comes to vertebrates, studies have mainly focused on the acquired branch of the immune system. Consequently, the direction and strength of selection acting on genes of the vertebrate innate immune defence remain poorly understood. Here, we present a molecular analysis of selection on an important receptor of the innate immune system of vertebrates, the Toll-like receptor 2 (TLR2), across 17 rodent species. Although purifying selection was the prevalent evolutionary force acting on most parts of the rodent TLR2, we found that codons in close proximity to pathogen-binding and TLR2-TLR1 heterodimerization sites have been subject to positive selection. This indicates that parasite-mediated selection is not restricted to acquired immune system genes like the major histocompatibility complex, but also affects innate defence genes. To obtain a comprehensive understanding of evolutionary processes in host-parasite systems, both innate and acquired immunity thus need to be considered. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

Integrated Controls-Structures Design Methodology: Redesign of an Evolutionary Test Structure

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Gupta, Sandeep; Elliot, Kenny B.; Joshi, Suresh M.

1997-01-01

An optimization-based integrated controls-structures design methodology for a class of flexible space structures is described, and the phase-0 Controls-Structures-Integration evolutionary model, a laboratory testbed at NASA Langley, is redesigned using this integrated design methodology. The integrated controls-structures design is posed as a nonlinear programming problem to minimize the control effort required to maintain a specified line-of-sight pointing performance, under persistent white noise disturbance. Static and dynamic dissipative control strategies are employed for feedback control, and parameters of these controllers are considered as the control design variables. Sizes of strut elements in various sections of the CEM are used as the structural design variables. Design guides for the struts are developed and employed in the integrated design process, to ensure that the redesigned structure can be effectively fabricated. The superiority of the integrated design methodology over the conventional design approach is demonstrated analytically by observing a significant reduction in the average control power needed to maintain specified pointing performance with the integrated design approach.

Space Station

NASA Image and Video Library

1982-01-01

McDornel Douglas performed an Evolutionary Space Platform Concept Study for the Marshall Space Flight Center in the early 1980's. The 10-month study was designed to define, evaluate, and compare approaches and concepts for evolving unmanned and manned capability platforms beyond the then current space platform concepts to an evolutionary goal of establishing a permanent-manned presence in space.

Questioning Clerkship: Applying Popper's Evolutionary Analysis of Learning to Medical Student Training

ERIC Educational Resources Information Center

Chitpin, Jeremy Sebastian; Chitpin, Stephanie

2017-01-01

Purpose: Through a series of critical discussions on Karl Popper's evolutionary analysis of learning and the non-authoritarian values it promotes, the purpose of this paper is to advocate a Popperian approach for building medical student knowledge. Specifically, it challenges positivist assumptions that permeate the design and management of many…

Using Loop Heat Pipes to Minimize Survival Heater Power for NASA's Evolutionary Xenon Thruster Power Processing Units

NASA Technical Reports Server (NTRS)

Choi, Michael K.

2017-01-01

A thermal design concept of using propylene loop heat pipes to minimize survival heater power for NASA's Evolutionary Xenon Thruster power processing units is presented. It reduces the survival heater power from 183 W to 35 W per power processing unit. The reduction is 81%.

Gender and Evolutionary Theory in Workplace Health Promotion

ERIC Educational Resources Information Center

Björklund, Erika; Wright, Jan

2017-01-01

Objective: Ideas from evolutionary theories are increasingly taken up in health promotion. This article seeks to demonstrate how such a trend has the potential to embed essentialist and limiting stereotypes of women and men in health promotion practice. Design: We draw on material gathered for a larger ethnographic study that examined how…

System 80+{trademark} standard design incorporates radiation protection lessons learned

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

Crom, T.D.; Naugle, C.L.; Turk, R.S.

1995-03-01

Many lessons have been learned from the current generation of nuclear plants in the area of radiation protection. The following paper will outline how the lessons learned have been incorporated into the design and operational philosophy of the System 80+{trademark} Standard Design currently under development by ABB Combustion Engineering (ABB-CE) with support from Duke Engineering and Services, Inc. and Stone and Webster Engineering Corporation in the Balance-of-Plant design. The System 80+{trademark} Standard Design is a complete nuclear power plant for national and international markets, designed in direct response to utility needs for the 1990`s, and scheduled for Nuclear Regulatory Commissionmore » (NRC) Design Certification under the new standardization rule (10 CFR Part 52). System 80+{trademark} is a natural extension of System 80{sup R} technology, an evolutionary change based on proven Nuclear Steam Supply System (NSSS) in operation at Palo Verde in Arizona and under construction at Yonggwang in the Republic of Korea. The System 80+{trademark} Containment and much of the Balance of Plant design is based upon Duke Power Company`s Cherokee Plant, which was partially constructed in the late 1970`s, but, was later canceled (due to rapid declined in electrical load growth). The System 80+{trademark} Standard Design meets the requirements given in the Electric Power Research Institute (EPRI) Advanced Light Water Reactor (ALWR) Requirements Document. One of these requirements is to limit the occupational exposure to 100 person-rem/yr. This paper illustrates how this goal can be achieved through the incorporation of lessons learned, innovative design, and the implementation of a common sense approach to operation and maintenances practices.« less

Formal Darwinism, the individual-as-maximizing-agent analogy and bet-hedging

PubMed Central

Grafen, A.

1999-01-01

The central argument of The origin of species was that mechanical processes (inheritance of features and the differential reproduction they cause) can give rise to the appearance of design. The 'mechanical processes' are now mathematically represented by the dynamic systems of population genetics, and the appearance of design by optimization and game theory in which the individual plays the part of the maximizing agent. Establishing a precise individual-as-maximizing-agent (IMA) analogy for a population-genetics system justifies optimization approaches, and so provides a modern formal representation of the core of Darwinism. It is a hitherto unnoticed implication of recent population-genetics models that, contrary to a decades-long consensus, an IMA analogy can be found in models with stochastic environments (subject to a convexity assumption), in which individuals maximize expected reproductive value. The key is that the total reproductive value of a species must be considered as constant, so therefore reproductive value should always be calculated in relative terms. This result removes a major obstacle from the theoretical challenge to find a unifying framework which establishes the IMA analogy for all of Darwinian biology, including as special cases inclusive fitness, evolutionarily stable strategies, evolutionary life-history theory, age-structured models and sex ratio theory. This would provide a formal, mathematical justification of fruitful and widespread but 'intentional' terms in evolutionary biology, such as 'selfish', 'altruism' and 'conflict'.

Buried treasure: evolutionary perspectives on microbial iron piracy

PubMed Central

Barber, Matthew F.; Elde, Nels C.

2015-01-01

Host-pathogen interactions provide valuable systems for the study of evolutionary genetics and natural selection. The sequestration of essential iron has emerged as a critical innate defense system termed nutritional immunity, leading pathogens to evolve mechanisms of `iron piracy' to scavenge this metal from host proteins. This battle for iron carries numerous consequences not only for host-pathogen evolution, but also microbial community interactions. Here we highlight recent and potential future areas of investigation on the evolutionary implications of microbial iron piracy in relation to molecular arms races, host range, competition, and virulence. Applying evolutionary genetic approaches to the study of microbial iron acquisition could also provide new inroads for understanding and combating infectious disease. PMID:26431675

A Genetic Representation for Evolutionary Fault Recovery in Virtex FPGAs

NASA Technical Reports Server (NTRS)

Lohn, Jason; Larchev, Greg; DeMara, Ronald; Korsmeyer, David (Technical Monitor)

2003-01-01

Most evolutionary approaches to fault recovery in FPGAs focus on evolving alternative logic configurations as opposed to evolving the intra-cell routing. Since the majority of transistors in a typical FPGA are dedicated to interconnect, nearly 80% according to one estimate, evolutionary fault-recovery systems should benefit hy accommodating routing. In this paper, we propose an evolutionary fault-recovery system employing a genetic representation that takes into account both logic and routing configurations. Experiments were run using a software model of the Xilinx Virtex FPGA. We report that using four Virtex combinational logic blocks, we were able to evolve a 100% accurate quadrature decoder finite state machine in the presence of a stuck-at-zero fault.

Development of an Evolutionary Algorithm for the ab Initio Discovery of Two-Dimensional Materials

NASA Astrophysics Data System (ADS)

Revard, Benjamin Charles

Crystal structure prediction is an important first step on the path toward computational materials design. Increasingly robust methods have become available in recent years for computing many materials properties, but because properties are largely a function of crystal structure, the structure must be known before these methods can be brought to bear. In addition, structure prediction is particularly useful for identifying low-energy structures of subperiodic materials, such as two-dimensional (2D) materials, which may adopt unexpected structures that differ from those of the corresponding bulk phases. Evolutionary algorithms, which are heuristics for global optimization inspired by biological evolution, have proven to be a fruitful approach for tackling the problem of crystal structure prediction. This thesis describes the development of an improved evolutionary algorithm for structure prediction and several applications of the algorithm to predict the structures of novel low-energy 2D materials. The first part of this thesis contains an overview of evolutionary algorithms for crystal structure prediction and presents our implementation, including details of extending the algorithm to search for clusters, wires, and 2D materials, improvements to efficiency when running in parallel, improved composition space sampling, and the ability to search for partial phase diagrams. We then present several applications of the evolutionary algorithm to 2D systems, including InP, the C-Si and Sn-S phase diagrams, and several group-IV dioxides. This thesis makes use of the Cornell graduate school's "papers" option. Chapters 1 and 3 correspond to the first-author publications of Refs. [131] and [132], respectively, and chapter 2 will soon be submitted as a first-author publication. The material in chapter 4 is taken from Ref. [144], in which I share joint first-authorship. In this case I have included only my own contributions.

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.

Solving Large-scale Spatial Optimization Problems in Water Resources Management through Spatial Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Wang, J.; Cai, X.

2007-12-01

A water resources system can be defined as a large-scale spatial system, within which distributed ecological system interacts with the stream network and ground water system. Water resources management, the causative factors and hence the solutions to be developed have a significant spatial dimension. This motivates a modeling analysis of water resources management within a spatial analytical framework, where data is usually geo- referenced and in the form of a map. One of the important functions of Geographic information systems (GIS) is to identify spatial patterns of environmental variables. The role of spatial patterns in water resources management has been well established in the literature particularly regarding how to design better spatial patterns for satisfying the designated objectives of water resources management. Evolutionary algorithms (EA) have been demonstrated to be successful in solving complex optimization models for water resources management due to its flexibility to incorporate complex simulation models in the optimal search procedure. The idea of combining GIS and EA motivates the development and application of spatial evolutionary algorithms (SEA). SEA assimilates spatial information into EA, and even changes the representation and operators of EA. In an EA used for water resources management, the mathematical optimization model should be modified to account the spatial patterns; however, spatial patterns are usually implicit, and it is difficult to impose appropriate patterns to spatial data. Also it is difficult to express complex spatial patterns by explicit constraints included in the EA. The GIS can help identify the spatial linkages and correlations based on the spatial knowledge of the problem. These linkages are incorporated in the fitness function for the preference of the compatible vegetation distribution. Unlike a regular GA for spatial models, the SEA employs a special hierarchical hyper-population and spatial genetic operators to represent spatial variables in a more efficient way. The hyper-population consists of a set of populations, which correspond to the spatial distributions of the individual agents (organisms). Furthermore spatial crossover and mutation operators are designed in accordance with the tree representation and then applied to both organisms and populations. This study applies the SEA to a specific problem of water resources management- maximizing the riparian vegetation coverage in accordance with the distributed groundwater system in an arid region. The vegetation coverage is impacted greatly by the nonlinear feedbacks and interactions between vegetation and groundwater and the spatial variability of groundwater. The SEA is applied to search for an optimal vegetation configuration compatible to the groundwater flow. The results from this example demonstrate the effectiveness of the SEA. Extension of the algorithm for other water resources management problems is discussed.

Optimizing RF gun cavity geometry within an automated injector design system

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

Alicia Hofler ,Pavel Evtushenko

2011-03-28

RF guns play an integral role in the success of several light sources around the world, and properly designed and optimized cw superconducting RF (SRF) guns can provide a path to higher average brightness. As the need for these guns grows, it is important to have automated optimization software tools that vary the geometry of the gun cavity as part of the injector design process. This will allow designers to improve existing designs for present installations, extend the utility of these guns to other applications, and develop new designs. An evolutionary algorithm (EA) based system can provide this capability becausemore » EAs can search in parallel a large parameter space (often non-linear) and in a relatively short time identify promising regions of the space for more careful consideration. The injector designer can then evaluate more cavity design parameters during the injector optimization process against the beam performance requirements of the injector. This paper will describe an extension to the APISA software that allows the cavity geometry to be modified as part of the injector optimization and provide examples of its application to existing RF and SRF gun designs.« less

Parallel Evolutionary Optimization for Neuromorphic Network Training

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

Schuman, Catherine D; Disney, Adam; Singh, Susheela

One of the key impediments to the success of current neuromorphic computing architectures is the issue of how best to program them. Evolutionary optimization (EO) is one promising programming technique; in particular, its wide applicability makes it especially attractive for neuromorphic architectures, which can have many different characteristics. In this paper, we explore different facets of EO on a spiking neuromorphic computing model called DANNA. We focus on the performance of EO in the design of our DANNA simulator, and on how to structure EO on both multicore and massively parallel computing systems. We evaluate how our parallel methods impactmore » the performance of EO on Titan, the U.S.'s largest open science supercomputer, and BOB, a Beowulf-style cluster of Raspberry Pi's. We also focus on how to improve the EO by evaluating commonality in higher performing neural networks, and present the result of a study that evaluates the EO performed by Titan.« less

In silico Evolutionary Developmental Neurobiology and the Origin of Natural Language

NASA Astrophysics Data System (ADS)

Szathmáry, Eörs; Szathmáry, Zoltán; Ittzés, Péter; Orbaán, Geroő; Zachár, István; Huszár, Ferenc; Fedor, Anna; Varga, Máté; Számadó, Szabolcs

It is justified to assume that part of our genetic endowment contributes to our language skills, yet it is impossible to tell at this moment exactly how genes affect the language faculty. We complement experimental biological studies by an in silico approach in that we simulate the evolution of neuronal networks under selection for language-related skills. At the heart of this project is the Evolutionary Neurogenetic Algorithm (ENGA) that is deliberately biomimetic. The design of the system was inspired by important biological phenomena such as brain ontogenesis, neuron morphologies, and indirect genetic encoding. Neuronal networks were selected and were allowed to reproduce as a function of their performance in the given task. The selected neuronal networks in all scenarios were able to solve the communication problem they had to face. The most striking feature of the model is that it works with highly indirect genetic encoding--just as brains do.

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.

A controllable sensor management algorithm capable of learning

NASA Astrophysics Data System (ADS)

Osadciw, Lisa A.; Veeramacheneni, Kalyan K.

2005-03-01

Sensor management technology progress is challenged by the geographic space it spans, the heterogeneity of the sensors, and the real-time timeframes within which plans controlling the assets are executed. This paper presents a new sensor management paradigm and demonstrates its application in a sensor management algorithm designed for a biometric access control system. This approach consists of an artificial intelligence (AI) algorithm focused on uncertainty measures, which makes the high level decisions to reduce uncertainties and interfaces with the user, integrated cohesively with a bottom up evolutionary algorithm, which optimizes the sensor network"s operation as determined by the AI algorithm. The sensor management algorithm presented is composed of a Bayesian network, the AI algorithm component, and a swarm optimization algorithm, the evolutionary algorithm. Thus, the algorithm can change its own performance goals in real-time and will modify its own decisions based on observed measures within the sensor network. The definition of the measures as well as the Bayesian network determine the robustness of the algorithm and its utility in reacting dynamically to changes in the global system.

Evolutionary Agent-based Models to design distributed water management strategies

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Evolution and social epidemiology.

PubMed

Nishi, Akihiro

2015-11-01

Evolutionary biology, which aims to explain the dynamic process of shaping the diversity of life, has not yet significantly affected thinking in social epidemiology. Current challenges in social epidemiology include understanding how social exposures can affect our biology, explaining the dynamics of society and health, and designing better interventions that are mindful of the impact of exposures during critical periods. I review how evolutionary concepts and tools, such as fitness gradient in cultural evolution, evolutionary game theory, and contemporary evolution in cancer, can provide helpful insights regarding social epidemiology. Copyright © 2015 Elsevier Ltd. All rights reserved.

Application of USNRC NUREG/CR-6661 and draft DG-1108 to evolutionary and advanced reactor designs

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

Chang 'Apollo', Chen

2006-07-01

For the seismic design of evolutionary and advanced nuclear reactor power plants, there are definite financial advantages in the application of USNRC NUREG/CR-6661 and draft Regulatory Guide DG-1108. NUREG/CR-6661, 'Benchmark Program for the Evaluation of Methods to Analyze Non-Classically Damped Coupled Systems', was by Brookhaven National Laboratory (BNL) for the USNRC, and Draft Regulatory Guide DG-1108 is the proposed revision to the current Regulatory Guide (RG) 1.92, Revision 1, 'Combining Modal Responses and Spatial Components in Seismic Response Analysis'. The draft Regulatory Guide DG-1108 is available at http://members.cox.net/apolloconsulting, which also provides a link to the USNRC ADAMS site to searchmore » for NUREG/CR-6661 in text file or image file. The draft Regulatory Guide DG-1108 removes unnecessary conservatism in the modal combinations for closely spaced modes in seismic response spectrum analysis. Its application will be very helpful in coupled seismic analysis for structures and heavy equipment to reduce seismic responses and in piping system seismic design. In the NUREG/CR-6661 benchmark program, which investigated coupled seismic analysis of structures and equipment or piping systems with different damping values, three of the four participants applied the complex mode solution method to handle different damping values for structures, equipment, and piping systems. The fourth participant applied the classical normal mode method with equivalent weighted damping values to handle differences in structural, equipment, and piping system damping values. Coupled analysis will reduce the equipment responses when equipment, or piping system and structure are in or close to resonance. However, this reduction in responses occurs only if the realistic DG-1108 modal response combination method is applied, because closely spaced modes will be produced when structure and equipment or piping systems are in or close to resonance. Otherwise, the conservatism in the current Regulatory Guide 1.92, Revision 1, will overshadow the advantage of coupled analysis. All four participants applied the realistic modal combination method of DG-1108. Consequently, more realistic and reduced responses were obtained. (authors)« less

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

NASA Technical Reports Server (NTRS)

Rai, Man Mohan

2006-01-01

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more flexible than other methods in dealing with design in the context of both steady and unsteady flows, partial and complete data sets, combined experimental and numerical data, inclusion of various constraints and rules of thumb, and other issues that characterize the aerodynamic design process. Neural networks provide a natural framework within which a succession of numerical solutions of increasing fidelity, incorporating more realistic flow physics, can be represented and utilized for optimization. Neural networks also offer an excellent framework for multiple-objective and multi-disciplinary design optimization. Simulation tools from various disciplines can be integrated within this framework and rapid trade-off studies involving one or many disciplines can be performed. The prospect of combining neural network based optimization methods and evolutionary algorithms to obtain a hybrid method with the best properties of both methods will be included in this presentation. Achieving solution diversity and accurate convergence to the exact Pareto front in multiple objective optimization usually requires a significant computational effort with evolutionary algorithms. In this lecture we will also explore the possibility of using neural networks to obtain estimates of the Pareto optimal front using non-dominated solutions generated by DE as training data. Neural network estimators have the potential advantage of reducing the number of function evaluations required to obtain solution accuracy and diversity, thus reducing cost to design.

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

PubMed

Walker, Jeffrey A

2010-12-01

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

Evolutionary genetics of plant adaptation.

PubMed

Anderson, Jill T; Willis, John H; Mitchell-Olds, Thomas

2011-07-01

Plants provide unique opportunities to study the mechanistic basis and evolutionary processes of adaptation to diverse environmental conditions. Complementary laboratory and field experiments are important for testing hypotheses reflecting long-term ecological and evolutionary history. For example, these approaches can infer whether local adaptation results from genetic tradeoffs (antagonistic pleiotropy), where native alleles are best adapted to local conditions, or if local adaptation is caused by conditional neutrality at many loci, where alleles show fitness differences in one environment, but not in a contrasting environment. Ecological genetics in natural populations of perennial or outcrossing plants can also differ substantially from model systems. In this review of the evolutionary genetics of plant adaptation, we emphasize the importance of field studies for understanding the evolutionary dynamics of model and nonmodel systems, highlight a key life history trait (flowering time) and discuss emerging conservation issues. Copyright © 2011 Elsevier Ltd. All rights reserved.

The Neural Systems of Forgiveness: An Evolutionary Psychological Perspective

PubMed Central

Billingsley, Joseph; Losin, Elizabeth A. R.

2017-01-01

Evolution-minded researchers posit that the suite of human cognitive adaptations may include forgiveness systems. According to these researchers, forgiveness systems regulate interpersonal motivation toward a transgressor in the wake of harm by weighing multiple factors that influence both the potential gains of future interaction with the transgressor and the likelihood of future harm. Although behavioral research generally supports this evolutionary model of forgiveness, the model’s claims have not been examined with available neuroscience specifically in mind, nor has recent neuroscientific research on forgiveness generally considered the evolutionary literature. The current review aims to help bridge this gap by using evolutionary psychology and cognitive neuroscience to mutually inform and interrogate one another. We briefly summarize the evolutionary research on forgiveness, then review recent neuroscientific findings on forgiveness in light of the evolutionary model. We emphasize neuroscientific research that links desire for vengeance to reward-based areas of the brain, that singles out prefrontal areas likely associated with inhibition of vengeful feelings, and that correlates the activity of a theory-of-mind network with assessments of the intentions and blameworthiness of those who commit harm. In addition, we identify gaps in the existing neuroscientific literature, and propose future research directions that might address them, at least in part. PMID:28539904

Design and analysis of radiometric instruments using high-level numerical models and genetic algorithms

NASA Astrophysics Data System (ADS)

Sorensen, Ira Joseph

A primary objective of the effort reported here is to develop a radiometric instrument modeling environment to provide complete end-to-end numerical models of radiometric instruments, integrating the optical, electro-thermal, and electronic systems. The modeling environment consists of a Monte Carlo ray-trace (MCRT) model of the optical system coupled to a transient, three-dimensional finite-difference electrothermal model of the detector assembly with an analytic model of the signal-conditioning circuitry. The environment provides a complete simulation of the dynamic optical and electrothermal behavior of the instrument. The modeling environment is used to create an end-to-end model of the CERES scanning radiometer, and its performance is compared to the performance of an operational CERES total channel as a benchmark. A further objective of this effort is to formulate an efficient design environment for radiometric instruments. To this end, the modeling environment is then combined with evolutionary search algorithms known as genetic algorithms (GA's) to develop a methodology for optimal instrument design using high-level radiometric instrument models. GA's are applied to the design of the optical system and detector system separately and to both as an aggregate function with positive results.

An evolutionary advantage for extravagant honesty.

PubMed

Bullock, Seth

2012-01-07

A game-theoretic model of handicap signalling over a pair of signalling channels is introduced in order to determine when one channel has an evolutionary advantage over the other. The stability conditions for honest handicap signalling are presented for a single channel and are shown to conform with the results of prior handicap signalling models. Evolutionary simulations are then used to show that, for a two-channel system in which honest signalling is possible on both channels, the channel featuring larger advertisements at equilibrium is favoured by evolution. This result helps to address a significant tension in the handicap principle literature. While the original theory was motivated by the prevalence of extravagant natural signalling, contemporary models have demonstrated that it is the cost associated with deception that stabilises honesty, and that the honest signals exhibited at equilibrium need not be extravagant at all. The current model suggests that while extravagant and wasteful signals are not required to ensure a signalling system's evolutionary stability, extravagant signalling systems may enjoy an advantage in terms of evolutionary attainability. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

Mankamo, T.; Kim, I.S.; Yang, Ji Wu

Failures in the auxiliary feedwater (AFW) system of pressurized water reactors (PWRs) are considered to involve substantial risk whether a decision is made to either continue power operation while repair is being done, or to shut down the plant to undertake repairs. Technical specification action requirements usually require immediate plant shutdown in the case of multiple failures in the system (in some cases, immediate repair of one train is required when all AFW trains fail). This paper presents a probabilistic risk assessment-based method to quantitatively evaluate and compare both the risks of continued power operation and of shutting the plantmore » down, given known failures in the system. The method is applied to the AFW system for four different PWRs. Results show that the risk of continued power operation and plant shutdown both are substantial, but the latter is larger than the former over the usual repair time. This was proven for four plants with different designs: two operating Westinghouse plants, one operating Asea-Brown Boveri Combustion Engineering Plant, and one of evolutionary design. The method can be used to analyze individual plant design and to improve AFW action requirements using risk-informed evaluations.« less

Emergent 1d Ising Behavior in AN Elementary Cellular Automaton Model

NASA Astrophysics Data System (ADS)

Kassebaum, Paul G.; Iannacchione, Germano S.

The fundamental nature of an evolving one-dimensional (1D) Ising model is investigated with an elementary cellular automaton (CA) simulation. The emergent CA simulation employs an ensemble of cells in one spatial dimension, each cell capable of two microstates interacting with simple nearest-neighbor rules and incorporating an external field. The behavior of the CA model provides insight into the dynamics of coupled two-state systems not expressible by exact analytical solutions. For instance, state progression graphs show the causal dynamics of a system through time in relation to the system's entropy. Unique graphical analysis techniques are introduced through difference patterns, diffusion patterns, and state progression graphs of the 1D ensemble visualizing the evolution. All analyses are consistent with the known behavior of the 1D Ising system. The CA simulation and new pattern recognition techniques are scalable (in both dimension, complexity, and size) and have many potential applications such as complex design of materials, control of agent systems, and evolutionary mechanism design.

Evolutionary growth for Space Station Freedom electrical power system

NASA Technical Reports Server (NTRS)

Marshall, Matthew Fisk; Mclallin, Kerry; Zernic, Mike

1989-01-01

Over an operational lifetime of at least 30 yr, Space Station Freedom will encounter increased Space Station user requirements and advancing technologies. The Space Station electrical power system is designed with the flexibility to accommodate these emerging technologies and expert systems and is being designed with the necessary software hooks and hardware scars to accommodate increased growth demand. The electrical power system is planned to grow from the initial 75 kW up to 300 kW. The Phase 1 station will utilize photovoltaic arrays to produce the electrical power; however, for growth to 300 kW, solar dynamic power modules will be utilized. Pairs of 25 kW solar dynamic power modules will be added to the station to reach the power growth level. The addition of solar dynamic power in the growth phase places constraints in the initial Space Station systems such as guidance, navigation, and control, external thermal, truss structural stiffness, computational capabilities and storage, which must be planned-in, in order to facilitate the addition of the solar dynamic modules.

Designing a training tool for imaging mental models

NASA Technical Reports Server (NTRS)

Dede, Christopher J.; Jayaram, Geetha

1990-01-01

The training process can be conceptualized as the student acquiring an evolutionary sequence of classification-problem solving mental models. For example a physician learns (1) classification systems for patient symptoms, diagnostic procedures, diseases, and therapeutic interventions and (2) interrelationships among these classifications (e.g., how to use diagnostic procedures to collect data about a patient's symptoms in order to identify the disease so that therapeutic measures can be taken. This project developed functional specifications for a computer-based tool, Mental Link, that allows the evaluative imaging of such mental models. The fundamental design approach underlying this representational medium is traversal of virtual cognition space. Typically intangible cognitive entities and links among them are visible as a three-dimensional web that represents a knowledge structure. The tool has a high degree of flexibility and customizability to allow extension to other types of uses, such a front-end to an intelligent tutoring system, knowledge base, hypermedia system, or semantic network.

Periodic table of virus capsids: implications for natural selection and design.

PubMed

Mannige, Ranjan V; Brooks, Charles L

2010-03-04

For survival, most natural viruses depend upon the existence of spherical capsids: protective shells of various sizes composed of protein subunits. So far, general evolutionary pressures shaping capsid design have remained elusive, even though an understanding of such properties may help in rationally impeding the virus life cycle and designing efficient nano-assemblies. This report uncovers an unprecedented and species-independent evolutionary pressure on virus capsids, based on the the notion that the simplest capsid designs (or those capsids with the lowest "hexamer complexity", C(h)) are the fittest, which was shown to be true for all available virus capsids. The theories result in a physically meaningful periodic table of virus capsids that uncovers strong and overarching evolutionary pressures, while also offering geometric explanations to other capsid properties (rigidity, pleomorphy, auxiliary requirements, etc.) that were previously considered to be unrelatable properties of the individual virus. Apart from describing a universal rule for virus capsid evolution, our work (especially the periodic table) provides a language with which highly diverse virus capsids, unified only by geometry, may be described and related to each other. Finally, the available virus structure databases and other published data reiterate the predicted geometry-derived rules, reinforcing the role of geometry in the natural selection and design of virus capsids.

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

PubMed

Shackelford, Todd K; Liddle, James R

2014-05-01

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

Artificial evolution by viability rather than competition.

PubMed

Maesani, Andrea; Fernando, Pradeep Ruben; Floreano, Dario

2014-01-01

Evolutionary algorithms are widespread heuristic methods inspired by natural evolution to solve difficult problems for which analytical approaches are not suitable. In many domains experimenters are not only interested in discovering optimal solutions, but also in finding the largest number of different solutions satisfying minimal requirements. However, the formulation of an effective performance measure describing these requirements, also known as fitness function, represents a major challenge. The difficulty of combining and weighting multiple problem objectives and constraints of possibly varying nature and scale into a single fitness function often leads to unsatisfactory solutions. Furthermore, selective reproduction of the fittest solutions, which is inspired by competition-based selection in nature, leads to loss of diversity within the evolving population and premature convergence of the algorithm, hindering the discovery of many different solutions. Here we present an alternative abstraction of artificial evolution, which does not require the formulation of a composite fitness function. Inspired from viability theory in dynamical systems, natural evolution and ethology, the proposed method puts emphasis on the elimination of individuals that do not meet a set of changing criteria, which are defined on the problem objectives and constraints. Experimental results show that the proposed method maintains higher diversity in the evolving population and generates more unique solutions when compared to classical competition-based evolutionary algorithms. Our findings suggest that incorporating viability principles into evolutionary algorithms can significantly improve the applicability and effectiveness of evolutionary methods to numerous complex problems of science and engineering, ranging from protein structure prediction to aircraft wing design.

Applying evolutionary psychology to a serious game about children's interpersonal conflict.

PubMed

Ingram, Gordon P D; Campos, Joana; Hondrou, Charline; Vasalou, Asimina; Martinho, Carlos; Joinson, Adam

2012-12-20

This article describes the use of evolutionary psychology to inform the design of a serious computer game aimed at improving 9-12-year-old children's conflict resolution skills. The design of the game will include dynamic narrative generation and emotional tagging, and there is a strong evolutionary rationale for the effect of both of these on conflict resolution. Gender differences will also be taken into consideration in designing the game. In interview research in schools in three countries (Greece, Portugal, and the UK) aimed at formalizing the game requirements, we found that gender differences varied in the extent to which they applied cross-culturally. Across the three countries, girls were less likely to talk about responding to conflict with physical aggression, talked more about feeling sad about conflict and about conflicts over friendship alliances, and talked less about conflicts in the context of sports or games. Predicted gender differences in anger and reconciliation were not found. Results are interpreted in terms of differing underlying models of friendship that are motivated by parental investment theory. This research will inform the design of the themes that we use in game scenarios for both girls and boys.

A Novel Handwritten Letter Recognizer Using Enhanced Evolutionary Neural Network

NASA Astrophysics Data System (ADS)

Mahmoudi, Fariborz; Mirzashaeri, Mohsen; Shahamatnia, Ehsan; Faridnia, Saed

This paper introduces a novel design for handwritten letter recognition by employing a hybrid back-propagation neural network with an enhanced evolutionary algorithm. Feeding the neural network consists of a new approach which is invariant to translation, rotation, and scaling of input letters. Evolutionary algorithm is used for the global search of the search space and the back-propagation algorithm is used for the local search. The results have been computed by implementing this approach for recognizing 26 English capital letters in the handwritings of different people. The computational results show that the neural network reaches very satisfying results with relatively scarce input data and a promising performance improvement in convergence of the hybrid evolutionary back-propagation algorithms is exhibited.

The Principle of Stasis: Why drift is not a Zero-Cause Law.

PubMed

Luque, Victor J

2016-06-01

This paper analyses the structure of evolutionary theory as a quasi-Newtonian theory and the need to establish a Zero-Cause Law. Several authors have postulated that the special character of drift is because it is the default behaviour or Zero-Cause Law of evolutionary systems, where change and not stasis is the normal state of them. For these authors, drift would be a Zero-Cause Law, the default behaviour and therefore a constituent assumption impossible to change without changing the system. I defend that drift's causal and explanatory power prevents it from being considered as a Zero-Cause Law. Instead, I propose that the default behaviour of evolutionary systems is what I call the Principle of Stasis, which posits that an evolutionary system where there is no selection, drift, mutation, migration, etc., and therefore no difference-maker, will not undergo any change (it will remain in stasis). Copyright © 2016 Elsevier Ltd. All rights reserved.

Adaptive Memory: Is There a Reproduction-Processing Effect?

PubMed

Seitz, Benjamin M; Polack, Cody W; Miller, Ralph R

2017-12-14

Like all biological systems, human memory is likely to have been influenced by evolutionary processes, and its abilities have been subjected to selective mechanisms. Consequently, human memory should be primed to better remember information relevant to one's evolutionary fitness. Supporting this view, participants asked to rate words based on their relevance to an imaginary survival situation better recall those words (even the words rated low in relevancy) than the same words rated with respect to non-survival situations. This mnemonic advantage is called the "survival-processing effect," and presumably it was selected for because it contributed to evolutionary fitness. The same reasoning suggests that there should be an advantage for recall of information that has been rated for relevancy to reproduction and/or mate seeking, although little evidence has existed to assess this proposition. We used an experimental design similar to that in the original survival-processing effect study (Nairne, Thompson, & Pandeirada, 2007) and across 3 experiments tested several newly designed scenarios to determine whether a reproduction-processing effect could be found in an ancestral environment, a modern mating environment, and an ancestral environment in which the emphasis was on raising offspring as opposed to finding a mate. Our results replicated the survival-processing effect but provided no evidence of a reproduction-processing effect when the scenario emphasized finding a mate. However, when rating items on their relevancy to raising one's offspring in an ancestral environment, a mnemonic advantage comparable to that of the survival-processing effect was found. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A Study of Driver's Route Choice Behavior Based on Evolutionary Game Theory

PubMed Central

Jiang, Xiaowei; Ji, Yanjie; Deng, Wei

2014-01-01

This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers' route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver's route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver's route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent. PMID:25610455

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

PubMed

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

2014-01-01

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

Short Lesson Plan Associated with Increased Acceptance of Evolutionary Theory and Potential Change in Three Alternate Conceptions of Macroevolution in Undergraduate Students

ERIC Educational Resources Information Center

Abraham, Joel K.; Perez, Kathryn E.; Downey, Nicholas; Herron, Jon C.; Meir, Eli

2012-01-01

Undergraduates commonly harbor alternate conceptions about evolutionary biology; these alternate conceptions often persist, even after intensive instruction, and may influence acceptance of evolution. We interviewed undergraduates to explore their alternate conceptions about macroevolutionary patterns and designed a 2-h lesson plan to present…

Dynamic Adaptive Neural Network Arrays: A Neuromorphic Architecture

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

Disney, Adam; Reynolds, John

2015-01-01

Dynamic Adaptive Neural Network Array (DANNA) is a neuromorphic hardware implementation. It differs from most other neuromorphic projects in that it allows for programmability of structure, and it is trained or designed using evolutionary optimization. This paper describes the DANNA structure, how DANNA is trained using evolutionary optimization, and an application of DANNA to a very simple classification task.

EvoluZion: A Computer Simulator for Teaching Genetic and Evolutionary Concepts

ERIC Educational Resources Information Center

Zurita, Adolfo R.

2017-01-01

EvoluZion is a forward-in-time genetic simulator developed in Java and designed to perform real time simulations on the evolutionary history of virtual organisms. These model organisms harbour a set of 13 genes that codify an equal number of phenotypic features. These genes change randomly during replication, and mutant genes can have null,…

Evolutionary Maps: A New Model for the Analysis of Conceptual Development, with Application to the Diurnal Cycle

ERIC Educational Resources Information Center

Navarro, Manuel

2014-01-01

This paper presents a model of how children generate concrete concepts from perception through processes of differentiation and integration. The model informs the design of a novel methodology ("evolutionary maps" or "emaps"), whose implementation on certain domains unfolds the web of itineraries that children may follow in the…

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

ERIC Educational Resources Information Center

Passmore, Cynthia; Stewart, James

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

Identifying the Evolutionary Building Blocks of the Cardiac Conduction System

PubMed Central

Jensen, Bjarke; Boukens, Bastiaan J. D.; Postma, Alex V.; Gunst, Quinn D.; van den Hoff, Maurice J. B.; Moorman, Antoon F. M.; Wang, Tobias; Christoffels, Vincent M.

2012-01-01

The endothermic state of mammals and birds requires high heart rates to accommodate the high rates of oxygen consumption. These high heart rates are driven by very similar conduction systems consisting of an atrioventricular node that slows the electrical impulse and a His-Purkinje system that efficiently activates the ventricular chambers. While ectothermic vertebrates have similar contraction patterns, they do not possess anatomical evidence for a conduction system. This lack amongst extant ectotherms is surprising because mammals and birds evolved independently from reptile-like ancestors. Using conserved genetic markers, we found that the conduction system design of lizard (Anolis carolinensis and A. sagrei), frog (Xenopus laevis) and zebrafish (Danio rerio) adults is strikingly similar to that of embryos of mammals (mouse Mus musculus, and man) and chicken (Gallus gallus). Thus, in ectothermic adults, the slow conducting atrioventricular canal muscle is present, no fibrous insulating plane is formed, and the spongy ventricle serves the dual purpose of conduction and contraction. Optical mapping showed base-to-apex activation of the ventricles of the ectothermic animals, similar to the activation pattern of mammalian and avian embryonic ventricles and to the His-Purkinje systems of the formed hearts. Mammalian and avian ventricles uniquely develop thick compact walls and septum and, hence, form a discrete ventricular conduction system from the embryonic spongy ventricle. Our study uncovers the evolutionary building plan of heart and indicates that the building blocks of the conduction system of adult ectothermic vertebrates and embryos of endotherms are similar. PMID:22984480

From wide to close binaries?

NASA Astrophysics Data System (ADS)

Eggleton, Peter P.

The mechanisms by which the periods of wide binaries (mass 8 solar mass or less and period 10-3000 d) are lengthened or shortened are discussed, synthesizing the results of recent theoretical investigations. A system of nomenclature involving seven evolutionary states, three geometrical states, and 10 types of orbital-period evolution is developed and applied; classifications of 71 binaries are presented in a table along with the basic observational parameters. Evolutionary processes in wide binaries (single-star-type winds, magnetic braking with tidal friction, and companion-reinforced attrition), late case B systems, low-mass X-ray binaries, and triple systems are examined in detail, and possible evolutionary paths are shown in diagrams.

Development of the CSI phase-3 evolutionary model testbed

NASA Technical Reports Server (NTRS)

Gronet, M. J.; Davis, D. A.; Tan, M. K.

1994-01-01

This report documents the development effort for the reconfiguration of the Controls-Structures Integration (CSI) Evolutionary Model (CEM) Phase-2 testbed into the CEM Phase-3 configuration. This step responds to the need to develop and test CSI technologies associated with typical planned earth science and remote sensing platforms. The primary objective of the CEM Phase-3 ground testbed is to simulate the overall on-orbit dynamic behavior of the EOS AM-1 spacecraft. Key elements of the objective include approximating the low-frequency appendage dynamic interaction of EOS AM-1, allowing for the changeout of components, and simulating the free-free on-orbit environment using an advanced suspension system. The fundamentals of appendage dynamic interaction are reviewed. A new version of the multiple scaling method is used to design the testbed to have the full-scale geometry and dynamics of the EOS AM-1 spacecraft, but at one-tenth the weight. The testbed design is discussed, along with the testing of the solar array, high gain antenna, and strut components. Analytical performance comparisons show that the CEM Phase-3 testbed simulates the EOS AM-1 spacecraft with good fidelity for the important parameters of interest.

Revealing evolutionary pathways by fitness landscape reconstruction.

PubMed

Kogenaru, Manjunatha; de Vos, Marjon G J; Tans, Sander J

2009-01-01

The concept of epistasis has since long been used to denote non-additive fitness effects of genetic changes and has played a central role in understanding the evolution of biological systems. Owing to an array of novel experimental methodologies, it has become possible to experimentally determine epistatic interactions as well as more elaborate genotype-fitness maps. These data have opened up the investigation of a host of long-standing questions in evolutionary biology, such as the ruggedness of fitness landscapes and the accessibility of mutational trajectories, the evolution of sex, and the origin of robustness and modularity. Here we review this recent and timely marriage between systems biology and evolutionary biology, which holds the promise to understand evolutionary dynamics in a more mechanistic and predictive manner.

Interdisciplinary multisensory fusion: design lessons from professional architects

NASA Astrophysics Data System (ADS)

Geiger, Ray W.; Snell, J. T.

1992-11-01

Psychocybernetic systems engineering design conceptualization is mimicking the evolutionary path of habitable environmental design and the professional practice of building architecture, construction, and facilities management. Human efficacy for innovation in architectural design has always reflected more the projected perceptual vision of the designer visa vis the hierarchical spirit of the design process. In pursuing better ways to build and/or design things, we have found surprising success in exploring certain more esoteric applications. One of those applications is the vision of an artistic approach in/and around creative problem solving. Our evaluation in research into vision and visual systems associated with environmental design and human factors has led us to discover very specific connections between the human spirit and quality design. We would like to share those very qualitative and quantitative parameters of engineering design, particularly as it relates to multi-faceted and interdisciplinary design practice. Discussion will cover areas of cognitive ergonomics, natural modeling sources, and an open architectural process of means and goal satisfaction, qualified by natural repetition, gradation, rhythm, contrast, balance, and integrity of process. One hypothesis is that the kinematic simulation of perceived connections between hard and soft sciences, centering on the life sciences and life in general, has become a very effective foundation for design theory and application.

Climate-related environmental variation in a visual signalling device: the male and female dewlap in Anolis sagrei lizards.

PubMed

Driessens, T; Baeckens, S; Balzarolo, M; Vanhooydonck, B; Huyghe, K; Van Damme, R

2017-10-01

Animals communicate using a variety of signals that differ dramatically among and within species. The astonishing dewlap diversity in anoles has attracted considerable attention in this respect. Yet, the evolutionary processes behind it remain elusive and have mostly been explored for males only. Here, we considered Anolis sagrei males and females to study signal divergence among populations. First, we assessed the degree of variation in dewlap design (size, pattern and colour) and displays by comparing 17 populations distributed across the Caribbean. Second, we assessed whether the observed dewlap diversity is associated with variation in climate-related environmental conditions. Results showed that populations differed in all dewlap characteristics, with the exception of display rate in females. We further found that males and females occurring in 'xeric' environments had a higher proportion of solid dewlaps with higher UV reflectance. In addition, lizards inhabiting 'mesic' environments had primarily marginal dewlaps showing high reflectance in red. For dewlap display, a correlation with environment was only observed in males. Our study provides evidence for a strong relationship between signal design and prevailing environmental conditions, which may result from differential selection on signal efficacy. Moreover, our study highlights the importance of including females when studying dewlaps in an evolutionary context. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

A comparison of the role of beamwidth in biological and engineered sonar.

PubMed

Todd, Bryan D; Müller, Rolf

2017-12-28

Sonar is an important sensory modality for engineers as well as in nature. In engineering, sonar is the dominating modality for underwater sensing. In nature, biosonar is likely to have been a central factor behind the unprecedented evolutionary success of bats, a highly diverse group that accounts for over 20% of all mammal species. However, it remains unclear to what extent engineered and biosonar follow similar design and operational principles. In the current work, the key sonar design characteristic of beamwidth is examined in technical and biosonar. To this end, beamwidth data has been obtained for 23 engineered sonar systems and from numerical beampattern predictions for 151 emission and reception elements (noseleaves and ears) representing bat biosonar. Beamwidth data from these sources is compared to the beamwidth of a planar ellipsoidal transducer as a reference. The results show that engineered and biological both obey the basic physical limit on beamwidth as a function of the ratio of aperture size and wavelength. However, beyond that, the beamwidth data revealed very different behaviors between the engineered and the biological sonar systems. Whereas the beamwidths of the technical sonar systems were very close to the planar transducer limit, the biological samples showed a very wide scatter away from this limit. This scatter was as large, if not wider, than what was seen in a small reference data set obtained with random aluminum cones. A possible interpretation of these differences in the variability could be that whereas sonar engineers try to minimize beamwidth subject to constraints on device size, the evolutionary optimization of bat biosonar beampatterns has been directed at other factors that have left beamwidth as a byproduct. Alternatively, the biosonar systems may require beamwidth values that are larger than the physical limit and differ between species and their sensory ecological niches.

Space migrations: Anthropology and the humanization of space

NASA Technical Reports Server (NTRS)

Finney, Ben R.

1992-01-01

Because of its broad evolutionary perspective and its focus on both technology and culture, anthropology offers a unique view of why we are going into space and what leaving Earth will mean for humanity. In addition, anthropology could help in the humanization of space through (1) overcoming socioculture barriers to working and living in space, (2) designing societies appropriate for permanent space settlement, (3) promoting understanding among differentiated branches of humankind scattered through space, (4) deciphering the cultural systems of any extraterrestrial civilizations contacted.

Report of Research at Technische Universitaet Darmstadt on Ultrahard Materials in the B-C-N-Si System

DTIC Science & Technology

2015-06-01

structure at the micro- and nanoscale. In other words, development of nanocomposites, multilayers, and superlattices via appropriate design and control of...C-B and C-N bonds as C-C and B-N bonds. Later, the same research group , based on first-principles total-energy, and dynamic phonon calculations...Vickers hardness values.7 Another research group employed an ab initio evolutionary algorithm42 to resolve the crystal structure of the observed

Inactivation of tumor suppressor genes and cancer therapy: An evolutionary game theory approach.

PubMed

Khadem, Heydar; Kebriaei, Hamed; Veisi, Zahra

2017-06-01

Inactivation of alleles in tumor suppressor genes (TSG) is one of the important issues resulting in evolution of cancerous cells. In this paper, the evolution of healthy, one and two missed allele cells is modeled using the concept of evolutionary game theory and replicator dynamics. The proposed model also takes into account the interaction rates of the cells as designing parameters of the system. Different combinations of the equilibrium points of the parameterized nonlinear system is studied and categorized into some cases. In each case, the interaction rates' values are suggested in a way that the equilibrium points of the replicator dynamics are located on an appropriate region of the state space. Based on the suggested interaction rates, it is proved that the system doesn't have any undesirable interior equilibrium point as well. Therefore, the system will converge to the desirable region, where there is a scanty level of cancerous cells. In addition, the proposed conditions for interaction rates guarantee that, when a trajectory of the system reaches the boundaries, then it will stay there forever which is a desirable property since the equilibrium points have been already located on the boundaries, appropriately. The simulation results show the effectiveness of the suggestions in the elimination of the cancerous cells in different scenarios. Copyright © 2017 Elsevier Inc. All rights reserved.

Using protistan examples to dispel the myths of intelligent design.

PubMed

Farmer, Mark A; Habura, Andrea

2010-01-01

In recent years the teaching of the religiously based philosophy of intelligent design (ID) has been proposed as an alternative to modern evolutionary theory. Advocates of ID are largely motivated by their opposition to naturalistic explanations of biological diversity, in accordance with their goal of challenging the philosophy of scientific materialism. Intelligent design has been embraced by a wide variety of creationists who promote highly questionable claims that purport to show the inadequacy of evolutionary theory, which they consider to be a threat to a theistic worldview. We find that examples from protistan biology are well suited for providing evidence of many key evolutionary concepts, and have often been misrepresented or roundly ignored by ID advocates. These include examples of adaptations and radiations that are said to be statistically impossible, as well as examples of speciation both in the laboratory and as documented in the fossil record. Because many biologists may not be familiar with the richness of the protist evolution dataset or with ID-based criticisms of evolution, we provide examples of current ID arguments and specific protistan counter-examples.

An evolutionary critique of cultural analysis in sociology.

PubMed

Crippen, T

1992-12-01

A noteworthy development that has transpired in American sociology in the past quarter century has been the increasingly sophisticated interest in the analysis of human cultural systems. Sadly, however, these analyses reveal that social scientists rarely appreciate the profoundly evolutionary aspects of human culture. The chief purpose of this essay is to address this shortcoming and to offer some tentative suggestions toward its rectification. The essay begins by briefly reviewing recent developments in the analysis of cultural systems, primarily by reference to the influential work of Wuthnow. Second, a common flaw in these approaches is addressed-namely, the absence of any recognition of the value of grounding sociocultural theory in an informed evolutionary framework-and the case is made that this shortcoming is avoidable, even within the context of the intellectual traditions of the social sciences. Third, the evolutionary foundations of human cultural behavior are explored in terms of an analysis of relevant theoretical and empirical developments in the evolutionary neurosciences. Fourth, the value of these insights is illustrated by reference to an evolutionary critique of a recent and thought-provoking contribution to the study of modern political culture-Douglas and Wildavsky's analysis ofRisk and Culture. Finally, the article concludes by emphasizing the value of and the necessity for incorporating evolutionary reasoning into the domain of sociocultural theory.

Bridging Developmental Systems Theory and Evolutionary Psychology Using Dynamic Optimization

ERIC Educational Resources Information Center

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

2013-01-01

Interactions between evolutionary psychologists and developmental systems theorists have been largely antagonistic. This is unfortunate because potential synergies between the two approaches remain unexplored. This article presents a method that may help to bridge the divide, and that has proven fruitful in biology: dynamic optimization. Dynamic…

NASA's Evolutionary Xenon Thruster (NEXT) Ion Propulsion System Information Summary

NASA Technical Reports Server (NTRS)

Pencil, Eirc S.; Benson, Scott W.

2008-01-01

This document is a guide to New Frontiers mission proposal teams. The document describes the development and status of the NASA's Evolutionary Xenon Thruster (NEXT) ion propulsion system (IPS) technology, its application to planetary missions, and the process anticipated to transition NEXT to the first flight mission.

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

Between "design" and "bricolage": genetic networks, levels of selection, and adaptive evolution.

PubMed

Wilkins, Adam S

2007-05-15

The extent to which "developmental constraints" in complex organisms restrict evolutionary directions remains contentious. Yet, other forms of internal constraint, which have received less attention, may also exist. It will be argued here that a set of partial constraints below the level of phenotypes, those involving genes and molecules, influences and channels the set of possible evolutionary trajectories. At the top-most organizational level there are the genetic network modules, whose operations directly underlie complex morphological traits. The properties of these network modules, however, have themselves been set by the evolutionary history of the component genes and their interactions. Characterization of the components, structures, and operational dynamics of specific genetic networks should lead to a better understanding not only of the morphological traits they underlie but of the biases that influence the directions of evolutionary change. Furthermore, such knowledge may permit assessment of the relative degrees of probability of short evolutionary trajectories, those on the microevolutionary scale. In effect, a "network perspective" may help transform evolutionary biology into a scientific enterprise with greater predictive capability than it has hitherto possessed.

Computationally mapping sequence space to understand evolutionary protein engineering.

PubMed

Armstrong, Kathryn A; Tidor, Bruce

2008-01-01

Evolutionary protein engineering has been dramatically successful, producing a wide variety of new proteins with altered stability, binding affinity, and enzymatic activity. However, the success of such procedures is often unreliable, and the impact of the choice of protein, engineering goal, and evolutionary procedure is not well understood. We have created a framework for understanding aspects of the protein engineering process by computationally mapping regions of feasible sequence space for three small proteins using structure-based design protocols. We then tested the ability of different evolutionary search strategies to explore these sequence spaces. The results point to a non-intuitive relationship between the error-prone PCR mutation rate and the number of rounds of replication. The evolutionary relationships among feasible sequences reveal hub-like sequences that serve as particularly fruitful starting sequences for evolutionary search. Moreover, genetic recombination procedures were examined, and tradeoffs relating sequence diversity and search efficiency were identified. This framework allows us to consider the impact of protein structure on the allowed sequence space and therefore on the challenges that each protein presents to error-prone PCR and genetic recombination procedures.

Rapid Preliminary Design of Interplanetary Trajectories Using the Evolutionary Mission Trajectory Generator

NASA Technical Reports Server (NTRS)

Englander, Jacob

2016-01-01

Preliminary design of interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. In addition, a time-history of control variables must be chosen that defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a hybrid optimal control problem. The method is demonstrated on notional high-thrust chemical and low-thrust electric propulsion missions. In the low-thrust case, the hybrid optimal control problem is augmented to include systems design optimization.

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.

Diversity and evolution of class 2 CRISPR–Cas systems

PubMed Central

Shmakov, Sergey; Smargon, Aaron; Scott, David; Cox, David; Pyzocha, Neena; Yan, Winston; Abudayyeh, Omar O.; Gootenberg, Jonathan S.; Makarova, Kira S.; Wolf, Yuri I.; Severinov, Konstantin; Zhang, Feng; Koonin, Eugene V.

2018-01-01

Class 2 CRISPR–Cas systems are characterized by effector modules that consist of a single multidomain protein, such as Cas9 or Cpf1. We designed a computational pipeline for the discovery of novel class 2 variants and used it to identify six new CRISPR–Cas subtypes. The diverse properties of these new systems provide potential for the development of versatile tools for genome editing and regulation. In this Analysis article, we present a comprehensive census of class 2 types and class 2 subtypes in complete and draft bacterial and archaeal genomes, outline evolutionary scenarios for the independent origin of different class 2 CRISPR–Cas systems from mobile genetic elements, and propose an amended classification and nomenclature of CRISPR–Cas. PMID:28111461

Insect form vision as one potential shaping force of spider web decoration design.

PubMed

Cheng, R-C; Yang, E-C; Lin, C-P; Herberstein, M E; Tso, I-M

2010-03-01

Properties of prey sensory systems are important factors shaping the design of signals generated by organisms exploiting them. In this study we assessed how prey sensory preference affected the exploiter signal design by investigating the evolutionary relationship and relative attractiveness of linear and cruciate form web decorations built by Argiope spiders. Because insects have an innate preference for bilaterally symmetrical patterns, we hypothesized that cruciate form decorations were evolved from linear form due to their higher visual attractiveness to insects. We first reconstructed a molecular phylogeny of the Asian members of the genus Argiope using mitochondrial markers to infer the evolutionary relationship of two decoration forms. Results of ancestral character state reconstruction showed that the linear form was ancestral and the cruciate form derived. To evaluate the luring effectiveness of two decoration forms, we performed field experiments in which the number and orientation of decoration bands were manipulated. Decoration bands arranged in a cruciate form were significantly more attractive to insects than those arranged in a linear form, no matter whether they were composed of silks or dummies. Moreover, dummy decoration bands arranged in a cruciate form attracted significantly more insects than those arranged in a vertical/horizontal form. Such results suggest that pollinator insects' innate preference for certain bilateral or radial symmetrical patterns might be one of the driving forces shaping the arrangement pattern of spider web decorations.

Evolution of a modular software network

PubMed Central

Fortuna, Miguel A.; Bonachela, Juan A.; Levin, Simon A.

2011-01-01

“Evolution behaves like a tinkerer” (François Jacob, Science, 1977). Software systems provide a singular opportunity to understand biological processes using concepts from network theory. The Debian GNU/Linux operating system allows us to explore the evolution of a complex network in a unique way. The modular design detected during its growth is based on the reuse of existing code in order to minimize costs during programming. The increase of modularity experienced by the system over time has not counterbalanced the increase in incompatibilities between software packages within modules. This negative effect is far from being a failure of design. A random process of package installation shows that the higher the modularity, the larger the fraction of packages working properly in a local computer. The decrease in the relative number of conflicts between packages from different modules avoids a failure in the functionality of one package spreading throughout the entire system. Some potential analogies with the evolutionary and ecological processes determining the structure of ecological networks of interacting species are discussed. PMID:22106260

Robust evaluation of time series classification algorithms for structural health monitoring

NASA Astrophysics Data System (ADS)

Harvey, Dustin Y.; Worden, Keith; Todd, Michael D.

2014-03-01

Structural health monitoring (SHM) systems provide real-time damage and performance information for civil, aerospace, and mechanical infrastructure through analysis of structural response measurements. The supervised learning methodology for data-driven SHM involves computation of low-dimensional, damage-sensitive features from raw measurement data that are then used in conjunction with machine learning algorithms to detect, classify, and quantify damage states. However, these systems often suffer from performance degradation in real-world applications due to varying operational and environmental conditions. Probabilistic approaches to robust SHM system design suffer from incomplete knowledge of all conditions a system will experience over its lifetime. Info-gap decision theory enables nonprobabilistic evaluation of the robustness of competing models and systems in a variety of decision making applications. Previous work employed info-gap models to handle feature uncertainty when selecting various components of a supervised learning system, namely features from a pre-selected family and classifiers. In this work, the info-gap framework is extended to robust feature design and classifier selection for general time series classification through an efficient, interval arithmetic implementation of an info-gap data model. Experimental results are presented for a damage type classification problem on a ball bearing in a rotating machine. The info-gap framework in conjunction with an evolutionary feature design system allows for fully automated design of a time series classifier to meet performance requirements under maximum allowable uncertainty.

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).

Evolutionary psychology and intelligence research.

PubMed

Kanazawa, Satoshi

2010-01-01

This article seeks to unify two subfields of psychology that have hitherto stood separately: evolutionary psychology and intelligence research/differential psychology. I suggest that general intelligence may simultaneously be an evolved adaptation and an individual-difference variable. Tooby and Cosmides's (1990a) notion of random quantitative variation on a monomorphic design allows us to incorporate heritable individual differences in evolved adaptations. The Savanna-IQ Interaction Hypothesis, which is one consequence of the integration of evolutionary psychology and intelligence research, can potentially explain why less intelligent individuals enjoy TV more, why liberals are more intelligent than conservatives, and why night owls are more intelligent than morning larks, among many other findings. The general approach proposed here will allow us to integrate evolutionary psychology with any other aspect of differential psychology. Copyright 2010 APA, all rights reserved.

In-Space Radiator Shape Optimization using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Hull, Patrick V.; Kittredge, Ken; Tinker, Michael; SanSoucie, Michael

2006-01-01

Future space exploration missions will require the development of more advanced in-space radiators. These radiators should be highly efficient and lightweight, deployable heat rejection systems. Typical radiators for in-space heat mitigation commonly comprise a substantial portion of the total vehicle mass. A small mass savings of even 5-10% can greatly improve vehicle performance. The objective of this paper is to present the development of detailed tools for the analysis and design of in-space radiators using evolutionary computation techniques. The optimality criterion is defined as a two-dimensional radiator with a shape demonstrating the smallest mass for the greatest overall heat transfer, thus the end result is a set of highly functional radiator designs. This cross-disciplinary work combines topology optimization and thermal analysis design by means of a genetic algorithm The proposed design tool consists of the following steps; design parameterization based on the exterior boundary of the radiator, objective function definition (mass minimization and heat loss maximization), objective function evaluation via finite element analysis (thermal radiation analysis) and optimization based on evolutionary algorithms. The radiator design problem is defined as follows: the input force is a driving temperature and the output reaction is heat loss. Appropriate modeling of the space environment is added to capture its effect on the radiator. The design parameters chosen for this radiator shape optimization problem fall into two classes, variable height along the width of the radiator and a spline curve defining the -material boundary of the radiator. The implementation of multiple design parameter schemes allows the user to have more confidence in the radiator optimization tool upon demonstration of convergence between the two design parameter schemes. This tool easily allows the user to manipulate the driving temperature regions thus permitting detailed design of in-space radiators for unique situations. Preliminary results indicate an optimized shape following that of the temperature distribution regions in the "cooler" portions of the radiator. The results closely follow the expected radiator shape.

Systems metabolic engineering strategies for the production of amino acids.

PubMed

Ma, Qian; Zhang, Quanwei; Xu, Qingyang; Zhang, Chenglin; Li, Yanjun; Fan, Xiaoguang; Xie, Xixian; Chen, Ning

2017-06-01

Systems metabolic engineering is a multidisciplinary area that integrates systems biology, synthetic biology and evolutionary engineering. It is an efficient approach for strain improvement and process optimization, and has been successfully applied in the microbial production of various chemicals including amino acids. In this review, systems metabolic engineering strategies including pathway-focused approaches, systems biology-based approaches, evolutionary approaches and their applications in two major amino acid producing microorganisms: Corynebacterium glutamicum and Escherichia coli, are summarized.

Evolutionary dynamics with fluctuating population sizes and strong mutualism.

PubMed

Chotibut, Thiparat; Nelson, David R

2015-08-01

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

Evolutionary dynamics with fluctuating population sizes and strong mutualism

NASA Astrophysics Data System (ADS)

Chotibut, Thiparat; Nelson, David R.

2015-08-01

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

Evolutionary engineering of industrial microorganisms-strategies and applications.

PubMed

Zhu, Zhengming; Zhang, Juan; Ji, Xiaomei; Fang, Zhen; Wu, Zhimeng; Chen, Jian; Du, Guocheng

2018-06-01

Microbial cells have been widely used in the industry to obtain various biochemical products, and evolutionary engineering is a common method in biological research to improve their traits, such as high environmental tolerance and improvement of product yield. To obtain better integrate functions of microbial cells, evolutionary engineering combined with other biotechnologies have attracted more attention in recent years. Classical laboratory evolution has been proven effective to letting more beneficial mutations occur in different genes but also has some inherent limitations such as a long evolutionary period and uncontrolled mutation frequencies. However, recent studies showed that some new strategies may gradually overcome these limitations. In this review, we summarize the evolutionary strategies commonly used in industrial microorganisms and discuss the combination of evolutionary engineering with other biotechnologies such as systems biology and inverse metabolic engineering. Finally, we prospect the importance and application prospect of evolutionary engineering as a powerful tool especially in optimization of industrial microbial cell factories.

Aerodynamic Shape Optimization Using Hybridized Differential Evolution

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2003-01-01

An aerodynamic shape optimization method that uses an evolutionary algorithm known at Differential Evolution (DE) in conjunction with various hybridization strategies is described. DE is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Various hybridization strategies for DE are explored, including the use of neural networks as well as traditional local search methods. A Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the hybrid DE optimizer. The method is implemented on distributed parallel computers so that new designs can be obtained within reasonable turnaround times. Results are presented for the inverse design of a turbine airfoil from a modern jet engine. (The final paper will include at least one other aerodynamic design application). The capability of the method to search large design spaces and obtain the optimal airfoils in an automatic fashion is demonstrated.

The scope and strength of sex-specific selection in genome evolution.

PubMed

Wright, A E; Mank, J E

2013-09-01

Males and females share the vast majority of their genomes and yet are often subject to different, even conflicting, selection. Genomic and transcriptomic developments have made it possible to assess sex-specific selection at the molecular level, and it is clear that sex-specific selection shapes the evolutionary properties of several genomic characteristics, including transcription, post-transcriptional regulation, imprinting, genome structure and gene sequence. Sex-specific selection is strongly influenced by mating system, which also causes neutral evolutionary changes that affect different regions of the genome in different ways. Here, we synthesize theoretical and molecular work in order to provide a cohesive view of the role of sex-specific selection and mating system in genome evolution. We also highlight the need for a combined approach, incorporating both genomic data and experimental phenotypic studies, in order to understand precisely how sex-specific selection drives evolutionary change across the genome. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

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

PubMed

Kasada, Minoru; Yamamichi, Masato; Yoshida, Takehito

2014-11-11

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

An optimal brain can be composed of conflicting agents

PubMed Central

Livnat, Adi; Pippenger, Nicholas

2006-01-01

Many behaviors have been attributed to internal conflict within the animal and human mind. However, internal conflict has not been reconciled with evolutionary principles, in that it appears maladaptive relative to a seamless decision-making process. We study this problem through a mathematical analysis of decision-making structures. We find that, under natural physiological limitations, an optimal decision-making system can involve “selfish” agents that are in conflict with one another, even though the system is designed for a single purpose. It follows that conflict can emerge within a collective even when natural selection acts on the level of the collective only. PMID:16492775

What is a vector?

PubMed Central

Morgan, Eric René; Booth, Mark; Norman, Rachel; Mideo, Nicole; McCallum, Hamish; Fenton, Andy

2017-01-01

Many important and rapidly emerging pathogens of humans, livestock and wildlife are ‘vector-borne’. However, the term ‘vector’ has been applied to diverse agents in a broad range of epidemiological systems. In this perspective, we briefly review some common definitions, identify the strengths and weaknesses of each and consider the functional differences between vectors and other hosts from a range of ecological, evolutionary and public health perspectives. We then consider how the use of designations can afford insights into our understanding of epidemiological and evolutionary processes that are not otherwise apparent. We conclude that from a medical and veterinary perspective, a combination of the ‘haematophagous arthropod’ and ‘mobility’ definitions is most useful because it offers important insights into contact structure and control and emphasizes the opportunities for pathogen shifts among taxonomically similar species with similar feeding modes and internal environments. From a population dynamics and evolutionary perspective, we suggest that a combination of the ‘micropredator’ and ‘sequential’ definition is most appropriate because it captures the key aspects of transmission biology and fitness consequences for the pathogen and vector itself. However, we explicitly recognize that the value of a definition always depends on the research question under study. This article is part of the themed issue ‘Opening the black box: re-examining the ecology and evolution of parasite transmission’. PMID:28289253

Nuclear and plastid markers reveal the persistence of genetic identity: a new perspective on the evolutionary history of Petunia exserta.

PubMed

Segatto, Ana Lúcia Anversa; Cazé, Ana Luíza Ramos; Turchetto, Caroline; Klahre, Ulrich; Kuhlemeier, Cris; Bonatto, Sandro Luis; Freitas, Loreta Brandão

2014-01-01

Recently divergent species that can hybridize are ideal models for investigating the genetic exchanges that can occur while preserving the species boundaries. Petunia exserta is an endemic species from a very limited and specific area that grows exclusively in rocky shelters. These shaded spots are an inhospitable habitat for all other Petunia species, including the closely related and widely distributed species P. axillaris. Individuals with intermediate morphologic characteristics have been found near the rocky shelters and were believed to be putative hybrids between P. exserta and P. axillaris, suggesting a situation where Petunia exserta is losing its genetic identity. In the current study, we analyzed the plastid intergenic spacers trnS/trnG and trnH/psbA and six nuclear CAPS markers in a large sampling design of both species to understand the evolutionary process occurring in this biological system. Bayesian clustering methods, cpDNA haplotype networks, genetic diversity statistics, and coalescence-based analyses support a scenario where hybridization occurs while two genetic clusters corresponding to two species are maintained. Our results reinforce the importance of coupling differentially inherited markers with an extensive geographic sample to assess the evolutionary dynamics of recently diverged species that can hybridize. Copyright © 2013 Elsevier Inc. 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 potential of the extrinsic incubation period of dengue virus in Aedes aegypti.

PubMed

Ye, Yixin H; Chenoweth, Stephen F; Carrasco, Alison M; Allen, Scott L; Frentiu, Francesca D; van den Hurk, Andrew F; Beebe, Nigel W; McGraw, Elizabeth A

2016-11-01

Dengue fever is the most common arboviral disease worldwide. It is caused by dengue viruses (DENV) and the mosquito Aedes aegypti is its primary vector. One of the most powerful determinants of a mosquito's ability to transmit DENV is the length of the extrinsic incubation period (EIP), the time it takes for a virus to be transmitted by a mosquito after consuming an infected blood meal. Here, we repeatedly measured DENV load in the saliva of individual mosquitoes over their lifetime and used this in combination with a breeding design to determine the extent to which EIP might respond to the evolutionary forces of drift and selection. We demonstrated that genetic variation among mosquitoes contributes significantly to transmission potential and length of EIP. We reveal that shorter EIP is genetically correlated with reduced mosquito lifespan, highlighting negative life-history consequences for virus-infected mosquitoes. This work highlights the capacity for local genetic variation in mosquito populations to evolve and to dramatically affect the nature of human outbreaks. It also provides the impetus for isolating mosquito genes that determine EIP. More broadly, our dual experimental approach offers new opportunities for studying the evolutionary potential of transmission traits in other vector/pathogen systems. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

The influence of developmental environment on courtship song in cactophilic Drosophila.

PubMed

Iglesias, Patricia P; Soto, Eduardo M; Soto, Ignacio M; Colines, Betina; Hasson, Esteban

2018-04-15

Closely related species often differ in the signals involved in sexual communication and mate recognition. Determining the factors influencing signal quality (i.e. signal's content and conspicuousness) provides an important insight into the potential pathways by which these interspecific differences evolve. Host specificity could bias the direction of the evolution of sexual communication and the mate recognition system, favouring sensory channels that work best in the different host conditions. In this study, we focus on the cactophilic sibling species Drosophila buzzatii and D. koepferae that have diverged not only in the sensory channel used for sexual communication and mate recognition but also in the cactus species that use as primary hosts. We evaluate the role of the developmental environment in generating courtship song variation using an isofemale line design. Our results show that host environment during development induces changes in the courtship song of D. koepferae males, but not in D. buzzatii males. Moreover, we report for the first time that host rearing environment affects the conspicuousness of courtship song (i.e. song volume). Our results are mainly discussed in the context of the sensory drive hypothesis. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

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.

On evolutionary systems.

PubMed

Alvarez de Lorenzana, J M; Ward, L M

1987-01-01

This paper develops a metatheoretical framework for understanding evolutionary systems (systems that develop in ways that increase their own variety). The framework addresses shortcomings seen in other popular systems theories. It concerns both living and nonliving systems, and proposes a metahierarchy of hierarchical systems. Thus, it potentially addresses systems at all descriptive levels. We restrict our definition of system to that of a core system whose parts have a different ontological status than the system, and characterize the core system in terms of five global properties: minimal length interval, minimal time interval, system cycle, total receptive capacity, and system potential. We propose two principles through the interaction of which evolutionary systems develop. The Principle of Combinatorial Expansion describes how a core system realizes its developmental potential through a process of progressive differentiation of the single primal state up to a limit stage. The Principle of Generative Condensation describes how the components of the last stage of combinatorial expansion condense and become the environment for and components of new, enriched systems. The early evolution of the Universe after the "big bang" is discussed in light of these ideas as an example of the application of the framework.

Shuttle/Agena study. Volume 2, part 2: Agena tug configurations, Shuttle/Agena interface, performance, safety, cost

NASA Technical Reports Server (NTRS)

1972-01-01

An evaluation of the compatibility of the space shuttle and Agena rocket vehicle was conducted. The Agena space tug configuration design is described in terms of the total vehicle system as well as the individual subsystems and major assemblies and components. The complete interface between the Agena space tug and the space shuttle orbiter is defined for in-flight and ground operations. The derivation and design of an evolutionary stage is also presented. This vehicle conforms to the same guidelines and interface requirements as the Agena space tug. Performance data developed for both vehicles for each of the three study baseline missions are included.

The Evolution of Human Handedness

PubMed Central

Smaers, Jeroen B; Steele, James; Case, Charleen R; Amunts, Katrin

2013-01-01

There is extensive evidence for an early vertebrate origin of lateralized motor behavior and of related asymmetries in underlying brain systems. We investigate human lateralized motor functioning in a broad comparative context of evolutionary neural reorganization. We quantify evolutionary trends in the fronto-cerebellar system (involved in motor learning) across 46 million years of divergent primate evolution by comparing rates of evolution of prefrontal cortex, frontal motor cortex, and posterior cerebellar hemispheres along individual branches of the primate tree of life. We provide a detailed evolutionary model of the neuroanatomical changes leading to modern human lateralized motor functioning, demonstrating an increased role for the fronto-cerebellar system in the apes dating to their evolutionary divergence from the monkeys (∼30 million years ago (Mya)), and a subsequent shift toward an increased role for prefrontal cortex over frontal motor cortex in the fronto-cerebellar system in the Homo-Pan ancestral lineage (∼10 Mya) and in the human ancestral lineage (∼6 Mya). We discuss these results in the context of cortico-cerebellar functions and their likely role in the evolution of human tool use and speech. PMID:23647442

Evolutionary Conflict Between Maternal and Paternal Interests: Integration with Evolutionary Endocrinology.

PubMed

Mokkonen, Mikael; Koskela, Esa; Mappes, Tapio; Mills, Suzanne C

2016-08-01

Conflict between mates, as well as conflict between parents and offspring are due to divergent evolutionary interests of the interacting individuals. Hormone systems provide genetically based proximate mechanisms for mediating phenotypic adaptation and maladaptation characteristic of evolutionary conflict between individuals. Testosterone (T) is among the most commonly studied hormones in evolutionary biology, and as such, its role in shaping sexually dimorphic behaviors and physiology is relatively well understood, but its role in evolutionary conflict is not as clear. In this review, we outline the genomic conflicts arising within the family unit, and incorporate multiple lines of evidence from the bank vole (Myodes glareolus) system to outline how T impacts traits associated with reproduction and survival, resulting in a sexually antagonistic genetic trade-off in fitness. A major prediction arising from this work is that lower T is favored in females, whereas the optimal T level in males fluctuates in relation to social and ecological factors. We additionally discuss future directions to further integrate endocrinology into the study of sexual and parent-offspring conflicts. © The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Vehicle expectations in air transportation for the year 2000

NASA Technical Reports Server (NTRS)

Hearth, D. P.

1980-01-01

This paper is intended to provide an overview of the air transportation system for the year 2000 in terms of vehicle expectations. Emphasis is placed on civil air transportation with the time period approached from the standpoint of evolutionary changes for the near term and also with the assumption of more revolutionary changes for the far term. The view along the evolutionary path begins with a historical review of airline market growth and the impact that technologies have had on airplane designs. Projections of the life expectancy of existing, derivative, and new airplanes are examined in terms of their productivity and fuel efficiency in view of the present and projected fuel usage and availability. The factors influencing airline growth are outlined and some views on whether another new generation of subsonic airplanes are in the offing are given along with an assessment of the economic viability of an advanced commercial supersonic transport in terms of its higher speed, higher productivity, and higher fuel usage. With regard to revolutionary changes, major technology breakthroughs are assumed to occur at a specified date. As an example, the impact of a dramatic reduction in skin friction drag is examined in terms of its effect on the airplane configuration, its propulsion systems, it projected fuel usage, and the air transportation system in which it must operate.

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

NASA Astrophysics Data System (ADS)

Kurismaa, Andres

2015-08-01

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

Evolving self-assembly in autonomous homogeneous robots: experiments with two physical robots.

PubMed

Ampatzis, Christos; Tuci, Elio; Trianni, Vito; Christensen, Anders Lyhne; Dorigo, Marco

2009-01-01

This research work illustrates an approach to the design of controllers for self-assembling robots in which the self-assembly is initiated and regulated by perceptual cues that are brought forth by the physical robots through their dynamical interactions. More specifically, we present a homogeneous control system that can achieve assembly between two modules (two fully autonomous robots) of a mobile self-reconfigurable system without a priori introduced behavioral or morphological heterogeneities. The controllers are dynamic neural networks evolved in simulation that directly control all the actuators of the two robots. The neurocontrollers cause the dynamic specialization of the robots by allocating roles between them based solely on their interaction. We show that the best evolved controller proves to be successful when tested on a real hardware platform, the swarm-bot. The performance achieved is similar to the one achieved by existing modular or behavior-based approaches, also due to the effect of an emergent recovery mechanism that was neither explicitly rewarded by the fitness function, nor observed during the evolutionary simulation. Our results suggest that direct access to the orientations or intentions of the other agents is not a necessary condition for robot coordination: Our robots coordinate without direct or explicit communication, contrary to what is assumed by most research works in collective robotics. This work also contributes to strengthening the evidence that evolutionary robotics is a design methodology that can tackle real-world tasks demanding fine sensory-motor coordination.

Excess digestive capacity in predators reflects a life of feast and famine.

PubMed

Armstrong, Jonathan B; Schindler, Daniel E

2011-07-06

A central challenge for predators is achieving positive energy balance when prey are spatially and temporally heterogeneous. Ecological heterogeneity produces evolutionary trade-offs in the physiological design of predators; this is because the ability to capitalize on pulses of food abundance requires high capacity for food-processing, yet maintaining such capacity imposes energetic costs that are taxing during periods of food scarcity. Recent advances in physiology show that when variation in foraging opportunities is predictable, animals may adjust energetic trade-offs by rapidly modulating their digestive system to track variation in foraging opportunities. However, it is increasingly recognized that foraging opportunities for animals are unpredictable, which should favour animals that maintain a capacity for food-processing that exceeds average levels of consumption (loads). Despite this basic principle of quantitative evolutionary design, estimates of digestive load:capacity ratios in wild animals are virtually non-existent. Here we provide an extensive assessment of load:capacity ratios for the digestive systems of predators in the wild, compiling 639 estimates across 38 species of fish. We found that piscine predators typically maintain the physiological capacity to feed at daily rates 2-3 times higher than what they experience on average. A numerical simulation of the trade-off between food-processing capacity and metabolic cost suggests that the observed level of physiological opportunism is profitable only if predator-prey encounters, and thus predator energy budgets, are far more variable in nature than currently assumed.

Convergent evolution in mechanical design of lamnid sharks and tunas.

PubMed

Donley, Jeanine M; Sepulveda, Chugey A; Konstantinidis, Peter; Gemballa, Sven; Shadwick, Robert E

2004-05-06

The evolution of 'thunniform' body shapes in several different groups of vertebrates, including whales, ichthyosaurs and several species of large pelagic fishes supports the view that physical and hydromechanical demands provided important selection pressures to optimize body design for locomotion during vertebrate evolution. Recognition of morphological similarities between lamnid sharks (the most well known being the great white and the mako) and tunas has led to a general expectation that they also have converged in their functional design; however, no quantitative data exist on the mechanical performance of the locomotor system in lamnid sharks. Here we examine the swimming kinematics, in vivo muscle dynamics and functional morphology of the force-transmission system in a lamnid shark, and show that the evolutionary convergence in body shape and mechanical design between the distantly related lamnids and tunas is much more than skin deep; it extends to the depths of the myotendinous architecture and the mechanical basis for propulsive movements. We demonstrate that not only have lamnids and tunas converged to a much greater extent than previously known, but they have also developed morphological and functional adaptations in their locomotor systems that are unlike virtually all other fishes.

Enzyme Sequestration as a Tuning Point in Controlling Response Dynamics of Signalling Networks

PubMed Central

Ollivier, Julien F.; Soyer, Orkun S.

2016-01-01

Signalling networks result from combinatorial interactions among many enzymes and scaffolding proteins. These complex systems generate response dynamics that are often essential for correct decision-making in cells. Uncovering biochemical design principles that underpin such response dynamics is a prerequisite to understand evolved signalling networks and to design synthetic ones. Here, we use in silico evolution to explore the possible biochemical design space for signalling networks displaying ultrasensitive and adaptive response dynamics. By running evolutionary simulations mimicking different biochemical scenarios, we find that enzyme sequestration emerges as a key mechanism for enabling such dynamics. Inspired by these findings, and to test the role of sequestration, we design a generic, minimalist model of a signalling cycle, featuring two enzymes and a single scaffolding protein. We show that this simple system is capable of displaying both ultrasensitive and adaptive response dynamics. Furthermore, we find that tuning the concentration or kinetics of the sequestering protein can shift system dynamics between these two response types. These empirical results suggest that enzyme sequestration through scaffolding proteins is exploited by evolution to generate diverse response dynamics in signalling networks and could provide an engineering point in synthetic biology applications. PMID:27163612

Faster Evolution of More Multifunctional Logic Circuits

NASA Technical Reports Server (NTRS)

Stoica, Adrian; Zebulum, Ricardo

2005-01-01

A modification in a method of automated evolutionary synthesis of voltage-controlled multifunctional logic circuits makes it possible to synthesize more circuits in less time. Prior to the modification, the computations for synthesizing a four-function logic circuit by this method took about 10 hours. Using the method as modified, it is possible to synthesize a six-function circuit in less than half an hour. The concepts of automated evolutionary synthesis and voltage-controlled multifunctional logic circuits were described in a number of prior NASA Tech Briefs articles. To recapitulate: A circuit is designed to perform one of several different logic functions, depending on the value of an applied control voltage. The circuit design is synthesized following an automated evolutionary approach that is so named because it is modeled partly after the repetitive trial-and-error process of biological evolution. In this process, random populations of integer strings that encode electronic circuits play a role analogous to that of chromosomes. An evolved circuit is tested by computational simulation (prior to testing in real hardware to verify a final design). Then, in a fitness-evaluation step, responses of the circuit are compared with specifications of target responses and circuits are ranked according to how close they come to satisfying specifications. The results of the evaluation provide guidance for refining designs through further iteration.

Laterality and the evolution of the prefronto-cerebellar system in anthropoids.

PubMed

Smaers, Jeroen B; Steele, James; Case, Charleen R; Amunts, Katrin

2013-06-01

There is extensive evidence for an early vertebrate origin of lateralized motor behavior and of related asymmetries in underlying brain systems. We investigate human lateralized motor functioning in a broad comparative context of evolutionary neural reorganization. We quantify evolutionary trends in the fronto-cerebellar system (involved in motor learning) across 46 million years of divergent primate evolution by comparing rates of evolution of prefrontal cortex, frontal motor cortex, and posterior cerebellar hemispheres along individual branches of the primate tree of life. We provide a detailed evolutionary model of the neuroanatomical changes leading to modern human lateralized motor functioning, demonstrating an increased role for the fronto-cerebellar system in the apes dating to their evolutionary divergence from the monkeys (∼30 million years ago (Mya)), and a subsequent shift toward an increased role for prefrontal cortex over frontal motor cortex in the fronto-cerebellar system in the Homo-Pan ancestral lineage (∼10 Mya) and in the human ancestral lineage (∼6 Mya). We discuss these results in the context of cortico-cerebellar functions and their likely role in the evolution of human tool use and speech. © 2013 New York Academy of Sciences.

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

PubMed

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

2016-09-01

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

The Role of Evolutionary Biology in Research and Control of Liver Flukes in Southeast Asia

PubMed Central

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

2016-01-01

Stimulated largely by the availability of new technology, biomedical research at the molecular-level and chemical-based control approaches arguably dominate the field of infectious diseases. Along with this, the proximate view of disease etiology predominates to the exclusion of the ultimate, evolutionary biology-based, causation perspective. Yet, historically and up to today, research in evolutionary biology has provided much of the foundation for understanding the mechanisms underlying disease transmission dynamics, virulence, and the design of effective integrated control strategies. Here we review the state of knowledge regarding the biology of Asian liver Fluke-host relationship, parasitology, phylodynamics, drug-based interventions and liver Fluke-related cancer etiology from an evolutionary biology perspective. We consider how evolutionary principles, mechanisms and research methods could help refine our understanding of clinical disease associated with infection by Liver Flukes as well as their transmission dynamics. We identify a series of questions for an evolutionary biology research agenda for the liver Fluke that should contribute to an increased understanding of liver Fluke-associated diseases. Finally, we describe an integrative evolutionary medicine approach to liver Fluke prevention and control highlighting the need to better contextualize interventions within a broader human health and sustainable development framework. PMID:27197053

Deep evolutionary origins of neurobiology

PubMed Central

Mancuso, Stefano

2009-01-01

It is generally assumed, both in common-sense argumentations and scientific concepts, that brains and neurons represent late evolutionary achievements which are present only in more advanced animals. Here we overview recently published data clearly revealing that our understanding of bacteria, unicellular eukaryotic organisms, plants, brains and neurons, rooted in the Aristotelian philosophy is flawed. Neural aspects of biological systems are obvious already in bacteria and unicellular biological units such as sexual gametes and diverse unicellular eukaryotic organisms. Altogether, processes and activities thought to represent evolutionary ‘recent’ specializations of the nervous system emerge rather to represent ancient and fundamental cell survival processes. PMID:19513267

Semantic Web Compatible Names and Descriptions for Organisms

NASA Astrophysics Data System (ADS)

Wang, H.; Wilson, N.; McGuinness, D. L.

2012-12-01

Modern scientific names are critical for understanding the biological literature and provide a valuable way to understand evolutionary relationships. To validly publish a name, a description is required to separate the described group of organisms from those described by other names at the same level of the taxonomic hierarchy. The frequent revision of descriptions due to new evolutionary evidence has lead to situations where a single given scientific name may over time have multiple descriptions associated with it and a given published description may apply to multiple scientific names. Because of these many-to-many relationships between scientific names and descriptions, the usage of scientific names as a proxy for descriptions is inevitably ambiguous. Another issue lies in the fact that the precise application of scientific names often requires careful microscopic work, or increasingly, genetic sequencing, as scientific names are focused on the evolutionary relatedness between and within named groups such as species, genera, families, etc. This is problematic to many audiences, especially field biologists, who often do not have access to the instruments and tools required to make identifications on a microscopic or genetic basis. To better connect scientific names to descriptions and find a more convenient way to support computer assisted identification, we proposed the Semantic Vernacular System, a novel naming system that creates named, machine-interpretable descriptions for groups of organisms, and is compatible with the Semantic Web. Unlike the evolutionary relationship based scientific naming system, it emphasizes the observable features of organisms. By independently naming the descriptions composed of sets of observational features, as well as maintaining connections to scientific names, it preserves the observational data used to identify organisms. The system is designed to support a peer-review mechanism for creating new names, and uses a controlled vocabulary encoded in the Web Ontology Language to represent the observational features. A prototype of the system is currently under development in collaboration with the Mushroom Observer website. It allows users to propose new names and descriptions for fungi, provide feedback on those proposals, and ultimately have them formally approved. It relies on SPARQL queries and semantic reasoning for data management. This effort will offer the mycology community a knowledge base of fungal observational features and a tool for identifying fungal observations. It will also serve as an operational specification of how the Semantic Vernacular System can be used in practice in one scientific community (in this case mycology).

A review and experimental study on the application of classifiers and evolutionary algorithms in EEG-based brain-machine interface systems

NASA Astrophysics Data System (ADS)

Tahernezhad-Javazm, Farajollah; Azimirad, Vahid; Shoaran, Maryam

2018-04-01

Objective. Considering the importance and the near-future development of noninvasive brain-machine interface (BMI) systems, this paper presents a comprehensive theoretical-experimental survey on the classification and evolutionary methods for BMI-based systems in which EEG signals are used. Approach. The paper is divided into two main parts. In the first part, a wide range of different types of the base and combinatorial classifiers including boosting and bagging classifiers and evolutionary algorithms are reviewed and investigated. In the second part, these classifiers and evolutionary algorithms are assessed and compared based on two types of relatively widely used BMI systems, sensory motor rhythm-BMI and event-related potentials-BMI. Moreover, in the second part, some of the improved evolutionary algorithms as well as bi-objective algorithms are experimentally assessed and compared. Main results. In this study two databases are used, and cross-validation accuracy (CVA) and stability to data volume (SDV) are considered as the evaluation criteria for the classifiers. According to the experimental results on both databases, regarding the base classifiers, linear discriminant analysis and support vector machines with respect to CVA evaluation metric, and naive Bayes with respect to SDV demonstrated the best performances. Among the combinatorial classifiers, four classifiers, Bagg-DT (bagging decision tree), LogitBoost, and GentleBoost with respect to CVA, and Bagging-LR (bagging logistic regression) and AdaBoost (adaptive boosting) with respect to SDV had the best performances. Finally, regarding the evolutionary algorithms, single-objective invasive weed optimization (IWO) and bi-objective nondominated sorting IWO algorithms demonstrated the best performances. Significance. We present a general survey on the base and the combinatorial classification methods for EEG signals (sensory motor rhythm and event-related potentials) as well as their optimization methods through the evolutionary algorithms. In addition, experimental and statistical significance tests are carried out to study the applicability and effectiveness of the reviewed methods.

Why don’t you use Evolutionary Algorithms in Big Data?

NASA Astrophysics Data System (ADS)

Stanovov, Vladimir; Brester, Christina; Kolehmainen, Mikko; Semenkina, Olga

2017-02-01

In this paper we raise the question of using evolutionary algorithms in the area of Big Data processing. We show that evolutionary algorithms provide evident advantages due to their high scalability and flexibility, their ability to solve global optimization problems and optimize several criteria at the same time for feature selection, instance selection and other data reduction problems. In particular, we consider the usage of evolutionary algorithms with all kinds of machine learning tools, such as neural networks and fuzzy systems. All our examples prove that Evolutionary Machine Learning is becoming more and more important in data analysis and we expect to see the further development of this field especially in respect to Big Data.

On the Materials Science of Nature's Arms Race.

PubMed

Liu, Zengqian; Zhang, Zhefeng; Ritchie, Robert O

2018-06-05

Biological material systems have evolved unique combinations of mechanical properties to fulfill their specific function through a series of ingenious designs. Seeking lessons from Nature by replicating the underlying principles of such biological materials offers new promise for creating unique combinations of properties in man-made systems. One case in point is Nature's means of attack and defense. During the long-term evolutionary "arms race," naturally evolved weapons have achieved exceptional mechanical efficiency with a synergy of effective offense and persistence-two characteristics that often tend to be mutually exclusive in many synthetic systems-which may present a notable source of new materials science knowledge and inspiration. This review categorizes Nature's weapons into ten distinct groups, and discusses the unique structural and mechanical designs of each group by taking representative systems as examples. The approach described is to extract the common principles underlying such designs that could be translated into man-made materials. Further, recent advances in replicating the design principles of natural weapons at differing lengthscales in artificial materials, devices and tools to tackle practical problems are revisited, and the challenges associated with biological and bioinspired materials research in terms of both processing and properties are discussed. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

System Analysis and Performance Benefits of an Optimized Rotorcraft Propulsion System

NASA Technical Reports Server (NTRS)

Bruckner, Robert J.

2007-01-01

The propulsion system of rotorcraft vehicles is the most critical system to the vehicle in terms of safety and performance. The propulsion system must provide both vertical lift and forward flight propulsion during the entire mission. Whereas propulsion is a critical element for all flight vehicles, it is particularly critical for rotorcraft due to their limited safe, un-powered landing capability. This unparalleled reliability requirement has led rotorcraft power plants down a certain evolutionary path in which the system looks and performs quite similarly to those of the 1960 s. By and large the advancements in rotorcraft propulsion have come in terms of safety and reliability and not in terms of performance. The concept of the optimized propulsion system is a means by which both reliability and performance can be improved for rotorcraft vehicles. The optimized rotorcraft propulsion system which couples an oil-free turboshaft engine to a highly loaded gearbox that provides axial load support for the power turbine can be designed with current laboratory proven technology. Such a system can provide up to 60% weight reduction of the propulsion system of rotorcraft vehicles. Several technical challenges are apparent at the conceptual design level and should be addressed with current research.

Do aggressive signals evolve towards higher reliability or lower costs of assessment?

PubMed

Ręk, P

2014-12-01

It has been suggested that the evolution of signals must be a wasteful process for the signaller, aimed at the maximization of signal honesty. However, the reliability of communication depends not only on the costs paid by signallers but also on the costs paid by receivers during assessment, and less attention has been given to the interaction between these two types of costs during the evolution of signalling systems. A signaller and receiver may accept some level of signal dishonesty by choosing signals that are cheaper in terms of assessment but that are stabilized with less reliable mechanisms. I studied the potential trade-off between signal reliability and the costs of signal assessment in the corncrake (Crex crex). I found that the birds prefer signals that are less costly regarding assessment rather than more reliable. Despite the fact that the fundamental frequency of calls was a strong predictor of male size, it was ignored by receivers unless they could directly compare signal variants. My data revealed a response advantage of costly signals when comparison between calls differing with fundamental frequencies is fast and straightforward, whereas cheap signalling is preferred in natural conditions. These data might improve our understanding of the influence of receivers on signal design because they support the hypothesis that fully honest signalling systems may be prone to dishonesty based on the effects of receiver costs and be replaced by signals that are cheaper in production and reception but more susceptible to cheating. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Darwin in Mind: New Opportunities for Evolutionary Psychology

PubMed Central

Bolhuis, Johan J.; Brown, Gillian R.; Richardson, Robert C.; Laland, Kevin N.

2011-01-01

Evolutionary Psychology (EP) views the human mind as organized into many modules, each underpinned by psychological adaptations designed to solve problems faced by our Pleistocene ancestors. We argue that the key tenets of the established EP paradigm require modification in the light of recent findings from a number of disciplines, including human genetics, evolutionary biology, cognitive neuroscience, developmental psychology, and paleoecology. For instance, many human genes have been subject to recent selective sweeps; humans play an active, constructive role in co-directing their own development and evolution; and experimental evidence often favours a general process, rather than a modular account, of cognition. A redefined EP could use the theoretical insights of modern evolutionary biology as a rich source of hypotheses concerning the human mind, and could exploit novel methods from a variety of adjacent research fields. PMID:21811401

Stochastic evolutionary voluntary public goods game with punishment in a Quasi-birth-and-death process.

PubMed

Quan, Ji; Liu, Wei; Chu, Yuqing; Wang, Xianjia

2017-11-23

Traditional replication dynamic model and the corresponding concept of evolutionary stable strategy (ESS) only takes into account whether the system can return to the equilibrium after being subjected to a small disturbance. In the real world, due to continuous noise, the ESS of the system may not be stochastically stable. In this paper, a model of voluntary public goods game with punishment is studied in a stochastic situation. Unlike the existing model, we describe the evolutionary process of strategies in the population as a generalized quasi-birth-and-death process. And we investigate the stochastic stable equilibrium (SSE) instead. By numerical experiments, we get all possible SSEs of the system for any combination of parameters, and investigate the influence of parameters on the probabilities of the system to select different equilibriums. It is found that in the stochastic situation, the introduction of the punishment and non-participation strategies can change the evolutionary dynamics of the system and equilibrium of the game. There is a large range of parameters that the system selects the cooperative states as its SSE with a high probability. This result provides us an insight and control method for the evolution of cooperation in the public goods game in stochastic situations.

An evolutionary algorithm technique for intelligence, surveillance, and reconnaissance plan optimization

NASA Astrophysics Data System (ADS)

Langton, John T.; Caroli, Joseph A.; Rosenberg, Brad

2008-04-01

To support an Effects Based Approach to Operations (EBAO), Intelligence, Surveillance, and Reconnaissance (ISR) planners must optimize collection plans within an evolving battlespace. A need exists for a decision support tool that allows ISR planners to rapidly generate and rehearse high-performing ISR plans that balance multiple objectives and constraints to address dynamic collection requirements for assessment. To meet this need we have designed an evolutionary algorithm (EA)-based "Integrated ISR Plan Analysis and Rehearsal System" (I2PARS) to support Effects-based Assessment (EBA). I2PARS supports ISR mission planning and dynamic replanning to coordinate assets and optimize their routes, allocation and tasking. It uses an evolutionary algorithm to address the large parametric space of route-finding problems which is sometimes discontinuous in the ISR domain because of conflicting objectives such as minimizing asset utilization yet maximizing ISR coverage. EAs are uniquely suited for generating solutions in dynamic environments and also allow user feedback. They are therefore ideal for "streaming optimization" and dynamic replanning of ISR mission plans. I2PARS uses the Non-dominated Sorting Genetic Algorithm (NSGA-II) to automatically generate a diverse set of high performing collection plans given multiple objectives, constraints, and assets. Intended end users of I2PARS include ISR planners in the Combined Air Operations Centers and Joint Intelligence Centers. Here we show the feasibility of applying the NSGA-II algorithm and EAs in general to the ISR planning domain. Unique genetic representations and operators for optimization within the ISR domain are presented along with multi-objective optimization criteria for ISR planning. Promising results of the I2PARS architecture design, early software prototype, and limited domain testing of the new algorithm are discussed. We also present plans for future research and development, as well as technology transition goals.

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

NASA Astrophysics Data System (ADS)

Gingras, Bruno; Marin, Manuela M.

2015-06-01

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

A Diagnostic Assessment of Evolutionary Multiobjective Optimization for Water Resources Systems

NASA Astrophysics Data System (ADS)

Reed, P.; Hadka, D.; Herman, J.; Kasprzyk, J.; Kollat, J.

2012-04-01

This study contributes a rigorous diagnostic assessment of state-of-the-art multiobjective evolutionary algorithms (MOEAs) and highlights key advances that the water resources field can exploit to better discover the critical tradeoffs constraining our systems. This study provides the most comprehensive diagnostic assessment of MOEAs for water resources to date, exploiting more than 100,000 MOEA runs and trillions of design evaluations. The diagnostic assessment measures the effectiveness, efficiency, reliability, and controllability of ten benchmark MOEAs for a representative suite of water resources applications addressing rainfall-runoff calibration, long-term groundwater monitoring (LTM), and risk-based water supply portfolio planning. The suite of problems encompasses a range of challenging problem properties including (1) many-objective formulations with 4 or more objectives, (2) multi-modality (or false optima), (3) nonlinearity, (4) discreteness, (5) severe constraints, (6) stochastic objectives, and (7) non-separability (also called epistasis). The applications are representative of the dominant problem classes that have shaped the history of MOEAs in water resources and that will be dominant foci in the future. Recommendations are provided for which modern MOEAs should serve as tools and benchmarks in the future water resources literature.

Insect immunity shows specificity in protection upon secondary pathogen exposure.

PubMed

Sadd, Ben M; Schmid-Hempel, Paul

2006-06-20

Immunological memory in vertebrates, conferring lasting specific protection after an initial pathogen exposure, has implications for a broad spectrum of evolutionary, epidemiological, and medical phenomena . However, the existence of specificity in protection upon secondary pathogen exposure in invertebrates remains controversial . To separate this functional phenomenon from a particular mechanism, we refer to it as specific immune priming. We investigate the presence of specific immune priming in workers of the social insect Bombus terrestris. Using three bacterial pathogens, we test whether a prior homologous pathogen exposure gives a benefit in terms of long-term protection against a later challenge, over and above a heterologous combination. With a reciprocally designed initial and second-exposure protocol (i.e., all combinations of bacteria were tested), we demonstrate, even several weeks after the clearance of a first exposure, increased protection and narrow specificity upon secondary exposure. This demonstrates that the invertebrate immune system is functionally capable of unexpectedly specific and durable induced protection. Ultimately, despite general broad differences between vertebrates and invertebrates, the ability of both immune systems to show specificity in protection suggests that their immune defenses have found comparable solutions to similar selective pressures over evolutionary time.

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 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.

Hybrid routing technique for a fault-tolerant, integrated information network

NASA Technical Reports Server (NTRS)

Meredith, B. D.

1986-01-01

The evolutionary growth of the space station and the diverse activities onboard are expected to require a hierarchy of integrated, local area networks capable of supporting data, voice, and video communications. In addition, fault-tolerant network operation is necessary to protect communications between critical systems attached to the net and to relieve the valuable human resources onboard the space station of time-critical data system repair tasks. A key issue for the design of the fault-tolerant, integrated network is the development of a robust routing algorithm which dynamically selects the optimum communication paths through the net. A routing technique is described that adapts to topological changes in the network to support fault-tolerant operation and system evolvability.

The Consolidated Planning and Scheduling System for Space Transportation and Space Station operations - Successful development experience

NASA Technical Reports Server (NTRS)

Hornstein, Rhoda S.; Willoughby, John K.; Gardner, Jo A.; Shinkle, Gerald L.

1993-01-01

In 1992, NASA made the decision to evolve a Consolidated Planning System (CPS) by adding the Space Transportation System (STS) requirements to the Space Station Freedom (SSF) planning software. This paper describes this evolutionary process, which began with a series of six-month design-build-test cycles, using a domain-independent architecture and a set of developmental tools known as the Advanced Scheduling Environment. It is shown that, during these tests, the CPS could be used at multiple organizational levels of planning and for integrating schedules from geographically distributed (including international) planning environments. The potential for using the CPS for other planning and scheduling tasks in the SSF program is being currently examined.

Evolutionary Models for Simple Biosystems

NASA Astrophysics Data System (ADS)

Bagnoli, Franco

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

Evolutionary morphology of the hemolymph vascular system of basal araneomorph spiders (Araneae: Araneomorphae).

PubMed

Huckstorf, Katarina; Michalik, Peter; Ramírez, Martín; Wirkner, Christian S

2015-11-01

The superfamily Austrochiloidea (Austrochilidae and Gradungulidae) take a pivotal position in araneomorph spider phylogeny. In this discussion crevice weaver spiders (Filistatidae) are of equal interest. Especially data from these phylogenetically uncertain yet basal off branching groups can enlighten our understanding on the evolution of organ systems. In the course of a survey on the evolutionary morphology of the circulatory system in spiders we therefore investigated the hemolymph vascular system in two austrochiloid and one filistatid species. Additionally some data on a hypochilid and a gradungulid species are included. Using up-to-date morphological methods, the vascular systems in these spiders are visualized three dimensionally. Ground pattern features of the circulatory systems in austrochiloid spiders are presented and the data discussed along recent lines of phylogenetic hypotheses. Special topics highlighted are the intraspecific variability of the origins of some prosomal arteries and the evolutionary correlation of respiratory and circulatory systems in spiders. Copyright © 2015 Elsevier Ltd. All rights reserved.

Optimization of the p-xylene oxidation process by a multi-objective differential evolution algorithm with adaptive parameters co-derived with the population-based incremental learning algorithm

NASA Astrophysics Data System (ADS)

Guo, Zhan; Yan, Xuefeng

2018-04-01

Different operating conditions of p-xylene oxidation have different influences on the product, purified terephthalic acid. It is necessary to obtain the optimal combination of reaction conditions to ensure the quality of the products, cut down on consumption and increase revenues. A multi-objective differential evolution (MODE) algorithm co-evolved with the population-based incremental learning (PBIL) algorithm, called PBMODE, is proposed. The PBMODE algorithm was designed as a co-evolutionary system. Each individual has its own parameter individual, which is co-evolved by PBIL. PBIL uses statistical analysis to build a model based on the corresponding symbiotic individuals of the superior original individuals during the main evolutionary process. The results of simulations and statistical analysis indicate that the overall performance of the PBMODE algorithm is better than that of the compared algorithms and it can be used to optimize the operating conditions of the p-xylene oxidation process effectively and efficiently.

Computational Aerothermodynamic Design Issues for Hypersonic Vehicles

NASA Technical Reports Server (NTRS)

Gnoffo, Peter A.; Weilmuenster, K. James; Hamilton, H. Harris, II; Olynick, David R.; Venkatapathy, Ethiraj

1997-01-01

A brief review of the evolutionary progress in computational aerothermodynamics is presented. The current status of computational aerothermodynamics is then discussed, with emphasis on its capabilities and limitations for contributions to the design process of hypersonic vehicles. Some topics to be highlighted include: (1) aerodynamic coefficient predictions with emphasis on high temperature gas effects; (2) surface heating and temperature predictions for thermal protection system (TPS) design in a high temperature, thermochemical nonequilibrium environment; (3) methods for extracting and extending computational fluid dynamic (CFD) solutions for efficient utilization by all members of a multidisciplinary design team; (4) physical models; (5) validation process and error estimation; and (6) gridding and solution generation strategies. Recent experiences in the design of X-33 will be featured. Computational aerothermodynamic contributions to Mars Pathfinder, METEOR, and Stardust (Comet Sample return) will also provide context for this discussion. Some of the barriers that currently limit computational aerothermodynamics to a predominantly reactive mode in the design process will also be discussed, with the goal of providing focus for future research.

Computational Aerothermodynamic Design Issues for Hypersonic Vehicles

NASA Technical Reports Server (NTRS)

Gnoffo, Peter A.; Weilmuenster, K. James; Hamilton, H. Harris, II; Olynick, David R.; Venkatapathy, Ethiraj

2005-01-01

A brief review of the evolutionary progress in computational aerothermodynamics is presented. The current status of computational aerothermodynamics is then discussed, with emphasis on its capabilities and limitations for contributions to the design process of hypersonic vehicles. Some topics to be highlighted include: (1) aerodynamic coefficient predictions with emphasis on high temperature gas effects; (2) surface heating and temperature predictions for thermal protection system (TPS) design in a high temperature, thermochemical nonequilibrium environment; (3) methods for extracting and extending computational fluid dynamic (CFD) solutions for efficient utilization by all members of a multidisciplinary design team; (4) physical models; (5) validation process and error estimation; and (6) gridding and solution generation strategies. Recent experiences in the design of X-33 will be featured. Computational aerothermodynamic contributions to Mars Path finder, METEOR, and Stardust (Comet Sample return) will also provide context for this discussion. Some of the barriers that currently limit computational aerothermodynamics to a predominantly reactive mode in the design process will also be discussed, with the goal of providing focus for future research.

Computational Aerothermodynamic Design Issues for Hypersonic Vehicles

NASA Technical Reports Server (NTRS)

Olynick, David R.; Venkatapathy, Ethiraj

2004-01-01

A brief review of the evolutionary progress in computational aerothermodynamics is presented. The current status of computational aerothermodynamics is then discussed, with emphasis on its capabilities and limitations for contributions to the design process of hypersonic vehicles. Some topics to be highlighted include: (1) aerodynamic coefficient predictions with emphasis on high temperature gas effects; (2) surface heating and temperature predictions for thermal protection system (TPS) design in a high temperature, thermochemical nonequilibrium environment; (3) methods for extracting and extending computational fluid dynamic (CFD) solutions for efficient utilization by all members of a multidisciplinary design team; (4) physical models; (5) validation process and error estimation; and (6) gridding and solution generation strategies. Recent experiences in the design of X-33 will be featured. Computational aerothermodynamic contributions to Mars Pathfinder, METEOR, and Stardust (Comet Sample return) will also provide context for this discussion. Some of the barriers that currently limit computational aerothermodynamics to a predominantly reactive mode in the design process will also be discussed, with the goal of providing focus for future research.

Metabolic analysis of adaptive evolution for in silico-designed lactate-producing strains.

PubMed

Hua, Qiang; Joyce, Andrew R; Fong, Stephen S; Palsson, Bernhard Ø

2006-12-05

Experimental evolution is now frequently applied to many biological systems to achieve desired objectives. To obtain optimized performance for metabolite production, a successful strategy has been recently developed that couples metabolic engineering techniques with laboratory evolution of microorganisms. Previously, we reported the growth characteristics of three lactate-producing, adaptively evolved Escherichia coli mutant strains designed by the OptKnock computational algorithm. Here, we describe the use of (13)C-labeled experiments and mass distribution measurements to study the evolutionary effects on the fluxome of these differently designed strains. Metabolic flux ratios and intracellular flux distributions as well as physiological data were used to elucidate metabolic responses over the course of adaptive evolution and metabolic differences among strains. The study of 3 unevolved and 12 evolved engineered strains as well as a wild-type strain suggests that evolution resulted in remarkable improvements in both substrate utilization rate and the proportion of glycolytic flux to total glucose utilization flux. Among three strain designs, the most significant increases in the fraction of glucose catabolized through glycolysis (>50%) and the glycolytic fluxes (>twofold) were observed in phosphotransacetylase and phosphofructokinase 1 (PFK1) double deletion (pta- pfkA) strains, which were likely attributed to the dramatic evolutionary increase in gene expression and catalytic activity of the minor PFK encoded by pfkB. These fluxomic studies also revealed the important role of acetate synthetic pathway in anaerobic lactate production. Moreover, flux analysis suggested that independent of genetic background, optimal relative flux distributions in cells could be achieved faster than physiological parameters such as nutrient utilization rate. (c) 2006 Wiley Periodicals, Inc.

Multiobjective Particle Swarm Optimization for the optimal design of photovoltaic grid-connected systems

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

Kornelakis, Aris

2010-12-15

Particle Swarm Optimization (PSO) is a highly efficient evolutionary optimization algorithm. In this paper a multiobjective optimization algorithm based on PSO applied to the optimal design of photovoltaic grid-connected systems (PVGCSs) is presented. The proposed methodology intends to suggest the optimal number of system devices and the optimal PV module installation details, such that the economic and environmental benefits achieved during the system's operational lifetime period are both maximized. The objective function describing the economic benefit of the proposed optimization process is the lifetime system's total net profit which is calculated according to the method of the Net Present Valuemore » (NPV). The second objective function, which corresponds to the environmental benefit, equals to the pollutant gas emissions avoided due to the use of the PVGCS. The optimization's decision variables are the optimal number of the PV modules, the PV modules optimal tilt angle, the optimal placement of the PV modules within the available installation area and the optimal distribution of the PV modules among the DC/AC converters. (author)« less

Thermal Development Test of the NEXT PM1 Ion Engine

NASA Technical Reports Server (NTRS)

Anderson, John R.; Snyder, John S.; VanNoord, Jonathan L.; Soulas, George C.

2010-01-01

NASA's Evolutionary Xenon Thruster (NEXT) is a next-generation high-power ion propulsion system under development by NASA as a part of the In-Space Propulsion Technology Program. NEXT is designed for use on robotic exploration missions of the solar system using solar electric power. Potential mission destinations that could benefit from a NEXT Solar Electric Propulsion (SEP) system include inner planets, small bodies, and outer planets and their moons. This range of robotic exploration missions generally calls for ion propulsion systems with deep throttling capability and system input power ranging from 0.6 to 25 kW, as referenced to solar array output at 1 Astronomical Unit (AU). Thermal development testing of the NEXT prototype model 1 (PM1) was conducted at JPL to assist in developing and validating a thruster thermal model and assessing the thermal design margins. NEXT PM1 performance prior to, during and subsequent to thermal testing are presented. Test results are compared to the predicted hot and cold environments expected missions and the functionality of the thruster for these missions is discussed.

Toward a revised evolutionary adaptationist analysis of depression: the social navigation hypothesis.

PubMed

Watson, Paul J; Andrews, Paul W

2002-10-01

Evolutionary biologists use Darwinian theory and functional design ("reverse engineering") analyses, to develop and test hypotheses about the adaptive functions of traits. Based upon a consideration of human social life and a functional design analysis of depression's core symptomatology we offer a comprehensive theory of its adaptive significance called the Social Navigation Hypothesis (SNH). The SNH attempts to account for all intensities of depression based on standard evolutionary theories of sociality, communication and psychological pain. The SNH suggests that depression evolved to perform two complimentary social problem-solving functions. First, depression induces cognitive changes that focus and enhance capacities for the accurate analysis and solution of key social problems, suggesting a social rumination function. Second, the costs associated with the anhedonia and psychomotor perturbation of depression can persuade reluctant social partners to provide help or make concessions via two possible mechanisms, namely, honest signaling and passive, unintentional fitness extortion. Thus it may also have a social motivation function.

A Multipopulation Coevolutionary Strategy for Multiobjective Immune Algorithm

PubMed Central

Shi, Jiao; Gong, Maoguo; Ma, Wenping; Jiao, Licheng

2014-01-01

How to maintain the population diversity is an important issue in designing a multiobjective evolutionary algorithm. This paper presents an enhanced nondominated neighbor-based immune algorithm in which a multipopulation coevolutionary strategy is introduced for improving the population diversity. In the proposed algorithm, subpopulations evolve independently; thus the unique characteristics of each subpopulation can be effectively maintained, and the diversity of the entire population is effectively increased. Besides, the dynamic information of multiple subpopulations is obtained with the help of the designed cooperation operator which reflects a mutually beneficial relationship among subpopulations. Subpopulations gain the opportunity to exchange information, thereby expanding the search range of the entire population. Subpopulations make use of the reference experience from each other, thereby improving the efficiency of evolutionary search. Compared with several state-of-the-art multiobjective evolutionary algorithms on well-known and frequently used multiobjective and many-objective problems, the proposed algorithm achieves comparable results in terms of convergence, diversity metrics, and running time on most test problems. PMID:24672330

Definition of technology development missions for early space station satellite servicing, volume 2

NASA Technical Reports Server (NTRS)

1983-01-01

The results of all aspects of the early space station satellite servicing study tasks are presented. These results include identification of servicing tasks (and locations), identification of servicing mission system and detailed objectives, functional/operational requirements analyses of multiple servicing scenarios, assessment of critical servicing technology capabilities and development of an evolutionary capability plan, design and validation of selected servicing technology development missions (TDMs), identification of space station satellite servicing accommodation needs, and the cost and schedule implications of acquiring both required technology capability development and conducting the selected TDMs.

An Application Development Platform for Neuromorphic Computing

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

Dean, Mark; Chan, Jason; Daffron, Christopher

2016-01-01

Dynamic Adaptive Neural Network Arrays (DANNAs) are neuromorphic computing systems developed as a hardware based approach to the implementation of neural networks. They feature highly adaptive and programmable structural elements, which model arti cial neural networks with spiking behavior. We design them to solve problems using evolutionary optimization. In this paper, we highlight the current hardware and software implementations of DANNA, including their features, functionalities and performance. We then describe the development of an Application Development Platform (ADP) to support efficient application implementation and testing of DANNA based solutions. We conclude with future directions.

CARE 3 User's Workshop

NASA Technical Reports Server (NTRS)

1988-01-01

A user's workshop for CARE 3, a reliability assessment tool designed and developed especially for the evaluation of high reliability fault tolerant digital systems, was held at NASA Langley Research Center on October 6 to 7, 1987. The main purpose of the workshop was to assess the evolutionary status of CARE 3. The activities of the workshop are documented and papers are included by user's of CARE 3 and NASA. Features and limitations of CARE 3 and comparisons to other tools are presented. The conclusions to a workshop questionaire are also discussed.

Improving processes through evolutionary optimization.

PubMed

Clancy, Thomas R

2011-09-01

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies on complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 18th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, I discuss methods to optimize complex healthcare processes through learning, adaptation, and evolutionary planning.

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 genetics of the Drosophila alcohol dehydrogenase gene-enzyme system.

PubMed

Heinstra, P W

1993-01-01

Evolutionary genetics embodies a broad research area that ranges from the DNA level to studies of genetic aspects in populations. In all cases the purpose is to determine the impact of genetic variation on evolutionary change. The broad range of evolutionary genetics requires the involvement of a diverse group of researchers: molecular biologists, (population) geneticists, biochemists, physiologists, ecologists, ethologists and theorists, each of which has its own insights and interests. For example, biochemists are often not concerned with the physiological function of a protein (with respect to pH, substrates, temperature, etc.), while ecologists, in turn, are often not interested in the biochemical-physiological aspects underlying the traits they study. This review deals with several evolutionary aspects of the Drosophila alcohol dehydrogenase gene-enzyme system, and includes my own personal viewpoints. I have tried to condense and integrate the current knowledge in this field as it has developed since the comprehensive review by van Delden (1982). Details on specific issues may be gained from Sofer and Martin (1987), Sullivan, Atkinson and Starmer (1990); Chambers (1988, 1991); Geer, Miller and Heinstra (1991); and Winberg and McKinley-McKee (1992).

Mechanically assisted liquid lens zoom system for mobile phone cameras

NASA Astrophysics Data System (ADS)

Wippermann, F. C.; Schreiber, P.; Bräuer, A.; Berge, B.

2006-08-01

Camera systems with small form factor are an integral part of today's mobile phones which recently feature auto focus functionality. Ready to market solutions without moving parts have been developed by using the electrowetting technology. Besides virtually no deterioration, easy control electronics and simple and therefore cost-effective fabrication, this type of liquid lenses enables extremely fast settling times compared to mechanical approaches. As a next evolutionary step mobile phone cameras will be equipped with zoom functionality. We present first order considerations for the optical design of a miniaturized zoom system based on liquid-lenses and compare it to its mechanical counterpart. We propose a design of a zoom lens with a zoom factor of 2.5 considering state-of-the-art commercially available liquid lens products. The lens possesses auto focus capability and is based on liquid lenses and one additional mechanical actuator. The combination of liquid lenses and a single mechanical actuator enables extremely short settling times of about 20ms for the auto focus and a simplified mechanical system design leading to lower production cost and longer life time. The camera system has a mechanical outline of 24mm in length and 8mm in diameter. The lens with f/# 3.5 provides market relevant optical performance and is designed for an image circle of 6.25mm (1/2.8" format sensor).

[Charles Darwin and the problem of evolutionary progress].

PubMed

Iordanskiĭ, N N

2010-01-01

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

Optimal lunar soft landing trajectories using taboo evolutionary programming

NASA Astrophysics Data System (ADS)

Mutyalarao, M.; Raj, M. Xavier James

A safe lunar landing is a key factor to undertake an effective lunar exploration. Lunar lander consists of four phases such as launch phase, the earth-moon transfer phase, circumlunar phase and landing phase. The landing phase can be either hard landing or soft landing. Hard landing means the vehicle lands under the influence of gravity without any deceleration measures. However, soft landing reduces the vertical velocity of the vehicle before landing. Therefore, for the safety of the astronauts as well as the vehicle lunar soft landing with an acceptable velocity is very much essential. So it is important to design the optimal lunar soft landing trajectory with minimum fuel consumption. Optimization of Lunar Soft landing is a complex optimal control problem. In this paper, an analysis related to lunar soft landing from a parking orbit around Moon has been carried out. A two-dimensional trajectory optimization problem is attempted. The problem is complex due to the presence of system constraints. To solve the time-history of control parameters, the problem is converted into two point boundary value problem by using the maximum principle of Pontrygen. Taboo Evolutionary Programming (TEP) technique is a stochastic method developed in recent years and successfully implemented in several fields of research. It combines the features of taboo search and single-point mutation evolutionary programming. Identifying the best unknown parameters of the problem under consideration is the central idea for many space trajectory optimization problems. The TEP technique is used in the present methodology for the best estimation of initial unknown parameters by minimizing objective function interms of fuel requirements. The optimal estimation subsequently results into an optimal trajectory design of a module for soft landing on the Moon from a lunar parking orbit. Numerical simulations demonstrate that the proposed approach is highly efficient and it reduces the minimum fuel consumption. The results are compared with the available results in literature shows that the solution of present algorithm is better than some of the existing algorithms. Keywords: soft landing, trajectory optimization, evolutionary programming, control parameters, Pontrygen principle.

The major synthetic evolutionary transitions.

PubMed

Solé, Ricard

2016-08-19

Evolution is marked by well-defined events involving profound innovations that are known as 'major evolutionary transitions'. They involve the integration of autonomous elements into a new, higher-level organization whereby the former isolated units interact in novel ways, losing their original autonomy. All major transitions, which include the origin of life, cells, multicellular systems, societies or language (among other examples), took place millions of years ago. Are these transitions unique, rare events? Have they instead universal traits that make them almost inevitable when the right pieces are in place? Are there general laws of evolutionary innovation? In order to approach this problem under a novel perspective, we argue that a parallel class of evolutionary transitions can be explored involving the use of artificial evolutionary experiments where alternative paths to innovation can be explored. These 'synthetic' transitions include, for example, the artificial evolution of multicellular systems or the emergence of language in evolved communicating robots. These alternative scenarios could help us to understand the underlying laws that predate the rise of major innovations and the possibility for general laws of evolved complexity. Several key examples and theoretical approaches are summarized and future challenges are outlined.This article is part of the themed issue 'The major synthetic evolutionary transitions'. © 2016 The Author(s).

Making evolutionary history count: biodiversity planning for coral reef fishes and the conservation of evolutionary processes

NASA Astrophysics Data System (ADS)

von der Heyden, Sophie

2017-03-01

Anthropogenic activities are having devastating impacts on marine systems with numerous knock-on effects on trophic functioning, species interactions and an accelerated loss of biodiversity. Establishing conservation areas can not only protect biodiversity, but also confer resilience against changes to coral reefs and their inhabitants. Planning for protection and conservation in marine systems is complex, but usually focuses on maintaining levels of biodiversity and protecting special and unique landscape features while avoiding negative impacts to socio-economic benefits. Conversely, the integration of evolutionary processes that have shaped extant species assemblages is rarely taken into account. However, it is as important to protect processes as it is to protect patterns for maintaining the evolutionary trajectories of populations and species. This review focuses on different approaches for integrating genetic analyses, such as phylogenetic diversity, phylogeography and the delineation of management units, temporal and spatial monitoring of genetic diversity and quantification of adaptive variation for protecting evolutionary resilience, into marine spatial planning, specifically for coral reef fishes. Many of these concepts are not yet readily applied to coral reef fish studies, but this synthesis highlights their potential and the importance of including historical processes into systematic biodiversity planning for conserving not only extant, but also future, biodiversity and its evolutionary potential.

The major synthetic evolutionary transitions

PubMed Central

Solé, Ricard

2016-01-01

Evolution is marked by well-defined events involving profound innovations that are known as ‘major evolutionary transitions'. They involve the integration of autonomous elements into a new, higher-level organization whereby the former isolated units interact in novel ways, losing their original autonomy. All major transitions, which include the origin of life, cells, multicellular systems, societies or language (among other examples), took place millions of years ago. Are these transitions unique, rare events? Have they instead universal traits that make them almost inevitable when the right pieces are in place? Are there general laws of evolutionary innovation? In order to approach this problem under a novel perspective, we argue that a parallel class of evolutionary transitions can be explored involving the use of artificial evolutionary experiments where alternative paths to innovation can be explored. These ‘synthetic’ transitions include, for example, the artificial evolution of multicellular systems or the emergence of language in evolved communicating robots. These alternative scenarios could help us to understand the underlying laws that predate the rise of major innovations and the possibility for general laws of evolved complexity. Several key examples and theoretical approaches are summarized and future challenges are outlined. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID:27431528

From experimental systems to evolutionary biology: an impossible journey?

PubMed

Morange, Michel

2013-01-01

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

Requirements controlled design: A method for discovery of discontinuous system boundaries in the requirements hyperspace

NASA Astrophysics Data System (ADS)

Hollingsworth, Peter Michael

The drive toward robust systems design, especially with respect to system affordability throughout the system life-cycle, has led to the development of several advanced design methods. While these methods have been extremely successful in satisfying the needs for which they have been developed, they inherently leave a critical area unaddressed. None of them fully considers the effect of requirements on the selection of solution systems. The goal of all of current modern design methodologies is to bring knowledge forward in the design process to the regions where more design freedom is available and design changes cost less. Therefore, it seems reasonable to consider the point in the design process where the greatest restrictions are placed on the final design, the point in which the system level requirements are set. Historically the requirements have been treated as something handed down from above. However, neither the customer nor the solution provider completely understood all of the options that are available in the broader requirements space. If a method were developed that provided the ability to understand the full scope of the requirements space, it would allow for a better comparison of potential solution systems with respect to both the current and potential future requirements. The key to a requirements conscious method is to treat requirements differently from the traditional approach. The method proposed herein is known as Requirements Controlled Design (RCD). By treating the requirements as a set of variables that control the behavior of the system, instead of variables that only define the response of the system, it is possible to determine a-priori what portions of the requirements space that any given system is capable of satisfying. Additionally, it should be possible to identify which systems can satisfy a given set of requirements and the locations where a small change in one or more requirements poses a significant risk to a design program. This thesis puts forth the theory and methodology to enable RCD, and details and validates a specific method called the Modified Strength Pareto Evolutionary Algorithm (MSPEA).

RiboMaker: computational design of conformation-based riboregulation.

PubMed

Rodrigo, Guillermo; Jaramillo, Alfonso

2014-09-01

The ability to engineer control systems of gene expression is instrumental for synthetic biology. Thus, bioinformatic methods that assist such engineering are appealing because they can guide the sequence design and prevent costly experimental screening. In particular, RNA is an ideal substrate to de novo design regulators of protein expression by following sequence-to-function models. We have implemented a novel algorithm, RiboMaker, aimed at the computational, automated design of bacterial riboregulation. RiboMaker reads the sequence and structure specifications, which codify for a gene regulatory behaviour, and optimizes the sequences of a small regulatory RNA and a 5'-untranslated region for an efficient intermolecular interaction. To this end, it implements an evolutionary design strategy, where random mutations are selected according to a physicochemical model based on free energies. The resulting sequences can then be tested experimentally, providing a new tool for synthetic biology, and also for investigating the riboregulation principles in natural systems. Web server is available at http://ribomaker.jaramillolab.org/. Source code, instructions and examples are freely available for download at http://sourceforge.net/projects/ribomaker/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Constraints imposed by pollinator behaviour on the ecology and evolution of plant mating systems.

PubMed

Devaux, C; Lepers, C; Porcher, E

2014-07-01

Most flowering plants rely on pollinators for their reproduction. Plant-pollinator interactions, although mutualistic, involve an inherent conflict of interest between both partners and may constrain plant mating systems at multiple levels: the immediate ecological plant selfing rates, their distribution in and contribution to pollination networks, and their evolution. Here, we review experimental evidence that pollinator behaviour influences plant selfing rates in pairs of interacting species, and that plants can modify pollinator behaviour through plastic and evolutionary changes in floral traits. We also examine how theoretical studies include pollinators, implicitly or explicitly, to investigate the role of their foraging behaviour in plant mating system evolution. In doing so, we call for more evolutionary models combining ecological and genetic factors, and additional experimental data, particularly to describe pollinator foraging behaviour. Finally, we show that recent developments in ecological network theory help clarify the impact of community-level interactions on plant selfing rates and their evolution and suggest new research avenues to expand the study of mating systems of animal-pollinated plant species to the level of the plant-pollinator networks. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Local Nash equilibrium in social networks.

PubMed

Zhang, Yichao; Aziz-Alaoui, M A; Bertelle, Cyrille; Guan, Jihong

2014-08-29

Nash equilibrium is widely present in various social disputes. As of now, in structured static populations, such as social networks, regular, and random graphs, the discussions on Nash equilibrium are quite limited. In a relatively stable static gaming network, a rational individual has to comprehensively consider all his/her opponents' strategies before they adopt a unified strategy. In this scenario, a new strategy equilibrium emerges in the system. We define this equilibrium as a local Nash equilibrium. In this paper, we present an explicit definition of the local Nash equilibrium for the two-strategy games in structured populations. Based on the definition, we investigate the condition that a system reaches the evolutionary stable state when the individuals play the Prisoner's dilemma and snow-drift game. The local Nash equilibrium provides a way to judge whether a gaming structured population reaches the evolutionary stable state on one hand. On the other hand, it can be used to predict whether cooperators can survive in a system long before the system reaches its evolutionary stable state for the Prisoner's dilemma game. Our work therefore provides a theoretical framework for understanding the evolutionary stable state in the gaming populations with static structures.

Local Nash Equilibrium in Social Networks

PubMed Central

Zhang, Yichao; Aziz-Alaoui, M. A.; Bertelle, Cyrille; Guan, Jihong

2014-01-01

Nash equilibrium is widely present in various social disputes. As of now, in structured static populations, such as social networks, regular, and random graphs, the discussions on Nash equilibrium are quite limited. In a relatively stable static gaming network, a rational individual has to comprehensively consider all his/her opponents' strategies before they adopt a unified strategy. In this scenario, a new strategy equilibrium emerges in the system. We define this equilibrium as a local Nash equilibrium. In this paper, we present an explicit definition of the local Nash equilibrium for the two-strategy games in structured populations. Based on the definition, we investigate the condition that a system reaches the evolutionary stable state when the individuals play the Prisoner's dilemma and snow-drift game. The local Nash equilibrium provides a way to judge whether a gaming structured population reaches the evolutionary stable state on one hand. On the other hand, it can be used to predict whether cooperators can survive in a system long before the system reaches its evolutionary stable state for the Prisoner's dilemma game. Our work therefore provides a theoretical framework for understanding the evolutionary stable state in the gaming populations with static structures. PMID:25169150

Local Nash Equilibrium in Social Networks

NASA Astrophysics Data System (ADS)

Zhang, Yichao; Aziz-Alaoui, M. A.; Bertelle, Cyrille; Guan, Jihong

2014-08-01

Nash equilibrium is widely present in various social disputes. As of now, in structured static populations, such as social networks, regular, and random graphs, the discussions on Nash equilibrium are quite limited. In a relatively stable static gaming network, a rational individual has to comprehensively consider all his/her opponents' strategies before they adopt a unified strategy. In this scenario, a new strategy equilibrium emerges in the system. We define this equilibrium as a local Nash equilibrium. In this paper, we present an explicit definition of the local Nash equilibrium for the two-strategy games in structured populations. Based on the definition, we investigate the condition that a system reaches the evolutionary stable state when the individuals play the Prisoner's dilemma and snow-drift game. The local Nash equilibrium provides a way to judge whether a gaming structured population reaches the evolutionary stable state on one hand. On the other hand, it can be used to predict whether cooperators can survive in a system long before the system reaches its evolutionary stable state for the Prisoner's dilemma game. Our work therefore provides a theoretical framework for understanding the evolutionary stable state in the gaming populations with static structures.

The concept of ageing in evolutionary algorithms: Discussion and inspirations for human ageing.

PubMed

Dimopoulos, Christos; Papageorgis, Panagiotis; Boustras, George; Efstathiades, Christodoulos

2017-04-01

This paper discusses the concept of ageing as this applies to the operation of Evolutionary Algorithms, and examines its relationship to the concept of ageing as this is understood for human beings. Evolutionary Algorithms constitute a family of search algorithms which base their operation on an analogy from the evolution of species in nature. The paper initially provides the necessary knowledge on the operation of Evolutionary Algorithms, focusing on the use of ageing strategies during the implementation of the evolutionary process. Background knowledge on the concept of ageing, as this is defined scientifically for biological systems, is subsequently presented. Based on this information, the paper provides a comparison between the two ageing concepts, and discusses the philosophical inspirations which can be drawn for human ageing based on the operation of Evolutionary Algorithms. Copyright © 2017 Elsevier B.V. All rights reserved.

Selection on Network Dynamics Drives Differential Rates of Protein Domain Evolution

PubMed Central

Mannakee, Brian K.; Gutenkunst, Ryan N.

2016-01-01

The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein’s rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate within networks in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces. PMID:27380265

Ecological and evolutionary traps

USGS Publications Warehouse

Schlaepfer, Martin A.; Runge, M.C.; Sherman, P.W.

2002-01-01

Organisms often rely on environmental cues to make behavioral and life-history decisions. However, in environments that have been altered suddenly by humans, formerly reliable cues might no longer be associated with adaptive outcomes. In such cases, organisms can become 'trapped' by their evolutionary responses to the cues and experience reduced survival or reproduction. Ecological traps occur when organisms make poor habitat choices based on cues that correlated formerly with habitat quality. Ecological traps are part of a broader phenomenon, evolutionary traps, involving a dissociation between cues that organisms use to make any behavioral or life-history decision and outcomes normally associated with that decision. A trap can lead to extinction if a population falls below a critical size threshold before adaptation to the novel environment occurs. Conservation and management protocols must be designed in light of, rather than in spite of, the behavioral mechanisms and evolutionary history of populations and species to avoid 'trapping' them.

Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

PubMed

Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

2011-07-01

In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

The design of a petabyte archive and distribution system for the NASA ECS project

NASA Technical Reports Server (NTRS)

Caulk, Parris M.

1994-01-01

The NASA EOS Data and Information System (EOSDIS) Core System (ECS) will contain one of the largest data management systems ever built - the ECS Science and Data Processing System (SDPS). SDPS is designed to support long term Global Change Research by acquiring, producing, and storing earth science data, and by providing efficient means for accessing and manipulating that data. The first two releases of SDPS, Release A and Release B, will be operational in 1997 and 1998, respectively. Release B will be deployed at eight Distributed Active Archiving Centers (DAAC's). Individual DAAC's will archive different collections of earth science data, and will vary in archive capacity. The storage and management of these data collections is the responsibility of the SDPS Data Server subsystem. It is anticipated that by the year 2001, the Data Server subsystem at the Goddard DAAC must support a near-line data storage capacity of one petabyte. The development of SDPS is a system integration effort in which COTS products will be used in favor of custom components in very possible way. Some software and hardware capabilities required to meet ECS data volume and storage management requirements beyond 1999 are not yet supported by available COTS products. The ECS project will not undertake major custom development efforts to provide these capabilities. Instead, SDPS and its Data Server subsystem are designed to support initial implementations with current products, and provide an evolutionary framework that facilitates the introduction of advanced COTS products as they become available. This paper provides a high-level description of the Data Server subsystem design from a COTS integration standpoint, and discussed some of the major issues driving the design. The paper focuses on features of the design that will make the system scalable and adaptable to changing technologies.

Evolutionary optimization of compact dielectric lens for farfield sub-wavelength imaging

PubMed Central

Zhang, Jingjing

2015-01-01

The resolution of conventional optical lenses is limited by diffraction. For decades researchers have made various attempts to beat the diffraction limit and realize subwavelength imaging. Here we present the approach to design modified solid immersion lenses that deliver the subwavelength information of objects into the far field, yielding magnified images. The lens is composed of an isotropic dielectric core and anisotropic or isotropic dielectric matching layers. It is designed by combining a transformation optics forward design with an inverse design scheme, where an evolutionary optimization procedure is applied to find the material parameters for the matching layers. Notably, the total radius of the lens is only 2.5 wavelengths and the resolution can reach λ/6. Compared to previous approaches based on the simple discretized approximation of a coordinate transformation design, our method allows for much more precise recovery of the information of objects, especially for those with asymmetric shapes. It allows for the far-field subwavelength imaging at optical frequencies with compact dielectric devices. PMID:26017657

Evolutionary Design of a Phased Array Antenna Element

NASA Technical Reports Server (NTRS)

Globus, Al; Linden, Derek; Lohn, Jason

2006-01-01

We present an evolved S-band phased array antenna element design that meets the requirements of NASA's TDRS-C communications satellite scheduled for launch early next decade. The original 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 genetic algorithm and stochastic hill-climbing has been fabricated and tested. Laboratory results are largely consistent with simulation. Researchers have been investigating evolutionary antenna design and optimization since the early 1990s, and the field has grown in recent years its computer speed has increased and electromagnetic simulators have improved. Many antenna types have been investigated, including wire antennas, antenna arrays and quadrifilar helical antennas. In particular, our laboratory evolved a wire antenna design for NASA's Space Technology 5 (ST5) spacecraft. This antenna has been fabricated, tested, and is scheduled for launch on the three spacecraft in 2006.

A Tale of Four Stories: Soil Ecology, Theory, Evolution and the Publication System

PubMed Central

Barot, Sébastien; Blouin, Manuel; Fontaine, Sébastien; Jouquet, Pascal; Lata, Jean-Christophe; Mathieu, Jérôme

2007-01-01

Background Soil ecology has produced a huge corpus of results on relations between soil organisms, ecosystem processes controlled by these organisms and links between belowground and aboveground processes. However, some soil scientists think that soil ecology is short of modelling and evolutionary approaches and has developed too independently from general ecology. We have tested quantitatively these hypotheses through a bibliographic study (about 23000 articles) comparing soil ecology journals, generalist ecology journals, evolutionary ecology journals and theoretical ecology journals. Findings We have shown that soil ecology is not well represented in generalist ecology journals and that soil ecologists poorly use modelling and evolutionary approaches. Moreover, the articles published by a typical soil ecology journal (Soil Biology and Biochemistry) are cited by and cite low percentages of articles published in generalist ecology journals, evolutionary ecology journals and theoretical ecology journals. Conclusion This confirms our hypotheses and suggests that soil ecology would benefit from an effort towards modelling and evolutionary approaches. This effort should promote the building of a general conceptual framework for soil ecology and bridges between soil ecology and general ecology. We give some historical reasons for the parsimonious use of modelling and evolutionary approaches by soil ecologists. We finally suggest that a publication system that classifies journals according to their Impact Factors and their level of generality is probably inadequate to integrate “particularity” (empirical observations) and “generality” (general theories), which is the goal of all natural sciences. Such a system might also be particularly detrimental to the development of a science such as ecology that is intrinsically multidisciplinary. PMID:18043755

Feeling good: autonomic nervous system responding in five positive emotions.

PubMed

Shiota, Michelle N; Neufeld, Samantha L; Yeung, Wan H; Moser, Stephanie E; Perea, Elaine F

2011-12-01

Although dozens of studies have examined the autonomic nervous system (ANS) aspects of negative emotions, less is known about ANS responding in positive emotion. An evolutionary framework was used to define five positive emotions in terms of fitness-enhancing function, and to guide hypotheses regarding autonomic responding. In a repeated measures design, participants viewed sets of visual images eliciting these positive emotions (anticipatory enthusiasm, attachment love, nurturant love, amusement, and awe) plus an emotionally neutral state. Peripheral measures of sympathetic and vagal parasympathetic activation were assessed. Results indicated that the emotion conditions were characterized by qualitatively distinct profiles of autonomic activation, suggesting the existence of multiple, physiologically distinct positive emotions. (c) 2011 APA, all rights reserved.

Evolution and physiology of neural oxygen sensing

PubMed Central

Costa, Kauê M.; Accorsi-Mendonça, Daniela; Moraes, Davi J. A.; Machado, Benedito H.

2014-01-01

Major evolutionary trends in animal physiology have been heavily influenced by atmospheric O2 levels. Amongst other important factors, the increase in atmospheric O2 which occurred in the Pre-Cambrian and the development of aerobic respiration beckoned the evolution of animal organ systems that were dedicated to the absorption and transportation of O2, e.g., the respiratory and cardiovascular systems of vertebrates. Global variations of O2 levels in post-Cambrian periods have also been correlated with evolutionary changes in animal physiology, especially cardiorespiratory function. Oxygen transportation systems are, in our view, ultimately controlled by the brain related mechanisms, which senses changes in O2 availability and regulates autonomic and respiratory responses that ensure the survival of the organism in the face of hypoxic challenges. In vertebrates, the major sensorial system for oxygen sensing and responding to hypoxia is the peripheral chemoreflex neuronal pathways, which includes the oxygen chemosensitive glomus cells and several brainstem regions involved in the autonomic regulation of the cardiovascular system and respiratory control. In this review we discuss the concept that regulating O2 homeostasis was one of the primordial roles of the nervous system. We also review the physiology of the peripheral chemoreflex, focusing on the integrative repercussions of chemoreflex activation and the evolutionary importance of this system, which is essential for the survival of complex organisms such as vertebrates. The contribution of hypoxia and peripheral chemoreflex for the development of diseases associated to the cardiovascular and respiratory systems is also discussed in an evolutionary context. PMID:25161625

Masses and ages of Delta Scuti stars in eclipsing binary systems

NASA Astrophysics Data System (ADS)

Tsvetkov, Ts. G.; Petrova, Ts. C.

1993-05-01

By using data mainly from Frolov et al. (1982) for four Delta Scuti stars in eclipsing binary systems, AB Cas, Y Cam, RS Cha, and AI Hya, their physical parameters, distances, and radial pulsation modes are determined. The evolutionary track systems of Iben (1967), Paczynski (1970), and Maeder and Meynet (1988) are interpolated in order to estimate evolutionary masses Me and ages t of these variables. Their pulsation masses MQ are estimated from the fitting formulae of Faulkner (1977) and Fitch (1981). Our estimates of evolutionary masses M(e) and pulsation masses M(Q) are close to the masses M determined by Frolov et al. from the star binarity. The only exception is AB Cas, for which there is no agreement between certain star parameters. Another, independent approach is also applied to the stars RS Cha and AI Hya: by using their photometric indices b - y and c(1) from the catalog of Lopez de Coca et al. (1990) and appropriate photometric calibrations, other sets of physical parameters, distances, modes, ages, and evolutionary and pulsation masses of both variables are obtained.

Quantifying rates of evolutionary adaptation in response to ocean acidification.

PubMed

Sunday, Jennifer M; Crim, Ryan N; Harley, Christopher D G; Hart, Michael W

2011-01-01

The global acidification of the earth's oceans is predicted to impact biodiversity via physiological effects impacting growth, survival, reproduction, and immunology, leading to changes in species abundances and global distributions. However, the degree to which these changes will play out critically depends on the evolutionary rate at which populations will respond to natural selection imposed by ocean acidification, which remains largely unquantified. Here we measure the potential for an evolutionary response to ocean acidification in larval development rate in two coastal invertebrates using a full-factorial breeding design. We show that the sea urchin species Strongylocentrotus franciscanus has vastly greater levels of phenotypic and genetic variation for larval size in future CO(2) conditions compared to the mussel species Mytilus trossulus. Using these measures we demonstrate that S. franciscanus may have faster evolutionary responses within 50 years of the onset of predicted year-2100 CO(2) conditions despite having lower population turnover rates. Our comparisons suggest that information on genetic variation, phenotypic variation, and key demographic parameters, may lend valuable insight into relative evolutionary potentials across a large number of species.

In Vitro "Evolutionary Arms-Races" Between Hosts and Parasites in an Artificial RNA Replication System

NASA Astrophysics Data System (ADS)

Furubayashi, T.; Bansho, Y.; Motooka, D.; Nakamura, S.; Ichihashi, N.

2017-07-01

We performed coevolution of artificial RNA self-replicators and parasitic replicators in microdroplets. We observed evolutionary arms-races with oscillating population dynamics and faster evolution of self-replicators caused by parasitic replicators.

Evolutionary mechanics: new engineering principles for the emergence of flexibility in a dynamic and uncertain world.

PubMed

Whitacre, James M; Rohlfshagen, Philipp; Bender, Axel; Yao, Xin

2012-09-01

Engineered systems are designed to deftly operate under predetermined conditions yet are notoriously fragile when unexpected perturbations arise. In contrast, biological systems operate in a highly flexible manner; learn quickly adequate responses to novel conditions, and evolve new routines and traits to remain competitive under persistent environmental change. A recent theory on the origins of biological flexibility has proposed that degeneracy-the existence of multi-functional components with partially overlapping functions-is a primary determinant of the robustness and adaptability found in evolved systems. While degeneracy's contribution to biological flexibility is well documented, there has been little investigation of degeneracy design principles for achieving flexibility in systems engineering. Actually, the conditions that can lead to degeneracy are routinely eliminated in engineering design. With the planning of transportation vehicle fleets taken as a case study, this article reports evidence that degeneracy improves the robustness and adaptability of a simulated fleet towards unpredicted changes in task requirements without incurring costs to fleet efficiency. We find that degeneracy supports faster rates of design adaptation and ultimately leads to better fleet designs. In investigating the limitations of degeneracy as a design principle, we consider decision-making difficulties that arise from degeneracy's influence on fleet complexity. While global decision-making becomes more challenging, we also find degeneracy accommodates rapid distributed decision-making leading to (near-optimal) robust system performance. Given the range of conditions where favorable short-term and long-term performance outcomes are observed, we propose that degeneracy may fundamentally alter the propensity for adaptation and is useful within different engineering and planning contexts.

Making evolutionary biology a basic science for medicine

PubMed Central

Nesse, Randolph M.; Bergstrom, Carl T.; Ellison, Peter T.; Flier, Jeffrey S.; Gluckman, Peter; Govindaraju, Diddahally R.; Niethammer, Dietrich; Omenn, Gilbert S.; Perlman, Robert L.; Schwartz, Mark D.; Thomas, Mark G.; Stearns, Stephen C.; Valle, David

2010-01-01

New applications of evolutionary biology in medicine are being discovered at an accelerating rate, but few physicians have sufficient educational background to use them fully. This article summarizes suggestions from several groups that have considered how evolutionary biology can be useful in medicine, what physicians should learn about it, and when and how they should learn it. Our general conclusion is that evolutionary biology is a crucial basic science for medicine. In addition to looking at established evolutionary methods and topics, such as population genetics and pathogen evolution, we highlight questions about why natural selection leaves bodies vulnerable to disease. Knowledge about evolution provides physicians with an integrative framework that links otherwise disparate bits of knowledge. It replaces the prevalent view of bodies as machines with a biological view of bodies shaped by evolutionary processes. Like other basic sciences, evolutionary biology needs to be taught both before and during medical school. Most introductory biology courses are insufficient to establish competency in evolutionary biology. Premedical students need evolution courses, possibly ones that emphasize medically relevant aspects. In medical school, evolutionary biology should be taught as one of the basic medical sciences. This will require a course that reviews basic principles and specific medical applications, followed by an integrated presentation of evolutionary aspects that apply to each disease and organ system. Evolutionary biology is not just another topic vying for inclusion in the curriculum; it is an essential foundation for a biological understanding of health and disease. PMID:19918069

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

PubMed

Nesse, Randolph M; Bergstrom, Carl T; Ellison, Peter T; Flier, Jeffrey S; Gluckman, Peter; Govindaraju, Diddahally R; Niethammer, Dietrich; Omenn, Gilbert S; Perlman, Robert L; Schwartz, Mark D; Thomas, Mark G; Stearns, Stephen C; Valle, David

2010-01-26

New applications of evolutionary biology in medicine are being discovered at an accelerating rate, but few physicians have sufficient educational background to use them fully. This article summarizes suggestions from several groups that have considered how evolutionary biology can be useful in medicine, what physicians should learn about it, and when and how they should learn it. Our general conclusion is that evolutionary biology is a crucial basic science for medicine. In addition to looking at established evolutionary methods and topics, such as population genetics and pathogen evolution, we highlight questions about why natural selection leaves bodies vulnerable to disease. Knowledge about evolution provides physicians with an integrative framework that links otherwise disparate bits of knowledge. It replaces the prevalent view of bodies as machines with a biological view of bodies shaped by evolutionary processes. Like other basic sciences, evolutionary biology needs to be taught both before and during medical school. Most introductory biology courses are insufficient to establish competency in evolutionary biology. Premedical students need evolution courses, possibly ones that emphasize medically relevant aspects. In medical school, evolutionary biology should be taught as one of the basic medical sciences. This will require a course that reviews basic principles and specific medical applications, followed by an integrated presentation of evolutionary aspects that apply to each disease and organ system. Evolutionary biology is not just another topic vying for inclusion in the curriculum; it is an essential foundation for a biological understanding of health and disease.

Driving factors for the evolution of species-specific echolocation call design in new world free-tailed bats (molossidae).

PubMed

Jung, Kirsten; Molinari, Jesús; Kalko, Elisabeth K V

2014-01-01

Phylogeny, ecology, and sensorial constraints are thought to be the most important factors influencing echolocation call design in bats. The Molossidae is a diverse bat family with a majority of species restricted to tropical and subtropical regions. Most molossids are specialized to forage for insects in open space, and thus share similar navigational challenges. We use an unprecedented dataset on the echolocation calls of 8 genera and 18 species of New World molossids to explore how habitat, phylogenetic relatedness, body mass, and prey perception contribute to echolocation call design. Our results confirm that, with the exception of the genus Molossops, echolocation calls of these bats show a typical design for open space foraging. Two lines of evidence point to echolocation call structure of molossids reflecting phylogenetic relatedness. First, such structure is significantly more similar within than among genera. Second, except for allometric scaling, such structure is nearly the same in congeneric species. Despite contrasting body masses, 12 of 18 species call within a relatively narrow frequency range of 20 to 35 kHz, a finding that we explain by using a modeling approach whose results suggest this frequency range to be an adaptation optimizing prey perception in open space. To conclude, we argue that the high variability in echolocation call design of molossids is an advanced evolutionary trait allowing the flexible adjustment of echolocation systems to various sensorial challenges, while conserving sender identity for social communication. Unraveling evolutionary drivers for echolocation call design in bats has so far been hampered by the lack of adequate model organisms sharing a phylogenetic origin and facing similar sensorial challenges. We thus believe that knowledge of the echolocation call diversity of New World molossid bats may prove to be landmark to understand the evolution and functionality of species-specific signal design in bats.

Driving Factors for the Evolution of Species-Specific Echolocation Call Design in New World Free-Tailed Bats (Molossidae)

PubMed Central

Jung, Kirsten; Molinari, Jesús

2014-01-01

Phylogeny, ecology, and sensorial constraints are thought to be the most important factors influencing echolocation call design in bats. The Molossidae is a diverse bat family with a majority of species restricted to tropical and subtropical regions. Most molossids are specialized to forage for insects in open space, and thus share similar navigational challenges. We use an unprecedented dataset on the echolocation calls of 8 genera and 18 species of New World molossids to explore how habitat, phylogenetic relatedness, body mass, and prey perception contribute to echolocation call design. Our results confirm that, with the exception of the genus Molossops, echolocation calls of these bats show a typical design for open space foraging. Two lines of evidence point to echolocation call structure of molossids reflecting phylogenetic relatedness. First, such structure is significantly more similar within than among genera. Second, except for allometric scaling, such structure is nearly the same in congeneric species. Despite contrasting body masses, 12 of 18 species call within a relatively narrow frequency range of 20 to 35 kHz, a finding that we explain by using a modeling approach whose results suggest this frequency range to be an adaptation optimizing prey perception in open space. To conclude, we argue that the high variability in echolocation call design of molossids is an advanced evolutionary trait allowing the flexible adjustment of echolocation systems to various sensorial challenges, while conserving sender identity for social communication. Unraveling evolutionary drivers for echolocation call design in bats has so far been hampered by the lack of adequate model organisms sharing a phylogenetic origin and facing similar sensorial challenges. We thus believe that knowledge of the echolocation call diversity of New World molossid bats may prove to be landmark to understand the evolution and functionality of species-specific signal design in bats. PMID:24454833

Shape and Reinforcement Optimization of Underground Tunnels

NASA Astrophysics Data System (ADS)

Ghabraie, Kazem; Xie, Yi Min; Huang, Xiaodong; Ren, Gang

Design of support system and selecting an optimum shape for the opening are two important steps in designing excavations in rock masses. Currently selecting the shape and support design are mainly based on designer's judgment and experience. Both of these problems can be viewed as material distribution problems where one needs to find the optimum distribution of a material in a domain. Topology optimization techniques have proved to be useful in solving these kinds of problems in structural design. Recently the application of topology optimization techniques in reinforcement design around underground excavations has been studied by some researchers. In this paper a three-phase material model will be introduced changing between normal rock, reinforced rock, and void. Using such a material model both problems of shape and reinforcement design can be solved together. A well-known topology optimization technique used in structural design is bi-directional evolutionary structural optimization (BESO). In this paper the BESO technique has been extended to simultaneously optimize the shape of the opening and the distribution of reinforcements. Validity and capability of the proposed approach have been investigated through some examples.

Viruses and mobile elements as drivers of evolutionary transitions

PubMed Central

2016-01-01

The history of life is punctuated by evolutionary transitions which engender emergence of new levels of biological organization that involves selection acting at increasingly complex ensembles of biological entities. Major evolutionary transitions include the origin of prokaryotic and then eukaryotic cells, multicellular organisms and eusocial animals. All or nearly all cellular life forms are hosts to diverse selfish genetic elements with various levels of autonomy including plasmids, transposons and viruses. I present evidence that, at least up to and including the origin of multicellularity, evolutionary transitions are driven by the coevolution of hosts with these genetic parasites along with sharing of ‘public goods’. Selfish elements drive evolutionary transitions at two distinct levels. First, mathematical modelling of evolutionary processes, such as evolution of primitive replicator populations or unicellular organisms, indicates that only increasing organizational complexity, e.g. emergence of multicellular aggregates, can prevent the collapse of the host–parasite system under the pressure of parasites. Second, comparative genomic analysis reveals numerous cases of recruitment of genes with essential functions in cellular life forms, including those that enable evolutionary transitions. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID:27431520

Viruses and mobile elements as drivers of evolutionary transitions.

PubMed

Koonin, Eugene V

2016-08-19

The history of life is punctuated by evolutionary transitions which engender emergence of new levels of biological organization that involves selection acting at increasingly complex ensembles of biological entities. Major evolutionary transitions include the origin of prokaryotic and then eukaryotic cells, multicellular organisms and eusocial animals. All or nearly all cellular life forms are hosts to diverse selfish genetic elements with various levels of autonomy including plasmids, transposons and viruses. I present evidence that, at least up to and including the origin of multicellularity, evolutionary transitions are driven by the coevolution of hosts with these genetic parasites along with sharing of 'public goods'. Selfish elements drive evolutionary transitions at two distinct levels. First, mathematical modelling of evolutionary processes, such as evolution of primitive replicator populations or unicellular organisms, indicates that only increasing organizational complexity, e.g. emergence of multicellular aggregates, can prevent the collapse of the host-parasite system under the pressure of parasites. Second, comparative genomic analysis reveals numerous cases of recruitment of genes with essential functions in cellular life forms, including those that enable evolutionary transitions.This article is part of the themed issue 'The major synthetic evolutionary transitions'. © 2016 The Authors.

US Navy SHF SATCOM: Past, present and future

NASA Astrophysics Data System (ADS)

Bushnell, Christopher J.

1994-06-01

This thesis discusses the Navy's Super High Frequency Satellite Communications (SHF SATCOM) capabilities prior to Desert Shield/Desert Storm, and the requirements for future systems that were generated due to Navy SATCOM shortcomings during the Gulf War. The four-phased evolutionary approach the Navy has designed (based on post-war requirements) to provide itself with a medium for SHF SATCOM into the 21st Century, as well as the Defense Satellite Communications Systems (DSCS), are examined in detail. Decreasing defense budgets have begun to have a significant impact on future military satellite communication (MILSATCOM) systems. A cost comparison between utilization of DSCS III satellites and the INMARSAT commercial SATCOM system is presented. Recommended improvements to current MILSATCOM procedures and training practices are proposed that could improve operational C4I capabilities. Finally, this study determines that future SATCOM architectures should include a mixture of commercial systems and MILSATCOM systems to provide both cost savings and command and control protection.

Thermal Development Test of the NEXT PM1 ION Engine

NASA Technical Reports Server (NTRS)

Anderson, John R.; Snyder, John Steven; Van Noord, Jonathan L.; Soulas, George C.

2007-01-01

NASA's Evolutionary Xenon Thruster (NEXT) is a next-generation high-power ion thruster under development by NASA as a part of the In-Space Propulsion Technology Program. NEXT is designed for use on robotic exploration missions of the solar system using solar electric power. Potential mission destinations that could benefit from a NEXT Solar Electric Propulsion (SEP) system include inner planets, small bodies, and outer planets and their moons. This range of robotic exploration missions generally calls for ion propulsion systems with deep throttling capability and system input power ranging from 0.6 to 25 kW, as referenced to solar array output at 1 Astronomical Unit (AU). Thermal development testing of the NEXT prototype model 1 (PM1) was conducted at JPL to assist in developing and validating a thruster thermal model and assessing the thermal design margins. NEXT PM1 performance prior to, during and subsequent to thermal testing are presented. Test results are compared to the predicted hot and cold environments expected missions and the functionality of the thruster for these missions is discussed.

NASA's Evolutionary Xenon Thruster (NEXT) Long-Duration Test as of 736 kg of Propellant Throughput

NASA Technical Reports Server (NTRS)

Shastry, Rohit; Herman, Daniel A.; Soulas, George C.; Patterson, Michael J.

2012-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is developing the next-generation solar-electric ion propulsion system with significant enhancements beyond the state-of-the-art NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) ion propulsion system to provide future NASA science missions with enhanced mission capabilities. A Long-Duration Test (LDT) was initiated in June 2005 to validate the thruster service life modeling and to qualify the thruster propellant throughput capability. The thruster has set electric propulsion records for the longest operating duration, highest propellant throughput, and most total impulse demonstrated. At the time of this publication, the NEXT LDT has surpassed 42,100 h of operation, processed more than 736 kg of xenon propellant, and demonstrated greater than 28.1 MN s total impulse. Thruster performance has been steady with negligible degradation. The NEXT thruster design has mitigated several lifetime limiting mechanisms encountered in the NSTAR design, including the NSTAR first failure mode, thereby drastically improving thruster capabilities. Component erosion rates and the progression of the predicted life-limiting erosion mechanism for the thruster compare favorably to pretest predictions based upon semi-empirical ion thruster models used in the thruster service life assessment. Service life model validation has been accomplished by the NEXT LDT. Assuming full-power operation until test article failure, the models and extrapolated erosion data predict penetration of the accelerator grid grooves after more than 45,000 hours of operation while processing over 800 kg of xenon propellant. Thruster failure due to degradation of the accelerator grid structural integrity is expected after groove penetration.

NASA's Evolutionary Xenon Thruster (NEXT) Long-Duration Test as of 736 kg of Propellant Throughput

NASA Technical Reports Server (NTRS)

Shastry, Rohit; Herman, Daniel A.; Soulas, George C.; Patterson, Michael J.

2012-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is developing the next-generation solar-electric ion propulsion system with significant enhancements beyond the state-of-the-art NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) ion propulsion system to provide future NASA science missions with enhanced mission capabilities. A Long-Duration Test (LDT) was initiated in June 2005 to validate the thruster service life modeling and to qualify the thruster propellant throughput capability. The thruster has set electric propulsion records for the longest operating duration, highest propellant throughput, and most total impulse demonstrated. At the time of this publication, the NEXT LDT has surpassed 42,100 h of operation, processed more than 736 kg of xenon propellant, and demonstrated greater than 28.1 MN s total impulse. Thruster performance has been steady with negligible degradation. The NEXT thruster design has mitigated several lifetime limiting mechanisms encountered in the NSTAR design, including the NSTAR first failure mode, thereby drastically improving thruster capabilities. Component erosion rates and the progression of the predicted life-limiting erosion mechanism for the thruster compare favorably to pretest predictions based upon semi-empirical ion thruster models used in the thruster service life assessment. Service life model validation has been accomplished by the NEXT LDT. Assuming full-power operation until test article failure, the models and extrapolated erosion data predict penetration of the accelerator grid grooves after more than 45,000 hours of operation while processing over 800 kg of xenon propellant. Thruster failure due to degradation of the accelerator grid structural integrity is expected after

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.

An Interdisciplinary Model for Teaching Evolutionary Ecology.

ERIC Educational Resources Information Center

Coletta, John

1992-01-01

Describes a general systems evolutionary model and demonstrates how a previously established ecological model is a function of its past development based on the evolution of the rock, nutrient, and water cycles. Discusses the applications of the model in environmental education. (MDH)

Evolving locomotion for a 12-DOF quadruped robot in simulated environments.

PubMed

Klaus, Gordon; Glette, Kyrre; Høvin, Mats

2013-05-01

We demonstrate the power of evolutionary robotics (ER) by comparing to a more traditional approach its performance and cost on the task of simulated robot locomotion. A novel quadruped robot is introduced, the legs of which - each having three non-coplanar degrees of freedom - are very maneuverable. Using a simplistic control architecture and a physics simulation of the robot, gaits are designed both by hand and using a highly parallel evolutionary algorithm (EA). It is found that the EA produces, in a small fraction of the time that takes to design by hand, gaits that travel at two to four times the speed of the hand-designed one. The flexibility of this approach is demonstrated by applying it across a range of differently configured simulators. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

[Evolutionary medicine].

PubMed

Wjst, M

2013-12-01

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

[MiRNA system in unicellular eukaryotes and its evolutionary implications].

PubMed

Zhang, Yan-Qiong; Wen, Jian-Fan

2010-02-01

microRNAs (miRNAs) in higher multicellular eukaryotes have been extensively studied in recent years. Great progresses have also been achieved for miRNAs in unicellular eukaryotes. All these studies not only enrich our knowledge about the complex expression regulation system in diverse organisms, but also have evolutionary significance for understanding the origin of this system. In this review, Authors summarize the recent advance in the studies of miRNA in unicellular eukaryotes, including that on the most primitive unicellular eukaryote--Giardia. The origin and evolution of miRNA system is also discussed.

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.

Mission Advantages of NEXT: Nasa's Evolutionary Xenon Thruster

NASA Technical Reports Server (NTRS)

Oleson, Steven; Gefert, Leon; Benson, Scott; Patterson, Michael; Noca, Muriel; Sims, Jon

2002-01-01

With the demonstration of the NSTAR propulsion system on the Deep Space One mission, the range of the Discovery class of NASA missions can now be expanded. NSTAR lacks, however, sufficient performance for many of the more challenging Office of Space Science (OSS) missions. Recent studies have shown that NASA's Evolutionary Xenon Thruster (NEXT) ion propulsion system is the best choice for many exciting potential OSS missions including outer planet exploration and inner solar system sample returns. The NEXT system provides the higher power, higher specific impulse, and higher throughput required by these science missions.

Analysis and specification tools in relation to the APSE

NASA Technical Reports Server (NTRS)

Hendricks, John W.

1986-01-01

Ada and the Ada Programming Support Environment (APSE) specifically address the phases of the system/software life cycle which follow after the user's problem was translated into system and software development specifications. The waterfall model of the life cycle identifies the analysis and requirements definition phases as preceeding program design and coding. Since Ada is a programming language and the APSE is a programming support environment, they are primarily targeted to support program (code) development, tecting, and maintenance. The use of Ada based or Ada related specification languages (SLs) and program design languages (PDLs) can extend the use of Ada back into the software design phases of the life cycle. Recall that the standardization of the APSE as a programming support environment is only now happening after many years of evolutionary experience with diverse sets of programming support tools. Restricting consideration to one, or even a few chosen specification and design tools, could be a real mistake for an organization or a major project such as the Space Station, which will need to deal with an increasingly complex level of system problems. To require that everything be Ada-like, be implemented in Ada, run directly under the APSE, and fit into a rigid waterfall model of the life cycle would turn a promising support environment into a straight jacket for progress.

Adult sex ratio variation: implications for breeding system evolution.

PubMed

Székely, T; Weissing, F J; Komdeur, J

2014-08-01

Adult sex ratio (ASR) exhibits immense variation in nature, although neither the causes nor the implications of this variation are fully understood. According to theory, the ASR is expected to influence sex roles and breeding systems, as the rarer sex in the population has more potential partners to mate with than the more common sex. Changes in mate choice, mating systems and parental care suggest that the ASR does influence breeding behaviour, although there is a need for more tests, especially experimental ones. In the context of breeding system evolution, the focus is currently on operational sex ratios (OSRs). We argue that the ASR plays a role of similar importance and urge researchers to study the ASR and the OSR side by side. Finally, we plead for a dynamic view of breeding system evolution with feedbacks between mating, parenting, OSR and ASR on both ecological and evolutionary time scales. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Pareto Design of State Feedback Tracking Control of a Biped Robot via Multiobjective PSO in Comparison with Sigma Method and Genetic Algorithms: Modified NSGAII and MATLAB's Toolbox

PubMed Central

Mahmoodabadi, M. J.; Taherkhorsandi, M.; Bagheri, A.

2014-01-01

An optimal robust state feedback tracking controller is introduced to control a biped robot. In the literature, the parameters of the controller are usually determined by a tedious trial and error process. To eliminate this process and design the parameters of the proposed controller, the multiobjective evolutionary algorithms, that is, the proposed method, modified NSGAII, Sigma method, and MATLAB's Toolbox MOGA, are employed in this study. Among the used evolutionary optimization algorithms to design the controller for biped robots, the proposed method operates better in the aspect of designing the controller since it provides ample opportunities for designers to choose the most appropriate point based upon the design criteria. Three points are chosen from the nondominated solutions of the obtained Pareto front based on two conflicting objective functions, that is, the normalized summation of angle errors and normalized summation of control effort. Obtained results elucidate the efficiency of the proposed controller in order to control a biped robot. PMID:24616619

Wind farm optimization using evolutionary algorithms

NASA Astrophysics Data System (ADS)

Ituarte-Villarreal, Carlos M.

In recent years, the wind power industry has focused its efforts on solving the Wind Farm Layout Optimization (WFLO) problem. Wind resource assessment is a pivotal step in optimizing the wind-farm design and siting and, in determining whether a project is economically feasible or not. In the present work, three (3) different optimization methods are proposed for the solution of the WFLO: (i) A modified Viral System Algorithm applied to the optimization of the proper location of the components in a wind-farm to maximize the energy output given a stated wind environment of the site. The optimization problem is formulated as the minimization of energy cost per unit produced and applies a penalization for the lack of system reliability. The viral system algorithm utilized in this research solves three (3) well-known problems in the wind-energy literature; (ii) a new multiple objective evolutionary algorithm to obtain optimal placement of wind turbines while considering the power output, cost, and reliability of the system. The algorithm presented is based on evolutionary computation and the objective functions considered are the maximization of power output, the minimization of wind farm cost and the maximization of system reliability. The final solution to this multiple objective problem is presented as a set of Pareto solutions and, (iii) A hybrid viral-based optimization algorithm adapted to find the proper component configuration for a wind farm with the introduction of the universal generating function (UGF) analytical approach to discretize the different operating or mechanical levels of the wind turbines in addition to the various wind speed states. The proposed methodology considers the specific probability functions of the wind resource to describe their proper behaviors to account for the stochastic comportment of the renewable energy components, aiming to increase their power output and the reliability of these systems. The developed heuristic considers a variable number of system components and wind turbines with different operating characteristics and sizes, to have a more heterogeneous model that can deal with changes in the layout and in the power generation requirements over the time. Moreover, the approach evaluates the impact of the wind-wake effect of the wind turbines upon one another to describe and evaluate the power production capacity reduction of the system depending on the layout distribution of the wind turbines.

Reliability-based optimization of an active vibration controller using evolutionary algorithms

NASA Astrophysics Data System (ADS)

Saraygord Afshari, Sajad; Pourtakdoust, Seid H.

2017-04-01

Many modern industrialized systems such as aircrafts, rotating turbines, satellite booms, etc. cannot perform their desired tasks accurately if their uninhibited structural vibrations are not controlled properly. Structural health monitoring and online reliability calculations are emerging new means to handle system imposed uncertainties. As stochastic forcing are unavoidable, in most engineering systems, it is often needed to take them into the account for the control design process. In this research, smart material technology is utilized for structural health monitoring and control in order to keep the system in a reliable performance range. In this regard, a reliability-based cost function is assigned for both controller gain optimization as well as sensor placement. The proposed scheme is implemented and verified for a wing section. Comparison of results for the frequency responses is considered to show potential applicability of the presented technique.

A switching control law approach for cancer immunotherapy of an evolutionary tumor growth model.

PubMed

Doban, Alina I; Lazar, Mircea

2017-02-01

We propose a new approach for tumor immunotherapy which is based on a switching control strategy defined on domains of attraction of equilibria of interest. For this, we consider a recently derived model which captures the effects of the tumor cells on the immune system and viceversa, through predator-prey competition terms. Additionally, it incorporates the immune system's mechanism for producing hunting immune cells, which makes the model suitable for immunotherapy strategies analysis and design. For computing domains of attraction for the tumor nonlinear dynamics, and thus, for deriving immunotherapeutic strategies we employ rational Lyapunov functions. Finally, we apply the switching control strategy to destabilize an invasive tumor equilibrium and steer the system trajectories to tumor dormancy. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Research on Novel Algorithms for Smart Grid Reliability Assessment and Economic Dispatch

NASA Astrophysics Data System (ADS)

Luo, Wenjin

In this dissertation, several studies of electric power system reliability and economy assessment methods are presented. To be more precise, several algorithms in evaluating power system reliability and economy are studied. Furthermore, two novel algorithms are applied to this field and their simulation results are compared with conventional results. As the electrical power system develops towards extra high voltage, remote distance, large capacity and regional networking, the application of a number of new technique equipments and the electric market system have be gradually established, and the results caused by power cut has become more and more serious. The electrical power system needs the highest possible reliability due to its complication and security. In this dissertation the Boolean logic Driven Markov Process (BDMP) method is studied and applied to evaluate power system reliability. This approach has several benefits. It allows complex dynamic models to be defined, while maintaining its easy readability as conventional methods. This method has been applied to evaluate IEEE reliability test system. The simulation results obtained are close to IEEE experimental data which means that it could be used for future study of the system reliability. Besides reliability, modern power system is expected to be more economic. This dissertation presents a novel evolutionary algorithm named as quantum evolutionary membrane algorithm (QEPS), which combines the concept and theory of quantum-inspired evolutionary algorithm and membrane computation, to solve the economic dispatch problem in renewable power system with on land and offshore wind farms. The case derived from real data is used for simulation tests. Another conventional evolutionary algorithm is also used to solve the same problem for comparison. The experimental results show that the proposed method is quick and accurate to obtain the optimal solution which is the minimum cost for electricity supplied by wind farm system.

Identification of vehicle suspension parameters by design optimization

NASA Astrophysics Data System (ADS)

Tey, J. Y.; Ramli, R.; Kheng, C. W.; Chong, S. Y.; Abidin, M. A. Z.

2014-05-01

The design of a vehicle suspension system through simulation requires accurate representation of the design parameters. These parameters are usually difficult to measure or sometimes unavailable. This article proposes an efficient approach to identify the unknown parameters through optimization based on experimental results, where the covariance matrix adaptation-evolutionary strategy (CMA-es) is utilized to improve the simulation and experimental results against the kinematic and compliance tests. This speeds up the design and development cycle by recovering all the unknown data with respect to a set of kinematic measurements through a single optimization process. A case study employing a McPherson strut suspension system is modelled in a multi-body dynamic system. Three kinematic and compliance tests are examined, namely, vertical parallel wheel travel, opposite wheel travel and single wheel travel. The problem is formulated as a multi-objective optimization problem with 40 objectives and 49 design parameters. A hierarchical clustering method based on global sensitivity analysis is used to reduce the number of objectives to 30 by grouping correlated objectives together. Then, a dynamic summation of rank value is used as pseudo-objective functions to reformulate the multi-objective optimization to a single-objective optimization problem. The optimized results show a significant improvement in the correlation between the simulated model and the experimental model. Once accurate representation of the vehicle suspension model is achieved, further analysis, such as ride and handling performances, can be implemented for further optimization.

Space Station Freedom Central Thermal Control System Evolution

NASA Technical Reports Server (NTRS)

Bullock, Richard; Olsson, Eric

1990-01-01

The objective of the evolution study is to review the proposed growth scenarios for Space Station Freedom and identify the major CTCS hardware scars and software hooks required to facilitate planned growth and technology obsolescence. The Station's two leading evolutionary configurations are: (1) the Research and Development node, where the fundamental mission is scientific research and commercial endeavors, and (2) the Transportation node, where the emphasis is on supporting Lunar and Mars human exploration. These two nodes evolve from the from the assembly complete configuration by the addition of manned modules, pocket labs, resource nodes, attached payloads, customer servicing facility, and an upper and lower keel and boom truss structure. In the case of the R & D node, the role of the dual keel will be to support external payloads for scientific research. In the case of the Transportation node, the keel will support the Lunar (LTV) and Mars (MTV) transportation vehicle service facilities In addition to external payloads. The transverse boom is extended outboard of the alpha gimbal to accommodate the new solar dynamic arrays for power generation, which will supplement the photovoltaic system. The design, development, deployment, and operation of SSF will take place over a 30 year time period and new Innovations and maturation in technologies can be expected. Evolutionary planning must include the obsolescence and insertion of the new technologies over the life of the program, and the technology growth issues must be addressed in parallel with the development of the baseline thermal control system. Technologies that mature and are available within the next 10 years are best suited for evolutionary consideration as the growth phase begins in the year 2000. To increase TCS capability to accommodate growth using baseline technology would require some penalty in mass, volume, EVA time, manifesting, and operational support. To be cost effective the capabilities of the heat acquisition, transport, and rejection subsystems must be increased.

Multiscale structure in eco-evolutionary dynamics

NASA Astrophysics Data System (ADS)

Stacey, Blake C.

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

Conserving the functional and phylogenetic trees of life of European tetrapods

PubMed Central

Thuiller, Wilfried; Maiorano, Luigi; Mazel, Florent; Guilhaumon, François; Ficetola, Gentile Francesco; Lavergne, Sébastien; Renaud, Julien; Roquet, Cristina; Mouillot, David

2015-01-01

Protected areas (PAs) are pivotal tools for biodiversity conservation on the Earth. Europe has had an extensive protection system since Natura 2000 areas were created in parallel with traditional parks and reserves. However, the extent to which this system covers not only taxonomic diversity but also other biodiversity facets, such as evolutionary history and functional diversity, has never been evaluated. Using high-resolution distribution data of all European tetrapods together with dated molecular phylogenies and detailed trait information, we first tested whether the existing European protection system effectively covers all species and in particular, those with the highest evolutionary or functional distinctiveness. We then tested the ability of PAs to protect the entire tetrapod phylogenetic and functional trees of life by mapping species' target achievements along the internal branches of these two trees. We found that the current system is adequately representative in terms of the evolutionary history of amphibians while it fails for the rest. However, the most functionally distinct species were better represented than they would be under random conservation efforts. These results imply better protection of the tetrapod functional tree of life, which could help to ensure long-term functioning of the ecosystem, potentially at the expense of conserving evolutionary history. PMID:25561666

The amazing evolutionary dynamics of non-linear optical systems with feedback

NASA Astrophysics Data System (ADS)

Yaroslavsky, Leonid

2013-09-01

Optical systems with feedback are, generally, non-linear dynamic systems. As such, they exhibit evolutionary behavior. In the paper we present results of experimental investigation of evolutionary dynamics of several models of such systems. The models are modifications of the famous mathematical "Game of Life". The modifications are two-fold: "Game of Life" rules are made stochastic and mutual influence of cells is made spatially non-uniform. A number of new phenomena in the evolutionary dynamics of the models are revealed: - "Ordering of chaos". Formation, from seed patterns, of stable maze-like patterns with chaotic "dislocations" that resemble natural patterns, such as skin patterns of some animals and fishes, see shell, fingerprints, magnetic domain patterns and alike, which one can frequently find in the nature. These patterns and their fragments exhibit a remarkable capability of unlimited growth. - "Self-controlled growth" of chaotic "live" formations into "communities" bounded, depending on the model, by a square, hexagon or octagon, until they reach a certain critical size, after which the growth stops. - "Eternal life in a bounded space" of "communities" after reaching a certain size and shape. - "Coherent shrinkage" of "mature", after reaching a certain size, "communities" into one of stable or oscillating patterns preserving in this process isomorphism of their bounding shapes until the very end.

Biological and geophysical feedbacks with fire in the Earth system

NASA Astrophysics Data System (ADS)

Archibald, S.; Lehmann, C. E. R.; Belcher, C. M.; Bond, W. J.; Bradstock, R. A.; Daniau, A.-L.; Dexter, K. G.; Forrestel, E. J.; Greve, M.; He, T.; Higgins, S. I.; Hoffmann, W. A.; Lamont, B. B.; McGlinn, D. J.; Moncrieff, G. R.; Osborne, C. P.; Pausas, J. G.; Price, O.; Ripley, B. S.; Rogers, B. M.; Schwilk, D. W.; Simon, M. F.; Turetsky, M. R.; Van der Werf, G. R.; Zanne, A. E.

2018-03-01

Roughly 3% of the Earth’s land surface burns annually, representing a critical exchange of energy and matter between the land and atmosphere via combustion. Fires range from slow smouldering peat fires, to low-intensity surface fires, to intense crown fires, depending on vegetation structure, fuel moisture, prevailing climate, and weather conditions. While the links between biogeochemistry, climate and fire are widely studied within Earth system science, these relationships are also mediated by fuels—namely plants and their litter—that are the product of evolutionary and ecological processes. Fire is a powerful selective force and, over their evolutionary history, plants have evolved traits that both tolerate and promote fire numerous times and across diverse clades. Here we outline a conceptual framework of how plant traits determine the flammability of ecosystems and interact with climate and weather to influence fire regimes. We explore how these evolutionary and ecological processes scale to impact biogeochemical and Earth system processes. Finally, we outline several research challenges that, when resolved, will improve our understanding of the role of plant evolution in mediating the fire feedbacks driving Earth system processes. Understanding current patterns of fire and vegetation, as well as patterns of fire over geological time, requires research that incorporates evolutionary biology, ecology, biogeography, and the biogeosciences.

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

Many-objective optimization and visual analytics reveal key trade-offs for London's water supply

NASA Astrophysics Data System (ADS)

Matrosov, Evgenii S.; Huskova, Ivana; Kasprzyk, Joseph R.; Harou, Julien J.; Lambert, Chris; Reed, Patrick M.

2015-12-01

In this study, we link a water resource management simulator to multi-objective search to reveal the key trade-offs inherent in planning a real-world water resource system. We consider new supplies and demand management (conservation) options while seeking to elucidate the trade-offs between the best portfolios of schemes to satisfy projected water demands. Alternative system designs are evaluated using performance measures that minimize capital and operating costs and energy use while maximizing resilience, engineering and environmental metrics, subject to supply reliability constraints. Our analysis shows many-objective evolutionary optimization coupled with state-of-the art visual analytics can help planners discover more diverse water supply system designs and better understand their inherent trade-offs. The approach is used to explore future water supply options for the Thames water resource system (including London's water supply). New supply options include a new reservoir, water transfers, artificial recharge, wastewater reuse and brackish groundwater desalination. Demand management options include leakage reduction, compulsory metering and seasonal tariffs. The Thames system's Pareto approximate portfolios cluster into distinct groups of water supply options; for example implementing a pipe refurbishment program leads to higher capital costs but greater reliability. This study highlights that traditional least-cost reliability constrained design of water supply systems masks asset combinations whose benefits only become apparent when more planning objectives are considered.

SPICA/SAFARI Fourier transform spectrometer mechanism evolutionary design

NASA Astrophysics Data System (ADS)

van den Dool, Teun C.; Kruizinga, Bob; Braam, Ben C.; Hamelinck, Roger F. M. M.; Loix, Nicolas; Van Loon, Dennis; Dams, Johan

2012-09-01

TNO, together with its partners, have designed a cryogenic scanning mechanism for use in the SAFARI1 Fourier Transform Spectrometer (FTS) on board of the SPICA mission. SPICA is one of the M-class missions competing to be launched in ESA's Cosmic Vision Programme2 in 2022. JAXA3 leads the development of the SPICA satellite and SRON is the prime investigator of the Safari instrument. The FTS scanning mechanism (FTSM) has to meet a 35 mm stroke requirement with an Optical Path Difference resolution of less then 15 nm and must fit in a small volume. It consists of two back-to-back roof-top mirrors mounted on a small carriage, which is moved using a magnetic bearing linear guiding system in combination with a magnetic linear motor serving as the OPD actuator. The FTSM will be used at cryogenic temperatures of 4 Kelvin inducing challenging requirements on the thermal power dissipation and heat leak. The magnetic bearing enables movements over a scanning stroke of 35.5 mm in a small volume. It supports the optics in a free-floating way with no friction, or other non-linearities, with sub-nanometer accuracy. This solution is based on the design of the breadboard ODL (Optical Delay Line) developed for the ESA Darwin mission4 and the MABE mechanism developed by Micromega Dynamics. During the last couple of years the initial design of the SAFARI instrument, as described in an earlier SPIE 2010 paper5, was adapted by the SAFARI team in an evolutionary way to meet the changing requirements of the SPICA payload module. This presentation will focus on the evolution of the FTSM to meet these changing requirements. This work is supported by the Netherlands Space Office (NSO).

Bursts of transposable elements as an evolutionary driving force.

PubMed

Belyayev, A

2014-12-01

A burst of transposable elements (TEs) is a massive outbreak that may cause radical genomic rebuilding. This phenomenon has been reported in connection with the formation of taxonomic groups and species and has therefore been associated with major evolutionary events in the past. Over the past few years, several research groups have discovered recent stress-induced bursts of different TEs. The events for which bursts of TEs have been recorded include domestication, polyploidy, changes in mating systems, interspecific and intergeneric hybridization and abiotic stress. Cases involving abiotic stress, particularly bursts of TEs in natural populations driven by environmental change, are of special interest because this phenomenon may underlie micro- and macro-evolutionary events and ultimately support the maintenance and generation of biological diversity. This study reviews the known cases of bursts of TEs and their possible consequences, with particular emphasis on the speciation process. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Invisible hand effect in an evolutionary minority game model

NASA Astrophysics Data System (ADS)

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

2005-03-01

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

Scalability, Timing, and System Design Issues for Intrinsic Evolvable Hardware

NASA Technical Reports Server (NTRS)

Hereford, James; Gwaltney, David

2004-01-01

In this paper we address several issues pertinent to intrinsic evolvable hardware (EHW). The first issue is scalability; namely, how the design space scales as the programming string for the programmable device gets longer. We develop a model for population size and the number of generations as a function of the programming string length, L, and show that the number of circuit evaluations is an O(L2) process. We compare our model to several successful intrinsic EHW experiments and discuss the many implications of our model. The second issue that we address is the timing of intrinsic EHW experiments. We show that the processing time is a small part of the overall time to derive or evolve a circuit and that major improvements in processor speed alone will have only a minimal impact on improving the scalability of intrinsic EHW. The third issue we consider is the system-level design of intrinsic EHW experiments. We review what other researchers have done to break the scalability barrier and contend that the type of reconfigurable platform and the evolutionary algorithm are tied together and impose limits on each other.

Performance of the NEXT Engineering Model Power Processing Unit

NASA Technical Reports Server (NTRS)

Pinero, Luis R.; Hopson, Mark; Todd, Philip C.; Wong, Brian

2007-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) project is developing an advanced ion propulsion system for future NASA missions for solar system exploration. An engineering model (EM) power processing unit (PPU) for the NEXT project was designed and fabricated by L-3 Communications under contract with NASA Glenn Research Center (GRC). This modular PPU is capable of processing up from 0.5 to 7.0 kW of output power for the NEXT ion thruster. Its design includes many significant improvements for better performance over the state-of-the-art PPU. The most significant difference is the beam supply which is comprised of six modules and capable of very efficient operation through a wide voltage range because of innovative features like dual controls, module addressing, and a high current mode. The low voltage power supplies are based on elements of the previously validated NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) PPU. The highly modular construction of the PPU resulted in improved manufacturability, simpler scalability, and lower cost. This paper describes the design of the EM PPU and the results of the bench-top performance tests.

Head shape evolution in Gymnophthalmidae: does habitat use constrain the evolution of cranial design in fossorial lizards?

PubMed

Barros, F C; Herrel, A; Kohlsdorf, T

2011-11-01

Habitat usage comprises interactions between ecological parameters and organismal capacities, and the selective pressures that ultimately determine the outcome of such processes in an evolutionary scale may be conflicting when the same morphological structure is recruited for different activities. Here, we investigate the roles of diet and locomotion in the evolution of cranial design in gymnophthalmid lizards and test the hypothesis that microhabitat use drives head shape evolution, particularly in head-first burrowers. Morphological factors were analysed in relation to continuous ecological indexes (prey hardness and substrate compactness) using conventional and phylogenetic approaches. Results suggest that the evolution of head morphology in Gymnophthalmidae was shaped under the influence of microhabitat use rather than diet: burrowers have shorter heads with lower rostral angulation, independently of the prey consumed. Food preferences appear to be relatively conserved throughout the phylogeny of the group, which may have permitted the extensive radiation of gymnophthalmids into fossorial microhabitats. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

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.

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.

How Can Evolution Learn?

PubMed

Watson, Richard A; Szathmáry, Eörs

2016-02-01

The theory of evolution links random variation and selection to incremental adaptation. In a different intellectual domain, learning theory links incremental adaptation (e.g., from positive and/or negative reinforcement) to intelligent behaviour. Specifically, learning theory explains how incremental adaptation can acquire knowledge from past experience and use it to direct future behaviours toward favourable outcomes. Until recently such cognitive learning seemed irrelevant to the 'uninformed' process of evolution. In our opinion, however, new results formally linking evolutionary processes to the principles of learning might provide solutions to several evolutionary puzzles - the evolution of evolvability, the evolution of ecological organisation, and evolutionary transitions in individuality. If so, the ability for evolution to learn might explain how it produces such apparently intelligent designs. Copyright © 2015 Elsevier Ltd. All rights reserved.

The reformulation of emotional security theory: the role of children's social defense in developmental psychopathology.

PubMed

Davies, Patrick T; Martin, Meredith J

2013-11-01

Although children's security in the context of the interparental relationship has been identified as a key explanatory mechanism in pathways between family discord and child psychopathology, little is known about the inner workings of emotional security as a goal system. Thus, the objective of this paper is to describe how our reformulation of emotional security theory within an ethological and evolutionary framework may advance the characterization of the architecture and operation of emotional security and, in the process, cultivate sustainable growing points in developmental psychopathology. The first section of the paper describes how children's security in the interparental relationship is organized around a distinctive behavioral system designed to defend against interpersonal threat. Building on this evolutionary foundation for emotional security, the paper offers an innovative taxonomy for identifying qualitatively different ways children try to preserve their security and its innovative implications for more precisely informing understanding of the mechanisms in pathways between family and developmental precursors and children's trajectories of mental health. In the final section, the paper highlights the potential of the reformulation of emotional security theory to stimulate new generations of research on understanding how children defend against social threats in ecologies beyond the interparental dyad, including both familial and extrafamilial settings.

The Reformulation of Emotional Security Theory: The Role of Children’s Social Defense in Developmental Psychopathology

PubMed Central

Davies, Patrick T.; Martin, Meredith J.

2014-01-01

Although children’s security in the context of the interparental relationship has been identified as a key explanatory mechanism in pathways between family discord and child psychopathology, little is known about the inner workings of emotional security as a goal system. Accordingly, the objective of this paper is to describe how our reformulation of emotional security theory (EST-R) within an ethological and evolutionary framework may advance the characterization of the architecture and operation of emotional security and, in the process, cultivate sustainable growing points in developmental psychopathology. The first section of the paper describes how children’s security in the interparental relationship is organized around a distinctive behavioral system designed to defend against interpersonal threat. Building on this evolutionary foundation for emotional security, the paper offers an innovative taxonomy for identifying qualitatively different ways children try to preserve their security and its innovative implications for more precisely informing understanding of the mechanisms in pathways between family and developmental precursors and children’s trajectories of mental health. In the final section, the paper highlights the potential of EST-R to stimulate new generations of research on understanding how children defend against social threats in ecologies beyond the interparental dyad, including both familial and extrafamilial settings. PMID:24342849

GALAXY: A new hybrid MOEA for the optimal design of Water Distribution Systems

NASA Astrophysics Data System (ADS)

Wang, Q.; Savić, D. A.; Kapelan, Z.

2017-03-01

A new hybrid optimizer, called genetically adaptive leaping algorithm for approximation and diversity (GALAXY), is proposed for dealing with the discrete, combinatorial, multiobjective design of Water Distribution Systems (WDSs), which is NP-hard and computationally intensive. The merit of GALAXY is its ability to alleviate to a great extent the parameterization issue and the high computational overhead. It follows the generational framework of Multiobjective Evolutionary Algorithms (MOEAs) and includes six search operators and several important strategies. These operators are selected based on their leaping ability in the objective space from the global and local search perspectives. These strategies steer the optimization and balance the exploration and exploitation aspects simultaneously. A highlighted feature of GALAXY lies in the fact that it eliminates majority of parameters, thus being robust and easy-to-use. The comparative studies between GALAXY and three representative MOEAs on five benchmark WDS design problems confirm its competitiveness. GALAXY can identify better converged and distributed boundary solutions efficiently and consistently, indicating a much more balanced capability between the global and local search. Moreover, its advantages over other MOEAs become more substantial as the complexity of the design problem increases.

Scalable computing for evolutionary genomics.

PubMed

Prins, Pjotr; Belhachemi, Dominique; Möller, Steffen; Smant, Geert

2012-01-01

Genomic data analysis in evolutionary biology is becoming so computationally intensive that analysis of multiple hypotheses and scenarios takes too long on a single desktop computer. In this chapter, we discuss techniques for scaling computations through parallelization of calculations, after giving a quick overview of advanced programming techniques. Unfortunately, parallel programming is difficult and requires special software design. The alternative, especially attractive for legacy software, is to introduce poor man's parallelization by running whole programs in parallel as separate processes, using job schedulers. Such pipelines are often deployed on bioinformatics computer clusters. Recent advances in PC virtualization have made it possible to run a full computer operating system, with all of its installed software, on top of another operating system, inside a "box," or virtual machine (VM). Such a VM can flexibly be deployed on multiple computers, in a local network, e.g., on existing desktop PCs, and even in the Cloud, to create a "virtual" computer cluster. Many bioinformatics applications in evolutionary biology can be run in parallel, running processes in one or more VMs. Here, we show how a ready-made bioinformatics VM image, named BioNode, effectively creates a computing cluster, and pipeline, in a few steps. This allows researchers to scale-up computations from their desktop, using available hardware, anytime it is required. BioNode is based on Debian Linux and can run on networked PCs and in the Cloud. Over 200 bioinformatics and statistical software packages, of interest to evolutionary biology, are included, such as PAML, Muscle, MAFFT, MrBayes, and BLAST. Most of these software packages are maintained through the Debian Med project. In addition, BioNode contains convenient configuration scripts for parallelizing bioinformatics software. Where Debian Med encourages packaging free and open source bioinformatics software through one central project, BioNode encourages creating free and open source VM images, for multiple targets, through one central project. BioNode can be deployed on Windows, OSX, Linux, and in the Cloud. Next to the downloadable BioNode images, we provide tutorials online, which empower bioinformaticians to install and run BioNode in different environments, as well as information for future initiatives, on creating and building such images.

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%.

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

Parasites, ecosystems and sustainability: an ecological and complex systems perspective.

PubMed

Horwitz, Pierre; Wilcox, Bruce A

2005-06-01

Host-parasite relationships can be conceptualised either narrowly, where the parasite is metabolically dependent on the host, or more broadly, as suggested by an ecological-evolutionary and complex systems perspective. In this view Host-parasite relationships are part of a larger set of ecological and co-evolutionary interdependencies and a complex adaptive system. These interdependencies affect not just the hosts, vectors, parasites, the immediate agents, but also those indirectly or consequentially affected by the relationship. Host-parasite relationships also can be viewed as systems embedded within larger systems represented by ecological communities and ecosystems. So defined, it can be argued that Host-parasite relationships may often benefit their hosts and contribute significantly to the structuring of ecological communities. The broader, complex adaptive system view also contributes to understanding the phenomenon of disease emergence, the ecological and evolutionary mechanisms involved, and the role of parasitology in research and management of ecosystems in light of the apparently growing problem of emerging infectious diseases in wildlife and humans. An expanded set of principles for integrated parasite management is suggested by this perspective.

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.

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.

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

PubMed

Chen, Bor-Sen; Yeh, Chin-Hsun

2017-12-01

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

Flat-walled multilayered anechoic linings: Optimization and application

NASA Astrophysics Data System (ADS)

Xu, Jingfeng; Buchholz, Jörg M.; Fricke, Fergus R.

2005-11-01

The concept of flat-walled multilayered absorbent linings for anechoic rooms was proposed three decades ago. Flat-walled linings have the advantage of being less complicated and, hence, less costly to manufacture and install than the individual units such as wedges. However, there are difficulties in optimizing the design of such absorbent linings. In the present work, the design of a flat-walled multilayered anechoic lining that targeted a 250 Hz cut-off frequency and a 300 mm maximum lining thickness was first optimized using an evolutionary algorithm. Sixteen of the most commonly used commercial fibrous building insulation materials available in Australia were investigated and fourteen design options (i.e., material combinations) were found by the evolutionary algorithm. These options were then evaluated in accordance with their costs and measured acoustic absorption performances. Finally, the completed anechoic room, where the optimized design was applied, was qualified and the results showed that a large percentage (75%-85%) of the distance between the sound source and the room boundaries, on the traverses made, were anechoic.

COMPASS Final Report: Enceladus Solar Electric Propulsion Stage

NASA Technical Reports Server (NTRS)

Oleson, Steven R.; McGuire, Melissa L.

2011-01-01

The results of the NASA Glenn Research Center (GRC) COllaborative Modeling and Parametric Assessment of Space Systems (COMPASS) internal Solar Electric Propulsion (SEP) stage design are documented in this report (Figure 1.1). The SEP Stage was designed to deliver a science probe to Saturn (the probe design was performed separately by the NASA Goddard Space Flight Center s (GSFC) Integrated Mission Design Center (IMDC)). The SEP Stage delivers the 2444 kg probe on a Saturn trajectory with a hyperbolic arrival velocity of 5.4 km/s. The design carried 30 percent mass, 10 percent power, and 6 percent propellant margins. The SEP Stage relies on the probe for substantial guidance, navigation and control (GN&C), command and data handling (C&DH), and Communications functions. The stage is configured to carry the probe and to minimize the packaging interference between the probe and the stage. The propulsion system consisted of a 1+1 (one active, one spare) configuration of gimbaled 7 kW NASA Evolutionary Xenon Thruster (NEXT) ion propulsion thrusters with a throughput of 309 kg Xe propellant. Two 9350 W GaAs triple junction (at 1 Astronomical Unit (AU), includes 10 percent margin) ultra-flex solar arrays provided power to the stage, with Li-ion batteries for launch and contingency operations power. The base structure was an Al-Li hexagonal skin-stringer frame built to withstand launch loads. A passive thermal control system consisted of heat pipes to north and south radiator panels, multilayer insulation (MLI) and heaters for the Xe tank. All systems except tanks and solar arrays were designed to be single fault tolerant.

Biogeography predicts macro‐evolutionary patterning of gestural display complexity in a passerine family

PubMed Central

Miles, Meredith C.; Cheng, Samantha; Fuxjager, Matthew J.

2017-01-01

Gestural displays are incorporated into the signaling repertoire of numerous animal species. These displays range from complex signals that involve impressive and challenging maneuvers, to simpler displays or no gesture at all. The factors that drive this evolution remain largely unclear, and we therefore investigate this issue in New World blackbirds by testing how factors related to a species’ geographical distribution and social mating system predict macro‐evolutionary patterns of display elaboration. We report that species inhabiting temperate regions produce more complex displays than species living in tropical regions, and we attribute this to (i) ecological factors that increase the competitiveness of the social environment in temperate regions, and (ii) different evolutionary and geological contexts under which species in temperate and tropical regions evolved. Meanwhile, we find no evidence that social mating system predicts species differences in display complexity, which is consistent with the idea that gestural displays evolve independently of social mating system. Together, these results offer some of the first insight into the role played by geographic factors and evolutionary context in the evolution of the remarkable physical displays of birds and other vertebrates. PMID:28240772

Formation of dominant mode by evolution in biological systems

NASA Astrophysics Data System (ADS)

Furusawa, Chikara; Kaneko, Kunihiko

2018-04-01

A reduction in high-dimensional phenotypic states to a few degrees of freedom is essential to understand biological systems. Here, we show evolutionary robustness causes such reduction which restricts possible phenotypic changes in response to a variety of environmental conditions. First, global protein expression changes in Escherichia coli after various environmental perturbations were shown to be proportional across components, across different types of environmental conditions. To examine if such dimension reduction is a result of evolution, we analyzed a cell model—with a huge number of components, that reproduces itself via a catalytic reaction network—and confirmed that common proportionality in the concentrations of all components is shaped through evolutionary processes. We found that the changes in concentration across all components in response to environmental and evolutionary changes are constrained to the changes along a one-dimensional major axis, within a huge-dimensional state space. On the basis of these observations, we propose a theory in which such constraints in phenotypic changes are achieved both by evolutionary robustness and plasticity and formulate this proposition in terms of dynamical systems. Accordingly, broad experimental and numerical results on phenotypic changes caused by evolution and adaptation are coherently explained.

The SW Sex Phenomenon as an Evolutionary Stage of Cataclysmic Variables

NASA Astrophysics Data System (ADS)

Schmidtobreick, L.

From recent large observing campaigns, one finds that nearly all non- or weakly magnetic cataclysmic variables in the orbital period range between 2.8 and 4 hours are of SW Sex type and as such experience very high mass transfer rates. The evolution of cataclysmic variables as for any interacting binary is driven by angular momentum loss which results in a decrease of the orbital period on evolutionary time scales. In particular, all long-period systems need to cross the SW Sex regime of the orbital period distribution before entering the period gap. This makes the SW Sex phenomenon an evolutionary stage in the life of a cataclysmic variable. Here, I present a short overview of the current state of research on these systems.

Design and Optimization of Low-thrust Orbit Transfers Using Q-law and Evolutionary Algorithms

NASA Technical Reports Server (NTRS)

Lee, Seungwon; vonAllmen, Paul; Fink, Wolfgang; Petropoulos, Anastassios; Terrile, Richard

2005-01-01

Future space missions will depend more on low-thrust propulsion (such as ion engines) thanks to its high specific impulse. Yet, the design of low-thrust trajectories is complex and challenging. Third-body perturbations often dominate the thrust, and a significant change to the orbit requires a long duration of thrust. In order to guide the early design phases, we have developed an efficient and efficacious method to obtain approximate propellant and flight-time requirements (i.e., the Pareto front) for orbit transfers. A search for the Pareto-optimal trajectories is done in two levels: optimal thrust angles and locations are determined by Q-law, while the Q-law is optimized with two evolutionary algorithms: a genetic algorithm and a simulated-annealing-related algorithm. The examples considered are several types of orbit transfers around the Earth and the asteroid Vesta.

Irreducible incoherence and intelligent design: a look into the conceptual toolbox of a pseudoscience.

PubMed

Boudry, Maarten; Blancke, Stefaan; Braeckman, Johan

2010-12-01

The concept of Irreducible Complexity (IC) has played a pivotal role in the resurgence of the creationist movement over the past two decades. Evolutionary biologists and philosophers have unambiguously rejected the purported demonstration of "intelligent design" in nature, but there have been several, apparently contradictory, lines of criticism. We argue that this is in fact due to Michael Behe's own incoherent definition and use of IC. This paper offers an analysis of several equivocations inherent in the concept of Irreducible Complexity and discusses the way in which advocates of the Intelligent Design Creationism (IDC) have conveniently turned IC into a moving target. An analysis of these rhetorical strategies helps us to understand why IC has gained such prominence in the IDC movement, and why, despite its complete lack of scientific merits, it has even convinced some knowledgeable persons of the impending demise of evolutionary theory.

ViLLaGEs: opto-mechanical design of an on-sky visible-light MEMS-based AO system

NASA Astrophysics Data System (ADS)

Grigsby, Bryant; Lockwood, Chris; Baumann, Brian; Gavel, Don; Johnson, Jess; Ammons, S. Mark; Dillon, Daren; Morzinski, Katie; Reinig, Marc; Palmer, Dave; Severson, Scott; Gates, Elinor

2008-07-01

Visible Light Laser Guidestar Experiments (ViLLaGEs) is a new Micro-Electro Mechanical Systems (MEMS) based visible-wavelength adaptive optics (AO) testbed on the Nickel 1-meter telescope at Lick Observatory. Closed loop Natural Guide Star (NGS) experiments were successfully carried out during engineering during the fall of 2007. This is a major evolutionary step, signaling the movement of AO technologies into visible light with a MEMS mirror. With on-sky Strehls in I-band of greater than 20% during second light tests, the science possibilities have become evident. Described here is the advanced engineering used in the design and construction of the ViLLaGEs system, comparing it to the LickAO infrared system, and a discussion of Nickel dome infrastructural improvements necessary for this system. A significant portion of the engineering discussion revolves around the sizable effort that went towards eliminating flexure. Then, we detail upgrades to ViLLaGEs to make it a facility class instrument. These upgrades will focus on Nyquist sampling the diffraction limited point spread function during open loop operations, motorization and automation for technician level alignments, adding dithering capabilities and changes for near infrared science.

Power system modeling and optimization methods vis-a-vis integrated resource planning (IRP)

NASA Astrophysics Data System (ADS)

Arsali, Mohammad H.

1998-12-01

The state-of-the-art restructuring of power industries is changing the fundamental nature of retail electricity business. As a result, the so-called Integrated Resource Planning (IRP) strategies implemented on electric utilities are also undergoing modifications. Such modifications evolve from the imminent considerations to minimize the revenue requirements and maximize electrical system reliability vis-a-vis capacity-additions (viewed as potential investments). IRP modifications also provide service-design bases to meet the customer needs towards profitability. The purpose of this research as deliberated in this dissertation is to propose procedures for optimal IRP intended to expand generation facilities of a power system over a stretched period of time. Relevant topics addressed in this research towards IRP optimization are as follows: (1) Historical prospective and evolutionary aspects of power system production-costing models and optimization techniques; (2) A survey of major U.S. electric utilities adopting IRP under changing socioeconomic environment; (3) A new technique designated as the Segmentation Method for production-costing via IRP optimization; (4) Construction of a fuzzy relational database of a typical electric power utility system for IRP purposes; (5) A genetic algorithm based approach for IRP optimization using the fuzzy relational database.

Towards Robust Designs Via Multiple-Objective Optimization Methods

NASA Technical Reports Server (NTRS)

Man Mohan, Rai

2006-01-01

Fabricating and operating complex systems involves dealing with uncertainty in the relevant variables. In the case of aircraft, flow conditions are subject to change during operation. Efficiency and engine noise may be different from the expected values because of manufacturing tolerances and normal wear and tear. Engine components may have a shorter life than expected because of manufacturing tolerances. In spite of the important effect of operating- and manufacturing-uncertainty on the performance and expected life of the component or system, traditional aerodynamic shape optimization has focused on obtaining the best design given a set of deterministic flow conditions. Clearly it is important to both maintain near-optimal performance levels at off-design operating conditions, and, ensure that performance does not degrade appreciably when the component shape differs from the optimal shape due to manufacturing tolerances and normal wear and tear. These requirements naturally lead to the idea of robust optimal design wherein the concept of robustness to various perturbations is built into the design optimization procedure. The basic ideas involved in robust optimal design will be included in this lecture. The imposition of the additional requirement of robustness results in a multiple-objective optimization problem requiring appropriate solution procedures. Typically the costs associated with multiple-objective optimization are substantial. Therefore efficient multiple-objective optimization procedures are crucial to the rapid deployment of the principles of robust design in industry. Hence the companion set of lecture notes (Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks ) deals with methodology for solving multiple-objective Optimization problems efficiently, reliably and with little user intervention. Applications of the methodologies presented in the companion lecture to robust design will be included here. The evolutionary method (DE) is first used to solve a relatively difficult problem in extended surface heat transfer wherein optimal fin geometries are obtained for different safe operating base temperatures. The objective of maximizing the safe operating base temperature range is in direct conflict with the objective of maximizing fin heat transfer. This problem is a good example of achieving robustness in the context of changing operating conditions. The evolutionary method is then used to design a turbine airfoil; the two objectives being reduced sensitivity of the pressure distribution to small changes in the airfoil shape and the maximization of the trailing edge wedge angle with the consequent increase in airfoil thickness and strength. This is a relevant example of achieving robustness to manufacturing tolerances and wear and tear in the presence of other objectives.

Modular electron transfer circuits for synthetic biology

PubMed Central

Agapakis, Christina M

2010-01-01

Electron transfer is central to a wide range of essential metabolic pathways, from photosynthesis to fermentation. The evolutionary diversity and conservation of proteins that transfer electrons makes these pathways a valuable platform for engineered metabolic circuits in synthetic biology. Rational engineering of electron transfer pathways containing hydrogenases has the potential to lead to industrial scale production of hydrogen as an alternative source of clean fuel and experimental assays for understanding the complex interactions of multiple electron transfer proteins in vivo. We designed and implemented a synthetic hydrogen metabolism circuit in Escherichia coli that creates an electron transfer pathway both orthogonal to and integrated within existing metabolism. The design of such modular electron transfer circuits allows for facile characterization of in vivo system parameters with applications toward further engineering for alternative energy production. PMID:21468209

Estimating the dilemma strength for game systems. Comment on "Universal scaling for the dilemma strength in evolutionary games", by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Chen, Xiaojie

2015-09-01

The puzzle of cooperation exists widely in the realistic world, including biological, social, and engineering systems. How to solve the cooperation puzzle has received considerable attention in recent years [1]. Evolutionary game theory provides a common mathematical framework to study the problem of cooperation. In principle, these practical biological, social, or engineering systems can be described by complex game models composed of multiple autonomous individuals with mutual interactions. And generally there exists a dilemma for the evolution of cooperation in the game systems.

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.

A replicated climate change field experiment reveals rapid evolutionary response in an ecologically important soil invertebrate.

PubMed

Bataillon, Thomas; Galtier, Nicolas; Bernard, Aurelien; Cryer, Nicolai; Faivre, Nicolas; Santoni, Sylvain; Severac, Dany; Mikkelsen, Teis N; Larsen, Klaus S; Beier, Claus; Sørensen, Jesper G; Holmstrup, Martin; Ehlers, Bodil K

2016-07-01

Whether species can respond evolutionarily to current climate change is crucial for the persistence of many species. Yet, very few studies have examined genetic responses to climate change in manipulated experiments carried out in natural field conditions. We examined the evolutionary response to climate change in a common annelid worm using a controlled replicated experiment where climatic conditions were manipulated in a natural setting. Analyzing the transcribed genome of 15 local populations, we found that about 12% of the genetic polymorphisms exhibit differences in allele frequencies associated to changes in soil temperature and soil moisture. This shows an evolutionary response to realistic climate change happening over short-time scale, and calls for incorporating evolution into models predicting future response of species to climate change. It also shows that designed climate change experiments coupled with genome sequencing offer great potential to test for the occurrence (or lack) of an evolutionary response. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

The evolutionary development of high specific impulse electric thruster technology

NASA Technical Reports Server (NTRS)

Sovey, James S.; Hamley, John A.; Patterson, Michael J.; Rawlin, Vincent K.; Myers, Roger M.

1992-01-01

Electric propulsion flight and technology demonstrations conducted in the USA, Europe, Japan, China, and USSR are reviewed with reference to the major flight qualified electric propulsion systems. These include resistojets, ion thrusters, ablative pulsed plasma thrusters, stationary plasma thrusters, pulsed magnetoplasmic thrusters, and arcjets. Evolutionary mission applications are presented for high specific impulse electric thruster systems. The current status of arcjet, ion, and magnetoplasmadynamic thrusters and their associated power processor technologies are summarized.

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.