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Sample records for genetic programming theory

  1. Genetic programming theory and practice XII

    CERN Document Server

    Riolo, Rick; Kotanchek, Mark

    2015-01-01

    These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: gene expression regulation, novel genetic models for glaucoma, inheritable epigenetics, combinators in genetic programming, sequential symbolic regression, system dynamics, sliding window symbolic regression, large feature problems, alignment in the error space, HUMIE winners, Boolean multiplexer funct

  2. Genetic programming theory and practice X

    CERN Document Server

    Riolo, Rick; Ritchie, Marylyn D; Moore, Jason H

    2013-01-01

    These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: evolutionary constraints, relaxation of selection mechanisms, diversity preservation strategies, flexing fitness evaluation, evolution in dynamic environments, multi-objective and multi-modal selection, foundations of evolvability, evolvable and adaptive evolutionary operators, foundation of  injecting

  3. Academic training: From Evolution Theory to Parallel and Distributed Genetic Programming

    CERN Multimedia

    2007-01-01

    2006-2007 ACADEMIC TRAINING PROGRAMME LECTURE SERIES 15, 16 March From 11:00 to 12:00 - Main Auditorium, bldg. 500 From Evolution Theory to Parallel and Distributed Genetic Programming F. FERNANDEZ DE VEGA / Univ. of Extremadura, SP Lecture No. 1: From Evolution Theory to Evolutionary Computation Evolutionary computation is a subfield of artificial intelligence (more particularly computational intelligence) involving combinatorial optimization problems, which are based to some degree on the evolution of biological life in the natural world. In this tutorial we will review the source of inspiration for this metaheuristic and its capability for solving problems. We will show the main flavours within the field, and different problems that have been successfully solved employing this kind of techniques. Lecture No. 2: Parallel and Distributed Genetic Programming The successful application of Genetic Programming (GP, one of the available Evolutionary Algorithms) to optimization problems has encouraged an ...

  4. A genetic program theory of aging using an RNA population model.

    Science.gov (United States)

    Wang, Xiufang; Ma, Zhihong; Cheng, Jianjun; Lv, Zhanjun

    2014-01-01

    Aging is a common characteristic of multicellular eukaryotes. Copious hypotheses have been proposed to explain the mechanisms of aging, but no single theory is generally acceptable. In this article, we refine the RNA population gene activating model (Lv et al., 2003) based on existing reports as well as on our own latest findings. We propose the RNA population model as a genetic theory of aging. The new model can also be applied to differentiation and tumorigenesis and could explain the biological significance of non-coding DNA, RNA, and repetitive sequence DNA. We provide evidence from the literature as well as from our own findings for the roles of repetitive sequences in gene activation. In addition, we predict several phenomena related to aging and differentiation based on this model.

  5. Applications of Genetic Programming

    DEFF Research Database (Denmark)

    Gaunholt, Hans; Toma, Laura

    1996-01-01

    In this report a study of genetic programming (GP) has been performed with respect to a number of applications such as Symbolic function regression, Solving Symbolic Differential Equations, Image encoding, the ant problem etc.......In this report a study of genetic programming (GP) has been performed with respect to a number of applications such as Symbolic function regression, Solving Symbolic Differential Equations, Image encoding, the ant problem etc....

  6. Applications of Genetic Programming

    DEFF Research Database (Denmark)

    Gaunholt, Hans; Toma, Laura

    1996-01-01

    In this report a study of genetic programming (GP) has been performed with respect to a number of applications such as Symbolic function regression, Solving Symbolic Differential Equations, Image encoding, the ant problem etc.......In this report a study of genetic programming (GP) has been performed with respect to a number of applications such as Symbolic function regression, Solving Symbolic Differential Equations, Image encoding, the ant problem etc....

  7. Cartesian genetic programming

    CERN Document Server

    Miller, Julian F

    2011-01-01

    Cartesian Genetic Programming (CGP) is a highly effective and increasingly popular form of genetic programming. It represents programs in the form of directed graphs, and a particular characteristic is that it has a highly redundant genotype - phenotype mapping, in that genes can be noncoding. It has spawned a number of new forms, each improving on the efficiency, among them modular, or embedded, CGP, and self-modifying CGP. It has been applied to many problems in both computer science and applied sciences. This book contains chapters written by the leading figures in the development and appli

  8. Generating information-rich high-throughput experimental materials genomes using functional clustering via multitree genetic programming and information theory.

    Science.gov (United States)

    Suram, Santosh K; Haber, Joel A; Jin, Jian; Gregoire, John M

    2015-04-13

    High-throughput experimental methodologies are capable of synthesizing, screening and characterizing vast arrays of combinatorial material libraries at a very rapid rate. These methodologies strategically employ tiered screening wherein the number of compositions screened decreases as the complexity, and very often the scientific information obtained from a screening experiment, increases. The algorithm used for down-selection of samples from higher throughput screening experiment to a lower throughput screening experiment is vital in achieving information-rich experimental materials genomes. The fundamental science of material discovery lies in the establishment of composition-structure-property relationships, motivating the development of advanced down-selection algorithms which consider the information value of the selected compositions, as opposed to simply selecting the best performing compositions from a high throughput experiment. Identification of property fields (composition regions with distinct composition-property relationships) in high throughput data enables down-selection algorithms to employ advanced selection strategies, such as the selection of representative compositions from each field or selection of compositions that span the composition space of the highest performing field. Such strategies would greatly enhance the generation of data-driven discoveries. We introduce an informatics-based clustering of composition-property functional relationships using a combination of information theory and multitree genetic programming concepts for identification of property fields in a composition library. We demonstrate our approach using a complex synthetic composition-property map for a 5 at. % step ternary library consisting of four distinct property fields and finally explore the application of this methodology for capturing relationships between composition and catalytic activity for the oxygen evolution reaction for 5429 catalyst compositions in a

  9. Program Theory Evaluation: Logic Analysis

    Science.gov (United States)

    Brousselle, Astrid; Champagne, Francois

    2011-01-01

    Program theory evaluation, which has grown in use over the past 10 years, assesses whether a program is designed in such a way that it can achieve its intended outcomes. This article describes a particular type of program theory evaluation--logic analysis--that allows us to test the plausibility of a program's theory using scientific knowledge.…

  10. Elementary number theory with programming

    CERN Document Server

    Lewinter, Marty

    2015-01-01

    A successful presentation of the fundamental concepts of number theory and computer programming Bridging an existing gap between mathematics and programming, Elementary Number Theory with Programming provides a unique introduction to elementary number theory with fundamental coverage of computer programming. Written by highly-qualified experts in the fields of computer science and mathematics, the book features accessible coverage for readers with various levels of experience and explores number theory in the context of programming without relying on advanced prerequisite knowledge and con

  11. Predicting High or Low Transfer Efficiency of Photovoltaic Systems Using a Novel Hybrid Methodology Combining Rough Set Theory, Data Envelopment Analysis and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Lee-Ing Tong

    2012-02-01

    Full Text Available Solar energy has become an important energy source in recent years as it generates less pollution than other energies. A photovoltaic (PV system, which typically has many components, converts solar energy into electrical energy. With the development of advanced engineering technologies, the transfer efficiency of a PV system has been increased from low to high. The combination of components in a PV system influences its transfer efficiency. Therefore, when predicting the transfer efficiency of a PV system, one must consider the relationship among system components. This work accurately predicts whether transfer efficiency of a PV system is high or low using a novel hybrid model that combines rough set theory (RST, data envelopment analysis (DEA, and genetic programming (GP. Finally, real data-set are utilized to demonstrate the accuracy of the proposed method.

  12. Behavioral program synthesis with genetic programming

    CERN Document Server

    Krawiec, Krzysztof

    2016-01-01

    Genetic programming (GP) is a popular heuristic methodology of program synthesis with origins in evolutionary computation. In this generate-and-test approach, candidate programs are iteratively produced and evaluated. The latter involves running programs on tests, where they exhibit complex behaviors reflected in changes of variables, registers, or memory. That behavior not only ultimately determines program output, but may also reveal its `hidden qualities' and important characteristics of the considered synthesis problem. However, the conventional GP is oblivious to most of that information and usually cares only about the number of tests passed by a program. This `evaluation bottleneck' leaves search algorithm underinformed about the actual and potential qualities of candidate programs. This book proposes behavioral program synthesis, a conceptual framework that opens GP to detailed information on program behavior in order to make program synthesis more efficient. Several existing and novel mechanisms subs...

  13. Genetic Programming and Genetic Algorithms for Propositions

    Directory of Open Access Journals (Sweden)

    Nabil M. HEWAHI

    2012-01-01

    Full Text Available In this paper we propose a mechanism to discover the compound proposition solutions for a given truth table without knowing the compound propositions that lead to the truth table results. The approach is based on two proposed algorithms, the first is called Producing Formula (PF algorithm which is based on the genetic programming idea, to find out the compound proposition solutions for the given truth table. The second algorithm is called the Solutions Optimization (SO algorithm which is based on genetic algorithms idea, to find a list of the optimum compound propositions that can solve the truth table. The obtained list will depend on the solutions obtained from the PF algorithm. Various types of genetic operators have been introduced to obtain the solutions either within the PF algorithm or SO algorithm.

  14. Scientific discovery using genetic programming

    DEFF Research Database (Denmark)

    Keijzer, Maarten

    2001-01-01

    programming paradigm. The induction of mathematical expressions based on data is called symbolic regression. In this work, genetic programming is extended to not just fit the data i.e., get the numbers right, but also to get the dimensions right. For this units of measurement are used. The main contribution...... in this work can be summarized as: The symbolic expressions produced by genetic programming can be made suitable for analysis and interpretation by using units of measurements to guide or restrict the search. To achieve this, the following has been accomplished: A standard genetic programming system...... that are numerically stable and correct. A case study using four real-world problems in the induction of dimensionally correct empirical equations on data using the two different methods is presented to illustrate to use and limitations of these methods in a framework of scientific discovery....

  15. Genetic Programming with Simple Loops

    Institute of Scientific and Technical Information of China (English)

    QI Yuesheng; WANG Baozhong; KANG Lishan

    1999-01-01

    A kind of loop function LoopN inGenetic Programming (GP) is proposed.Different from other forms of loopfunction, such as While-Do and Repeat-Until, LoopNtakes only oneargument as its loop body and makes its loop body simply run N times,soinfinite loops will never happen. The problem of how to avoid too manylayers ofloops in Genetic Programming is also solved. The advantage ofLoopN in GP is shown bythe computational results in solving the mowerproblem.

  16. Dynamical genetic programming in XCSF.

    Science.gov (United States)

    Preen, Richard J; Bull, Larry

    2013-01-01

    A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to artificial neural networks. This paper presents results from an investigation into using a temporally dynamic symbolic representation within the XCSF learning classifier system. In particular, dynamical arithmetic networks are used to represent the traditional condition-action production system rules to solve continuous-valued reinforcement learning problems and to perform symbolic regression, finding competitive performance with traditional genetic programming on a number of composite polynomial tasks. In addition, the network outputs are later repeatedly sampled at varying temporal intervals to perform multistep-ahead predictions of a financial time series.

  17. Arguments against non-programmed aging theories.

    Science.gov (United States)

    Goldsmith, T C

    2013-09-01

    Until recently, non-programmed theories of biological aging were popular because of the widespread perception that the evolution process could not support the development and retention of programmed aging in mammals. However, newer evolutionary mechanics theories including group selection, kin selection, and evolvability theory support mammal programmed aging, and multiple programmed aging theories have been published based on the new mechanics. Some proponents of non-programmed aging still contend that their non-programmed theories are superior despite the new mechanics concepts. However, as summarized here, programmed theories provide a vastly better fit to empirical evidence and do not suffer from multiple implausible assumptions that are required by non-programmed theories. This issue is important because programmed theories suggest very different mechanisms for the aging process and therefore different mechanisms behind highly age-related diseases and conditions such as cancer, heart disease, and stroke.

  18. Theory and practice in quantitative genetics.

    Science.gov (United States)

    Posthuma, Daniëlle; Beem, A Leo; de Geus, Eco J C; van Baal, G Caroline M; von Hjelmborg, Jacob B; Iachine, Ivan; Boomsma, Dorret I

    2003-10-01

    With the rapid advances in molecular biology, the near completion of the human genome, the development of appropriate statistical genetic methods and the availability of the necessary computing power, the identification of quantitative trait loci has now become a realistic prospect for quantitative geneticists. We briefly describe the theoretical biometrical foundations underlying quantitative genetics. These theoretical underpinnings are translated into mathematical equations that allow the assessment of the contribution of observed (using DNA samples) and unobserved (using known genetic relationships) genetic variation to population variance in quantitative traits. Several statistical models for quantitative genetic analyses are described, such as models for the classical twin design, multivariate and longitudinal genetic analyses, extended twin analyses, and linkage and association analyses. For each, we show how the theoretical biometrical model can be translated into algebraic equations that may be used to generate scripts for statistical genetic software packages, such as Mx, Lisrel, SOLAR, or MERLIN. For using the former program a web-library (available from http://www.psy.vu.nl/mxbib) has been developed of freely available scripts that can be used to conduct all genetic analyses described in this paper.

  19. Atmospheric Downscaling using Genetic Programming

    Science.gov (United States)

    Zerenner, Tanja; Venema, Victor; Simmer, Clemens

    2013-04-01

    Coupling models for the different components of the Soil-Vegetation-Atmosphere-System requires up-and downscaling procedures. Subject of our work is the downscaling scheme used to derive high resolution forcing data for land-surface and subsurface models from coarser atmospheric model output. The current downscaling scheme [Schomburg et. al. 2010, 2012] combines a bi-quadratic spline interpolation, deterministic rules and autoregressive noise. For the development of the scheme, training and validation data sets have been created by carrying out high-resolution runs of the atmospheric model. The deterministic rules in this scheme are partly based on known physical relations and partly determined by an automated search for linear relationships between the high resolution fields of the atmospheric model output and high resolution data on surface characteristics. Up to now deterministic rules are available for downscaling surface pressure and partially, depending on the prevailing weather conditions, for near surface temperature and radiation. Aim of our work is to improve those rules and to find deterministic rules for the remaining variables, which require downscaling, e.g. precipitation or near surface specifc humidity. To accomplish that, we broaden the search by allowing for interdependencies between different atmospheric parameters, non-linear relations, non-local and time-lagged relations. To cope with the vast number of possible solutions, we use genetic programming, a method from machine learning, which is based on the principles of natural evolution. We are currently working with GPLAB, a Genetic Programming toolbox for Matlab. At first we have tested the GP system to retrieve the known physical rule for downscaling surface pressure, i.e. the hydrostatic equation, from our training data. We have found this to be a simple task to the GP system. Furthermore we have improved accuracy and efficiency of the GP solution by implementing constant variation and

  20. Information theory and the ethylene genetic network.

    Science.gov (United States)

    González-García, José S; Díaz, José

    2011-10-01

    The original aim of the Information Theory (IT) was to solve a purely technical problem: to increase the performance of communication systems, which are constantly affected by interferences that diminish the quality of the transmitted information. That is, the theory deals only with the problem of transmitting with the maximal precision the symbols constituting a message. In Shannon's theory messages are characterized only by their probabilities, regardless of their value or meaning. As for its present day status, it is generally acknowledged that Information Theory has solid mathematical foundations and has fruitful strong links with Physics in both theoretical and experimental areas. However, many applications of Information Theory to Biology are limited to using it as a technical tool to analyze biopolymers, such as DNA, RNA or protein sequences. The main point of discussion about the applicability of IT to explain the information flow in biological systems is that in a classic communication channel, the symbols that conform the coded message are transmitted one by one in an independent form through a noisy communication channel, and noise can alter each of the symbols, distorting the message; in contrast, in a genetic communication channel the coded messages are not transmitted in the form of symbols but signaling cascades transmit them. Consequently, the information flow from the emitter to the effector is due to a series of coupled physicochemical processes that must ensure the accurate transmission of the message. In this review we discussed a novel proposal to overcome this difficulty, which consists of the modeling of gene expression with a stochastic approach that allows Shannon entropy (H) to be directly used to measure the amount of uncertainty that the genetic machinery has in relation to the correct decoding of a message transmitted into the nucleus by a signaling pathway. From the value of H we can define a function I that measures the amount of

  1. Information theory and the ethylene genetic network

    Science.gov (United States)

    González-García, José S

    2011-01-01

    The original aim of the Information Theory (IT) was to solve a purely technical problem: to increase the performance of communication systems, which are constantly affected by interferences that diminish the quality of the transmitted information. That is, the theory deals only with the problem of transmitting with the maximal precision the symbols constituting a message. In Shannon's theory messages are characterized only by their probabilities, regardless of their value or meaning. As for its present day status, it is generally acknowledged that Information Theory has solid mathematical foundations and has fruitful strong links with Physics in both theoretical and experimental areas. However, many applications of Information Theory to Biology are limited to using it as a technical tool to analyze biopolymers, such as DNA, RNA or protein sequences. The main point of discussion about the applicability of IT to explain the information flow in biological systems is that in a classic communication channel, the symbols that conform the coded message are transmitted one by one in an independent form through a noisy communication channel, and noise can alter each of the symbols, distorting the message; in contrast, in a genetic communication channel the coded messages are not transmitted in the form of symbols but signaling cascades transmit them. Consequently, the information flow from the emitter to the effector is due to a series of coupled physicochemical processes that must ensure the accurate transmission of the message. In this review we discussed a novel proposal to overcome this difficulty, which consists of the modeling of gene expression with a stochastic approach that allows Shannon entropy (H) to be directly used to measure the amount of uncertainty that the genetic machinery has in relation to the correct decoding of a message transmitted into the nucleus by a signaling pathway. From the value of H we can define a function I that measures the amount of

  2. Recognition of Objects by Using Genetic Programming

    Directory of Open Access Journals (Sweden)

    Nerses Safaryan

    2013-01-01

    Full Text Available This document is devoted to the task of object detection and recognition in digital images by using genetic programming. The goal was to improve and simplify existing approaches. The detection and recognition are achieved by means of extracting the features. A genetic program is used to extract and classify features of objects. Simple features and primitive operators are processed in genetic programming operations. We are trying to detect and to recognize objects in SAR images. Due to the new approach described in this article, five and seven types of objects were recognized with good recognition results.

  3. Applied genetic programming and machine learning

    CERN Document Server

    Iba, Hitoshi; Paul, Topon Kumar

    2009-01-01

    What do financial data prediction, day-trading rule development, and bio-marker selection have in common? They are just a few of the tasks that could potentially be resolved with genetic programming and machine learning techniques. Written by leaders in this field, Applied Genetic Programming and Machine Learning delineates the extension of Genetic Programming (GP) for practical applications. Reflecting rapidly developing concepts and emerging paradigms, this book outlines how to use machine learning techniques, make learning operators that efficiently sample a search space, navigate the searc

  4. On the relation between gene flow theory and genetic gain

    Directory of Open Access Journals (Sweden)

    Woolliams John A

    2000-01-01

    Full Text Available Abstract In conventional gene flow theory the rate of genetic gain is calculated as the summed products of genetic selection differential and asymptotic proportion of genes deriving from sex-age groups. Recent studies have shown that asymptotic proportions of genes predicted from conventional gene flow theory may deviate considerably from true proportions. However, the rate of genetic gain predicted from conventional gene flow theory was accurate. The current note shows that the connection between asymptotic proportions of genes and rate of genetic gain that is embodied in conventional gene flow theory is invalid, even though genetic gain may be predicted correctly from it.

  5. Genetic Parallel Programming: design and implementation.

    Science.gov (United States)

    Cheang, Sin Man; Leung, Kwong Sak; Lee, Kin Hong

    2006-01-01

    This paper presents a novel Genetic Parallel Programming (GPP) paradigm for evolving parallel programs running on a Multi-Arithmetic-Logic-Unit (Multi-ALU) Processor (MAP). The MAP is a Multiple Instruction-streams, Multiple Data-streams (MIMD), general-purpose register machine that can be implemented on modern Very Large-Scale Integrated Circuits (VLSIs) in order to evaluate genetic programs at high speed. For human programmers, writing parallel programs is more difficult than writing sequential programs. However, experimental results show that GPP evolves parallel programs with less computational effort than that of their sequential counterparts. It creates a new approach to evolving a feasible problem solution in parallel program form and then serializes it into a sequential program if required. The effectiveness and efficiency of GPP are investigated using a suite of 14 well-studied benchmark problems. Experimental results show that GPP speeds up evolution substantially.

  6. Manufacturing Resource Planning Technology Based on Genetic Programming Simulation

    Institute of Scientific and Technical Information of China (English)

    GAO Shiwen; LIAO Wenhe; GUO Yu; LIU Jinshan; SU Yan

    2009-01-01

    Network-based manufacturing is a kind of distributed system, which enables manufacturers to finish production tasks as well as to grasp the opportunities in the market, even if manufacturing resources are insufficient. One of the main problems in network-based manufacturing is the allocation of resources and the assignment of tasks rationally, according to flexible resource distribution. The mapping rules and relations between production techniques and resources are proposed, followed by the definition of the resource unit. Ultimately, the genetic programming method for the optimization of the manufacturing system is put forward. A set of software for the optimization system of simulation process using genetic programming techniques has been developed, and the problems of manufacturing resource planning in network-based manufacturing are solved with the simulation of optimizing methods by genetic programming. The optimum proposal of hardware planning, selection of company and scheduling will be obtained in theory to help company managers in scientific decision-making.

  7. Programming cells: towards an automated 'Genetic Compiler'.

    Science.gov (United States)

    Clancy, Kevin; Voigt, Christopher A

    2010-08-01

    One of the visions of synthetic biology is to be able to program cells using a language that is similar to that used to program computers or robotics. For large genetic programs, keeping track of the DNA on the level of nucleotides becomes tedious and error prone, requiring a new generation of computer-aided design (CAD) software. To push the size of projects, it is important to abstract the designer from the process of part selection and optimization. The vision is to specify genetic programs in a higher-level language, which a genetic compiler could automatically convert into a DNA sequence. Steps towards this goal include: defining the semantics of the higher-level language, algorithms to select and assemble parts, and biophysical methods to link DNA sequence to function. These will be coupled to graphic design interfaces and simulation packages to aid in the prediction of program dynamics, optimize genes, and scan projects for errors.

  8. Theories for Mechanical Proofs of Imperative Programs

    NARCIS (Netherlands)

    Hesselink, Wim H.

    1997-01-01

    For convenient application of a first-order theorem prover to verification of imperative programs, it is important to encapsulate the operational semantics in generic theories. The possibility to do so is illustrated by two theories for the Boyer-Moore theorem prover Nqthm. The first theory is an Nq

  9. Applications of graph theory to landscape genetics.

    Science.gov (United States)

    Garroway, Colin J; Bowman, Jeff; Carr, Denis; Wilson, Paul J

    2008-11-01

    We investigated the relationships among landscape quality, gene flow, and population genetic structure of fishers (Martes pennanti) in ON, Canada. We used graph theory as an analytical framework considering each landscape as a network node. The 34 nodes were connected by 93 edges. Network structure was characterized by a higher level of clustering than expected by chance, a short mean path length connecting all pairs of nodes, and a resiliency to the loss of highly connected nodes. This suggests that alleles can be efficiently spread through the system and that extirpations and conservative harvest are not likely to affect their spread. Two measures of node centrality were negatively related to both the proportion of immigrants in a node and node snow depth. This suggests that central nodes are producers of emigrants, contain high-quality habitat (i.e., deep snow can make locomotion energetically costly) and that fishers were migrating from high to low quality habitat. A method of community detection on networks delineated five genetic clusters of nodes suggesting cryptic population structure. Our analyses showed that network models can provide system-level insight into the process of gene flow with implications for understanding how landscape alterations might affect population fitness and evolutionary potential.

  10. The genetical theory of social behaviour.

    Science.gov (United States)

    Lehmann, Laurent; Rousset, François

    2014-05-19

    We survey the population genetic basis of social evolution, using a logically consistent set of arguments to cover a wide range of biological scenarios. We start by reconsidering Hamilton's (Hamilton 1964 J. Theoret. Biol. 7, 1-16 (doi:10.1016/0022-5193(64)90038-4)) results for selection on a social trait under the assumptions of additive gene action, weak selection and constant environment and demography. This yields a prediction for the direction of allele frequency change in terms of phenotypic costs and benefits and genealogical concepts of relatedness, which holds for any frequency of the trait in the population, and provides the foundation for further developments and extensions. We then allow for any type of gene interaction within and between individuals, strong selection and fluctuating environments and demography, which may depend on the evolving trait itself. We reach three conclusions pertaining to selection on social behaviours under broad conditions. (i) Selection can be understood by focusing on a one-generation change in mean allele frequency, a computation which underpins the utility of reproductive value weights; (ii) in large populations under the assumptions of additive gene action and weak selection, this change is of constant sign for any allele frequency and is predicted by a phenotypic selection gradient; (iii) under the assumptions of trait substitution sequences, such phenotypic selection gradients suffice to characterize long-term multi-dimensional stochastic evolution, with almost no knowledge about the genetic details underlying the coevolving traits. Having such simple results about the effect of selection regardless of population structure and type of social interactions can help to delineate the common features of distinct biological processes. Finally, we clarify some persistent divergences within social evolution theory, with respect to exactness, synergies, maximization, dynamic sufficiency and the role of genetic arguments.

  11. Integer programming theory, applications, and computations

    CERN Document Server

    Taha, Hamdy A

    1975-01-01

    Integer Programming: Theory, Applications, and Computations provides information pertinent to the theory, applications, and computations of integer programming. This book presents the computational advantages of the various techniques of integer programming.Organized into eight chapters, this book begins with an overview of the general categorization of integer applications and explains the three fundamental techniques of integer programming. This text then explores the concept of implicit enumeration, which is general in a sense that it is applicable to any well-defined binary program. Other

  12. Separable programming theory and methods

    CERN Document Server

    Stefanov, Stefan M

    2001-01-01

    In this book, the author considers separable programming and, in particular, one of its important cases - convex separable programming Some general results are presented, techniques of approximating the separable problem by linear programming and dynamic programming are considered Convex separable programs subject to inequality equality constraint(s) and bounds on variables are also studied and iterative algorithms of polynomial complexity are proposed As an application, these algorithms are used in the implementation of stochastic quasigradient methods to some separable stochastic programs Numerical approximation with respect to I1 and I4 norms, as a convex separable nonsmooth unconstrained minimization problem, is considered as well Audience Advanced undergraduate and graduate students, mathematical programming operations research specialists

  13. An analysis of the metabolic theory of the origin of the genetic code

    Science.gov (United States)

    Amirnovin, R.; Bada, J. L. (Principal Investigator)

    1997-01-01

    A computer program was used to test Wong's coevolution theory of the genetic code. The codon correlations between the codons of biosynthetically related amino acids in the universal genetic code and in randomly generated genetic codes were compared. It was determined that many codon correlations are also present within random genetic codes and that among the random codes there are always several which have many more correlations than that found in the universal code. Although the number of correlations depends on the choice of biosynthetically related amino acids, the probability of choosing a random genetic code with the same or greater number of codon correlations as the universal genetic code was found to vary from 0.1% to 34% (with respect to a fairly complete listing of related amino acids). Thus, Wong's theory that the genetic code arose by coevolution with the biosynthetic pathways of amino acids, based on codon correlations between biosynthetically related amino acids, is statistical in nature.

  14. Genetic program based data mining to reverse engineer digital logic

    Science.gov (United States)

    Smith, James F., III; Nguyen, Thanh Vu H.

    2006-04-01

    A data mining based procedure for automated reverse engineering and defect discovery has been developed. The data mining algorithm for reverse engineering uses a genetic program (GP) as a data mining function. A genetic program is an algorithm based on the theory of evolution that automatically evolves populations of computer programs or mathematical expressions, eventually selecting one that is optimal in the sense it maximizes a measure of effectiveness, referred to as a fitness function. The system to be reverse engineered is typically a sensor. Design documents for the sensor are not available and conditions prevent the sensor from being taken apart. The sensor is used to create a database of input signals and output measurements. Rules about the likely design properties of the sensor are collected from experts. The rules are used to create a fitness function for the genetic program. Genetic program based data mining is then conducted. This procedure incorporates not only the experts' rules into the fitness function, but also the information in the database. The information extracted through this process is the internal design specifications of the sensor. Uncertainty related to the input-output database and the expert based rule set can significantly alter the reverse engineering results. Significant experimental and theoretical results related to GP based data mining for reverse engineering will be provided. Methods of quantifying uncertainty and its effects will be presented. Finally methods for reducing the uncertainty will be examined.

  15. Regulating genetic information--exploring the options in legal theory.

    Science.gov (United States)

    2014-12-01

    Ground-breaking genetic discoveries and technological advances have introduced a new world of genetic exploration, and technological advances have facilitated the discovery of the genetic basis of a myriad of diseases. Genetic testing promises to potentially revolutionise health care and offer the potential ofpersonalised medicine. Genetic technology may also offer the means to detect potential future disabilities. In light of rapid advances in genetic science and technology, questions arise as to whether an appropriate framework exists to protect the interests of individuals, prevent the misuse of genetic information by interested third parties, and also to encourage further advances in genetic science. In consideration of rapidly advancing genetic technologies and the ethical and legal concerns that arise, this article examines the regulation of genetic information, primarily from a theoretical perspective. It explores the preferable mode of regulation and choice of regulatory frameworks in legal theory, including non-discrimination, privacy and property.

  16. Genetic Programming for Automatic Hydrological Modelling

    Science.gov (United States)

    Chadalawada, Jayashree; Babovic, Vladan

    2017-04-01

    One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach

  17. Theory and Practice in Quantitative Genetics

    DEFF Research Database (Denmark)

    Posthuma, Daniëlle; Beem, A Leo; de Geus, Eco J C

    2003-01-01

    With the rapid advances in molecular biology, the near completion of the human genome, the development of appropriate statistical genetic methods and the availability of the necessary computing power, the identification of quantitative trait loci has now become a realistic prospect for quantitative...... geneticists. We briefly describe the theoretical biometrical foundations underlying quantitative genetics. These theoretical underpinnings are translated into mathematical equations that allow the assessment of the contribution of observed (using DNA samples) and unobserved (using known genetic relationships......) genetic variation to population variance in quantitative traits. Several statistical models for quantitative genetic analyses are described, such as models for the classical twin design, multivariate and longitudinal genetic analyses, extended twin analyses, and linkage and association analyses. For each...

  18. Evolving evolutionary algorithms using linear genetic programming.

    Science.gov (United States)

    Oltean, Mihai

    2005-01-01

    A new model for evolving Evolutionary Algorithms is proposed in this paper. The model is based on the Linear Genetic Programming (LGP) technique. Every LGP chromosome encodes an EA which is used for solving a particular problem. Several Evolutionary Algorithms for function optimization, the Traveling Salesman Problem and the Quadratic Assignment Problem are evolved by using the considered model. Numerical experiments show that the evolved Evolutionary Algorithms perform similarly and sometimes even better than standard approaches for several well-known benchmarking problems.

  19. Genetic Programming Framework for Fingerprint Matching

    CERN Document Server

    Ismail, Ismail A; Abd-ElWahid, Mohammed A; ElKafrawy, Passent M; Nasef, Mohammed M

    2009-01-01

    A fingerprint matching is a very difficult problem. Minutiae based matching is the most popular and widely used technique for fingerprint matching. The minutiae points considered in automatic identification systems are based normally on termination and bifurcation points. In this paper we propose a new technique for fingerprint matching using minutiae points and genetic programming. The goal of this paper is extracting the mathematical formula that defines the minutiae points.

  20. Deterministic Pattern Classifier Based on Genetic Programming

    Institute of Scientific and Technical Information of China (English)

    LI Jian-wu; LI Min-qiang; KOU Ji-song

    2001-01-01

    This paper proposes a supervised training-test method with Genetic Programming (GP) for pattern classification. Compared and contrasted with traditional methods with regard to deterministic pattern classifiers, this method is true for both linear separable problems and linear non-separable problems. For specific training samples, it can formulate the expression of discriminate function well without any prior knowledge. At last, an experiment is conducted, and the result reveals that this system is effective and practical.

  1. Grammar Based Genetic Programming Using Linear Representations

    Institute of Scientific and Technical Information of China (English)

    ZHANGHong; LUYinan; WANGFei

    2003-01-01

    In recent years,there has been a great interest in genetic programming(GP),which is used to solve many applications such as data mining,electronic engineering and pattern recognition etc.. Genetic programming paradigm as a from of adaptive learning is a functional approach to many problems that require a nonfixed representation and GP typically operates on a population of parse which usually represent computer programs whose nodes have single data type.In this paper GP using context-free grammars(CFGs) is described.This technique separates search space from solution space through a genotype to phenotype mapping.The genotypes and phenotypes of the individuals both act on different linear representations.A phenotype is postfix expression,a new method of representing which is described by making use of the definition and related features of a context-free grammar,i.e.a genotype is a variable length,linear valid genome determined by a simplifled derivation tree(SDT) generated from a context-free grammar.A CFG is used to specify how the possible solutions are created according to experiential knowledge and to direct legal crossover(ormutation)operations without any explicit reference to the process of program generation and parsing,and automatically ensuring typing and syntax correctness.Some related definitions involving genetic operators are described.Fitness evaluation is given.This technique is applied to a symbol regression problem-the identification of nonlinear dynamic characteristics of cushioning packaging.Experimental results show this method can flnd good relations between variables and is better than basic GP without a grammar.Future research on it is outlined.

  2. Linear programming mathematics, theory and algorithms

    CERN Document Server

    1996-01-01

    Linear Programming provides an in-depth look at simplex based as well as the more recent interior point techniques for solving linear programming problems. Starting with a review of the mathematical underpinnings of these approaches, the text provides details of the primal and dual simplex methods with the primal-dual, composite, and steepest edge simplex algorithms. This then is followed by a discussion of interior point techniques, including projective and affine potential reduction, primal and dual affine scaling, and path following algorithms. Also covered is the theory and solution of the linear complementarity problem using both the complementary pivot algorithm and interior point routines. A feature of the book is its early and extensive development and use of duality theory. Audience: The book is written for students in the areas of mathematics, economics, engineering and management science, and professionals who need a sound foundation in the important and dynamic discipline of linear programming.

  3. Functional Localization of Genetic Network Programming

    Science.gov (United States)

    Eto, Shinji; Hirasawa, Kotaro; Hu, Jinglu

    According to the knowledge of brain science, it is suggested that there exists cerebral functional localization, which means that a specific part of the cerebrum is activated depending on various kinds of information human receives. The aim of this paper is to build an artificial model to realize functional localization based on Genetic Network Programming (GNP), a new evolutionary computation method recently developed. GNP has a directed graph structure suitable for realizing functional localization. We studied the basic characteristics of the proposed system by making GNP work in a functionally localized way.

  4. Bias-variance decomposition in Genetic Programming

    Directory of Open Access Journals (Sweden)

    Kowaliw Taras

    2016-01-01

    Full Text Available We study properties of Linear Genetic Programming (LGP through several regression and classification benchmarks. In each problem, we decompose the results into bias and variance components, and explore the effect of varying certain key parameters on the overall error and its decomposed contributions. These parameters are the maximum program size, the initial population, and the function set used. We confirm and quantify several insights into the practical usage of GP, most notably that (a the variance between runs is primarily due to initialization rather than the selection of training samples, (b parameters can be reasonably optimized to obtain gains in efficacy, and (c functions detrimental to evolvability are easily eliminated, while functions well-suited to the problem can greatly improve performance—therefore, larger and more diverse function sets are always preferable.

  5. LIGO detector characterization with genetic programming

    Science.gov (United States)

    Cavaglia, Marco; Staats, Kai; Errico, Luciano; Mogushi, Kentaro; Gabbard, Hunter

    2017-01-01

    Genetic Programming (GP) is a supervised approach to Machine Learning. GP has for two decades been applied to a diversity of problems, from predictive and financial modelling to data mining, from code repair to optical character recognition and product design. GP uses a stochastic search, tournament, and fitness function to explore a solution space. GP evolves a population of individual programs, through multiple generations, following the principals of biological evolution (mutation and reproduction) to discover a model that best fits or categorizes features in a given data set. We apply GP to categorization of LIGO noise and show that it can effectively be used to characterize the detector non-astrophysical noise both in low latency and offline searches. National Science Foundation award PHY-1404139.

  6. Quasispecies theory in the context of population genetics

    Directory of Open Access Journals (Sweden)

    Wilke Claus O

    2005-08-01

    Full Text Available Abstract Background A number of recent papers have cast doubt on the applicability of the quasispecies concept to virus evolution, and have argued that population genetics is a more appropriate framework to describe virus evolution than quasispecies theory. Results I review the pertinent literature, and demonstrate for a number of cases that the quasispecies concept is equivalent to the concept of mutation-selection balance developed in population genetics, and that there is no disagreement between the population genetics of haploid, asexually-replicating organisms and quasispecies theory. Conclusion Since quasispecies theory and mutation-selection balance are two sides of the same medal, the discussion about which is more appropriate to describe virus evolution is moot. In future work on virus evolution, we would do good to focus on the important questions, such as whether we can develop accurate, quantitative models of virus evolution, and to leave aside discussions about the relative merits of perfectly equivalent concepts.

  7. Improving Search Properties in Genetic Programming

    Science.gov (United States)

    Janikow, Cezary Z.; DeWeese, Scott

    1997-01-01

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

  8. Reflections on the Field of Human Genetics: A Call for Increased Disease Genetics Theory.

    Science.gov (United States)

    Schrodi, Steven J

    2016-01-01

    Development of human genetics theoretical models and the integration of those models with experiment and statistical evaluation are critical for scientific progress. This perspective argues that increased effort in disease genetics theory, complementing experimental, and statistical efforts, will escalate the unraveling of molecular etiologies of complex diseases. In particular, the development of new, realistic disease genetics models will help elucidate complex disease pathogenesis, and the predicted patterns in genetic data made by these models will enable the concurrent, more comprehensive statistical testing of multiple aspects of disease genetics predictions, thereby better identifying disease loci. By theoretical human genetics, I intend to encompass all investigations devoted to modeling the heritable architecture underlying disease traits and studies of the resulting principles and dynamics of such models. Hence, the scope of theoretical disease genetics work includes construction and analysis of models describing how disease-predisposing alleles (1) arise, (2) are transmitted across families and populations, and (3) interact with other risk and protective alleles across both the genome and environmental factors to produce disease states. Theoretical work improves insight into viable genetic models of diseases consistent with empirical results from linkage, transmission, and association studies as well as population genetics. Furthermore, understanding the patterns of genetic data expected under realistic disease models will enable more powerful approaches to discover disease-predisposing alleles and additional heritable factors important in common diseases. In spite of the pivotal role of disease genetics theory, such investigation is not particularly vibrant.

  9. Unifying diseases from a genetic point of view: the example of the genetic theory of infectious diseases.

    Science.gov (United States)

    Darrason, Marie

    2013-08-01

    In the contemporary biomedical literature, every disease is considered genetic. This extension of the concept of genetic disease is usually interpreted either in a trivial or genocentrist sense, but it is never taken seriously as the expression of a genetic theory of disease. However, a group of French researchers defend the idea of a genetic theory of infectious diseases. By identifying four common genetic mechanisms (Mendelian predisposition to multiple infections, Mendelian predisposition to one infection, and major gene and polygenic predispositions), they attempt to unify infectious diseases from a genetic point of view. In this article, I analyze this explicit example of a genetic theory, which relies on mechanisms and is applied only to a specific category of diseases, what we call "a regional genetic theory." I have three aims: to prove that a genetic theory of disease can be devoid of genocentrism, to consider the possibility of a genetic theory applied to every disease, and to introduce two hypotheses about the form that such a genetic theory could take by distinguishing between a genetic theory of diseases and a genetic theory of Disease. Finally, I suggest that network medicine could be an interesting framework for a genetic theory of Disease.

  10. Implementing a Moral Education Program through Attitude Change Theory.

    Science.gov (United States)

    Hughes, Richard L.; Casper, Daniel

    1979-01-01

    Major theories of attitude change are explained: stimulus-response and reinforcement theory, functional theory, social judgment theory, and consistency theory. These theories are applied to the problems of influencing staff toward implementing a program of moral education. (Author/SJL)

  11. On Using Surrogates with Genetic Programming.

    Science.gov (United States)

    Hildebrandt, Torsten; Branke, Jürgen

    2015-01-01

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

  12. Genetic Programming Transforms in Linear Regression Situations

    Science.gov (United States)

    Castillo, Flor; Kordon, Arthur; Villa, Carlos

    The chapter summarizes the use of Genetic Programming (GP) inMultiple Linear Regression (MLR) to address multicollinearity and Lack of Fit (LOF). The basis of the proposed method is applying appropriate input transforms (model respecification) that deal with these issues while preserving the information content of the original variables. The transforms are selected from symbolic regression models with optimal trade-off between accuracy of prediction and expressional complexity, generated by multiobjective Pareto-front GP. The chapter includes a comparative study of the GP-generated transforms with Ridge Regression, a variant of ordinary Multiple Linear Regression, which has been a useful and commonly employed approach for reducing multicollinearity. The advantages of GP-generated model respecification are clearly defined and demonstrated. Some recommendations for transforms selection are given as well. The application benefits of the proposed approach are illustrated with a real industrial application in one of the broadest empirical modeling areas in manufacturing - robust inferential sensors. The chapter contributes to increasing the awareness of the potential of GP in statistical model building by MLR.

  13. Improved Evolvability in Genetic Programming with Polyandry

    Directory of Open Access Journals (Sweden)

    Anisa Waganda Ragalo

    2013-12-01

    Full Text Available This paper proposes Polyandry, a new nature-inspired modification to canonical Genetic Programming (GP. Polyandry aims to improve evolvability in GP. Evolvability is a critically important GP trait, the maintenance of which determines the arrival of the GP at the global optimum solution. Specifically evolvability is defined as the ability of the genetic operators employed in GP to produce offspring that are fitter than their parents. When GP fails to exhibit evolvability, further adaptation of the GP individuals towards the global optimum solution becomes impossible. Polyandry improves evolvability by improving the typically disruptive standard GP crossover operator. The algorithm employs a dual strategy towards this goal. The chief part of this strategy is an incorporation of genetic material from multiple mating partners into broods of offspring. Given such a brood, the offspring in the brood then compete according to a culling function, which we make equivalent to the main GP fitness function. Polyandry’s incorporation of genetic material from multiple GP individuals into broods of offspring represents a more aggressive search for building block information. This characteristic of the algorithm leads to an advanced explorative capability in both GP structural space and fitness space. The second component of the Polyandry strategy is an attempt at multiple crossover points, in order to find crossover points that minimize building block disruption from parents to offspring. This strategy is employed by a similar algorithm, Brood Recombination. We conduct experiments to compare Polyandry with the canonical GP. Our experiments demonstrate that Polyandry consistently exhibits better evolvability than the canonical GP. As a consequence, Polyandry achieves higher success rates and finds solutions faster than the latter. The result of these observations is that given certain brood size settings, Polyandry requires less computational effort to

  14. Solving Classification Problems Using Genetic Programming Algorithms on GPUs

    Science.gov (United States)

    Cano, Alberto; Zafra, Amelia; Ventura, Sebastián

    Genetic Programming is very efficient in problem solving compared to other proposals but its performance is very slow when the size of the data increases. This paper proposes a model for multi-threaded Genetic Programming classification evaluation using a NVIDIA CUDA GPUs programming model to parallelize the evaluation phase and reduce computational time. Three different well-known Genetic Programming classification algorithms are evaluated using the parallel evaluation model proposed. Experimental results using UCI Machine Learning data sets compare the performance of the three classification algorithms in single and multithreaded Java, C and CUDA GPU code. Results show that our proposal is much more efficient.

  15. An Approach to Theory-Based Youth Programming

    Science.gov (United States)

    Duerden, Mat D.; Gillard, Ann

    2011-01-01

    A key but often overlooked aspect of intentional, out-of-school-time programming is the integration of a guiding theoretical framework. The incorporation of theory in programming can provide practitioners valuable insights into essential processes and principles of successful programs. While numerous theories exist that relate to youth development…

  16. An Approach to Theory-Based Youth Programming

    Science.gov (United States)

    Duerden, Mat D.; Gillard, Ann

    2011-01-01

    A key but often overlooked aspect of intentional, out-of-school-time programming is the integration of a guiding theoretical framework. The incorporation of theory in programming can provide practitioners valuable insights into essential processes and principles of successful programs. While numerous theories exist that relate to youth development…

  17. Adaptable Constrained Genetic Programming: Extensions and Applications

    Science.gov (United States)

    Janikow, Cezary Z.

    2005-01-01

    An evolutionary algorithm applies evolution-based principles to problem solving. To solve a problem, the user defines the space of potential solutions, the representation space. Sample solutions are encoded in a chromosome-like structure. The algorithm maintains a population of such samples, which undergo simulated evolution by means of mutation, crossover, and survival of the fittest principles. Genetic Programming (GP) uses tree-like chromosomes, providing very rich representation suitable for many problems of interest. GP has been successfully applied to a number of practical problems such as learning Boolean functions and designing hardware circuits. To apply GP to a problem, the user needs to define the actual representation space, by defining the atomic functions and terminals labeling the actual trees. The sufficiency principle requires that the label set be sufficient to build the desired solution trees. The closure principle allows the labels to mix in any arity-consistent manner. To satisfy both principles, the user is often forced to provide a large label set, with ad hoc interpretations or penalties to deal with undesired local contexts. This unfortunately enlarges the actual representation space, and thus usually slows down the search. In the past few years, three different methodologies have been proposed to allow the user to alleviate the closure principle by providing means to define, and to process, constraints on mixing the labels in the trees. Last summer we proposed a new methodology to further alleviate the problem by discovering local heuristics for building quality solution trees. A pilot system was implemented last summer and tested throughout the year. This summer we have implemented a new revision, and produced a User's Manual so that the pilot system can be made available to other practitioners and researchers. We have also designed, and partly implemented, a larger system capable of dealing with much more powerful heuristics.

  18. Alternative Living Kidney Donation Programs Boost Genetically Unrelated Donation

    Directory of Open Access Journals (Sweden)

    Rosalie A. Poldervaart

    2015-01-01

    Full Text Available Donor-recipient ABO and/or HLA incompatibility used to lead to donor decline. Development of alternative transplantation programs enabled transplantation of incompatible couples. How did that influence couple characteristics? Between 2000 and 2014, 1232 living donor transplantations have been performed. In conventional and ABO-incompatible transplantation the willing donor becomes an actual donor for the intended recipient. In kidney-exchange and domino-donation the donor donates indirectly to the intended recipient. The relationship between the donor and intended recipient was studied. There were 935 conventional and 297 alternative program transplantations. There were 66 ABO-incompatible, 68 domino-paired, 62 kidney-exchange, and 104 altruistic donor transplantations. Waiting list recipients (n=101 were excluded as they did not bring a living donor. 1131 couples remained of whom 196 participated in alternative programs. Genetically unrelated donors (486 were primarily partners. Genetically related donors (645 were siblings, parents, children, and others. Compared to genetically related couples, almost three times as many genetically unrelated couples were incompatible and participated in alternative programs (P<0.001. 62% of couples were genetically related in the conventional donation program versus 32% in alternative programs (P<0.001. Patient and graft survival were not significantly different between recipient programs. Alternative donation programs increase the number of transplantations by enabling genetically unrelated donors to donate.

  19. Using genetic programming to discover nonlinear variable interactions.

    Science.gov (United States)

    Westbury, Chris; Buchanan, Lori; Sanderson, Michael; Rhemtulla, Mijke; Phillips, Leah

    2003-05-01

    Psychology has to deal with many interacting variables. The analyses usually used to uncover such relationships have many constraints that limit their utility. We briefly discuss these and describe recent work that uses genetic programming to evolve equations to combine variables in nonlinear ways in a number of different domains. We focus on four studies of interactions from lexical access experiments and psychometric problems. In all cases, genetic programming described nonlinear combinations of items in a manner that was subsequently independently verified. We discuss the general implications of genetic programming and related computational methods for multivariate problems in psychology.

  20. Formal Theory versus Stakeholder Theory: New Insights from a Tobacco-Focused Prevention Program Evaluation

    Science.gov (United States)

    Chen, Huey T.; Turner, Nannette C.

    2012-01-01

    Health promotion and social betterment program interventions are based on either formal theory from academia or stakeholder theory from stakeholders' observations and experiences in working with clients. Over time, formal theory-based interventions have acquired high prestige, while stakeholder theory-based interventions have been held in low…

  1. Genetic Programming Approach for Predicting Surface Subsidence Induced by Mining

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The surface subsidence induced by mining is a complex problem, which is related with many complex and uncertain factors.Genetic programming (GP) has a good ability to deal with complex and nonlinear problems, therefore genetic programming approach is proposed to predict mining induced surface subsidence in this article.First genetic programming technique is introduced, second, surface subsidence genetic programming model is set up by selecting its main affective factors and training relating to practical engineering data, and finally, predictions are made by the testing of data, whose results show that the relative error is approximately less than 10%, which can meet the engineering needs, and therefore, this proposed approach is valid and applicable in predicting mining induced surface subsidence.The model offers a novel method to predict surface subsidence in mining.

  2. Stochastic linear programming models, theory, and computation

    CERN Document Server

    Kall, Peter

    2011-01-01

    This new edition of Stochastic Linear Programming: Models, Theory and Computation has been brought completely up to date, either dealing with or at least referring to new material on models and methods, including DEA with stochastic outputs modeled via constraints on special risk functions (generalizing chance constraints, ICC’s and CVaR constraints), material on Sharpe-ratio, and Asset Liability Management models involving CVaR in a multi-stage setup. To facilitate use as a text, exercises are included throughout the book, and web access is provided to a student version of the authors’ SLP-IOR software. Additionally, the authors have updated the Guide to Available Software, and they have included newer algorithms and modeling systems for SLP. The book is thus suitable as a text for advanced courses in stochastic optimization, and as a reference to the field. From Reviews of the First Edition: "The book presents a comprehensive study of stochastic linear optimization problems and their applications. … T...

  3. Theories of schizophrenia: a genetic-inflammatory-vascular synthesis

    Directory of Open Access Journals (Sweden)

    Gottesman Irving I

    2005-02-01

    Full Text Available Abstract Background Schizophrenia, a relatively common psychiatric syndrome, affects virtually all brain functions yet has eluded explanation for more than 100 years. Whether by developmental and/or degenerative processes, abnormalities of neurons and their synaptic connections have been the recent focus of attention. However, our inability to fathom the pathophysiology of schizophrenia forces us to challenge our theoretical models and beliefs. A search for a more satisfying model to explain aspects of schizophrenia uncovers clues pointing to genetically mediated CNS microvascular inflammatory disease. Discussion A vascular component to a theory of schizophrenia posits that the physiologic abnormalities leading to illness involve disruption of the exquisitely precise regulation of the delivery of energy and oxygen required for normal brain function. The theory further proposes that abnormalities of CNS metabolism arise because genetically modulated inflammatory reactions damage the microvascular system of the brain in reaction to environmental agents, including infections, hypoxia, and physical trauma. Damage may accumulate with repeated exposure to triggering agents resulting in exacerbation and deterioration, or healing with their removal. There are clear examples of genetic polymorphisms in inflammatory regulators leading to exaggerated inflammatory responses. There is also ample evidence that inflammatory vascular disease of the brain can lead to psychosis, often waxing and waning, and exhibiting a fluctuating course, as seen in schizophrenia. Disturbances of CNS blood flow have repeatedly been observed in people with schizophrenia using old and new technologies. To account for the myriad of behavioral and other curious findings in schizophrenia such as minor physical anomalies, or reported decreased rates of rheumatoid arthritis and highly visible nail fold capillaries, we would have to evoke a process that is systemic such as the vascular

  4. Pangenesis as a source of new genetic information. The history of a now disproven theory.

    Science.gov (United States)

    Bergman, Gerald

    2006-01-01

    Evolution is based on natural selection of existing biological phenotypic traits. Natural selection can only eliminate traits. It cannot create new ones, requiring a theory to explain the origin of new genetic information. The theory of pangenesis was a major attempt to explain the source of new genetic information required to produce phenotypic variety. This theory, advocated by Darwin as the main source of genetic variety, has now been empirically disproved. It is currently a theory mainly of interest to science historians.

  5. Use of Program Theory in a Nutrition Program for Grandchildren and Grandparents

    Science.gov (United States)

    Koenings, Mallory; Arscott, Sara

    2013-01-01

    Grandparents University ® (GPU) is a 2-day campus-based nutrition education program for grandparents and grandchildren based on constructs from Social Cognitive Theory and the Theory of Planned Behavior. This article describes how program theory was used to develop a working model, design activities, and select outcome measures of a 2-day…

  6. Use of Program Theory in a Nutrition Program for Grandchildren and Grandparents

    Science.gov (United States)

    Koenings, Mallory; Arscott, Sara

    2013-01-01

    Grandparents University ® (GPU) is a 2-day campus-based nutrition education program for grandparents and grandchildren based on constructs from Social Cognitive Theory and the Theory of Planned Behavior. This article describes how program theory was used to develop a working model, design activities, and select outcome measures of a 2-day…

  7. Biotech 101: an educational outreach program in genetics and biotechnology.

    Science.gov (United States)

    East, Kelly M; Hott, Adam M; Callanan, Nancy P; Lamb, Neil E

    2012-10-01

    Recent advances in research and biotechnology are making genetics and genomics increasingly relevant to the lives and health of the general public. For the public to make informed healthcare and public policy decisions relating to genetic information, there is a need for increased genetic literacy. Biotech 101 is a free, short-course for the local community introducing participants to topics in genetics, genomics, and biotechnology, created at the HudsonAlpha Institute for Biotechnology. This study evaluated the effectiveness of Biotech 101 in increasing the genetic literacy of program participants through pre-and-post surveys. Genetic literacy was measured through increases in self-perceived knowledge for each content area covered through the course and the self-reported impact the course had on various aspects of participants' lives. Three hundred ninety-two individuals attended Biotech 101 during the first three course offerings. Participants reported a significant increase in self-perceived knowledge for each content area (p biotechnology.

  8. Linear and integer programming theory and practice

    CERN Document Server

    Sierksma, Gerard

    2001-01-01

    Linear optimisation; basic concepts; Dantzig's simplex method; duality and optimality; sensitivity analysis; karmarkar's interior path method; integer linear optimisation; linear network models; computational complexity issues; model building, case studies, and advanced techniques; solutions to selected exercises. Appendices: linear algebra; convexity; graph theory; optimisation theory; computer package INTPM.

  9. The "Genetic Program": Behind the Genesis of an Influential Metaphor.

    Science.gov (United States)

    Peluffo, Alexandre E

    2015-07-01

    The metaphor of the "genetic program," indicating the genome as a set of instructions required to build a phenotype, has been very influential in biology despite various criticisms over the years. This metaphor, first published in 1961, is thought to have been invented independently in two different articles, one by Ernst Mayr and the other by François Jacob and Jacques Monod. Here, after a detailed analysis of what both parties meant by "genetic program," I show, using unpublished archives, the strong resemblance between the ideas of Mayr and Monod and suggest that their idea of genetic program probably shares a common origin. I explore the possibility that the two men met before 1961 and also exchanged their ideas through common friends and colleagues in the field of molecular biology. Based on unpublished correspondence of Jacob and Monod, I highlight the important events that influenced the preparation of their influential paper, which introduced the concept of the genetic program. Finally, I suggest that the genetic program metaphor may have preceded both papers and that it was probably used informally before 1961.

  10. Genetic programming and serial processing for time series classification.

    Science.gov (United States)

    Alfaro-Cid, Eva; Sharman, Ken; Esparcia-Alcázar, Anna I

    2014-01-01

    This work describes an approach devised by the authors for time series classification. In our approach genetic programming is used in combination with a serial processing of data, where the last output is the result of the classification. The use of genetic programming for classification, although still a field where more research in needed, is not new. However, the application of genetic programming to classification tasks is normally done by considering the input data as a feature vector. That is, to the best of our knowledge, there are not examples in the genetic programming literature of approaches where the time series data are processed serially and the last output is considered as the classification result. The serial processing approach presented here fills a gap in the existing literature. This approach was tested in three different problems. Two of them are real world problems whose data were gathered for online or conference competitions. As there are published results of these two problems this gives us the chance to compare the performance of our approach against top performing methods. The serial processing of data in combination with genetic programming obtained competitive results in both competitions, showing its potential for solving time series classification problems. The main advantage of our serial processing approach is that it can easily handle very large datasets.

  11. The genetics of loneliness: linking evolutionary theory to genome-wide genetics, epigenetics, and social science.

    Science.gov (United States)

    Goossens, Luc; van Roekel, Eeske; Verhagen, Maaike; Cacioppo, John T; Cacioppo, Stephanie; Maes, Marlies; Boomsma, Dorret I

    2015-03-01

    As a complex trait, loneliness is likely to be influenced by the interplay of numerous genetic and environmental factors. Studies in behavioral genetics indicate that loneliness has a sizable degree of heritability. Candidate-gene and gene-expression studies have pointed to several genes related to neurotransmitters and the immune system. The notion that these genes are related to loneliness is compatible with the basic tenets of the evolutionary theory of loneliness. Research on gene-environment interactions indicates that social-environmental factors (e.g., low social support) may have a more pronounced effect and lead to higher levels of loneliness if individuals carry the sensitive variant of these candidate genes. Currently, there is no extant research on loneliness based on genome-wide association studies, gene-environment-interaction studies, or studies in epigenetics. Such studies would allow researchers to identify networks of genes that contribute to loneliness. The contribution of genetics to loneliness research will become stronger when genome-wide genetics and epigenetics are integrated and used along with well-established methods in psychology to analyze the complex process of gene-environment interplay.

  12. A Theory Based Introductory Programming Course

    DEFF Research Database (Denmark)

    Hansen, Michael Reichhardt; Kristensen, Jens Thyge; Rischel, Hans

    1999-01-01

    This paper presents an introductory programming course designed to teach programming as an intellectual activity. The course emphasizes understandable concepts which can be useful in designing programs, while the oddities of today's technology are considered of secondary importance. An important...... goal is to fight the trial-and-error approach to programming which is a result of the students battles with horribly designed and documented systems and languages prior to their studies at university. Instead, the authors strive for giving the students a good experience of programming as a systematic......, intellectual activity where the solution of a programming problem can be described in an understandable way. The approach is illustrated by an example which is a commented solution of a problem posed to the students in the course....

  13. Mendelian Genetics: Paradigm, Conjecture, or Research Program.

    Science.gov (United States)

    Oldham, V.; Brouwer, W.

    1984-01-01

    Applies Kuhn's model of the structure of scientific revolutions, Popper's hypothetic-deductive model of science, and Lakatos' methodology of competing research programs to a historical biological episode. Suggests using Kuhn's model (emphasizing the nonrational basis of science) and Popper's model (emphasizing the rational basis of science) in…

  14. Mendelian Genetics: Paradigm, Conjecture, or Research Program.

    Science.gov (United States)

    Oldham, V.; Brouwer, W.

    1984-01-01

    Applies Kuhn's model of the structure of scientific revolutions, Popper's hypothetic-deductive model of science, and Lakatos' methodology of competing research programs to a historical biological episode. Suggests using Kuhn's model (emphasizing the nonrational basis of science) and Popper's model (emphasizing the rational basis of science) in…

  15. Primer on Molecular Genetics; DOE Human Genome Program

    Science.gov (United States)

    1992-04-01

    This report is taken from the April 1992 draft of the DOE Human Genome 1991--1992 Program Report, which is expected to be published in May 1992. The primer is intended to be an introduction to basic principles of molecular genetics pertaining to the genome project. The material contained herein is not final and may be incomplete. Techniques of genetic mapping and DNA sequencing are described.

  16. Primer on molecular genetics. DOE Human Genome Program

    Energy Technology Data Exchange (ETDEWEB)

    1992-04-01

    This report is taken from the April 1992 draft of the DOE Human Genome 1991--1992 Program Report, which is expected to be published in May 1992. The primer is intended to be an introduction to basic principles of molecular genetics pertaining to the genome project. The material contained herein is not final and may be incomplete. Techniques of genetic mapping and DNA sequencing are described.

  17. An adaptive genetic algorithm for solving bilevel linear programming problem

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Bilevel linear programming, which consists of the objective functions of the upper level and lower level, is a useful tool for modeling decentralized decision problems.Various methods are proposed for solving this problem. Of all the algorithms, the genetic algorithm is an alternative to conventional approaches to find the solution of the bilevel linear programming. In this paper, we describe an adaptive genetic algorithm for solving the bilevel linear programming problem to overcome the difficulty of determining the probabilities of crossover and mutation. In addition, some techniques are adopted not only to deal with the difficulty that most of the chromosomes may be infeasible in solving constrained optimization problem with genetic algorithm but also to improve the efficiency of the algorithm. The performance of this proposed algorithm is illustrated by the examples from references.

  18. Polyglot programming in applications used for genetic data analysis.

    Science.gov (United States)

    Nowak, Robert M

    2014-01-01

    Applications used for the analysis of genetic data process large volumes of data with complex algorithms. High performance, flexibility, and a user interface with a web browser are required by these solutions, which can be achieved by using multiple programming languages. In this study, I developed a freely available framework for building software to analyze genetic data, which uses C++, Python, JavaScript, and several libraries. This system was used to build a number of genetic data processing applications and it reduced the time and costs of development.

  19. Genetic Programming for Medicinal Plant Family Identification System

    Directory of Open Access Journals (Sweden)

    Indra Laksmana

    2014-11-01

    Full Text Available Information about medicinal plants that is available in text documents is generally quite easy to access, however, one needs some efforts to use it. This research was aimed at utilizing crucial information taken from a text document to identify the family of several species of medicinal plants using a heuristic approach, i.e. genetic programming. Each of the species has its unique features. The genetic program puts the characteristics or special features of each family into a tree form. There are a number of processes involved in the investigated method, i.e. data acquisition, booleanization, grouping of training and test data, evaluation, and analysis. The genetic program uses a training process to select the best individual, initializes a generate-rule process to create several individuals and then executes a fitness evaluation. The next procedure is a genetic operation process, which consists of tournament selection to choose the best individual based on a fitness value, the crossover operation and the mutation operation. These operations have the purpose of complementing the individual. The best individual acquired is the expected solution, which is a rule for classifying medicinal plants. This process produced three rules, one for each plant family, displaying a feature structure that distinguishes each of the families from each other. The genetic program then used these rules to identify the medicinal plants, achieving an average accuracy of 86.47%.

  20. Genetic Evolution of Shape-Altering Programs for Supersonic Aerodynamics

    Science.gov (United States)

    Kennelly, Robert A., Jr.; Bencze, Daniel P. (Technical Monitor)

    2002-01-01

    Two constrained shape optimization problems relevant to aerodynamics are solved by genetic programming, in which a population of computer programs evolves automatically under pressure of fitness-driven reproduction and genetic crossover. Known optimal solutions are recovered using a small, naive set of elementary operations. Effectiveness is improved through use of automatically defined functions, especially when one of them is capable of a variable number of iterations, even though the test problems lack obvious exploitable regularities. An attempt at evolving new elementary operations was only partially successful.

  1. Template learning of cellular neural network using genetic programming.

    Science.gov (United States)

    Radwan, Elsayed; Tazaki, Eiichiro

    2004-08-01

    A new learning algorithm for space invariant Uncoupled Cellular Neural Network is introduced. Learning is formulated as an optimization problem. Genetic Programming has been selected for creating new knowledge because they allow the system to find new rules both near to good ones and far from them, looking for unknown good control actions. According to the lattice Cellular Neural Network architecture, Genetic Programming will be used in deriving the Cloning Template. Exploration of any stable domain is possible by the current approach. Details of the algorithm are discussed and several application results are shown.

  2. Practical Application of Theory-Driven Intervention to Extension Programming

    Science.gov (United States)

    Bird, Carolyn; McClelland, Jacquelyn

    2010-01-01

    For education to be effective, educators need to understand pertinent theories concerning behavior change and to apply them in programming. The study reported here sought to determine if the Theory of Planned Behavior (TPB) could be used to design, implement, and evaluate a brief educational session. Results show a significant increase in…

  3. Practical Application of Theory-Driven Intervention to Extension Programming

    Science.gov (United States)

    Bird, Carolyn; McClelland, Jacquelyn

    2010-01-01

    For education to be effective, educators need to understand pertinent theories concerning behavior change and to apply them in programming. The study reported here sought to determine if the Theory of Planned Behavior (TPB) could be used to design, implement, and evaluate a brief educational session. Results show a significant increase in…

  4. Assessment of a Professional Development Program on Adult Learning Theory

    Science.gov (United States)

    Malik, Melinda

    2016-01-01

    Librarians at colleges and universities invested in graduate education must understand and incorporate adult learning theories in their reference and instruction interactions with graduate students to more effectively support the students' learning. After participating in a professional development program about adult learning theory, librarians…

  5. Exploring the conceptualization of program theories in Dutch community programs: a multiple case study.

    Science.gov (United States)

    Harting, Janneke; van Assema, Patricia

    2011-03-01

    Our objective was to evaluate whether the limited effectiveness of most community programs intended to prevent disease and promote health should be attributed to the quality of the conceptualization of their program theories. In a retrospective multiple case study we assessed the program theories of 16 community programs (cases) in the Netherlands (1990-2004). Methods were a document analysis, supplemented with member checks (insider information from representatives). We developed a community approach reference framework to guide us in reconstructing and evaluating the program theories. On the whole, programs did not clearly spell out the process theories (enabling the implementation of effective interventions), the program components (interventions) and/or the impact theories (describing pathways from interventions to ultimate effects). Program theories usually turned out to be neither specific nor entirely plausible (complete and valid). The limited effectiveness of most community programs should most probably be attributed to the limited conceptualization of program theories to begin with. Such a failure generally also precludes a thorough examination of the effectiveness of the community approach as such.

  6. Genetic programming applied to RFI mitigation in radio astronomy

    Science.gov (United States)

    Staats, K.

    2016-12-01

    Genetic Programming is a type of machine learning that employs a stochastic search of a solutions space, genetic operators, a fitness function, and multiple generations of evolved programs to resolve a user-defined task, such as the classification of data. At the time of this research, the application of machine learning to radio astronomy was relatively new, with a limited number of publications on the subject. Genetic Programming had never been applied, and as such, was a novel approach to this challenging arena. Foundational to this body of research, the application Karoo GP was developed in the programming language Python following the fundamentals of tree-based Genetic Programming described in "A Field Guide to Genetic Programming" by Poli, et al. Karoo GP was tasked with the classification of data points as signal or radio frequency interference (RFI) generated by instruments and machinery which makes challenging astronomers' ability to discern the desired targets. The training data was derived from the output of an observation run of the KAT-7 radio telescope array built by the South African Square Kilometre Array (SKA-SA). Karoo GP, kNN, and SVM were comparatively employed, the outcome of which provided noteworthy correlations between input parameters, the complexity of the evolved hypotheses, and performance of raw data versus engineered features. This dissertation includes description of novel approaches to GP, such as upper and lower limits to the size of syntax trees, an auto-scaling multiclass classifier, and a Numpy array element manager. In addition to the research conducted at the SKA-SA, it is described how Karoo GP was applied to fine-tuning parameters of a weather prediction model at the South African Astronomical Observatory (SAAO), to glitch classification at the Laser Interferometer Gravitational-wave Observatory (LIGO), and to astro-particle physics at The Ohio State University.

  7. Theories of Specialized Discourses and Writing Fellows Programs

    Science.gov (United States)

    Severino, Carol; Trachsel, Mary

    2008-01-01

    How much do specialized academic discourse communities matter to undergraduate writers? To what degree should theories of specialized discourses influence the design of undergraduate Writing Across the Curriculum (WAC) programs? At the University of Iowa, where an undergraduate Writing Fellows program engages peer tutors in writing-intensive…

  8. Variation Theory Applied to Students' Conceptions of Computer Programming

    Science.gov (United States)

    Thune, Michael; Eckerdal, Anna

    2009-01-01

    The present work has its focus on university-level engineering education students that do not intend to major in computer science but still have to take a mandatory programming course. Phenomenography and variation theory are applied to empirical data from a study of students' conceptions of computer programming. A phenomenographic outcome space…

  9. Explicating Practicum Program Theory: A Case Example in Human Ecology

    Science.gov (United States)

    Chandler, Kathryn M. M.; Williamson, Deanna L.

    2013-01-01

    This study explicated the theory underpinning the Human Ecology Practicum Program offered in the Department of Human Ecology at the University of Alberta. The program has operated for 40 years but never been formally evaluated. Using a document analysis, focus group and individual interviews, and a stakeholder working group, we explored…

  10. Explicating Practicum Program Theory: A Case Example in Human Ecology

    Science.gov (United States)

    Chandler, Kathryn M. M.; Williamson, Deanna L.

    2013-01-01

    This study explicated the theory underpinning the Human Ecology Practicum Program offered in the Department of Human Ecology at the University of Alberta. The program has operated for 40 years but never been formally evaluated. Using a document analysis, focus group and individual interviews, and a stakeholder working group, we explored…

  11. Feature extraction from multiple data sources using genetic programming.

    Energy Technology Data Exchange (ETDEWEB)

    Szymanski, J. J. (John J.); Brumby, Steven P.; Pope, P. A. (Paul A.); Eads, D. R. (Damian R.); Galassi, M. C. (Mark C.); Harvey, N. R. (Neal R.); Perkins, S. J. (Simon J.); Porter, R. B. (Reid B.); Theiler, J. P. (James P.); Young, A. C. (Aaron Cody); Bloch, J. J. (Jeffrey J.); David, N. A. (Nancy A.); Esch-Mosher, D. M. (Diana M.)

    2002-01-01

    Feature extration from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. The tool used is the GENetic Imagery Exploitation (GENIE) software, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniques to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land-cover features including towns, grasslands, wild fire burn scars, and several types of forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.

  12. A Stability Theory in Nonlinear Programming

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    We propose a new method for finding the local optimal points ofthe constrained nonlinear programming by Ordinary Differential Equations (ODE), and prove asymptotic stability of the singular points of partial variables in this paper. The condition of overall uniform, asymptotic stability is also given.

  13. Proof theory of epistemic logic of programs

    NARCIS (Netherlands)

    Maffezioli, Paolo; Naibo, Alberto

    2014-01-01

    A combination of epistemic logic and dynamic logic of programs is presented. Although rich enough to formalize some simple game-theoretic scenarios, its axiomatization is problematic as it leads to the paradoxical conclusion that agents are omniscient. A cut-free labelled Gentzen-style proof system

  14. Towards a Theory for Testing Non-terminating Programs

    DEFF Research Database (Denmark)

    Gotlieb, Arnaud; Petit, Matthieu

    2009-01-01

    Non-terminating programs are programs that legally perform unbounded computations. Though they are ubiquitous in real-world applications, testing these programs requires new theoretic developments as usual definitions of test data adequacy criteria ignore infinite paths. This paper develops...... a theory of program-based structural testing based on operational semantics. Reasoning at the program semantics level permits to cope with infinite paths (and non-feasible paths) when defining test data adequacy criteria. As a result, our criteria respect the first Weyuker’s property on finite...

  15. Considering genetic characteristics in German Holstein breeding programs.

    Science.gov (United States)

    Segelke, D; Täubert, H; Reinhardt, F; Thaller, G

    2016-01-01

    Recently, several research groups have demonstrated that several haplotypes may cause embryonic loss in the homozygous state. Up to now, carriers of genetic disorders were often excluded from mating, resulting in a decrease of genetic gain and a reduced number of sires available for the breeding program. Ongoing research is very likely to identify additional genetic defects causing embryonic loss and calf mortality by genotyping a large proportion of the female cattle population and sequencing key ancestors. Hence, a clear demand is present to develop a method combining selection against recessive defects (e.g., Holstein haplotypes HH1-HH5) with selection for economically beneficial traits (e.g., polled) for mating decisions. Our proposed method is a genetic index that accounts for the allele frequencies in the population and the economic value of the genetic characteristic without excluding carriers from breeding schemes. Fertility phenotypes from routine genetic evaluations were used to determine the economic value per embryo lost. Previous research has shown that embryo loss caused by HH1 and HH2 occurs later than the loss for HH3, HH4, and HH5. Therefore, an economic value of € 97 was used against HH1 and HH2 and € 70 against HH3, HH4, and HH5. For polled, € 7 per polled calf was considered. Minor allele frequencies of the defects ranged between 0.8 and 3.3%. The polled allele has a frequency of 4.1% in the German Holstein population. A genomic breeding program was simulated to study the effect of changing the selection criteria from assortative mating based on breeding values to selecting the females using the genetic index. Selection for a genetic index on the female path is a useful method to control the allele frequencies by reducing undesirable alleles and simultaneously increasing economical beneficial characteristics maintaining most of the genetic gain in production and functional traits. Additionally, we applied the genetic index to real data and

  16. How genetic analysis tests theories of animal aging.

    Science.gov (United States)

    Hekimi, Siegfried

    2006-09-01

    Each animal species displays a specific life span, rate of aging and pattern of development of age-dependent diseases. The genetic bases of these related features are being studied experimentally in invertebrate and vertebrate model systems as well as in humans through medical records. Three types of mutants are being analyzed: (i) short-lived mutants that are prone to age-dependent diseases and might be models of accelerated aging; (ii) mutants that show overt molecular defects but that do not live shorter lives than controls, and can be used to test specific theories about the molecular causes of aging and age-dependent diseases; and (iii) long-lived mutants that might advance the understanding of the molecular physiology of slow-aging animals and aid the discovery of molecular targets that could be used to manipulate rates of aging to benefit human health. Here, I analyze some of what we know today and discuss what we should try to find out in the future to understand the aging phenomenon.

  17. Learning Theories Applied to Teaching Technology: Constructivism versus Behavioral Theory for Instructing Multimedia Software Programs

    Science.gov (United States)

    Reed, Cajah S.

    2012-01-01

    This study sought to find evidence for a beneficial learning theory to teach computer software programs. Additionally, software was analyzed for each learning theory's applicability to resolve whether certain software requires a specific method of education. The results are meant to give educators more effective teaching tools, so students…

  18. Learning Theories Applied to Teaching Technology: Constructivism versus Behavioral Theory for Instructing Multimedia Software Programs

    Science.gov (United States)

    Reed, Cajah S.

    2012-01-01

    This study sought to find evidence for a beneficial learning theory to teach computer software programs. Additionally, software was analyzed for each learning theory's applicability to resolve whether certain software requires a specific method of education. The results are meant to give educators more effective teaching tools, so students…

  19. SPSS and SAS programs for generalizability theory analyses.

    Science.gov (United States)

    Mushquash, Christopher; O'Connor, Brian P

    2006-08-01

    The identification and reduction of measurement errors is a major challenge in psychological testing. Most investigators rely solely on classical test theory for assessing reliability, whereas most experts have long recommended using generalizability theory instead. One reason for the common neglect of generalizability theory is the absence of analytic facilities for this purpose in popular statistical software packages. This article provides a brief introduction to generalizability theory, describes easy to use SPSS, SAS, and MATLAB programs for conducting the recommended analyses, and provides an illustrative example, using data (N = 329) for the Rosenberg Self-Esteem Scale. Program output includes variance components, relative and absolute errors and generalizability coefficients, coefficients for D studies, and graphs of D study results.

  20. Online Financial Education Programs: Theory, Research, and Recommendations

    Directory of Open Access Journals (Sweden)

    Jinhee Kim

    2017-03-01

    Full Text Available Technological advances have created unprecedented opportunities for online financial education that can be used to improve financial literacy and money management practices. While online financial education programs have become popular, relevant research and theoretical frameworks have rarely been considered in the development of such programs. This article synthesizes lessons from literature and theories for the development of an effective online financial education program. Drawing from literature on financial literacy education and online education, implications and recommendations for integrating technology into online financial education programs for adults are discussed.

  1. Mathematical programming and game theory for decision making

    CERN Document Server

    Bapat, R B; Das, A K; Parthasarathy, T

    2008-01-01

    This edited book presents recent developments and state-of-the-art review in various areas of mathematical programming and game theory. It is a peer-reviewed research monograph under the ISI Platinum Jubilee Series on Statistical Science and Interdisciplinary Research. This volume provides a panoramic view of theory and the applications of the methods of mathematical programming to problems in statistics, finance, games and electrical networks. It also provides an important as well as timely overview of research trends and focuses on the exciting areas like support vector machines, bilevel pro

  2. Initialization Method for Grammar-Guided Genetic Programming

    Science.gov (United States)

    García-Arnau, M.; Manrique, D.; Ríos, J.; Rodríguez-Patón, A.

    This paper proposes a new tree-generation algorithm for grammarguided genetic programming that includes a parameter to control the maximum size of the trees to be generated. An important feature of this algorithm is that the initial populations generated are adequately distributed in terms of tree size and distribution within the search space. Consequently, genetic programming systems starting from the initial populations generated by the proposed method have a higher convergence speed. Two different problems have been chosen to carry out the experiments: a laboratory test involving searching for arithmetical equalities and the real-world task of breast cancer prognosis. In both problems, comparisons have been made to another five important initialization methods.

  3. Multigene Genetic Programming for Estimation of Elastic Modulus of Concrete

    Directory of Open Access Journals (Sweden)

    Alireza Mohammadi Bayazidi

    2014-01-01

    Full Text Available This paper presents a new multigene genetic programming (MGGP approach for estimation of elastic modulus of concrete. The MGGP technique models the elastic modulus behavior by integrating the capabilities of standard genetic programming and classical regression. The main aim is to derive precise relationships between the tangent elastic moduli of normal and high strength concrete and the corresponding compressive strength values. Another important contribution of this study is to develop a generalized prediction model for the elastic moduli of both normal and high strength concrete. Numerous concrete compressive strength test results are obtained from the literature to develop the models. A comprehensive comparative study is conducted to verify the performance of the models. The proposed models perform superior to the existing traditional models, as well as those derived using other powerful soft computing tools.

  4. Genetic variability of broodstocks of restocking programs in Brazil

    Directory of Open Access Journals (Sweden)

    Nelson Lopera-Barrero

    2015-09-01

    Full Text Available Objective. The aim of this study was evaluate the genetic diversity of the following broodstocks: piapara (Leporinus elongatus, dourado (Salminus brasiliensis, jundiá (Rhamdia quelen and cachara (Pseudoplatystoma fasciatum already useful for restocking programs in the Paranapanema, Iguaçu and Paraná Brazilian Rivers. Materials and methods. Samples from the caudal fin of 122 fish were analyzed. DNA was extracted by NaCl protocol. PCR products were separated by a horizontal agarose gel electrophoresis. The fragments were visualized by staining with ethidium bromide. Results. The amplification of 25 primers generated different fragments in studied species that allowed characterizing 440 fragments of 100-2900 bp. High percentage of polymorphic fragments (66.67 to 86.29, Shannon index (0.365 to 0.486 and genetic diversity of Nei (0.248 to 0.331 were detected. Conclusions. The level of genetic variability in the broodstocks was adequate for allowing their use in restocking programs in the studied Rivers. However, periodical monitoring studies of genetic variability in these stocks, the mating system, reproductive system and general management must be made to guarantee the preservation of wild populations.

  5. Finding Approximate Analytic Solutions to Differential Equations by Seed Selection Genetic Programming

    Institute of Scientific and Technical Information of China (English)

    侯进军

    2007-01-01

    @@ 1 Seed Selection Genetic Programming In Genetic Programming, each tree in population shows an algebraic or surmounting expression, and each algebraic or surmounting expression shows an approximate analytic solution to differential equations.

  6. Genetic regulation of programmed cell death in Drosophila

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Programmed cell death plays an important role in maintaining homeostasis during animal development, and has been conserved in animals as different as nematodes and humans. Recent studies of Drosophila have provided valuable information toward our understanding of genetic regulation of death. Different signals trigger the novel death regulators rpr, hid, and grim, that utilize the evolutionarily conserved iap and ark genes to modulate caspase function. Subsequent removal of dying cells also appears to be accomplished by conserved mechanisms. The similarity between Drosophila and human in cell death signaling pathways illustrate the promise of fruit flies as a model system to elucidate the mechanisms underlying regulation of programmed cell death.

  7. Genetic programming-based chaotic time series modeling

    Institute of Scientific and Technical Information of China (English)

    张伟; 吴智铭; 杨根科

    2004-01-01

    This paper proposes a Genetic Programming-Based Modeling (GPM) algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space, and the Particle Swarm Optimization (PSO) algorithm is used for Nonlinear Parameter Estimation (NPE) of dynamic model structures. In addition, GPM integrates the results of Nonlinear Time Series Analysis (NTSA) to adjust the parameters and takes them as the criteria of established models. Experiments showed the effectiveness of such improvements on chaotic time series modeling.

  8. Long Term Energy Consumption Forecasting Using Genetic Programming

    OpenAIRE

    KARABULUT, Korhan; Alkan, Ahmet; YILMAZ, Ahmet

    2008-01-01

    Managing electrical energy supply is a complex task. The most important part of electric utility resource planning is forecasting of the future load demand in the regional or national service area. This is usually achieved by constructing models on relative information, such as climate and previous load demand data. In this paper, a genetic programming approach is proposed to forecast long term electrical power consumption in the area covered by a utility situated in the southeast of Turkey. ...

  9. Tracking the Genetic Stability of a Honey Bee (Hymenoptera: Apidae) Breeding Program With Genetic Markers.

    Science.gov (United States)

    Bourgeois, Lelania; Beaman, Lorraine

    2017-08-01

    A genetic stock identification (GSI) assay was developed in 2008 to distinguish Russian honey bees from other honey bee stocks that are commercially produced in the United States. Probability of assignment (POA) values have been collected and maintained since the stock release in 2008 to the Russian Honey Bee Breeders Association. These data were used to assess stability of the breeding program and the diversity levels of the contemporary breeding stock through comparison of POA values and genetic diversity parameters from the initial release to current values. POA values fluctuated throughout 2010-2016, but have recovered to statistically similar levels in 2016 (POA(2010) = 0.82, POA(2016) = 0.74; P = 0.33). Genetic diversity parameters (i.e., allelic richness and gene diversity) in 2016 also remained at similar levels when compared to those in 2010. Estimates of genetic structure revealed stability (FST(2009/2016) = 0.0058) with a small increase in the estimate of the inbreeding coefficient (FIS(2010) = 0.078, FIS(2016) = 0.149). The relationship among breeding lines, based on genetic distance measurement, was similar in 2008 and 2016 populations, but with increased homogeneity among lines (i.e., decreased genetic distance). This was expected based on the closed breeding system used for Russian honey bees. The successful application of the GSI assay in a commercial breeding program demonstrates the utility and stability of such technology to contribute to and monitor the genetic integrity of a breeding stock of an insect species. Published by Oxford University Press on behalf of Entomological Society of America 2017. This work is written by US Government employees and is in the public domain in the US.

  10. Generation Expansion Planning in pool market: A hybrid modified game theory and improved genetic algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Shayanfar, H.A.; Lahiji, A. Saliminia; Aghaei, J.; Rabiee, A. [Center of Excellence for Power System Automation and Operation, Electrical Engineering Department, Iran University of Science and Technology (IUST), Tehran (Iran)

    2009-05-15

    Unlike the traditional policy, Generation Expansion Planning (GEP) problem in competitive framework is complicated. In the new policy, each Generation Company (GENCO) decides to invest in such a way that obtains as much profit as possible. This paper presents a new hybrid algorithm to determine GEP in a Pool market. The proposed algorithm is divided in two programming levels: master and slave. In the master level a Modified Game Theory (MGT) is proposed to evaluate the contrast of GENCOs by the Independent System Operator (ISO). In the slave level, an Improved Genetic Algorithm (IGA) method is used to find the best solution of each GENCO for decision-making of investment. The validity of the proposed method is examined in the case study including three GENCOs with multi-type of power plants. The results show that the presented method is both satisfactory and consistent with expectation. (author)

  11. Genetic Programming Modeling and Complexity Analysis of the Magnetoencephalogram of Epileptic Patients

    Science.gov (United States)

    Georgopoulos, Efstratios F.; Adamopoulos, Adam V.; Likothanassis, Spiridon D.

    In this work MagnetoEncephaloGram (MEG) recordings of epileptic patients are modeled using a genetic programming approach. This is the first time that genetic programming is used to model MEG signal. Numerous experiments were conducted giving highly successful results. It is demonstrated that genetic programming can produce very simple nonlinear models that fit with great accuracy the observed data of MEG.

  12. Genetic algorithms principles and perspectives : a guide to GA theory

    CERN Document Server

    Reeves, Colin R; Reeves, Colin R

    2002-01-01

    Genetic Algorithms (GAs) have become a highly effective tool for solving hard optimization problems. This text provides a survey of some important theoretical contributions, many of which have been proposed and developed in the Foundations of Genetic Algorithms series of workshops.

  13. Integrating Program Theory and Systems-Based Procedures in Program Evaluation: A Dynamic Approach to Evaluate Educational Programs

    Science.gov (United States)

    Grammatikopoulos, Vasilis

    2012-01-01

    The current study attempts to integrate parts of program theory and systems-based procedures in educational program evaluation. The educational program that was implemented, called the "Early Steps" project, proposed that physical education can contribute to various educational goals apart from the usual motor skills improvement. Basic…

  14. Integrating Program Theory and Systems-Based Procedures in Program Evaluation: A Dynamic Approach to Evaluate Educational Programs

    Science.gov (United States)

    Grammatikopoulos, Vasilis

    2012-01-01

    The current study attempts to integrate parts of program theory and systems-based procedures in educational program evaluation. The educational program that was implemented, called the "Early Steps" project, proposed that physical education can contribute to various educational goals apart from the usual motor skills improvement. Basic…

  15. Integrating Program Theory and Systems-Based Procedures in Program Evaluation: A Dynamic Approach to Evaluate Educational Programs

    Science.gov (United States)

    Grammatikopoulos, Vasilis

    2012-01-01

    The current study attempts to integrate parts of program theory and systems-based procedures in educational program evaluation. The educational program that was implemented, called the "Early Steps" project, proposed that physical education can contribute to various educational goals apart from the usual motor skills improvement. Basic elements of…

  16. The Behavior Intervention Support Team (BIST) Program: Underlying Theories

    Science.gov (United States)

    Boulden, Walter T.

    2010-01-01

    The Behavior Intervention Support Team (BIST) is a proactive school-wide behavior management plan for all students, emphasizing schools partnering with students and parents through caring relationships and high expectations. The BIST program is well-grounded in behavioral theory and combines strength-based and resiliency principles within the…

  17. Modern evolutionary mechanics theories and resolving the programmed/non-programmed aging controversy.

    Science.gov (United States)

    Goldsmith, Theodore C

    2014-10-01

    Modern programmed (adaptive) theories of biological aging contend that organisms including mammals have generally evolved mechanisms that purposely limit their lifespans in order to obtain an evolutionary benefit. Modern non-programmed theories contend that mammal aging generally results from natural deteriorative processes, and that lifespan differences between species are explained by differences in the degree to which they resist those processes. Originally proposed in the 19th century, programmed aging in mammals has historically been widely summarily rejected as obviously incompatible with the mechanics of the evolution process. However, relatively recent and continuing developments described here have dramatically changed this situation, and programmed mammal aging now has a better evolutionary basis than non-programmed aging. Resolution of this issue is critically important to medical research because the two theories predict that very different biological mechanisms are ultimately responsible for age-related diseases and conditions.

  18. Using genetic algorithm based fuzzy adaptive resonance theory for clustering analysis

    Institute of Scientific and Technical Information of China (English)

    LIU Bo; WANG Yong; WANG Hong-jian

    2006-01-01

    In the clustering applications field, fuzzy adaptive resonance theory system has been widely applied. But, three parameters of fuzzy adaptive resonance theory need to be adjusted manually for obtaining better clustering. It needs much time to test and does not assure a best result. Genetic algorithm is an optimal mathematical search technique based on the principles of natural selection and genetic recombination. So, to make the fuzzy adaptive resonance theory parameters choosing process automation, an approach incorporating genetic algorithm and fuzzy adaptive resonance theory neural network has been applied. Then, the best clustering result can be obtained.Through experiment, it can be proved that the most appropriate parameters of fuzzy adaptive resonance theory can be gained effectively by this approach.

  19. Genetic Programming Neural Networks: A Powerful Bioinformatics Tool for Human Genetics.

    Science.gov (United States)

    Ritchie, Marylyn D; Motsinger, Alison A; Bush, William S; Coffey, Christopher S; Moore, Jason H

    2007-01-01

    The identification of genes that influence the risk of common, complex disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. This challenge is partly due to the limitations of parametric statistical methods for detecting genetic effects that are dependent solely or partially on interactions. We have previously introduced a genetic programming neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of genetic and gene-environment combinations associated with disease risk. Previous empirical studies suggest GPNN has excellent power for identifying gene-gene and gene-environment interactions. The goal of this study was to compare the power of GPNN to stepwise logistic regression (SLR) and classification and regression trees (CART) for identifying gene-gene and gene-environment interactions. SLR and CART are standard methods of analysis for genetic association studies. Using simulated data, we show that GPNN has higher power to identify gene-gene and gene-environment interactions than SLR and CART. These results indicate that GPNN may be a useful pattern recognition approach for detecting gene-gene and gene-environment interactions in studies of human disease.

  20. An Interpretation of Part of Gilbert Gottlieb's Legacy: Developmental Systems Theory Contra Developmental Behavior Genetics

    Science.gov (United States)

    Molenaar, Peter C. M.

    2015-01-01

    The main theme of this paper concerns the persistent critique of Gilbert Gottlieb on developmental behavior genetics and my reactions to this critique, the latter changing from rejection to complete acceptation. Concise characterizations of developmental behavior genetics, developmental systems theory (to which Gottlieb made essential…

  1. Human genetics of infectious diseases: a unified theory

    Science.gov (United States)

    Casanova, Jean-Laurent; Abel, Laurent

    2007-01-01

    Since the early 1950s, the dominant paradigm in the human genetics of infectious diseases postulates that rare monogenic immunodeficiencies confer vulnerability to multiple infectious diseases (one gene, multiple infections), whereas common infections are associated with the polygenic inheritance of multiple susceptibility genes (one infection, multiple genes). Recent studies, since 1996 in particular, have challenged this view. A newly recognised group of primary immunodeficiencies predisposing the individual to a principal or single type of infection is emerging. In parallel, several common infections have been shown to reflect the inheritance of one major susceptibility gene, at least in some populations. This novel causal relationship (one gene, one infection) blurs the distinction between patient-based Mendelian genetics and population-based complex genetics, and provides a unified conceptual frame for exploring the molecular genetic basis of infectious diseases in humans. PMID:17255931

  2. NASA's Heliophysics Theory Program - Accomplishments in Life Cycle Ending 2011

    Science.gov (United States)

    Grebowsky, J.

    2011-01-01

    NASA's Heliophysics Theory Program (HTP) is now into a new triennial cycle of funded research, with new research awards beginning in 2011. The theory program was established by the (former) Solar Terrestrial Division in 1980 to redress a weakness of support in the theory area. It has been a successful, evolving scientific program with long-term funding of relatively large "critical mass groups" pursuing theory and modeling on a scale larger than that available within the limits of traditional NASA Supporting Research and Technology (SR&T) awards. The results of the last 3 year funding cycle, just ended, contributed to ever more cutting edge theoretical understanding of all parts of the Sun-Earth Connection chain. Advances ranged from the core of the Sun out into the corona, through the solar wind into the Earth's magnetosphere and down to the ionosphere and lower atmosphere, also contributing to understanding the environments of other solar system bodies. The HTP contributions were not isolated findings but continued to contribute to the planning and implementation of NASA spacecraft missions and to the development of the predictive computer models that have become the workhorses for analyzing satellite and ground-based measurements.

  3. Feedback Control of Turbulent Shear Flows by Genetic Programming

    CERN Document Server

    Duriez, Thomas; von Krbek, Kai; Bonnet, Jean-Paul; Cordier, Laurent; Noack, Bernd R; Segond, Marc; Abel, Markus; Gautier, Nicolas; Aider, Jean-Luc; Raibaudo, Cedric; Cuvier, Christophe; Stanislas, Michel; Debien, Antoine; Mazellier, Nicolas; Kourta, Azeddine; Brunton, Steven L

    2015-01-01

    Turbulent shear flows have triggered fundamental research in nonlinear dynamics, like transition scenarios, pattern formation and dynamical modeling. In particular, the control of nonlinear dynamics is subject of research since decades. In this publication, actuated turbulent shear flows serve as test-bed for a nonlinear feedback control strategy which can optimize an arbitrary cost function in an automatic self-learning manner. This is facilitated by genetic programming providing an analytically treatable control law. Unlike control based on PID laws or neural networks, no structure of the control law needs to be specified in advance. The strategy is first applied to low-dimensional dynamical systems featuring aspects of turbulence and for which linear control methods fail. This includes stabilizing an unstable fixed point of a nonlinearly coupled oscillator model and maximizing mixing, i.e.\\ the Lyapunov exponent, for forced Lorenz equations. For the first time, we demonstrate the applicability of genetic p...

  4. A theory-informed, process-oriented Resident Scholarship Program

    Directory of Open Access Journals (Sweden)

    Satid Thammasitboon

    2016-06-01

    Full Text Available Background: The Accreditation Council for Graduate Medical Education requires residency programs to provide curricula for residents to engage in scholarly activities but does not specify particular guidelines for instruction. We propose a Resident Scholarship Program that is framed by the self-determination theory (SDT and emphasize the process of scholarly activity versus a scholarly product. Methods: The authors report on their longitudinal Resident Scholarship Program, which aimed to support psychological needs central to SDT: autonomy, competence, and relatedness. By addressing those needs in program aims and program components, the program may foster residents’ intrinsic motivation to learn and to engage in scholarly activity. To this end, residents’ engagement in scholarly processes, and changes in perceived autonomy, competence, and relatedness were assessed. Results: Residents engaged in a range of scholarly projects and expressed positive regard for the program. Compared to before residency, residents felt more confident in the process of scholarly activity, as determined by changes in increased perceived autonomy, competence, and relatedness. Scholarly products were accomplished in return for a focus on scholarly process. Conclusions: Based on our experience, and in line with the SDT, supporting residents’ autonomy, competence, and relatedness through a process-oriented scholarship program may foster the curiosity, inquisitiveness, and internal motivation to learn that drives scholarly activity and ultimately the production of scholarly products.

  5. Stream Flow Prediction by Remote Sensing and Genetic Programming

    Science.gov (United States)

    Chang, Ni-Bin

    2009-01-01

    A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.

  6. Genetic programming-based chaotic time series modeling

    Institute of Scientific and Technical Information of China (English)

    张伟; 吴智铭; 杨根科

    2004-01-01

    This paper proposes a Genetic Programming-Based Modeling(GPM)algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space,and the Particle Swarm Optimization(PSO)algorithm is used for Nonlinear Parameter Estimation(NPE)of dynamic model structures. In addition,GPM integrates the results of Nonlinear Time Series Analysis(NTSA)to adjust the parameters and takes them as the criteria of established models.Experiments showed the effectiveness of such improvements on chaotic time series modeling.

  7. Combining classifiers generated by multi-gene genetic programming for protein fold recognition using genetic algorithm.

    Science.gov (United States)

    Bardsiri, Mahshid Khatibi; Eftekhari, Mahdi; Mousavi, Reza

    2015-01-01

    In this study the problem of protein fold recognition, that is a classification task, is solved via a hybrid of evolutionary algorithms namely multi-gene Genetic Programming (GP) and Genetic Algorithm (GA). Our proposed method consists of two main stages and is performed on three datasets taken from the literature. Each dataset contains different feature groups and classes. In the first step, multi-gene GP is used for producing binary classifiers based on various feature groups for each class. Then, different classifiers obtained for each class are combined via weighted voting so that the weights are determined through GA. At the end of the first step, there is a separate binary classifier for each class. In the second stage, the obtained binary classifiers are combined via GA weighting in order to generate the overall classifier. The final obtained classifier is superior to the previous works found in the literature in terms of classification accuracy.

  8. The QB program: Analysing resonances using R-matrix theory

    Science.gov (United States)

    Quigley, Lisa; Berrington, Keith; Pelan, John

    1998-11-01

    A procedure for analysing resonances in atomic and molecular collision theory is programmed, which exploits the analytic properties of R-matrix theory to obtain the energy derivative of the reactance ( K) matrix. This procedure is based on the QB method (J. Phys. B 29 (1996) 4529) which defines matrices Q and B in terms of asymptotic solutions, the R-matrix and energy derivatives, such that d K/d E= B-1Q, from which eigenphase gradients of the K matrix can be obtained. Resonance positions are defined at the points of maximum gradient; resonance widths are related to the inverse of the eigenphase gradients; resonance identifications are estimated from outer region solutions. The program is tested on the twenty lowest Be-like Ne resonances 1 s22 P1/2,3/2nl J - 1° ( n ≤ 10). The test data is incorporated in the Fortran program, which can therefore be compiled and run as it stands; otherwise the program is designed for input of an 'H-file' in the format defined by RMATRX1 (Comput. Phys. Commun. 92 (1995) 290).

  9. Information theory, multivariate dependence, and genetic network inference

    CERN Document Server

    Nemenman, Ilya

    2007-01-01

    We define the concept of dependence among multiple variables using maximum entropy techniques and introduce a graphical notation to denote the dependencies. Direct inference of information theoretic quantities from data uncovers dependencies even in undersampled regimes when the joint probability distribution cannot be reliably estimated. The method is tested on synthetic data. We anticipate it to be useful for inference of genetic circuits and other biological signaling networks.

  10. EVOLVING RETRIEVAL ALGORITHMS WITH A GENETIC PROGRAMMING SCHEME

    Energy Technology Data Exchange (ETDEWEB)

    J. THEILER; ET AL

    1999-06-01

    The retrieval of scene properties (surface temperature, material type, vegetation health, etc.) from remotely sensed data is the ultimate goal of many earth observing satellites. The algorithms that have been developed for these retrievals are informed by physical models of how the raw data were generated. This includes models of radiation as emitted and/or rejected by the scene, propagated through the atmosphere, collected by the optics, detected by the sensor, and digitized by the electronics. To some extent, the retrieval is the inverse of this ''forward'' modeling problem. But in contrast to this forward modeling, the practical task of making inferences about the original scene usually requires some ad hoc assumptions, good physical intuition, and a healthy dose of trial and error. The standard MTI data processing pipeline will employ algorithms developed with this traditional approach. But we will discuss some preliminary research on the use of a genetic programming scheme to ''evolve'' retrieval algorithms. Such a scheme cannot compete with the physical intuition of a remote sensing scientist, but it may be able to automate some of the trial and error. In this scenario, a training set is used, which consists of multispectral image data and the associated ''ground truth;'' that is, a registered map of the desired retrieval quantity. The genetic programming scheme attempts to combine a core set of image processing primitives to produce an IDL (Interactive Data Language) program which estimates this retrieval quantity from the raw data.

  11. Behavioural Susceptibility Theory: Professor Jane Wardle and the Role of Appetite in Genetic Risk of Obesity.

    Science.gov (United States)

    Llewellyn, Clare H; Fildes, Alison

    2017-03-01

    There is considerable variability in human body weight, despite the ubiquity of the 'obesogenic' environment. Human body weight has a strong genetic basis and it has been hypothesised that genetic susceptibility to the environment explains variation in human body weight, with differences in appetite being implicated as the mediating mechanism; so-called 'behavioural susceptibility theory' (BST), first described by Professor Jane Wardle. This review summarises the evidence for the role of appetite as a mediator of genetic risk of obesity. Variation in appetitive traits is observable from infancy, drives early weight gain and is highly heritable in infancy and childhood. Obesity-related common genetic variants identified through genome-wide association studies show associations with appetitive traits, and appetite mediates part of the observed association between genetic risk and adiposity. Obesity results from an interaction between genetic susceptibility to overeating and exposure to an 'obesogenic' food environment.

  12. A new crossover operator in genetic programming for object classification.

    Science.gov (United States)

    Zhang, Mengjie; Gao, Xiaoying; Lou, Weijun

    2007-10-01

    The crossover operator has been considered "the centre of the storm" in genetic programming (GP). However, many existing GP approaches to object recognition suggest that the standard GP crossover is not sufficiently powerful in producing good child programs due to the totally random choice of the crossover points. To deal with this problem, this paper introduces an approach with a new crossover operator in GP for object recognition, particularly object classification. In this approach, a local hill-climbing search is used in constructing good building blocks, a weight called looseness is introduced to identify the good building blocks in individual programs, and the looseness values are used as heuristics in choosing appropriate crossover points to preserve good building blocks. This approach is examined and compared with the standard crossover operator and the headless chicken crossover (HCC) method on a sequence of object classification problems. The results suggest that this approach outperforms the HCC, the standard crossover, and the standard crossover operator with hill climbing on all of these problems in terms of the classification accuracy. Although this approach spends a bit longer time than the standard crossover operator, it significantly improves the system efficiency over the HCC method.

  13. Using Program Theory-Driven Evaluation Science to Crack the Da Vinci Code

    Science.gov (United States)

    Donaldson, Stewart I.

    2005-01-01

    Program theory-driven evaluation science uses substantive knowledge, as opposed to method proclivities, to guide program evaluations. It aspires to update, clarify, simplify, and make more accessible the evolving theory of evaluation practice commonly referred to as theory-driven or theory-based evaluation. The evaluator in this chapter provides a…

  14. Genetic counseling services and development of training programs in Malaysia.

    Science.gov (United States)

    Lee, Juliana Mei-Har; Thong, Meow-Keong

    2013-12-01

    Genetic counseling service is urgently required in developing countries. In Malaysia, the first medical genetic service was introduced in 1994 at one of the main teaching hospitals in Kuala Lumpur. Two decades later, the medical genetic services have improved with the availability of genetic counseling, genetic testing and diagnosis, for both paediatric conditions and adult-onset inherited conditions, at four main centers of medical genetic services in Malaysia. Prenatal diagnosis services and assisted reproductive technologies are available at tertiary centres and private medical facilities. Positive developments include governmental recognition of Clinical Genetics as a subspecialty, increased funding for genetics services, development of medical ethics guidelines, and establishment of support groups. However, the country lacked qualified genetic counselors. Proposals were presented to policy-makers to develop genetic counseling courses. Challenges encountered included limited resources and public awareness, ethical dilemmas such as religious and social issues and inadequate genetic health professionals especially genetic counselors.

  15. Practice-based competencies for accreditation of and training in graduate programs in genetic counseling.

    Science.gov (United States)

    Fine, B A; Baker, D L; Fiddler, M B

    1996-09-01

    In January 1996, the American Board of Genetic Counseling (ABGC) adopted 27 practice-based competencies as a standard for assessing the training of graduate students in genetic counseling. These competencies were identified and refined through a collective, narrative process that took place from January through November 1994, and included directors of graduate programs in genetic counseling, ABGC board members and expert consultants. These competencies now form the basis of the document "Requirements for Graduate Programs in Genetic Counseling Seeking Accreditation by the American Board of Genetic Counseling" (American Board of Genetic Counseling, 1996). The competencies are organized into four domains and are presented and discussed in this article.

  16. Integer programming model for optimizing bus timetable using genetic algorithm

    Science.gov (United States)

    Wihartiko, F. D.; Buono, A.; Silalahi, B. P.

    2017-01-01

    Bus timetable gave an information for passengers to ensure the availability of bus services. Timetable optimal condition happened when bus trips frequency could adapt and suit with passenger demand. In the peak time, the number of bus trips would be larger than the off-peak time. If the number of bus trips were more frequent than the optimal condition, it would make a high operating cost for bus operator. Conversely, if the number of trip was less than optimal condition, it would make a bad quality service for passengers. In this paper, the bus timetabling problem would be solved by integer programming model with modified genetic algorithm. Modification was placed in the chromosomes design, initial population recovery technique, chromosomes reconstruction and chromosomes extermination on specific generation. The result of this model gave the optimal solution with accuracy 99.1%.

  17. GENETIC PROGRAMMING TO PREDICT SKI-JUMP BUCKET SPILLWAY SCOUR

    Institute of Scientific and Technical Information of China (English)

    AZAMATHULLA H. MD; GHANI A. AB; ZAKARIA N. A; LAI S. H; CHANG C. K; LEOW C. S; ABUHASAN Z

    2008-01-01

    Researchers in the past had noticed that application of Artificial Neural Networks (ANN) in place of conventional statistics on the basis of data mining techniques predicts more accurate results in hydraulic predictions. Mostly these works pertained to applications of ANN. Recently, another tool of soft computing, namely, Genetic Programming (GP) has caught the attention of researchers in civil engineering computing. This article examines the usefulness of the GP based approach to predict the relative scour depth downstream of a common type of ski-jump bucket spillway. Actual field measurements were used to develop the GP model. The GP based estimations were found to be equally and more accurate than the ANN based ones, especially, when the underlying cause-effect relationship became more uncertain to model.

  18. Reversible circuit synthesis by genetic programming using dynamic gate libraries

    Science.gov (United States)

    Abubakar, Mustapha Y.; Jung, Low Tang; Zakaria, Nordin; Younes, Ahmed; Abdel-Aty, Abdel-Haleem

    2017-06-01

    We have defined a new method for automatic construction of reversible logic circuits by using the genetic programming approach. The choice of the gate library is 100% dynamic. The algorithm is capable of accepting all possible combinations of the following gate types: NOT TOFFOLI, NOT PERES, NOT CNOT TOFFOLI, NOT CNOT SWAP FREDKIN, NOT CNOT TOFFOLI SWAP FREDKIN, NOT CNOT PERES, NOT CNOT SWAP FREDKIN PERES, NOT CNOT TOFFOLI PERES and NOT CNOT TOFFOLI SWAP FREDKIN PERES. Our method produced near optimum circuits in some cases when a particular subset of gate types was used in the library. Meanwhile, in some cases, optimal circuits were produced due to the heuristic nature of the algorithm. We compared the outcomes of our method with several existing synthesis methods, and it was shown that our algorithm performed relatively well compared to the previous synthesis methods in terms of the output efficiency of the algorithm and execution time as well.

  19. A Comparison of Genetic Programming Variants for Hyper-Heuristics

    Energy Technology Data Exchange (ETDEWEB)

    Harris, Sean [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-03-01

    Modern society is faced with ever more complex problems, many of which can be formulated as generate-and-test optimization problems. General-purpose optimization algorithms are not well suited for real-world scenarios where many instances of the same problem class need to be repeatedly and efficiently solved, such as routing vehicles over highways with constantly changing traffic flows, because they are not targeted to a particular scenario. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario. Hyper-heuristics typically employ Genetic Programming (GP) and this project has investigated the relationship between the choice of GP and performance in Hyper-heuristics. Results are presented demonstrating the existence of problems for which there is a statistically significant performance differential between the use of different types of GP.

  20. Forecasting tourist arrivals to balearic islands using genetic programming

    Directory of Open Access Journals (Sweden)

    Rosselló-Nadal, Jaume

    2007-01-01

    Full Text Available Traditionally, univariate time-series models have largely dominated forecasting for international tourism demand. In this paper, the ability of a Genetic Program (GP to predict monthly tourist arrivals from UK and Germany to Balearic Islands (Spain is explored. GP has already been employed satisfactorily in different scientific areas, including economics. The technique shows different advantages regarding to other forecasting methods. Firstly, it does not assume a priori a rigid functional form of the model. Secondly, it is more robust and easy-to-use than other non-parametric methods. Finally, it provides explicitly a mathematical equation which allows a simple ad hoc interpretation of the results. Comparing the performance of the proposed technique against other method commonly used in tourism forecasting (no-change model, Moving Average and ARIMA, the empirical results reveal that GP can be a valuable tool in this field.

  1. Comprehensive bidding strategies with genetic programming/finite state automata

    Energy Technology Data Exchange (ETDEWEB)

    Richter, C.W. Jr.; Sheble, G.B.; Ashlock, D.

    1999-11-01

    This research is an extension of the authors' previous work in double auctions aimed at developing bidding strategies for electric utilities which trade electricity competitively. The improvements detailed in this paper come from using data structures which combine genetic programming and finite state automata termed GP-Automata. The strategies developed by the method described here are adaptive--reacting to inputs--whereas the previously developed strategies were only suitable in the particular scenario for which they had been designed. The strategies encoded in the GP-Automata are tested in an auction simulator. The simulator pits them against other distribution companies (distcos) and generation companies (gencos), buying and selling power via double auctions implemented in regional commodity exchanges. The GP-Automata are evolved with a genetic algorithm so that they possess certain characteristics. In addition to designing successful bidding strategies (whose usage would result in higher profits) the resulting strategies can also be designed to imitate certain types of trading behaviors. The resulting strategies can be implemented directly in on-line trading, or can be used as realistic competitors in an off-line trading simulator.

  2. Accurate construction of consensus genetic maps via integer linear programming.

    Science.gov (United States)

    Wu, Yonghui; Close, Timothy J; Lonardi, Stefano

    2011-01-01

    We study the problem of merging genetic maps, when the individual genetic maps are given as directed acyclic graphs. The computational problem is to build a consensus map, which is a directed graph that includes and is consistent with all (or, the vast majority of) the markers in the input maps. However, when markers in the individual maps have ordering conflicts, the resulting consensus map will contain cycles. Here, we formulate the problem of resolving cycles in the context of a parsimonious paradigm that takes into account two types of errors that may be present in the input maps, namely, local reshuffles and global displacements. The resulting combinatorial optimization problem is, in turn, expressed as an integer linear program. A fast approximation algorithm is proposed, and an additional speedup heuristic is developed. Our algorithms were implemented in a software tool named MERGEMAP which is freely available for academic use. An extensive set of experiments shows that MERGEMAP consistently outperforms JOINMAP, which is the most popular tool currently available for this task, both in terms of accuracy and running time. MERGEMAP is available for download at http://www.cs.ucr.edu/~yonghui/mgmap.html.

  3. A novel genetic programming approach for epileptic seizure detection.

    Science.gov (United States)

    Bhardwaj, Arpit; Tiwari, Aruna; Krishna, Ramesh; Varma, Vishaal

    2016-02-01

    The human brain is a delicate mix of neurons (brain cells), electrical impulses and chemicals, known as neurotransmitters. Any damage has the potential to disrupt the workings of the brain and cause seizures. These epileptic seizures are the manifestations of epilepsy. The electroencephalograph (EEG) signals register average neuronal activity from the cerebral cortex and label changes in activity over large areas. A detailed analysis of these electroencephalograph (EEG) signals provides valuable insights into the mechanisms instigating epileptic disorders. Moreover, the detection of interictal spikes and epileptic seizures in an EEG signal plays an important role in the diagnosis of epilepsy. Automatic seizure detection methods are required, as these epileptic seizures are volatile and unpredictable. This paper deals with an automated detection of epileptic seizures in EEG signals using empirical mode decomposition (EMD) for feature extraction and proposes a novel genetic programming (GP) approach for classifying the EEG signals. Improvements in the standard GP approach are made using a Constructive Genetic Programming (CGP) in which constructive crossover and constructive subtree mutation operators are introduced. A hill climbing search is integrated in crossover and mutation operators to remove the destructive nature of these operators. A new concept of selecting the Globally Prime offspring is also presented to select the best fitness offspring generated during crossover. To decrease the time complexity of GP, a new dynamic fitness value computation (DFVC) is employed to increase the computational speed. We conducted five different sets of experiments to evaluate the performance of the proposed model in the classification of different mixtures of normal, interictal and ictal signals, and the accuracies achieved are outstandingly high. The experimental results are compared with the existing methods on same datasets, and these results affirm the potential use of

  4. Multi-Center Genetic Study of Hypertension: The Family Blood Pressure Program (FBPP)

    National Research Council Canada - National Science Library

    The FBPP Investigators

    2002-01-01

    The Family Blood Pressure Program (FBPP) consists of 4 independently established multicenter networks of investigators who have complementary approaches to the genetics of blood pressure levels and hypertension...

  5. Using Implementation and Program Theory to Examine Communication Strategies in National Wildlife Federation's Backyard Wildlife Habitat Program

    Science.gov (United States)

    Palmer, Dain; Dann, Shari L.

    2004-01-01

    Our evaluative approach used implementation theory and program theory, adapted from Weiss (1998) to examine communication processes and results for a national wildlife habitat stewardship education program. Using a mail survey of 1427 participants certified in National Wildlife Federation's (NWF) Backyard Wildlife Habitat (BWH) program and a study…

  6. A convergence theory for a class of nonlinear programming problems.

    Science.gov (United States)

    Rauch, S. W.

    1973-01-01

    A recent convergence theory of Elkin concerning methods for unconstrained minimization is extended to a certain class of nonlinear programming problems. As in Elkin's original approach, the analysis of a variety of step-length algorithms is treated entirely separately from that of several direction algorithms. This allows for their combination into many different methods for solving the constrained problem. These include some of the methods of Rosen and Zoutendijk. We also extend the results of Topkis and Veinott to nonconvex sets and drop their requirement of the uniform feasibility of a subsequence of the search directions.

  7. Automatic cone photoreceptor segmentation using graph theory and dynamic programming.

    Science.gov (United States)

    Chiu, Stephanie J; Lokhnygina, Yuliya; Dubis, Adam M; Dubra, Alfredo; Carroll, Joseph; Izatt, Joseph A; Farsiu, Sina

    2013-06-01

    Geometrical analysis of the photoreceptor mosaic can reveal subclinical ocular pathologies. In this paper, we describe a fully automatic algorithm to identify and segment photoreceptors in adaptive optics ophthalmoscope images of the photoreceptor mosaic. This method is an extension of our previously described closed contour segmentation framework based on graph theory and dynamic programming (GTDP). We validated the performance of the proposed algorithm by comparing it to the state-of-the-art technique on a large data set consisting of over 200,000 cones and posted the results online. We found that the GTDP method achieved a higher detection rate, decreasing the cone miss rate by over a factor of five.

  8. Condemned by Birth: The implications of Genetics for the Theories of Crime and Punishment

    Directory of Open Access Journals (Sweden)

    Meghna Rajadhyaksha

    2010-01-01

    Full Text Available This article traces debates around relevance of genetics in determining culpability. The chief trends in this regard are illustrated by decisions of the American Courts over the past century, which have moved from applications of blind heredity to sophisticated molecular analyses. Since genetics impacts the basic assumption of "free will" in criminal law, its use as a defence has been examined at length. Finally, this article examines the methodsand theories of punishment, and their effectiveness in preventing and penalizing the actions of "genetic offenders".

  9. Structural health monitoring feature design by genetic programming

    Science.gov (United States)

    Harvey, Dustin Y.; Todd, Michael D.

    2014-09-01

    Structural health monitoring (SHM) systems provide real-time damage and performance information for civil, aerospace, and other high-capital or life-safety critical structures. Conventional data processing involves pre-processing and extraction of low-dimensional features from in situ time series measurements. The features are then input to a statistical pattern recognition algorithm to perform the relevant classification or regression task necessary to facilitate decisions by the SHM system. Traditional design of signal processing and feature extraction algorithms can be an expensive and time-consuming process requiring extensive system knowledge and domain expertise. Genetic programming, a heuristic program search method from evolutionary computation, was recently adapted by the authors to perform automated, data-driven design of signal processing and feature extraction algorithms for statistical pattern recognition applications. The proposed method, called Autofead, is particularly suitable to handle the challenges inherent in algorithm design for SHM problems where the manifestation of damage in structural response measurements is often unclear or unknown. Autofead mines a training database of response measurements to discover information-rich features specific to the problem at hand. This study provides experimental validation on three SHM applications including ultrasonic damage detection, bearing damage classification for rotating machinery, and vibration-based structural health monitoring. Performance comparisons with common feature choices for each problem area are provided demonstrating the versatility of Autofead to produce significant algorithm improvements on a wide range of problems.

  10. The Development of Genetics in the Light of Thomas Kuhn's Theory of Scientific Revolutions.

    Science.gov (United States)

    Portin, Petter

    2015-01-01

    The concept of a paradigm is in the key position in Thomas Kuhn's theory of scientific revolutions. A paradigm is the framework within which the results, concepts, hypotheses and theories of scientific research work are understood. According to Kuhn, a paradigm guides the working and efforts of scientists during the time period which he calls the period of normal science. Before long, however, normal science leads to unexplained matters, a situation that then leads the development of the scientific discipline in question to a paradigm shift--a scientific revolution. When a new theory is born, it has either gradually emerged as an extension of the past theory, or the old theory has become a borderline case in the new theory. In the former case, one can speak of a paradigm extension. According to the present author, the development of modern genetics has, until very recent years, been guided by a single paradigm, the Mendelian paradigm which Gregor Mendel launched 150 years ago, and under the guidance of this paradigm the development of genetics has proceeded in a normal fashion in the spirit of logical positivism. Modern discoveries in genetics have, however, created a situation which seems to be leading toward a paradigm shift. The most significant of these discoveries are the findings of adaptive mutations, the phenomenon of transgenerational epigenetic inheritance, and, above all, the present deeply critical state of the concept of the gene.

  11. Genetic basis of common diseases: the general theory of Mendelian recessive genetics.

    Science.gov (United States)

    Hutchinson, Michael; Spanaki, Cleanthe; Lebedev, Sergey; Plaitakis, Andreas

    2005-01-01

    Common diseases tend to appear sporadically, i.e., they appear in an individual who has no first or second degree relatives with the disease. Yet diseases are often associated with a slight but definite increase in risk to the children of an affected individual. This weak pattern of inheritability cannot be explained by conventional interpretations of Mendelian genetics, and it is therefore commonly held that there is "incomplete penetrance" of a gene, or that there are polygenic, or multifactorial modes of inheritance. However, such arguments are heuristic and lack predictive power. Here, we explore the possibility that "incomplete penetrance" means the existence of a second, disease-related, gene. By examining in detail a specific common condition, Parkinson's disease (PD), we show that the sporadic form of the disease can be fully explained by a compact fully penetrant genotype involving an interaction between two, and only two, genes. In this model, therefore PD is fundamentally genetic. Our digenic model is complementary to Mendelian recessive genetics, but taken together with the latter forms a complete description for recessive genetics on one chromosome. It explains the slight increase in risk to the children if one parent has sporadic PD, and makes strict predictions where both parents coincidentally have sporadic PD. These predictions were verified in two large and carefully selected kindred, where the data also argue against other genetic models, including oligogenic and polygenic schemes. Since the inheritance patterns of sporadic PD are reminiscent of what is seen in many common diseases, it is plausible that similar genetic forms could apply to other diseases. Seen in this light, diseases wash in and out of every family, so that in a sense, over time every human family is equally at risk for most diseases.

  12. Empirical valence bond models for reactive potential energy surfaces: a parallel multilevel genetic program approach.

    Science.gov (United States)

    Bellucci, Michael A; Coker, David F

    2011-07-28

    We describe a new method for constructing empirical valence bond potential energy surfaces using a parallel multilevel genetic program (PMLGP). Genetic programs can be used to perform an efficient search through function space and parameter space to find the best functions and sets of parameters that fit energies obtained by ab initio electronic structure calculations. Building on the traditional genetic program approach, the PMLGP utilizes a hierarchy of genetic programming on two different levels. The lower level genetic programs are used to optimize coevolving populations in parallel while the higher level genetic program (HLGP) is used to optimize the genetic operator probabilities of the lower level genetic programs. The HLGP allows the algorithm to dynamically learn the mutation or combination of mutations that most effectively increase the fitness of the populations, causing a significant increase in the algorithm's accuracy and efficiency. The algorithm's accuracy and efficiency is tested against a standard parallel genetic program with a variety of one-dimensional test cases. Subsequently, the PMLGP is utilized to obtain an accurate empirical valence bond model for proton transfer in 3-hydroxy-gamma-pyrone in gas phase and protic solvent.

  13. Using IBMs to Investigate Spatially-dependent Processes in Landscape Genetics Theory

    Science.gov (United States)

    Much of landscape and conservation genetics theory has been derived using non-spatialmathematical models. Here, we use a mechanistic, spatially-explicit, eco-evolutionary IBM to examine the utility of this theoretical framework in landscapes with spatial structure. Our analysis...

  14. Using IBMs to Investigate Spatially-dependent Processes in Landscape Genetics Theory

    Science.gov (United States)

    Much of landscape and conservation genetics theory has been derived using non-spatialmathematical models. Here, we use a mechanistic, spatially-explicit, eco-evolutionary IBM to examine the utility of this theoretical framework in landscapes with spatial structure. Our analysis...

  15. Interfacing theories of program with theories of evaluation for advancing evaluation practice: Reductionism, systems thinking, and pragmatic synthesis.

    Science.gov (United States)

    Chen, Huey T

    2016-12-01

    Theories of program and theories of evaluation form the foundation of program evaluation theories. Theories of program reflect assumptions on how to conceptualize an intervention program for evaluation purposes, while theories of evaluation reflect assumptions on how to design useful evaluation. These two types of theories are related, but often discussed separately. This paper attempts to use three theoretical perspectives (reductionism, systems thinking, and pragmatic synthesis) to interface them and discuss the implications for evaluation practice. Reductionism proposes that an intervention program can be broken into crucial components for rigorous analyses; systems thinking view an intervention program as dynamic and complex, requiring a holistic examination. In spite of their contributions, reductionism and systems thinking represent the extreme ends of a theoretical spectrum; many real-world programs, however, may fall in the middle. Pragmatic synthesis is being developed to serve these moderate- complexity programs. These three theoretical perspectives have their own strengths and challenges. Knowledge on these three perspectives and their evaluation implications can provide a better guide for designing fruitful evaluations, improving the quality of evaluation practice, informing potential areas for developing cutting-edge evaluation approaches, and contributing to advancing program evaluation toward a mature applied science.

  16. Modeling the MagnetoencephaloGram (MEG) Of Epileptic Patients Using Genetic Programming and Minimizing the Derived Models Using Genetic Algorithms

    Science.gov (United States)

    Theofilatos, Konstantinos; Georgopoulos, Efstratios; Likothanassis, Spiridon

    2009-09-01

    In this paper, a variation of traditional Genetic Programming(GP) is used to model the MagnetoencephaloGram(MEG) of Epileptic Patients. This variation is Linear Genetic Programming(LGP). LGP is a particular subset of GP wherein computer programs in population are represented as a sequence of instructions from imperative programming language or machine language. The derived models from this method were simplified using genetic algorithms. The proposed method was used to model the MEG signal of epileptic patients using 6 different datasets. Each dataset uses different number of previous values of MEG to predict the next value. The models were tested in datasets different from the ones which were used to produce them and the results were very promising.

  17. The Genetic Theory of Infectious Diseases: A Brief History and Selected Illustrations

    Science.gov (United States)

    Casanova, Jean-Laurent; Abel, Laurent

    2016-01-01

    Until the mid-nineteenth century, life expectancy at birth averaged 20 years worldwide, owing mostly to childhood fevers. The germ theory of diseases then gradually overcame the belief that diseases were intrinsic. However, around the turn of the twentieth century, asymptomatic infection was discovered to be much more common than clinical disease. Paradoxically, this observation barely challenged the newly developed notion that infectious diseases were fundamentally extrinsic. Moreover, interindividual variability in the course of infection was typically explained by the emerging immunological (or somatic) theory of infectious diseases, best illustrated by the impact of vaccination. This powerful explanation is, however, best applicable to reactivation and secondary infections, particularly in adults; it can less easily account for interindividual variability in the course of primary infection during childhood. Population and clinical geneticists soon proposed a complementary hypothesis, a germline genetic theory of infectious diseases. Over the past century, this idea has gained some support, particularly among clinicians and geneticists, but has also encountered resistance, particularly among microbiologists and immunologists. We present here the genetic theory of infectious diseases and briefly discuss its history and the challenges encountered during its emergence in the context of the apparently competing but actually complementary microbiological and immunological theories. We also illustrate its recent achievements by highlighting inborn errors of immunity underlying eight life-threatening infectious diseases of children and young adults. Finally, we consider the far-reaching biological and clinical implications of the ongoing human genetic dissection of severe infectious diseases. PMID:23724903

  18. The genetic theory of infectious diseases: a brief history and selected illustrations.

    Science.gov (United States)

    Casanova, Jean-Laurent; Abel, Laurent

    2013-01-01

    Until the mid-nineteenth century, life expectancy at birth averaged 20 years worldwide, owing mostly to childhood fevers. The germ theory of diseases then gradually overcame the belief that diseases were intrinsic. However, around the turn of the twentieth century, asymptomatic infection was discovered to be much more common than clinical disease. Paradoxically, this observation barely challenged the newly developed notion that infectious diseases were fundamentally extrinsic. Moreover, interindividual variability in the course of infection was typically explained by the emerging immunological (or somatic) theory of infectious diseases, best illustrated by the impact of vaccination. This powerful explanation is, however, best applicable to reactivation and secondary infections, particularly in adults; it can less easily account for interindividual variability in the course of primary infection during childhood. Population and clinical geneticists soon proposed a complementary hypothesis, a germline genetic theory of infectious diseases. Over the past century, this idea has gained some support, particularly among clinicians and geneticists, but has also encountered resistance, particularly among microbiologists and immunologists. We present here the genetic theory of infectious diseases and briefly discuss its history and the challenges encountered during its emergence in the context of the apparently competing but actually complementary microbiological and immunological theories. We also illustrate its recent achievements by highlighting inborn errors of immunity underlying eight life-threatening infectious diseases of children and young adults. Finally, we consider the far-reaching biological and clinical implications of the ongoing human genetic dissection of severe infectious diseases.

  19. Applying the genetic theories of ageing to the cytoplasm: cytoplasmic genetic covariation for fitness and lifespan.

    Science.gov (United States)

    Dowling, D K; Maklakov, A A; Friberg, U; Hailer, F

    2009-04-01

    Two genetic models exist to explain the evolution of ageing - mutation accumulation (MA) and antagonistic pleiotropy (AP). Under MA, a reduced intensity of selection with age results in accumulation of late-acting deleterious mutations. Under AP, late-acting deleterious mutations accumulate because they confer beneficial effects early in life. Recent studies suggest that the mitochondrial genome is a major player in ageing. It therefore seems plausible that the MA and AP models will be relevant to genomes within the cytoplasm. This possibility has not been considered previously. We explore whether patterns of covariation between fitness and ageing across 25 cytoplasmic lines, sampled from a population of Drosophila melanogaster, are consistent with the genetic associations predicted under MA or AP. We find negative covariation for fitness and the rate of ageing, and positive covariation for fitness and lifespan. Notably, the direction of these associations is opposite to that typically predicted under AP.

  20. Population genetics analysis using R and the Geneland program

    DEFF Research Database (Denmark)

    Guillot, Gilles; Santos, Filipe; Estoup, Arnaud

    2011-01-01

    Geneland program documentation 2011 Program distributed under GNU license as an R package on the Comprehensive R Archive Network.......Geneland program documentation 2011 Program distributed under GNU license as an R package on the Comprehensive R Archive Network....

  1. Goodness of Fit Assessment of an Alcohol Intervention Program and the Underlying Theories of Change

    Science.gov (United States)

    Ramos, Diana; Perkins, Daniel F.

    2006-01-01

    The authors conducted an investigation of The Pennsylvania State University's Alcohol Intervention Program Level 2 (AIP2) to determine goodness of fit of the program components and its underpinning theories. They determined that the Health Belief Model, Social Norms Theory, Social Learning Theory, and the Transtheoretical Model Stages of Change…

  2. Coevolution Theory of the Genetic Code at Age Forty: Pathway to Translation and Synthetic Life.

    Science.gov (United States)

    Wong, J Tze-Fei; Ng, Siu-Kin; Mat, Wai-Kin; Hu, Taobo; Xue, Hong

    2016-03-16

    The origins of the components of genetic coding are examined in the present study. Genetic information arose from replicator induction by metabolite in accordance with the metabolic expansion law. Messenger RNA and transfer RNA stemmed from a template for binding the aminoacyl-RNA synthetase ribozymes employed to synthesize peptide prosthetic groups on RNAs in the Peptidated RNA World. Coevolution of the genetic code with amino acid biosynthesis generated tRNA paralogs that identify a last universal common ancestor (LUCA) of extant life close to Methanopyrus, which in turn points to archaeal tRNA introns as the most primitive introns and the anticodon usage of Methanopyrus as an ancient mode of wobble. The prediction of the coevolution theory of the genetic code that the code should be a mutable code has led to the isolation of optional and mandatory synthetic life forms with altered protein alphabets.

  3. Coevolution Theory of the Genetic Code at Age Forty: Pathway to Translation and Synthetic Life

    Directory of Open Access Journals (Sweden)

    J. Tze-Fei Wong

    2016-03-01

    Full Text Available The origins of the components of genetic coding are examined in the present study. Genetic information arose from replicator induction by metabolite in accordance with the metabolic expansion law. Messenger RNA and transfer RNA stemmed from a template for binding the aminoacyl-RNA synthetase ribozymes employed to synthesize peptide prosthetic groups on RNAs in the Peptidated RNA World. Coevolution of the genetic code with amino acid biosynthesis generated tRNA paralogs that identify a last universal common ancestor (LUCA of extant life close to Methanopyrus, which in turn points to archaeal tRNA introns as the most primitive introns and the anticodon usage of Methanopyrus as an ancient mode of wobble. The prediction of the coevolution theory of the genetic code that the code should be a mutable code has led to the isolation of optional and mandatory synthetic life forms with altered protein alphabets.

  4. Coevolution Theory of the Genetic Code at Age Forty: Pathway to Translation and Synthetic Life

    Science.gov (United States)

    Wong, J. Tze-Fei; Ng, Siu-Kin; Mat, Wai-Kin; Hu, Taobo; Xue, Hong

    2016-01-01

    The origins of the components of genetic coding are examined in the present study. Genetic information arose from replicator induction by metabolite in accordance with the metabolic expansion law. Messenger RNA and transfer RNA stemmed from a template for binding the aminoacyl-RNA synthetase ribozymes employed to synthesize peptide prosthetic groups on RNAs in the Peptidated RNA World. Coevolution of the genetic code with amino acid biosynthesis generated tRNA paralogs that identify a last universal common ancestor (LUCA) of extant life close to Methanopyrus, which in turn points to archaeal tRNA introns as the most primitive introns and the anticodon usage of Methanopyrus as an ancient mode of wobble. The prediction of the coevolution theory of the genetic code that the code should be a mutable code has led to the isolation of optional and mandatory synthetic life forms with altered protein alphabets. PMID:26999216

  5. Genetic programming approach to evaluate complexity of texture images

    Science.gov (United States)

    Ciocca, Gianluigi; Corchs, Silvia; Gasparini, Francesca

    2016-11-01

    We adopt genetic programming (GP) to define a measure that can predict complexity perception of texture images. We perform psychophysical experiments on three different datasets to collect data on the perceived complexity. The subjective data are used for training, validation, and test of the proposed measure. These data are also used to evaluate several possible candidate measures of texture complexity related to both low level and high level image features. We select four of them (namely roughness, number of regions, chroma variance, and memorability) to be combined in a GP framework. This approach allows a nonlinear combination of the measures and could give hints on how the related image features interact in complexity perception. The proposed complexity measure M exhibits Pearson correlation coefficients of 0.890 on the training set, 0.728 on the validation set, and 0.724 on the test set. M outperforms each of all the single measures considered. From the statistical analysis of different GP candidate solutions, we found that the roughness measure evaluated on the gray level image is the most dominant one, followed by the memorability, the number of regions, and finally the chroma variance.

  6. Automating the packing heuristic design process with genetic programming.

    Science.gov (United States)

    Burke, Edmund K; Hyde, Matthew R; Kendall, Graham; Woodward, John

    2012-01-01

    The literature shows that one-, two-, and three-dimensional bin packing and knapsack packing are difficult problems in operational research. Many techniques, including exact, heuristic, and metaheuristic approaches, have been investigated to solve these problems and it is often not clear which method to use when presented with a new instance. This paper presents an approach which is motivated by the goal of building computer systems which can design heuristic methods. The overall aim is to explore the possibilities for automating the heuristic design process. We present a genetic programming system to automatically generate a good quality heuristic for each instance. It is not necessary to change the methodology depending on the problem type (one-, two-, or three-dimensional knapsack and bin packing problems), and it therefore has a level of generality unmatched by other systems in the literature. We carry out an extensive suite of experiments and compare with the best human designed heuristics in the literature. Note that our heuristic design methodology uses the same parameters for all the experiments. The contribution of this paper is to present a more general packing methodology than those currently available, and to show that, by using this methodology, it is possible for a computer system to design heuristics which are competitive with the human designed heuristics from the literature. This represents the first packing algorithm in the literature able to claim human competitive results in such a wide variety of packing domains.

  7. Genetic Programming Based Ensemble System for Microarray Data Classification

    Directory of Open Access Journals (Sweden)

    Kun-Hong Liu

    2015-01-01

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

  8. The Theory and Practice of Programmed Instruction; A Guide for Teachers.

    Science.gov (United States)

    Pocztar, Jerry

    A historical sketch which traces behavioral theory from Pavlov to Skinner and explains the application of Skinner's theory to teaching begins this introduction to programed instruction. Next, three models of programed courses, Skinner's, Crowder's, and skip-branching, are described. The third section, techniques for elaborating programed courses,…

  9. [Neurosis and genetic theory of etiology and pathogenesis of ulcer disease].

    Science.gov (United States)

    Kolotilova, M L; Ivanov, L N

    2014-01-01

    Based on the analysis of literature data and our own research, we have developed the original concept of etiology and pathogenesis of peptic ulcer disease. An analysis of the literature shows that none of the theories of pathogenesis of peptic ulcer disease does not cover the full diversity of the involved functions and their shifts, which lead to the development of ulcers in the stomach and the duodenum. Our neurogenic-genetic theory of etiology and pathogenesis of gastric ulcer and duodenal ulcer very best explains the cause-and-effect relationships in the patient peptic ulcer, allowing options for predominance in one or the other case factors of neurosis or genetic factors. However, it is clear that the only other: combination of neurogenic factor with genetically modified reactivity of gastroduodenal system (the presence of the target organ) cause the chronicity of the sores. The theory of peptic ulcer disease related to psychosomatic pathologies allows us to develop effective schema therapy, including drugs with psychocorrective action. On the basis of our theory of the role of Helicobacter pylori infection is treated as a pathogenetic factor in the development of peptic ulcer disease.

  10. Granularity of Knowledge Computed by Genetic Algorithms Based on Rough Sets Theory

    Institute of Scientific and Technical Information of China (English)

    Wenyuan Yang; Xiaoping Ye; Yong Tang; Pingping Wei

    2006-01-01

    Rough set philosophy hinges on the granularity of data, which is used to build all its basic concepts, like approximations, dependencies, reduction etc. Genetic Algorithms provides a general frame to optimize problem solution of complex system without depending on the domain of problem. It is robust to many kinds of problems. The paper combines Genetic Algorithms and rough sets theory to compute granular of knowledge through an example of information table. The combination enable us to compute granular of knowledge effectively. It is also useful for computer auto-computing and information processing.

  11. Social contract theory and just decision making: lessons from genetic testing for the BRCA mutations.

    Science.gov (United States)

    Williams-Jones, Bryn; Burgess, Michael M

    2004-06-01

    Decisions about funding health services are crucial to controlling costs in health care insurance plans, yet they encounter serious challenges from intellectual property protection--e.g., patents--of health care services. Using Myriad Genetics' commercial genetic susceptibility test for hereditary breast cancer (BRCA testing) in the context of the Canadian health insurance system as a case study, this paper applies concepts from social contract theory to help develop more just and rational approaches to health care decision making. Specifically, Daniel's and Sabin's "accountability for reasonableness" is compared to broader notions of public consultation, demonstrating that expert assessments in specific decisions must be transparent and accountable and supplemented by public consultation.

  12. Studying the learning of programming using grounded theory to support activity theory

    Directory of Open Access Journals (Sweden)

    Graham Alsop

    2011-02-01

    Full Text Available Teaching programming to first year undergraduates in large numbers is challenging. Currently, online supported learning is becoming more dominant, even on face-to-face courses, and this trend will increase in the future. This paper uses activity theory (AT to analyse the use of tools to support learning. Data collection took place during 2008-2010 at Kingston University and involves over one hundred responses. This has been analysed into activity systems offering a detailed analysis of the use of a number of tools being used (in AT these include physical tools, such as technologies including books, and non-physical tools, such as conversation. When teaching programming to large numbers of students it is difficult to offer one-to-one attention and the reliance on such tools becomes more important. For example, in student responses a good integrated development environment (IDE is shown to make learning easier and more enjoyable, whereas a bad IDE makes the learning experience poor. Teaching materials, and access to these, were often mentioned positively. These included online communication, discussion boards and video lectures. Using AT offers sufficiently rich detail to identify key interventions and aids the redesign of the learning process. For example, the choice of an IDE for a specific language can have a larger impact than is initially apparent. This paper will report on the data collected to show where simple improvements to the use of tools may have a large impact on students' abilities to learn programming.

  13. Estimating soil wetting patterns for drip irrigation using genetic programming

    Energy Technology Data Exchange (ETDEWEB)

    Samadianfard, S.; Sadraddini, A. A.; Nazemi, A. H.; Provenzano, G.; Kisi, O.

    2012-07-01

    Drip irrigation is considered as one of the most efficient irrigation systems. Knowledge of the soil wetted perimeter arising from infiltration of water from drippers is important in the design and management of efficient irrigation systems. To this aim, numerical models can represent a powerful tool to analyze the evolution of the wetting pattern during irrigation, in order to explore drip irrigation management strategies, to set up the duration of irrigation, and finally to optimize water use efficiency. This paper examines the potential of genetic programming (GP) in simulating wetting patterns of drip irrigation. First by considering 12 different soil textures of USDA-SCS soil texture triangle, different emitter discharge and duration of irrigation, soil wetting patterns have been simulated by using HYDRUS 2D software. Then using the calculated values of depth and radius of wetting pattern as target outputs, two different GP models have been considered. Finally, the capability of GP for simulating wetting patterns was analyzed using some values of data set that were not used in training. Results showed that the GP method had good agreement with results of HYDRUS 2D software in the case of considering full set of operators with R{sup 2} of 0.99 and 0.99 and root mean squared error of 2.88 and 4.94 in estimation of radius and depth of wetting patterns, respectively. Also, field experimental results in a sandy loam soil with emitter discharge of 4 L h{sup -}1 showed reasonable agreement with GP results. As a conclusion, the results of the study demonstrate the usefulness of the GP method for estimating wetting patterns of drip irrigation. (Author) 40 refs.

  14. Mathematical Modeling of Intestinal Iron Absorption Using Genetic Programming

    Science.gov (United States)

    Colins, Andrea; Gerdtzen, Ziomara P.; Nuñez, Marco T.; Salgado, J. Cristian

    2017-01-01

    Iron is a trace metal, key for the development of living organisms. Its absorption process is complex and highly regulated at the transcriptional, translational and systemic levels. Recently, the internalization of the DMT1 transporter has been proposed as an additional regulatory mechanism at the intestinal level, associated to the mucosal block phenomenon. The short-term effect of iron exposure in apical uptake and initial absorption rates was studied in Caco-2 cells at different apical iron concentrations, using both an experimental approach and a mathematical modeling framework. This is the first report of short-term studies for this system. A non-linear behavior in the apical uptake dynamics was observed, which does not follow the classic saturation dynamics of traditional biochemical models. We propose a method for developing mathematical models for complex systems, based on a genetic programming algorithm. The algorithm is aimed at obtaining models with a high predictive capacity, and considers an additional parameter fitting stage and an additional Jackknife stage for estimating the generalization error. We developed a model for the iron uptake system with a higher predictive capacity than classic biochemical models. This was observed both with the apical uptake dataset used for generating the model and with an independent initial rates dataset used to test the predictive capacity of the model. The model obtained is a function of time and the initial apical iron concentration, with a linear component that captures the global tendency of the system, and a non-linear component that can be associated to the movement of DMT1 transporters. The model presented in this paper allows the detailed analysis, interpretation of experimental data, and identification of key relevant components for this complex biological process. This general method holds great potential for application to the elucidation of biological mechanisms and their key components in other complex

  15. A genetic programming approach to oral cancer prognosis

    Directory of Open Access Journals (Sweden)

    Mei Sze Tan

    2016-09-01

    Full Text Available Background The potential of genetic programming (GP on various fields has been attained in recent years. In bio-medical field, many researches in GP are focused on the recognition of cancerous cells and also on gene expression profiling data. In this research, the aim is to study the performance of GP on the survival prediction of a small sample size of oral cancer prognosis dataset, which is the first study in the field of oral cancer prognosis. Method GP is applied on an oral cancer dataset that contains 31 cases collected from the Malaysia Oral Cancer Database and Tissue Bank System (MOCDTBS. The feature subsets that is automatically selected through GP were noted and the influences of this subset on the results of GP were recorded. In addition, a comparison between the GP performance and that of the Support Vector Machine (SVM and logistic regression (LR are also done in order to verify the predictive capabilities of the GP. Result The result shows that GP performed the best (average accuracy of 83.87% and average AUROC of 0.8341 when the features selected are smoking, drinking, chewing, histological differentiation of SCC, and oncogene p63. In addition, based on the comparison results, we found that the GP outperformed the SVM and LR in oral cancer prognosis. Discussion Some of the features in the dataset are found to be statistically co-related. This is because the accuracy of the GP prediction drops when one of the feature in the best feature subset is excluded. Thus, GP provides an automatic feature selection function, which chooses features that are highly correlated to the prognosis of oral cancer. This makes GP an ideal prediction model for cancer clinical and genomic data that can be used to aid physicians in their decision making stage of diagnosis or prognosis.

  16. Improving the Impact and Implementation of Disaster Education: Programs for Children Through Theory-Based Evaluation.

    Science.gov (United States)

    Johnson, Victoria A; Ronan, Kevin R; Johnston, David M; Peace, Robin

    2016-11-01

    A main weakness in the evaluation of disaster education programs for children is evaluators' propensity to judge program effectiveness based on changes in children's knowledge. Few studies have articulated an explicit program theory of how children's education would achieve desired outcomes and impacts related to disaster risk reduction in households and communities. This article describes the advantages of constructing program theory models for the purpose of evaluating disaster education programs for children. Following a review of some potential frameworks for program theory development, including the logic model, the program theory matrix, and the stage step model, the article provides working examples of these frameworks. The first example is the development of a program theory matrix used in an evaluation of ShakeOut, an earthquake drill practiced in two Washington State school districts. The model illustrates a theory of action; specifically, the effectiveness of school earthquake drills in preventing injuries and deaths during disasters. The second example is the development of a stage step model used for a process evaluation of What's the Plan Stan?, a voluntary teaching resource distributed to all New Zealand primary schools for curricular integration of disaster education. The model illustrates a theory of use; specifically, expanding the reach of disaster education for children through increased promotion of the resource. The process of developing the program theory models for the purpose of evaluation planning is discussed, as well as the advantages and shortcomings of the theory-based approaches.

  17. A Domain-Independent Window Approach to Multiclass Object Detection Using Genetic Programming

    Directory of Open Access Journals (Sweden)

    Mengjie Zhang

    2003-07-01

    Full Text Available This paper describes a domain-independent approach to the use of genetic programming for object detection problems in which the locations of small objects of multiple classes in large images must be found. The evolved program is scanned over the large images to locate the objects of interest. The paper develops three terminal sets based on domain-independent pixel statistics and considers two different function sets. The fitness function is based on the detection rate and the false alarm rate. We have tested the method on three object detection problems of increasing difficulty. This work not only extends genetic programming to multiclass-object detection problems, but also shows how to use a single evolved genetic program for both object classification and localisation. The object classification map developed in this approach can be used as a general classification strategy in genetic programming for multiple-class classification problems.

  18. Genetic programming as alternative for predicting development effort of individual software projects.

    Directory of Open Access Journals (Sweden)

    Arturo Chavoya

    Full Text Available Statistical and genetic programming techniques have been used to predict the software development effort of large software projects. In this paper, a genetic programming model was used for predicting the effort required in individually developed projects. Accuracy obtained from a genetic programming model was compared against one generated from the application of a statistical regression model. A sample of 219 projects developed by 71 practitioners was used for generating the two models, whereas another sample of 130 projects developed by 38 practitioners was used for validating them. The models used two kinds of lines of code as well as programming language experience as independent variables. Accuracy results from the model obtained with genetic programming suggest that it could be used to predict the software development effort of individual projects when these projects have been developed in a disciplined manner within a development-controlled environment.

  19. R. A. Fisher. The relevance of the genetical theory of natural selection

    Directory of Open Access Journals (Sweden)

    Paola Monari

    2013-05-01

    Full Text Available Starting from the main statement that “. . . natural selection is not evolution. . . ”, R.A. Fisher built the foundation of the genetic theory of population in his famous work Genetical Theory of Natural Selection (1930. He rewrote the scientific paradigm proposed by Darwin in statistical terms using the calculus of probability and, most importantly, statistics. The key to his formal transposition is in the analysis of variance inwhich Fisher interpreted as phenomenical variability by means of random variability: this completely original result would become a fundamental chapter of statisticalmethod. It is not by chance that at the same time he published his statistical method for research workers in which the analysis of variance dominated his primary elements of the design of experiments.

  20. CDPOP: A spatially explicit cost distance population genetics program

    Science.gov (United States)

    Erin L. Landguth; S. A. Cushman

    2010-01-01

    Spatially explicit simulation of gene flow in complex landscapes is essential to explain observed population responses and provide a foundation for landscape genetics. To address this need, we wrote a spatially explicit, individual-based population genetics model (CDPOP). The model implements individual-based population modelling with Mendelian inheritance and k-allele...

  1. SAM: The "Search and Match" Computer Program of the Escherichia coli Genetic Stock Center

    Science.gov (United States)

    Bachmann, B. J.; And Others

    1973-01-01

    Describes a computer program used at a genetic stock center to locate particular strains of bacteria. The program can match up to 30 strain descriptions requested by a researcher with the records on file. Uses of this particular program can be made in many fields. (PS)

  2. Genetic engineering of mice to test the oxidative damage theory of aging.

    Science.gov (United States)

    Martin, George M

    2005-12-01

    The laboratory mouse Mus musculus domesticus provides the best current mammalian models for the genetic analysis of aging. We give a brief overview of the use of transgenic manipulations to test the oxidative damage theory of aging. These manipulations are of two types: The first approach engineers mice that exhibit increased sensitivities to oxidative damage and thus produces mice that are likely to be short-lived. The second approach engineers mice to be more resistant to such injuries, and thus may produce mice that exhibit enhanced longevities, something that is much harder to engineer. The latter result is thus more meaningful, with the caveat that it may result from some special vulnerability of a particular lab strain or lab strains in general. The first approach, most elegantly carried out by Arlan Richardson's laboratory, provides evidence against the oxidative damage theory. My colleagues and I have been engaged in the second approach and have accumulated evidence supporting the theory. These conventional transgenic experiments, however, should be supplemented by alternative genetic approaches. One that is surprisingly neglected takes advantage of the pleuripotency of embryonic stem cells and the power of somatic cell genetics. A cautionary note is that interventions that minimize oxidative stress may be complicated by unwanted compromises of physiologically adaptive actions such as superoxide signaling and the possible protective effects of certain oxidatively modified proteins.

  3. Genetics of the peloponnesean populations and the theory of extinction of the medieval peloponnesean Greeks.

    Science.gov (United States)

    Stamatoyannopoulos, George; Bose, Aritra; Teodosiadis, Athanasios; Tsetsos, Fotis; Plantinga, Anna; Psatha, Nikoletta; Zogas, Nikos; Yannaki, Evangelia; Zalloua, Pierre; Kidd, Kenneth K; Browning, Brian L; Stamatoyannopoulos, John; Paschou, Peristera; Drineas, Petros

    2017-05-01

    Peloponnese has been one of the cradles of the Classical European civilization and an important contributor to the ancient European history. It has also been the subject of a controversy about the ancestry of its population. In a theory hotly debated by scholars for over 170 years, the German historian Jacob Philipp Fallmerayer proposed that the medieval Peloponneseans were totally extinguished by Slavic and Avar invaders and replaced by Slavic settlers during the 6th century CE. Here we use 2.5 million single-nucleotide polymorphisms to investigate the genetic structure of Peloponnesean populations in a sample of 241 individuals originating from all districts of the peninsula and to examine predictions of the theory of replacement of the medieval Peloponneseans by Slavs. We find considerable heterogeneity of Peloponnesean populations exemplified by genetically distinct subpopulations and by gene flow gradients within Peloponnese. By principal component analysis (PCA) and ADMIXTURE analysis the Peloponneseans are clearly distinguishable from the populations of the Slavic homeland and are very similar to Sicilians and Italians. Using a novel method of quantitative analysis of ADMIXTURE output we find that the Slavic ancestry of Peloponnesean subpopulations ranges from 0.2 to 14.4%. Subpopulations considered by Fallmerayer to be Slavic tribes or to have Near Eastern origin, have no significant ancestry of either. This study rejects the theory of extinction of medieval Peloponneseans and illustrates how genetics can clarify important aspects of the history of a human population.

  4. Theory in the Service of Practice: Theories in Action Research Dissertations Written by Students in Education Doctorate Programs

    Science.gov (United States)

    Zambo, Debby

    2014-01-01

    Educational leaders are enrolling in second-generation education doctorate (EdD) programs because these are allowing them to remain in the field as they pursue their degree and perform action research within their workplace. As part of degree requirements, students in these programs are challenged to cross the theory-to-practice divide. However,…

  5. Revisiting the antagonistic pleiotropy theory of aging: TOR-driven program and quasi-program.

    Science.gov (United States)

    Blagosklonny, Mikhail V

    2010-08-15

    A half century ago, the antagonistic pleiotropy (AP) theory had solved a mystery of aging, by postulating genes beneficial early in life at the cost of aging. Recently it was argued however that there are very few clear-cut examples of antagonistically pleiotropic (AP) genes other than p53. In contrast, here I discuss that p53 is not a clear-cut example of AP genes but is rather an aging-suppressor (gerosuppressor). In contrast, clear-cut examples of AP genes are genes that encode the TOR (target of rapamycin) pathway. TOR itself is the ultimate example of AP gene because its deletion is lethal in embryogenesis. Early in life the TOR pathway drives developmental program, which persists later in life as an aimless quasi-program of aging and age-related diseases.

  6. Promoting theory of mind during middle childhood: a training program.

    Science.gov (United States)

    Lecce, Serena; Bianco, Federica; Devine, Rory T; Hughes, Claire; Banerjee, Robin

    2014-10-01

    Evidence that conversations about the mind foster improvements in theory of mind (ToM) is growing, but their efficacy in typically developing school-aged children has yet to be demonstrated. To address this gap, we designed a conversation-based training program for 9- and 10-year-olds and measured its effectiveness by pre- and post-test comparisons of performance on age-appropriate ToM tasks for two groups (matched at pre-test for gender, age, socioeconomic background, verbal ability, reading comprehension, executive functions, and ToM) who were assigned to either the intervention condition (n=45) or an active control condition (n=46). The intervention group showed significantly greater gains in ToM than the control group; this contrast was stable over 2 months, and (in a subsample) the improvement in ToM was independent of any changes in executive functions. Implications for the role of conversations about the mind in children's mental state reasoning are discussed.

  7. The Father Friendly Initiative within Families: Using a logic model to develop program theory for a father support program.

    Science.gov (United States)

    Gervais, Christine; de Montigny, Francine; Lacharité, Carl; Dubeau, Diane

    2015-10-01

    The transition to fatherhood, with its numerous challenges, has been well documented. Likewise, fathers' relationships with health and social services have also begun to be explored. Yet despite the problems fathers experience in interactions with healthcare services, few programs have been developed for them. To explain this, some authors point to the difficulty practitioners encounter in developing and structuring the theory of programs they are trying to create to promote and support father involvement (Savaya, R., & Waysman, M. (2005). Administration in Social Work, 29(2), 85), even when such theory is key to a program's effectiveness (Chen, H.-T. (2005). Practical program evaluation. Thousand Oaks, CA: Sage Publications). The objective of the present paper is to present a tool, the logic model, to bridge this gap and to equip practitioners for structuring program theory. This paper addresses two questions: (1) What would be a useful instrument for structuring the development of program theory in interventions for fathers? (2) How would the concepts of a father involvement program best be organized? The case of the Father Friendly Initiative within Families (FFIF) program is used to present and illustrate six simple steps for developing a logic model that are based on program theory and demonstrate its relevance.

  8. A Genetic-Algorithms-Based Approach for Programming Linear and Quadratic Optimization Problems with Uncertainty

    Directory of Open Access Journals (Sweden)

    Weihua Jin

    2013-01-01

    Full Text Available This paper proposes a genetic-algorithms-based approach as an all-purpose problem-solving method for operation programming problems under uncertainty. The proposed method was applied for management of a municipal solid waste treatment system. Compared to the traditional interactive binary analysis, this approach has fewer limitations and is able to reduce the complexity in solving the inexact linear programming problems and inexact quadratic programming problems. The implementation of this approach was performed using the Genetic Algorithm Solver of MATLAB (trademark of MathWorks. The paper explains the genetic-algorithms-based method and presents details on the computation procedures for each type of inexact operation programming problems. A comparison of the results generated by the proposed method based on genetic algorithms with those produced by the traditional interactive binary analysis method is also presented.

  9. Developing close combat behaviors for simulated soldiers using genetic programming techniques.

    Energy Technology Data Exchange (ETDEWEB)

    Pryor, Richard J.; Schaller, Mark J.

    2003-10-01

    Genetic programming is a powerful methodology for automatically producing solutions to problems in a variety of domains. It has been used successfully to develop behaviors for RoboCup soccer players and simple combat agents. We will attempt to use genetic programming to solve a problem in the domain of strategic combat, keeping in mind the end goal of developing sophisticated behaviors for compound defense and infiltration. The simplified problem at hand is that of two armed agents in a small room, containing obstacles, fighting against each other for survival. The base case and three changes are considered: a memory of positions using stacks, context-dependent genetic programming, and strongly typed genetic programming. Our work demonstrates slight improvements from the first two techniques, and no significant improvement from the last.

  10. Evolving Rule-Based Systems in two Medical Domains using Genetic Programming

    DEFF Research Database (Denmark)

    Tsakonas, A.; Dounias, G.; Jantzen, Jan

    2004-01-01

    We demonstrate, compare and discuss the application of two genetic programming methodologies for the construction of rule-based systems in two medical domains: the diagnosis of Aphasia's subtypes and the classification of Pap-Smear Test examinations. The first approach consists of a scheme...... that combines genetic programming and heuristic hierarchical crisp rule-base construction. The second model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems. Results are also compared for their efficiency, accuracy and comprehensibility, to those...... of a standard entropy based machine learning approach and to those of a standard genetic programming symbolic expression approach. In the diagnosis of subtypes of Aphasia, two models for crisp rule-bases are presented. The first one discriminates between four major types and the second attempts...

  11. Program theory-driven evaluation science in a youth development context.

    Science.gov (United States)

    Deane, Kelsey L; Harré, Niki

    2014-08-01

    Program theory-driven evaluation science (PTDES) provides a useful framework for uncovering the mechanisms responsible for positive change resulting from participation in youth development (YD) programs. Yet it is difficult to find examples of PTDES that capture the complexity of such experiences. This article offers a much-needed example of PTDES applied to Project K, a youth development program with adventure, service-learning and mentoring components. Findings from eight program staff focus groups, 351 youth participants' comments, four key program documents, and results from six previous Project K research projects were integrated to produce a theory of change for the program. A direct logic analysis was then conducted to assess the plausibility of the proposed theory against relevant research literature. This demonstrated that Project K incorporates many of the best practice principles discussed in the literature that covers the three components of the program. The contributions of this theory-building process to organizational learning and development are discussed.

  12. National Survey of Genetics Content in Basic Nursing Preparatory Programs in the United States.

    Science.gov (United States)

    Hetteberg, Carol G.; Prows, Cynthia A.; Deets, Carol; Monsen, Rita B.; Kenner, Carole A.

    1999-01-01

    A sample of 879 basic nursing programs was used to identify the type and amount of genetics content in curricula. Recommendations were made for increasing genetics content as a result of the synthesis of the survey data with previously collected data. (25 references) (Author/JOW)

  13. Effects of genotype x environment interaction on genetic gain in breeding programs

    NARCIS (Netherlands)

    Mulder, H.A.; Bijma, P.

    2005-01-01

    Genotype x environment interaction (G x E) is increasingly important, because breeding programs tend to be more internationally oriented. The aim of this theoretical study was to investigate the effects of G x E on genetic gain in sib-testing and progeny-testing schemes. Loss of genetic gain due to

  14. Some pungent arguments against the physico-chemical theories of the origin of the genetic code and corroborating the coevolution theory.

    Science.gov (United States)

    Di Giulio, Massimo

    2017-02-07

    Whereas it is extremely easy to prove that "if the biosynthetic relationships between amino acids were fundamental in the structuring of the genetic code, then their physico-chemical properties might also be revealed in the genetic code table"; it is, on the contrary, impossible to prove that "if the physico-chemical properties of amino acids were fundamental in the structuring of the genetic code, then the presence of the biosynthetic relationships between amino acids should not be revealed in the genetic code". And, given that in the genetic code table are mirrored both the biosynthetic relationships between amino acids and their physico-chemical properties, all this would be a test that would falsify the physico-chemical theories of the origin of the genetic code. That is to say, if the physico-chemical properties of amino acids had a fundamental role in organizing the genetic code, then we would not have duly revealed the presence - in the genetic code - of the biosynthetic relationships between amino acids, and on the contrary this has been observed. Therefore, this falsifies the physico-chemical theories of genetic code origin. Whereas, the coevolution theory of the origin of the genetic code would be corroborated by this analysis, because it would be able to give a description of evolution of the genetic code more coherent with the indisputable empirical observations that link both the biosynthetic relationships of amino acids and their physico-chemical properties to the evolutionary organization of the genetic code. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Design of Autonomous Navigation Controllers for Unmanned Aerial Vehicles Using Multi-Objective Genetic Programming

    Science.gov (United States)

    2004-03-01

    In Genetic Programming 1997: Proceedings of the Second Annual Conference, pages 398–406, 1997. [23] Emilio Frazzoli. Maneuver-based motion planning...Evolutionary approaches to neural control of rolling, walking, swimming and flying animats or robots. In Richard J. Duro, Jose Santos, and Manuel Grana...objective genetic programming. In Proceedings of the Congress on Evolutionary Computation, Portland, OR, June 2004. [66] Peter Pacheco . Parallel

  16. Theory of mind and the social brain: implications for understanding the genetic basis of schizophrenia.

    Science.gov (United States)

    Martin, A K; Robinson, G; Dzafic, I; Reutens, D; Mowry, B

    2014-01-01

    Genome-wide association studies in schizophrenia have recently made significant progress in our understanding of the complex genetic architecture of this disorder. Many genetic loci have been identified and now require functional investigation. One approach involves studying their correlation with neuroimaging and neurocognitive endophenotypes. Theory of Mind (ToM) deficits are well established in schizophrenia and they appear to fulfill criteria for being considered an endophenotype. We aim to review the behavioral and neuroimaging-based studies of ToM in schizophrenia, assess its suitability as an endophenotype, discuss current findings, and propose future research directions. Suitable research articles were sourced from a comprehensive literature search and from references identified through other studies. ToM deficits are repeatable, stable, and heritable: First-episode patients, those in remission and unaffected relatives all show deficits. Activation and structural differences in brain regions believed important for ToM are also consistently reported in schizophrenia patients at all stages of illness, although no research to date has examined unaffected relatives. Studies using ToM as an endophenotype are providing interesting genetic associations with both single nucleotide polymorphisms (SNPs) and specific copy number variations (CNVs) such as the 22q11.2 deletion syndrome. We conclude that ToM is an important cognitive endophenotype for consideration in future studies addressing the complex genetic architecture of schizophrenia, and may help identify more homogeneous clinical sub-types for further study.

  17. The potential use of genetics to increase the effectiveness of treatment programs for criminal offenders.

    Science.gov (United States)

    Beaver, Kevin M; Jackson, Dylan B; Flesher, Dillon

    2014-01-01

    During the past couple of decades, the amount of research examining the genetic underpinnings to antisocial behaviors, including crime, has exploded. Findings from this body of work have generated a great deal of information linking genetics to criminal involvement. As a partial result, there is now a considerable amount of interest in how these findings should be integrated into the criminal justice system. In the current paper, we outline the potential ways that genetic information can be used to increase the effectiveness of treatment programs designed to reduce recidivism among offenders. We conclude by drawing attention to how genetic information can be used by rehabilitation programs to increase program effectiveness, reduce offender recidivism rates, and enhance public safety.

  18. Discovering Pair-Wise Genetic Interactions: An Information Theory-Based Approach

    Science.gov (United States)

    Ignac, Tomasz M.; Skupin, Alexander; Sakhanenko, Nikita A.; Galas, David J.

    2014-01-01

    Phenotypic variation, including that which underlies health and disease in humans, results in part from multiple interactions among both genetic variation and environmental factors. While diseases or phenotypes caused by single gene variants can be identified by established association methods and family-based approaches, complex phenotypic traits resulting from multi-gene interactions remain very difficult to characterize. Here we describe a new method based on information theory, and demonstrate how it improves on previous approaches to identifying genetic interactions, including both synthetic and modifier kinds of interactions. We apply our measure, called interaction distance, to previously analyzed data sets of yeast sporulation efficiency, lipid related mouse data and several human disease models to characterize the method. We show how the interaction distance can reveal novel gene interaction candidates in experimental and simulated data sets, and outperforms other measures in several circumstances. The method also allows us to optimize case/control sample composition for clinical studies. PMID:24670935

  19. Evidence for the multiple hits genetic theory for inherited language impairment: a case study

    Directory of Open Access Journals (Sweden)

    Tracy M Centanni

    2015-08-01

    Full Text Available Communication disorders have complex genetic origins, with constellations of relevant gene markers that vary across individuals. Some genetic variants are present in healthy individuals as well as those affected by developmental disorders. Growing evidence suggests that some variants may increase susceptibility to these disorders in the presence of other pathogenic gene mutations. In the current study, we describe eight children with specific language impairment and four of these children had a copy number variant in one of these potential susceptibility regions on chromosome 15. Three of these four children also had variants in other genes previously associated with language impairment. Our data support the theory that 15q11.2 is a susceptibility region for developmental disorders, specifically language impairment.

  20. Heuristic Genetic Algorithm for Discretization of Continuous Attributes in Rough Set Theory

    Institute of Scientific and Technical Information of China (English)

    CAO Yun-feng; WANG Yao-cai; WANG Jun-wei

    2006-01-01

    Discretization based on rough set theory aims to seek the possible minimum number of the cut set without weakening the indiscernibility of the original decision system. Optimization of discretization is an NP-complete problem and the genetic algorithm is an appropriate method to solve it. In order to achieve optimal discretization, first the choice of the initial set of cut set is discussed, because a good initial cut set can enhance the efficiency and quality of the follow-up algorithm. Second, an effective heuristic genetic algorithm for discretization of continuous attributes of the decision table is proposed, which takes the significance of cut dots as heuristic information and introduces a novel operator to maintain the indiscernibility of the original decision system and enhance the local research ability of the algorithm. So the algorithm converges quickly and has global optimizing ability. Finally, the effectiveness of the algorithm is validated through experiment.

  1. Human-competitive evolution of quantum computing artefacts by Genetic Programming.

    Science.gov (United States)

    Massey, Paul; Clark, John A; Stepney, Susan

    2006-01-01

    We show how Genetic Programming (GP) can be used to evolve useful quantum computing artefacts of increasing sophistication and usefulness: firstly specific quantum circuits, then quantum programs, and finally system-independent quantum algorithms. We conclude the paper by presenting a human-competitive Quantum Fourier Transform (QFT) algorithm evolved by GP.

  2. Research program in elementary particle theory, 1980. Progress report

    Energy Technology Data Exchange (ETDEWEB)

    Sudarshan, E. C.G.; Ne' eman, Y.

    1980-01-01

    Research is reported for these subject areas: particle physics in relativistic astrophysics and cosmology; phenomenology of weak and electromagnetic interactions; strong interaction physics, QCD, and quark-parton physics; quantum field theory, quantum mechanics and fundamental problems; groups, gauges, and grand unified theories; and supergeometry, superalgebra, and unification. (GHT)

  3. Improving the accuracy of density-functional theory calculation: the genetic algorithm and neural network approach.

    Science.gov (United States)

    Li, Hui; Shi, LiLi; Zhang, Min; Su, Zhongmin; Wang, XiuJun; Hu, LiHong; Chen, GuanHua

    2007-04-14

    The combination of genetic algorithm and neural network approach (GANN) has been developed to improve the calculation accuracy of density functional theory. As a demonstration, this combined quantum mechanical calculation and GANN correction approach has been applied to evaluate the optical absorption energies of 150 organic molecules. The neural network approach reduces the root-mean-square (rms) deviation of the calculated absorption energies of 150 organic molecules from 0.47 to 0.22 eV for the TDDFTB3LYP6-31G(d) calculation, and the newly developed GANN correction approach reduces the rms deviation to 0.16 eV.

  4. Bilevel programming problems theory, algorithms and applications to energy networks

    CERN Document Server

    Dempe, Stephan; Pérez-Valdés, Gerardo A; Kalashnykova, Nataliya; Kalashnikova, Nataliya

    2015-01-01

    This book describes recent theoretical findings relevant to bilevel programming in general, and in mixed-integer bilevel programming in particular. It describes recent applications in energy problems, such as the stochastic bilevel optimization approaches used in the natural gas industry. New algorithms for solving linear and mixed-integer bilevel programming problems are presented and explained.

  5. Artificial intelligence programming with LabVIEW: genetic algorithms for instrumentation control and optimization.

    Science.gov (United States)

    Moore, J H

    1995-06-01

    A genetic algorithm for instrumentation control and optimization was developed using the LabVIEW graphical programming environment. The usefulness of this methodology for the optimization of a closed loop control instrument is demonstrated with minimal complexity and the programming is presented in detail to facilitate its adaptation to other LabVIEW applications. Closed loop control instruments have variety of applications in the biomedical sciences including the regulation of physiological processes such as blood pressure. The program presented here should provide a useful starting point for those wishing to incorporate genetic algorithm approaches to LabVIEW mediated optimization of closed loop control instruments.

  6. Towards a Sound Theory of Adaptation for the Simple Genetic Algorithm

    CERN Document Server

    Burjorjee, Keki

    2007-01-01

    The pace of progress in the fields of Evolutionary Computation and Machine Learning is currently limited -- in the former field, by the improbability of making advantageous extensions to evolutionary algorithms when their capacity for adaptation is poorly understood, and in the latter by the difficulty of finding effective semi-principled reductions of hard real-world problems to relatively simple optimization problems. In this paper we explain why a theory which can accurately explain the simple genetic algorithm's remarkable capacity for adaptation has the potential to address both these limitations. We describe what we believe to be the impediments -- historic and analytic -- to the discovery of such a theory and highlight the negative role that the building block hypothesis (BBH) has played. We argue based on experimental results that a fundamental limitation which is widely believed to constrain the SGA's adaptive ability (and is strongly implied by the BBH) is in fact illusionary and does not exist. The...

  7. Learning in Context: Technology Integration in a Teacher Preparation Program Informed by Situated Learning Theory

    Science.gov (United States)

    Bell, Randy L.; Maeng, Jennifer L.; Binns, Ian C.

    2013-01-01

    This investigation explores the effectiveness of a teacher preparation program aligned with situated learning theory on preservice science teachers' use of technology during their student teaching experiences. Participants included 26 preservice science teachers enrolled in a 2-year Master of Teaching program. A specific program goal was to…

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

    Science.gov (United States)

    Catania, Francesco; Schmitz, Jürgen

    2015-01-01

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

  9. Genetic associations with intimate partner violence in a sample of hazardous drinking men in batterer intervention programs.

    Science.gov (United States)

    Stuart, Gregory L; McGeary, John E; Shorey, Ryan C; Knopik, Valerie S; Beaucage, Kayla; Temple, Jeff R

    2014-04-01

    The etiology of intimate partner violence (IPV) is multifactorial. However, etiological theories of IPV have rarely included potential genetic factors. The purpose of the present study was to examine whether a cumulative genetic score (CGS) containing the monoamine oxidase A (MAOA) and the human serotonin transporter gene linked polymorphism (5-HTTLPR) was associated with IPV perpetration after accounting for the effects of alcohol problems, drug problems, age, and length of relationship. We obtained DNA from 97 men in batterer intervention programs in the state of Rhode Island. In the full sample, the CGS was significantly associated with physical and psychological aggression and injuries caused to one's partner, even after controlling for the effects of alcohol problems, drug problems, age, and length of relationship. Two of the men in the sample likely had Klinefelter's syndrome, and analyses were repeated excluding these two individuals, leading to similar results. The implications of the genetic findings for the etiology and treatment of IPV among men in batterer intervention programs are briefly discussed.

  10. Forecasting Shaharchay River Flow in Lake Urmia Basin using Genetic Programming and M5 Model Tree

    Directory of Open Access Journals (Sweden)

    S. Samadianfard

    2017-01-01

    Full Text Available Introduction: Precise prediction of river flows is the key factor for proper planning and management of water resources. Thus, obtaining the reliable methods for predicting river flows has great importance in water resource engineering. In the recent years, applications of intelligent methods such as artificial neural networks, fuzzy systems and genetic programming in water science and engineering have been grown extensively. These mentioned methods are able to model nonlinear process of river flows without any need to geometric properties. A huge number of studies have been reported in the field of using intelligent methods in water resource engineering. For example, Noorani and Salehi (23 presented a model for predicting runoff in Lighvan basin using adaptive neuro-fuzzy network and compared the performance of it with neural network and fuzzy inference methods in east Azerbaijan, Iran. Nabizadeh et al. (21 used fuzzy inference system and adaptive neuro-fuzzy inference system in order to predict river flow in Lighvan river. Khalili et al. (13 proposed a BL-ARCH method for prediction of flows in Shaharchay River in Urmia. Khu et al. (16 used genetic programming for runoff prediction in Orgeval catchment in France. Firat and Gungor (11 evaluated the fuzzy-neural model for predicting Mendes river flow in Turkey. The goal of present study is comparing the performance of genetic programming and M5 model trees for prediction of Shaharchay river flow in the basin of Lake Urmia and obtaining a comprehensive insight of their abilities. Materials and Methods: Shaharchay river as a main source of providing drinking water of Urmia city and agricultural needs of surrounding lands and finally one of the main input sources of Lake Urmia is quite important in the region. For obtaining the predetermined goals of present study, average monthly flows of Shaharchay River in Band hydrometric station has been gathered from 1951 to 2011. Then, two third of mentioned

  11. Review of the Fusion Theory and Computing Program. Fusion Energy Sciences Advisory Committee (FESAC)

    Energy Technology Data Exchange (ETDEWEB)

    Antonsen, Thomas M. [Univ. of Maryland, College Park, MD (United States); Berry, Lee A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Brown, Michael R. [Swarthmore College, PA (United States); Dahlburg, Jill P. [General Atomics, San Diego, CA (United States); Davidson, Ronald C. [Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States); Greenwald, Martin [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Hegna, Chris C. [Univ. of Wisconsin, Madison, WI (United States); McCurdy, William [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Newman, David E. [Univ. of Alaska, Fairbanks, AK (United States); Pellegrini, Claudio [Univ. of California, Los Angeles, CA (United States); Phillips, Cynthia K. [Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States); Post, Douglass E. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Rosenbluth, Marshall N. [Univ. of California, San Diego, CA (United States); Sheffield, John [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Simonen, Thomas C. [Munising, MI (United States); Van Dam, James [Univ. of Texas, Austin, TX (United States)

    2001-08-01

    At the November 14-15, 2000, meeting of the Fusion Energy Sciences Advisory Committee, a Panel was set up to address questions about the Theory and Computing program, posed in a charge from the Office of Fusion Energy Sciences (see Appendix A). This area was of theory and computing/simulations had been considered in the FESAC Knoxville meeting of 1999 and in the deliberations of the Integrated Program Planning Activity (IPPA) in 2000. A National Research Council committee provided a detailed review of the scientific quality of the fusion energy sciences program, including theory and computing, in 2000.

  12. A novel holistic framework for genetic-based captive-breeding and reintroduction programs.

    Science.gov (United States)

    Attard, C R M; Möller, L M; Sasaki, M; Hammer, M P; Bice, C M; Brauer, C J; Carvalho, D C; Harris, J O; Beheregaray, L B

    2016-10-01

    Research in reintroduction biology has provided a greater understanding of the often limited success of species reintroductions and highlighted the need for scientifically rigorous approaches in reintroduction programs. We examined the recent genetic-based captive-breeding and reintroduction literature to showcase the underuse of the genetic data gathered. We devised a framework that takes full advantage of the genetic data through assessment of the genetic makeup of populations before (past component of the framework), during (present component), and after (future component) captive-breeding and reintroduction events to understand their conservation potential and maximize their success. We empirically applied our framework to two small fishes: Yarra pygmy perch (Nannoperca obscura) and southern pygmy perch (Nannoperca australis). Each of these species has a locally adapted and geographically isolated lineage that is endemic to the highly threatened lower Murray-Darling Basin in Australia. These two populations were rescued during Australia's recent decade-long Millennium Drought, when their persistence became entirely dependent on captive-breeding and subsequent reintroduction efforts. Using historical demographic analyses, we found differences and similarities between the species in the genetic impacts of past natural and anthropogenic events that occurred in situ, such as European settlement (past component). Subsequently, successful maintenance of genetic diversity in captivity-despite skewed brooder contribution to offspring-was achieved through carefully managed genetic-based breeding (present component). Finally, genetic monitoring revealed the survival and recruitment of released captive-bred offspring in the wild (future component). Our holistic framework often requires no additional data collection to that typically gathered in genetic-based breeding programs, is applicable to a wide range of species, advances the genetic considerations of reintroduction

  13. Leadership Theory Taught in Air Force Distant Learning Programs

    Science.gov (United States)

    2013-03-01

    the force, fundamental gaps in motivation could be an underlying cause. Sociability/ Charisma Sociability is the characteristic of a leader to be...underpin the development of our officer force. These leadership theories form the base of our leader training and drive future leader behavior. Aspects of...force. These leadership theories form the base of our leader training and drive future leader behavior. Aspects of leadership and management will

  14. A neurofuzzy system based on rough set theory and genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    LUO Jian-xu; SHAO Hui-he

    2005-01-01

    This paper presents a hybrid soft computing modeling approach for a rough set theory and the genetic algorithms (NFRSGA). The fundamental problem of a neurofuzzy system is that when the input dimension increases, the fuzzy rule base increases exponentially. This leads to a huge infra structure network which results in slow convergence. To solve this problem, rough set theory is used to obtain the reductive rules, which are used as fuzzy rules of the fuzzy system. The number of rules decrease, and each rule does not need all the conditional attribute values. This results in a reduced, or not fully connected, neural network. The structure of the neural network is relatively small and thus the weights to be trained decrease. The genetic algorithm is used to search the optimal discretization of the continuous attributes. The NFRSGA approach has been applied in the practical application of building a soft sensor model for estimating the freezing point of the light diesel fuel in a Fluid Catalytic Cracking Unit ( FCCU), and satisfying results are obtained.

  15. An Autotrophic Origin for the Coded Amino Acids is Concordant with the Coevolution Theory of the Genetic Code.

    Science.gov (United States)

    Di Giulio, Massimo

    2016-10-01

    The coevolution theory of the origin of the genetic code maintains that the biosynthetic relationships between amino acids co-evolved with the genetic code organization. In other words, the metabolism of amino acids co-evolved with the organization of the genetic code because the biosynthetic pathways of amino acids occurred on tRNA-like molecules. Thus, a heterotrophic origin of amino acids-also only of those involved in the early phase of the structuring of the genetic code-would seem to contradict the main postulate of the coevolution theory. As a matter of fact, this origin not being linked to the metabolism of amino acids in any way-being taken from a physical setting-would seem to remove the possibility that this metabolism had instead heavily contributed to the structuring of the genetic code. Therefore, I have analyzed the structure of the genetic code and mechanisms that brought to its structuring for understanding if the coevolution theory is compatible with autotrophic or heterotrophic conditions. One of the arguments was that an autotrophic origin of amino acids would have the advantage to be able to directly link their metabolism to the structure of the genetic code if-as hypothesized by the coevolution theory-the biosyntheses of amino acids occurred on tRNA-like molecules. Simultaneously, a heterotrophic origin would not have been able to link the metabolism of amino acids to the structure of the genetic code for the absence of a precise determinism of allocation of amino acids, that is to say of a clear mechanism-linked to tRNA-like molecules, for example-that would have determined the specific pattern observed in the genetic code of the biosynthetic relationships between amino acids. The conclusion is that an autotrophic origin of coded amino acids would seem to be the condition under which the genetic code originated.

  16. Interpretation of findings of founder population genetics studies applying lineage extinction theory

    Science.gov (United States)

    Livni, Haim; Livni, Joseph

    2016-11-01

    Population genetic investigation of founder events produce intriguing results and this work discusses how branching processes help the cross-examination of such results. For example one reads that 40% of the current Ashkenazi population carry the mtDNA of four founding mothers, (Behar et al., 2006) half of the Ashkenazi Levites descend from one founder (Behar et al., 2003), and 22% of the Malagasy population are descendants of a Polynesian ancestor, (Cox et al., 2012). Probability distributions obtained using a Galton-Watson lineage extinction model yield statistical relations between current population and founder population data. These relations lead to most likely estimates and 90% confidence intervals of the founder population size. The investigation compares the Galton-Watson methodology with the Wright-Fisher model adopted by coalescent theory and a back-to-back analysis of the Malagasy founder event produces matching results. The results reconcile the previous knowledge about the roots of Ashkenazi Jewry with published population genetic findings. They also confirm that random drift is sufficient to explain the genetic findings of the examined examples.

  17. Quantitative genetics theory for non-inbred populations in linkage disequilibrium

    Directory of Open Access Journals (Sweden)

    José Marcelo Soriano Viana

    2004-01-01

    Full Text Available Although linkage disequilibrium, epistasis and inbreeding are common phenomena in genetic systems that control quantitative traits, theory development and analysis are very complex, especially when they are considered together. The objective of this study is to offer additional quantitative genetics theory to define and analyze, in relation to non-inbred cross pollinating populations, components of genotypic variance, heritabilities and predicted gains, assuming linkage disequilibrium and absence of epistasis. The genotypic variance and its components, additive and due to dominance genetic variances, are invariant over the generations only in regard to completely linked genes and to those in equilibrium. When the population is structured in half-sib families, the additive variance in the parents' generation and the genotypic variance in the population can be estimated. When the population is structured in full-sib families, none of the components of genotypic variance can be estimated. The narrow sense heritability level at plant level can be estimated from the parent-offspring or mid parent-offspring regression. When there is dominance, the narrow sense heritability estimate in the in F2 is biased due to linkage disequilibrium when estimated by the Warner method, but not when estimated by means of the plant F2-family F3 regression. The bias is proportional to the number of pairs of linked genes, without independent assortment, and to the degree of dominance, and tends to be positive when genes in the coupling phase predominate or negative and of higher value when genes in the repulsion phase predominate. Linkage disequilibrium is also cause of bias in estimates of the narrow sense heritabilities at full-sib family mean and at plant within half-sib and full-sib families levels. Generally, the magnitude of the bias is proportional to the number of pairs of genes in disequilibrium and to the frequency of recombining gametes.

  18. Using Self-Determination Theory in Correctional Education Program Development

    Science.gov (United States)

    McKinney, Dani; Cotronea, Michael A.

    2011-01-01

    As funding has become available through the Second Chance Act of 2007, many correctional facilities have developed new educational programs in an effort to ease the transition from prison to community. Many new programs are developed based on the belief that incarcerated individuals are a special and unique population of student. The present…

  19. Solution for integer linear bilevel programming problems using orthogonal genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    Hong Li; Li Zhang; Yongchang Jiao

    2014-01-01

    An integer linear bilevel programming problem is firstly transformed into a binary linear bilevel programming problem, and then converted into a single-level binary implicit program-ming. An orthogonal genetic algorithm is developed for solving the binary linear implicit programming problem based on the ortho-gonal design. The orthogonal design with the factor analysis, an experimental design method is applied to the genetic algorithm to make the algorithm more robust, statistical y sound and quickly convergent. A crossover operator formed by the orthogonal array and the factor analysis is presented. First, this crossover operator can generate a smal but representative sample of points as off-spring. After al of the better genes of these offspring are selected, a best combination among these offspring is then generated. The simulation results show the effectiveness of the proposed algo-rithm.

  20. Inductive Data Types Based on Fibrations Theory in Programming

    Directory of Open Access Journals (Sweden)

    Decheng Miao

    2016-03-01

    Full Text Available Traditional methods including algebra and category theory have some deficiencies in analyzing semantics properties and describing inductive rules of inductive data types, we present a method based on Fibrations theory aiming at those questions above. We systematically analyze some basic logical structures of inductive data types about a fibration such as re-indexing functor, truth functor and comprehension functor, make semantics models of non-indexed fibration, single-sorted indexed fibration and many-sorted indexed fibration respectively. On this basis, we thoroughly discuss semantics properties of fibred, single-sorted indexed and many-sorted indexed inductive data types, and abstractly describe their inductive rules with universality. Furthermore, we briefly introduce applications of the three inductive dana types for analyzing semantics properties and describing inductive rules based on Fibrations theory via some examples. Compared with traditional methods, our works have the following three advantages. Firstly, brief descriptions and flexible expansibility of Fibrations theory can analyze semantics properties of inductive data types accurately, whose semantics are computed automatically. Secondly, superior abstractness of Fibrations theory does not rely on particular computing environments to depict inductive rules of inductive data types with universality. Thirdly, its rigorousness and consistence provide sound basis for testing and maintenance of software development.

  1. Minimalist program and its fundamental improvements in syntactic theory: evidence from agreement asymmetry in standard Arabic

    OpenAIRE

    Al-Horais, Nasser

    2012-01-01

    The Minimalist Program is a major line of inquiry that has been developing inside Generative Grammar since the early nineties, when it was proposed by Chomsky (1993, 1995). At the outset, Chomsky (1998: 5) presented Minimalist Program as a program, not as a theory, but today, the Minimalist Program lays out a very specific view of the basis of syntactic grammar that, when compared to other formalisms, is often taken to look very much like a theory. The prime concern of this paper, however, is...

  2. Exploring Teaching Programming Online through Web Conferencing System: The Lens of Activity Theory

    National Research Council Canada - National Science Library

    Ünal Çakıroğlu; Mehmet Kokoç; Elvan Kol; Ebru Turan

    2016-01-01

    .... The findings were discussed through Mwanza’s Activity notations based on Activity Theory. The results indicated that, by using web conferencing tools, students could develop programming knowledge through the learning tasks by interacting each other...

  3. Selecting the Best Forecasting-Implied Volatility Model Using Genetic Programming

    Directory of Open Access Journals (Sweden)

    Wafa Abdelmalek

    2009-01-01

    Full Text Available The volatility is a crucial variable in option pricing and hedging strategies. The aim of this paper is to provide some initial evidence of the empirical relevance of genetic programming to volatility's forecasting. By using real data from S&P500 index options, the genetic programming's ability to forecast Black and Scholes-implied volatility is compared between time series samples and moneyness-time to maturity classes. Total and out-of-sample mean squared errors are used as forecasting's performance measures. Comparisons reveal that the time series model seems to be more accurate in forecasting-implied volatility than moneyness time to maturity models. Overall, results are strongly encouraging and suggest that the genetic programming approach works well in solving financial problems.

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

    Science.gov (United States)

    Goldsmith, Theodore C

    2016-12-01

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

  5. The Course Research for the Software Program Based on the Constructivism Teaching Theories

    Science.gov (United States)

    Zhang, Quanyou; Kou, Qiongjie

    The theory of constructivism teaching emphasizes that: firstly, the center of teaching should be students; secondly, teaching should cultivate the student's character of autonomy and cooperation. The constructivism teaching gets rid of some disadvantage in the traditional teaching. Through using constructivism teaching theories to instruct programming course, it can liven up the lesson mood and cultivate the independent study; improve the team spirit and the ability of programming software for students.

  6. A New Hybrid Intelligent Algorithm for Fuzzy Multiobjective Programming Problem Based on Credibility Theory

    OpenAIRE

    Zu-Tong Wang; Jian-Sheng Guo; Ming-Fa Zheng; Ying Wang

    2014-01-01

    Based on the credibility theory, this paper is devoted to the fuzzy multiobjective programming problem. Firstly, the expected-value model of fuzzy multiobjective programming problem is provided based on credibility theory; then two new approaches for obtaining efficient solutions are proposed on the basis of the expected-value model, whose validity has been proven. For solving the fuzzy MOP problem efficiently, Latin hypercube sampling, fuzzy simulation, support vector machine, an...

  7. Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer

    Directory of Open Access Journals (Sweden)

    Mauro Castelli

    2015-01-01

    Full Text Available Energy consumption forecasting (ECF is an important policy issue in today’s economies. An accurate ECF has great benefits for electric utilities and both negative and positive errors lead to increased operating costs. The paper proposes a semantic based genetic programming framework to address the ECF problem. In particular, we propose a system that finds (quasi-perfect solutions with high probability and that generates models able to produce near optimal predictions also on unseen data. The framework blends a recently developed version of genetic programming that integrates semantic genetic operators with a local search method. The main idea in combining semantic genetic programming and a local searcher is to couple the exploration ability of the former with the exploitation ability of the latter. Experimental results confirm the suitability of the proposed method in predicting the energy consumption. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that including a local searcher in the geometric semantic genetic programming system can speed up the search process and can result in fitter models that are able to produce an accurate forecasting also on unseen data.

  8. Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer.

    Science.gov (United States)

    Castelli, Mauro; Trujillo, Leonardo; Vanneschi, Leonardo

    2015-01-01

    Energy consumption forecasting (ECF) is an important policy issue in today's economies. An accurate ECF has great benefits for electric utilities and both negative and positive errors lead to increased operating costs. The paper proposes a semantic based genetic programming framework to address the ECF problem. In particular, we propose a system that finds (quasi-)perfect solutions with high probability and that generates models able to produce near optimal predictions also on unseen data. The framework blends a recently developed version of genetic programming that integrates semantic genetic operators with a local search method. The main idea in combining semantic genetic programming and a local searcher is to couple the exploration ability of the former with the exploitation ability of the latter. Experimental results confirm the suitability of the proposed method in predicting the energy consumption. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that including a local searcher in the geometric semantic genetic programming system can speed up the search process and can result in fitter models that are able to produce an accurate forecasting also on unseen data.

  9. Analysis of genetic structure and relationship among nine indigenous Chinese chicken populations by the Structure program

    Indian Academy of Sciences (India)

    H. F. Li; W. Han; Y. F. Zhu; J. T. Shu; X. Y. Zhang; K. W. Chen

    2009-08-01

    The multi-locus model-based clustering method Structure program was used to infer the genetic structure of nine indigenous Chinese chicken (Gallus gallus) populations based on 16 microsatellite markers. Twenty runs were carried out at each chosen value of predefined cluster numbers $(K)$ under admixture model. The Structure program properly inferred the presence of genetic structure with 0.999 probabilities. The genetic structure not only indicated that the nine kinds of chicken populations were defined actually by their locations, phenotypes or culture, but also reflected the underlying genetic variations. At $K = 2$, nine chicken populations were divided into two main clusters, one light-body type, including Chahua chicken (CHA), Tibet chicken (TIB), Xianju chicken (XIA), Gushi chicken (GUS) and Baier chicken (BAI); and the other heavy-body type, including Beijing You chicken (YOU), Xiaoshan chicken (XIA), Luyuan chicken (LUY) and Dagu chicken (DAG). GUS and DAG were divided into independent clusters respectively when equaled 4, 5, or 6. XIA and BIA chicken, XIA and LUY chicken, TIB and CHA chicken still clustered together when equaled 6, 7, and 8, respectively. These clustering results were consistent with the breeding directions of the nine chicken populations. The Structure program also identified migrants or admixed individuals. The admixed individuals were distributed in all the nine chicken populations, while migrants were only distributed in TIB, XIA and LUY populations. These results indicated that the clustering analysis using the Structure program might provide an accurate representation of the genetic relationship among the breeds.

  10. Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer

    Science.gov (United States)

    Vanneschi, Leonardo

    2015-01-01

    Energy consumption forecasting (ECF) is an important policy issue in today's economies. An accurate ECF has great benefits for electric utilities and both negative and positive errors lead to increased operating costs. The paper proposes a semantic based genetic programming framework to address the ECF problem. In particular, we propose a system that finds (quasi-)perfect solutions with high probability and that generates models able to produce near optimal predictions also on unseen data. The framework blends a recently developed version of genetic programming that integrates semantic genetic operators with a local search method. The main idea in combining semantic genetic programming and a local searcher is to couple the exploration ability of the former with the exploitation ability of the latter. Experimental results confirm the suitability of the proposed method in predicting the energy consumption. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that including a local searcher in the geometric semantic genetic programming system can speed up the search process and can result in fitter models that are able to produce an accurate forecasting also on unseen data. PMID:26106410

  11. The Impact of Duty to Warn (And Other Legal Theories) on Countering Violent Extremism Intervention Programs

    Science.gov (United States)

    2016-12-01

    highlighting the importance of cooperation.183 Mental health and LE will always overlap. The theory of therapeutic justice seeks to educate...OTHER LEGAL THEORIES ) ON COUNTERING VIOLENT EXTREMISM INTERVENTION PROGRAMS by Michael Ward December 2016 Thesis Co-Advisors: Lauren Wollman...DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE THE IMPACT OF “DUTY TO WARN” (AND OTHER LEGAL THEORIES ) ON COUNTERING VIOLENT EXTREMISM

  12. Identifying Barriers in Implementing Outcomes-Based Assessment Program Review: A Grounded Theory Analysis

    Science.gov (United States)

    Bresciani, Marilee J.

    2011-01-01

    The purpose of this grounded theory study was to identify the typical barriers encountered by faculty and administrators when implementing outcomes-based assessment program review. An analysis of interviews with faculty and administrators at nine institutions revealed a theory that faculty and administrators' promotion, tenure (if applicable),…

  13. Research program in elementary-particle theory, 1983. Progress report

    Energy Technology Data Exchange (ETDEWEB)

    Sudarshan, E C.G.; Ne& #x27; eman, Y

    1983-08-01

    Progress is reviewed on the following topics: physics of ultra high energies and cosmology; phenomenology of particle physics; quantum field theory, supersymmetry and models of particles; and geometric formulations and algebraic models. Recent DOE reports resulting from the contract are listed. (WHK)

  14. A survey of application: genomics and genetic programming, a new frontier.

    Science.gov (United States)

    Khan, Mohammad Wahab; Alam, Mansaf

    2012-08-01

    The aim of this paper is to provide an introduction to the rapidly developing field of genetic programming (GP). Particular emphasis is placed on the application of GP to genomics. First, the basic methodology of GP is introduced. This is followed by a review of applications in the areas of gene network inference, gene expression data analysis, SNP analysis, epistasis analysis and gene annotation. Finally this paper concluded by suggesting potential avenues of possible future research on genetic programming, opportunities to extend the technique, and areas for possible practical applications.

  15. Genetic testing and Alzheimer disease: recommendations of the Stanford Program in Genomics, Ethics, and Society.

    Science.gov (United States)

    McConnell, L M; Koenig, B A; Greely, H T; Raffin, T A

    1999-01-01

    Several genes associated with Alzheimer disease (AD) have been localized and cloned; two genetic tests are already commercially available, and new tests are being developed. Genetic testing for AD--either for disease prediction or for diagnosis--raises critical ethical concerns. The multidisciplinary Alzheimer Disease Working Group of the Stanford Program in Genomics, Ethics, and Society (PGES) presents comprehensive recommendations on genetic testing for AD. The Group concludes that under current conditions, genetic testing for AD prediction or diagnosis is only rarely appropriate. Criteria for judging the readiness of a test for introduction into routine clinical practice typically rely heavily on evaluation of technical efficacy. PGES recommends a broader and more comprehensive approach, considering: 1) the unique social and historical meanings of AD; 2) the availability of procedures to promote good surrogate decision making for incompetent patients and to safeguard confidentiality; 3) access to sophisticated genetic counselors able to communicate complex risk information and effectively convey the social costs and psychological burdens of testing, such as unintentional disclosure of predictive genetic information to family members; 4) protection from inappropriate advertising and marketing of genetic tests; and 5) recognition of the need for public education about the meaning and usefulness of predictive and diagnostic tests for AD. In this special issue of Genetic Testing, the PGES recommendations are published along with comprehensive background papers authored by Working Group members.

  16. GESP: A computer program for modeling genetic effective population size, inbreeding, and divergence in substructured populations.

    Science.gov (United States)

    Olsson, Fredrik; Laikre, Linda; Hössjer, Ola; Ryman, Nils

    2017-03-24

    The genetically effective population size (Ne) is of key importance for quantifying rates of inbreeding and genetic drift, and is often used in conservation management to set targets for genetic viability. The concept was developed for single, isolated populations and the mathematical means for analyzing the expected Ne in complex, subdivided populations have previously not been available. We recently developed such analytical theory and central parts of that work have now been incorporated into a freely available software tool presented here. GESP (Genetic Effective population size, inbreeding, and divergence in Substructured Populations) is R-based and designed to model short and long term patterns of genetic differentiation and effective population size of subdivided populations. The algorithms performed by GESP allow exact computation of global and local inbreeding and eigenvalue effective population size, predictions of genetic divergence among populations (GST) as well as departures from random mating (FIS, FIT) while varying i) subpopulation census and effective size, separately or including trend of the global population size, ii) rate and direction of migration between all pairs of subpopulations, iii) degree of relatedness and divergence among subpopulations, iv) ploidy (haploid or diploid), and v) degree of selfing. Here, we describe GESP and exemplify its use in conservation genetics modeling. This article is protected by copyright. All rights reserved.

  17. Genetics

    Science.gov (United States)

    ... Inheritance; Heterozygous; Inheritance patterns; Heredity and disease; Heritable; Genetic markers ... The chromosomes are made up of strands of genetic information called DNA. Each chromosome contains sections of ...

  18. Sir Francis Galton, epigenetic rules, genetic similarity theory, and human life-history analysis.

    Science.gov (United States)

    Rushton, J P

    1990-03-01

    In this article, an evolutionary perspective is applied to individual differences. Among the issues discussed are (a) the seminal contributions of Francis Galton and the subsequent ideological reaction, (b) the distal proximal continuum for understanding levels of explanation in social behavior, (c) consistent patterns of group differences in behavior (age, sex, social class,and race), (d) the heritability of personality and the role epigenetic rules play in guiding development in one direction over alternatives, (e) the genetic similarity theory perspective on friendship and mate choice, and (f) the view that personality is part of an r-K reproductive strategy involving a compensatory exchange between the production of gametes and parental care. It is suggested in conclusion that personality traits be considered aspects of a coordinated life cycle deeply embedded m evolutionary history.

  19. Designing mixed metal halide ammines for ammonia storage using density functional theory and genetic algorithms

    DEFF Research Database (Denmark)

    Jensen, Peter Bjerre; Lysgaard, Steen; Quaade, Ulrich J.

    2014-01-01

    Metal halide ammines have great potential as a future, high-density energy carrier in vehicles. So far known materials, e.g. Mg(NH3)6Cl2 and Sr(NH3)8Cl2, are not suitable for automotive, fuel cell applications, because the release of ammonia is a multi-step reaction, requiring too much heat...... to be supplied, making the total efficiency lower. Here, we apply density functional theory (DFT) calculations to predict new mixed metal halide ammines with improved storage capacities and the ability to release the stored ammonia in one step, at temperatures suitable for system integration with polymer...... electrolyte membrane fuel cells (PEMFC). We use genetic algorithms (GAs) to search for materials containing up to three different metals (alkaline-earth, 3d and 4d) and two different halides (Cl, Br and I) – almost 27000 combinations, and have identified novel mixtures, with significantly improved storage...

  20. GENETIC ALGORITHMS AND GAME THEORY FOR HIGH LIFT DESIGN PROBLEMS IN AERODYNAMICS

    Institute of Scientific and Technical Information of China (English)

    PériauxJacques; WangJiangfeng; WuYizhao

    2002-01-01

    A multi-objective evolutionary optimization method (combining genetic algorithms(GAs)and game theory(GT))is presented for high lift multi-airfoil systems in aerospace engineering.Due to large dimension global op-timization problems and the increasing importance of low cost distributed parallel environments,it is a natural idea to replace a globar optimization by decentralized local sub-optimizations using GT which introduces the notion of games associated to an optimization problem.The GT/GAs combined optimization method is used for recon-struction and optimization problems by high lift multi-air-foil desing.Numerical results are favorably compared with single global GAs.The method shows teh promising robustness and efficient parallel properties of coupled GAs with different game scenarios for future advanced multi-disciplinary aerospace techmologies.

  1. An optimization design for evacuation planning based on fuzzy credibility theory and genetic algorithm

    Science.gov (United States)

    Zhang, D.; Zhang, W. Y.

    2017-08-01

    Evacuation planning is an important activity in disaster management. It has to be planned in advance due to the unpredictable occurrence of disasters. It is necessary that the evacuation plans are as close as possible to the real evacuation work. However, the evacuation plan is extremely challenging because of the inherent uncertainty of the required information. There is a kind of vehicle routing problem based on the public traffic evacuation. In this paper, the demand for each evacuation set point is a fuzzy number, and each routing selection of the point is based on the fuzzy credibility preference index. This paper proposes an approximate optimal solution for this problem by the genetic algorithm based on the fuzzy reliability theory. Finally, the algorithm is applied to an optimization model, and the experiment result shows that the algorithm is effective.

  2. Research in mathematical theory of computation. [computer programming applications

    Science.gov (United States)

    Mccarthy, J.

    1973-01-01

    Research progress in the following areas is reviewed: (1) new version of computer program LCF (logic for computable functions) including a facility to search for proofs automatically; (2) the description of the language PASCAL in terms of both LCF and in first order logic; (3) discussion of LISP semantics in LCF and attempt to prove the correctness of the London compilers in a formal way; (4) design of both special purpose and domain independent proving procedures specifically program correctness in mind; (5) design of languages for describing such proof procedures; and (6) the embedding of ideas in the first order checker.

  3. THE GENERAL ATOMICS FUSION THEORY PROGRAM ANNUAL REPORT FOR GRANT YEAR 2004

    Energy Technology Data Exchange (ETDEWEB)

    PROJECT STAFF

    2004-12-01

    The dual objective of the fusion theory program at General Atomics (GA) is to significantly advance our scientific understanding of the physics of fusion plasmas and to support the DIII-D and other tokamak experiments. The program plan is aimed at contributing significantly to the Fusion Energy Science and the Tokamak Concept Improvement goals of the Office of Fusion Energy Sciences (OFES).

  4. Leveraging Sociocultural Theory to Create a Mentorship Program for Doctoral Students

    Science.gov (United States)

    Crosslin, Matt; Wakefield, Jenny S.; Bennette, Phyllis; Black, James William, III

    2013-01-01

    This paper details a proposed doctoral student connections program that is based on sociocultural theory. It is designed to assist new students with starting their educational journey. This program is designed to leverage social interactions, peer mentorship, personal reflection, purposeful planning, and existing resources to assist students in…

  5. Intervention mapping protocol for developing a theory-based diabetes self-management education program.

    Science.gov (United States)

    Song, Misoon; Choi, Suyoung; Kim, Se-An; Seo, Kyoungsan; Lee, Soo Jin

    2015-01-01

    Development of behavior theory-based health promotion programs is encouraged with the paradigm shift from contents to behavior outcomes. This article describes the development process of the diabetes self-management program for older Koreans (DSME-OK) using intervention mapping (IM) protocol. The IM protocol includes needs assessment, defining goals and objectives, identifying theory and determinants, developing a matrix to form change objectives, selecting strategies and methods, structuring the program, and planning for evaluation and pilot testing. The DSME-OK adopted seven behavior objectives developed by the American Association of Diabetes Educators as behavioral outcomes. The program applied an information-motivation-behavioral skills model, and interventions were targeted to 3 determinants to change health behaviors. Specific methods were selected to achieve each objective guided by IM protocol. As the final step, program evaluation was planned including a pilot test. The DSME-OK was structured as the 3 determinants of the IMB model were intervened to achieve behavior objectives in each session. The program has 12 weekly 90-min sessions tailored for older adults. Using the IM protocol in developing a theory-based self-management program was beneficial in terms of providing a systematic guide to developing theory-based and behavior outcome-focused health education programs.

  6. A Grounded Theory of Connectivity and Persistence in a Limited Residency Doctoral Program

    Science.gov (United States)

    Terrell, Steven R.; Snyder, Martha M.; Dringus, Laurie P.; Maddrey, Elizabeth

    2012-01-01

    Limited-residency and online doctoral programs have an attrition rate significantly higher than traditional programs. This grounded-theory study focused on issues pertaining to communication between students, their peers and faculty and how interpersonal communication may affect persistence. Data were collected from 17 students actively working on…

  7. A CAL Program to Teach the Basic Principles of Genetic Engineering--A Change from the Traditional Approach.

    Science.gov (United States)

    Dewhurst, D. G.; And Others

    1989-01-01

    An interactive computer-assisted learning program written for the BBC microcomputer to teach the basic principles of genetic engineering is described. Discussed are the hardware requirements software, use of the program, and assessment. (Author/CW)

  8. A CAL Program to Teach the Basic Principles of Genetic Engineering--A Change from the Traditional Approach.

    Science.gov (United States)

    Dewhurst, D. G.; And Others

    1989-01-01

    An interactive computer-assisted learning program written for the BBC microcomputer to teach the basic principles of genetic engineering is described. Discussed are the hardware requirements software, use of the program, and assessment. (Author/CW)

  9. Controlling inbreeding and maximizing genetic gain using semi-definite programming with pedigree-based and genomic relationships.

    Science.gov (United States)

    Schierenbeck, S; Pimentel, E C G; Tietze, M; Körte, J; Reents, R; Reinhardt, F; Simianer, H; König, S

    2011-12-01

    Because of the relatively high levels of genetic relationships among potential bull sires and bull dams, innovative selection tools should consider both genetic gain and genetic relationships in a long-term perspective. Optimum genetic contribution theory using official estimated breeding values for a moderately heritable trait (production index, Index-PROD), and a lowly heritable functional trait (index for somatic cell score, Index-SCS) was applied to find optimal allocations of bull dams and bull sires. In contrast to previous practical applications using optimizations based on Lagrange multipliers, we focused on semi-definite programming (SDP). The SDP methodology was combined with either pedigree (a(ij)) or genomic relationships (f(ij)) among selection candidates. Selection candidates were 484 genotyped bulls, and 499 preselected genotyped bull dams completing a central test on station. In different scenarios separately for PROD and SCS, constraints on the average pedigree relationships among future progeny were varied from a(ij)=0.08 to a(ij)=0.20 in increments of 0.01. Corresponding constraints for single nucleotide polymorphism-based kinship coefficients were derived from regression analysis. Applying the coefficient of 0.52 with an intercept of 0.14 estimated for the regression pedigree relationship on genomic relationship, the corresponding range to alter genomic relationships varied from f(ij) = 0.18 to f(ij) = 0.24. Despite differences for some bulls in genomic and pedigree relationships, the same trends were observed for constraints on pedigree and corresponding genomic relationships regarding results in genetic gain and achieved coefficients of relationships. Generally, allowing higher values for relationships resulted in an increase of genetic gain for Index-PROD and Index-SCS and in a reduction in the number of selected sires. Interestingly, more sires were selected for all scenarios when restricting genomic relationships compared with restricting

  10. Some Aspects About Coalgebras In Mathematical Theory Of Programming

    Directory of Open Access Journals (Sweden)

    Valerie Novitzká

    2009-10-01

    Full Text Available Behavior of running program can be described by evaluating a coalgebraic structure over a collection of algebraic terms on state space. Coalgebras are defined by polynomial endofunctors. We formulate substantiation of coalgebras in categories. We use approach via Kleisli categories together with monads beside the approach via topoi and comonads as dual structures to monads.

  11. Employee wellness program marketing: an organizational theory perspective.

    Science.gov (United States)

    Campbell, D P

    1992-01-01

    An employee wellness program (EWP) marketing system can be analyzed as an adhocracy, an organizational form proposed by Mintzberg and is characterized by sharing of power, mutual adjustment among its members, and ability to innovate. The design parameters of informal behavior, planning and control, liaison, and decentralization appear to be particularly important to the success of EWPs.

  12. A Tension between Theory and Practice: Shared Reading Program

    Science.gov (United States)

    Ong, Justina

    2014-01-01

    This study had two main aims: first, to offer a descriptive account of shared reading program using an evaluative lens and second, to examine whether teachers' perceptions of the importance of phonological awareness, word decoding, and text comprehension in helping young learners develop their reading abilities were indeed emphasized during…

  13. A Tension between Theory and Practice: Shared Reading Program

    Science.gov (United States)

    Ong, Justina

    2014-01-01

    This study had two main aims: first, to offer a descriptive account of shared reading program using an evaluative lens and second, to examine whether teachers' perceptions of the importance of phonological awareness, word decoding, and text comprehension in helping young learners develop their reading abilities were indeed emphasized during…

  14. Genetic algorithms and genetic programming for multiscale modeling: Applications in materials science and chemistry and advances in scalability

    Science.gov (United States)

    Sastry, Kumara Narasimha

    2007-03-01

    Effective and efficient rnultiscale modeling is essential to advance both the science and synthesis in a, wide array of fields such as physics, chemistry, materials science; biology, biotechnology and pharmacology. This study investigates the efficacy and potential of rising genetic algorithms for rnultiscale materials modeling and addresses some of the challenges involved in designing competent algorithms that solve hard problems quickly, reliably and accurately. In particular, this thesis demonstrates the use of genetic algorithms (GAs) and genetic programming (GP) in multiscale modeling with the help of two non-trivial case studies in materials science and chemistry. The first case study explores the utility of genetic programming (GP) in multi-timescaling alloy kinetics simulations. In essence, GP is used to bridge molecular dynamics and kinetic Monte Carlo methods to span orders-of-magnitude in simulation time. Specifically, GP is used to regress symbolically an inline barrier function from a limited set of molecular dynamics simulations to enable kinetic Monte Carlo that simulate seconds of real time. Results on a non-trivial example of vacancy-assisted migration on a surface of a face-centered cubic (fcc) Copper-Cobalt (CuxCo 1-x) alloy show that GP predicts all barriers with 0.1% error from calculations for less than 3% of active configurations, independent of type of potentials used to obtain the learning set of barriers via molecular dynamics. The resulting method enables 2--9 orders-of-magnitude increase in real-time dynamics simulations taking 4--7 orders-of-magnitude less CPU time. The second case study presents the application of multiobjective genetic algorithms (MOGAs) in multiscaling quantum chemistry simulations. Specifically, MOGAs are used to bridge high-level quantum chemistry and semiempirical methods to provide accurate representation of complex molecular excited-state and ground-state behavior. Results on ethylene and benzene---two common

  15. Genetic Algorithm Based on Duality Principle for Bilevel Programming Problem in Steel-making Production

    Institute of Scientific and Technical Information of China (English)

    Shuo Lin; Fangjun Luan; Zhonghua Han; Xisheng Lü; Xiaofeng Zhou; Wei Liu

    2014-01-01

    Steel-making and continuous/ingot casting are the key processes of modern iron and steel enterprises. Bilevel programming problems (BLPPs) are the optimization problems with hierarchical structure. In steel-making pro-duction, the plan is not only decided by the steel-making scheduling, but also by the transportation equipment. This paper proposes a genetic algorithm to solve continuous and ingot casting scheduling problems. Based on the characteristics of the problems involved, a genetic algorithm is proposed for solving the bilevel programming problem in steel-making production. Furthermore, based on the simplex method, a new crossover operator is designed to improve the efficiency of the genetic algorithm. Finally, the convergence is analyzed. Using actual data the validity of the proposed algorithm is proved and the application results in the steel plant are analyzed.

  16. Innate and adaptive immunity in bacteria: mechanisms of programmed genetic variation to fight bacteriophages.

    Science.gov (United States)

    Bikard, David; Marraffini, Luciano A

    2012-02-01

    Bacteria are constantly challenged by bacteriophages (viruses that infect bacteria), the most abundant microorganism on earth. Bacteria have evolved a variety of immunity mechanisms to resist bacteriophage infection. In response, bacteriophages can evolve counter-resistance mechanisms and launch a 'virus versus host' evolutionary arms race. In this context, rapid evolution is fundamental for the survival of the bacterial cell. Programmed genetic variation mechanisms at loci involved in immunity against bacteriophages generate diversity at a much faster rate than random point mutation and enable bacteria to quickly adapt and repel infection. Diversity-generating retroelements (DGRs) and phase variation mechanisms enhance the generic (innate) immune response against bacteriophages. On the other hand, the integration of small bacteriophage sequences in CRISPR loci provide bacteria with a virus-specific and sequence-specific adaptive immune response. Therefore, although using different molecular mechanisms, both prokaryotes and higher organisms rely on programmed genetic variation to increase genetic diversity and fight rapidly evolving infectious agents.

  17. Optimization of Turning Operations by Using a Hybrid Genetic Algorithm with Sequential Quadratic Programming

    Directory of Open Access Journals (Sweden)

    A. Belloufi*

    2013-01-01

    Full Text Available The determination of optimal cutting parameters is one of the most important elements in any process planning ofmetal parts. In this paper, a new hybrid genetic algorithm by using sequential quadratic programming is used for theoptimization of cutting conditions. It is used for the resolution of a multipass turning optimization case by minimizingthe production cost under a set of machining constraints. The genetic algorithm (GA is the main optimizer of thisalgorithm whereas SQP Is used to fine tune the results obtained from the GA. Furthermore, the convergencecharacteristics and robustness of the proposed method have been explored through comparisons with resultsreported in literature. The obtained results indicate that the proposed hybrid genetic algorithm by using a sequentialquadratic programming is effective compared to other techniques carried out by different researchers.

  18. Model-based problem solving through symbolic regression via pareto genetic programming

    NARCIS (Netherlands)

    Vladislavleva, E.

    2008-01-01

    Pareto genetic programming methodology is extended by additional generic model selection and generation strategies that (1) drive the modeling engine to creation of models of reduced non-linearity and increased generalization capabilities, and (2) improve the effectiveness of the search for robust m

  19. Application of Genetic Programming in Predicting Infinite Dilution Activity Coefficients of Organic Compounds in Water

    Institute of Scientific and Technical Information of China (English)

    Yi Lin CAO; Huan Ying LI

    2003-01-01

    In this paper, we calculated 37 structural descriptors of 174 organic compounds. The154 molecules were used to derive quantitative structure-infinite dilution activity coefficientrelationship by genetic programming, the other 20 compounds were used to test the model. Theresult showed that molecular partition property and three-dimensional structural descriptors havesignificant influence on the infinite dilution activity coefficients.

  20. Genetic Diversity of Some Tomato Cultivars and Breeding Lines Commonly Used in Pakistani Breeding Program

    Directory of Open Access Journals (Sweden)

    Muhammad Azhar Shah

    2014-10-01

    Full Text Available Genetic diversity present in gene pool is an important determination for breeding programs, and characterization is useful of building crop plant collections primarily based on the knowledge of the presence of valuable genes and traits. Developing successful varieties for increasing the future yield and quality of tomato depend mainly on the genetic diversity of parents used in the breeding program. Molecular characterization of 21 tomato genotypes used in in Pakistani breeding program was studied using random amplified polymorphic DNA (RAPD markers. Total 102 bands were amplified among 21 genotypes using 20 RAPD primers. Overall 73.5% polymorphism was shown as 75 out of 102 loci were polymorphic. High degree of divergence between varieties was indicated by low level of monomorphic bands. The number of PCR products per primer varied from 2-8 with an average of 5.1 bands per primer. Primer GL J-20 and GL C-09 produced maximum number of bands whereas the primers GL A-09 produced the lowest. The polymorphism per RAPD primer ranged from 50% to 100% with an average of 73.5%. The accumulative analysis of amplified products generated by RAPD’s was enough to assess the genetic diversity among the genotypes. The information would be helpful for formulating future breeding and genome mapping programs. This study will also work as an indicator for tomato breeders to evolve varieties with genetic diverse back ground to achieve sustainability in tomato production in the country.

  1. Behaviour of genetically modified amylose free potato clones as progenitors in a breeding program.

    NARCIS (Netherlands)

    Heeres, P.; Jacobsen, E.; Visser, R.G.F.

    1997-01-01

    Three amylose-free genetically modified potato clones were used both as male and female parents in a breeding program with non-GMO potato clones. Segregation data on the expression of the inserted antisense gene construct in tubers of progeny plants were in agreement with previous molecular analysis

  2. A new measurement for the revised reinforcement sensitivity theory: psychometric criteria and genetic validation

    Directory of Open Access Journals (Sweden)

    Martin eReuter

    2015-03-01

    Full Text Available Jeffrey Gray’s Reinforcement Sensitivity Theory (RST represents one of the most influential biologically-based personality theories describing individual differences in approach and avoidance tendencies. The most prominent self-report inventory to measure individual differences in approach and avoidance behavior to date is the BIS/BAS scale by Carver & White (1994. As Gray & McNaughton (2000 revised the RST after its initial formulation in the 1970/80s, and given the Carver & White measure is based on the initial conceptualization of RST, there is a growing need for self-report inventories measuring individual differences in the revised behavioral inhibition system (BIS, behavioral activation system (BAS and the fight, flight, freezing system (FFFS. Therefore, in this paper we present a new questionnaire measuring individual differences in the revised constructs of the BIS, BAS and FFFS in N = 1814 participants (German sample. An English translated version of the new measure is also presented and tested in N = 299 English language participants. A large number of German participants (N = 1090 also filled in the BIS/BAS scales by Carver & White (1994 and the correlations between these measures are presented. Finally, this same subgroup of participants provided buccal swaps for the investigation of the arginine vasopressin receptor 1a (AVPR1a gene. Here, a functional genetic polymorphism (rs11174811 on the AVPR1a gene was shown to be associated with individual differences in both the revised BIS and classic BIS dimensions.

  3. New Approach to Optimize the Apfs Placement Based on Instantaneous Reactive Power Theory by Genetic Algorithm

    Science.gov (United States)

    Hashemi-Dezaki, Hamed; Mohammadalizadeh-Shabestary, Masoud; Askarian-Abyaneh, Hossein; Rezaei-Jegarluei, Mohammad

    2014-01-01

    In electrical distribution systems, a great amount of power are wasting across the lines, also nowadays power factors, voltage profiles and total harmonic distortions (THDs) of most loads are not as would be desired. So these important parameters of a system play highly important role in wasting money and energy, and besides both consumers and sources are suffering from a high rate of distortions and even instabilities. Active power filters (APFs) are innovative ideas for solving of this adversity which have recently used instantaneous reactive power theory. In this paper, a novel method is proposed to optimize the allocation of APFs. The introduced method is based on the instantaneous reactive power theory in vectorial representation. By use of this representation, it is possible to asses different compensation strategies. Also, APFs proper placement in the system plays a crucial role in either reducing the losses costs and power quality improvement. To optimize the APFs placement, a new objective function has been defined on the basis of five terms: total losses, power factor, voltage profile, THD and cost. Genetic algorithm has been used to solve the optimization problem. The results of applying this method to a distribution network illustrate the method advantages.

  4. A new measure for the revised reinforcement sensitivity theory: psychometric criteria and genetic validation.

    Science.gov (United States)

    Reuter, Martin; Cooper, Andrew J; Smillie, Luke D; Markett, Sebastian; Montag, Christian

    2015-01-01

    Jeffrey Gray's Reinforcement Sensitivity Theory (RST) represents one of the most influential biologically-based personality theories describing individual differences in approach and avoidance tendencies. The most prominent self-report inventory to measure individual differences in approach and avoidance behavior to date is the BIS/BAS scale by Carver and White (1994). As Gray and McNaughton (2000) revised the RST after its initial formulation in the 1970/80s, and given the Carver and White measure is based on the initial conceptualization of RST, there is a growing need for self-report inventories measuring individual differences in the revised behavioral inhibition system (BIS), behavioral activation system (BAS) and the fight, flight, freezing system (FFFS). Therefore, in this paper we present a new questionnaire measuring individual differences in the revised constructs of the BIS, BAS and FFFS in N = 1814 participants (German sample). An English translated version of the new measure is also presented and tested in N = 299 English language participants. A large number of German participants (N = 1090) also filled in the BIS/BAS scales by Carver and White (1994) and the correlations between these measures are presented. Finally, this same subgroup of participants provided buccal swaps for the investigation of the arginine vasopressin receptor 1a (AVPR1a) gene. Here, a functional genetic polymorphism (rs11174811) on the AVPR1a gene was shown to be associated with individual differences in both the revised BIS and classic BIS dimensions.

  5. Dynamic Programming and Genetic Algorithm for Business Processes Optimisation

    Directory of Open Access Journals (Sweden)

    Mateusz Wibig

    2012-12-01

    Full Text Available There are many business process modelling techniques, which allow to capture features of those processes, but graphical, diagrammatic models seems to be used most in companies and organizations. Although the modelling notations are more and more mature and can be used not only to visualise the process idea but also to implement it in the workflow solution and although modern software allows us to gather a lot of data for analysis purposes, there is still not much commercial used business process optimisation methods. In this paper the scheduling / optimisation method for automatic task scheduling in business processes models is described. The Petri Net model is used, but it can be easily applied to any other modelling notation, where the process is presented as a set of tasks, i.e. BPMN (Business Process Modelling Notation. The method uses Petri Nets’, business processes’ scalability and dynamic programming concept to reduce the necessary computations, by revising only those parts of the model, to which the change was applied.

  6. Using organization theory to understand the determinants of effective implementation of worksite health promotion programs.

    Science.gov (United States)

    Weiner, Bryan J; Lewis, Megan A; Linnan, Laura A

    2009-04-01

    The field of worksite health promotion has moved toward the development and testing of comprehensive programs that target health behaviors with interventions operating at multiple levels of influence. Yet, observational and process evaluation studies indicate that such programs are challenging for worksites to implement effectively. Research has identified several organizational factors that promote or inhibit effective implementation of comprehensive worksite health promotion programs. However, no integrated theory of implementation has emerged from this research. This article describes a theory of the organizational determinants of effective implementation of comprehensive worksite health promotion programs. The model is adapted from theory and research on the implementation of complex innovations in manufacturing, education and health care settings. The article uses the Working Well Trial to illustrate the model's theoretical constructs. Although the article focuses on comprehensive worksite health promotion programs, the conceptual model may also apply to other types of complex health promotion programs. An organization-level theory of the determinants of effective implementation of worksite health promotion programs.

  7. Portability of Prolog programs: theory and case-studies

    CERN Document Server

    Wielemaker, Jan

    2010-01-01

    (Non-)portability of Prolog programs is widely considered as an important factor in the lack of acceptance of the language. Since 1995, the core of the language is covered by the ISO standard 13211-1. Since 2007, YAP and SWI-Prolog have established a basic compatibility framework. This article describes and evaluates this framework. The aim of the framework is running the same code on both systems rather than migrating an application. We show that today, the portability within the family of Edinburgh/Quintus derived Prolog implementations is good enough to allow for maintaining portable real-world applications.

  8. Potential function methods for approximately solving linear programming problems theory and practice

    CERN Document Server

    Bienstock, Daniel

    2002-01-01

    Potential Function Methods For Approximately Solving Linear Programming Problems breaks new ground in linear programming theory. The book draws on the research developments in three broad areas: linear and integer programming, numerical analysis, and the computational architectures which enable speedy, high-level algorithm design. During the last ten years, a new body of research within the field of optimization research has emerged, which seeks to develop good approximation algorithms for classes of linear programming problems. This work both has roots in fundamental areas of mathematical programming and is also framed in the context of the modern theory of algorithms. The result of this work, in which Daniel Bienstock has been very much involved, has been a family of algorithms with solid theoretical foundations and with growing experimental success. This book will examine these algorithms, starting with some of the very earliest examples, and through the latest theoretical and computational developments.

  9. Telegenetics: application of a tele-education program in genetic syndromes for Brazilian students.

    Science.gov (United States)

    Maximino, Luciana Paula; Picolini-Pereira, Mirela Machado; Carvalho, José Luiz Brito

    2014-01-01

    With the high occurrence of genetic anomalies in Brazil and the manifestations of communication disorders associated with these conditions, the development of educative actions that comprise these illnesses can bring unique benefits in the identification and appropriate treatment of these clinical pictures. Objective The aim of this study was to develop and analyze an educational program in genetic syndromes for elementary students applied in two Brazilian states, using an Interactive Tele-education model. Material and Methods The study was carried out in 4 schools: two in the state of São Paulo, Southeast Region, Brazil, and two in the state of Amazonas, North Region, Brazil. Forty-five students, both genders, aged between 13 and 14 years, of the 9th grade of the basic education of both public and private system, were divided into two groups: 21 of São Paulo Group (SPG) and 24 of Amazonas Group (AMG). The educational program lasted about 3 months and was divided into two stages including both classroom and distance activities on genetic syndromes. The classroom activity was carried out separately in each school, with expository lessons, graphs and audiovisual contents. In the activity at a distance the educational content was presented to students by means of the Interactive Tele-education model. In this stage, the students had access a Cybertutor, using the Young Doctor Project methodology. In order to measure the effectiveness of the educational program, the Problem Situation Questionnaire (PSQ) and the Web Site Motivational Analysis Checklist adapted (FPM) were used. Results The program developed was effective for knowledge acquisition in 80% of the groups. FPM showed a high satisfaction index from the participants in relation to the Interactive Tele-education, evaluating the program as "awesome course". No statistically significant differences between the groups regarding type of school or state were observed. Conclusion Thus, the Tele-Education Program can

  10. Potential of gene drives with genome editing to increase genetic gain in livestock breeding programs.

    Science.gov (United States)

    Gonen, Serap; Jenko, Janez; Gorjanc, Gregor; Mileham, Alan J; Whitelaw, C Bruce A; Hickey, John M

    2017-01-04

    This paper uses simulation to explore how gene drives can increase genetic gain in livestock breeding programs. Gene drives are naturally occurring phenomena that cause a mutation on one chromosome to copy itself onto its homologous chromosome. We simulated nine different breeding and editing scenarios with a common overall structure. Each scenario began with 21 generations of selection, followed by 20 generations of selection based on true breeding values where the breeder used selection alone, selection in combination with genome editing, or selection with genome editing and gene drives. In the scenarios that used gene drives, we varied the probability of successfully incorporating the gene drive. For each scenario, we evaluated genetic gain, genetic variance [Formula: see text], rate of change in inbreeding ([Formula: see text]), number of distinct quantitative trait nucleotides (QTN) edited, rate of increase in favourable allele frequencies of edited QTN and the time to fix favourable alleles. Gene drives enhanced the benefits of genome editing in seven ways: (1) they amplified the increase in genetic gain brought about by genome editing; (2) they amplified the rate of increase in the frequency of favourable alleles and reduced the time it took to fix them; (3) they enabled more rapid targeting of QTN with lesser effect for genome editing; (4) they distributed fixed editing resources across a larger number of distinct QTN across generations; (5) they focussed editing on a smaller number of QTN within a given generation; (6) they reduced the level of inbreeding when editing a subset of the sires; and (7) they increased the efficiency of converting genetic variation into genetic gain. Genome editing in livestock breeding results in short-, medium- and long-term increases in genetic gain. The increase in genetic gain occurs because editing increases the frequency of favourable alleles in the population. Gene drives accelerate the increase in allele frequency

  11. Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier.

    Science.gov (United States)

    Pandey, Daya Shankar; Pan, Indranil; Das, Saptarshi; Leahy, James J; Kwapinski, Witold

    2015-03-01

    A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well.

  12. Indicators of theory of mind in narrative production : a comparison between individuals with genetic syndromes and typically developing children

    NARCIS (Netherlands)

    Lorusso, M. L.; Galli, R.; Libera, L.; Gagliardi, C.; Borgatti, R.; Hollebrandse, B.

    2007-01-01

    It is a matter of debate whether the development of theory of mind (ToM) depends on linguistic development or is, rather, an expression of cognitive development. The study of genetic syndromes, which are characterized by intellectual impairment as well as by different linguistic profiles, may provid

  13. Indicators of theory of mind in narrative production : a comparison between individuals with genetic syndromes and typically developing children

    NARCIS (Netherlands)

    Lorusso, M. L.; Galli, R.; Libera, L.; Gagliardi, C.; Borgatti, R.; Hollebrandse, B.

    2007-01-01

    It is a matter of debate whether the development of theory of mind (ToM) depends on linguistic development or is, rather, an expression of cognitive development. The study of genetic syndromes, which are characterized by intellectual impairment as well as by different linguistic profiles, may provid

  14. Potential benefits of genomic selection on genetic gain of small ruminant breeding programs.

    Science.gov (United States)

    Shumbusho, F; Raoul, J; Astruc, J M; Palhiere, I; Elsen, J M

    2013-08-01

    In conventional small ruminant breeding programs, only pedigree and phenotype records are used to make selection decisions but prospects of including genomic information are now under consideration. The objective of this study was to assess the potential benefits of genomic selection on the genetic gain in French sheep and goat breeding designs of today. Traditional and genomic scenarios were modeled with deterministic methods for 3 breeding programs. The models included decisional variables related to male selection candidates, progeny testing capacity, and economic weights that were optimized to maximize annual genetic gain (AGG) of i) a meat sheep breeding program that improved a meat trait of heritability (h(2)) = 0.30 and a maternal trait of h(2) = 0.09 and ii) dairy sheep and goat breeding programs that improved a milk trait of h(2) = 0.30. Values of ±0.20 of genetic correlation between meat and maternal traits were considered to study their effects on AGG. The Bulmer effect was accounted for and the results presented here are the averages of AGG after 10 generations of selection. Results showed that current traditional breeding programs provide an AGG of 0.095 genetic standard deviation (σa) for meat and 0.061 σa for maternal trait in meat breed and 0.147 σa and 0.120 σa in sheep and goat dairy breeds, respectively. By optimizing decisional variables, the AGG with traditional selection methods increased to 0.139 σa for meat and 0.096 σa for maternal traits in meat breeding programs and to 0.174 σa and 0.183 σa in dairy sheep and goat breeding programs, respectively. With a medium-sized reference population (nref) of 2,000 individuals, the best genomic scenarios gave an AGG that was 17.9% greater than with traditional selection methods with optimized values of decisional variables for combined meat and maternal traits in meat sheep, 51.7% in dairy sheep, and 26.2% in dairy goats. The superiority of genomic schemes increased with the size of the

  15. Multi-Objective Genetic Programming with Redundancy-Regulations for Automatic Construction of Image Feature Extractors

    Science.gov (United States)

    Watchareeruetai, Ukrit; Matsumoto, Tetsuya; Takeuchi, Yoshinori; Kudo, Hiroaki; Ohnishi, Noboru

    We propose a new multi-objective genetic programming (MOGP) for automatic construction of image feature extraction programs (FEPs). The proposed method was originated from a well known multi-objective evolutionary algorithm (MOEA), i.e., NSGA-II. The key differences are that redundancy-regulation mechanisms are applied in three main processes of the MOGP, i.e., population truncation, sampling, and offspring generation, to improve population diversity as well as convergence rate. Experimental results indicate that the proposed MOGP-based FEP construction system outperforms the two conventional MOEAs (i.e., NSGA-II and SPEA2) for a test problem. Moreover, we compared the programs constructed by the proposed MOGP with four human-designed object recognition programs. The results show that the constructed programs are better than two human-designed methods and are comparable with the other two human-designed methods for the test problem.

  16. THEORY OF CREATION AND THE GENETIC INTEGRITY OF THE WORLD – THE FUTURE OF HUMANITY BASIS OF IDEOLOGY

    Directory of Open Access Journals (Sweden)

    B. A. Astafyev

    2013-01-01

    Full Text Available Article describes one of the most difficult problems – the Theory of genetic energy-information unity of the World, according to which the World is the single entity hierarchically organized and directed by the World Creator, appearance of the Creator and creation by Him the Basic Genome of the World (BGW. The integral-dynamic formula of the BGW is described. The World Genome manifests the basic idea of the evolution: it is the code for structural and functional organization and evolution of all entities. The World Genome forms the General Laws of the World. The Theory of genetic energy-information unity of the World is proved the general idea – modern crisis can be transformed by realization of genetic energyinformation unity of the World-Natura-Man.

  17. National Swine Genetic Improvement: An overview of essential program components and organizational structure needed for success

    Institute of Scientific and Technical Information of China (English)

    John; MABRY

    2005-01-01

    The swine industry in China is a thrivingand evolving industry that has shown phenome-nal growth over the past10years.Newand mod-ern swine farms have been started in locationsacross the country.Genetics has been importedfrom many different countries in an effort to up-grade the quality and efficiency of the traditionalbreeds of swine.But to insure long term successand viability in a worldwide competitive industrysuch as pork,there is need for a National SwineGenetic Improvement Program.This programneeds to ...

  18. Dynamic Simulations of Nonlinear Multi-Domain Systems Based on Genetic Programming and Bond Graphs

    Institute of Scientific and Technical Information of China (English)

    DI Wenhui; SUN Bo; XU Lixin

    2009-01-01

    A dynamic simulation method for non-linear systems based on genetic programming (GP) and bond graphs (BG) was developed to improve the design of nonlinear multi-domain energy conversion sys-tems. The genetic operators enable the embryo bond graph to evolve towards the target graph according to the fitness function. Better simulation requires analysis of the optimization of the eigenvalue and the filter circuit evolution. The open topological design and space search ability of this method not only gives a more optimized convergence for the operation, but also reduces the generation time for the new circuit graph for the design of nonlinear multi-domain systems.

  19. Hospice programs and the hospice movement: an investigation based on general systems theory.

    Science.gov (United States)

    Russell, G

    1989-01-01

    This study used General Systems Theory as the framework for examining hospice programs and the hospice movement. Data drawn from program administrators and archival sources were used to test the thesis that two broad types of hospice programs exist in the United States. Results indicate that independent programs tend to be characterized by processes that amplify change in the extant medical delivery system--that is, deviation amplification. Hospices associated with preexisting institutions tend to be characterized by processes that counteract change, thus maintaining the status quo--that is, deviation counteracting processes.

  20. wisepair: a computer program for individual matching in genetic tracking studies.

    Science.gov (United States)

    Rothstein, Andrew P; McLaughlin, Ryan; Acevedo-Gutiérrez, Alejandro; Schwarz, Dietmar

    2017-03-01

    Individual-based data sets tracking organisms over space and time are fundamental to answering broad questions in ecology and evolution. A 'permanent' genetic tag circumvents a need to invasively mark or tag animals, especially if there are little phenotypic differences among individuals. However, genetic tracking of individuals does not come without its limits; correctly matching genotypes and error rates associated with laboratory work can make it difficult to parse out matched individuals. In addition, defining a sampling design that effectively matches individuals in the wild can be a challenge for researchers. Here, we combine the two objectives of defining sampling design and reducing genotyping error through an efficient Python-based computer-modelling program, wisepair. We describe the methods used to develop the computer program and assess its effectiveness through three empirical data sets, with and without reference genotypes. Our results show that wisepair outperformed similar genotype matching programs using previously published from reference genotype data of diurnal poison frogs (Allobates femoralis) and without-reference (faecal) genotype sample data sets of harbour seals (Phoca vitulina) and Eurasian otters (Lutra lutra). In addition, due to limited sampling effort in the harbour seal data, we present optimal sampling designs for future projects. wisepair allows for minimal sacrifice in the available methods as it incorporates sample rerun error data, allelic pairwise comparisons and probabilistic simulations to determine matching thresholds. Our program is the lone tool available to researchers to define parameters a priori for genetic tracking studies.

  1. Integrating design science theory and methods to improve the development and evaluation of health communication programs.

    Science.gov (United States)

    Neuhauser, Linda; Kreps, Gary L

    2014-12-01

    Traditional communication theory and research methods provide valuable guidance about designing and evaluating health communication programs. However, efforts to use health communication programs to educate, motivate, and support people to adopt healthy behaviors often fail to meet the desired goals. One reason for this failure is that health promotion issues are complex, changeable, and highly related to the specific needs and contexts of the intended audiences. It is a daunting challenge to effectively influence health behaviors, particularly culturally learned and reinforced behaviors concerning lifestyle factors related to diet, exercise, and substance (such as alcohol and tobacco) use. Too often, program development and evaluation are not adequately linked to provide rapid feedback to health communication program developers so that important revisions can be made to design the most relevant and personally motivating health communication programs for specific audiences. Design science theory and methods commonly used in engineering, computer science, and other fields can address such program and evaluation weaknesses. Design science researchers study human-created programs using tightly connected build-and-evaluate loops in which they use intensive participatory methods to understand problems and develop solutions concurrently and throughout the duration of the program. Such thinking and strategies are especially relevant to address complex health communication issues. In this article, the authors explore the history, scientific foundation, methods, and applications of design science and its potential to enhance health communication programs and their evaluation.

  2. Educational Program Evaluation Model, From the Perspective of the New Theories

    Directory of Open Access Journals (Sweden)

    Soleiman Ahmady

    2014-05-01

    Full Text Available Introduction: This study is focused on common theories that influenced the history of program evaluation and introduce the educational program evaluation proposal format based on the updated theory. Methods: Literature searches were carried out in March-December 2010 with a combination of key words, MeSH terms and other free text terms as suitable for the purpose. A comprehensive search strategy was developed to search Medline by the PubMed interface, ERIC (Education Resources Information Center and the main journal of medical education regarding current evaluation models and theories. We included all study designs in our study. We found 810 articles related to our topic, and finally 63 with the full text article included. We compared documents and used expert consensus for selection the best model. Results: We found that the complexity theory using logic model suggests compatible evaluation proposal formats, especially with new medical education programs. Common components of a logic model are: situation, inputs, outputs, and outcomes that our proposal format is based on. Its contents are: title page, cover letter, situation and background, introduction and rationale, project description, evaluation design, evaluation methodology, reporting, program evaluation management, timeline, evaluation budget based on the best evidences, and supporting documents. Conclusion: We found that the logic model is used for evaluation program planning in many places, but more research is needed to see if it is suitable for our context.

  3. The genetic diversity of triticale genotypes involved in Polish breeding programs.

    Science.gov (United States)

    Niedziela, Agnieszka; Orłowska, Renata; Machczyńska, Joanna; Bednarek, Piotr T

    2016-01-01

    Genetic diversity analysis of triticale populations is useful for breeding programs, as it helps to select appropriate genetic material for classifying the parental lines, heterotic groups and predicting hybrid performance. In our study 232 breeding forms were analyzed using diversity arrays technology markers. Principal coordinate analysis followed by model-based Bayesian analysis of population structure revealed the presence of weak data structuring with three groups of data. In the first group, 17 spring and 17 winter forms were clustered. The second and the third groups were represented by 101 and 26 winter forms, respectively. Polymorphic information content values, as well as Shannon's Information Index, were higher for the first (0.319) and second (0.309) than for third (0.234) group. AMOVA analysis demonstrated a higher level of within variation (86 %) than among populations (14 %). This study provides the basic information on the presence of structure within a genetic pool of triticale breeding forms.

  4. Interactive computer program for learning genetic principles of segregation and independent assortment through meiosis.

    Science.gov (United States)

    Yang, Xiaoli; Ge, Rong; Yang, Yufei; Shen, Hao; Li, Yingjie; Tseng, Charles C

    2009-01-01

    Teaching fundamental principles of genetics such as segregation and independent assortment of genes could be challenging for high school and college biology instructors. Students without thorough knowledge in meiosis often end up of frustration and failure in genetics courses. Although all textbooks and laboratory manuals have excellent graphic demonstrations and photographs of meiotic process, students may not always master the concept due to the lack of hands-on exercise. In response to the need for an effective lab exercise to understand the segregation of allelic genes and the independent assortment of the unlinked genes, we developed an interactive program for students to manually manipulate chromosome models and visualize each major step of meiosis so that these two genetic principles can be thoroughly understood.

  5. Designing mixed metal halide ammines for ammonia storage using density functional theory and genetic algorithms.

    Science.gov (United States)

    Jensen, Peter Bjerre; Lysgaard, Steen; Quaade, Ulrich J; Vegge, Tejs

    2014-09-28

    Metal halide ammines have great potential as a future, high-density energy carrier in vehicles. So far known materials, e.g. Mg(NH3)6Cl2 and Sr(NH3)8Cl2, are not suitable for automotive, fuel cell applications, because the release of ammonia is a multi-step reaction, requiring too much heat to be supplied, making the total efficiency lower. Here, we apply density functional theory (DFT) calculations to predict new mixed metal halide ammines with improved storage capacities and the ability to release the stored ammonia in one step, at temperatures suitable for system integration with polymer electrolyte membrane fuel cells (PEMFC). We use genetic algorithms (GAs) to search for materials containing up to three different metals (alkaline-earth, 3d and 4d) and two different halides (Cl, Br and I) - almost 27,000 combinations, and have identified novel mixtures, with significantly improved storage capacities. The size of the search space and the chosen fitness function make it possible to verify that the found candidates are the best possible candidates in the search space, proving that the GA implementation is ideal for this kind of computational materials design, requiring calculations on less than two percent of the candidates to identify the global optimum.

  6. Normal loads program for aerodynamic lifting surface theory. [evaluation of spanwise and chordwise loading distributions

    Science.gov (United States)

    Medan, R. T.; Ray, K. S.

    1974-01-01

    A description of and users manual are presented for a U.S.A. FORTRAN 4 computer program which evaluates spanwise and chordwise loading distributions, lift coefficient, pitching moment coefficient, and other stability derivatives for thin wings in linearized, steady, subsonic flow. The program is based on a kernel function method lifting surface theory and is applicable to a large class of planforms including asymmetrical ones and ones with mixed straight and curved edges.

  7. Using AFLP markers and the Geneland program for the inference of population genetic structure

    DEFF Research Database (Denmark)

    Guillot, Gilles; Santos, Filipe

    2010-01-01

    The use of dominant markers such as amplified fragment length polymorphism (AFLP) for population genetics analyses is often impeded by the lack of appropriate computer programs and rarely motivated by objective considerations. The point of the present note is twofold: (i) we describe how the comp......The use of dominant markers such as amplified fragment length polymorphism (AFLP) for population genetics analyses is often impeded by the lack of appropriate computer programs and rarely motivated by objective considerations. The point of the present note is twofold: (i) we describe how...... such as single nucleotide polymorphisms (SNP) markers but this difference becomes negligible for data sets of common size (number of individuals n≥100, number of markers L≥200). The latest Geneland version (3.2.1) handling dominant markers is freely available as an R package with a fully clickable graphical...

  8. Extracting classification rules from an informatic security incidents repository by genetic programming

    Directory of Open Access Journals (Sweden)

    Carlos Javier Carvajal Montealegre

    2015-04-01

    Full Text Available This paper describes the data mining process to obtain classification rules over an information security incident data collection, explaining in detail the use of genetic programming as a mean to model the incidents behavior and representing such rules as decision trees. The described mining process includes several tasks, such as the GP (Genetic Programming approach evaluation, the individual's representation and the algorithm parameters tuning to upgrade the performance. The paper concludes with the result analysis and the description of the rules obtained, suggesting measures to avoid the occurrence of new informatics attacks. This paper is a part of the thesis work degree: Information Security Incident Analytics by Data Mining for Behavioral Modeling and Pattern Recognition (Carvajal, 2012.

  9. The genetic equidistance result: misreading by the molecular clock and neutral theory and reinterpretation nearly half of a century later.

    Science.gov (United States)

    Hu, Taobo; Long, Mengping; Yuan, Dejian; Zhu, Zhubing; Huang, Yimin; Huang, Shi

    2013-03-01

    In 1963, Margoliash discovered the unexpected genetic equidistance result after comparing cytochrome c sequences from different species. This finding, together with the hemoglobin analyses of Zuckerkandl and Pauling in 1962, directly inspired the ad hoc molecular clock hypothesis. Unfortunately, however, many biologists have since mistakenly viewed the molecular clock as a genuine reality, which in turn inspired Kimura, King, and Jukes to propose the neutral theory of molecular evolution. Many years of studies have found numerous contradictions to the theory, and few today believe in a universal constant clock. What is being neglected, however, is that the failure of the molecular clock hypothesis has left the original equidistance result an unsolved mystery. In recent years, we fortuitously rediscovered the equidistance result, which remains unknown to nearly all researchers. Incorporating the proven virtues of existing evolutionary theories and introducing the novel concept of maximum genetic diversity, we proposed a more complete hypothesis of evolutionary genetics and reinterpreted the equidistance result and other major evolutionary phenomena. The hypothesis may rewrite molecular phylogeny and population genetics and solve major biomedical problems that challenge the existing framework of evolutionary biology.

  10. The influence of genetic background versus commercial breeding programs on chicken immunocompetence.

    Science.gov (United States)

    Emam, Mehdi; Mehrabani-Yeganeh, Hassan; Barjesteh, Neda; Nikbakht, Gholamreza; Thompson-Crispi, Kathleen; Charkhkar, Saeid; Mallard, Bonnie

    2014-01-01

    Immunocompetence of livestock plays an important role in farm profitability because it directly affects health maintenance. Genetics significantly influences the immune system, and the genotypic structure of modern fast-growing chickens has been changed, particularly after decades of breeding for higher production. Therefore, this study was designed to help determine if intensive breeding programs have adversely affected immunocompetence or whether the immune response profiles are controlled to greater extent by genetic background. Thus, 3 indigenous chicken populations from different genetic backgrounds and 2 globally available modern broiler strains, Ross 308 and Cobb 500, were evaluated for various aspects of immune response. These included antibody responses against sheep red blood cells and Brucella abortus antigen, as well as some aspects of cell-mediated immunocompetence by toe web swelling test and in vitro blood mononuclear cell proliferation. Significant differences (P chickens is most likely due to differences in the genetic background between each strain of chicken rather than by commercial selection programs for high production.

  11. An integrated biochemistry and genetics outreach program designed for elementary school students.

    Science.gov (United States)

    Ross, Eric D; Lee, Sarah K; Radebaugh, Catherine A; Stargell, Laurie A

    2012-02-01

    Exposure to genetic and biochemical experiments typically occurs late in one's academic career. By the time students have the opportunity to select specialized courses in these areas, many have already developed negative attitudes toward the sciences. Given little or no direct experience with the fields of genetics and biochemistry, it is likely that many young people rule these out as potential areas of study or career path. To address this problem, we developed a 7-week (~1 hr/week) hands-on course to introduce fifth grade students to basic concepts in genetics and biochemistry. These young students performed a series of investigations (ranging from examining phenotypic variation, in vitro enzymatic assays, and yeast genetic experiments) to explore scientific reasoning through direct experimentation. Despite the challenging material, the vast majority of students successfully completed each experiment, and most students reported that the experience increased their interest in science. Additionally, the experiments within the 7-week program are easily performed by instructors with basic skills in biological sciences. As such, this program can be implemented by others motivated to achieve a broader impact by increasing the accessibility of their university and communicating to a young audience a positive impression of the sciences and the potential for science as a career.

  12. STICAP: A linear circuit analysis program with stiff systems capability. Volume 1: Theory manual. [network analysis

    Science.gov (United States)

    Cooke, C. H.

    1975-01-01

    STICAP (Stiff Circuit Analysis Program) is a FORTRAN 4 computer program written for the CDC-6400-6600 computer series and SCOPE 3.0 operating system. It provides the circuit analyst a tool for automatically computing the transient responses and frequency responses of large linear time invariant networks, both stiff and nonstiff (algorithms and numerical integration techniques are described). The circuit description and user's program input language is engineer-oriented, making simple the task of using the program. Engineering theories underlying STICAP are examined. A user's manual is included which explains user interaction with the program and gives results of typical circuit design applications. Also, the program structure from a systems programmer's viewpoint is depicted and flow charts and other software documentation are given.

  13. A three year outcome evaluation of a theory based drink driving education program.

    Science.gov (United States)

    Sheehan, M; Schonfeld, C; Ballard, R; Schofield, F; Najman, J; Siskind, V

    1996-01-01

    This study reports on the impact of a "drink driving education program" taught to grade ten high school students. The program which involves twelve lessons uses strategies based on the Ajzen and Madden theory of planned behavior. Students were trained to use alternatives to drink driving and passenger behaviors. One thousand seven hundred and seventy-four students who had been taught the program in randomly assigned control and intervention schools were followed up three years later. There had been a major reduction in drink driving behaviors in both intervention and control students. In addition to this cohort change there was a trend toward reduced drink driving in the intervention group and a significant reduction in passenger behavior in this group. Readiness to use alternatives suggested that the major impact of the program was on students who were experimenting with the behavior at the time the program was taught. The program seems to have optimized concurrent social attitude and behavior change.

  14. Program Theory and Quality Matter: Changing the Course of Extension Program Evaluation

    Science.gov (United States)

    Arnold, Mary E.; Cater, Melissa

    2016-01-01

    As internal evaluators for the 4-H program in two states, we simultaneously yet independently began to change the way we approached our evaluation practices, turning from evaluation capacity building (ECB) efforts that prepared educators to define and measure program outcomes to strategies that engage educators in defining and measuring program…

  15. Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming

    OpenAIRE

    Palika Chopra; Rajendra Kumar Sharma; Maneek Kumar

    2016-01-01

    An effort has been made to develop concrete compressive strength prediction models with the help of two emerging data mining techniques, namely, Artificial Neural Networks (ANNs) and Genetic Programming (GP). The data for analysis and model development was collected at 28-, 56-, and 91-day curing periods through experiments conducted in the laboratory under standard controlled conditions. The developed models have also been tested on in situ concrete data taken from literature. A comparison o...

  16. Prediction of jet engine parameters for control design using genetic programming

    OpenAIRE

    Martínez-Arellano, G; Cant, R; Nolle, L

    2014-01-01

    The simulation of a jet engine behavior is widely used in many different aspects of the engine development and maintenance. Achieving high quality jet engine control systems requires the iterative use of these simulations to virtually test the performance of the engine avoiding any possible damage on the real engine. Jet engine simulations involve the use of mathematical models which are complex and may not always be available. This paper introduces an approach based on Genetic Programming (G...

  17. Lasing from Escherichia coli bacteria genetically programmed to express green fluorescent protein

    Science.gov (United States)

    Gather, Malte C.; Yun, Seok Hyun

    2011-08-01

    We report on lasing action from colonies of Escherichia coli bacteria that are genetically programmed to synthesize the green fluorescent protein (GFP). When embedded in a Fabry--Perot type cavity and excited by ns-pulses of blue light (465nm), the bacteria generate green laser emission (˜520nm). Broad illumination of pump light yields simultaneous lasing over a large area in bacterial colonies.

  18. Statistical studies in genetic toxicology: a perspective from the U.S. National Toxicology Program.

    OpenAIRE

    Margolin, B H

    1985-01-01

    This paper surveys recent, as yet unpublished, statistical studies arising from research in genetic toxicology within the U.S. National Toxicology Program (NTP). These studies all involve analyses of data from Ames Salmonella/microsome mutagenicity tests, but the statistical methodologies are broadly applicable. Three issues are addressed: First, what is a tenable sampling model for Ames test data, and how does one best test the adequacy of the Poisson sampling assumption? Second, given that ...

  19. A High Precision Comprehensive Evaluation Method for Flood Disaster Loss Based on Improved Genetic Programming

    Institute of Scientific and Technical Information of China (English)

    ZHOU Yuliang; LU Guihua; JIN Juliang; TONG Fang; ZHOU Ping

    2006-01-01

    Precise comprehensive evaluation of flood disaster loss is significant for the prevention and mitigation of flood disasters. Here, one of the difficulties involved is how to establish a model capable of describing the complex relation between the input and output data of the system of flood disaster loss. Genetic programming (GP) solves problems by using ideas from genetic algorithm and generates computer programs automatically. In this study a new method named the evaluation of the grade of flood disaster loss (EGFD) on the basis of improved genetic programming (IGP) is presented (IGPEGFD). The flood disaster area and the direct economic loss are taken as the evaluation indexes of flood disaster loss. Obviously that the larger the evaluation index value, the larger the corresponding value of the grade of flood disaster loss is. Consequently the IGP code is designed to make the value of the grade of flood disaster be an increasing function of the index value. The result of the application of the IGP-EGFD model to Henan Province shows that a good function expression can be obtained within a bigger searched function space; and the model is of high precision and considerable practical significance.Thus, IGP-EGFD can be widely used in automatic modeling and other evaluation systems.

  20. Modeling the Isentropic Head Value of Centrifugal Gas Compressor using Genetic Programming

    Directory of Open Access Journals (Sweden)

    Safiyullah Ferozkhan

    2016-01-01

    Full Text Available Gas compressor performance is vital in oil and gas industry because of the equipment criticality which requires continuous operations. Plant operators often face difficulties in predicting appropriate time for maintenance and would usually rely on time based predictive maintenance intervals as recommended by original equipment manufacturer (OEM. The objective of this work is to develop the computational model to find the isentropic head value using genetic programming. The isentropic head value is calculated from the OEM performance chart. Inlet mass flow rate and speed of the compressor are taken as the input value. The obtained results from the GP computational models show good agreement with experimental and target data with the average prediction error of 1.318%. The genetic programming computational model will assist machinery engineers to quantify performance deterioration of gas compressor and the results from this study will be then utilized to estimate future maintenance requirements based on the historical data. In general, this genetic programming modelling provides a powerful solution for gas compressor operators to realize predictive maintenance approach in their operations.

  1. Genetic variability and population structure of Salvia lachnostachys: implications for breeding and conservation programs.

    Science.gov (United States)

    Erbano, Marianna; Schühli, Guilherme Schnell E; Santos, Élide Pereira Dos

    2015-04-08

    The genetic diversity and population structure of Salvia lachnostachys Benth were assessed. Inter Simple Sequence Repeat (ISSR) molecular markers were used to investigate the restricted distribution of S. lachnostachys in Parana State, Brazil. Leaves of 73 individuals representing three populations were collected. DNA was extracted and submitted to PCR-ISSR amplification with nine tested primers. Genetic diversity parameters were evaluated. Our analysis indicated 95.6% polymorphic loci (stress value 0.02) with a 0.79 average Simpson's index. The Nei-Li distance dendrogram and principal component analysis largely recovered the geographical origin of each sample. Four major clusters were recognized representing each collected population. Nei's gene diversity and Shannon's information index were 0.25 and 0.40 respectively. As is typical for outcrossing herbs, the majority of genetic variation occurred at the population level (81.76%). A high gene flow (Nm = 2.48) was observed with a correspondingly low fixation index. These values were generally similar to previous studies on congeneric species. The results of principal coordinate analysis (PCA) and of arithmetic average (UPGMA) were consistent and all three populations appear distinct as in STRUCTURE analysis. In addition, this analysis indicated a majority intrapopulation genetic variation. Despite the human pressure on natural populations our study found high levels of genetic diversity for S. lachnostachys. This was the first molecular assessment for this endemic species with medicinal proprieties and the results can guide for subsequent bioprospection, breeding programs or conservation actions.

  2. Towards a Theory-Based Design Framework for an Effective E-Learning Computer Programming Course

    Science.gov (United States)

    McGowan, Ian S.

    2016-01-01

    Built on Dabbagh (2005), this paper presents a four component theory-based design framework for an e-learning session in introductory computer programming. The framework, driven by a body of exemplars component, emphasizes the transformative interaction between the knowledge building community (KBC) pedagogical model, a mixed instructional…

  3. How Robotics Programs Influence Young Women's Career Choices: A Grounded Theory Model

    Science.gov (United States)

    Craig, Cecilia Dosh-Bluhm

    2014-01-01

    The fields of engineering, computer science, and physics have a paucity of women despite decades of intervention by universities and organizations. Women's graduation rates in these fields continue to stagnate, posing a critical problem for society. This qualitative grounded theory (GT) study sought to understand how robotics programs influenced…

  4. How Robotics Programs Influence Young Women's Career Choices: A Grounded Theory Model

    Science.gov (United States)

    Craig, Cecilia Dosh-Bluhm

    2014-01-01

    The fields of engineering, computer science, and physics have a paucity of women despite decades of intervention by universities and organizations. Women's graduation rates in these fields continue to stagnate, posing a critical problem for society. This qualitative grounded theory (GT) study sought to understand how robotics programs influenced…

  5. Connecting Neuroscience, Cognitive, and Educational Theories and Research to Practice: A Review of Mathematics Intervention Programs

    Science.gov (United States)

    Kroeger, Lori A.; Brown, Rhonda Douglas; O'Brien, Beth A.

    2012-01-01

    Research Findings: This article describes major theories and research on math cognition across the fields of neuroscience, cognitive psychology, and education and connects these literatures to intervention practices. Commercially available math intervention programs were identified and evaluated using the following questions: (a) Did neuroscience…

  6. A Structuration Theory Analysis of the Refugee Action Support Program in Greater Western Sydney

    Science.gov (United States)

    Naidoo, Loshini

    2009-01-01

    This article uses Gidden's structuration theory to analyse the Refugee Action Support program in Greater Western Sydney. The study shows that many refugee students in Australian high schools experience difficulty with academic transition in mainstream classrooms due to their previous experiences in war-torn countries. As a result of the trauma…

  7. Students' Understanding of Loops and Nested Loops in Computer Programming: An APOS Theory Perspective

    Science.gov (United States)

    Cetin, Ibrahim

    2015-01-01

    The purpose of this study is to explore students' understanding of loops and nested loops concepts. Sixty-three mechanical engineering students attending an introductory programming course participated in the study. APOS (Action, Process, Object, Schema) is a constructivist theory developed originally for mathematics education. This study is the…

  8. Overloading on Slides: Cognitive Load Theory and Microsoft's Slide Program PowerPoint

    Science.gov (United States)

    Cooper, Elizabeth

    2009-01-01

    The integration of Microsoft's PowerPoint and other slideware programs into the classroom setting may hinder educational progress rather than help it. An examination of the literature focusing on Cognitive Load Theory recognizes that students' have a limited tolerance for the amount of sights and sounds on display at any given time, especially in…

  9. Connecting Neuroscience, Cognitive, and Educational Theories and Research to Practice: A Review of Mathematics Intervention Programs

    Science.gov (United States)

    Kroeger, Lori A.; Brown, Rhonda Douglas; O'Brien, Beth A.

    2012-01-01

    Research Findings: This article describes major theories and research on math cognition across the fields of neuroscience, cognitive psychology, and education and connects these literatures to intervention practices. Commercially available math intervention programs were identified and evaluated using the following questions: (a) Did neuroscience…

  10. Mindstorms Robots and the Application of Cognitive Load Theory in Introductory Programming

    Science.gov (United States)

    Mason, Raina; Cooper, Graham

    2013-01-01

    This paper reports on a series of introductory programming workshops, initially targeting female high school students, which utilised Lego Mindstorms robots. Cognitive load theory (CLT) was applied to the instructional design of the workshops, and a controlled experiment was also conducted investigating aspects of the interface. Results indicated…

  11. A Theory of Information Genetics: How Four Subforces Generate Information and the Implications for Total Quality Knowledge Management.

    Science.gov (United States)

    Tsai, Bor-sheng

    2002-01-01

    Proposes a model called information genetics to elaborate on the origin of information generating. Explains conceptual and data models; and describes a software program that was developed for citation data mining, infomapping, and information repackaging for total quality knowledge management in Web representation. (Contains 112 references.)…

  12. A Theory of Information Genetics: How Four Subforces Generate Information and the Implications for Total Quality Knowledge Management.

    Science.gov (United States)

    Tsai, Bor-sheng

    2002-01-01

    Proposes a model called information genetics to elaborate on the origin of information generating. Explains conceptual and data models; and describes a software program that was developed for citation data mining, infomapping, and information repackaging for total quality knowledge management in Web representation. (Contains 112 references.)…

  13. Evaluation of a preschool nutrition education program based on the theory of multiple intelligences.

    Science.gov (United States)

    Cason, K L

    2001-01-01

    This report describes the evaluation of a preschool nutrition education program based on the theory of multiple intelligences. Forty-six nutrition educators provided a series of 12 lessons to 6102 preschool-age children. The program was evaluated using a pretest/post-test design to assess differences in fruit and vegetable identification, healthy snack choices, willingness to taste foods, and eating behaviors. Subjects showed significant improvement in food identification and recognition, healthy snack identification, willingness to taste foods, and frequency of fruit, vegetable, meat, and dairy consumption. The evaluation indicates that the program was an effective approach for educating preschool children about nutrition.

  14. Community supported agriculture programs: a novel venue for theory-based health behavior change interventions.

    Science.gov (United States)

    Wharton, Christopher M; Hughner, Renee Shaw; MacMillan, Lexi; Dumitrescu, Claudia

    2015-01-01

    Local foods programs such as community supported agriculture programs (CSAs) and farmers' markets have increased greatly in popularity. However, little research has been conducted regarding the effect of involvement in local foods programs on diet-related attitudes and behaviors. A series of focus groups was conducted to identify the motives that propel individuals to join a CSA, the experiences of belonging to a CSA, and the diet-related outcomes of CSA membership. Using the Theory of Planned Behavior (TPB) as a framework to categorize findings, data suggest the potential of CSAs as a viable intervention strategy for promoting healthful diets and behaviors.

  15. Efficacy of a Transition Theory-Based Discharge Planning Program for Childhood Asthma Management.

    Science.gov (United States)

    Ekim, Ayfer; Ocakci, Ayse Ferda

    2016-02-01

    This study tested the efficacy of a nurse-led discharge planning program for childhood asthma management, based on transition theory. A quasi-experimental design was used. The sample comprised 120 children with asthma and their parents (intervention group n = 60, control group n = 60). The asthma management self-efficacy perception level of parents in the intervention group increased significantly and the number of triggers their children were exposed to at home was reduced by 60.8%. The rates of admission to emergency departments and unscheduled outpatient visits were significantly lower in the intervention group compared with the control group. Transition theory-based nursing interventions can provide successful outcomes on childhood asthma management. Transition theory-based discharge planning program can guide nursing interventions to standardize care of the child with asthma. Combining care at home with hospital care strengthens ongoing qualified asthma management. © 2015 NANDA International, Inc.

  16. Concept of automatic programming of NC machine for metal plate cutting by genetic algorithm method

    Directory of Open Access Journals (Sweden)

    B. Vaupotic

    2005-12-01

    Full Text Available Purpose: In this paper the concept of automatic programs of the NC machine for metal plate cutting by genetic algorithm method has been presented.Design/methodology/approach: The paper was limited to automatic creation of NC programs for two-dimensional cutting of material by means of adaptive heuristic search algorithms.Findings: Automatic creation of NC programs in laser cutting of materials combines the CAD concepts, the recognition of features and creation and optimization of NC programs. The proposed intelligent system is capable to recognize automatically the nesting of products in the layout, to determine the incisions and sequences of cuts forming the laid out products. Position of incisions is determined at the relevant places on the cut. The system is capable to find the shortest path between individual cuts and to record the NC program.Research limitations/implications: It would be appropriate to orient future researches towards conceiving an improved system for three-dimensional cutting with optional determination of positions of incisions, with the capability to sense collisions and with optimization of the speed and acceleration during cutting.Practical implications: The proposed system assures automatic preparation of NC program without NC programer.Originality/value: The proposed concept shows a high degree of universality, efficiency and reliability and it can be simply adapted to other NC-machines.

  17. Developmental system at the crossroads of system theory, computer science, and genetic engineering

    CERN Document Server

    Węgrzyn, Stefan; Vidal, Pierre

    1990-01-01

    Many facts were at the origin of the present monograph. The ftrst is the beauty of maple leaves in Quebec forests in Fall. It raised the question: how does nature create and reproduce such beautiful patterns? The second was the reading of A. Lindenmayer's works on L systems. Finally came the discovery of "the secrets of DNA" together with many stimulating ex­ changes with biologists. Looking at such facts from the viewpoint of recursive numerical systems led to devise a simple model based on six elementary operations organized in a generating word, the analog of the program of a computer and of the genetic code of DNA in the cells of a living organism. It turned out that such a model, despite its simplicity, can account for a great number of properties of living organisms, e.g. their hierarchical structure, their ability to regenerate after a trauma, the possibility of cloning, their sensitivity to mutation, their growth, decay and reproduction. The model lends itself to analysis: the knowledge of the genera...

  18. Microsatellite data analysis for population genetics.

    Science.gov (United States)

    Kim, Kyung Seok; Sappington, Thomas W

    2013-01-01

    Theories and analytical tools of population genetics have been widely applied for addressing various questions in the fields of ecological genetics, conservation biology, and any context where the role of dispersal or gene flow is important. Underlying much of population genetics is the analysis of variation at selectively neutral marker loci, and microsatellites continue to be a popular choice of marker. In recent decades, software programs to estimate population genetics parameters have been developed at an increasing pace as computational science and theoretical knowledge advance. Numerous population genetics software programs are presently available to analyze microsatellite genotype data, but only a handful are commonly employed for calculating parameters such as genetic variation, genetic structure, patterns of spatial and temporal gene flow, population demography, individual population assignment, and genetic relationships within and between populations. In this chapter, we introduce statistical analyses and relevant population genetic software programs that are commonly employed in the field of population genetics and molecular ecology.

  19. Telegenetics: application of a tele-education program in genetic syndromes for Brazilian students

    Directory of Open Access Journals (Sweden)

    Luciana Paula MAXIMINO

    2014-12-01

    Full Text Available With the high occurrence of genetic anomalies in Brazil and the manifestations of communication disorders associated with these conditions, the development of educative actions that comprise these illnesses can bring unique benefits in the identification and appropriate treatment of these clinical pictures. Objective The aim of this study was to develop and analyze an educational program in genetic syndromes for elementary students applied in two Brazilian states, using an Interactive Tele-education model. Material and Methods The study was carried out in 4 schools: two in the state of São Paulo, Southeast Region, Brazil, and two in the state of Amazonas, North Region, Brazil. Forty-five students, both genders, aged between 13 and 14 years, of the 9th grade of the basic education of both public and private system, were divided into two groups: 21 of São Paulo Group (SPG and 24 of Amazonas Group (AMG. The educational program lasted about 3 months and was divided into two stages including both classroom and distance activities on genetic syndromes. The classroom activity was carried out separately in each school, with expository lessons, graphs and audiovisual contents. In the activity at a distance the educational content was presented to students by means of the Interactive Tele-education model. In this stage, the students had access a Cybertutor, using the Young Doctor Project methodology. In order to measure the effectiveness of the educational program, the Problem Situation Questionnaire (PSQ and the Web Site Motivational Analysis Checklist adapted (FPM were used. Results The program developed was effective for knowledge acquisition in 80% of the groups. FPM showed a high satisfaction index from the participants in relation to the Interactive Tele-education, evaluating the program as "awesome course". No statistically significant differences between the groups regarding type of school or state were observed. Conclusion Thus, the Tele

  20. The Mouse House: A brief history of the ORNL mouse-genetics program, 1947–2009

    Energy Technology Data Exchange (ETDEWEB)

    Russell, Liane B.

    2013-10-01

    The large mouse genetics program at the Oak Ridge National Lab is often re-membered chiefly for the germ-cell mutation-rate data it generated and their uses in estimating the risk of heritable radiation damage. In fact, it soon became a multi-faceted research effort that, over a period of almost 60 years, generated a wealth of information in the areas of mammalian mutagenesis, basic genetics (later enriched by molecular techniques), cytogenetics, reproductive biology, biochemistry of germ cells, and teratology. Research in the area of germ-cell mutagenesis explored the important physical and biological factors that affect the frequency and nature of induced mutations and made several unexpected discoveries, such as the major importance of the perigametic interval (the zygote stage) for the origin of spontaneous mutations and for the sensitivity to induced genetic change. Of practical value was the discovery that ethylnitrosourea was a supermutagen for point mutations, making high-efficiency mutagenesis in the mouse feasible worldwide. Teratogenesis findings resulted in recommendations still generally accepted in radiological practice. Studies supporting the mutagenesis research added whole bodies of information about mammalian germ-cell development and about molecular targets in germ cells. The early decision to not merely count but propagate genetic variants of all sorts made possible further discoveries, such as the Y-Chromosome s importance in mammalian sex determination and the identification of rare X-autosome translocations, which, in turn, led to the formulation of the single-active-X hypothesis and provided tools for studies of functional mosaicism for autosomal genes, male sterility, and chromosome-pairing mechanism. Extensive genetic and then molecular analyses of large numbers of induced specific-locus mutants resulted in fine-structure physical and correlated functional mapping of significant portions of the mouse genome and constituted a valuable

  1. Exponential distribution-based genetic algorithm for solving mixed-integer bilevel programming problems

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Two classes of mixed-integer nonlinear bilevel programming problems are discussed. One is that the follower's functions are separable with respect to the follower's variables, and the other is that the follower's functions are convex if the follower's variables are not restricted to integers. A genetic algorithm based on an exponential distribution is proposed for the aforementioned problems. First, for each fixed leader's variable x, it is proved that the optimal solution y of the follower's mixed-integer programming can be obtained by solving associated relaxed problems, and according to the convexity of the functions involved, a simplified branch and bound approach is given to solve the follower's programming for the second class of problems. Furthermore, based on an exponential distribution with a parameter A, a new crossover operator is designed in which the best individuals are used to generate better offspring of crossover. The simulation results illustrate that the proposed algorithm is efficient and robust.

  2. A Genetic Programming Method for the Identification of Signal Peptides and Prediction of Their Cleavage Sites

    Directory of Open Access Journals (Sweden)

    David Lennartsson

    2004-01-01

    Full Text Available A novel approach to signal peptide identification is presented. We use an evolutionary algorithm for automatic evolution of classification programs, so-called programmatic motifs. The variant of evolutionary algorithm used is called genetic programming where a population of solution candidates in the form of full computer programs is evolved, based on training examples consisting of signal peptide sequences. The method is compared with a previous work using artificial neural network (ANN approaches. Some advantages compared to ANNs are noted. The programmatic motif can perform computational tasks beyond that of feed-forward neural networks and has also other advantages such as readability. The best motif evolved was analyzed and shown to detect the h-region of the signal peptide. A powerful parallel computer cluster was used for the experiment.

  3. Genetic Programming for the Generation of Crisp and Fuzzy Rule Bases in Classification and Diagnosis of Medical Data

    DEFF Research Database (Denmark)

    Dounias, George; Tsakonas, Athanasios; Jantzen, Jan

    2002-01-01

    This paper demonstrates two methodologies for the construction of rule-based systems in medical decision making. The first approach consists of a method combining genetic programming and heuristic hierarchical rule-base construction. The second model is composed by a strongly-typed genetic progra...

  4. DNAStat, version 2.1--a computer program for processing genetic profile databases and biostatistical calculations.

    Science.gov (United States)

    Berent, Jarosław

    2010-01-01

    This paper presents the new DNAStat version 2.1 for processing genetic profile databases and biostatistical calculations. The popularization of DNA studies employed in the judicial system has led to the necessity of developing appropriate computer programs. Such programs must, above all, address two critical problems, i.e. the broadly understood data processing and data storage, and biostatistical calculations. Moreover, in case of terrorist attacks and mass natural disasters, the ability to identify victims by searching related individuals is very important. DNAStat version 2.1 is an adequate program for such purposes. The DNAStat version 1.0 was launched in 2005. In 2006, the program was updated to 1.1 and 1.2 versions. There were, however, slight differences between those versions and the original one. The DNAStat version 2.0 was launched in 2007 and the major program improvement was an introduction of the group calculation options with the potential application to personal identification of mass disasters and terrorism victims. The last 2.1 version has the option of language selection--Polish or English, which will enhance the usage and application of the program also in other countries.

  5. Introductory Computer Programming Course Teaching Improvement Using Immersion Language, Extreme Programming, and Education Theories

    Science.gov (United States)

    Velez-Rubio, Miguel

    2013-01-01

    Teaching computer programming to freshmen students in Computer Sciences and other Information Technology areas has been identified as a complex activity. Different approaches have been studied looking for the best one that could help to improve this teaching process. A proposed approach was implemented which is based in the language immersion…

  6. Advancing genetic theory and application by metabolic quantitative trait loci analysis.

    Science.gov (United States)

    Kliebenstein, Danielj

    2009-06-01

    This review describes recent advances in the analysis of metabolism using quantitative genetics. It focuses on how recent metabolic quantitative trait loci (QTL) studies enhance our understanding of the genetic architecture underlying naturally variable phenotypes and the impact of this fundamental research on agriculture, specifically crop breeding. In particular, the role of whole-genome duplications in generating quantitative genetic variation within a species is highlighted and the potential uses of this phenomenon presented. Additionally, the review describes how new observations from metabolic QTL mapping analyses are helping to shape and expand the concepts of genetic epistasis.

  7. On the Calibration of Multigene Genetic Programming to Simulate Low Flows in the Moselle River

    Directory of Open Access Journals (Sweden)

    Ali DANANDEH MEHR

    2016-12-01

    Full Text Available The aim of this paper is to calibrate a data-driven model to simulate Moselle River flows and compare the performance with three different hydrologic models from a previous study. For consistency a similar set up and error metric are used to evaluate the model results. Precipitation, potential evapotranspiration and streamflow from previous day have been used as inputs. Based on the calibration and validation results, the proposed multigene genetic programming model is the best performing model among four models. The timing and the magnitude of extreme low flow events could be captured even when we use root mean squared error as the objective function for model calibration. Although the model is developed and calibrated for Moselle River flows, the multigene genetic algorithm offers a great opportunity for hydrologic prediction and forecast problems in the river basins with scarce data issues.

  8. Real Time Updating Genetic Network Programming for Adapting to the Change of Stock Prices

    Science.gov (United States)

    Chen, Yan; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro

    The key in stock trading model is to take the right actions for trading at the right time, primarily based on the accurate forecast of future stock trends. Since an effective trading with given information of stock prices needs an intelligent strategy for the decision making, we applied Genetic Network Programming (GNP) to creating a stock trading model. In this paper, we propose a new method called Real Time Updating Genetic Network Programming (RTU-GNP) for adapting to the change of stock prices. There are three important points in this paper: First, the RTU-GNP method makes a stock trading decision considering both the recommendable information of technical indices and the candlestick charts according to the real time stock prices. Second, we combine RTU-GNP with a Sarsa learning algorithm to create the programs efficiently. Also, sub-nodes are introduced in each judgment and processing node to determine appropriate actions (buying/selling) and to select appropriate stock price information depending on the situation. Third, a Real Time Updating system has been firstly introduced in our paper considering the change of the trend of stock prices. The experimental results on the Japanese stock market show that the trading model with the proposed RTU-GNP method outperforms other models without real time updating. We also compared the experimental results using the proposed method with Buy&Hold method to confirm its effectiveness, and it is clarified that the proposed trading model can obtain much higher profits than Buy&Hold method.

  9. Modern Biological Theories of Aging.

    Science.gov (United States)

    Jin, Kunlin

    2010-10-01

    Despite recent advances in molecular biology and genetics, the mysteries that control human lifespan are yet to be unraveled. Many theories, which fall into two main categories: programmed and error theories, have been proposed to explain the process of aging, but neither of them appears to be fully satisfactory. These theories may interact with each other in a complex way. By understanding and testing the existing and new aging theories, it may be possible to promote successful aging.

  10. Bridging the Gap Between Theory and Practice in a B.A. Program in EFL

    Directory of Open Access Journals (Sweden)

    Julia Zoraida Posada Ortiz

    2014-04-01

    Full Text Available This article describes the theoretical principles underlying the research component of the Bachelor’s program of Basic Education with an Emphasis in English at a public university in Bogotá (Colombia, and an exercise of syllabus revision that served to link theory and practice through the research component of the program. The aim of the exercise was to reflect upon the syllabus and discuss how, from the different components of the program, student-teachers can understand research as the bridge to link what they learn in class and their practice in school contexts. A group of teachers revised the theoretical foundations as well as their practice in each cycle of the program, using the main tenets of critical pedagogy, teacher research, reflective teaching, and case study.

  11. Optimal in silico target gene deletion through nonlinear programming for genetic engineering.

    Science.gov (United States)

    Hong, Chung-Chien; Song, Mingzhou

    2010-02-24

    Optimal selection of multiple regulatory genes, known as targets, for deletion to enhance or suppress the activities of downstream genes or metabolites is an important problem in genetic engineering. Such problems become more feasible to address in silico due to the availability of more realistic dynamical system models of gene regulatory and metabolic networks. The goal of the computational problem is to search for a subset of genes to knock out so that the activity of a downstream gene or a metabolite is optimized. Based on discrete dynamical system modeling of gene regulatory networks, an integer programming problem is formulated for the optimal in silico target gene deletion problem. In the first result, the integer programming problem is proved to be NP-hard and equivalent to a nonlinear programming problem. In the second result, a heuristic algorithm, called GKONP, is designed to approximate the optimal solution, involving an approach to prune insignificant terms in the objective function, and the parallel differential evolution algorithm. In the third result, the effectiveness of the GKONP algorithm is demonstrated by applying it to a discrete dynamical system model of the yeast pheromone pathways. The empirical accuracy and time efficiency are assessed in comparison to an optimal, but exhaustive search strategy. Although the in silico target gene deletion problem has enormous potential applications in genetic engineering, one must overcome the computational challenge due to its NP-hardness. The presented solution, which has been demonstrated to approximate the optimal solution in a practical amount of time, is among the few that address the computational challenge. In the experiment on the yeast pheromone pathways, the identified best subset of genes for deletion showed advantage over genes that were selected empirically. Once validated in vivo, the optimal target genes are expected to achieve higher genetic engineering effectiveness than a trial

  12. Optimal in silico target gene deletion through nonlinear programming for genetic engineering.

    Directory of Open Access Journals (Sweden)

    Chung-Chien Hong

    Full Text Available BACKGROUND: Optimal selection of multiple regulatory genes, known as targets, for deletion to enhance or suppress the activities of downstream genes or metabolites is an important problem in genetic engineering. Such problems become more feasible to address in silico due to the availability of more realistic dynamical system models of gene regulatory and metabolic networks. The goal of the computational problem is to search for a subset of genes to knock out so that the activity of a downstream gene or a metabolite is optimized. METHODOLOGY/PRINCIPAL FINDINGS: Based on discrete dynamical system modeling of gene regulatory networks, an integer programming problem is formulated for the optimal in silico target gene deletion problem. In the first result, the integer programming problem is proved to be NP-hard and equivalent to a nonlinear programming problem. In the second result, a heuristic algorithm, called GKONP, is designed to approximate the optimal solution, involving an approach to prune insignificant terms in the objective function, and the parallel differential evolution algorithm. In the third result, the effectiveness of the GKONP algorithm is demonstrated by applying it to a discrete dynamical system model of the yeast pheromone pathways. The empirical accuracy and time efficiency are assessed in comparison to an optimal, but exhaustive search strategy. SIGNIFICANCE: Although the in silico target gene deletion problem has enormous potential applications in genetic engineering, one must overcome the computational challenge due to its NP-hardness. The presented solution, which has been demonstrated to approximate the optimal solution in a practical amount of time, is among the few that address the computational challenge. In the experiment on the yeast pheromone pathways, the identified best subset of genes for deletion showed advantage over genes that were selected empirically. Once validated in vivo, the optimal target genes are

  13. Mini core germplasm collections for infusing genetic diversity in plant breeding programs

    Directory of Open Access Journals (Sweden)

    Hari D Upadhyaya*, Devvart Yadav, Naresh Dronavalli, CLL Gowda, and Sube Singh

    2010-07-01

    Full Text Available Plant genetic resources are essential components to meet future food security needs of world. Crop germplasm diversitycontributes to developing improved crop cultivars aimed at increasing crop productivity. The large size of germplasmcollections, coupled with unavailability of detailed data and information, has resulted in low use (<1% of germplasmleading to a narrow genetic base in many crops. The miniaturization of crop collections with almost full representation ofgenetic diversity in the form of mini core (~1% of the entire collection approach is an effective methodology to enrichand enhance crop improvement programs. The concept and process of developing mini core at The International CropsResearch Institute for the Semi-Arid Tropics (ICRISAT has been recognized worldwide as an “International PublicGood” (IPG. The mini core provides a means for accessing the larger collections for further exploration and also helps inproper assessment of genetic diversity and population structure and for association mapping and targeted gene mining.Use of mini core approach will lead to greater utilization of diverse germplasm for developing broad-based cultivars,especially in the context of climate change. Many national programs have shown immense interest in evaluating minicore as reflected by the supply of 114 sets of mini core of chickpea, groundnut, pigeonpea, sorghum, pearl millet, foxtailmillet and finger millet to researchers in 14 countries. Scientists have been able to identify new and diverse sources ofvariation for morpho-agronomic, quality, biotic, and abiotic stress resistance traits in various crops. The molecularcharacterization of the mini core will further enhance its use in plant breeding programs.

  14. Genetic Variability and Population Structure of Salvia lachnostachys: Implications for Breeding and Conservation Programs

    Directory of Open Access Journals (Sweden)

    Marianna Erbano

    2015-04-01

    Full Text Available The genetic diversity and population structure of Salvia lachnostachys Benth were assessed. Inter Simple Sequence Repeat (ISSR molecular markers were used to investigate the restricted distribution of S. lachnostachys in Parana State, Brazil. Leaves of 73 individuals representing three populations were collected. DNA was extracted and submitted to PCR-ISSR amplification with nine tested primers. Genetic diversity parameters were evaluated. Our analysis indicated 95.6% polymorphic loci (stress value 0.02 with a 0.79 average Simpson’s index. The Nei-Li distance dendrogram and principal component analysis largely recovered the geographical origin of each sample. Four major clusters were recognized representing each collected population. Nei’s gene diversity and Shannon’s information index were 0.25 and 0.40 respectively. As is typical for outcrossing herbs, the majority of genetic variation occurred at the population level (81.76%. A high gene flow (Nm = 2.48 was observed with a correspondingly low fixation index. These values were generally similar to previous studies on congeneric species. The results of principal coordinate analysis (PCA and of arithmetic average (UPGMA were consistent and all three populations appear distinct as in STRUCTURE analysis. In addition, this analysis indicated a majority intrapopulation genetic variation. Despite the human pressure on natural populations our study found high levels of genetic diversity for S. lachnostachys. This was the first molecular assessment for this endemic species with medicinal proprieties and the results can guide for subsequent bioprospection, breeding programs or conservation actions.

  15. System Response Analysis and Model Order Reduction, Using Conventional Method, Bond Graph Technique and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Lubna Moin

    2009-04-01

    Full Text Available This research paper basically explores and compares the different modeling and analysis techniques and than it also explores the model order reduction approach and significance. The traditional modeling and simulation techniques for dynamic systems are generally adequate for single-domain systems only, but the Bond Graph technique provides new strategies for reliable solutions of multi-domain system. They are also used for analyzing linear and non linear dynamic production system, artificial intelligence, image processing, robotics and industrial automation. This paper describes a unique technique of generating the Genetic design from the tree structured transfer function obtained from Bond Graph. This research work combines bond graphs for model representation with Genetic programming for exploring different ideas on design space tree structured transfer function result from replacing typical bond graph element with their impedance equivalent specifying impedance lows for Bond Graph multiport. This tree structured form thus obtained from Bond Graph is applied for generating the Genetic Tree. Application studies will identify key issues and importance for advancing this approach towards becoming on effective and efficient design tool for synthesizing design for Electrical system. In the first phase, the system is modeled using Bond Graph technique. Its system response and transfer function with conventional and Bond Graph method is analyzed and then a approach towards model order reduction is observed. The suggested algorithm and other known modern model order reduction techniques are applied to a 11th order high pass filter [1], with different approach. The model order reduction technique developed in this paper has least reduction errors and secondly the final model retains structural information. The system response and the stability analysis of the system transfer function taken by conventional and by Bond Graph method is compared and

  16. System Response Analysis and Model Order Reduction, Using Conventional Method, Bond Graph Technique and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Shahid Ali

    2009-04-01

    Full Text Available This research paper basically explores and compares the different modeling and analysis techniques and than it also explores the model order reduction approach and significance. The traditional modeling and simulation techniques for dynamic systems are generally adequate for single-domain systems only, but the Bond Graph technique provides new strategies for reliable solutions of multi-domain system. They are also used for analyzing linear and non linear dynamic production system, artificial intelligence, image processing, robotics and industrial automation. This paper describes a unique technique of generating the Genetic design from the tree structured transfer function obtained from Bond Graph. This research work combines bond graphs for model representation with Genetic programming for exploring different ideas on design space tree structured transfer function result from replacing typical bond graph element with their impedance equivalent specifying impedance lows for Bond Graph multiport. This tree structured form thus obtained from Bond Graph is applied for generating the Genetic Tree. Application studies will identify key issues and importance for advancing this approach towards becoming on effective and efficient design tool for synthesizing design for Electrical system. In the first phase, the system is modeled using Bond Graph technique. Its system response and transfer function with conventional and Bond Graph method is analyzed and then a approach towards model order reduction is observed. The suggested algorithm and other known modern model order reduction techniques are applied to a 11th order high pass filter [1], with different approach. The model order reduction technique developed in this paper has least reduction errors and secondly the final model retains structural information. The system response and the stability analysis of the system transfer function taken by conventional and by Bond Graph method is compared and

  17. Nurse residency programs: an evidence-based review of theory, process, and outcomes.

    Science.gov (United States)

    Anderson, Gwen; Hair, Carole; Todero, Catherine

    2012-01-01

    Nursing shortages exist worldwide while job stress, dissatisfaction, lack of peer support and limited professional opportunities still contribute to attrition. The aim of this systematic review is to describe and evaluate the quality of the science, report recommendations and lessons learned about implementing and evaluating nurse residency programs (NRPs) designed to improve new graduate transitioning. Databases were searched between 1980 and 2010 using five search terms: nurse, intern, extern, transition and residency programs. Twenty studies reporting programs for new RNs fit the inclusion criteria. Three major discoveries include: 1. Wide variation in content, teaching and learning strategies make comparison across programs difficult; 2. Lack of theory in designing the educational intervention has limited the selection and development of new instruments to measure program effectiveness; and 3. Well designed quasi-experimental studies are needed. As a major nursing education redesign, NRPs could be used to test the principles, concepts and strategies of organizational transformation and experiential-interactive learning theory. By focusing on fiscal outcomes, current administrators of NRPs are missing the opportunity to implement an organizational strategy that could improve workplace environments. Healthcare organizations need to envision NRPs as a demonstration of positive clinical learning environments that can enhance intra- and interprofessional education and practice.

  18. Paired-permanent approach for VB theory (II) -An ab initio spin-free VB program

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Paired-permanent approach for VB theory is extensively developed. Canonical expan sion of a paired-permanent is deduced. Furthermore, it is shown that a paired-permanent may be expressed in terms of the products of sub-paired-permanents of any given order and their corre sponding minors. An ab initio spin-free valence bond program, called Xiamen, is implemented by using paired-permanent approach. Test calculation shows that Xiamen package is more efficient than some other programs based on the traditional VB algorithm, and it provides a new practical tool for quantum chemistry.

  19. Buying and Selling Stocks of Multi Brands Using Genetic Network Programming with Control Nodes

    Science.gov (United States)

    Ohkawa, Etsushi; Chen, Yan; Bao, Zhiguo; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro

    A new evolutionary method named “Genetic Network Programming with control nodes, GNPcn” has been applied to determine the timing of buying or selling stocks. GNPcn represents its solutions as directed graph structures which has some useful features inherently. For example, GNPcn has an implicit memory function which memorizes the past action sequences of agents and GNPcn can re-use nodes repeatedly in the network flow, so very compact graph structures can be made. GNPcn can determine the strategy of buying and selling stocks of multi issues. The effectiveness of the proposed method is confirmed by simulations.

  20. An Inventory-Theory-Based Inexact Multistage Stochastic Programming Model for Water Resources Management

    Directory of Open Access Journals (Sweden)

    M. Q. Suo

    2013-01-01

    Full Text Available An inventory-theory-based inexact multistage stochastic programming (IB-IMSP method is developed for planning water resources systems under uncertainty. The IB-IMSP is based on inexact multistage stochastic programming and inventory theory. The IB-IMSP cannot only effectively handle system uncertainties represented as probability density functions and discrete intervals but also efficiently reflect dynamic features of system conditions under different flow levels within a multistage context. Moreover, it can provide reasonable transferring schemes (i.e., the amount and batch of transferring as well as the corresponding transferring period associated with various flow scenarios for solving water shortage problems. The applicability of the proposed IB-IMSP is demonstrated by a case study of planning water resources management. The solutions obtained are helpful for decision makers in not only identifying different transferring schemes when the promised water is not met, but also making decisions of water allocation associated with different economic objectives.

  1. The effect of an interventional program based on the Theory of Ethology on infant breastfeeding competence

    Directory of Open Access Journals (Sweden)

    aghdas karimi

    2014-08-01

    Full Text Available Introduction: according to the ethology theory mother infant separation immediately after birth can interfere with the infants innate behaviors for the initiation of breastfeeding. The aim of this study was to the effect of an interventional program based on the Theory of Ethology on infant breast feeding competence Materials and Methods: 114 primiparous, Iranian, healthy, full term mothers between 18-35 years with normal vaginal delivery who intended to breastfeed their babies. They were put in direct skin to skin contact with their infants immediately after birth for two hours. Then, rates of infant breastfeeding competence were compared with a control group receiving routine hospital cares. Results: Rates of infant breastfeeding competence were higher in the skin to skin contact group compared to routine care group (p=0.0001. Conclusion: mother- infant early skin to skin contact promotes infants natural feeding behaviors leading to higher rates of infant breastfeeding competence. These findings confirm the Theory of Ethology.

  2. The effect of an interventional program based on the Theory of Ethology on infant breastfeeding competence

    Directory of Open Access Journals (Sweden)

    aghdas karimi

    2014-12-01

    Full Text Available Introduction: according to the ethology theory mother infant separation immediately after birth can interfere with the infants innate behaviors for the initiation of breastfeeding. The aim of this study was to the effect of an interventional program based on the Theory of Ethology on infant breast feeding competence Materials and Methods: 114 primiparous, Iranian, healthy, full term mothers between 18-35 years with normal vaginal delivery who intended to breastfeed their babies. They were put in direct skin to skin contact with their infants immediately after birth for two hours. Then, rates of infant breastfeeding competence were compared with a control group receiving routine hospital cares. Results: Rates of infant breastfeeding competence were higher in the skin to skin contact group compared to routine care group (p=0.0001. Conclusion: mother- infant early skin to skin contact promotes infants natural feeding behaviors leading to higher rates of infant breastfeeding competence. These findings confirm the Theory of Ethology.

  3. Development of a program theory for shared decision-making: a realist review protocol.

    Science.gov (United States)

    Groot, Gary; Waldron, Tamara; Carr, Tracey; McMullen, Linda; Bandura, Lori-Ann; Neufeld, Shelley-May; Duncan, Vicky

    2017-06-17

    The practicality of applying evidence to healthcare systems with the aim of implementing change is an ongoing challenge for practitioners, policy makers, and academics. Shared decision- making (SDM), a method of medical decision-making that allows a balanced relationship between patients, physicians, and other key players in the medical decision process, is purported to improve patient and system outcomes. Despite the oft-mentioned benefits, there are gaps in the current literature between theory and implementation that would benefit from a realist approach given the value of this methodology to analyze complex interventions. In this protocol, we outline a study that will explore: "In which situations, how, why, and for whom does SDM between patients and health care providers contribute to improved decision making?" A seven step iterative process will be described including preliminary theory development, establishment of a search strategy, selection and appraisal of literature, data extraction, analysis and synthesis of extracted results from literature, and formation of a revised program theory with the input of patients, physicians, nurse navigators, and policy makers from a stakeholder session. The goal of the realist review will be to identify and refine a program theory for SDM through the identification of mechanisms which shape the characteristics of when, how, and why SDM will, and will not, work. PROSPERO CRD42017062609.

  4. Better-than-classical circuits for OR and AND/OR found using genetic programming

    CERN Document Server

    Barnum, H N; Spector, L; Barnum, Howard; Bernstein, Herbert J.; Spector, Lee

    1999-01-01

    We present a quantum circuit evolved using genetic programming. From it we derive the first better-than-classical one-query bounded-error circuit for OR of one-bit black-box functions. The larger evolved circuit calculates, with error probability lower than any possible classical one-query algorithm, the property defined by a depth-two binary AND/OR tree with the four possible function input values as leaves. We analyze it as a kind of recursive application of the OR circuit. Since the OR and AND/OR trees have fan-in 2, these circuits may be useful in investigating the uniform binary AND/OR tree in the large-N asymptotic regime, a problem whose classical query complexity is completely understood and which has applications in game tree evaluation, logic programming, theorem-proving, and many other areas.

  5. Open pre-schools at integrated health services - A program theory

    Directory of Open Access Journals (Sweden)

    Agneta Abrahamsson

    2013-04-01

    Full Text Available Introduction: Family centres in Sweden are integrated services that reach all prospective parents and parents with children up to their sixth year, because of the co-location of the health service with the social service and the open pre-school. The personnel on the multi-professional site work together to meet the needs of the target group. The article explores a program theory focused on the open pre-schools at family centres. Method: A multi-case design is used and the sample consists of open pre-schools at six family centres. The hypothesis is based on previous research and evaluation data. It guides the data collection which is collected and analysed stepwise. Both parents and personnel are interviewed individually and in groups at each centre. Findings: The hypothesis was expanded to a program theory. The compliance of the professionals was the most significant element that explained why the open access service facilitated positive parenting. The professionals act in a compliant manner to meet the needs of the children and parents as well as in creating good conditions for social networking and learning amongst the parents. Conclusion: The compliance of the professionals in this program theory of open pre-schools at family centres can be a standard in integrated and open access services, whereas the organisation form can vary. The best way of increasing the number of integrative services is to support and encourage professionals that prefer to work in a compliant manner.

  6. Open pre-schools at integrated health services - A program theory

    Directory of Open Access Journals (Sweden)

    Agneta Abrahamsson

    2013-04-01

    Full Text Available Introduction: Family centres in Sweden are integrated services that reach all prospective parents and parents with children up to their sixth year, because of the co-location of the health service with the social service and the open pre-school. The personnel on the multi-professional site work together to meet the needs of the target group. The article explores a program theory focused on the open pre-schools at family centres.Method: A multi-case design is used and the sample consists of open pre-schools at six family centres. The hypothesis is based on previous research and evaluation data. It guides the data collection which is collected and analysed stepwise. Both parents and personnel are interviewed individually and in groups at each centre.Findings: The hypothesis was expanded to a program theory. The compliance of the professionals was the most significant element that explained why the open access service facilitated positive parenting. The professionals act in a compliant manner to meet the needs of the children and parents as well as in creating good conditions for social networking and learning amongst the parents. Conclusion: The compliance of the professionals in this program theory of open pre-schools at family centres can be a standard in integrated and open access services, whereas the organisation form can vary. The best way of increasing the number of integrative services is to support and encourage professionals that prefer to work in a compliant manner.

  7. A Hybrid Genetic Algorithm for Reduct of Attributes in Decision System Based on Rough Set Theory

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Knowledge reduction is an important issue when dealing with huge amounts of data. And it has been proved that computing the minimal reduct of decision system is NP-complete. By introducing heuristic information into genetic algorithm, we proposed a heuristic genetic algorithm. In the genetic algorithm, we constructed a new operator to maintaining the classification ability. The experiment shows that our algorithm is efficient and effective for minimal reduct, even for the special example that the simple heuristic algorithm can't get the right result.

  8. Learning to solve planning problems efficiently by means of genetic programming.

    Science.gov (United States)

    Aler, R; Borrajo, D; Isasi, P

    2001-01-01

    Declarative problem solving, such as planning, poses interesting challenges for Genetic Programming (GP). There have been recent attempts to apply GP to planning that fit two approaches: (a) using GP to search in plan space or (b) to evolve a planner. In this article, we propose to evolve only the heuristics to make a particular planner more efficient. This approach is more feasible than (b) because it does not have to build a planner from scratch but can take advantage of already existing planning systems. It is also more efficient than (a) because once the heuristics have been evolved, they can be used to solve a whole class of different planning problems in a planning domain, instead of running GP for every new planning problem. Empirical results show that our approach (EvoCK) is able to evolve heuristics in two planning domains (the blocks world and the logistics domain) that improve PRODIGY4.0 performance. Additionally, we experiment with a new genetic operator --Instance-Based Crossover--that is able to use traces of the base planner as raw genetic material to be injected into the evolving population.

  9. Minimalist Program and its fundamental improvements in syntactic theory: evidence from Agreement Asymmetry in Standard Arabic

    Directory of Open Access Journals (Sweden)

    Nasser Al-Horais

    2012-11-01

    Full Text Available Normal 0 21 false false false EN-US X-NONE AR-SA /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:auto; mso-para-margin-right:1.0cm; mso-para-margin-bottom:auto; mso-para-margin-left:2.0cm; text-align:justify; text-indent:-1.0cm; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi; mso-ansi-language:EN-US; mso-fareast-language:EN-US;} The Minimalist Program is a major line of inquiry that has been developing inside Generative Grammar since the early nineties, when it was proposed by Chomsky  (1993, 1995. In that time, Chomsky (1998: 5 presents Minimalist Program as a program, not as a theory, but today, Minimalist Program lays out a very specific view of the basis of syntactic grammar that, when compared to other formalisms, is often taken to look very much like a theory. The prime concern of this paper, however, is  to provide a comprehensive and accessible introduction to the art of minimalist approach to the theory of grammar. In this regard, this paper discusses some new ideas articulated recently by Chomsky, and have led to several fundamental improvements in syntactic theory  such as changing the function of movement and the Extended Projection Principle (EPP feature, or proposing new theories such as Phases and Feature Inheritance. In order to evidence the significance of these fundamental improvements, the current paper provides a minimalist analysis to account for agreement and word-order asymmetry in Stranded Arabic. This fresh minimalist account meets the challenges (to the basic tenets of syntactic theory occurred

  10. Wavelet-linear genetic programming: A new approach for modeling monthly streamflow

    Science.gov (United States)

    Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur

    2017-06-01

    The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predict the monthly streamflow (Q) in two gauging stations, Pataveh and Shahmokhtar, on the Beshar River at the Yasuj, Iran were used in this study. In the proposed WLGP model, the wavelet analysis was linked to the LGP model where the original time series of streamflow were decomposed into the sub-time series comprising wavelet coefficients. The results were compared with the single LGP, artificial neural network (ANN), a hybrid wavelet-ANN (WANN) and Multi Linear Regression (MLR) models. The comparisons were done by some of the commonly utilized relevant physical statistics. The Nash coefficients (E) were found as 0.877 and 0.817 for the WLGP model, for the Pataveh and Shahmokhtar stations, respectively. The comparison of the results showed that the WLGP model could significantly increase the streamflow prediction accuracy in both stations. Since, the results demonstrate a closer approximation of the peak streamflow values by the WLGP model, this model could be utilized for the simulation of cumulative streamflow data prediction in one month ahead.

  11. Multiobjective Genetic Algorithms Program for the Optimization of an OTA for Front-End Electronics

    Directory of Open Access Journals (Sweden)

    Abdelghani Dendouga

    2014-01-01

    Full Text Available The design of an interface to a specific sensor induces costs and design time mainly related to the analog part. So to reduce these costs, it should have been standardized like digital electronics. The aim of the present work is the elaboration of a method based on multiobjectives genetic algorithms (MOGAs to allow automated synthesis of analog and mixed systems. This proposed methodology is used to find the optimal dimensional transistor parameters (length and width in order to obtain operational amplifier performances for analog and mixed CMOS-(complementary metal oxide semiconductor- based circuit applications. Six performances are considered in this study, direct current (DC gain, unity-gain bandwidth (GBW, phase margin (PM, power consumption (P, area (A, and slew rate (SR. We used the Matlab optimization toolbox to implement the program. Also, by using variables obtained from genetic algorithms, the operational transconductance amplifier (OTA is simulated by using Cadence Virtuoso Spectre circuit simulator in standard TSMC (Taiwan Semiconductor Manufacturing Company RF 0.18 μm CMOS technology. A good agreement is observed between the program optimization and electric simulation.

  12. Coregulation of genetic programs by the transcription factors NFIB and STAT5.

    Science.gov (United States)

    Robinson, Gertraud W; Kang, Keunsoo; Yoo, Kyung Hyun; Tang, Yong; Zhu, Bing-Mei; Yamaji, Daisuke; Colditz, Vera; Jang, Seung Jian; Gronostajski, Richard M; Hennighausen, Lothar

    2014-05-01

    Mammary-specific genetic programs are activated during pregnancy by the common transcription factor signal transducer and activator of transcription (STAT) 5. More than one third of these genes carry nuclear factor I/B (NFIB) binding motifs that coincide with STAT5 in vivo binding, suggesting functional synergy between these two transcription factors. The role of NFIB in this governance was investigated in mice from which Nfib had been inactivated in mammary stem cells or in differentiating alveolar epithelium. Although NFIB was not required for alveolar expansion, the combined absence of NFIB and STAT5 prevented the formation of functional alveoli. NFIB controlled the expression of mammary-specific and STAT5-regulated genes and chromatin immunoprecipitation-sequencing established STAT5 and NFIB binding at composite regulatory elements containing histone H3 lysine dimethylation enhancer marks and progesterone receptor binding. By integrating previously published chromatin immunoprecipitation-sequencing data sets, the presence of NFIB-STAT5 modules in other cell types was investigated. Notably, genomic sites bound by NFIB in hair follicle stem cells were also occupied by STAT5 in mammary epithelium and coincided with enhancer marks. Many of these genes were under NFIB control in both hair follicle stem cells and mammary alveolar epithelium. We propose that NFIB-STAT5 modules, possibly in conjunction with other transcription factors, control cell-specific genetic programs.

  13. A wavelet-linear genetic programming model for sodium (Na+) concentration forecasting in rivers

    Science.gov (United States)

    Ravansalar, Masoud; Rajaee, Taher; Zounemat-Kermani, Mohammad

    2016-06-01

    The prediction of water quality parameters in water resources such as rivers is of importance issue that needs to be considered in better management of irrigation systems and water supplies. In this respect, this study proposes a new hybrid wavelet-linear genetic programming (WLGP) model for prediction of monthly sodium (Na+) concentration. The 23-year monthly data used in this study, were measured from the Asi River at the Demirköprü gauging station located in Antakya, Turkey. At first, the measured discharge (Q) and Na+ datasets are initially decomposed into several sub-series using discrete wavelet transform (DWT). Then, these new sub-series are imposed to the ad hoc linear genetic programming (LGP) model as input patterns to predict monthly Na+ one month ahead. The results of the new proposed WLGP model are compared with LGP, WANN and ANN models. Comparison of the models represents the superiority of the WLGP model over the LGP, WANN and ANN models such that the Nash-Sutcliffe efficiencies (NSE) for WLGP, WANN, LGP and ANN models were 0.984, 0.904, 0.484 and 0.351, respectively. The achieved results even points to the superiority of the single LGP model than the ANN model. Continuously, the capability of the proposed WLGP model in terms of prediction of the Na+ peak values is also presented in this study.

  14. Drag reduction of a car model by linear genetic programming control

    Science.gov (United States)

    Li, Ruiying; Noack, Bernd R.; Cordier, Laurent; Borée, Jacques; Harambat, Fabien

    2017-08-01

    We investigate open- and closed-loop active control for aerodynamic drag reduction of a car model. Turbulent flow around a blunt-edged Ahmed body is examined at ReH≈ 3× 105 based on body height. The actuation is performed with pulsed jets at all trailing edges (multiple inputs) combined with a Coanda deflection surface. The flow is monitored with 16 pressure sensors distributed at the rear side (multiple outputs). We apply a recently developed model-free control strategy building on genetic programming in Dracopoulos and Kent (Neural Comput Appl 6:214-228, 1997) and Gautier et al. (J Fluid Mech 770:424-441, 2015). The optimized control laws comprise periodic forcing, multi-frequency forcing and sensor-based feedback including also time-history information feedback and combinations thereof. Key enabler is linear genetic programming (LGP) as powerful regression technique for optimizing the multiple-input multiple-output control laws. The proposed LGP control can select the best open- or closed-loop control in an unsupervised manner. Approximately 33% base pressure recovery associated with 22% drag reduction is achieved in all considered classes of control laws. Intriguingly, the feedback actuation emulates periodic high-frequency forcing. In addition, the control identified automatically the only sensor which listens to high-frequency flow components with good signal to noise ratio. Our control strategy is, in principle, applicable to all multiple actuators and sensors experiments.

  15. Linear genetic programming for time-series modelling of daily flow rate

    Indian Academy of Sciences (India)

    Aytac Guven

    2009-04-01

    In this study linear genetic programming (LGP),which is a variant of Genetic Programming,and two versions of Neural Networks (NNs)are used in predicting time-series of daily flow rates at a station on Schuylkill River at Berne,PA,USA.Daily flow rate at present is being predicted based on different time-series scenarios.For this purpose,various LGP and NN models are calibrated with training sets and validated by testing sets.Additionally,the robustness of the proposed LGP and NN models are evaluated by application data,which are used neither in training nor at testing stage.The results showed that both techniques predicted the flow rate data in quite good agreement with the observed ones,and the predictions of LGP and NN are challenging.The performance of LGP,which was moderately better than NN,is very promising and hence supports the use of LGP in predicting of river flow data.

  16. A Constraint programming-based genetic algorithm for capacity output optimization

    Directory of Open Access Journals (Sweden)

    Kate Ean Nee Goh

    2014-10-01

    Full Text Available Purpose: The manuscript presents an investigation into a constraint programming-based genetic algorithm for capacity output optimization in a back-end semiconductor manufacturing company.Design/methodology/approach: In the first stage, constraint programming defining the relationships between variables was formulated into the objective function. A genetic algorithm model was created in the second stage to optimize capacity output. Three demand scenarios were applied to test the robustness of the proposed algorithm.Findings: CPGA improved both the machine utilization and capacity output once the minimum requirements of a demand scenario were fulfilled. Capacity outputs of the three scenarios were improved by 157%, 7%, and 69%, respectively.Research limitations/implications: The work relates to aggregate planning of machine capacity in a single case study. The constraints and constructed scenarios were therefore industry-specific.Practical implications: Capacity planning in a semiconductor manufacturing facility need to consider multiple mutually influenced constraints in resource availability, process flow and product demand. The findings prove that CPGA is a practical and an efficient alternative to optimize the capacity output and to allow the company to review its capacity with quick feedback.Originality/value: The work integrates two contemporary computational methods for a real industry application conventionally reliant on human judgement.

  17. Drag reduction of a car model by linear genetic programming control

    CERN Document Server

    Li, Ruiying; Cordier, Laurent; Borée, Jacques; Harambat, Fabien; Kaiser, Eurika; Duriez, Thomas

    2016-01-01

    We investigate open- and closed-loop active control for aerodynamic drag reduction of a car model. Turbulent flow around a blunt-edged Ahmed body is examined at $Re_{H}\\approx3\\times10^{5}$ based on body height. The actuation is performed with pulsed jets at all trailing edges combined with a Coanda deflection surface. The flow is monitored with pressure sensors distributed at the rear side. We apply a model-free control strategy building on Dracopoulos & Kent (Neural Comput. & Applic., vol. 6, 1997, pp. 214-228) and Gautier et al. (J. Fluid Mech., vol. 770, 2015, pp. 442-457). The optimized control laws comprise periodic forcing, multi-frequency forcing and sensor-based feedback including also time-history information feedback and combination thereof. Key enabler is linear genetic programming as simple and efficient framework for multiple inputs (actuators) and multiple outputs (sensors). The proposed linear genetic programming control can select the best open- or closed-loop control in an unsupervis...

  18. Lean and leadership practices: development of an initial realist program theory.

    Science.gov (United States)

    Goodridge, Donna; Westhorp, Gill; Rotter, Thomas; Dobson, Roy; Bath, Brenna

    2015-09-07

    Lean as a management system has been increasingly adopted in health care settings in an effort to enhance quality, capacity and safety, while simultaneously containing or reducing costs. The Ministry of Health in the province of Saskatchewan, Canada has made a multi-million dollar investment in Lean initiatives to create "better health, better value, better care, and better teams", affording a unique opportunity to advance our understanding of the way in which Lean philosophy, principles and tools work in health care. In order to address the questions, "What changes in leadership practices are associated with the implementation of Lean?" and "When leadership practices change, how do the changed practices contribute to subsequent outcomes?", we used a qualitative, multi-stage approach to work towards developing an initial realist program theory. We describe the implications of realist assumptions for evaluation of this Lean initiative. Formal theories including Normalization Process Theory, Theories of Double Loop and Organization Leaning and the Theory of Cognitive Dissonance help understand this initial rough program theory. Data collection included: key informant consultation; a stakeholder workshop; documentary review; 26 audiotaped and transcribed interviews with health region personnel; and team discussions. A set of seven initial hypotheses regarding the manner in which Lean changes leadership practices were developed from our data. We hypothesized that Lean, as implemented in this particular setting, changes leadership practices in the following ways. Lean: a) aligns the aims and objectives of health regions; b) authorizes attention and resources to quality improvement and change management c) provides an integrated set of tools for particular tasks; d) changes leaders' attitudes or beliefs about appropriate leadership and management styles and behaviors; e) demands increased levels of expertise, accountability and commitment from leaders; f) measures and

  19. Generating Stock Trading Rules Using Genetic Network Programming with Flag Nodes and Adjustment of Importance Indexes

    Science.gov (United States)

    Mabu, Shingo; Chen, Yan; Hirasawa, Kotaro

    Genetic Network Programming (GNP) is an evolutionary algorithm which represents its solutions using graph structures. Since GNP can create quite compact programs and has an implicit memory function, GNP works well especially in dynamic environments. In addition, a study on creating trading rules on stock markets using GNP with Importance Index (GNP-IMX) has been done. IMX is one of the criterions for decision making. However, the values of IMXs must be deteminined by our experience/knowledge. Therefore in this paper, IMXs are adjusted appropriately during the stock trading in order to predict the rise and fall of the stocks. Moreover, newly defined flag nodes are introduced to GNP, which can appropriately judge the current situation of the stock prices, and also contributes to the use of many kinds of nodes in GNP program. In the simulation, programs are evolved using the stock prices of 20 companies. Then the generalization ability is tested and compared with GNP without flag nodes, GNP without IMX adjustment and Buy&Hold.

  20. Trading Rules on Stock Markets Using Genetic Network Programming with Reinforcement Learning and Importance Index

    Science.gov (United States)

    Mabu, Shingo; Hirasawa, Kotaro; Furuzuki, Takayuki

    Genetic Network Programming (GNP) is an evolutionary computation which represents its solutions using graph structures. Since GNP can create quite compact programs and has an implicit memory function, it has been clarified that GNP works well especially in dynamic environments. In addition, a study on creating trading rules on stock markets using GNP with Importance Index (GNP-IMX) has been done. IMX is a new element which is a criterion for decision making. In this paper, we combined GNP-IMX with Actor-Critic (GNP-IMX&AC) and create trading rules on stock markets. Evolution-based methods evolve their programs after enough period of time because they must calculate fitness values, however reinforcement learning can change programs during the period, therefore the trading rules can be created efficiently. In the simulation, the proposed method is trained using the stock prices of 10 brands in 2002 and 2003. Then the generalization ability is tested using the stock prices in 2004. The simulation results show that the proposed method can obtain larger profits than GNP-IMX without AC and Buy&Hold.

  1. What is "the patient perspective" in patient engagement programs? Implicit logics and parallels to feminist theories.

    Science.gov (United States)

    Rowland, Paula; McMillan, Sarah; McGillicuddy, Patti; Richards, Joy

    2017-01-01

    Public and patient involvement (PPI) in health care may refer to many different processes, ranging from participating in decision-making about one's own care to participating in health services research, health policy development, or organizational reforms. Across these many forms of public and patient involvement, the conceptual and theoretical underpinnings remain poorly articulated. Instead, most public and patient involvement programs rely on policy initiatives as their conceptual frameworks. This lack of conceptual clarity participates in dilemmas of program design, implementation, and evaluation. This study contributes to the development of theoretical understandings of public and patient involvement. In particular, we focus on the deployment of patient engagement programs within health service organizations. To develop a deeper understanding of the conceptual underpinnings of these programs, we examined the concept of "the patient perspective" as used by patient engagement practitioners and participants. Specifically, we focused on the way this phrase was used in the singular: "the" patient perspective or "the" patient voice. From qualitative analysis of interviews with 20 patient advisers and 6 staff members within a large urban health network in Canada, we argue that "the patient perspective" is referred to as a particular kind of situated knowledge, specifically an embodied knowledge of vulnerability. We draw parallels between this logic of patient perspective and the logic of early feminist theory, including the concepts of standpoint theory and strong objectivity. We suggest that champions of patient engagement may learn much from the way feminist theorists have constructed their arguments and addressed critique.

  2. The Features of Genetic Prion Diseases Based on Chinese Surveillance Program.

    Directory of Open Access Journals (Sweden)

    Qi Shi

    Full Text Available To identify the features of Chinese genetic prion diseases.Suspected Creutzfeldt-Jakob disease (CJD cases that were reported under CJD surveillance were diagnosed and subtyped using the diagnostic criteria issued by the WHO. The general information concerning the patient, their clinical, MRI and EEG data, and the results of CSF 14-3-3 and PRNP sequencing were carefully collected from the database of the national CJD surveillance program and analyzed using the SPSS 11.5 statistical software program.Since 2006, 69 patients were diagnosed with genetic prion diseases and as having 15 different mutations. The median age of the 69 patients at disease onset was 53.5 years, varying from 19 to 80 years. The majority of patients displaying clinical symptoms were in the 50-59 years of age. FFI, T188K gCJD and E200K were the three most common subtypes. The disease appeared in the family histories of 43.48% of the patients. The clinical manifestations varied considerably among the various diseases. Patients who carried mutations in the N-terminus displayed a younger age of onset, were CSF 14-3-3 negative, had a family history of the condition, and experienced a longer duration of the condition. The clinical courses of T188K were significantly shorter than those of FFI and E200K gCJD, while the symptoms in the FFI group appeared at a younger age and for a longer duration. Moreover, the time intervals between the initial neurologist visit to the final diagnosis were similar among patients with FFI, T188K gCJD, E200K gCJD and other diseases.The features of Chinese genetic prion diseases are different from those seen in Europe and other Asian countries.

  3. Genetic algorithm based on virus theory of evolution for traveling salesman problem; Virus shinkaron ni motozuku identeki algorithm no junkai salesman mondai eno oyo

    Energy Technology Data Exchange (ETDEWEB)

    Kubota, N. [Osaka Inst. of Technology, Osaka (Japan); Fukuda, T. [Nagoya University, Nagoya (Japan)

    1998-05-31

    This paper deals with virus evolutionary genetic algorithm. The genetic algorithms (GAs) have been demonstrated its effectiveness in optimization problems in these days. In general, the GAs simulate the survival of fittest by natural selection and the heredity of the Darwin`s theory of evolution. However, some types of evolutionary hypotheses such as neutral theory of molecular evolution, Imanishi`s evolutionary theory, serial symbiosis theory, and virus theory of evolution, have been proposed in addition to the Darwinism. Virus theory of evolution is based on the view that the virus transduction is a key mechanism for transporting segments of DNA across species. This paper proposes genetic algorithm based on the virus theory of evolution (VE-GA), which has two types of populations: host population and virus population. The VE-GA is composed of genetic operators and virus operators such as reverse transcription and incorporation. The reverse transcription operator transcribes virus genes on the chromosome of host individual and the incorporation operator creates new genotype of virus from host individual. These operators by virus population make it possible to transmit segment of DNA between individuals in the host population. Therefore, the VE-GA realizes not only vertical but also horizontal propagation of genetic information. Further, the VE-GA is applied to the traveling salesman problem in order to show the effectiveness. 20 refs., 10 figs., 3 tabs.

  4. Genetics

    DEFF Research Database (Denmark)

    Christensen, Kaare; McGue, Matt

    2016-01-01

    The sequenced genomes of individuals aged ≥80 years, who were highly educated, self-referred volunteers and with no self-reported chronic diseases were compared to young controls. In these data, healthy ageing is a distinct phenotype from exceptional longevity and genetic factors that protect...

  5. Affective and cognitive attitudes, uncertainty avoidance and intention to obtain genetic testing: an extension of the Theory of Planned Behaviour.

    Science.gov (United States)

    Wolff, Katharina; Nordin, Karin; Brun, Wibecke; Berglund, Gunilla; Kvale, Gerd

    2011-09-01

    To ensure successful implementation of genetic screening and counselling according to patients best interests, the attitudes and motives of the public are important to consider. The aim of this study was to apply a theoretical framework in order to investigate which individual and disease characteristics might facilitate the uptake of genetic testing. A questionnaire using an extended version of the Theory of Planned Behaviour was developed to assess the predictive value of affective and cognitive expected outcomes, subjective norms, perceived control and uncertainty avoidance on the intention to undergo genetic testing. In addition to these individual characteristics, the predictive power of two disease characteristics was investigated by systematically varying the diseases fatality and penetrance (i.e. the probability of getting ill in case one is a mutation carrier). This resulted in four versions of the questionnaire which was mailed to a random sample of 2400 Norwegians. Results showed genetic test interest to be quite high, and to vary depending on the characteristics of the disease, with participants preferring tests for highly penetrant diseases. The most important individual predictor was uncertainty avoidance.

  6. Mindstorms robots and the application of cognitive load theory in introductory programming

    Science.gov (United States)

    Mason, Raina; Cooper, Graham

    2013-12-01

    This paper reports on a series of introductory programming workshops, initially targeting female high school students, which utilised Lego Mindstorms robots. Cognitive load theory (CLT) was applied to the instructional design of the workshops, and a controlled experiment was also conducted investigating aspects of the interface. Results indicated that a truncated interface led to better learning by novice programmers as measured by test performance by participants, as well as enhanced shifts in self-efficacy and lowered perception of difficulty. There was also a transfer effect to another programming environment (Alice). It is argued that the results indicate that for novice programmers, the mere presence on-screen of additional (redundant) entities acts as a form of tacit distraction, thus impeding learning. The utility of CLT to analyse, design and deliver aspects of computer programming environments and instructional materials is discussed.

  7. A Coding Scheme Development Methodology Using Grounded Theory For Qualitative Analysis Of Pair Programming

    Directory of Open Access Journals (Sweden)

    Stephan Salinger

    2008-01-01

    Full Text Available A number of quantitative studies of pair programming (the practice of two programmers working together using just one computer have partially conflicting results. Qualitative studies are needed to explain what is really going on. We support such studies by taking a grounded theory (GT approach for deriving a coding scheme for the objective conceptual description of specific pair programming sessions independent of a particular research goal. The present article explains why our initial attempts at using GT failed and describes how to avoid these difficulties by a predetermined perspective on the data, concept naming rules, an analysis results metamodel, and pair coding. These practices may be helpful in all GT situations, particularly those involving very rich data such as video data. We illustrate the operation and usefulness of these practices by real examples derived from our coding work and present a few preliminary hypotheses regarding pair programming that have surfaced.

  8. Understanding emotional responses to breast/ovarian cancer genetic risk assessment: an applied test of a cognitive theory of emotion.

    Science.gov (United States)

    Phelps, Ceri; Bennett, Paul; Brain, Kate

    2008-10-01

    This study explored whether Smith and Lazarus' (1990, 1993) cognitive theory of emotion could predict emotional responses to an emotionally ambiguous real-life situation. Questionnaire data were collected from 145 women upon referral for cancer genetic risk assessment. These indicated a mixed emotional reaction of both positive and negative emotions to the assessment. Hierarchical regression analyses revealed that the hypothesised models explained between 20% and 33% of the variance of anxiety, hope and gratitude scores, but only 10% of the variance for challenge scores. For the previously unmodelled emotion of relief, 31% of the variance was explained by appraisals and core relational themes. The findings help explain why emotional responses to cancer genetic risk assessment vary and suggest that improving the accuracy of individuals' beliefs and expectations about the assessment process may help subsequent adaptation to risk information.

  9. Gene cuisine or Frankenfood? The theory of reasoned action as an audience segmentation strategy for messages about genetically modified foods.

    Science.gov (United States)

    Silk, Kami J; Weiner, Judith; Parrott, Roxanne L

    2005-12-01

    Genetically modified (GM) foods are currently a controversial topic about which the lay public in the United States knows little. Formative research has demonstrated that the lay public is uncertain and concerned about GM foods. This study (N = 858) extends focus group research by using the Theory of Reasoned Action (TRA) to examine attitudes and subjective norms related to GM foods as a theoretical strategy for audience segmentation. A hierarchical cluster analysis revealed four unique audiences based on their attitude and subjective norm toward GM foods (ambivalent-biotech, antibiotech, biotech-normer, and biotech individual). Results are discussed in terms of the theoretical and practical significance for audience segmentation.

  10. A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction

    Science.gov (United States)

    Danandeh Mehr, Ali; Kahya, Ercan

    2017-06-01

    Genetic programming (GP) is able to systematically explore alternative model structures of different accuracy and complexity from observed input and output data. The effectiveness of GP in hydrological system identification has been recognized in recent studies. However, selecting a parsimonious (accurate and simple) model from such alternatives still remains a question. This paper proposes a Pareto-optimal moving average multigene genetic programming (MA-MGGP) approach to develop a parsimonious model for single-station streamflow prediction. The three main components of the approach that take us from observed data to a validated model are: (1) data pre-processing, (2) system identification and (3) system simplification. The data pre-processing ingredient uses a simple moving average filter to diminish the lagged prediction effect of stand-alone data-driven models. The multigene ingredient of the model tends to identify the underlying nonlinear system with expressions simpler than classical monolithic GP and, eventually simplification component exploits Pareto front plot to select a parsimonious model through an interactive complexity-efficiency trade-off. The approach was tested using the daily streamflow records from a station on Senoz Stream, Turkey. Comparing to the efficiency results of stand-alone GP, MGGP, and conventional multi linear regression prediction models as benchmarks, the proposed Pareto-optimal MA-MGGP model put forward a parsimonious solution, which has a noteworthy importance of being applied in practice. In addition, the approach allows the user to enter human insight into the problem to examine evolved models and pick the best performing programs out for further analysis.

  11. A comparison between John Dewey's theory of inquiry and Jean Piaget's genetic analysis of intelligence.

    Science.gov (United States)

    Seltzer, E

    1977-06-01

    This article compares John Dewey's theory of inquiry with Jean Piaget's analysis of the mechanisms implied in the increase of knowledge. The sources for this paper are Dewey's studies on logic and the theory of inquiry and Piaget's historical-critical and psychogenetic investigations. Three major conclusions result from the comparison: first, there are significant convergences between the two theories; second, Piaget's developmental analysis makes explicit what is programmatic in Dewey's investigations; and, finally, Piaget is incorrect in characterizing Dewey's pragmatism as a method that does not meet the criteria of intelligent activity.

  12. Competent Geometric Semantic Genetic Programming for Symbolic Regression and Boolean Function Synthesis.

    Science.gov (United States)

    Pawlak, Tomasz P; Krawiec, Krzysztof

    2017-02-16

    Program semantics is a promising recent research thread in Genetic Programming (GP). Over a dozen of semantic-aware search, selection, and initialization operators for GP have been proposed to date. Some of those operators are designed to exploit the geometric properties of semantic space, while some others focus on making offspring effective, i.e., semantically different from their parents. Only a small fraction of previous works aimed at addressing both these features simultaneously. In this paper, we propose a suite of competent operators that combine effectiveness with geometry for population initialization, mate selection, mutation and crossover. We present a theoretical rationale behind these operators and compare them experimentally to operators known from literature on symbolic regression and Boolean function synthesis benchmarks. We analyze each operator in isolation as well as verify how they fare together in an evolutionary run, concluding that the competent operators are superior on a wide range of performance indicators, including best-of-run fitness, test-set fitness, and program size.

  13. Binary Image Classification: A Genetic Programming Approach to the Problem of Limited Training Instances.

    Science.gov (United States)

    Al-Sahaf, Harith; Zhang, Mengjie; Johnston, Mark

    2016-01-01

    In the computer vision and pattern recognition fields, image classification represents an important yet difficult task. It is a challenge to build effective computer models to replicate the remarkable ability of the human visual system, which relies on only one or a few instances to learn a completely new class or an object of a class. Recently we proposed two genetic programming (GP) methods, one-shot GP and compound-GP, that aim to evolve a program for the task of binary classification in images. The two methods are designed to use only one or a few instances per class to evolve the model. In this study, we investigate these two methods in terms of performance, robustness, and complexity of the evolved programs. We use ten data sets that vary in difficulty to evaluate these two methods. We also compare them with two other GP and six non-GP methods. The results show that one-shot GP and compound-GP outperform or achieve results comparable to competitor methods. Moreover, the features extracted by these two methods improve the performance of other classifiers with handcrafted features and those extracted by a recently developed GP-based method in most cases.

  14. On the Predictability of Risk Box Approach by Genetic Programming Method for Bankruptcy Prediction

    Directory of Open Access Journals (Sweden)

    Alireza Bahiraie

    2009-01-01

    Full Text Available Problem statement: Theoretical based data representation is an important tool for model selection and interpretations in bankruptcy analysis since the numerical representation are much less transparent. Some methodological problems concerning financial ratios such as non-proportionality, non-asymetricity, non-scalicity are solved in this study and we presented a complementary technique for empirical analysis of financial ratios and bankruptcy risk. Approach: This study presented new geometric technique for empirical analysis of bankruptcy risk using financial ratios. Within this framework, we proposed the use of a new ratio representation which named Risk Box measure (RB. We demonstrated the application of this geometric approach for variable representation, data visualization and financial ratios at different stages of corporate bankruptcy prediction models based on financial balance sheet ratios. These stages were the selection of variables (predictors, accuracy of each estimation model and the representation of each model for transformed and common ratios. Results: We provided evidence of extent to which changes in values of this index were associated with changes in each axis values and how this may alter our economic interpretation of changes in the patterns and direction of risk components. Results of Genetic Programming (GP models were compared as different classification models and results showed the classifiers outperform by modified ratios. Conclusion/Recommendations: In this study, a new dimension to risk measurement and data representation with the advent of the Share Risk method (SR was proposed. Genetic programming method is substantially superior to the traditional methods such as MDA or Logistic method. It was strongly suggested the use of SR methodology for ratio analysis, which provided a conceptual and complimentary methodological solution to many problems associated with the use of ratios. Respectively, GP will provide

  15. A QUALITATIVE METHODOLOGY FOR THEORY ELUCIDATION, EXPLICATION, AND DEVELOPMENT APPLIED WITHIN AN INTENSIVE GROUP PSYCHOTHERAPY PROGRAM

    Directory of Open Access Journals (Sweden)

    Jaime Williams

    2012-04-01

    Full Text Available Mental health day treatment (MHDT programs provide intensive group psychotherapy for patients with psychiatric pathology complicated by personality disorder. Recently, researchers have begun to examine specific components of these programs. Of importance is the theoretical rationale, which may be challenging to understand given the complexity of the treatment. The purpose of this project was to investigate the theory of one MHDT program. Community-based participatory research was chosen and accordingly, all stages of the project were collaborative with the MHDT clinical team. We engaged in a six-month, iterative process of weekly action-reflection cycles wherein material was discussed, analyzed for themes, and the findings presented back to the team to further the conversation. Results summarize this program’s Theories of Dysfunction and Therapeutic Change, which were primarily psychodynamic, but also integrative through assimilation of elements from other paradigms. Usefulness of the research process is discussed and recommendations are provided for others wishing to undergo a similar process.

  16. Reducing cyberbullying: A theory of reasoned action-based video prevention program for college students.

    Science.gov (United States)

    Doane, Ashley N; Kelley, Michelle L; Pearson, Matthew R

    2016-01-01

    Few studies have evaluated the effectiveness of cyberbullying prevention/intervention programs. The goals of the present study were to develop a Theory of Reasoned Action (TRA)-based video program to increase cyberbullying knowledge (1) and empathy toward cyberbullying victims (2), reduce favorable attitudes toward cyberbullying (3), decrease positive injunctive (4) and descriptive norms about cyberbullying (5), and reduce cyberbullying intentions (6) and cyberbullying behavior (7). One hundred sixty-seven college students were randomly assigned to an online video cyberbullying prevention program or an assessment-only control group. Immediately following the program, attitudes and injunctive norms for all four types of cyberbullying behavior (i.e., unwanted contact, malice, deception, and public humiliation), descriptive norms for malice and public humiliation, empathy toward victims of malice and deception, and cyberbullying knowledge significantly improved in the experimental group. At one-month follow-up, malice and public humiliation behavior, favorable attitudes toward unwanted contact, deception, and public humiliation, and injunctive norms for public humiliation were significantly lower in the experimental than the control group. Cyberbullying knowledge was significantly higher in the experimental than the control group. These findings demonstrate a brief cyberbullying video is capable of improving, at one-month follow-up, cyberbullying knowledge, cyberbullying perpetration behavior, and TRA constructs known to predict cyberbullying perpetration. Considering the low cost and ease with which a video-based prevention/intervention program can be delivered, this type of approach should be considered to reduce cyberbullying.

  17. Posture management program based on theory of planned behavior for adolescents with mild idiopathic scoliosis.

    Science.gov (United States)

    Choi, Jihea; Kim, Hee Soon; Kim, Gwang Suk; Lee, Hyejung; Jeon, Hye-Seon; Chung, Kyong-Mee

    2013-09-01

    The purpose of this study was to evaluate the effects of a devised posture management program based on the Theory of Planned Behavior in adolescents with mild idiopathic scoliosis. A quasi-experimental study was conducted. It involved a nonequivalent comparison group design with pretest and posttest. Forty-four female adolescents with mild idiopathic scoliosis participated; data from 35 participants (20 for the test group, 15 for the control group) were used for the final analyses. The devised posture management program ran for 6 weeks. Posture management behavioral determinants (attitude, subjective norms, perceived behavioral control, and behavioral intention) as cognitive outcomes and muscular strength and flexibility as physical outcomes were measured three times: at baseline, week 6 and week 8. Cobb's angle as another physical outcome was measured twice: at baseline and week 8. Descriptive analysis, repeated measures analysis of variance and t test were used for data analyses. Attitude, perceived control, and behavioral intention were consistently enhanced by the posture management program. The intervention increased flexibility and muscular strength and decreased Cobb's angle, which reduced spinal curvature. Frequency of posture management exercise showed a gradual increase in the test group. The results indicate that the posture management program is effective in maintaining posture management behavior in adolescents with mild idiopathic scoliosis for both cognitive and physical outcomes. The posture management program should be helpful in expanding the role of school nurses in improving the health status of adolescents with mild idiopathic scoliosis. Copyright © 2013. Published by Elsevier B.V.

  18. Genetic Programming for the Generation of Crisp and Fuzzy Rule Bases in Classification and Diagnosis of Medical Data

    DEFF Research Database (Denmark)

    Dounias, George; Tsakonas, Athanasios; Jantzen, Jan;

    2002-01-01

    This paper demonstrates two methodologies for the construction of rule-based systems in medical decision making. The first approach consists of a method combining genetic programming and heuristic hierarchical rule-base construction. The second model is composed by a strongly-typed genetic progra...... systems. Comparisons on the system's comprehensibility and the transparency are included. These comparisons include for the Aphasia domain, previous work consisted of two neural network models....

  19. Applying Monte Carlo Concept and Linear Programming in Modern Portfolio Theory to Obtain Best Weighting Structure

    Directory of Open Access Journals (Sweden)

    Tumpal Sihombing

    2013-01-01

    Full Text Available The world is entering the era of recession when the trend is bearish and market is not so favorable. The capital markets in every major country were experiencing great amount of loss and people suffered in their investment. The Jakarta Composite Index (JCI has shown a great downturn for the past one year but the trend bearish year of the JCI. Therefore, rational investors should consider restructuring their portfolio to set bigger proportion in bonds and cash instead of stocks. Investors can apply modern portfolio theory by Harry Markowitz to find the optimum asset allocation for their portfolio. Higher return is always associated with higher risk. This study shows investors how to find out the lowest risk of a portfolio investment by providing them with several structures of portfolio weighting. By this way, investor can compare and make the decision based on risk-return consideration and opportunity cost as well. Keywords: Modern portfolio theory, Monte Carlo, linear programming

  20. Partial discharge localization in power transformers based on the sequential quadratic programming-genetic algorithm adopting acoustic emission techniques

    Science.gov (United States)

    Liu, Hua-Long; Liu, Hua-Dong

    2014-10-01

    Partial discharge (PD) in power transformers is one of the prime reasons resulting in insulation degradation and power faults. Hence, it is of great importance to study the techniques of the detection and localization of PD in theory and practice. The detection and localization of PD employing acoustic emission (AE) techniques, as a kind of non-destructive testing, plus due to the advantages of powerful capability of locating and high precision, have been paid more and more attention. The localization algorithm is the key factor to decide the localization accuracy in AE localization of PD. Many kinds of localization algorithms exist for the PD source localization adopting AE techniques including intelligent and non-intelligent algorithms. However, the existed algorithms possess some defects such as the premature convergence phenomenon, poor local optimization ability and unsuitability for the field applications. To overcome the poor local optimization ability and easily caused premature convergence phenomenon of the fundamental genetic algorithm (GA), a new kind of improved GA is proposed, namely the sequence quadratic programming-genetic algorithm (SQP-GA). For the hybrid optimization algorithm, SQP-GA, the sequence quadratic programming (SQP) algorithm which is used as a basic operator is integrated into the fundamental GA, so the local searching ability of the fundamental GA is improved effectively and the premature convergence phenomenon is overcome. Experimental results of the numerical simulations of benchmark functions show that the hybrid optimization algorithm, SQP-GA, is better than the fundamental GA in the convergence speed and optimization precision, and the proposed algorithm in this paper has outstanding optimization effect. At the same time, the presented SQP-GA in the paper is applied to solve the ultrasonic localization problem of PD in transformers, then the ultrasonic localization method of PD in transformers based on the SQP-GA is proposed. And

  1. Genetic and Cultural Deficit Theories: Two Sides of the Same Racist Coin.

    Science.gov (United States)

    Persell, Caroline Hodges

    1981-01-01

    Examines the current models (genetic-deficit and cultural-deprivation) which explain IQ and achievement differences between members of the dominant and nondominant cultures. Concludes that both paradigms place blame on children and their families, and divert attention from the need to equalize wealth and power. (DA)

  2. Quantitative genetics theory for genomic selection and efficiency of breeding value prediction in open-pollinated populations

    Directory of Open Access Journals (Sweden)

    José Marcelo Soriano Viana

    2016-06-01

    Full Text Available ABSTRACT To date, the quantitative genetics theory for genomic selection has focused mainly on the relationship between marker and additive variances assuming one marker and one quantitative trait locus (QTL. This study extends the quantitative genetics theory to genomic selection in order to prove that prediction of breeding values based on thousands of single nucleotide polymorphisms (SNPs depends on linkage disequilibrium (LD between markers and QTLs, assuming dominance. We also assessed the efficiency of genomic selection in relation to phenotypic selection, assuming mass selection in an open-pollinated population, all QTLs of lower effect, and reduced sample size, based on simulated data. We show that the average effect of a SNP substitution is proportional to LD measure and to average effect of a gene substitution for each QTL that is in LD with the marker. Weighted (by SNP frequencies and unweighted breeding value predictors have the same accuracy. Efficiency of genomic selection in relation to phenotypic selection is inversely proportional to heritability. Accuracy of breeding value prediction is not affected by the dominance degree and the method of analysis, however, it is influenced by LD extent and magnitude of additive variance. The increase in the number of markers asymptotically improved accuracy of breeding value prediction. The decrease in the sample size from 500 to 200 did not reduce considerably accuracy of breeding value prediction.

  3. Automated synthesis of both the topology and numerical parameters for seven patented optical lens systems using genetic programming

    Science.gov (United States)

    Jones, Lee W.; Al-Sakran, Sameer H.; Koza, John R.

    2005-08-01

    This paper describes how genetic programming was used as an automated invention machine to synthesize both the topology and numerical parameters for seven previously patented optical lens systems, including one aspherical system and one issued in the 21st-century. Two of the evolved optical lens systems infringe the claims of the patents and the others are novel solutions that satisfy the design goals stated in the patent. The automatic synthesis was done "from scratch"--that is, without starting from a pre-existing good design and without pre-specifying the number of lenses, the topological layout of the lenses, or the numerical parameters of the lenses. Genetic programming is a form of evolutionary computation used to automatically solve problems. It starts from a high-level statement of what needs to be done and progressively breeds a population of candidate individuals over many generations using the principle of Darwinian natural selection and genetic recombination. The paper describes how genetic programming created eyepieces that duplicated the functionality of seven previously patented lens systems. The seven designs were created in a substantially similar and routine way, suggesting that the use of genetic programming in the automated design of both the topology and numerical parameters for optical lens systems may have widespread utility.

  4. Using Fuzzy Gaussian Inference and Genetic Programming to Classify 3D Human Motions

    Science.gov (United States)

    Khoury, Mehdi; Liu, Honghai

    This research introduces and builds on the concept of Fuzzy Gaussian Inference (FGI) (Khoury and Liu in Proceedings of UKCI, 2008 and IEEE Workshop on Robotic Intelligence in Informationally Structured Space (RiiSS 2009), 2009) as a novel way to build Fuzzy Membership Functions that map to hidden Probability Distributions underlying human motions. This method is now combined with a Genetic Programming Fuzzy rule-based system in order to classify boxing moves from natural human Motion Capture data. In this experiment, FGI alone is able to recognise seven different boxing stances simultaneously with an accuracy superior to a GMM-based classifier. Results seem to indicate that adding an evolutionary Fuzzy Inference Engine on top of FGI improves the accuracy of the classifier in a consistent way.

  5. Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Palika Chopra

    2016-01-01

    Full Text Available An effort has been made to develop concrete compressive strength prediction models with the help of two emerging data mining techniques, namely, Artificial Neural Networks (ANNs and Genetic Programming (GP. The data for analysis and model development was collected at 28-, 56-, and 91-day curing periods through experiments conducted in the laboratory under standard controlled conditions. The developed models have also been tested on in situ concrete data taken from literature. A comparison of the prediction results obtained using both the models is presented and it can be inferred that the ANN model with the training function Levenberg-Marquardt (LM for the prediction of concrete compressive strength is the best prediction tool.

  6. Modeling of Drilling Forces Based on Twist Drill Point Angles Using Multigene Genetic Programming

    Directory of Open Access Journals (Sweden)

    Myong-Il Kim

    2016-01-01

    Full Text Available The mathematical model was developed for predicting the influence of the drill point angles on the cutting forces in drilling with the twist drills, which was used to optimize those angles for reducing drilling forces. The approach was based on multigene genetic programming, for the training data, the grinding tests of twist drill were firstly conducted for the different drill point angles in Biglide parallel machine, and then drilling tests were performed on carbon fiber reinforced plastics using the grinded drills. The effectiveness of the proposed approach was verified through comparing with published data. It was found that the proposed model agreed well with the experimental data and was useful for improving the performance of twist drill.

  7. Genetic programming:  a novel method for the quantitative analysis of pyrolysis mass spectral data.

    Science.gov (United States)

    Gilbert, R J; Goodacre, R; Woodward, A M; Kell, D B

    1997-11-01

    A technique for the analysis of multivariate data by genetic programming (GP) is described, with particular reference to the quantitative analysis of orange juice adulteration data collected by pyrolysis mass spectrometry (PyMS). The dimensionality of the input space was reduced by ranking variables according to product moment correlation or mutual information with the outputs. The GP technique as described gives predictive errors equivalent to, if not better than, more widespread methods such as partial least squares and artificial neural networks but additionally can provide a means for easing the interpretation of the correlation between input and output variables. The described application demonstrates that by using the GP method for analyzing PyMS data the adulteration of orange juice with 10% sucrose solution can be quantified reliably over a 0-20% range with an RMS error in the estimate of ∼1%.

  8. Estimation of hydraulic jump on corrugated bed using artificial neural networks and genetic programming

    Institute of Scientific and Technical Information of China (English)

    Akram ABBASPOUR; Davood FARSADIZADEH; Mohammad Ali GHORBANI

    2013-01-01

    Artificial neural networks (ANNs) and genetic programming (GP) have recently been used for the estimation of hydraulic data. In this study, they were used as alternative tools to estimate the characteristics of hydraulic jumps, such as the free surface location and energy dissipation. The dimensionless hydraulic parameters, including jump depth, jump length, and energy dissipation, were determined as functions of the Froude number and the height and length of corrugations. The estimations of the ANN and GP models were found to be in good agreement with the measured data. The results of the ANN model were compared with those of the GP model, showing that the proposed ANN models are much more accurate than the GP models.

  9. Performance of Cost Assessment on Reusable Components for Software Development using Genetic Programming

    Directory of Open Access Journals (Sweden)

    T.Tejaswini

    2015-08-01

    Full Text Available Reusability is the quality of a piece of software, which enables it to be used again, be it partial, modified or complete. A wide range of modeling techniques have been proposed and applied for software quality predictions. Complexity and size metrics have been used to predict the number of defects in software components. Estimation of cost is important, during the process of software development. There are two main types of cost estimation approaches: algorithmic methods and non-algorithmic methods. In this work, using genetic programming which is a branch of evolutionary algorithms, a new algorithmic method is presented for software development cost estimation, using the implementation of this method; new formulas were obtained for software development cost estimation in which reusability of components is given priority. After evaluation of these formulas, the mean and standard deviation of the magnitude of relative error is better than related algorithmic methods such as COCOMO formulas.

  10. Statistical studies in genetic toxicology: a perspective from the U.S. National Toxicology Program.

    Science.gov (United States)

    Margolin, B H

    1985-11-01

    This paper surveys recent, as yet unpublished, statistical studies arising from research in genetic toxicology within the U.S. National Toxicology Program (NTP). These studies all involve analyses of data from Ames Salmonella/microsome mutagenicity tests, but the statistical methodologies are broadly applicable. Three issues are addressed: First, what is a tenable sampling model for Ames test data, and how does one best test the adequacy of the Poisson sampling assumption? Second, given that nonmonotone dose-response curves are fairly common in the Salmonella assay, what new statistical techniques or modifications of existing ones seem appropriate to accommodate to this reality? Finally, an intriguing question: How can the extensive NTP Ames test data base be used to assess the characteristics of any mutagen-nonmutagen decision rule? The last issue is illustrated with the commonly used "two-times background" rule.

  11. Evolving Rule-Based Systems in two Medical Domains using Genetic Programming

    DEFF Research Database (Denmark)

    Tsakonas, A.; Dounias, G.; Jantzen, Jan;

    2004-01-01

    We demonstrate, compare and discuss the application of two genetic programming methodologies for the construction of rule-based systems in two medical domains: the diagnosis of Aphasia's subtypes and the classification of Pap-Smear Test examinations. The first approach consists of a scheme...... the classification between all common types. A third model consisting of a GP-generated fuzzy rule-based system is tested on the same field. In the classification of Pap-Smear Test examinations, a crisp rule-based system is constructed. Results denote the effectiveness of the proposed systems. Comments...... and comparisons are made between the proposed methods and previous attempts on the selected fields of application....

  12. On the Performance of Different Genetic Programming Approaches for the SORTING Problem.

    Science.gov (United States)

    Wagner, Markus; Neumann, Frank; Urli, Tommaso

    2015-01-01

    In genetic programming, the size of a solution is typically not specified in advance, and solutions of larger size may have a larger benefit. The flexibility often comes at the cost of the so-called bloat problem: individuals grow without providing additional benefit to the quality of solutions, and the additional elements can block the optimization process. Consequently, problems that are relatively easy to optimize cannot be handled by variable-length evolutionary algorithms. In this article, we analyze different single- and multiobjective algorithms on the sorting problem, a problem that typically lacks independent and additive fitness structures. We complement the theoretical results with comprehensive experiments to indicate the tightness of existing bounds, and to indicate bounds where theoretical results are missing.

  13. Robust automatic segmentation of corneal layer boundaries in SDOCT images using graph theory and dynamic programming.

    Science.gov (United States)

    Larocca, Francesco; Chiu, Stephanie J; McNabb, Ryan P; Kuo, Anthony N; Izatt, Joseph A; Farsiu, Sina

    2011-06-01

    Segmentation of anatomical structures in corneal images is crucial for the diagnosis and study of anterior segment diseases. However, manual segmentation is a time-consuming and subjective process. This paper presents an automatic approach for segmenting corneal layer boundaries in Spectral Domain Optical Coherence Tomography images using graph theory and dynamic programming. Our approach is robust to the low-SNR and different artifact types that can appear in clinical corneal images. We show that our method segments three corneal layer boundaries in normal adult eyes more accurately compared to an expert grader than a second grader-even in the presence of significant imaging outliers.

  14. Genetic and epigenetic catalysts in early-life programming of adult cardiometabolic disorders

    Directory of Open Access Journals (Sweden)

    Estampador AC

    2014-12-01

    Full Text Available Angela C Estampador,1,2 Paul W Franks1,3,4 1Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital Malmö, Malmö, Sweden; 2Department of Endocrinology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark; 3Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden; 4Department of Nutrition, Harvard School of Public Health, Boston, MA, USA Abstract: Evidence has emerged across the past few decades that the lifetime risk of developing morbidities like type 2 diabetes, obesity, and cardiovascular disease may be influenced by exposures that occur in utero and in childhood. Developmental abnormalities are known to occur at various stages in fetal growth. Epidemiological and mechanistic studies have sought to delineate developmental processes and plausible risk factors influencing pregnancy outcomes and later health. Whether these observations reflect causal processes or are confounded by genetic and social factors remains unclear, although animal (and some human studies suggest that epigenetic programming events may be involved. Regardless of the causal basis to observations of early-life risk factors and later disease risk, the fact that such associations exist and that they are of a fairly large magnitude justifies further research around this topic. Furthermore, additional information is needed to substantiate public health guidelines on lifestyle behaviors during pregnancy to improve infant health outcomes. Indeed, lifestyle intervention clinical trials in pregnancy are now coming online, where materials and data are being collected that should facilitate understanding of the causal nature of intrauterine exposures related with gestational weight gain, such as elevated maternal blood glucose concentrations. In this review, we provide an overview of these concepts. Keywords: early-life, epigenetic, programming, pregnancy, cardiometabolic

  15. Genetic Programming Applied to Base-Metal Prospectivity Mapping in the Aravalli Province, India

    Science.gov (United States)

    Lewkowski, Christopher; Porwal, Alok; González-Álvarez, Ignacio

    2010-05-01

    Genetic Programming Applied to Base-Metal Prospectivity Mapping in the Aravalli Province, India Mineral prospectivity mapping of an area involves demarcation of potentially mineralized zones based on geologic features associated with the targeted mineral deposits. These features are sometimes directly observable and mapped; more often, their presence is inferred from their responses in various geoscience datasets, which are appropriately processed, generally in a GIS software environment, to derive their spatial proxies, also called predictor maps layers. Most approaches to mineral prospectivity mapping use mathematical models to approximate the relation between predictor map layers and the presence (or absence) of the targeted mineral deposits and to label unique combinations of spatially coincident predictor map layers as mineralized or barren. Essentially, the procedure involves recognizing and distinguishing the patterns of predictor map layers associated with mineralized locations from those associated with barren locations. Machine learning algorithms such as neural networks, support vector machines, and Bayesian classifiers are highly efficient pattern recognizers and classifiers. They are being increasingly applied to mineral prospectivity mapping, within or outside a GIS environment. However, most of these algorithms have a black-box-type implementation, that is, the output of these models do not generate new conceptual geological knowledge about the relative importance of various variables and their mutual relationships. Genetic Programming (GP) is a category of machine learning algorithms that address this problem effectively. In addition to generating the output classification map, GP also generates a set of rules that reveal the mutual relationships of the predictor variables, based on empirical analyses. These rules can be used to validate conceptual knowledge against empirical data, and also reveal new patterns in the data, resulting in new

  16. Disaggregating sorghum yield reductions under warming scenarios exposes narrow genetic diversity in US breeding programs.

    Science.gov (United States)

    Tack, Jesse; Lingenfelser, Jane; Jagadish, S V Krishna

    2017-08-29

    Historical adaptation of sorghum production to arid and semiarid conditions has provided promise regarding its sustained productivity under future warming scenarios. Using Kansas field-trial sorghum data collected from 1985 to 2014 and spanning 408 hybrid cultivars, we show that sorghum productivity under increasing warming scenarios breaks down. Through extensive regression modeling, we identify a temperature threshold of 33 °C, beyond which yields start to decline. We show that this decline is robust across both field-trial and on-farm data. Moderate and higher warming scenarios of 2 °C and 4 °C resulted in roughly 17% and 44% yield reductions, respectively. The average reduction across warming scenarios from 1 to 5 °C is 10% per degree Celsius. Breeding efforts over the last few decades have developed high-yielding cultivars with considerable variability in heat resilience, but even the most tolerant cultivars did not offer much resilience to warming temperatures. This outcome points to two concerns regarding adaption to global warming, the first being that adaptation will not be as simple as producers' switching among currently available cultivars and the second being that there is currently narrow genetic diversity for heat resilience in US breeding programs. Using observed flowering dates and disaggregating heat-stress impacts, both pre- and postflowering stages were identified to be equally important for overall yields. These findings suggest the adaptation potential for sorghum under climate change would be greatly facilitated by introducing wider genetic diversity for heat resilience into ongoing breeding programs, and that there should be additional efforts to improve resilience during the preflowering phase.

  17. The aminoacyl-tRNA synthetases had only a marginal role in the origin of the organization of the genetic code: Evidence in favor of the coevolution theory.

    Science.gov (United States)

    Di Giulio, Massimo

    2017-11-07

    The coevolution theory of the origin of the genetic code suggests that the organization of the genetic code coevolved with the biosynthetic relationships between amino acids. The mechanism that allowed this coevolution was based on tRNA-like molecules on which-this theory-would postulate the biosynthetic transformations between amino acids to have occurred. This mechanism makes a prediction on how the role conducted by the aminoacyl-tRNA synthetases (ARSs), in the origin of the genetic code, should have been. Indeed, if the biosynthetic transformations between amino acids occurred on tRNA-like molecules, then there was no need to link amino acids to these molecules because amino acids were already charged on tRNA-like molecules, as the coevolution theory suggests. In spite of the fact that ARSs make the genetic code responsible for the first interaction between a component of nucleic acids and that of proteins, for the coevolution theory the role of ARSs should have been entirely marginal in the genetic code origin. Therefore, I have conducted a further analysis of the distribution of the two classes of ARSs and of their subclasses-in the genetic code table-in order to perform a falsification test of the coevolution theory. Indeed, in the case in which the distribution of ARSs within the genetic code would have been highly significant, then the coevolution theory would be falsified since the mechanism on which it is based would not predict a fundamental role of ARSs in the origin of the genetic code. I found that the statistical significance of the distribution of the two classes of ARSs in the table of the genetic code is low or marginal, whereas that of the subclasses of ARSs statistically significant. However, this is in perfect agreement with the postulates of the coevolution theory. Indeed, the only case of statistical significance-regarding the classes of ARSs-is appreciable for the CAG code, whereas for its complement-the UNN/NUN code-only a marginal

  18. FCJ-117 Four Regimes of Entropy: For an Ecology of Genetics and Biomorphic Media Theory

    Directory of Open Access Journals (Sweden)

    Matteo Pasquinelli

    2011-04-01

    Full Text Available This essay approaches the definition of media ecology from two opposite perspectives. On one hand, it tests the homogeneity of the biomimetic continuum, which supposes the mediascape as an extension of the biological realm. On the other, it analyses the biodigital continuum, which takes, for instance, digital code as a universal grammar for genetic code. The problematic relation between biological and technological paradigms and between linguistics and genetics is clarified with reference to Erwin Schrödinger’s concept of negative entropy. Four different regimes of entropic density are then suggested to describe the physical, biological, technological, and cognitive domains. On the basis of this ‘energetic geology’, a new ecology of machines is proposed.

  19. Genetic modulation of lipid profiles following lifestyle modification or metformin treatment: the Diabetes Prevention Program.

    Directory of Open Access Journals (Sweden)

    Toni I Pollin

    Full Text Available Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04-1 × 10(-17. Except for total HDL particles (r = -0.03, P = 0.26, all components of the lipid profile correlated with the GRS (partial |r| = 0.07-0.17, P = 5 × 10(-5-1 10(-19. The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE ± 0.22 mg/dl/allele, P = 8 × 10(-5, P(interaction = 0.02 in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE ± 0.22 mg/dl/allele, P = 0.35 or metformin (β = -0.03, SEE ± 0.22 mg/dl/allele, P = 0.90; P(interaction = 0.64 groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE ± 0.012 ln nmol/L/allele, P = 0.01, P(interaction = 0.01 but not in the placebo (β = -0.002, SEE ± 0.008 ln nmol/L/allele, P = 0.74 or metformin (β = +0.013, SEE ± 0.008 nmol/L/allele, P = 0.12; P(interaction = 0.24 groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss.

  20. Genetic modulation of lipid profiles following lifestyle modification or metformin treatment: the Diabetes Prevention Program.

    Science.gov (United States)

    Pollin, Toni I; Isakova, Tamara; Jablonski, Kathleen A; de Bakker, Paul I W; Taylor, Andrew; McAteer, Jarred; Pan, Qing; Horton, Edward S; Delahanty, Linda M; Altshuler, David; Shuldiner, Alan R; Goldberg, Ronald B; Florez, Jose C; Franks, Paul W

    2012-01-01

    Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS) based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR) lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04-1 × 10(-17)). Except for total HDL particles (r = -0.03, P = 0.26), all components of the lipid profile correlated with the GRS (partial |r| = 0.07-0.17, P = 5 × 10(-5)-1 10(-19)). The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE ± 0.22 mg/dl/allele, P = 8 × 10(-5), P(interaction) = 0.02) in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE ± 0.22 mg/dl/allele, P = 0.35) or metformin (β = -0.03, SEE ± 0.22 mg/dl/allele, P = 0.90; P(interaction) = 0.64) groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE ± 0.012 ln nmol/L/allele, P = 0.01, P(interaction) = 0.01) but not in the placebo (β = -0.002, SEE ± 0.008 ln nmol/L/allele, P = 0.74) or metformin (β = +0.013, SEE ± 0.008 nmol/L/allele, P = 0.12; P(interaction) = 0.24) groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss.

  1. Genetic Modulation of Lipid Profiles following Lifestyle Modification or Metformin Treatment: The Diabetes Prevention Program

    Science.gov (United States)

    Jablonski, Kathleen A.; de Bakker, Paul I. W.; Taylor, Andrew; McAteer, Jarred; Pan, Qing; Horton, Edward S.; Delahanty, Linda M.; Altshuler, David; Shuldiner, Alan R.; Goldberg, Ronald B.; Florez, Jose C.; Bray, George A.; Culbert, Iris W.; Champagne, Catherine M.; Eberhardt, Barbara; Greenway, Frank; Guillory, Fonda G.; Herbert, April A.; Jeffirs, Michael L.; Kennedy, Betty M.; Lovejoy, Jennifer C.; Morris, Laura H.; Melancon, Lee E.; Ryan, Donna; Sanford, Deborah A.; Smith, Kenneth G.; Smith, Lisa L.; Amant, Julia A. St.; Tulley, Richard T.; Vicknair, Paula C.; Williamson, Donald; Zachwieja, Jeffery J.; Polonsky, Kenneth S.; Tobian, Janet; Ehrmann, David; Matulik, Margaret J.; Clark, Bart; Czech, Kirsten; DeSandre, Catherine; Hilbrich, Ruthanne; McNabb, Wylie; Semenske, Ann R.; Caro, Jose F.; Watson, Pamela G.; Goldstein, Barry J.; Smith, Kellie A.; Mendoza, Jewel; Liberoni, Renee; Pepe, Constance; Spandorfer, John; Donahue, Richard P.; Goldberg, Ronald B.; Prineas, Ronald; Rowe, Patricia; Calles, Jeanette; Cassanova-Romero, Paul; Florez, Hermes J.; Giannella, Anna; Kirby, Lascelles; Larreal, Carmen; McLymont, Valerie; Mendez, Jadell; Ojito, Juliet; Perry, Arlette; Saab, Patrice; Haffner, Steven M.; Montez, Maria G.; Lorenzo, Carlos; Martinez, Arlene; Hamman, Richard F.; Nash, Patricia V.; Testaverde, Lisa; Anderson, Denise R.; Ballonoff, Larry B.; Bouffard, Alexis; Calonge, B. Ned; Delve, Lynne; Farago, Martha; Hill, James O.; Hoyer, Shelley R.; Jortberg, Bonnie T.; Lenz, Dione; Miller, Marsha; Price, David W.; Regensteiner, Judith G.; Seagle, Helen; Smith, Carissa M.; Steinke, Sheila C.; VanDorsten, Brent; Horton, Edward S.; Lawton, Kathleen E.; Arky, Ronald A.; Bryant, Marybeth; Burke, Jacqueline P.; Caballero, Enrique; Callaphan, Karen M.; Ganda, Om P.; Franklin, Therese; Jackson, Sharon D.; Jacobsen, Alan M.; Jacobsen, Alan M.; Kula, Lyn M.; Kocal, Margaret; Malloy, Maureen A.; Nicosia, Maryanne; Oldmixon, Cathryn F.; Pan, Jocelyn; Quitingon, Marizel; Rubtchinsky, Stacy; Seely, Ellen W.; Schweizer, Dana; Simonson, Donald; Smith, Fannie; Solomon, Caren G.; Warram, James; Kahn, Steven E.; Montgomery, Brenda K.; Fujimoto, Wilfred; Knopp, Robert H.; Lipkin, Edward W.; Marr, Michelle; Trence, Dace; Kitabchi, Abbas E.; Murphy, Mary E.; Applegate, William B.; Bryer-Ash, Michael; Frieson, Sandra L.; Imseis, Raed; Lambeth, Helen; Lichtermann, Lynne C.; Oktaei, Hooman; Rutledge, Lily M.K.; Sherman, Amy R.; Smith, Clara M.; Soberman, Judith E.; Williams-Cleaves, Beverly; Metzger, Boyd E.; Johnson, Mariana K.; Behrends, Catherine; Cook, Michelle; Fitzgibbon, Marian; Giles, Mimi M.; Heard, Deloris; Johnson, Cheryl K.H.; Larsen, Diane; Lowe, Anne; Lyman, Megan; McPherson, David; Molitch, Mark E.; Pitts, Thomas; Reinhart, Renee; Roston, Susan; Schinleber, Pamela A.; Nathan, David M.; McKitrick, Charles; Turgeon, Heather; Abbott, Kathy; Anderson, Ellen; Bissett, Laurie; Cagliero, Enrico; Florez, Jose C.; Delahanty, Linda; Goldman, Valerie; Poulos, Alexandra; Olefsky, Jerrold M.; Carrion-Petersen, Mary Lou; Barrett-Connor, Elizabeth; Edelman, Steven V.; Henry, Robert R.; Horne, Javiva; Janesch, Simona Szerdi; Leos, Diana; Mudaliar, Sundar; Polonsky, William; Smith, Jean; Vejvoda, Karen; Pi-Sunyer, F. Xavier; Lee, Jane E.; Allison, David B.; Aronoff, Nancy J.; Crandall, Jill P.; Foo, Sandra T.; Pal, Carmen; Parkes, Kathy; Pena, Mary Beth; Rooney, Ellen S.; Wye, Gretchen E.H. Van; Viscovich, Kristine A.; Marrero, David G.; Prince, Melvin J.; Kelly, Susie M.; Dotson, Yolanda F.; Fineberg, Edwin S.; Guare, John C; Hadden, Angela M.; Ignaut, James M.; Jackson, Marcia L.; Kirkman, Marion S.; Mather, Kieren J.; Porter, Beverly D.; Roach, Paris J.; Rowland, Nancy D.; Wheeler, Madelyn L.; Ratner, Robert E.; Youssef, Gretchen; Shapiro, Sue; Bavido-Arrage, Catherine; Boggs, Geraldine; Bronsord, Marjorie; Brown, Ernestine; Cheatham, Wayman W.; Cola, Susan; Evans, Cindy; Gibbs, Peggy; Kellum, Tracy; Levatan, Claresa; Nair, Asha K.; Passaro, Maureen; Uwaifo, Gabriel; Saad, Mohammed F.; Budget, Maria; Jinagouda, Sujata; Akbar, Khan; Conzues, Claudia; Magpuri, Perpetua; Ngo, Kathy; Rassam, Amer; Waters, Debra; Xapthalamous, Kathy; Santiago, Julio V.; Dagogo-Jack, Samuel; White, Neil H.; Das, Samia; Santiago, Ana; Brown, Angela; Fisher, Edwin; Hurt, Emma; Jones, Tracy; Kerr, Michelle; Ryder, Lucy; Wernimont, Cormarie; Saudek, Christopher D.; Bradley, Vanessa; Sullivan, Emily; Whittington, Tracy; Abbas, Caroline; Brancati, Frederick L.; Clark, Jeanne M.; Charleston, Jeanne B.; Freel, Janice; Horak, Katherine; Jiggetts, Dawn; Johnson, Deloris; Joseph, Hope; Loman, Kimberly; Mosley, Henry; Rubin, Richard R.; Samuels, Alafia; Stewart, Kerry J.; Williamson, Paula; Schade, David S.; Adams, Karwyn S.; Johannes, Carolyn; Atler, Leslie F.; Boyle, Patrick J.; Burge, Mark R.; Canady, Janene L.; Chai, Lisa; Gonzales, Ysela; Hernandez-McGinnis, Doris A.; Katz, Patricia; King, Carolyn; Rassam, Amer; Rubinchik, Sofya; Senter, Willette; Waters, Debra; Shamoon, Harry; Brown, Janet O.; Adorno, Elsie; Cox, Liane; Crandall, Jill; Duffy, Helena; Engel, Samuel; Friedler, Allison; Howard-Century, Crystal J.; Kloiber, Stacey; Longchamp, Nadege; Martinez, Helen; Pompi, Dorothy; Scheindlin, Jonathan; Violino, Elissa; Walker, Elizabeth; Wylie-Rosett, Judith; Zimmerman, Elise; Zonszein, Joel; Orchard, Trevor; Wing, Rena R.; Koenning, Gaye; Kramer, M. Kaye; Barr, Susan; Boraz, Miriam; Clifford, Lisa; Culyba, Rebecca; Frazier, Marlene; Gilligan, Ryan; Harrier, Susan; Harris, Louann; Jeffries, Susan; Kriska, Andrea; Manjoo, Qurashia; Mullen, Monica; Noel, Alicia; Otto, Amy; Semler, Linda; Smith, Cheryl F.; Smith, Marie; Venditti, Elizabeth; Weinzierl, Valarie; Williams, Katherine V.; Wilson, Tara; Arakaki, Richard F.; Latimer, Renee W.; Baker-Ladao, Narleen K.; Beddow, Ralph; Dias, Lorna; Inouye, Jillian; Mau, Marjorie K.; Mikami, Kathy; Mohideen, Pharis; Odom, Sharon K.; Perry, Raynette U.; Knowler, William C.; Cooeyate, Norman; Hoskin, Mary A.; Percy, Carol A.; Acton, Kelly J.; Andre, Vickie L.; Barber, Rosalyn; Begay, Shandiin; Bennett, Peter H.; Benson, Mary Beth; Bird, Evelyn C.; Broussard, Brenda A.; Chavez, Marcella; Dacawyma, Tara; Doughty, Matthew S.; Duncan, Roberta; Edgerton, Cyndy; Ghahate, Jacqueline M.; Glass, Justin; Glass, Martia; Gohdes, Dorothy; Grant, Wendy; Hanson, Robert L.; Horse, Ellie; Ingraham, Louise E.; Jackson, Merry; Jay, Priscilla; Kaskalla, Roylen S.; Kessler, David; Kobus, Kathleen M.; Krakoff, Jonathan; Manus, Catherine; Michaels, Sara; Morgan, Tina; Nashboo, Yolanda; Nelson, Julie A.; Poirier, Steven; Polczynski, Evette; Reidy, Mike; Roumain, Jeanine; Rowse, Debra; Sangster, Sandra; Sewenemewa, Janet; Tonemah, Darryl; Wilson, Charlton; Yazzie, Michelle; Bain, Raymond; Fowler, Sarah; Brenneman, Tina; Abebe, Solome; Bamdad, Julie; Callaghan, Jackie; Edelstein, Sharon L.; Gao, Yuping; Grimes, Kristina L.; Grover, Nisha; Haffner, Lori; Jones, Steve; Jones, Tara L.; Katz, Richard; Lachin, John M.; Mucik, Pamela; Orlosky, Robert; Rochon, James; Sapozhnikova, Alla; Sherif, Hanna; Stimpson, Charlotte; Temprosa, Marinella; Walker-Murray, Fredricka; Marcovina, Santica; Strylewicz, Greg; Aldrich, F. Alan; O'Leary, Dan; Stamm, Elizabeth; Rautaharju, Pentti; Prineas, Ronald J.; Alexander, Teresa; Campbell, Charles; Hall, Sharon; Li, Yabing; Mills, Margaret; Pemberton, Nancy; Rautaharju, Farida; Zhang, Zhuming; Mayer-Davis, Elizabeth; Moran, Robert R.; Ganiats, Ted; David, Kristin; Sarkin, Andrew J.; Eastman, R.; Fradkin, Judith; Garfield, Sanford; Gregg, Edward; Zhang, Ping; Herman, William; Florez, Jose C.; Altshuler, David; de Bakker, Paul I.W.; Franks, Paul W.; Hanson, Robert L.; Jablonski, Kathleen; Knowler, William C.; McAteer, Jarred B.; Pollin, Toni I.; Shuldiner, Alan R.

    2012-01-01

    Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS) based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR) lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04–1×10−17). Except for total HDL particles (r = −0.03, P = 0.26), all components of the lipid profile correlated with the GRS (partial |r| = 0.07–0.17, P = 5×10−5–1×10−19). The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE±0.22 mg/dl/allele, P = 8×10−5, P interaction = 0.02) in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE±0.22 mg/dl/allele, P = 0.35) or metformin (β = −0.03, SEE±0.22 mg/dl/allele, P = 0.90; P interaction = 0.64) groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE±0.012 ln nmol/L/allele, P = 0.01, P interaction = 0.01) but not in the placebo (β = −0.002, SEE±0.008 ln nmol/L/allele, P = 0.74) or metformin (β = +0.013, SEE±0.008 nmol/L/allele, P = 0.12; P interaction = 0.24) groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss. PMID:22951888

  2. Qualitative data analysis using the n Vivo programe and the application of the methodology of grounded theory procedures

    Directory of Open Access Journals (Sweden)

    Niedbalski Jakub

    2012-02-01

    Full Text Available The main aim of the article is to identify the capabilities and constraints of using CAQDAS (Computer-Assisted Qualitative Data Analysis Software programs in qualitative data analysis. Our considerations are based on the personal experiences gained while conducting the research projects using the methodology of grounded theory (GT and the NVivo 8 program. In presented article we focusedon relations between the methodological principles of grounded theory and the technical possibilities of NVivo 8. The paper presents our opinion about the most important options available in NVivo 8 and their application in the studies based on the methodology of grounded theory.

  3. Evolution equation of population genetics: relation to the density-matrix theory of quasiparticles with general dispersion laws.

    Science.gov (United States)

    Bezák, V

    2003-02-01

    The Waxman-Peck theory of population genetics is discussed in regard of soil bacteria. Each bacterium is understood as a carrier of a phenotypic parameter p. The central objective is the calculation of the probability density with respect to p, Phi(p,t;p(0)), of the carriers living at time t>0, provided that initially at t(0)=0, all bacteria carried the phenotypic parameter p(0)=0. The theory involves two small parameters: the mutation probability mu and a parameter gamma involved in a function w(p) defining the fitness of the bacteria to survive the generation time tau and give birth to an offspring. The mutation from a state p to a state q is defined by a Gaussian with a dispersion sigma(2)(m). The author focuses our attention on a function phi(p,t) which determines uniquely the function Phi(p,t;p(0)) and satisfies a linear equation (Waxman's equation). The Green function of this equation is mathematically identical with the one-particle Bloch density matrix, where mu characterizes the order of magnitude of the potential energy. (In the x representation, the potential energy is proportional to the inverted Gaussian with the dispersion sigma(2)(m)). The author solves Waxman's equation in the standard style of a perturbation theory and discusses how the solution depends on the choice of the fitness function w(p). In a sense, the function c(p)=1-w(p)/w(0) is analogous to the dispersion function E(p) of fictitious quasiparticles. In contrast to Waxman's approximation, where c(p) was taken as a quadratic function, c(p) approximately gammap(2), the author exemplifies the problem with another function, c(p)=gamma[1-exp(-ap(2))], where gamma is small but a may be large. The author shows that the use of this function in the theory of the population genetics is the same as the use of a nonparabolic dispersion law E=E(p) in the density-matrix theory. With a general function c(p), the distribution function Phi(p,t;0) is composed of a delta-function component, N

  4. An evolution equation of the population genetics relation to the density-matrix theory of quasiparticles with general dispersion laws

    CERN Document Server

    Bezak, V

    2002-01-01

    The Waxman-Peck theory of the population genetics is discussed in regard of soil bacteria. Each bacterium is understood as a carrier of a phenotypic parameter p. The central aim is the calculation of the probability density with respect to p of the carriers living at time t>0. The theory involves two small parameters: the mutation probability $\\mu$ and a parameter $\\gamma$ involved in a function w(p) defining the fitness of the bacteria to survive the generation time $\\tau$ and give birth to offspring. The mutation from a state p to a state q is defined by a Gaussian. The author focuses attention on an equation generalizing Waxman's equation. The author solves this equation in the standard style of a perturbation theory and discusses how the solution depends on the choice of the fitness function w(p). In a sense, the function $c(p)=1-w(p)/w(0)$ is analogous to the dispersion function E(p) of fictitious quasiparticles. With a general function c(p), the distribution function ${\\mathit\\Phi}(p,t;0)$ is composed o...

  5. CONFERENCE SUMMARY--FROM THEORY TO PRACTICE. THE DESCRIPTION AND DEMONSTRATION OF A GUIDANCE PROGRAM IN ONE DISTRICT K-12.

    Science.gov (United States)

    Palo Alto Unified School District, CA.

    VARIOUS ASPECTS OF THE PALO ALTO GUIDANCE PROGRAM WERE PRESENTED AT THE CONFERENCE. THE OBJECTIVES OF THE PROGRAM WERE BASED ON THE BELIEF THAT GUIDANCE SHOULD FOSTER INDIVIDUALIZATION IN THE DEVELOPMENT OF ALL CHILDREN BY PROVIDING CONDITIONS WHICH WOULD ENSURE THIS INDIVIDUALIZATION. THESE TWO THEORETICAL CONSTRUCTS, REINFORCEMENT THEORY AND…

  6. Useful genetic sources of economic importance and their utlization in wheat-breeding programs in Pakistan.

    Science.gov (United States)

    Qureshi, S A

    Wheat breeders the world over have been utilizing genetic sources to tailor the varieties to meet ever-changing requirements. In the late 1940s Dr. Borlaug at CIMMYT recognized that further increase in yield would be possible only if lodging in the existing wheat varieties could be avoided, for which he began to look for a suitable source for dwarfness. The Japanese had developed semidwarf Norin strains through a series of crosses involving a local line, Daruma; American soft red winter variety, Fultz; and American hard red winter variety, Turkey Red. One of the Norin strains, Norin-10, was used in the breeding programs, first in Italy and then in the United States where Dr. Orville Vogel developed two to three semidwarf varieties. In 1953 Dr. Vogel supplied some F2 seeds of Norin-10 Brevor to the CIMMYT program in Mexico, where this source was employed extensively in the breeding rogram; a large number of varieties were developed, some of which worth mentioning are Pitic, Penjamo, Lerma, Sonora, Inia, Tobari, and Siete Cerros.

  7. Effects of genetic variants previously associated with fasting glucose and insulin in the Diabetes Prevention Program.

    Directory of Open Access Journals (Sweden)

    Jose C Florez

    Full Text Available Common genetic variants have been recently associated with fasting glucose and insulin levels in white populations. Whether these associations replicate in pre-diabetes is not known. We extended these findings to the Diabetes Prevention Program, a clinical trial in which participants at high risk for diabetes were randomized to placebo, lifestyle modification or metformin for diabetes prevention. We genotyped previously reported polymorphisms (or their proxies in/near G6PC2, MTNR1B, GCK, DGKB, GCKR, ADCY5, MADD, CRY2, ADRA2A, FADS1, PROX1, SLC2A2, GLIS3, C2CD4B, IGF1, and IRS1 in 3,548 Diabetes Prevention Program participants. We analyzed variants for association with baseline glycemic traits, incident diabetes and their interaction with response to metformin or lifestyle intervention. We replicated associations with fasting glucose at MTNR1B (P<0.001, G6PC2 (P = 0.002 and GCKR (P = 0.001. We noted impaired β-cell function in carriers of glucose-raising alleles at MTNR1B (P<0.001, and an increase in the insulinogenic index for the glucose-raising allele at G6PC2 (P<0.001. The association of MTNR1B with fasting glucose and impaired β-cell function persisted at 1 year despite adjustment for the baseline trait, indicating a sustained deleterious effect at this locus. We also replicated the association of MADD with fasting proinsulin levels (P<0.001. We detected no significant impact of these variants on diabetes incidence or interaction with preventive interventions. The association of several polymorphisms with quantitative glycemic traits is replicated in a cohort of high-risk persons. These variants do not have a detectable impact on diabetes incidence or response to metformin or lifestyle modification in the Diabetes Prevention Program.

  8. Effects of genetic variants previously associated with fasting glucose and insulin in the Diabetes Prevention Program.

    Science.gov (United States)

    Florez, Jose C; Jablonski, Kathleen A; McAteer, Jarred B; Franks, Paul W; Mason, Clinton C; Mather, Kieren; Horton, Edward; Goldberg, Ronald; Dabelea, Dana; Kahn, Steven E; Arakaki, Richard F; Shuldiner, Alan R; Knowler, William C

    2012-01-01

    Common genetic variants have been recently associated with fasting glucose and insulin levels in white populations. Whether these associations replicate in pre-diabetes is not known. We extended these findings to the Diabetes Prevention Program, a clinical trial in which participants at high risk for diabetes were randomized to placebo, lifestyle modification or metformin for diabetes prevention. We genotyped previously reported polymorphisms (or their proxies) in/near G6PC2, MTNR1B, GCK, DGKB, GCKR, ADCY5, MADD, CRY2, ADRA2A, FADS1, PROX1, SLC2A2, GLIS3, C2CD4B, IGF1, and IRS1 in 3,548 Diabetes Prevention Program participants. We analyzed variants for association with baseline glycemic traits, incident diabetes and their interaction with response to metformin or lifestyle intervention. We replicated associations with fasting glucose at MTNR1B (P<0.001), G6PC2 (P = 0.002) and GCKR (P = 0.001). We noted impaired β-cell function in carriers of glucose-raising alleles at MTNR1B (P<0.001), and an increase in the insulinogenic index for the glucose-raising allele at G6PC2 (P<0.001). The association of MTNR1B with fasting glucose and impaired β-cell function persisted at 1 year despite adjustment for the baseline trait, indicating a sustained deleterious effect at this locus. We also replicated the association of MADD with fasting proinsulin levels (P<0.001). We detected no significant impact of these variants on diabetes incidence or interaction with preventive interventions. The association of several polymorphisms with quantitative glycemic traits is replicated in a cohort of high-risk persons. These variants do not have a detectable impact on diabetes incidence or response to metformin or lifestyle modification in the Diabetes Prevention Program.

  9. Functional Genetic Screen to Identify Interneurons Governing Behaviorally Distinct Aspects of Drosophila Larval Motor Programs

    Directory of Open Access Journals (Sweden)

    Matt Q. Clark

    2016-07-01

    Full Text Available Drosophila larval crawling is an attractive system to study rhythmic motor output at the level of animal behavior. Larval crawling consists of waves of muscle contractions generating forward or reverse locomotion. In addition, larvae undergo additional behaviors, including head casts, turning, and feeding. It is likely that some neurons (e.g., motor neurons are used in all these behaviors, but the identity (or even existence of neurons dedicated to specific aspects of behavior is unclear. To identify neurons that regulate specific aspects of larval locomotion, we performed a genetic screen to identify neurons that, when activated, could elicit distinct motor programs. We used 165 Janelia CRM-Gal4 lines—chosen for sparse neuronal expression—to ectopically express the warmth-inducible neuronal activator TrpA1, and screened for locomotor defects. The primary screen measured forward locomotion velocity, and we identified 63 lines that had locomotion velocities significantly slower than controls following TrpA1 activation (28°. A secondary screen was performed on these lines, revealing multiple discrete behavioral phenotypes, including slow forward locomotion, excessive reverse locomotion, excessive turning, excessive feeding, immobile, rigid paralysis, and delayed paralysis. While many of the Gal4 lines had motor, sensory, or muscle expression that may account for some or all of the phenotype, some lines showed specific expression in a sparse pattern of interneurons. Our results show that distinct motor programs utilize distinct subsets of interneurons, and provide an entry point for characterizing interneurons governing different elements of the larval motor program.

  10. Mapping of the stochastic Lotka-Volterra model to models of population genetics and game theory

    Science.gov (United States)

    Constable, George W. A.; McKane, Alan J.

    2017-08-01

    The relationship between the M -species stochastic Lotka-Volterra competition (SLVC) model and the M -allele Moran model of population genetics is explored via timescale separation arguments. When selection for species is weak and the population size is large but finite, precise conditions are determined for the stochastic dynamics of the SLVC model to be mappable to the neutral Moran model, the Moran model with frequency-independent selection, and the Moran model with frequency-dependent selection (equivalently a game-theoretic formulation of the Moran model). We demonstrate how these mappings can be used to calculate extinction probabilities and the times until a species' extinction in the SLVC model.

  11. Genetic Program Based Data Mining of Fuzzy Decision Trees and Methods of Improving Convergence and Reducing Bloat

    Science.gov (United States)

    2007-04-01

    A data mining procedure for automatic determination of fuzzy decision tree structure using a genetic program (GP) is discussed. A GP is an algorithm...that evolves other algorithms or mathematical expressions. Innovative methods for accelerating convergence of the data mining procedure and reducing...Finally, additional methods that have been used to validate the data mining algorithm are referenced.

  12. Genetic Programmed Theory and Aging%遗传程序学说与衰老

    Institute of Scientific and Technical Information of China (English)

    李响; 梁杰; 罗少军

    2009-01-01

    随着社会人口的老龄化,衰老引起的疾病日益增加,同时人们对健康长寿的愿望也越来越强烈,因此,如何延缓衰老已经成为当今世界医学界最重要的课题之一.现代医学对衰老机制的研究涉及到很多方面,究其原因,遗传在影响衰老的进程中起重要作用.目前认为物种最高寿限与遗传相关.从遗传因素看,衰老是一连串基因激活和阻抑及其通过各自产物相互作用的结果.

  13. Game Theory, Adaptation, and Genetic Programming: Some Perspectives on Operations Research for Counter-IED

    Science.gov (United States)

    2011-06-01

    memes” ( Dawkins , 1989; Gabora, 1995; Boal & Schultz, 2007). As Weeks & Galunic (2003) point out: “Memes are the replicators in cultural evolution...Books. Dawkins , R. (1989), The Selfish Gene, 2 nd ed., Oxford University Press. Dekker, A.H. (2010), “Agent-Based Simulation for Counter-IED: A

  14. System network planning expansion using mathematical programming, genetic algorithms and tabu search

    Energy Technology Data Exchange (ETDEWEB)

    Sadegheih, A. [Department of Industrial Engineering, University of Yazd, P.O. Box 89195-741, Yazd (Iran); Drake, P.R. [E-Business and Operations Management Division, University of Liverpool Management School, University of Liverpool, Liverpool (United Kingdom)

    2008-06-15

    In this paper, system network planning expansion is formulated for mixed integer programming, a genetic algorithm (GA) and tabu search (TS). Compared with other optimization methods, GAs are suitable for traversing large search spaces, since they can do this relatively rapidly and because the use of mutation diverts the method away from local minima, which will tend to become more common as the search space increases in size. GA's give an excellent trade off between solution quality and computing time and flexibility for taking into account specific constraints in real situations. TS has emerged as a new, highly efficient, search paradigm for finding quality solutions to combinatorial problems. It is characterized by gathering knowledge during the search and subsequently profiting from this knowledge. The attractiveness of the technique comes from its ability to escape local optimality. The cost function of this problem consists of the capital investment cost in discrete form, the cost of transmission losses and the power generation costs. The DC load flow equations for the network are embedded in the constraints of the mathematical model to avoid sub-optimal solutions that can arise if the enforcement of such constraints is done in an indirect way. The solution of the model gives the best line additions and also provides information regarding the optimal generation at each generation point. This method of solution is demonstrated on the expansion of a 10 bus bar system to 18 bus bars. Finally, a steady-state genetic algorithm is employed rather than generational replacement, also uniform crossover is used. (author)

  15. Automatic Generation of English-Japanese Translation Pattern Utilizing Genetic Programming Technique

    Science.gov (United States)

    Matsumura, Koki; Tamekuni, Yuji; Kimura, Shuhei

    There are a lot of constructional differences in an English-Japanese phrase template, and that often makes the act of translation difficult. Moreover, there exist various and tremendous phrase templates and sentence to be refered to. It is not easy to prepare the corpus that covers the all. Therefore, it is very significant to generate the translation pattern of the sentence pattern automatically from a viewpoint of the translation success rate and the capacity of the pattern dictionary. Then, for the purpose of realizing the automatic generation of the translation pattern, this paper proposed the new method for the generation of the translation pattern by using the genetic programming technique (GP). The technique tries to generate the translation pattern of various sentences which are not registered in the phrase template dictionary automatically by giving the genetic operation to the parsing tree of a basic pattern. The tree consists of the pair of the English-Japanese sentence generated as the first stage population. The analysis tree data base with 50,100,150,200 pairs was prepared as the first stage population. And this system was applied and executed for an English input of 1,555 sentences. As a result, the analysis tree increases from 200 to 517, and the accuracy rate of the translation pattern has improved from 42.57% to 70.10%. And, 86.71% of the generated translations was successfully done, whose meanings are enough acceptable and understandable. It seemed that this proposal technique became a clue to raise the translation success rate, and to find the possibility of the reduction of the analysis tree data base.

  16. Introducing PROFESS: A new program for orbital-free density functional theory calculations

    Science.gov (United States)

    Ho, Gregory S.; Lignères, Vincent L.; Carter, Emily A.

    2008-12-01

    We present PROFESS (PRinceton Orbital-Free Electronic Structure Software), a new software package that performs orbital-free density functional theory (OF-DFT) calculations. OF-DFT is a first principles quantum mechanics method primarily for condensed matter that can be made to scale linearly with system size. We describe the implementation of energy, force, and stress functionals and the methods used to optimize the electron density under periodic boundary conditions. All electronic energy and potential terms scale linearly while terms involving the ions exhibit quadratic scaling in our code. Despite the latter scaling, the program can treat tens of thousands of atoms with quantum mechanics on a single processor, as we demonstrate here. Limitations of the method are also outlined, the most serious of which is the accuracy of state-of-the-art kinetic energy functionals, which limits the applicability of the method to main group elements at present. Program summaryProgram title: PROFESS Catalogue identifier: AEBN_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBN_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 35 933 No. of bytes in distributed program, including test data, etc.: 329 924 Distribution format: tar.gz Programming language: Fortran 90 Computer: Intel with ifort; AMD Opteron with pathf90 Operating system: Linux RAM: Problem dependent, but 2 GB is sufficient for up to 10,000 ions Classification: 7.3 External routines: FFTW ( http://www.fftw.org), MINPACK-2 Nature of problem: Given a set of coordinates describing the initial ion positions under periodic boundary conditions, recovers the ground state energy, electron density, ion positions, and cell lattice vectors predicted by orbital-free density functional theory. Except for computation of the

  17. Explicit Building-Block Multiobjective Genetic Algorithms: Theory, Analysis, and Development

    Science.gov (United States)

    2003-03-01

    Penthouse. You have all helped me with either Matlab , C and MPI programming or just the occasional meaningless conversation that we all need to maintain...Based Multiobjective Optimization Technique for the Design of Robot Arms. Robotica , 16(4):401–414, July–August 1998. 29. Coello Coello, Carlos A. and

  18. Ultra-broadband Reflective Metamaterial with RCS Reduction based on Polarization Convertor, Information Entropy Theory and Genetic Optimization Algorithm

    Science.gov (United States)

    Li, Si Jia; Cao, Xiang Yu; Xu, Li Ming; Zhou, Long Jian; Yang, Huan Huan; Han, Jiang Feng; Zhang, Zhao; Zhang, Di; Liu, Xiao; Zhang, Chen; Zheng, Yue Jun; Zhao, Yi

    2016-11-01

    We proposed an ultra-broadband reflective metamaterial with controlling the scattering electromagnetic fields based on a polarization convertor. The unit cell of the polarization convertor was composed of a three layers substrate with double metallic split-rings structure and a metal ground plane. The proposed polarization convertor and that with rotation angle of 90 deg had been employed as the “0” and “1” elements to design the digital reflective metamaterial. The numbers of the “0” and “1” elements were chosen based on the information entropy theory. Then, the optimized combinational format was selected by genetic optimization algorithm. The scattering electromagnetic fields had been manipulated due to destructive interference, which was attributed to the control of phase and amplitude by the proposed polarization convertor. Simulated and experimental results indicated that the reflective metamaterial exhibited significantly RCS reduction in an ultra-broad frequency band for both normal and oblique incidences.

  19. A multimedia adult literacy program: Combining NASA technology, instructional design theory, and authentic literacy concepts

    Science.gov (United States)

    Willis, Jerry W.

    1993-01-01

    be the most effective or most desirable way to use computer technology in literacy programs. This project is developing a series of instructional packages that are based on a different instructional model - authentic instruction. The instructional development model used to create these packages is also different. Instead of using the traditional five stage linear, sequential model based on behavioral learning theory, the project uses the recursive, reflective design and development model (R2D2) that is based on cognitive learning theory, particularly the social constructivism of Vygotsky, and an epistemology based on critical theory. Using alternative instructional and instructional development theories, the result of the summer faculty fellowship is LiteraCity, a multimedia adult literacy instructional package that is a simulation of finding and applying for a job. The program, which is about 120 megabytes, is distributed on CD-ROM.

  20. Hierarchical On-line Scheduling of Multiproduct Batch Plants with a Combined Approach of Mathematical Programming and Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    陈理; 王克峰; 徐霄羽; 姚平经

    2004-01-01

    In this contribution we present an online scheduling algorithm for a real world multiproduct batch plant. The overall mixed integer nonlinear programming (MINLP) problem is hierarchically structured into a mixed integer linear programming (MILP) problem first and then a reduced dimensional MINLP problem, which are optimized by mathematical programming (MP) and genetic algorithm (GA) respectively. The basis idea relies on combining MP with GA to exploit their complementary capacity. The key features of the hierarchical model are explained and illustrated with some real world cases from the multiproduct batch plants.

  1. Genetic Algorithm and Graph Theory Based Matrix Factorization Method for Online Friend Recommendation

    Directory of Open Access Journals (Sweden)

    Qu Li

    2014-01-01

    Full Text Available Online friend recommendation is a fast developing topic in web mining. In this paper, we used SVD matrix factorization to model user and item feature vector and used stochastic gradient descent to amend parameter and improve accuracy. To tackle cold start problem and data sparsity, we used KNN model to influence user feature vector. At the same time, we used graph theory to partition communities with fairly low time and space complexity. What is more, matrix factorization can combine online and offline recommendation. Experiments showed that the hybrid recommendation algorithm is able to recommend online friends with good accuracy.

  2. A colorful origin for the genetic code: information theory, statistical mechanics and the emergence of molecular codes.

    Science.gov (United States)

    Tlusty, Tsvi

    2010-09-01

    The genetic code maps the sixty-four nucleotide triplets (codons) to twenty amino-acids. While the biochemical details of this code were unraveled long ago, its origin is still obscure. We review information-theoretic approaches to the problem of the code's origin and discuss the results of a recent work that treats the code in terms of an evolving, error-prone information channel. Our model - which utilizes the rate-distortion theory of noisy communication channels - suggests that the genetic code originated as a result of the interplay of the three conflicting evolutionary forces: the needs for diverse amino-acids, for error-tolerance and for minimal cost of resources. The description of the code as an information channel allows us to mathematically identify the fitness of the code and locate its emergence at a second-order phase transition when the mapping of codons to amino-acids becomes nonrandom. The noise in the channel brings about an error-graph, in which edges connect codons that are likely to be confused. The emergence of the code is governed by the topology of the error-graph, which determines the lowest modes of the graph-Laplacian and is related to the map coloring problem. (c) 2010 Elsevier B.V. All rights reserved.

  3. Heterozygosities and genetic relationship of tea cultivars revealed by simple sequence repeat markers and implications for breeding and genetic mapping programs.

    Science.gov (United States)

    Tan, L Q; Zhang, C C; Qi, G N; Wang, L Y; Wei, K; Chen, S X; Zou, Y; Wu, L Y; Cheng, H

    2015-03-06

    Genetic maps are essential tools for quantitative trait locus analysis and marker-assisted selection breeding. In order to select parents that are highly heterozygous for genetic mapping, the heterozygosity (HS) of 24 tea cultivars (Camellia sinensis) was analyzed with 72 simple sequence repeat markers. In total, 359 alleles were obtained with an average of 4.99 per marker. The HS varied greatly from 37.5 to 71.0% with an average of 51.3%. On average, tea cultivars from Fujian Province showed a higher level of heterozygosity (59.8%) than those from Zhejiang (48.5%) and Yunnan (44.5%), and the 12 national tea cultivars were generally more heterozygous than the 12 provincial cultivars. Unweighted pair-group analysis using the arithmetic average grouping divided the 24 cultivars into 2 groups that are consistent with the morphological classification. All dual combinations of the 24 cultivars were studied to calculate the percentage of mappable markers when using pseudo-testcross mapping strategy, and results showed that this value also varied greatly from 51.4 to 90.3%. The genetic relationships and HS differences among different cultivars were discussed, and tea cultivars with high HS were recommended as cross parents for genetic mapping programs.

  4. State estimation for delayed genetic regulatory networks based on passivity theory.

    Science.gov (United States)

    Vembarasan, V; Nagamani, G; Balasubramaniam, P; Park, Ju H

    2013-08-01

    This paper is concerned with the state estimation problem for delayed genetic regulatory networks (GRNs) based on passivity analysis approach. The main purpose of the problem is to design the estimator to approximate the true concentrations of the mRNA and protein through available measurement outputs. Time-varying delays are explicitly assumed to be non-differentiable and constraint on the derivative of the time-varying delay is less than one can be removed. Based on the Lyapunov-Krasovskii functionals involving triple integral terms, using some integral inequalities and convex combination technique, a delay-dependent passivity criterion is established for GRNs in terms of linear matrix inequalities (LMIs) that can efficiently be solved by any available LMI solvers. Finally, numerical examples and simulation are presented to demonstrate the efficiency of the proposed estimation schemes.

  5. Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks

    Science.gov (United States)

    Beal, Jacob; Lu, Ting; Weiss, Ron

    2011-01-01

    Background The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. Methodology/Principal Findings To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes () and latency of the optimized engineered gene networks. Conclusions/Significance Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems. PMID:21850228

  6. Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming.

    Science.gov (United States)

    Chiu, Stephanie J; Toth, Cynthia A; Bowes Rickman, Catherine; Izatt, Joseph A; Farsiu, Sina

    2012-05-01

    This paper presents a generalized framework for segmenting closed-contour anatomical and pathological features using graph theory and dynamic programming (GTDP). More specifically, the GTDP method previously developed for quantifying retinal and corneal layer thicknesses is extended to segment objects such as cells and cysts. The presented technique relies on a transform that maps closed-contour features in the Cartesian domain into lines in the quasi-polar domain. The features of interest are then segmented as layers via GTDP. Application of this method to segment closed-contour features in several ophthalmic image types is shown. Quantitative validation experiments for retinal pigmented epithelium cell segmentation in confocal fluorescence microscopy images attests to the accuracy of the presented technique.

  7. Quantum field theory and the linguistic Minimalist Program: a remarkable isomorphism

    Science.gov (United States)

    Piattelli-Palmarini, M.; Vitiello, G.

    2017-08-01

    By resorting to recent results, we show that an isomorphism exist between linguistic features of the Minimalist Program and the quantum field theory formalism of condensed matter physics. Specific linguistic features which admit a representation in terms of the many-body algebraic formalism are the unconstrained nature of recursive Merge, the operation of the Labeling Algorithm, the difference between pronounced and un-pronounced copies of elements in a sentence and the build-up of the Fibonacci sequence in the syntactic derivation of sentence structures. The collective dynamical nature of the formation process of Logical Forms leading to the individuation of the manifold of concepts and the computational self-consistency of languages are also discussed.

  8. Semantic Search-Based Genetic Programming and the Effect of Intron Deletion.

    Science.gov (United States)

    Castelli, Mauro; Vanneschi, Leonardo; Silva, Sara

    2014-01-01

    The concept of semantics (in the sense of input-output behavior of solutions on training data) has been the subject of a noteworthy interest in the genetic programming (GP) research community over the past few years. In this paper, we present a new GP system that uses the concept of semantics to improve search effectiveness. It maintains a distribution of different semantic behaviors and biases the search toward solutions that have similar semantics to the best solutions that have been found so far. We present experimental evidence of the fact that the new semantics-based GP system outperforms the standard GP and the well-known bacterial GP on a set of test functions, showing particularly interesting results for noncontinuous (i.e., generally harder to optimize) test functions. We also observe that the solutions generated by the proposed GP system often have a larger size than the ones returned by standard GP and bacterial GP and contain an elevated number of introns, i.e., parts of code that do not have any effect on the semantics. Nevertheless, we show that the deletion of introns during the evolution does not affect the performance of the proposed method.

  9. Genetic and epigenetic catalysts in early-life programming of adult cardiometabolic disorders.

    Science.gov (United States)

    Estampador, Angela C; Franks, Paul W

    2014-01-01

    Evidence has emerged across the past few decades that the lifetime risk of developing morbidities like type 2 diabetes, obesity, and cardiovascular disease may be influenced by exposures that occur in utero and in childhood. Developmental abnormalities are known to occur at various stages in fetal growth. Epidemiological and mechanistic studies have sought to delineate developmental processes and plausible risk factors influencing pregnancy outcomes and later health. Whether these observations reflect causal processes or are confounded by genetic and social factors remains unclear, although animal (and some human) studies suggest that epigenetic programming events may be involved. Regardless of the causal basis to observations of early-life risk factors and later disease risk, the fact that such associations exist and that they are of a fairly large magnitude justifies further research around this topic. Furthermore, additional information is needed to substantiate public health guidelines on lifestyle behaviors during pregnancy to improve infant health outcomes. Indeed, lifestyle intervention clinical trials in pregnancy are now coming online, where materials and data are being collected that should facilitate understanding of the causal nature of intrauterine exposures related with gestational weight gain, such as elevated maternal blood glucose concentrations. In this review, we provide an overview of these concepts.

  10. Application of genetic programming in shape optimization of concrete gravity dams by metaheuristics

    Directory of Open Access Journals (Sweden)

    Abdolhossein Baghlani

    2014-12-01

    Full Text Available A gravity dam maintains its stability against the external loads by its massive size. Hence, minimization of the weight of the dam can remarkably reduce the construction costs. In this paper, a procedure for finding optimal shape of concrete gravity dams with a computationally efficient approach is introduced. Genetic programming (GP in conjunction with metaheuristics is used for this purpose. As a case study, shape optimization of the Bluestone dam is presented. Pseudo-dynamic analysis is carried out on a total number of 322 models in order to establish a database of the results. This database is then used to find appropriate relations based on GP for design criteria of the dam. This procedure eliminates the necessity of the time-consuming process of structural analyses in evolutionary optimization methods. The method is hybridized with three different metaheuristics, including particle swarm optimization, firefly algorithm (FA, and teaching–learning-based optimization, and a comparison is made. The results show that although all algorithms are very suitable, FA is slightly superior to other two algorithms in finding a lighter structure in less number of iterations. The proposed method reduces the weight of dam up to 14.6% with very low computational effort.

  11. Genetic Programming for the Downscaling of Extreme Rainfall Events on the East Coast of Peninsular Malaysia

    Directory of Open Access Journals (Sweden)

    Sahar Hadi Pour

    2014-11-01

    Full Text Available A genetic programming (GP-based logistic regression method is proposed in the present study for the downscaling of extreme rainfall indices on the east coast of Peninsular Malaysia, which is considered one of the zones in Malaysia most vulnerable to climate change. A National Centre for Environmental Prediction reanalysis dataset at 42 grid points surrounding the study area was used to select the predictors. GP models were developed for the downscaling of three extreme rainfall indices: days with larger than or equal to the 90th percentile of rainfall during the north-east monsoon; consecutive wet days; and consecutive dry days in a year. Daily rainfall data for the time periods 1961–1990 and 1991–2000 were used for the calibration and validation of models, respectively. The results are compared with those obtained using the multilayer perceptron neural network (ANN and linear regression-based statistical downscaling model (SDSM. It was found that models derived using GP can predict both annual and seasonal extreme rainfall indices more accurately compared to ANN and SDSM.

  12. Evolving Software Effort Estimation Models Using Multigene Symbolic Regression Genetic Programming

    Directory of Open Access Journals (Sweden)

    Sultan Aljahdali

    2013-12-01

    Full Text Available Software has played an essential role in engineering, economic development, stock market growth and military applications. Mature software industry count on highly predictive software effort estimation models. Correct estimation of software effort lead to correct estimation of budget and development time. It also allows companies to develop appropriate time plan for marketing campaign. Now a day it became a great challenge to get these estimates due to the increasing number of attributes which affect the software development life cycle. Software cost estimation models should be able to provide sufficient confidence on its prediction capabilities. Recently, Computational Intelligence (CI paradigms were explored to handle the software effort estimation problem with promising results. In this paper we evolve two new models for software effort estimation using Multigene Symbolic Regression Genetic Programming (GP. One model utilizes the Source Line Of Code (SLOC as input variable to estimate the Effort (E; while the second model utilize the Inputs, Outputs, Files, and User Inquiries to estimate the Function Point (FP. The proposed GP models show better estimation capabilities compared to other reported models in the literature. The validation results are accepted based Albrecht data set.

  13. Neural networks with multiple general neuron models: a hybrid computational intelligence approach using Genetic Programming.

    Science.gov (United States)

    Barton, Alan J; Valdés, Julio J; Orchard, Robert

    2009-01-01

    Classical neural networks are composed of neurons whose nature is determined by a certain function (the neuron model), usually pre-specified. In this paper, a type of neural network (NN-GP) is presented in which: (i) each neuron may have its own neuron model in the form of a general function, (ii) any layout (i.e network interconnection) is possible, and (iii) no bias nodes or weights are associated to the connections, neurons or layers. The general functions associated to a neuron are learned by searching a function space. They are not provided a priori, but are rather built as part of an Evolutionary Computation process based on Genetic Programming. The resulting network solutions are evaluated based on a fitness measure, which may, for example, be based on classification or regression errors. Two real-world examples are presented to illustrate the promising behaviour on classification problems via construction of a low-dimensional representation of a high-dimensional parameter space associated to the set of all network solutions.

  14. Discovering link communities in complex networks by an integer programming model and a genetic algorithm.

    Science.gov (United States)

    Li, Zhenping; Zhang, Xiang-Sun; Wang, Rui-Sheng; Liu, Hongwei; Zhang, Shihua

    2013-01-01

    Identification of communities in complex networks is an important topic and issue in many fields such as sociology, biology, and computer science. Communities are often defined as groups of related nodes or links that correspond to functional subunits in the corresponding complex systems. While most conventional approaches have focused on discovering communities of nodes, some recent studies start partitioning links to find overlapping communities straightforwardly. In this paper, we propose a new quantity function for link community identification in complex networks. Based on this quantity function we formulate the link community partition problem into an integer programming model which allows us to partition a complex network into overlapping communities. We further propose a genetic algorithm for link community detection which can partition a network into overlapping communities without knowing the number of communities. We test our model and algorithm on both artificial networks and real-world networks. The results demonstrate that the model and algorithm are efficient in detecting overlapping community structure in complex networks.

  15. Genetic programming-based approach to elucidate biochemical interaction networks from data.

    Science.gov (United States)

    Kandpal, Manoj; Kalyan, Chakravarthy Mynampati; Samavedham, Lakshminarayanan

    2013-02-01

    Biochemical systems are characterised by cyclic/reversible reciprocal actions, non-linear interactions and a mixed relationship structures (linear and non-linear; static and dynamic). Deciphering the architecture of such systems using measured data to provide quantitative information regarding the nature of relationships that exist between the measured variables is a challenging proposition. Causality detection is one of the methodologies that are applied to elucidate biochemical networks from such data. Autoregressive-based modelling approach such as granger causality, partial directed coherence, directed transfer function and canonical variate analysis have been applied on different systems for deciphering such interactions, but with limited success. In this study, the authors propose a genetic programming-based causality detection (GPCD) methodology which blends evolutionary computation-based procedures along with parameter estimation methods to derive a mathematical model of the system. Application of the GPCD methodology on five data sets that contained the different challenges mentioned above indicated that GPCD performs better than the other methods in uncovering the exact structure with less false positives. On a glycolysis data set, GPCD was able to fill the 'interaction gaps' which were missed by other methods.

  16. Elevator Group Supervisory Control System Using Genetic Network Programming with Macro Nodes and Reinforcement Learning

    Science.gov (United States)

    Zhou, Jin; Yu, Lu; Mabu, Shingo; Hirasawa, Kotaro; Hu, Jinglu; Markon, Sandor

    Elevator Group Supervisory Control System (EGSCS) is a very large scale stochastic dynamic optimization problem. Due to its vast state space, significant uncertainty and numerous resource constraints such as finite car capacities and registered hall/car calls, it is hard to manage EGSCS using conventional control methods. Recently, many solutions for EGSCS using Artificial Intelligence (AI) technologies have been reported. Genetic Network Programming (GNP), which is proposed as a new evolutionary computation method several years ago, is also proved to be efficient when applied to EGSCS problem. In this paper, we propose an extended algorithm for EGSCS by introducing Reinforcement Learning (RL) into GNP framework, and an improvement of the EGSCS' performances is expected since the efficiency of GNP with RL has been clarified in some other studies like tile-world problem. Simulation tests using traffic flows in a typical office building have been made, and the results show an actual improvement of the EGSCS' performances comparing to the algorithms using original GNP and conventional control methods. Furthermore, as a further study, an importance weight optimization algorithm is employed based on GNP with RL and its efficiency is also verified with the better performances.

  17. Soil temperature modeling at different depths using neuro-fuzzy, neural network, and genetic programming techniques

    Science.gov (United States)

    Kisi, Ozgur; Sanikhani, Hadi; Cobaner, Murat

    2016-05-01

    The applicability of artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS), and genetic programming (GP) techniques in estimating soil temperatures (ST) at different depths is investigated in this study. Weather data from two stations, Mersin and Adana, Turkey, were used as inputs to the applied models in order to model monthly STs. The first part of the study focused on comparison of ANN, ANFIS, and GP models in modeling ST of two stations at the depths of 10, 50, and 100 cm. GP was found to perform better than the ANN and ANFIS-SC in estimating monthly ST. The effect of periodicity (month of the year) on models' accuracy was also investigated. Including periodicity component in models' inputs considerably increased their accuracies. The root mean square error (RMSE) of ANN models was respectively decreased by 34 and 27 % for the depths of 10 and 100 cm adding the periodicity input. In the second part of the study, the accuracies of the ANN, ANFIS, and GP models were compared in estimating ST of Mersin Station using the climatic data of Adana Station. The ANN models generally performed better than the ANFIS-SC and GP in modeling ST of Mersin Station without local climatic inputs.

  18. Object detection via feature synthesis using MDL-based genetic programming.

    Science.gov (United States)

    Lin, Yingqiang; Bhanu, Bir

    2005-06-01

    In this paper, we use genetic programming (GP) to synthesize composite operators and composite features from combinations of primitive operations and primitive features for object detection. The motivation for using GP is to overcome the human experts' limitations of focusing only on conventional combinations of primitive image processing operations in the feature synthesis. GP attempts many unconventional combinations that in some cases yield exceptionally good results. To improve the efficiency of GP and prevent its well-known code bloat problem without imposing severe restriction on the GP search, we design a new fitness function based on minimum description length principle to incorporate both the pixel labeling error and the size of a composite operator into the fitness evaluation process. To further improve the efficiency of GP, smart crossover, smart mutation and a public library ideas are incorporated to identify and keep the effective components of composite operators. Our experiments, which are performed on selected training regions of a training image to reduce the training time, show that compared to normal GP, our GP algorithm finds effective composite operators more quickly and the learned composite operators can be applied to the whole training image and other similar testing images. Also, compared to a traditional region-of-interest extraction algorithm, the composite operators learned by GP are more effective and efficient for object detection.

  19. Genetic Algorithm Combination of Boolean Constraint Programming for Solving Course of Action Optimization in Influence Nets

    Directory of Open Access Journals (Sweden)

    Yanguang Zhu

    2011-06-01

    Full Text Available A military decision maker is typically confronted by the task of determining optimal course of action under some constraints in complex uncertain situation. Thus, a new class of Combinational Constraint Optimization Problem (CCOP is formalized, that is utilized to solve this complex Operation Optimization Problem. The object function of CCOP is modeled by Influence net, and the constraints of CCOP relate to resource and collaboration. These constraints are expressed by Pseudo-Boolean and Boolean constraints. Thus CCOP holds a complex mathematical configuration, which is expressed as a 0 1 integer optimization problem with compositional constraints and unobvious optimal object function. A novel method of Genetic Algorithm (GA combination of Boolean Constraint Programming (BCP is proposed to solve CCOP. The constraints of CCOP can be easily reduced and transformed into Disjunctive Normal Form (DNF by BCP. The DNF representation then can be used to drive GA so as to solve CCOP. Finally, a numerical experiment is given to demonstrate the effectiveness of above method.

  20. Soil temperature modeling at different depths using neuro-fuzzy, neural network, and genetic programming techniques

    Science.gov (United States)

    Kisi, Ozgur; Sanikhani, Hadi; Cobaner, Murat

    2017-08-01

    The applicability of artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS), and genetic programming (GP) techniques in estimating soil temperatures (ST) at different depths is investigated in this study. Weather data from two stations, Mersin and Adana, Turkey, were used as inputs to the applied models in order to model monthly STs. The first part of the study focused on comparison of ANN, ANFIS, and GP models in modeling ST of two stations at the depths of 10, 50, and 100 cm. GP was found to perform better than the ANN and ANFIS-SC in estimating monthly ST. The effect of periodicity (month of the year) on models' accuracy was also investigated. Including periodicity component in models' inputs considerably increased their accuracies. The root mean square error (RMSE) of ANN models was respectively decreased by 34 and 27 % for the depths of 10 and 100 cm adding the periodicity input. In the second part of the study, the accuracies of the ANN, ANFIS, and GP models were compared in estimating ST of Mersin Station using the climatic data of Adana Station. The ANN models generally performed better than the ANFIS-SC and GP in modeling ST of Mersin Station without local climatic inputs.

  1. Real Time Wave Forecasting Using Wind Time History and Genetic Programming

    Directory of Open Access Journals (Sweden)

    A.R. Kambekar

    2014-12-01

    Full Text Available The significant wave height and average wave period form an essential input for operational activities in ocean and coastal areas. Such information is important in issuing appropriate warnings to people planning any construction or instillation works in the oceanic environment. Many countries over the world routinely collect wave and wind data through a network of wave rider buoys. The data collecting agencies transmit the resulting information online to their registered users through an internet or a web-based system. Operational wave forecasts in addition to the measured data are also made and supplied online to the users. This paper discusses operational wave forecasting in real time mode at locations where wind rather than wave data are continuously recorded. It is based on the time series modeling and incorporates an artificial intelligence technique of genetic programming. The significant wave height and average wave period values are forecasted over a period of 96 hr in future from the observations of wind speed and directions extending to a similar time scale in the past. Wind measurements made by floating buoys at eight different locations around India over a period varying from 1.5 yr to 9.0 yr were considered. The platform of Matlab and C++ was used to develop a graphical user interface that will extend an internet based user-friendly access of the forecasts to any registered user of the data dissemination authority.

  2. Improving probabilistic flood forecasting through a data assimilation scheme based on genetic programming

    Directory of Open Access Journals (Sweden)

    L. Mediero

    2012-12-01

    Full Text Available Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time.

  3. Genetic characterization of physical activity behaviours in university students enrolled in kinesiology degree programs.

    Science.gov (United States)

    Many, Gina M; Kendrick, Zachary; Deschamps, Chelsea L; Sprouse, Courtney; Tosi, Laura L; Devaney, Joseph M; Gordish-Dressman, Heather; Barfield, Whitney; Hoffman, Eric P; Houmard, Joseph A; Pescatello, Linda S; Vogel, Hans J; Shearer, Jane; Hittel, Dustin S

    2017-03-01

    Studies of physical activity behaviours have increasingly shown the importance of heritable factors such as genetic variation. Nonsynonymous polymorphisms of alpha-actinin 3 (ACTN3) and the β-adrenergic receptors 1 and 3 (ADRB1 and ADRB3) have been previously associated with exercise capacity and cardiometabolic health. We thus hypothesized that these polymorphisms are also related to physical activity behaviours in young adults. To test this hypothesis we examined relationships between ACTN3 (R577X), ARDB1 (Arg389Gly), ADRB3 (Trp64Arg), and physical activity behaviours in university students. We stratified for student enrollment in kinesiology degree programs compared with nonmajors as we previously found this to be a predictor of physical activity. We did not identify novel associations between physical activity and ACTN3. However, the minor alleles of ADRB1 and ADRB3 were significantly underrepresented in kinesiology students compared with nonmajors. Furthermore, carriers of the ADRB1 minor allele reported reduced participation in moderate physical activity and increased afternoon fatigue compared with ancestral allele homozygotes. Together, these findings suggest that the heritability of physical activity behaviours in young adults may be linked to nonsynonymous polymorphisms within β-adrenergic receptors.

  4. Designing A Nonlinear Integer Programming Model For A Cross-Dock By A Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Bahareh Vaisi

    2015-03-01

    Full Text Available Abstract This paper presents a non-linear integer programming model for a cross-dock problem that considers the total transportation cost of inbound and outbound trucks from an origin to a destination and the total cost of assigning strip and stack doors to trucks based on their number of trips and the distance between doors in cross-dock. In previous studies these two cost-based problems are modeled separately however it is more realistic and practical to use both of them as an integrated cross-docking model. Additionally this model is solved for a randomly generated numerical example with three suppliers and two customers by the use of a genetic algorithm. By comparing two different parameter levels i.e. low and high numbers of populations the optimum solution is obtained considering a high level population size. A number of strip and stack doors are equal to a number of inbound and outbound trucks in the same sequence as 4 and 6 respectively. Finally the conclusion is presented.

  5. Closed-loop separation control over a sharp edge ramp using Genetic Programming

    CERN Document Server

    Debien, Antoine; Mazellier, Nicolas; Duriez, Thomas; Cordier, Laurent; Noack, Bernd R; Abel, Markus W; Kourta, Azeddine

    2015-01-01

    We experimentally perform open and closed-loop control of a separating turbulent boundary layer downstream from a sharp edge ramp. The turbulent boundary layer just above the separation point has a Reynolds number $Re_{\\theta}\\approx 3\\,500$ based on momentum thickness. The goal of the control is to mitigate separation and early re-attachment. The forcing employs a spanwise array of active vortex generators. The flow state is monitored with skin-friction sensors downstream of the actuators. The feedback control law is obtained using model-free genetic programming control (GPC) (Gautier et al. 2015). The resulting flow is assessed using the momentum coefficient, pressure distribution and skin friction over the ramp and stereo PIV. The PIV yields vector field statistics, e.g. shear layer growth, the backflow area and vortex region. GPC is benchmarked against the best periodic forcing. While open-loop control achieves separation reduction by locking-on the shedding mode, GPC gives rise to similar benefits by acc...

  6. Unified description of structure and reactions: implementing the nuclear field theory program

    Science.gov (United States)

    Broglia, R. A.; Bortignon, P. F.; Barranco, F.; Vigezzi, E.; Idini, A.; Potel, G.

    2016-06-01

    The modern theory of the atomic nucleus results from the merging of the liquid drop model of Niels Bohr and Fritz Kalckar, and of the shell model of Marie Goeppert Meyer and Hans Jensen. The first model contributed the concepts of collective excitations. The second, those of independent-particle motion. The unification of these apparently contradictory views in terms of the particle-vibration and particle-rotation couplings carried out by Aage Bohr and Ben Mottelson has allowed for an ever more complete, accurate and detailed description of nuclear structure. Nuclear field theory (NFT), developed by the Copenhagen-Buenos Aires collaboration, provided a powerful quantal embodiment of this unification. Reactions are not only at the basis of quantum mechanics (statistical interpretation, Max Born), but also the specific tools to probe the atomic nucleus. It is then natural that NFT is being extended to deal with processes which involve the continuum in an intrinsic fashion, so as to be able to treat them on an equal footing with those associated with bound states (structure). As a result, spectroscopic studies of transfer to continuum states could eventually make use of the NFT rules, properly extended to take care of recoil effects. In the present contribution we review the implementation of the NFT program of structure and reactions, setting special emphasis on open problems and outstanding predictions.

  7. Queuing theory to guide the implementation of a heart failure inpatient registry program.

    Science.gov (United States)

    Zai, Adrian H; Farr, Kit M; Grant, Richard W; Mort, Elizabeth; Ferris, Timothy G; Chueh, Henry C

    2009-01-01

    OBJECTIVE The authors previously implemented an electronic heart failure registry at a large academic hospital to identify heart failure patients and to connect these patients with appropriate discharge services. Despite significant improvements in patient identification and connection rates, time to connection remained high, with an average delay of 3.2 days from the time patients were admitted to the time connections were made. Our objective for this current study was to determine the most effective solution to minimize time to connection. DESIGN We used a queuing theory model to simulate 3 different potential solutions to decrease the delay from patient identification to connection with discharge services. MEASUREMENTS The measures included average rate at which patients were being connected to the post discharge heart failure services program, average number of patients in line, and average patient waiting time. RESULTS Using queuing theory model simulations, we were able to estimate for our current system the minimum rate at which patients need to be connected (262 patients/mo), the ideal patient arrival rate (174 patients/mo) and the maximal patient arrival rate that could be achieved by adding 1 extra nurse (348 patients/mo). CONCLUSIONS Our modeling approach was instrumental in helping us characterize key process parameters and estimate the impact of adding staff on the time between identifying patients with heart failure and connecting them with appropriate discharge services.

  8. Program package for multicanonical simulations of U(1) lattice gauge theory-Second version

    Science.gov (United States)

    Bazavov, Alexei; Berg, Bernd A.

    2013-03-01

    A new version STMCMUCA_V1_1 of our program package is available. It eliminates compatibility problems of our Fortran 77 code, originally developed for the g77 compiler, with Fortran 90 and 95 compilers. New version program summaryProgram title: STMC_U1MUCA_v1_1 Catalogue identifier: AEET_v1_1 Licensing provisions: Standard CPC license, http://cpc.cs.qub.ac.uk/licence/licence.html Programming language: Fortran 77 compatible with Fortran 90 and 95 Computers: Any capable of compiling and executing Fortran code Operating systems: Any capable of compiling and executing Fortran code RAM: 10 MB and up depending on lattice size used No. of lines in distributed program, including test data, etc.: 15059 No. of bytes in distributed program, including test data, etc.: 215733 Keywords: Markov chain Monte Carlo, multicanonical, Wang-Landau recursion, Fortran, lattice gauge theory, U(1) gauge group, phase transitions of continuous systems Classification: 11.5 Catalogue identifier of previous version: AEET_v1_0 Journal Reference of previous version: Computer Physics Communications 180 (2009) 2339-2347 Does the new version supersede the previous version?: Yes Nature of problem: Efficient Markov chain Monte Carlo simulation of U(1) lattice gauge theory (or other continuous systems) close to its phase transition. Measurements and analysis of the action per plaquette, the specific heat, Polyakov loops and their structure factors. Solution method: Multicanonical simulations with an initial Wang-Landau recursion to determine suitable weight factors. Reweighting to physical values using logarithmic coding and calculating jackknife error bars. Reasons for the new version: The previous version was developed for the g77 compiler Fortran 77 version. Compiler errors were encountered with Fortran 90 and Fortran 95 compilers (specified below). Summary of revisions: epsilon=one/10**10 is replaced by epsilon/10.0D10 in the parameter statements of the subroutines u1_bmha.f, u1_mucabmha.f, u1wl

  9. The Topological Field Theory of Data: a program towards a novel strategy for data mining through data language

    Science.gov (United States)

    Rasetti, M.; Merelli, E.

    2015-07-01

    This paper aims to challenge the current thinking in IT for the 'Big Data' question, proposing - almost verbatim, with no formulas - a program aiming to construct an innovative methodology to perform data analytics in a way that returns an automaton as a recognizer of the data language: a Field Theory of Data. We suggest to build, directly out of probing data space, a theoretical framework enabling us to extract the manifold hidden relations (patterns) that exist among data, as correlations depending on the semantics generated by the mining context. The program, that is grounded in the recent innovative ways of integrating data into a topological setting, proposes the realization of a Topological Field Theory of Data, transferring and generalizing to the space of data notions inspired by physical (topological) field theories and harnesses the theory of formal languages to define the potential semantics necessary to understand the emerging patterns.

  10. Premarital Screening and Genetic Counseling program: knowledge, attitude, and satisfaction of attendees of governmental outpatient clinics in Jeddah.

    Science.gov (United States)

    Ibrahim, Nahla Khamis; Bashawri, Jamel; Al Bar, Hussein; Al Ahmadi, Jawaher; Al Bar, Adnan; Qadi, Mahdi; Milaat, Waleed; Feda, Hashim

    2013-02-01

    Premarital care (PMC) is a worldwide activity that aims to diagnose and treat unrecognized disorders and reduce the transmission of diseases to couples and children. To assess the knowledge and attitude of individuals attending governmental outpatient clinics regarding the Premarital Screening and Genetic Counseling (PMSGC) programs, to identify predictors of high knowledge scores and to determine the satisfaction and recommendations of clients of the program. A cross-sectional study was conducted from January to April 2009. Individuals who attended three governmental hospital outpatient clinics on the day of the interview and agreed to participate in the study were recruited. The three hospitals were the two hospitals in Jeddah that offer the PMSGC programs and the King Abdulaziz University Hospital. Ethical considerations were followed and data were collected through an interview questionnaire that had been constructed for the study. The questionnaire asked for personal and socio-demographic data and for responses, on a 5-point Likert scale, to 30 knowledge items and 14 attitude statements. Individuals who participated in the PMSGC program were asked questions regarding the services and activities of the program to ascertain their satisfaction with the program and their recommendations for program improvement. The statistical analysis was performed using SPSS version 16 (SPSS Inc., Chicago, IL). The sample included 655 participants, of whom 38.8% completed the PMSGC program. The participants' knowledge about the program was generally low. Education was the first predictor of a high knowledge score; individuals having ≥ university degree obtained a higher score (aOR=2.73; 95% CI: 1.77-4.20). The second predictor was the nationality of the participants, with Saudis gaining a higher score (aOR=2.04; 95% CI: 1.002-4.16). The third predictor was monthly income. Regarding attitudes, the vast majority of participants (96.0%) strongly agreed on the importance of the

  11. Mass Releases of Genetically Modified Insects in Area-Wide Pest Control Programs and Their Impact on Organic Farmers

    Directory of Open Access Journals (Sweden)

    R. Guy Reeves

    2017-01-01

    Full Text Available The mass release of irradiated insects to reduce the size of agricultural pest populations of the same species has a more than 50-year record of success. Using these techniques, insect pests can be suppressed without necessarily dispersing chemical insecticides into the environment. Ongoing release programs include the suppression of medfly at numerous locations around the globe (e.g., California, Chile and Israel and the pink bollworm eradication program across the southern USA and northern Mexico. These, and other successful area-wide programs, encompass a large number of diverse organic farms without incident. More recently, mass release techniques have been proposed that involve the release of genetically modified insects. Given that the intentional use of genetically modified organisms by farmers will in many jurisdictions preclude organic certification, this prohibits the deliberate use of this technology by organic farmers. However, mass releases of flying insects are not generally conducted by individual farmers but are done on a regional basis, often without the explicit consent of all situated farms (frequently under the auspices of government agencies or growers’ collectives. Consequently, there exists the realistic prospect of organic farms becoming involved in genetically modified insect releases as part of area-wide programs or experiments. Herein, we describe genetically modified insects engineered for mass release and examine their potential impacts on organic farmers, both intended and unintended. This is done both generally and also focusing on a hypothetical organic farm located near an approved experimental release of genetically modified (GM diamondback moths in New York State (USA.

  12. Needs and preference assessment for an in-home nutrition education program using social marketing theory.

    Science.gov (United States)

    Francis, Sarah L; Taylor, Martha L; Strickland, Amy Williams

    2004-01-01

    Nutrition education programs for elder caregivers (CG) and their elder care recipients (CR) are important in preventing malnutrition. Using Social Marketing Theory, this study assessed the needs and preferences for nutrition education in elder CGs and their CRs in Guilford County, NC. Thirty-two pairs of community-residing elder CGs/CRs and three focus groups (FGs) participated. Health and diet questionnaires were administered to all CGs/CRs during in-home interviews. CGs/CRs and FGs evaluated nutrition education materials. Questionnaires were analyzed using SPSS v9. Ethnograph v5.0 was used to code the interviews regarding the education materials. The CGs were middle age (58.9 years), overweight (BMI = 28.8) Caucasian women. The CRs were old (79.4 years), overweight (BMI = 26.0) Caucasian women. Identified malnutrition risk factors of CGs and CRs included inadequate fluid and dietary intake, polypharmacy, and chronic disease. Identified nutrition needs and education preferences of CGs/CRs were similar. Perceived nutrition education preferences of the FGs did not reflect the interests of the CGs/CRs. This information is being used to revise the education materials and develop an in-home nutrition education program for CGs and CRs in Guilford County, NC.

  13. The U.S. National Sheep Improvement Program: across-flock genetic evaluations and new trait development.

    Science.gov (United States)

    Notter, D R

    1998-09-01

    The U.S. National Sheep Improvement Program (NSIP) began in 1987 to provide within-flock genetic evaluations for the American sheep industry. An evaluation of operating procedures and methodology for NSIP began in 1993 and has resulted in across-flock, multiple-trait EPD for three breeds: Targhee, Suffolk, and Polypay. Traits reported in the across-flock analyses included direct and maternal effects on weaning weight in all breeds, postweaning weight at 120 d in Suffolk and Polypay and at 365 d in Targhee, greasy fleece weight in Targhee and Polypay, and wool fiber diameter in Targhee. Number born per ewe lambing was also evaluated in single-trait analyses for all breeds. Genetic parameters were derived separately for each breed. Important genetic antagonisms include an unfavorable genetic correlation of .51 between fleece weight and fiber diameter in Targhee and a genetic correlation of -.55 between direct and maternal effects on weaning weight in Polypay. Estimates of genetic trends between 1987 and 1995 were consistent with perceived breed roles. In Targhee, direct and maternal effects on body weights increased, fiber diameter declined, fleece weight was maintained, and number born declined. In Suffolk, direct effects on body weight increased, but number born and maternal effects on weaning weight did not change. In Polypay, number born and maternal contributions to weaning weight increased, but direct genetic merit for body weight declined. Prospective enhancements to NSIP include methods for genetic evaluation of performance in accelerated lambing and of carcass leanness and development of breeding objectives and selection aids for various production systems.

  14. Assessment of various failure theories for weight and cost optimized laminated composites using genetic algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Goyal, T. [Indian Institute of Technology Kanpur. Dept. of Aerospace Engineering, UP (India); Gupta, R. [Infotech Enterprises Ltd., Hyderabad (India)

    2012-07-01

    In this work, minimum weight-cost design for laminated composites is presented. A genetic algorithm has been developed for the optimization process. Maximum-Stress, Tsai-Wu and Tsai-Hill failure criteria have been used along with buckling analysis parameter for the margin of safety calculations. The design variables include three materials; namely Carbon-Epoxy, Glass-Epoxy, Kevlar-Epoxy; number of plies; ply orientation angles, varying from -75 deg. to 90 deg. in the intervals of 15 deg. and ply thicknesses which depend on the material in use. The total cost is a sum of material cost and layup cost. Layup cost is a function of the ply angle. Validation studies for solution convergence and weight-cost inverse proportionality are carried out. One set of results for shear loading are also validated from literature for a particular case. A Pareto-Optimal solution set is demonstrated for biaxial loading conditions. It is then extended to applied moments. It is found that global optimum for a given loading condition is a function of the failure criteria for shear loading, with Maximum Stress criteria giving the lightest-cheapest and Tsai-Wu criteria giving the heaviest-costliest optimized laminates. Optimized weight results are plotted from the three criteria to do a comparative study. This work gives a global optimized laminated composite and also a set of other local optimum laminates for a given set of loading conditions. The current algorithm also provides with adequate data to supplement the use of different failure criteria for varying loadings. This work can find use in the industry and/or academia considering the increased use of laminated composites in modern wind blades. (Author)

  15. Germany-US Nuclear Theory Exchange Program for QCD Studies of Hadrons & Nuclei 'GAUSTEQ'

    Energy Technology Data Exchange (ETDEWEB)

    Dudek, Jozef [Old Dominion Univ., Norfolk, VA (United States); Melnitchouk, Wally [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States)

    2016-03-07

    GAUSTEQ was a Germany-U.S. exchange program in nuclear theory whose purpose was to focus research efforts on QCD studies of hadrons and nuclei, centered around the current and future research programs of Jefferson Lab and the Gesellschaft fur Schwerionenforschung (GSI) in Germany. GAUSTEQ provided travel support for theoretical physicists at US institutions conducting collaborative research with physicists in Germany. GSI (with its Darmstadt and Helmholtz Institute Mainz braches) served as the German “hub” for visits of U.S. physicists, while Jefferson Lab served as the corresponding “hub” for visits of German physicists visiting U.S. institutions through the reciprocal GUSTEHP (German-US Theory Exchange in Hadron Physics) program. GAUSTEQ was funded by the Office of Nuclear Physics of the U.S. Department of Energy, under Contract No.DE-SC0006758 and officially managed through Old Dominion University in Norfolk, Virginia. The program ran between 2011 and 2015.

  16. Genetic differences between wild and hatchery populations of Diplodus sargus and D. vulgaris inferred from RAPD markers: implications for production and restocking programs design.

    Science.gov (United States)

    Pereira, J C; Lino, P G; Leitão, A; Joaquim, S; Chaves, R; Pousão-Ferreira, P; Guedes-Pinto, H; dos Santos, M Neves

    2010-01-01

    Restocking and stock enhancement programs are now recognized as an important tool for the management of fishery resources. It is important, however, to have an adequate knowledge on the genetic population structure of both the released stock and the wild population before carrying out such programs. In this study, random amplified polymorphic DNA (RAPD) markers were applied to assess genetic diversity and population structure of wild and hatchery populations of the white seabream Diplodus sargus and the common two-banded seabream D. vulgaris (Sparidae). The estimated values for intrapopulation genetic variation, measured using the percentage of polymorphic loci (%P), Shannon index (H'), and Nei's gene diversity (h), showed high values for all populations. The percentage of genetic variation within D. sargus and D. vulgaris populations, based on coefficient of gene differentiation, reached 82.5% and 90% of the total genetic variation, respectively. An undeniable decrease in genetic variation was found in both hatchery populations, particularly in D. sargus, compared to the wild ones. However, the high values of variation within all populations and the low levels of genetic variation among populations did not indicate inbreeding or depression effects, thus indicating a fairly proper hatchery management. Nevertheless, the results of this study highlight the importance of monitoring the genetic variation of hatchery populations, particularly those to be used in restocking programs. The creation of a genetic baseline database will contribute to a more efficient conservation management and to the design of genetically sustainable restocking programs.

  17. Engaging nurses in genetics: the strategic approach of the NHS National Genetics Education and Development Centre.

    Science.gov (United States)

    Kirk, Maggie; Tonkin, Emma; Burke, Sarah

    2008-04-01

    The UK government announced the establishment of an NHS National Genetics Education and Development Centre in its Genetics White Paper. The Centre aims to lead and coordinate developments to enhance genetics literacy of health professionals. The nursing program takes a strategic approach based on Ajzen's Theory of Planned Behavior, using the UK nursing genetics competences as the platform for development. The program team uses innovative approaches to raise awareness of the relevance of genetics, working collaboratively with policy stakeholders, as key agents of change in promoting competence. Providing practical help in preparing learning and teaching resources lends further encouragement. Evaluation of the program is dependent on gathering baseline data, and the program has been informed by an education needs analysis. The challenges faced are substantial and necessitate international collaboration where expertise and resources can be shared to produce a global system of influence to facilitate the engagement of non-genetic nurses.

  18. Pedigree analysis: One teaching strategy to incorporate genetics into a full FNP program.

    Science.gov (United States)

    Schumacher, Gretchen; Conway, Alice E; Sparlin, Judith A

    2006-05-01

    The successful completion of the genome project in April 2003 and explosion of genetic knowledge is impacting healthcare at a dramatic rate. All healthcare providers need to update themselves on genetics in order to provide comprehensive care. This article describes a national grant obtained to educate faculty regarding incorporating genetics into courses. It also presents an innovate method for incorporating genetics into a full Family Nurse Practitioner (FNP) curriculum. Student responses and guidelines for one assignment are included. Utilizing this type of assignment in FNP courses is beneficial to both students and faculty. With more FNPs assessing patterns for illness in families, primary prevention and earlier intervention in primary care can be achieved.

  19. The application of theory in childhood asthma self-help programs.

    Science.gov (United States)

    Bruhn, J G

    1983-11-01

    Theories from research in health education and compliance (adherence) behavior are reviewed and examined for their applicability to studies of self-management of childhood asthma. Specific theories discussed include: (1) the health belief model, (2) models of health, illness, and sick-role behavior, (3) social learning theory, (4) models of physician-patient relationships, (5) self-regulation model, (6) communication theory, (7) attribution, control, and decision-making theory, (8) grounded theory, (9) ecologic theory, and (10) family and social systems theories. A scheme to guide development and testing of theories in children's health and illness behavior is presented. The key common elements in the examined theories on adherence behavior are integrated and organized into a paradigm for the family determinants of the self-management of chronic illness.

  20. Genetic programming approach on evaporation losses and its effect on climate change for Vaipar Basin

    Directory of Open Access Journals (Sweden)

    K.S.Kasiviswanathan

    2011-09-01

    Full Text Available Climate change is the major problem that every human being is facing over the world. The rise in fossil fuel usage increases the emission of `greenhouse' gases, particularly carbon dioxide continuously into the earth's atmosphere. This causes a rise in the amount of heat from the sun withheld in the earth's atmosphere that would normally radiated back into space. This increase in heat has led to the greenhouse effect, resulting in climate change and rise in temperature along with other climatological parameters directly affects evaporation losses. Accurate modelling and forecasting of these evaporation losses are important for preventing further effects due to climate change. Evaporation is purely non-linear and varying both spatially and temporally. This needs suitable data driven approach to model and should have the ability to take care of all these non-linear behaviour of the system. As such, though there are many empirical and analytical models suggested in the literature for the estimation of evaporation losses, such models should be used with care and caution. Further, difficulties arise in obtaining all the climatological data used in a given analytical or empirical model. Genetic programming (GP is one such technique applied where the non-linearity exist. GP has the flexible mathematical structure which is capable of identifying the non-linear relationship between input and output data sets. Thus, it is easy to construct 'local' models for estimating evaporation losses. The performance of GP model is compared with Thornthwaite method, and results from the study indicate that the GP model performed better than the Thornthwaite method. Forecasting of meteorological parameters such as temperature, relative humidity and wind velocity has been performed using Markovian chain series analysis subsequently it is used to estimate the future evaporation losses using developed GP model. Finally the effect of possible future climate change on

  1. Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices.

    Science.gov (United States)

    Goel, Purva; Bapat, Sanket; Vyas, Renu; Tambe, Amruta; Tambe, Sanjeev S

    2015-11-13

    The development of quantitative structure-retention relationships (QSRR) aims at constructing an appropriate linear/nonlinear model for the prediction of the retention behavior (such as Kovats retention index) of a solute on a chromatographic column. Commonly, multi-linear regression and artificial neural networks are used in the QSRR development in the gas chromatography (GC). In this study, an artificial intelligence based data-driven modeling formalism, namely genetic programming (GP), has been introduced for the development of quantitative structure based models predicting Kovats retention indices (KRI). The novelty of the GP formalism is that given an example dataset, it searches and optimizes both the form (structure) and the parameters of an appropriate linear/nonlinear data-fitting model. Thus, it is not necessary to pre-specify the form of the data-fitting model in the GP-based modeling. These models are also less complex, simple to understand, and easy to deploy. The effectiveness of GP in constructing QSRRs has been demonstrated by developing models predicting KRIs of light hydrocarbons (case study-I) and adamantane derivatives (case study-II). In each case study, two-, three- and four-descriptor models have been developed using the KRI data available in the literature. The results of these studies clearly indicate that the GP-based models possess an excellent KRI prediction accuracy and generalization capability. Specifically, the best performing four-descriptor models in both the case studies have yielded high (>0.9) values of the coefficient of determination (R(2)) and low values of root mean squared error (RMSE) and mean absolute percent error (MAPE) for training, test and validation set data. The characteristic feature of this study is that it introduces a practical and an effective GP-based method for developing QSRRs in gas chromatography that can be gainfully utilized for developing other types of data-driven models in chromatography science.

  2. Diversity and genetic stability in banana genotypes in a breeding program using inter simple sequence repeats (ISSR) markers.

    Science.gov (United States)

    Silva, A V C; Nascimento, A L S; Vitória, M F; Rabbani, A R C; Soares, A N R; Lédo, A S

    2017-02-23

    Banana (Musa spp) is a fruit species frequently cultivated and consumed worldwide. Molecular markers are important for estimating genetic diversity in germplasm and between genotypes in breeding programs. The objective of this study was to analyze the genetic diversity of 21 banana genotypes (FHIA 23, PA42-44, Maçã, Pacovan Ken, Bucaneiro, YB42-47, Grand Naine, Tropical, FHIA 18, PA94-01, YB42-17, Enxerto, Japira, Pacovã, Prata-Anã, Maravilha, PV79-34, Caipira, Princesa, Garantida, and Thap Maeo), by using inter-simple sequence repeat (ISSR) markers. Material was generated from the banana breeding program of Embrapa Cassava & Fruits and evaluated at Embrapa Coastal Tablelands. The 12 primers used in this study generated 97.5% polymorphism. Four clusters were identified among the different genotypes studied, and the sum of the first two principal components was 48.91%. From the Unweighted Pair Group Method using Arithmetic averages (UPGMA) dendrogram, it was possible to identify two main clusters and subclusters. Two genotypes (Garantida and Thap Maeo) remained isolated from the others, both in the UPGMA clustering and in the principal cordinate analysis (PCoA). Using ISSR markers, we could analyze the genetic diversity of the studied material and state that these markers were efficient at detecting sufficient polymorphism to estimate the genetic variability in banana genotypes.

  3. Self-management programs based on the social cognitive theory for Koreans with chronic disease: a systematic review.

    Science.gov (United States)

    Jang, Yeonsoo; Yoo, Hyera

    2012-02-01

    Self-management programs based on social cognitive theory are useful to improve health care outcomes for patients with chronic diseases in Western culture. The purpose of this review is to identify and synthesize published research on the theory to enhance self-efficacy in disease management and examine its applicability to Korean culture regarding the learning strategies used. Ultimately, it was to identify the optimal use of these learning strategies to improve the self-efficacy of Korean patients in self-management of their hypertension and diabetic mellitus. The authors searched the Korean and international research databases from January 2000 to September 2009. Twenty studies were selected and reviewed. The most frequently used learning strategies of social cognitive theory was skill mastery by practice and feedback (N = 13), followed by social or verbal persuasion by group members (N = 7) and, however, observation learning and reinterpretation of symptoms by debriefing or discussion were not used any of the studies. Eight studies used only one strategy to enhance self-efficacy and six used two. A lack of consistency regarding the content and clinical efficacy of the self-efficacy theory-based self-management programs is found among the reviewed studies on enhancing self-efficacy in Koreans with hypertension and diabetes mellitus. Further research on the effectiveness of these theory-based self-management programs for patients with chronic diseases in Korea and other countries is recommended.

  4. The lack of foundation in the mechanism on which are based the physico-chemical theories for the origin of the genetic code is counterposed to the credible and natural mechanism suggested by the coevolution theory.

    Science.gov (United States)

    Di Giulio, Massimo

    2016-06-21

    I analyze the mechanism on which are based the majority of theories that put to the center of the origin of the genetic code the physico-chemical properties of amino acids. As this mechanism is based on excessive mutational steps, I conclude that it could not have been operative or if operative it would not have allowed a full realization of predictions of these theories, because this mechanism contained, evidently, a high indeterminacy. I make that disapproving the four-column theory of the origin of the genetic code (Higgs, 2009) and reply to the criticism that was directed towards the coevolution theory of the origin of the genetic code. In this context, I suggest a new hypothesis that clarifies the mechanism by which the domains of codons of the precursor amino acids would have evolved, as predicted by the coevolution theory. This mechanism would have used particular elongation factors that would have constrained the evolution of all amino acids belonging to a given biosynthetic family to the progenitor pre-tRNA, that for first recognized, the first codons that evolved in a certain codon domain of a determined precursor amino acid. This happened because the elongation factors recognized two characteristics of the progenitor pre-tRNAs of precursor amino acids, which prevented the elongation factors from recognizing the pre-tRNAs belonging to biosynthetic families of different precursor amino acids. Finally, I analyze by means of Fisher's exact test, the distribution, within the genetic code, of the biosynthetic classes of amino acids and the ones of polarity values of amino acids. This analysis would seem to support the biosynthetic classes of amino acids over the ones of polarity values, as the main factor that led to the structuring of the genetic code, with the physico-chemical properties of amino acids playing only a subsidiary role in this evolution. As a whole, the full analysis brings to the conclusion that the coevolution theory of the origin of the

  5. A Formative Evaluation of Healthy Heroes: A Photo Comic Book-Social Cognitive Theory Based Obesity Prevention Program

    Science.gov (United States)

    Branscum, Paul; Housley, Alexandra; Bhochhibhoya, Amir; Hayes, Logan

    2016-01-01

    Purpose: Low consumption of fruits and vegetables is often associated with poor diet quality, and childhood obesity. The purpose of this study was to assess the feasibility, and conduct a formative evaluation, of Healthy Heroes, an innovative, social cognitive theory-based program that uses child created photo-comic books to promote fruit and…

  6. A Program Based on the Pragmatic Theory to Develop Grammatical Structure Comprehension Skills for Foreign Learners of Arabic

    Science.gov (United States)

    Elsamman, Marwan

    2014-01-01

    This study aimed at designing a program based on the Pragmatic theory to develop grammatical structure comprehension skills for foreign learners of Arabic and examining its effectiveness. Hence, the problem of the study has been summarized in the weakness of grammatical structure comprehension skills for foreign learners of Arabic and in the need…

  7. Cope and Grow: A Grounded Theory Approach to Early College Entrants' Lived Experiences and Changes in a STEM Program

    Science.gov (United States)

    Dai, David Yun; Steenbergen-Hu, Saiying; Zhou, Yehan

    2015-01-01

    In this grounded theory qualitative study, we interviewed 34 graduates from one cohort of 51 students from a prestigious early college entrance program in China. Based on the interview data, we identified distinct convergent and divergent patterns of lived experiences and changes. We found several dominant themes, including peers' mutual…

  8. Challenges of implementating a doctoral program in an international exchange in Cuba through the lens of Kanter's empowerment theory.

    Science.gov (United States)

    Scanlan, Judith M; Abdul Hernandéz, C

    2014-08-01

    The literature in international education focuses primarily on the experiences of western students in developing countries, international students in western universities, the development of an educational program in a developing country, or internationalization of curricula in western universities. There is little in the literature that addresses the challenges students and participating faculty face when implementing a graduate program in a developing country. The purpose of this paper is to describe and analyze the challenges of implementing a doctoral program in an international exchange through the lens of Kanter's theory of empowerment. Recommendations to address these challenges will be made.

  9. Non-genetic risk factors in haemophilia A inhibitor management - the danger theory and the use of animal models.

    Science.gov (United States)

    Lövgren, K M; Søndergaard, H; Skov, S; Wiinberg, B

    2016-09-01

    In haemophilia A (HA) management, antidrug antibodies, or inhibitors, are a serious complication that renders factor VIII (FVIII) replacement therapy ineffective, increases morbidity and reduces quality of life for affected patients. Inhibitor development aetiology is multifactorial and covers both genetic and therapy related risk factors. Many therapy-related risk factors have proven difficult to confirm due to several confounding factors and the small study populations available. However, clinical studies indicate that e.g. on-demand treatment and surgery affect inhibitor development, and explanations for this association are being investigated. A potential explanation is the danger signal effect, where the immune response is activated by endogenous or exogenous danger or damage signals present at the time and site of FVIII administration. The danger theory explains how alarm signals from stressed, injured or dying cells can activate an immune reaction, without the involvement of foreign antigens. Bleeds, trauma, surgery or concomitant infection could be events initiating danger signalling in HA patients, resulting in an immune reaction towards administered FVIII that otherwise would pass unnoticed. This role of danger in HA inhibitor formation has previously been suggested, but a thorough discussion of this subject is lacking. The present review will discuss the potential role of danger signals in haemophilia and inhibitor development, with focus on treatment related risk factors with a suspected danger signal aetiology; on-demand treatment, treatment during major bleeds or surgery, and treatment during infection or vaccination. Clinical studies as well as animal experiments addressing these factors will be reviewed.

  10. Probing the input-output behavior of biochemical and genetic systems system identification methods from control theory.

    Science.gov (United States)

    Ang, Jordan; Ingalls, Brian; McMillen, David

    2011-01-01

    A key aspect of the behavior of any system is the timescale on which it operates: when inputs change, do responses take milliseconds, seconds, minutes, hours, days, months? Does the system respond preferentially to inputs at certain timescales? These questions are well addressed by the methods of frequency response analysis. In this review, we introduce these methods and outline a procedure for applying this analysis directly to experimental data. This procedure, known as system identification, is a well-established tool in engineering systems and control theory and allows the construction of a predictive dynamic model of a biological system in the absence of any mechanistic details. When studying biochemical and genetic systems, the required experiments are not standard laboratory practice, but with advances in both our ability to measure system outputs (e.g., using fluorescent reporters) and our ability to generate precise inputs (with microfluidic chambers capable of changing cells' environments rapidly and under fine control), these frequency response methods are now experimentally practical for a wide range of biological systems, as evidenced by a number of successful recent applications of these techniques. We use a yeast G-protein signaling cascade as a running example, illustrating both theoretical concepts and practical considerations while keeping mathematical details to a minimum. The review aims to provide the reader with the tools required to design frequency response experiments for their own biological system and the background required to analyze and interpret the resulting data.

  11. Applying probability theory for the quality assessment of a wildfire spread prediction framework based on genetic algorithms.

    Science.gov (United States)

    Cencerrado, Andrés; Cortés, Ana; Margalef, Tomàs

    2013-01-01

    This work presents a framework for assessing how the existing constraints at the time of attending an ongoing forest fire affect simulation results, both in terms of quality (accuracy) obtained and the time needed to make a decision. In the wildfire spread simulation and prediction area, it is essential to properly exploit the computational power offered by new computing advances. For this purpose, we rely on a two-stage prediction process to enhance the quality of traditional predictions, taking advantage of parallel computing. This strategy is based on an adjustment stage which is carried out by a well-known evolutionary technique: Genetic Algorithms. The core of this framework is evaluated according to the probability theory principles. Thus, a strong statistical study is presented and oriented towards the characterization of such an adjustment technique in order to help the operation managers deal with the two aspects previously mentioned: time and quality. The experimental work in this paper is based on a region in Spain which is one of the most prone to forest fires: El Cap de Creus.

  12. Applying Probability Theory for the Quality Assessment of a Wildfire Spread Prediction Framework Based on Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Andrés Cencerrado

    2013-01-01

    Full Text Available This work presents a framework for assessing how the existing constraints at the time of attending an ongoing forest fire affect simulation results, both in terms of quality (accuracy obtained and the time needed to make a decision. In the wildfire spread simulation and prediction area, it is essential to properly exploit the computational power offered by new computing advances. For this purpose, we rely on a two-stage prediction process to enhance the quality of traditional predictions, taking advantage of parallel computing. This strategy is based on an adjustment stage which is carried out by a well-known evolutionary technique: Genetic Algorithms. The core of this framework is evaluated according to the probability theory principles. Thus, a strong statistical study is presented and oriented towards the characterization of such an adjustment technique in order to help the operation managers deal with the two aspects previously mentioned: time and quality. The experimental work in this paper is based on a region in Spain which is one of the most prone to forest fires: El Cap de Creus.

  13. A theory-based newsletter nutrition education program reduces nutritional risk and improves dietary intake for congregate meal participants.

    Science.gov (United States)

    Francis, Sarah L; MacNab, Lindsay; Shelley, Mack

    2014-01-01

    At-risk older adults need community-based nutrition programs that improve nutritional status and practices. This 6-month study assessed the impact of the traditional Chef Charles (CC) program (Control) compared to a theory-based CC program (Treatment) on nutritional risk (NR), dietary intakes, self-efficacy (SE), food security (FS), and program satisfaction for congregate meal participants. Participants were mostly educated, single, "food secure" White females. NR change for the treatment group was significantly higher (P = 0.042) than the control group. No differences were noted for SE or FS change and program satisfaction between groups. The overall distribution classification levels of FS changed significantly (P < .001) from pre to post. Over half (n = 46, 76.7%) reported making dietary changes and the majority (n = 52, 86.7%) rated CC as good to excellent. Results suggest the theory-based CC program (treatment) is more effective in reducing NR and dietary practices than the traditional CC program (control).

  14. Investigating the genetic basis of theory of mind (ToM: the role of catechol-O-methyltransferase (COMT gene polymorphisms.

    Directory of Open Access Journals (Sweden)

    Haiwei Xia

    Full Text Available The ability to deduce other persons' mental states and emotions which has been termed 'theory of mind (ToM' is highly heritable. First molecular genetic studies focused on some dopamine-related genes, while the genetic basis underlying different components of ToM (affective ToM and cognitive ToM remain unknown. The current study tested 7 candidate polymorphisms (rs4680, rs4633, rs2020917, rs2239393, rs737865, rs174699 and rs59938883 on the catechol-O-methyltransferase (COMT gene. We investigated how these polymorphisms relate to different components of ToM. 101 adults participated in our study; all were genetically unrelated, non-clinical and healthy Chinese subjects. Different ToM tasks were applied to detect their theory of mind ability. The results showed that the COMT gene rs2020917 and rs737865 SNPs were associated with cognitive ToM performance, while the COMT gene rs5993883 SNP was related to affective ToM, in which a significant gender-genotype interaction was found (p = 0.039. Our results highlighted the contribution of DA-related COMT gene on ToM performance. Moreover, we found out that the different SNP at the same gene relates to the discriminative aspect of ToM. Our research provides some preliminary evidence to the genetic basis of theory of mind which still awaits further studies.

  15. Investigating the genetic basis of theory of mind (ToM): the role of catechol-O-methyltransferase (COMT) gene polymorphisms.

    Science.gov (United States)

    Xia, Haiwei; Wu, Nan; Su, Yanjie

    2012-01-01

    The ability to deduce other persons' mental states and emotions which has been termed 'theory of mind (ToM)' is highly heritable. First molecular genetic studies focused on some dopamine-related genes, while the genetic basis underlying different components of ToM (affective ToM and cognitive ToM) remain unknown. The current study tested 7 candidate polymorphisms (rs4680, rs4633, rs2020917, rs2239393, rs737865, rs174699 and rs59938883) on the catechol-O-methyltransferase (COMT) gene. We investigated how these polymorphisms relate to different components of ToM. 101 adults participated in our study; all were genetically unrelated, non-clinical and healthy Chinese subjects. Different ToM tasks were applied to detect their theory of mind ability. The results showed that the COMT gene rs2020917 and rs737865 SNPs were associated with cognitive ToM performance, while the COMT gene rs5993883 SNP was related to affective ToM, in which a significant gender-genotype interaction was found (p = 0.039). Our results highlighted the contribution of DA-related COMT gene on ToM performance. Moreover, we found out that the different SNP at the same gene relates to the discriminative aspect of ToM. Our research provides some preliminary evidence to the genetic basis of theory of mind which still awaits further studies.

  16. SAFSIM theory manual: A computer program for the engineering simulation of flow systems

    Energy Technology Data Exchange (ETDEWEB)

    Dobranich, D.

    1993-12-01

    SAFSIM (System Analysis Flow SIMulator) is a FORTRAN computer program for simulating the integrated performance of complex flow systems. SAFSIM provides sufficient versatility to allow the engineering simulation of almost any system, from a backyard sprinkler system to a clustered nuclear reactor propulsion system. In addition to versatility, speed and robustness are primary SAFSIM development goals. SAFSIM contains three basic physics modules: (1) a fluid mechanics module with flow network capability; (2) a structure heat transfer module with multiple convection and radiation exchange surface capability; and (3) a point reactor dynamics module with reactivity feedback and decay heat capability. Any or all of the physics modules can be implemented, as the problem dictates. SAFSIM can be used for compressible and incompressible, single-phase, multicomponent flow systems. Both the fluid mechanics and structure heat transfer modules employ a one-dimensional finite element modeling approach. This document contains a description of the theory incorporated in SAFSIM, including the governing equations, the numerical methods, and the overall system solution strategies.

  17. Expansion of Parents' Undetermined Experience in Socioeducational Programs: Extending the Dialogical Self Theory.

    Science.gov (United States)

    Boulanger, Dany

    2017-09-16

    The Dialogic Self Theory (DST-Hermans et al. Integrative Psychology and Behavioral Sciences, 51(4), 1-31, 2017) is extended here in its dynamic aspects through focusing on the notions of indeterminacy, emptiness and movement. Linking with Husserl, I propose moving the dialogical self (DS) from a clear position in the "repertory of the Self" to an undetermined horizon. This makes it possible to introduce "holes" (emptiness) into the schematic representation of the "repertory of the Self". Yet Husserl's concept of horizon seems to focus too much on making the indeterminable determinate. To overcome this limit, I incorporate Bergson's concept of empty form into the DST. This enables conceptualising the extension and emergence of horizon. Extending Bergson's concept of organisation, it is possible to see how the expansion of the horizon in a movement of globalisation does not necessarily entail the disorganisation of the DS but rather to its further organisation. Extending the system of DS by Hermans et al. Integrative Psychology and Behavioral Sciences, 51(4), 1-31, (2017), I open by suggesting that movements are both horizontal (between people) and vertical (between the person, the institutions and the norms) connectors. My conceptual propositions are illustrated by parents' and educators' discourses in two Canadian socio-educational programs.

  18. Genetic evaluation of the Association of Zoos and Aquariums Matschie's tree kangaroo (Dendrolagus matschiei) captive breeding program.

    Science.gov (United States)

    McGreevy, Thomas J; Dabek, Lisa; Husband, Thomas P

    2011-01-01

    Matschie's tree kangaroo (Dendrolagus matschiei) is an endangered species that has been bred in captivity since the 1970s. In 1992, the Tree Kangaroo Species Survival Plan(®) (TKSSP) was established to coordinate the captive management of Association of Zoos and Aquariums (AZA) D. matschiei. The TKSSP makes annual breeding recommendations primarily based on the mean kinship (MK) strategy. Captive breeding programs often use the MK strategy to preserve genetic diversity in small populations-to avoid the negative consequences of inbreeding and retain their adaptive potential. The ability of a captive breeding program to retain the population's genetic diversity over time can be evaluated by comparing the genetic diversity of the captive population to wild populations. We analyzed DNA extracted from blood and fecal samples from AZA (n = 71), captive (n = 28), and wild (n = 22) D. matschiei using eight microsatellite markers and sequenced the partial mitochondrial DNA control region gene. AZA D. matschiei had a similar expected heterozygosity (H(e) = 0.595 ± 0.184) compared with wild D. matschiei (H(e) = 0.628 ± 0.143), but they had different allelic frequencies (F(ST) = 0.126; P < 0.001). AZA D. matschiei haplotype diversity was almost two times lower than wild D. matschiei Ĥ = 0.740 ± 0.063. These data will assist management of AZA D. matschiei and serve as a baseline for AZA and wild D. matschiei genetic diversity values that could be used to monitor future changes in their genetic diversity. © 2010 Wiley Periodicals, Inc.

  19. [Prenatal diagnosis. I: Prenatal diagnosis program at the Medical Genetics Unit of the Universidad de Zulia, Maracaibo, Venezuela].

    Science.gov (United States)

    Prieto-Carrasquero, M; Molero, A; Carrasquero, N; Paz, V; González, S; Pineda-Del Villar, L; Del Villar, A; Rojas-Atencio, A; Quintero, M; Fulcado, W; Mena, R; Morales-Machin, A

    1998-06-01

    The Prenatal Diagnosis Program of the Medical Genetic Unit of University of Zulia has the following objectives: Identification of Genetic Risk Factors (GRF) in those couples who attend to the Prenatal Genetic Clinic, application of different prenatal diagnostic procedures (PDP), and providing adequate genetic counseling. The goal of this paper is to show preliminary results obtained between January 1993 and December 1996. Three hundred and twenty one pregnant women were analyzed by determining the GRF and taking into account the genetic clinical history. The GRF analyzed were: Advanced maternal age (AMA), congenital malformation history (CMH), previous child with chromosomic anomalies (PCCA), defects of neural tube history (DNTH), congenital heart disease history (CHDH), any parent carrier of chromosomic anomaly (PCA), habitual abortion (HA), abnormal fetal echography (AFE), altered maternal serum levels of alpha-feto-protein (AMSAFP) and OTHERS: exposure to teratogenic agents, history of Mendelian diseases, maternal systemic diseases and anxiety in the mother or in her partner. The PDP was designed according to the GRF, which included fetal echography (FE), fetal echocardiography (FEc), amniocentesis (AMN), chordocentesis (CCT) and AMSAFP. Results showed that 58.4% of the expectant mothers asked for counseling during the 2nd trimester, 70% of the total showed only one GRF, and AMA was the most frequent GRF found (40.3%), followed by PCCA, AFE, CHDH, HA, DNTH, PCA, and OTHERS in that order. The specific PDP applied to the identified GRF allowed a health evaluation of the fetus. The GRF identification gave the opportunity of establishing a Prenatal Diagnostic Program producing a response to the couple's needs and showed the utility of an integral and multidisciplinary management directed to any expecting mother in order to identify any high GRF.

  20. Six-year outcome of the national premarital screening and genetic counseling program for sickle cell disease and β-thalassemia in Saudi Arabia

    National Research Council Canada - National Science Library

    Memish, Ziad Ahmed; Saeedi, Mohammad Y

    2011-01-01

    Saudi Arabia has a high prevalence of hereditary hemoglobin disorders. Data has been collected by the Saudi Premarital Screening and Genetic Counseling Program on the prevalence of sickle cell disease and β...

  1. A social marketing theory-based diet-education program for women ages 54 to 83 years improved dietary status.

    Science.gov (United States)

    Francis, Sarah L; Taylor, Martha L

    2009-12-01

    Social Marketing Theory is a comprehensive approach of program development encompassing the needs and preferences of the intended audience. It was hypothesized a Social Marketing Theory-based, registered dietitian-led, in-home, cardiovascular disease-targeted diet-education program would improve the dietary status of community-residing older women. Using a randomized control group design, this 90-day program in two North Carolina counties included 58 women (30 control; 28 intervention) ages 54 to 83 years. Data were collected using the Mini Nutritional Assessment, three 3-day food records, and program evaluations. The intervention group received two individual registered dietitian-led in-home education sessions and the control group received education material mailings (Visits 2 and 3). Pretested education materials were used. Visits/mailings were scheduled 28 to 30 days apart. Variables measured included cardiovascular disease-related dietary practices and dietary status (Mini Nutritional Assessment). Data were analyzed using descriptive statistics, paired sample t tests, multivariant analyses, and independent t tests. Intervention and control Mini Nutritional Assessment scores improved (P=0.0001). Intervention subjects consumed more fiber than control (P=0.013) and reduced sodium intake (P=0.02). Controls reduced energy (P=0.01) and cholesterol intakes (P=0.029), likely because of the decreased food intake. The majority (n=51, 87.9%) rated the program as good to excellent and almost all (n=55, 94.8%) would recommend the program to a friend. The most popular features of the program were the individualized sessions (n=20, 34.5%) and diet analyses (n=11, 19%). These results suggest that cardiovascular disease diet-education materials utilizing Social Marketing Theory principles can lead to improved dietary status among community-residing older women.

  2. The general practitioner's role in promoting physical activity to older adults: a review based on program theory.

    Science.gov (United States)

    Hinrichs, Timo; Brach, Michael

    2012-02-01

    Positive influences of physical activity both on many chronic diseases and on preservation of mobility are well documented. But chronically ill or mobility restricted elderly living in their own homes are difficult to reach for interventions. The general practitioner's (GP) surgery offers one of the few opportunities to give advice for physical activity to those people. We used program theory to sound out knowledge on GP-centered physical activity counseling. The "conceptual theory" (evidence for training effects in old age) and the "implementation theory" (unique position of the GP) were reviewed narratively. The "action theory" (effects of GP counseling) was reviewed systematically. According to program theory, appropriate MeSH (Medical subject headings) concepts were Aged OR Aged, 80 and over (Target group), Physicians, Family OR Primary Health Care (Implementation/Setting), Counseling OR Patient Education as Topic OR Disease Management OR Health promotion (Intervention), Exercise OR Motor Activity OR Physical Fitness OR Sports (Determinants). The resulting six review papers (Pubmed, 2000-2009) were presented using the STARLITE mnemonic. Authors agree, that the GP plays a central role in the promotion of physical activity to elderly people, but there is conflicting evidence concerning counseling effectiveness. Utilizing behavioral change strategies and the collaboration between GPs and specialised professions are recommended and currently under research.

  3. Effect of care management program structure on implementation: a normalization process theory analysis.

    Science.gov (United States)

    Holtrop, Jodi Summers; Potworowski, Georges; Fitzpatrick, Laurie; Kowalk, Amy; Green, Lee A

    2016-08-15

    Care management in primary care can be effective in helping patients with chronic disease improve their health status, however, primary care practices are often challenged with implementation. Further, there are different ways to structure care management that may make implementation more or less successful. Normalization process theory (NPT) provides a means of understanding how a new complex intervention can become routine (normalized) in practice. In this study, we used NPT to understand how care management structure affected how well care management became routine in practice. Data collection involved semi-structured interviews and observations conducted at 25 practices in five physician organizations in Michigan, USA. Practices were selected to reflect variation in physician organizations, type of care management program, and degree of normalization. Data were transcribed, qualitatively coded and analyzed, initially using an editing approach and then a template approach with NPT as a guiding framework. Seventy interviews and 25 observations were completed. Two key structures for care management organization emerged: practice-based care management where the care managers were embedded in the practice as part of the practice team; and centralized care management where the care managers worked independently of the practice work flow and was located outside the practice. There were differences in normalization of care management across practices. Practice-based care management was generally better normalized as compared to centralized care management. Differences in normalization were well explained by the NPT, and in particular the collective action construct. When care managers had multiple and flexible opportunities for communication (interactional workability), had the requisite knowledge, skills, and personal characteristics (skill set workability), and the organizational support and resources (contextual integration), a trusting professional relationship

  4. Rethinking the transmission gap: What behavioral genetics and evolutionary psychology mean for attachment theory: A comment on Verhage et al. (2016).

    Science.gov (United States)

    Barbaro, Nicole; Boutwell, Brian B; Barnes, J C; Shackelford, Todd K

    2017-01-01

    Traditional attachment theory posits that attachment in infancy and early childhood is the result of intergenerational transmission of attachment from parents to offspring. Verhage et al. (2016) present meta-analytic evidence addressing the intergenerational transmission of attachment between caregivers and young children. In this commentary, we argue that their appraisal of the behavioral genetics literature is incomplete. The suggested research focus on shared environmental effects may dissuade the pursuit of profitable avenues of research and may hinder progress in attachment theory. Specifically, further research on the "transmission gap" will continue to limit our understanding of attachment etiology. We discuss recent theoretical developments from an evolutionary psychological perspective that can provide a valuable framework to account for the existing behavioral genetic data. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  5. Preservation of the wild European mouflon: the first example of genetic management using a complete program of reproductive biotechnologies.

    Science.gov (United States)

    Ptak, Grazyna; Clinton, Michael; Barboni, Barbara; Muzzeddu, Marco; Cappai, Pietro; Tischner, Marian; Loi, Pasqualino

    2002-03-01

    Although the potential use of reproductive biotechnologies for safeguarding endangered wildlife species is undoubted, practical efforts have met with limited success to date. In those instances in which modern technologies have been adapted to rescuing rare or endangered species, procedures have been applied piecemeal, and no consistent breeding program based on reproductive biotechnologies has been undertaken. Here we describe for the first time the rescue of an endangered species, the European mouflon (Ovis orientalis musimon), by the application of an integrated package of reproductive biotechnologies. This genetic management extended from the initial collection of gametes, through the in vitro production of embryos and interspecific transfer, to the birth of healthy mouflon offspring. In addition, a genetic resource bank for the European mouflon was established, with cryopreserved sperm, embryos, and somatic cells.

  6. Negative Selection on BRCA1 Susceptibility Alleles Sheds Light on the Population Genetics of Late-Onset Diseases and Aging Theory

    OpenAIRE

    Samuel Pavard; C. Jessica E. Metcalf

    2007-01-01

    The magnitude of negative selection on alleles involved in age-specific mortality decreases with age. This is the foundation of the evolutionary theory of senescence. Because of this decrease in negative selection with age, and because of the absence of reproduction after menopause, alleles involved in women's late-onset diseases are generally considered evolutionarily neutral. Recently, genetic and epidemiological data on alleles involved in late onset-diseases have become available. It is t...

  7. The use of a genetic-counselling program by Dutch breeders for four hereditary health problems in boxer dogs.

    Science.gov (United States)

    van Hagen, Marjan A E; Janss, Luc L G; van den Broek, Jan; Knol, Bart W

    2004-04-30

    Our group developed a genetic-counselling program for boxer-dog breeders in The Netherlands, using data for cryptorchidism (uni- and/or bilateral), epilepsy, knee-problems (including ligament rupture, fractured or ruptured meniscus, severe osteo-arthrosis of the knee, or a combination of these disorders), and schisis (including cheiloschisis, palatoschisis, or cheilopalatoschisis). We transformed the estimated breeding values (EBVs) into odds ratios (ORs), to enable the breeder to compare the risk for each of the traits for a certain dam-sire combination with the average population risk (set at 1). The goal of the study was to evaluate the use of our genetic-counselling program by Dutch breeders of boxer dogs. We asked breeders of the Dutch Boxer Club to send in an application form for genetic-counselling from June 1 to December 1, 2000. Breeders indicated on this application form three desirable sires for their dam (sire 1, sire 2, sire 3) in random order. On the basis of this information, a counselling report was produced which included ORs for the four diseases in litters of the dam-sire combinations indicated on the application form. Together with the counselling report, the breeders received an evaluation form. We received 129 application forms from 70 breeders, and collected 125 evaluations. Of these evaluations, 96 were informative about the influence of the counselling report on sire choice. The most-important criteria used by breeders to select sires were: the exterior characteristics (60%) and known progeny (52%). Although it was the first time breeders could make use of genetic-counselling, 32% of the breeders indicated that the genetic-counselling played a major role in their sire selection. Breeders expressed little difference in importance for the four genetic traits, but there was a tendency to consider epilepsy more than the others. Breeders hesitated to put long-term population interest above short-term personal interest. Nevertheless, the general

  8. Community aging initiatives and social capital: developing theories of change in the context of NORC Supportive Service Programs.

    Science.gov (United States)

    Greenfield, Emily A

    2014-03-01

    This study aimed to develop theory on how Naturally Occurring Retirement Communities (NORC) Supportive Service Programs potentially transform social relationships within communities to promote aging in place. Data were analyzed from semi-structured in-depth interviews with 10 lead agencies representing 15 NORC programs in New Jersey. Results indicated that professionals seek to infuse capital within three domains of relationships: lead agency staff's relationships with older adults, formal service providers' relationships with each other, and older adults' relationships with each other. This social capital potentially enhances the amount of community-based services and supports within a residential area, as well as their accessibility, appropriateness, responsiveness, and coherence.

  9. Application of the CUDA programming model in the simulation of genetic sequences evolution

    Directory of Open Access Journals (Sweden)

    Freddy Yasmany Chávez

    2017-03-01

    Full Text Available Simulation is a powerful approach in the study of the molecular evolution of genetic sequences and their divergence over time; there are different procedures for the simulation of molecular evolution, but all of them have high computational complexity, and in most cases the genetic sequences have large size, increasing the execution time of the implementations of those procedures. Based on this problem, this paper describes a proposal of parallelization model using CUDA technology and the results of this proposal are compared with its sequential equivalent.

  10. A queuing-theory-based interval-fuzzy robust two-stage programming model for environmental management under uncertainty

    Science.gov (United States)

    Sun, Y.; Li, Y. P.; Huang, G. H.

    2012-06-01

    In this study, a queuing-theory-based interval-fuzzy robust two-stage programming (QB-IRTP) model is developed through introducing queuing theory into an interval-fuzzy robust two-stage (IRTP) optimization framework. The developed QB-IRTP model can not only address highly uncertain information for the lower and upper bounds of interval parameters but also be used for analysing a variety of policy scenarios that are associated with different levels of economic penalties when the promised targets are violated. Moreover, it can reflect uncertainties in queuing theory problems. The developed method has been applied to a case of long-term municipal solid waste (MSW) management planning. Interval solutions associated with different waste-generation rates, different waiting costs and different arriving rates have been obtained. They can be used for generating decision alternatives and thus help managers to identify desired MSW management policies under various economic objectives and system reliability constraints.

  11. sup 2 sup 5 sup 2 Cf source-correlated transmission measurements and genetic programming for nuclear safeguards

    CERN Document Server

    Pozzi, S A

    2002-01-01

    One of the main targets of nuclear safeguards is to determine the mass and enrichment of fissile samples enclosed in special, non-accessible containers. In this paper, we present a method to estimate the mass of uranium oxide samples based on sup 2 sup 5 sup 2 Cf source-driven noise-analysis measurements. We show that the mass of the samples can be successfully predicted using a genetic programming algorithm. The input presented to the algorithm was in the form of features extracted from the physical properties of the measured correlation functions.

  12. Analysis of the Multi Strategy Goal Programming for Micro-Grid Based on Dynamic ant Genetic Algorithm

    Science.gov (United States)

    Qiu, J. P.; Niu, D. X.

    Micro-grid is one of the key technologies of the future energy supplies. Take economic planning. reliability, and environmental protection of micro grid as a basis for the analysis of multi-strategy objective programming problems for micro grid which contains wind power, solar power, and battery and micro gas turbine. Establish the mathematical model of each power generation characteristics and energy dissipation. and change micro grid planning multi-objective function under different operating strategies to a single objective model based on AHP method. Example analysis shows that in combination with dynamic ant mixed genetic algorithm can get the optimal power output of this model.

  13. Genetically Programming Interfaces between Active Materials, Conductive Pathway and Current Collector in Li Ion Batteries

    Science.gov (United States)

    2012-01-01

    assembled into coin cell with metallic lithium as counter electrode. Electrochemical characterization was conducted by galvanostatically cycling the half...encodes either A1, A2, S7, T7 or H7. These DNAs were then introduced into bacteria cells for amplification. Genetic sequencing performed on the

  14. Mechanism design: theory and application to welfare-to-work programs

    NARCIS (Netherlands)

    Onderstal, S.

    2008-01-01

    In October 2007, Leonid Hurwicz , Eric Maskin, and Roger Myerson won the Nobel Prize in Economic Sciences "for having laid the foundations of mechanism design theory". My aim is to give you a flavor of what mechanism design theory is and how we can apply it in practice. More in particular, I will ap

  15. Mechanism design: theory and application to welfare-to-work programs

    NARCIS (Netherlands)

    Onderstal, S.

    2008-01-01

    In October 2007, Leonid Hurwicz , Eric Maskin, and Roger Myerson won the Nobel Prize in Economic Sciences "for having laid the foundations of mechanism design theory". My aim is to give you a flavor of what mechanism design theory is and how we can apply it in practice. More in particular, I will

  16. Een Program Theory benadering voor het theoretisch onderbouwen van sociale interventies: een casestudie van vijf Nederlandse maatjesprojecten

    Directory of Open Access Journals (Sweden)

    Michelle van der Tier

    2016-12-01

    Full Text Available Een Program Theory benadering voor het theoretisch onderbouwen van sociale interventies: een casestudie van vijf Nederlandse maatjesprojectenSociale professionals worden steeds meer gevraagd het professioneel handelen te verantwoorden. De sociale sector weet zich echter slechts marginaal te verantwoorden en te profileren als kenniseigenaar op het eigen domein. Het aantal sociale interventies dat theoretisch dan wel wetenschappelijk onderbouwd is, is beperkt. In de literatuur zijn verschillende benaderingen te onderscheiden die een antwoord beogen te geven op de vraag hoe en op basis waarvan een sociale interventie verantwoord dient te worden. In dit artikel geven we een methodebeschrijving van de “Program Theory” benadering en reflecteren we aan de hand van een casestudie op de praktische en wetenschappelijke meerwaarde van deze methode voor het theoretisch onderbouwen van sociale interventies. We argumenteren dat een Program Theory benadering vanuit de uitgangspunten van het kritisch realisme een waardevolle aanvulling biedt op de “evidence-based practice” benadering, die vooral inzicht geeft in de effecten van een interventie. Een Program Theory aanpak levert daarnaast een verklarende theorie over de effectiviteit van de interventie en neemt de werking van de praktijkcontext hierin mee door een interventietheorie “bottom-up” te ontwikkelen vanuit de praktijk en deze theorie tevens te onderbouwen met wetenschappelijke evidentie. Deze benadering biedt daarmee een collaboratieve leeromgeving voor professionals en onderzoekers, door de werking van mechanismen binnen een praktijkcontext te onderzoeken en te expliciteren. Doordat sociale professionals eigenaarschap blijven houden over hun eigen interventietheorie draagt de benadering bovendien bij aan de professionalisering en versterking van de kennisbasis van het sociaal werk.  Theorizing social interventions using a Program Theory approach: a case study of five Dutch buddy

  17. The SEEK Mentoring Program: An Application of the Goal-Setting Theory

    Science.gov (United States)

    Sorrentino, Diane M.

    2007-01-01

    This article describes a pilot academic mentoring program carried out over 1 semester in the SEEK Program at the College of Staten Island, CUNY. The program was utilized to provide a resource for students whose overall grade point average was below 2.5, placing them at risk for academic dismissal. A goal-setting approach was used to aid the…

  18. The Role of Program Theory in Evaluation Research: A Consideration of the What Works Clearinghouse Standards in the Case of Mathematics Education

    Science.gov (United States)

    Munter, Charles; Cobb, Paul; Shekell, Calli

    2016-01-01

    We examined the extent to which mathematics program evaluations that have been conducted according to methodologically rigorous standards have attended to the theories underlying the programs being evaluated. Our analysis focused on the 37 reports of K-12 mathematics program evaluations in the last two decades that have met standards for inclusion…

  19. DNA Commission of the International Society for Forensic Genetics: Recommendations on the validation of software programs performing biostatistical calculations for forensic genetics applications.

    Science.gov (United States)

    Coble, M D; Buckleton, J; Butler, J M; Egeland, T; Fimmers, R; Gill, P; Gusmão, L; Guttman, B; Krawczak, M; Morling, N; Parson, W; Pinto, N; Schneider, P M; Sherry, S T; Willuweit, S; Prinz, M

    2016-11-01

    The use of biostatistical software programs to assist in data interpretation and calculate likelihood ratios is essential to forensic geneticists and part of the daily case work flow for both kinship and DNA identification laboratories. Previous recommendations issued by the DNA Commission of the International Society for Forensic Genetics (ISFG) covered the application of bio-statistical evaluations for STR typing results in identification and kinship cases, and this is now being expanded to provide best practices regarding validation and verification of the software required for these calculations. With larger multiplexes, more complex mixtures, and increasing requests for extended family testing, laboratories are relying more than ever on specific software solutions and sufficient validation, training and extensive documentation are of upmost importance. Here, we present recommendations for the minimum requirements to validate bio-statistical software to be used in forensic genetics. We distinguish between developmental validation and the responsibilities of the software developer or provider, and the internal validation studies to be performed by the end user. Recommendations for the software provider address, for example, the documentation of the underlying models used by the software, validation data expectations, version control, implementation and training support, as well as continuity and user notifications. For the internal validations the recommendations include: creating a validation plan, requirements for the range of samples to be tested, Standard Operating Procedure development, and internal laboratory training and education. To ensure that all laboratories have access to a wide range of samples for validation and training purposes the ISFG DNA commission encourages collaborative studies and public repositories of STR typing results. Published by Elsevier Ireland Ltd.

  20. Search for Lambda+(c) ---> p K+ pi- and D+(s) ---> K+ K+ pi- using genetic programming event selection

    Energy Technology Data Exchange (ETDEWEB)

    Link, J.M.; Yager, P.M.; Anjos, J.C.; Bediaga, I.; Castromonte, C.; Machado, A.A.; Magnin, J.; Massafferri, A.; de Miranda, J.M.; Pepe, I.M.; Polycarpo, E.; dos Reis,; Carrillo, S.; Casimiro, E.; Cuautle, E.; Sanchez-Hernandez, A.; Uribe, C.; Vazquez, F.; Agostino, L.; Cinquini, L.; Cumalat, J.P.; /Wisconsin U., Madison

    2005-07-01

    The authors apply a genetic programming technique to search for the doubly Cabibbo suppressed decays {Lambda}{sub c}{sup +} {yields} pK{sup +} {pi}{sup -} and D{sub s}{sup +} {yields} K{sup +}K{sup +}{pi}{sup -}. They normalize these decays to their Cabibbo favored partners and find BR({Lambda}{sub c}{sup +} {yields} pK{sup +}{pi}{sup -})/BR({Lambda}{sub c}{sup +} {yields} pK{sup -}{pi}{sup +}) = (0.05 {+-} 0.26 {+-} 0.02)% and BR(D{sub s}{sup +} {yields} K{sup +}K{sup +}{pi}{sup -})/BR(D{sub s}{sup +} {yields} K{sup -}K{sup +}{pi}{sup +}) = (0.52 {+-} 0.17 {+-} 0.11)% where the first errors are statistical and the second are systematic. Expressed as 90% confidence levels (CL), they find < 0.46% and < 0.78% respectively. This is the first successful use of genetic programming in a high energy physics data analysis.