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.

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.

Genetic algorithm for investigating flight MH370 in Indian Ocean using remotely sensed data

NASA Astrophysics Data System (ADS)

Marghany, Maged; Mansor, Shattri; Shariff, Abdul Rashid Bin Mohamed

2016-06-01

This study utilized Genetic algorithm (GA) for automatic detection and simulation trajectory movements of flight MH370 debris. In doing so, the Ocean Surface Topography Mission(OSTM) on the Jason- 2 satellite have been used within 1 and half year covers data to simulate the pattern of Flight MH370 debris movements across the southern Indian Ocean. Further, multi-objectives evolutionary algorithm also used to discriminate uncertainty of flight MH370 imagined and detection. The study shows that the ocean surface current speed is 0.5 m/s. This current patterns have developed a large anticlockwise gyre over a water depth of 8,000 m. The multi-objectives evolutionary algorithm suggested that objects are existed on satellite data are not flight MH370 debris. In addition, multiobjectives evolutionary algorithm suggested that the difficulties to acquire the exact location of flight MH370 due to complicated hydrodynamic movements across the southern Indian Ocean.

Cost versus life cycle assessment-based environmental impact optimization of drinking water production plants.

PubMed

Capitanescu, F; Rege, S; Marvuglia, A; Benetto, E; Ahmadi, A; Gutiérrez, T Navarrete; Tiruta-Barna, L

2016-07-15

Empowering decision makers with cost-effective solutions for reducing industrial processes environmental burden, at both design and operation stages, is nowadays a major worldwide concern. The paper addresses this issue for the sector of drinking water production plants (DWPPs), seeking for optimal solutions trading-off operation cost and life cycle assessment (LCA)-based environmental impact while satisfying outlet water quality criteria. This leads to a challenging bi-objective constrained optimization problem, which relies on a computationally expensive intricate process-modelling simulator of the DWPP and has to be solved with limited computational budget. Since mathematical programming methods are unusable in this case, the paper examines the performances in tackling these challenges of six off-the-shelf state-of-the-art global meta-heuristic optimization algorithms, suitable for such simulation-based optimization, namely Strength Pareto Evolutionary Algorithm (SPEA2), Non-dominated Sorting Genetic Algorithm (NSGA-II), Indicator-based Evolutionary Algorithm (IBEA), Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), Differential Evolution (DE), and Particle Swarm Optimization (PSO). The results of optimization reveal that good reduction in both operating cost and environmental impact of the DWPP can be obtained. Furthermore, NSGA-II outperforms the other competing algorithms while MOEA/D and DE perform unexpectedly poorly. Copyright © 2016 Elsevier Ltd. All rights reserved.

MOCASSIN-prot: A multi-objective clustering approach for protein similarity networks

USDA-ARS?s Scientific Manuscript database

Motivation: Proteins often include multiple conserved domains. Various evolutionary events including duplication and loss of domains, domain shuffling, as well as sequence divergence contribute to generating complexities in protein structures, and consequently, in their functions. The evolutionary h...

A novel model-based evolutionary algorithm for multi-objective deformable image registration with content mismatch and large deformations: benchmarking efficiency and quality

NASA Astrophysics Data System (ADS)

Bouter, Anton; Alderliesten, Tanja; Bosman, Peter A. N.

2017-02-01

Taking a multi-objective optimization approach to deformable image registration has recently gained attention, because such an approach removes the requirement of manually tuning the weights of all the involved objectives. Especially for problems that require large complex deformations, this is a non-trivial task. From the resulting Pareto set of solutions one can then much more insightfully select a registration outcome that is most suitable for the problem at hand. To serve as an internal optimization engine, currently used multi-objective algorithms are competent, but rather inefficient. In this paper we largely improve upon this by introducing a multi-objective real-valued adaptation of the recently introduced Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) for discrete optimization. In this work, GOMEA is tailored specifically to the problem of deformable image registration to obtain substantially improved efficiency. This improvement is achieved by exploiting a key strength of GOMEA: iteratively improving small parts of solutions, allowing to faster exploit the impact of such updates on the objectives at hand through partial evaluations. We performed experiments on three registration problems. In particular, an artificial problem containing a disappearing structure, a pair of pre- and post-operative breast CT scans, and a pair of breast MRI scans acquired in prone and supine position were considered. Results show that compared to the previously used evolutionary algorithm, GOMEA obtains a speed-up of up to a factor of 1600 on the tested registration problems while achieving registration outcomes of similar quality.

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

PubMed

Deb, Kalyanmoy; Sinha, Ankur

2010-01-01

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

Evolutionary algorithms for multi-objective optimization: fuzzy preference aggregation and multisexual EAs

NASA Astrophysics Data System (ADS)

Bonissone, Stefano R.

2001-11-01

There are many approaches to solving multi-objective optimization problems using evolutionary algorithms. We need to select methods for representing and aggregating preferences, as well as choosing strategies for searching in multi-dimensional objective spaces. First we suggest the use of linguistic variables to represent preferences and the use of fuzzy rule systems to implement tradeoff aggregations. After a review of alternatives EA methods for multi-objective optimizations, we explore the use of multi-sexual genetic algorithms (MSGA). In using a MSGA, we need to modify certain parts of the GAs, namely the selection and crossover operations. The selection operator groups solutions according to their gender tag to prepare them for crossover. The crossover is modified by appending a gender tag at the end of the chromosome. We use single and double point crossovers. We determine the gender of the offspring by the amount of genetic material provided by each parent. The parent that contributed the most to the creation of a specific offspring determines the gender that the offspring will inherit. This is still a work in progress, and in the conclusion we examine many future extensions and experiments.

Multi-objective flexible job shop scheduling problem using variable neighborhood evolutionary algorithm

NASA Astrophysics Data System (ADS)

Wang, Chun; Ji, Zhicheng; Wang, Yan

2017-07-01

In this paper, multi-objective flexible job shop scheduling problem (MOFJSP) was studied with the objects to minimize makespan, total workload and critical workload. A variable neighborhood evolutionary algorithm (VNEA) was proposed to obtain a set of Pareto optimal solutions. First, two novel crowded operators in terms of the decision space and object space were proposed, and they were respectively used in mating selection and environmental selection. Then, two well-designed neighborhood structures were used in local search, which consider the problem characteristics and can hold fast convergence. Finally, extensive comparison was carried out with the state-of-the-art methods specially presented for solving MOFJSP on well-known benchmark instances. The results show that the proposed VNEA is more effective than other algorithms in solving MOFJSP.

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.

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.

Multi Objective Optimization of Yarn Quality and Fibre Quality Using Evolutionary Algorithm

NASA Astrophysics Data System (ADS)

Ghosh, Anindya; Das, Subhasis; Banerjee, Debamalya

2013-03-01

The quality and cost of resulting yarn play a significant role to determine its end application. The challenging task of any spinner lies in producing a good quality yarn with added cost benefit. The present work does a multi-objective optimization on two objectives, viz. maximization of cotton yarn strength and minimization of raw material quality. The first objective function has been formulated based on the artificial neural network input-output relation between cotton fibre properties and yarn strength. The second objective function is formulated with the well known regression equation of spinning consistency index. It is obvious that these two objectives are conflicting in nature i.e. not a single combination of cotton fibre parameters does exist which produce maximum yarn strength and minimum cotton fibre quality simultaneously. Therefore, it has several optimal solutions from which a trade-off is needed depending upon the requirement of user. In this work, the optimal solutions are obtained with an elitist multi-objective evolutionary algorithm based on Non-dominated Sorting Genetic Algorithm II (NSGA-II). These optimum solutions may lead to the efficient exploitation of raw materials to produce better quality yarns at low costs.

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.

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.

A hybrid multi-objective evolutionary algorithm for wind-turbine blade optimization

NASA Astrophysics Data System (ADS)

Sessarego, M.; Dixon, K. R.; Rival, D. E.; Wood, D. H.

2015-08-01

A concurrent-hybrid non-dominated sorting genetic algorithm (hybrid NSGA-II) has been developed and applied to the simultaneous optimization of the annual energy production, flapwise root-bending moment and mass of the NREL 5 MW wind-turbine blade. By hybridizing a multi-objective evolutionary algorithm (MOEA) with gradient-based local search, it is believed that the optimal set of blade designs could be achieved in lower computational cost than for a conventional MOEA. To measure the convergence between the hybrid and non-hybrid NSGA-II on a wind-turbine blade optimization problem, a computationally intensive case was performed using the non-hybrid NSGA-II. From this particular case, a three-dimensional surface representing the optimal trade-off between the annual energy production, flapwise root-bending moment and blade mass was achieved. The inclusion of local gradients in the blade optimization, however, shows no improvement in the convergence for this three-objective problem.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Constructing Robust Cooperative Networks using a Multi-Objective Evolutionary Algorithm

PubMed Central

Wang, Shuai; Liu, Jing

2017-01-01

The design and construction of network structures oriented towards different applications has attracted much attention recently. The existing studies indicated that structural heterogeneity plays different roles in promoting cooperation and robustness. Compared with rewiring a predefined network, it is more flexible and practical to construct new networks that satisfy the desired properties. Therefore, in this paper, we study a method for constructing robust cooperative networks where the only constraint is that the number of nodes and links is predefined. We model this network construction problem as a multi-objective optimization problem and propose a multi-objective evolutionary algorithm, named MOEA-Netrc, to generate the desired networks from arbitrary initializations. The performance of MOEA-Netrc is validated on several synthetic and real-world networks. The results show that MOEA-Netrc can construct balanced candidates and is insensitive to the initializations. MOEA-Netrc can find the Pareto fronts for networks with different levels of cooperation and robustness. In addition, further investigation of the robustness of the constructed networks revealed the impact on other aspects of robustness during the construction process. PMID:28134314

PGA/MOEAD: a preference-guided evolutionary algorithm for multi-objective decision-making problems with interval-valued fuzzy preferences

NASA Astrophysics Data System (ADS)

Luo, Bin; Lin, Lin; Zhong, ShiSheng

2018-02-01

In this research, we propose a preference-guided optimisation algorithm for multi-criteria decision-making (MCDM) problems with interval-valued fuzzy preferences. The interval-valued fuzzy preferences are decomposed into a series of precise and evenly distributed preference-vectors (reference directions) regarding the objectives to be optimised on the basis of uniform design strategy firstly. Then the preference information is further incorporated into the preference-vectors based on the boundary intersection approach, meanwhile, the MCDM problem with interval-valued fuzzy preferences is reformulated into a series of single-objective optimisation sub-problems (each sub-problem corresponds to a decomposed preference-vector). Finally, a preference-guided optimisation algorithm based on MOEA/D (multi-objective evolutionary algorithm based on decomposition) is proposed to solve the sub-problems in a single run. The proposed algorithm incorporates the preference-vectors within the optimisation process for guiding the search procedure towards a more promising subset of the efficient solutions matching the interval-valued fuzzy preferences. In particular, lots of test instances and an engineering application are employed to validate the performance of the proposed algorithm, and the results demonstrate the effectiveness and feasibility of the algorithm.

Spatial evolutionary epidemiology of spreading epidemics

PubMed Central

2016-01-01

Most spatial models of host–parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation. PMID:27798295

Spatial evolutionary epidemiology of spreading epidemics.

PubMed

Lion, S; Gandon, S

2016-10-26

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

Community detection in complex networks by using membrane algorithm

NASA Astrophysics Data System (ADS)

Liu, Chuang; Fan, Linan; Liu, Zhou; Dai, Xiang; Xu, Jiamei; Chang, Baoren

Community detection in complex networks is a key problem of network analysis. In this paper, a new membrane algorithm is proposed to solve the community detection in complex networks. The proposed algorithm is based on membrane systems, which consists of objects, reaction rules, and a membrane structure. Each object represents a candidate partition of a complex network, and the quality of objects is evaluated according to network modularity. The reaction rules include evolutionary rules and communication rules. Evolutionary rules are responsible for improving the quality of objects, which employ the differential evolutionary algorithm to evolve objects. Communication rules implement the information exchanged among membranes. Finally, the proposed algorithm is evaluated on synthetic, real-world networks with real partitions known and the large-scaled networks with real partitions unknown. The experimental results indicate the superior performance of the proposed algorithm in comparison with other experimental algorithms.

Multiobjective Optimization Using a Pareto Differential Evolution Approach

NASA Technical Reports Server (NTRS)

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

2002-01-01

Differential Evolution is a simple, fast, and robust evolutionary algorithm that has proven effective in determining the global optimum for several difficult single-objective optimization problems. In this paper, the Differential Evolution algorithm is extended to multiobjective optimization problems by using a Pareto-based approach. The algorithm performs well when applied to several test optimization problems from the literature.

Multi-Objective UAV Mission Planning Using Evolutionary Computation

DTIC Science & Technology

2008-03-01

on a Solution Space. . . . . . . . . . . . . . . . . . . . 41 4.3. Crowding distance calculation. Dark points are non-dominated solutions. [14...SPEA2 was devel- oped by Zitzler [64] as an improvement to the original SPEA algorithm [65]. SPEA2 Figure 4.3: Crowding distance calculation. Dark ...thesis, Los Angeles, CA, USA, 2003. Adviser-Maja J. Mataric . 114 21. Homberger, Joerg and Hermann Gehring. “Two Evolutionary Metaheuristics for the

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.

Computational characterization of HPGe detectors usable for a wide variety of source geometries by using Monte Carlo simulation and a multi-objective evolutionary algorithm

NASA Astrophysics Data System (ADS)

Guerra, J. G.; Rubiano, J. G.; Winter, G.; Guerra, A. G.; Alonso, H.; Arnedo, M. A.; Tejera, A.; Martel, P.; Bolivar, J. P.

2017-06-01

In this work, we have developed a computational methodology for characterizing HPGe detectors by implementing in parallel a multi-objective evolutionary algorithm, together with a Monte Carlo simulation code. The evolutionary algorithm is used for searching the geometrical parameters of a model of detector by minimizing the differences between the efficiencies calculated by Monte Carlo simulation and two reference sets of Full Energy Peak Efficiencies (FEPEs) corresponding to two given sample geometries, a beaker of small diameter laid over the detector window and a beaker of large capacity which wrap the detector. This methodology is a generalization of a previously published work, which was limited to beakers placed over the window of the detector with a diameter equal or smaller than the crystal diameter, so that the crystal mount cap (which surround the lateral surface of the crystal), was not considered in the detector model. The generalization has been accomplished not only by including such a mount cap in the model, but also using multi-objective optimization instead of mono-objective, with the aim of building a model sufficiently accurate for a wider variety of beakers commonly used for the measurement of environmental samples by gamma spectrometry, like for instance, Marinellis, Petris, or any other beaker with a diameter larger than the crystal diameter, for which part of the detected radiation have to pass through the mount cap. The proposed methodology has been applied to an HPGe XtRa detector, providing a model of detector which has been successfully verificated for different source-detector geometries and materials and experimentally validated using CRMs.

Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction

NASA Astrophysics Data System (ADS)

Chu, J.; Zhang, C.; Fu, G.; Li, Y.; Zhou, H.

2015-08-01

This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed method dramatically reduces the computational demands required for attaining high-quality approximations of optimal trade-off relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed dimension reduction and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform dimension reduction of optimization problems when solving complex multi-objective reservoir operation problems.

Improving multi-objective reservoir operation optimization with sensitivity-informed problem decomposition

NASA Astrophysics Data System (ADS)

Chu, J. G.; Zhang, C.; Fu, G. T.; Li, Y.; Zhou, H. C.

2015-04-01

This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce the computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed problem decomposition dramatically reduces the computational demands required for attaining high quality approximations of optimal tradeoff relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed problem decomposition and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform problem decomposition when solving the complex multi-objective reservoir operation problems.

International Conference on Artificial Immune Systems (1st) ICARIS 2002, held on 9, 10, and 11 September 2002

DTIC Science & Technology

2002-03-07

Michalewicz, Eds., Evolutionary Computation 1: Basic Algorithms and Operators, Institute of Physics, Bristol (UK), 2000. [3] David A. Van Veldhuizen ...2000. [4] Carlos A. Coello Coello, David A. Van Veldhuizen , and Gary B. Lamont, Evolutionary Algorithms for Solving Multi-Objective Problems, Kluwer...Academic Publishers, 233 Spring St., New York, NY 10013, 2002. [5] David A. Van Veldhuizen , Multiobjective Evolution- ary Algorithms: Classifications

Confronting Decision Cliffs: Diagnostic Assessment of Multi-Objective Evolutionary Algorithms' Performance for Addressing Uncertain Environmental Thresholds

NASA Astrophysics Data System (ADS)

Ward, V. L.; Singh, R.; Reed, P. M.; Keller, K.

2014-12-01

As water resources problems typically involve several stakeholders with conflicting objectives, multi-objective evolutionary algorithms (MOEAs) are now key tools for understanding management tradeoffs. Given the growing complexity of water planning problems, it is important to establish if an algorithm can consistently perform well on a given class of problems. This knowledge allows the decision analyst to focus on eliciting and evaluating appropriate problem formulations. This study proposes a multi-objective adaptation of the classic environmental economics "Lake Problem" as a computationally simple but mathematically challenging MOEA benchmarking problem. The lake problem abstracts a fictional town on a lake which hopes to maximize its economic benefit without degrading the lake's water quality to a eutrophic (polluted) state through excessive phosphorus loading. The problem poses the challenge of maintaining economic activity while confronting the uncertainty of potentially crossing a nonlinear and potentially irreversible pollution threshold beyond which the lake is eutrophic. Objectives for optimization are maximizing economic benefit from lake pollution, maximizing water quality, maximizing the reliability of remaining below the environmental threshold, and minimizing the probability that the town will have to drastically change pollution policies in any given year. The multi-objective formulation incorporates uncertainty with a stochastic phosphorus inflow abstracting non-point source pollution. We performed comprehensive diagnostics using 6 algorithms: Borg, MOEAD, eMOEA, eNSGAII, GDE3, and NSGAII to ascertain their controllability, reliability, efficiency, and effectiveness. The lake problem abstracts elements of many current water resources and climate related management applications where there is the potential for crossing irreversible, nonlinear thresholds. We show that many modern MOEAs can fail on this test problem, indicating its suitability as a useful and nontrivial benchmarking problem.

Co-optimization of Energy and Demand-Side Reserves in Day-Ahead Electricity Markets

NASA Astrophysics Data System (ADS)

Surender Reddy, S.; Abhyankar, A. R.; Bijwe, P. R.

2015-04-01

This paper presents a new multi-objective day-ahead market clearing (DAMC) mechanism with demand-side reserves/demand response (DR) offers, considering realistic voltage-dependent load modeling. The paper proposes objectives such as social welfare maximization (SWM) including demand-side reserves, and load served error (LSE) minimization. In this paper, energy and demand-side reserves are cleared simultaneously through co-optimization process. The paper clearly brings out the unsuitability of conventional SWM for DAMC in the presence of voltage-dependent loads, due to reduction of load served (LS). Under such circumstances multi-objective DAMC with DR offers is essential. Multi-objective Strength Pareto Evolutionary Algorithm 2+ (SPEA 2+) has been used to solve the optimization problem. The effectiveness of the proposed scheme is confirmed with results obtained from IEEE 30 bus system.

POCO-MOEA: Using Evolutionary Algorithms to Solve the Controller Placement Problem

DTIC Science & Technology

2016-03-24

to gather data on POCO-MOEA performance to a series of iv model networks. The algorithm’s behavior is then evaluated and compared to ex- haustive... evaluation of a third heuristic based on a Multi 3 Objective Evolutionary Algorithm (MOEA). This heuristic is modeled after one of the most well known MOEAs...researchers to extend into more realistic evaluations of the performance characteristics of SDN controllers, such as the use of simulators or live

The many voices of Darwin's descendants: reply to Schmitt (2014).

PubMed

Eastwick, Paul W; Luchies, Laura B; Finkel, Eli J; Hunt, Lucy L

2014-05-01

This article elaborates on evolutionary perspectives relevant to the meta-analytic portion of our recent review (Eastwick, Luchies, Finkel, & Hunt, 2014). We suggested that if men and women evolved sex-differentiated ideals (i.e., mate preferences), then they should exhibit sex-differentiated desires (e.g., romantic attraction) and/or relational outcomes (e.g., relationship satisfaction) with respect to live opposite-sex targets. Our meta-analysis revealed no support for these sex-differentiated desires and relational outcomes in either established relationship or mate selection contexts. With respect to established relationships, Schmitt (2014) has objected to the idea that relationship quality (one of our primarily romantic evaluation dependent measures) has functional relevance. In doing so, he neglects myriad evolutionary perspectives on the adaptive importance of the pair-bond and the wealth of data suggesting that relationship quality predicts the dissolution of pair-bonds. With respect to mate selection, Schmitt (2014) has continued to suggest that sex-differentiated patterns should emerge in these contexts despite the fact that our meta-analysis included this literature and found no sex differences. Schmitt (2014) also generated several novel sex-differentiated predictions with respect to attractiveness and earning prospects, but neither the existing literature nor reanalyses of our meta-analytic data reveal any support for his "proper" function-related hypotheses. In short, there are diverse evolutionary perspectives relevant to mating, including our own synthesis; Schmitt's (2014) conceptual analysis is not the one-and-only evolutionary psychological view, and his alternative explanations for our meta-analytic data remain speculative.

Transient responses' optimization by means of set-based multi-objective evolution

NASA Astrophysics Data System (ADS)

Avigad, Gideon; Eisenstadt, Erella; Goldvard, Alex; Salomon, Shaul

2012-04-01

In this article, a novel solution to multi-objective problems involving the optimization of transient responses is suggested. It is claimed that the common approach of treating such problems by introducing auxiliary objectives overlooks tradeoffs that should be presented to the decision makers. This means that, if at some time during the responses, one of the responses is optimal, it should not be overlooked. An evolutionary multi-objective algorithm is suggested in order to search for these optimal solutions. For this purpose, state-wise domination is utilized with a new crowding measure for ordered sets being suggested. The approach is tested on both artificial as well as on real life problems in order to explain the methodology and demonstrate its applicability and importance. The results indicate that, from an engineering point of view, the approach possesses several advantages over existing approaches. Moreover, the applications highlight the importance of set-based evolution.

Evaluating and Improving Automatic Sleep Spindle Detection by Using Multi-Objective Evolutionary Algorithms

PubMed Central

Liu, Min-Yin; Huang, Adam; Huang, Norden E.

2017-01-01

Sleep spindles are brief bursts of brain activity in the sigma frequency range (11–16 Hz) measured by electroencephalography (EEG) mostly during non-rapid eye movement (NREM) stage 2 sleep. These oscillations are of great biological and clinical interests because they potentially play an important role in identifying and characterizing the processes of various neurological disorders. Conventionally, sleep spindles are identified by expert sleep clinicians via visual inspection of EEG signals. The process is laborious and the results are inconsistent among different experts. To resolve the problem, numerous computerized methods have been developed to automate the process of sleep spindle identification. Still, the performance of these automated sleep spindle detection methods varies inconsistently from study to study. There are two reasons: (1) the lack of common benchmark databases, and (2) the lack of commonly accepted evaluation metrics. In this study, we focus on tackling the second problem by proposing to evaluate the performance of a spindle detector in a multi-objective optimization context and hypothesize that using the resultant Pareto fronts for deriving evaluation metrics will improve automatic sleep spindle detection. We use a popular multi-objective evolutionary algorithm (MOEA), the Strength Pareto Evolutionary Algorithm (SPEA2), to optimize six existing frequency-based sleep spindle detection algorithms. They include three Fourier, one continuous wavelet transform (CWT), and two Hilbert-Huang transform (HHT) based algorithms. We also explore three hybrid approaches. Trained and tested on open-access DREAMS and MASS databases, two new hybrid methods of combining Fourier with HHT algorithms show significant performance improvement with F1-scores of 0.726–0.737. PMID:28572762

A multi-objective genetic algorithm for a mixed-model assembly U-line balancing type-I problem considering human-related issues, training, and learning

NASA Astrophysics Data System (ADS)

Rabbani, Masoud; Montazeri, Mona; Farrokhi-Asl, Hamed; Rafiei, Hamed

2016-12-01

Mixed-model assembly lines are increasingly accepted in many industrial environments to meet the growing trend of greater product variability, diversification of customer demands, and shorter life cycles. In this research, a new mathematical model is presented considering balancing a mixed-model U-line and human-related issues, simultaneously. The objective function consists of two separate components. The first part of the objective function is related to balance problem. In this part, objective functions are minimizing the cycle time, minimizing the number of workstations, and maximizing the line efficiencies. The second part is related to human issues and consists of hiring cost, firing cost, training cost, and salary. To solve the presented model, two well-known multi-objective evolutionary algorithms, namely non-dominated sorting genetic algorithm and multi-objective particle swarm optimization, have been used. A simple solution representation is provided in this paper to encode the solutions. Finally, the computational results are compared and analyzed.

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been provEn effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. Several approaches that have proven effective for other evolutionary algorithms are modified and implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for standard test optimization problems and for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

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

NASA Astrophysics Data System (ADS)

Sharma, Deepak; Barakat, Nada

2018-02-01

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

Proposed method to construct Boolean functions with maximum possible annihilator immunity

NASA Astrophysics Data System (ADS)

Goyal, Rajni; Panigrahi, Anupama; Bansal, Rohit

2017-07-01

Nonlinearity and Algebraic(annihilator) immunity are two core properties of a Boolean function because optimum values of Annihilator Immunity and nonlinearity are required to resist fast algebraic attack and differential cryptanalysis respectively. For a secure cypher system, Boolean function(S-Boxes) should resist maximum number of attacks. It is possible if a Boolean function has optimal trade-off among its properties. Before constructing Boolean functions, we fixed the criteria of our constructions based on its properties. In present work, our construction is based on annihilator immunity and nonlinearity. While keeping above facts in mind,, we have developed a multi-objective evolutionary approach based on NSGA-II and got the optimum value of annihilator immunity with good bound of nonlinearity. We have constructed balanced Boolean functions having the best trade-off among balancedness, Annihilator immunity and nonlinearity for 5, 6 and 7 variables by the proposed method.

Multi-Objective Control Optimization for Greenhouse Environment Using Evolutionary Algorithms

PubMed Central

Hu, Haigen; Xu, Lihong; Wei, Ruihua; Zhu, Bingkun

2011-01-01

This paper investigates the issue of tuning the Proportional Integral and Derivative (PID) controller parameters for a greenhouse climate control system using an Evolutionary Algorithm (EA) based on multiple performance measures such as good static-dynamic performance specifications and the smooth process of control. A model of nonlinear thermodynamic laws between numerous system variables affecting the greenhouse climate is formulated. The proposed tuning scheme is tested for greenhouse climate control by minimizing the integrated time square error (ITSE) and the control increment or rate in a simulation experiment. The results show that by tuning the gain parameters the controllers can achieve good control performance through step responses such as small overshoot, fast settling time, and less rise time and steady state error. Besides, it can be applied to tuning the system with different properties, such as strong interactions among variables, nonlinearities and conflicting performance criteria. The results implicate that it is a quite effective and promising tuning method using multi-objective optimization algorithms in the complex greenhouse production. PMID:22163927

A hybrid flower pollination algorithm based modified randomized location for multi-threshold medical image segmentation.

PubMed

Wang, Rui; Zhou, Yongquan; Zhao, Chengyan; Wu, Haizhou

2015-01-01

Multi-threshold image segmentation is a powerful image processing technique that is used for the preprocessing of pattern recognition and computer vision. However, traditional multilevel thresholding methods are computationally expensive because they involve exhaustively searching the optimal thresholds to optimize the objective functions. To overcome this drawback, this paper proposes a flower pollination algorithm with a randomized location modification. The proposed algorithm is used to find optimal threshold values for maximizing Otsu's objective functions with regard to eight medical grayscale images. When benchmarked against other state-of-the-art evolutionary algorithms, the new algorithm proves itself to be robust and effective through numerical experimental results including Otsu's objective values and standard deviations.

Differential Correlates of Multi-Type Maltreatment among Urban Youth

ERIC Educational Resources Information Center

Arata, Catalina M.; Langhinrichsen-Rohling, Jennifer; Bowers, David; O'Brien, Natalie

2007-01-01

Objective: The aim of this study was to examine the differential effects of multi-types of maltreatment in an adolescent sample. Different combinations of maltreatment (emotional, sexual, physical, neglect) were examined in relation to both negative affect and externalizing symptoms in male and female youth. Method: One thousand four hundred…

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.

Development of antibiotic regimens using graph based evolutionary algorithms.

PubMed

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

2013-12-01

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

Exploring the Pareto frontier using multisexual evolutionary algorithms: an application to a flexible manufacturing problem

NASA Astrophysics Data System (ADS)

Bonissone, Stefano R.; Subbu, Raj

2002-12-01

In multi-objective optimization (MOO) problems we need to optimize many possibly conflicting objectives. For instance, in manufacturing planning we might want to minimize the cost and production time while maximizing the product's quality. We propose the use of evolutionary algorithms (EAs) to solve these problems. Solutions are represented as individuals in a population and are assigned scores according to a fitness function that determines their relative quality. Strong solutions are selected for reproduction, and pass their genetic material to the next generation. Weak solutions are removed from the population. The fitness function evaluates each solution and returns a related score. In MOO problems, this fitness function is vector-valued, i.e. it returns a value for each objective. Therefore, instead of a global optimum, we try to find the Pareto-optimal or non-dominated frontier. We use multi-sexual EAs with as many genders as optimization criteria. We have created new crossover and gender assignment functions, and experimented with various parameters to determine the best setting (yielding the highest number of non-dominated solutions.) These experiments are conducted using a variety of fitness functions, and the algorithms are later evaluated on a flexible manufacturing problem with total cost and time minimization objectives.

The System of Simulation and Multi-objective Optimization for the Roller Kiln

NASA Astrophysics Data System (ADS)

Huang, He; Chen, Xishen; Li, Wugang; Li, Zhuoqiu

It is somewhat a difficult researching problem, to get the building parameters of the ceramic roller kiln simulation model. A system integrated of evolutionary algorithms (PSO, DE and DEPSO) and computational fluid dynamics (CFD), is proposed to solve the problem. And the temperature field uniformity and the environment disruption are studied in this paper. With the help of the efficient parallel calculation, the ceramic roller kiln temperature field uniformity and the NOx emissions field have been researched in the system at the same time. A multi-objective optimization example of the industrial roller kiln proves that the system is of excellent parameter exploration capability.

Dynamic systems and inferential information processing in human communication.

PubMed

Grammer, Karl; Fink, Bernhard; Renninger, LeeAnn

2002-12-01

Research in human communication on an ethological basis is almost obsolete. The reasons for this are manifold and lie partially in methodological problems connected to the observation and description of behavior, as well as the nature of human behavior itself. In this chapter, we present a new, non-intrusive, technical approach to the analysis of human non-verbal behavior, which could help to solve the problem of categorization that plagues the traditional approaches. We utilize evolutionary theory to propose a new theory-driven methodological approach to the 'multi-unit multi-channel modulation' problem of human nonverbal communication. Within this concept, communication is seen as context-dependent (the meaning of a signal is adapted to the situation), as a multi-channel and a multi-unit process (a string of many events interrelated in 'communicative' space and time), and as related to the function it serves. Such an approach can be utilized to successfully bridge the gap between evolutionary psychological research, which focuses on social cognition adaptations, and human ethology, which describes every day behavior in an objective, systematic way.

Prediction of protein-protein interaction network using a multi-objective optimization approach.

PubMed

Chowdhury, Archana; Rakshit, Pratyusha; Konar, Amit

2016-06-01

Protein-Protein Interactions (PPIs) are very important as they coordinate almost all cellular processes. This paper attempts to formulate PPI prediction problem in a multi-objective optimization framework. The scoring functions for the trial solution deal with simultaneous maximization of functional similarity, strength of the domain interaction profiles, and the number of common neighbors of the proteins predicted to be interacting. The above optimization problem is solved using the proposed Firefly Algorithm with Nondominated Sorting. Experiments undertaken reveal that the proposed PPI prediction technique outperforms existing methods, including gene ontology-based Relative Specific Similarity, multi-domain-based Domain Cohesion Coupling method, domain-based Random Decision Forest method, Bagging with REP Tree, and evolutionary/swarm algorithm-based approaches, with respect to sensitivity, specificity, and F1 score.

NARMAX model identification of a palm oil biodiesel engine using multi-objective optimization differential evolution

NASA Astrophysics Data System (ADS)

Mansor, Zakwan; Zakaria, Mohd Zakimi; Nor, Azuwir Mohd; Saad, Mohd Sazli; Ahmad, Robiah; Jamaluddin, Hishamuddin

2017-09-01

This paper presents the black-box modelling of palm oil biodiesel engine (POB) using multi-objective optimization differential evolution (MOODE) algorithm. Two objective functions are considered in the algorithm for optimization; minimizing the number of term of a model structure and minimizing the mean square error between actual and predicted outputs. The mathematical model used in this study to represent the POB system is nonlinear auto-regressive moving average with exogenous input (NARMAX) model. Finally, model validity tests are applied in order to validate the possible models that was obtained from MOODE algorithm and lead to select an optimal model.

Balancing exploration, uncertainty and computational demands in many objective reservoir optimization

NASA Astrophysics Data System (ADS)

Zatarain Salazar, Jazmin; Reed, Patrick M.; Quinn, Julianne D.; Giuliani, Matteo; Castelletti, Andrea

2017-11-01

Reservoir operations are central to our ability to manage river basin systems serving conflicting multi-sectoral demands under increasingly uncertain futures. These challenges motivate the need for new solution strategies capable of effectively and efficiently discovering the multi-sectoral tradeoffs that are inherent to alternative reservoir operation policies. Evolutionary many-objective direct policy search (EMODPS) is gaining importance in this context due to its capability of addressing multiple objectives and its flexibility in incorporating multiple sources of uncertainties. This simulation-optimization framework has high potential for addressing the complexities of water resources management, and it can benefit from current advances in parallel computing and meta-heuristics. This study contributes a diagnostic assessment of state-of-the-art parallel strategies for the auto-adaptive Borg Multi Objective Evolutionary Algorithm (MOEA) to support EMODPS. Our analysis focuses on the Lower Susquehanna River Basin (LSRB) system where multiple sectoral demands from hydropower production, urban water supply, recreation and environmental flows need to be balanced. Using EMODPS with different parallel configurations of the Borg MOEA, we optimize operating policies over different size ensembles of synthetic streamflows and evaporation rates. As we increase the ensemble size, we increase the statistical fidelity of our objective function evaluations at the cost of higher computational demands. This study demonstrates how to overcome the mathematical and computational barriers associated with capturing uncertainties in stochastic multiobjective reservoir control optimization, where parallel algorithmic search serves to reduce the wall-clock time in discovering high quality representations of key operational tradeoffs. Our results show that emerging self-adaptive parallelization schemes exploiting cooperative search populations are crucial. Such strategies provide a promising new set of tools for effectively balancing exploration, uncertainty, and computational demands when using EMODPS.

Geomagnetic Navigation of Autonomous Underwater Vehicle Based on Multi-objective Evolutionary Algorithm.

PubMed

Li, Hong; Liu, Mingyong; Zhang, Feihu

2017-01-01

This paper presents a multi-objective evolutionary algorithm of bio-inspired geomagnetic navigation for Autonomous Underwater Vehicle (AUV). Inspired by the biological navigation behavior, the solution was proposed without using a priori information, simply by magnetotaxis searching. However, the existence of the geomagnetic anomalies has significant influence on the geomagnetic navigation system, which often disrupts the distribution of the geomagnetic field. An extreme value region may easily appear in abnormal regions, which makes AUV lost in the navigation phase. This paper proposes an improved bio-inspired algorithm with behavior constraints, for sake of making AUV escape from the abnormal region. First, the navigation problem is considered as the optimization problem. Second, the environmental monitoring operator is introduced, to determine whether the algorithm falls into the geomagnetic anomaly region. Then, the behavior constraint operator is employed to get out of the abnormal region. Finally, the termination condition is triggered. Compared to the state-of- the-art, the proposed approach effectively overcomes the disturbance of the geomagnetic abnormal. The simulation result demonstrates the reliability and feasibility of the proposed approach in complex environments.

Geomagnetic Navigation of Autonomous Underwater Vehicle Based on Multi-objective Evolutionary Algorithm

PubMed Central

Li, Hong; Liu, Mingyong; Zhang, Feihu

2017-01-01

This paper presents a multi-objective evolutionary algorithm of bio-inspired geomagnetic navigation for Autonomous Underwater Vehicle (AUV). Inspired by the biological navigation behavior, the solution was proposed without using a priori information, simply by magnetotaxis searching. However, the existence of the geomagnetic anomalies has significant influence on the geomagnetic navigation system, which often disrupts the distribution of the geomagnetic field. An extreme value region may easily appear in abnormal regions, which makes AUV lost in the navigation phase. This paper proposes an improved bio-inspired algorithm with behavior constraints, for sake of making AUV escape from the abnormal region. First, the navigation problem is considered as the optimization problem. Second, the environmental monitoring operator is introduced, to determine whether the algorithm falls into the geomagnetic anomaly region. Then, the behavior constraint operator is employed to get out of the abnormal region. Finally, the termination condition is triggered. Compared to the state-of- the-art, the proposed approach effectively overcomes the disturbance of the geomagnetic abnormal. The simulation result demonstrates the reliability and feasibility of the proposed approach in complex environments. PMID:28747884

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

PubMed

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

2009-01-01

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

Modelling the Evolution of Social Structure

PubMed Central

Sutcliffe, A. G.; Dunbar, R. I. M.; Wang, D.

2016-01-01

Although simple social structures are more common in animal societies, some taxa (mainly mammals) have complex, multi-level social systems, in which the levels reflect differential association. We develop a simulation model to explore the conditions under which multi-level social systems of this kind evolve. Our model focuses on the evolutionary trade-offs between foraging and social interaction, and explores the impact of alternative strategies for distributing social interaction, with fitness criteria for wellbeing, alliance formation, risk, stress and access to food resources that reward social strategies differentially. The results suggest that multi-level social structures characterised by a few strong relationships, more medium ties and large numbers of weak ties emerge only in a small part of the overall fitness landscape, namely where there are significant fitness benefits from wellbeing and alliance formation and there are high levels of social interaction. In contrast, ‘favour-the-few’ strategies are more competitive under a wide range of fitness conditions, including those producing homogeneous, single-level societies of the kind found in many birds and mammals. The simulations suggest that the development of complex, multi-level social structures of the kind found in many primates (including humans) depends on a capacity for high investment in social time, preferential social interaction strategies, high mortality risk and/or differential reproduction. These conditions are characteristic of only a few mammalian taxa. PMID:27427758

An analysis of parameter sensitivities of preference-inspired co-evolutionary algorithms

NASA Astrophysics Data System (ADS)

Wang, Rui; Mansor, Maszatul M.; Purshouse, Robin C.; Fleming, Peter J.

2015-10-01

Many-objective optimisation problems remain challenging for many state-of-the-art multi-objective evolutionary algorithms. Preference-inspired co-evolutionary algorithms (PICEAs) which co-evolve the usual population of candidate solutions with a family of decision-maker preferences during the search have been demonstrated to be effective on such problems. However, it is unknown whether PICEAs are robust with respect to the parameter settings. This study aims to address this question. First, a global sensitivity analysis method - the Sobol' variance decomposition method - is employed to determine the relative importance of the parameters controlling the performance of PICEAs. Experimental results show that the performance of PICEAs is controlled for the most part by the number of function evaluations. Next, we investigate the effect of key parameters identified from the Sobol' test and the genetic operators employed in PICEAs. Experimental results show improved performance of the PICEAs as more preferences are co-evolved. Additionally, some suggestions for genetic operator settings are provided for non-expert users.

Provisional-Ideal-Point-Based Multi-objective Optimization Method for Drone Delivery Problem

NASA Astrophysics Data System (ADS)

Omagari, Hiroki; Higashino, Shin-Ichiro

2018-04-01

In this paper, we proposed a new evolutionary multi-objective optimization method for solving drone delivery problems (DDP). It can be formulated as a constrained multi-objective optimization problem. In our previous research, we proposed the "aspiration-point-based method" to solve multi-objective optimization problems. However, this method needs to calculate the optimal values of each objective function value in advance. Moreover, it does not consider the constraint conditions except for the objective functions. Therefore, it cannot apply to DDP which has many constraint conditions. To solve these issues, we proposed "provisional-ideal-point-based method." The proposed method defines a "penalty value" to search for feasible solutions. It also defines a new reference solution named "provisional-ideal point" to search for the preferred solution for a decision maker. In this way, we can eliminate the preliminary calculations and its limited application scope. The results of the benchmark test problems show that the proposed method can generate the preferred solution efficiently. The usefulness of the proposed method is also demonstrated by applying it to DDP. As a result, the delivery path when combining one drone and one truck drastically reduces the traveling distance and the delivery time compared with the case of using only one truck.

Design Optimization of a Centrifugal Fan with Splitter Blades

NASA Astrophysics Data System (ADS)

Heo, Man-Woong; Kim, Jin-Hyuk; Kim, Kwang-Yong

2015-05-01

Multi-objective optimization of a centrifugal fan with additionally installed splitter blades was performed to simultaneously maximize the efficiency and pressure rise using three-dimensional Reynolds-averaged Navier-Stokes equations and hybrid multi-objective evolutionary algorithm. Two design variables defining the location of splitter, and the height ratio between inlet and outlet of impeller were selected for the optimization. In addition, the aerodynamic characteristics of the centrifugal fan were investigated with the variation of design variables in the design space. Latin hypercube sampling was used to select the training points, and response surface approximation models were constructed as surrogate models of the objective functions. With the optimization, both the efficiency and pressure rise of the centrifugal fan with splitter blades were improved considerably compared to the reference model.

Evaluation of the influence of dominance rules for the assembly line design problem under consideration of product design alternatives

NASA Astrophysics Data System (ADS)

Oesterle, Jonathan; Lionel, Amodeo

2018-06-01

The current competitive situation increases the importance of realistically estimating product costs during the early phases of product and assembly line planning projects. In this article, several multi-objective algorithms using difference dominance rules are proposed to solve the problem associated with the selection of the most effective combination of product and assembly lines. The list of developed algorithms includes variants of ant colony algorithms, evolutionary algorithms and imperialist competitive algorithms. The performance of each algorithm and dominance rule is analysed by five multi-objective quality indicators and fifty problem instances. The algorithms and dominance rules are ranked using a non-parametric statistical test.

The In-Transit Vigilant Covering Tour Problem of Routing Unmanned Ground Vehicles

DTIC Science & Technology

2012-08-01

of vertices in both vertex sets V and W, rather than exclusively in the vertex set V. A metaheuristic algorithm which follows the Greedy Randomized...window (VRPTW) approach, with the application of Java-encoded metaheuristic , was used [O’Rourke et al., 2001] for the dynamic routing of UAVs. Harder et...minimize both the two conflicting objectives; tour length and the coverage distance via a multi-objective evolutionary algorithm . This approach avoids a

A multi-resolution strategy for a multi-objective deformable image registration framework that accommodates large anatomical differences

NASA Astrophysics Data System (ADS)

Alderliesten, Tanja; Bosman, Peter A. N.; Sonke, Jan-Jakob; Bel, Arjan

2014-03-01

Currently, two major challenges dominate the field of deformable image registration. The first challenge is related to the tuning of the developed methods to specific problems (i.e. how to best combine different objectives such as similarity measure and transformation effort). This is one of the reasons why, despite significant progress, clinical implementation of such techniques has proven to be difficult. The second challenge is to account for large anatomical differences (e.g. large deformations, (dis)appearing structures) that occurred between image acquisitions. In this paper, we study a framework based on multi-objective optimization to improve registration robustness and to simplify tuning for specific applications. Within this framework we specifically consider the use of an advanced model-based evolutionary algorithm for optimization and a dual-dynamic transformation model (i.e. two "non-fixed" grids: one for the source- and one for the target image) to accommodate for large anatomical differences. The framework computes and presents multiple outcomes that represent efficient trade-offs between the different objectives (a so-called Pareto front). In image processing it is common practice, for reasons of robustness and accuracy, to use a multi-resolution strategy. This is, however, only well-established for single-objective registration methods. Here we describe how such a strategy can be realized for our multi-objective approach and compare its results with a single-resolution strategy. For this study we selected the case of prone-supine breast MRI registration. Results show that the well-known advantages of a multi-resolution strategy are successfully transferred to our multi-objective approach, resulting in superior (i.e. Pareto-dominating) outcomes.

Aspiration dynamics of multi-player games in finite populations

PubMed Central

Du, Jinming; Wu, Bin; Altrock, Philipp M.; Wang, Long

2014-01-01

On studying strategy update rules in the framework of evolutionary game theory, one can differentiate between imitation processes and aspiration-driven dynamics. In the former case, individuals imitate the strategy of a more successful peer. In the latter case, individuals adjust their strategies based on a comparison of their pay-offs from the evolutionary game to a value they aspire, called the level of aspiration. Unlike imitation processes of pairwise comparison, aspiration-driven updates do not require additional information about the strategic environment and can thus be interpreted as being more spontaneous. Recent work has mainly focused on understanding how aspiration dynamics alter the evolutionary outcome in structured populations. However, the baseline case for understanding strategy selection is the well-mixed population case, which is still lacking sufficient understanding. We explore how aspiration-driven strategy-update dynamics under imperfect rationality influence the average abundance of a strategy in multi-player evolutionary games with two strategies. We analytically derive a condition under which a strategy is more abundant than the other in the weak selection limiting case. This approach has a long-standing history in evolutionary games and is mostly applied for its mathematical approachability. Hence, we also explore strong selection numerically, which shows that our weak selection condition is a robust predictor of the average abundance of a strategy. The condition turns out to differ from that of a wide class of imitation dynamics, as long as the game is not dyadic. Therefore, a strategy favoured under imitation dynamics can be disfavoured under aspiration dynamics. This does not require any population structure, and thus highlights the intrinsic difference between imitation and aspiration dynamics. PMID:24598208

Aspiration dynamics of multi-player games in finite populations.

PubMed

Du, Jinming; Wu, Bin; Altrock, Philipp M; Wang, Long

2014-05-06

On studying strategy update rules in the framework of evolutionary game theory, one can differentiate between imitation processes and aspiration-driven dynamics. In the former case, individuals imitate the strategy of a more successful peer. In the latter case, individuals adjust their strategies based on a comparison of their pay-offs from the evolutionary game to a value they aspire, called the level of aspiration. Unlike imitation processes of pairwise comparison, aspiration-driven updates do not require additional information about the strategic environment and can thus be interpreted as being more spontaneous. Recent work has mainly focused on understanding how aspiration dynamics alter the evolutionary outcome in structured populations. However, the baseline case for understanding strategy selection is the well-mixed population case, which is still lacking sufficient understanding. We explore how aspiration-driven strategy-update dynamics under imperfect rationality influence the average abundance of a strategy in multi-player evolutionary games with two strategies. We analytically derive a condition under which a strategy is more abundant than the other in the weak selection limiting case. This approach has a long-standing history in evolutionary games and is mostly applied for its mathematical approachability. Hence, we also explore strong selection numerically, which shows that our weak selection condition is a robust predictor of the average abundance of a strategy. The condition turns out to differ from that of a wide class of imitation dynamics, as long as the game is not dyadic. Therefore, a strategy favoured under imitation dynamics can be disfavoured under aspiration dynamics. This does not require any population structure, and thus highlights the intrinsic difference between imitation and aspiration dynamics.

Multiobjective Aerodynamic Shape Optimization Using Pareto Differential Evolution and Generalized Response Surface Metamodels

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple, fast, and robust evolutionary algorithm that has proven effective in determining the global optimum for several difficult single-objective optimization problems. The DE algorithm has been recently extended to multiobjective optimization problem by using a Pareto-based approach. In this paper, a Pareto DE algorithm is applied to multiobjective aerodynamic shape optimization problems that are characterized by computationally expensive objective function evaluations. To improve computational expensive the algorithm is coupled with generalized response surface meta-models based on artificial neural networks. Results are presented for some test optimization problems from the literature to demonstrate the capabilities of the method.

Hybridization between multi-objective genetic algorithm and support vector machine for feature selection in walker-assisted gait.

PubMed

Martins, Maria; Costa, Lino; Frizera, Anselmo; Ceres, Ramón; Santos, Cristina

2014-03-01

Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, comparatively to a non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information that often is difficult to interpret. This study addresses the problem of selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. For that purpose, it is presented an efficient approach that combines evolutionary techniques, based on genetic algorithms, and support vector machine algorithms, to discriminate differences between assisted and non-assisted gait with a walker with forearm supports. For comparison purposes, other classification algorithms are verified. Results with healthy subjects show that the main differences are characterized by balance and joints excursion in the sagittal plane. These results, confirmed by clinical evidence, allow concluding that this technique is an efficient feature selection approach. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Application of multi-objective controller to optimal tuning of PID gains for a hydraulic turbine regulating system using adaptive grid particle swam optimization.

PubMed

Chen, Zhihuan; Yuan, Yanbin; Yuan, Xiaohui; Huang, Yuehua; Li, Xianshan; Li, Wenwu

2015-05-01

A hydraulic turbine regulating system (HTRS) is one of the most important components of hydropower plant, which plays a key role in maintaining safety, stability and economical operation of hydro-electrical installations. At present, the conventional PID controller is widely applied in the HTRS system for its practicability and robustness, and the primary problem with respect to this control law is how to optimally tune the parameters, i.e. the determination of PID controller gains for satisfactory performance. In this paper, a kind of multi-objective evolutionary algorithms, named adaptive grid particle swarm optimization (AGPSO) is applied to solve the PID gains tuning problem of the HTRS system. This newly AGPSO optimized method, which differs from a traditional one-single objective optimization method, is designed to take care of settling time and overshoot level simultaneously, in which a set of non-inferior alternatives solutions (i.e. Pareto solution) is generated. Furthermore, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto set. An illustrative example associated with the best compromise solution for parameter tuning of the nonlinear HTRS system is introduced to verify the feasibility and the effectiveness of the proposed AGPSO-based optimization approach, as compared with two another prominent multi-objective algorithms, i.e. Non-dominated Sorting Genetic Algorithm II (NSGAII) and Strength Pareto Evolutionary Algorithm II (SPEAII), for the quality and diversity of obtained Pareto solutions set. Consequently, simulation results show that this AGPSO optimized approach outperforms than compared methods with higher efficiency and better quality no matter whether the HTRS system works under unload or load conditions. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Constrained multi-objective optimization of storage ring lattices

NASA Astrophysics Data System (ADS)

Husain, Riyasat; Ghodke, A. D.

2018-03-01

The storage ring lattice optimization is a class of constrained multi-objective optimization problem, where in addition to low beam emittance, a large dynamic aperture for good injection efficiency and improved beam lifetime are also desirable. The convergence and computation times are of great concern for the optimization algorithms, as various objectives are to be optimized and a number of accelerator parameters to be varied over a large span with several constraints. In this paper, a study of storage ring lattice optimization using differential evolution is presented. The optimization results are compared with two most widely used optimization techniques in accelerators-genetic algorithm and particle swarm optimization. It is found that the differential evolution produces a better Pareto optimal front in reasonable computation time between two conflicting objectives-beam emittance and dispersion function in the straight section. The differential evolution was used, extensively, for the optimization of linear and nonlinear lattices of Indus-2 for exploring various operational modes within the magnet power supply capabilities.

Implications of Preference and Problem Formulation on the Operating Policies of Complex Multi-Reservoir Systems

NASA Astrophysics Data System (ADS)

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

2016-12-01

Optimizing the operations of multi-reservoir systems poses several challenges: 1) the high dimension of the problem's states and controls, 2) the need to balance conflicting multi-sector objectives, and 3) understanding how uncertainties impact system performance. These difficulties motivated the development of the Evolutionary Multi-Objective Direct Policy Search (EMODPS) framework, in which multi-reservoir operating policies are parameterized in a given family of functions and then optimized for multiple objectives through simulation over a set of stochastic inputs. However, properly framing these objectives remains a severe challenge and a neglected source of uncertainty. Here, we use EMODPS to optimize operating policies for a 4-reservoir system in the Red River Basin in Vietnam, exploring the consequences of optimizing to different sets of objectives related to 1) hydropower production, 2) meeting multi-sector water demands, and 3) providing flood protection to the capital city of Hanoi. We show how coordinated operation of the reservoirs can differ markedly depending on how decision makers weigh these concerns. Moreover, we illustrate how formulation choices that emphasize the mean, tail, or variability of performance across objective combinations must be evaluated carefully. Our results show that these choices can significantly improve attainable system performance, or yield severe unintended consequences. Finally, we show that satisfactory validation of the operating policies on a set of out-of-sample stochastic inputs depends as much or more on the formulation of the objectives as on effective optimization of the policies. These observations highlight the importance of carefully considering how we abstract stakeholders' objectives and of iteratively optimizing and visualizing multiple problem formulation hypotheses to ensure that we capture the most important tradeoffs that emerge from different stakeholder preferences.

Investigating multi-objective fluence and beam orientation IMRT optimization

NASA Astrophysics Data System (ADS)

Potrebko, Peter S.; Fiege, Jason; Biagioli, Matthew; Poleszczuk, Jan

2017-07-01

Radiation Oncology treatment planning requires compromises to be made between clinical objectives that are invariably in conflict. It would be beneficial to have a ‘bird’s-eye-view’ perspective of the full spectrum of treatment plans that represent the possible trade-offs between delivering the intended dose to the planning target volume (PTV) while optimally sparing the organs-at-risk (OARs). In this work, the authors demonstrate Pareto-aware radiotherapy evolutionary treatment optimization (PARETO), a multi-objective tool featuring such bird’s-eye-view functionality, which optimizes fluence patterns and beam angles for intensity-modulated radiation therapy (IMRT) treatment planning. The problem of IMRT treatment plan optimization is managed as a combined monolithic problem, where all beam fluence and angle parameters are treated equally during the optimization. To achieve this, PARETO is built around a powerful multi-objective evolutionary algorithm, called Ferret, which simultaneously optimizes multiple fitness functions that encode the attributes of the desired dose distribution for the PTV and OARs. The graphical interfaces within PARETO provide useful information such as: the convergence behavior during optimization, trade-off plots between the competing objectives, and a graphical representation of the optimal solution database allowing for the rapid exploration of treatment plan quality through the evaluation of dose-volume histograms and isodose distributions. PARETO was evaluated for two relatively complex clinical cases, a paranasal sinus and a pancreas case. The end result of each PARETO run was a database of optimal (non-dominated) treatment plans that demonstrated trade-offs between the OAR and PTV fitness functions, which were all equally good in the Pareto-optimal sense (where no one objective can be improved without worsening at least one other). Ferret was able to produce high quality solutions even though a large number of parameters, such as beam fluence and beam angles, were included in the optimization.

MONSS: A multi-objective nonlinear simplex search approach

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

SU-F-R-46: Predicting Distant Failure in Lung SBRT Using Multi-Objective Radiomics Model

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

Zhou, Z; Folkert, M; Iyengar, P

2016-06-15

Purpose: To predict distant failure in lung stereotactic body radiation therapy (SBRT) in early stage non-small cell lung cancer (NSCLC) by using a new multi-objective radiomics model. Methods: Currently, most available radiomics models use the overall accuracy as the objective function. However, due to data imbalance, a single object may not reflect the performance of a predictive model. Therefore, we developed a multi-objective radiomics model which considers both sensitivity and specificity as the objective functions simultaneously. The new model is used to predict distant failure in lung SBRT using 52 patients treated at our institute. Quantitative imaging features of PETmore » and CT as well as clinical parameters are utilized to build the predictive model. Image features include intensity features (9), textural features (12) and geometric features (8). Clinical parameters for each patient include demographic parameters (4), tumor characteristics (8), treatment faction schemes (4) and pretreatment medicines (6). The modelling procedure consists of two steps: extracting features from segmented tumors in PET and CT; and selecting features and training model parameters based on multi-objective. Support Vector Machine (SVM) is used as the predictive model, while a nondominated sorting-based multi-objective evolutionary computation algorithm II (NSGA-II) is used for solving the multi-objective optimization. Results: The accuracy for PET, clinical, CT, PET+clinical, PET+CT, CT+clinical, PET+CT+clinical are 71.15%, 84.62%, 84.62%, 85.54%, 82.69%, 84.62%, 86.54%, respectively. The sensitivities for the above seven combinations are 41.76%, 58.33%, 50.00%, 50.00%, 41.67%, 41.67%, 58.33%, while the specificities are 80.00%, 92.50%, 90.00%, 97.50%, 92.50%, 97.50%, 97.50%. Conclusion: A new multi-objective radiomics model for predicting distant failure in NSCLC treated with SBRT was developed. The experimental results show that the best performance can be obtained by combining all features.« less

Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

NASA Astrophysics Data System (ADS)

Dickes, Amanda Catherine; Sengupta, Pratim

2013-06-01

In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these agents obey simple rules assigned or manipulated by the user (e.g., speeding up, slowing down, etc.). It is the interactions between these agents, based on the rules assigned by the user, that give rise to emergent, aggregate-level behavior (e.g., formation and movement of the traffic jam). Natural selection is such an emergent phenomenon, which has been shown to be challenging for novices (K16 students) to understand. Whereas prior research on learning evolutionary phenomena with MABMs has typically focused on high school students and beyond, we investigate how elementary students (4th graders) develop multi-level explanations of some introductory aspects of natural selection—species differentiation and population change—through scaffolded interactions with an MABM that simulates predator-prey dynamics in a simple birds-butterflies ecosystem. We conducted a semi-clinical interview based study with ten participants, in which we focused on the following: a) identifying the nature of learners' initial interpretations of salient events or elements of the represented phenomena, b) identifying the roles these interpretations play in the development of their multi-level explanations, and c) how attending to different levels of the relevant phenomena can make explicit different mechanisms to the learners. In addition, our analysis also shows that although there were differences between high- and low-performing students (in terms of being able to explain population-level behaviors) in the pre-test, these differences disappeared in the post-test.

Pareto-optimal multi-objective dimensionality reduction deep auto-encoder for mammography classification.

PubMed

Taghanaki, Saeid Asgari; Kawahara, Jeremy; Miles, Brandon; Hamarneh, Ghassan

2017-07-01

Feature reduction is an essential stage in computer aided breast cancer diagnosis systems. Multilayer neural networks can be trained to extract relevant features by encoding high-dimensional data into low-dimensional codes. Optimizing traditional auto-encoders works well only if the initial weights are close to a proper solution. They are also trained to only reduce the mean squared reconstruction error (MRE) between the encoder inputs and the decoder outputs, but do not address the classification error. The goal of the current work is to test the hypothesis that extending traditional auto-encoders (which only minimize reconstruction error) to multi-objective optimization for finding Pareto-optimal solutions provides more discriminative features that will improve classification performance when compared to single-objective and other multi-objective approaches (i.e. scalarized and sequential). In this paper, we introduce a novel multi-objective optimization of deep auto-encoder networks, in which the auto-encoder optimizes two objectives: MRE and mean classification error (MCE) for Pareto-optimal solutions, rather than just MRE. These two objectives are optimized simultaneously by a non-dominated sorting genetic algorithm. We tested our method on 949 X-ray mammograms categorized into 12 classes. The results show that the features identified by the proposed algorithm allow a classification accuracy of up to 98.45%, demonstrating favourable accuracy over the results of state-of-the-art methods reported in the literature. We conclude that adding the classification objective to the traditional auto-encoder objective and optimizing for finding Pareto-optimal solutions, using evolutionary multi-objective optimization, results in producing more discriminative features. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

A Hybrid Optimization Framework with POD-based Order Reduction and Design-Space Evolution Scheme

NASA Astrophysics Data System (ADS)

Ghoman, Satyajit S.

The main objective of this research is to develop an innovative multi-fidelity multi-disciplinary design, analysis and optimization suite that integrates certain solution generation codes and newly developed innovative tools to improve the overall optimization process. The research performed herein is divided into two parts: (1) the development of an MDAO framework by integration of variable fidelity physics-based computational codes, and (2) enhancements to such a framework by incorporating innovative features extending its robustness. The first part of this dissertation describes the development of a conceptual Multi-Fidelity Multi-Strategy and Multi-Disciplinary Design Optimization Environment (M3 DOE), in context of aircraft wing optimization. M 3 DOE provides the user a capability to optimize configurations with a choice of (i) the level of fidelity desired, (ii) the use of a single-step or multi-step optimization strategy, and (iii) combination of a series of structural and aerodynamic analyses. The modularity of M3 DOE allows it to be a part of other inclusive optimization frameworks. The M 3 DOE is demonstrated within the context of shape and sizing optimization of the wing of a Generic Business Jet aircraft. Two different optimization objectives, viz. dry weight minimization, and cruise range maximization are studied by conducting one low-fidelity and two high-fidelity optimization runs to demonstrate the application scope of M3 DOE. The second part of this dissertation describes the development of an innovative hybrid optimization framework that extends the robustness of M 3 DOE by employing a proper orthogonal decomposition-based design-space order reduction scheme combined with the evolutionary algorithm technique. The POD method of extracting dominant modes from an ensemble of candidate configurations is used for the design-space order reduction. The snapshot of candidate population is updated iteratively using evolutionary algorithm technique of fitness-driven retention. This strategy capitalizes on the advantages of evolutionary algorithm as well as POD-based reduced order modeling, while overcoming the shortcomings inherent with these techniques. When linked with M3 DOE, this strategy offers a computationally efficient methodology for problems with high level of complexity and a challenging design-space. This newly developed framework is demonstrated for its robustness on a nonconventional supersonic tailless air vehicle wing shape optimization problem.

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

PubMed

Pohlheim, Hartmut

2006-01-01

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

Comparative evolutionary diversity and phylogenetic structure across multiple forest dynamics plots: a mega-phylogeny approach

PubMed Central

Erickson, David L.; Jones, Frank A.; Swenson, Nathan G.; Pei, Nancai; Bourg, Norman A.; Chen, Wenna; Davies, Stuart J.; Ge, Xue-jun; Hao, Zhanqing; Howe, Robert W.; Huang, Chun-Lin; Larson, Andrew J.; Lum, Shawn K. Y.; Lutz, James A.; Ma, Keping; Meegaskumbura, Madhava; Mi, Xiangcheng; Parker, John D.; Fang-Sun, I.; Wright, S. Joseph; Wolf, Amy T.; Ye, W.; Xing, Dingliang; Zimmerman, Jess K.; Kress, W. John

2014-01-01

Forest dynamics plots, which now span longitudes, latitudes, and habitat types across the globe, offer unparalleled insights into the ecological and evolutionary processes that determine how species are assembled into communities. Understanding phylogenetic relationships among species in a community has become an important component of assessing assembly processes. However, the application of evolutionary information to questions in community ecology has been limited in large part by the lack of accurate estimates of phylogenetic relationships among individual species found within communities, and is particularly limiting in comparisons between communities. Therefore, streamlining and maximizing the information content of these community phylogenies is a priority. To test the viability and advantage of a multi-community phylogeny, we constructed a multi-plot mega-phylogeny of 1347 species of trees across 15 forest dynamics plots in the ForestGEO network using DNA barcode sequence data (rbcL, matK, and psbA-trnH) and compared community phylogenies for each individual plot with respect to support for topology and branch lengths, which affect evolutionary inference of community processes. The levels of taxonomic differentiation across the phylogeny were examined by quantifying the frequency of resolved nodes throughout. In addition, three phylogenetic distance (PD) metrics that are commonly used to infer assembly processes were estimated for each plot [PD, Mean Phylogenetic Distance (MPD), and Mean Nearest Taxon Distance (MNTD)]. Lastly, we examine the partitioning of phylogenetic diversity among community plots through quantification of inter-community MPD and MNTD. Overall, evolutionary relationships were highly resolved across the DNA barcode-based mega-phylogeny, and phylogenetic resolution for each community plot was improved when estimated within the context of the mega-phylogeny. Likewise, when compared with phylogenies for individual plots, estimates of phylogenetic diversity in the mega-phylogeny were more consistent, thereby removing a potential source of bias at the plot-level, and demonstrating the value of assessing phylogenetic relationships simultaneously within a mega-phylogeny. An unexpected result of the comparisons among plots based on the mega-phylogeny was that the communities in the ForestGEO plots in general appear to be assemblages of more closely related species than expected by chance, and that differentiation among communities is very low, suggesting deep floristic connections among communities and new avenues for future analyses in community ecology. PMID:25414723

On the usefulness of gradient information in multi-objective deformable image registration using a B-spline-based dual-dynamic transformation model: comparison of three optimization algorithms

NASA Astrophysics Data System (ADS)

Pirpinia, Kleopatra; Bosman, Peter A. N.; Sonke, Jan-Jakob; van Herk, Marcel; Alderliesten, Tanja

2015-03-01

The use of gradient information is well-known to be highly useful in single-objective optimization-based image registration methods. However, its usefulness has not yet been investigated for deformable image registration from a multi-objective optimization perspective. To this end, within a previously introduced multi-objective optimization framework, we use a smooth B-spline-based dual-dynamic transformation model that allows us to derive gradient information analytically, while still being able to account for large deformations. Within the multi-objective framework, we previously employed a powerful evolutionary algorithm (EA) that computes and advances multiple outcomes at once, resulting in a set of solutions (a so-called Pareto front) that represents efficient trade-offs between the objectives. With the addition of the B-spline-based transformation model, we studied the usefulness of gradient information in multiobjective deformable image registration using three different optimization algorithms: the (gradient-less) EA, a gradientonly algorithm, and a hybridization of these two. We evaluated the algorithms to register highly deformed images: 2D MRI slices of the breast in prone and supine positions. Results demonstrate that gradient-based multi-objective optimization significantly speeds up optimization in the initial stages of optimization. However, allowing sufficient computational resources, better results could still be obtained with the EA. Ultimately, the hybrid EA found the best overall approximation of the optimal Pareto front, further indicating that adding gradient-based optimization for multiobjective optimization-based deformable image registration can indeed be beneficial

[Multi-mathematical modelings for compatibility optimization of Jiangzhi granules].

PubMed

Yang, Ming; Zhang, Li; Ge, Yingli; Lu, Yanliu; Ji, Guang

2011-12-01

To investigate into the method of "multi activity index evaluation and combination optimized of mult-component" for Chinese herbal formulas. According to the scheme of uniform experimental design, efficacy experiment, multi index evaluation, least absolute shrinkage, selection operator (LASSO) modeling, evolutionary optimization algorithm, validation experiment, we optimized the combination of Jiangzhi granules based on the activity indexes of blood serum ALT, ALT, AST, TG, TC, HDL, LDL and TG level of liver tissues, ratio of liver tissue to body. Analytic hierarchy process (AHP) combining with criteria importance through intercriteria correlation (CRITIC) for multi activity index evaluation was more reasonable and objective, it reflected the information of activity index's order and objective sample data. LASSO algorithm modeling could accurately reflect the relationship between different combination of Jiangzhi granule and the activity comprehensive indexes. The optimized combination of Jiangzhi granule showed better values of the activity comprehensive indexed than the original formula after the validation experiment. AHP combining with CRITIC can be used for multi activity index evaluation and LASSO algorithm, it is suitable for combination optimized of Chinese herbal formulas.

Nonmathematical concepts of selection, evolutionary energy, and levels of evolution.

PubMed

Darlington, P J

1972-05-01

The place of mathematics in hypotheticodeductive processes and in biological research is discussed. (Natural) Selection is defined and described as differential elimination of performed sets at any level. Sets and acting sets are groups of units (themselves sets of smaller units) at any level that may or do interact. A pseudomathematical equation describes directional change (evolution) in sets at any level. Selection is the ram of evolution; it cannot generate, but can only direct, evolutionary energy. The energy of evolution is derived from molecular or chemical levels, is transmitted upwards through the increasingly complex sets of sets that form living systems, and is turned in directions determined by the sum of selective processes, at different levels, which may either supplement or oppose each other. All evolutionary processes conform to the pseudomathematical equation referred to above, use energy as described above, and have a P/OE (ratio of programming to open-endedness) that cannot be measured, but can be related to other P/OE values. Phylogeny and ontogeny are compared as processes af directional change with set selection. Stages in the evolution of multi-cellular individuals are suggested, and are essentially the same as stages in the evolution of some multi-individual insect societies. Thinking is considered as a part of ontogeny involving an irreversible, nonrepetitive process of set selection in the brain.

Atmospheric lidar multi-user instrument system definition study

NASA Technical Reports Server (NTRS)

Greco, R. V. (Editor)

1980-01-01

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

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

PubMed

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

2006-03-15

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

Multi-objective evolutionary optimization for constructing neural networks for virtual reality visual data mining: application to geophysical prospecting.

PubMed

Valdés, Julio J; Barton, Alan J

2007-05-01

A method for the construction of virtual reality spaces for visual data mining using multi-objective optimization with genetic algorithms on nonlinear discriminant (NDA) neural networks is presented. Two neural network layers (the output and the last hidden) are used for the construction of simultaneous solutions for: (i) a supervised classification of data patterns and (ii) an unsupervised similarity structure preservation between the original data matrix and its image in the new space. A set of spaces are constructed from selected solutions along the Pareto front. This strategy represents a conceptual improvement over spaces computed by single-objective optimization. In addition, genetic programming (in particular gene expression programming) is used for finding analytic representations of the complex mappings generating the spaces (a composition of NDA and orthogonal principal components). The presented approach is domain independent and is illustrated via application to the geophysical prospecting of caves.

Mechanisms of global diversification in the marine species Madeiran Storm-petrel Oceanodroma castro and Monteiro's Storm-petrel O. monteiroi: Insights from a multi-locus approach.

PubMed

Silva, Mauro F; Smith, Andrea L; Friesen, Vicki L; Bried, Joël; Hasegawa, Osamu; Coelho, M Manuela; Silva, Mónica C

2016-05-01

The evolutionary mechanisms underlying the geographic distribution of gene lineages in the marine environment are not as well understood as those affecting terrestrial groups. The continuous nature of the pelagic marine environment may limit opportunities for divergence to occur and lineages to spatially segregate, particularly in highly mobile species. Here, we studied the phylogeography and historical demography of two tropically distributed, pelagic seabirds, the Madeiran Storm-petrel Oceanodroma castro, sampled in the Azores, Madeira, Galapagos and Japan, and its sister species Monteiro's Storm-petrel O. monteiroi (endemic to the Azores), using a multi-locus dataset consisting of 12 anonymous nuclear loci and the mitochondrial locus control region. Both marker types support the existence of four significantly differentiated genetic clusters, including the sampled O. monteiroi population and three populations within O. castro, although only the mitochondrial locus suggests complete lineage sorting. Multi-locus coalescent analyses suggest that most divergence events occurred within the last 200,000years. The proximity in divergence times precluded robust inferences of the species tree, in particular of the evolutionary relationships of the Pacific populations. Despite the great potential for dispersal, divergence among populations apparently proceeded in the absence of gene flow, emphasizing the effect of non-physical barriers, such as those driven by the paleo-oceanographical environments, philopatry and local adaptation, as important mechanisms of population divergence and speciation in highly mobile marine species. In view of the predicted climate change impacts, future changes in the demography and evolutionary dynamics of marine populations might be expected. Copyright © 2016 Elsevier Inc. All rights reserved.

Efficient hybrid evolutionary algorithm for optimization of a strip coiling process

NASA Astrophysics Data System (ADS)

Pholdee, Nantiwat; Park, Won-Woong; Kim, Dong-Kyu; Im, Yong-Taek; Bureerat, Sujin; Kwon, Hyuck-Cheol; Chun, Myung-Sik

2015-04-01

This article proposes an efficient metaheuristic based on hybridization of teaching-learning-based optimization and differential evolution for optimization to improve the flatness of a strip during a strip coiling process. Differential evolution operators were integrated into the teaching-learning-based optimization with a Latin hypercube sampling technique for generation of an initial population. The objective function was introduced to reduce axial inhomogeneity of the stress distribution and the maximum compressive stress calculated by Love's elastic solution within the thin strip, which may cause an irregular surface profile of the strip during the strip coiling process. The hybrid optimizer and several well-established evolutionary algorithms (EAs) were used to solve the optimization problem. The comparative studies show that the proposed hybrid algorithm outperformed other EAs in terms of convergence rate and consistency. It was found that the proposed hybrid approach was powerful for process optimization, especially with a large-scale design problem.

The optimal design of UAV wing structure

NASA Astrophysics Data System (ADS)

Długosz, Adam; Klimek, Wiktor

2018-01-01

The paper presents an optimal design of UAV wing, made of composite materials. The aim of the optimization is to improve strength and stiffness together with reduction of the weight of the structure. Three different types of functionals, which depend on stress, stiffness and the total mass are defined. The paper presents an application of the in-house implementation of the evolutionary multi-objective algorithm in optimization of the UAV wing structure. Values of the functionals are calculated on the basis of results obtained from numerical simulations. Numerical FEM model, consisting of different composite materials is created. Adequacy of the numerical model is verified by results obtained from the experiment, performed on a tensile testing machine. Examples of multi-objective optimization by means of Pareto-optimal set of solutions are presented.

Multi-objective evolutionary optimization for the joint operation of reservoirs of water supply under water-food-energy nexus management

NASA Astrophysics Data System (ADS)

Uen, T. S.; Tsai, W. P.; Chang, F. J.; Huang, A.

2016-12-01

In recent years, urbanization had a great effect on the growth of population and the resource management scheme of water, food and energy nexus (WFE nexus) in Taiwan. Resource shortages of WFE become a long-term and thorny issue due to the complex interactions of WFE nexus. In consideration of rapid socio-economic development, it is imperative to explore an efficient and practical approach for WFE resources management. This study aims to search the optimal solution to WFE nexus and construct a stable water supply system for multiple stakeholders. The Shimen Reservoir and Feitsui Reservoir in northern Taiwan are chosen to conduct the joint operation of the two reservoirs for water supply. This study intends to achieve water resource allocation from the two reservoirs subject to different operating rules and restrictions of resource allocation. The multi-objectives of the joint operation aim at maximizing hydro-power synergistic gains while minimizing water supply deficiency as well as food shortages. We propose to build a multi-objective evolutionary optimization model for analyzing the hydro-power synergistic gains to suggest the most favorable solutions in terms of tradeoffs between WFE. First, this study collected data from two reservoirs and Taiwan power company. Next, we built a WFE nexus model based on system dynamics. Finally, this study optimized the joint operation of the two reservoirs and calculated the synergy of hydro-power generation. The proposed methodology can tackle the complex joint reservoir operation problems. Results can suggest a reliable policy for joint reservoir operation for creating a green economic city under the lowest risks of water supply.

LORENE: Spectral methods differential equations solver

NASA Astrophysics Data System (ADS)

Gourgoulhon, Eric; Grandclément, Philippe; Marck, Jean-Alain; Novak, Jérôme; Taniguchi, Keisuke

2016-08-01

LORENE (Langage Objet pour la RElativité NumériquE) solves various problems arising in numerical relativity, and more generally in computational astrophysics. It is a set of C++ classes and provides tools to solve partial differential equations by means of multi-domain spectral methods. LORENE classes implement basic structures such as arrays and matrices, but also abstract mathematical objects, such as tensors, and astrophysical objects, such as stars and black holes.

Linear antenna array optimization using flower pollination algorithm.

PubMed

Saxena, Prerna; Kothari, Ashwin

2016-01-01

Flower pollination algorithm (FPA) is a new nature-inspired evolutionary algorithm used to solve multi-objective optimization problems. The aim of this paper is to introduce FPA to the electromagnetics and antenna community for the optimization of linear antenna arrays. FPA is applied for the first time to linear array so as to obtain optimized antenna positions in order to achieve an array pattern with minimum side lobe level along with placement of deep nulls in desired directions. Various design examples are presented that illustrate the use of FPA for linear antenna array optimization, and subsequently the results are validated by benchmarking along with results obtained using other state-of-the-art, nature-inspired evolutionary algorithms such as particle swarm optimization, ant colony optimization and cat swarm optimization. The results suggest that in most cases, FPA outperforms the other evolutionary algorithms and at times it yields a similar performance.

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.

Hybrid Robust Multi-Objective Evolutionary Optimization Algorithm

DTIC Science & Technology

2009-03-10

pp. 594-606. 8. Inverse Approaches to Drying of Thin Bodies With Significant Shrinkage Effects (with G. H. Kanevce, L. P. Kanevce, V. B. Mitrevski ...Kanevce, L. Kanevce, V. Mitrevski ), ICCES󈧌: International Conference on Computational & Experimental Engineering and Sciences, Honolulu, Hawaii, March 17...Miami Beach, FL, April 16-18, 2007. 16. Inverse Approaches to Drying of Sliced Foods (with Kanevce, G. H., Kanevce, Lj. P., and Mitrevski , V. B

Evolutionary Psychology and Intelligence Research Cannot Be Integrated the Way Kanazawa (2010) Suggested

ERIC Educational Resources Information Center

Penke, Lars; Borsboom, Denny; Johnson, Wendy; Kievit, Rogier A.; Ploeger, Annemie; Wicherts, Jelte M.

2011-01-01

This article shares the authors' comments on a record by Kanazawa. Evolutionary psychologists search for human universals, differential psychologists for variation around common human themes. So far, evolutionary psychology and differential psychology seem somewhat disparate and unconnected, although Kanazawa is certainly not the first to attempt…

Many-objective robust decision making for water allocation under climate change.

PubMed

Yan, Dan; Ludwig, Fulco; Huang, He Qing; Werners, Saskia E

2017-12-31

Water allocation is facing profound challenges due to climate change uncertainties. To identify adaptive water allocation strategies that are robust to climate change uncertainties, a model framework combining many-objective robust decision making and biophysical modeling is developed for large rivers. The framework was applied to the Pearl River basin (PRB), China where sufficient flow to the delta is required to reduce saltwater intrusion in the dry season. Before identifying and assessing robust water allocation plans for the future, the performance of ten state-of-the-art MOEAs (multi-objective evolutionary algorithms) is evaluated for the water allocation problem in the PRB. The Borg multi-objective evolutionary algorithm (Borg MOEA), which is a self-adaptive optimization algorithm, has the best performance during the historical periods. Therefore it is selected to generate new water allocation plans for the future (2079-2099). This study shows that robust decision making using carefully selected MOEAs can help limit saltwater intrusion in the Pearl River Delta. However, the framework could perform poorly due to larger than expected climate change impacts on water availability. Results also show that subjective design choices from the researchers and/or water managers could potentially affect the ability of the model framework, and cause the most robust water allocation plans to fail under future climate change. Developing robust allocation plans in a river basin suffering from increasing water shortage requires the researchers and water managers to well characterize future climate change of the study regions and vulnerabilities of their tools. Copyright © 2017 Elsevier B.V. All rights reserved.

Mono and multi-objective optimization techniques applied to a large range of industrial test cases using Metamodel assisted Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Fourment, Lionel; Ducloux, Richard; Marie, Stéphane; Ejday, Mohsen; Monnereau, Dominique; Massé, Thomas; Montmitonnet, Pierre

2010-06-01

The use of material processing numerical simulation allows a strategy of trial and error to improve virtual processes without incurring material costs or interrupting production and therefore save a lot of money, but it requires user time to analyze the results, adjust the operating conditions and restart the simulation. Automatic optimization is the perfect complement to simulation. Evolutionary Algorithm coupled with metamodelling makes it possible to obtain industrially relevant results on a very large range of applications within a few tens of simulations and without any specific automatic optimization technique knowledge. Ten industrial partners have been selected to cover the different area of the mechanical forging industry and provide different examples of the forming simulation tools. It aims to demonstrate that it is possible to obtain industrially relevant results on a very large range of applications within a few tens of simulations and without any specific automatic optimization technique knowledge. The large computational time is handled by a metamodel approach. It allows interpolating the objective function on the entire parameter space by only knowing the exact function values at a reduced number of "master points". Two algorithms are used: an evolution strategy combined with a Kriging metamodel and a genetic algorithm combined with a Meshless Finite Difference Method. The later approach is extended to multi-objective optimization. The set of solutions, which corresponds to the best possible compromises between the different objectives, is then computed in the same way. The population based approach allows using the parallel capabilities of the utilized computer with a high efficiency. An optimization module, fully embedded within the Forge2009 IHM, makes possible to cover all the defined examples, and the use of new multi-core hardware to compute several simulations at the same time reduces the needed time dramatically. The presented examples demonstrate the method versatility. They include billet shape optimization of a common rail, the cogging of a bar and a wire drawing problem.

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

Multi locus analysis of Pristionchus pacificus on La Réunion Island reveals an evolutionary history shaped by multiple introductions, constrained dispersal events and rare out-crossing.

PubMed

Morgan, Katy; McGaughran, Angela; Villate, Laure; Herrmann, Matthias; Witte, Hanh; Bartelmes, Gabi; Rochat, Jacques; Sommer, Ralf J

2012-01-01

Pristionchus pacificus, recently established as a model organism in evolutionary biology, is a cosmopolitan nematode that has a necromenic association with scarab beetles. The diverse array of host beetle species and habitat types occupied by P. pacificus make it a good model for investigating local adaptation to novel environments. Presence of P. pacificus on La Réunion Island, a young volcanic island with a dynamic geological history and a wide variety of ecozones, facilitates such investigation in an island biogeographic setting. Microsatellite data from 20 markers and 223 strains and mitochondrial sequence data from 272 strains reveal rich genetic diversity among La Réunion P. pacificus isolates, shaped by differentially timed introductions from diverse sources and in association with different beetle species. Distinctions between volcanic zones and between arid western and wet eastern climatic zones have likely limited westward dispersal of recently colonized lineages and maintained a genetic distinction between eastern and western clades. The highly selfing lifestyle of P. pacificus contributes to the strong fine-scale population structure detected, with each beetle host harbouring strongly differentiated assemblages of strains. Periodic out-crossing generates admixture between genetically diverse lineages, creating a diverse array of allelic combinations likely to increase the evolutionary potential of the species and facilitate adaptation to local environments and beetle hosts. © 2011 Blackwell Publishing Ltd.

Incorporating Objective Function Information Into the Feasibility Rule for Constrained Evolutionary Optimization.

PubMed

Wang, Yong; Wang, Bing-Chuan; Li, Han-Xiong; Yen, Gary G

2016-12-01

When solving constrained optimization problems by evolutionary algorithms, an important issue is how to balance constraints and objective function. This paper presents a new method to address the above issue. In our method, after generating an offspring for each parent in the population by making use of differential evolution (DE), the well-known feasibility rule is used to compare the offspring and its parent. Since the feasibility rule prefers constraints to objective function, the objective function information has been exploited as follows: if the offspring cannot survive into the next generation and if the objective function value of the offspring is better than that of the parent, then the offspring is stored into a predefined archive. Subsequently, the individuals in the archive are used to replace some individuals in the population according to a replacement mechanism. Moreover, a mutation strategy is proposed to help the population jump out of a local optimum in the infeasible region. Note that, in the replacement mechanism and the mutation strategy, the comparison of individuals is based on objective function. In addition, the information of objective function has also been utilized to generate offspring in DE. By the above processes, this paper achieves an effective balance between constraints and objective function in constrained evolutionary optimization. The performance of our method has been tested on two sets of benchmark test functions, namely, 24 test functions at IEEE CEC2006 and 18 test functions with 10-D and 30-D at IEEE CEC2010. The experimental results have demonstrated that our method shows better or at least competitive performance against other state-of-the-art methods. Furthermore, the advantage of our method increases with the increase of the number of decision variables.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Enhancing the performance of MOEAs: an experimental presentation of a new fitness guided mutation operator

NASA Astrophysics Data System (ADS)

Liagkouras, K.; Metaxiotis, K.

2017-01-01

Multi-objective evolutionary algorithms (MOEAs) are currently a dynamic field of research that has attracted considerable attention. Mutation operators have been utilized by MOEAs as variation mechanisms. In particular, polynomial mutation (PLM) is one of the most popular variation mechanisms and has been utilized by many well-known MOEAs. In this paper, we revisit the PLM operator and we propose a fitness-guided version of the PLM. Experimental results obtained by non-dominated sorting genetic algorithm II and strength Pareto evolutionary algorithm 2 show that the proposed fitness-guided mutation operator outperforms the classical PLM operator, based on different performance metrics that evaluate both the proximity of the solutions to the Pareto front and their dispersion on it.

Differential evolution-based multi-objective optimization for the definition of a health indicator for fault diagnostics and prognostics

NASA Astrophysics Data System (ADS)

Baraldi, P.; Bonfanti, G.; Zio, E.

2018-03-01

The identification of the current degradation state of an industrial component and the prediction of its future evolution is a fundamental step for the development of condition-based and predictive maintenance approaches. The objective of the present work is to propose a general method for extracting a health indicator to measure the amount of component degradation from a set of signals measured during operation. The proposed method is based on the combined use of feature extraction techniques, such as Empirical Mode Decomposition and Auto-Associative Kernel Regression, and a multi-objective Binary Differential Evolution (BDE) algorithm for selecting the subset of features optimal for the definition of the health indicator. The objectives of the optimization are desired characteristics of the health indicator, such as monotonicity, trendability and prognosability. A case study is considered, concerning the prediction of the remaining useful life of turbofan engines. The obtained results confirm that the method is capable of extracting health indicators suitable for accurate prognostics.

Modelling Evolutionary Algorithms with Stochastic Differential Equations.

PubMed

Heredia, Jorge Pérez

2017-11-20

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

Multi-objective optimisation of wastewater treatment plant control to reduce greenhouse gas emissions.

PubMed

Sweetapple, Christine; Fu, Guangtao; Butler, David

2014-05-15

This study investigates the potential of control strategy optimisation for the reduction of operational greenhouse gas emissions from wastewater treatment in a cost-effective manner, and demonstrates that significant improvements can be realised. A multi-objective evolutionary algorithm, NSGA-II, is used to derive sets of Pareto optimal operational and control parameter values for an activated sludge wastewater treatment plant, with objectives including minimisation of greenhouse gas emissions, operational costs and effluent pollutant concentrations, subject to legislative compliance. Different problem formulations are explored, to identify the most effective approach to emissions reduction, and the sets of optimal solutions enable identification of trade-offs between conflicting objectives. It is found that multi-objective optimisation can facilitate a significant reduction in greenhouse gas emissions without the need for plant redesign or modification of the control strategy layout, but there are trade-offs to consider: most importantly, if operational costs are not to be increased, reduction of greenhouse gas emissions is likely to incur an increase in effluent ammonia and total nitrogen concentrations. Design of control strategies for a high effluent quality and low costs alone is likely to result in an inadvertent increase in greenhouse gas emissions, so it is of key importance that effects on emissions are considered in control strategy development and optimisation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Artificial Bee Colony Optimization for Short-Term Hydrothermal Scheduling

NASA Astrophysics Data System (ADS)

Basu, M.

2014-12-01

Artificial bee colony optimization is applied to determine the optimal hourly schedule of power generation in a hydrothermal system. Artificial bee colony optimization is a swarm-based algorithm inspired by the food foraging behavior of honey bees. The algorithm is tested on a multi-reservoir cascaded hydroelectric system having prohibited operating zones and thermal units with valve point loading. The ramp-rate limits of thermal generators are taken into consideration. The transmission losses are also accounted for through the use of loss coefficients. The algorithm is tested on two hydrothermal multi-reservoir cascaded hydroelectric test systems. The results of the proposed approach are compared with those of differential evolution, evolutionary programming and particle swarm optimization. From numerical results, it is found that the proposed artificial bee colony optimization based approach is able to provide better solution.

Particle Swarm Optimization Toolbox

NASA Technical Reports Server (NTRS)

Grant, Michael J.

2010-01-01

The Particle Swarm Optimization Toolbox is a library of evolutionary optimization tools developed in the MATLAB environment. The algorithms contained in the library include a genetic algorithm (GA), a single-objective particle swarm optimizer (SOPSO), and a multi-objective particle swarm optimizer (MOPSO). Development focused on both the SOPSO and MOPSO. A GA was included mainly for comparison purposes, and the particle swarm optimizers appeared to perform better for a wide variety of optimization problems. All algorithms are capable of performing unconstrained and constrained optimization. The particle swarm optimizers are capable of performing single and multi-objective optimization. The SOPSO and MOPSO algorithms are based on swarming theory and bird-flocking patterns to search the trade space for the optimal solution or optimal trade in competing objectives. The MOPSO generates Pareto fronts for objectives that are in competition. A GA, based on Darwin evolutionary theory, is also included in the library. The GA consists of individuals that form a population in the design space. The population mates to form offspring at new locations in the design space. These offspring contain traits from both of the parents. The algorithm is based on this combination of traits from parents to hopefully provide an improved solution than either of the original parents. As the algorithm progresses, individuals that hold these optimal traits will emerge as the optimal solutions. Due to the generic design of all optimization algorithms, each algorithm interfaces with a user-supplied objective function. This function serves as a "black-box" to the optimizers in which the only purpose of this function is to evaluate solutions provided by the optimizers. Hence, the user-supplied function can be numerical simulations, analytical functions, etc., since the specific detail of this function is of no concern to the optimizer. These algorithms were originally developed to support entry trajectory and guidance design for the Mars Science Laboratory mission but may be applied to any optimization problem.

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

PubMed Central

Marsh, Tim; Boag, Simon

2013-01-01

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

Of Hissing Snakes and Angry Voices: Human Infants Are Differentially Responsive to Evolutionary Fear-Relevant Sounds

ERIC Educational Resources Information Center

Erlich, Nicole; Lipp, Ottmar V.; Slaughter, Virginia

2013-01-01

Adult humans demonstrate differential processing of stimuli that were recurrent threats to safety and survival throughout evolutionary history. Recent studies suggest that differential processing of evolutionarily ancient threats occurs in human infants, leading to the proposal of an inborn mechanism for rapid identification of, and response to,…

The feasibility of manual parameter tuning for deformable breast MR image registration from a multi-objective optimization perspective.

PubMed

Pirpinia, Kleopatra; Bosman, Peter A N; Loo, Claudette E; Winter-Warnars, Gonneke; Janssen, Natasja N Y; Scholten, Astrid N; Sonke, Jan-Jakob; van Herk, Marcel; Alderliesten, Tanja

2017-06-23

Deformable image registration is typically formulated as an optimization problem involving a linearly weighted combination of terms that correspond to objectives of interest (e.g. similarity, deformation magnitude). The weights, along with multiple other parameters, need to be manually tuned for each application, a task currently addressed mainly via trial-and-error approaches. Such approaches can only be successful if there is a sensible interplay between parameters, objectives, and desired registration outcome. This, however, is not well established. To study this interplay, we use multi-objective optimization, where multiple solutions exist that represent the optimal trade-offs between the objectives, forming a so-called Pareto front. Here, we focus on weight tuning. To study the space a user has to navigate during manual weight tuning, we randomly sample multiple linear combinations. To understand how these combinations relate to desirability of registration outcome, we associate with each outcome a mean target registration error (TRE) based on expert-defined anatomical landmarks. Further, we employ a multi-objective evolutionary algorithm that optimizes the weight combinations, yielding a Pareto front of solutions, which can be directly navigated by the user. To study how the complexity of manual weight tuning changes depending on the registration problem, we consider an easy problem, prone-to-prone breast MR image registration, and a hard problem, prone-to-supine breast MR image registration. Lastly, we investigate how guidance information as an additional objective influences the prone-to-supine registration outcome. Results show that the interplay between weights, objectives, and registration outcome makes manual weight tuning feasible for the prone-to-prone problem, but very challenging for the harder prone-to-supine problem. Here, patient-specific, multi-objective weight optimization is needed, obtaining a mean TRE of 13.6 mm without guidance information reduced to 7.3 mm with guidance information, but also providing a Pareto front that exhibits an intuitively sensible interplay between weights, objectives, and registration outcome, allowing outcome selection.

The feasibility of manual parameter tuning for deformable breast MR image registration from a multi-objective optimization perspective

NASA Astrophysics Data System (ADS)

Pirpinia, Kleopatra; Bosman, Peter A. N.; E Loo, Claudette; Winter-Warnars, Gonneke; Y Janssen, Natasja N.; Scholten, Astrid N.; Sonke, Jan-Jakob; van Herk, Marcel; Alderliesten, Tanja

2017-07-01

Deformable image registration is typically formulated as an optimization problem involving a linearly weighted combination of terms that correspond to objectives of interest (e.g. similarity, deformation magnitude). The weights, along with multiple other parameters, need to be manually tuned for each application, a task currently addressed mainly via trial-and-error approaches. Such approaches can only be successful if there is a sensible interplay between parameters, objectives, and desired registration outcome. This, however, is not well established. To study this interplay, we use multi-objective optimization, where multiple solutions exist that represent the optimal trade-offs between the objectives, forming a so-called Pareto front. Here, we focus on weight tuning. To study the space a user has to navigate during manual weight tuning, we randomly sample multiple linear combinations. To understand how these combinations relate to desirability of registration outcome, we associate with each outcome a mean target registration error (TRE) based on expert-defined anatomical landmarks. Further, we employ a multi-objective evolutionary algorithm that optimizes the weight combinations, yielding a Pareto front of solutions, which can be directly navigated by the user. To study how the complexity of manual weight tuning changes depending on the registration problem, we consider an easy problem, prone-to-prone breast MR image registration, and a hard problem, prone-to-supine breast MR image registration. Lastly, we investigate how guidance information as an additional objective influences the prone-to-supine registration outcome. Results show that the interplay between weights, objectives, and registration outcome makes manual weight tuning feasible for the prone-to-prone problem, but very challenging for the harder prone-to-supine problem. Here, patient-specific, multi-objective weight optimization is needed, obtaining a mean TRE of 13.6 mm without guidance information reduced to 7.3 mm with guidance information, but also providing a Pareto front that exhibits an intuitively sensible interplay between weights, objectives, and registration outcome, allowing outcome selection.

Spinning Gland Transcriptomics from Two Main Clades of Spiders (Order: Araneae) - Insights on Their Molecular, Anatomical and Behavioral Evolution

PubMed Central

Prosdocimi, Francisco; Bittencourt, Daniela; da Silva, Felipe Rodrigues; Kirst, Matias; Motta, Paulo C.; Rech, Elibio L.

2011-01-01

Characterized by distinctive evolutionary adaptations, spiders provide a comprehensive system for evolutionary and developmental studies of anatomical organs, including silk and venom production. Here we performed cDNA sequencing using massively parallel sequencers (454 GS-FLX Titanium) to generate ∼80,000 reads from the spinning gland of Actinopus spp. (infraorder: Mygalomorphae) and Gasteracantha cancriformis (infraorder: Araneomorphae, Orbiculariae clade). Actinopus spp. retains primitive characteristics on web usage and presents a single undifferentiated spinning gland while the orbiculariae spiders have seven differentiated spinning glands and complex patterns of web usage. MIRA, Celera Assembler and CAP3 software were used to cluster NGS reads for each spider. CAP3 unigenes passed through a pipeline for automatic annotation, classification by biological function, and comparative transcriptomics. Genes related to spider silks were manually curated and analyzed. Although a single spidroin gene family was found in Actinopus spp., a vast repertoire of specialized spider silk proteins was encountered in orbiculariae. Astacin-like metalloproteases (meprin subfamily) were shown to be some of the most sampled unigenes and duplicated gene families in G. cancriformis since its evolutionary split from mygalomorphs. Our results confirm that the evolution of the molecular repertoire of silk proteins was accompanied by the (i) anatomical differentiation of spinning glands and (ii) behavioral complexification in the web usage. Finally, a phylogenetic tree was constructed to cluster most of the known spidroins in gene clades. This is the first large-scale, multi-organism transcriptome for spider spinning glands and a first step into a broad understanding of spider web systems biology and evolution. PMID:21738742

Scalable multi-objective control for large scale water resources systems under uncertainty

NASA Astrophysics Data System (ADS)

Giuliani, Matteo; Quinn, Julianne; Herman, Jonathan; Castelletti, Andrea; Reed, Patrick

2016-04-01

The use of mathematical models to support the optimal management of environmental systems is rapidly expanding over the last years due to advances in scientific knowledge of the natural processes, efficiency of the optimization techniques, and availability of computational resources. However, undergoing changes in climate and society introduce additional challenges for controlling these systems, ultimately motivating the emergence of complex models to explore key causal relationships and dependencies on uncontrolled sources of variability. In this work, we contribute a novel implementation of the evolutionary multi-objective direct policy search (EMODPS) method for controlling environmental systems under uncertainty. The proposed approach combines direct policy search (DPS) with hierarchical parallelization of multi-objective evolutionary algorithms (MOEAs) and offers a threefold advantage: the DPS simulation-based optimization can be combined with any simulation model and does not add any constraint on modeled information, allowing the use of exogenous information in conditioning the decisions. Moreover, the combination of DPS and MOEAs prompts the generation or Pareto approximate set of solutions for up to 10 objectives, thus overcoming the decision biases produced by cognitive myopia, where narrow or restrictive definitions of optimality strongly limit the discovery of decision relevant alternatives. Finally, the use of large-scale MOEAs parallelization improves the ability of the designed solutions in handling the uncertainty due to severe natural variability. The proposed approach is demonstrated on a challenging water resources management problem represented by the optimal control of a network of four multipurpose water reservoirs in the Red River basin (Vietnam). As part of the medium-long term energy and food security national strategy, four large reservoirs have been constructed on the Red River tributaries, which are mainly operated for hydropower production, flood control, and water supply. Numerical results under historical as well as synthetically generated hydrologic conditions show that our approach is able to discover key system tradeoffs in the operations of the system. The ability of the algorithm to find near-optimal solutions increases with the number of islands in the adopted hierarchical parallelization scheme. In addition, although significant performance degradation is observed when the solutions designed over history are re-evaluated over synthetically generated inflows, we successfully reduced these vulnerabilities by identifying alternative solutions that are more robust to hydrologic uncertainties, while also addressing the tradeoffs across the Red River multi-sector services.

Remarks on Hierarchic Control for a Linearized Micropolar Fluids System in Moving Domains

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

Jesus, Isaías Pereira de, E-mail: isaias@ufpi.edu.br

We study a Stackelberg strategy subject to the evolutionary linearized micropolar fluids equations in domains with moving boundaries, considering a Nash multi-objective equilibrium (non necessarily cooperative) for the “follower players” (as is called in the economy field) and an optimal problem for the leader player with approximate controllability objective. We will obtain the following main results: the existence and uniqueness of Nash equilibrium and its characterization, the approximate controllability of the linearized micropolar system with respect to the leader control and the existence and uniqueness of the Stackelberg–Nash problem, where the optimality system for the leader is given.

A climate for speciation: rapid spatial diversification within the Sorex cinereus complex of shrews

USGS Publications Warehouse

Hope, Andrew G.; Speer, Kelly A.; Demboski, John R.; Talbot, Sandra L.; Cook, Joseph A.

2012-01-01

The cyclic climate regime of the late Quaternary caused dramatic environmental change at high latitudes. Although these events may have been brief in periodicity from an evolutionary standpoint, multiple episodes of allopatry and divergence have been implicated in rapid radiations of a number of organisms. Shrews of the Sorex cinereus complex have long challenged taxonomists due to similar morphology and parapatric geographic ranges. Here, multi-locus phylogenetic and demographic assessments using a coalescent framework were combined to investigate spatiotemporal evolution of 13 nominal species with a widespread distribution throughout North America and across Beringia into Siberia. For these species, we first test a hypothesis of recent differentiation in response to Pleistocene climate versus more ancient divergence that would coincide with pre-Pleistocene perturbations. We then investigate the processes driving diversification over multiple continents. Our genetic analyses highlight novel diversity within these morphologically conserved mammals and clarify relationships between geographic distribution and evolutionary history. Demography within and among species indicates both regional stability and rapid expansion. Ancestral ecological differentiation coincident with early cladogenesis within the complex enabled alternating and repeated episodes of allopatry and expansion where successive glacial and interglacial phases each promoted divergence. The Sorex cinereus complex constitutes a valuable model for future comparative assessments of evolution in response to cyclic environmental change.

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. These approaches are implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

Evolutionary model selection and parameter estimation for protein-protein interaction network based on differential evolution algorithm

PubMed Central

Huang, Lei; Liao, Li; Wu, Cathy H.

2016-01-01

Revealing the underlying evolutionary mechanism plays an important role in understanding protein interaction networks in the cell. While many evolutionary models have been proposed, the problem about applying these models to real network data, especially for differentiating which model can better describe evolutionary process for the observed network urgently remains as a challenge. The traditional way is to use a model with presumed parameters to generate a network, and then evaluate the fitness by summary statistics, which however cannot capture the complete network structures information and estimate parameter distribution. In this work we developed a novel method based on Approximate Bayesian Computation and modified Differential Evolution (ABC-DEP) that is capable of conducting model selection and parameter estimation simultaneously and detecting the underlying evolutionary mechanisms more accurately. We tested our method for its power in differentiating models and estimating parameters on the simulated data and found significant improvement in performance benchmark, as compared with a previous method. We further applied our method to real data of protein interaction networks in human and yeast. Our results show Duplication Attachment model as the predominant evolutionary mechanism for human PPI networks and Scale-Free model as the predominant mechanism for yeast PPI networks. PMID:26357273

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.

An efficient non-dominated sorting method for evolutionary algorithms.

PubMed

Fang, Hongbing; Wang, Qian; Tu, Yi-Cheng; Horstemeyer, Mark F

2008-01-01

We present a new non-dominated sorting algorithm to generate the non-dominated fronts in multi-objective optimization with evolutionary algorithms, particularly the NSGA-II. The non-dominated sorting algorithm used by NSGA-II has a time complexity of O(MN(2)) in generating non-dominated fronts in one generation (iteration) for a population size N and M objective functions. Since generating non-dominated fronts takes the majority of total computational time (excluding the cost of fitness evaluations) of NSGA-II, making this algorithm faster will significantly improve the overall efficiency of NSGA-II and other genetic algorithms using non-dominated sorting. The new non-dominated sorting algorithm proposed in this study reduces the number of redundant comparisons existing in the algorithm of NSGA-II by recording the dominance information among solutions from their first comparisons. By utilizing a new data structure called the dominance tree and the divide-and-conquer mechanism, the new algorithm is faster than NSGA-II for different numbers of objective functions. Although the number of solution comparisons by the proposed algorithm is close to that of NSGA-II when the number of objectives becomes large, the total computational time shows that the proposed algorithm still has better efficiency because of the adoption of the dominance tree structure and the divide-and-conquer mechanism.

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

Online Build-Order Optimization for Real-Time Strategy Agents using Multi-Objective Evolutionary Algorithms

DTIC Science & Technology

2014-03-27

Their chromosome representation is a binary string of 13 actions or 39 bits. Plans consist of a limited number of build actions for the creation of...injected via case-injection which resembles case-base reasoning. Expert actions are recorded and then transformed into chromosomes for injection into GAPs...sites supply a finite amount of a resource. For example, a gold mine in AOE will disappear after a player’s workers have extracted the finite amount of

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.

Modeling and optimization of the multiobjective stochastic joint replenishment and delivery problem under supply chain environment.

PubMed

Wang, Lin; Qu, Hui; Liu, Shan; Dun, Cai-xia

2013-01-01

As a practical inventory and transportation problem, it is important to synthesize several objectives for the joint replenishment and delivery (JRD) decision. In this paper, a new multiobjective stochastic JRD (MSJRD) of the one-warehouse and n-retailer systems considering the balance of service level and total cost simultaneously is proposed. The goal of this problem is to decide the reasonable replenishment interval, safety stock factor, and traveling routing. Secondly, two approaches are designed to handle this complex multi-objective optimization problem. Linear programming (LP) approach converts the multi-objective to single objective, while a multi-objective evolution algorithm (MOEA) solves a multi-objective problem directly. Thirdly, three intelligent optimization algorithms, differential evolution algorithm (DE), hybrid DE (HDE), and genetic algorithm (GA), are utilized in LP-based and MOEA-based approaches. Results of the MSJRD with LP-based and MOEA-based approaches are compared by a contrastive numerical example. To analyses the nondominated solution of MOEA, a metric is also used to measure the distribution of the last generation solution. Results show that HDE outperforms DE and GA whenever LP or MOEA is adopted.

Modeling and Optimization of the Multiobjective Stochastic Joint Replenishment and Delivery Problem under Supply Chain Environment

PubMed Central

Dun, Cai-xia

2013-01-01

As a practical inventory and transportation problem, it is important to synthesize several objectives for the joint replenishment and delivery (JRD) decision. In this paper, a new multiobjective stochastic JRD (MSJRD) of the one-warehouse and n-retailer systems considering the balance of service level and total cost simultaneously is proposed. The goal of this problem is to decide the reasonable replenishment interval, safety stock factor, and traveling routing. Secondly, two approaches are designed to handle this complex multi-objective optimization problem. Linear programming (LP) approach converts the multi-objective to single objective, while a multi-objective evolution algorithm (MOEA) solves a multi-objective problem directly. Thirdly, three intelligent optimization algorithms, differential evolution algorithm (DE), hybrid DE (HDE), and genetic algorithm (GA), are utilized in LP-based and MOEA-based approaches. Results of the MSJRD with LP-based and MOEA-based approaches are compared by a contrastive numerical example. To analyses the nondominated solution of MOEA, a metric is also used to measure the distribution of the last generation solution. Results show that HDE outperforms DE and GA whenever LP or MOEA is adopted. PMID:24302880

Optimizing LX-17 Thermal Decomposition Model Parameters with Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Moore, Jason; McClelland, Matthew; Tarver, Craig; Hsu, Peter; Springer, H. Keo

2017-06-01

We investigate and model the cook-off behavior of LX-17 because this knowledge is critical to understanding system response in abnormal thermal environments. Thermal decomposition of LX-17 has been explored in conventional ODTX (One-Dimensional Time-to-eXplosion), PODTX (ODTX with pressure-measurement), TGA (thermogravimetric analysis), and DSC (differential scanning calorimetry) experiments using varied temperature profiles. These experimental data are the basis for developing multiple reaction schemes with coupled mechanics in LLNL's multi-physics hydrocode, ALE3D (Arbitrary Lagrangian-Eulerian code in 2D and 3D). We employ evolutionary algorithms to optimize reaction rate parameters on high performance computing clusters. Once experimentally validated, this model will be scalable to a number of applications involving LX-17 and can be used to develop more sophisticated experimental methods. Furthermore, the optimization methodology developed herein should be applicable to other high explosive materials. This work was performed under the auspices of the U.S. DOE by LLNL under contract DE-AC52-07NA27344. LLNS, LLC.

Fixation times in differentiation and evolution in the presence of bottlenecks, deserts, and oases.

PubMed

Chou, Tom; Wang, Yu

2015-05-07

Cellular differentiation and evolution are stochastic processes that can involve multiple types (or states) of particles moving on a complex, high-dimensional state-space or "fitness" landscape. Cells of each specific type can thus be quantified by their population at a corresponding node within a network of states. Their dynamics across the state-space network involve genotypic or phenotypic transitions that can occur upon cell division, such as during symmetric or asymmetric cell differentiation, or upon spontaneous mutation. Here, we use a general multi-type branching processes to study first passage time statistics for a single cell to appear in a specific state. Our approach readily allows for nonexponentially distributed waiting times between transitions, reflecting, e.g., the cell cycle. For simplicity, we restrict most of our detailed analysis to exponentially distributed waiting times (Poisson processes). We present results for a sequential evolutionary process in which L successive transitions propel a population from a "wild-type" state to a given "terminally differentiated," "resistant," or "cancerous" state. Analytic and numeric results are also found for first passage times across an evolutionary chain containing a node with increased death or proliferation rate, representing a desert/bottleneck or an oasis. Processes involving cell proliferation are shown to be "nonlinear" (even though mean-field equations for the expected particle numbers are linear) resulting in first passage time statistics that depend on the position of the bottleneck or oasis. Our results highlight the sensitivity of stochastic measures to cell division fate and quantify the limitations of using certain approximations (such as the fixed-population and mean-field assumptions) in evaluating fixation times. Published by Elsevier Ltd.

Multi-Objective Algorithm for Blood Supply via Unmanned Aerial Vehicles to the Wounded in an Emergency Situation

PubMed Central

Wen, Tingxi; Zhang, Zhongnan; Wong, Kelvin K. L.

2016-01-01

Unmanned aerial vehicle (UAV) has been widely used in many industries. In the medical environment, especially in some emergency situations, UAVs play an important role such as the supply of medicines and blood with speed and efficiency. In this paper, we study the problem of multi-objective blood supply by UAVs in such emergency situations. This is a complex problem that includes maintenance of the supply blood’s temperature model during transportation, the UAVs’ scheduling and routes’ planning in case of multiple sites requesting blood, and limited carrying capacity. Most importantly, we need to study the blood’s temperature change due to the external environment, the heating agent (or refrigerant) and time factor during transportation, and propose an optimal method for calculating the mixing proportion of blood and appendage in different circumstances and delivery conditions. Then, by introducing the idea of transportation appendage into the traditional Capacitated Vehicle Routing Problem (CVRP), this new problem is proposed according to the factors of distance and weight. Algorithmically, we use the combination of decomposition-based multi-objective evolutionary algorithm and local search method to perform a series of experiments on the CVRP public dataset. By comparing our technique with the traditional ones, our algorithm can obtain better optimization results and time performance. PMID:27163361

Multi-Objective Algorithm for Blood Supply via Unmanned Aerial Vehicles to the Wounded in an Emergency Situation.

PubMed

Wen, Tingxi; Zhang, Zhongnan; Wong, Kelvin K L

2016-01-01

Unmanned aerial vehicle (UAV) has been widely used in many industries. In the medical environment, especially in some emergency situations, UAVs play an important role such as the supply of medicines and blood with speed and efficiency. In this paper, we study the problem of multi-objective blood supply by UAVs in such emergency situations. This is a complex problem that includes maintenance of the supply blood's temperature model during transportation, the UAVs' scheduling and routes' planning in case of multiple sites requesting blood, and limited carrying capacity. Most importantly, we need to study the blood's temperature change due to the external environment, the heating agent (or refrigerant) and time factor during transportation, and propose an optimal method for calculating the mixing proportion of blood and appendage in different circumstances and delivery conditions. Then, by introducing the idea of transportation appendage into the traditional Capacitated Vehicle Routing Problem (CVRP), this new problem is proposed according to the factors of distance and weight. Algorithmically, we use the combination of decomposition-based multi-objective evolutionary algorithm and local search method to perform a series of experiments on the CVRP public dataset. By comparing our technique with the traditional ones, our algorithm can obtain better optimization results and time performance.

Adaptive evolutionary conservation: towards a unified concept for defining conservation units.

PubMed

Fraser, D J; Bernatchez, L

2001-12-01

Recent years have seen a debate over various methods that could objectively prioritize conservation value below the species level. Most prominent among these has been the evolutionarily significant unit (ESU). We reviewed ESU concepts with the aim of proposing a more unified concept that would reconcile opposing views. Like species concepts, conflicting ESU concepts are all essentially aiming to define the same thing: segments of species whose divergence can be measured or evaluated by putting differential emphasis on the role of evolutionary forces at varied temporal scales. Thus, differences between ESU concepts lie more in the criteria used to define the ESUs themselves rather than in their fundamental essence. We provide a context-based framework for delineating ESUs which circumvents much of this situation. Rather than embroil in a befuddled debate over an optimal criterion, the key to a solution is accepting that differing criteria will work more dynamically than others and can be used alone or in combination depending on the situation. These assertions constitute the impetus behind adaptive evolutionary conservation.

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

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

Multi-objective Optimization of Pulsed Gas Metal Arc Welding Process Using Neuro NSGA-II

NASA Astrophysics Data System (ADS)

Pal, Kamal; Pal, Surjya K.

2018-05-01

Weld quality is a critical issue in fabrication industries where products are custom-designed. Multi-objective optimization results number of solutions in the pareto-optimal front. Mathematical regression model based optimization methods are often found to be inadequate for highly non-linear arc welding processes. Thus, various global evolutionary approaches like artificial neural network, genetic algorithm (GA) have been developed. The present work attempts with elitist non-dominated sorting GA (NSGA-II) for optimization of pulsed gas metal arc welding process using back propagation neural network (BPNN) based weld quality feature models. The primary objective to maintain butt joint weld quality is the maximization of tensile strength with minimum plate distortion. BPNN has been used to compute the fitness of each solution after adequate training, whereas NSGA-II algorithm generates the optimum solutions for two conflicting objectives. Welding experiments have been conducted on low carbon steel using response surface methodology. The pareto-optimal front with three ranked solutions after 20th generations was considered as the best without further improvement. The joint strength as well as transverse shrinkage was found to be drastically improved over the design of experimental results as per validated pareto-optimal solutions obtained.

Analysis and optimization of hybrid electric vehicle thermal management systems

NASA Astrophysics Data System (ADS)

Hamut, H. S.; Dincer, I.; Naterer, G. F.

2014-02-01

In this study, the thermal management system of a hybrid electric vehicle is optimized using single and multi-objective evolutionary algorithms in order to maximize the exergy efficiency and minimize the cost and environmental impact of the system. The objective functions are defined and decision variables, along with their respective system constraints, are selected for the analysis. In the multi-objective optimization, a Pareto frontier is obtained and a single desirable optimal solution is selected based on LINMAP decision-making process. The corresponding solutions are compared against the exergetic, exergoeconomic and exergoenvironmental single objective optimization results. The results show that the exergy efficiency, total cost rate and environmental impact rate for the baseline system are determined to be 0.29, ¢28 h-1 and 77.3 mPts h-1 respectively. Moreover, based on the exergoeconomic optimization, 14% higher exergy efficiency and 5% lower cost can be achieved, compared to baseline parameters at an expense of a 14% increase in the environmental impact. Based on the exergoenvironmental optimization, a 13% higher exergy efficiency and 5% lower environmental impact can be achieved at the expense of a 27% increase in the total cost.

Performance assessment and optimization of an irreversible nano-scale Stirling engine cycle operating with Maxwell-Boltzmann gas

NASA Astrophysics Data System (ADS)

Ahmadi, Mohammad H.; Ahmadi, Mohammad-Ali; Pourfayaz, Fathollah

2015-09-01

Developing new technologies like nano-technology improves the performance of the energy industries. Consequently, emerging new groups of thermal cycles in nano-scale can revolutionize the energy systems' future. This paper presents a thermo-dynamical study of a nano-scale irreversible Stirling engine cycle with the aim of optimizing the performance of the Stirling engine cycle. In the Stirling engine cycle the working fluid is an Ideal Maxwell-Boltzmann gas. Moreover, two different strategies are proposed for a multi-objective optimization issue, and the outcomes of each strategy are evaluated separately. The first strategy is proposed to maximize the ecological coefficient of performance (ECOP), the dimensionless ecological function (ecf) and the dimensionless thermo-economic objective function ( F . Furthermore, the second strategy is suggested to maximize the thermal efficiency ( η), the dimensionless ecological function (ecf) and the dimensionless thermo-economic objective function ( F). All the strategies in the present work are executed via a multi-objective evolutionary algorithms based on NSGA∥ method. Finally, to achieve the final answer in each strategy, three well-known decision makers are executed. Lastly, deviations of the outcomes gained in each strategy and each decision maker are evaluated separately.

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.

A method for optimizing multi-objective reservoir operation upon human and riverine ecosystem demands

NASA Astrophysics Data System (ADS)

Ai, Xueshan; Dong, Zuo; Mo, Mingzhu

2017-04-01

The optimal reservoir operation is in generally a multi-objective problem. In real life, most of the reservoir operation optimization problems involve conflicting objectives, for which there is no single optimal solution which can simultaneously gain an optimal result of all the purposes, but rather a set of well distributed non-inferior solutions or Pareto frontier exists. On the other hand, most of the reservoirs operation rules is to gain greater social and economic benefits at the expense of ecological environment, resulting to the destruction of riverine ecology and reduction of aquatic biodiversity. To overcome these drawbacks, this study developed a multi-objective model for the reservoir operating with the conflicting functions of hydroelectric energy generation, irrigation and ecological protection. To solve the model with the objectives of maximize energy production, maximize the water demand satisfaction rate of irrigation and ecology, we proposed a multi-objective optimization method of variable penalty coefficient (VPC), which was based on integrate dynamic programming (DP) with discrete differential dynamic programming (DDDP), to generate a well distributed non-inferior along the Pareto front by changing the penalties coefficient of different objectives. This method was applied to an existing China reservoir named Donggu, through a course of a year, which is a multi-annual storage reservoir with multiple purposes. The case study results showed a good relationship between any two of the objectives and a good Pareto optimal solutions, which provide a reference for the reservoir decision makers.

A Pareto-based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets.

PubMed

Fernández, Alberto; Carmona, Cristobal José; José Del Jesus, María; Herrera, Francisco

2017-09-01

Imbalanced classification is related to those problems that have an uneven distribution among classes. In addition to the former, when instances are located into the overlapped areas, the correct modeling of the problem becomes harder. Current solutions for both issues are often focused on the binary case study, as multi-class datasets require an additional effort to be addressed. In this research, we overcome these problems by carrying out a combination between feature and instance selections. Feature selection will allow simplifying the overlapping areas easing the generation of rules to distinguish among the classes. Selection of instances from all classes will address the imbalance itself by finding the most appropriate class distribution for the learning task, as well as possibly removing noise and difficult borderline examples. For the sake of obtaining an optimal joint set of features and instances, we embedded the searching for both parameters in a Multi-Objective Evolutionary Algorithm, using the C4.5 decision tree as baseline classifier in this wrapper approach. The multi-objective scheme allows taking a double advantage: the search space becomes broader, and we may provide a set of different solutions in order to build an ensemble of classifiers. This proposal has been contrasted versus several state-of-the-art solutions on imbalanced classification showing excellent results in both binary and multi-class problems.

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.

Analytical model for orbital debris environmental management

NASA Technical Reports Server (NTRS)

Talent, David L.

1990-01-01

A differential equation, also referred to as the PIB (particle-in-a-box) model, expressing the time rate of change of the number of objects in orbit, is developed, and its applicability is illustrated. The model can be used as a tool for the assessment of LEO environment stability, and as a starting point for the development of numerical evolutionary models. Within the context of the model, evolutionary scenarios are examined, and found to be sensitive to the growth rate. It is determined that the present environment is slightly unstable to catastrophic growth, and that the number of particles on orbit will continue to increase until approximately 2250-2350 AD, with a maximum of 2,000,000. The model is expandable to the more realistic (complex) case of multiple species in a multiple-tier system.

Combining environment-driven adaptation and task-driven optimisation in evolutionary robotics.

PubMed

Haasdijk, Evert; Bredeche, Nicolas; Eiben, A E

2014-01-01

Embodied evolutionary robotics is a sub-field of evolutionary robotics that employs evolutionary algorithms on the robotic hardware itself, during the operational period, i.e., in an on-line fashion. This enables robotic systems that continuously adapt, and are therefore capable of (re-)adjusting themselves to previously unknown or dynamically changing conditions autonomously, without human oversight. This paper addresses one of the major challenges that such systems face, viz. that the robots must satisfy two sets of requirements. Firstly, they must continue to operate reliably in their environment (viability), and secondly they must competently perform user-specified tasks (usefulness). The solution we propose exploits the fact that evolutionary methods have two basic selection mechanisms-survivor selection and parent selection. This allows evolution to tackle the two sets of requirements separately: survivor selection is driven by the environment and parent selection is based on task-performance. This idea is elaborated in the Multi-Objective aNd open-Ended Evolution (monee) framework, which we experimentally validate. Experiments with robotic swarms of 100 simulated e-pucks show that monee does indeed promote task-driven behaviour without compromising environmental adaptation. We also investigate an extension of the parent selection process with a 'market mechanism' that can ensure equitable distribution of effort over multiple tasks, a particularly pressing issue if the environment promotes specialisation in single tasks.

Multi-Objective Scheduling for the Cluster II Constellation

NASA Technical Reports Server (NTRS)

Johnston, Mark D.; Giuliano, Mark

2011-01-01

This paper describes the application of the MUSE multiobjecctive scheduling framework to the Cluster II WBD scheduling domain. Cluster II is an ESA four-spacecraft constellation designed to study the plasma environment of the Earth and it's magnetosphere. One of the instruments on each of the four spacecraft is the Wide Band Data (WBD) plasma wave experiment. We have applied the MUSE evolutionary algorithm to the scheduling problem represented by this instrument, and the result has been adopted and utilized by the WBD schedulers for nearly a year. This paper describes the WBD scheduling problem, its representation in MUSE, and some of the visualization elements that provide insight into objective value tradeoffs.

Multi-strategy coevolving aging particle optimization.

PubMed

Iacca, Giovanni; Caraffini, Fabio; Neri, Ferrante

2014-02-01

We propose Multi-Strategy Coevolving Aging Particles (MS-CAP), a novel population-based algorithm for black-box optimization. In a memetic fashion, MS-CAP combines two components with complementary algorithm logics. In the first stage, each particle is perturbed independently along each dimension with a progressively shrinking (decaying) radius, and attracted towards the current best solution with an increasing force. In the second phase, the particles are mutated and recombined according to a multi-strategy approach in the fashion of the ensemble of mutation strategies in Differential Evolution. The proposed algorithm is tested, at different dimensionalities, on two complete black-box optimization benchmarks proposed at the Congress on Evolutionary Computation 2010 and 2013. To demonstrate the applicability of the approach, we also test MS-CAP to train a Feedforward Neural Network modeling the kinematics of an 8-link robot manipulator. The numerical results show that MS-CAP, for the setting considered in this study, tends to outperform the state-of-the-art optimization algorithms on a large set of problems, thus resulting in a robust and versatile optimizer.

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.

Stochastic eco-evolutionary model of a prey-predator community.

PubMed

Costa, Manon; Hauzy, Céline; Loeuille, Nicolas; Méléard, Sylvie

2016-02-01

We are interested in the impact of natural selection in a prey-predator community. We introduce an individual-based model of the community that takes into account both prey and predator phenotypes. Our aim is to understand the phenotypic coevolution of prey and predators. The community evolves as a multi-type birth and death process with mutations. We first consider the infinite particle approximation of the process without mutation. In this limit, the process can be approximated by a system of differential equations. We prove the existence of a unique globally asymptotically stable equilibrium under specific conditions on the interaction among prey individuals. When mutations are rare, the community evolves on the mutational scale according to a Markovian jump process. This process describes the successive equilibria of the prey-predator community and extends the polymorphic evolutionary sequence to a coevolutionary framework. We then assume that mutations have a small impact on phenotypes and consider the evolution of monomorphic prey and predator populations. The limit of small mutation steps leads to a system of two differential equations which is a version of the canonical equation of adaptive dynamics for the prey-predator coevolution. We illustrate these different limits with an example of prey-predator community that takes into account different prey defense mechanisms. We observe through simulations how these various prey strategies impact the community.

Power-Aware Intrusion Detection in Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

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

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

Detection et caracterisation de naines brunes et exoplanetes avec un filtre accordable pour applications dans l'espace

NASA Astrophysics Data System (ADS)

Ingraham, Patrick Jon

This thesis determines the capability of detecting faint companions in the presence of speckle noise when performing space-based high-contrast imaging through spectral differential imagery (SDI) using a low-order Fabry-Perot etalon as a tunable filter. The performance of such a tunable filter is illustrated through the Tunable Filter Imager (TFI), an instrument designed for the James Webb Space Telescope (JWST). Using a TFI prototype etalon and a custom designed test bed, the etalon's ability to perform speckle-suppression through SDI is demonstrated experimentally. Improvements in contrast vary with separation, ranging from a factor of ˜10 at working angles greater than 11 lambda/D and increasing up to a factor of ˜60 at 5 lambda/D. These measurements are consistent with a Fresnel optical propagation model which shows the speckle suppression capability is limited by the test bed and not the etalon. This result demonstrates that a tunable filter is an attractive option to perform high-contrast imaging through SDI. To explore the capability of space-based SDI using an etalon, we perform an end-to-end Fresnel propagation of JWST and TFI. Using this simulation, a contrast improvement ranging from a factor of ˜7 to ˜100 is predicted, depending on the instrument's configuration. The performance of roll-subtraction is simulated and compared to that of SDI. The SDI capability of the Near-Infrared Imager and Slitless Spectrograph (NIRISS), the science instrument module to replace TFI in the JWST Fine Guidance Sensor is also determined. Using low resolution, multi-band (0.85-2.4 microm) multi-object spectroscopy, 104 objects towards the central region of the Orion Nebular Cluster have been assigned spectral types including 7 new brown dwarfs, and 4 new planetary mass candidates. These objects are useful for determining the substellar initial mass function and for testing evolutionary and atmospheric models of young stellar and substellar objects. Using the measured H band magnitudes, combined with our determined extinction values, the classified objects are used to create an Hertzsprung-Russell diagram for the cluster. Our results indicate a single epoch of star formation beginning ˜1 Myr ago. The initial mass function of the cluster is derived and found to be consistent with the values determined for other young clusters and the galactic disk.

Hybrid Microgrid Configuration Optimization with Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Lopez, Nicolas

This dissertation explores the Renewable Energy Integration Problem, and proposes a Genetic Algorithm embedded with a Monte Carlo simulation to solve large instances of the problem that are impractical to solve via full enumeration. The Renewable Energy Integration Problem is defined as finding the optimum set of components to supply the electric demand to a hybrid microgrid. The components considered are solar panels, wind turbines, diesel generators, electric batteries, connections to the power grid and converters, which can be inverters and/or rectifiers. The methodology developed is explained as well as the combinatorial formulation. In addition, 2 case studies of a single objective optimization version of the problem are presented, in order to minimize cost and to minimize global warming potential (GWP) followed by a multi-objective implementation of the offered methodology, by utilizing a non-sorting Genetic Algorithm embedded with a monte Carlo Simulation. The method is validated by solving a small instance of the problem with known solution via a full enumeration algorithm developed by NREL in their software HOMER. The dissertation concludes that the evolutionary algorithms embedded with Monte Carlo simulation namely modified Genetic Algorithms are an efficient form of solving the problem, by finding approximate solutions in the case of single objective optimization, and by approximating the true Pareto front in the case of multiple objective optimization of the Renewable Energy Integration Problem.

Low-cost interferometric TDM technology for dynamic sensing applications

NASA Astrophysics Data System (ADS)

Bush, Jeff; Cekorich, Allen

2004-12-01

A low-cost design approach for Time Division Multiplexed (TDM) fiber-optic interferometric interrogation of multi-channel sensor arrays is presented. This paper describes the evolutionary design process of the subject design. First, the requisite elements of interferometric interrogation are defined for a single channel sensor. The concept is then extended to multi-channel sensor interrogation implementing a TDM multiplex scheme where "traditional" design elements are utilized. The cost of the traditional TDM interrogator is investigated and concluded to be too high for entry into many markets. A new design approach is presented which significantly reduces the cost for TDM interrogation. This new approach, in accordance with the cost objectives, shows promise to bring this technology to within the threshold of commercial acceptance for a wide range of distributed fiber sensing applications.

Optimal harvesting for a predator-prey agent-based model using difference equations.

PubMed

Oremland, Matthew; Laubenbacher, Reinhard

2015-03-01

In this paper, a method known as Pareto optimization is applied in the solution of a multi-objective optimization problem. The system in question is an agent-based model (ABM) wherein global dynamics emerge from local interactions. A system of discrete mathematical equations is formulated in order to capture the dynamics of the ABM; while the original model is built up analytically from the rules of the model, the paper shows how minor changes to the ABM rule set can have a substantial effect on model dynamics. To address this issue, we introduce parameters into the equation model that track such changes. The equation model is amenable to mathematical theory—we show how stability analysis can be performed and validated using ABM data. We then reduce the equation model to a simpler version and implement changes to allow controls from the ABM to be tested using the equations. Cohen's weighted κ is proposed as a measure of similarity between the equation model and the ABM, particularly with respect to the optimization problem. The reduced equation model is used to solve a multi-objective optimization problem via a technique known as Pareto optimization, a heuristic evolutionary algorithm. Results show that the equation model is a good fit for ABM data; Pareto optimization provides a suite of solutions to the multi-objective optimization problem that can be implemented directly in the ABM.

Multi-functional roles of a soldier-specific volatile as a worker arrestant, primer pheromone and an antimicrobial agent in a termite.

PubMed

Mitaka, Yuki; Mori, Naoki; Matsuura, Kenji

2017-07-26

Division of labour in eusocial insects is characterized by efficient communication systems based on pheromones. Among such insects, termites have evolved specialized sterile defenders, called soldiers. Because they are incapable of feeding themselves, it has been suggested that soldiers are sustained by workers and emit the pheromone arresting workers. However, such a soldier pheromone has not been identified in any termite species, and the details of the soldier-worker interaction remain to be explored. Here, we identified a soldier-specific volatile sesquiterpene as a worker arrestant, which also acts as a primer pheromone regulating soldier differentiation and fungistatic agent in a termite Reticulitermes speratus Chemical analyses revealed that (-)- β -elemene is the major component of soldier extract, and its authentic standard exhibited arrestant activity to workers and inhibited the differentiation from workers to soldiers. This compound also showed fungistatic activity against entomopathogenic fungi. These suggest that (-)- β -elemene secreted by soldiers acts not only as a worker arrestant but also as one component of inhibitory primer pheromone and an anti-pathogenic agent. Our study provides novel evidence supporting the multi-functionality of termite soldier pheromone and provides new insights into the role of soldiers and the evolutionary mechanisms of pheromone compounds. © 2017 The Author(s).

Modeling Kuiper belt objects Charon, Orcus and Salacia by means of a new equation of state for porous icy bodies

NASA Astrophysics Data System (ADS)

Malamud, Uri; Prialnik, Dina

2015-01-01

We use a one-dimensional adaptive-grid thermal evolution code to model Kuiper belt objects Charon, Orcus and Salacia and compare their measured bulk densities with those resulting from evolutionary calculations at the end of 4.6 Gyr. Our model assumes an initial homogeneous composition of mixed ice and rock, and follows the multiphase flow of water through the porous rocky medium, consequent differentiation and aqueous chemical alterations in the rock. Heating sources include long-lived radionuclides, serpentinization reactions, release of gravitational potential energy due to compaction, and crystallization of amorphous ice. The density profile is calculated by assuming hydrostatic equilibrium to be maintained through changes in composition, pressure and temperature. To this purpose, we construct an equation of state suitable for porous icy bodies with radii of a few hundred km, based on the best available empirical studies of ice and rock compaction, and on comparisons with rock porosities in Earth analog and Solar System silicates. We show that the observed bulk densities can be reproduced by assuming the same set of initial and physical parameters, including the same rock/ice mass ratio for all three bodies. We conclude that the mass of the object uniquely determines the evolution of porosity, and thus explains the observed differences in bulk density. The final structure of all three objects is differentiated, with an inner rocky core, and outer ice-enriched mantle. The degree of differentiation, too, is determined by the object's mass.

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.

Classification of heavy metal ions present in multi-frequency multi-electrode potable water data using evolutionary algorithm

NASA Astrophysics Data System (ADS)

Karkra, Rashmi; Kumar, Prashant; Bansod, Baban K. S.; Bagchi, Sudeshna; Sharma, Pooja; Krishna, C. Rama

2017-11-01

Access to potable water for the common people is one of the most challenging tasks in the present era. Contamination of drinking water has become a serious problem due to various anthropogenic and geogenic events. The paper demonstrates the application of evolutionary algorithms, viz., particle swan optimization and genetic algorithm to 24 water samples containing eight different heavy metal ions (Cd, Cu, Co, Pb, Zn, Ar, Cr and Ni) for the optimal estimation of electrode and frequency to classify the heavy metal ions. The work has been carried out on multi-variate data, viz., single electrode multi-frequency, single frequency multi-electrode and multi-frequency multi-electrode water samples. The electrodes used are platinum, gold, silver nanoparticles and glassy carbon electrodes. Various hazardous metal ions present in the water samples have been optimally classified and validated by the application of Davis Bouldin index. Such studies are useful in the segregation of hazardous heavy metal ions found in water resources, thereby quantifying the degree of water quality.

Multispecies genetic objectives in spatial conservation planning.

PubMed

Nielsen, Erica S; Beger, Maria; Henriques, Romina; Selkoe, Kimberly A; von der Heyden, Sophie

2017-08-01

Growing threats to biodiversity and global alteration of habitats and species distributions make it increasingly necessary to consider evolutionary patterns in conservation decision making. Yet, there is no clear-cut guidance on how genetic features can be incorporated into conservation-planning processes, despite multiple molecular markers and several genetic metrics for each marker type to choose from. Genetic patterns differ between species, but the potential tradeoffs among genetic objectives for multiple species in conservation planning are currently understudied. We compared spatial conservation prioritizations derived from 2 metrics of genetic diversity (nucleotide and haplotype diversity) and 2 metrics of genetic isolation (private haplotypes and local genetic differentiation) in mitochondrial DNA of 5 marine species. We compared outcomes of conservation plans based only on habitat representation with plans based on genetic data and habitat representation. Fewer priority areas were selected for conservation plans based solely on habitat representation than on plans that included habitat and genetic data. All 4 genetic metrics selected approximately similar conservation-priority areas, which is likely a result of prioritizing genetic patterns across a genetically diverse array of species. Largely, our results suggest that multispecies genetic conservation objectives are vital to creating protected-area networks that appropriately preserve community-level evolutionary patterns. © 2016 Society for Conservation Biology.

An Evolutionary Framework for Understanding the Origin of Eukaryotes.

PubMed

Blackstone, Neil W

2016-04-27

Two major obstacles hinder the application of evolutionary theory to the origin of eukaryotes. The first is more apparent than real-the endosymbiosis that led to the mitochondrion is often described as "non-Darwinian" because it deviates from the incremental evolution championed by the modern synthesis. Nevertheless, endosymbiosis can be accommodated by a multi-level generalization of evolutionary theory, which Darwin himself pioneered. The second obstacle is more serious-all of the major features of eukaryotes were likely present in the last eukaryotic common ancestor thus rendering comparative methods ineffective. In addition to a multi-level theory, the development of rigorous, sequence-based phylogenetic and comparative methods represents the greatest achievement of modern evolutionary theory. Nevertheless, the rapid evolution of major features in the eukaryotic stem group requires the consideration of an alternative framework. Such a framework, based on the contingent nature of these evolutionary events, is developed and illustrated with three examples: the putative intron proliferation leading to the nucleus and the cell cycle; conflict and cooperation in the origin of eukaryotic bioenergetics; and the inter-relationship between aerobic metabolism, sterol synthesis, membranes, and sex. The modern synthesis thus provides sufficient scope to develop an evolutionary framework to understand the origin of eukaryotes.

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

MultiSeq: unifying sequence and structure data for evolutionary analysis

PubMed Central

Roberts, Elijah; Eargle, John; Wright, Dan; Luthey-Schulten, Zaida

2006-01-01

Background Since the publication of the first draft of the human genome in 2000, bioinformatic data have been accumulating at an overwhelming pace. Currently, more than 3 million sequences and 35 thousand structures of proteins and nucleic acids are available in public databases. Finding correlations in and between these data to answer critical research questions is extremely challenging. This problem needs to be approached from several directions: information science to organize and search the data; information visualization to assist in recognizing correlations; mathematics to formulate statistical inferences; and biology to analyze chemical and physical properties in terms of sequence and structure changes. Results Here we present MultiSeq, a unified bioinformatics analysis environment that allows one to organize, display, align and analyze both sequence and structure data for proteins and nucleic acids. While special emphasis is placed on analyzing the data within the framework of evolutionary biology, the environment is also flexible enough to accommodate other usage patterns. The evolutionary approach is supported by the use of predefined metadata, adherence to standard ontological mappings, and the ability for the user to adjust these classifications using an electronic notebook. MultiSeq contains a new algorithm to generate complete evolutionary profiles that represent the topology of the molecular phylogenetic tree of a homologous group of distantly related proteins. The method, based on the multidimensional QR factorization of multiple sequence and structure alignments, removes redundancy from the alignments and orders the protein sequences by increasing linear dependence, resulting in the identification of a minimal basis set of sequences that spans the evolutionary space of the homologous group of proteins. Conclusion MultiSeq is a major extension of the Multiple Alignment tool that is provided as part of VMD, a structural visualization program for analyzing molecular dynamics simulations. Both are freely distributed by the NIH Resource for Macromolecular Modeling and Bioinformatics and MultiSeq is included with VMD starting with version 1.8.5. The MultiSeq website has details on how to download and use the software: PMID:16914055

Evolutionary potential games on lattices

NASA Astrophysics Data System (ADS)

Szabó, György; Borsos, István

2016-04-01

Game theory provides a general mathematical background to study the effect of pair interactions and evolutionary rules on the macroscopic behavior of multi-player games where players with a finite number of strategies may represent a wide scale of biological objects, human individuals, or even their associations. In these systems the interactions are characterized by matrices that can be decomposed into elementary matrices (games) and classified into four types. The concept of decomposition helps the identification of potential games and also the evaluation of the potential that plays a crucial role in the determination of the preferred Nash equilibrium, and defines the Boltzmann distribution towards which these systems evolve for suitable types of dynamical rules. This survey draws parallel between the potential games and the kinetic Ising type models which are investigated for a wide scale of connectivity structures. We discuss briefly the applicability of the tools and concepts of statistical physics and thermodynamics. Additionally the general features of ordering phenomena, phase transitions and slow relaxations are outlined and applied to evolutionary games. The discussion extends to games with three or more strategies. Finally we discuss what happens when the system is weakly driven out of the "equilibrium state" by adding non-potential components representing games of cyclic dominance.

LS³: A Method for Improving Phylogenomic Inferences When Evolutionary Rates Are Heterogeneous among Taxa

PubMed Central

Rivera-Rivera, Carlos J.; Montoya-Burgos, Juan I.

2016-01-01

Phylogenetic inference artifacts can occur when sequence evolution deviates from assumptions made by the models used to analyze them. The combination of strong model assumption violations and highly heterogeneous lineage evolutionary rates can become problematic in phylogenetic inference, and lead to the well-described long-branch attraction (LBA) artifact. Here, we define an objective criterion for assessing lineage evolutionary rate heterogeneity among predefined lineages: the result of a likelihood ratio test between a model in which the lineages evolve at the same rate (homogeneous model) and a model in which different lineage rates are allowed (heterogeneous model). We implement this criterion in the algorithm Locus Specific Sequence Subsampling (LS³), aimed at reducing the effects of LBA in multi-gene datasets. For each gene, LS³ sequentially removes the fastest-evolving taxon of the ingroup and tests for lineage rate homogeneity until all lineages have uniform evolutionary rates. The sequences excluded from the homogeneously evolving taxon subset are flagged as potentially problematic. The software implementation provides the user with the possibility to remove the flagged sequences for generating a new concatenated alignment. We tested LS³ with simulations and two real datasets containing LBA artifacts: a nucleotide dataset regarding the position of Glires within mammals and an amino-acid dataset concerning the position of nematodes within bilaterians. The initially incorrect phylogenies were corrected in all cases upon removing data flagged by LS³. PMID:26912812

Self-emergence of Lexicon Consensus in a Population of Autonomous Agents by Means of Evolutionary Strategies

NASA Astrophysics Data System (ADS)

Maravall, Darío; de Lope, Javier; Domínguez, Raúl

In Multi-agent systems, the study of language and communication is an active field of research. In this paper we present the application of evolutionary strategies to the self-emergence of a common lexicon in a population of agents. By modeling the vocabulary or lexicon of each agent as an association matrix or look-up table that maps the meanings (i.e. the objects encountered by the agents or the states of the environment itself) into symbols or signals we check whether it is possible for the population to converge in an autonomous, decentralized way to a common lexicon, so that the communication efficiency of the entire population is optimal. We have conducted several experiments, from the simplest case of a 2×2 association matrix (i.e. two meanings and two symbols) to a 3×3 lexicon case and in both cases we have attained convergence to the optimal communication system by means of evolutionary strategies. To analyze the convergence of the population of agents we have defined the population's consensus when all the agents (i.e. the 100% of the population) share the same association matrix or lexicon. As a general conclusion we have shown that evolutionary strategies are powerful enough optimizers to guarantee the convergence to lexicon consensus in a population of autonomous agents.

Aphid specialization on different summer hosts is associated with strong genetic differentiation and unequal symbiont communities despite a common mating habitat.

PubMed

Vorburger, C; Herzog, J; Rouchet, R

2017-04-01

Specialization on different host plants can promote evolutionary diversification of herbivorous insects. Work on pea aphids (Acyrthosiphon pisum) has contributed significantly to the understanding of this process, demonstrating that populations associated with different host plants exhibit performance trade-offs across hosts, show adaptive host choice and genetic differentiation and possess different communities of bacterial endosymbionts. Populations specialized on different secondary host plants during the parthenogenetic summer generations are also described for the black bean aphid (Aphis fabae complex) and are usually treated as different (morphologically cryptic) subspecies. In contrast to pea aphids, however, host choice and mate choice are decoupled in black bean aphids, because populations from different summer hosts return to the same primary host plant to mate and lay overwintering eggs. This could counteract evolutionary divergence, and it is currently unknown to what extent black bean aphids using different summer hosts are indeed differentiated. We addressed this question by microsatellite genotyping and endosymbiont screening of black bean aphids collected in summer from the goosefoot Chenopodium album (subspecies A. f. fabae) and from thistles of the genus Cirsium (subspecies A. f. cirsiiacanthoides) across numerous sites in Switzerland and France. Our results show clearly that aphids from Cirsium and Chenopodium exhibit strong and geographically consistent genetic differentiation and that they differ in their frequencies of infection with particular endosymbionts. The dependence on a joint winter host has thus not prevented the evolutionary divergence into summer host-adapted populations that appear to have evolved mechanisms of reproductive isolation within a common mating habitat. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Population delimitation across contrasting evolutionary clines in deer mice (Peromyscus maniculatus)

PubMed Central

Yang, D-S; Kenagy, G

2011-01-01

Despite current interest in population genetics, a concrete definition of a “population” remains elusive. Multiple ecologically and evolutionarily based definitions of population are in current use, which focus, respectively, on demographic and genetic interactions. Accurate population delimitation is crucial for not only evolutionary and ecological population biology, but also for conservation of threatened populations. Along the Pacific Coast of North America, two contrasting patterns of geographic variation in deer mice (Peromyscus maniculatus) converge within the state of Oregon. Populations of these mice diverge morphologically across an east–west axis, and they diverge in mitochondrial DNA haplotypes across a north–south axis. In this study, we investigate these geographically contrasting patterns of differentiation in the context of ecological and evolutionary definitions (paradigms) of populations. We investigate these patterns using a new and geographically expansive sample that integrates data on morphology, mitochondrial DNA, and nuclear DNA. We found no evidence of nuclear genetic differentiation between the morphologically and mitochondrially distinct populations, thus indicating the occurrence of gene flow across Oregon. Under the evolutionary paradigm, Oregon populations can be considered a single population, whereas morphological and mitochondrial differentiations do not indicate distinct populations. In contrast, under the ecological paradigm morphological differentiation indicates distinct populations based on the low likelihood of demographic interactions between geographically distant individuals. The two sympatric but mitochondrially distinct haplogroups form a single population under the ecological paradigm. Hence, we find that the difference between evolutionary and ecological paradigms is the time-scale of interest, and we believe that the more chronologically inclusive evolutionary paradigm may be preferable except in cases where only a single generation is of interest. PMID:22393480

Co-evolution for Problem Simplification

NASA Technical Reports Server (NTRS)

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

1999-01-01

This paper explores a co-evolutionary approach applicable to difficult problems with limited failure/success performance feedback. Like familiar "predator-prey" frameworks this algorithm evolves two populations of individuals - the solutions (predators) and the problems (prey). The approach extends previous work by rewarding only the problems that match their difficulty to the level of solut,ion competence. In complex problem domains with limited feedback, this "tractability constraint" helps provide an adaptive fitness gradient that, effectively differentiates the candidate solutions. The algorithm generates selective pressure toward the evolution of increasingly competent solutions by rewarding solution generality and uniqueness and problem tractability and difficulty. Relative (inverse-fitness) and absolute (static objective function) approaches to evaluating problem difficulty are explored and discussed. On a simple control task, this co-evolutionary algorithm was found to have significant advantages over a genetic algorithm with either a static fitness function or a fitness function that changes on a hand-tuned schedule.

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.

Diagnostic Assessment of the Difficulty Using Direct Policy Search in Many-Objective Reservoir Control

NASA Astrophysics Data System (ADS)

Zatarain-Salazar, J.; Reed, P. M.; Herman, J. D.; Giuliani, M.; Castelletti, A.

2014-12-01

Globally reservoir operations provide fundamental services to water supply, energy generation, recreation, and ecosystems. The pressures of expanding populations, climate change, and increased energy demands are motivating a significant investment in re-operationalizing existing reservoirs or defining operations for new reservoirs. Recent work has highlighted the potential benefits of exploiting recent advances in many-objective optimization and direct policy search (DPS) to aid in addressing these systems' multi-sector demand tradeoffs. This study contributes to a comprehensive diagnostic assessment of multi-objective evolutionary optimization algorithms (MOEAs) efficiency, effectiveness, reliability, and controllability when supporting DPS for the Conowingo dam in the Lower Susquehanna River Basin. The Lower Susquehanna River is an interstate water body that has been subject to intensive water management efforts due to the system's competing demands from urban water supply, atomic power plant cooling, hydropower production, and federally regulated environmental flows. Seven benchmark and state-of-the-art MOEAs are tested on deterministic and stochastic instances of the Susquehanna test case. In the deterministic formulation, the operating objectives are evaluated over the historical realization of the hydroclimatic variables (i.e., inflows and evaporation rates). In the stochastic formulation, the same objectives are instead evaluated over an ensemble of stochastic inflows and evaporation rates realizations. The algorithms are evaluated in their ability to support DPS in discovering reservoir operations that compose the tradeoffs for six multi-sector performance objectives with thirty-two decision variables. Our diagnostic results highlight that many-objective DPS is very challenging for modern MOEAs and that epsilon dominance is critical for attaining high levels of performance. Epsilon dominance algorithms epsilon-MOEA, epsilon-NSGAII and the auto adaptive Borg MOEA, are statistically superior for the six-objective Susquehanna instance of this important class of problems. Additionally, shifting from deterministic history-based DPS to stochastic DPS significantly increases the difficulty of the problem.

Parametric Sensitivity Analysis of Oscillatory Delay Systems with an Application to Gene Regulation.

PubMed

Ingalls, Brian; Mincheva, Maya; Roussel, Marc R

2017-07-01

A parametric sensitivity analysis for periodic solutions of delay-differential equations is developed. Because phase shifts cause the sensitivity coefficients of a periodic orbit to diverge, we focus on sensitivities of the extrema, from which amplitude sensitivities are computed, and of the period. Delay-differential equations are often used to model gene expression networks. In these models, the parametric sensitivities of a particular genotype define the local geometry of the evolutionary landscape. Thus, sensitivities can be used to investigate directions of gradual evolutionary change. An oscillatory protein synthesis model whose properties are modulated by RNA interference is used as an example. This model consists of a set of coupled delay-differential equations involving three delays. Sensitivity analyses are carried out at several operating points. Comments on the evolutionary implications of the results are offered.

Analysis of the expected density of internal equilibria in random evolutionary multi-player multi-strategy games.

PubMed

Duong, Manh Hong; Han, The Anh

2016-12-01

In this paper, we study the distribution and behaviour of internal equilibria in a d-player n-strategy random evolutionary game where the game payoff matrix is generated from normal distributions. The study of this paper reveals and exploits interesting connections between evolutionary game theory and random polynomial theory. The main contributions of the paper are some qualitative and quantitative results on the expected density, [Formula: see text], and the expected number, E(n, d), of (stable) internal equilibria. Firstly, we show that in multi-player two-strategy games, they behave asymptotically as [Formula: see text] as d is sufficiently large. Secondly, we prove that they are monotone functions of d. We also make a conjecture for games with more than two strategies. Thirdly, we provide numerical simulations for our analytical results and to support the conjecture. As consequences of our analysis, some qualitative and quantitative results on the distribution of zeros of a random Bernstein polynomial are also obtained.

Dynamical tuning for MPC using population games: A water supply network application.

PubMed

Barreiro-Gomez, Julian; Ocampo-Martinez, Carlos; Quijano, Nicanor

2017-07-01

Model predictive control (MPC) is a suitable strategy for the control of large-scale systems that have multiple design requirements, e.g., multiple physical and operational constraints. Besides, an MPC controller is able to deal with multiple control objectives considering them within the cost function, which implies to determine a proper prioritization for each of the objectives. Furthermore, when the system has time-varying parameters and/or disturbances, the appropriate prioritization might vary along the time as well. This situation leads to the need of a dynamical tuning methodology. This paper addresses the dynamical tuning issue by using evolutionary game theory. The advantages of the proposed method are highlighted and tested over a large-scale water supply network with periodic time-varying disturbances. Finally, results are analyzed with respect to a multi-objective MPC controller that uses static tuning. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Modeling KBOs Charon, Orcus and Salacia by means of a new equation of state for porous icy bodies

NASA Astrophysics Data System (ADS)

Malamud, U.; Prialnik, D.

2015-10-01

We use a one-dimensional adaptive-grid thermal evolution code to model intermediate sized Kuiper belt objects Charon, Orcus and Salacia and compare their measured bulk densities with those resulting from evolutionary calculations at the end of 4.6 Gyr. Our model assumes an initial homogeneous composition of mixed ice and rock, and follows the multiphase flow of water through the porous rocky medium, consequent differentiation and aqueous chemical alterations in the rock. Heating sources include long-lived radionuclides, serpentinization reactions, release of gravitational potential energy due to compaction, and crystallization of amorphous ice. The density profile is calculated by assuming hydrostatic equilibrium to be maintained through changes in composition, pressure and temperature. To this purpose, we construct an equation of state suitable for porous icy bodies with radii of a few hundred km, based on the best available empirical studies of ice and rock compaction, and on comparisons with rock porosities in Earth analog and Solar System silicates. We show that the observed bulk densities can be reproduced by assuming the same set of initial and physical parameters, including the same rock/ice mass ratio for all three bodies. We conclude that the mass of the object uniquely determines the evolution of porosity, and thus explains the observed differences in bulk density. The final structure of all three objects is differentiated, with an inner rocky core, and outer ice-enriched mantle. The degree of differentiation, too, is determined by the object's mass.

The role of selection and historical factors in driving population differentiation along an elevational gradient in an island bird.

PubMed

Bertrand, J A M; Delahaie, B; Bourgeois, Y X C; Duval, T; García-Jiménez, R; Cornuault, J; Pujol, B; Thébaud, C; Milá, B

2016-04-01

Adaptation to local environmental conditions and the range dynamics of populations can influence evolutionary divergence along environmental gradients. Thus, it is important to investigate patterns of both phenotypic and genetic variations among populations to reveal the respective roles of these two types of factors in driving population differentiation. Here, we test for evidence of phenotypic and genetic structure across populations of a passerine bird (Zosterops borbonicus) distributed along a steep elevational gradient on the island of Réunion. Using 11 microsatellite loci screened in 401 individuals from 18 localities distributed along the gradient, we found that genetic differentiation occurred at two spatial levels: (i) between two main population groups corresponding to highland and lowland areas, respectively, and (ii) within each of these two groups. In contrast, several morphological traits varied gradually along the gradient. Comparison of neutral genetic differentiation (FST ) and phenotypic differentiation (PST ) showed that PST largely exceeds FST at several morphological traits, which is consistent with a role for local adaptation in driving morphological divergence along the gradient. Overall, our results revealed an area of secondary contact midway up the gradient between two major, cryptic, population groups likely diverged in allopatry. Remarkably, local adaptation has shaped phenotypic differentiation irrespective of population history, resulting in different patterns of variation along the elevational gradient. Our findings underscore the importance of understanding both historical and selective factors when trying to explain variation along environmental gradients. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Balancing Exploration, Uncertainty Representation and Computational Time in Many-Objective Reservoir Policy Optimization

NASA Astrophysics Data System (ADS)

Zatarain-Salazar, J.; Reed, P. M.; Quinn, J.; Giuliani, M.; Castelletti, A.

2016-12-01

As we confront the challenges of managing river basin systems with a large number of reservoirs and increasingly uncertain tradeoffs impacting their operations (due to, e.g. climate change, changing energy markets, population pressures, ecosystem services, etc.), evolutionary many-objective direct policy search (EMODPS) solution strategies will need to address the computational demands associated with simulating more uncertainties and therefore optimizing over increasingly noisy objective evaluations. Diagnostic assessments of state-of-the-art many-objective evolutionary algorithms (MOEAs) to support EMODPS have highlighted that search time (or number of function evaluations) and auto-adaptive search are key features for successful optimization. Furthermore, auto-adaptive MOEA search operators are themselves sensitive to having a sufficient number of function evaluations to learn successful strategies for exploring complex spaces and for escaping from local optima when stagnation is detected. Fortunately, recent parallel developments allow coordinated runs that enhance auto-adaptive algorithmic learning and can handle scalable and reliable search with limited wall-clock time, but at the expense of the total number of function evaluations. In this study, we analyze this tradeoff between parallel coordination and depth of search using different parallelization schemes of the Multi-Master Borg on a many-objective stochastic control problem. We also consider the tradeoff between better representing uncertainty in the stochastic optimization, and simplifying this representation to shorten the function evaluation time and allow for greater search. Our analysis focuses on the Lower Susquehanna River Basin (LSRB) system where multiple competing objectives for hydropower production, urban water supply, recreation and environmental flows need to be balanced. Our results provide guidance for balancing exploration, uncertainty, and computational demands when using the EMODPS framework to discover key tradeoffs within the LSRB system.

An Evolutionary Framework for Understanding the Origin of Eukaryotes

PubMed Central

Blackstone, Neil W.

2016-01-01

Two major obstacles hinder the application of evolutionary theory to the origin of eukaryotes. The first is more apparent than real—the endosymbiosis that led to the mitochondrion is often described as “non-Darwinian” because it deviates from the incremental evolution championed by the modern synthesis. Nevertheless, endosymbiosis can be accommodated by a multi-level generalization of evolutionary theory, which Darwin himself pioneered. The second obstacle is more serious—all of the major features of eukaryotes were likely present in the last eukaryotic common ancestor thus rendering comparative methods ineffective. In addition to a multi-level theory, the development of rigorous, sequence-based phylogenetic and comparative methods represents the greatest achievement of modern evolutionary theory. Nevertheless, the rapid evolution of major features in the eukaryotic stem group requires the consideration of an alternative framework. Such a framework, based on the contingent nature of these evolutionary events, is developed and illustrated with three examples: the putative intron proliferation leading to the nucleus and the cell cycle; conflict and cooperation in the origin of eukaryotic bioenergetics; and the inter-relationship between aerobic metabolism, sterol synthesis, membranes, and sex. The modern synthesis thus provides sufficient scope to develop an evolutionary framework to understand the origin of eukaryotes. PMID:27128953

The virtue of innovation: innovation through the lenses of biological evolution.

PubMed

Kell, Douglas B; Lurie-Luke, Elena

2015-02-06

We rehearse the processes of innovation and discovery in general terms, using as our main metaphor the biological concept of an evolutionary fitness landscape. Incremental and disruptive innovations are seen, respectively, as successful searches carried out locally or more widely. They may also be understood as reflecting evolution by mutation (incremental) versus recombination (disruptive). We also bring a platonic view, focusing on virtue and memory. We use 'virtue' as a measure of efforts, including the knowledge required to come up with disruptive and incremental innovations, and 'memory' as a measure of their lifespan, i.e. how long they are remembered. Fostering innovation, in the evolutionary metaphor, means providing the wherewithal to promote novelty, good objective functions that one is trying to optimize, and means to improve one's knowledge of, and ability to navigate, the landscape one is searching. Recombination necessarily implies multi- or inter-disciplinarity. These principles are generic to all kinds of creativity, novel ideas formation and the development of new products and technologies.

Solving multi-objective water management problems using evolutionary computation.

PubMed

Lewis, A; Randall, M

2017-12-15

Water as a resource is becoming increasingly more valuable given the changes in global climate. In an agricultural sense, the role of water is vital to ensuring food security. Therefore the management of it has become a subject of increasing attention and the development of effective tools to support participative decision-making in water management will be a valuable contribution. In this paper, evolutionary computation techniques and Pareto optimisation are incorporated in a model-based system for water management. An illustrative test case modelling optimal crop selection across dry, average and wet years based on data from the Murrumbidgee Irrigation Area in Australia is presented. It is shown that sets of trade-off solutions that provide large net revenues, or minimise environmental flow deficits can be produced rapidly, easily and automatically. The system is capable of providing detailed information on optimal solutions to achieve desired outcomes, responding to a variety of factors including climate conditions and economics. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

The virtue of innovation: innovation through the lenses of biological evolution

PubMed Central

Kell, Douglas B.; Lurie-Luke, Elena

2015-01-01

We rehearse the processes of innovation and discovery in general terms, using as our main metaphor the biological concept of an evolutionary fitness landscape. Incremental and disruptive innovations are seen, respectively, as successful searches carried out locally or more widely. They may also be understood as reflecting evolution by mutation (incremental) versus recombination (disruptive). We also bring a platonic view, focusing on virtue and memory. We use ‘virtue’ as a measure of efforts, including the knowledge required to come up with disruptive and incremental innovations, and ‘memory’ as a measure of their lifespan, i.e. how long they are remembered. Fostering innovation, in the evolutionary metaphor, means providing the wherewithal to promote novelty, good objective functions that one is trying to optimize, and means to improve one's knowledge of, and ability to navigate, the landscape one is searching. Recombination necessarily implies multi- or inter-disciplinarity. These principles are generic to all kinds of creativity, novel ideas formation and the development of new products and technologies. PMID:25505138

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.

Time: The Biggest Pattern in Natural History Research

NASA Astrophysics Data System (ADS)

Gontier, Nathalie

2016-10-01

We distinguish between four cosmological transitions in the history of Western intellectual thought, and focus on how these cosmologies differentially define matter, space and time. We demonstrate that how time is conceptualized significantly impacts a cosmology's notion on causality, and hone in on how time is conceptualized differentially in modern physics and evolutionary biology. The former conflates time with space into a single space-time continuum and focuses instead on the movement of matter, while the evolutionary sciences have a tradition to understand time as a given when they cartography how organisms change across generations over or in time, thereby proving the phenomenon of evolution. The gap becomes more fundamental when we take into account that phenomena studied by chrono-biologists demonstrate that numerous organisms, including humans, have evolved a "sense" of time. And micro-evolutionary/genetic, meso-evolutionary/developmental and macro-evolutionary phenomena including speciation and extinction not only occur by different evolutionary modes and at different rates, they are also timely phenomena that follow different periodicities. This article focusses on delineating the problem by finding its historical roots. We conclude that though time might be an obsolete concept for the physical sciences, it is crucial for the evolutionary sciences where evolution is defined as the change that biological individuals undergo in/over or through time.

Multi-iPPseEvo: A Multi-label Classifier for Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into Chou's General PseAAC via Grey System Theory.

PubMed

Qiu, Wang-Ren; Zheng, Quan-Shu; Sun, Bi-Qian; Xiao, Xuan

2017-03-01

Predicting phosphorylation protein is a challenging problem, particularly when query proteins have multi-label features meaning that they may be phosphorylated at two or more different type amino acids. In fact, human protein usually be phosphorylated at serine, threonine and tyrosine. By introducing the "multi-label learning" approach, a novel predictor has been developed that can be used to deal with the systems containing both single- and multi-label phosphorylation protein. Here we proposed a predictor called Multi-iPPseEvo by (1) incorporating the protein sequence evolutionary information into the general pseudo amino acid composition (PseAAC) via the grey system theory, (2) balancing out the skewed training datasets by the asymmetric bootstrap approach, and (3) constructing an ensemble predictor by fusing an array of individual random forest classifiers thru a voting system. Rigorous cross-validations via a set of multi-label metrics indicate that the multi-label phosphorylation predictor is very promising and encouraging. The current approach represents a new strategy to deal with the multi-label biological problems, and the software is freely available for academic use at http://www.jci-bioinfo.cn/Multi-iPPseEvo. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Prior knowledge guided active modules identification: an integrated multi-objective approach.

PubMed

Chen, Weiqi; Liu, Jing; He, Shan

2017-03-14

Active module, defined as an area in biological network that shows striking changes in molecular activity or phenotypic signatures, is important to reveal dynamic and process-specific information that is correlated with cellular or disease states. A prior information guided active module identification approach is proposed to detect modules that are both active and enriched by prior knowledge. We formulate the active module identification problem as a multi-objective optimisation problem, which consists two conflicting objective functions of maximising the coverage of known biological pathways and the activity of the active module simultaneously. Network is constructed from protein-protein interaction database. A beta-uniform-mixture model is used to estimate the distribution of p-values and generate scores for activity measurement from microarray data. A multi-objective evolutionary algorithm is used to search for Pareto optimal solutions. We also incorporate a novel constraints based on algebraic connectivity to ensure the connectedness of the identified active modules. Application of proposed algorithm on a small yeast molecular network shows that it can identify modules with high activities and with more cross-talk nodes between related functional groups. The Pareto solutions generated by the algorithm provides solutions with different trade-off between prior knowledge and novel information from data. The approach is then applied on microarray data from diclofenac-treated yeast cells to build network and identify modules to elucidate the molecular mechanisms of diclofenac toxicity and resistance. Gene ontology analysis is applied to the identified modules for biological interpretation. Integrating knowledge of functional groups into the identification of active module is an effective method and provides a flexible control of balance between pure data-driven method and prior information guidance.

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.

Low-metallicity (sub-SMC) massive stars

NASA Astrophysics Data System (ADS)

Garcia, Miriam; Herrero, Artemio; Najarro, Francisco; Camacho, Inés; Lennon, Daniel J.; Urbaneja, Miguel A.; Castro, Norberto

2017-11-01

The double distance and metallicity frontier marked by the SMC has been finally broken with the aid of powerful multi-object spectrographs installed at 8-10m class telescopes. VLT, GTC and Keck have enabled studies of massive stars in dwarf irregular galaxies of the Local Group with poorer metal-content than the SMC. The community is working to test the predictions of evolutionary models in the low-metallicity regime, set the new standard for the metal-poor high-redshift Universe, and test the extrapolation of the physics of massive stars to environments of decreasing metallicity. In this paper, we review current knowledge on this topic.

Multi-objective analysis of the conjunctive use of surface water and groundwater in a multisource water supply system

NASA Astrophysics Data System (ADS)

Vieira, João; da Conceição Cunha, Maria

2017-04-01

A multi-objective decision model has been developed to identify the Pareto-optimal set of management alternatives for the conjunctive use of surface water and groundwater of a multisource urban water supply system. A multi-objective evolutionary algorithm, Borg MOEA, is used to solve the multi-objective decision model. The multiple solutions can be shown to stakeholders allowing them to choose their own solutions depending on their preferences. The multisource urban water supply system studied here is dependent on surface water and groundwater and located in the Algarve region, southernmost province of Portugal, with a typical warm Mediterranean climate. The rainfall is low, intermittent and concentrated in a short winter, followed by a long and dry period. A base population of 450 000 inhabitants and visits by more than 13 million tourists per year, mostly in summertime, turns water management critical and challenging. Previous studies on single objective optimization after aggregating multiple objectives together have already concluded that only an integrated and interannual water resources management perspective can be efficient for water resource allocation in this drought prone region. A simulation model of the multisource urban water supply system using mathematical functions to represent the water balance in the surface reservoirs, the groundwater flow in the aquifers, and the water transport in the distribution network with explicit representation of water quality is coupled with Borg MOEA. The multi-objective problem formulation includes five objectives. Two objective evaluate separately the water quantity and the water quality supplied for the urban use in a finite time horizon, one objective calculates the operating costs, and two objectives appraise the state of the two water sources - the storage in the surface reservoir and the piezometric levels in aquifer - at the end of the time horizon. The decision variables are the volume of withdrawals from each water source in each time step (i.e., reservoir diversion and groundwater pumping). The results provide valuable information for analysing the impacts of the conjunctive use of surface water and groundwater. For example, considering a drought scenario, the results show how the same level of total water supplied can be achieved by different management alternatives with different impact on the water quality, costs, and the state of the water sources at the end of the time horizon. The results allow also the clear understanding of the potential benefits from the conjunctive use of surface water and groundwater thorough the mitigation of the variation in the availability of surface water, improving the water quantity and/or water quality delivered to the users, or the better adaptation of such systems to a changing world.

LS³: A Method for Improving Phylogenomic Inferences When Evolutionary Rates Are Heterogeneous among Taxa.

PubMed

Rivera-Rivera, Carlos J; Montoya-Burgos, Juan I

2016-06-01

Phylogenetic inference artifacts can occur when sequence evolution deviates from assumptions made by the models used to analyze them. The combination of strong model assumption violations and highly heterogeneous lineage evolutionary rates can become problematic in phylogenetic inference, and lead to the well-described long-branch attraction (LBA) artifact. Here, we define an objective criterion for assessing lineage evolutionary rate heterogeneity among predefined lineages: the result of a likelihood ratio test between a model in which the lineages evolve at the same rate (homogeneous model) and a model in which different lineage rates are allowed (heterogeneous model). We implement this criterion in the algorithm Locus Specific Sequence Subsampling (LS³), aimed at reducing the effects of LBA in multi-gene datasets. For each gene, LS³ sequentially removes the fastest-evolving taxon of the ingroup and tests for lineage rate homogeneity until all lineages have uniform evolutionary rates. The sequences excluded from the homogeneously evolving taxon subset are flagged as potentially problematic. The software implementation provides the user with the possibility to remove the flagged sequences for generating a new concatenated alignment. We tested LS³ with simulations and two real datasets containing LBA artifacts: a nucleotide dataset regarding the position of Glires within mammals and an amino-acid dataset concerning the position of nematodes within bilaterians. The initially incorrect phylogenies were corrected in all cases upon removing data flagged by LS³. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Universal approximators for multi-objective direct policy search in water reservoir management problems: a comparative analysis

NASA Astrophysics Data System (ADS)

Giuliani, Matteo; Mason, Emanuele; Castelletti, Andrea; Pianosi, Francesca

2014-05-01

The optimal operation of water resources systems is a wide and challenging problem due to non-linearities in the model and the objectives, high dimensional state-control space, and strong uncertainties in the hydroclimatic regimes. The application of classical optimization techniques (e.g., SDP, Q-learning, gradient descent-based algorithms) is strongly limited by the dimensionality of the system and by the presence of multiple, conflicting objectives. This study presents a novel approach which combines Direct Policy Search (DPS) and Multi-Objective Evolutionary Algorithms (MOEAs) to solve high-dimensional state and control space problems involving multiple objectives. DPS, also known as parameterization-simulation-optimization in the water resources literature, is a simulation-based approach where the reservoir operating policy is first parameterized within a given family of functions and, then, the parameters optimized with respect to the objectives of the management problem. The selection of a suitable class of functions to which the operating policy belong to is a key step, as it might restrict the search for the optimal policy to a subspace of the decision space that does not include the optimal solution. In the water reservoir literature, a number of classes have been proposed. However, many of these rules are based largely on empirical or experimental successes and they were designed mostly via simulation and for single-purpose reservoirs. In a multi-objective context similar rules can not easily inferred from the experience and the use of universal function approximators is generally preferred. In this work, we comparatively analyze two among the most common universal approximators: artificial neural networks (ANN) and radial basis functions (RBF) under different problem settings to estimate their scalability and flexibility in dealing with more and more complex problems. The multi-purpose HoaBinh water reservoir in Vietnam, accounting for hydropower production and flood control, is used as a case study. Preliminary results show that the RBF policy parametrization is more effective than the ANN one. In particular, the approximated Pareto front obtained with RBF control policies successfully explores the full tradeoff space between the two conflicting objectives, while most of the ANN solutions results to be Pareto-dominated by the RBF ones.

Advancing X-ray scattering metrology using inverse genetic algorithms.

PubMed

Hannon, Adam F; Sunday, Daniel F; Windover, Donald; Kline, R Joseph

2016-01-01

We compare the speed and effectiveness of two genetic optimization algorithms to the results of statistical sampling via a Markov chain Monte Carlo algorithm to find which is the most robust method for determining real space structure in periodic gratings measured using critical dimension small angle X-ray scattering. Both a covariance matrix adaptation evolutionary strategy and differential evolution algorithm are implemented and compared using various objective functions. The algorithms and objective functions are used to minimize differences between diffraction simulations and measured diffraction data. These simulations are parameterized with an electron density model known to roughly correspond to the real space structure of our nanogratings. The study shows that for X-ray scattering data, the covariance matrix adaptation coupled with a mean-absolute error log objective function is the most efficient combination of algorithm and goodness of fit criterion for finding structures with little foreknowledge about the underlying fine scale structure features of the nanograting.

Multiple sequence alignment using multi-objective based bacterial foraging optimization algorithm.

PubMed

Rani, R Ranjani; Ramyachitra, D

2016-12-01

Multiple sequence alignment (MSA) is a widespread approach in computational biology and bioinformatics. MSA deals with how the sequences of nucleotides and amino acids are sequenced with possible alignment and minimum number of gaps between them, which directs to the functional, evolutionary and structural relationships among the sequences. Still the computation of MSA is a challenging task to provide an efficient accuracy and statistically significant results of alignments. In this work, the Bacterial Foraging Optimization Algorithm was employed to align the biological sequences which resulted in a non-dominated optimal solution. It employs Multi-objective, such as: Maximization of Similarity, Non-gap percentage, Conserved blocks and Minimization of gap penalty. BAliBASE 3.0 benchmark database was utilized to examine the proposed algorithm against other methods In this paper, two algorithms have been proposed: Hybrid Genetic Algorithm with Artificial Bee Colony (GA-ABC) and Bacterial Foraging Optimization Algorithm. It was found that Hybrid Genetic Algorithm with Artificial Bee Colony performed better than the existing optimization algorithms. But still the conserved blocks were not obtained using GA-ABC. Then BFO was used for the alignment and the conserved blocks were obtained. The proposed Multi-Objective Bacterial Foraging Optimization Algorithm (MO-BFO) was compared with widely used MSA methods Clustal Omega, Kalign, MUSCLE, MAFFT, Genetic Algorithm (GA), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Hybrid Genetic Algorithm with Artificial Bee Colony (GA-ABC). The final results show that the proposed MO-BFO algorithm yields better alignment than most widely used methods. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Dual deep modeling: multi-level modeling with dual potencies and its formalization in F-Logic.

PubMed

Neumayr, Bernd; Schuetz, Christoph G; Jeusfeld, Manfred A; Schrefl, Michael

2018-01-01

An enterprise database contains a global, integrated, and consistent representation of a company's data. Multi-level modeling facilitates the definition and maintenance of such an integrated conceptual data model in a dynamic environment of changing data requirements of diverse applications. Multi-level models transcend the traditional separation of class and object with clabjects as the central modeling primitive, which allows for a more flexible and natural representation of many real-world use cases. In deep instantiation, the number of instantiation levels of a clabject or property is indicated by a single potency. Dual deep modeling (DDM) differentiates between source potency and target potency of a property or association and supports the flexible instantiation and refinement of the property by statements connecting clabjects at different modeling levels. DDM comes with multiple generalization of clabjects, subsetting/specialization of properties, and multi-level cardinality constraints. Examples are presented using a UML-style notation for DDM together with UML class and object diagrams for the representation of two-level user views derived from the multi-level model. Syntax and semantics of DDM are formalized and implemented in F-Logic, supporting the modeler with integrity checks and rich query facilities.

Optimum oil production planning using infeasibility driven evolutionary algorithm.

PubMed

Singh, Hemant Kumar; Ray, Tapabrata; Sarker, Ruhul

2013-01-01

In this paper, we discuss a practical oil production planning optimization problem. For oil wells with insufficient reservoir pressure, gas is usually injected to artificially lift oil, a practice commonly referred to as enhanced oil recovery (EOR). The total gas that can be used for oil extraction is constrained by daily availability limits. The oil extracted from each well is known to be a nonlinear function of the gas injected into the well and varies between wells. The problem is to identify the optimal amount of gas that needs to be injected into each well to maximize the amount of oil extracted subject to the constraint on the total daily gas availability. The problem has long been of practical interest to all major oil exploration companies as it has the potential to derive large financial benefit. In this paper, an infeasibility driven evolutionary algorithm is used to solve a 56 well reservoir problem which demonstrates its efficiency in solving constrained optimization problems. Furthermore, a multi-objective formulation of the problem is posed and solved using a number of algorithms, which eliminates the need for solving the (single objective) problem on a regular basis. Lastly, a modified single objective formulation of the problem is also proposed, which aims to maximize the profit instead of the quantity of oil. It is shown that even with a lesser amount of oil extracted, more economic benefits can be achieved through the modified formulation.

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.

Differences in bacterial diversity of host-associated populations of Phylloxera notabilis Pergande (Hemiptera: Phylloxeridae) in pecan and water hickory.

PubMed

Medina, R F; Nachappa, P; Tamborindeguy, C

2011-04-01

Host-associated differentiation (HAD) is the presence of genetically divergent, host-associated populations. It has been suggested that microbial symbionts of insect herbivores may play a role in HAD by allowing their insect hosts to use different plant species. The objective of this study was to document if host-associated populations of Phylloxera notabilis Pergande (Hemiptera: Phylloxeridae) in pecan and water hickory corresponded with differences in the composition of their associated bacteria. To test this hypothesis, we characterized the symbionts present in P. notabilis associated with these two tree species through metagenomic analyses using 454 sequencing. Differences in bacterial diversity were found between P. notabilis populations associated with pecan and water hickory. The bacteria, Pantoea agglomerans and Serratia marcescens, were absent in the P. notabilis water hickory population, whereas both species accounted for more than 69.72% of bacterial abundance in the pecan population. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

Evolutionary Fuzzy Block-Matching-Based Camera Raw Image Denoising.

PubMed

Yang, Chin-Chang; Guo, Shu-Mei; Tsai, Jason Sheng-Hong

2017-09-01

An evolutionary fuzzy block-matching-based image denoising algorithm is proposed to remove noise from a camera raw image. Recently, a variance stabilization transform is widely used to stabilize the noise variance, so that a Gaussian denoising algorithm can be used to remove the signal-dependent noise in camera sensors. However, in the stabilized domain, the existed denoising algorithm may blur too much detail. To provide a better estimate of the noise-free signal, a new block-matching approach is proposed to find similar blocks by the use of a type-2 fuzzy logic system (FLS). Then, these similar blocks are averaged with the weightings which are determined by the FLS. Finally, an efficient differential evolution is used to further improve the performance of the proposed denoising algorithm. The experimental results show that the proposed denoising algorithm effectively improves the performance of image denoising. Furthermore, the average performance of the proposed method is better than those of two state-of-the-art image denoising algorithms in subjective and objective measures.

Biological hierarchies and the nature of extinction.

PubMed

Congreve, Curtis R; Falk, Amanda R; Lamsdell, James C

2018-05-01

Hierarchy theory recognises that ecological and evolutionary units occur in a nested and interconnected hierarchical system, with cascading effects occurring between hierarchical levels. Different biological disciplines have routinely come into conflict over the primacy of different forcing mechanisms behind evolutionary and ecological change. These disconnects arise partly from differences in perspective (with some researchers favouring ecological forcing mechanisms while others favour developmental/historical mechanisms), as well as differences in the temporal framework in which workers operate. In particular, long-term palaeontological data often show that large-scale (macro) patterns of evolution are predominantly dictated by shifts in the abiotic environment, while short-term (micro) modern biological studies stress the importance of biotic interactions. We propose that thinking about ecological and evolutionary interactions in a hierarchical framework is a fruitful way to resolve these conflicts. Hierarchy theory suggests that changes occurring at lower hierarchical levels can have unexpected, complex effects at higher scales due to emergent interactions between simple systems. In this way, patterns occurring on short- and long-term time scales are equally valid, as changes that are driven from lower levels will manifest in different forms at higher levels. We propose that the dual hierarchy framework fits well with our current understanding of evolutionary and ecological theory. Furthermore, we describe how this framework can be used to understand major extinction events better. Multi-generational attritional loss of reproductive fitness (MALF) has recently been proposed as the primary mechanism behind extinction events, whereby extinction is explainable solely through processes that result in extirpation of populations through a shutdown of reproduction. While not necessarily explicit, the push to explain extinction through solely population-level dynamics could be used to suggest that environmentally mediated patterns of extinction or slowed speciation across geological time are largely artefacts of poor preservation or a coarse temporal scale. We demonstrate how MALF fits into a hierarchical framework, showing that MALF can be a primary forcing mechanism at lower scales that still results in differential survivorship patterns at the species and clade level which vary depending upon the initial environmental forcing mechanism. Thus, even if MALF is the primary mechanism of extinction across all mass extinction events, the primary environmental cause of these events will still affect the system and result in differential responses. Therefore, patterns at both temporal scales are relevant. © 2017 Cambridge Philosophical Society.

Gender imbalance in infant mortality: a cross-national study of social structure and female infanticide.

PubMed

Fuse, Kana; Crenshaw, Edward M

2006-01-01

Sex differentials in infant mortality vary widely across nations. Because newborn girls are biologically advantaged in surviving to their first birthday, sex differentials in infant mortality typically arise from genetic factors that result in higher male infant mortality rates. Nonetheless, there are cases where mortality differentials arise from social or behavioral factors reflecting deliberate discrimination by adults in favor of boys over girls, resulting in atypical male to female infant mortality ratios. This cross-national study of 93 developed and developing countries uses such macro-social theories as modernization theory, gender perspectives, human ecology, and sociobiology/evolutionary psychology to predict gender differentials in infant mortality. We find strong evidence for modernization theory, human ecology, and the evolutionary psychology of group process, but mixed evidence for gender perspectives.

A hybrid credibility-based fuzzy multiple objective optimisation to differential pricing and inventory policies with arbitrage consideration

NASA Astrophysics Data System (ADS)

Ghasemy Yaghin, R.; Fatemi Ghomi, S. M. T.; Torabi, S. A.

2015-10-01

In most markets, price differentiation mechanisms enable manufacturers to offer different prices for their products or services in different customer segments; however, the perfect price discrimination is usually impossible for manufacturers. The importance of accounting for uncertainty in such environments spurs an interest to develop appropriate decision-making tools to deal with uncertain and ill-defined parameters in joint pricing and lot-sizing problems. This paper proposes a hybrid bi-objective credibility-based fuzzy optimisation model including both quantitative and qualitative objectives to cope with these issues. Taking marketing and lot-sizing decisions into account simultaneously, the model aims to maximise the total profit of manufacturer and to improve service aspects of retailing simultaneously to set different prices with arbitrage consideration. After applying appropriate strategies to defuzzify the original model, the resulting non-linear multi-objective crisp model is then solved by a fuzzy goal programming method. An efficient stochastic search procedure using particle swarm optimisation is also proposed to solve the non-linear crisp model.

Transcriptome analysis in Coffea eugenioides, an Arabica coffee ancestor, reveals differentially expressed genes in leaves and fruits.

PubMed

Yuyama, Priscila Mary; Reis Júnior, Osvaldo; Ivamoto, Suzana Tiemi; Domingues, Douglas Silva; Carazzolle, Marcelo Falsarella; Pereira, Gonçalo Amarante Guimarães; Charmetant, Pierre; Leroy, Thierry; Pereira, Luiz Filipe Protasio

2016-02-01

Studies in diploid parental species of polyploid plants are important to understand their contributions to the formation of plant and species evolution. Coffea eugenioides is a diploid species that is considered to be an ancestor of allopolyploid Coffea arabica together with Coffea canephora. Despite its importance in the evolutionary history of the main economic species of coffee, no study has focused on C. eugenioides molecular genetics. RNA-seq creates the possibility to generate reference transcriptomes and identify coding genes and potential candidates related to important agronomic traits. Therefore, the main objectives were to obtain a global overview of transcriptionally active genes in this species using next-generation sequencing and to analyze specific genes that were highly expressed in leaves and fruits with potential exploratory characteristics for breeding and understanding the evolutionary biology of coffee. A de novo assembly generated 36,935 contigs that were annotated using eight databases. We observed a total of ~5000 differentially expressed genes between leaves and fruits. Several genes exclusively expressed in fruits did not exhibit similarities with sequences in any database. We selected ten differentially expressed unigenes in leaves and fruits to evaluate transcriptional profiles using qPCR. Our study provides the first gene catalog for C. eugenioides and enhances the knowledge concerning the mechanisms involved in the C. arabica homeologous. Furthermore, this work will open new avenues for studies into specific genes and pathways in this species, especially related to fruit, and our data have potential value in assisted breeding applications.

Early differential sensitivity of evoked-potentials to local and global shape during the perception of three-dimensional objects.

PubMed

Leek, E Charles; Roberts, Mark; Oliver, Zoe J; Cristino, Filipe; Pegna, Alan J

2016-08-01

Here we investigated the time course underlying differential processing of local and global shape information during the perception of complex three-dimensional (3D) objects. Observers made shape matching judgments about pairs of sequentially presented multi-part novel objects. Event-related potentials (ERPs) were used to measure perceptual sensitivity to 3D shape differences in terms of local part structure and global shape configuration - based on predictions derived from hierarchical structural description models of object recognition. There were three types of different object trials in which stimulus pairs (1) shared local parts but differed in global shape configuration; (2) contained different local parts but shared global configuration or (3) shared neither local parts nor global configuration. Analyses of the ERP data showed differential amplitude modulation as a function of shape similarity as early as the N1 component between 146-215ms post-stimulus onset. These negative amplitude deflections were more similar between objects sharing global shape configuration than local part structure. Differentiation among all stimulus types was reflected in N2 amplitude modulations between 276-330ms. sLORETA inverse solutions showed stronger involvement of left occipitotemporal areas during the N1 for object discrimination weighted towards local part structure. The results suggest that the perception of 3D object shape involves parallel processing of information at local and global scales. This processing is characterised by relatively slow derivation of 'fine-grained' local shape structure, and fast derivation of 'coarse-grained' global shape configuration. We propose that the rapid early derivation of global shape attributes underlies the observed patterns of N1 amplitude modulations. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Evolutionary Psychology and Intelligence Research

ERIC Educational Resources Information Center

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…

The dynamic evolutionary history of the bananaquit (Coereba flaveola) in the Caribbean revealed by a multigene analysis

PubMed Central

2008-01-01

Background The bananaquit (Coereba flaveola) is a small nectivorous and frugivorous emberizine bird (order Passeriformes) that is an abundant resident throughout the Caribbean region. We used multi-gene analyses to investigate the evolutionary history of this species throughout its distribution in the West Indies and in South and Middle America. We sequenced six mitochondrial genes (3744 base pairs) and three nuclear genes (2049 base pairs) for forty-four bananaquits and three outgroup species. We infer the ancestral area of the present-day bananaquit populations, report on the species' phylogenetic, biogeographic and evolutionary history, and propose scenarios for its diversification and range expansion. Results Phylogenetic concordance between mitochondrial and nuclear genes at the base of the bananaquit phylogeny supported a West Indian origin for continental populations. Multi-gene analysis showing genetic remnants of successive colonization events in the Lesser Antilles reinforced earlier research demonstrating that bananaquits alternate periods of invasiveness and colonization with biogeographic quiescence. Although nuclear genes provided insufficient information at the tips of the tree to further evaluate relationships of closely allied but strongly supported mitochondrial DNA clades, the discrepancy between mitochondrial and nuclear data in the population of Dominican Republic suggested that the mitochondrial genome was recently acquired by introgression from Jamaica. Conclusion This study represents one of the most complete phylogeographic analyses of its kind and reveals three patterns that are not commonly appreciated in birds: (1) island to mainland colonization, (2) multiple expansion phases, and (3) mitochondrial genome replacement. The detail revealed by this analysis will guide evolutionary analyses of populations in archipelagos such as the West Indies, which include islands varying in size, age, and geological history. Our results suggest that multi-gene phylogenies will permit improved comparative analysis of the evolutionary histories of different lineages in the same geographical setting, which provide replicated "natural experiments" for testing evolutionary hypotheses. PMID:18718030

Regulatory and evolutionary signatures of sex-biased genes on both the X chromosome and the autosomes.

PubMed

Shen, Jiangshan J; Wang, Ting-You; Yang, Wanling

2017-11-02

Sex is an important but understudied factor in the genetics of human diseases. Analyses using a combination of gene expression data, ENCODE data, and evolutionary data of sex-biased gene expression in human tissues can give insight into the regulatory and evolutionary forces acting on sex-biased genes. In this study, we analyzed the differentially expressed genes between males and females. On the X chromosome, we used a novel method and investigated the status of genes that escape X-chromosome inactivation (escape genes), taking into account the clonality of lymphoblastoid cell lines (LCLs). To investigate the regulation of sex-biased differentially expressed genes (sDEG), we conducted pathway and transcription factor enrichment analyses on the sDEGs, as well as analyses on the genomic distribution of sDEGs. Evolutionary analyses were also conducted on both sDEGs and escape genes. Genome-wide, we characterized differential gene expression between sexes in 462 RNA-seq samples and identified 587 sex-biased genes, or 3.2% of the genes surveyed. On the X chromosome, sDEGs were distributed in evolutionary strata in a similar pattern as escape genes. We found a trend of negative correlation between the gene expression breadth and nonsynonymous over synonymous mutation (dN/dS) ratios, showing a possible pleiotropic constraint on evolution of genes. Genome-wide, nine transcription factors were found enriched in binding to the regions surrounding the transcription start sites of female-biased genes. Many pathways and protein domains were enriched in sex-biased genes, some of which hint at sex-biased physiological processes. These findings lend insight into the regulatory and evolutionary forces shaping sex-biased gene expression and their involvement in the physiological and pathological processes in human health and diseases.

Convergence analysis of evolutionary algorithms that are based on the paradigm of information geometry.

PubMed

Beyer, Hans-Georg

2014-01-01

The convergence behaviors of so-called natural evolution strategies (NES) and of the information-geometric optimization (IGO) approach are considered. After a review of the NES/IGO ideas, which are based on information geometry, the implications of this philosophy w.r.t. optimization dynamics are investigated considering the optimization performance on the class of positive quadratic objective functions (the ellipsoid model). Exact differential equations describing the approach to the optimizer are derived and solved. It is rigorously shown that the original NES philosophy optimizing the expected value of the objective functions leads to very slow (i.e., sublinear) convergence toward the optimizer. This is the real reason why state of the art implementations of IGO algorithms optimize the expected value of transformed objective functions, for example, by utility functions based on ranking. It is shown that these utility functions are localized fitness functions that change during the IGO flow. The governing differential equations describing this flow are derived. In the case of convergence, the solutions to these equations exhibit an exponentially fast approach to the optimizer (i.e., linear convergence order). Furthermore, it is proven that the IGO philosophy leads to an adaptation of the covariance matrix that equals in the asymptotic limit-up to a scalar factor-the inverse of the Hessian of the objective function considered.

Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization.

PubMed

Mousavi, Maryam; Yap, Hwa Jen; Musa, Siti Nurmaya; Tahriri, Farzad; Md Dawal, Siti Zawiah

2017-01-01

Flexible manufacturing system (FMS) enhances the firm's flexibility and responsiveness to the ever-changing customer demand by providing a fast product diversification capability. Performance of an FMS is highly dependent upon the accuracy of scheduling policy for the components of the system, such as automated guided vehicles (AGVs). An AGV as a mobile robot provides remarkable industrial capabilities for material and goods transportation within a manufacturing facility or a warehouse. Allocating AGVs to tasks, while considering the cost and time of operations, defines the AGV scheduling process. Multi-objective scheduling of AGVs, unlike single objective practices, is a complex and combinatorial process. In the main draw of the research, a mathematical model was developed and integrated with evolutionary algorithms (genetic algorithm (GA), particle swarm optimization (PSO), and hybrid GA-PSO) to optimize the task scheduling of AGVs with the objectives of minimizing makespan and number of AGVs while considering the AGVs' battery charge. Assessment of the numerical examples' scheduling before and after the optimization proved the applicability of all the three algorithms in decreasing the makespan and AGV numbers. The hybrid GA-PSO produced the optimum result and outperformed the other two algorithms, in which the mean of AGVs operation efficiency was found to be 69.4, 74, and 79.8 percent in PSO, GA, and hybrid GA-PSO, respectively. Evaluation and validation of the model was performed by simulation via Flexsim software.

Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization

PubMed Central

Yap, Hwa Jen; Musa, Siti Nurmaya; Tahriri, Farzad; Md Dawal, Siti Zawiah

2017-01-01

Flexible manufacturing system (FMS) enhances the firm’s flexibility and responsiveness to the ever-changing customer demand by providing a fast product diversification capability. Performance of an FMS is highly dependent upon the accuracy of scheduling policy for the components of the system, such as automated guided vehicles (AGVs). An AGV as a mobile robot provides remarkable industrial capabilities for material and goods transportation within a manufacturing facility or a warehouse. Allocating AGVs to tasks, while considering the cost and time of operations, defines the AGV scheduling process. Multi-objective scheduling of AGVs, unlike single objective practices, is a complex and combinatorial process. In the main draw of the research, a mathematical model was developed and integrated with evolutionary algorithms (genetic algorithm (GA), particle swarm optimization (PSO), and hybrid GA-PSO) to optimize the task scheduling of AGVs with the objectives of minimizing makespan and number of AGVs while considering the AGVs’ battery charge. Assessment of the numerical examples’ scheduling before and after the optimization proved the applicability of all the three algorithms in decreasing the makespan and AGV numbers. The hybrid GA-PSO produced the optimum result and outperformed the other two algorithms, in which the mean of AGVs operation efficiency was found to be 69.4, 74, and 79.8 percent in PSO, GA, and hybrid GA-PSO, respectively. Evaluation and validation of the model was performed by simulation via Flexsim software. PMID:28263994

Young globular clusters in NGC 1316

NASA Astrophysics Data System (ADS)

Sesto, Leandro A.; Faifer, Favio R.; Smith Castelli, Analía V.; Forte, Juan C.; Escudero, Carlos G.

2018-05-01

We present multi-object spectroscopy of the inner zone of the globular cluster (GC) system associated with the intermediate-age merger remnant NGC 1316. Using the multi-object mode of the GMOS camera, we obtained spectra for 35 GCs. We find pieces of evidence that the innermost GCs of NGC 1316 rotate almost perpendicular to the stellar component of the galaxy. In a second stage, we determined ages, metallicities and α-element abundances for each GC present in the sample, through the measurement of different Lick/IDS indices and their comparison with simple stellar population models. We confirmed the existence of multiple GC populations associated with NGC 1316, where the presence of a dominant subpopulation of very young GCs, with an average age of 2.1 Gyr, metallicities between -0.5 < [Z/H] < 0.5 dex and α-element abundances in the range -0.2 < [α/Fe] < 0.3 dex, stands out. Several objects in our sample present subsolar values of [α/Fe] and a large spread of [Z/H] and ages. Some of these objects could actually be stripped nuclei, possibly accreted during minor merger events. Finally, the results have been analyzed with the aim of describing the different episodes of star formation and thus provide a more complete picture about the evolutionary history of the galaxy. We conclude that these pieces of evidence could indicate that this galaxy has cannibalized one or more gas-rich galaxies, where the last fusion event occurred about 2 Gyr ago.

Multi-Hamiltonian structure of Plebanski's second heavenly equation

NASA Astrophysics Data System (ADS)

Neyzi, F.; Nutku, Y.; Sheftel, M. B.

2005-09-01

We show that Plebanski's second heavenly equation, when written as a first-order nonlinear evolutionary system, admits multi-Hamiltonian structure. Therefore by Magri's theorem it is a completely integrable system. Thus it is an example of a completely integrable system in four dimensions.

Utilization of Expert Knowledge in a Multi-Objective Hydrologic Model Automatic Calibration Process

NASA Astrophysics Data System (ADS)

Quebbeman, J.; Park, G. H.; Carney, S.; Day, G. N.; Micheletty, P. D.

2016-12-01

Spatially distributed continuous simulation hydrologic models have a large number of parameters for potential adjustment during the calibration process. Traditional manual calibration approaches of such a modeling system is extremely laborious, which has historically motivated the use of automatic calibration procedures. With a large selection of model parameters, achieving high degrees of objective space fitness - measured with typical metrics such as Nash-Sutcliffe, Kling-Gupta, RMSE, etc. - can easily be achieved using a range of evolutionary algorithms. A concern with this approach is the high degree of compensatory calibration, with many similarly performing solutions, and yet grossly varying parameter set solutions. To help alleviate this concern, and mimic manual calibration processes, expert knowledge is proposed for inclusion within the multi-objective functions, which evaluates the parameter decision space. As a result, Pareto solutions are identified with high degrees of fitness, but also create parameter sets that maintain and utilize available expert knowledge resulting in more realistic and consistent solutions. This process was tested using the joint SNOW-17 and Sacramento Soil Moisture Accounting method (SAC-SMA) within the Animas River basin in Colorado. Three different elevation zones, each with a range of parameters, resulted in over 35 model parameters simultaneously calibrated. As a result, high degrees of fitness were achieved, in addition to the development of more realistic and consistent parameter sets such as those typically achieved during manual calibration procedures.

How multi-partner endosymbioses function.

PubMed

Douglas, Angela E

2016-12-01

Various animals are associated with specific endosymbiotic microorganisms that provide the host with essential nutrients or confer protection against natural enemies. Genomic analyses of the many endosymbioses that are found in plant sap-feeding hemipteran insects have revealed independent acquisitions - and occasional replacements - of endosymbionts, such that many of these endosymbioses involve two or more microbial partners. In this Review, I discuss how partitioning of the genetic capacity for metabolic function between different endosymbionts has sustained nutritional function in multi-partner endosymbioses, and how the phenotypic traits of these endosymbionts can be shaped by co-evolutionary interactions with both co-occurring microbial taxa and the host, which often operate over long evolutionary timescales.

A Generalized National Planning Approach for Admission Capacity in Higher Education: A Nonlinear Integer Goal Programming Model with a Novel Differential Evolution Algorithm

PubMed Central

El-Qulity, Said Ali; Mohamed, Ali Wagdy

2016-01-01

This paper proposes a nonlinear integer goal programming model (NIGPM) for solving the general problem of admission capacity planning in a country as a whole. The work aims to satisfy most of the required key objectives of a country related to the enrollment problem for higher education. The system general outlines are developed along with the solution methodology for application to the time horizon in a given plan. The up-to-date data for Saudi Arabia is used as a case study and a novel evolutionary algorithm based on modified differential evolution (DE) algorithm is used to solve the complexity of the NIGPM generated for different goal priorities. The experimental results presented in this paper show their effectiveness in solving the admission capacity for higher education in terms of final solution quality and robustness. PMID:26819583

A Generalized National Planning Approach for Admission Capacity in Higher Education: A Nonlinear Integer Goal Programming Model with a Novel Differential Evolution Algorithm.

PubMed

El-Qulity, Said Ali; Mohamed, Ali Wagdy

2016-01-01

This paper proposes a nonlinear integer goal programming model (NIGPM) for solving the general problem of admission capacity planning in a country as a whole. The work aims to satisfy most of the required key objectives of a country related to the enrollment problem for higher education. The system general outlines are developed along with the solution methodology for application to the time horizon in a given plan. The up-to-date data for Saudi Arabia is used as a case study and a novel evolutionary algorithm based on modified differential evolution (DE) algorithm is used to solve the complexity of the NIGPM generated for different goal priorities. The experimental results presented in this paper show their effectiveness in solving the admission capacity for higher education in terms of final solution quality and robustness.

Differential binding of colors to objects in memory: red and yellow stick better than blue and green.

PubMed

Kuhbandner, Christof; Spitzer, Bernhard; Lichtenfeld, Stephanie; Pekrun, Reinhard

2015-01-01

Both evolutionary considerations and recent research suggest that the color red serves as a signal indicating an object's importance. However, until now, there is no evidence that this signaling function of red is also reflected in human memory. To examine the effect of red on memory, we conducted four experiments in which we presented objects colored in four different colors (red, green, blue, and yellow) and measured later memory for the presence of an object and for the color of an object. Across experiments, we varied the type of objects (words vs. pictures), task complexity (single objects vs. multiple objects in visual scenes), and intentionality of encoding (intentional vs. incidental learning). Memory for the presence of an object was not influenced by color. However, in all four experiments, memory for the color of an object depended on color type and was particularly high for red and yellow-colored objects and particularly low for green-colored objects, indicating that the binding of colors into object memory representations varies as a function of color type. Analyzing the observers' confidence in their color memories revealed that color not only influenced objective memory performance but also subjective confidence. Subjective confidence judgments differentiated well between correct and incorrect color memories for red-colored objects, but poorly for green-colored objects. Our findings reveal a previously unknown color effect which may be of considerable interest for both basic color research and applied settings like eyewitness testimony in which memory for color features is relevant. Furthermore, our results indicate that feature binding in memory is not a uniform process by which any attended feature is automatically bound into unitary memory representations. Rather, memory binding seems to vary across different subtypes of features, a finding that supports recent research showing that object features are stored in memory rather independently from each other.

Cosmic Evolution Through UV Spectroscopy (CETUS): A NASA Probe-Class Mission Concept

NASA Astrophysics Data System (ADS)

Heap, Sara R.; CETUS Team

2017-01-01

CETUS is a probe-class mission concept proposed for study to NASA in November 2016. Its overarching objective is to provide access to the ultraviolet (~100-400 nm) after Hubble has died. CETUS will be a major player in the emerging global network of powerful, new telescopes such as E-ROSITA, DESI, Subaru/PFS, GMT, LSST, WFIRST, JWST, and SKA. The CETUS mission concept provisionally features a 1.5-m telescope with a suite of instruments including a near-UV multi-object spectrograph (200-400 nm) complementing Subaru/PFS observations, wide-field far-UV and near-UV cameras, and far-UV and near-UV spectrographs that can be operated in either high-resolution or low-resolution mode. We have derived the scope and specific science requirements for CETUS for understanding the evolutionary history of galaxies, stars, and dust, but other applications are possible.

NOBAI: a web server for character coding of geometrical and statistical features in RNA structure

PubMed Central

Knudsen, Vegeir; Caetano-Anollés, Gustavo

2008-01-01

The Numeration of Objects in Biology: Alignment Inferences (NOBAI) web server provides a web interface to the applications in the NOBAI software package. This software codes topological and thermodynamic information related to the secondary structure of RNA molecules as multi-state phylogenetic characters, builds character matrices directly in NEXUS format and provides sequence randomization options. The web server is an effective tool that facilitates the search for evolutionary history embedded in the structure of functional RNA molecules. The NOBAI web server is accessible at ‘http://www.manet.uiuc.edu/nobai/nobai.php’. This web site is free and open to all users and there is no login requirement. PMID:18448469

Emotional engagements predict and enhance social cognition in young chimpanzees

PubMed Central

Bard, Kim A; Bakeman, Roger; Boysen, Sarah T; Leavens, David A

2014-01-01

Social cognition in infancy is evident in coordinated triadic engagements, that is, infants attending jointly with social partners and objects. Current evolutionary theories of primate social cognition tend to highlight species differences in cognition based on human-unique cooperative motives. We consider a developmental model in which engagement experiences produce differential outcomes. We conducted a 10-year-long study in which two groups of laboratory-raised chimpanzee infants were given quantifiably different engagement experiences. Joint attention, cooperativeness, affect, and different levels of cognition were measured in 5- to 12-month-old chimpanzees, and compared to outcomes derived from a normative human database. We found that joint attention skills significantly improved across development for all infants, but by 12 months, the humans significantly surpassed the chimpanzees. We found that cooperativeness was stable in the humans, but by 12 months, the chimpanzee group given enriched engagement experiences significantly surpassed the humans. Past engagement experiences and concurrent affect were significant unique predictors of both joint attention and cooperativeness in 5- to 12-month-old chimpanzees. When engagement experiences and concurrent affect were statistically controlled, joint attention and cooperation were not associated. We explain differential social cognition outcomes in terms of the significant influences of previous engagement experiences and affect, in addition to cognition. Our study highlights developmental processes that underpin the emergence of social cognition in support of evolutionary continuity. PMID:24410843

Probing multi-scale self-similarity of tissue structures using light scattering spectroscopy: prospects in pre-cancer detection

NASA Astrophysics Data System (ADS)

Chatterjee, Subhasri; Das, Nandan K.; Kumar, Satish; Mohapatra, Sonali; Pradhan, Asima; Panigrahi, Prasanta K.; Ghosh, Nirmalya

2013-02-01

Multi-resolution analysis on the spatial refractive index inhomogeneities in the connective tissue regions of human cervix reveals clear signature of multifractality. We have thus developed an inverse analysis strategy for extraction and quantification of the multifractality of spatial refractive index fluctuations from the recorded light scattering signal. The method is based on Fourier domain pre-processing of light scattering data using Born approximation, and its subsequent analysis through Multifractal Detrended Fluctuation Analysis model. The method has been validated on several mono- and multi-fractal scattering objects whose self-similar properties are user controlled and known a-priori. Following successful validation, this approach has initially been explored for differentiating between different grades of precancerous human cervical tissues.

Multi-Objectives Optimization of Ventilation Controllers for Passive Cooling in Residential Buildings

PubMed Central

Grygierek, Krzysztof; Ferdyn-Grygierek, Joanna

2018-01-01

An inappropriate indoor climate, mostly indoor temperature, may cause occupants’ discomfort. There are a great number of air conditioning systems that make it possible to maintain the required thermal comfort. Their installation, however, involves high investment costs and high energy demand. The study analyses the possibilities of limiting too high a temperature in residential buildings using passive cooling by means of ventilation with ambient cool air. A fuzzy logic controller whose aim is to control mechanical ventilation has been proposed and optimized. In order to optimize the controller, the modified Multiobjective Evolutionary Algorithm, based on the Strength Pareto Evolutionary Algorithm, has been adopted. The optimization algorithm has been implemented in MATLAB®, which is coupled by MLE+ with EnergyPlus for performing dynamic co-simulation between the programs. The example of a single detached building shows that the occupants’ thermal comfort in a transitional climate may improve significantly owing to mechanical ventilation controlled by the suggested fuzzy logic controller. When the system is connected to the traditional cooling system, it may further bring about a decrease in cooling demand. PMID:29642525

Methods to mitigate data truncation artifacts in multi-contrast tomosynthesis image reconstructions

NASA Astrophysics Data System (ADS)

Garrett, John; Ge, Yongshuai; Li, Ke; Chen, Guang-Hong

2015-03-01

Differential phase contrast imaging is a promising new image modality that utilizes the refraction rather than the absorption of x-rays to image an object. A Talbot-Lau interferometer may be used to permit differential phase contrast imaging with a conventional medical x-ray source and detector. However, the current size of the gratings fabricated for these interferometers are often relatively small. As a result, data truncation image artifacts are often observed in a tomographic acquisition and reconstruction. When data are truncated in x-ray absorption imaging, the methods have been introduced to mitigate the truncation artifacts. However, the same strategy to mitigate absorption truncation artifacts may not be appropriate for differential phase contrast or dark field tomographic imaging. In this work, several new methods to mitigate data truncation artifacts in a multi-contrast imaging system have been proposed and evaluated for tomosynthesis data acquisitions. The proposed methods were validated using experimental data acquired for a bovine udder as well as several cadaver breast specimens using a benchtop system at our facility.

An effective and comprehensive model for optimal rehabilitation of separate sanitary sewer systems.

PubMed

Diogo, António Freire; Barros, Luís Tiago; Santos, Joana; Temido, Jorge Santos

2018-01-15

In the field of rehabilitation of separate sanitary sewer systems, a large number of technical, environmental, and economic aspects are often relevant in the decision-making process, which may be modelled as a multi-objective optimization problem. Examples are those related with the operation and assessment of networks, optimization of structural, hydraulic, sanitary, and environmental performance, rehabilitation programmes, and execution works. In particular, the cost of investment, operation and maintenance needed to reduce or eliminate Infiltration from the underground water table and Inflows of storm water surface runoff (I/I) using rehabilitation techniques or related methods can be significantly lower than the cost of transporting and treating these flows throughout the lifespan of the systems or period studied. This paper presents a comprehensive I/I cost-benefit approach for rehabilitation that explicitly considers all elements of the systems and shows how the approximation is incorporated as an objective function in a general evolutionary multi-objective optimization model. It takes into account network performance and wastewater treatment costs, average values of several input variables, and rates that can reflect the adoption of different predictable or limiting scenarios. The approach can be used as a practical and fast tool to support decision-making in sewer network rehabilitation in any phase of a project. The fundamental aspects, modelling, implementation details and preliminary results of a two-objective optimization rehabilitation model using a genetic algorithm, with a second objective function related to the structural condition of the network and the service failure risk, are presented. The basic approach is applied to three real world cases studies of sanitary sewerage systems in Coimbra and the results show the simplicity, suitability, effectiveness, and usefulness of the approximation implemented and of the objective function proposed. Copyright © 2017 Elsevier B.V. All rights reserved.

Differential binding of colors to objects in memory: red and yellow stick better than blue and green

PubMed Central

Kuhbandner, Christof; Spitzer, Bernhard; Lichtenfeld, Stephanie; Pekrun, Reinhard

2015-01-01

Both evolutionary considerations and recent research suggest that the color red serves as a signal indicating an object’s importance. However, until now, there is no evidence that this signaling function of red is also reflected in human memory. To examine the effect of red on memory, we conducted four experiments in which we presented objects colored in four different colors (red, green, blue, and yellow) and measured later memory for the presence of an object and for the color of an object. Across experiments, we varied the type of objects (words vs. pictures), task complexity (single objects vs. multiple objects in visual scenes), and intentionality of encoding (intentional vs. incidental learning). Memory for the presence of an object was not influenced by color. However, in all four experiments, memory for the color of an object depended on color type and was particularly high for red and yellow-colored objects and particularly low for green-colored objects, indicating that the binding of colors into object memory representations varies as a function of color type. Analyzing the observers’ confidence in their color memories revealed that color not only influenced objective memory performance but also subjective confidence. Subjective confidence judgments differentiated well between correct and incorrect color memories for red-colored objects, but poorly for green-colored objects. Our findings reveal a previously unknown color effect which may be of considerable interest for both basic color research and applied settings like eyewitness testimony in which memory for color features is relevant. Furthermore, our results indicate that feature binding in memory is not a uniform process by which any attended feature is automatically bound into unitary memory representations. Rather, memory binding seems to vary across different subtypes of features, a finding that supports recent research showing that object features are stored in memory rather independently from each other. PMID:25784892

CA1 and CA3 differentially support spontaneous retrieval of episodic contexts within human hippocampal subfields.

PubMed

Dimsdale-Zucker, Halle R; Ritchey, Maureen; Ekstrom, Arne D; Yonelinas, Andrew P; Ranganath, Charan

2018-01-18

The hippocampus plays a critical role in spatial and episodic memory. Mechanistic models predict that hippocampal subfields have computational specializations that differentially support memory. However, there is little empirical evidence suggesting differences between the subfields, particularly in humans. To clarify how hippocampal subfields support human spatial and episodic memory, we developed a virtual reality paradigm where participants passively navigated through houses (spatial contexts) across a series of videos (episodic contexts). We then used multivariate analyses of high-resolution fMRI data to identify neural representations of contextual information during recollection. Multi-voxel pattern similarity analyses revealed that CA1 represented objects that shared an episodic context as more similar than those from different episodic contexts. CA23DG showed the opposite pattern, differentiating between objects encountered in the same episodic context. The complementary characteristics of these subfields explain how we can parse our experiences into cohesive episodes while retaining the specific details that support vivid recollection.

Incorporating evolution of transcription factor binding sites into annotated alignments.

PubMed

Bais, Abha S; Grossmann, Stefen; Vingron, Martin

2007-08-01

Identifying transcription factor binding sites (TFBSs) is essential to elucidate putative regulatory mechanisms. A common strategy is to combine cross-species conservation with single sequence TFBS annotation to yield "conserved TFBSs". Most current methods in this field adopt a multi-step approach that segregates the two aspects. Again, it is widely accepted that the evolutionary dynamics of binding sites differ from those of the surrounding sequence. Hence, it is desirable to have an approach that explicitly takes this factor into account. Although a plethora of approaches have been proposed for the prediction of conserved TFBSs, very few explicitly model TFBS evolutionary properties, while additionally being multi-step. Recently, we introduced a novel approach to simultaneously align and annotate conserved TFBSs in a pair of sequences. Building upon the standard Smith-Waterman algorithm for local alignments, SimAnn introduces additional states for profiles to output extended alignments or annotated alignments. That is, alignments with parts annotated as gaplessly aligned TFBSs (pair-profile hits)are generated. Moreover,the pair- profile related parameters are derived in a sound statistical framework. In this article, we extend this approach to explicitly incorporate evolution of binding sites in the SimAnn framework. We demonstrate the extension in the theoretical derivations through two position-specific evolutionary models, previously used for modelling TFBS evolution. In a simulated setting, we provide a proof of concept that the approach works given the underlying assumptions,as compared to the original work. Finally, using a real dataset of experimentally verified binding sites in human-mouse sequence pairs,we compare the new approach (eSimAnn) to an existing multi-step tool that also considers TFBS evolution. Although it is widely accepted that binding sites evolve differently from the surrounding sequences, most comparative TFBS identification methods do not explicitly consider this.Additionally, prediction of conserved binding sites is carried out in a multi-step approach that segregates alignment from TFBS annotation. In this paper, we demonstrate how the simultaneous alignment and annotation approach of SimAnn can be further extended to incorporate TFBS evolutionary relationships. We study how alignments and binding site predictions interplay at varying evolutionary distances and for various profile qualities.

Single and multiple objective biomass-to-biofuel supply chain optimization considering environmental impacts

NASA Astrophysics Data System (ADS)

Valles Sosa, Claudia Evangelina

Bioenergy has become an important alternative source of energy to alleviate the reliance on petroleum energy. Bioenergy offers diminishing climate change by reducing Green House Gas Emissions, as well as providing energy security and enhancing rural development. The Energy Independence and Security Act mandate the use of 21 billion gallons of advanced biofuels including 16 billion gallons of cellulosic biofuels by the year 2022. It is clear that Biomass can make a substantial contribution to supply future energy demand in a sustainable way. However, the supply of sustainable energy is one of the main challenges that mankind will face over the coming decades. For instance, many logistical challenges will be faced in order to provide an efficient and reliable supply of quality feedstock to biorefineries. 700 million tons of biomass will be required to be sustainably delivered to biorefineries annually to meet the projected use of biofuels by the year of 2022. Approaching this complex logistic problem as a multi-commodity network flow structure, the present work proposes the use of a genetic algorithm as a single objective optimization problem that considers the maximization of profit and the present work also proposes the use of a Multiple Objective Evolutionary Algorithm to simultaneously maximize profit while minimizing global warming potential. Most transportation optimization problems available in the literature have mostly considered the maximization of profit or the minimization of total travel time as potential objectives to be optimized. However, on this research work, we take a more conscious and sustainable approach for this logistic problem. Planners are increasingly expected to adopt a multi-disciplinary approach, especially due to the rising importance of environmental stewardship. The role of a transportation planner and designer is shifting from simple economic analysis to promoting sustainability through the integration of environmental objectives. To respond to these new challenges, the Modified Multiple Objective Evolutionary Algorithm for the design optimization of a biomass to bio-refinery logistic system that considers the simultaneous maximization of the total profit and the minimization of three environmental impacts is presented. Sustainability balances economic, social and environmental goals and objectives. There exist several works in the literature that have considered economic and environmental objectives for the presented supply chain problem. However, there is a lack of research performed in the social aspect of a sustainable logistics system. This work proposes a methodology to integrate social aspect assessment, based on employment creation. Finally, most of the assessment methodologies considered in the literature only contemplate deterministic values, when in realistic situations uncertainties in the supply chain are present. In this work, Value-at-Risk, an advanced risk measure commonly used in portfolio optimization is included to consider the uncertainties in biofuel prices, among the others.

A TYPE Ia SUPERNOVA AT REDSHIFT 1.55 IN HUBBLE SPACE TELESCOPE INFRARED OBSERVATIONS FROM CANDELS

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

Rodney, Steven A.; Riess, Adam G.; Jones, David O.

2012-02-10

We report the discovery of a Type Ia supernova (SN Ia) at redshift z = 1.55 with the infrared detector of the Wide Field Camera 3 (WFC3-IR) on the Hubble Space Telescope (HST). This object was discovered in CANDELS imaging data of the Hubble Ultra Deep Field and followed as part of the CANDELS+CLASH Supernova project, comprising the SN search components from those two HST multi-cycle treasury programs. This is the highest redshift SN Ia with direct spectroscopic evidence for classification. It is also the first SN Ia at z > 1 found and followed in the infrared, providing amore » full light curve in rest-frame optical bands. The classification and redshift are securely defined from a combination of multi-band and multi-epoch photometry of the SN, ground-based spectroscopy of the host galaxy, and WFC3-IR grism spectroscopy of both the SN and host. This object is the first of a projected sample at z > 1.5 that will be discovered by the CANDELS and CLASH programs. The full CANDELS+CLASH SN Ia sample will enable unique tests for evolutionary effects that could arise due to differences in SN Ia progenitor systems as a function of redshift. This high-z sample will also allow measurement of the SN Ia rate out to z Almost-Equal-To 2, providing a complementary constraint on SN Ia progenitor models.« less

Genomic evolution, recombination, and inter-strain diversity of chelonid alphaherpesvirus 5 from Florida and Hawaii green sea turtles with fibropapillomatosis.

PubMed

Morrison, Cheryl L; Iwanowicz, Luke; Work, Thierry M; Fahsbender, Elizabeth; Breitbart, Mya; Adams, Cynthia; Iwanowicz, Deb; Sanders, Lakyn; Ackermann, Mathias; Cornman, Robert S

2018-01-01

Chelonid alphaherpesvirus 5 (ChHV5) is a herpesvirus associated with fibropapillomatosis (FP) in sea turtles worldwide. Single-locus typing has previously shown differentiation between Atlantic and Pacific strains of this virus, with low variation within each geographic clade. However, a lack of multi-locus genomic sequence data hinders understanding of the rate and mechanisms of ChHV5 evolutionary divergence, as well as how these genomic changes may contribute to differences in disease manifestation. To assess genomic variation in ChHV5 among five Hawaii and three Florida green sea turtles, we used high-throughput short-read sequencing of long-range PCR products amplified from tumor tissue using primers designed from the single available ChHV5 reference genome from a Hawaii green sea turtle. This strategy recovered sequence data from both geographic regions for approximately 75% of the predicted ChHV5 coding sequences. The average nucleotide divergence between geographic populations was 1.5%; most of the substitutions were fixed differences between regions. Protein divergence was generally low (average 0.08%), and ranged between 0 and 5.3%. Several atypical genes originally identified and annotated in the reference genome were confirmed in ChHV5 genomes from both geographic locations. Unambiguous recombination events between geographic regions were identified, and clustering of private alleles suggests the prevalence of recombination in the evolutionary history of ChHV5. This study significantly increased the amount of sequence data available from ChHV5 strains, enabling informed selection of loci for future population genetic and natural history studies, and suggesting the (possibly latent) co-infection of individuals by well-differentiated geographic variants.

Genomic evolution, recombination, and inter-strain diversity of chelonid alphaherpesvirus 5 from Florida and Hawaii green sea turtles with fibropapillomatosis

USGS Publications Warehouse

Morrison, Cheryl L.; Iwanowicz, Luke R.; Work, Thierry M.; Fahsbender, Elizabeth; Breitbart, Mya; Adams, Cynthia; Iwanowicz, Deborah; Sanders, Lakyn; Ackermann, Mathias; Cornman, Robert S.

2018-01-01

Chelonid alphaherpesvirus 5 (ChHV5) is a herpesvirus associated with fibropapillomatosis (FP) in sea turtles worldwide. Single-locus typing has previously shown differentiation between Atlantic and Pacific strains of this virus, with low variation within each geographic clade. However, a lack of multi-locus genomic sequence data hinders understanding of the rate and mechanisms of ChHV5 evolutionary divergence, as well as how these genomic changes may contribute to differences in disease manifestation. To assess genomic variation in ChHV5 among five Hawaii and three Florida green sea turtles, we used high-throughput short-read sequencing of long-range PCR products amplified from tumor tissue using primers designed from the single available ChHV5 reference genome from a Hawaii green sea turtle. This strategy recovered sequence data from both geographic regions for approximately 75% of the predicted ChHV5 coding sequences. The average nucleotide divergence between geographic populations was 1.5%; most of the substitutions were fixed differences between regions. Protein divergence was generally low (average 0.08%), and ranged between 0 and 5.3%. Several atypical genes originally identified and annotated in the reference genome were confirmed in ChHV5 genomes from both geographic locations. Unambiguous recombination events between geographic regions were identified, and clustering of private alleles suggests the prevalence of recombination in the evolutionary history of ChHV5. This study significantly increased the amount of sequence data available from ChHV5 strains, enabling informed selection of loci for future population genetic and natural history studies, and suggesting the (possibly latent) co-infection of individuals by well-differentiated geographic variants.

Genomic evolution, recombination, and inter-strain diversity of chelonid alphaherpesvirus 5 from Florida and Hawaii green sea turtles with fibropapillomatosis

PubMed Central

Iwanowicz, Luke; Work, Thierry M.; Fahsbender, Elizabeth; Breitbart, Mya; Adams, Cynthia; Iwanowicz, Deb; Sanders, Lakyn; Ackermann, Mathias; Cornman, Robert S.

2018-01-01

Chelonid alphaherpesvirus 5 (ChHV5) is a herpesvirus associated with fibropapillomatosis (FP) in sea turtles worldwide. Single-locus typing has previously shown differentiation between Atlantic and Pacific strains of this virus, with low variation within each geographic clade. However, a lack of multi-locus genomic sequence data hinders understanding of the rate and mechanisms of ChHV5 evolutionary divergence, as well as how these genomic changes may contribute to differences in disease manifestation. To assess genomic variation in ChHV5 among five Hawaii and three Florida green sea turtles, we used high-throughput short-read sequencing of long-range PCR products amplified from tumor tissue using primers designed from the single available ChHV5 reference genome from a Hawaii green sea turtle. This strategy recovered sequence data from both geographic regions for approximately 75% of the predicted ChHV5 coding sequences. The average nucleotide divergence between geographic populations was 1.5%; most of the substitutions were fixed differences between regions. Protein divergence was generally low (average 0.08%), and ranged between 0 and 5.3%. Several atypical genes originally identified and annotated in the reference genome were confirmed in ChHV5 genomes from both geographic locations. Unambiguous recombination events between geographic regions were identified, and clustering of private alleles suggests the prevalence of recombination in the evolutionary history of ChHV5. This study significantly increased the amount of sequence data available from ChHV5 strains, enabling informed selection of loci for future population genetic and natural history studies, and suggesting the (possibly latent) co-infection of individuals by well-differentiated geographic variants. PMID:29479497

On the preservation of cooperation in two-strategy games with nonlocal interactions.

PubMed

Aydogmus, Ozgur; Zhou, Wen; Kang, Yun

2017-03-01

Nonlocal interactions such as spatial interaction are ubiquitous in nature and may alter the equilibrium in evolutionary dynamics. Models including nonlocal spatial interactions can provide a further understanding on the preservation and emergence of cooperation in evolutionary dynamics. In this paper, we consider a variety of two-strategy evolutionary spatial games with nonlocal interactions based on an integro-differential replicator equation. By defining the invasion speed and minimal traveling wave speed for the derived model, we study the effects of the payoffs, the selection pressure and the spatial parameter on the preservation of cooperation. One of our most interesting findings is that, for the Prisoners Dilemma games in which the defection is the only evolutionary stable strategy for unstructured populations, analyses on its asymptotic speed of propagation suggest that, in contrast with spatially homogeneous games, the cooperators can invade the habitat under proper conditions. Other two-strategy evolutionary spatial games are also explored. Both our theoretical and numerical studies show that the nonlocal spatial interaction favors diversity in strategies in a population and is able to preserve cooperation in a competing environment. A real data application in a virus mutation study echoes our theoretical observations. In addition, we compare the results of our model to the partial differential equation approach to demonstrate the importance of including non-local interaction component in evolutionary game models. Copyright © 2016 Elsevier Inc. All rights reserved.

Evidence Combination From an Evolutionary Game Theory Perspective

PubMed Central

Deng, Xinyang; Han, Deqiang; Dezert, Jean; Deng, Yong; Shyr, Yu

2017-01-01

Dempster-Shafer evidence theory is a primary methodology for multi-source information fusion because it is good at dealing with uncertain information. This theory provides a Dempster’s rule of combination to synthesize multiple evidences from various information sources. However, in some cases, counter-intuitive results may be obtained based on that combination rule. Numerous new or improved methods have been proposed to suppress these counter-intuitive results based on perspectives, such as minimizing the information loss or deviation. Inspired by evolutionary game theory, this paper considers a biological and evolutionary perspective to study the combination of evidences. An evolutionary combination rule (ECR) is proposed to help find the most biologically supported proposition in a multi-evidence system. Within the proposed ECR, we develop a Jaccard matrix game (JMG) to formalize the interaction between propositions in evidences, and utilize the replicator dynamics to mimick the evolution of propositions. Experimental results show that the proposed ECR can effectively suppress the counter-intuitive behaviors appeared in typical paradoxes of evidence theory, compared with many existing methods. Properties of the ECR, such as solution’s stability and convergence, have been mathematically proved as well. PMID:26285231

Evidence of at least two evolutionary lineages in Melipona subnitida (Apidae, Meliponini) suggested by mtDNA variability and geometric morphometrics of forewings.

PubMed

Bonatti, Vanessa; Simões, Zilá Luz Paulino; Franco, Fernando Faria; Francoy, Tiago Mauricio

2014-01-01

Melipona subnitida, a tropical stingless bee, is an endemic species of the Brazilian northeast and exhibits great potential for honey and pollen production in addition to its role as one of the main pollinators of the Caatinga biome. To understand the genetic structure and better assist in the conservation of this species, we characterized the population variability of M. subnitida using geometric morphometrics of the forewing and cytochrome c oxidase I gene fragment sequencing. We collected workers from six localities in the northernmost distribution. Both methodologies indicated that the variability among the sampled populations is related both to the environment in which samples were collected and the geographical distance between the sampling sites, indicating that differentiation among the populations is due to the existence of at least evolutionary lineages. Molecular clock data suggest that this differentiation may have begun in the middle Pleistocene, approximately 396 kya. The conservation of all evolutionary lineages is important since they can present differential resistance to environmental changes, as resistance to drought and diseases.

Evidence of at least two evolutionary lineages in Melipona subnitida (Apidae, Meliponini) suggested by mtDNA variability and geometric morphometrics of forewings

NASA Astrophysics Data System (ADS)

Bonatti, Vanessa; Simões, Zilá Luz Paulino; Franco, Fernando Faria; Francoy, Tiago Mauricio

2014-01-01

Melipona subnitida, a tropical stingless bee, is an endemic species of the Brazilian northeast and exhibits great potential for honey and pollen production in addition to its role as one of the main pollinators of the Caatinga biome. To understand the genetic structure and better assist in the conservation of this species, we characterized the population variability of M. subnitida using geometric morphometrics of the forewing and cytochrome c oxidase I gene fragment sequencing. We collected workers from six localities in the northernmost distribution. Both methodologies indicated that the variability among the sampled populations is related both to the environment in which samples were collected and the geographical distance between the sampling sites, indicating that differentiation among the populations is due to the existence of at least evolutionary lineages. Molecular clock data suggest that this differentiation may have begun in the middle Pleistocene, approximately 396 kya. The conservation of all evolutionary lineages is important since they can present differential resistance to environmental changes, as resistance to drought and diseases.

Rotational properties of hypermassive neutron stars from binary mergers

NASA Astrophysics Data System (ADS)

Hanauske, Matthias; Takami, Kentaro; Bovard, Luke; Rezzolla, Luciano; Font, José A.; Galeazzi, Filippo; Stöcker, Horst

2017-08-01

Determining the differential-rotation law of compact stellar objects produced in binary neutron stars mergers or core-collapse supernovae is an old problem in relativistic astrophysics. Addressing this problem is important because it impacts directly on the maximum mass these objects can attain and, hence, on the threshold to black-hole formation under realistic conditions. Using the results from a large number of numerical simulations in full general relativity of binary neutron star mergers described with various equations of state and masses, we study the rotational properties of the resulting hypermassive neutron stars. We find that the angular-velocity distribution shows only a modest dependence on the equation of state, thus exhibiting the traits of "quasiuniversality" found in other aspects of compact stars, both isolated and in binary systems. The distributions are characterized by an almost uniformly rotating core and a "disk." Such a configuration is significantly different from the j -constant differential-rotation law that is commonly adopted in equilibrium models of differentially rotating stars. Furthermore, the rest-mass contained in such a disk can be quite large, ranging from ≃0.03 M⊙ in the case of high-mass binaries with stiff equations of state, up to ≃0.2 M⊙ for low-mass binaries with soft equations of state. We comment on the astrophysical implications of our findings and on the long-term evolutionary scenarios that can be conjectured on the basis of our simulations.

Time Parallel Solution of Linear Partial Differential Equations on the Intel Touchstone Delta Supercomputer

NASA Technical Reports Server (NTRS)

Toomarian, N.; Fijany, A.; Barhen, J.

1993-01-01

Evolutionary partial differential equations are usually solved by decretization in time and space, and by applying a marching in time procedure to data and algorithms potentially parallelized in the spatial domain.

Hybrid zone studies: An interdisciplinary approach for the analysis of evolutionary processes

USGS Publications Warehouse

Scribner, Kim T.

1994-01-01

There has been considerable debate in the ecological and evolutionary literature over the relative importance and rate by which microevolutionary processes operating at the population level result in separation and differentiation of lineages and populations, and ultimately in speciation. Our understanding of evolutionary processes have need greatly enhances through the study of hybridization and hybrid zones. Indeed, hybrid zones have been described as “natural laboratories” (Barton, N. H., and G .M. Hewitt, 189. Adaptation, speciation, and hybrid zones. Nature 341:497-503) or as “windows on the evolutionary processes” (Harrison, R. G. 1990. Hybrid zones: windows on the evolutionary process. Oxford Surveys in Evolutionary Biology 7:69-128). Hybrid zones greatly facilitate analyses of evolutionary dynamics because differences in factors such as mating preference, fertility, and viability are likely to be magnified, making the consequences easier to document over short periods of time.

Uncovering hidden nodes in complex networks in the presence of noise

PubMed Central

Su, Ri-Qi; Lai, Ying-Cheng; Wang, Xiao; Do, Younghae

2014-01-01

Ascertaining the existence of hidden objects in a complex system, objects that cannot be observed from the external world, not only is curiosity-driven but also has significant practical applications. Generally, uncovering a hidden node in a complex network requires successful identification of its neighboring nodes, but a challenge is to differentiate its effects from those of noise. We develop a completely data-driven, compressive-sensing based method to address this issue by utilizing complex weighted networks with continuous-time oscillatory or discrete-time evolutionary-game dynamics. For any node, compressive sensing enables accurate reconstruction of the dynamical equations and coupling functions, provided that time series from this node and all its neighbors are available. For a neighboring node of the hidden node, this condition cannot be met, resulting in abnormally large prediction errors that, counterintuitively, can be used to infer the existence of the hidden node. Based on the principle of differential signal, we demonstrate that, when strong noise is present, insofar as at least two neighboring nodes of the hidden node are subject to weak background noise only, unequivocal identification of the hidden node can be achieved. PMID:24487720

Differential Adhesion between Moving Particles as a Mechanism for the Evolution of Social Groups

PubMed Central

Garcia, Thomas; Brunnet, Leonardo Gregory; De Monte, Silvia

2014-01-01

The evolutionary stability of cooperative traits, that are beneficial to other individuals but costly to their carrier, is considered possible only through the establishment of a sufficient degree of assortment between cooperators. Chimeric microbial populations, characterized by simple interactions between unrelated individuals, restrain the applicability of standard mechanisms generating such assortment, in particular when cells disperse between successive reproductive events such as happens in Dicyostelids and Myxobacteria. In this paper, we address the evolutionary dynamics of a costly trait that enhances attachment to others as well as group cohesion. By modeling cells as self-propelled particles moving on a plane according to local interaction forces and undergoing cycles of aggregation, reproduction and dispersal, we show that blind differential adhesion provides a basis for assortment in the process of group formation. When reproductive performance depends on the social context of players, evolution by natural selection can lead to the success of the social trait, and to the concomitant emergence of sizeable groups. We point out the conditions on the microscopic properties of motion and interaction that make such evolutionary outcome possible, stressing that the advent of sociality by differential adhesion is restricted to specific ecological contexts. Moreover, we show that the aggregation process naturally implies the existence of non-aggregated particles, and highlight their crucial evolutionary role despite being largely neglected in theoretical models for the evolution of sociality. PMID:24586133

Adjustment of multi-CCD-chip-color-camera heads

NASA Astrophysics Data System (ADS)

Guyenot, Volker; Tittelbach, Guenther; Palme, Martin

1999-09-01

The principle of beam-splitter-multi-chip cameras consists in splitting an image into differential multiple images of different spectral ranges and in distributing these onto separate black and white CCD-sensors. The resulting electrical signals from the chips are recombined to produce a high quality color picture on the monitor. Because this principle guarantees higher resolution and sensitivity in comparison to conventional single-chip camera heads, the greater effort is acceptable. Furthermore, multi-chip cameras obtain the compete spectral information for each individual object point while single-chip system must rely on interpolation. In a joint project, Fraunhofer IOF and STRACON GmbH and in future COBRA electronic GmbH develop methods for designing the optics and dichroitic mirror system of such prism color beam splitter devices. Additionally, techniques and equipment for the alignment and assembly of color beam splitter-multi-CCD-devices on the basis of gluing with UV-curable adhesives have been developed, too.

Evolutionary relevance facilitates visual information processing.

PubMed

Jackson, Russell E; Calvillo, Dusti P

2013-11-03

Visual search of the environment is a fundamental human behavior that perceptual load affects powerfully. Previously investigated means for overcoming the inhibitions of high perceptual load, however, generalize poorly to real-world human behavior. We hypothesized that humans would process evolutionarily relevant stimuli more efficiently than evolutionarily novel stimuli, and evolutionary relevance would mitigate the repercussions of high perceptual load during visual search. Animacy is a significant component to evolutionary relevance of visual stimuli because perceiving animate entities is time-sensitive in ways that pose significant evolutionary consequences. Participants completing a visual search task located evolutionarily relevant and animate objects fastest and with the least impact of high perceptual load. Evolutionarily novel and inanimate objects were located slowest and with the highest impact of perceptual load. Evolutionary relevance may importantly affect everyday visual information processing.

Exaggeration and suppression of iridescence: the evolution of two-dimensional butterfly structural colours

PubMed Central

Wickham, Shelley; Large, Maryanne C.J; Poladian, Leon; Jermiin, Lars S

2005-01-01

Many butterfly species possess ‘structural’ colour, where colour is due to optical microstructures found in the wing scales. A number of such structures have been identified in butterfly scales, including three variations on a simple multi-layer structure. In this study, we optically characterize examples of all three types of multi-layer structure, as found in 10 species. The optical mechanism of the suppression and exaggeration of the angle-dependent optical properties (iridescence) of these structures is described. In addition, we consider the phylogeny of the butterflies, and are thus able to relate the optical properties of the structures to their evolutionary development. By applying two different types of analysis, the mechanism of adaptation is addressed. A simple parsimony analysis, in which all evolutionary changes are given an equal weighting, suggests convergent evolution of one structure. A Dollo parsimony analysis, in which the evolutionary ‘cost’ of losing a structure is less than that of gaining it, implies that ‘latent’ structures can be reused. PMID:16849221

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

ERIC Educational Resources Information Center

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

2012-01-01

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

An Evolutionary Perspective on Family Studies: Differential Susceptibility to Environmental Influences.

PubMed

Hartman, Sarah; Belsky, Jay

2016-12-01

An evolutionary perspective of human development provides the basis for the differential-susceptibility hypothesis which stipulates that individuals should differ in their susceptibility to environmental influences, with some being more affected than others by both positive and negative developmental experiences and environmental exposures. This paper reviews evidence consistent with this claim while revealing that temperamental and genetic characteristics play a role in distinguishing more and less susceptible individuals. The differential-susceptibility framework under consideration is contrasted to the traditional diathesis-stress view that "vulnerability" traits predispose some to being disproportionately affected by (only) adverse experiences. We raise several issues stimulated by the literature that need to be clarified in further research. Lastly, we suggest that therapy may differ in its effects depending on an individual's susceptibility. © 2015 Family Process Institute.

Bringing Together Evolution on Serpentine and Polyploidy: Spatiotemporal History of the Diploid-Tetraploid Complex of Knautia arvensis (Dipsacaceae)

PubMed Central

Kolář, Filip; Fér, Tomáš; Štech, Milan; Trávníček, Pavel; Dušková, Eva; Schönswetter, Peter; Suda, Jan

2012-01-01

Polyploidization is one of the leading forces in the evolution of land plants, providing opportunities for instant speciation and rapid gain of evolutionary novelties. Highly selective conditions of serpentine environments act as an important evolutionary trigger that can be involved in various speciation processes. Whereas the significance of both edaphic speciation on serpentine and polyploidy is widely acknowledged in plant evolution, the links between polyploid evolution and serpentine differentiation have not yet been examined. To fill this gap, we investigated the evolutionary history of the perennial herb Knautia arvensis (Dipsacaceae), a diploid-tetraploid complex that exhibits an intriguing pattern of eco-geographic differentiation. Using plastid DNA sequencing and AFLP genotyping of 336 previously cytotyped individuals from 40 populations from central Europe, we unravelled the patterns of genetic variation among the cytotypes and the edaphic types. Diploids showed the highest levels of genetic differentiation, likely as a result of long term persistence of several lineages in ecologically distinct refugia and/or independent immigration. Recurrent polyploidization, recorded in one serpentine island, seems to have opened new possibilities for the local serpentine genotype. Unlike diploids, the serpentine tetraploids were able to escape from the serpentine refugium and spread further; this was also attributable to hybridization with the neighbouring non-serpentine tetraploid lineages. The spatiotemporal history of K. arvensis allows tracing the interplay of polyploid evolution and ecological divergence on serpentine, resulting in a complex evolutionary pattern. Isolated serpentine outcrops can act as evolutionary capacitors, preserving distinct karyological and genetic diversity. The serpentine lineages, however, may not represent evolutionary ‘dead-ends’ but rather dynamic systems with a potential to further influence the surrounding populations, e.g., via independent polyplodization and hybridization. The complex eco-geographical pattern together with the incidence of both primary and secondary diploid-tetraploid contact zones makes K. arvensis a unique system for addressing general questions of polyploid research. PMID:22792207

Derived heuristics-based consistent optimization of material flow in a gold processing plant

NASA Astrophysics Data System (ADS)

Myburgh, Christie; Deb, Kalyanmoy

2018-01-01

Material flow in a chemical processing plant often follows complicated control laws and involves plant capacity constraints. Importantly, the process involves discrete scenarios which when modelled in a programming format involves if-then-else statements. Therefore, a formulation of an optimization problem of such processes becomes complicated with nonlinear and non-differentiable objective and constraint functions. In handling such problems using classical point-based approaches, users often have to resort to modifications and indirect ways of representing the problem to suit the restrictions associated with classical methods. In a particular gold processing plant optimization problem, these facts are demonstrated by showing results from MATLAB®'s well-known fmincon routine. Thereafter, a customized evolutionary optimization procedure which is capable of handling all complexities offered by the problem is developed. Although the evolutionary approach produced results with comparatively less variance over multiple runs, the performance has been enhanced by introducing derived heuristics associated with the problem. In this article, the development and usage of derived heuristics in a practical problem are presented and their importance in a quick convergence of the overall algorithm is demonstrated.

Dynamic replanning on demand of UAS constellations performing ISR missions

NASA Astrophysics Data System (ADS)

Stouch, Daniel W.; Zeidman, Ernest; Callahan, William; McGraw, Kirk

2011-05-01

Unmanned aerial systems (UAS) have proven themselves to be indispensable in providing intelligence, surveillance, and reconnaissance (ISR) over the battlefield. Constellations of heterogeneous, multi-purpose UAS are being tasked to provide ISR in an unpredictable environment. This necessitates the dynamic replanning of critical missions as weather conditions change, new observation targets are identified, aircraft are lost or equipment malfunctions, and new airspace restrictions are introduced. We present a method to generate coordinated mission plans for constellations of UAS with multiple flight goals and potentially competing objectives, and update them on demand as the operational situation changes. We use a fast evolutionary algorithm-based, multi-objective optimization technique. The updated flight routes maintain continuity by considering where the ISR assets have already flown and where they still need to go. Both the initial planning and replanning take into account factors such as area of analysis coverage, restricted operating zones, maximum control station range, adverse weather effects, military terrain value, and sensor performance. Our results demonstrate that by constraining the space of potential solutions using an intelligently-formed air maneuver network with a subset of potential airspace corridors and navigational waypoints, we can ensure global optimization for multiple objectives considering the situation both before and after the replanning is initiated. We employ sophisticated visualization techniques using a geographic information system to help the user 'look under the hood" of the algorithms to understand the effectiveness and viability of the generated ISR mission plans and identify potential gaps in coverage.

Toward a multi-objective decision support framework to support regulations of unconventional oil and gas development

NASA Astrophysics Data System (ADS)

Alongi, M.; Howard, C.; Kasprzyk, J. R.; Ryan, J. N.

2015-12-01

Unconventional oil and gas development (UOGD) using hydraulic fracturing and horizontal drilling has recently fostered an unprecedented acceleration in energy development. Regulations seek to protect environmental quality of areas surrounding UOGD, while maintaining economic benefits. One such regulation is a setback distance, which dictates the minimum proximity between an oil and gas well and an object such as a residential or commercial building, property line, or water source. In general, most setback regulations have been strongly politically motivated without a clear scientific basis for understanding the relationship between the setback distance and various performance outcomes. This presentation discusses a new decision support framework for setback regulations, as part of a large NSF-funded sustainability research network (SRN) on UOGD. The goal of the decision support framework is to integrate a wide array of scientific information from the SRN into a coherent framework that can help inform policy regarding UOGD. The decision support framework employs multiobjective evolutionary algorithm (MOEA) optimization coupled with simulation models of air quality and other performance-based outcomes on UOGD. The result of the MOEA optimization runs are quantitative tradeoff curves among different objectives. For example, one such curve could demonstrate air pollution concentrations versus estimates of energy development profits, for different levels of setback distance. Our results will also inform policy-relevant discussions surrounding UOGD such as comparing single- and multi-well pads, as well as regulations on the density of well development over a spatial area.

Evaluation of Generation Alternation Models in Evolutionary Robotics

NASA Astrophysics Data System (ADS)

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

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

Differences in Multi-Modal Ultrasound Imaging between Triple Negative and Non-Triple Negative Breast Cancer.

PubMed

Li, Ziyao; Tian, Jiawei; Wang, Xiaowei; Wang, Ying; Wang, Zhenzhen; Zhang, Lei; Jing, Hui; Wu, Tong

2016-04-01

The objective of this study was to identify multi-modal ultrasound imaging parameters that could potentially help to differentiate between triple negative breast cancer (TNBC) and non-TNBC. Conventional ultrasonography, ultrasound strain elastography and 3-D ultrasound (3-D-US) findings from 50 TNBC and 179 non-TNBC patients were retrospectively reviewed. Immunohistochemical examination was used as the reference gold standard for cancer subtyping. Different ultrasound modalities were initially analyzed to define TNBC-related features. Subsequently, logistic regression analysis was applied to TNBC-related features to establish models for predicting TNBC. TNBCs often presented as micro-lobulated, markedly hypo-echoic masses with an abrupt interface (p = 0.015, 0.0015 and 0.004, compared with non-TNBCs, respectively) on conventional ultrasound, and showed a diminished retraction pattern phenomenon in the coronal plane (p = 0.035) on 3-D-US. Our findings suggest that B-mode ultrasound and 3-D-US in multi-modality ultrasonography could be a useful non-invasive technique for differentiating TNBCs from non-TNBCs. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Gloss uniformity measurement update for ISO/IEC 19751

NASA Astrophysics Data System (ADS)

Ng, Yee S.; Cui, Chengwu; Kuo, Chunghui; Maggard, Eric; Mashtare, Dale; Morris, Peter

2005-01-01

To address the standardization issues of perceptually based image quality for printing systems, ISO/IEC JTC1/SC28, the standardization committee for office equipment chartered the W1.1 project with the responsibility of drafting a proposal for an international standard for the evaluation of printed image quality1. An ISO draft Standard2, ISO/WD 19751-1, Office Equipment - Appearance-based image quality standards for printers - Part 1: Overview, Procedure and Common Methods, 2004 describes the overview of this multi-part appearance-based image quality standard. One of the ISO 19751 multi-part Standard"s tasks is to address the appearance-based gloss and gloss uniformity issues (in ISO 19751-2). This paper summarizes the current status and technical progress since the last two updates3, 4. In particular, we will be discussion our attempt to include 75 degree gloss (G75) objective measurement5 in differential gloss and within-page gloss uniformity. The result for a round-robin experiment involving objective measurement of differential gloss using G60 and G75 gloss measurement geometry is described. The results for two perceptual-based round-robin experiments relating to haze effect on the perception of gloss, and gloss artifacts (gloss streaks/bands, gloss graininess/mottle) are discussed.

Gloss uniformity measurement update for ISO/IEC 19751

NASA Astrophysics Data System (ADS)

Ng, Yee S.; Cui, Chengwu; Kuo, Chunghui; Maggard, Eric; Mashtare, Dale; Morris, Peter

2004-10-01

To address the standardization issues of perceptually based image quality for printing systems, ISO/IEC JTC1/SC28, the standardization committee for office equipment chartered the W1.1 project with the responsibility of drafting a proposal for an international standard for the evaluation of printed image quality1. An ISO draft Standard2, ISO/WD 19751-1, Office Equipment - Appearance-based image quality standards for printers - Part 1: Overview, Procedure and Common Methods, 2004 describes the overview of this multi-part appearance-based image quality standard. One of the ISO 19751 multi-part Standard"s tasks is to address the appearance-based gloss and gloss uniformity issues (in ISO 19751-2). This paper summarizes the current status and technical progress since the last two updates3, 4. In particular, we will be discussion our attempt to include 75 degree gloss (G75) objective measurement5 in differential gloss and within-page gloss uniformity. The result for a round-robin experiment involving objective measurement of differential gloss using G60 and G75 gloss measurement geometry is described. The results for two perceptual-based round-robin experiments relating to haze effect on the perception of gloss, and gloss artifacts (gloss streaks/bands, gloss graininess/mottle) are discussed.

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…

Emotional engagements predict and enhance social cognition in young chimpanzees.

PubMed

Bard, Kim A; Bakeman, Roger; Boysen, Sarah T; Leavens, David A

2014-09-01

Social cognition in infancy is evident in coordinated triadic engagements, that is, infants attending jointly with social partners and objects. Current evolutionary theories of primate social cognition tend to highlight species differences in cognition based on human-unique cooperative motives. We consider a developmental model in which engagement experiences produce differential outcomes. We conducted a 10-year-long study in which two groups of laboratory-raised chimpanzee infants were given quantifiably different engagement experiences. Joint attention, cooperativeness, affect, and different levels of cognition were measured in 5- to 12-month-old chimpanzees, and compared to outcomes derived from a normative human database. We found that joint attention skills significantly improved across development for all infants, but by 12 months, the humans significantly surpassed the chimpanzees. We found that cooperativeness was stable in the humans, but by 12 months, the chimpanzee group given enriched engagement experiences significantly surpassed the humans. Past engagement experiences and concurrent affect were significant unique predictors of both joint attention and cooperativeness in 5- to 12-month-old chimpanzees. When engagement experiences and concurrent affect were statistically controlled, joint attention and cooperation were not associated. We explain differential social cognition outcomes in terms of the significant influences of previous engagement experiences and affect, in addition to cognition. Our study highlights developmental processes that underpin the emergence of social cognition in support of evolutionary continuity. © 2014 The Authors. Developmental Science Published by John Wiley & Sons Ltd.

Multiple Fingers - One Gestalt.

PubMed

Lezkan, Alexandra; Manuel, Steven G; Colgate, J Edward; Klatzky, Roberta L; Peshkin, Michael A; Drewing, Knut

2016-01-01

The Gestalt theory of perception offered principles by which distributed visual sensations are combined into a structured experience ("Gestalt"). We demonstrate conditions whereby haptic sensations at two fingertips are integrated in the perception of a single object. When virtual bumps were presented simultaneously to the right hand's thumb and index finger during lateral arm movements, participants reported perceiving a single bump. A discrimination task measured the bump's perceived location and perceptual reliability (assessed by differential thresholds) for four finger configurations, which varied in their adherence to the Gestalt principles of proximity (small versus large finger separation) and synchrony (virtual spring to link movements of the two fingers versus no spring). According to models of integration, reliability should increase with the degree to which multi-finger cues integrate into a unified percept. Differential thresholds were smaller in the virtual-spring condition (synchrony) than when fingers were unlinked. Additionally, in the condition with reduced synchrony, greater proximity led to lower differential thresholds. Thus, with greater adherence to Gestalt principles, thresholds approached values predicted for optimal integration. We conclude that the Gestalt principles of synchrony and proximity apply to haptic perception of surface properties and that these principles can interact to promote multi-finger integration.

Islamic Medicine and Evolutionary Medicine: A Comparative Analysis

PubMed Central

Saniotis, Arthur

2012-01-01

The advent of evolutionary medicine in the last two decades has provided new insights into the causes of human disease and possible preventative strategies. One of the strengths of evolutionary medicine is that it follows a multi-disciplinary approach. Such an approach is vital to future biomedicine as it enables for the infiltration of new ideas. Although evolutionary medicine uses Darwinian evolution as a heuristic for understanding human beings’ susceptibility to disease, this is not necessarily in conflict with Islamic medicine. It should be noted that current evolutionary theory was first expounded by various Muslim scientists such as al-Jāḥiẓ, al-Ṭūsī, Ibn Khaldūn and Ibn Maskawayh centuries before Darwin and Wallace. In this way, evolution should not be viewed as being totally antithetical to Islam. This article provides a comparative overview of Islamic medicine and Evolutionary medicine as well as drawing points of comparison between the two approaches which enables their possible future integration. PMID:23864992

Islamic medicine and evolutionary medicine: a comparative analysis.

PubMed

Saniotis, Arthur

2012-01-01

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

Rapid Multi-Locus Sequence Typing Using Microfluidic Biochips

DTIC Science & Technology

2010-05-12

Sequence Types. The evolutionary history of all the B. cereus MLST concatenated Sequence Types (545 taxa, 2,394 nucleotide positions) was inferred using...the Neighbor-Joining method [28]. The bootstrap consensus tree inferred from 100 replicates was taken to represent the evolutionary history of the... Chlamydia (manuscript in preparation) and performed pilot studies on Staphylococcus aureus and Streptoccus pneumoniae (Data S4 and Text S2). Another potential

How to get the most bang for your buck: the evolution and physiology of nutrition-dependent resource allocation strategies.

PubMed

Ng'oma, Enoch; Perinchery, Anna M; King, Elizabeth G

2017-06-28

All organisms use resources to grow, survive and reproduce. The supply of these resources varies widely across landscapes and time, imposing ultimate constraints on the maximal trait values for allocation-related traits. In this review, we address three key questions fundamental to our understanding of the evolution of allocation strategies and their underlying mechanisms. First, we ask: how diverse are flexible resource allocation strategies among different organisms? We find there are many, varied, examples of flexible strategies that depend on nutrition. However, this diversity is often ignored in some of the best-known cases of resource allocation shifts, such as the commonly observed pattern of lifespan extension under nutrient limitation. A greater appreciation of the wide variety of flexible allocation strategies leads directly to our second major question: what conditions select for different plastic allocation strategies? Here, we highlight the need for additional models that explicitly consider the evolution of phenotypically plastic allocation strategies and empirical tests of the predictions of those models in natural populations. Finally, we consider the question: what are the underlying mechanisms determining resource allocation strategies? Although evolutionary biologists assume differential allocation of resources is a major factor limiting trait evolution, few proximate mechanisms are known that specifically support the model. We argue that an integrated framework can reconcile evolutionary models with proximate mechanisms that appear at first glance to be in conflict with these models. Overall, we encourage future studies to: (i) mimic ecological conditions in which those patterns evolve, and (ii) take advantage of the 'omic' opportunities to produce multi-level data and analytical models that effectively integrate across physiological and evolutionary theory. © 2017 The Author(s).

How to get the most bang for your buck: the evolution and physiology of nutrition-dependent resource allocation strategies

PubMed Central

2017-01-01

All organisms use resources to grow, survive and reproduce. The supply of these resources varies widely across landscapes and time, imposing ultimate constraints on the maximal trait values for allocation-related traits. In this review, we address three key questions fundamental to our understanding of the evolution of allocation strategies and their underlying mechanisms. First, we ask: how diverse are flexible resource allocation strategies among different organisms? We find there are many, varied, examples of flexible strategies that depend on nutrition. However, this diversity is often ignored in some of the best-known cases of resource allocation shifts, such as the commonly observed pattern of lifespan extension under nutrient limitation. A greater appreciation of the wide variety of flexible allocation strategies leads directly to our second major question: what conditions select for different plastic allocation strategies? Here, we highlight the need for additional models that explicitly consider the evolution of phenotypically plastic allocation strategies and empirical tests of the predictions of those models in natural populations. Finally, we consider the question: what are the underlying mechanisms determining resource allocation strategies? Although evolutionary biologists assume differential allocation of resources is a major factor limiting trait evolution, few proximate mechanisms are known that specifically support the model. We argue that an integrated framework can reconcile evolutionary models with proximate mechanisms that appear at first glance to be in conflict with these models. Overall, we encourage future studies to: (i) mimic ecological conditions in which those patterns evolve, and (ii) take advantage of the ‘omic’ opportunities to produce multi-level data and analytical models that effectively integrate across physiological and evolutionary theory. PMID:28637856

Evolutionary inevitability of sexual antagonism.

PubMed

Connallon, Tim; Clark, Andrew G

2014-02-07

Sexual antagonism, whereby mutations are favourable in one sex and disfavourable in the other, is common in natural populations, yet the root causes of sexual antagonism are rarely considered in evolutionary theories of adaptation. Here, we explore the evolutionary consequences of sex-differential selection and genotype-by-sex interactions for adaptation in species with separate sexes. We show that sexual antagonism emerges naturally from sex differences in the direction of selection on phenotypes expressed by both sexes or from sex-by-genotype interactions affecting the expression of such phenotypes. Moreover, modest sex differences in selection or genotype-by-sex effects profoundly influence the long-term evolutionary trajectories of populations with separate sexes, as these conditions trigger the evolution of strong sexual antagonism as a by-product of adaptively driven evolutionary change. The theory demonstrates that sexual antagonism is an inescapable by-product of adaptation in species with separate sexes, whether or not selection favours evolutionary divergence between males and females.

Characterizing behavioural ‘characters’: an evolutionary framework

PubMed Central

Araya-Ajoy, Yimen G.; Dingemanse, Niels J.

2014-01-01

Biologists often study phenotypic evolution assuming that phenotypes consist of a set of quasi-independent units that have been shaped by selection to accomplish a particular function. In the evolutionary literature, such quasi-independent functional units are called ‘evolutionary characters’, and a framework based on evolutionary principles has been developed to characterize them. This framework mainly focuses on ‘fixed’ characters, i.e. those that vary exclusively between individuals. In this paper, we introduce multi-level variation and thereby expand the framework to labile characters, focusing on behaviour as a worked example. We first propose a concept of ‘behavioural characters’ based on the original evolutionary character concept. We then detail how integration of variation between individuals (cf. ‘personality’) and within individuals (cf. ‘individual plasticity’) into the framework gives rise to a whole suite of novel testable predictions about the evolutionary character concept. We further propose a corresponding statistical methodology to test whether observed behaviours should be considered expressions of a hypothesized evolutionary character. We illustrate the application of our framework by characterizing the behavioural character ‘aggressiveness’ in wild great tits, Parus major. PMID:24335984

Probing the Evolution of Massive Young Stellar Objects using Weak Class II 6.7GHz Methanol Maser Emission

NASA Astrophysics Data System (ADS)

Ludwig, Bethany Ann; Cunningham, Nichol

2017-01-01

We present results from an investigation of class II 6.7GHz methanol masers towards four Massive Young Stellar Objects (MYSOs). The sources, selected from the Red MSX Source (RMS) Survey (Lumsden et al. 2013), were previously understood to be non-detections for class II methanol maser emission in the methanol multi-beam (MMB) Survey (Caswell et al. 2010.) Class II methanol masers are a well-known sign post of massive star forming regions and may be utilized to probe their relatively poorly understood formation. It is possible that these non-detections are simply weak masers that are potentially associated with a younger evolutionary phase of MYSOs as hypothesized by Olmi et al. (2014). The sources were chosen to sample various stages of evolution, having similar 21 to 8 micron flux ratios and bolometric luminosities as other MYSOs with previous class II methanol maser detections. We observed all 4 MYSOs with ATCA (~2" resolution) at 10 times deeper sensitivity than previously obtained with the MMB survey and have a spectral resolution of 0.087kms^-1 . The raw data is reduced using the program Miriad (Sault, R. J., et al., 1995) and deconvolutioned using the program CASA (McMullin, J. P., et al. 2007.) We determine one of the four observed MYSOs is harboring a weak class II methanol maser. We discuss the possibility of sensitivity limitations on the remaining sources as well as environmental and evolutionary differences between the sources.

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.

The Proposal of a Evolutionary Strategy Generating the Data Structures Based on a Horizontal Tree for the Tests

NASA Astrophysics Data System (ADS)

Żukowicz, Marek; Markiewicz, Michał

2016-09-01

The aim of the article is to present a mathematical definition of the object model, that is known in computer science as TreeList and to show application of this model for design evolutionary algorithm, that purpose is to generate structures based on this object. The first chapter introduces the reader to the problem of presenting data using the TreeList object. The second chapter describes the problem of testing data structures based on TreeList. The third one shows a mathematical model of the object TreeList and the parameters, used in determining the utility of structures created through this model and in evolutionary strategy, that generates these structures for testing purposes. The last chapter provides a brief summary and plans for future research related to the algorithm presented in the article.

How learning might strengthen existing visual object representations in human object-selective cortex.

PubMed

Brants, Marijke; Bulthé, Jessica; Daniels, Nicky; Wagemans, Johan; Op de Beeck, Hans P

2016-02-15

Visual object perception is an important function in primates which can be fine-tuned by experience, even in adults. Which factors determine the regions and the neurons that are modified by learning is still unclear. Recently, it was proposed that the exact cortical focus and distribution of learning effects might depend upon the pre-learning mapping of relevant functional properties and how this mapping determines the informativeness of neural units for the stimuli and the task to be learned. From this hypothesis we would expect that visual experience would strengthen the pre-learning distributed functional map of the relevant distinctive object properties. Here we present a first test of this prediction in twelve human subjects who were trained in object categorization and differentiation, preceded and followed by a functional magnetic resonance imaging session. Specifically, training increased the distributed multi-voxel pattern information for trained object distinctions in object-selective cortex, resulting in a generalization from pre-training multi-voxel activity patterns to after-training activity patterns. Simulations show that the increased selectivity combined with the inter-session generalization is consistent with a training-induced strengthening of a pre-existing selectivity map. No training-related neural changes were detected in other regions. In sum, training to categorize or individuate objects strengthened pre-existing representations in human object-selective cortex, providing a first indication that the neuroanatomical distribution of learning effects depends upon the pre-learning mapping of visual object properties. Copyright © 2015 Elsevier Inc. All rights reserved.

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

Janowiecki, Steven; Salzer, John J.; Zee, Liese van

We discuss and test possible evolutionary connections between blue compact dwarf galaxies (BCDs) and other types of dwarf galaxies. BCDs provide ideal laboratories to study intense star formation episodes in low-mass dwarf galaxies, and have sometimes been considered a short-lived evolutionary stage between types of dwarf galaxies. To test these connections, we consider a sample of BCDs as well as a comparison sample of nearby galaxies from the Local Volume Legacy (LVL) survey for context. We fit the multi-wavelength spectral energy distributions (SED, far-ultra-violet to far-infrared) of each galaxy with a grid of theoretical models to determine their stellar massesmore » and star formation properties. We compare our results for BCDs with the LVL galaxies to put BCDs in the context of normal galaxy evolution. The SED fits demonstrate that the star formation events currently underway in BCDs are at the extreme of the continuum of normal dwarf galaxies, both in terms of the relative mass involved and in the relative increase over previous star formation rates. Today’s BCDs are distinctive objects in a state of extreme star formation that is rapidly transforming them. This study also suggests ways to identify former BCDs whose star formation episodes have since faded.« less

Adaptive grid based multi-objective Cauchy differential evolution for stochastic dynamic economic emission dispatch with wind power uncertainty

PubMed Central

Lei, Xiaohui; Wang, Chao; Yue, Dong; Xie, Xiangpeng

2017-01-01

Since wind power is integrated into the thermal power operation system, dynamic economic emission dispatch (DEED) has become a new challenge due to its uncertain characteristics. This paper proposes an adaptive grid based multi-objective Cauchy differential evolution (AGB-MOCDE) for solving stochastic DEED with wind power uncertainty. To properly deal with wind power uncertainty, some scenarios are generated to simulate those possible situations by dividing the uncertainty domain into different intervals, the probability of each interval can be calculated using the cumulative distribution function, and a stochastic DEED model can be formulated under different scenarios. For enhancing the optimization efficiency, Cauchy mutation operation is utilized to improve differential evolution by adjusting the population diversity during the population evolution process, and an adaptive grid is constructed for retaining diversity distribution of Pareto front. With consideration of large number of generated scenarios, the reduction mechanism is carried out to decrease the scenarios number with covariance relationships, which can greatly decrease the computational complexity. Moreover, the constraint-handling technique is also utilized to deal with the system load balance while considering transmission loss among thermal units and wind farms, all the constraint limits can be satisfied under the permitted accuracy. After the proposed method is simulated on three test systems, the obtained results reveal that in comparison with other alternatives, the proposed AGB-MOCDE can optimize the DEED problem while handling all constraint limits, and the optimal scheme of stochastic DEED can decrease the conservation of interval optimization, which can provide a more valuable optimal scheme for real-world applications. PMID:28961262

Different characteristics of mesenchymal stem cells isolated from different layers of full term placenta

PubMed Central

Ha, Chul-Won; Kim, Jin A; Heo, Jin-Chul; Han, Woo-Jung; Oh, Soo-Young; Choi, Suk-Joo

2017-01-01

Background The placenta is a very attractive source of mesenchymal stem cells (MSCs) for regenerative medicine due to readily availability, non-invasive acquisition, and avoidance of ethical issues. Isolating MSCs from parts of placenta tissue has obtained growing interest because they are assumed to exhibit different proliferation and differentiation potentials due to complex structures and functions of the placenta. The objective of this study was to isolate MSCs from different parts of the placenta and compare their characteristics. Methods Placenta was divided into amniotic epithelium (AE), amniotic membrane (AM), chorionic membrane (CM), chorionic villi (CV), chorionic trophoblast without villi (CT-V), decidua (DC), and whole placenta (Pla). Cells isolated from each layer were subjected to analyses for their morphology, proliferation ability, surface markers, and multi-lineage differentiation potential. MSCs were isolated from all placental layers and their characteristics were compared. Findings Surface antigen phenotype, morphology, and differentiation characteristics of cells from all layers indicated that they exhibited properties of MSCs. MSCs from different placental layers had different proliferation rates and differentiation potentials. MSCs from CM, CT-V, CV, and DC had better population doubling time and multi-lineage differentiation potentials compared to those from other layers. Conclusions Our results indicate that MSCs with different characteristics can be isolated from all layers of term placenta. These finding suggest that it is necessary to appropriately select MSCs from different placental layers for successful and consistent outcomes in clinical applications. PMID:28225815

Comparative Genomics Study of Multi-Drug-Resistance Mechanisms in the Antibiotic-Resistant Streptococcus suis R61 Strain

PubMed Central

Zhang, Anding; Wu, Jiayan; Chen, Bo; Hua, Yafeng; Yu, Jun; Chen, Huanchun; Xiao, Jingfa; Jin, Meilin

2011-01-01

Background Streptococcus suis infections are a serious problem for both humans and pigs worldwide. The emergence and increasing prevalence of antibiotic-resistant S. suis strains pose significant clinical and societal challenges. Results In our study, we sequenced one multi-drug-resistant S. suis strain, R61, and one S. suis strain, A7, which is fully sensitive to all tested antibiotics. Comparative genomic analysis revealed that the R61 strain is phylogenetically distinct from other S. suis strains, and the genome of R61 exhibits extreme levels of evolutionary plasticity with high levels of gene gain and loss. Our results indicate that the multi-drug-resistant strain R61 has evolved three main categories of resistance. Conclusions Comparative genomic analysis of S. suis strains with diverse drug-resistant phenotypes provided evidence that horizontal gene transfer is an important evolutionary force in shaping the genome of multi-drug-resistant strain R61. In this study, we discovered novel and previously unexamined mutations that are strong candidates for conferring drug resistance. We believe that these mutations will provide crucial clues for designing new drugs against this pathogen. In addition, our work provides a clear demonstration that the use of drugs has driven the emergence of the multi-drug-resistant strain R61. PMID:21966396

Comparative genomics study of multi-drug-resistance mechanisms in the antibiotic-resistant Streptococcus suis R61 strain.

PubMed

Hu, Pan; Yang, Ming; Zhang, Anding; Wu, Jiayan; Chen, Bo; Hua, Yafeng; Yu, Jun; Chen, Huanchun; Xiao, Jingfa; Jin, Meilin

2011-01-01

Streptococcus suis infections are a serious problem for both humans and pigs worldwide. The emergence and increasing prevalence of antibiotic-resistant S. suis strains pose significant clinical and societal challenges. In our study, we sequenced one multi-drug-resistant S. suis strain, R61, and one S. suis strain, A7, which is fully sensitive to all tested antibiotics. Comparative genomic analysis revealed that the R61 strain is phylogenetically distinct from other S. suis strains, and the genome of R61 exhibits extreme levels of evolutionary plasticity with high levels of gene gain and loss. Our results indicate that the multi-drug-resistant strain R61 has evolved three main categories of resistance. Comparative genomic analysis of S. suis strains with diverse drug-resistant phenotypes provided evidence that horizontal gene transfer is an important evolutionary force in shaping the genome of multi-drug-resistant strain R61. In this study, we discovered novel and previously unexamined mutations that are strong candidates for conferring drug resistance. We believe that these mutations will provide crucial clues for designing new drugs against this pathogen. In addition, our work provides a clear demonstration that the use of drugs has driven the emergence of the multi-drug-resistant strain R61.

The Contribution of the Cerebellum in the Hierarchial Development of the Self.

PubMed

Ceylan, Mehmet Emin; Dönmez, Aslıhan; Ülsalver, Barış Önen

2015-12-01

What distinguishes human beings from other living organisms is that a human perceives himself as a "self". The self is developed hierarchially in a multi-layered process, which is based on the evolutionary maturation of the nervous system and patterns according to the rules and demands of the external world. Many researchers have attempted to explain the different aspects of the self, as well as the related neural substrates. In this paper, we first review the previously proposed ideas regarding the neurobiology of the self. We then suggest a new hypothesis regarding the hierarchial self, which proposes that the self is developed at three stages: subjective, objective, and reflective selves. In the second part, we attempt to answer the question "Why do we need a self?" We therefore explain that different parts of the self developed in an effort to identify stability in space, stability against constantly changing objects, and stability against changing cognitions. Finally, we discuss the role of the cerebellum as the neural substrate for the self.

Curious creatures: a multi-taxa investigation of responses to novelty in a zoo environment.

PubMed

Hall, Belinda A; Melfi, Vicky; Burns, Alicia; McGill, David M; Doyle, Rebecca E

2018-01-01

The personality trait of curiosity has been shown to increase welfare in humans. If this positive welfare effect is also true for non-humans, animals with high levels of curiosity may be able to cope better with stressful situations than their conspecifics. Before discoveries can be made regarding the effect of curiosity on an animal's ability to cope in their environment, a way of measuring curiosity across species in different environments must be created to standardise testing. To determine the suitability of novel objects in testing curiosity, species from different evolutionary backgrounds with sufficient sample sizes were chosen. Barbary sheep ( Ammotragus lervia) n  = 12, little penguins ( Eudyptula minor) n  = 10, ringtail lemurs ( Lemur catta) n  = 8 , red tailed black cockatoos ( Calyptorhynchus banksia) n  = 7, Indian star tortoises ( Geochelone elegans) n  = 5 and red kangaroos ( Macropus rufus) n  = 5 were presented with a stationary object, a moving object and a mirror. Having objects with different characteristics increased the likelihood individuals would find at least one motivating. Conspecifics were all assessed simultaneously for time to first orientate towards object (s), latency to make contact (s), frequency of interactions, and total duration of interaction (s). Differences in curiosity were recorded in four of the six species; the Barbary sheep and red tailed black cockatoos did not interact with the novel objects suggesting either a low level of curiosity or that the objects were not motivating for these animals. Variation in curiosity was seen between and within species in terms of which objects they interacted with and how long they spent with the objects. This was determined by the speed in which they interacted, and the duration of interest. By using the measure of curiosity towards novel objects with varying characteristics across a range of zoo species, we can see evidence of evolutionary, husbandry and individual influences on their response. Further work to obtain data on multiple captive populations of a single species using a standardised method could uncover factors that nurture the development of curiosity. In doing so, it would be possible to isolate and modify sub-optimal husbandry practices to improve welfare in the zoo environment.

Curious creatures: a multi-taxa investigation of responses to novelty in a zoo environment

PubMed Central

Melfi, Vicky; Burns, Alicia; McGill, David M.; Doyle, Rebecca E.

2018-01-01

The personality trait of curiosity has been shown to increase welfare in humans. If this positive welfare effect is also true for non-humans, animals with high levels of curiosity may be able to cope better with stressful situations than their conspecifics. Before discoveries can be made regarding the effect of curiosity on an animal’s ability to cope in their environment, a way of measuring curiosity across species in different environments must be created to standardise testing. To determine the suitability of novel objects in testing curiosity, species from different evolutionary backgrounds with sufficient sample sizes were chosen. Barbary sheep (Ammotragus lervia) n = 12, little penguins (Eudyptula minor) n = 10, ringtail lemurs (Lemur catta) n = 8, red tailed black cockatoos (Calyptorhynchus banksia) n = 7, Indian star tortoises (Geochelone elegans) n = 5 and red kangaroos (Macropus rufus) n = 5 were presented with a stationary object, a moving object and a mirror. Having objects with different characteristics increased the likelihood individuals would find at least one motivating. Conspecifics were all assessed simultaneously for time to first orientate towards object (s), latency to make contact (s), frequency of interactions, and total duration of interaction (s). Differences in curiosity were recorded in four of the six species; the Barbary sheep and red tailed black cockatoos did not interact with the novel objects suggesting either a low level of curiosity or that the objects were not motivating for these animals. Variation in curiosity was seen between and within species in terms of which objects they interacted with and how long they spent with the objects. This was determined by the speed in which they interacted, and the duration of interest. By using the measure of curiosity towards novel objects with varying characteristics across a range of zoo species, we can see evidence of evolutionary, husbandry and individual influences on their response. Further work to obtain data on multiple captive populations of a single species using a standardised method could uncover factors that nurture the development of curiosity. In doing so, it would be possible to isolate and modify sub-optimal husbandry practices to improve welfare in the zoo environment. PMID:29568703

Object-oriented biomedical system modelling--the language.

PubMed

Hakman, M; Groth, T

1999-11-01

The paper describes a new object-oriented biomedical continuous system modelling language (OOBSML). It is fully object-oriented and supports model inheritance, encapsulation, and model component instantiation and behaviour polymorphism. Besides the traditional differential and algebraic equation expressions the language includes also formal expressions for documenting models and defining model quantity types and quantity units. It supports explicit definition of model input-, output- and state quantities, model components and component connections. The OOBSML model compiler produces self-contained, independent, executable model components that can be instantiated and used within other OOBSML models and/or stored within model and model component libraries. In this way complex models can be structured as multilevel, multi-component model hierarchies. Technically the model components produced by the OOBSML compiler are executable computer code objects based on distributed object and object request broker technology. This paper includes both the language tutorial and the formal language syntax and semantic description.

Functionality and Evolutionary History of the Chaperonins in Thermophilic Archaea. A Bioinformatical Perspective

NASA Technical Reports Server (NTRS)

Karlin, Samuel

2004-01-01

We used bioinformatics methods to study phylogenetic relations and differentiation patterns of the archaeal chaperonin 60 kDa heat-shock protein (HSP60) genes in support of the study of differential expression patterns of the three chaperonin genes encoded in Sulfolobus shibatae.

An Evolutionary Optimization of the Refueling Simulation for a CANDU Reactor

NASA Astrophysics Data System (ADS)

Do, Q. B.; Choi, H.; Roh, G. H.

2006-10-01

This paper presents a multi-cycle and multi-objective optimization method for the refueling simulation of a 713 MWe Canada deuterium uranium (CANDU-6) reactor based on a genetic algorithm, an elitism strategy and a heuristic rule. The proposed algorithm searches for the optimal refueling patterns for a single cycle that maximizes the average discharge burnup, minimizes the maximum channel power and minimizes the change in the zone controller unit water fills while satisfying the most important safety-related neutronic parameters of the reactor core. The heuristic rule generates an initial population of individuals very close to a feasible solution and it reduces the computing time of the optimization process. The multi-cycle optimization is carried out based on a single cycle refueling simulation. The proposed approach was verified by a refueling simulation of a natural uranium CANDU-6 reactor for an operation period of 6 months at an equilibrium state and compared with the experience-based automatic refueling simulation and the generalized perturbation theory. The comparison has shown that the simulation results are consistent from each other and the proposed approach is a reasonable optimization method of the refueling simulation that controls all the safety-related parameters of the reactor core during the simulation

A mission-oriented orbit design method of remote sensing satellite for region monitoring mission based on evolutionary algorithm

NASA Astrophysics Data System (ADS)

Shen, Xin; Zhang, Jing; Yao, Huang

2015-12-01

Remote sensing satellites play an increasingly prominent role in environmental monitoring and disaster rescue. Taking advantage of almost the same sunshine condition to same place and global coverage, most of these satellites are operated on the sun-synchronous orbit. However, it brings some problems inevitably, the most significant one is that the temporal resolution of sun-synchronous orbit satellite can't satisfy the demand of specific region monitoring mission. To overcome the disadvantages, two methods are exploited: the first one is to build satellite constellation which contains multiple sunsynchronous satellites, just like the CHARTER mechanism has done; the second is to design non-predetermined orbit based on the concrete mission demand. An effective method for remote sensing satellite orbit design based on multiobjective evolution algorithm is presented in this paper. Orbit design problem is converted into a multi-objective optimization problem, and a fast and elitist multi-objective genetic algorithm is utilized to solve this problem. Firstly, the demand of the mission is transformed into multiple objective functions, and the six orbit elements of the satellite are taken as genes in design space, then a simulate evolution process is performed. An optimal resolution can be obtained after specified generation via evolution operation (selection, crossover, and mutation). To examine validity of the proposed method, a case study is introduced: Orbit design of an optical satellite for regional disaster monitoring, the mission demand include both minimizing the average revisit time internal of two objectives. The simulation result shows that the solution for this mission obtained by our method meet the demand the users' demand. We can draw a conclusion that the method presented in this paper is efficient for remote sensing orbit design.

Collaborative Workshops for Assessment and Creation of Multi-Objective Decision Support for Multiple Sectors

NASA Astrophysics Data System (ADS)

Kasprzyk, J. R.; Smith, R.; Raseman, W. J.; DeRousseau, M. A.; Dilling, L.; Ozekin, K.; Summers, R. S.; Balaji, R.; Livneh, B.; Rosario-Ortiz, F.; Sprain, L.; Srubar, W. V., III

2017-12-01

This presentation will report on three projects that used interactive workshops with stakeholders to develop problem formulations for Multi-Objective Evolutionary Algorithm (MOEA)-based decision support in diverse fields - water resources planning, water quality engineering under climate extremes, and sustainable materials design. When combined with a simulation model of a system, MOEAs use intelligent search techniques to provide new plans or designs. This approach is gaining increasing prominence in design and planning for environmental sustainability. To use this technique, a problem formulation - objectives and constraints (quantitative measures of performance) and decision variables (actions that can be modified to improve the system) - must be identified. Although critically important for MOEA effectiveness, the problem formulations are not always developed with stakeholders' interests in mind. To ameliorate this issue, project workshops were organized to improve the tool's relevance as well as collaboratively build problem formulations that can be used in applications. There were interesting differences among the projects, which altered the findings of each workshop. Attendees ranged from a group of water managers on the Front Range of Colorado, to water utility representatives from across the country, to a set of designers, academics, and trade groups. The extent to which the workshop participants were already familiar with simulation tools contributed to their willingness to accept the solutions that were generated using the tool. Moreover, in some instances, brainstorming new objectives to include within the MOEA expanded the scope of the problem formulation, relative to the initial conception of the researchers. Through describing results across a diversity of projects, the goal of this presentation is to report on how our approach may inform future decision support collaboration with a variety of stakeholders and sectors.

Young Stellar Objects in Lynds 1641: Disks and Accretion

NASA Astrophysics Data System (ADS)

Fang, Min; Kim, Jinyoung Serena; van Boekel, Roy; Sicilia-Aguilar, Aurora; Henning, Thomas; Flaherty, Kevin

2013-07-01

We investigate the young stellar objects (YSOs) in the Lynds 1641 (L1641) cloud using multi-wavelength data including Spitzer, WISE, 2MASS, and XMM covering 1390 YSOs across a range of evolutionary stages. In addition, we targeted a sub-sample of YSOs for optical spectroscopy with the MMT/Hectospec and the MMT/Hectochelle. We use this data, along with archival photometric data, to derive spectral types, masses, ages and extinction values. We also use the H_alpha and H_beta lines to derive accretion rates. We calculate the disk fraction as N(II)/N(II+III), where N(II) and N(III) are numbers of Class\\ II and Class\\ III sources, respectively, and obtain a disk fraction of 50% in L1641. We find that the disk frequency is almost constant as a function of stellar mass with a slight peak at log(M_*/M_sun) -0.25. The analysis of multi-epoch data indicates that the accretion variability of YSOs cannot explain the two orders of magnitude of scatter for YSOs with similar masses in the M_acc vs. M_* plot. Forty-six new transition disk objects are confirmed in our spectroscopic survey and we find that the fraction of transition disks that are actively accreting is lower than for optically thick disks (40-45% vs. 77-79% respectively). We confirm our previous result that the accreting YSOs with transition disks have a similar median accretion rate to normal optically thick disks. Analyzing the age distributions of various populations, we find that the diskless YSOs are statistically older than the YSOs with optically-thick disks and the transition disk objects have a median age which is intermediate between the two populations.

Young Stellar Objects in Lynds 1641: Disks, Accretion, and Star Formation History

NASA Astrophysics Data System (ADS)

Fang, Min; Kim, Jinyoung Serena; van Boekel, Roy; Sicilia-Aguilar, Aurora; Henning, Thomas; Flaherty, Kevin

2013-07-01

We investigate the young stellar objects (YSOs) in the Lynds 1641 (L1641) cloud using multi-wavelength data including Spitzer, WISE, the Two Micron All Sky Survey, and XMM covering ~1390 YSOs across a range of evolutionary stages. In addition, we targeted a sub-sample of YSOs for optical spectroscopy with the MMT/Hectospec and the MMT/Hectochelle. We use these data, along with archival photometric data, to derive spectral types, extinction values, masses, ages, and accretion rates. We obtain a disk fraction of ~50% in L1641. The disk frequency is almost constant as a function of stellar mass with a slight peak at log (M */M ⊙) ≈ -0.25. The analysis of multi-epoch spectroscopic data indicates that the accretion variability of YSOs cannot explain the two orders of magnitude of scatter for YSOs with similar masses. Forty-six new transition disk (TD) objects are confirmed in this work, and we find that the fraction of accreting TDs is lower than for optically thick disks (40%-45% versus 77%-79%, respectively). We confirm our previous result that the accreting TDs have a median accretion rate similar to normal optically thick disks. We confirm that two star formation modes (isolated versus clustered) exist in L1641. We find that the diskless YSOs are statistically older than the YSOs with optically thick disks and the TD objects have a median age that is intermediate between those of the other two populations. We tentatively study the star formation history in L1641 based on the age distribution and find that star formation started to be active 2-3 Myr ago.

Producing regionally-relevant multiobjective tradeoffs to engage with Colorado water managers

NASA Astrophysics Data System (ADS)

Smith, R.; Kasprzyk, J. R.; Basdekas, L.; Dilling, L.

2016-12-01

Disseminating results from water resources systems analysis research can be challenging when there are political or regulatory barriers associated with real-world models, or when a research model does not incorporate management context to which practitioners can relate. As part of a larger transdisciplinary study, we developed a broadly-applicable case study in collaboration with our partners at six diverse water utilities in the Front Range of Colorado, USA. Our model, called the "Eldorado Utility Planning Model", incorporates realistic water management decisions and objectives and achieves a pragmatic balance between system complexity and simplicity. Using the sophisticated modeling platform RiverWare, we modeled a spatially distributed regional network in which, under varying climate scenarios, the Eldorado Utility can meet growing demand from its variety of sources and by interacting with other users in the network. In accordance with complicated Front Range water laws, ownership, priority of use, and restricted uses of water are tracked through RiverWare's accounting functionality. To achieve good system performance, Eldorado can make decisions such as expand/build a reservoir, purchase rights from one or more actors, and enact conservation. This presentation introduces the model, and motivates how it can be used to aid researchers in developing multi-objective evolutionary algorithm (MOEA)-based optimization for similar multi-reservoir systems in Colorado and the Western US. Within the optimization, system performance is quantified by 5 objectives: minimizing time in restrictions; new storage capacity; newly developed supply; and uncaptured water; and maximizing year-end storage. Our results demonstrate critical tradeoffs between the objectives and show how these tradeoffs are affected by several realistic climate change scenarios. These results were used within an interactive workshop that helped demonstrate the application of MOEA-based optimization for water management in the western US.

Modelling and multi objective optimization of WEDM of commercially Monel super alloy using evolutionary algorithms

NASA Astrophysics Data System (ADS)

Varun, Sajja; Reddy, Kalakada Bhargav Bal; Vardhan Reddy, R. R. Vishnu

2016-09-01

In this research work, development of a multi response optimization technique has been undertaken, using traditional desirability analysis and non-traditional particle swarm optimization techniques (for different customer's priorities) in wire electrical discharge machining (WEDM). Monel 400 has been selected as work material for experimentation. The effect of key process parameters such as pulse on time (TON), pulse off time (TOFF), peak current (IP), wire feed (WF) were on material removal rate (MRR) and surface roughness(SR) in WEDM operation were investigated. Further, the responses such as MRR and SR were modelled empirically through regression analysis. The developed models can be used by the machinists to predict the MRR and SR over a wide range of input parameters. The optimization of multiple responses has been done for satisfying the priorities of multiple users by using Taguchi-desirability function method and particle swarm optimization technique. The analysis of variance (ANOVA) is also applied to investigate the effect of influential parameters. Finally, the confirmation experiments were conducted for the optimal set of machining parameters, and the betterment has been proved.

[Regeneration of planarians: experimental object].

PubMed

Sheĭman, I M; Kreshchenko, I D

2015-01-01

We discuss the expediency of using invertebrates, such as flatworms and planarians, as experimental objects. Free-living planarian flatworms (phylum Platyhelminthes, class Turbellaria) are invertebrate animals in which a bilateral symmetry appears for the first time in evolution and organs and tissues form. As the highest ecological link of the food chain--predators--these animals are characterized by a set of behavioral reactions controlled by a differentiated central nervous system. Planarians have unsurpassed ability to regenerate lost or damaged body parts. Owing to the ease of their breeding and their convenience for manipulations, these animals are used to study the influence of chemical and physical factors on the processes of life, growth, and reproduction. Currently, planarians are recognized as a model for biological research in the field of regeneration, stem cell biology, study of their proliferation and differentiation, as well as the regulatory mechanisms of morphogenetic processes. The genome of the planarian Schmidtea mediterranea was fully sequenced, which opened up the opportunity to work with this object at the molecular biological level. Furthermore, planarians are used in neurobiological and toxicological studies, in studying the evolutionary aspects of centralization of the nervous system, mechanisms of muscle contraction, and in the development of new antiparasitic drugs. This review aims to demonstrate the relevance and diversity of research conducted on simple biological objects--planarians--to awider audience to show the historical continuity of these studies and their wide geographical distribution and to focus on the studies carried out in Russia, which, as a rule, are not included in the foreign reviews on planarian regeneration.

Proposal for Teaching Evolutionary Biology: A Bridge between Research and Educational Practice

ERIC Educational Resources Information Center

Alvarez Pérez, Eréndira; Ruiz Gutiérrez, Rosaura

2016-01-01

We present quantitative results for the doctoral thesis of the first-named author of this article. The objective was to recommend and test a teaching proposal for core knowledge of evolutionary biology in secondary education. The focus of the study is "Problem cores in teaching". The "Weaving evolutionary thinking" teaching…

Particle swarm optimization: an alternative in marine propeller optimization?

NASA Astrophysics Data System (ADS)

Vesting, F.; Bensow, R. E.

2018-01-01

This article deals with improving and evaluating the performance of two evolutionary algorithm approaches for automated engineering design optimization. Here a marine propeller design with constraints on cavitation nuisance is the intended application. For this purpose, the particle swarm optimization (PSO) algorithm is adapted for multi-objective optimization and constraint handling for use in propeller design. Three PSO algorithms are developed and tested for the optimization of four commercial propeller designs for different ship types. The results are evaluated by interrogating the generation medians and the Pareto front development. The same propellers are also optimized utilizing the well established NSGA-II genetic algorithm to provide benchmark results. The authors' PSO algorithms deliver comparable results to NSGA-II, but converge earlier and enhance the solution in terms of constraints violation.

Using Multi-Objective Optimization to Explore Robust Policies in the Colorado River Basin

NASA Astrophysics Data System (ADS)

Alexander, E.; Kasprzyk, J. R.; Zagona, E. A.; Prairie, J. R.; Jerla, C.; Butler, A.

2017-12-01

The long term reliability of water deliveries in the Colorado River Basin has degraded due to the imbalance of growing demand and dwindling supply. The Colorado River meanders 1,450 miles across a watershed that covers seven US states and Mexico and is an important cultural, economic, and natural resource for nearly 40 million people. Its complex operating policy is based on the "Law of the River," which has evolved since the Colorado River Compact in 1922. Recent (2007) refinements to address shortage reductions and coordinated operations of Lakes Powell and Mead were negotiated with stakeholders in which thousands of scenarios were explored to identify operating guidelines that could ultimately be agreed on. This study explores a different approach to searching for robust operating policies to inform the policy making process. The Colorado River Simulation System (CRSS), a long-term water management simulation model implemented in RiverWare, is combined with the Borg multi-objective evolutionary algorithm (MOEA) to solve an eight objective problem formulation. Basin-wide performance metrics are closely tied to system health through incorporating critical reservoir pool elevations, duration, frequency and quantity of shortage reductions in the objective set. For example, an objective to minimize the frequency that Lake Powell falls below the minimum power pool elevation of 3,490 feet for Glen Canyon Dam protects a vital economic and renewable energy source for the southwestern US. The decision variables correspond to operating tiers in Lakes Powell and Mead that drive the implementation of various shortage and release policies, thus affecting system performance. The result will be a set of non-dominated solutions that can be compared with respect to their trade-offs based on the various objectives. These could inform policy making processes by eliminating dominated solutions and revealing robust solutions that could remain hidden under conventional analysis.

Genetic diversity, structure, and patterns of differentiation in the genus vitis

USDA-ARS?s Scientific Manuscript database

Vitis (Vitaceae) is a taxonomically complicated genus with ca. 60 taxa divided into two subgenera, Vitis and Muscadinia. We used population genetic approaches to gain insights into the genetic diversity, patterns of evolutionary differentiation and to decipher the taxonomic status of some of the con...

On a model of the processes of maintaining a technological area by a manipulator

NASA Astrophysics Data System (ADS)

Ghukasyan, A. A.; Ordyan, A. Ya

2018-04-01

The research refers to the results of mathematical modeling of the process of maintaining a technological area which consists of unstable or fixed objects (targets) and a controlled multi-link manipulator [1–9]. It is assumed that, in the maintenance process, the dynamic characteristics and the phase vector of the manipulator state can change at certain finite times depending on the mass of the cargo or instrument [10, 11]. Some controllability problems are investigated in the case where the manipulator motion on each maintenance interval is described by linear differential equations with constant coefficients and the motions of the objects are given.

Ecological divergence and evolutionary transition of resprouting types in Banksia attenuata.

PubMed

He, Tianhua

2014-08-01

Resprouting is a key functional trait that allows plants to survive diverse disturbances. The fitness benefits associated with resprouting include a rapid return to adult growth, early flowering, and setting seed. The resprouting responses observed following fire are varied, as are the ecological outcomes. Understanding the ecological divergence and evolutionary pathways of different resprouting types and how the environment and genetics interact to drive such morphological evolution represents an important, but under-studied, topic. In the present study, microsatellite markers and microevolutionary approaches were used to better understand: (1) whether genetic differentiation is related to morphological divergence among resprouting types and if so, whether there are any specific genetic variations associated with morphological divergence and (2) the evolutionary pathway of the transitions between two resprouting types in Banksia attenuata (epicormic resprouting from aerial stems or branch; resprouting from a underground lignotuber). The results revealed an association between population genetic differentiation and the morphological divergence of postfire resprouting types in B. attenuata. A microsatellite allele has been shown to be associated with epicormic populations. Approximate Bayesian Computation analysis revealed a likely evolutionary transition from epicormic to lignotuberous resprouting in B. attenuata. It is concluded that the postfire resprouting type in B. attenuata is likely determined by the fire's characteristics. The differentiated expression of postfire resprouting types in different environments is likely a consequence of local genetic adaptation. The capacity to shift the postfire resprouting type to adapt to diverse fire regimes is most likely the key factor explaining why B. attenuata is the most widespread member of the Banksia genus.

Adaptive divergence despite strong genetic drift: genomic analysis of the evolutionary mechanisms causing genetic differentiation in the island fox (Urocyon littoralis)

PubMed Central

FUNK, W. CHRIS; LOVICH, ROBERT E.; HOHENLOHE, PAUL A.; HOFMAN, COURTNEY A.; MORRISON, SCOTT A.; SILLETT, T. SCOTT; GHALAMBOR, CAMERON K.; MALDONADO, JESUS E.; RICK, TORBEN C.; DAY, MITCH D.; POLATO, NICHOLAS R.; FITZPATRICK, SARAH W.; COONAN, TIMOTHY J.; CROOKS, KEVIN R.; DILLON, ADAM; GARCELON, DAVID K.; KING, JULIE L.; BOSER, CHRISTINA L.; GOULD, NICHOLAS; ANDELT, WILLIAM F.

2016-01-01

The evolutionary mechanisms generating the tremendous biodiversity of islands have long fascinated evolutionary biologists. Genetic drift and divergent selection are predicted to be strong on islands and both could drive population divergence and speciation. Alternatively, strong genetic drift may preclude adaptation. We conducted a genomic analysis to test the roles of genetic drift and divergent selection in causing genetic differentiation among populations of the island fox (Urocyon littoralis). This species consists of 6 subspecies, each of which occupies a different California Channel Island. Analysis of 5293 SNP loci generated using Restriction-site Associated DNA (RAD) sequencing found support for genetic drift as the dominant evolutionary mechanism driving population divergence among island fox populations. In particular, populations had exceptionally low genetic variation, small Ne (range = 2.1–89.7; median = 19.4), and significant genetic signatures of bottlenecks. Moreover, islands with the lowest genetic variation (and, by inference, the strongest historical genetic drift) were most genetically differentiated from mainland gray foxes, and vice versa, indicating genetic drift drives genome-wide divergence. Nonetheless, outlier tests identified 3.6–6.6% of loci as high FST outliers, suggesting that despite strong genetic drift, divergent selection contributes to population divergence. Patterns of similarity among populations based on high FST outliers mirrored patterns based on morphology, providing additional evidence that outliers reflect adaptive divergence. Extremely low genetic variation and small Ne in some island fox populations, particularly on San Nicolas Island, suggest that they may be vulnerable to fixation of deleterious alleles, decreased fitness, and reduced adaptive potential. PMID:26992010

Spatial and ecological population genetic structures within two island-endemic Aeonium species of different niche width.

PubMed

Harter, David E V; Thiv, Mike; Weig, Alfons; Jentsch, Anke; Beierkuhnlein, Carl

2015-10-01

The Crassulacean genus Aeonium is a well-known example for plant species radiation on oceanic archipelagos. However, while allopatric speciation among islands is documented for this genus, the role of intra-island speciation due to population divergence by topographical isolation or ecological heterogeneity has not yet been addressed. The aim of this study was to investigate intraspecific genetic structures and to identify spatial and ecological drivers of genetic population differentiation on the island scale. We analyzed inter simple sequence repeat variation within two island-endemic Aeonium species of La Palma: one widespread generalist that covers a large variety of different habitat types (Ae. davidbramwellii) and one narrow ecological specialist (Ae. nobile), in order to assess evolutionary potentials on this island. Gene pool differentiation and genetic diversity patterns were associated with major landscape structures in both species, with phylogeographic implications. However, overall levels of genetic differentiation were low. For the generalist species, outlier loci detection and loci-environment correlation approaches indicated moderate signatures of divergent selection pressures linked to temperature and precipitation variables, while the specialist species missed such patterns. Our data point to incipient differentiation among populations, emphasizing that ecological heterogeneity and topographical structuring within the small scales of an island can foster evolutionary processes. Very likely, such processes have contributed to the radiation of Aeonium on the Canary Islands. There is also support for different evolutionary mechanisms between generalist and specialist species.

Elastography for the differentiation of benign and malignant liver lesions: a meta-analysis.

PubMed

Ma, Xuelei; Zhan, Wenli; Zhang, Binglan; Wei, Benling; Wu, Xin; Zhou, Min; Liu, Lei; Li, Ping

2014-05-01

The objective of this paper was to evaluate the overall accuracy of elastography in the diagnosis of benign and malignant liver lesions by liver biopsy as the gold standard. Literature databases were searched. The studies which were related to evaluate the diagnostic value of elastography for differentiation in benign and malignant liver lesions in English or Chinese were included. The summary receiver operating characteristic (SROC) curve was performed, and the areas under the curve (AUC) were also calculated to present the accuracy of the elastography for the diagnosis of benign and malignant liver lesions. Six studies which included a total of 448 liver lesions in 384 patients were analyzed. The summary sensitivity and specificity of elastography for the differentiation of malignant liver lesions were 85% (95% CI, 80 to 89%) and 84% (95% CI, 80 to 88%), respectively. And the summary diagnostic odds ratio was 46.33 (95% CI, 15.22 to 141.02), and the SROC was 0.9328. Elastography has a high sensitivity and specificity differentiation for benign and malignant liver lesions. As a non-invasive method, it is promising to be applied to clinical practice. To estimate elastography objectively, a large, prospective, international, and multi-center study is still needed.

Geographic variation and genetic structure in Spotted Owls

USGS Publications Warehouse

Haig, Susan M.; Wagner, R.S.; Forsman, E.D.; Mullins, Thomas D.

2001-01-01

We examined genetic variation, population structure, and definition of conservation units in Spotted Owls (Strix occidentalis). Spotted Owls are mostly non-migratory, long-lived, socially monogamous birds that have decreased population viability due to their occupation of highly-fragmented late successional forests in western North America. To investigate potential effects of habitat fragmentation on population structure, we used random amplified polymorphic DNA (RAPD) to examine genetic variation hierarchically among local breeding areas, subregional groups, regional groups, and subspecies via sampling of 21 breeding areas (276 individuals) among the three subspecies of Spotted Owls. Data from 11 variable bands suggest a significant relationship between geographic distance among local breeding groups and genetic distance (Mantel r = 0.53, P < 0.02) although multi-dimensional scaling of three significant axes did not identify significant grouping at any hierarchical level. Similarly, neighbor-joining clustering of Manhattan distances indicated geographic structure at all levels and identified Mexican Spotted Owls as a distinct clade. RAPD analyses did not clearly differentiate Northern Spotted Owls from California Spotted Owls. Among Northern Spotted Owls, estimates of population differentiation (FST) ranged from 0.27 among breeding areas to 0.11 among regions. Concordantly, within-group agreement values estimated via multi-response permutation procedures of Jaccarda??s distances ranged from 0.22 among local sites to 0.11 among regions. Pairwise comparisons of FST and geographic distance within regions suggested only the Klamath region was in equilibrium with respect to gene flow and genetic drift. Merging nuclear data with recent mitochondrial data provides support for designation of an Evolutionary Significant Unit for Mexican Spotted Owls and two overlapping Management Units for Northern and California Spotted Owls.

Insights from life history theory for an explicit treatment of trade-offs in conservation biology.

PubMed

Charpentier, Anne

2015-06-01

As economic and social contexts become more embedded within biodiversity conservation, it becomes obvious that resources are a limiting factor in conservation. This recognition is leading conservation scientists and practitioners to increasingly frame conservation decisions as trade-offs between conflicting societal objectives. However, this framing is all too often done in an intuitive way, rather than by addressing trade-offs explicitly. In contrast, the concept of trade-off is a keystone in evolutionary biology, where it has been investigated extensively. I argue that insights from evolutionary theory can provide methodological and theoretical support to evaluating and quantifying trade-offs in biodiversity conservation. I reviewed the diverse ways in which trade-offs have emerged within the context of conservation and how advances from evolutionary theory can help avoid the main pitfalls of an implicit approach. When studying both evolutionary trade-offs (e.g., reproduction vs. survival) and conservation trade-offs (e.g., biodiversity conservation vs. agriculture), it is crucial to correctly identify the limiting resource, hold constant the amount of this resource when comparing different scenarios, and choose appropriate metrics to quantify the extent to which the objectives have been achieved. Insights from studies in evolutionary theory also reveal how an inadequate selection of conservation solutions may result from considering suboptimal rather than optional solutions when examining whether a trade-off exits between 2 objectives. Furthermore, the shape of a trade-off curve (i.e., whether the relationship between 2 objectives follows a concave, convex, or linear form) is known to affect crucially the definition of optimal solutions in evolutionary biology and very likely affects decisions in biodiversity conservation planning too. This interface between evolutionary biology and biodiversity conservation can therefore provide methodological guidance to support decision makers in the difficult task of choosing among conservation solutions. © 2015 Society for Conservation Biology.

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.

Quantitative Image Informatics for Cancer Research (QIICR) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Imaging has enormous untapped potential to improve cancer research through software to extract and process morphometric and functional biomarkers. In the era of non-cytotoxic treatment agents, multi- modality image-guided ablative therapies and rapidly evolving computational resources, quantitative imaging software can be transformative in enabling minimally invasive, objective and reproducible evaluation of cancer treatment response. Post-processing algorithms are integral to high-throughput analysis and fine- grained differentiation of multiple molecular targets.

Integrated design of the CSI evolutionary structure: A verification of the design methodology

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Joshi, S. M.; Elliott, Kenny B.; Walz, J. E.

1993-01-01

One of the main objectives of the Controls-Structures Interaction (CSI) program is to develop and evaluate integrated controls-structures design methodology for flexible space structures. Thus far, integrated design methodologies for a class of flexible spacecraft, which require fine attitude pointing and vibration suppression with no payload articulation, have been extensively investigated. Various integrated design optimization approaches, such as single-objective optimization, and multi-objective optimization, have been implemented with an array of different objectives and constraints involving performance and cost measures such as total mass, actuator mass, steady-state pointing performance, transient performance, control power, and many more. These studies have been performed using an integrated design software tool (CSI-DESIGN CODE) which is under development by the CSI-ADM team at the NASA Langley Research Center. To date, all of these studies, irrespective of the type of integrated optimization posed or objectives and constraints used, have indicated that integrated controls-structures design results in an overall spacecraft design which is considerably superior to designs obtained through a conventional sequential approach. Consequently, it is believed that validation of some of these results through fabrication and testing of a structure which is designed through an integrated design approach is warranted. The objective of this paper is to present and discuss the efforts that have been taken thus far for the validation of the integrated design methodology.

Biological Races in Humans

PubMed Central

Templeton, Alan R.

2013-01-01

Races may exist in humans in a cultural sense, but biological concepts of race are needed to access their reality in a non-species-specific manner and to see if cultural categories correspond to biological categories within humans. Modern biological concepts of race can be implemented objectively with molecular genetic data through hypothesis-testing. Genetic data sets are used to see if biological races exist in humans and in our closest evolutionary relative, the chimpanzee. Using the two most commonly used biological concepts of race, chimpanzees are indeed subdivided into races but humans are not. Adaptive traits, such as skin color, have frequently been used to define races in humans, but such adaptive traits reflect the underlying environmental factor to which they are adaptive and not overall genetic differentiation, and different adaptive traits define discordant groups. There are no objective criteria for choosing one adaptive trait over another to define race. As a consequence, adaptive traits do not define races in humans. Much of the recent scientific literature on human evolution portrays human populations as separate branches on an evolutionary tree. A tree-like structure among humans has been falsified whenever tested, so this practice is scientifically indefensible. It is also socially irresponsible as these pictorial representations of human evolution have more impact on the general public than nuanced phrases in the text of a scientific paper. Humans have much genetic diversity, but the vast majority of this diversity reflects individual uniqueness and not race. PMID:23684745

3D printing nano conductive multi-walled carbon nanotube scaffolds for nerve regeneration

NASA Astrophysics Data System (ADS)

Lee, Se-Jun; Zhu, Wei; Nowicki, Margaret; Lee, Grace; Nyoung Heo, Dong; Kim, Junghoon; Zuo, Yi Y.; Zhang, Lijie Grace

2018-02-01

Objective. Nanomaterials, such as carbon nanotubes (CNTs), have been introduced to modify the surface properties of scaffolds, thus enhancing the interaction between the neural cells and biomaterials. In addition to superior electrical conductivity, CNTs can provide nanoscale structures similar to those present in the natural neural environment. The primary objective of this study is to investigate the proliferative capability and differential potential of neural stem cells (NSCs) seeded on a CNT incorporated scaffold. Approach. Amine functionalized multi-walled carbon nanotubes (MWCNTs) were incorporated with a PEGDA polymer to provide enhanced electrical properties as well as nanofeatures on the surface of the scaffold. A stereolithography 3D printer was employed to fabricate a well-dispersed MWCNT-hydrogel composite neural scaffold with a tunable porous structure. 3D printing allows easy fabrication of complex 3D scaffolds with extremely intricate microarchitectures and controlled porosity. Main results. Our results showed that MWCNT-incorporated scaffolds promoted neural stem cell proliferation and early neuronal differentiation when compared to those scaffolds without the MWCNTs. Furthermore, biphasic pulse stimulation with 500 µA current promoted neuronal maturity quantified through protein expression analysis by quantitative polymerase chain reaction. Significance. Results of this study demonstrated that an electroconductive MWCNT scaffold, coupled with electrical stimulation, may have a synergistic effect on promoting neurite outgrowth for therapeutic application in nerve regeneration.

Multi-objective optimization for conjunctive water use using coupled hydrogeological and agronomic models: a case study in Heihe mid-reach (China)

NASA Astrophysics Data System (ADS)

LI, Y.; Kinzelbach, W.; Pedrazzini, G.

2017-12-01

Groundwater is a vital water resource to buffer unexpected drought risk in agricultural production, which is however apt to unsustainable exploitation due to its open access characteristic and a much underestimated marginal cost. Being a wicked problem of general water resource management, groundwater staying hidden from surface terrain further amplifies difficulties of management. China has been facing this challenge in last decades, particularly in the northern part where irrigated agriculture resides despite of scarce surface water available compared to the south. Farmers therefore have been increasingly exploiting groundwater as an alternative in order to reach Chinese food self-sufficiency requirements and feed fast socio-economic development. In this work, we studied Heihe mid-reach located in northern China, which represents one of a few regions suffering from symptoms of unsustainable groundwater use, such as a large drawdown of the groundwater table in some irrigation districts, or soil salinization due to phreatic evaporation in others. In addition, we focus on solving a multi-objective optimization problem of conjunctive water use in order to find an alternative management scheme that fits decision makers' preference. The methodology starts with a global sensitivity analysis to determine the most influential decision variables. Then a state-of-the-art multi-objective evolutionary algorithm (MOEA) is employed to search a hyper-dimensional Pareto Front. The aquifer system is simulated with a distributed Modflow model, which is able to capture the main phenomenon of interest. Results show that the current water allocation scheme seems to exploit the water resources in an inefficient way, where areas with depression cones and areas with salinization or groundwater table rise can both be mitigated with an alternative management scheme. When assuming uncertain boundary conditions according to future climate change, the optimal solutions can yield better performance in economical productivity by reducing opportunity cost under unexpected drought conditions.

Phosphorene/rhenium disulfide heterojunction-based negative differential resistance device for multi-valued logic

NASA Astrophysics Data System (ADS)

Shim, Jaewoo; Oh, Seyong; Kang, Dong-Ho; Jo, Seo-Hyeon; Ali, Muhammad Hasnain; Choi, Woo-Young; Heo, Keun; Jeon, Jaeho; Lee, Sungjoo; Kim, Minwoo; Song, Young Jae; Park, Jin-Hong

2016-11-01

Recently, negative differential resistance devices have attracted considerable attention due to their folded current-voltage characteristic, which presents multiple threshold voltage values. Because of this remarkable property, studies associated with the negative differential resistance devices have been explored for realizing multi-valued logic applications. Here we demonstrate a negative differential resistance device based on a phosphorene/rhenium disulfide (BP/ReS2) heterojunction that is formed by type-III broken-gap band alignment, showing high peak-to-valley current ratio values of 4.2 and 6.9 at room temperature and 180 K, respectively. Also, the carrier transport mechanism of the BP/ReS2 negative differential resistance device is investigated in detail by analysing the tunnelling and diffusion currents at various temperatures with the proposed analytic negative differential resistance device model. Finally, we demonstrate a ternary inverter as a multi-valued logic application. This study of a two-dimensional material heterojunction is a step forward toward future multi-valued logic device research.

Phosphorene/rhenium disulfide heterojunction-based negative differential resistance device for multi-valued logic

PubMed Central

Shim, Jaewoo; Oh, Seyong; Kang, Dong-Ho; Jo, Seo-Hyeon; Ali, Muhammad Hasnain; Choi, Woo-Young; Heo, Keun; Jeon, Jaeho; Lee, Sungjoo; Kim, Minwoo; Song, Young Jae; Park, Jin-Hong

2016-01-01

Recently, negative differential resistance devices have attracted considerable attention due to their folded current–voltage characteristic, which presents multiple threshold voltage values. Because of this remarkable property, studies associated with the negative differential resistance devices have been explored for realizing multi-valued logic applications. Here we demonstrate a negative differential resistance device based on a phosphorene/rhenium disulfide (BP/ReS2) heterojunction that is formed by type-III broken-gap band alignment, showing high peak-to-valley current ratio values of 4.2 and 6.9 at room temperature and 180 K, respectively. Also, the carrier transport mechanism of the BP/ReS2 negative differential resistance device is investigated in detail by analysing the tunnelling and diffusion currents at various temperatures with the proposed analytic negative differential resistance device model. Finally, we demonstrate a ternary inverter as a multi-valued logic application. This study of a two-dimensional material heterojunction is a step forward toward future multi-valued logic device research. PMID:27819264

Speciation on oceanic islands: rapid adaptive divergence vs. cryptic speciation in a Guadalupe Island songbird (Aves: Junco).

PubMed

Aleixandre, Pau; Hernández Montoya, Julio; Milá, Borja

2013-01-01

The evolutionary divergence of island populations, and in particular the tempo and relative importance of neutral and selective factors, is of central interest to the study of speciation. The rate of phenotypic evolution upon island colonization can vary greatly among taxa, and cases of convergent evolution can further confound the inference of correct evolutionary histories. Given the potential lability of phenotypic characters, molecular dating of insular lineages analyzed in a phylogenetic framework provides a critical tool to test hypotheses of phenotypic divergence since colonization. The Guadalupe junco is the only insular form of the polymorphic dark-eyed junco (Junco hyemalis), and shares eye and plumage color with continental morphs, yet presents an enlarged bill and reduced body size. Here we use variation in mtDNA sequence, morphological traits and song variables to test whether the Guadalupe junco evolved rapidly following a recent colonization by a mainland form of the dark-eyed junco, or instead represents a well-differentiated "cryptic" lineage adapted to the insular environment through long-term isolation, with plumage coloration a result of evolutionary convergence. We found high mtDNA divergence of the island lineage with respect to both continental J. hyemalis and J. phaeonotus, representing a history of isolation of about 600,000 years. The island lineage was also significantly differentiated in morphological and male song variables. Moreover, and contrary to predictions regarding diversity loss on small oceanic islands, we document relatively high levels of both haplotypic and song-unit diversity on Guadalupe Island despite long-term isolation in a very small geographic area. In contrast to prevailing taxonomy, the Guadalupe junco is an old, well-differentiated evolutionary lineage, whose similarity to mainland juncos in plumage and eye color is due to evolutionary convergence. Our findings confirm the role of remote islands in driving divergence and speciation, but also their potential role as repositories of ancestral diversity.

How Much Can Evolutionary Psychology Inform the Educational Sciences?

ERIC Educational Resources Information Center

Halpern, Diane F.

2008-01-01

In response to a stimulating article by David C. Geary on the value of understanding the evolutionary basis of learning as a guide to instruction, I raise several objections. When evolutionary theory is used to explain everything from sex differences in math and reading to why children are bored in school, it loses its explanatory power. There is…

Transverse field focused system

DOEpatents

Anderson, O.A.

1983-06-01

It is an object of the invention to provide a transport apparatus for a high current negative-ion beam which will bend the beam around corners through a baffled path in a differential pump or a neutron trap. It is another object of the invention to provide a transport apparatus for a high current negative-ion beam which will allow gas molecules in the beam to exit outwardly from the transport apparatus. A further object of the invention is to provide a multi-stage accelerator for a high current negative-ion beam which will enable acceleration of the beam to very high energy levels with a minimum loss of current carrying capacity. A still further object of the invention is to provide an apparatus for transport or accelertion of a sheet beam of negative ions which is shaped to confine the beam against divergence or expansion.

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

PubMed Central

Nguyen, Nga Thi Thuy; Vincens, Pierre

2018-01-01

Abstract Since 2010, the Genomicus web server is available online at http://genomicus.biologie.ens.fr/genomicus. This graphical browser provides access to comparative genomic analyses in four different phyla (Vertebrate, Plants, Fungi, and non vertebrate Metazoans). Users can analyse genomic information from extant species, as well as ancestral gene content and gene order for vertebrates and flowering plants, in an integrated evolutionary context. New analyses and visualization tools have recently been implemented in Genomicus Vertebrate. Karyotype structures from several genomes can now be compared along an evolutionary pathway (Multi-KaryotypeView), and synteny blocks can be computed and visualized between any two genomes (PhylDiagView). PMID:29087490

Landscape community genomics: understanding eco-evolutionary processes in complex environments

USGS Publications Warehouse

Hand, Brian K.; Lowe, Winsor H.; Kovach, Ryan P.; Muhlfeld, Clint C.; Luikart, Gordon

2015-01-01

Extrinsic factors influencing evolutionary processes are often categorically lumped into interactions that are environmentally (e.g., climate, landscape) or community-driven, with little consideration of the overlap or influence of one on the other. However, genomic variation is strongly influenced by complex and dynamic interactions between environmental and community effects. Failure to consider both effects on evolutionary dynamics simultaneously can lead to incomplete, spurious, or erroneous conclusions about the mechanisms driving genomic variation. We highlight the need for a landscape community genomics (LCG) framework to help to motivate and challenge scientists in diverse fields to consider a more holistic, interdisciplinary perspective on the genomic evolution of multi-species communities in complex environments.

Evolutionary grinding model for nanometric control of surface roughness for aspheric optical surfaces.

PubMed

Han, Jeong-Yeol; Kim, Sug-Whan; Han, Inwoo; Kim, Geon-Hee

2008-03-17

A new evolutionary grinding process model has been developed for nanometric control of material removal from an aspheric surface of Zerodur substrate. The model incorporates novel control features such as i) a growing database; ii) an evolving, multi-variable regression equation; and iii) an adaptive correction factor for target surface roughness (Ra) for the next machine run. This process model demonstrated a unique evolutionary controllability of machining performance resulting in the final grinding accuracy (i.e. averaged difference between target and measured surface roughness) of -0.2+/-2.3(sigma) nm Ra over seven trial machine runs for the target surface roughness ranging from 115 nm to 64 nm Ra.

Evolution of Microbial Quorum Sensing to Human Global Quorum Sensing: An Insight into How Gap Junctional Intercellular Communication Might Be Linked to the Global Metabolic Disease Crisis.

PubMed

Trosko, James E

2016-06-15

The first anaerobic organism extracted energy for survival and reproduction from its source of nutrients, with the genetic means to ensure protection of its individual genome but also its species survival. While it had a means to communicate with its community via simple secreted molecules ("quorum sensing"), the eventual shift to an aerobic environment led to multi-cellular metazoan organisms, with evolutionary-selected genes to form extracellular matrices, stem cells, stem cell niches, and a family of gap junction or "connexin" genes. These germinal and somatic stem cells responded to extracellular signals that triggered intra-cellular signaling to regulate specific genes out of the total genome. These extra-cellular induced intra-cellular signals also modulated gap junctional intercellular communication (GJIC) in order to regulate the new cellular functions of symmetrical and asymmetrical cell division, cell differentiation, modes of cell death, and senescence. Within the hierarchical and cybernetic concepts, differentiated by neurons organized in the brain of the Homo sapiens, the conscious mind led to language, abstract ideas, technology, myth-making, scientific reasoning, and moral decision-making, i.e., the creation of culture. Over thousands of years, this has created the current collision between biological and cultural evolution, leading to the global "metabolic disease" crisis.

Comparative genomic analysis of Helicobacter pylori from Malaysia identifies three distinct lineages suggestive of differential evolution

PubMed Central

Kumar, Narender; Mariappan, Vanitha; Baddam, Ramani; Lankapalli, Aditya K.; Shaik, Sabiha; Goh, Khean-Lee; Loke, Mun Fai; Perkins, Tim; Benghezal, Mohammed; Hasnain, Seyed E.; Vadivelu, Jamuna; Marshall, Barry J.; Ahmed, Niyaz

2015-01-01

The discordant prevalence of Helicobacter pylori and its related diseases, for a long time, fostered certain enigmatic situations observed in the countries of the southern world. Variation in H. pylori infection rates and disease outcomes among different populations in multi-ethnic Malaysia provides a unique opportunity to understand dynamics of host–pathogen interaction and genome evolution. In this study, we extensively analyzed and compared genomes of 27 Malaysian H. pylori isolates and identified three major phylogeographic lineages: hspEastAsia, hpEurope and hpSouthIndia. The analysis of the virulence genes within the core genome, however, revealed a comparable pathogenic potential of the strains. In addition, we identified four genes limited to strains of East-Asian lineage. Our analyses identified a few strain-specific genes encoding restriction modification systems and outlined 311 core genes possibly under differential evolutionary constraints, among the strains representing different ethnic groups. The cagA and vacA genes also showed variations in accordance with the host genetic background of the strains. Moreover, restriction modification genes were found to be significantly enriched in East-Asian strains. An understanding of these variations in the genome content would provide significant insights into various adaptive and host modulation strategies harnessed by H. pylori to effectively persist in a host-specific manner. PMID:25452339

Population differentiation in the context of Holocene climate change for a migratory marine species, the southern elephant seal.

PubMed

Corrigan, L J; Fabiani, A; Chauke, L F; McMahon, C R; de Bruyn, M; Bester, M N; Bastos, A; Campagna, C; Muelbert, M M C; Hoelzel, A R

2016-09-01

Understanding observed patterns of connectivity requires an understanding of the evolutionary processes that determine genetic structure among populations, with the most common models being associated with isolation by distance, allopatry or vicariance. Pinnipeds are annual breeders with the capacity for extensive range overlap during seasonal migrations, establishing the potential for the evolution of isolation by distance. Here, we assess the pattern of differentiation among six breeding colonies of the southern elephant seal, Mirounga leonina, based on mtDNA and 15 neutral microsatellite DNA markers, and consider measures of their demography and connectivity. We show that all breeding colonies are genetically divergent and that connectivity in this highly mobile pinniped is not strongly associated with geographic distance, but more likely linked to Holocene climate change and demographic processes. Estimates of divergence times between populations were all after the last glacial maximum, and there was evidence for directional migration in a clockwise pattern (with the prevailing current) around the Antarctic. We discuss the mechanisms by which climate change may have contributed to the contemporary genetic structure of southern elephant seal populations and the broader implications. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Transcriptional analysis reveals the critical role of RNA polymerase-binding transcription factor, DksA, in regulating multi-drug resistance of Escherichia coli.

PubMed

Wang, Jiawei; Cao, Li; Yang, Xiaowen; Wu, Qingmin; Lu, Lin; Wang, Zhen

2018-05-07

The objective of this study was to comprehensively identify the target genes regulated by the RNA polymerase-binding transcription factor DksA in Escherichia coli, and to clarify the role of DksA in multi-drug resistance. A clinical E. coli strain, E8, was selected to construct the dksA gene deletion mutant by using the Red recombination system. The minimum inhibitory concentrations (MICs) of 12 antibiotics in the E8ΔdksA (mutant) were markedly lower than those in the wild-type strain, E8. Genes differentially expressed in the wild-type and dksA mutant were detected using RNA-Seq and were validated by performing quantitative real-time PCR (qRT-PCR). In total, 168 differentially expressed genes were identified in E8ΔdksA, including 81 up-regulated and 87 down-regulated genes. Many of the genes identified are involved in metabolism, two-component systems, transcriptional regulators, and transport/membrane proteins. Interestingly, genes encoding the transcriptional regulator, MarR, which is known to repress the multiple drug resistance operon, marRAB; MdfA, a transport protein that exhibits multidrug efflux activities; oligopeptide transport system proteins OppA and OppD were among those differentially expressed, and could potentially contribute to the increased drug susceptibility of E8ΔdksA. In conclusion, DksA plays an important role in the multi-drug resistance of this E. coli strain, and directly or indirectly regulates the expression of several genes related to antibiotic resistance. Copyright © 2018. Published by Elsevier B.V.

Assessment of Surface Air Temperature over China Using Multi-criterion Model Ensemble Framework

NASA Astrophysics Data System (ADS)

Li, J.; Zhu, Q.; Su, L.; He, X.; Zhang, X.

2017-12-01

The General Circulation Models (GCMs) are designed to simulate the present climate and project future trends. It has been noticed that the performances of GCMs are not always in agreement with each other over different regions. Model ensemble techniques have been developed to post-process the GCMs' outputs and improve their prediction reliabilities. To evaluate the performances of GCMs, root-mean-square error, correlation coefficient, and uncertainty are commonly used statistical measures. However, the simultaneous achievements of these satisfactory statistics cannot be guaranteed when using many model ensemble techniques. Meanwhile, uncertainties and future scenarios are critical for Water-Energy management and operation. In this study, a new multi-model ensemble framework was proposed. It uses a state-of-art evolutionary multi-objective optimization algorithm, termed Multi-Objective Complex Evolution Global Optimization with Principle Component Analysis and Crowding Distance (MOSPD), to derive optimal GCM ensembles and demonstrate the trade-offs among various solutions. Such trade-off information was further analyzed with a robust Pareto front with respect to different statistical measures. A case study was conducted to optimize the surface air temperature (SAT) ensemble solutions over seven geographical regions of China for the historical period (1900-2005) and future projection (2006-2100). The results showed that the ensemble solutions derived with MOSPD algorithm are superior over the simple model average and any single model output during the historical simulation period. For the future prediction, the proposed ensemble framework identified that the largest SAT change would occur in the South Central China under RCP 2.6 scenario, North Eastern China under RCP 4.5 scenario, and North Western China under RCP 8.5 scenario, while the smallest SAT change would occur in the Inner Mongolia under RCP 2.6 scenario, South Central China under RCP 4.5 scenario, and South Central China under RCP 8.5 scenario.

Multi-target drugs to address multiple checkpoints in complex inflammatory pathologies: evolutionary cues for novel "first-in-class" anti-inflammatory drug candidates: a reviewer's perspective.

PubMed

Mathew, Geetha; Unnikrishnan, M K

2015-10-01

Inflammation is a complex, metabolically expensive process involving multiple signaling pathways and regulatory mechanisms which have evolved over evolutionary timescale. Addressing multiple targets of inflammation holistically, in moderation, is probably a more evolutionarily viable strategy, as compared to current therapy which addresses drug targets in isolation. Polypharmacology, addressing multiple targets, is commonly used in complex ailments, suggesting the superior safety and efficacy profile of multi-target (MT) drugs. Phenotypic drug discovery, which generated successful MT and first-in-class drugs in the past, is now re-emerging. A multi-pronged approach, which modulates the evolutionarily conserved, robust and pervasive cellular mechanisms of tissue repair, with AMPK at the helm, regulating the complex metabolic/immune/redox pathways underlying inflammation, is perhaps a more viable strategy than addressing single targets in isolation. Molecules that modulate multiple molecular mechanisms of inflammation in moderation (modulating TH cells toward the anti-inflammatory phenotype, activating AMPK, stimulating Nrf2 and inhibiting NFκB) might serve as a model for a novel Darwinian "first-in-class" therapeutic category that holistically addresses immune, redox and metabolic processes associated with inflammatory repair. Such a multimodal biological activity is supported by the fact that several non-calorific pleiotropic natural products with anti-inflammatory action have been incorporated into diet (chiefly guided by the adaptive development of olfacto-gustatory preferences over evolutionary timescales) rendering such molecules, endowed with evolutionarily privileged molecular scaffolds, naturally oriented toward multiple targets.

Adaptive surrogate model based multi-objective transfer trajectory optimization between different libration points

NASA Astrophysics Data System (ADS)

Peng, Haijun; Wang, Wei

2016-10-01

An adaptive surrogate model-based multi-objective optimization strategy that combines the benefits of invariant manifolds and low-thrust control toward developing a low-computational-cost transfer trajectory between libration orbits around the L1 and L2 libration points in the Sun-Earth system has been proposed in this paper. A new structure for a multi-objective transfer trajectory optimization model that divides the transfer trajectory into several segments and gives the dominations for invariant manifolds and low-thrust control in different segments has been established. To reduce the computational cost of multi-objective transfer trajectory optimization, a mixed sampling strategy-based adaptive surrogate model has been proposed. Numerical simulations show that the results obtained from the adaptive surrogate-based multi-objective optimization are in agreement with the results obtained using direct multi-objective optimization methods, and the computational workload of the adaptive surrogate-based multi-objective optimization is only approximately 10% of that of direct multi-objective optimization. Furthermore, the generating efficiency of the Pareto points of the adaptive surrogate-based multi-objective optimization is approximately 8 times that of the direct multi-objective optimization. Therefore, the proposed adaptive surrogate-based multi-objective optimization provides obvious advantages over direct multi-objective optimization methods.

Optimisation of Ferrochrome Addition Using Multi-Objective Evolutionary and Genetic Algorithms for Stainless Steel Making via AOD Converter

NASA Astrophysics Data System (ADS)

Behera, Kishore Kumar; Pal, Snehanshu

2018-03-01

This paper describes a new approach towards optimum utilisation of ferrochrome added during stainless steel making in AOD converter. The objective of optimisation is to enhance end blow chromium content of steel and reduce the ferrochrome addition during refining. By developing a thermodynamic based mathematical model, a study has been conducted to compute the optimum trade-off between ferrochrome addition and end blow chromium content of stainless steel using a predator prey genetic algorithm through training of 100 dataset considering different input and output variables such as oxygen, argon, nitrogen blowing rate, duration of blowing, initial bath temperature, chromium and carbon content, weight of ferrochrome added during refining. Optimisation is performed within constrained imposed on the input parameters whose values fall within certain ranges. The analysis of pareto fronts is observed to generate a set of feasible optimal solution between the two conflicting objectives that provides an effective guideline for better ferrochrome utilisation. It is found out that after a certain critical range, further addition of ferrochrome does not affect the chromium percentage of steel. Single variable response analysis is performed to study the variation and interaction of all individual input parameters on output variables.

Diversity and distribution of genetic variation in gammarids: Comparing patterns between invasive and non-invasive species.

PubMed

Baltazar-Soares, Miguel; Paiva, Filipa; Chen, Yiyong; Zhan, Aibin; Briski, Elizabeta

2017-10-01

Biological invasions are worldwide phenomena that have reached alarming levels among aquatic species. There are key challenges to understand the factors behind invasion propensity of non-native populations in invasion biology. Interestingly, interpretations cannot be expanded to higher taxonomic levels due to the fact that in the same genus, there are species that are notorious invaders and those that never spread outside their native range. Such variation in invasion propensity offers the possibility to explore, at fine-scale taxonomic level, the existence of specific characteristics that might predict the variability in invasion success. In this work, we explored this possibility from a molecular perspective. The objective was to provide a better understanding of the genetic diversity distribution in the native range of species that exhibit contrasting invasive propensities. For this purpose, we used a total of 784 sequences of the cytochrome c oxidase subunit I of mitochondrial DNA (mtDNA-COI) collected from seven Gammaroidea, a superfamily of Amphipoda that includes species that are both successful invaders ( Gammarus tigrinus , Pontogammarus maeoticus, and Obesogammarus crassus ) and strictly restricted to their native regions ( Gammarus locusta , Gammarus salinus , Gammarus zaddachi, and Gammarus oceanicus ). Despite that genetic diversity did not differ between invasive and non-invasive species, we observed that populations of non-invasive species showed a higher degree of genetic differentiation. Furthermore, we found that both geographic and evolutionary distances might explain genetic differentiation in both non-native and native ranges. This suggests that the lack of population genetic structure may facilitate the distribution of mutations that despite arising in the native range may be beneficial in invasive ranges. The fact that evolutionary distances explained genetic differentiation more often than geographic distances points toward that deep lineage divergence holds an important role in the distribution of neutral genetic diversity.

Our Preferences: Why We Like What We Like

NASA Astrophysics Data System (ADS)

Grammer, Karl; Oberzaucher, Elisabeth

Humans tend to judge and sort their social and non-social environment permanently into a few basic categories: 'likes' and 'don't likes'. Indeed we have developed general preferences for our social and non-social environment. These preferences can be subsumed under the term 'evolutionary aesthetics' (Voland & Grammer 2003). Indeed humans and animals have evolved preferences for mates, food, habitats, odors, and objects. Those stimuli that promoted reproductive success are bound to evoke positive emotional responses, and humans develop an obsession-like attitude towards aesthetics and beauty. Although we are 'all legally equal', people are often treated differently according to their physical appearance. This differential treatment by others starts early in life. Three-month-old children gaze longer at attractive faces than at unattractive faces. From these results, Langlois et al. (1990) conclude that beauty standards are not learned, but that there is an innate beauty detector. Attractive children receive less punishment than unattractive children for the same types of misbehavior. Differential treatment goes on at school, college, and even university (Baugh & Parry 1991). In this part of our lives attractiveness is coupled to academic achievements - attractive students receive better grades. Even when we apply for jobs, appearance may dominate qualification (Collins & Zebrowitz 1995). This differential treatment reaches its peak perhaps in jurisdiction, where attractiveness can lead to better treatment and lighter sentences. However, this is only the case if attractiveness did not play a role in the crime (Hateld & Sprecher 1986). We even believe that attractive people are better - 'what is beautiful is good' is a common standard in our thinking, according to Dion et al. (1972). The question then arises: Where does this obsessive preoccupation with beauty and attractiveness come from?We will outline here the thesis that human mate selection criteria, which have evolved through human evolutionary history, are responsible for shaping our perception of attractiveness and beauty.

A New Algorithm Using the Non-Dominated Tree to Improve Non-Dominated Sorting.

PubMed

Gustavsson, Patrik; Syberfeldt, Anna

2018-01-01

Non-dominated sorting is a technique often used in evolutionary algorithms to determine the quality of solutions in a population. The most common algorithm is the Fast Non-dominated Sort (FNS). This algorithm, however, has the drawback that its performance deteriorates when the population size grows. The same drawback applies also to other non-dominating sorting algorithms such as the Efficient Non-dominated Sort with Binary Strategy (ENS-BS). An algorithm suggested to overcome this drawback is the Divide-and-Conquer Non-dominated Sort (DCNS) which works well on a limited number of objectives but deteriorates when the number of objectives grows. This article presents a new, more efficient algorithm called the Efficient Non-dominated Sort with Non-Dominated Tree (ENS-NDT). ENS-NDT is an extension of the ENS-BS algorithm and uses a novel Non-Dominated Tree (NDTree) to speed up the non-dominated sorting. ENS-NDT is able to handle large population sizes and a large number of objectives more efficiently than existing algorithms for non-dominated sorting. In the article, it is shown that with ENS-NDT the runtime of multi-objective optimization algorithms such as the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) can be substantially reduced.

Economic game theory for mutualism and cooperation.

PubMed

Archetti, Marco; Scheuring, István; Hoffman, Moshe; Frederickson, Megan E; Pierce, Naomi E; Yu, Douglas W

2011-12-01

We review recent work at the interface of economic game theory and evolutionary biology that provides new insights into the evolution of partner choice, host sanctions, partner fidelity feedback and public goods. (1) The theory of games with asymmetrical information shows that the right incentives allow hosts to screen-out parasites and screen-in mutualists, explaining successful partner choice in the absence of signalling. Applications range from ant-plants to microbiomes. (2) Contract theory distinguishes two longstanding but weakly differentiated explanations of host response to defectors: host sanctions and partner fidelity feedback. Host traits that selectively punish misbehaving symbionts are parsimoniously interpreted as pre-adaptations. Yucca-moth and legume-rhizobia mutualisms are argued to be examples of partner fidelity feedback. (3) The theory of public goods shows that cooperation in multi-player interactions can evolve in the absence of assortment, in one-shot social dilemmas among non-kin. Applications include alarm calls in vertebrates and exoenzymes in microbes. 2011 Blackwell Publishing Ltd/CNRS.

Computer modeling describes gravity-related adaptation in cell cultures.

PubMed

Alexandrov, Ludmil B; Alexandrova, Stoyana; Usheva, Anny

2009-12-16

Questions about the changes of biological systems in response to hostile environmental factors are important but not easy to answer. Often, the traditional description with differential equations is difficult due to the overwhelming complexity of the living systems. Another way to describe complex systems is by simulating them with phenomenological models such as the well-known evolutionary agent-based model (EABM). Here we developed an EABM to simulate cell colonies as a multi-agent system that adapts to hyper-gravity in starvation conditions. In the model, the cell's heritable characteristics are generated and transferred randomly to offspring cells. After a qualitative validation of the model at normal gravity, we simulate cellular growth in hyper-gravity conditions. The obtained data are consistent with previously confirmed theoretical and experimental findings for bacterial behavior in environmental changes, including the experimental data from the microgravity Atlantis and the Hypergravity 3000 experiments. Our results demonstrate that it is possible to utilize an EABM with realistic qualitative description to examine the effects of hypergravity and starvation on complex cellular entities.

The Relationship Between College Zoology Students' Religious Beliefs and Their Ability to Objectively View the Scientific Evidence Supporting Evolutionary Theory.

ERIC Educational Resources Information Center

Sinclair, Anne; Baldwin, Beatrice

An anonymous 12-item, multiple-choice questionnaire was administered to 218 southern college, introductory zoology students prior to and following a study of evolutionary theory to assess their understanding and acceptance of the credibility of the evidence supporting the theory. Key topics addressed were the history of evolutionary thought, basic…

Universal scaling in the branching of the tree of life.

PubMed

Herrada, E Alejandro; Tessone, Claudio J; Klemm, Konstantin; Eguíluz, Víctor M; Hernández-García, Emilio; Duarte, Carlos M

2008-07-23

Understanding the patterns and processes of diversification of life in the planet is a key challenge of science. The Tree of Life represents such diversification processes through the evolutionary relationships among the different taxa, and can be extended down to intra-specific relationships. Here we examine the topological properties of a large set of interspecific and intraspecific phylogenies and show that the branching patterns follow allometric rules conserved across the different levels in the Tree of Life, all significantly departing from those expected from the standard null models. The finding of non-random universal patterns of phylogenetic differentiation suggests that similar evolutionary forces drive diversification across the broad range of scales, from macro-evolutionary to micro-evolutionary processes, shaping the diversity of life on the planet.

Evolution and Christian Faith

NASA Astrophysics Data System (ADS)

Roughgarden, J. E.

2006-12-01

My recent book, Evolution and Christian Faith explores how evolutionary biology can be portrayed from the religious perspective of Christianity. The principal metaphors for evolutionary biology---differential success at breeding and random mutation, probably originate with the dawn of agriculture and clearly occur in the Bible. The central narrative of evolutionary biology can be presented using Biblical passages, providing an account of evolution that is inherently friendly to a Christian perspective. Still, evolutionary biology is far from complete, and problematic areas pertain to species in which the concept of an individual is poorly defined, and to species in which the expression of gender and sexuality depart from Darwin's sexual-selection templates. The present- day controversy in the US about teaching evolution in the schools provides an opportunity to engage the public about science education.

Reliable Multi-Label Learning via Conformal Predictor and Random Forest for Syndrome Differentiation of Chronic Fatigue in Traditional Chinese Medicine

PubMed Central

Wang, Huazhen; Liu, Xin; Lv, Bing; Yang, Fan; Hong, Yanzhu

2014-01-01

Objective Chronic Fatigue (CF) still remains unclear about its etiology, pathophysiology, nomenclature and diagnostic criteria in the medical community. Traditional Chinese medicine (TCM) adopts a unique diagnostic method, namely ‘bian zheng lun zhi’ or syndrome differentiation, to diagnose the CF with a set of syndrome factors, which can be regarded as the Multi-Label Learning (MLL) problem in the machine learning literature. To obtain an effective and reliable diagnostic tool, we use Conformal Predictor (CP), Random Forest (RF) and Problem Transformation method (PT) for the syndrome differentiation of CF. Methods and Materials In this work, using PT method, CP-RF is extended to handle MLL problem. CP-RF applies RF to measure the confidence level (p-value) of each label being the true label, and then selects multiple labels whose p-values are larger than the pre-defined significance level as the region prediction. In this paper, we compare the proposed CP-RF with typical CP-NBC(Naïve Bayes Classifier), CP-KNN(K-Nearest Neighbors) and ML-KNN on CF dataset, which consists of 736 cases. Specifically, 95 symptoms are used to identify CF, and four syndrome factors are employed in the syndrome differentiation, including ‘spleen deficiency’, ‘heart deficiency’, ‘liver stagnation’ and ‘qi deficiency’. The Results CP-RF demonstrates an outstanding performance beyond CP-NBC, CP-KNN and ML-KNN under the general metrics of subset accuracy, hamming loss, one-error, coverage, ranking loss and average precision. Furthermore, the performance of CP-RF remains steady at the large scale of confidence levels from 80% to 100%, which indicates its robustness to the threshold determination. In addition, the confidence evaluation provided by CP is valid and well-calibrated. Conclusion CP-RF not only offers outstanding performance but also provides valid confidence evaluation for the CF syndrome differentiation. It would be well applicable to TCM practitioners and facilitate the utilities of objective, effective and reliable computer-based diagnosis tool. PMID:24918430

Comparison of differentiation potential of male mouse adipose tissue and bone marrow derived-mesenchymal stem cells into germ cells

PubMed Central

Hosseinzadeh Shirzeily, Maryam; Pasbakhsh, Parichehr; Amidi, Fardin; Mehrannia, Kobra; Sobhani, Aligholi

2013-01-01

Background: Recent publications about differentiation of stem cells to germ cells have motivated researchers to make new approaches to infertility. In vitro production of germ cells improves understanding differentiation process of male and female germ cells. Due to the problem of using embryonic stem cells (ESC), it’s necessary the mentioned cells be replaced with some adult multi-potent stem cells in laboratories. Objective: The aim of this study was to obtain germ cells from appropriate source beyond ESC and compare differential potentials of adipocytes derived stem cells (ADMSCs) with bone marrow derived stem cells (BMMSCs). Materials and Methods: To find multi-potential entity, after providing purified ADMSCs and BMMSCs, differentiation to osteoblast and adipocyte was confirmed by using appropriate culture medium. To confirm mesenchymal lineage production superficial markers (expression of CD90 and CD44 and non-expression of CD45 and CD31) were investigated by flowcytometry. Then the cells were differentiated to germ cells in inductive medium containing retinoic acid for 7days. To evaluate germ cells characteristic markers [Dazl (Deleted in azoospermia-like), Mvh (Mouse vasa homolog gene), Stra8 (Stimulated by retinoic acid) and Scp3 (Synaptonemal complex protein 3)] flowcytometry, imunoflorescence and real time PCR were used. Results: Both types of cells were able to differentiate into osteoblast and adipocyte cells and presentation of stem cell superficial markers (CD90, CD44) and absence of endothelial and blood cell markers (CD31, CD45) were confirmative The flowcytometry, imunoflorescence and real time PCR results showed remarkable expression of germ cells characteristic markers (Mvh, Dazl, Stra8, and Scp3). Conclusion: It was found that although ADMSCs were attained easier and also cultured and differentiated rapidly, germ cell markers were expressed in BMMSCs significantly more than ADMSCs. This article extracted from M.Sc. thesis. (Maryam Hosseinzadeh Shirzeily) PMID:24639722

Distributed Evaluation Functions for Fault Tolerant Multi-Rover Systems

NASA Technical Reports Server (NTRS)

Agogino, Adrian; Turner, Kagan

2005-01-01

The ability to evolve fault tolerant control strategies for large collections of agents is critical to the successful application of evolutionary strategies to domains where failures are common. Furthermore, while evolutionary algorithms have been highly successful in discovering single-agent control strategies, extending such algorithms to multiagent domains has proven to be difficult. In this paper we present a method for shaping evaluation functions for agents that provide control strategies that both are tolerant to different types of failures and lead to coordinated behavior in a multi-agent setting. This method neither relies of a centralized strategy (susceptible to single point of failures) nor a distributed strategy where each agent uses a system wide evaluation function (severe credit assignment problem). In a multi-rover problem, we show that agents using our agent-specific evaluation perform up to 500% better than agents using the system evaluation. In addition we show that agents are still able to maintain a high level of performance when up to 60% of the agents fail due to actuator, communication or controller faults.

Patterns and processes in the genetic differentiation of the Brachionus calyciflorus complex, a passively dispersing freshwater zooplankton.

PubMed

Xiang, Xian-ling; Xi, Yi-long; Wen, Xin-li; Zhang, Gen; Wang, Jin-xia; Hu, Ke

2011-05-01

Elucidating the evolutionary patterns and processes of extant species is an important objective of any research program that seeks to understand population divergence and, ultimately, speciation. The island-like nature and temporal fluctuation of limnetic habitats create opportunities for genetic differentiation in rotifers through space and time. To gain further understanding of spatio-temporal patterns of genetic differentiation in rotifers other than the well-studied Brachionus plicatilis complex in brackish water, a total of 318 nrDNA ITS sequences from the B. calyciflorus complex in freshwater were analysed using phylogenetic and phylogeographic methods. DNA taxonomy conducted by both the sequence divergence and the GMYC model suggested the occurrence of six potential cryptic species, supported also by reproductive isolation among the tested lineages. The significant genetic differentiation and non-significant correlation between geographic and genetic distances existed in the most abundant cryptic species, BcI-W and Bc-SW. The large proportion of genetic variability for cryptic species Bc-SW was due to differences between sampling localities within seasons, rather than between different seasons. Nested Clade Analysis suggested allopatric or past fragmentation, contiguous range expansion and long-distance colonization possibly coupled with subsequent fragmentation as the probable main forces shaping the present-day phylogeographic structure of the B. calyciflorus species complex. Copyright © 2011 Elsevier Inc. All rights reserved.

Long-Term Research in Ecology and Evolution (LTREE): 2015 survey data.

PubMed

Bradford, Mark A; Leiserowitz, Anthony; Feinberg, Geoffrey; Rosenthal, Seth A; Lau, Jennifer A

2017-11-01

To systematically assess views on contributions and future activities for long-term research in ecology and evolution (LTREE), we conducted and here provide data responses and associated metadata for a survey of ecological and evolutionary scientists. The survey objectives were to: (1) Identify and prioritize research questions that are important to address through long-term, ecological field experiments; and (2) understand the role that these experiments might play in generating and applying ecological and evolutionary knowledge. The survey was developed adhering to the standards of the American Association for Public Opinion Research. It was administered online using Qualtrics Survey Software. Survey creation was a multi-step process, with questions and format developed and then revised with, for example, input from an external advisory committee comprising senior and junior ecological and evolutionary researchers. The final questionnaire was released to ~100 colleagues to ensure functionality and then fielded 2 d later (January 7 th , 2015). Two professional societies distributed it to their membership, including the Ecological Society of America, and it was posted to three list serves. The questionnaire was available through February 8th 2015 and completed by 1,179 respondents. The distribution approach targeted practicing ecologists and evolutionary biologists in the U.S. Quantitative (both ordinal and categorical) closed-ended questions used a predefined set of response categories, facilitating direct comparison across all respondents. Qualitative, open-ended questions, provided respondents the opportunity to develop their own answers. We employed quantitative questions to score views on the extent to which long-term experimental research has contributed to understanding in ecology and evolutionary biology; its role compared to other approaches (e.g., short-term experiments); justifications for and caveats to long-term experiments; and the relative importance of incentives for conducting long-term research. Qualitative questions were used to assess community views on the most important topics and questions for long-term research to address, and primary incentives and challenges to realizing this work. Finally, demographic data were collected to determine if views were conditional on such things as years of experience and field of expertise. The final questionnaire and all responses are provided for unrestricted use. © 2017 by the Ecological Society of America.

Evolutionary history of Leishmania killicki (synonymous Leishmania tropica) and taxonomic implications.

PubMed

Chaara, Dhekra; Ravel, Christophe; Bañuls, Anne- Laure; Haouas, Najoua; Lami, Patrick; Talignani, Loïc; El Baidouri, Fouad; Jaouadi, Kaouther; Harrat, Zoubir; Dedet, Jean-Pierre; Babba, Hamouda; Pratlong, Francine

2015-04-01

The taxonomic status of Leishmania (L.) killicki, a parasite that causes chronic cutaneous leishmaniasis, is not well defined yet. Indeed, some researchers suggested that this taxon could be included in the L. tropica complex, whereas others considered it as a distinct phylogenetic complex. To try to solve this taxonomic issue we carried out a detailed study on the evolutionary history of L. killicki relative to L. tropica. Thirty-five L. killicki and 25 L. tropica strains isolated from humans and originating from several countries were characterized using the MultiLocus Enzyme Electrophoresis (MLEE) and the MultiLocus Sequence Typing (MLST) approaches. The results of the genetic and phylogenetic analyses strongly support the hypothesis that L. killicki belongs to the L. tropica complex. Our data suggest that L. killicki emerged from a single founder event and that it evolved independently from L. tropica. However, they do not validate the hypothesis that L. killicki is a distinct complex. Therefore, we suggest naming this taxon L. killicki (synonymous L. tropica) until further epidemiological and phylogenetic studies justify the L. killicki denomination. This study provides taxonomic and phylogenetic information on L. killicki and improves our knowledge on the evolutionary history of this taxon.

Evolutionary branching under multi-dimensional evolutionary constraints.

PubMed

Ito, Hiroshi; Sasaki, Akira

2016-10-21

The fitness of an existing phenotype and of a potential mutant should generally depend on the frequencies of other existing phenotypes. Adaptive evolution driven by such frequency-dependent fitness functions can be analyzed effectively using adaptive dynamics theory, assuming rare mutation and asexual reproduction. When possible mutations are restricted to certain directions due to developmental, physiological, or physical constraints, the resulting adaptive evolution may be restricted to subspaces (constraint surfaces) with fewer dimensionalities than the original trait spaces. To analyze such dynamics along constraint surfaces efficiently, we develop a Lagrange multiplier method in the framework of adaptive dynamics theory. On constraint surfaces of arbitrary dimensionalities described with equality constraints, our method efficiently finds local evolutionarily stable strategies, convergence stable points, and evolutionary branching points. We also derive the conditions for the existence of evolutionary branching points on constraint surfaces when the shapes of the surfaces can be chosen freely. Copyright © 2016 Elsevier Ltd. All rights reserved.

Searching for δ Scuti-type pulsation and characterising northern pre-main-sequence field stars

NASA Astrophysics Data System (ADS)

Díaz-Fraile, D.; Rodríguez, E.; Amado, P. J.

2014-08-01

Context. Pre-main-sequence (PMS) stars are objects evolving from the birthline to the zero-age main sequence (ZAMS). Given a mass range near the ZAMS, the temperatures and luminosities of PMS and main-sequence stars are very similar. Moreover, their evolutionary tracks intersect one another causing some ambiguity in the determination of their evolutionary status. In this context, the detection and study of pulsations in PMS stars is crucial for differentiating between both types of stars by obtaining information of their interiors via asteroseismic techniques. Aims: A photometric variability study of a sample of northern field stars, which previously classified as either PMS or Herbig Ae/Be objects, has been undertaken with the purpose of detecting δ Scuti-type pulsations. Determination of physical parameters for these stars has also been carried out to locate them on the Hertzsprung-Russell diagram and check the instability strip for this type of pulsators. Methods: Multichannel photomultiplier and CCD time series photometry in the uvby Strömgren and BVI Johnson bands were obtained during four consecutive years from 2007 to 2010. The light curves have been analysed, and a variability criterion has been established. Among the objects classified as variable stars, we have selected those which present periodicities above 4 d-1, which was established as the lowest limit for δ Scuti-type pulsations in this investigation. Finally, these variable stars have been placed in a colour-magnitude diagram using the physical parameters derived with the collected uvbyβ Strömgren-Crawford photometry. Results: Five PMS δ Scuti- and three probable β Cephei-type stars have been detected. Two additional PMS δ Scuti stars are also confirmed in this work. Moreover, three new δ Scuti- and two γ Doradus-type stars have been detected among the main-sequence objects used as comparison or check stars.

Analytical solutions for coupling fractional partial differential equations with Dirichlet boundary conditions

NASA Astrophysics Data System (ADS)

Ding, Xiao-Li; Nieto, Juan J.

2017-11-01

In this paper, we consider the analytical solutions of coupling fractional partial differential equations (FPDEs) with Dirichlet boundary conditions on a finite domain. Firstly, the method of successive approximations is used to obtain the analytical solutions of coupling multi-term time fractional ordinary differential equations. Then, the technique of spectral representation of the fractional Laplacian operator is used to convert the coupling FPDEs to the coupling multi-term time fractional ordinary differential equations. By applying the obtained analytical solutions to the resulting multi-term time fractional ordinary differential equations, the desired analytical solutions of the coupling FPDEs are given. Our results are applied to derive the analytical solutions of some special cases to demonstrate their applicability.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Adaptive divergence despite strong genetic drift: genomic analysis of the evolutionary mechanisms causing genetic differentiation in the island fox (Urocyon littoralis).

PubMed

Funk, W Chris; Lovich, Robert E; Hohenlohe, Paul A; Hofman, Courtney A; Morrison, Scott A; Sillett, T Scott; Ghalambor, Cameron K; Maldonado, Jesus E; Rick, Torben C; Day, Mitch D; Polato, Nicholas R; Fitzpatrick, Sarah W; Coonan, Timothy J; Crooks, Kevin R; Dillon, Adam; Garcelon, David K; King, Julie L; Boser, Christina L; Gould, Nicholas; Andelt, William F

2016-05-01

The evolutionary mechanisms generating the tremendous biodiversity of islands have long fascinated evolutionary biologists. Genetic drift and divergent selection are predicted to be strong on islands and both could drive population divergence and speciation. Alternatively, strong genetic drift may preclude adaptation. We conducted a genomic analysis to test the roles of genetic drift and divergent selection in causing genetic differentiation among populations of the island fox (Urocyon littoralis). This species consists of six subspecies, each of which occupies a different California Channel Island. Analysis of 5293 SNP loci generated using Restriction-site Associated DNA (RAD) sequencing found support for genetic drift as the dominant evolutionary mechanism driving population divergence among island fox populations. In particular, populations had exceptionally low genetic variation, small Ne (range = 2.1-89.7; median = 19.4), and significant genetic signatures of bottlenecks. Moreover, islands with the lowest genetic variation (and, by inference, the strongest historical genetic drift) were most genetically differentiated from mainland grey foxes, and vice versa, indicating genetic drift drives genome-wide divergence. Nonetheless, outlier tests identified 3.6-6.6% of loci as high FST outliers, suggesting that despite strong genetic drift, divergent selection contributes to population divergence. Patterns of similarity among populations based on high FST outliers mirrored patterns based on morphology, providing additional evidence that outliers reflect adaptive divergence. Extremely low genetic variation and small Ne in some island fox populations, particularly on San Nicolas Island, suggest that they may be vulnerable to fixation of deleterious alleles, decreased fitness and reduced adaptive potential. © 2016 John Wiley & Sons Ltd.

Role of selection and gene flow in population differentiation at the edge vs. interior of the species range differing in climatic conditions.

PubMed

Volis, S; Ormanbekova, D; Shulgina, I

2016-04-01

Evaluating the relative importance of neutral and adaptive processes as determinants of population differentiation across environments is a central theme of evolutionary biology. We applied the QST-FST comparison flanked by a direct test for local adaptation to infer the role of climate-driven selection and gene flow in population differentiation of an annual grass Avena sterilis in two distinct parts of the species range, edge and interior, which represent two globally different climates, desert and Mediterranean. In a multiyear reciprocal transplant experiment, the plants of desert and Mediterranean origin demonstrated home advantage, and population differentiation in several phenotypic traits related to reproduction exceeded neutral predictions, as determined by comparisons of QST values with theoretical FST distributions. Thus, variation in these traits likely resulted from local adaptation to desert and Mediterranean environments. The two separate common garden experiments conducted with different experimental design revealed that two population comparisons, in contrast to multi-population comparisons, are likely to detect population differences in virtually every trait, but many of these differences reflect effects of local rather than regional environment. We detected a general reduction in neutral (SSR) genetic variation but not in adaptive quantitative trait variation in peripheral desert as compared with Mediterranean core populations. On the other hand, the molecular data indicated intensive gene flow from the Mediterranean core towards desert periphery. Although species range position in our study (edge vs. interior) was confounded with climate (desert vs. Mediterranean), the results suggest that the gene flow from the species core does not have negative consequences for either performance of the peripheral plants or their adaptive potential. © 2016 John Wiley & Sons Ltd.

Multiobjective evolutionary optimization of water distribution systems: Exploiting diversity with infeasible solutions.

PubMed

Tanyimboh, Tiku T; Seyoum, Alemtsehay G

2016-12-01

This article investigates the computational efficiency of constraint handling in multi-objective evolutionary optimization algorithms for water distribution systems. The methodology investigated here encourages the co-existence and simultaneous development including crossbreeding of subpopulations of cost-effective feasible and infeasible solutions based on Pareto dominance. This yields a boundary search approach that also promotes diversity in the gene pool throughout the progress of the optimization by exploiting the full spectrum of non-dominated infeasible solutions. The relative effectiveness of small and moderate population sizes with respect to the number of decision variables is investigated also. The results reveal the optimization algorithm to be efficient, stable and robust. It found optimal and near-optimal solutions reliably and efficiently. The real-world system based optimization problem involved multiple variable head supply nodes, 29 fire-fighting flows, extended period simulation and multiple demand categories including water loss. The least cost solutions found satisfied the flow and pressure requirements consistently. The best solutions achieved indicative savings of 48.1% and 48.2% based on the cost of the pipes in the existing network, for populations of 200 and 1000, respectively. The population of 1000 achieved slightly better results overall. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Thermal evolution of cometary nuclei

NASA Astrophysics Data System (ADS)

Prialnik, D.

2014-07-01

Thermal modeling of comet nuclei and similar objects involves the solution of conservation equations for energy and masses of the various components over time. For simplicity, the body is generally, but not necessarily, assumed to be of spherical shape. The processes included in such calculations are heat transfer, gas flow, dust drag, phase transitions, internal heating by various sources, internal structure alterations, surface sublimation. Physical properties --- such as the thermal conductivity, permeability, material strength, and porous structure --- are assumed, based on the best available estimates from laboratory experiments and space-mission results. Calculations employ various numerical procedures and require significant computational power, data analysis, and often sophisticated methods of graphical presentation. They start with a body of given size, mass, and composition, as well as a given orbit. The results yield properties and activity patterns that can be confronted with observations. Initial parameters may be adjusted until agreement is achieved. A glimpse into the internal structure of the object, which is inaccessible to direct observation, is thus obtained. The last decade, since the extensive overview of the subject was published (Modeling the structure and activity of comet nuclei, Prialnik, D.; Benkhoff, J.; Podolak, M., in Comets II, M. C. Festou, H. U. Keller, and H. A. Weaver, eds., University of Arizona Press, Tucson, p.359-387), thermal modeling has significantly advanced. This was prompted both by new properties and phenomena gleaned from observations, one example being main-belt comets, and the continual increase in computational power and performance. Progress was made on two fronts. On the computational side, multi-dimensional models have been developed, adaptive-grid and moving-boundaries techniques have been adopted, and long-term evolutionary calculations have become possible, even spanning the lifetime of the Solar System. On the chemo-physical side, additional chemical processes like serpentinization, and formation and decompositions of clathrates have been investigated. Special efforts have been devoted to related classes of objects: main-belt comets, Centaurs, Kuiper-belt objects and also to other ice-rich bodies, such as icy satellites. Since some of these objects are sufficiently large for hydrostatic pressure to become important, hydrostatic equilibrium was introduced into the modeling. This required the addition of an appropriate equation of state. Interesting new results have thus been obtained: retention of ice in the deep interior of main-belt comets over the age of the Solar System, differentiation between core and mantle in the larger Kuiper-belt objects, and complex patterns of outburst for active comets, simulating observed ones.

Evolving bipartite authentication graph partitions

DOE PAGES

Pope, Aaron Scott; Tauritz, Daniel Remy; Kent, Alexander D.

2017-01-16

As large scale enterprise computer networks become more ubiquitous, finding the appropriate balance between user convenience and user access control is an increasingly challenging proposition. Suboptimal partitioning of users’ access and available services contributes to the vulnerability of enterprise networks. Previous edge-cut partitioning methods unduly restrict users’ access to network resources. This paper introduces a novel method of network partitioning superior to the current state-of-the-art which minimizes user impact by providing alternate avenues for access that reduce vulnerability. Networks are modeled as bipartite authentication access graphs and a multi-objective evolutionary algorithm is used to simultaneously minimize the size of largemore » connected components while minimizing overall restrictions on network users. Lastly, results are presented on a real world data set that demonstrate the effectiveness of the introduced method compared to previous naive methods.« less

HD139614: the Interferometric Case for a Group-Ib Pre-Transitional Young Disk

NASA Technical Reports Server (NTRS)

Labadie, Lucas; Matter, Alexis; Kreplin, Alexander; Lopez, Bruno; Wolf, Sebastian; Weigelt, Gerd; Ertel, Steve; Berger, Jean-Philippe; Pott, Jorg-Uwe; Danchi, William C.

2014-01-01

The Herbig Ae star HD139614 is a group-Ib object, which featureless SED indicates disk flaring and a possible pre-transitional evolutionary stage. We present mid- and near-IR interferometric results collected with MIDI, AMBER and PIONIER with the aim of constraining the spatial structure of the 0.1-10 AU disk region and assess its possible multi-component structure. A two-component disk model composed of an optically thin 2-AU wide inner disk and an outer temperature-gradient disk starting at 5.6 AU reproduces well the observations. This is an additional argument to the idea that group-I HAeBe inner disks could be already in the disk-clearing transient stage. HD139614 will become a prime target for mid-IR interferometric imaging with the second-generation instrument MATISSE of the VLTI.

Evolving bipartite authentication graph partitions

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

Pope, Aaron Scott; Tauritz, Daniel Remy; Kent, Alexander D.

As large scale enterprise computer networks become more ubiquitous, finding the appropriate balance between user convenience and user access control is an increasingly challenging proposition. Suboptimal partitioning of users’ access and available services contributes to the vulnerability of enterprise networks. Previous edge-cut partitioning methods unduly restrict users’ access to network resources. This paper introduces a novel method of network partitioning superior to the current state-of-the-art which minimizes user impact by providing alternate avenues for access that reduce vulnerability. Networks are modeled as bipartite authentication access graphs and a multi-objective evolutionary algorithm is used to simultaneously minimize the size of largemore » connected components while minimizing overall restrictions on network users. Lastly, results are presented on a real world data set that demonstrate the effectiveness of the introduced method compared to previous naive methods.« less

Range-wide genetic differentiation among North American great gray owls (Strix nebulosa) reveals a distinct lineage limited to the Sierra Nevada, California

Treesearch

J.M. Hull; J.J. Keane; W.K. Savage; S.A. Godwin; J. Shafer; E.P. Jepsen; R. Gerhardt; C. Stermer; H.B. Ernest

2010-01-01

Investigations of regional genetic differentiation are essential for describing phylogeographic patterns and informing management efforts for species of conservation concern. In this context, we investigated genetic diversity and evolutionary relationships among great gray owl (Strix nebulosa) populations in western North America, which...

Comparative Transcriptomes and EVO-DEVO Studies Depending on Next Generation Sequencing.

PubMed

Liu, Tiancheng; Yu, Lin; Liu, Lei; Li, Hong; Li, Yixue

2015-01-01

High throughput technology has prompted the progressive omics studies, including genomics and transcriptomics. We have reviewed the improvement of comparative omic studies, which are attributed to the high throughput measurement of next generation sequencing technology. Comparative genomics have been successfully applied to evolution analysis while comparative transcriptomics are adopted in comparison of expression profile from two subjects by differential expression or differential coexpression, which enables their application in evolutionary developmental biology (EVO-DEVO) studies. EVO-DEVO studies focus on the evolutionary pressure affecting the morphogenesis of development and previous works have been conducted to illustrate the most conserved stages during embryonic development. Old measurements of these studies are based on the morphological similarity from macro view and new technology enables the micro detection of similarity in molecular mechanism. Evolutionary model of embryo development, which includes the "funnel-like" model and the "hourglass" model, has been evaluated by combination of these new comparative transcriptomic methods with prior comparative genomic information. Although the technology has promoted the EVO-DEVO studies into a new era, technological and material limitation still exist and further investigations require more subtle study design and procedure.

Finding the Genomic Basis of Local Adaptation: Pitfalls, Practical Solutions, and Future Directions.

PubMed

Hoban, Sean; Kelley, Joanna L; Lotterhos, Katie E; Antolin, Michael F; Bradburd, Gideon; Lowry, David B; Poss, Mary L; Reed, Laura K; Storfer, Andrew; Whitlock, Michael C

2016-10-01

Uncovering the genetic and evolutionary basis of local adaptation is a major focus of evolutionary biology. The recent development of cost-effective methods for obtaining high-quality genome-scale data makes it possible to identify some of the loci responsible for adaptive differences among populations. Two basic approaches for identifying putatively locally adaptive loci have been developed and are broadly used: one that identifies loci with unusually high genetic differentiation among populations (differentiation outlier methods) and one that searches for correlations between local population allele frequencies and local environments (genetic-environment association methods). Here, we review the promises and challenges of these genome scan methods, including correcting for the confounding influence of a species' demographic history, biases caused by missing aspects of the genome, matching scales of environmental data with population structure, and other statistical considerations. In each case, we make suggestions for best practices for maximizing the accuracy and efficiency of genome scans to detect the underlying genetic basis of local adaptation. With attention to their current limitations, genome scan methods can be an important tool in finding the genetic basis of adaptive evolutionary change.

Avoiding Local Optima with Interactive Evolutionary Robotics

DTIC Science & Technology

2012-07-09

the top of a flight of stairs selects for climbing ; suspending the robot and the target object above the ground and creating rungs between the two will...REPORT Avoiding Local Optimawith Interactive Evolutionary Robotics 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: The main bottleneck in evolutionary... robotics has traditionally been the time required to evolve robot controllers. However with the continued acceleration in computational resources, the

Controlled recovery of phylogenetic communities from an evolutionary model using a network approach

NASA Astrophysics Data System (ADS)

Sousa, Arthur M. Y. R.; Vieira, André P.; Prado, Carmen P. C.; Andrade, Roberto F. S.

2016-04-01

This works reports the use of a complex network approach to produce a phylogenetic classification tree of a simple evolutionary model. This approach has already been used to treat proteomic data of actual extant organisms, but an investigation of its reliability to retrieve a traceable evolutionary history is missing. The used evolutionary model includes key ingredients for the emergence of groups of related organisms by differentiation through random mutations and population growth, but purposefully omits other realistic ingredients that are not strictly necessary to originate an evolutionary history. This choice causes the model to depend only on a small set of parameters, controlling the mutation probability and the population of different species. Our results indicate that for a set of parameter values, the phylogenetic classification produced by the used framework reproduces the actual evolutionary history with a very high average degree of accuracy. This includes parameter values where the species originated by the evolutionary dynamics have modular structures. In the more general context of community identification in complex networks, our model offers a simple setting for evaluating the effects, on the efficiency of community formation and identification, of the underlying dynamics generating the network itself.

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

PubMed

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

2018-01-04

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

Evolution of the vertebrate jaw: comparative embryology and molecular developmental biology reveal the factors behind evolutionary novelty

PubMed Central

Kuratani, Shigeru

2004-01-01

It is generally believed that the jaw arose through the simple transformation of an ancestral rostral gill arch. The gnathostome jaw differentiates from Hox-free crest cells in the mandibular arch, and this is also apparent in the lamprey. The basic Hox code, including the Hox-free default state in the mandibular arch, may have been present in the common ancestor, and jaw patterning appears to have been secondarily constructed in the gnathostomes. The distribution of the cephalic neural crest cells is similar in the early pharyngula of gnathostomes and lampreys, but different cell subsets form the oral apparatus in each group through epithelial–mesenchymal interactions: and this heterotopy is likely to have been an important evolutionary change that permitted jaw differentiation. This theory implies that the premandibular crest cells differentiate into the upper lip, or the dorsal subdivision of the oral apparatus in the lamprey, whereas the equivalent cell population forms the trabecula of the skull base in gnathostomes. Because the gnathostome oral apparatus is derived exclusively from the mandibular arch, the concepts ‘oral’ and ‘mandibular’ must be dissociated. The ‘lamprey trabecula’ develops from mandibular mesoderm, and is not homologous with the gnathostome trabecula, which develops from premandibular crest cells. Thus the jaw evolved as an evolutionary novelty through tissue rearrangements and topographical changes in tissue interactions. PMID:15575882

Relationship between the column density distribution and evolutionary class of molecular clouds as viewed by ATLASGAL

NASA Astrophysics Data System (ADS)

Abreu-Vicente, J.; Kainulainen, J.; Stutz, A.; Henning, Th.; Beuther, H.

2015-09-01

We present the first study of the relationship between the column density distribution of molecular clouds within nearby Galactic spiral arms and their evolutionary status as measured from their stellar content. We analyze a sample of 195 molecular clouds located at distances below 5.5 kpc, identified from the ATLASGAL 870 μm data. We define three evolutionary classes within this sample: starless clumps, star-forming clouds with associated young stellar objects, and clouds associated with H ii regions. We find that the N(H2) probability density functions (N-PDFs) of these three classes of objects are clearly different: the N-PDFs of starless clumps are narrowest and close to log-normal in shape, while star-forming clouds and H ii regions exhibit a power-law shape over a wide range of column densities and log-normal-like components only at low column densities. We use the N-PDFs to estimate the evolutionary time-scales of the three classes of objects based on a simple analytic model from literature. Finally, we show that the integral of the N-PDFs, the dense gas mass fraction, depends on the total mass of the regions as measured by ATLASGAL: more massive clouds contain greater relative amounts of dense gas across all evolutionary classes. Appendices are available in electronic form at http://www.aanda.org

Unusual chromosomal organization of telomeric sequences and expeditious karyotypic differentiation in the recently evolved Mus terricolor complex.

PubMed

Sharma, G G; Sharma, T

1998-01-01

The Mus terricolor complex displays a stable homozygous arrangement of autosomal heterochromatin variations in the form of accretion of definitive autosomal short arms among three nonoverlapping populations, in concert with an expeditious evolutionary differentiation into three chromosomal species: M. terricolor I, II, and III. In contrast to the highly conservative M. musculus-like chromosomes in the coexisting sibling species, M. booduga, reshuffling and differentiation of centric heterochromatin has occurred in harmony with a revision of centric configurations, resulting in acrocentric and submetacentric autosomes. The chromosomal distribution of the prevalent vertebrate telomeric sequence (TTAGGG)n was examined by fluorescence in situ hybridization to metaphase cells of M. terricolor I, II, and III. An unusual centric organization of internal telomeric sequences was detected in all the submetacentric and acrocentric autosomes. An auxiliary role of these presumably fragile, recombinogenic telomeric sequences in the evolutionary revision of centric configurations in the terricolor complex is hypothesized.

Evolution of cooperation in Axelrod tournament using cellular automata

NASA Astrophysics Data System (ADS)

Schimit, P. H. T.; Santos, B. O.; Soares, C. A.

2015-11-01

Results of the Axelrod Tournament were published in 1981, and since then, evolutionary game theory emerged as an idea for understanding relations, like conflict and cooperation, between rational decision-makers. Robert Axelrod organized it as a round-robin tournament where strategies for iterated Prisoner's Dilemma were faced in a sequence of two players game. Here, we attempt to simulate the strategies submitted to the tournament in a multi-agent context, where individuals play a two-player game with their neighbors. Each individual has one of the strategies, and it plays the Prisoner's Dilemma with its neighbors. According to actions chosen (cooperate or defect), points of life are subtracted from their profiles. When an individual dies, some fitness functions are defined to choose the most successful strategy which the new individual will copy. Although tit-for-tat was the best strategy, on average, in the tournament, in our evolutionary multi-agent context, it has not been successful.

Random Evolutionary Dynamics Driven by Fitness and House-of-Cards Mutations: Sampling Formulae

NASA Astrophysics Data System (ADS)

Huillet, Thierry E.

2017-07-01

We first revisit the multi-allelic mutation-fitness balance problem, especially when mutations obey a house of cards condition, where the discrete-time deterministic evolutionary dynamics of the allelic frequencies derives from a Shahshahani potential. We then consider multi-allelic Wright-Fisher stochastic models whose deviation to neutrality is from the Shahshahani mutation/selection potential. We next focus on the weak selection, weak mutation cases and, making use of a Gamma calculus, we compute the normalizing partition functions of the invariant probability densities appearing in their Wright-Fisher diffusive approximations. Using these results, generalized Ewens sampling formulae (ESF) from the equilibrium distributions are derived. We start treating the ESF in the mixed mutation/selection potential case and then we restrict ourselves to the ESF in the simpler house-of-cards mutations only situation. We also address some issues concerning sampling problems from infinitely-many alleles weak limits.

The organization and control of an evolving interdependent population

PubMed Central

Vural, Dervis C.; Isakov, Alexander; Mahadevan, L.

2015-01-01

Starting with Darwin, biologists have asked how populations evolve from a low fitness state that is evolutionarily stable to a high fitness state that is not. Specifically of interest is the emergence of cooperation and multicellularity where the fitness of individuals often appears in conflict with that of the population. Theories of social evolution and evolutionary game theory have produced a number of fruitful results employing two-state two-body frameworks. In this study, we depart from this tradition and instead consider a multi-player, multi-state evolutionary game, in which the fitness of an agent is determined by its relationship to an arbitrary number of other agents. We show that populations organize themselves in one of four distinct phases of interdependence depending on one parameter, selection strength. Some of these phases involve the formation of specialized large-scale structures. We then describe how the evolution of independence can be manipulated through various external perturbations. PMID:26040593

ABC of multi-fractal spacetimes and fractional sea turtles

NASA Astrophysics Data System (ADS)

Calcagni, Gianluca

2016-04-01

We clarify what it means to have a spacetime fractal geometry in quantum gravity and show that its properties differ from those of usual fractals. A weak and a strong definition of multi-scale and multi-fractal spacetimes are given together with a sketch of the landscape of multi-scale theories of gravitation. Then, in the context of the fractional theory with q-derivatives, we explore the consequences of living in a multi-fractal spacetime. To illustrate the behavior of a non-relativistic body, we take the entertaining example of a sea turtle. We show that, when only the time direction is fractal, sea turtles swim at a faster speed than in an ordinary world, while they swim at a slower speed if only the spatial directions are fractal. The latter type of geometry is the one most commonly found in quantum gravity. For time-like fractals, relativistic objects can exceed the speed of light, but strongly so only if their size is smaller than the range of particle-physics interactions. We also find new results about log-oscillating measures, the measure presentation and their role in physical observations and in future extensions to nowhere-differentiable stochastic spacetimes.

PsiQuaSP-A library for efficient computation of symmetric open quantum systems.

PubMed

Gegg, Michael; Richter, Marten

2017-11-24

In a recent publication we showed that permutation symmetry reduces the numerical complexity of Lindblad quantum master equations for identical multi-level systems from exponential to polynomial scaling. This is important for open system dynamics including realistic system bath interactions and dephasing in, for instance, the Dicke model, multi-Λ system setups etc. Here we present an object-oriented C++ library that allows to setup and solve arbitrary quantum optical Lindblad master equations, especially those that are permutationally symmetric in the multi-level systems. PsiQuaSP (Permutation symmetry for identical Quantum Systems Package) uses the PETSc package for sparse linear algebra methods and differential equations as basis. The aim of PsiQuaSP is to provide flexible, storage efficient and scalable code while being as user friendly as possible. It is easily applied to many quantum optical or quantum information systems with more than one multi-level system. We first review the basics of the permutation symmetry for multi-level systems in quantum master equations. The application of PsiQuaSP to quantum dynamical problems is illustrated with several typical, simple examples of open quantum optical systems.

Highly conserved Z and molecularly diverged W chromosomes in the fish genus Triportheus (Characiformes, Triportheidae).

PubMed

Yano, C F; Bertollo, L A C; Ezaz, T; Trifonov, V; Sember, A; Liehr, T; Cioffi, M B

2017-03-01

The main objectives of this study were to test: (1) whether the W-chromosome differentiation matches to species' evolutionary divergence (phylogenetic concordance) and (2) whether sex chromosomes share a common ancestor within a congeneric group. The monophyletic genus Triportheus (Characiformes, Triportheidae) was the model group for this study. All species in this genus so far analyzed have ZW sex chromosome system, where the Z is always the largest chromosome of the karyotype, whereas the W chromosome is highly variable ranging from almost homomorphic to highly heteromorphic. We applied conventional and molecular cytogenetic approaches including C-banding, ribosomal DNA mapping, comparative genomic hybridization (CGH) and cross-species whole chromosome painting (WCP) to test our questions. We developed Z- and W-chromosome paints from T. auritus for cross-species WCP and performed CGH in a representative species (T. signatus) to decipher level of homologies and rates of differentiation of W chromosomes. Our study revealed that the ZW sex chromosome system had a common origin, showing highly conserved Z chromosomes and remarkably divergent W chromosomes. Notably, the W chromosomes have evolved to different shapes and sequence contents within ~15-25 Myr of divergence time. Such differentiation highlights a dynamic process of W-chromosome evolution within congeneric species of Triportheus.

Optimizing homeostatic cell renewal in hierarchical tissues

PubMed Central

Fider, Nicole A.

2018-01-01

In order to maintain homeostasis, mature cells removed from the top compartment of hierarchical tissues have to be replenished by means of differentiation and self-renewal events happening in the more primitive compartments. As each cell division is associated with a risk of mutation, cell division patterns have to be optimized, in order to minimize or delay the risk of malignancy generation. Here we study this optimization problem, focusing on the role of division tree length, that is, the number of layers of cells activated in response to the loss of terminally differentiated cells, which is related to the balance between differentiation and self-renewal events in the compartments. Using both analytical methods and stochastic simulations in a metapopulation-style model, we find that shorter division trees are advantageous if the objective is to minimize the total number of one-hit mutants in the cell population. Longer division trees on the other hand minimize the accumulation of two-hit mutants, which is a more likely evolutionary goal given the key role played by tumor suppressor genes in cancer initiation. While division tree length is the most important property determining mutant accumulation, we also find that increasing the size of primitive compartments helps to delay two-hit mutant generation. PMID:29447149

Incorporating Green Infrastructure into Water Resources Management Plans to Address Water Quality Impairments

NASA Astrophysics Data System (ADS)

Piscopo, A. N.; Detenbeck, N. E.

2017-12-01

Managers of urban watersheds with excessive nutrient loads are more frequently turning to green infrastructure (GI) to manage their water quality impairments. The effectiveness of GI is dependent on a number of factors, including (1) the type and placement of GI within the watershed, (2) the specific nutrients to be treated, and (3) the uncertainty in future climates. Although many studies have investigated the effectiveness of individual GI units for different types of nutrients, relatively few have considered the effectiveness of GI on a watershed scale, the scale most relevant to management plans. At the watershed scale, endless combinations of GI type and location are possible, each with different effectiveness in reducing nutrient loads, minimizing costs, and maximizing co-benefits such as reducing runoff. To efficiently generate management plan options that balance the tradeoffs between these objectives, we simulate candidate options using EPA's Stormwater Management Model for multiple future climates and determine the Pareto optimal set of solution options using a multi-objective evolutionary algorithm. Our approach is demonstrated for an urban watershed in Rockville, Maryland.

Multi-Excitation Magnetoacoustic Tomography with Magnetic Induction for Bioimpedance Imaging

PubMed Central

Li, Xu; He, Bin

2011-01-01

Magnetoacoustic tomography with magnetic induction (MAT-MI) is an imaging approach proposed to conduct non-invasive electrical conductivity imaging of biological tissue with high spatial resolution. In the present study, based on the analysis of the relationship between the conductivity distribution and the generated MAT-MI acoustic source, we propose a new multi-excitation MAT-MI approach and the corresponding reconstruction algorithms. In the proposed method, multiple magnetic excitations using different coil configurations are employed and ultrasound measurements corresponding to each excitation are collected to derive the conductivity distribution inside the sample. A modified reconstruction algorithm is also proposed for the multi-excitation MAT-MI imaging approach when only limited bandwidth acoustic measurements are available. Computer simulation and phantom experiment studies have been done to demonstrate the merits of the proposed method. It is shown that if unlimited bandwidth acoustic data is available, we can accurately reconstruct the internal conductivity contrast of an object using the proposed method. With limited bandwidth data and the use of the modified algorithm we can reconstruct the relative conductivity contrast of an object instead of only boundaries at the conductivity heterogeneity. Benefits that come with this new method include better differentiation of tissue types with conductivity contrast using the MAT-MI approach, specifically for potential breast cancer screening application in the future. PMID:20529729

A multi-populations multi-strategies differential evolution algorithm for structural optimization of metal nanoclusters

NASA Astrophysics Data System (ADS)

Fan, Tian-E.; Shao, Gui-Fang; Ji, Qing-Shuang; Zheng, Ji-Wen; Liu, Tun-dong; Wen, Yu-Hua

2016-11-01

Theoretically, the determination of the structure of a cluster is to search the global minimum on its potential energy surface. The global minimization problem is often nondeterministic-polynomial-time (NP) hard and the number of local minima grows exponentially with the cluster size. In this article, a multi-populations multi-strategies differential evolution algorithm has been proposed to search the globally stable structure of Fe and Cr nanoclusters. The algorithm combines a multi-populations differential evolution with an elite pool scheme to keep the diversity of the solutions and avoid prematurely trapping into local optima. Moreover, multi-strategies such as growing method in initialization and three differential strategies in mutation are introduced to improve the convergence speed and lower the computational cost. The accuracy and effectiveness of our algorithm have been verified by comparing the results of Fe clusters with Cambridge Cluster Database. Meanwhile, the performance of our algorithm has been analyzed by comparing the convergence rate and energy evaluations with the classical DE algorithm. The multi-populations, multi-strategies mutation and growing method in initialization in our algorithm have been considered respectively. Furthermore, the structural growth pattern of Cr clusters has been predicted by this algorithm. The results show that the lowest-energy structure of Cr clusters contains many icosahedra, and the number of the icosahedral rings rises with increasing size.

Genomics of Parallel Ecological Speciation in Lake Victoria Cichlids.

PubMed

Meier, Joana Isabel; Marques, David Alexander; Wagner, Catherine Elise; Excoffier, Laurent; Seehausen, Ole

2018-06-01

The genetic basis of parallel evolution of similar species is of great interest in evolutionary biology. In the adaptive radiation of Lake Victoria cichlid fishes, sister species with either blue or red-back male nuptial coloration have evolved repeatedly, often associated with shallower and deeper water, respectively. One such case is blue and red-backed Pundamilia species, for which we recently showed that a young species pair may have evolved through "hybrid parallel speciation". Coalescent simulations suggested that the older species P. pundamilia (blue) and P. nyererei (red-back) admixed in the Mwanza Gulf and that new "nyererei-like" and "pundamilia-like" species evolved from the admixed population. Here, we use genome scans to study the genomic architecture of differentiation, and assess the influence of hybridization on the evolution of the younger species pair. For each of the two species pairs, we find over 300 genomic regions, widespread across the genome, which are highly differentiated. A subset of the most strongly differentiated regions of the older pair are also differentiated in the younger pair. These shared differentiated regions often show parallel allele frequency differences, consistent with the hypothesis that admixture-derived alleles were targeted by divergent selection in the hybrid population. However, two-thirds of the genomic regions that are highly differentiated between the younger species are not highly differentiated between the older species, suggesting independent evolutionary responses to selection pressures. Our analyses reveal how divergent selection on admixture-derived genetic variation can facilitate new speciation events.

Risk assessment and adaptive runoff utilization in water resource system considering the complex relationship among water supply, electricity generation and environment

NASA Astrophysics Data System (ADS)

Zhou, J.; Zeng, X.; Mo, L.; Chen, L.; Jiang, Z.; Feng, Z.; Yuan, L.; He, Z.

2017-12-01

Generally, the adaptive utilization and regulation of runoff in the source region of China's southwest rivers is classified as a typical multi-objective collaborative optimization problem. There are grim competitions and incidence relation in the subsystems of water supply, electricity generation and environment, which leads to a series of complex problems represented by hydrological process variation, blocked electricity output and water environment risk. Mathematically, the difficulties of multi-objective collaborative optimization focus on the description of reciprocal relationships and the establishment of evolving model of adaptive systems. Thus, based on the theory of complex systems science, this project tries to carry out the research from the following aspects: the changing trend of coupled water resource, the covariant factor and driving mechanism, the dynamic evolution law of mutual feedback dynamic process in the supply-generation-environment coupled system, the environmental response and influence mechanism of coupled mutual feedback water resource system, the relationship between leading risk factor and multiple risk based on evolutionary stability and dynamic balance, the transfer mechanism of multiple risk response with the variation of the leading risk factor, the multidimensional coupled feedback system of multiple risk assessment index system and optimized decision theory. Based on the above-mentioned research results, the dynamic method balancing the efficiency of multiple objectives in the coupled feedback system and optimized regulation model of water resources is proposed, and the adaptive scheduling mode considering the internal characteristics and external response of coupled mutual feedback system of water resource is established. In this way, the project can make a contribution to the optimal scheduling theory and methodology of water resource management under uncertainty in the source region of Southwest River.

Multi-off-grid methods in multi-step integration of ordinary differential equations

NASA Technical Reports Server (NTRS)

Beaudet, P. R.

1974-01-01

Description of methods of solving first- and second-order systems of differential equations in which all derivatives are evaluated at off-grid locations in order to circumvent the Dahlquist stability limitation on the order of on-grid methods. The proposed multi-off-grid methods require off-grid state predictors for the evaluation of the n derivatives at each step. Progressing forward in time, the off-grid states are predicted using a linear combination of back on-grid state values and off-grid derivative evaluations. A comparison is made between the proposed multi-off-grid methods and the corresponding Adams and Cowell on-grid integration techniques in integrating systems of ordinary differential equations, showing a significant reduction in the error at larger step sizes in the case of the multi-off-grid integrator.

Battling Arrow's Paradox to Discover Robust Water Management Alternatives

NASA Astrophysics Data System (ADS)

Kasprzyk, J. R.; Reed, P. M.; Hadka, D.

2013-12-01

This study explores whether or not Arrow's Impossibility Theorem, a theory of social choice, affects the formulation of water resources systems planning problems. The theorem discusses creating an aggregation function for voters choosing from more than three alternatives for society. The Impossibility Theorem is also called Arrow's Paradox, because when trying to add more voters, a single individual's preference will dictate the optimal group decision. In the context of water resources planning, our study is motivated by recent theoretical work that has generalized the insights for Arrow's Paradox to the design of complex engineered systems. In this framing of the paradox, states of society are equivalent to water planning or design alternatives, and the voters are equivalent to multiple planning objectives (e.g. minimizing cost or maximizing performance). Seen from this point of view, multi-objective water planning problems are functionally equivalent to the social choice problem described above. Traditional solutions to such multi-objective problems aggregate multiple performance measures into a single mathematical objective. The Theorem implies that a subset of performance concerns will inadvertently dictate the overall design evaluations in unpredictable ways using such an aggregation. We suggest that instead of aggregation, an explicit many-objective approach to water planning can help overcome the challenges posed by Arrow's Paradox. Many-objective planning explicitly disaggregates measures of performance while supporting the discovery of the planning tradeoffs, employing multiobjective evolutionary algorithms (MOEAs) to find solutions. Using MOEA-based search to address Arrow's Paradox requires that the MOEAs perform robustly with increasing problem complexity, such as adding additional objectives and/or decisions. This study uses comprehensive diagnostic evaluation of MOEA search performance across multiple problem formulations (both aggregated and many-objective) to show whether or not aggregating performance measures biases decision making. In this study, we explore this hypothesis using an urban water portfolio management case study in the Lower Rio Grande Valley. The diagnostic analysis shows that modern self-adaptive MOEA search is efficient, effective, and reliable for the more complex many-objective LRGV planning formulations. Results indicate that although many classical water systems planning frameworks seek to account for multiple objectives, the common practice of reducing the problem into one or more highly aggregated performance measures can severely and negatively bias planning decisions.

Student concepts of Natural Selection from a resource-based perspective

NASA Astrophysics Data System (ADS)

Benjamin, Scott Shawn

The past two decades have produced a substantial amount of research about the teaching and learning of evolution; however, recent research often lacks a theoretical foundation. Application of a new theoretical framework could help fill the void and improve research about student concepts of evolution. This study seeks to show that a resource-based framework (Hammer et al., 2005) can improve research into student concepts of natural selection. Concepts of natural selection from urban community college students were assessed via qualitative (interviews, written open-response questions, and write/think aloud procedures) and quantitative methods (coded open response analysis, Concept Inventory for Natural Selection (CINS)(Anderson, Fisher, & Norman, 2002). Results showed that students demonstrate four important aspects of resource-based framework: the multi-faceted construction of concepts, context sensitivity/ concept flexibility, at-the-moment activation of resources, and perceptual frames. In open response assessment, evolutionary-gain responses produced significantly different responses than evolutionary-loss questions with: 1) significantly more correct answers for the gain than loss question (Wilcoxon signed rank test, z = -3.68, p=0.0002); 2) more Lamarckian responses to loss than the gain question (Fisher exact, p=0.0039); and significantly different distributions in expanded need vs basic need answers (Fishers exact, p = 0.02). Results from CINS scores showed significant differences in post activity scores between students that held different naive concepts associated with origin of variation, origin of species, differential reproduction, and limited survival suggesting that some naive ideas facilitate learning. Outcomes also suggest that an everyday or self-experience typological perceptual frame is an underlying source of many incorrect ideas about evolution. Interview and write/think aloud assessments propose four process resources applied by students as they explain evolutionary change: list what I know, why story, compare past to present, mapping self-experience. The study concludes that a resource-based framework is a valuable tool to advance the study student concepts of natural selection.

On the numerical treatment of selected oscillatory evolutionary problems

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

STE/ICE (Simplified Test Equipment/Internal Combustion Engines) Design Guide for Vehicle Diagnostic Connector Assemblies

DTIC Science & Technology

1982-08-01

19 3.2 Diesel Engine Speed Transducer 20 3.3 Pressure Transducer 20 3.4 Temperature Transducer 22 3.5 Differential Pressure Switch 22 3.6 Differential... Pressure Switch , Multi-Point 22 3.7 Current Measurement Transducer 23 - 3.8 Electrolyte Level Probes 23 3.9 Diagnostic Connector 24 3.10 Harness...12258933 Differential Pressure Switch - Multi-point 12258934 K -. Differential Pressure Switch 12258938 Electrolyte Level Sensor 12258935 Shunt 1000

A novel fruit shape classification method based on multi-scale analysis

NASA Astrophysics Data System (ADS)

Gui, Jiangsheng; Ying, Yibin; Rao, Xiuqin

2005-11-01

Shape is one of the major concerns and which is still a difficult problem in automated inspection and sorting of fruits. In this research, we proposed the multi-scale energy distribution (MSED) for object shape description, the relationship between objects shape and its boundary energy distribution at multi-scale was explored for shape extraction. MSED offers not only the mainly energy which represent primary shape information at the lower scales, but also subordinate energy which represent local shape information at higher differential scales. Thus, it provides a natural tool for multi resolution representation and can be used as a feature for shape classification. We addressed the three main processing steps in the MSED-based shape classification. They are namely, 1) image preprocessing and citrus shape extraction, 2) shape resample and shape feature normalization, 3) energy decomposition by wavelet and classification by BP neural network. Hereinto, shape resample is resample 256 boundary pixel from a curve which is approximated original boundary by using cubic spline in order to get uniform raw data. A probability function was defined and an effective method to select a start point was given through maximal expectation, which overcame the inconvenience of traditional methods in order to have a property of rotation invariants. The experiment result is relatively well normal citrus and serious abnormality, with a classification rate superior to 91.2%. The global correct classification rate is 89.77%, and our method is more effective than traditional method. The global result can meet the request of fruit grading.

Characterization of the Gaseous Companion k Andromedae B* New Keck and LBTI High-contrast Observations

NASA Technical Reports Server (NTRS)

Bonnefoy, M.; Currie, T.; Marleau, G.-D.; Schlieder, J. E.; Wisniewski, J.; Carson, J.; Covey, K. R.; Henning, T.; Biller, B.; Hinz, P.;

Genetic differentiation associated with host plants and geography among six widespread species of South American Blepharoneura fruit flies (Tephritidae).

PubMed

Ottens, K; Winkler, I S; Lewis, M L; Scheffer, S J; Gomes-Costa, G A; Condon, M A; Forbes, A A

2017-04-01

Tropical herbivorous insects are astonishingly diverse, and many are highly host-specific. Much evidence suggests that herbivorous insect diversity is a function of host plant diversity; yet, the diversity of some lineages exceeds the diversity of plants. Although most species of herbivorous fruit flies in the Neotropical genus Blepharoneura are strongly host-specific (they deposit their eggs in a single host plant species and flower sex), some species are collected from multiple hosts or flowers and these may represent examples of lineages that are diversifying via changes in host use. Here, we investigate patterns of diversification within six geographically widespread Blepharoneura species that have been collected and reared from at least two host plant species or host plant parts. We use microsatellites to (1) test for evidence of local genetic differentiation associated with different sympatric hosts (different plant species or flower sexes) and (2) examine geographic patterns of genetic differentiation across multiple South American collection sites. In four of the six fly species, we find evidence of local genetic differences between flies collected from different hosts. All six species show evidence of geographic structure, with consistent differences between flies collected in the Guiana Shield and flies collected in Amazonia. Continent-wide analyses reveal - in all but one instance - that genetically differentiated flies collected in sympatry from different host species or different sex flowers are not one another's closest relatives, indicating that genetic differences often arise in allopatry before, or at least coincident with, the evolution of novel host use. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

On shifted Jacobi spectral method for high-order multi-point boundary value problems

NASA Astrophysics Data System (ADS)

Doha, E. H.; Bhrawy, A. H.; Hafez, R. M.

2012-10-01

This paper reports a spectral tau method for numerically solving multi-point boundary value problems (BVPs) of linear high-order ordinary differential equations. The construction of the shifted Jacobi tau approximation is based on conventional differentiation. This use of differentiation allows the imposition of the governing equation at the whole set of grid points and the straight forward implementation of multiple boundary conditions. Extension of the tau method for high-order multi-point BVPs with variable coefficients is treated using the shifted Jacobi Gauss-Lobatto quadrature. Shifted Jacobi collocation method is developed for solving nonlinear high-order multi-point BVPs. The performance of the proposed methods is investigated by considering several examples. Accurate results and high convergence rates are achieved.

Synthetic consciousness: the distributed adaptive control perspective

PubMed Central

2016-01-01

Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID:27431526

Synthetic consciousness: the distributed adaptive control perspective.

PubMed

Verschure, Paul F M J

2016-08-19

Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene.This article is part of the themed issue 'The major synthetic evolutionary transitions'. © 2016 The Author(s).

Real-time myoelectric control of a multi-fingered hand prosthesis using principal components analysis.

PubMed

Matrone, Giulia C; Cipriani, Christian; Carrozza, Maria Chiara; Magenes, Giovanni

2012-06-15

In spite of the advances made in the design of dexterous anthropomorphic hand prostheses, these sophisticated devices still lack adequate control interfaces which could allow amputees to operate them in an intuitive and close-to-natural way. In this study, an anthropomorphic five-fingered robotic hand, actuated by six motors, was used as a prosthetic hand emulator to assess the feasibility of a control approach based on Principal Components Analysis (PCA), specifically conceived to address this problem. Since it was demonstrated elsewhere that the first two principal components (PCs) can describe the whole hand configuration space sufficiently well, the controller here employed reverted the PCA algorithm and allowed to drive a multi-DoF hand by combining a two-differential channels EMG input with these two PCs. Hence, the novelty of this approach stood in the PCA application for solving the challenging problem of best mapping the EMG inputs into the degrees of freedom (DoFs) of the prosthesis. A clinically viable two DoFs myoelectric controller, exploiting two differential channels, was developed and twelve able-bodied participants, divided in two groups, volunteered to control the hand in simple grasp trials, using forearm myoelectric signals. Task completion rates and times were measured. The first objective (assessed through one group of subjects) was to understand the effectiveness of the approach; i.e., whether it is possible to drive the hand in real-time, with reasonable performance, in different grasps, also taking advantage of the direct visual feedback of the moving hand. The second objective (assessed through a different group) was to investigate the intuitiveness, and therefore to assess statistical differences in the performance throughout three consecutive days. Subjects performed several grasp, transport and release trials with differently shaped objects, by operating the hand with the myoelectric PCA-based controller. Experimental trials showed that the simultaneous use of the two differential channels paradigm was successful. This work demonstrates that the proposed two-DoFs myoelectric controller based on PCA allows to drive in real-time a prosthetic hand emulator into different prehensile patterns with excellent performance. These results open up promising possibilities for the development of intuitive, effective myoelectric hand controllers.

Research a Novel Integrated and Dynamic Multi-object Trade-Off Mechanism in Software Project

NASA Astrophysics Data System (ADS)

Jiang, Weijin; Xu, Yuhui

Aiming at practical requirements of present software project management and control, the paper presented to construct integrated multi-object trade-off model based on software project process management, so as to actualize integrated and dynamic trade-oil of the multi-object system of project. Based on analyzing basic principle of dynamic controlling and integrated multi-object trade-off system process, the paper integrated method of cybernetics and network technology, through monitoring on some critical reference points according to the control objects, emphatically discussed the integrated and dynamic multi- object trade-off model and corresponding rules and mechanism in order to realize integration of process management and trade-off of multi-object system.

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

PubMed Central

Van Holle, Sofie; De Schutter, Kristof; Eggermont, Lore; Tsaneva, Mariya; Dang, Liuyi; Van Damme, Els J. M.

2017-01-01

Lectins are present throughout the plant kingdom and are reported to be involved in diverse biological processes. In this study, we provide a comparative analysis of the lectin families from model species in a phylogenetic framework. The analysis focuses on the different plant lectin domains identified in five representative core angiosperm genomes (Arabidopsis thaliana, Glycine max, Cucumis sativus, Oryza sativa ssp. japonica and Oryza sativa ssp. indica). The genomes were screened for genes encoding lectin domains using a combination of Basic Local Alignment Search Tool (BLAST), hidden Markov models, and InterProScan analysis. Additionally, phylogenetic relationships were investigated by constructing maximum likelihood phylogenetic trees. The results demonstrate that the majority of the lectin families are present in each of the species under study. Domain organization analysis showed that most identified proteins are multi-domain proteins, owing to the modular rearrangement of protein domains during evolution. Most of these multi-domain proteins are widespread, while others display a lineage-specific distribution. Furthermore, the phylogenetic analyses reveal that some lectin families evolved to be similar to the phylogeny of the plant species, while others share a closer evolutionary history based on the corresponding protein domain architecture. Our results yield insights into the evolutionary relationships and functional divergence of plant lectins. PMID:28587095

The numerical solution of linear multi-term fractional differential equations: systems of equations

NASA Astrophysics Data System (ADS)

Edwards, John T.; Ford, Neville J.; Simpson, A. Charles

2002-11-01

In this paper, we show how the numerical approximation of the solution of a linear multi-term fractional differential equation can be calculated by reduction of the problem to a system of ordinary and fractional differential equations each of order at most unity. We begin by showing how our method applies to a simple class of problems and we give a convergence result. We solve the Bagley Torvik equation as an example. We show how the method can be applied to a general linear multi-term equation and give two further examples.

Multi-spectral endogenous fluorescence imaging for bacterial differentiation

NASA Astrophysics Data System (ADS)

Chernomyrdin, Nikita V.; Babayants, Margarita V.; Korotkov, Oleg V.; Kudrin, Konstantin G.; Rimskaya, Elena N.; Shikunova, Irina A.; Kurlov, Vladimir N.; Cherkasova, Olga P.; Komandin, Gennady A.; Reshetov, Igor V.; Zaytsev, Kirill I.

2017-07-01

In this paper, the multi-spectral endogenous fluorescence imaging was implemented for bacterial differentiation. The fluorescence imaging was performed using a digital camera equipped with a set of visual bandpass filters. Narrowband 365 nm ultraviolet radiation passed through a beam homogenizer was used to excite the sample fluorescence. In order to increase a signal-to-noise ratio and suppress a non-fluorescence background in images, the intensity of the UV excitation was modulated using a mechanical chopper. The principal components were introduced for differentiating the samples of bacteria based on the multi-spectral endogenous fluorescence images.

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

PubMed

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

2017-01-01

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

Segmenting healthcare terminology users: a strategic approach to large scale evolutionary development.

PubMed

Price, C; Briggs, K; Brown, P J

1999-01-01

Healthcare terminologies have become larger and more complex, aiming to support a diverse range of functions across the whole spectrum of healthcare activity. Prioritization of development, implementation and evaluation can be achieved by regarding the "terminology" as an integrated system of content-based and functional components. Matching these components to target segments within the healthcare community, supports a strategic approach to evolutionary development and provides essential product differentiation to enable terminology providers and systems suppliers to focus on end-user requirements.

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.

Nanotube Heterojunctions and Endo-Fullerenes for Nanoelectronics

NASA Technical Reports Server (NTRS)

Srivastava, Deepak; Menon, M.; Andriotis, Antonis; Cho, K.; Park, Jun; Biegel, Bryan A. (Technical Monitor)

2002-01-01

Topics discussed include: (1) Light-Weight Multi-Functional Materials: Nanomechanics; Nanotubes and Composites; Thermal/Chemical/Electrical Characterization; (2) Biomimetic/Revolutionary Concepts: Evolutionary Computing and Sensing; Self-Heating Materials; (3) Central Computing System: Molecular Electronics; Materials for Quantum Bits; and (4) Molecular Machines.

Replaying evolutionary transitions from the dental fossil record

PubMed Central

Harjunmaa, Enni; Seidel, Kerstin; Häkkinen, Teemu; Renvoisé, Elodie; Corfe, Ian J.; Kallonen, Aki; Zhang, Zhao-Qun; Evans, Alistair R.; Mikkola, Marja L.; Salazar-Ciudad, Isaac; Klein, Ophir D.; Jernvall, Jukka

2014-01-01

The evolutionary relationships of extinct species are ascertained primarily through the analysis of morphological characters. Character inter-dependencies can have a substantial effect on evolutionary interpretations, but the developmental underpinnings of character inter-dependence remain obscure because experiments frequently do not provide detailed resolution of morphological characters. Here we show experimentally and computationally how gradual modification of development differentially affects characters in the mouse dentition. We found that intermediate phenotypes could be produced by gradually adding ectodysplasin A (EDA) protein in culture to tooth explants carrying a null mutation in the tooth-patterning gene Eda. By identifying development-based character interdependencies, we show how to predict morphological patterns of teeth among mammalian species. Finally, in vivo inhibition of sonic hedgehog signalling in Eda null teeth enabled us to reproduce characters deep in the rodent ancestry. Taken together, evolutionarily informative transitions can be experimentally reproduced, thereby providing development-based expectations for character state transitions used in evolutionary studies. PMID:25079326

Individual-based modeling of ecological and evolutionary processes

USGS Publications Warehouse

DeAngelis, Donald L.; Mooij, Wolf M.

2005-01-01

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

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

[An evolutionary analysis of the concept of self-care].

PubMed

Mailhot, Tanya; Cossette, Sylvie; Alderson, Marie

2013-03-01

The nursing community seems to agree on the general meaning of "self-care" as a concept allowing the individual to take care of his health. Yet the terms self-care and other "self-concepts" are often used interchangeably. Since this concept is central to nursing, it appeared crucial to lead an effort to clarify and to deepen the understanding of its development within the field of nursing. The objective of this evolutionary concept analysis was to identify the state of precision or clarity of the concept in the available nursing literature. The identification of attributes, antecedents and consequences has highlighted the characteristics as it has been used by various authors and ultimately provides a basis for further research. After this analysis, it is possible to propose that the concept of self-care refers to an activity initiated, consciously and following learning, which is appropriate to the situation and focused on a goal. Furthermore, this concept is widely used in contexts of long-term illnesses and much less so in contexts of acute diseases. In conclusion, work remains to be done to better differentiate the concept of self-care from other self-concepts when used in situations where a third party is involved in the realization of self-care.

Evolution of Microbial Quorum Sensing to Human Global Quorum Sensing: An Insight into How Gap Junctional Intercellular Communication Might Be Linked to the Global Metabolic Disease Crisis

PubMed Central

Trosko, James E.

2016-01-01

The first anaerobic organism extracted energy for survival and reproduction from its source of nutrients, with the genetic means to ensure protection of its individual genome but also its species survival. While it had a means to communicate with its community via simple secreted molecules (“quorum sensing”), the eventual shift to an aerobic environment led to multi-cellular metazoan organisms, with evolutionary-selected genes to form extracellular matrices, stem cells, stem cell niches, and a family of gap junction or “connexin” genes. These germinal and somatic stem cells responded to extracellular signals that triggered intra-cellular signaling to regulate specific genes out of the total genome. These extra-cellular induced intra-cellular signals also modulated gap junctional intercellular communication (GJIC) in order to regulate the new cellular functions of symmetrical and asymmetrical cell division, cell differentiation, modes of cell death, and senescence. Within the hierarchical and cybernetic concepts, differentiated by neurons organized in the brain of the Homo sapiens, the conscious mind led to language, abstract ideas, technology, myth-making, scientific reasoning, and moral decision–making, i.e., the creation of culture. Over thousands of years, this has created the current collision between biological and cultural evolution, leading to the global “metabolic disease” crisis. PMID:27314399

Comparative genomic analysis of Helicobacter pylori from Malaysia identifies three distinct lineages suggestive of differential evolution.

PubMed

Kumar, Narender; Mariappan, Vanitha; Baddam, Ramani; Lankapalli, Aditya K; Shaik, Sabiha; Goh, Khean-Lee; Loke, Mun Fai; Perkins, Tim; Benghezal, Mohammed; Hasnain, Seyed E; Vadivelu, Jamuna; Marshall, Barry J; Ahmed, Niyaz

2015-01-01

The discordant prevalence of Helicobacter pylori and its related diseases, for a long time, fostered certain enigmatic situations observed in the countries of the southern world. Variation in H. pylori infection rates and disease outcomes among different populations in multi-ethnic Malaysia provides a unique opportunity to understand dynamics of host-pathogen interaction and genome evolution. In this study, we extensively analyzed and compared genomes of 27 Malaysian H. pylori isolates and identified three major phylogeographic lineages: hspEastAsia, hpEurope and hpSouthIndia. The analysis of the virulence genes within the core genome, however, revealed a comparable pathogenic potential of the strains. In addition, we identified four genes limited to strains of East-Asian lineage. Our analyses identified a few strain-specific genes encoding restriction modification systems and outlined 311 core genes possibly under differential evolutionary constraints, among the strains representing different ethnic groups. The cagA and vacA genes also showed variations in accordance with the host genetic background of the strains. Moreover, restriction modification genes were found to be significantly enriched in East-Asian strains. An understanding of these variations in the genome content would provide significant insights into various adaptive and host modulation strategies harnessed by H. pylori to effectively persist in a host-specific manner. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Multivariable optimization of an auto-thermal ammonia synthesis reactor using genetic algorithm

NASA Astrophysics Data System (ADS)

Anh-Nga, Nguyen T.; Tuan-Anh, Nguyen; Tien-Dung, Vu; Kim-Trung, Nguyen

2017-09-01

The ammonia synthesis system is an important chemical process used in the manufacture of fertilizers, chemicals, explosives, fibers, plastics, refrigeration. In the literature, many works approaching the modeling, simulation and optimization of an auto-thermal ammonia synthesis reactor can be found. However, they just focus on the optimization of the reactor length while keeping the others parameters constant. In this study, the other parameters are also considered in the optimization problem such as the temperature of feed gas enters the catalyst zone. The optimal problem requires the maximization of a multivariable objective function which subjects to a number of equality constraints involving the solution of coupled differential equations and also inequality constraints. The solution of an optimization problem can be found through, among others, deterministic or stochastic approaches. The stochastic methods, such as evolutionary algorithm (EA), which is based on natural phenomenon, can overcome the drawbacks such as the requirement of the derivatives of the objective function and/or constraints, or being not efficient in non-differentiable or discontinuous problems. Genetic algorithm (GA) which is a class of EA, exceptionally simple, robust at numerical optimization and is more likely to find a true global optimum. In this study, the genetic algorithm is employed to find the optimum profit of the process. The inequality constraints were treated using penalty method. The coupled differential equations system was solved using Runge-Kutta 4th order method. The results showed that the presented numerical method could be applied to model the ammonia synthesis reactor. The optimum economic profit obtained from this study are also compared to the results from the literature. It suggests that the process should be operated at higher temperature of feed gas in catalyst zone and the reactor length is slightly longer.

An Effective Hybrid Evolutionary Algorithm for Solving the Numerical Optimization Problems

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal.

PubMed

Turajlic, Samra; Xu, Hang; Litchfield, Kevin; Rowan, Andrew; Horswell, Stuart; Chambers, Tim; O'Brien, Tim; Lopez, Jose I; Watkins, Thomas B K; Nicol, David; Stares, Mark; Challacombe, Ben; Hazell, Steve; Chandra, Ashish; Mitchell, Thomas J; Au, Lewis; Eichler-Jonsson, Claudia; Jabbar, Faiz; Soultati, Aspasia; Chowdhury, Simon; Rudman, Sarah; Lynch, Joanna; Fernando, Archana; Stamp, Gordon; Nye, Emma; Stewart, Aengus; Xing, Wei; Smith, Jonathan C; Escudero, Mickael; Huffman, Adam; Matthews, Nik; Elgar, Greg; Phillimore, Ben; Costa, Marta; Begum, Sharmin; Ward, Sophia; Salm, Max; Boeing, Stefan; Fisher, Rosalie; Spain, Lavinia; Navas, Carolina; Grönroos, Eva; Hobor, Sebastijan; Sharma, Sarkhara; Aurangzeb, Ismaeel; Lall, Sharanpreet; Polson, Alexander; Varia, Mary; Horsfield, Catherine; Fotiadis, Nicos; Pickering, Lisa; Schwarz, Roland F; Silva, Bruno; Herrero, Javier; Luscombe, Nick M; Jamal-Hanjani, Mariam; Rosenthal, Rachel; Birkbak, Nicolai J; Wilson, Gareth A; Pipek, Orsolya; Ribli, Dezso; Krzystanek, Marcin; Csabai, Istvan; Szallasi, Zoltan; Gore, Martin; McGranahan, Nicholas; Van Loo, Peter; Campbell, Peter; Larkin, James; Swanton, Charles

2018-04-19

The evolutionary features of clear-cell renal cell carcinoma (ccRCC) have not been systematically studied to date. We analyzed 1,206 primary tumor regions from 101 patients recruited into the multi-center prospective study, TRACERx Renal. We observe up to 30 driver events per tumor and show that subclonal diversification is associated with known prognostic parameters. By resolving the patterns of driver event ordering, co-occurrence, and mutual exclusivity at clone level, we show the deterministic nature of clonal evolution. ccRCC can be grouped into seven evolutionary subtypes, ranging from tumors characterized by early fixation of multiple mutational and copy number drivers and rapid metastases to highly branched tumors with >10 subclonal drivers and extensive parallel evolution associated with attenuated progression. We identify genetic diversity and chromosomal complexity as determinants of patient outcome. Our insights reconcile the variable clinical behavior of ccRCC and suggest evolutionary potential as a biomarker for both intervention and surveillance. Copyright © 2018 Francis Crick Institute. Published by Elsevier Inc. All rights reserved.

Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation.

PubMed

Liu, Xiaofeng; Bai, Fang; Ouyang, Sisheng; Wang, Xicheng; Li, Honglin; Jiang, Hualiang

2009-03-31

Conformation generation is a ubiquitous problem in molecule modelling. Many applications require sampling the broad molecular conformational space or perceiving the bioactive conformers to ensure success. Numerous in silico methods have been proposed in an attempt to resolve the problem, ranging from deterministic to non-deterministic and systemic to stochastic ones. In this work, we described an efficient conformation sampling method named Cyndi, which is based on multi-objective evolution algorithm. The conformational perturbation is subjected to evolutionary operation on the genome encoded with dihedral torsions. Various objectives are designated to render the generated Pareto optimal conformers to be energy-favoured as well as evenly scattered across the conformational space. An optional objective concerning the degree of molecular extension is added to achieve geometrically extended or compact conformations which have been observed to impact the molecular bioactivity (J Comput -Aided Mol Des 2002, 16: 105-112). Testing the performance of Cyndi against a test set consisting of 329 small molecules reveals an average minimum RMSD of 0.864 A to corresponding bioactive conformations, indicating Cyndi is highly competitive against other conformation generation methods. Meanwhile, the high-speed performance (0.49 +/- 0.18 seconds per molecule) renders Cyndi to be a practical toolkit for conformational database preparation and facilitates subsequent pharmacophore mapping or rigid docking. The copy of precompiled executable of Cyndi and the test set molecules in mol2 format are accessible in Additional file 1. On the basis of MOEA algorithm, we present a new, highly efficient conformation generation method, Cyndi, and report the results of validation and performance studies comparing with other four methods. The results reveal that Cyndi is capable of generating geometrically diverse conformers and outperforms other four multiple conformer generators in the case of reproducing the bioactive conformations against 329 structures. The speed advantage indicates Cyndi is a powerful alternative method for extensive conformational sampling and large-scale conformer database preparation.

Settling Efficiency of Urban Particulate Matter Transported by Stormwater Runoff.

PubMed

Carbone, Marco; Penna, Nadia; Piro, Patrizia

2015-09-01

The main purpose of control measures in urban areas is to retain particulate matter washed out by stormwater over impermeable surfaces. In stormwater control measures, particulate matter removal typically occurs via sedimentation. Settling column tests were performed to examine the settling efficiency of such units using monodisperse and heterodisperse particulate matter (for which the particle size distributions were measured and modelled by the cumulative gamma distribution). To investigate the dependence of settling efficiency from the particulate matter, a variant of the evolutionary polynomial regression (EPR), a Microsoft Excel function based on multi-objective EPR technique (EPR-MOGA), called EPR MOGA XL, was used as a data-mining strategy. The results from this study have shown that settling efficiency is a function of the initial total suspended solids (TSS) concentration and of the median diameter (d50 index), obtained from the particle size distributions (PSDs) of the samples.

Use HypE to Hide Association Rules by Adding Items

PubMed Central

Cheng, Peng; Lin, Chun-Wei; Pan, Jeng-Shyang

2015-01-01

During business collaboration, partners may benefit through sharing data. People may use data mining tools to discover useful relationships from shared data. However, some relationships are sensitive to the data owners and they hope to conceal them before sharing. In this paper, we address this problem in forms of association rule hiding. A hiding method based on evolutionary multi-objective optimization (EMO) is proposed, which performs the hiding task by selectively inserting items into the database to decrease the confidence of sensitive rules below specified thresholds. The side effects generated during the hiding process are taken as optimization goals to be minimized. HypE, a recently proposed EMO algorithm, is utilized to identify promising transactions for modification to minimize side effects. Results on real datasets demonstrate that the proposed method can effectively perform sanitization with fewer damages to the non-sensitive knowledge in most cases. PMID:26070130

VizieR Online Data Catalog: Massive stars in 30 Dor (Schneider+, 2018)

NASA Astrophysics Data System (ADS)

Schneider, F. R. N.; Sana, H.; Evans, C. J.; Bestenlehner, J. M.; Castro, N.; Fossati, L.; Grafener, G.; Langer, N.; Ramirez-Agudelo, O. H.; Sabin-Sanjulian, C.; Simon-Diaz, S.; Tramper, F.; Crowther, P. A.; de Koter, A.; de Mink, S. E.; Dufton, P. L.; Garcia, M.; Gieles, M.; Henault-Brunet, V.; Herrero, A.; Izzard, R. G.; Kalari, V.; Lennon, D. J.; Apellaniz, J. M.; Markova, N.; Najarro, F.; Podsiadlowski, P.; Puls, J.; Taylor, W. D.; van Loon, J. T.; Vink, J. S.; Norman, C.

2018-02-01

Through the use of the Fibre Large Array Multi Element Spectrograph (FLAMES) on the Very Large Telescope (VLT), the VLT-FLAMES Tarantula Survey (VFTS) has obtained optical spectra of ~800 massive stars in 30 Dor, avoiding the core region of the dense star cluster R136 because of difficulties with crowding. Repeated observations at multiple epochs allow determination of the orbital motion of potentially binary objects. For a sample of 452 apparently single stars, robust stellar parameters-such as effective temperatures, luminosities, surface gravities, and projected rotational velocities-are determined by modeling the observed spectra. Composite spectra of visual multiple systems and spectroscopic binaries are not considered here because their parameters cannot be reliably inferred from the VFTS data. To match the derived atmospheric parameters of the apparently single VFTS stars to stellar evolutionary models, we use the Bayesian code Bonnsai. (2 data files).

Optimization of multi-objective micro-grid based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Zhang, Jian; Gan, Yang

2018-04-01

The paper presents a multi-objective optimal configuration model for independent micro-grid with the aim of economy and environmental protection. The Pareto solution set can be obtained by solving the multi-objective optimization configuration model of micro-grid with the improved particle swarm algorithm. The feasibility of the improved particle swarm optimization algorithm for multi-objective model is verified, which provides an important reference for multi-objective optimization of independent micro-grid.

Confirming Planetary Mass Candidate Companions in Ophiuchus

NASA Astrophysics Data System (ADS)

Fontanive, Clemence

2016-10-01

We propose for follow-up observations to confirm common proper motion for two candidate planetary mass companions, identified as part of our GO 12944 (PI Allers) search for companions to the youngest ( 0.5 Myr) brown dwarfs in the nearby Ophiuchus star-forming region. If confirmed to be co-moving, these would be among the lowest mass planetary mass companions imaged to date, with estimated masses <5 Jupiter Masses and would be vital benchmark objects for evolutionary models at these young ages. With our multi-band optical and IR photometric approach based on the SpT-Q relation seen for Ophiuchus brown dwarfs (Allers in prep.), we have already estimated the spectral type of our candidate companions. This approach distinguishes substellar objects from background interlopers based on the strength of the 1.4 um water feature robustly observed in MLTY objects but not in reddened background stars - both our candidates show clear evidence of absorption at 1.4 um. If confirmed, these candidate companions would significantly increase the census of young planetary mass companions around extremely young brown dwarfs. These candidate companions are too faint to be observed with ground-based laser guide star adaptive optics (LGS AO) nor is the 1.4 um water feature observable from the ground for such faint objects due to telluric absorption, thus HST is the only telescope in the world suitable for these observations.

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.

Evolutionary genetics of maternal effects

PubMed Central

Wolf, Jason B.; Wade, Michael J.

2016-01-01

Maternal genetic effects (MGEs), where genes expressed by mothers affect the phenotype of their offspring, are important sources of phenotypic diversity in a myriad of organisms. We use a single‐locus model to examine how MGEs contribute patterns of heritable and nonheritable variation and influence evolutionary dynamics in randomly mating and inbreeding populations. We elucidate the influence of MGEs by examining the offspring genotype‐phenotype relationship, which determines how MGEs affect evolutionary dynamics in response to selection on offspring phenotypes. This approach reveals important results that are not apparent from classic quantitative genetic treatments of MGEs. We show that additive and dominance MGEs make different contributions to evolutionary dynamics and patterns of variation, which are differentially affected by inbreeding. Dominance MGEs make the offspring genotype‐phenotype relationship frequency dependent, resulting in the appearance of negative frequency‐dependent selection, while additive MGEs contribute a component of parent‐of‐origin dependent variation. Inbreeding amplifies the contribution of MGEs to the additive genetic variance and, therefore enhances their evolutionary response. Considering evolutionary dynamics of allele frequency change on an adaptive landscape, we show that this landscape differs from the mean fitness surface, and therefore, under some condition, fitness peaks can exist but not be “available” to the evolving population. PMID:26969266

Non-blind acoustic invisibility by dual layers of homogeneous single-negative media

NASA Astrophysics Data System (ADS)

Gao, He; Zhu, Yi-Fan; Fan, Xu-Dong; Liang, Bin; Yang, Jing; Cheng, Jian-Chun

2017-02-01

Non-blind invisibility cloaks allowing the concealed object to sense the outside world have great application potentials such as in high-precision sensing or underwater camouflage. However the existing designs based on coordinate transformation techniques need complicated spatially-varying negative index or intricate multi-layered configurations, substantially increasing the difficulty in practical realization. Here we report on the non-blind acoustic invisibility for a circular object in free space with simple distribution of cloak parameters. The mechanism is that, instead of utilizing the transformation acoustics technique, we develop the analytical formulae for fast prediction of the scattering from the object and then use an evolutionary optimization to retrieve the desired cloak parameters for minimizing the scattered field. In this way, it is proven possible to break through the fundamental limit of complementary condition that must be satisfied by the effective parameters of the components in transformation acoustics-based cloaks. Numerical results show that the resulting cloak produces a non-bflind invisibility as perfect as in previous designs, but only needs two layers with homogenous single-negative parameters. With full simplification in parameter distribution and broken symmetry in complementary relationship, our scheme opens new route to free-space non-blind invisibility, taking a significant step towards real-world application of cloaking devices.

Non-blind acoustic invisibility by dual layers of homogeneous single-negative media

PubMed Central

Gao, He; Zhu, Yi-fan; Fan, Xu-dong; Liang, Bin; Yang, Jing; Cheng, Jian-Chun

2017-01-01

Non-blind invisibility cloaks allowing the concealed object to sense the outside world have great application potentials such as in high-precision sensing or underwater camouflage. However the existing designs based on coordinate transformation techniques need complicated spatially-varying negative index or intricate multi-layered configurations, substantially increasing the difficulty in practical realization. Here we report on the non-blind acoustic invisibility for a circular object in free space with simple distribution of cloak parameters. The mechanism is that, instead of utilizing the transformation acoustics technique, we develop the analytical formulae for fast prediction of the scattering from the object and then use an evolutionary optimization to retrieve the desired cloak parameters for minimizing the scattered field. In this way, it is proven possible to break through the fundamental limit of complementary condition that must be satisfied by the effective parameters of the components in transformation acoustics-based cloaks. Numerical results show that the resulting cloak produces a non-bflind invisibility as perfect as in previous designs, but only needs two layers with homogenous single-negative parameters. With full simplification in parameter distribution and broken symmetry in complementary relationship, our scheme opens new route to free-space non-blind invisibility, taking a significant step towards real-world application of cloaking devices. PMID:28195227

Evolutionary ecology of resprouting and seeding in fire-prone ecosystems

USGS Publications Warehouse

Pausas, Juli G.; Keeley, Jon E.

2014-01-01

There are two broad mechanisms by which plant populations persist under recurrent disturbances: resprouting from surviving tissues, and seedling recruitment. Species can have one of these mechanisms or both. However, a coherent framework explaining the differential evolutionary pressures driving these regeneration mechanisms is lacking. We propose a bottom-up approach in addressing this question that considers the relative survivorship of adults and juveniles in an evolutionary context, based on two assumptions. First, resprouting and seeding can be interpreted by analogy with annual versus perennial life histories; that is, if we consider disturbance cycles to be analogous to annual cycles, then resprouting species are analogous to the perennial life history with iteroparous reproduction, and obligate seeding species that survive disturbances solely through seed banks are analogous to the annual life history with semelparous reproduction. Secondly, changes in the selective regimes differentially modify the survival rates of adults and juveniles and thus the relative costs and benefits of resprouting versus seeding. Our approach provides a framework for understanding temporal and spatial variation in resprouting and seeding under crown-fire regimes. It accounts for patterns of coexistence and environmental changes that contribute to the evolution of seeding from resprouting ancestors.

Evolution of High Mobility Group Nucleosome-Binding Proteins and Its Implications for Vertebrate Chromatin Specialization

PubMed Central

González-Romero, Rodrigo; Eirín-López, José M.; Ausió, Juan

2015-01-01

High mobility group (HMG)-N proteins are a family of small nonhistone proteins that bind to nucleosomes (N). Despite the amount of information available on their structure and function, there is an almost complete lack of information on the molecular evolutionary mechanisms leading to their exclusive differentiation. In the present work, we provide evidence suggesting that HMGN lineages constitute independent monophyletic groups derived from a common ancestor prior to the diversification of vertebrates. Based on observations of the functional diversification across vertebrate HMGN proteins and on the extensive silent nucleotide divergence, our results suggest that the long-term evolution of HMGNs occurs under strong purifying selection, resulting from the lineage-specific functional constraints of their different protein domains. Selection analyses on independent lineages suggest that their functional specialization was mediated by bursts of adaptive selection at specific evolutionary times, in a small subset of codons with functional relevance—most notably in HMGN1, and in the rapidly evolving HMGN5. This work provides useful information to our understanding of the specialization imparted on chromatin metabolism by HMGNs, especially on the evolutionary mechanisms underlying their functional differentiation in vertebrates. PMID:25281808

Characteristics of a Signal Data Converter for a Multi-runway Visibility Measuring System

DOT National Transportation Integrated Search

1971-10-01

The characteristics of a signal data converter (SDC) are developed with application to airport visibility measuring systems. The SDC is discussed in the context of an evolutionary growth of the visibility measuring system stemming from the present FA...

Shape design of internal cooling passages within a turbine blade

NASA Astrophysics Data System (ADS)

Nowak, Grzegorz; Nowak, Iwona

2012-04-01

The article concerns the optimization of the shape and location of non-circular passages cooling the blade of a gas turbine. To model the shape, four Bezier curves which form a closed profile of the passage were used. In order to match the shape of the passage to the blade profile, a technique was put forward to copy and scale the profile fragments into the component, and build the outline of the passage on the basis of them. For so-defined cooling passages, optimization calculations were carried out with a view to finding their optimal shape and location in terms of the assumed objectives. The task was solved as a multi-objective problem with the use of the Pareto method, for a cooling system composed of four and five passages. The tool employed for the optimization was the evolutionary algorithm. The article presents the impact of the population on the task convergence, and discusses the impact of different optimization objectives on the Pareto optimal solutions obtained. Due to the problem of different impacts of individual objectives on the position of the solution front which was noticed during the calculations, a two-step optimization procedure was introduced. Also, comparative optimization calculations for the scalar objective function were carried out and set up against the non-dominated solutions obtained in the Pareto approach. The optimization process resulted in a configuration of the cooling system that allows a significant reduction in the temperature of the blade and its thermal stress.

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.

Isotropic differential phase contrast microscopy for quantitative phase bio-imaging.

PubMed

Chen, Hsi-Hsun; Lin, Yu-Zi; Luo, Yuan

2018-05-16

Quantitative phase imaging (QPI) has been investigated to retrieve optical phase information of an object and applied to biological microscopy and related medical studies. In recent examples, differential phase contrast (DPC) microscopy can recover phase image of thin sample under multi-axis intensity measurements in wide-field scheme. Unlike conventional DPC, based on theoretical approach under partially coherent condition, we propose a new method to achieve isotropic differential phase contrast (iDPC) with high accuracy and stability for phase recovery in simple and high-speed fashion. The iDPC is simply implemented with a partially coherent microscopy and a programmable thin-film transistor (TFT) shield to digitally modulate structured illumination patterns for QPI. In this article, simulation results show consistency of our theoretical approach for iDPC under partial coherence. In addition, we further demonstrate experiments of quantitative phase images of a standard micro-lens array, as well as label-free live human cell samples. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Phenotypic divergence despite low genetic differentiation in house sparrow populations.

PubMed

Ben Cohen, Shachar; Dor, Roi

2018-01-10

Studying patterns of phenotypic variation among populations can shed light on the drivers of evolutionary processes. The house sparrow (Passer domesticus) is one of the world's most ubiquitous bird species, as well as a successful invader. We investigated phenotypic variation in house sparrow populations across a climatic gradient and in relation to a possible scenario of an invasion. We measured variation in morphological, coloration, and behavioral traits (exploratory behavior and neophobia) and compared it to the neutral genetic variation. We found that sparrows were larger and darker in northern latitudes, in accordance with Bergmann's and Gloger's biogeographic rules. Morphology and behavior mostly differed between the southernmost populations and the other regions, supporting the possibility of an invasion. Genetic differentiation was low and diversity levels were similar across populations, indicating high gene flow. Nevertheless, the southernmost and northern populations differed genetically to some extent. Furthermore, genetic differentiation (F ST ) was lower in comparison to phenotypic variation (P ST ), indicating that the phenotypic variation is shaped by directional selection or by phenotypic plasticity. This study expands our knowledge on evolutionary mechanisms and biological invasions.

Differentiated evolutionary relationships among chordates from comparative alignments of multiple sequences of MyoD and MyoG myogenic regulatory factors.

PubMed

Oliani, L C; Lidani, K C F; Gabriel, J E

2015-10-16

MyoD and MyoG are transcription factors that have essential roles in myogenic lineage determination and muscle differentiation. The purpose of this study was to compare multiple amino acid sequences of myogenic regulatory proteins to infer evolutionary relationships among chordates. Protein sequences from Mus musculus (P10085 and P12979), human Homo sapiens (P15172 and P15173), bovine Bos taurus (Q7YS82 and Q7YS81), wild pig Sus scrofa (P49811 and P49812), quail Coturnix coturnix (P21572 and P34060), chicken Gallus gallus (P16075 and P17920), rat Rattus norvegicus (Q02346 and P20428), domestic water buffalo Bubalus bubalis (D2SP11 and A7L034), and sheep Ovis aries (Q90477 and D3YKV7) were searched from a non-redundant protein sequence database UniProtKB/Swiss-Prot, and subsequently analyzed using the Mega6.0 software. MyoD evolutionary analyses revealed the presence of three main clusters with all mammals branched in one cluster, members of the order Rodentia (mouse and rat) in a second branch linked to the first, and birds of the order Galliformes (chicken and quail) remaining isolated in a third. MyoG evolutionary analyses aligned sequences in two main clusters, all mammalian specimens grouped in different sub-branches, and birds clustered in a second branch. These analyses suggest that the evolution of MyoD and MyoG was driven by different pathways.

Evolutionary Games in Multi-Agent Systems of Weighted Social Networks

NASA Astrophysics Data System (ADS)

Du, Wen-Bo; Cao, Xian-Bin; Zheng, Hao-Ran; Zhou, Hong; Hu, Mao-Bin

Much empirical evidence has shown realistic networks are weighted. Compared with those on unweighted networks, the dynamics on weighted network often exhibit distinctly different phenomena. In this paper, we investigate the evolutionary game dynamics (prisoner's dilemma game and snowdrift game) on a weighted social network consisted of rational agents and focus on the evolution of cooperation in the system. Simulation results show that the cooperation level is strongly affected by the weighted nature of the network. Moreover, the variation of time series has also been investigated. Our work may be helpful in understanding the cooperative behavior in the social systems.

Parallel evolution of image processing tools for multispectral imagery

NASA Astrophysics Data System (ADS)

Harvey, Neal R.; Brumby, Steven P.; Perkins, Simon J.; Porter, Reid B.; Theiler, James P.; Young, Aaron C.; Szymanski, John J.; Bloch, Jeffrey J.

2000-11-01

We describe the implementation and performance of a parallel, hybrid evolutionary-algorithm-based system, which optimizes image processing tools for feature-finding tasks in multi-spectral imagery (MSI) data sets. Our system uses an integrated spatio-spectral approach and is capable of combining suitably-registered data from different sensors. We investigate the speed-up obtained by parallelization of the evolutionary process via multiple processors (a workstation cluster) and develop a model for prediction of run-times for different numbers of processors. We demonstrate our system on Landsat Thematic Mapper MSI , covering the recent Cerro Grande fire at Los Alamos, NM, USA.

Genomics and evolutionary aspect of calcium signaling event in calmodulin and calmodulin-like proteins in plants.

PubMed

Mohanta, Tapan Kumar; Kumar, Pradeep; Bae, Hanhong

2017-02-03

Ca 2+ ion is a versatile second messenger that operate in a wide ranges of cellular processes that impact nearly every aspect of life. Ca 2+ regulates gene expression and biotic and abiotic stress responses in organisms ranging from unicellular algae to multi-cellular higher plants through the cascades of calcium signaling processes. In this study, we deciphered the genomics and evolutionary aspects of calcium signaling event of calmodulin (CaM) and calmodulin like- (CML) proteins. We studied the CaM and CML gene family of 41 different species across the plant lineages. Genomic analysis showed that plant encodes more calmodulin like-protein than calmodulins. Further analyses showed, the majority of CMLs were intronless, while CaMs were intron rich. Multiple sequence alignment showed, the EF-hand domain of CaM contains four conserved D-x-D motifs, one in each EF-hand while CMLs contain only one D-x-D-x-D motif in the fourth EF-hand. Phylogenetic analysis revealed that, the CMLs were evolved earlier than CaM and later diversified. Gene expression analysis demonstrated that different CaM and CMLs genes were express differentially in different tissues in a spatio-temporal manner. In this study we provided in detailed genome-wide identifications and characterization of CaM and CML protein family, phylogenetic relationships, and domain structure. Expression study of CaM and CML genes were conducted in Glycine max and Phaseolus vulgaris. Our study provides a strong foundation for future functional research in CaM and CML gene family in plant kingdom.

Spiny trapdoor spiders (Euoplos) of eastern Australia: Broadly sympatric clades are differentiated by burrow architecture and male morphology.

PubMed

Wilson, Jeremy D; Hughes, Jane M; Raven, Robert J; Rix, Michael G; Schmidt, Daniel J

2018-05-01

Spiders of the infraorder Mygalomorphae are fast becoming model organisms for the study of biogeography and speciation. However, these spiders can be difficult to study in the absence of fundamental life history information. In particular, their cryptic nature hinders comprehensive sampling, and linking males with conspecific females can be challenging. Recently discovered differences in burrow entrance architecture and male morphology indicated that these challenges may have impeded our understanding of the trapdoor spider genus Euoplos in Australia's eastern mesic zone. We investigated the evolutionary significance of these discoveries using a multi-locus phylogenetic approach. Our results revealed the existence of a second, previously undocumented, lineage of Euoplos in the eastern mesic zone. This new lineage occurs in sympatry with a lineage previously known from the region, and the two are consistently divergent in their burrow entrance architecture and male morphology, revealing the suitability of these characters for use in phylogenetic studies. Divergent burrow entrance architecture and observed differences in microhabitat preferences are suggested to facilitate sympatry and syntopy between the lineages. Finally, by investigating male morphology and plotting it onto the phylogeny, we revealed that the majority of Euoplos species remain undescribed, and that males of an unnamed species from the newly discovered lineage had historically been linked, erroneously, to a described species from the opposite lineage. This paper clarifies the evolutionary relationships underlying life history diversity in the Euoplos of eastern Australia, and provides a foundation for urgently needed taxonomic revision of this genus. Copyright © 2018 Elsevier Inc. All rights reserved.

Automated design of spacecraft systems power subsystems

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

The Relationship between College Zoology Students' Beliefs about Evolutionary Theory and Religion.

ERIC Educational Resources Information Center

Sinclair, Anne; And Others

1997-01-01

Researchers administered surveys to college zoology students prior to, and immediately following a study of evolutionary theory, to assess their understanding and acceptance of evidence supporting the theory. Results showed students had many misconceptions about the theory. Their beliefs interfered with their ability to objectively view scientific…

The Genetic Precursors and the Advantageous and Disadvantageous Sequelae of Inhibited Temperament: An Evolutionary Perspective

PubMed Central

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

2014-01-01

Guided by evolutionary game theory (Korte, Koolhaas, Wingfield, & McEwen, 2005), this study aimed to identify the genetic precursors and the psychosocial sequelae of inhibited temperament in a sociodemographically disadvantaged and racially diverse sample of 201 two-year-old children who experienced elevated levels of domestic violence. Using a multi-method, prospective design across three annual measurement occasions, SEM analyses indicated that trained observer ratings of inhibited temperament at age two were uniquely predicted by polymorphisms in dopamine and serotonin transporter genes. Children's inhibited temperament, in turn, indirectly predicted decreases in their externalizing problems at age four through its association with greater behavioral flexibility at three years of age. Results highlight the value of integrating evolutionary and developmental conceptualizations in more comprehensively charting the developmental cascades of inhibited temperament. PMID:23527493

Evolutionary Design in Biological Physics and Materials Science

NASA Astrophysics Data System (ADS)

Yang, M.; Park, J.-M.; Deem, M. W.

In this chapter we provide a thorough discussion of the theoretical description of the multi-site approach to cancer vaccination. The discussion is somewhat demanding from a biological point of view. References to primary biological publications are given. A general reference on immunology is [1].

Evolutionary design of a generalized polynomial neural network for modelling sediment transport in clean pipes

NASA Astrophysics Data System (ADS)

Ebtehaj, Isa; Bonakdari, Hossein; Khoshbin, Fatemeh

2016-10-01

To determine the minimum velocity required to prevent sedimentation, six different models were proposed to estimate the densimetric Froude number (Fr). The dimensionless parameters of the models were applied along with a combination of the group method of data handling (GMDH) and the multi-target genetic algorithm. Therefore, an evolutionary design of the generalized GMDH was developed using a genetic algorithm with a specific coding scheme so as not to restrict connectivity configurations to abutting layers only. In addition, a new preserving mechanism by the multi-target genetic algorithm was utilized for the Pareto optimization of GMDH. The results indicated that the most accurate model was the one that used the volumetric concentration of sediment (CV), relative hydraulic radius (d/R), dimensionless particle number (Dgr) and overall sediment friction factor (λs) in estimating Fr. Furthermore, the comparison between the proposed method and traditional equations indicated that GMDH is more accurate than existing equations.

An adaptive framework to differentiate receiving water quality impacts on a multi-scale level.

PubMed

Blumensaat, F; Tränckner, J; Helm, B; Kroll, S; Dirckx, G; Krebs, P

2013-01-01

The paradigm shift in recent years towards sustainable and coherent water resources management on a river basin scale has changed the subject of investigations to a multi-scale problem representing a great challenge for all actors participating in the management process. In this regard, planning engineers often face an inherent conflict to provide reliable decision support for complex questions with a minimum of effort. This trend inevitably increases the risk to base decisions upon uncertain and unverified conclusions. This paper proposes an adaptive framework for integral planning that combines several concepts (flow balancing, water quality monitoring, process modelling, multi-objective assessment) to systematically evaluate management strategies for water quality improvement. As key element, an S/P matrix is introduced to structure the differentiation of relevant 'pressures' in affected regions, i.e. 'spatial units', which helps in handling complexity. The framework is applied to a small, but typical, catchment in Flanders, Belgium. The application to the real-life case shows: (1) the proposed approach is adaptive, covers problems of different spatial and temporal scale, efficiently reduces complexity and finally leads to a transparent solution; and (2) water quality and emission-based performance evaluation must be done jointly as an emission-based performance improvement does not necessarily lead to an improved water quality status, and an assessment solely focusing on water quality criteria may mask non-compliance with emission-based standards. Recommendations derived from the theoretical analysis have been put into practice.

Shaking the Tree: Multi-locus Sequence Typing Usurps Current Onchocercid (Filarial Nematode) Phylogeny

PubMed Central

Lefoulon, Emilie; Bourret, Jérôme; Junker, Kerstin; Guerrero, Ricardo; Cañizales, Israel; Kuzmin, Yuriy; Satoto, Tri Baskoro T.; Cardenas-Callirgos, Jorge Manuel; de Souza Lima, Sueli; Raccurt, Christian; Mutafchiev, Yasen; Gavotte, Laurent; Martin, Coralie

2015-01-01

During the past twenty years, a number of molecular analyses have been performed to determine the evolutionary relationships of Onchocercidae, a family of filarial nematodes encompassing several species of medical or veterinary importance. However, opportunities for broad taxonomic sampling have been scarce, and analyses were based mainly on 12S rDNA and coxI gene sequences. While being suitable for species differentiation, these mitochondrial genes cannot be used to infer phylogenetic hypotheses at higher taxonomic levels. In the present study, 48 species, representing seven of eight subfamilies within the Onchocercidae, were sampled and sequences of seven gene loci (nuclear and mitochondrial) analysed, resulting in the hitherto largest molecular phylogenetic investigation into this family. Although our data support the current hypothesis that the Oswaldofilariinae, Waltonellinae and Icosiellinae subfamilies separated early from the remaining onchocercids, Setariinae was recovered as a well separated clade. Dirofilaria, Loxodontofilaria and Onchocerca constituted a strongly supported clade despite belonging to different subfamilies (Onchocercinae and Dirofilariinae). Finally, the separation between Splendidofilariinae, Dirofilariinae and Onchocercinae will have to be reconsidered. PMID:26588229

Multi-objective Optimization Design of Gear Reducer Based on Adaptive Genetic Algorithms

NASA Astrophysics Data System (ADS)

Li, Rui; Chang, Tian; Wang, Jianwei; Wei, Xiaopeng; Wang, Jinming

2008-11-01

An adaptive Genetic Algorithm (GA) is introduced to solve the multi-objective optimized design of the reducer. Firstly, according to the structure, strength, etc. in a reducer, a multi-objective optimized model of the helical gear reducer is established. And then an adaptive GA based on a fuzzy controller is introduced, aiming at the characteristics of multi-objective, multi-parameter, multi-constraint conditions. Finally, a numerical example is illustrated to show the advantages of this approach and the effectiveness of an adaptive genetic algorithm used in optimized design of a reducer.

The Needs of the Highly Able and the Needs of Society: A Multidisciplinary Analysis of Talent Differentiation and Its Significance to Gifted Education and Issues of Societal Inequality

ERIC Educational Resources Information Center

Persson, Roland S.

2014-01-01

Does gifted education affect societal inequality, and does societal inequality suppress and/or distort the development of high ability? Drawing from several academic disciplines and current political discourse, a differentiated use of terms used to describe the highly able is explored in this article. A social evolutionary framework is proposed as…

Creating ensembles of oblique decision trees with evolutionary algorithms and sampling

DOEpatents

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

2006-06-13

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

Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects.

PubMed

Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao

2016-01-01

Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems.

Improved multi-objective ant colony optimization algorithm and its application in complex reasoning

NASA Astrophysics Data System (ADS)

Wang, Xinqing; Zhao, Yang; Wang, Dong; Zhu, Huijie; Zhang, Qing

2013-09-01

The problem of fault reasoning has aroused great concern in scientific and engineering fields. However, fault investigation and reasoning of complex system is not a simple reasoning decision-making problem. It has become a typical multi-constraint and multi-objective reticulate optimization decision-making problem under many influencing factors and constraints. So far, little research has been carried out in this field. This paper transforms the fault reasoning problem of complex system into a paths-searching problem starting from known symptoms to fault causes. Three optimization objectives are considered simultaneously: maximum probability of average fault, maximum average importance, and minimum average complexity of test. Under the constraints of both known symptoms and the causal relationship among different components, a multi-objective optimization mathematical model is set up, taking minimizing cost of fault reasoning as the target function. Since the problem is non-deterministic polynomial-hard(NP-hard), a modified multi-objective ant colony algorithm is proposed, in which a reachability matrix is set up to constrain the feasible search nodes of the ants and a new pseudo-random-proportional rule and a pheromone adjustment mechinism are constructed to balance conflicts between the optimization objectives. At last, a Pareto optimal set is acquired. Evaluation functions based on validity and tendency of reasoning paths are defined to optimize noninferior set, through which the final fault causes can be identified according to decision-making demands, thus realize fault reasoning of the multi-constraint and multi-objective complex system. Reasoning results demonstrate that the improved multi-objective ant colony optimization(IMACO) can realize reasoning and locating fault positions precisely by solving the multi-objective fault diagnosis model, which provides a new method to solve the problem of multi-constraint and multi-objective fault diagnosis and reasoning of complex system.

Multi-Objectivising Combinatorial Optimisation Problems by Means of Elementary Landscape Decompositions.

PubMed

Ceberio, Josu; Calvo, Borja; Mendiburu, Alexander; Lozano, Jose A

2018-02-15

In the last decade, many works in combinatorial optimisation have shown that, due to the advances in multi-objective optimisation, the algorithms from this field could be used for solving single-objective problems as well. In this sense, a number of papers have proposed multi-objectivising single-objective problems in order to use multi-objective algorithms in their optimisation. In this article, we follow up this idea by presenting a methodology for multi-objectivising combinatorial optimisation problems based on elementary landscape decompositions of their objective function. Under this framework, each of the elementary landscapes obtained from the decomposition is considered as an independent objective function to optimise. In order to illustrate this general methodology, we consider four problems from different domains: the quadratic assignment problem and the linear ordering problem (permutation domain), the 0-1 unconstrained quadratic optimisation problem (binary domain), and the frequency assignment problem (integer domain). We implemented two widely known multi-objective algorithms, NSGA-II and SPEA2, and compared their performance with that of a single-objective GA. The experiments conducted on a large benchmark of instances of the four problems show that the multi-objective algorithms clearly outperform the single-objective approaches. Furthermore, a discussion on the results suggests that the multi-objective space generated by this decomposition enhances the exploration ability, thus permitting NSGA-II and SPEA2 to obtain better results in the majority of the tested instances.

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.

Repositioning forelimb superficialis muscles: tendon attachment and muscle activity enable active relocation of functional myofibers.

PubMed

Huang, Alice H; Riordan, Timothy J; Wang, Lingyan; Eyal, Shai; Zelzer, Elazar; Brigande, John V; Schweitzer, Ronen

2013-09-16

The muscles that govern hand motion are composed of extrinsic muscles that reside within the forearm and intrinsic muscles that reside within the hand. We find that the extrinsic muscles of the flexor digitorum superficialis (FDS) first differentiate as intrinsic muscles within the hand and then relocate as myofibers to their final position in the arm. This remarkable translocation of differentiated myofibers across a joint is dependent on muscle contraction and muscle-tendon attachment. Interestingly, the intrinsic flexor digitorum brevis (FDB) muscles of the foot are identical to the FDS in tendon pattern and delayed developmental timing but undergo limited muscle translocation, providing strong support for evolutionary homology between the FDS and FDB muscles. We propose that the intrinsic FDB pattern represents the original tetrapod limb and that translocation of the muscles to form the FDS is a mammalian evolutionary addition. Copyright © 2013 Elsevier Inc. All rights reserved.

Re-positioning forelimb superficialis muscles: tendon attachment and muscle activity enable active relocation of functional myofibers

PubMed Central

Huang, Alice H.; Riordan, Timothy J.; Wang, Lingyan; Eyal, Shai; Zelzer, Elazar; Brigande, John V.; Schweitzer, Ronen

2013-01-01

Summary The muscles that govern hand motion are composed of extrinsic muscles that reside within the forearm and intrinsic muscles that reside within the hand. We find that the extrinsic muscles of the flexor digitorum superficialis (FDS) first differentiate as intrinsic muscles within the hand and then relocate as myofibers to their final position in the arm. This unique translocation of differentiated myofibers across a joint is dependent on muscle contraction and muscle-tendon attachment. Interestingly, the intrinsic flexor digitorum brevis (FDB) muscles of the foot are identical to the FDS in tendon pattern and delayed developmental timing, but undergo limited muscle translocation, providing strong support for evolutionary homology between the FDS and FDB muscles. We propose that the intrinsic FDB pattern represents the original tetrapod limb and translocation of the muscles to form the FDS is a mammalian evolutionary addition. PMID:24044893

Peptide Signaling in Plant Development

PubMed Central

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

2011-01-01

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

The evolutionary theory of asymmetry by V. Geodakyan

NASA Astrophysics Data System (ADS)

Geodakyan, Sergey V.

2015-08-01

For more than 150 years, all biological theories, including those of C. Darwin and Mendel, were based on the idea of synchronous evolution. They fit for unitary monomodal systems (asexual, symmetrical) but do not work for binary (dioecious, asymmetrical) ones. Examples of such binary conjugated differentiations are two sexes, DNA-proteins, autosomes-sex chromosomes, right and left brain hemispheres, and hands. For their understanding, "asynchronous" theories are needed. Such theories were proposed by Russian theoretical biologist Vigen A. Geodakyan for sexual, brain and body, and chromosomal differentiations. All theories are interconnected and are based on the principle of conjugated subsystems. This article covers the basic tenets of the evolutionary theory of asymmetry and answers the following questions: What benefits does lateralization provide? What logic, what principle is it based on? Why do brain hemispheres control the opposite sides of the body? Why laterality is closely related to sex? What are the biological prerequisites of terrorism?

The competition between thermal contraction and differentiation in the stress history of the moon

NASA Astrophysics Data System (ADS)

Kirk, Randolph L.; Stevenson, David J.

1989-09-01

The stress history of the moon is discussed, taking into consideration the effects of thermal contraction and differentiation. The amount of expansion caused by extracting basalt from undifferentiated lunar material is estimated taking account of the uncertainty in the knowledge of the appropriate compositions, and the resulting estimate of the expansion is used to compare the relative importance of the thermal and differentiation effects in the moon's volumetric history. The results of calculations show that differentiation is likely to be of major importance and, thus, thermal expansion is not the sole possible contributor to evolutionary changes in the lunar radius.

A Spectroscopic Study of Young Stellar Objects in the Serpens Cloud Core and NGC 1333

NASA Astrophysics Data System (ADS)

Winston, E.; Megeath, S. T.; Wolk, S. J.; Hernandez, J.; Gutermuth, R.; Muzerolle, J.; Hora, J. L.; Covey, K.; Allen, L. E.; Spitzbart, B.; Peterson, D.; Myers, P.; Fazio, G. G.

2009-06-01

We present spectral observations of 130 young stellar objects (YSOs) in the Serpens Cloud Core and NGC 1333 embedded clusters. The observations consist of near-IR spectra in the H and K bands from SpeX on the IRTF and far-red spectra (6000-9000 Å) from Hectospec on the Multi-Mirror Telescope. These YSOs were identified in previous Spitzer and Chandra observations, and the evolutionary classes of the YSOs were determined from the Spitzer mid-IR photometry. With these spectra we search for corroborating evidence for the pre-main-sequence nature of the objects, study the properties of the detected emission lines as a function of evolutionary class, and obtain spectral types for the observed YSOs. The temperatures implied by the spectral types are combined with luminosities determined from the near-IR photometry to construct Hertzsprung-Russell (H-R) diagrams for the clusters. By comparing the positions of the YSOs in the H-R diagrams with the pre-main-sequence tracks of Baraffe (1998), we determine the ages of the embedded sources and study the relative ages of the YSOs with and without optically thick circumstellar disks. The apparent isochronal ages of the YSOs in both clusters range from less than 1 Myr to 10 Myr, with most objects below 3 Myr. The observed distributions of ages for the Class II and Class III objects are statistically indistinguishable. We examine the spatial distribution and extinction of the YSOs as a function of their isochronal ages. We find the sources <3 Myr to be concentrated in the molecular cloud gas, while the older sources are spatially dispersed and are not deeply embedded. Nonetheless, the sources with isochronal ages >3 Myr show all the characteristics of YSOs in their spectra, their IR spectral energy distributions, and their X-ray emission; we find no evidence that they are contaminating background giants or foreground dwarfs. However, we find no corresponding decrease in the fraction of sources with infrared excess with isochronal age; this suggests that the older isochronal ages may not measure the true age of the >3 Myr YSOs. Thus, the nature of the apparently older sources and their implications for cluster formation remain unresolved.

Observational Effects of Magnetism in O Stars: Surface Nitrogen Abundances

NASA Technical Reports Server (NTRS)

Martins, F.; Escolano, C.; Wade, G. A.; Donati, J. F.; Bouret, J. C.

2011-01-01

Aims. We investigate the surface nitrogen content of the six magnetic O stars known to date as well as of the early B-type star Tau Sco.. We compare these abundances to predictions of evolutionary models to isolate the effects of magnetic field on the transport of elements in stellar interiors. Methods. We conduct a quantitative spectroscopic analysis of the ample stars with state-of-the-art atmosphere models. We rely on high signal-to-noise ratio, high resolution optical spectra obtained with ESPADONS at CFHT and NARVAL at TBL. Atmosphere models and synthetic spectra are computed with the code CMFGEN. Values of N/H together with their uncertainties are determined and compared to predictions of evolutionary models. Results. We find that the magnetic stars can be divided into two groups: one with stars displaying no N enrichment (one object); and one with stars most likely showing extra N enrichment (5 objects). For one star (Ori C) no robust conclusion can be drawn due to its young age. The star with no N enrichment is the one with the weakest magnetic field, possibly of dynamo origin. It might be a star having experienced strong magnetic braking under the condition of solid body rotation, but its rotational velocity is still relatively large. The five stars with high N content were probably slow rotators on the zero age main sequence, but they have surface N/H typical of normal O stars, indicating that the presence of a (probably fossil) magnetic field leads to extra enrichment. These stars may have a strong differential rotation inducing shear mixing. Our results shOuld be viewed as a basis on which new theoretical simulations can rely to better understand the effect of magnetism on the evolution of massive stars.

Concepts in solid tumor evolution.

PubMed

Sidow, Arend; Spies, Noah

2015-04-01

Evolutionary mechanisms in cancer progression give tumors their individuality. Cancer evolution is different from organismal evolution, however, and we discuss where concepts from evolutionary genetics are useful or limited in facilitating an understanding of cancer. Based on these concepts we construct and apply the simplest plausible model of tumor growth and progression. Simulations using this simple model illustrate the importance of stochastic events early in tumorigenesis, highlight the dominance of exponential growth over linear growth and differentiation, and explain the clonal substructure of tumors. Copyright © 2015 Elsevier Ltd. All rights reserved.

Developmental biology, the stem cell of biological disciplines.

PubMed

Gilbert, Scott F

2017-12-01

Developmental biology (including embryology) is proposed as "the stem cell of biological disciplines." Genetics, cell biology, oncology, immunology, evolutionary mechanisms, neurobiology, and systems biology each has its ancestry in developmental biology. Moreover, developmental biology continues to roll on, budding off more disciplines, while retaining its own identity. While its descendant disciplines differentiate into sciences with a restricted set of paradigms, examples, and techniques, developmental biology remains vigorous, pluripotent, and relatively undifferentiated. In many disciplines, especially in evolutionary biology and oncology, the developmental perspective is being reasserted as an important research program.

Different roles of TGF-β in the multi-lineage differentiation of stem cells

PubMed Central

Wang, Ming-Ke; Sun, Hui-Qin; Xiang, Ying-Chun; Jiang, Fan; Su, Yong-Ping; Zou, Zhong-Min

2012-01-01

Stem cells are a population of cells that has infinite or long-term self-renewal ability and can produce various kinds of descendent cells. Transforming growth factor β (TGF-β) family is a superfamily of growth factors, including TGF-β1, TGF-β2 and TGF-β3, bone morphogenetic proteins, activin/inhibin, and some other cytokines such as nodal, which plays very important roles in regulating a wide variety of biological processes, such as cell growth, differentiation, cell death. TGF-β, a pleiotropic cytokine, has been proved to be differentially involved in the regulation of multi-lineage differentiation of stem cells, through the Smad pathway, non-Smad pathways including mitogen-activated protein kinase pathways, phosphatidylinositol-3-kinase/AKT pathways and Rho-like GTPase signaling pathways, and their cross-talks. For instance, it is generally known that TGF-β promotes the differentiation of stem cells into smooth muscle cells, immature cardiomyocytes, chondrocytes, neurocytes, hepatic stellate cells, Th17 cells, and dendritic cells. However, TGF-β inhibits the differentiation of stem cells into myotubes, adipocytes, endothelial cells, and natural killer cells. Additionally, TGF-β can provide competence for early stages of osteoblastic differentiation, but at late stages TGF-β acts as an inhibitor. The three mammalian isoforms (TGF-β1, 2 and 3) have distinct but overlapping effects on hematopoiesis. Understanding the mechanisms underlying the regulatory effect of TGF-β in the stem cell multi-lineage differentiation is of importance in stem cell biology, and will facilitate both basic research and clinical applications of stem cells. In this article, we discuss the current status and progress in our understanding of different mechanisms by which TGF-β controls multi-lineage differentiation of stem cells. PMID:22993659

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…

Generative Representations for Evolving Families of Designs

NASA Technical Reports Server (NTRS)

Hornby, Gregory S.

2003-01-01

Since typical evolutionary design systems encode only a single artifact with each individual, each time the objective changes a new set of individuals must be evolved. When this objective varies in a way that can be parameterized, a more general method is to use a representation in which a single individual encodes an entire class of artifacts. In addition to saving time by preventing the need for multiple evolutionary runs, the evolution of parameter-controlled designs can create families of artifacts with the same style and a reuse of parts between members of the family. In this paper an evolutionary design system is described which uses a generative representation to encode families of designs. Because a generative representation is an algorithmic encoding of a design, its input parameters are a way to control aspects of the design it generates. By evaluating individuals multiple times with different input parameters the evolutionary design system creates individuals in which the input parameter controls specific aspects of a design. This system is demonstrated on two design substrates: neural-networks which solve the 3/5/7-parity problem and three-dimensional tables of varying heights.

Resolving the Mortierellaceae phylogeny through Multi-Locus Sequence Typing (MLST) and phylogenomics

USDA-ARS?s Scientific Manuscript database

The Mortierellaceae (Mortierellomycotina) are a diverse family of fungi that are of evolutionary and ecological relevance. They are the closest lineage to the arbuscular mycorrhizae (Glomeromycotina) and include some of the first species to evolve fruiting body production. The Mortierellaceae are es...

Digital fabrication of multi-material biomedical objects.

PubMed

Cheung, H H; Choi, S H

2009-12-01

This paper describes a multi-material virtual prototyping (MMVP) system for modelling and digital fabrication of discrete and functionally graded multi-material objects for biomedical applications. The MMVP system consists of a DMMVP module, an FGMVP module and a virtual reality (VR) simulation module. The DMMVP module is used to model discrete multi-material (DMM) objects, while the FGMVP module is for functionally graded multi-material (FGM) objects. The VR simulation module integrates these two modules to perform digital fabrication of multi-material objects, which can be subsequently visualized and analysed in a virtual environment to optimize MMLM processes for fabrication of product prototypes. Using the MMVP system, two biomedical objects, including a DMM human spine and an FGM intervertebral disc spacer are modelled and digitally fabricated for visualization and analysis in a VR environment. These studies show that the MMVP system is a practical tool for modelling, visualization, and subsequent fabrication of biomedical objects of discrete and functionally graded multi-materials for biomedical applications. The system may be adapted to control MMLM machines with appropriate hardware for physical fabrication of biomedical objects.

Evolution of Bow-Tie Architectures in Biology

PubMed Central

Friedlander, Tamar; Mayo, Avraham E.; Tlusty, Tsvi; Alon, Uri

2015-01-01

Bow-tie or hourglass structure is a common architectural feature found in many biological systems. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. Little is known, however, about how bow-tie architectures evolve. Here, we address the evolution of bow-tie architectures using simulations of multi-layered systems evolving to fulfill a given input-output goal. We find that bow-ties spontaneously evolve when the information in the evolutionary goal can be compressed. Mathematically speaking, bow-ties evolve when the rank of the input-output matrix describing the evolutionary goal is deficient. The maximal compression possible (the rank of the goal) determines the size of the narrowest part of the network—that is the bow-tie. A further requirement is that a process is active to reduce the number of links in the network, such as product-rule mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations. This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the effective rank of the goals under which they evolved. PMID:25798588

Large-scale hydropower system optimization using dynamic programming and object-oriented programming: the case of the Northeast China Power Grid.

PubMed

Li, Ji-Qing; Zhang, Yu-Shan; Ji, Chang-Ming; Wang, Ai-Jing; Lund, Jay R

2013-01-01

This paper examines long-term optimal operation using dynamic programming for a large hydropower system of 10 reservoirs in Northeast China. Besides considering flow and hydraulic head, the optimization explicitly includes time-varying electricity market prices to maximize benefit. Two techniques are used to reduce the 'curse of dimensionality' of dynamic programming with many reservoirs. Discrete differential dynamic programming (DDDP) reduces the search space and computer memory needed. Object-oriented programming (OOP) and the ability to dynamically allocate and release memory with the C++ language greatly reduces the cumulative effect of computer memory for solving multi-dimensional dynamic programming models. The case study shows that the model can reduce the 'curse of dimensionality' and achieve satisfactory results.

Core principles of evolutionary medicine

PubMed Central

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

2018-01-01

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

Genetic architecture and balancing selection: the life and death of differentiated variants.

PubMed

Llaurens, Violaine; Whibley, Annabel; Joron, Mathieu

2017-05-01

Balancing selection describes any form of natural selection, which results in the persistence of multiple variants of a trait at intermediate frequencies within populations. By offering up a snapshot of multiple co-occurring functional variants and their interactions, systems under balancing selection can reveal the evolutionary mechanisms favouring the emergence and persistence of adaptive variation in natural populations. We here focus on the mechanisms by which several functional variants for a given trait can arise, a process typically requiring multiple epistatic mutations. We highlight how balancing selection can favour specific features in the genetic architecture and review the evolutionary and molecular mechanisms shaping this architecture. First, balancing selection affects the number of loci underlying differentiated traits and their respective effects. Control by one or few loci favours the persistence of differentiated functional variants by limiting intergenic recombination, or its impact, and may sometimes lead to the evolution of supergenes. Chromosomal rearrangements, particularly inversions, preventing adaptive combinations from being dissociated are increasingly being noted as features of such systems. Similarly, due to the frequency of heterozygotes maintained by balancing selection, dominance may be a key property of adaptive variants. High heterozygosity and limited recombination also influence associated genetic load, as linked recessive deleterious mutations may be sheltered. The capture of deleterious elements in a locus under balancing selection may reinforce polymorphism by further promoting heterozygotes. Finally, according to recent genomewide scans, balanced polymorphism might be more pervasive than generally thought. We stress the need for both functional and ecological studies to characterize the evolutionary mechanisms operating in these systems. © 2017 John Wiley & Sons Ltd.

Promotion of cooperation induced by discriminators in the spatial multi-player donor-recipient game

NASA Astrophysics Data System (ADS)

Cui, Guang-Hai; Wang, Zhen; Ren, Jian-Kang; Lu, Kun; Li, Ming-Chu

2016-11-01

Although the two-player donor-recipient game has been used extensively in studying cooperation in social dilemmas, the scenario in which a donor can simultaneously donate resources to multiple recipients is also common in human societies, economic systems, and social networks. This paper formulates a model of the multi-player donor-recipient game considering a multi-recipient scenario. The promotion of cooperation is also studied by introducing a discriminative cooperation strategy into the game, which donates resources to recipients in proportion to their previous donations with a cost for the collection of information. The evolutionary dynamics of individual strategies are explored in homogeneous and heterogeneous scenarios by leveraging spatial evolutionary game theory. The results show that in a homogeneous scenario, defectors can dominate the network at the equilibrium state only when the cost-to-benefit ratio (R) of donated resources is large. In a heterogeneous scenario, three strategies can coexist all the time within the range of R that was studied, and the promotion of cooperation is more effective when the values of R are smaller. Results from a single node evolution and the formation of local patterns of interaction are provided, and it is analytically shown that discriminators can maintain fairness in resource donation and guarantee long-term cooperation when R is not too large.

Evolutionary public health: introducing the concept.

PubMed

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

2017-07-29

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

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

Diversity and adaptive evolution of Saccharomyces wine yeast: a review

PubMed Central

Marsit, Souhir; Dequin, Sylvie

2015-01-01

Saccharomyces cerevisiae and related species, the main workhorses of wine fermentation, have been exposed to stressful conditions for millennia, potentially resulting in adaptive differentiation. As a result, wine yeasts have recently attracted considerable interest for studying the evolutionary effects of domestication. The widespread use of whole-genome sequencing during the last decade has provided new insights into the biodiversity, population structure, phylogeography and evolutionary history of wine yeasts. Comparisons between S. cerevisiae isolates from various origins have indicated that a variety of mechanisms, including heterozygosity, nucleotide and structural variations, introgressions, horizontal gene transfer and hybridization, contribute to the genetic and phenotypic diversity of S. cerevisiae. This review will summarize the current knowledge on the diversity and evolutionary history of wine yeasts, focusing on the domestication fingerprints identified in these strains. PMID:26205244

Multi-Criteria Optimization of Regulation in Metabolic Networks

PubMed Central

Higuera, Clara; Villaverde, Alejandro F.; Banga, Julio R.; Ross, John; Morán, Federico

2012-01-01

Determining the regulation of metabolic networks at genome scale is a hard task. It has been hypothesized that biochemical pathways and metabolic networks might have undergone an evolutionary process of optimization with respect to several criteria over time. In this contribution, a multi-criteria approach has been used to optimize parameters for the allosteric regulation of enzymes in a model of a metabolic substrate-cycle. This has been carried out by calculating the Pareto set of optimal solutions according to two objectives: the proper direction of flux in a metabolic cycle and the energetic cost of applying the set of parameters. Different Pareto fronts have been calculated for eight different “environments” (specific time courses of end product concentrations). For each resulting front the so-called knee point is identified, which can be considered a preferred trade-off solution. Interestingly, the optimal control parameters corresponding to each of these points also lead to optimal behaviour in all the other environments. By calculating the average of the different parameter sets for the knee solutions more frequently found, a final and optimal consensus set of parameters can be obtained, which is an indication on the existence of a universal regulation mechanism for this system.The implications from such a universal regulatory switch are discussed in the framework of large metabolic networks. PMID:22848435

Application of the gravity search algorithm to multi-reservoir operation optimization

NASA Astrophysics Data System (ADS)

Bozorg-Haddad, Omid; Janbaz, Mahdieh; Loáiciga, Hugo A.

2016-12-01

Complexities in river discharge, variable rainfall regime, and drought severity merit the use of advanced optimization tools in multi-reservoir operation. The gravity search algorithm (GSA) is an evolutionary optimization algorithm based on the law of gravity and mass interactions. This paper explores the GSA's efficacy for solving benchmark functions, single reservoir, and four-reservoir operation optimization problems. The GSA's solutions are compared with those of the well-known genetic algorithm (GA) in three optimization problems. The results show that the GSA's results are closer to the optimal solutions than the GA's results in minimizing the benchmark functions. The average values of the objective function equal 1.218 and 1.746 with the GSA and GA, respectively, in solving the single-reservoir hydropower operation problem. The global solution equals 1.213 for this same problem. The GSA converged to 99.97% of the global solution in its average-performing history, while the GA converged to 97% of the global solution of the four-reservoir problem. Requiring fewer parameters for algorithmic implementation and reaching the optimal solution in fewer number of functional evaluations are additional advantages of the GSA over the GA. The results of the three optimization problems demonstrate a superior performance of the GSA for optimizing general mathematical problems and the operation of reservoir systems.

Multi-Objective Optimization for Speed and Stability of a Sony AIBO Gait

DTIC Science & Technology

2007-09-01

MULTI-OBJECTIVE OPTIMIZATION FOR SPEED AND STABILITY OF A SONY AIBO GAIT THESIS Christopher A. Patterson, Second Lieutenant, USAF AFIT/GCS...07-17 MULTI-OBJECTIVE OPTIMIZATION FOR SPEED AND STABILITY OF A SONY AIBO GAIT THESIS Presented to the Faculty Department of...MULTI-OBJECTIVE OPTIMIZATION FOR SPEED AND STABILITY OF A SONY AIBO GAIT Christopher A. Patterson, BS Second Lieutenant, USAF

An optimization model to design and manage subsurface drip irrigation system for alfalfa

NASA Astrophysics Data System (ADS)

Kandelous, M.; Kamai, T.; Vrugt, J. A.; Simunek, J.; Hanson, B.; Hopmans, J. W.

2010-12-01

Subsurface drip irrigation (SDI) is one of the most efficient and cost-effective methods for watering alfalfa plants. Lateral installation depth and distance, emitter discharge, and irrigation time and frequency of SDI, in addition to soil and climatic conditions affect alfalfa’s root water uptake and yield. Here we use a multi-objective optimization approach to find optimal SDI strategies. Our approach uses the AMALGAM evolutionary search method, in combination with the HYDRUS-2D unsaturated flow model to maximize water uptake by alfalfa’s plant roots, and minimize loss of irrigation and drainage water to the atmosphere or groundwater. We use a variety of different objective functions to analyze SDI. These criteria include the lateral installation depth and distance, the lateral discharge, irrigation duration, and irrigation frequency. Our framework includes explicit recognition of the soil moisture status during the simulation period to make sure that the top soil is dry for harvesting during the growing season. Initial results show a wide spectrum of optimized SDI strategies for different root distributions, soil textures and climate conditions. The developed tool should be useful in helping farmers optimize their irrigation strategy and design.

Gene-Culture Coevolution in a Social Cetacean: Integrating Acoustic and Genetic Data to Understand Population Structure in the Short-Finned Pilot Whale (Globicephala macrorhynchus)

NASA Astrophysics Data System (ADS)

Van Cise, Amy

The evolutionary ecology of a species is driven by a combination of random events, ecological and environmental mechanisms, and social behavior. Gene-culture coevolutionary theory attempts to understand the evolutionary trajectory of a species by examining the interactions between these potential drivers. Further, our choice of data type will affect the patterns we observe, therefore by integrating several types of data we achieve a holistic understanding of the various aspects of evolutionary ecology within a species. In order to understand population structure in short-finned pilot whales, I use a combination of genetic and acoustic data to examine structure on evolutionary (genetic) and cultural (acoustic) timescales. I first examine structure among geographic populations in the Pacific Ocean. Using genetic sequences from the mitochondrial control region, I show that two genetically and morphologically distinct types of short-finned pilot whale, described off the coast of Japan, have non-overlapping distributions throughout their range in the Pacific Ocean. Analysis of the acoustic features of their social calls indicates that they are acoustically differentiated, possibly due to limited communication between the two types. This evidence supports the hypothesis that the two types may be separate species or subspecies. Next, I examine structure among island communities and social groups within the Hawaiian Island population of short-finned pilot whales. Using a combination of mitochondrial and nuclear DNA, I showed that the hierarchical social structure in Hawaiian pilot whales is driven by genetic relatedness; individuals remain in groups with their immediate family members, and preferentially associate with relatives. Similarly, social structure affects genetic differentiation, likely by restricting access to mates. Acoustic differentiation among social groups indicates that social structure may also restrict the flow of cultural information, such as vocal repertoire or dialect. The qualitative correlation between social structure, cultural information transfer, and genetic structure suggest that gene-culture coevolution may be an important mechanism to the evolutionary ecology of short-finned pilot whales. Further research may reveal a similar structure in the transmission of ecological behaviors, such as diet preference, habitat use, or movements. The results of this research underscore the applicability of gene-culture coevolutionary theory to non-human taxa.

Multi-Tiered System of Support: Best Differentiation Practices for English Language Learners in Tier 1

ERIC Educational Resources Information Center

Izaguirre, Cecilia

2017-01-01

Purpose: This qualitative case study explored the best practices of differentiation of Tier 1 instruction within a multi-tiered system of support for English Language Learners who were predominately Spanish speaking. Theoretical Framework: The zone of proximal development theory, cognitive theory, and the affective filter hypothesis guided this…

Are there laws of genome evolution?

PubMed

Koonin, Eugene V

2011-08-01

Research in quantitative evolutionary genomics and systems biology led to the discovery of several universal regularities connecting genomic and molecular phenomic variables. These universals include the log-normal distribution of the evolutionary rates of orthologous genes; the power law-like distributions of paralogous family size and node degree in various biological networks; the negative correlation between a gene's sequence evolution rate and expression level; and differential scaling of functional classes of genes with genome size. The universals of genome evolution can be accounted for by simple mathematical models similar to those used in statistical physics, such as the birth-death-innovation model. These models do not explicitly incorporate selection; therefore, the observed universal regularities do not appear to be shaped by selection but rather are emergent properties of gene ensembles. Although a complete physical theory of evolutionary biology is inconceivable, the universals of genome evolution might qualify as "laws of evolutionary genomics" in the same sense "law" is understood in modern physics.

Conservation of sex chromosomes in lacertid lizards.

PubMed

Rovatsos, Michail; Vukić, Jasna; Altmanová, Marie; Johnson Pokorná, Martina; Moravec, Jiří; Kratochvíl, Lukáš

2016-07-01

Sex chromosomes are believed to be stable in endotherms, but young and evolutionary unstable in most ectothermic vertebrates. Within lacertids, the widely radiated lizard group, sex chromosomes have been reported to vary in morphology and heterochromatinization, which may suggest turnovers during the evolution of the group. We compared the partial gene content of the Z-specific part of sex chromosomes across major lineages of lacertids and discovered a strong evolutionary stability of sex chromosomes. We can conclude that the common ancestor of lacertids, living around 70 million years ago (Mya), already had the same highly differentiated sex chromosomes. Molecular data demonstrating an evolutionary conservation of sex chromosomes have also been documented for iguanas and caenophidian snakes. It seems that differences in the evolutionary conservation of sex chromosomes in vertebrates do not reflect the distinction between endotherms and ectotherms, but rather between amniotes and anamniotes, or generally, the differences in the life history of particular lineages. © 2016 John Wiley & Sons Ltd.

Analytical model for minority games with evolutionary learning

NASA Astrophysics Data System (ADS)

Campos, Daniel; Méndez, Vicenç; Llebot, Josep E.; Hernández, Germán A.

2010-06-01

In a recent work [D. Campos, J.E. Llebot, V. Méndez, Theor. Popul. Biol. 74 (2009) 16] we have introduced a biological version of the Evolutionary Minority Game that tries to reproduce the intraspecific competition for limited resources in an ecosystem. In comparison with the complex decision-making mechanisms used in standard Minority Games, only two extremely simple strategies ( juveniles and adults) are accessible to the agents. Complexity is introduced instead through an evolutionary learning rule that allows younger agents to learn taking better decisions. We find that this game shows many of the typical properties found for Evolutionary Minority Games, like self-segregation behavior or the existence of an oscillation phase for a certain range of the parameter values. However, an analytical treatment becomes much easier in our case, taking advantage of the simple strategies considered. Using a model consisting of a simple dynamical system, the phase diagram of the game (which differentiates three phases: adults crowd, juveniles crowd and oscillations) is reproduced.

Using a multi-gene approach to infer the complicated phylogeny and evolutionary history of lorises (Order Primates: Family Lorisidae).

PubMed

Munds, Rachel A; Titus, Chelsea L; Eggert, Lori S; Blomquist, Gregory E

2018-05-25

Extensive phylogenetic studies have found robust phylogenies are modeled by using a multi-gene approach and sampling from the majority of the taxa of interest. Yet, molecular studies focused on the lorises, a cryptic primate family, have often relied on one gene, or just mitochondrial DNA, and many were unable to include all four genera in the analyses, resulting in inconclusive phylogenies. Past phylogenetic loris studies resulted in lorises being monophyletic, paraphyletic, or an unresolvable trichotomy with the closely related galagos. The purpose of our study is to improve our understanding of loris phylogeny and evolutionary history by using a multi-gene approach. We used the mitochondrial genes cytochrome b, and cytochrome c oxidase subunit 1, along with a nuclear intron (recombination activating gene 2) and nuclear exon (the melanocortin 1 receptor). Maximum Likelihood and Bayesian phylogenetic analyses were conducted based on data from each locus, as well as on the concatenated sequences. The robust, concatenated results found lorises to be a monophyletic family (Lorisidae) (PP ≥ 0.99) with two distinct subfamilies: the African Perodictinae (PP ≥ 0.99) and the Asian Lorisinae (PP ≥ 0.99). Additionally, from these analyses all four genera were all recovered as monophyletic (PP ≥ 0.99). Some of our single-gene analyses recovered monophyly, but many had discordances, with some showing paraphyly or a deep-trichotomy. Bayesian partitioned analyses inferred the most recent common ancestors of lorises emerged ∼42 ± 6 million years ago (mya), the Asian Lorisinae separated ∼30 ± 9 mya, and Perodictinae arose ∼26 ± 10 mya. These times fit well with known historical tectonic shifts of the area, as well as with the sparse loris fossil record. Additionally, our results agree with previous multi-gene studies on Lorisidae which found lorises to be monophyletic and arising ∼40 mya (Perelman et al., 2011; Pozzi et al., 2014). By taking a multi-gene approach, we were able to recover a well-supported, monophyletic loris phylogeny and inferred the evolutionary history of this cryptic family. Copyright © 2018 Elsevier Inc. All rights reserved.

Using multi-species occupancy models in structured decision making on managed lands

USGS Publications Warehouse

Sauer, John R.; Blank, Peter J.; Zipkin, Elise F.; Fallon, Jane E.; Fallon, Frederick W.

2013-01-01

Land managers must balance the needs of a variety of species when manipulating habitats. Structured decision making provides a systematic means of defining choices and choosing among alternative management options; implementation of a structured decision requires quantitative approaches to predicting consequences of management on the relevant species. Multi-species occupancy models provide a convenient framework for making structured decisions when the management objective is focused on a collection of species. These models use replicate survey data that are often collected on managed lands. Occupancy can be modeled for each species as a function of habitat and other environmental features, and Bayesian methods allow for estimation and prediction of collective responses of groups of species to alternative scenarios of habitat management. We provide an example of this approach using data from breeding bird surveys conducted in 2008 at the Patuxent Research Refuge in Laurel, Maryland, evaluating the effects of eliminating meadow and wetland habitats on scrub-successional and woodland-breeding bird species using summed total occupancy of species as an objective function. Removal of meadows and wetlands decreased value of an objective function based on scrub-successional species by 23.3% (95% CI: 20.3–26.5), but caused only a 2% (0.5, 3.5) increase in value of an objective function based on woodland species, documenting differential effects of elimination of meadows and wetlands on these groups of breeding birds. This approach provides a useful quantitative tool for managers interested in structured decision making.

Superorganismality and caste differentiation as points of no return: how the major evolutionary transitions were lost in translation.

PubMed

Boomsma, Jacobus J; Gawne, Richard

2018-02-01

More than a century ago, William Morton Wheeler proposed that social insect colonies can be regarded as superorganisms when they have morphologically differentiated reproductive and nursing castes that are analogous to the metazoan germ-line and soma. Following the rise of sociobiology in the 1970s, Wheeler's insights were largely neglected, and we were left with multiple new superorganism concepts that are mutually inconsistent and uninformative on how superorganismality originated. These difficulties can be traced to the broadened sociobiological concept of eusociality, which denies that physical queen-worker caste differentiation is a universal hallmark of superorganismal colonies. Unlike early evolutionary naturalists and geneticists such as Weismann, Huxley, Fisher and Haldane, who set out to explain the acquisition of an unmated worker caste, the goal of sociobiology was to understand the evolution of eusociality, a broad-brush convenience category that covers most forms of cooperative breeding. By lumping a diverse spectrum of social systems into a single category, and drawing attention away from the evolution of distinct quantifiable traits, the sociobiological tradition has impeded straightforward connections between inclusive fitness theory and the major evolutionary transitions paradigm for understanding irreversible shifts to higher organizational complexity. We evaluate the history by which these inconsistencies accumulated, develop a common-cause approach for understanding the origins of all major transitions in eukaryote hierarchical complexity, and use Hamilton's rule to argue that they are directly comparable. We show that only Wheeler's original definition of superorganismality can be unambiguously linked to irreversible evolutionary transitions from context-dependent reproductive altruism to unconditional differentiation of permanently unmated castes in the ants, corbiculate bees, vespine wasps and higher termites. We argue that strictly monogamous parents were a necessary, albeit not sufficient condition for all transitions to superorganismality, analogous to single-zygote bottlenecking being a necessary but not sufficient condition for the convergent origins of complex soma across multicellular eukaryotes. We infer that conflict reduction was not a necessary condition for the origin of any of these major transitions, and conclude that controversies over the status of inclusive fitness theory primarily emanate from the arbitrarily defined sociobiological concepts of superorganismality and eusociality, not from the theory itself. © 2017 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.

Evolutionary toxicology: Meta-analysis of evolutionary events in response to chemical stressors.

PubMed

M Oziolor, Elias; De Schamphelaere, Karel; Matson, Cole W

2016-12-01

The regulatory decision-making process regarding chemical safety is most often informed by evidence based on ecotoxicity tests that consider growth, reproduction and survival as end-points, which can be quantitatively linked to short-term population outcomes. Changes in these end-points resulting from chemical exposure can cause alterations in micro-evolutionary forces (mutation, drift, selection and gene flow) that control the genetic composition of populations. With multi-generation exposures, anthropogenic contamination can lead to a population with an altered genetic composition, which may respond differently to future stressors. These evolutionary changes are rarely discussed in regulatory or risk assessment frameworks, but the growing body of literature that documents their existence suggests that these important population-level impacts should be considered. In this meta-analysis we have compared existing contamination levels of polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs) that have been documented to be associated with evolutionary changes in resident aquatic organisms to regulatory benchmarks for these contaminants. The original intent of this project was to perform a meta-analysis on evolutionary events associated with PCB and PAH contamination. However, this effort was hindered by a lack of consistency in congener selection for "total" PCB or PAH measurements. We expanded this manuscript to include a discussion of methods used to determine PCB and PAH total contamination in addition to comparing regulatory guidelines and contamination that has caused evolutionary effects. Micro-evolutionary responses often lead populations onto unique and unpredictable trajectories. Therefore, to better understand the risk of population-wide alterations occurring, we need to improve comparisons of chemical contamination between affected locations. In this manuscript we offer several possibilities to unify chemical comparisons for PCBs and PAHs that would improve comparability among evolutionary toxicology investigations, and with regulatory guidelines. In addition, we identify studies documenting evolutionary change in the presence of PCB and PAH contamination levels below applicable regulatory benchmarks.

Evolutionary dynamics on graphs

NASA Astrophysics Data System (ADS)

Lieberman, Erez; Hauert, Christoph; Nowak, Martin A.

2005-01-01

Evolutionary dynamics have been traditionally studied in the context of homogeneous or spatially extended populations. Here we generalize population structure by arranging individuals on a graph. Each vertex represents an individual. The weighted edges denote reproductive rates which govern how often individuals place offspring into adjacent vertices. The homogeneous population, described by the Moran process, is the special case of a fully connected graph with evenly weighted edges. Spatial structures are described by graphs where vertices are connected with their nearest neighbours. We also explore evolution on random and scale-free networks. We determine the fixation probability of mutants, and characterize those graphs for which fixation behaviour is identical to that of a homogeneous population. Furthermore, some graphs act as suppressors and others as amplifiers of selection. It is even possible to find graphs that guarantee the fixation of any advantageous mutant. We also study frequency-dependent selection and show that the outcome of evolutionary games can depend entirely on the structure of the underlying graph. Evolutionary graph theory has many fascinating applications ranging from ecology to multi-cellular organization and economics.

Controlling Tensegrity Robots Through Evolution

NASA Technical Reports Server (NTRS)

Iscen, Atil; Agogino, Adrian; SunSpiral, Vytas; Tumer, Kagan

2013-01-01

Tensegrity structures (built from interconnected rods and cables) have the potential to offer a revolutionary new robotic design that is light-weight, energy-efficient, robust to failures, capable of unique modes of locomotion, impact tolerant, and compliant (reducing damage between the robot and its environment). Unfortunately robots built from tensegrity structures are difficult to control with traditional methods due to their oscillatory nature, nonlinear coupling between components and overall complexity. Fortunately this formidable control challenge can be overcome through the use of evolutionary algorithms. In this paper we show that evolutionary algorithms can be used to efficiently control a ball-shaped tensegrity robot. Experimental results performed with a variety of evolutionary algorithms in a detailed soft-body physics simulator show that a centralized evolutionary algorithm performs 400 percent better than a hand-coded solution, while the multi-agent evolution performs 800 percent better. In addition, evolution is able to discover diverse control solutions (both crawling and rolling) that are robust against structural failures and can be adapted to a wide range of energy and actuation constraints. These successful controls will form the basis for building high-performance tensegrity robots in the near future.

System and method having multi-tube fuel nozzle with differential flow

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

Hughes, Michael John; Johnson, Thomas Edward; Berry, Jonathan Dwight

A system includes a multi-tube fuel nozzle with a fuel nozzle body and a plurality of tubes. The fuel nozzle body includes a nozzle wall surrounding a chamber. The plurality of tubes extend through the chamber, wherein each tube of the plurality of tubes includes an air intake portion, a fuel intake portion, and an air-fuel mixture outlet portion. The multi-tube fuel nozzle also includes a differential configuration of the air intake portions among the plurality of tubes.

Job strain, occupational category, and hypertension prevalence: The Multi-Ethnic Study of Atherosclerosis

PubMed Central

Landsbergis, Paul A.; Diez-Roux, Ana V.; Fujishiro, Kaori; Baron, Sherry; Kaufman, Joel D.; Meyer, John D.; Koutsouras, George; Shimbo, Daichi; Shrager, Sandi; Stukovsky, Karen Hinckley; Szklo, Moyses

2015-01-01

Objective To assess associations of occupational categories and job characteristics with prevalent hypertension. Methods We analyzed 2,517 Multi-Ethnic Study of Atherosclerosis (MESA) participants, working 20+ hours per week, in 2002–4. Results Higher job decision latitude was associated with a lower prevalence of hypertension, prevalence ratio (PR)=0.78 (95% CI 0.66–0.91) for the top vs. bottom quartile of job decision latitude. However, associations differed by occupation: decision latitude was associated with a higher prevalence of hypertension in healthcare support occupations (interaction p=.02). Occupation modified associations of gender with hypertension: a higher prevalence of hypertension in women (vs men) was observed in healthcare support and in blue-collar occupations (interaction p=.03). Conclusions Lower job decision latitude is associated with hypertension prevalence in many occupations. Further research is needed to determine reasons for differential impact of decision latitude and gender on hypertension across occupations. PMID:26539765

Multi-scale Imaging of Cellular and Sub-cellular Structures using Scanning Probe Recognition Microscopy.

NASA Astrophysics Data System (ADS)

Chen, Q.; Rice, A. F.

2005-03-01

Scanning Probe Recognition Microscopy is a new scanning probe capability under development within our group to reliably return to and directly interact with a specific nanobiological feature of interest. In previous work, we have successfully recognized and classified tubular versus globular biological objects from experimental atomic force microscope images using a method based on normalized central moments [ref. 1]. In this paper we extend this work to include recognition schemes appropriate for cellular and sub-cellular structures. Globular cells containing tubular actin filaments are under investigation. Thus there are differences in external/internal shapes and scales. Continuous Wavelet Transform with a differential Gaussian mother wavelet is employed for multi- scale analysis. [ref. 1] Q. Chen, V. Ayres and L. Udpa, ``Biological Investigation Using Scanning Probe Recognition Microscopy,'' Proceedings 3rd IEEE Conference on Nanotechnology, vol. 2, p 863-865 (2003).

Multi-shaped beam: development status and update on lithography results

NASA Astrophysics Data System (ADS)

Slodowski, Matthias; Doering, Hans-Joachim; Dorl, Wolfgang; Stolberg, Ines A.

2011-04-01

According to the ITRS [1] photo mask is a significant challenge for the 22nm technology node requirements and beyond. Mask making capability and cost escalation continue to be critical for future lithography progress. On the technological side mask specifications and complexity have increased more quickly than the half-pitch requirements on the wafer designated by the roadmap due to advanced optical proximity correction and double patterning demands. From the economical perspective mask costs have significantly increased each generation, in which mask writing represents a major portion. The availability of a multi-electron-beam lithography system for mask write application is considered a potential solution to overcome these challenges [2, 3]. In this paper an update of the development status of a full-package high-throughput multi electron-beam writer, called Multi Shaped Beam (MSB), will be presented. Lithography performance results, which are most relevant for mask writing applications, will be disclosed. The MSB technology is an evolutionary development of the matured single Variable Shaped Beam (VSB) technology. An arrangement of Multi Deflection Arrays (MDA) allows operation with multiple shaped beams of variable size, which can be deflected and controlled individually [4]. This evolutionary MSB approach is associated with a lower level of risk and a relatively short time to implementation compared to the known revolutionary concepts [3, 5, 6]. Lithography performance is demonstrated through exposed pattern. Further details of the substrate positioning platform performance will be disclosed. It will become apparent that the MSB operational mode enables lithography on the same and higher performance level compared to single VSB and that there are no specific additional lithography challenges existing beside those which have already been addressed [1].

Enemy targeting, trade-offs, and the evolutionary assembly of a tortoise beetle defense arsenal

USDA-ARS?s Scientific Manuscript database

In response to intense enemy selection, immature folivorous insects have evolved elaborate, multi-trait defense arsenals. How enemies foster trait diversification and arsenal assembly depends on which selective mode they impose: whether different enemies select for the same defense or exert conflict...

Sex Reversal in Reptiles: Reproductive Oddity or Powerful Driver of Evolutionary Change?

PubMed

Holleley, Clare E; Sarre, Stephen D; O'Meally, Denis; Georges, Arthur

2016-01-01

Is sex a product of genes, the environment, or both? In this review, we describe the diversity of sex-determining mechanisms in reptiles, with a focus on systems that display gene-environment interactions. We summarise the field and laboratory-based evidence for the occurrence of environmental sex reversal in reptiles and ask whether this is a widespread evolutionary mechanism affecting the evolution of sex chromosomes and speciation in vertebrates. Sex determination systems exist across a continuum of genetic and environmental influences, blurring the lines between what was once considered a strict dichotomy between genetic sex determination and temperature-dependent sex determination. Across this spectrum, we identify the potential for sex reversal in species with clearly differentiated heteromorphic sex chromosomes (Pogona vitticeps, Bassiana duperreyi, Eremias multiocellata, Gekko japonicus), weakly differentiated homomorphic sex chromosomes (Niveoscincus ocellatus), and species with only a weak heritable predisposition for sex (Emys orbicularis, Trachemys scripta). We argue that sex reversal is widespread in reptiles (Testudines, Lacertidae, Agamidae, Scincidae, Gekkonidae) and has the potential to have an impact on individual fitness, resulting in reproductively, morphologically, and behaviourally unique phenotypes. Sex reversal is likely to be a powerful evolutionary force responsible for generating and maintaining lability and diversity in reptile sex-determining modes. © 2016 S. Karger AG, Basel.

Analytical Framework for Identifying and Differentiating Recent Hitchhiking and Severe Bottleneck Effects from Multi-Locus DNA Sequence Data

DOE PAGES

Sargsyan, Ori

2012-05-25

Hitchhiking and severe bottleneck effects have impact on the dynamics of genetic diversity of a population by inducing homogenization at a single locus and at the genome-wide scale, respectively. As a result, identification and differentiation of the signatures of such events from DNA sequence data at a single locus is challenging. This study develops an analytical framework for identifying and differentiating recent homogenization events at multiple neutral loci in low recombination regions. The dynamics of genetic diversity at a locus after a recent homogenization event is modeled according to the infinite-sites mutation model and the Wright-Fisher model of reproduction withmore » constant population size. In this setting, I derive analytical expressions for the distribution, mean, and variance of the number of polymorphic sites in a random sample of DNA sequences from a locus affected by a recent homogenization event. Based on this framework, three likelihood-ratio based tests are presented for identifying and differentiating recent homogenization events at multiple loci. Lastly, I apply the framework to two data sets. First, I consider human DNA sequences from four non-coding loci on different chromosomes for inferring evolutionary history of modern human populations. The results suggest, in particular, that recent homogenization events at the loci are identifiable when the effective human population size is 50000 or greater in contrast to 10000, and the estimates of the recent homogenization events are agree with the “Out of Africa” hypothesis. Second, I use HIV DNA sequences from HIV-1-infected patients to infer the times of HIV seroconversions. The estimates are contrasted with other estimates derived as the mid-time point between the last HIV-negative and first HIV-positive screening tests. Finally, the results show that significant discrepancies can exist between the estimates.« less

Rapid evolution of larval life history, adult immune function and flight muscles in a poleward-moving damselfly.

PubMed

Therry, L; Nilsson-Örtman, V; Bonte, D; Stoks, R

2014-01-01

Although a growing number of studies have documented the evolution of adult dispersal-related traits at the range edge of poleward-expanding species, we know little about evolutionary changes in immune function or traits expressed by nondispersing larvae. We investigated differentiation in larval (growth and development) and adult traits (immune function and flight-related traits) between replicated core and edge populations of the poleward-moving damselfly Coenagrion scitulum. These traits were measured on individuals reared in a common garden experiment at two different food levels, as allocation trade-offs may be easier to detect under energy shortage. Edge individuals had a faster larval life history (growth and development rates), a higher adult immune function and a nearly significant higher relative flight muscle mass. Most of the differentiation between core and edge populations remained and edge populations had a higher relative flight muscle mass when corrected for latitude-specific thermal regimes, and hence could likely be attributed to the range expansion process per se. We here for the first time document a higher immune function in individuals at the expansion front of a poleward-expanding species and documented the rarely investigated evolution of faster life histories during range expansion. The rapid multivariate evolution in these ecological relevant traits between edge and core populations is expected to translate into changed ecological interactions and therefore has the potential to generate novel eco-evolutionary dynamics at the expansion front. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

Genes mirror geography in Daphnia magna.

PubMed

Fields, Peter D; Reisser, Céline; Dukić, Marinela; Haag, Christoph R; Ebert, Dieter

2015-09-01

Identifying the presence and magnitude of population genetic structure remains a major consideration in evolutionary biology as doing so allows one to understand the demographic history of a species as well as make predictions of how the evolutionary process will proceed. Next-generation sequencing methods allow us to reconsider previous ideas and conclusions concerning the distribution of genetic variation, and what this distribution implies about a given species evolutionary history. A previous phylogeographic study of the crustacean Daphnia magna suggested that, despite strong genetic differentiation among populations at a local scale, the species shows only moderate genetic structure across its European range, with a spatially patchy occurrence of individual lineages. We apply RAD sequencing to a sample of D. magna collected across a wide swath of the species' Eurasian range and analyse the data using principle component analysis (PCA) of genetic variation and Procrustes analytical approaches, to quantify spatial genetic structure. We find remarkable consistency between the first two PCA axes and the geographic coordinates of individual sampling points, suggesting that, on a continent-wide scale, genetic differentiation is driven to a large extent by geographic distance. The observed pattern is consistent with unimpeded (i.e. no barriers, landscape or otherwise) migration at large spatial scales, despite the fragmented and patchy nature of favourable habitats at local scales. With high-resolution genetic data similar patterns may be uncovered for other species with wide geographic distributions, allowing an increased understanding of how genetic drift and selection have shaped their evolutionary history. © 2015 John Wiley & Sons Ltd.

A multi-domain spectral method for time-fractional differential equations

NASA Astrophysics Data System (ADS)

Chen, Feng; Xu, Qinwu; Hesthaven, Jan S.

2015-07-01

This paper proposes an approach for high-order time integration within a multi-domain setting for time-fractional differential equations. Since the kernel is singular or nearly singular, two main difficulties arise after the domain decomposition: how to properly account for the history/memory part and how to perform the integration accurately. To address these issues, we propose a novel hybrid approach for the numerical integration based on the combination of three-term-recurrence relations of Jacobi polynomials and high-order Gauss quadrature. The different approximations used in the hybrid approach are justified theoretically and through numerical examples. Based on this, we propose a new multi-domain spectral method for high-order accurate time integrations and study its stability properties by identifying the method as a generalized linear method. Numerical experiments confirm hp-convergence for both time-fractional differential equations and time-fractional partial differential equations.

The role of long non-coding RNA H19 in musculoskeletal system: A new player in an old game.

PubMed

Liu, Yang; Li, Gang; Zhang, Jin-Fang

2017-11-15

The long non-coding RNAs (lncRNAs) have gained much attention due to its essential roles in molecular regulation. As one of the classic lncRNAs, H19 is strongly expressed during embryogenesis and plays a crucial biological function during development. Mesenchymal stem cells (MSCs) are an ideal cell source for tissue engineering in musculoskeletal system as they own the multi-differentiation ability towards osteogenesis, adipogenesis, tenogenesis or chondrogenesis. In recent years, many studies have been found in the field of H19 mediated cellular differentiation of MSCs. Here, we summarized the current understanding of H19 during multi-differentiation of MSCs and its application in tissue regeneration of musculoskeletal system. Particularly, its molecular regulation and biological function during the multi-differentiation were also discussed. Copyright © 2017 Elsevier Inc. All rights reserved.

Evolutionary turnover of kinetochore proteins: a ship of Theseus?

PubMed Central

Drinnenberg, Ines A.; Henikoff, Steven; Malik, Harmit S.

2016-01-01

Summary The kinetochore is a multi-protein complex that mediates the attachment of a eukaryotic chromosome to the mitotic spindle. The protein composition of kinetochores is similar across species as divergent as yeast and human. However, recent findings have revealed an unexpected degree of compositional diversity in kinetochores. For example, kinetochore proteins that are essential in some species have been lost in others, whereas new kinetochore proteins have emerged in other lineages. Even in lineages with similar kinetochore composition, individual kinetochore proteins have functionally diverged to acquire either essential or redundant roles. Thus, despite functional conservation, the repertoire of kinetochore proteins has undergone recurrent evolutionary turnover. PMID:26877204

OH masers towards IRAS 19092+0841

NASA Astrophysics Data System (ADS)

Edris, K. A.; Fuller, G. A.; Etoka, S.; Cohen, R. J.

2017-12-01

Context. Maser emission is a strong tool for studying high-mass star-forming regions and their evolutionary stages. OH masers in particular can trace the circumstellar material around protostars and determine their magnetic field strengths at milliarcsecond resolution. Aims: We seek to image OH maser emission towards high-mass protostellar objects to determine their evolutionary stages and to locate the detected maser emission in the process of high-mass star formation. Methods: In 2007, we surveyed OH maser emission towards 217 high-mass protostellar objects to study its presence. In this paper, we present follow-up MERLIN observations of a ground-state OH maser emission towards one of these objects, IRAS 19092+0841. Results: We detect emissions from the two OH main spectral lines, 1665 and 1667 MHz, close to the central object. We determine the positions and velocities of the OH maser features. The masers are distributed over a region of 5'' corresponding to 22 400 AU (or 0.1 pc) at a distance of 4.48 kpc. The polarization properties of the OH maser features are determined as well. We identify three Zeeman pairs from which we inferred a magnetic field strength of 4.4 mG pointing towards the observer. Conclusions: The relatively small velocity spread and relatively wide spacial distribution of the OH maser features support the suggestion that this object could be in an early evolutionary state before the presence of disk, jets or outflows.

Advanced algorithms for radiographic material discrimination and inspection system design

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

Gilbert, Andrew J.; McDonald, Benjamin S.; Deinert, Mark R.

X-ray and neutron radiography are powerful tools for non-invasively inspecting the interior of objects. Materials can be discriminated by noting how the radiographic signal changes with variations in the input spectrum or inspection mode. However, current methods are limited in their ability to differentiate when multiple materials are present, especially within large and complex objects. With X-ray radiography, the inability to distinguish materials of a similar atomic number is especially problematic. To overcome these critical limitations, we augmented our existing inverse problem framework with two important expansions: 1) adapting the previous methodology for use with multi-modal radiography and energy-integrating detectors,more » and 2) applying the Cramer-Rao lower bound to select an optimal set of inspection modes for a given application a priori. Adding these expanded capabilities to our algorithmic framework with adaptive regularization, we observed improved discrimination between high-Z materials, specifically plutonium and tungsten. The combined system can estimate plutonium mass within our simulated system to within 1%. Three types of inspection modes were modeled: multi-endpoint X-ray radiography alone; in combination with neutron radiography using deuterium-deuterium (DD); or in combination with neutron radiography using deuterium-tritium (DT) sources.« less

Designing a multi-objective, multi-support accuracy assessment of the 2001 National Land Cover Data (NLCD 2001) of the conterminous United States

USGS Publications Warehouse

Stehman, S.V.; Wickham, J.D.; Wade, T.G.; Smith, J.H.

2008-01-01

The database design and diverse application of NLCD 2001 pose significant challenges for accuracy assessment because numerous objectives are of interest, including accuracy of land-cover, percent urban imperviousness, percent tree canopy, land-cover composition, and net change. A multi-support approach is needed because these objectives require spatial units of different sizes for reference data collection and analysis. Determining a sampling design that meets the full suite of desirable objectives for the NLCD 2001 accuracy assessment requires reconciling potentially conflicting design features that arise from targeting the different objectives. Multi-stage cluster sampling provides the general structure to achieve a multi-support assessment, and the flexibility to target different objectives at different stages of the design. We describe the implementation of two-stage cluster sampling for the initial phase of the NLCD 2001 assessment, and identify gaps in existing knowledge where research is needed to allow full implementation of a multi-objective, multi-support assessment. ?? 2008 American Society for Photogrammetry and Remote Sensing.

Multiband tissue classification for ultrasonic transmission tomography using spectral profile detection

NASA Astrophysics Data System (ADS)

Jeong, Jeong-Won; Kim, Tae-Seong; Shin, Dae-Chul; Do, Synho; Marmarelis, Vasilis Z.

2004-04-01

Recently it was shown that soft tissue can be differentiated with spectral unmixing and detection methods that utilize multi-band information obtained from a High-Resolution Ultrasonic Transmission Tomography (HUTT) system. In this study, we focus on tissue differentiation using the spectral target detection method based on Constrained Energy Minimization (CEM). We have developed a new tissue differentiation method called "CEM filter bank". Statistical inference on the output of each CEM filter of a filter bank is used to make a decision based on the maximum statistical significance rather than the magnitude of each CEM filter output. We validate this method through 3-D inter/intra-phantom soft tissue classification where target profiles obtained from an arbitrary single slice are used for differentiation in multiple tomographic slices. Also spectral coherence between target and object profiles of an identical tissue at different slices and phantoms is evaluated by conventional cross-correlation analysis. The performance of the proposed classifier is assessed using Receiver Operating Characteristic (ROC) analysis. Finally we apply our method to classify tiny structures inside a beef kidney such as Styrofoam balls (~1mm), chicken tissue (~5mm), and vessel-duct structures.

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

ERIC Educational Resources Information Center

Camperio Ciani, Andrea S.; Fontanesi, Lilybeth

2012-01-01

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

Diversity and endemism in deglaciated areas: ploidy, relative genome size and niche differentiation in the Galium pusillum complex (Rubiaceae) in Northern and Central Europe

PubMed Central

Kolář, Filip; Lučanová, Magdalena; Vít, Petr; Urfus, Tomáš; Chrtek, Jindřich; Fér, Tomáš; Ehrendorfer, Friedrich; Suda, Jan

2013-01-01

Background and Aims Plants endemic to areas covered by ice sheets during the last glaciation represent paradigmatic examples of rapid speciation in changing environments, yet very few systems outside the harsh arctic zone have been comprehensively investigated so far. The Galium pusillum aggregate (Rubiaceae) is a challenging species complex that exhibits a marked differentiation in boreal parts of Northern Europe. As a first step towards understanding its evolutionary history in deglaciated regions, this study assesses cytological variation and ecological preferences of the northern endemics and compares the results with corresponding data for species occurring in neighbouring unglaciated parts of Central and Western Europe. Methods DNA flow cytometry was used together with confirmatory chromosome counts to determine ploidy levels and relative genome sizes in 1158 individuals from 181 populations. A formalized analysis of habitat preferences was applied to explore niche differentiation among species and ploidy levels. Key Results The G. pusillum complex evolved at diploid and tetraploid levels in Northern Europe, in contrast to the high-polyploid evolution of most other northern endemics. A high level of eco-geographic segregation was observed between different species (particularly along gradients of soil pH and competition) which is unusual for plants in deglaciated areas and most probably contributes to maintaining species integrity. Relative monoploid DNA contents of the species from previously glaciated regions were significantly lower than those of their counterparts from mostly unglaciated Central Europe, suggesting independent evolutionary histories. Conclusions The aggregate of G. pusillum in Northern Europe represents an exceptional case with a geographically vicariant and ecologically distinct diploid/tetraploid species endemic to formerly glaciated areas. The high level of interspecific differentiation substantially widens our perception of the evolutionary dynamics and speciation rates in the dramatically changing environments of Northern Europe. PMID:23589633

Understanding variation in human fertility: what can we learn from evolutionary demography?

PubMed

Sear, Rebecca; Lawson, David W; Kaplan, Hillard; Shenk, Mary K

2016-04-19

Decades of research on human fertility has presented a clear picture of how fertility varies, including its dramatic decline over the last two centuries in most parts of the world. Why fertility varies, both between and within populations, is not nearly so well understood. Fertility is a complex phenomenon, partly physiologically and partly behaviourally determined, thus an interdisciplinary approach is required to understand it. Evolutionary demographers have focused on human fertility since the 1980s. The first wave of evolutionary demographic research made major theoretical and empirical advances, investigating variation in fertility primarily in terms of fitness maximization. Research focused particularly on variation within high-fertility populations and small-scale subsistence societies and also yielded a number of hypotheses for why fitness maximization seems to break down as fertility declines during the demographic transition. A second wave of evolutionary demography research on fertility is now underway, paying much more attention to the cultural and psychological mechanisms underpinning fertility. It is also engaging with the complex, multi-causal nature of fertility variation, and with understanding fertility in complex modern and transitioning societies. Here, we summarize the history of evolutionary demographic work on human fertility, describe the current state of the field, and suggest future directions. © 2016 The Author(s).

Understanding variation in human fertility: what can we learn from evolutionary demography?

PubMed Central

Sear, Rebecca; Lawson, David W.; Kaplan, Hillard

2016-01-01

Decades of research on human fertility has presented a clear picture of how fertility varies, including its dramatic decline over the last two centuries in most parts of the world. Why fertility varies, both between and within populations, is not nearly so well understood. Fertility is a complex phenomenon, partly physiologically and partly behaviourally determined, thus an interdisciplinary approach is required to understand it. Evolutionary demographers have focused on human fertility since the 1980s. The first wave of evolutionary demographic research made major theoretical and empirical advances, investigating variation in fertility primarily in terms of fitness maximization. Research focused particularly on variation within high-fertility populations and small-scale subsistence societies and also yielded a number of hypotheses for why fitness maximization seems to break down as fertility declines during the demographic transition. A second wave of evolutionary demography research on fertility is now underway, paying much more attention to the cultural and psychological mechanisms underpinning fertility. It is also engaging with the complex, multi-causal nature of fertility variation, and with understanding fertility in complex modern and transitioning societies. Here, we summarize the history of evolutionary demographic work on human fertility, describe the current state of the field, and suggest future directions. PMID:27022071

Identifying Differential Item Functioning in Multi-Stage Computer Adaptive Testing

ERIC Educational Resources Information Center

Gierl, Mark J.; Lai, Hollis; Li, Johnson

2013-01-01

The purpose of this study is to evaluate the performance of CATSIB (Computer Adaptive Testing-Simultaneous Item Bias Test) for detecting differential item functioning (DIF) when items in the matching and studied subtest are administered adaptively in the context of a realistic multi-stage adaptive test (MST). MST was simulated using a 4-item…