Genetic technologies to enhance the Sterile Insect Technique (SIT)

Energy Technology Data Exchange (ETDEWEB)

Alphey, Luke; Baker, Pam; Condon, George C; Condon, Kirsty C; Dafa' alla, Tarig H; Fu, Guoliang; Jin, Li; Labbe, Genevieve; Morrison, Neil M; Nimmo, Derric D; O' Connell, Sinead; Phillips, Caroline E; Plackett, Andrew; Scaife, Sarah; Woods, Alexander [Oxitec Ltd., Oxford (United Kingdom); Burton, Rosemary S; Epton, Matthew J; Gong, Peng [University of Oxford (United Kingdom). Dept. of Zoology

2006-07-01

The Sterile Insect Technique (SIT) has been used very successfully against range of pest insects, including various tephritid fruit flies, several moths and a small number of livestock pests. However, modern genetics could potentially provide several improvements that would increase the cost-effectiveness of SIT, and extend the range of suitable species. These include improved identification of released individuals by incorporation of a stable, heritable, genetic marker; built-in sex separation (genetic sexing); reduction of the hazard posed by non-irradiated accidental releases from mass-rearing facility (fail-safe); elimination of the need for sterilization by irradiation (genetic sterilization). We discuss applications of these methods and the state of the art, at the time of this meeting, in developing suitable strains. We have demonstrated, in several key pest species, that the required strains can be constructed by introducing a repressible dominant lethal genetic system, a method known as RIDL(trade mark). Based on field experience with Medfly, incorporation of a genetic sexing system into SIT programs for other tephritids could potentially provide a very significant improvement in cost-effectiveness. We have now been able to make efficient female-lethal strains for Medfly. One advantage of our approach is that it should be possible rapidly to extend this technology to other fruit fly species; indeed we have recently been able also to make genetic sexing strains of Medfly (Anastrepha ludens). (author)

Linear genetic programming

CERN Document Server

Brameier, Markus

2007-01-01

Presents a variant of Genetic Programming that evolves imperative computer programs as linear sequences of instructions, in contrast to the more traditional functional expressions or syntax trees. This book serves as a reference for researchers, but also contains sufficient introduction for students and those who are new to the field

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

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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.

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

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

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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

Multigene Genetic Programming for Estimation of Elastic Modulus of Concrete

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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.

Behavioral program synthesis with genetic programming

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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...

When Darwin meets Lorenz: Evolving new chaotic attractors through genetic programming

International Nuclear Information System (INIS)

Pan, Indranil; Das, Saptarshi

2015-01-01

Highlights: •New 3D continuous time chaotic systems with analytical expressions are obtained. •The multi-gene genetic programming (MGGP) paradigm is employed to achieve this. •Extends earlier works for evolving generalised family of Lorenz attractors. •Over one hundred of new chaotic attractors along with their parameters are reported. •The MGGP method have the potential for finding other similar chaotic attractors. -- Abstract: In this paper, we propose a novel methodology for automatically finding new chaotic attractors through a computational intelligence technique known as multi-gene genetic programming (MGGP). We apply this technique to the case of the Lorenz attractor and evolve several new chaotic attractors based on the basic Lorenz template. The MGGP algorithm automatically finds new nonlinear expressions for the different state variables starting from the original Lorenz system. The Lyapunov exponents of each of the attractors are calculated numerically based on the time series of the state variables using time delay embedding techniques. The MGGP algorithm tries to search the functional space of the attractors by aiming to maximise the largest Lyapunov exponent (LLE) of the evolved attractors. To demonstrate the potential of the proposed methodology, we report over one hundred new chaotic attractor structures along with their parameters, which are evolved from just the Lorenz system alone

Soil temperature modeling at different depths using neuro-fuzzy, neural network, and genetic programming techniques

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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.

The sheep blowfly genetic control program in Australia

International Nuclear Information System (INIS)

Foster, Geoffrey G.

1989-01-01

The blowfly Lucilia cuprina is the most important myiasis pet of sheep in Australia. Other species are associated with sheep myiasis, but L. cuprina is probably responsible for initiating more than 90% of infestations. Annual costs of production losses, prevention and treatment have been estimated at $149 millions in 1985. Prevention and treatment encompass both insecticidal applications to sheep and non-chemical management practices. In the absence of effective preventive measures, the sheep industry would be non-viable over much of Australia. Insecticide usage against L. cuprina has been marked by the appearance of widespread resistance to cyclodienes in 1956, the organophosphates in 1965, and carbamates in 1966. Resistance has not yet been reported against the triazine compounds introduced for blowfly control in 1981. The most effective non-chemical control measures are surgical (removal of skin from the breech in certain breeds of sheep, and tail-docking). They protect sheep by reducing favourable oviposition sites (dung and urine-stained wool). The spectre of insecticide resistance and the early success of the sterile insect technique (SIT) against screwworm fly in the U.S.A., led this Division to consider SIT and other autocidal methods in the 1960s. The L. cuprina genetics research program was established in 1966 and subsequently expanded in 1971. More recently, lobbying by animal welfare groups against surgical blowfly control practices, as well as increasing consumer awareness of insecticide residues in animal products, have accelerated the search for alternatives to chemical control. When SIT was first considered for L. cuprina control in 1960, little was known about the population dynamics of L. cuprina. There were insufficient ecological data to evaluate the prospects of alternative strategies such as suppression or containment. The number of flies which would have to be released in a SIT program was unknown, as were the costs. Assuming that the cost of

Genetic Network Programming with Reconstructed Individuals

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

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

Developing robotic behavior using a genetic programming model

International Nuclear Information System (INIS)

Pryor, R.J.

1998-01-01

This report describes the methodology for using a genetic programming model to develop tracking behaviors for autonomous, microscale robotic vehicles. The use of such vehicles for surveillance and detection operations has become increasingly important in defense and humanitarian applications. Through an evolutionary process similar to that found in nature, the genetic programming model generates a computer program that when downloaded onto a robotic vehicle's on-board computer will guide the robot to successfully accomplish its task. Simulations of multiple robots engaged in problem-solving tasks have demonstrated cooperative behaviors. This report also discusses the behavior model produced by genetic programming and presents some results achieved during the study

Testing the Structure of Hydrological Models using Genetic Programming

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Selle, B.; Muttil, N.

2009-04-01

Genetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that genetic programming can be used to test the structure hydrological models and to identify dominant processes in hydrological systems. To test this, genetic programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, water table depths and water ponding times during surface irrigation. Using genetic programming, a simple model of deep percolation was consistently evolved in multiple model runs. This simple and interpretable model confirmed the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that genetic programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

Testing the structure of a hydrological model using Genetic Programming

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Selle, Benny; Muttil, Nitin

2011-01-01

SummaryGenetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that Genetic Programming can be used to test the structure of hydrological models and to identify dominant processes in hydrological systems. To test this, Genetic Programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, watertable depths and water ponding times during surface irrigation. Using Genetic Programming, a simple model of deep percolation was recurrently evolved in multiple Genetic Programming runs. This simple and interpretable model supported the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that Genetic Programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

Genetic algorithms - A new technique for solving the neutron spectrum unfolding problem

International Nuclear Information System (INIS)

Freeman, David W.; Edwards, D. Ray; Bolon, Albert E.

1999-01-01

A new technique utilizing genetic algorithms has been applied to the Bonner sphere neutron spectrum unfolding problem. Genetic algorithms are part of a relatively new field of 'evolutionary' solution techniques that mimic living systems with computer-simulated 'chromosome' solutions. Solutions mate and mutate to create better solutions. Several benchmark problems, considered representative of radiation protection environments, have been evaluated using the newly developed UMRGA code which implements the genetic algorithm unfolding technique. The results are compared with results from other well-established unfolding codes. The genetic algorithm technique works remarkably well and produces solutions with relatively high spectral qualities. UMRGA appears to be a superior technique in the absence of a priori data - it does not rely on 'lucky' guesses of input spectra. Calculated personnel doses associated with the unfolded spectra match benchmark values within a few percent

Genetics Education in Nurse Residency Programs: A Natural Fit.

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Hamilton, Nalo M; Stenman, Christina W; Sang, Elaine; Palmer, Christina

2017-08-01

Scientific advances are shedding light on the genetic underpinning of common diseases. With such insight, the entire health care team is faced with the need to address patient questions regarding genetic risk, testing, and the psychosocial aspects of genetics information. Nurses are in a prime position to help with patient education about genetic conditions, yet they often lack adequate genetics education within their nursing curriculum to address patient questions and provide resources. One mechanism to address this knowledge deficit is the incorporation of a genetics-based curriculum into nurse residency programs. This article describes a novel genetics-based curriculum designed and implemented in the UCLA Health System Nurse Residency Program. J Contin Educ Nurs. 2017;48(8):379-384. Copyright 2017, SLACK Incorporated.

Evolution of Genetic Techniques: Past, Present, and Beyond

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Asude Alpman Durmaz

2015-01-01

Full Text Available Genetics is the study of heredity, which means the study of genes and factors related to all aspects of genes. The scientific history of genetics began with the works of Gregor Mendel in the mid-19th century. Prior to Mendel, genetics was primarily theoretical whilst, after Mendel, the science of genetics was broadened to include experimental genetics. Developments in all fields of genetics and genetic technology in the first half of the 20th century provided a basis for the later developments. In the second half of the 20th century, the molecular background of genetics has become more understandable. Rapid technological advancements, followed by the completion of Human Genome Project, have contributed a great deal to the knowledge of genetic factors and their impact on human life and diseases. Currently, more than 1800 disease genes have been identified, more than 2000 genetic tests have become available, and in conjunction with this at least 350 biotechnology-based products have been released onto the market. Novel technologies, particularly next generation sequencing, have dramatically accelerated the pace of biological research, while at the same time increasing expectations. In this paper, a brief summary of genetic history with short explanations of most popular genetic techniques is given.

Genetic Programming for Medicinal Plant Family Identification System

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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%.

Mathematical programming models for solving in equal-sized facilities layout problems. A genetic search method

International Nuclear Information System (INIS)

Tavakkoli-Moghaddam, R.

1999-01-01

This paper present unequal-sized facilities layout solutions generated by a genetic search program. named Layout Design using a Genetic Algorithm) 9. The generalized quadratic assignment problem requiring pre-determined distance and material flow matrices as the input data and the continuous plane model employing a dynamic distance measure and a material flow matrix are discussed. Computational results on test problems are reported as compared with layout solutions generated by the branch - and bound algorithm a hybrid method merging simulated annealing and local search techniques, and an optimization process of an enveloped block

Forecasting tourist arrivals to balearic islands using genetic programming

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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.

Amount of Genetics Education is Low Among Didactic Programs in Dietetics.

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Beretich, Kaitlan; Pope, Janet; Erickson, Dawn; Kennedy, Angela

2017-01-01

Nutritional genomics is a growing area of research. Research has shown registered dietitian nutritionists (RDNs) have limited knowledge of genetics. Limited research is available regarding how didactic programs in dietetics (DPDs) meet the genetics knowledge requirement of the Accreditation Council for Education in Nutrition and Dietetics (ACEND®). The purpose of this study was to determine the extent to which the study of nutritional genomics is incorporated into undergraduate DPDs in response to the Academy of Nutrition and Dietetics position statement on nutritional genomics. The sample included 62 DPD directors in the U.S. Most programs (63.9%) reported the ACEND genetics knowledge requirement was being met by integrating genetic information into the current curriculum. However, 88.7% of programs reported devoting only 1-10 clock hours to genetics education. While 60.3% of directors surveyed reported they were confident in their program's ability to teach information related to genetics, only 6 directors reported having specialized training in genetics. The overall amount of clock hours devoted to genetics education is low. DPD directors, faculty, and instructors are not adequately trained to provide this education to students enrolled in DPDs. Therefore, the primary recommendation of this study is the development of a standardized curriculum for genetics education in DPDs.

Resizing Technique-Based Hybrid Genetic Algorithm for Optimal Drift Design of Multistory Steel Frame Buildings

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Hyo Seon Park

2014-01-01

Full Text Available Since genetic algorithm-based optimization methods are computationally expensive for practical use in the field of structural optimization, a resizing technique-based hybrid genetic algorithm for the drift design of multistory steel frame buildings is proposed to increase the convergence speed of genetic algorithms. To reduce the number of structural analyses required for the convergence, a genetic algorithm is combined with a resizing technique that is an efficient optimal technique to control the drift of buildings without the repetitive structural analysis. The resizing technique-based hybrid genetic algorithm proposed in this paper is applied to the minimum weight design of three steel frame buildings. To evaluate the performance of the algorithm, optimum weights, computational times, and generation numbers from the proposed algorithm are compared with those from a genetic algorithm. Based on the comparisons, it is concluded that the hybrid genetic algorithm shows clear improvements in convergence properties.

Portfolio optimization by using linear programing models based on genetic algorithm

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Sukono; Hidayat, Y.; Lesmana, E.; Putra, A. S.; Napitupulu, H.; Supian, S.

2018-01-01

In this paper, we discussed the investment portfolio optimization using linear programming model based on genetic algorithms. It is assumed that the portfolio risk is measured by absolute standard deviation, and each investor has a risk tolerance on the investment portfolio. To complete the investment portfolio optimization problem, the issue is arranged into a linear programming model. Furthermore, determination of the optimum solution for linear programming is done by using a genetic algorithm. As a numerical illustration, we analyze some of the stocks traded on the capital market in Indonesia. Based on the analysis, it is shown that the portfolio optimization performed by genetic algorithm approach produces more optimal efficient portfolio, compared to the portfolio optimization performed by a linear programming algorithm approach. Therefore, genetic algorithms can be considered as an alternative on determining the investment portfolio optimization, particularly using linear programming models.

Genetic algorithms applied to nuclear reactor design optimization

International Nuclear Information System (INIS)

Pereira, C.M.N.A.; Schirru, R.; Martinez, A.S.

2000-01-01

A genetic algorithm is a powerful search technique that simulates natural evolution in order to fit a population of computational structures to the solution of an optimization problem. This technique presents several advantages over classical ones such as linear programming based techniques, often used in nuclear engineering optimization problems. However, genetic algorithms demand some extra computational cost. Nowadays, due to the fast computers available, the use of genetic algorithms has increased and its practical application has become a reality. In nuclear engineering there are many difficult optimization problems related to nuclear reactor design. Genetic algorithm is a suitable technique to face such kind of problems. This chapter presents applications of genetic algorithms for nuclear reactor core design optimization. A genetic algorithm has been designed to optimize the nuclear reactor cell parameters, such as array pitch, isotopic enrichment, dimensions and cells materials. Some advantages of this genetic algorithm implementation over a classical method based on linear programming are revealed through the application of both techniques to a simple optimization problem. In order to emphasize the suitability of genetic algorithms for design optimization, the technique was successfully applied to a more complex problem, where the classical method is not suitable. Results and comments about the applications are also presented. (orig.)

Stigmatization of carrier status: social implications of heterozygote genetic screening programs.

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Kenen, R H; Schmidt, R M

1978-01-01

Possible latent psychological and social consequences ensuing from genetic screening programs need to be investigated during the planning phase of national genetic screening programs. The relatively few studies which have been performed to determine psychological, social, and economic consequences resulting from a genetic screening program are reviewed. Stigmatization of carrier-status, having major psychosocial implications in heterozygote genetic screening programs, is discussed and related to Erving Goffman's work in the area of stigmatization. Questions are raised regarding the relationship between such variables as religiosity and sex of the individual and acceptance of the status of newly identified carrier of a mutant gene. Severity of the deleterious gene and visibility of the carrier status are two important factors to consider in an estimation of potential stigma. Specific implications are discussed for four genetic diseases: Tay-Sachs, Sickle-Cell Anemia, Huntington's disease and Hemophilia. PMID:152585

Routine human-competitive machine intelligence by means of genetic programming

Science.gov (United States)

Koza, John R.; Streeter, Matthew J.; Keane, Martin

2004-01-01

Genetic programming is a systematic method for getting computers to automatically solve a problem. Genetic programming starts from a high-level statement of what needs to be done and automatically creates a computer program to solve the problem. The paper demonstrates that genetic programming (1) now routinely delivers high-return human-competitive machine intelligence; (2) is an automated invention machine; (3) can automatically create a general solution to a problem in the form of a parameterized topology; and (4) has delivered a progression of qualitatively more substantial results in synchrony with five approximately order-of-magnitude increases in the expenditure of computer time. Recent results involving the automatic synthesis of the topology and sizing of analog electrical circuits and controllers demonstrate these points.

Genetic programming applied to RFI mitigation in radio astronomy

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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.

Applications of genetic programming in cancer research.

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

2009-02-01

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

Genetic programs can be compressed and autonomously decompressed in live cells

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Lapique, Nicolas; Benenson, Yaakov

2018-04-01

Fundamental computer science concepts have inspired novel information-processing molecular systems in test tubes1-13 and genetically encoded circuits in live cells14-21. Recent research has shown that digital information storage in DNA, implemented using deep sequencing and conventional software, can approach the maximum Shannon information capacity22 of two bits per nucleotide23. In nature, DNA is used to store genetic programs, but the information content of the encoding rarely approaches this maximum24. We hypothesize that the biological function of a genetic program can be preserved while reducing the length of its DNA encoding and increasing the information content per nucleotide. Here we support this hypothesis by describing an experimental procedure for compressing a genetic program and its subsequent autonomous decompression and execution in human cells. As a test-bed we choose an RNAi cell classifier circuit25 that comprises redundant DNA sequences and is therefore amenable for compression, as are many other complex gene circuits15,18,26-28. In one example, we implement a compressed encoding of a ten-gene four-input AND gate circuit using only four genetic constructs. The compression principles applied to gene circuits can enable fitting complex genetic programs into DNA delivery vehicles with limited cargo capacity, and storing compressed and biologically inert programs in vivo for on-demand activation.

Role of population genetics in the sterile insect technique

International Nuclear Information System (INIS)

Krafsur, E.S.

2005-01-01

The detection and analysis of genetic variation in natural and laboratory populations are reviewed. The application of population genetic methods and theory can help to plan and evaluate the implementation of area-wide integrated pest management (AW-IPM) programmes that use the sterile insect technique (SIT). Population genetic studies can play an important role in estimating dispersal rates and thus gene flow among target populations, determining if sibling species exist, establishing the origin of outbreaks or reintroductions, and supporting the quality control of mass-reared colonies. The target's population history may be examined, in terms of 'bottlenecks', range fragmentations, and expansions. Genetic methods can be helpful in distinguishing wild insects from released sterile or substerile ones, and in ascertaining, together with mating cross-compatibility studies, the compatibility of mass-reared colonies with target wild insects. (author)

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. © 2011 American Institute of Physics

Selecting the Best Forecasting-Implied Volatility Model Using Genetic Programming

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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.

Genetic divergence of rubber tree estimated by multivariate techniques and microsatellite markers

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Lígia Regina Lima Gouvêa

2010-01-01

Full Text Available Genetic diversity of 60 Hevea genotypes, consisting of Asiatic, Amazonian, African and IAC clones, and pertaining to the genetic breeding program of the Agronomic Institute (IAC, Brazil, was estimated. Analyses were based on phenotypic multivariate parameters and microsatellites. Five agronomic descriptors were employed in multivariate procedures, such as Standard Euclidian Distance, Tocher clustering and principal component analysis. Genetic variability among the genotypes was estimated with 68 selected polymorphic SSRs, by way of Modified Rogers Genetic Distance and UPGMA clustering. Structure software in a Bayesian approach was used in discriminating among groups. Genetic diversity was estimated through Nei's statistics. The genotypes were clustered into 12 groups according to the Tocher method, while the molecular analysis identified six groups. In the phenotypic and microsatellite analyses, the Amazonian and IAC genotypes were distributed in several groups, whereas the Asiatic were in only a few. Observed heterozygosity ranged from 0.05 to 0.96. Both high total diversity (H T' = 0.58 and high gene differentiation (Gst' = 0.61 were observed, and indicated high genetic variation among the 60 genotypes, which may be useful for breeding programs. The analyzed agronomic parameters and SSRs markers were effective in assessing genetic diversity among Hevea genotypes, besides proving to be useful for characterizing genetic variability.

Evolving rule-based systems in two medical domains using genetic programming.

Science.gov (United States)

Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan; Axer, Hubertus; Bjerregaard, Beth; von Keyserlingk, Diedrich Graf

2004-11-01

To demonstrate and compare the application of different genetic programming (GP) based intelligent methodologies for the construction of rule-based systems in two medical domains: the diagnosis of aphasia's subtypes and the classification of pap-smear examinations. Past data representing (a) successful diagnosis of aphasia's subtypes from collaborating medical experts through a free interview per patient, and (b) correctly classified smears (images of cells) by cyto-technologists, previously stained using the Papanicolaou method. Initially a hybrid approach is proposed, which combines standard genetic programming and heuristic hierarchical crisp rule-base construction. Then, genetic programming for the production of crisp rule based systems is attempted. Finally, another hybrid intelligent model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems. Results denote the effectiveness of the proposed systems, while they are also compared for their efficiency, accuracy and comprehensibility, to those of an inductive machine learning approach as well as to those of a standard genetic programming symbolic expression approach. The proposed GP-based intelligent methodologies are able to produce accurate and comprehensible results for medical experts performing competitive to other intelligent approaches. The aim of the authors was the production of accurate but also sensible decision rules that could potentially help medical doctors to extract conclusions, even at the expense of a higher classification score achievement.

Modelling the effect of structural QSAR parameters on skin penetration using genetic programming

International Nuclear Information System (INIS)

Chung, K K; Do, D Q

2010-01-01

In order to model relationships between chemical structures and biological effects in quantitative structure–activity relationship (QSAR) data, an alternative technique of artificial intelligence computing—genetic programming (GP)—was investigated and compared to the traditional method—statistical. GP, with the primary advantage of generating mathematical equations, was employed to model QSAR data and to define the most important molecular descriptions in QSAR data. The models predicted by GP agreed with the statistical results, and the most predictive models of GP were significantly improved when compared to the statistical models using ANOVA. Recently, artificial intelligence techniques have been applied widely to analyse QSAR data. With the capability of generating mathematical equations, GP can be considered as an effective and efficient method for modelling QSAR data

A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics

Science.gov (United States)

Kobayashi, Takahisa; Simon, Donald L.

2001-01-01

In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.

Lesbian motherhood and mitochondrial replacement techniques: reproductive freedom and genetic kinship.

Science.gov (United States)

Cavaliere, Giulia; Palacios-González, César

2018-02-28

In this paper, we argue that lesbian couples who wish to have children who are genetically related to both of them should be allowed access to mitochondrial replacement techniques (MRTs). First, we provide a brief explanation of mitochondrial diseases and MRTs. We then present the reasons why MRTs are not, by nature, therapeutic. The upshot of the view that MRTs are non-therapeutic techniques is that their therapeutic potential cannot be invoked for restricting their use only to those cases where a mitochondrial DNA disease could be 'cured'. We then argue that a positive case for MRTs is justified by an appeal to reproductive freedom, and that the criteria to access these techniques should hence be extended to include lesbian couples who wish to share genetic parenthood. Finally, we consider a potential objection to our argument: that the desire to have genetically related kin is not a morally sufficient reason to allow lesbian couples to access MRTs. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Guidelines on the use of molecular genetics in reintroduction programs

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Michael K. Schwartz

2005-01-01

The use of molecular genetics can play a key role in reintroduction efforts. Prior to the introduction of any individuals, molecular genetics can be used to identify the most appropriate source population for the reintroduction, ensure that no relic populations exist in the reintroduction area, and guide captive breeding programs. The use of molecular genetics post-...

Genetic basis of the sterile insect technique

International Nuclear Information System (INIS)

Robinson, A.S.

2005-01-01

The use of the sterile insect technique (SIT) for insect control relies on the introduction of sterility in the females of the wild population. This sterility is produced following the mating of these females with released males carrying, in their sperm, dominant lethal mutations that have been induced by ionizing radiation. The reasons why the SIT can only be effective when the induced sterility in the released males is in the form of dominant lethal mutations, and not some form of sperm inactivation, are discussed, together with the relationship of dominant lethal mutations to dose, sex, developmental stage and the particular species. The combination of genetic sterility with that induced by radiation is also discussed in relation to the use of genetic sexing strains of the Mediterranean fruit fly Ceratitis capitata (Wiedemann) in area-wide integrated pest management (AW-IPM) programmes that integrate the SIT. A case is made to lower the radiation dose used in such programmes so as to produce a more competitive sterile insect. Increased competitiveness can also be achieved by using different radiation environments. As well as radiation-induced sterility, natural mechanisms can be recruited, especially the use of hybrid sterility exemplified by a successful field trial with tsetse flies Glossina spp. in the 1940s. Genetic transformation will make some impact on the SIT, especially regarding the introduction of markers for released flies, and the construction of genetic sexing strains. It is concluded that using a physical process, such as radiation, will always have significant advantages over genetic and other methods of sterilization for the large-scale application of the SIT. (author)

Drag reduction of a car model by linear genetic programming control

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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.

Non-linear nuclear engineering models as genetic programming application; Modelos nao-lineares de engenharia nuclear como aplicacao de programacao genetica

Energy Technology Data Exchange (ETDEWEB)

Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

1997-12-01

This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs.

Traditional genetic improvement and use of biotechnological techniques in searching of resistance to main fungi pathogens of Musa spp.

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Michel Leiva-Mora

2006-07-01

Full Text Available Bananas and plantain are important food staple in human diet, even cooked or consumed fresh. Fungal diseases caused by Fusarium oxysporum f. sp. cubense (Foc and Mycosphaerella fijiensis have threated to distroy Musa spp. Those crops are difficult to breed genetically because they are steriles, do not produce fertil seeds and they are partenocarpic. Genetic crossing by hibridization have been used successfully in FHIA and IITA Musa breeding programs, they have released numerous improved hybrids to those diseases. Plant Biotechnology has developed a set of techniques for Musa micropropagation to increase multiplication rates, healthy and safety plant material for plantation. Mutagenic techniques, somaclonal variation, somatic embryogenesis and more recient genetic transformation have enabled advances and complementation with clasical Musa breeding for searching resistance to principal fungal pathogen of Musa spp. Field evaluation systems to find Musa resistant genotypes to Foc and M. fijiensis have demostrated to be usefull but laborious. Nevertheless to enhance eficacy in selection of promissory genotypes the development of reproducible early evaluation methodologies by using fungal pathogens or their derivates is needed. Key words: evaluation and selection, Fusarium oxysporum, improvement

Considering genetic characteristics in German Holstein breeding programs.

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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

Genetics and bioethics: how our thinking has changed since 1969.

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Walters, LeRoy

2012-02-01

In 1969, the field of human genetics was in its infancy. Amniocentesis was a new technique for prenatal diagnosis, and a newborn genetic screening program had been established in one state. There were also concerns about the potential hazards of genetic engineering. A research group at the Hastings Center and Paul Ramsey pioneered in the discussion of genetics and bioethics. Two principal techniques have emerged as being of enduring importance: human gene transfer research and genetic testing and screening. This essay tracks the development and use of these techniques and considers the ethical issues that they raise.

Polyglot programming in applications used for genetic data analysis.

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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.

Genetic variability of broodstocks of restocking programs in Brazil

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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.

Genetic similarity of polyploids - A new version of the computer program POPDIST (ver. 1.2.0) considers intraspecific genetic differentiation

DEFF Research Database (Denmark)

Tomiuk, Jürgen; Guldbrandtsen, Bernt; Loeschcke, Volker

2009-01-01

For evolutionary studies of polyploid species estimates of the genetic identity between species with different degrees of ploidy are particularly required because gene counting in samples of polyploid individuals often cannot be done, e.g., in triploids the phenotype AB can be genotypically either...... ABB or AAB. We recently suggested a genetic distance measure that is based on phenotype counting and made available the computer program POPDIST. The program provides maximum-likelihood estimates of the genetic identities and distances between polyploid populations, but this approach...

Performance improvement of developed program by using multi-thread technique

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Surasak Jabal

2015-03-01

Full Text Available This research presented how to use a multi-thread programming technique to improve the performance of a program written by Windows Presentation Foundation (WPF. The Computer Assisted Instruction (CAI software, named GAME24, was selected to use as a case study. This study composed of two main parts. The first part was about design and modification of the program structure upon the Object Oriented Programing (OOP approach. The second part was about coding the program using the multi-thread technique which the number of threads were based on the calculated Catalan number. The result showed that the multi-thread programming technique increased the performance of the program 44%-88% compared to the single-thread technique. In addition, it has been found that the number of cores in the CPU also increase the performance of multithreaded program proportionally.

Using genetic programming to find Lyapunov functions

NARCIS (Netherlands)

Soute, I.A.C.; Molengraft, van de M.J.G.; Angelis, G.Z.; Ryan, C; Spector, L.

2001-01-01

In this paper Genetic Programming is used to find Lyapunov functions for (non)linear dif ferential equations of autonomous systems. As Lyapunov functions can be difficult to find, we use OP to make the decisions concerning the form of the Lyapunov function. As an e5cample two systems are taken to

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.

Linear genetic programming application for successive-station monthly streamflow prediction

Science.gov (United States)

Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit

2014-09-01

In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.

A Simulation of AI Programming Techniques in BASIC.

Science.gov (United States)

Mandell, Alan

1986-01-01

Explains the functions of and the techniques employed in expert systems. Offers the program "The Periodic Table Expert," as a model for using artificial intelligence techniques in BASIC. Includes the program listing and directions for its use on: Tandy 1000, 1200, and 2000; IBM PC; PC Jr; TRS-80; and Apple computers. (ML)

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

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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.

Depauperate genetic variability detected in the American and European bison using genomic techniques

DEFF Research Database (Denmark)

Pertoldi, Cino; Tokarska, Magorzata; Wójcik, Jan M

2009-01-01

, likely reflecting drift overwhelming selection. We suggest that utilization of genome-wide screening technologies, followed by utilization of less expensive techniques (e.g. VeraCode and Fluidigm EP1), holds large potential for genetic monitoring of populations. Additionally, these techniques will allow...

Estimation of genetic variability and heritability of wheat agronomic traits resulted from some gamma rays irradiation techniques

International Nuclear Information System (INIS)

Wijaya Murti Indriatama; Trikoesoemaningtyas; Syarifah Iis Aisyah; Soeranto Human

2016-01-01

Gamma irradiation techniques have significant effect on frequency and spectrum of macro-mutation but the study of its effect on micro-mutation that related to genetic variability on mutated population is very limited. The aim of this research was to study the effect of gamma irradiation techniques on genetic variability and heritability of wheat agronomic characters at M2 generation. This research was conducted from July to November 2014, at Cibadak experimental station, Indonesian Center for Agricultural Biotechnology and Genetic Resources Research and Development, Ministry of Agriculture. Three introduced wheat breeding lines (F-44, Kiran-95 & WL-711) were treated by 3 gamma irradiation techniques (acute, fractionated and intermittent). M1 generation of combination treatments were planted and harvested its spike individually per plants. As M2 generation, seeds of 75 M1 spike were planted at the field with one row one spike method and evaluated on the agronomic characters and its genetic components. The used of gamma irradiation techniques decreased mean but increased range values of agronomic traits in M2 populations. Fractionated irradiation induced higher mean and wider range on spike length and number of spike let per spike than other irradiation techniques. Fractionated and intermittent irradiation resulted greater variability of grain weight per plant than acute irradiation. The number of tillers, spike weight, grain weight per spike and grain weight per plant on M2 population resulted from induction of three gamma irradiation techniques have high estimated heritability and broad sense of genetic variability coefficient values. The three gamma irradiation techniques increased genetic variability of agronomic traits on M2 populations, except plant height. (author)

Genetic programming over context-free languages with linear constraints for the knapsack problem: first results.

Science.gov (United States)

Bruhn, Peter; Geyer-Schulz, Andreas

2002-01-01

In this paper, we introduce genetic programming over context-free languages with linear constraints for combinatorial optimization, apply this method to several variants of the multidimensional knapsack problem, and discuss its performance relative to Michalewicz's genetic algorithm with penalty functions. With respect to Michalewicz's approach, we demonstrate that genetic programming over context-free languages with linear constraints improves convergence. A final result is that genetic programming over context-free languages with linear constraints is ideally suited to modeling complementarities between items in a knapsack problem: The more complementarities in the problem, the stronger the performance in comparison to its competitors.

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

Molecular profiling techniques as tools to detect potential unintended effects in genetically engineered maize

CSIR Research Space (South Africa)

Barros, E

2010-05-01

Full Text Available Molecular Profiling Techniques as Tools to Detect Potential Unintended Effects in Genetically Engineered Maize Eugenia Barros Introduction In the early stages of production and commercialization of foods derived from genetically engineered (GE) plants... systems. In a recent paper published in Plant Biotechnology Journal,4 we compared two transgenic white maize lines with the non-transgenic counterpart to investigate two possible sources of variation: genetic engineering and environmental variation...

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.

Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

International Nuclear Information System (INIS)

Ortiz R, J. M.; Martinez B, M. R.; Vega C, H. R.; Gallego D, E.; Lorente F, A.; Mendez V, R.; Los Arcos M, J. M.; Guerrero A, J. E.

2011-01-01

With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks (Ann) have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Ann still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning Ann parameters. In recent years the use of hybrid technologies, combining Ann and genetic algorithms, has been utilized to. In this work, several Ann topologies were trained and tested using Ann and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out. (Author)

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

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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

Swarm, genetic and evolutionary programming algorithms applied to multiuser detection

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Paul Jean Etienne Jeszensky

2005-02-01

Full Text Available In this paper, the particles swarm optimization technique, recently published in the literature, and applied to Direct Sequence/Code Division Multiple Access systems (DS/CDMA with multiuser detection (MuD is analyzed, evaluated and compared. The Swarm algorithm efficiency when applied to the DS-CDMA multiuser detection (Swarm-MuD is compared through the tradeoff performance versus computational complexity, being the complexity expressed in terms of the number of necessary operations in order to reach the performance obtained through the optimum detector or the Maximum Likelihood detector (ML. The comparison is accomplished among the genetic algorithm, evolutionary programming with cloning and Swarm algorithm under the same simulation basis. Additionally, it is proposed an heuristics-MuD complexity analysis through the number of computational operations. Finally, an analysis is carried out for the input parameters of the Swarm algorithm in the attempt to find the optimum parameters (or almost-optimum for the algorithm applied to the MuD problem.

Management intensity and genetics affect loblolly pine seedling performance

Science.gov (United States)

Scott D. Roberts; Randall J. Rousseau; B. Landis Herrin

2012-01-01

Capturing potential genetic gains from tree improvement programs requires selection of the appropriate genetic stock and application of appropriate silvicultural management techniques. Limited information is available on how specific loblolly pine varietal genotypes perform under differing growing environments and management approaches. This study was established in...

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.

Comparative Analysis of Rank Aggregation Techniques for Metasearch Using Genetic Algorithm

Science.gov (United States)

Kaur, Parneet; Singh, Manpreet; Singh Josan, Gurpreet

2017-01-01

Rank Aggregation techniques have found wide applications for metasearch along with other streams such as Sports, Voting System, Stock Markets, and Reduction in Spam. This paper presents the optimization of rank lists for web queries put by the user on different MetaSearch engines. A metaheuristic approach such as Genetic algorithm based rank…

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

Learning Programming Technique through Visual Programming Application as Learning Media with Fuzzy Rating

Science.gov (United States)

Buditjahjanto, I. G. P. Asto; Nurlaela, Luthfiyah; Ekohariadi; Riduwan, Mochamad

2017-01-01

Programming technique is one of the subjects at Vocational High School in Indonesia. This subject contains theory and application of programming utilizing Visual Programming. Students experience some difficulties to learn textual learning. Therefore, it is necessary to develop media as a tool to transfer learning materials. The objectives of this…

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.

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

Science.gov (United States)

Russell, Liane B

2013-01-01

The large mouse genetics program at the Oak Ridge National Laboratory (ORNL) is often remembered 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

Data verification and evaluation techniques for groundwater monitoring programs

International Nuclear Information System (INIS)

Mercier, T.M.; Turner, R.R.

1990-12-01

To ensure that data resulting from groundwater monitoring programs are of the quality required to fulfill program objectives, it is suggested that a program of data verification and evaluation be implemented. These procedures are meant to supplement and support the existing laboratory quality control/quality assurance programs by identifying aberrant data resulting from a variety of unforeseen circumstances: sampling problems, data transformations in the lab, data input at the lab, data transfer, end-user data input. Using common-sense principles, pattern recognition techniques, and hydrogeological principles, a computer program was written which scans the data for suspected abnormalities and produces a text file stating sample identifiers, the suspect data, and a statement of how the data has departed from the expected. The techniques described in this paper have been developed to support the Y-12 Plant Groundwater Protection Program Management Plan

A NEW MUTATION OPERATOR IN GENETIC PROGRAMMING

Directory of Open Access Journals (Sweden)

Anuradha Purohit

2013-01-01

Full Text Available This paper proposes a new type of mutation operator, FEDS (Fitness, Elitism, Depth, and Size mutation in genetic programming. The concept behind the new mutation operator is inspired from already introduced FEDS crossover operator to handle the problem of code bloating. FEDS mutation operates by using local elitism replacement in combination with depth limit and size of the trees to reduce bloat with a subsequent improvement in the performance of trees (program structures. We have designed a multiclass classifier for some benchmark datasets to test the performance of proposed mutation. The results show that when the initial run uses FEDS crossover and the concluding run uses FEDS mutation, then not only is the final result significantly improved but there is reduction in bloat also.

Report on an Investigation into an Entry Level Clinical Doctorate for the Genetic Counseling Profession and a Survey of the Association of Genetic Counseling Program Directors.

Science.gov (United States)

Reiser, Catherine; LeRoy, Bonnie; Grubs, Robin; Walton, Carol

2015-10-01

The master's degree is the required entry-level degree for the genetic counseling profession in the US and Canada. In 2012 the Association of Genetic Counseling Program Directors (AGCPD) passed resolutions supporting retention of the master's as the entry-level and terminal degree and opposing introduction of an entry-level clinical doctorate (CD) degree. An AGCPD workgroup surveyed directors of all 34 accredited training programs with the objective of providing the Genetic Counseling Advanced Degrees Task Force (GCADTF) with information regarding potential challenges if master's programs were required to transition to an entry-level CD. Program demographics, projected ability to transition to an entry-level CD, factors influencing ability to transition, and potential effects of transition on programs, students and the genetic counseling workforce were characterized. Two programs would definitely be able to transition, four programs would close, thirteen programs would be at risk to close and fourteen programs would probably be able to transition with varying degrees of difficulty. The most frequently cited limiting factors were economic, stress on clinical sites, and administrative approval of a new degree/program. Student enrollment under an entry-level CD model was projected to decrease by 26.2 %, negatively impacting the workforce pipeline. The results further illuminate and justify AGCPD's position to maintain the master's as the entry-level degree.

Genetics of the Mediterranean fruit fly in the sterile insect technique

International Nuclear Information System (INIS)

Roessler, Y.

1997-01-01

Altogether 27 morphological mutations on the five autosomes of the Mediterranean fruit fly, Ceratitis capitata (Wied.), have been isolated and studied in the author's laboratory during 22 years of research on the genetics of this species. Of the 27 loci, 18 were located on chromosomes 4 and 5. No mutant loci were identified on the sex chromosome in the laboratory. Linkage relations, map distances and linear arrangements on the respective chromosomes were established for most of the 27 mutant traits. The wp and dp traits were utilized in the construction of genetic sexing lines in laboratories involved in studies of the sterile insect technique. The occurrence and consequences of male recombination are discussed. (author)

Moving Speciation Genetics Forward: Modern Techniques Build on Foundational Studies in Drosophila.

Science.gov (United States)

Castillo, Dean M; Barbash, Daniel A

2017-11-01

The question of how new species evolve has been examined at every level, from macroevolutionary patterns of diversification to molecular population genetic analyses of specific genomic regions between species pairs. Drosophila has been at the center of many of these research efforts. Though our understanding of the speciation process has grown considerably over the past few decades, very few genes have been identified that contribute to barriers to reproduction. The development of advanced molecular genetic and genomic methods provides promising avenues for the rapid discovery of more genes that contribute to speciation, particularly those involving prezygotic isolation. The continued expansion of tools and resources, especially for species other than Drosophila melanogaster , will be most effective when coupled with comparative approaches that reveal the genetic basis of reproductive isolation across a range of divergence times. Future research programs in Drosophila have high potential to answer long-standing questions in speciation. These include identifying the selective forces that contribute to divergence between populations and the genetic basis of traits that cause reproductive isolation. The latter can be expanded upon to understand how the genetic basis of reproductive isolation changes over time and whether certain pathways and genes are more commonly involved. Copyright © 2017 by the Genetics Society of America.

Genetic counseling for schizophrenia: a review of referrals to a provincial medical genetics program from 1968–2007

Science.gov (United States)

Hunter, MJ; Hippman, Catriona; Honer, William G; Austin, Jehannine C.

2014-01-01

Purpose Recent studies have shown that individuals with schizophrenia and their family members are interested in genetic counseling, but few have received this service. We conducted an exploratory, retrospective study to describe (a) the population of individuals who were referred to the provincial program for genetic counseling for a primary indication of schizophrenia, and (b) trends in number of referrals between 1968 and 2007. Methods Referrals for a primary indication of schizophrenia were identified through the provincial program database. Charts were reviewed and the following information was recorded: discipline of referring physician, demographics, psychiatric diagnosis, referred individual’s and partner’s (if applicable) family history, and any current pregnancy history. Data were characterized using descriptive statistics. Results Between 1968 and 2007, 288 referrals were made for a primary indication of schizophrenia. Most referrals were made: (a) for individuals who had a first-degree family member with schizophrenia, rather than for affected individuals, (b) for preconception counseling, and (c) by family physicians (69%), with only 2% by psychiatrists. Conclusions In British Columbia, individuals affected with schizophrenia and their family members are rarely referred for psychiatric genetic counseling. There is a need to identify barriers to psychiatric genetic counseling and develop strategies to improve access. PMID:20034078

Implementation of the program for conservation and sustainable utilization of forest genetic resources in Republic of Serbia

Directory of Open Access Journals (Sweden)

Šijačić-Nikolić Mirjana

2017-01-01

Full Text Available Program for conservation and sustainable utilization of forest genetic resources has been defined for 2016-2025 period and it is a base for concrete activities in this field. This Program could be divided into several parts that deal with: the legal framework for the conservation and sustainable utilization of forest genetic resources; status of forest genetic resources in Serbia; previous activities on the conservation of forest genetic resources; and objectives, priorities and measures of conservation. The Program should have an impact on the development of the forestry sector through the following activities: conservation and sustainable utilization of the available gene pool; improving forest management in accordance with conservation principles; improving the production of reproductive material of forest trees; make the public awareness of the need for conservation and sustainable utilization of forest genetic resources; fulfillment of international obligations related to this field and the possibility of joining FAO activities related to forest genetic resources - development of the national report as a part of the publication The State of the World's Forest Genetic Resources. Implementation of the Program will depend upon raising the awareness on the importance, conservation and sustainable utilization of forest genetic resources, as a precondition for the forests survival; it will depend of funds that will be allocated for this purpose and enthusiasm of people who deal with these issues.

Including nonadditive genetic effects in mating programs to maximize dairy farm profitability.

Science.gov (United States)

Aliloo, H; Pryce, J E; González-Recio, O; Cocks, B G; Goddard, M E; Hayes, B J

2017-02-01

We compared the outcome of mating programs based on different evaluation models that included nonadditive genetic effects (dominance and heterozygosity) in addition to additive effects. The additive and dominance marker effects and the values of regression on average heterozygosity were estimated using 632,003 single nucleotide polymorphisms from 7,902 and 7,510 Holstein cows with calving interval and production (milk, fat, and protein yields) records, respectively. Expected progeny values were computed based on the estimated genetic effects and genotype probabilities of hypothetical progeny from matings between the available genotyped cows and the top 50 young genomic bulls. An index combining the traits based on their economic values was developed and used to evaluate the performance of different mating scenarios in terms of dollar profit. We observed that mating programs with nonadditive genetic effects performed better than a model with only additive effects. Mating programs with dominance and heterozygosity effects increased milk, fat, and protein yields by up to 38, 1.57, and 1.21 kg, respectively. The inclusion of dominance and heterozygosity effects decreased calving interval by up to 0.70 d compared with random mating. The average reduction in progeny inbreeding by the inclusion of nonadditive genetic effects in matings compared with random mating was between 0.25 to 1.57 and 0.64 to 1.57 percentage points for calving interval and production traits, respectively. The reduction in inbreeding was accompanied by an average of A$8.42 (Australian dollars) more profit per mating for a model with additive, dominance, and heterozygosity effects compared with random mating. Mate allocations that benefit from nonadditive genetic effects can improve progeny performance only in the generation where it is being implemented, and the gain from specific combining abilities cannot be accumulated over generations. Continuous updating of genomic predictions and mate

Genetic dissimilarity among jabuticaba trees native to southwestern Paraná, Brazil

Directory of Open Access Journals (Sweden)

Moeses Andrigo Danner

2011-06-01

Full Text Available Knowledge on the genetic diversity within and between genotype groups is of great importance for breeding programs. The purpose of this study was to estimate the genetic dissimilarity among 36 native jabuticaba trees (Plinia cauliflora from five sites in the southwestern region of Paraná, Brazil. Sixteen fruit traits were analyzed, based on multivariate techniques (canonical variables, Tocher and UPGMA, using Mahalanobis' distance as dissimilarity measure. By the techniques of clustering and graphic dispersion, together with the comparison of means, the genetic diversity among native jabuticaba trees was efficiently identified, indicating a high potential of these genotypes for breeding programs. The traits of greatest importance for dissimilarity were percentage of pulp and of skin, which are easily measured. The clustering structure is related to the collection sites and for breeding programs, genotypes from different sites should be crossed to generate progenies to be tested. Genotypes 'CV5' and 'VT3' should be conserved in genebanks, due to its important agronomic traits.

Control of Angra 1' PZR by a fuzzy rule base build through genetic programming

International Nuclear Information System (INIS)

Caldas, Gustavo Henrique Flores; Schirru, Roberto

2002-01-01

There is an optimum pressure for the normal operation of nuclear power plant reactors and thresholds that must be respected during transients, what make the pressurizer an important control mechanism. Inside a pressurizer there are heaters and a shower. From their actuation levels, they control the vapor pressure inside the pressurizer and, consequently, inside the primary circuit. Therefore, the control of the pressurizer consists in controlling the actuation levels of the heaters and of the shower. In the present work this function is implemented through a fuzzy controller. Besides the efficient way of exerting control, this approach presents the possibility of extracting knowledge of how this control is been made. A fuzzy controller consists basically in an inference machine and a rule base, the later been constructed with specialized knowledge. In some circumstances, however, this knowledge is not accurate, and may lead to non-efficient results. With the development of artificial intelligence techniques, there wore found methods to substitute specialists, simulating its knowledge. Genetic programming is an evolutionary algorithm particularly efficient in manipulating rule base structures. In this work genetic programming was used as a substitute for the specialist. The goal is to test if an irrational object, a computer, is capable, by it self, to find out a rule base reproducing a pre-established actuation levels profile. The result is positive, with the discovery of a fuzzy rule base presenting an insignificant error. A remarkable result that proves the efficiency of the approach. (author)

Genetic basis of the sterile insect technique

International Nuclear Information System (INIS)

Robinson, A.S.

2014-01-01

The use of the sterile insect technique for insect control relies on the introduction of sterility in the females of the wild population. This sterility is produced following the mating of these females with released males carrying, in their sperm, dominant lethal mutations that have been induced by ionizing radiation. As well as radiation-induced sterility, natural mechanisms can be recruited, especially the use of hybrid sterility. Radiation is usually one of the last procedures that insects undergo before leaving mass-rearing facilities for release in the field. It is essential that the dosimetry of the radiation source be checked to ensure that all the insects receive the required minimum dose. A dose should be chosen that maximizes the level of introduced sterility in the wild females in the field. Irradiation in nitrogen can provide protection against the detrimental somatic effects of radiation. Currently, the development of molecular methods to sterilize pest insects in the field, by the release of fertile insects carrying trans genes, is very much in vogue. It is concluded that using a physical process, such as radiation, will always have significant advantages over genetic and other methods of sterilization for the large-scale application of the sterile insect technique. (author)

Geometric Semantic Genetic Programming Algorithm and Slump Prediction

OpenAIRE

Xu, Juncai; Shen, Zhenzhong; Ren, Qingwen; Xie, Xin; Yang, Zhengyu

2017-01-01

Research on the performance of recycled concrete as building material in the current world is an important subject. Given the complex composition of recycled concrete, conventional methods for forecasting slump scarcely obtain satisfactory results. Based on theory of nonlinear prediction method, we propose a recycled concrete slump prediction model based on geometric semantic genetic programming (GSGP) and combined it with recycled concrete features. Tests show that the model can accurately p...

Weighted thinned linear array design with the iterative FFT technique

CSIR Research Space (South Africa)

Du Plessis, WP

2011-09-01

Full Text Available techniques utilise simulated annealing [3]?[5], [10], mixed integer linear programming [7], genetic algorithms [9], and a hyrid approach combining a genetic algorithm and a local optimiser [8]. The iterative Fourier technique (IFT) developed by Keizer [2... algorithm being well- suited to obtaining low CTRs. Test problems from the literature are considered, and the results obtained with the IFT considerably exceed those achieved with other algorithms. II. DESCRIPTION OF THE ALGORITHM A flowchart describing...

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

DOE transporation programs - computerized techniques

Energy Technology Data Exchange (ETDEWEB)

Joy, D.S.; Johnson, P.E.; Fore, C.S.; Peterson, B.E.

1983-01-01

One of the major thrusts of the transportation programs at the Oak Ridge National Laboratory has been the development of a number of computerized transportation programs and data bases. The U.S. Department of Energy (DOE) is supporting these efforts through the Transportation Technology Center at Sandia National Laboratories and the Tranportation Operations and Traffic Management (TOTM) organization at DOE Headquarters. Initially this project was centered upon research activities. However, since these tools provide traffic managers and key personnel involved in preshipment planning with a unique resource for ensuring that the movement of radioactive materials can be properly accomplished, additional interest and support is coming from the operational side of DOE. The major accomplishments include the development of two routing models (one for rail shipments and the other for highway shipments), an emergency response assistance program, and two data bases containing pertinent legislative and regulatory information. This paper discusses the mose recent advances in, and additions to, these computerized techniques and provides examples of how they are used.

Advanced network programming principles and techniques : network application programming with Java

CERN Document Server

Ciubotaru, Bogdan

2013-01-01

Answering the need for an accessible overview of the field, this text/reference presents a manageable introduction to both the theoretical and practical aspects of computer networks and network programming. Clearly structured and easy to follow, the book describes cutting-edge developments in network architectures, communication protocols, and programming techniques and models, supported by code examples for hands-on practice with creating network-based applications. Features: presents detailed coverage of network architectures; gently introduces the reader to the basic ideas underpinning comp

76 FR 72424 - Submission for OMB Review; Comment Request Information Program on the Genetic Testing Registry

Science.gov (United States)

2011-11-23

... particular tests; and (3) facilitating genetic and genomic data-sharing for research and new scientific...; Comment Request Information Program on the Genetic Testing Registry AGENCY: National Institutes of Health... currently valid OMB control number. Proposed Collection: Title: The Genetic Testing Registry; Type of...

The Use of TILLING Technique to Detect Mutations and genetic diversity in Potato

International Nuclear Information System (INIS)

Elias, R; Al-Safadi, B; Till, B

2008-01-01

TILLING technique has been used, for the first time, to detect genetic variation, at the molecular level, among potato mutants (induced by gamma irradiation) and genetic diversity among 3 potato cultivars. Three potato mutant lines (every mutant represents a cultivar) tolerant to salinity have been used along with their controls. Three primer pairs were designed with the help of Potato Genome Sequencing Consortium on the web and were evaluated using agarose gel then sequencing. Primer pairs passing these tests were fluorescently labeled. Li-Cor based TILLING was applied using 2 forward primers one of them is labeled and 2 reverse primers one of them is labeled. The results have shown the success of using this technique on potato (tetraploid species) where the average density of nucleotide polymorphisms per sample was 16 polymorphisms per 1 kb. The optimal concentration was also determined between 0.1 and 1 ng/ul for potato genomic DNAs to be used in Li-Cor based TILLING assays. (author)

US Department of Energy transportation programs: computerized techniques

International Nuclear Information System (INIS)

Joy, D.S.; Johnson, P.E.; Fore, C.S.; Peterson, B.E.

1984-01-01

The US Department of Energy is currently sponsoring the development of four specialized computer-based transportation programs at Oak Ridge National Laboratory. The programs function as research tools that provide unique computerized techniques for planning the safe shipment of radioactive and hazardous materials. Major achievements include the development of interactive rail and highway routing models, an emergency response assistance program, a data base focusing on legislative requirements, and a resource file identifying key state and local contacts. A discussion of the programs and data bases is presented, and several examples reflecting each project's applications to the overall DOE transportation program are provided. The interface of these programs offers a dynamic resource of data for use during preshipment planning stages. 10 refs., 4 figs., 2 tabs

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.

Improvements of methanogenesis by genetic techniques

International Nuclear Information System (INIS)

Baresi, L.

1985-01-01

The objective of this research is to characterize the genetic system of one or two strains of methanogenic bacteria. Both ultraviolet exposure and chemical screening will be used to isolate mutant species. These species will be tested for genetic recombination. Bacteriophages and plasmids will be sought. Two species, Methanococcus voltae and Methanobacterium thermoautotrophicum, will be subjected to extensive screening and manipulation. Nutritional mutants of these two strains will be studied to determine uptake rates. Once a set of satisfactory mutants is obtained, two types of genetic recombination experiments (conjugation and DNA transformation) will be carried out

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.

Home visit program improves technique survival in peritoneal dialysis.

Science.gov (United States)

Martino, Francesca; Adıbelli, Z; Mason, G; Nayak, A; Ariyanon, W; Rettore, E; Crepaldi, Carlo; Rodighiero, Mariapia; Ronco, Claudio

2014-01-01

Peritoneal dialysis (PD) is a home therapy, and technique survival is related to the adherence to PD prescription at home. The presence of a home visit program could improve PD outcomes. We evaluated its effects on clinical outcome during 1 year of follow-up. This was a case-control study. The case group included all 96 patients who performed PD in our center on January 1, 2013, and who attended a home visit program; the control group included all 92 patients who performed PD on January 1, 2008. The home visit program consisted of several additional visits to reinforce patients' confidence in PD management in their own environment. Outcomes were defined as technique failure, peritonitis episode, and hospitalization. Clinical and dialysis features were evaluated for each patient. The case group was significantly older (p = 0.048), with a lower grade of autonomy (p = 0.033), but a better hemoglobin level (p = 0.02) than the control group. During the observational period, we had 11 episodes of technique failure. We found a significant reduction in the rate of technique failure in the case group (p = 0.004). Furthermore, survival analysis showed a significant extension of PD treatment in the patients supported by the home visit program (52 vs. 48.8 weeks, p = 0.018). We did not find any difference between the two groups in terms of peritonitis and hospitalization rate; however, trends toward a reduction of Gram-positive peritonitis rates as well as prevalence and duration of hospitalization related to PD problems were identified in the case group. The retrospective nature of the analysis was a limitation of this study. The home visit program improves the survival of PD patients and could reduce the rate of Gram-positive peritonitis and hospitalization. Video Journal Club "Cappuccino with Claudio Ronco" at http://www.karger.com/?doi=365168.

Evolutionary Computation Techniques for Predicting Atmospheric Corrosion

Directory of Open Access Journals (Sweden)

Amine Marref

2013-01-01

Full Text Available Corrosion occurs in many engineering structures such as bridges, pipelines, and refineries and leads to the destruction of materials in a gradual manner and thus shortening their lifespan. It is therefore crucial to assess the structural integrity of engineering structures which are approaching or exceeding their designed lifespan in order to ensure their correct functioning, for example, carrying ability and safety. An understanding of corrosion and an ability to predict corrosion rate of a material in a particular environment plays a vital role in evaluating the residual life of the material. In this paper we investigate the use of genetic programming and genetic algorithms in the derivation of corrosion-rate expressions for steel and zinc. Genetic programming is used to automatically evolve corrosion-rate expressions while a genetic algorithm is used to evolve the parameters of an already engineered corrosion-rate expression. We show that both evolutionary techniques yield corrosion-rate expressions that have good accuracy.

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

Research on non-uniform strain profile reconstruction along fiber Bragg grating via genetic programming algorithm and interrelated experimental verification

Science.gov (United States)

Zheng, Shijie; Zhang, Nan; Xia, Yanjun; Wang, Hongtao

2014-03-01

A new heuristic strategy for the non-uniform strain profile reconstruction along Fiber Bragg Gratings is proposed in this paper, which is based on the modified transfer matrix and Genetic Programming(GP) algorithm. The present method uses Genetic Programming to determine the applied strain field as a function of position along the fiber length. The structures that undergo adaptation in genetic programming are hierarchical structures which are different from that of conventional genetic algorithm operating on strings. GP regress the strain profile function which matches the 'measured' spectrum best and makes space resolution of strain reconstruction arbitrarily high, or even infinite. This paper also presents an experimental verification of the reconstruction of non-homogeneous strain fields using GP. The results are compared with numerical calculations of finite element method. Both the simulation examples and experimental results demonstrate that Genetic Programming can effectively reconstruct continuous profile expression along the whole FBG, and greatly improves its computational efficiency and accuracy.

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...

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

Bio-Inspired Genetic Algorithms with Formalized Crossover Operators for Robotic Applications.

Science.gov (United States)

Zhang, Jie; Kang, Man; Li, Xiaojuan; Liu, Geng-Yang

2017-01-01

Genetic algorithms are widely adopted to solve optimization problems in robotic applications. In such safety-critical systems, it is vitally important to formally prove the correctness when genetic algorithms are applied. This paper focuses on formal modeling of crossover operations that are one of most important operations in genetic algorithms. Specially, we for the first time formalize crossover operations with higher-order logic based on HOL4 that is easy to be deployed with its user-friendly programing environment. With correctness-guaranteed formalized crossover operations, we can safely apply them in robotic applications. We implement our technique to solve a path planning problem using a genetic algorithm with our formalized crossover operations, and the results show the effectiveness of our technique.

Epileptic MEG Spike Detection Using Statistical Features and Genetic Programming with KNN

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Turky N. Alotaiby

2017-01-01

Full Text Available Epilepsy is a neurological disorder that affects millions of people worldwide. Monitoring the brain activities and identifying the seizure source which starts with spike detection are important steps for epilepsy treatment. Magnetoencephalography (MEG is an emerging epileptic diagnostic tool with high-density sensors; this makes manual analysis a challenging task due to the vast amount of MEG data. This paper explores the use of eight statistical features and genetic programing (GP with the K-nearest neighbor (KNN for interictal spike detection. The proposed method is comprised of three stages: preprocessing, genetic programming-based feature generation, and classification. The effectiveness of the proposed approach has been evaluated using real MEG data obtained from 28 epileptic patients. It has achieved a 91.75% average sensitivity and 92.99% average specificity.

From evolution theory to parallel and distributed genetic

CERN Multimedia

CERN. Geneva

2007-01-01

Lecture #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 #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 increasing number of researchers to apply these techniques to a large set of problems. Given the difficulty of some problems, much effort has been applied to improving the efficiency of GP during the last few years. Among the available proposals,...

Labview advanced programming techniques, second edition

CERN Document Server

Bitter, Rick; Nawrocki, Matt

2006-01-01

Whether seeking deeper knowledge of LabVIEW®'s capabilities or striving to build enhanced VIs, professionals know they will find everything they need in LabVIEW: Advanced Programming Techniques. Now accompanied by LabVIEW 2011, this classic second edition, focusing on LabVIEW 8.0, delves deeply into the classic features that continue to make LabVIEW one of the most popular and widely used graphical programming environments across the engineering community. The authors review the front panel controls, the Standard State Machine template, drivers, the instrument I/O assistant, error handling functions, hyperthreading, and Express VIs. It covers the introduction of the Shared Variables function in LabVIEW 8.0 and explores the LabVIEW project view. The chapter on ActiveX includes discussion of the Microsoft™ .NET® framework and new examples of programming in LabVIEW using .NET. Numerous illustrations and step-by-step explanations provide hands-on guidance. Reviewing LabVIEW 8.0 and accompanied by the latest s...

Genetic diversity of tambaqui broodstocks in stock enhancement programs

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Americo Moraes Neto

2017-06-01

Full Text Available Natural populations of tambaqui (Colossoma macropomum have significantly decreased in recent decades especially due to human extraction activities. So that the environmental impact may be reduced, the restocking of fish and increase in fish production are enhanced. Genetic evaluations using molecular markers are essential for this purpose. Current study evaluates the genetic variability of two tambaqui broodstocks used in restocking programs. Sixty-five samples (33 samples from broodstock A and 32 samples from broodstock B were collected. DNA was extracted from caudal fin samples, with the amplification of four microsatellite loci: Cm1A11 (EU685307 Cm1C8 (EU685308 Cm1F4 (EU685311 and Cm1H8 (EU685315. Fourteen alleles in the stock of broodstock A were produced, five alleles for Cm1A11 locus (230, 255, 260, 270 and 276 bp, three alleles Cm1C8 (239, 260, and 273 bp, two alleles Cm1F4 (211 and 245 bp, four alleles for Cm1H8 (275, 290, 320 and 331 bp and two unique alleles were found for Cm1A11 loci (alleles 270 and 276 bp and Cm1H8 (alleles 275 and 331 bp. In broodstock B, ten alleles were produced, the same alleles of the first stock except for alleles 270 and 276 bp in Cm1A11 locus and 275 and 331 bp in Cm1H8 locus. Broodstock A revealed low frequency alleles in Cm1A11 loci, Cm1C8, Cm1F4 and Cm1H8, whereas broodstock B had no locus with low allelic frequency. Loci Cm1A11, Cm1C8 and Cm1H8 exhibited significant deficit of heterozygotes in both broodstocks, revealing changes in Hardy-Weinberg equilibrium. Genetic diversity between stocks was 0.1120, whilst genetic similarity was 0.894, with FST rate = 0.05, and Nm = 3.93, indicating gene flow between the two broodstocks. Results show that broodstocks are genetically closely related, with no great genetic variability. Strategies such as a previous genetic analysis of breeding with its marking, use of a large Ne crossing between the most genetically divergent specimens, and the introduction of new

Object oriented programming techniques applied to device access and control

International Nuclear Information System (INIS)

Goetz, A.; Klotz, W.D.; Meyer, J.

1992-01-01

In this paper a model, called the device server model, has been presented for solving the problem of device access and control faced by all control systems. Object Oriented Programming techniques were used to achieve a powerful yet flexible solution. The model provides a solution to the problem which hides device dependancies. It defines a software framework which has to be respected by implementors of device classes - this is very useful for developing groupware. The decision to implement remote access in the root class means that device servers can be easily integrated in a distributed control system. A lot of the advantages and features of the device server model are due to the adoption of OOP techniques. The main conclusion that can be drawn from this paper is that 1. the device access and control problem is adapted to being solved with OOP techniques, 2. OOP techniques offer a distinct advantage over traditional programming techniques for solving the device access problem. (J.P.N.)

Improved Genetic and Simulating Annealing Algorithms to Solve the Traveling Salesman Problem Using Constraint Programming

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M. Abdul-Niby

2016-04-01

Full Text Available The Traveling Salesman Problem (TSP is an integer programming problem that falls into the category of NP-Hard problems. As the problem become larger, there is no guarantee that optimal tours will be found within reasonable computation time. Heuristics techniques, like genetic algorithm and simulating annealing, can solve TSP instances with different levels of accuracy. Choosing which algorithm to use in order to get a best solution is still considered as a hard choice. This paper suggests domain reduction as a tool to be combined with any meta-heuristic so that the obtained results will be almost the same. The hybrid approach of combining domain reduction with any meta-heuristic encountered the challenge of choosing an algorithm that matches the TSP instance in order to get the best results.

The use of genetic programming to develop a predictor of swash excursion on sandy beaches

Science.gov (United States)

Passarella, Marinella; Goldstein, Evan B.; De Muro, Sandro; Coco, Giovanni

2018-02-01

We use genetic programming (GP), a type of machine learning (ML) approach, to predict the total and infragravity swash excursion using previously published data sets that have been used extensively in swash prediction studies. Three previously published works with a range of new conditions are added to this data set to extend the range of measured swash conditions. Using this newly compiled data set we demonstrate that a ML approach can reduce the prediction errors compared to well-established parameterizations and therefore it may improve coastal hazards assessment (e.g. coastal inundation). Predictors obtained using GP can also be physically sound and replicate the functionality and dependencies of previous published formulas. Overall, we show that ML techniques are capable of both improving predictability (compared to classical regression approaches) and providing physical insight into coastal processes.

Empirical study of self-configuring genetic programming algorithm performance and behaviour

International Nuclear Information System (INIS)

KrasnoyarskiyRabochiy prospect, Krasnoyarsk, 660014 (Russian Federation))" data-affiliation=" (Siberian State Aerospace University named after Academician M.F. Reshetnev 31 KrasnoyarskiyRabochiy prospect, Krasnoyarsk, 660014 (Russian Federation))" >Semenkin, E; KrasnoyarskiyRabochiy prospect, Krasnoyarsk, 660014 (Russian Federation))" data-affiliation=" (Siberian State Aerospace University named after Academician M.F. Reshetnev 31 KrasnoyarskiyRabochiy prospect, Krasnoyarsk, 660014 (Russian Federation))" >Semenkina, M

2015-01-01

The behaviour of the self-configuring genetic programming algorithm with a modified uniform crossover operator that implements a selective pressure on the recombination stage, is studied over symbolic programming problems. The operator's probabilistic rates interplay is studied and the role of operator variants on algorithm performance is investigated. Algorithm modifications based on the results of investigations are suggested. The performance improvement of the algorithm is demonstrated by the comparative analysis of suggested algorithms on the benchmark and real world problems

Towards ABET accreditation for a SWE program: alternative student assessment techniques

International Nuclear Information System (INIS)

Alghamdi, A.; Nasir, M.; Alnafjan, K.

2011-01-01

This paper describes assessment techniques utilized for assessing undergraduate students studying in a software engineering program. The purpose behind this work is to get the program accredited by the Accreditation Board of Engineering and Technology (ABET). Therefore, a number of applied direct and indirect assessment techniques are described. These techniques are implemented towards the end of the semester to assess the extent to which the student and course outcomes are satisfied. Consequently, results are obtained and analyzed and various learning issues are eventually identified. Finally, the paper provides suggestions for improvement in course delivery as well as learning mechanism. (author)

34 CFR 429.1 - What is the Bilingual Vocational Materials, Methods, and Techniques Program?

Science.gov (United States)

2010-07-01

... techniques for bilingual vocational training for individuals with limited English proficiency. (Authority..., and Techniques Program? 429.1 Section 429.1 Education Regulations of the Offices of the Department of... MATERIALS, METHODS, AND TECHNIQUES PROGRAM General § 429.1 What is the Bilingual Vocational Materials...

Microchip capillary gel electrophoresis using programmed field strength gradients for the ultra-fast analysis of genetically modified organisms in soybeans.

Science.gov (United States)

Kim, Yun-Jeong; Chae, Joon-Seok; Chang, Jun Keun; Kang, Seong Ho

2005-08-12

We have developed a novel method for the ultra-fast analysis of genetically modified organisms (GMOs) in soybeans by microchip capillary gel electrophoresis (MCGE) using programmed field strength gradients (PFSG) in a conventional glass double-T microchip. Under the programmed electric field strength and 0.3% poly(ethylene oxide) sieving matrix, the GMO in soybeans was analyzed within only 11 s of the microchip. The MCGE-PFSG method was a program that changes the electric field strength during GMO analysis, and was also applied to the ultra-fast analysis of PCR products. Compared to MCGE using a conventional and constantly applied electric field, the MCGE-PFSG analysis generated faster results without the loss of resolving power and reproducibility for specific DNA fragments (100- and 250-bp DNA) of GM-soybeans. The MCGE-PFSG technique may prove to be a new tool in the GMO analysis due to its speed, simplicity, and high efficiency.

The use of genetic programming to develop a predictor of swash excursion on sandy beaches

Directory of Open Access Journals (Sweden)

M. Passarella

2018-02-01

Full Text Available We use genetic programming (GP, a type of machine learning (ML approach, to predict the total and infragravity swash excursion using previously published data sets that have been used extensively in swash prediction studies. Three previously published works with a range of new conditions are added to this data set to extend the range of measured swash conditions. Using this newly compiled data set we demonstrate that a ML approach can reduce the prediction errors compared to well-established parameterizations and therefore it may improve coastal hazards assessment (e.g. coastal inundation. Predictors obtained using GP can also be physically sound and replicate the functionality and dependencies of previous published formulas. Overall, we show that ML techniques are capable of both improving predictability (compared to classical regression approaches and providing physical insight into coastal processes.

A Novel Technique for Steganography Method Based on Improved Genetic Algorithm Optimization in Spatial Domain

Directory of Open Access Journals (Sweden)

M. Soleimanpour-moghadam

2013-06-01

Full Text Available This paper devotes itself to the study of secret message delivery using cover image and introduces a novel steganographic technique based on genetic algorithm to find a near-optimum structure for the pair-wise least-significant-bit (LSB matching scheme. A survey of the related literatures shows that the LSB matching method developed by Mielikainen, employs a binary function to reduce the number of changes of LSB values. This method verifiably reduces the probability of detection and also improves the visual quality of stego images. So, our proposal draws on the Mielikainen's technique to present an enhanced dual-state scoring model, structured upon genetic algorithm which assesses the performance of different orders for LSB matching and searches for a near-optimum solution among all the permutation orders. Experimental results confirm superiority of the new approach compared to the Mielikainen’s pair-wise LSB matching scheme.

Owning genetic information and gene enhancement techniques: why privacy and property rights may undermine social control of the human genome.

Science.gov (United States)

Moore, A D

2000-04-01

In this article I argue that the proper subjects of intangible property claims include medical records, genetic profiles, and gene enhancement techniques. Coupled with a right to privacy these intangible property rights allow individuals a zone of control that will, in most cases, justifiably exclude governmental or societal invasions into private domains. I argue that the threshold for overriding privacy rights and intangible property rights is higher, in relation to genetic enhancement techniques and sensitive personal information, than is commonly suggested. Once the bar is raised, so-to-speak, the burden of overriding it is formidable. Thus many policy decisions that have been recently proposed or enacted--citywide audio and video surveillance, law enforcement DNA sweeps, genetic profiling, national bans on genetic testing and enhancement of humans, to name a few--will have to be backed by very strong arguments.

Genetic Techniques for Manipulation of the Phytosterol Biotransformation Strain Mycobacterium neoaurum NRRL B-3805.

Science.gov (United States)

Loraine, Jessica K; Smith, Margaret C M

2017-01-01

Mycobacterium neoaurum is a saprophytic, soil-dwelling bacterium. The strain NRRL B-3805 converts phytosterols to androst-4-ene-3,17-dione (androstenedione; AD), a precursor of multiple C19 steroids of importance to industry. NRRL B-3805 itself is able to convert AD to other steroid products, including testosterone (Ts) and androst-1,4-diene-3,17-dione (androstadienedione; ADD). However to improve this strain for industrial use, genetic modification is a priority. In this chapter, we describe a range of genetic techniques that can be used for M. neoaurum NRRL B-3805. Methods for transformation, expression, and gene knockouts are presented as well as plasmid maintenance and stability.

System network planning expansion using mathematical programming, genetic algorithms and tabu search

International Nuclear Information System (INIS)

Sadegheih, A.; Drake, P.R.

2008-01-01

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

The genetic algorithm for the nonlinear programming of water pollution control system

Energy Technology Data Exchange (ETDEWEB)

Wei, J.; Zhang, J. [China University of Geosciences (China)

1999-08-01

In the programming of water pollution control system the combined method of optimization with simulation is used generally. It is not only laborious in calculation, but also the global optimum of the obtained solution is guaranteed difficult. In this paper, the genetic algorithm (GA) used in the nonlinear programming of water pollution control system is given, by which the preferred conception for the programming of waste water system is found in once-through operation. It is more succinct than the conventional method and the global optimum of the obtained solution could be ensured. 6 refs., 4 figs., 3 tabs.

Multi-objective genetic algorithm for solving N-version program design problem

Energy Technology Data Exchange (ETDEWEB)

Yamachi, Hidemi [Department of Computer and Information Engineering, Nippon Institute of Technology, Miyashiro, Saitama 345-8501 (Japan) and Department of Production and Information Systems Engineering, Tokyo Metropolitan Institute of Technology, Hino, Tokyo 191-0065 (Japan)]. E-mail: yamachi@nit.ac.jp; Tsujimura, Yasuhiro [Department of Computer and Information Engineering, Nippon Institute of Technology, Miyashiro, Saitama 345-8501 (Japan)]. E-mail: tujimr@nit.ac.jp; Kambayashi, Yasushi [Department of Computer and Information Engineering, Nippon Institute of Technology, Miyashiro, Saitama 345-8501 (Japan)]. E-mail: yasushi@nit.ac.jp; Yamamoto, Hisashi [Department of Production and Information Systems Engineering, Tokyo Metropolitan Institute of Technology, Hino, Tokyo 191-0065 (Japan)]. E-mail: yamamoto@cc.tmit.ac.jp

2006-09-15

N-version programming (NVP) is a programming approach for constructing fault tolerant software systems. Generally, an optimization model utilized in NVP selects the optimal set of versions for each module to maximize the system reliability and to constrain the total cost to remain within a given budget. In such a model, while the number of versions included in the obtained solution is generally reduced, the budget restriction may be so rigid that it may fail to find the optimal solution. In order to ameliorate this problem, this paper proposes a novel bi-objective optimization model that maximizes the system reliability and minimizes the system total cost for designing N-version software systems. When solving multi-objective optimization problem, it is crucial to find Pareto solutions. It is, however, not easy to obtain them. In this paper, we propose a novel bi-objective optimization model that obtains many Pareto solutions efficiently. We formulate the optimal design problem of NVP as a bi-objective 0-1 nonlinear integer programming problem. In order to overcome this problem, we propose a Multi-objective genetic algorithm (MOGA), which is a powerful, though time-consuming, method to solve multi-objective optimization problems. When implementing genetic algorithm (GA), the use of an appropriate genetic representation scheme is one of the most important issues to obtain good performance. We employ random-key representation in our MOGA to find many Pareto solutions spaced as evenly as possible along the Pareto frontier. To pursue improve further performance, we introduce elitism, the Pareto-insertion and the Pareto-deletion operations based on distance between Pareto solutions in the selection process. The proposed MOGA obtains many Pareto solutions along the Pareto frontier evenly. The user of the MOGA can select the best compromise solution among the candidates by controlling the balance between the system reliability and the total cost.

Multi-objective genetic algorithm for solving N-version program design problem

International Nuclear Information System (INIS)

Yamachi, Hidemi; Tsujimura, Yasuhiro; Kambayashi, Yasushi; Yamamoto, Hisashi

2006-01-01

N-version programming (NVP) is a programming approach for constructing fault tolerant software systems. Generally, an optimization model utilized in NVP selects the optimal set of versions for each module to maximize the system reliability and to constrain the total cost to remain within a given budget. In such a model, while the number of versions included in the obtained solution is generally reduced, the budget restriction may be so rigid that it may fail to find the optimal solution. In order to ameliorate this problem, this paper proposes a novel bi-objective optimization model that maximizes the system reliability and minimizes the system total cost for designing N-version software systems. When solving multi-objective optimization problem, it is crucial to find Pareto solutions. It is, however, not easy to obtain them. In this paper, we propose a novel bi-objective optimization model that obtains many Pareto solutions efficiently. We formulate the optimal design problem of NVP as a bi-objective 0-1 nonlinear integer programming problem. In order to overcome this problem, we propose a Multi-objective genetic algorithm (MOGA), which is a powerful, though time-consuming, method to solve multi-objective optimization problems. When implementing genetic algorithm (GA), the use of an appropriate genetic representation scheme is one of the most important issues to obtain good performance. We employ random-key representation in our MOGA to find many Pareto solutions spaced as evenly as possible along the Pareto frontier. To pursue improve further performance, we introduce elitism, the Pareto-insertion and the Pareto-deletion operations based on distance between Pareto solutions in the selection process. The proposed MOGA obtains many Pareto solutions along the Pareto frontier evenly. The user of the MOGA can select the best compromise solution among the candidates by controlling the balance between the system reliability and the total cost

Marine biosurfaces research program

Science.gov (United States)

The Office of Naval Research (ONR) of the U.S. Navy is starting a basic research program to address the initial events that control colonization of surfaces by organisms in marine environments. The program “arises from the Navy's need to understand and ultimately control biofouling and biocorrosion in marine environments,” according to a Navy announcement.The program, “Biological Processes Controlling Surface Modification in the Marine Environment,” will emphasize the application of in situ techniques and modern molecular biological, biochemical, and biophysical approaches; it will also encourage the development of interdisciplinary projects. Specific areas of interest include sensing and response to environmental surface (physiology/physical chemistry), factors controlling movement to and retention at surfaces (behavior/hydrodynamics), genetic regulation of attachment (molecular genetics), and mechanisms of attachment (biochemistry/surface chemistry).

Designing a Web Spam Classifier Based on Feature Fusion in the Layered Multi-Population Genetic Programming Framework

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Amir Hosein KEYHANIPOUR

2013-11-01

Full Text Available Nowadays, Web spam pages are a critical challenge for Web retrieval systems which have drastic influence on the performance of such systems. Although these systems try to combat the impact of spam pages on their final results list, spammers increasingly use more sophisticated techniques to increase the number of views for their intended pages in order to have more commercial success. This paper employs the recently proposed Layered Multi-population Genetic Programming model for Web spam detection task as well application of correlation coefficient analysis for feature space reduction. Based on our tentative results, the designed classifier, which is based on a combination of easy to compute features, has a very reasonable performance in comparison with similar methods.

Weight optimization of plane truss using genetic algorithm

Science.gov (United States)

Neeraja, D.; Kamireddy, Thejesh; Santosh Kumar, Potnuru; Simha Reddy, Vijay

2017-11-01

Optimization of structure on basis of weight has many practical benefits in every engineering field. The efficiency is proportionally related to its weight and hence weight optimization gains prime importance. Considering the field of civil engineering, weight optimized structural elements are economical and easier to transport to the site. In this study, genetic optimization algorithm for weight optimization of steel truss considering its shape, size and topology aspects has been developed in MATLAB. Material strength and Buckling stability have been adopted from IS 800-2007 code of construction steel. The constraints considered in the present study are fabrication, basic nodes, displacements, and compatibility. Genetic programming is a natural selection search technique intended to combine good solutions to a problem from many generations to improve the results. All solutions are generated randomly and represented individually by a binary string with similarities of natural chromosomes, and hence it is termed as genetic programming. The outcome of the study is a MATLAB program, which can optimise a steel truss and display the optimised topology along with element shapes, deflections, and stress results.

Implementation of genetic conservation practices in a muskellunge propagation and stocking program

Science.gov (United States)

Jennings, Martin J.; Sloss, Brian L.; Hatzenbeler, Gene R.; Kampa, Jeffrey M.; Simonson, Timothy D.; Avelallemant, Steven P.; Lindenberger, Gary A.; Underwood, Bruce D.

2010-01-01

Conservation of genetic resources is a challenging issue for agencies managing popular sport fishes. To address the ongoing potential for genetic risks, we developed a comprehensive set of recommendations to conserve genetic diversity of muskellunge (Esox masquinongy) in Wisconsin, and evaluated the extent to which the recommendations can be implemented. Although some details are specific to Wisconsin's muskellunge propagation program, many of the practical issues affecting implementation are applicable to other species and production systems. We developed guidelines to restrict future broodstock collection operations to lakes with natural reproduction and to develop a set of brood lakes to use on a rotational basis within regional stock boundaries, but implementation will require considering lakes with variable stocking histories. Maintaining an effective population size sufficient to minimize the risk of losing alleles requires limiting broodstock collection to large lakes. Recommendations to better approximate the temporal distribution of spawning in hatchery operations and randomize selection of brood fish are feasible. Guidelines to modify rearing and distribution procedures face some logistic constraints. An evaluation of genetic diversity of hatchery-produced fish during 2008 demonstrated variable success representing genetic variation of the source population. Continued evaluation of hatchery operations will optimize operational efficiency while moving toward genetic conservation goals.

Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks

International Nuclear Information System (INIS)

Zameer, Aneela; Arshad, Junaid; Khan, Asifullah; Raja, Muhammad Asif Zahoor

2017-01-01

Highlights: • Genetic programming based ensemble of neural networks is employed for short term wind power prediction. • Proposed predictor shows resilience against abrupt changes in weather. • Genetic programming evolves nonlinear mapping between meteorological measures and wind-power. • Proposed approach gives mathematical expressions of wind power to its independent variables. • Proposed model shows relatively accurate and steady wind-power prediction performance. - Abstract: The inherent instability of wind power production leads to critical problems for smooth power generation from wind turbines, which then requires an accurate forecast of wind power. In this study, an effective short term wind power prediction methodology is presented, which uses an intelligent ensemble regressor that comprises Artificial Neural Networks and Genetic Programming. In contrast to existing series based combination of wind power predictors, whereby the error or variation in the leading predictor is propagated down the stream to the next predictors, the proposed intelligent ensemble predictor avoids this shortcoming by introducing Genetical Programming based semi-stochastic combination of neural networks. It is observed that the decision of the individual base regressors may vary due to the frequent and inherent fluctuations in the atmospheric conditions and thus meteorological properties. The novelty of the reported work lies in creating ensemble to generate an intelligent, collective and robust decision space and thereby avoiding large errors due to the sensitivity of the individual wind predictors. The proposed ensemble based regressor, Genetic Programming based ensemble of Artificial Neural Networks, has been implemented and tested on data taken from five different wind farms located in Europe. Obtained numerical results of the proposed model in terms of various error measures are compared with the recent artificial intelligence based strategies to demonstrate the

Future strategy and puzzles of heavy ion beam mediated technique in genetic improvement of biological bodies

International Nuclear Information System (INIS)

Huang Qunce

2007-01-01

The 7 research puzzles in the genetic improvement of biological bodies made by ion beam mediated technique, are worth noticed. The technical ideas, including one mediated technique in physics, 2 significant subjects, 3 effective changes, the mediated evidences of 4 aspects and 5 biological characteristics, were particularly put forward according to the existing states in the field. The 2 significant subjects consist of the mechanics of the allogenetic materials entering into the acceptor and they being to be recombined. The 3 effective changes include from studying morphology to genetic laws, from researching M1 generation to the next generations, from determining the single character to the synthetic traits. The mediated evidences of 4 aspects come from morphology, physiology and biochemistry, molecule biology. The 5 biological characteristics are mainly reproduction, development, photosynthesis, bad condition-resistant and quality. (authors)

Adaptive Test Selection for Factorization-based Surrogate Fitness in Genetic Programming

Directory of Open Access Journals (Sweden)

Krawiec Krzysztof

2017-12-01

Full Text Available Genetic programming (GP is a variant of evolutionary algorithm where the entities undergoing simulated evolution are computer programs. A fitness function in GP is usually based on a set of tests, each of which defines the desired output a correct program should return for an exemplary input. The outcomes of interactions between programs and tests in GP can be represented as an interaction matrix, with rows corresponding to programs in the current population and columns corresponding to tests. In previous work, we proposed SFIMX, a method that performs only a fraction of interactions and employs non-negative matrix factorization to estimate the outcomes of remaining ones, shortening GP’s runtime. In this paper, we build upon that work and propose three extensions of SFIMX, in which the subset of tests drawn to perform interactions is selected with respect to test difficulty. The conducted experiment indicates that the proposed extensions surpass the original SFIMX on a suite of discrete GP benchmarks.

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.

Mitigation of inbreeding while preserving genetic gain in genomic breeding programs for outbred plants.

Science.gov (United States)

Lin, Zibei; Shi, Fan; Hayes, Ben J; Daetwyler, Hans D

2017-05-01

Heuristic genomic inbreeding controls reduce inbreeding in genomic breeding schemes without reducing genetic gain. Genomic selection is increasingly being implemented in plant breeding programs to accelerate genetic gain of economically important traits. However, it may cause significant loss of genetic diversity when compared with traditional schemes using phenotypic selection. We propose heuristic strategies to control the rate of inbreeding in outbred plants, which can be categorised into three types: controls during mate allocation, during selection, and simultaneous selection and mate allocation. The proposed mate allocation measure GminF allocates two or more parents for mating in mating groups that minimise coancestry using a genomic relationship matrix. Two types of relationship-adjusted genomic breeding values for parent selection candidates ([Formula: see text]) and potential offspring ([Formula: see text]) are devised to control inbreeding during selection and even enabling simultaneous selection and mate allocation. These strategies were tested in a case study using a simulated perennial ryegrass breeding scheme. As compared to the genomic selection scheme without controls, all proposed strategies could significantly decrease inbreeding while achieving comparable genetic gain. In particular, the scenario using [Formula: see text] in simultaneous selection and mate allocation reduced inbreeding to one-third of the original genomic selection scheme. The proposed strategies are readily applicable in any outbred plant breeding program.

Analysis of the efficiency of the linearization techniques for solving multi-objective linear fractional programming problems by goal programming

Directory of Open Access Journals (Sweden)

Tunjo Perić

2017-01-01

Full Text Available This paper presents and analyzes the applicability of three linearization techniques used for solving multi-objective linear fractional programming problems using the goal programming method. The three linearization techniques are: (1 Taylor’s polynomial linearization approximation, (2 the method of variable change, and (3 a modification of the method of variable change proposed in [20]. All three linearization techniques are presented and analyzed in two variants: (a using the optimal value of the objective functions as the decision makers’ aspirations, and (b the decision makers’ aspirations are given by the decision makers. As the criteria for the analysis we use the efficiency of the obtained solutions and the difficulties the analyst comes upon in preparing the linearization models. To analyze the applicability of the linearization techniques incorporated in the linear goal programming method we use an example of a financial structure optimization problem.

Conservation genetics of otters: Review about the use of non-invasive samples

OpenAIRE

Aristizábal Duque, Sandra L.; Orozco-Jiménez, Luz Y.; Zapata-Escobar, Carolina; Palacio-Baena, Jaime A.

2018-01-01

Abstract: Wild population management programs require determining some fundamental aspects for conservation, including population structure, flow between populations, evolutionary history and kinship, among others. Since sample collection from wild mammals for DNA extraction is a complex task, conservation genetics has developed non-invasive sampling techniques, which allow obtaining DNA without the need to capture individuals. For the genetic characterization of otter populations, stools are...

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.

Genetic Diversity in Commercial Rapeseed (Brassica napus L.) Varieties from Turkey as Revealed by RAPD

OpenAIRE

Özlem ÖZBEK; Betül Uçar GIDIK

2013-01-01

In cultivated commercial crop species, genetic diversity tends to decrease because of the extensive breeding processes. Therefore, germplasm of commercial crop species, such as Brassica napus L. should be evaluated and the genotypes, which have higher genetic diversity index, should be addressed as potential parental cross materials in breeding programs. In this study, the genetic diversity was analysed by using randomly amplified polymorphic DNA analysis (RAPD) technique in nine Turkish com...

Prediksi Nilai Tukar Rupiah Terhadap US Dollar Menggunakan Metode Genetic Programming

Directory of Open Access Journals (Sweden)

Daneswara Jauhari

2016-12-01

Exchange currency rate has a wide influence in the economy of a country, both domestically or internationally. The importance of knowing the pattern of exchange rate against the IDR to USD could help the economic growth due to foreign trade involves the use of currencies of different countries. Therefore, we need an application that can predict the value of IDR against the USD in the future. In this research, the authors use genetic programming (GP method which produces solutions (chromosome that obtained from the evaluation of exchange rate and then this solution used as an approximation or prediction of currency exchange rate in the future. These solutions formed from the combination of the set terminal and the set of function that generated randomly. After testing by the number popsize and different iterations, it was found that the GP algorithm can predict the value of the rupiah against the US Dollar with a very good, judging from the value of Mean Absolute Percentage Error (MAPE generated by 0.08%. This research can be developed even better by adding terminal parameters and operating parameters so they can add variation calculation results. Keywords:  prediction, exchange currency rate, genetic programming, MAPE.

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

Science.gov (United States)

Zhang, Yang; Rockett, Peter I

2009-01-01

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

A comparison of machine learning techniques for survival prediction in breast cancer.

Science.gov (United States)

Vanneschi, Leonardo; Farinaccio, Antonella; Mauri, Giancarlo; Antoniotti, Mauro; Provero, Paolo; Giacobini, Mario

2011-05-11

The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions. In recent years gene expression data have been successfully used to complement the clinical and histological criteria traditionally used in such prediction. Many "gene expression signatures" have been developed, i.e. sets of genes whose expression values in a tumor can be used to predict the outcome of the pathology. Here we investigate the use of several machine learning techniques to classify breast cancer patients using one of such signatures, the well established 70-gene signature. We show that Genetic Programming performs significantly better than Support Vector Machines, Multilayered Perceptrons and Random Forests in classifying patients from the NKI breast cancer dataset, and comparably to the scoring-based method originally proposed by the authors of the 70-gene signature. Furthermore, Genetic Programming is able to perform an automatic feature selection. Since the performance of Genetic Programming is likely to be improvable compared to the out-of-the-box approach used here, and given the biological insight potentially provided by the Genetic Programming solutions, we conclude that Genetic Programming methods are worth further investigation as a tool for cancer patient classification based on gene expression data.

A comparison of machine learning techniques for survival prediction in breast cancer

Directory of Open Access Journals (Sweden)

Vanneschi Leonardo

2011-05-01

Full Text Available Abstract Background The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions. In recent years gene expression data have been successfully used to complement the clinical and histological criteria traditionally used in such prediction. Many "gene expression signatures" have been developed, i.e. sets of genes whose expression values in a tumor can be used to predict the outcome of the pathology. Here we investigate the use of several machine learning techniques to classify breast cancer patients using one of such signatures, the well established 70-gene signature. Results We show that Genetic Programming performs significantly better than Support Vector Machines, Multilayered Perceptrons and Random Forests in classifying patients from the NKI breast cancer dataset, and comparably to the scoring-based method originally proposed by the authors of the 70-gene signature. Furthermore, Genetic Programming is able to perform an automatic feature selection. Conclusions Since the performance of Genetic Programming is likely to be improvable compared to the out-of-the-box approach used here, and given the biological insight potentially provided by the Genetic Programming solutions, we conclude that Genetic Programming methods are worth further investigation as a tool for cancer patient classification based on gene expression data.

Managing complex processing of medical image sequences by program supervision techniques

Science.gov (United States)

Crubezy, Monica; Aubry, Florent; Moisan, Sabine; Chameroy, Virginie; Thonnat, Monique; Di Paola, Robert

1997-05-01

Our objective is to offer clinicians wider access to evolving medical image processing (MIP) techniques, crucial to improve assessment and quantification of physiological processes, but difficult to handle for non-specialists in MIP. Based on artificial intelligence techniques, our approach consists in the development of a knowledge-based program supervision system, automating the management of MIP libraries. It comprises a library of programs, a knowledge base capturing the expertise about programs and data and a supervision engine. It selects, organizes and executes the appropriate MIP programs given a goal to achieve and a data set, with dynamic feedback based on the results obtained. It also advises users in the development of new procedures chaining MIP programs.. We have experimented the approach for an application of factor analysis of medical image sequences as a means of predicting the response of osteosarcoma to chemotherapy, with both MRI and NM dynamic image sequences. As a result our program supervision system frees clinical end-users from performing tasks outside their competence, permitting them to concentrate on clinical issues. Therefore our approach enables a better exploitation of possibilities offered by MIP and higher quality results, both in terms of robustness and reliability.

Reverse genetics with animal viruses. NSV reverse genetics

International Nuclear Information System (INIS)

Mebatsion, T.

2005-01-01

New strategies to genetically manipulate the genomes of several important animal pathogens have been established in recent years. This article focuses on the reverse genetics techniques, which enables genetic manipulation of the genomes of non-segmented negative-sense RNA viruses. Recovery of a negative-sense RNA virus entirely from cDNA was first achieved for rabies virus in 1994. Since then, reverse genetic systems have been established for several pathogens of medical and veterinary importance. Based on the reverse genetics technique, it is now possible to design safe and more effective live attenuated vaccines against important viral agents. In addition, genetically tagged recombinant viruses can be designed to facilitate serological differentiation of vaccinated animals from infected animals. The approach of delivering protective immunogens of different pathogens using a single vector was made possible with the introduction of the reverse genetics system, and these novel broad-spectrum vaccine vectors have potential applications in improving animal health in developing countries. (author)

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)

Recent advances in preimplantation genetic diagnosis

Directory of Open Access Journals (Sweden)

Kahraman S

2015-04-01

Full Text Available Semra Kahraman, Çağri Beyazyürek, Hüseyin Avni Taç, Caroline Pirkevi, Murat Cetinkaya, Neşe Gülüm IVF and Reproductive Genetics Center, Istanbul Memorial Hospital, Istanbul, Turkey Abstract: Preimplantation genetic diagnosis (PGD is an important method for the identification chromosomal abnormalities and genes responsible for genetic defects in embryos that are created through in vitro fertilization before pregnancy. As the list of conditions and indications for PGD testing is continuing to extend enormously, novel in vitro fertilization techniques and newly established genetic analysis techniques have been implemented in clinical settings in the recent years. Blastocyst-stage biopsy, vitrification techniques, time-lapse imaging, whole-genome amplification, array-based diagnostic techniques, and next-generation sequencing techniques are promising techniques for the accurate diagnosis of diverse genetic conditions and also for the selection of the best embryo that has the highest implantation capacity. The timing and technique used for biopsy, the amplification techniques, the genetic diagnosis techniques, and appropriate genetic counseling play important roles in establishing a successful PGD. In this review, those key points of PGD will be reviewed in detail. Keywords: preimplantation genetic diagnosis, array comparative genomic hybridization, single-nucleotide polymorphism arrays, next-generation sequencing, monogenic disorders, aneuploidy testing 

A Genetic Algorithm Approach to the Optimization of a Radioactive Waste Treatment System

International Nuclear Information System (INIS)

Yang, Yeongjin; Lee, Kunjai; Koh, Y.; Mun, J.H.; Kim, H.S.

1998-01-01

This study is concerned with the applications of goal programming and genetic algorithm techniques to the analysis of management and operational problems in the radioactive waste treatment system (RWTS). A typical RWTS is modeled and solved by goal program and genetic algorithm to study and resolve the effects of conflicting objectives such as cost, limitation of released radioactivity to the environment, equipment utilization and total treatable radioactive waste volume before discharge and disposal. The developed model is validated and verified using actual data obtained from the RWTS at Kyoto University in Japan. The solution by goal programming and genetic algorithm would show the optimal operation point which is to maximize the total treatable radioactive waste volume and minimize the released radioactivity of liquid waste even under the restricted resources. The comparison of two methods shows very similar results. (author)

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.

The Development of a Post-Baccalaureate Certificate Program in Molecular Diagnostics

Science.gov (United States)

Williams, Gail S.; Brown, Judith D.; Keagle, Martha B.

2000-01-01

A post-baccalaureate certificate program in diagnostic molecular sciences was created in 1995 by the Diagnostic Genetic Sciences Program in the School of Allied Health at the University of Connecticut. The required on-campus lecture and laboratory courses include basic laboratory techniques, health care issues, cell biology, immunology, human genetics, research, management, and molecular diagnostic techniques and laboratory in molecular diagnostics. These courses precede a 6-month, full-time practicum at an affiliated full-service molecular laboratory. The practicum includes amplification and blotting methods, a research project, and a choice of specialized electives including DNA sequencing, mutagenesis, in situ hybridization methods, or molecular diagnostic applications in microbiology. Graduates of the program are immediately eligible to sit for the National Credentialing Agency examination in molecular biology to obtain the credential Clinical Laboratory Specialist in Molecular Biology (CLSp(MB). This description of the University of Connecticut program may assist other laboratory science programs in creating similar curricula. PMID:11232107

Training Software in Artificial-Intelligence Computing Techniques

Science.gov (United States)

Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

2005-01-01

The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.

Comprehensive bidding strategies with genetic programming/finite state automata

International Nuclear Information System (INIS)

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

1999-01-01

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

Comparison of collinearity mitigation techniques used in predicting BLUP breeding values and genetic gains over generations

CSIR Research Space (South Africa)

Eatwell, KA

2011-01-01

Full Text Available techniques and of two computational numerical precisions on the genetic gains in breeding populations. Multiple-trait, multiple-trial BLUP selection scenarios were run on Eucalyptus grandis (F1, F2 and F3) and Pinus patula (F1 and F2) data, comparing...

DNA fingerprinting techniques for the analysis of genetic and epigenetic alterations in colorectal cancer.

Science.gov (United States)

Samuelsson, Johanna K; Alonso, Sergio; Yamamoto, Fumiichiro; Perucho, Manuel

2010-11-10

Genetic somatic alterations are fundamental hallmarks of cancer. In addition to point and other small mutations targeting cancer genes, solid tumors often exhibit aneuploidy as well as multiple chromosomal rearrangements of large fragments of the genome. Whether somatic chromosomal alterations and aneuploidy are a driving force or a mere consequence of tumorigenesis remains controversial. Recently it became apparent that not only genetic but also epigenetic alterations play a major role in carcinogenesis. Epigenetic regulation mechanisms underlie the maintenance of cell identity crucial for development and differentiation. These epigenetic regulatory mechanisms have been found substantially altered during cancer development and progression. In this review, we discuss approaches designed to analyze genetic and epigenetic alterations in colorectal cancer, especially DNA fingerprinting approaches to detect changes in DNA copy number and methylation. DNA fingerprinting techniques, despite their modest throughput, played a pivotal role in significant discoveries in the molecular basis of colorectal cancer. The aim of this review is to revisit the fingerprinting technologies employed and the oncogenic processes that they unveiled. 2010 Elsevier B.V. All rights reserved.

Multidisciplinary Techniques and Novel Aircraft Control Systems

Science.gov (United States)

Padula, Sharon L.; Rogers, James L.; Raney, David L.

2000-01-01

The Aircraft Morphing Program at NASA Langley Research Center explores opportunities to improve airframe designs with smart technologies. Two elements of this basic research program are multidisciplinary design optimization (MDO) and advanced flow control. This paper describes examples where MDO techniques such as sensitivity analysis, automatic differentiation, and genetic algorithms contribute to the design of novel control systems. In the test case, the design and use of distributed shape-change devices to provide low-rate maneuvering capability for a tailless aircraft is considered. The ability of MDO to add value to control system development is illustrated using results from several years of research funded by the Aircraft Morphing Program.

Evaluation of two-year Jewish genetic disease screening program in Atlanta: insight into community genetic screening approaches.

Science.gov (United States)

Shao, Yunru; Liu, Shuling; Grinzaid, Karen

2015-04-01

Improvements in genetic testing technologies have led to the development of expanded carrier screening panels for the Ashkenazi Jewish population; however, there are major inconsistencies in current screening practices. A 2-year pilot program was launched in Atlanta in 2010 to promote and facilitate screening for 19 Jewish genetic diseases. We analyzed data from this program, including participant demographics and outreach efforts. This retrospective analysis is based on a de-identified dataset of 724 screenees. Data were obtained through medical chart review and questionnaires and included demographic information, screening results, response to outreach efforts, and follow-up behavior and preferences. We applied descriptive analysis, chi-square tests, and logistic regression to analyze the data and compare findings with published literature. The majority of participants indicated that they were not pregnant or did not have a partner who was pregnant were affiliated with Jewish organizations and reported 100 % AJ ancestry. Overall, carrier frequency was 1 in 3.9. Friends, rabbis, and family members were the most common influencers of the decision to receive screening. People who were older, had a history of pregnancy, and had been previously screened were more likely to educate others (all p influencers who then encouraged screening in the target population. Educating influencers and increasing overall awareness were the most effective outreach strategies.

The use of PCR techniques to detect genetic variations in Cassava (Manihot esculenta L. Crantz): minisatellite and RAPD analysis

International Nuclear Information System (INIS)

Pawlicki, N.; Sangwan, R.S.; Sangwan-Norreel, B.; Koffi Konan, N.

1998-01-01

Cassava is an important tuber crop grown in the tropical and subtropical regions. Recently, we developed protocols for efficient somatic embryogenesis using zygotic embryos and nodal axillary meristems in order to reduce the genotype effect. Thereafter flow cytophotometry and randomly amplified polymorphic DNA (RAPD) markers were used to assess the ploidy level and the genetic fidelity of cassava plants regenerated by somatic embryogenesis. No change in the ploidy level of the regenerated plants was observed in comparison with the control plants. In the same way, monomorphic profiles of RAPD were obtained for the different cassava plants regenerated by somatic embryogenesis. The genetic analysis of calli showed only a few differences. Using two pairs of heterologous micro satellite primers developed in a wild African grass, a monomorphic pattern was also detected. Moreover, cultivars of different origins were also analysed using these PCR techniques. Our data from RAPD and materialistic analyses suggested that these techniques can be efficiently used to detect genetic variations in cassava. (author)

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...

Estimation of genetic parameters for growth traits in a breeding program for rainbow trout (Oncorhynchus mykiss) in China.

Science.gov (United States)

Hu, G; Gu, W; Bai, Q L; Wang, B Q

2013-04-26

Genetic parameters and breeding values for growth traits were estimated in the first and, currently, the only family selective breeding program for rainbow trout (Oncorhynchus mykiss) in China. Genetic and phenotypic data were collected for growth traits from 75 full-sibling families with a 2-generation pedigree. Genetic parameters and breeding values for growth traits of rainbow trout were estimated using the derivative-free restricted maximum likelihood method. The goodness-of-fit of the models was tested using Akaike and Bayesian information criteria. Genetic parameters and breeding values were estimated using the best-fit model for each trait. The values for heritability estimating body weight and length ranged from 0.20 to 0.45 and from 0.27 to 0.60, respectively, and the heritability of condition factor was 0.34. Our results showed a moderate degree of heritability for growth traits in this breeding program and suggested that the genetic and phenotypic tendency of body length, body weight, and condition factor were similar. Therefore, the selection of phenotypic values based on pedigree information was also suitable in this research population.

Experimental control of a fluidic pinball using genetic programming

Science.gov (United States)

Raibaudo, Cedric; Zhong, Peng; Noack, Bernd R.; Martinuzzi, Robert J.

2017-11-01

The wake stabilization of a triangular cluster of three rotating cylinders was investigated in the present study. Experiments were performed at Reynolds number Re 6000, and compared with URANS-2D simulations at same flow conditions. 2D2C PIV measurements and constant temperature anemometry were used to characterize the flow without and with actuation. Open-loop actuation was first considered for the identification of particular control strategies. Machine learning control was also implemented for the experimental study. Linear genetic programming has been used for the optimization of open-loop parameters and closed-loop controllers. Considering a cost function J based on the fluctuations of the velocity measured by the hot-wire sensor, significant performances were achieved using the machine learning approach. The present work is supported by the senior author's (R. J. Martinuzzi) NSERC discovery Grant. C. Raibaudo acknowledges the financial support of the University of Calgary Eyes-High PDF program.

Genetic diversity analysis in Malaysian giant prawns using expressed sequence tag microsatellite markers for stock improvement program.

Science.gov (United States)

Atin, K H; Christianus, A; Fatin, N; Lutas, A C; Shabanimofrad, M; Subha, B

2017-08-17

The Malaysian giant prawn is among the most commonly cultured species of the genus Macrobrachium. Stocks of giant prawns from four rivers in Peninsular Malaysia have been used for aquaculture over the past 25 years, which has led to repeated harvesting, restocking, and transplantation between rivers. Consequently, a stock improvement program is now important to avoid the depletion of wild stocks and the loss of genetic diversity. However, the success of such an improvement program depends on our knowledge of the genetic variation of these base populations. The aim of the current study was to estimate genetic variation and differentiation of these riverine sources using novel expressed sequence tag-microsatellite (EST-SSR) markers, which not only are informative on genetic diversity but also provide information on immune and metabolic traits. Our findings indicated that the tested stocks have inbreeding depression due to a significant deficiency in heterozygotes, and F IS was estimated as 0.15538 to 0.31938. An F-statistics analysis suggested that the stocks are composed of one large panmictic population. Among the four locations, stocks from Johor, in the southern region of the peninsular, showed higher allelic and genetic diversity than the other stocks. To overcome inbreeding problems, the Johor population could be used as a base population in a stock improvement program by crossing to the other populations. The study demonstrated that EST-SSR markers can be incorporated in future marker assisted breeding to aid the proper management of the stocks by breeders and stakeholders in Malaysia.

Object matching using a locally affine invariant and linear programming techniques.

Science.gov (United States)

Li, Hongsheng; Huang, Xiaolei; He, Lei

2013-02-01

In this paper, we introduce a new matching method based on a novel locally affine-invariant geometric constraint and linear programming techniques. To model and solve the matching problem in a linear programming formulation, all geometric constraints should be able to be exactly or approximately reformulated into a linear form. This is a major difficulty for this kind of matching algorithm. We propose a novel locally affine-invariant constraint which can be exactly linearized and requires a lot fewer auxiliary variables than other linear programming-based methods do. The key idea behind it is that each point in the template point set can be exactly represented by an affine combination of its neighboring points, whose weights can be solved easily by least squares. Errors of reconstructing each matched point using such weights are used to penalize the disagreement of geometric relationships between the template points and the matched points. The resulting overall objective function can be solved efficiently by linear programming techniques. Our experimental results on both rigid and nonrigid object matching show the effectiveness of the proposed algorithm.

A Heuristics Approach for Classroom Scheduling Using Genetic Algorithm Technique

Science.gov (United States)

Ahmad, Izah R.; Sufahani, Suliadi; Ali, Maselan; Razali, Siti N. A. M.

2018-04-01

Reshuffling and arranging classroom based on the capacity of the audience, complete facilities, lecturing time and many more may lead to a complexity of classroom scheduling. While trying to enhance the productivity in classroom planning, this paper proposes a heuristic approach for timetabling optimization. A new algorithm was produced to take care of the timetabling problem in a university. The proposed of heuristics approach will prompt a superior utilization of the accessible classroom space for a given time table of courses at the university. Genetic Algorithm through Java programming languages were used in this study and aims at reducing the conflicts and optimizes the fitness. The algorithm considered the quantity of students in each class, class time, class size, time accessibility in each class and lecturer who in charge of the classes.

Crop improvement through mutation techniques in Chinese agriculture

International Nuclear Information System (INIS)

Wen, X.; Qu, L.

1996-01-01

Induced mutations for crop improvement is the most developed field in China's nuclear-agricultural sciences. It is well known that China has supported 22% of the world's population with only 7% of its cultivated land. The continued rise in population stresses the importance of increasing food production. Although developing crop varieties is efficient in increasing food production, plant breeders are approaching the outer limits of existing and useful genetic variability. As nuclear techniques provide an efficient route to inducing genetic mutations, more and more efforts have been focused on induced genetic variability. Induced mutations have become an effective way of improving cultivars and supplementing existing germplasm. Since 1981 two nationwide co-operation programs for mutation breeding, organized by the IAEA, have been carried out. 3 tabs

Recent trends on crop genetic improvement using mutation techniques

International Nuclear Information System (INIS)

Kang, Siyong

2008-01-01

The radiation breeding technology has been significantly achieved on creation of mutation genetic resources of plants for commercial cultivation and genomic study since 1920s. According to the FAO-IAEA Mutant Variety Database, more than 2600 varieties have been released in the world. Induction of mutations with radiation has been the most frequently used by sources of X-ray and gamma ray, but in recent Japanese scientist have been used the heavy ion beam as a new radiation sources. And China has been made remarkable outcomes in the mutant creation using new space breeding technology since 1990s. In Korea, more about 40 varieties have been developed by using the mutation breeding method since the mid-1960s. Most of the released mutant varieties in Korea were food and oil seed crops, especially for improving agronomic traits such as yield, lodging tolerance, maturity, and functional compounds. Currently the mutation breeding program in Korea has assigned more resources to develop high functional crops and ornamental plants. These functional and ornamental plants are ideal systems for a mutation breeding. A research program for the development of potential varieties of flowering and ornamental crops as rose, chrysanthemum, lily, carnation, orchids, and wild flowers was started with financial support from the Bio green 21 project of Korean government. The potential outcomes from the program will be new highly valued-added varieties which will provide greater money gains to Korean farmers and lots of valued mutants used for a gene isolation of interest and reverse genetics or functional genomic. Scientific interest in mutation breeding has drastically be ed focused to the field of functional genomic. Scientific interest in mutation breeding has drastically be ed focused to the field of functional genomic after a completion of genome sequencing of some model plant species. A direct approach of discovering the function of a novel gene is to use a mutant which has altered

Recent trends on crop genetic improvement using mutation techniques

Energy Technology Data Exchange (ETDEWEB)

Kang, Siyong [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2008-04-15

The radiation breeding technology has been significantly achieved on creation of mutation genetic resources of plants for commercial cultivation and genomic study since 1920s. According to the FAO-IAEA Mutant Variety Database, more than 2600 varieties have been released in the world. Induction of mutations with radiation has been the most frequently used by sources of X-ray and gamma ray, but in recent Japanese scientist have been used the heavy ion beam as a new radiation sources. And China has been made remarkable outcomes in the mutant creation using new space breeding technology since 1990s. In Korea, more about 40 varieties have been developed by using the mutation breeding method since the mid-1960s. Most of the released mutant varieties in Korea were food and oil seed crops, especially for improving agronomic traits such as yield, lodging tolerance, maturity, and functional compounds. Currently the mutation breeding program in Korea has assigned more resources to develop high functional crops and ornamental plants. These functional and ornamental plants are ideal systems for a mutation breeding. A research program for the development of potential varieties of flowering and ornamental crops as rose, chrysanthemum, lily, carnation, orchids, and wild flowers was started with financial support from the Bio green 21 project of Korean government. The potential outcomes from the program will be new highly valued-added varieties which will provide greater money gains to Korean farmers and lots of valued mutants used for a gene isolation of interest and reverse genetics or functional genomic. Scientific interest in mutation breeding has drastically be ed focused to the field of functional genomic. Scientific interest in mutation breeding has drastically be ed focused to the field of functional genomic after a completion of genome sequencing of some model plant species. A direct approach of discovering the function of a novel gene is to use a mutant which has altered

Screening Out Controversy: Human Genetics, Emerging Techniques of Diagnosis, and the Origins of the Social Issues Committee of the American Society of Human Genetics, 1964-1973.

Science.gov (United States)

Mitchell, M X

2017-05-01

In the years following World War II, and increasingly during the 1960s and 1970s, professional scientific societies developed internal sub-committees to address the social implications of their scientific expertise (Moore, Disrupting Science: Social Movements, American Scientists, and the Politics of the Military, 1945-1975. Princeton: Princeton University Press, 2008). This article explores the early years of one such committee, the American Society of Human Genetics' "Social Issues Committee," founded in 1967. Although the committee's name might suggest it was founded to increase the ASHG's public and policy engagement, exploration of the committee's early years reveals a more complicated reality. Affronted by legislators' recent unwillingness to seek the expert advice of human geneticists before adopting widespread neonatal screening programs for phenylketonuria (PKU), and feeling pressed to establish their relevance in an increasingly resource-scarce funding environment, committee members sought to increase the discipline's expert authority. Painfully aware of controversy over abortion rights and haunted by the taint of the discipline's eugenic past, however, the committee proceeded with great caution. Seeking to harness interest in and assert professional control over emerging techniques of genetic diagnosis, the committee strove to protect the society's image by relegating ethical and policy questions about their use to the individual consciences of member scientists. It was not until 1973, after the committee's modest success in organizing support for a retrospective public health study of PKU screening and following the legalization of abortion on demand, that the committee decided to take a more publicly engaged stance.

Development of new techniques of using irradiation in the genetic improvement of warm season grasses and an assessment of the genetic and cytogenetic effects. Annual report, August 1, 1976--October 31, 1977

International Nuclear Information System (INIS)

Burton, G.W.; Hanna, W.W.

1977-08-01

New techniques of using irradiation in the genetic improvement of several warm season grasses are described. The economic value of radiation induced plant mutants and the genetic and cytogenetic effects of these treatments are discussed. Alterations in protein quality in pearl millet grain and improved varieties of Bermuda grass following radiation treatment are reported

MetaGenyo: a web tool for meta-analysis of genetic association studies.

Science.gov (United States)

Martorell-Marugan, Jordi; Toro-Dominguez, Daniel; Alarcon-Riquelme, Marta E; Carmona-Saez, Pedro

2017-12-16

Genetic association studies (GAS) aims to evaluate the association between genetic variants and phenotypes. In the last few years, the number of this type of study has increased exponentially, but the results are not always reproducible due to experimental designs, low sample sizes and other methodological errors. In this field, meta-analysis techniques are becoming very popular tools to combine results across studies to increase statistical power and to resolve discrepancies in genetic association studies. A meta-analysis summarizes research findings, increases statistical power and enables the identification of genuine associations between genotypes and phenotypes. Meta-analysis techniques are increasingly used in GAS, but it is also increasing the amount of published meta-analysis containing different errors. Although there are several software packages that implement meta-analysis, none of them are specifically designed for genetic association studies and in most cases their use requires advanced programming or scripting expertise. We have developed MetaGenyo, a web tool for meta-analysis in GAS. MetaGenyo implements a complete and comprehensive workflow that can be executed in an easy-to-use environment without programming knowledge. MetaGenyo has been developed to guide users through the main steps of a GAS meta-analysis, covering Hardy-Weinberg test, statistical association for different genetic models, analysis of heterogeneity, testing for publication bias, subgroup analysis and robustness testing of the results. MetaGenyo is a useful tool to conduct comprehensive genetic association meta-analysis. The application is freely available at http://bioinfo.genyo.es/metagenyo/ .

Automatic Creation of Machine Learning Workflows with Strongly Typed Genetic Programming

Czech Academy of Sciences Publication Activity Database

Křen, T.; Pilát, M.; Neruda, Roman

2017-01-01

Roč. 26, č. 5 (2017), č. článku 1760020. ISSN 0218-2130 R&D Projects: GA ČR GA15-19877S Grant - others:GA MŠk(CZ) LM2015042 Institutional support: RVO:67985807 Keywords : genetic programming * machine learning workflows * asynchronous evolutionary algorithm Subject RIV: IN - Informatics, Computer Science OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.778, year: 2016

FORTRAN programs for transient eddy current calculations using a perturbation-polynomial expansion technique

International Nuclear Information System (INIS)

Carpenter, K.H.

1976-11-01

A description is given of FORTRAN programs for transient eddy current calculations in thin, non-magnetic conductors using a perturbation-polynomial expansion technique. Basic equations are presented as well as flow charts for the programs implementing them. The implementation is in two steps--a batch program to produce an intermediate data file and interactive programs to produce graphical output. FORTRAN source listings are included for all program elements, and sample inputs and outputs are given for the major programs

Development of programming techniques for behaviors of nuclear robot in real environment

International Nuclear Information System (INIS)

Tsukune, Hideo; Ogasawara, Tsukasa; Hirukawa, Hirohisa; Kitagaki, Kosei; Onda, Hiromu; Nakamura, Akira

1999-01-01

This study aims at establishment of synthetic autonomous technique on nuclear robot for a basic technique to realize remote control and automation of works in a nuclear plant by means of development on action programming function under actual environment. Before 1997 fiscal year, development of manipulation description system due to contact state transition series, development of mechanical assembly work instruction system using contact actuating system, development of new manipulator system with excellent controllability, development of quasi contact point monitoring method, and development of environmental model construction method using range finder and instruction tree, had been conducted. In 1997 fiscal year, probability of nuclear robot, on synthetic autonomous technique was shown by synthesis of many results on action programming planning function into a prototype system under an actual environment obtained by those developments. (G.K.)

IESIP - AN IMPROVED EXPLORATORY SEARCH TECHNIQUE FOR PURE INTEGER LINEAR PROGRAMMING PROBLEMS

Science.gov (United States)

Fogle, F. R.

1994-01-01

IESIP, an Improved Exploratory Search Technique for Pure Integer Linear Programming Problems, addresses the problem of optimizing an objective function of one or more variables subject to a set of confining functions or constraints by a method called discrete optimization or integer programming. Integer programming is based on a specific form of the general linear programming problem in which all variables in the objective function and all variables in the constraints are integers. While more difficult, integer programming is required for accuracy when modeling systems with small numbers of components such as the distribution of goods, machine scheduling, and production scheduling. IESIP establishes a new methodology for solving pure integer programming problems by utilizing a modified version of the univariate exploratory move developed by Robert Hooke and T.A. Jeeves. IESIP also takes some of its technique from the greedy procedure and the idea of unit neighborhoods. A rounding scheme uses the continuous solution found by traditional methods (simplex or other suitable technique) and creates a feasible integer starting point. The Hook and Jeeves exploratory search is modified to accommodate integers and constraints and is then employed to determine an optimal integer solution from the feasible starting solution. The user-friendly IESIP allows for rapid solution of problems up to 10 variables in size (limited by DOS allocation). Sample problems compare IESIP solutions with the traditional branch-and-bound approach. IESIP is written in Borland's TURBO Pascal for IBM PC series computers and compatibles running DOS. Source code and an executable are provided. The main memory requirement for execution is 25K. This program is available on a 5.25 inch 360K MS DOS format diskette. IESIP was developed in 1990. IBM is a trademark of International Business Machines. TURBO Pascal is registered by Borland International.

Optimal Draft requirement for vibratory tillage equipment using Genetic Algorithm Technique

Science.gov (United States)

Rao, Gowripathi; Chaudhary, Himanshu; Singh, Prem

2018-03-01

Agriculture is an important sector of Indian economy. Primary and secondary tillage operations are required for any land preparation process. Conventionally different tractor-drawn implements such as mouldboard plough, disc plough, subsoiler, cultivator and disc harrow, etc. are used for primary and secondary manipulations of soils. Among them, oscillatory tillage equipment is one such type which uses vibratory motion for tillage purpose. Several investigators have reported that the requirement for draft consumption in primary tillage implements is more as compared to oscillating one because they are always in contact with soil. Therefore in this paper, an attempt is made to find out the optimal parameters from the experimental data available in the literature to obtain minimum draft consumption through genetic algorithm technique.

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.

Loss of genetic diversity in Culex quinquefasciatus targeted by a lymphatic filariasis vector control program in Recife, Brazil.

Science.gov (United States)

Cartaxo, Marina F S; Ayres, Constância F J; Weetman, David

2011-09-01

Recife is one of the largest cities in north-eastern Brazil and is endemic for lymphatic filariasis transmitted by Culex quinquefasciatus. Since 2003 a control program has targeted mosquito larvae by elimination of breeding sites and bimonthly application of Bacillus sphaericus. To assess the impact of this program on the local vector population we monitored the genetic diversity and differentiation of Cx. quinquefasciatus using microsatellites and a B. sphaericus-resistance associated mutation (cqm1(REC)) over a 3-year period. We detected a significant but gradual decline in allelic diversity, which, coupled with subtle temporal genetic structure, suggests a major impact of the control program on the vector population. Selection on cqm1(REC) does not appear to be involved with loss of neutral diversity from the population, with no temporal trend in resistant allele frequency and no correlation with microsatellite differentiation. The evidence for short-term genetic drift we detected suggests a low ratio of effective population size: census population size for Cx. quinquefasciatus, perhaps coupled with strong geographically-restricted population structure. Spatial definition of populations will be an important step for success of an expanded vector control program. Copyright © 2011 Royal Society of Tropical Medicine and Hygiene. Published by Elsevier Ltd. All rights reserved.

Development of new techniques of using irradiation in the genetic improvement of warm season grasses, the assessment of their genetic and cytogenetic effects and biomass production from grass. Annual progress report, November 1, 1979 to October 31, 1980

International Nuclear Information System (INIS)

Burton, G.W.; Hanna, W.W.

1980-01-01

New techniques are described for using irradiation and chemical mutagens in the genetic improvement of several warm season grasses. Genetic and cytogenetic effects of these treatments are also being studied

Efficient experimental design of high-fidelity three-qubit quantum gates via genetic programming

Science.gov (United States)

Devra, Amit; Prabhu, Prithviraj; Singh, Harpreet; Arvind; Dorai, Kavita

2018-03-01

We have designed efficient quantum circuits for the three-qubit Toffoli (controlled-controlled-NOT) and the Fredkin (controlled-SWAP) gate, optimized via genetic programming methods. The gates thus obtained were experimentally implemented on a three-qubit NMR quantum information processor, with a high fidelity. Toffoli and Fredkin gates in conjunction with the single-qubit Hadamard gates form a universal gate set for quantum computing and are an essential component of several quantum algorithms. Genetic algorithms are stochastic search algorithms based on the logic of natural selection and biological genetics and have been widely used for quantum information processing applications. We devised a new selection mechanism within the genetic algorithm framework to select individuals from a population. We call this mechanism the "Luck-Choose" mechanism and were able to achieve faster convergence to a solution using this mechanism, as compared to existing selection mechanisms. The optimization was performed under the constraint that the experimentally implemented pulses are of short duration and can be implemented with high fidelity. We demonstrate the advantage of our pulse sequences by comparing our results with existing experimental schemes and other numerical optimization methods.

PhyloGeoViz: a web-based program that visualizes genetic data on maps.

Science.gov (United States)

Tsai, Yi-Hsin E

2011-05-01

The first step of many population genetic studies is the simple visualization of allele frequencies on a landscape. This basic data exploration can be challenging without proprietary software, and the manual plotting of data is cumbersome and unfeasible at large sample sizes. I present an open source, web-based program that plots any kind of frequency or count data as pie charts in Google Maps (Google Inc., Mountain View, CA). Pie polygons are then exportable to Google Earth (Google Inc.), a free Geographic Information Systems platform. Import of genetic data into Google Earth allows phylogeographers access to a wealth of spatial information layers integral to forming hypotheses and understanding patterns in the data. © 2010 Blackwell Publishing Ltd.

A comparison of fitness-case sampling methods for genetic programming

Science.gov (United States)

Martínez, Yuliana; Naredo, Enrique; Trujillo, Leonardo; Legrand, Pierrick; López, Uriel

2017-11-01

Genetic programming (GP) is an evolutionary computation paradigm for automatic program induction. GP has produced impressive results but it still needs to overcome some practical limitations, particularly its high computational cost, overfitting and excessive code growth. Recently, many researchers have proposed fitness-case sampling methods to overcome some of these problems, with mixed results in several limited tests. This paper presents an extensive comparative study of four fitness-case sampling methods, namely: Interleaved Sampling, Random Interleaved Sampling, Lexicase Selection and Keep-Worst Interleaved Sampling. The algorithms are compared on 11 symbolic regression problems and 11 supervised classification problems, using 10 synthetic benchmarks and 12 real-world data-sets. They are evaluated based on test performance, overfitting and average program size, comparing them with a standard GP search. Comparisons are carried out using non-parametric multigroup tests and post hoc pairwise statistical tests. The experimental results suggest that fitness-case sampling methods are particularly useful for difficult real-world symbolic regression problems, improving performance, reducing overfitting and limiting code growth. On the other hand, it seems that fitness-case sampling cannot improve upon GP performance when considering supervised binary classification.

Education and certification of genetic counselors.

Science.gov (United States)

Katsichti, L; Hadzipetros-Bardanis, M; Bartsocas, C S

1999-01-01

Genetic counseling is defined by the American Society of Human Genetics as a communication process which deals with the human problems associated with the occurrence, or risk of occurrence, of a genetic disorder in a family. The first graduate program (Master's degree) in genetic counseling started in 1969 at Sarah Lawrence College, NY, USA, while in 1979 the National Society of Genetic Counseling (NSGC) was established. Today, there are 29 programs in U.S.A. offering a Master's degree in Genetic Counseling, five programs in Canada, one in Mexico, one in England and one in S. Africa. Most of these graduate programs offer two year training, consisting of graduate courses, seminars, research and practical training. Emphasis is given in human physiology, biochemistry, clinical genetics, cytogenetics, molecular and biochemical genetics, population genetics and statistics, prenatal diagnosis, teratology and genetic counseling in relation to psychosocial and ethical issues. Certification for eligible candidates is available through the American Board of Medical Genetics (ABMG). Requirements for certification include a master's degree in human genetics, training at sites accredited by the ABMG, documentation of genetic counseling experience, evidence of continuing education and successful completion of a comprehensive ABMG certification examination. As professionals, genetic counselors should maintain expertise, should insure mechanisms for professional advancement and should always maintain the ability to approach their patients.

Programming peptidomimetic syntheses by translating genetic codes designed de novo.

Science.gov (United States)

Forster, Anthony C; Tan, Zhongping; Nalam, Madhavi N L; Lin, Hening; Qu, Hui; Cornish, Virginia W; Blacklow, Stephen C

2003-05-27

Although the universal genetic code exhibits only minor variations in nature, Francis Crick proposed in 1955 that "the adaptor hypothesis allows one to construct, in theory, codes of bewildering variety." The existing code has been expanded to enable incorporation of a variety of unnatural amino acids at one or two nonadjacent sites within a protein by using nonsense or frameshift suppressor aminoacyl-tRNAs (aa-tRNAs) as adaptors. However, the suppressor strategy is inherently limited by compatibility with only a small subset of codons, by the ways such codons can be combined, and by variation in the efficiency of incorporation. Here, by preventing competing reactions with aa-tRNA synthetases, aa-tRNAs, and release factors during translation and by using nonsuppressor aa-tRNA substrates, we realize a potentially generalizable approach for template-encoded polymer synthesis that unmasks the substantially broader versatility of the core translation apparatus as a catalyst. We show that several adjacent, arbitrarily chosen sense codons can be completely reassigned to various unnatural amino acids according to de novo genetic codes by translating mRNAs into specific peptide analog polymers (peptidomimetics). Unnatural aa-tRNA substrates do not uniformly function as well as natural substrates, revealing important recognition elements for the translation apparatus. Genetic programming of peptidomimetic synthesis should facilitate mechanistic studies of translation and may ultimately enable the directed evolution of small molecules with desirable catalytic or pharmacological properties.

Genetic improvement of Pacific white shrimp (Penaeus (Litopenaeus vannamei: perspectives for genomic selection

Directory of Open Access Journals (Sweden)

Héctor eCastillo-Juárez

2015-03-01

Full Text Available The use of breeding programs for the Pacific white shrimp (Penaeus (Litopenaeus vannamei based on mixed linear models with pedigreed data are described. The application of these classic breeding methods yielded continuous progress of great value to increase the profitability of the shrimp industry in several countries. Recent advances in such areas as genomics in shrimp will allow for the development of new breeding programs in the near future that will increase genetic progress. In particular, these novel techniques may help increase disease resistance to specific emerging diseases, which is today a very important component of shrimp breeding programs. Thanks to increased selection accuracy, simulated genetic advance using genomic selection for survival to a disease challenge was up to 2.6 times that of phenotypic sib selection.

ActionScript 30 Design Patterns Object Oriented Programming Techniques

CERN Document Server

Sanders, William

2008-01-01

If you're an experienced Flash or Flex developer ready to tackle sophisticated programming techniques with ActionScript 3.0, this hands-on introduction to design patterns takes you step by step through the process. You learn about various types of design patterns and construct small abstract examples before trying your hand at building full-fledged working applications outlined in the book.

Improved model reduction and tuning of fractional-order PI(λ)D(μ) controllers for analytical rule extraction with genetic programming.

Science.gov (United States)

Das, Saptarshi; Pan, Indranil; Das, Shantanu; Gupta, Amitava

2012-03-01

Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time domain tuning of proportional-integral-derivative (PID) and fractional-order (FO) PI(λ)D(μ) controllers. Simulation studies show that the new Nyquist-based model reduction technique outperforms the conventional H(2)-norm-based reduced parameter modeling technique. With the tuned controller parameters and reduced-order model parameter dataset, optimum tuning rules have been developed with a test-bench of higher-order processes via genetic programming (GP). The GP performs a symbolic regression on the reduced process parameters to evolve a tuning rule which provides the best analytical expression to map the data. The tuning rules are developed for a minimum time domain integral performance index described by a weighted sum of error index and controller effort. From the reported Pareto optimal front of the GP-based optimal rule extraction technique, a trade-off can be made between the complexity of the tuning formulae and the control performance. The efficacy of the single-gene and multi-gene GP-based tuning rules has been compared with the original GA-based control performance for the PID and PI(λ)D(μ) controllers, handling four different classes of representative higher-order processes. These rules are very useful for process control engineers, as they inherit the power of the GA-based tuning methodology, but can be easily calculated without the requirement for running the computationally intensive GA every time. Three-dimensional plots of the required variation in PID/fractional-order PID (FOPID) controller parameters with reduced process parameters have been shown as a guideline for the operator. Parametric robustness of the reported GP-based tuning rules has also been shown with credible simulation examples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

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.

Genetic Programming and Standardization in Water Temperature Modelling

Directory of Open Access Journals (Sweden)

Maritza Arganis

2009-01-01

Full Text Available An application of Genetic Programming (an evolutionary computational tool without and with standardization data is presented with the aim of modeling the behavior of the water temperature in a river in terms of meteorological variables that are easily measured, to explore their explanatory power and to emphasize the utility of the standardization of variables in order to reduce the effect of those with large variance. Recorded data corresponding to the water temperature behavior at the Ebro River, Spain, are used as analysis case, showing a performance improvement on the developed model when data are standardized. This improvement is reflected in a reduction of the mean square error. Finally, the models obtained in this document were applied to estimate the water temperature in 2004, in order to provide evidence about their applicability to forecasting purposes.

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.

Recognizing and Managing Complexity: Teaching Advanced Programming Concepts and Techniques Using the Zebra Puzzle

OpenAIRE

Xihui "Paul" Zhang; John D. Crabtree

2015-01-01

Teaching advanced programming can be a challenge, especially when the students are pursuing different majors with diverse analytical and problem-solving capabilities. The purpose of this paper is to explore the efficacy of using a particular problem as a vehicle for imparting a broad set of programming concepts and problem-solving techniques. We present a classic brain teaser that is used to communicate and demonstrate advanced software development concepts and techniques. Our results show th...

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

Science.gov (United States)

Muduli, Pradyut; Das, Sarat

2014-06-01

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

Genetic diversity of Prochilodus lineatus stocks using in the stocking program of Tietê River, Brazil

Directory of Open Access Journals (Sweden)

Ricardo Ribeiro

2013-11-01

Full Text Available Objective. Assess the genetic diversity in four brood stocks and one juvenile stock of curimba Prochilodus lineatus in a Hydropower plant in São Paulo - Brazil, using the Tietê River stocking program. Materials and methods. Five RAPD primers were used to amplify the extracted DNA from 150 fin-clip samples. Results. Fifty-nine fragments were polymorphic, 52 had frequencies with significant differences (p<0.05, 45 had low frequencies, 54 were excluded, and two were fixed fragments. High values for polymorphic fragments (71.19% to 91.53% and Shannon index (0.327 to 0.428 were observed. The genetic divergence values within each stock were greater than 50%. Most of the genetic variation was found within the groups through the AMOVA analysis, which was confirmed by the results of the identity and genetic distance. High ancestry levels (FST among the groups value indicated high and moderate genetic differentiation. The estimates of number of migrants by generation (Nm indicated low levels of gene flow. High and moderate genetic divergence between groups (0.58 to 0.83 was observed. Conclusions. The results indicate high variability within the stocks, and genetic differentiation among them. The fish stocks analyzed represent a large genetic base that will allow the fish technicians to release juveniles without genetic risks to wild populations present in the river. These genetic procedures may be used as models for other migratory species, including those threatened by extinction.

Genetic diversity of Coccidioides posadasii from Brazil.

Science.gov (United States)

Brilhante, Raimunda Sâmia Nogueira; de Lima, Rita Amanda Chaves; Ribeiro, Joyce Fonteles; de Camargo, Zoilo Pires; Castelo-Branco, Débora de Souza Collares Maia; Grangeiro, Thalles Barbosa; Cordeiro, Rossana de Aguiar; Gadelha Rocha, Marcos Fábio; Sidrim, José Júlio Costa

2013-05-01

Studies of the genetic variation within populations of Coccidioides posadasii are scarce, especially for those recovered from South America. Understanding the distribution of genotypes among populations is important for epidemiological surveillance. This study evaluated the genetic diversity of 18 Brazilian strains of C. posadasii through the sequencing of the 18-28S region of nuclear rDNA, as well as through RAPD and M13-PCR fingerprinting techniques. The sequences obtained were compared to Coccidioides spp. previously deposited in GenBank. The MEGA5 program was used to perform phylogenetic analyses. Within the C. posadasii clade, a single cluster was observed, containing seven isolates from Ceará, which presented a single nucleotide polymorphism. These isolates were from the same geographical area. The strains of C. posadasii showed a lower rate of genetic diversity in the ITS1 and ITS2 regions. The results of M13 and RAPD-PCR fingerprinting indicated a similar electrophoretic profile. No differences between clinical and environmental isolates were detected. This was the first study assessing the genetic variability of a larger number of C. posadasii isolates from Brazil.

Application of Genetic Algorithm and Particle Swarm Optimization techniques for improved image steganography systems

Directory of Open Access Journals (Sweden)

Jude Hemanth Duraisamy

2016-01-01

Full Text Available Image steganography is one of the ever growing computational approaches which has found its application in many fields. The frequency domain techniques are highly preferred for image steganography applications. However, there are significant drawbacks associated with these techniques. In transform based approaches, the secret data is embedded in random manner in the transform coefficients of the cover image. These transform coefficients may not be optimal in terms of the stego image quality and embedding capacity. In this work, the application of Genetic Algorithm (GA and Particle Swarm Optimization (PSO have been explored in the context of determining the optimal coefficients in these transforms. Frequency domain transforms such as Bandelet Transform (BT and Finite Ridgelet Transform (FRIT are used in combination with GA and PSO to improve the efficiency of the image steganography system.

Preimplantation genetic screening.

Science.gov (United States)

Harper, Joyce C

2018-03-01

Preimplantation genetic diagnosis was first successfully performed in 1989 as an alternative to prenatal diagnosis for couples at risk of transmitting a genetic or chromosomal abnormality, such as cystic fibrosis, to their child. From embryos generated in vitro, biopsied cells are genetically tested. From the mid-1990s, this technology has been employed as an embryo selection tool for patients undergoing in vitro fertilisation, screening as many chromosomes as possible, in the hope that selecting chromosomally normal embryos will lead to higher implantation and decreased miscarriage rates. This procedure, preimplantation genetic screening, was initially performed using fluorescent in situ hybridisation, but 11 randomised controlled trials of screening using this technique showed no improvement in in vitro fertilisation delivery rates. Progress in genetic testing has led to the introduction of array comparative genomic hybridisation, quantitative polymerase chain reaction, and next generation sequencing for preimplantation genetic screening, and three small randomised controlled trials of preimplantation genetic screening using these new techniques indicate a modest benefit. Other trials are still in progress but, regardless of their results, preimplantation genetic screening is now being offered globally. In the near future, it is likely that sequencing will be used to screen the full genetic code of the embryo.

Detonation of high explosives in Lagrangian hydrodynamic codes using the programmed burn technique

International Nuclear Information System (INIS)

Berger, M.E.

1975-09-01

Two initiation methods were developed for improving the programmed burn technique for detonation of high explosives in smeared-shock Lagrangian hydrodynamic codes. The methods are verified by comparing the improved programmed burn with existing solutions in one-dimensional plane, converging, and diverging geometries. Deficiencies in the standard programmed burn are described. One of the initiation methods has been determined to be better for inclusion in production hydrodynamic codes

A Chromosome-Scale Assembly of the Bactrocera cucurbitae Genome Provides Insight to the Genetic Basis of white pupae

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Sheina B. Sim

2017-06-01

Full Text Available Genetic sexing strains (GSS used in sterile insect technique (SIT programs are textbook examples of how classical Mendelian genetics can be directly implemented in the management of agricultural insect pests. Although the foundation of traditionally developed GSS are single locus, autosomal recessive traits, their genetic basis are largely unknown. With the advent of modern genomic techniques, the genetic basis of sexing traits in GSS can now be further investigated. This study is the first of its kind to integrate traditional genetic techniques with emerging genomics to characterize a GSS using the tephritid fruit fly pest Bactrocera cucurbitae as a model. These techniques include whole-genome sequencing, the development of a mapping population and linkage map, and quantitative trait analysis. The experiment designed to map the genetic sexing trait in B. cucurbitae, white pupae (wp, also enabled the generation of a chromosome-scale genome assembly by integrating the linkage map with the assembly. Quantitative trait loci analysis revealed SNP loci near position 42 MB on chromosome 3 to be tightly linked to wp. Gene annotation and synteny analysis show a near perfect relationship between chromosomes in B. cucurbitae and Muller elements A–E in Drosophila melanogaster. This chromosome-scale genome assembly is complete, has high contiguity, was generated using a minimal input DNA, and will be used to further characterize the genetic mechanisms underlying wp. Knowledge of the genetic basis of genetic sexing traits can be used to improve SIT in this species and expand it to other economically important Diptera.

Adults' perceptions of genetic counseling and genetic testing.

Science.gov (United States)

Houfek, Julia Fisco; Soltis-Vaughan, Brigette S; Atwood, Jan R; Reiser, Gwendolyn M; Schaefer, G Bradley

2015-02-01

This study described the perceptions of genetic counseling and testing of adults (N = 116) attending a genetic education program. Understanding perceptions of genetic counseling, including the importance of counseling topics, will contribute to patient-focused care as clinical genetic applications for common, complex disorders evolve. Participants completed a survey addressing: the importance of genetic counseling topics, benefits and negative effects of genetic testing, and sharing test results. Topics addressing practical information about genetic conditions were rated most important; topics involving conceptual genetic/genomic principles were rated least important. The most frequently identified benefit and negative effect of testing were prevention/early detection/treatment and psychological distress. Participants perceived that they were more likely to share test results with first-degree than other relatives. Findings suggest providing patients with practical information about genetic testing and genetic contributions to disease, while also determining whether their self-care abilities would be enhanced by teaching genetic/genomic principles. Copyright © 2014 Elsevier Inc. All rights reserved.

A research on applications of qualitative reasoning techniques in Human Acts Simulation Program

International Nuclear Information System (INIS)

Far, B.H.

1992-04-01

Human Acts Simulation Program (HASP) is a ten-year research project of the Computing and Information Systems Center of JAERI. In HASP the goal is developing programs for an advanced intelligent robot to accomplish multiple instructions (for instance, related to surveillance, inspection and maintenance) in nuclear power plants. Some recent artificial intelligence techniques can contribute to this project. This report introduces some original contributions concerning application of Qualitative Reasoning (QR) techniques in HASP. The focus is on the knowledge-intensive tasks, including model-based reasoning, analytic learning, fault diagnosis and functional reasoning. The multi-level extended qualitative modeling for the Skill-Rule-Knowledge (S-R-K) based reasoning, that included the coordination and timing of events, Qualitative Sensitivity analysis (Q S A), Subjective Qualitative Fault Diagnosis (S Q F D) and Qualitative Function Formation (Q F F ) techniques are introduced. (author) 123 refs

The Virtual Genetics Lab II: Improvements to a Freely Available Software Simulation of Genetics

Science.gov (United States)

White, Brian T.

2012-01-01

The Virtual Genetics Lab II (VGLII) is an improved version of the highly successful genetics simulation software, the Virtual Genetics Lab (VGL). The software allows students to use the techniques of genetic analysis to design crosses and interpret data to solve realistic genetics problems involving a hypothetical diploid insect. This is a brief…

Extraction of Static and Dynamic Reservoir Operation Rules by Genetic Programming

Directory of Open Access Journals (Sweden)

Habib Akbari Alashti

2014-11-01

Full Text Available Considering the necessity of desirable operation of limited water resources and assuming the significant role of dams in controlling and consuming the surface waters, highlights the advantageous of suitable operation rules for optimal and sustainable operation of dams. This study investigates the hydroelectric supply of a one-reservoir system of Karoon3 using nonlinear programming (NLP, genetic algorithm (GA, genetic programming (GP and fixed length gen GP (FLGGP in real-time operation of dam considering two approaches of static and dynamic operation rules. In static operation rule, only one rule curve is extracted for all months in a year whereas in dynamic operation rule, monthly rule curves (12 rules are extracted for each month of a year. In addition, nonlinear decision rule (NLDR curves are considered, and the total deficiency function as the target (objective function have been used for evaluating the performance of each method and approach. Results show appropriate efficiency of GP and FLGGP methods in extracting operation rules in both approaches. Superiority of these methods to operation methods yielded by GA and NLP is 5%. Moreover, according to the results, it can be remarked that, FLGGP method is an alternative for GP method, whereas the GP method cannot be used due to its limitations. Comparison of two approaches of static and dynamic operation rules demonstrated the superiority of dynamic operation rule to static operation rule (about 10% and therefore this method has more capabilities in real-time operation of the reservoirs systems.

Breeding technique of Anastrepha fraterculus (Wied.) for genetic studies

International Nuclear Information System (INIS)

Manso, F.

1999-01-01

Various samples of Anastrepha fraterculus from different areas in Argentina were obtained to develop artificial breeding in the laboratory. Based on a modification of Salles's method, an improved artificial rearing of the species was developed with satisfactory results for genetic analysis. The advances made will contribute towards the search for genetic mechanisms for control. (author)

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.

Genetic evaluation of reproductive potential in the Zatorska goose under a conservation program.

Science.gov (United States)

Graczyk, Magdalena; Andres, Krzysztof; Kapkowska, Ewa; Szwaczkowski, Tomasz

2018-05-01

The aim of this study was to estimate the genetic parameters and inbreeding effect on the fertility, embryo mortality and hatchability traits in the Zatorska goose covered by the animal genetic resources conservation program. The material for this study contains information about results of hatching of 18 863 eggs from 721 dams and 168 sires, laid between 1998-2015. Genetic parameters were estimated based on the threshold animal model by the use of Restricted Maximum Likelihood and Gibbs sampling. The percentage of fertilized eggs ranged yearly between 37-80%. The percentage of embryo mortality was very low, ranging between 4.63-23.73%. The percentage of the hatched goslings from the total number of analyzed eggs was on average 33.18%, and 53.72% from fertilized eggs. On average based on both methods, the heritability estimates of the fertility, embryo mortality and hatchability reached 0.36, 0.07, 0.24 for males and 0.44, 0.11, 0.32 for females. The genetic trend had increasing tendency for fertility and hatchability and was stable for embryo mortality for both sexes. The obtained result shows that the Zatorska goose can be still maintained in the reserves of the local gene pool according to current rules and use in the local market as a breed with good reproductive potential. © 2018 Japanese Society of Animal Science.

[Training program design of acupuncture and moxibustion manipulation techniques].

Science.gov (United States)

Dong, Qin

2009-12-01

As an important component of acupuncture-moxibustion science, needling and moxibustion is one methodology and technology and its technical characteristics determine its special status and role in training programs. It is closely ralated to meridians-collaterals-acupoints and acupuncture treatment. Therefore, it demands an overall planning for acupuncture professional skills that consists of meridians-collaterals-acupoints knowledge and acupuncture treatment techniques. The practical training courses are the step by step progress involving repeated practices.

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.

Genetic Gain and Inbreeding from Genomic Selection in a Simulated Commercial Breeding Program for Perennial Ryegrass

Directory of Open Access Journals (Sweden)

Zibei Lin

2016-03-01

Full Text Available Genomic selection (GS provides an attractive option for accelerating genetic gain in perennial ryegrass ( improvement given the long cycle times of most current breeding programs. The present study used simulation to investigate the level of genetic gain and inbreeding obtained from GS breeding strategies compared with traditional breeding strategies for key traits (persistency, yield, and flowering time. Base population genomes were simulated through random mating for 60,000 generations at an effective population size of 10,000. The degree of linkage disequilibrium (LD in the resulting population was compared with that obtained from empirical studies. Initial parental varieties were simulated to match diversity of current commercial cultivars. Genomic selection was designed to fit into a company breeding program at two selection points in the breeding cycle (spaced plants and miniplot. Genomic estimated breeding values (GEBVs for productivity traits were trained with phenotypes and genotypes from plots. Accuracy of GEBVs was 0.24 for persistency and 0.36 for yield for single plants, while for plots it was lower (0.17 and 0.19, respectively. Higher accuracy of GEBVs was obtained for flowering time (up to 0.7, partially as a result of the larger reference population size that was available from the clonal row stage. The availability of GEBVs permit a 4-yr reduction in cycle time, which led to at least a doubling and trebling genetic gain for persistency and yield, respectively, than the traditional program. However, a higher rate of inbreeding per cycle among varieties was also observed for the GS strategy.

Genetic Gain and Inbreeding from Genomic Selection in a Simulated Commercial Breeding Program for Perennial Ryegrass.

Science.gov (United States)

Lin, Zibei; Cogan, Noel O I; Pembleton, Luke W; Spangenberg, German C; Forster, John W; Hayes, Ben J; Daetwyler, Hans D

2016-03-01

Genomic selection (GS) provides an attractive option for accelerating genetic gain in perennial ryegrass () improvement given the long cycle times of most current breeding programs. The present study used simulation to investigate the level of genetic gain and inbreeding obtained from GS breeding strategies compared with traditional breeding strategies for key traits (persistency, yield, and flowering time). Base population genomes were simulated through random mating for 60,000 generations at an effective population size of 10,000. The degree of linkage disequilibrium (LD) in the resulting population was compared with that obtained from empirical studies. Initial parental varieties were simulated to match diversity of current commercial cultivars. Genomic selection was designed to fit into a company breeding program at two selection points in the breeding cycle (spaced plants and miniplot). Genomic estimated breeding values (GEBVs) for productivity traits were trained with phenotypes and genotypes from plots. Accuracy of GEBVs was 0.24 for persistency and 0.36 for yield for single plants, while for plots it was lower (0.17 and 0.19, respectively). Higher accuracy of GEBVs was obtained for flowering time (up to 0.7), partially as a result of the larger reference population size that was available from the clonal row stage. The availability of GEBVs permit a 4-yr reduction in cycle time, which led to at least a doubling and trebling genetic gain for persistency and yield, respectively, than the traditional program. However, a higher rate of inbreeding per cycle among varieties was also observed for the GS strategy. Copyright © 2016 Crop Science Society of America.

Fungal Genetics and Functional Diversity of Microbial Communities in the Soil under Long-Term Monoculture of Maize Using Different Cultivation Techniques

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Anna Gałązka

2018-01-01

Full Text Available Fungal diversity in the soil may be limited under natural conditions by inappropriate environmental factors such as: nutrient resources, biotic and abiotic factors, tillage system and microbial interactions that prevent the occurrence or survival of the species in the environment. The aim of this paper was to determine fungal genetic diversity and community level physiological profiling of microbial communities in the soil under long-term maize monoculture. The experimental scheme involved four cultivation techniques: direct sowing (DS, reduced tillage (RT, full tillage (FT, and crop rotation (CR. Soil samples were taken in two stages: before sowing of maize (DSBS-direct sowing, RTBS-reduced tillage, FTBS-full tillage, CRBS-crop rotation and the flowering stage of maize growth (DSF-direct sowing, RTF-reduced tillage, FTF-full tillage, CRF-crop rotation. The following plants were used in the crop rotation: spring barley, winter wheat and maize. The study included fungal genetic diversity assessment by ITS-1 next generation sequencing (NGS analyses as well as the characterization of the catabolic potential of microbial communities (Biolog EcoPlates in the soil under long-term monoculture of maize using different cultivation techniques. The results obtained from the ITS-1 NGS technique enabled to classify and correlate the fungi species or genus to the soil metabolome. The research methods used in this paper have contributed to a better understanding of genetic diversity and composition of the population of fungi in the soil under the influence of the changes that have occurred in the soil under long-term maize cultivation. In all cultivation techniques, the season had a great influence on the fungal genetic structure in the soil. Significant differences were found on the family level (P = 0.032, F = 3.895, genus level (P = 0.026, F = 3.313 and on the species level (P = 0.033, F = 2.718. This study has shown that: (1 fungal diversity was changed

Analysis of Program Obfuscation Schemes with Variable Encoding Technique

Science.gov (United States)

Fukushima, Kazuhide; Kiyomoto, Shinsaku; Tanaka, Toshiaki; Sakurai, Kouichi

Program analysis techniques have improved steadily over the past several decades, and software obfuscation schemes have come to be used in many commercial programs. A software obfuscation scheme transforms an original program or a binary file into an obfuscated program that is more complicated and difficult to analyze, while preserving its functionality. However, the security of obfuscation schemes has not been properly evaluated. In this paper, we analyze obfuscation schemes in order to clarify the advantages of our scheme, the XOR-encoding scheme. First, we more clearly define five types of attack models that we defined previously, and define quantitative resistance to these attacks. Then, we compare the security, functionality and efficiency of three obfuscation schemes with encoding variables: (1) Sato et al.'s scheme with linear transformation, (2) our previous scheme with affine transformation, and (3) the XOR-encoding scheme. We show that the XOR-encoding scheme is superior with regard to the following two points: (1) the XOR-encoding scheme is more secure against a data-dependency attack and a brute force attack than our previous scheme, and is as secure against an information-collecting attack and an inverse transformation attack as our previous scheme, (2) the XOR-encoding scheme does not restrict the calculable ranges of programs and the loss of efficiency is less than in our previous scheme.

POPULATION GENETICS OF Atta sexdens rubropilosa (HYMENOPTERA: FORMICIDAE

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Liriana Belizário Cantagalli

2013-01-01

Full Text Available The genetic variability of Atta sexdens rubropilosa leaf-cutting ants collected from five brazilian localities was evaluated with PCR-RAPD technique. We used 15 primers producing 148 fragments of which 123 (83,11 % contained polymorphisms. The estimated Shannon index was 0.3836 ± 0.2335 showing that these ants possess high genetic diversity. The GST value was 0,2372 and PT = 0,184, indicating that the analyzed populations are moderately differentiated and 82 % of the variation obtained occur within populations. Although Mantel’s test had shown correlation between genetic distances and geographic was observed that Ivatuba and Itambé (33,8 km have the small geographical distance and the largest genetic distance. The lower genetic distance was estimated for Maringá and Ivatuba but this localities have a small geographic distance (42,3 km, indicating that there are no barriers for mating among reproducers in these populations. The high degree of polymorphism (83,11 % and the ability to cross among the populations in the studied regions indicate that this species of leaf-cutting ant is well adapted to the region; therefore, integrated control programs can be developed.

Population genetics of Atta sexdens rubropilosa (Hymenoptera: Formicidae)

International Nuclear Information System (INIS)

Belizario Cantagalli, Liriana; Aparecida Mangolin, Claudete; Colla Ruvolo Takasusuki, Maria Claudia

2013-01-01

The genetic variability of Atta sexdens rubropilosa leaf-cutting ants collected from five Brazilian localities was evaluated with PCR-RAPD technique. we used 15 primers producing 148 fragments of which 123 (83.11 %) contained polymorphisms. the estimated Shannon index was 0.3836 ± 0.2335 showing that these ants possess high genetic diversity. the G S T value was 0.2372 and Φ p t = 0.184, indicating that the analyzed populations are moderately differentiated and 82 % of the variation obtained occur within populations. although mantel's test had shown correlation between genetic distances and geographic was observed that Ivatuba and Itambe (33.8 km) have the small geographical distance and the largest genetic distance. the lower genetic distance was estimated for Maringa and Ivatuba but this localities have a small geographic distance (42.3 km), indicating that there are no barriers for mating among reproducers in these populations. the high degree of polymorphism (83.11 %) and the ability to cross among the populations in the studied regions indicate that this species of leaf-cutting ant is well adapted to the region; therefore, integrated control programs can be developed.

Genetics of pediatric obesity.

Science.gov (United States)

Manco, Melania; Dallapiccola, Bruno

2012-07-01

Onset of obesity has been anticipated at earlier ages, and prevalence has dramatically increased worldwide over the past decades. Epidemic obesity is mainly attributable to modern lifestyle, but family studies prove the significant role of genes in the individual's predisposition to obesity. Advances in genotyping technologies have raised great hope and expectations that genetic testing will pave the way to personalized medicine and that complex traits such as obesity will be prevented even before birth. In the presence of the pressing offer of direct-to-consumer genetic testing services from private companies to estimate the individual's risk for complex phenotypes including obesity, the present review offers pediatricians an update of the state of the art on genomics obesity in childhood. Discrepancies with respect to genomics of adult obesity are discussed. After an appraisal of findings from genome-wide association studies in pediatric populations, the rare variant-common disease hypothesis, the theoretical soil for next-generation sequencing techniques, is discussed as opposite to the common disease-common variant hypothesis. Next-generation sequencing techniques are expected to fill the gap of "missing heritability" of obesity, identifying rare variants associated with the trait and clarifying the role of epigenetics in its heritability. Pediatric obesity emerges as a complex phenotype, modulated by unique gene-environment interactions that occur in periods of life and are "permissive" for the programming of adult obesity. With the advent of next-generation sequencing techniques and advances in the field of exposomics, sensitive and specific tools to predict the obesity risk as early as possible are the challenge for the next decade.

Aerobic Exercise Combined with Techniques Programe Can Be Increased Groundstroke Skill of Tennis Athlet

OpenAIRE

Nasrulloh, Ahmad

2012-01-01

Professional tennis athletes should be able to master all the basic techniques of playing tennis and having physical fitness. Therefore, it is necessary to get an exercise that can give meaning to the skills and physical fitness. One of the proper exercises is with aerobic exercise combined with the technique.Aerobic exercise program combined with techniques is: (1) a number of players consisting of six to seven people with backward sequential formation techniques performing forehand and back...

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.

Structural health monitoring feature design by genetic programming

International Nuclear Information System (INIS)

Harvey, Dustin Y; Todd, Michael D

2014-01-01

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. (paper)

Genetic algorithms and fuzzy multiobjective optimization

CERN Document Server

Sakawa, Masatoshi

2002-01-01

Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields. Over the years, many excellent books in genetic algorithm optimization have been published; however, they focus mainly on single-objective discrete or other hard optimization problems under certainty. There appears to be no book that is designed to present genetic algorithms for solving not only single-objective but also fuzzy and multiobjective optimization problems in a unified way. Genetic Algorithms And Fuzzy Multiobjective Optimization introduces the latest advances in the field of genetic algorithm optimization for 0-1 programming, integer programming, nonconvex programming, and job-shop scheduling problems under multiobjectiveness and fuzziness. In addition, the book treats a w...

Biochemical and genetic variation of some Syrian wheat varieties using NIR, RAPD and AFLPs techniques

International Nuclear Information System (INIS)

Saleh, B.

2012-01-01

This study was performed to assess chemical components and genetic variability of five Syrian wheat varieties using NIR, RAPD and AFLP techniques. NIR technique showed that Cham6 was the best variety in term of wheat grain quality due to their lowest protein (%), hardness, water uptake and baking volume and the highest starch (%) compared to the other tested varieties. PCR amplifications with 21 RAPD primers and 13 AFLP PCs primer combinations gave 104 and 466 discernible loci of which 24 (18.823%) and 199 (45.527%) were polymorphic for the both techniques respectively. Our data indicated that the three techniques gave similar results regarding the degree of relatedness among the tested varieties. In the present investigation, AFLP fingerprinting was more efficient than the RAPD assay. Where the letter exhibited lower Marker Index (MI) average (0.219) compared to AFLP one (3.203). The pattern generated by RAPD, AFLPs markers or by NIR separated the five wheat varieties into two groups. The first group consists of two subclusters. The first subcluster involved Cham8 and Bohous6, while the second one includes Cham6 that is very closed to precedent varieties. The second group consists of Bohous9 and Cham7 that were also closely related. Based on this study, the use of NIR, RAPD and AFLP techniques could be a powerful tool to detect the effectiveness relationships of these technologies. (author)

Risk-informed decision making in the nuclear industry: Application and effectiveness comparison of different genetic algorithm techniques

International Nuclear Information System (INIS)

Gjorgiev, Blaže; Kančev, Duško; Čepin, Marko

2012-01-01

Highlights: ► Multi-objective optimization of STI based on risk-informed decision making. ► Four different genetic algorithms (GAs) techniques are used as optimization tool. ► Advantages/disadvantages among the four different GAs applied are emphasized. - Abstract: The risk-informed decision making (RIDM) process, where insights gained from the probabilistic safety assessment are contemplated together with other engineering insights, is gaining an ever-increasing attention in the process industries. Increasing safety systems availability by applying RIDM is one of the prime goals for the authorities operating with nuclear power plants. Additionally, equipment ageing is gradually becoming a major concern in the process industries and especially in the nuclear industry, since more and more safety-related components are approaching or are already in their wear-out phase. A significant difficulty regarding the consideration of ageing effects on equipment (un)availability is the immense uncertainty the available equipment ageing data are associated to. This paper presents an approach for safety system unavailability reduction by optimizing the related test and maintenance schedule suggested by the technical specifications in the nuclear industry. Given the RIDM philosophy, two additional insights, i.e. ageing data uncertainty and test and maintenance costs, are considered along with unavailability insights gained from the probabilistic safety assessment for a selected standard safety system. In that sense, an approach for multi-objective optimization of the equipment surveillance test interval is proposed herein. Three different objective functions related to each one of the three different insights discussed above comprise the multi-objective nature of the optimization process. Genetic algorithm technique is utilized as an optimization tool. Four different types of genetic algorithms are utilized and consequently comparative analysis is conducted given the

System safety and reliability using object-oriented programming techniques

International Nuclear Information System (INIS)

Patterson-Hine, F.A.; Koen, B.V.

1987-01-01

Direct evaluation fault tree codes have been written in recursive, list-processing computer languages such as PL/1 (PATREC-I) and LISP (PATREC-L). The pattern-matching strategy implemented in these codes has been used extensively in France to evaluate system reliability. Recent reviews of the risk management process suggest that a data base containing plant-specific information be integrated with a package of codes used for probabilistic risk assessment (PRA) to alleviate some of the difficulties that make a PRA so costly and time-intensive. A new programming paradigm, object-oriented programming, is uniquely suited for the development of such a software system. A knowledge base and fault tree evaluation algorithm, based on previous experience with PATREC-L, have been implemented using object-oriented techniques, resulting in a reliability assessment environment that is easy to develop, modify, and extend

Phenotypic and Genetic Characterization of Circulating Tumor Cells by Combining Immunomagnetic Selection and FICTION Techniques

Science.gov (United States)

Campos, María; Prior, Celia; Warleta, Fernando; Zudaire, Isabel; Ruíz-Mora, Jesús; Catena, Raúl; Calvo, Alfonso; Gaforio, José J.

2008-01-01

The presence of circulating tumor cells (CTCs) in breast cancer patients has been proven to have clinical relevance. Cytogenetic characterization of these cells could have crucial relevance for targeted cancer therapies. We developed a method that combines an immunomagnetic selection of CTCs from peripheral blood with the fluorescence immunophenotyping and interphase cytogenetics as a tool for investigation of neoplasm (FICTION) technique. Briefly, peripheral blood (10 ml) from healthy donors was spiked with a predetermined number of human breast cancer cells. Nucleated cells were separated by double density gradient centrifugation of blood samples. Tumor cells (TCs) were immunomagnetically isolated with an anti-cytokeratin antibody and placed onto slides for FICTION analysis. For immunophenotyping and genetic characterization of TCs, a mixture of primary monoclonal anti-pancytokeratin antibodies was used, followed by fluorescent secondary antibodies, and finally hybridized with a TOP2A/HER-2/CEP17 multicolor probe. Our results show that TCs can be efficiently isolated from peripheral blood and characterized by FICTION. Because genetic amplification of TOP2A and ErbB2 (HER-2) in breast cancer correlates with response to anthracyclines and herceptin therapies, respectively, this novel methodology could be useful for a better classification of patients according to the genetic alterations of CTCs and for the application of targeted therapies. (J Histochem Cytochem 56:667–675, 2008) PMID:18413646

Review: fetal programming of polycystic ovary syndrome by androgen excess: evidence from experimental, clinical, and genetic association studies.

Science.gov (United States)

Xita, Nectaria; Tsatsoulis, Agathocles

2006-05-01

Polycystic ovary syndrome (PCOS) is a common endocrine disorder of premenopausal women, characterized by hyperandrogenism, polycystic ovaries, and chronic anovulation along with insulin resistance and abdominal obesity as frequent metabolic traits. Although PCOS manifests clinically during adolescence, emerging data suggest that the natural history of PCOS may originate in intrauterine life. Evidence from experimental, clinical, and genetic research supporting the hypothesis for the fetal origins of PCOS has been analyzed. Female primates, exposed in utero to androgen excess, exhibit the phenotypic features of PCOS during adult life. Clinical observations also support a potential fetal origin of PCOS. Women with fetal androgen excess disorders, including congenital 21-hydroxylase deficiency and congenital adrenal virilizing tumors, develop features characteristic of PCOS during adulthood despite the normalization of androgen excess after birth. The potential mechanisms of fetal androgen excess leading to a PCOS phenotype in humans are not clearly understood. However, maternal and/or fetal hyperandrogenism can provide a plausible mechanism for fetal programing of PCOS, and this, in part, may be genetically determined. Thus, genetic association studies have indicated that common polymorphic variants of genes determining androgen activity or genes that influence the availability of androgens to target tissues are associated with PCOS and increased androgen levels. These genomic variants may provide the genetic link to prenatal androgenization in human PCOS. Prenatal androgenization of the female fetus induced by genetic and environmental factors, or the interaction of both, may program differentiating target tissues toward the development of PCOS phenotype in adult life.

Genetic diversity of sesame (sesamum indicum L.) germplasm from Pakistan using RAPD markers

Energy Technology Data Exchange (ETDEWEB)

Akbar, F; Rabbani, M A; Masood, M S; Shinwari, Z.K., E-mail: shinwari@qau.edu.p

2011-08-15

Genetic diversity among 20 sesame (Sesamum indicum L.) accessions was examined at DNA level by means of random amplified polymorphic DNA (RAPD) analysis. Ten primers used produced a total of 93 RAPD fragments, of which 70 (75%) were polymorphic. Each primer generated 5 to 17 amplified fragments with an average of 9.3 bands per primer. Based on pair-wise comparisons of RAPD amplification products, Nei and Li's similarity coefficients were computed to assess the associations among the accessions. Pair-wise similarity indices varied from 0.65 to 0.91. A UPGMA cluster analysis based on these genetic similarities located most of the accessions far apart from one another, showing a high level of polymorphism. Genetically, all the genotypes were classified into two major groups and six subgroups or clusters. A single accession (22243) was relatively distinct from rest of the accessions and created independent cluster. In conclusion, even with the use of a limited set of primers, RAPD technique revealed a high level of genetic variation among sesame accessions collected from diverse ecologies of Pakistan. This high level of genetic diversity among the genotypes suggested that RAPD technique is valuable for sesame systematic, and can be helpful for the upholding of germplasm banks and the competent choice of parents in breeding programs. (author)

Genetic diversity of sesame (sesamum indicum L.) germplasm from Pakistan using RAPD markers

International Nuclear Information System (INIS)

Akbar, F; Rabbani, M.A.; Masood, M.S.; Shinwari, Z.K.

2011-01-01

Genetic diversity among 20 sesame (Sesamum indicum L.) accessions was examined at DNA level by means of random amplified polymorphic DNA (RAPD) analysis. Ten primers used produced a total of 93 RAPD fragments, of which 70 (75%) were polymorphic. Each primer generated 5 to 17 amplified fragments with an average of 9.3 bands per primer. Based on pair-wise comparisons of RAPD amplification products, Nei and Li's similarity coefficients were computed to assess the associations among the accessions. Pair-wise similarity indices varied from 0.65 to 0.91. A UPGMA cluster analysis based on these genetic similarities located most of the accessions far apart from one another, showing a high level of polymorphism. Genetically, all the genotypes were classified into two major groups and six subgroups or clusters. A single accession (22243) was relatively distinct from rest of the accessions and created independent cluster. In conclusion, even with the use of a limited set of primers, RAPD technique revealed a high level of genetic variation among sesame accessions collected from diverse ecologies of Pakistan. This high level of genetic diversity among the genotypes suggested that RAPD technique is valuable for sesame systematic, and can be helpful for the upholding of germplasm banks and the competent choice of parents in breeding programs. (author)

Tools and techniques used in US Department of Energy decommissioning programs

International Nuclear Information System (INIS)

Miller, R. L.

1988-01-01

Since the decommissioning projects are located at various sites across the United States, a centralized technology transfer program was established to ensure that information on new technologies and techniques developed to support specific tasks is available to all contractors performing similar decommissioning work. This sharing of information avoids duplication of effort and helps to avoid the expenditure of resources on tools or techniques that are not cost effective. This article discusses several of the tools and techniques that have been successfully used for various tasks during the course of decommissioning nuclear facilities. Since decommissioning is labor-intensive work, tools and techniques that reduce either personnel radiation exposure or time required to perform a task are desirable. Other factors that are considered when selecting particular tools or techniques are waste volume reduction, recontamination avoidance, simplicity or operation, and avoiding introduction of large quantities of hazardous/toxic materials that may require special handling and disposal. Finally, the tool, depending on the intended work environment, must be cost effective, easily disposable or easily decontaminated for reuse

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.

Studies of Genetic Differences between KDML 105 and its Photo period-insensitive Mutants using DNA techniques

International Nuclear Information System (INIS)

Boonsirichai, Kanokporn; Klakhaeng, Kanchana; Phadvibulya, Valailak

2007-08-01

Full text: Photo period-insensitive mutants of KDML 105 could be planted for grains during and outside the regular cropping season. From genetic studies, the mutant characteristics appeared recessive. A DNA-fingerprinting technique was used to compare gene expression profiles in the leaves of mutants and KDML 105. Differences in the level of expression were found for several loci. Examination of the essential part of the gene for fragrance showed no differences between the mutants and the parental KDML 105

Genetic Parameters and the Impact of Off-Types for Theobroma cacao L. in a Breeding Program in Brazil

Science.gov (United States)

DuVal, Ashley; Gezan, Salvador A.; Mustiga, Guiliana; Stack, Conrad; Marelli, Jean-Philippe; Chaparro, José; Livingstone, Donald; Royaert, Stefan; Motamayor, Juan C.

2017-01-01

Breeding programs of cacao (Theobroma cacao L.) trees share the many challenges of breeding long-living perennial crops, and genetic progress is further constrained by both the limited understanding of the inheritance of complex traits and the prevalence of technical issues, such as mislabeled individuals (off-types). To better understand the genetic architecture of cacao, in this study, 13 years of phenotypic data collected from four progeny trials in Bahia, Brazil were analyzed jointly in a multisite analysis. Three separate analyses (multisite, single site with and without off-types) were performed to estimate genetic parameters from statistical models fitted on nine important agronomic traits (yield, seed index, pod index, % healthy pods, % pods infected with witches broom, % of pods other loss, vegetative brooms, diameter, and tree height). Genetic parameters were estimated along with variance components and heritabilities from the multisite analysis, and a trial was fingerprinted with low-density SNP markers to determine the impact of off-types on estimations. Heritabilities ranged from 0.37 to 0.64 for yield and its components and from 0.03 to 0.16 for disease resistance traits. A weighted index was used to make selections for clonal evaluation, and breeding values estimated for the parental selection and estimation of genetic gain. The impact of off-types to breeding progress in cacao was assessed for the first time. Even when present at <5% of the total population, off-types altered selections by 48%, and impacted heritability estimations for all nine of the traits analyzed, including a 41% difference in estimated heritability for yield. These results show that in a mixed model analysis, even a low level of pedigree error can significantly alter estimations of genetic parameters and selections in a breeding program. PMID:29250097

Reactor Network Synthesis Using Coupled Genetic Algorithm with the Quasi-linear Programming Method

OpenAIRE

Soltani, H.; Shafiei, S.; Edraki, J.

2016-01-01

This research is an attempt to develop a new procedure for the synthesis of reactor networks (RNs) using a genetic algorithm (GA) coupled with the quasi-linear programming (LP) method. The GA is used to produce structural configuration, whereas continuous variables are handled using a quasi-LP formulation for finding the best objective function. Quasi-LP consists of LP together with a search loop to find the best reactor conversions (xi), as well as split and recycle ratios (yi). Quasi-LP rep...

Admission Control Techniques for UMTS System

Directory of Open Access Journals (Sweden)

P. Kejik

2010-09-01

Full Text Available Universal mobile telecommunications system (UMTS is one of the 3rd generation (3G cell phone technologies. The capacity of UMTS is interference limited. Radio resources management (RRM functions are therefore used. They are responsible for supplying optimum coverage, ensuring efficient use of physical resources, and providing the maximum planned capacity. This paper deals with admission control techniques for UMTS. An own UMTS simulation program and several versions of proposed admission control algorithms are presented in this paper. These algorithms are based on fuzzy logic and genetic algorithms. The performance of algorithms is verified via simulations.

Recognizing and Managing Complexity: Teaching Advanced Programming Concepts and Techniques Using the Zebra Puzzle

Directory of Open Access Journals (Sweden)

Xihui "Paul" Zhang

2015-06-01

Full Text Available Teaching advanced programming can be a challenge, especially when the students are pursuing different majors with diverse analytical and problem-solving capabilities. The purpose of this paper is to explore the efficacy of using a particular problem as a vehicle for imparting a broad set of programming concepts and problem-solving techniques. We present a classic brain teaser that is used to communicate and demonstrate advanced software development concepts and techniques. Our results show that students with varied academic experiences and goals, assuming at least one procedural/structured programming pre-requisite, can benefit from and also be challenged by such an exercise. Although this problem has been used by others in the classroom, we believe that our use of this problem in imparting such a broad range of topics to a diverse student population is unique.

Application of genetic algorithm (GA) technique on demand estimation of fossil fuels in Turkey

International Nuclear Information System (INIS)

Canyurt, Olcay Ersel; Ozturk, Harun Kemal

2008-01-01

The main objective is to investigate Turkey's fossil fuels demand, projection and supplies by using the structure of the Turkish industry and economic conditions. This study develops scenarios to analyze fossil fuels consumption and makes future projections based on a genetic algorithm (GA). The models developed in the nonlinear form are applied to the coal, oil and natural gas demand of Turkey. Genetic algorithm demand estimation models (GA-DEM) are developed to estimate the future coal, oil and natural gas demand values based on population, gross national product, import and export figures. It may be concluded that the proposed models can be used as alternative solutions and estimation techniques for the future fossil fuel utilization values of any country. In the study, coal, oil and natural gas consumption of Turkey are projected. Turkish fossil fuel demand is increased dramatically. Especially, coal, oil and natural gas consumption values are estimated to increase almost 2.82, 1.73 and 4.83 times between 2000 and 2020. In the figures GA-DEM results are compared with World Energy Council Turkish National Committee (WECTNC) projections. The observed results indicate that WECTNC overestimates the fossil fuel consumptions. (author)

Recognizing and Managing Complexity: Teaching Advanced Programming Concepts and Techniques Using the Zebra Puzzle

Science.gov (United States)

Crabtree, John; Zhang, Xihui

2015-01-01

Teaching advanced programming can be a challenge, especially when the students are pursuing different majors with diverse analytical and problem-solving capabilities. The purpose of this paper is to explore the efficacy of using a particular problem as a vehicle for imparting a broad set of programming concepts and problem-solving techniques. We…

Genetic screening: programs, principles, and research--thirty years later. Reviewing the recommendations of the Committee for the Study of Inborn Errors of Metabolism (SIEM).

Science.gov (United States)

Simopoulos, A P

2009-01-01

Screening programs for genetic diseases and characteristics have multiplied in the last 50 years. 'Genetic Screening: Programs, Principles, and Research' is the report of the Committee for the Study of Inborn Errors of Metabolism (SIEM Committee) commissioned by the Division of Medical Sciences of the National Research Council at the National Academy of Sciences in Washington, DC, published in 1975. The report is considered a classic in the field worldwide, therefore it was thought appropriate 30 years later to present the Committee's modus operandi and bring the Committee's recommendations to the attention of those involved in genetics, including organizational, educational, legal, and research aspects of genetic screening. The Committee's report anticipated many of the legal, ethical, economic, social, medical, and policy aspects of genetic screening. The recommendations are current, and future committees should be familiar with them. In 1975 the Committee stated: 'As new screening tests are devised, they should be carefully reviewed. If the experimental rate of discovery of new genetic characteristics means an accelerating rate of appearance of new screening tests, now is the time to develop the medical and social apparatus to accommodate what later on may otherwise turn out to be unmanageable growth.' What a prophetic statement that was. If the Committee's recommendations had been implemented on time, there would be today a federal agency in existence, responsive and responsible to carry out the programs and support research on various aspects of genetic screening, including implementation of a federal law that protects consumers from discrimination by their employers and the insurance industry on the basis of genetic information. Copyright 2008 S. Karger AG, Basel.

Direct evaluation of fault trees using object-oriented programming techniques

Science.gov (United States)

Patterson-Hine, F. A.; Koen, B. V.

1989-01-01

Object-oriented programming techniques are used in an algorithm for the direct evaluation of fault trees. The algorithm combines a simple bottom-up procedure for trees without repeated events with a top-down recursive procedure for trees with repeated events. The object-oriented approach results in a dynamic modularization of the tree at each step in the reduction process. The algorithm reduces the number of recursive calls required to solve trees with repeated events and calculates intermediate results as well as the solution of the top event. The intermediate results can be reused if part of the tree is modified. An example is presented in which the results of the algorithm implemented with conventional techniques are compared to those of the object-oriented approach.

Effects of genetic distance on heterosis in a Drosophila melanogaster model system

DEFF Research Database (Denmark)

Jensen, Charlotte; Ørsted, Michael; Kristensen, Torsten Nygaard

2018-01-01

Habitat fragmentation and small population sizes can lead to inbreeding and loss of genetic variation, which can potentially cause inbreeding depression and decrease the ability of populations to adapt to altered environmental conditions. One solution to these genetic problems is the implementation...... of genetic rescue, which re-establishes gene flow between separated populations. Similar techniques are being used in animal and plant breeding to produce superior production animals and plants. To optimize fitness benefits in genetic rescue programs and to secure high yielding domestic varieties in animal...... exceptions to this pattern. The best predictor of heterosis was performance of parental lines with poorly performing parental lines showing higher hybrid vigour when crossed, i.e. the potential for heterosis was proportional to the level of inbreeding depression. Overall, our results show that outcrossing...

Performance comparison of genetic algorithms and particle swarm optimization for model integer programming bus timetabling problem

Science.gov (United States)

Wihartiko, F. D.; Wijayanti, H.; Virgantari, F.

2018-03-01

Genetic Algorithm (GA) is a common algorithm used to solve optimization problems with artificial intelligence approach. Similarly, the Particle Swarm Optimization (PSO) algorithm. Both algorithms have different advantages and disadvantages when applied to the case of optimization of the Model Integer Programming for Bus Timetabling Problem (MIPBTP), where in the case of MIPBTP will be found the optimal number of trips confronted with various constraints. The comparison results show that the PSO algorithm is superior in terms of complexity, accuracy, iteration and program simplicity in finding the optimal solution.

Structured behavioral observation techniques as components of an effective fitness-for-duty program

International Nuclear Information System (INIS)

Hauth, J.T.; Barnes, V.E.; Moore, C.J.; Toquam, J.L.

1989-01-01

Performance-based tests are designed to evaluate physical and cognitive performance and have several attractive features that may be useful in nuclear power plant fitness-for-duty programs. Three types of performance-based testing that may eventually be useful in the nuclear power industry are reviewed in this paper: (a) the Los Angeles Police Department's Drug Recognition Expert program, (b) performance assessment batteries, and (c) performance assessment devices. Each of these techniques is evaluated here in terms of the following measures of effectiveness: (1) scope, or the range of potential problems that can be detected; (2) reliability, or the consistency of results; (3) sensitivity, or the ability of the test to detect impairment or the presence of drugs at low levels; (4) specificity, or the ability of the test to correctly identify the source of impairment or the drug present; (5) implementation, or the practicality of using the technique in the nuclear power plant setting. This information analyzed in this paper indicates that although performance and cognitive assessment techniques currently lack the reliability, sensitivity, and specificity of random chemical screening to detect and deter substance abuse, they can address a variety of fitness-for-duty concerns that may not be adequately addressed by a urinalysis testing program alone. These include detection of drug use not detected by urinalysis, psychological stress, or physical injury or illness

Human Genome Program

Energy Technology Data Exchange (ETDEWEB)

1993-01-01

The DOE Human Genome program has grown tremendously, as shown by the marked increase in the number of genome-funded projects since the last workshop held in 1991. The abstracts in this book describe the genome research of DOE-funded grantees and contractors and invited guests, and all projects are represented at the workshop by posters. The 3-day meeting includes plenary sessions on ethical, legal, and social issues pertaining to the availability of genetic data; sequencing techniques, informatics support; and chromosome and cDNA mapping and sequencing.

Genetic analysis of seasonal runoff based on automatic techniques of hydrometeorological data processing

Science.gov (United States)

Kireeva, Maria; Sazonov, Alexey; Rets, Ekaterina; Ezerova, Natalia; Frolova, Natalia; Samsonov, Timofey

2017-04-01

Detection of the rivers' feeding type is a complex and multifactor task. Such partitioning should be based, on the one hand, on the genesis of the feeding water, on the other hand, on its physical path. At the same time it should consider relationship of the feeding type with corresponding phase of the water regime. Due to the above difficulties and complexity of the approach, there are many different variants of separation of flow hydrograph for feeding types. The most common method is extraction of so called basic component which in one way or another reflects groundwater feeding of the river. In this case, the selection most often is based on the principle of local minima or graphic separation of this component. However, in this case neither origin of the water nor corresponding phase of water regime is considered. In this paper, the authors offer a method of complex automated analysis of genetic components of the river's feeding together with the separation of specific phases of the water regime. The objects of the study are medium and large rivers of European Russia having a pronounced spring flood, formed due to melt water, and summer-autumn and winter low water which is periodically interrupted by rain or thaw flooding. The method is based on genetic separation of hydrograph proposed in 1960s years by B. I. Kudelin. This technique is considered for large rivers having hydraulic connection with groundwater horizons during flood. For better detection of floods genesis the analysis involves reanalysis data on temperature and precipitation. Separation is based on the following fundamental graphic-analytical principles: • Ground feeding during the passage of flood peak tends to zero • Beginning of the flood is determined as the exceeding of critical value of low water discharge • Flood periods are determined on the basis of exceeding the critical low-water discharge; they relate to thaw in case of above-zero temperatures • During thaw and rain floods

A study on maintenance reliability allocation of urban transit brake system using hybrid neuro-genetic technique

International Nuclear Information System (INIS)

Bae, Chul Ho; Kim, Hyun Jun; Lee, Jung Hwan; Suh, Myung Won; Chu, Yul

2007-01-01

For reasonable establishing of maintenance strategies, safety security and cost limitation must be considered at the same time. In this paper, the concept of system reliability introduces and optimizes as the key of reasonable maintenance strategies. This study aims at optimizing component's reliability that satisfies the target reliability of brake system in the urban transit. First of all, constructed reliability evaluation system is used to predict and analyze reliability. This data is used for the optimization. To identify component reliability in a system, a method is presented in this paper which uses hybrid neuro-genetic technique. Feed-forward multi-layer neural networks trained by back propagation are used to find out the relationship between component reliability (input) and system reliability (output) of a structural system. The inverse problem can be formulated by using neural network. Genetic algorithm is used to find the minimum square error. Finally, this paper presents reasonable maintenance cycle of urban transit brake system by using optimal system reliability

Genetic programming for evolving due-date assignment models in job shop environments.

Science.gov (United States)

Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

2014-01-01

Due-date assignment plays an important role in scheduling systems and strongly influences the delivery performance of job shops. Because of the stochastic and dynamic nature of job shops, the development of general due-date assignment models (DDAMs) is complicated. In this study, two genetic programming (GP) methods are proposed to evolve DDAMs for job shop environments. The experimental results show that the evolved DDAMs can make more accurate estimates than other existing dynamic DDAMs with promising reusability. In addition, the evolved operation-based DDAMs show better performance than the evolved DDAMs employing aggregate information of jobs and machines.

Within a smoking-cessation program, what impact does genetic information on lung cancer need to have to demonstrate cost-effectiveness?

Directory of Open Access Journals (Sweden)

Gordon Louisa G

2010-09-01

Full Text Available Abstract Background Many smoking-cessation programs and pharmaceutical aids demonstrate substantial health gains for a relatively low allocation of resources. Genetic information represents a type of individualized or personal feedback regarding the risk of developing lung cancer, and hence the potential benefits from stopping smoking, may motivate the person to remain smoke-free. The purpose of this study was to explore what the impact of a genetic test needs to have within a typical smoking-cessation program aimed at heavy smokers in order to be cost-effective. Methods Two strategies were modelled for a hypothetical cohort of heavy smokers aged 50 years; individuals either received or did not receive a genetic test within the course of a usual smoking-cessation intervention comprising nicotine replacement therapy (NRT and counselling. A Markov model was constructed using evidence from published randomized controlled trials and meta-analyses for estimates on 12-month quit rates and long-term relapse rates. Epidemiological data were used for estimates on lung cancer risk stratified by time since quitting and smoking patterns. Extensive sensitivity analyses were used to explore parameter uncertainty. Results The discounted incremental cost per QALY was AU$34,687 (95% CI $12,483, $87,734 over 35 years. At a willingness-to-pay of AU$20,000 per QALY gained, the genetic testing strategy needs to produce a 12-month quit rate of at least 12.4% or a relapse rate 12% lower than NRT and counselling alone for it to be equally cost-effective. The likelihood that adding a genetic test to the usual smoking-cessation intervention is cost-effective was 20.6% however cost-effectiveness ratios were favourable in certain situations (e.g., applied to men only, a 60 year old cohort. Conclusions The findings were sensitive to small changes in critical variables such as the 12-month quit rates and relapse rates. As such, the cost-effectiveness of the genetic testing

Assembling networks of microbial genomes using linear programming.

Science.gov (United States)

Holloway, Catherine; Beiko, Robert G

2010-11-20

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

Water Curtain System Pre-design for Crude Oil Storage URCs : A Numerical Modeling and Genetic Programming Approach

NARCIS (Netherlands)

Ghotbi Ravandi, Ebrahim; Rahmannejad, Reza; Karimi-Nasab, Saeed; Sarrafi, Amir; Raoof, Amir

In this paper the main criteria of the water curtain system for unlined rock caverns (URCs) is described. By the application of numerical modeling and genetic programming (GP), a method for water curtain system pre-design for Iranian crude oil storage URCs (common dimension worldwide) is presented.

Korean round-robin result for new international program to assess the reliability of emerging nondestructive techniques

Energy Technology Data Exchange (ETDEWEB)

Kim, Kyung Cho; Kim, Jin Gyum; Kang, Sung Sik; Jhung, Myung Jo [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

2017-04-15

The Korea Institute of Nuclear Safety, as a representative organization of Korea, in February 2012 participated in an international Program to Assess the Reliability of Emerging Nondestructive Techniques initiated by the U.S. Nuclear Regulatory Commission. The goal of the Program to Assess the Reliability of Emerging Nondestructive Techniques is to investigate the performance of emerging and prospective novel nondestructive techniques to find flaws in nickel-alloy welds and base materials. In this article, Korean round-robin test results were evaluated with respect to the test blocks and various nondestructive examination techniques. The test blocks were prepared to simulate large-bore dissimilar metal welds, small-bore dissimilar metal welds, and bottom-mounted instrumentation penetration welds in nuclear power plants. Also, lessons learned from the Korean round-robin test were summarized and discussed.

Disability training in the genetic counseling curricula: bridging the gap between genetic counselors and the disability community.

Science.gov (United States)

Sanborn, Erica; Patterson, Annette R

2014-08-01

Over the past two decades, disability activists, ethicists, and genetic counselors have examined the moral complexities inherent in prenatal genetic counseling and considered whether and in what ways genetic counseling may negatively affect individuals in the disability community. Many have expressed concerns about defining disability in the context of prenatal decision-making, as the definition presented may influence prenatal choices. In the past few years, publications have begun to explore the responsibility of counselors in presenting a balanced view of disability and have questioned the preparedness of counselors for this duty. Currently, the Accreditation Council for Genetic Counseling (ACGC) only minimally includes disability training in their competencies for genetic counselors, and in their accreditation requirements for training programs. In an attempt to describe current practice, this article details two studies that assess disability training in ABGC-accredited genetic counseling programs. Results from these studies demonstrate that experience with disability is not required by the majority of programs prior to matriculation. Though most program directors agree on the importance of including disability training in the curriculum, there is wide variability in the amount and types of training students receive. Hours dedicated to disability exposure among programs ranged from 10 to 600 hours. Eighty-five percent of program directors surveyed agree that skills for addressing disability should be added to the core competencies. Establishing a set of disability competencies would help to ensure that all graduates have the skills necessary to provide patients with an accurate understanding of disability that facilitates informed decision-making. © 2014 Wiley Periodicals, Inc.

Evaluating a hybrid web-based basic genetics course for health professionals.

Science.gov (United States)

Wallen, Gwenyth R; Cusack, Georgie; Parada, Suzan; Miller-Davis, Claiborne; Cartledge, Tannia; Yates, Jan

2011-08-01

Health professionals, particularly nurses, continue to struggle with the expanding role of genetics information in the care of their patients. This paper describes an evaluation study of the effectiveness of a hybrid basic genetics course for healthcare professionals combining web-based learning with traditional face-to-face instructional techniques. A multidisciplinary group from the National Institutes of Health (NIH) created "Basic Genetics Education for Healthcare Providers" (BGEHCP). This program combined 7 web-based self-education modules with monthly traditional face-to-face lectures by genetics experts. The course was pilot tested by 186 healthcare providers from various disciplines with 69% (n=129) of the class registrants enrolling in a pre-post evaluation trial. Outcome measures included critical thinking knowledge items and a Web-based Learning Environment Inventory (WEBLEI). Results indicated a significant (peffectiveness particularly in the area of convenience, access and the course structure and design. Although significant increases in overall knowledge scores were achieved, scores in content areas surrounding genetic risk identification and ethical issues regarding genetic testing reflected continued gaps in knowledge. Web-based genetics education may help overcome genetics knowledge deficits by providing access for health professionals with diverse schedules in a variety of national and international settings. Published by Elsevier Ltd.

Fast implementations of 3D PET reconstruction using vector and parallel programming techniques

International Nuclear Information System (INIS)

Guerrero, T.M.; Cherry, S.R.; Dahlbom, M.; Ricci, A.R.; Hoffman, E.J.

1993-01-01

Computationally intensive techniques that offer potential clinical use have arisen in nuclear medicine. Examples include iterative reconstruction, 3D PET data acquisition and reconstruction, and 3D image volume manipulation including image registration. One obstacle in achieving clinical acceptance of these techniques is the computational time required. This study focuses on methods to reduce the computation time for 3D PET reconstruction through the use of fast computer hardware, vector and parallel programming techniques, and algorithm optimization. The strengths and weaknesses of i860 microprocessor based workstation accelerator boards are investigated in implementations of 3D PET reconstruction

Genetic assessment of captive red panda (Ailurus fulgens) population.

Science.gov (United States)

Kumar, Arun; Rai, Upashna; Roka, Bhupen; Jha, Alankar K; Reddy, P Anuradha

2016-01-01

Red panda (Ailurus fulgens) is threatened across its range by detrimental human activities and rapid habitat changes necessitating captive breeding programs in various zoos globally to save this flagship species from extinction. One of the ultimate aims of ex situ conservation is reintroduction of endangered animals into their natural habitats while maintaining 90 % of the founder genetic diversity. Advances in molecular genetics and microsatellite genotyping techniques make it possible to accurately estimate genetic diversity of captive animals of unknown ancestry. Here we assess genetic diversity of the red panda population in Padmaja Naidu Himalayan Zoological Park, Darjeeling, which plays a pivotal role in ex situ conservation of red panda in India. We generated microsatellite genotypes of fifteen red pandas with a set of fourteen loci. This population is genetically diverse with 68 % observed heterozygosity (H O ) and mean inbreeding (F IS ) coefficient of 0.05. However population viability analysis reveals that this population has a very low survival probability (<2 %) and will rapidly loose its genetic diversity to 37 % mainly due to small population size and skewed male-biased sex ratio. Regular supplementation with a pair of adult individuals every five years will increase survival probability and genetic diversity to 99 and 61 % respectively and will also support future harvesting of individuals for reintroduction into the wild and exchange with other zoos.

A high-resolution neutron spectra unfolding method using the Genetic Algorithm technique

CERN Document Server

Mukherjee, B

2002-01-01

The Bonner sphere spectrometers (BSS) are commonly used to determine the neutron spectra within various nuclear facilities. Sophisticated mathematical tools are used to unfold the neutron energy distribution from the output data of the BSS. This paper highlights a novel high-resolution neutron spectra-unfolding method using the Genetic Algorithm (GA) technique. The GA imitates the biological evolution process prevailing in the nature to solve complex optimisation problems. The GA method was utilised to evaluate the neutron energy distribution, average energy, fluence and equivalent dose rates at important work places of a DIDO class research reactor and a high-energy superconducting heavy ion cyclotron. The spectrometer was calibrated with a sup 2 sup 4 sup 1 Am/Be (alpha,n) neutron standard source. The results of the GA method agreed satisfactorily with the results obtained by using the well-known BUNKI neutron spectra unfolding code.

Genetic conservation and paddlefish propagation

Science.gov (United States)

Sloss, Brian L.; Klumb, Robert A.; Heist, Edward J.

2009-01-01

The conservation of genetic diversity of our natural resources is overwhelmingly one of the central foci of 21st century management practices. Three recommendations related to the conservation of paddlefish Polyodon spathula genetic diversity are to (1) identify genetic diversity at both nuclear and mitochondrial DNA loci using a suggested list of 20 sampling locations, (2) use genetic diversity estimates to develop genetic management units, and (3) identify broodstock sources to minimize effects of supplemental stocking on the genetic integrity of native paddlefish populations. We review previous genetic work on paddlefish and described key principles and concepts associated with maintaining genetic diversity within and among paddlefish populations and also present a genetic case study of current paddlefish propagation at the U.S. Fish and Wildlife Service Gavins Point National Fish Hatchery. This study confirmed that three potential sources of broodfish were genetically indistinguishable at the loci examined, allowing the management agencies cooperating on this program flexibility in sampling gametes. This study also showed significant bias in the hatchery occurred in terms of male reproductive contribution, which resulted in a shift in the genetic diversity of progeny compared to the broodfish. This shift was shown to result from differential male contributions, partially attributed to the mode of egg fertilization. Genetic insights enable implementation of a paddlefish propagation program within an adaptive management strategy that conserves inherent genetic diversity while achieving demographic goals.

Genetic manipulation of Francisella tularensis

Directory of Open Access Journals (Sweden)

Xhavit eZogaj

2011-01-01

Full Text Available Francisella tularensis is a facultative intracellular pathogen that causes the disease tularemia. F. tularensis subsp. tularensis causes the most severe disease in humans and has been classified as a select A agent and potential bioweapon. There is currently no vaccine approved for human use, making genetic manipulation of this organism critical to unraveling the genetic basis of pathogenesis and developing countermeasures against tularemia. The development of genetic techniques applicable to F. tularensis have lagged behind those routinely used for other bacteria, primarily due to lack of research and the restricted nature of the biocontainment required for studying this pathogen. However, in recent years, genetic techniques, such as transposon mutagenesis and targeted gene disruption, have been developed, that have had a dramatic impact on our understanding of the genetic basis of F. tularensis virulence. In this review, we describe some of the methods developed for genetic manipulation of F. tularensis.

Intelligent Testing of Traffic Light Programs: Validation in Smart Mobility Scenarios

OpenAIRE

Javier Ferrer; José García-Nieto; Enrique Alba; Francisco Chicano

2016-01-01

In smart cities, the use of intelligent automatic techniques to find efficient cycle programs of traffic lights is becoming an innovative front for traffic flow management. However, this automatic programming of traffic lights requires a validation process of the generated solutions, since they can affect the mobility (and security) of millions of citizens. In this paper, we propose a validation strategy based on genetic algorithms and feature models for the automatic generation of different ...

Comparison of acrylamide intake from Western and guideline based diets using probabilistic techniques and linear programming.

Science.gov (United States)

Katz, Josh M; Winter, Carl K; Buttrey, Samuel E; Fadel, James G

2012-03-01

Western and guideline based diets were compared to determine if dietary improvements resulting from following dietary guidelines reduce acrylamide intake. Acrylamide forms in heat treated foods and is a human neurotoxin and animal carcinogen. Acrylamide intake from the Western diet was estimated with probabilistic techniques using teenage (13-19 years) National Health and Nutrition Examination Survey (NHANES) food consumption estimates combined with FDA data on the levels of acrylamide in a large number of foods. Guideline based diets were derived from NHANES data using linear programming techniques to comport to recommendations from the Dietary Guidelines for Americans, 2005. Whereas the guideline based diets were more properly balanced and rich in consumption of fruits, vegetables, and other dietary components than the Western diets, acrylamide intake (mean±SE) was significantly greater (Plinear programming and results demonstrate that linear programming techniques can be used to model specific diets for the assessment of toxicological and nutritional dietary components. Copyright © 2011 Elsevier Ltd. All rights reserved.

Evaluation of genetically altered medflies for use in sterile insect technique programmes. Proceedings of the final research co-ordination meeting

International Nuclear Information System (INIS)

1997-01-01

Although the medfly is a key pest in many areas of the world, there are important fruit growing areas where other fruit flies are key pests. It was concluded that it would be of value for any future CRP on genetic sexing to include these species. For the development of genetic sexing systems in these species much can be gained from the experiences with the medfly. However, at present, a similar procedure will have to be followed which will entail the construction of genetic maps, the development of cytological techniques and the induction of male linked translocation. In future, the availability of molecular methods could enable sexing systems to be transferred between species. The proceedings contain 11 papers, which range from an initial molecular analysis of the genome of the fly to a field experiment to assess the impact of an all-male release

Experimental program for development and evaluation of nondestructive assay techniques for plutonium holdup

International Nuclear Information System (INIS)

Brumbach, S.B.

1977-05-01

An outline is presented for an experimental program to develop and evaluate nondestructive assay techniques applicable to holdup measurement in plutonium-containing fuel fabrication facilities. The current state-of-the-art in holdup measurements is reviewed. Various aspects of the fuel fabrication process and the fabrication facility are considered for their potential impact on holdup measurements. The measurement techniques considered are those using gamma-ray counting, neutron counting, and temperature measurement. The advantages and disadvantages of each technique are discussed. Potential difficulties in applying the techniques to holdup measurement are identified. Experiments are proposed to determine the effects of such problems as variation in sample thickness, in sample distribution, and in background radiation. These experiments are also directed toward identification of techniques most appropriate to various applications. Also proposed are experiments to quantify the uncertainties expected for each measurement

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.

Airway Clearance Techniques (ACTs)

Medline Plus

Full Text Available ... closer to a cure. Basics of the CFTR Protein Role of Genetics in CF CF Genetics The ... CF Foundation Biorepository CFTR Chemical Compound Program CFTR Protein Domains Patient Registry Data Requests Get Involved X ...

Airway Clearance Techniques (ACTs)

Medline Plus

Full Text Available ... closer to a cure. Basics of the CFTR Protein Role of Genetics in CF CF Genetics The ... Assays CFFT Biorepository CFTR Chemical Compound Program CFTR Protein Domains Patient Registry Data Requests Get Involved X ...

Genetic sexing strains in Mediterranean fruit fly, an example for other species amenable to large-scale rearing for the sterile insect technique

International Nuclear Information System (INIS)

Franz, G.

2005-01-01

Through genetic and molecular manipulations, strains can be developed that are more suitable for the sterile insect technique (SIT). In this chapter the development of genetic sexing strains (GSSs) is given as an example. GSSs increase the effectiveness of area-wide integrated pest management (AW-IPM) programmes that use the SIT by enabling the large-scale release of only sterile males. For species that transmit disease, the removal of females is mandatory. For the Mediterranean fruit fly Ceratitis capitata (Wiedemann), genetic sexing systems have been developed; they are stable enough to be used in operational programmes for extended periods of time. Until recently, the only way to generate such strains was through Mendelian genetics. In this chapter, the basic principle of translocation-based sexing strains is described, and Mediterranean fruit fly strains are used as examples to indicate the problems encountered in such strains. Furthermore, the strategies used to solve these problems are described. The advantages of following molecular strategies in the future development of sexing strains are outlined, especially for species where little basic knowledge of genetics exists. (author)

Affirmative Action. Module Number 16. Work Experience Program Modules. Coordination Techniques Series.

Science.gov (United States)

Shawhan, Carl; Morley, Ray

This self-instructional module, the last in a series of 16 on techniques for coordinating work experience programs, deals with affirmative action. Addressed in the module are the following topics: the nature of affirmative action legislation and regulations, the role of the teacher-coordinator as a resource person for affirmative action…

The use of genetic engineering techniques to improve the lipid composition in meat, milk and fish products: a review.

Science.gov (United States)

Świątkiewicz, S; Świątkiewicz, M; Arczewska-Włosek, A; Józefiak, D

2015-04-01

The health-promoting properties of dietary long-chain n-3 polyunsaturated fatty acids (n-3 LCPUFAs) for humans are well-known. Products of animal-origin enriched with n-3 LCPUFAs can be a good example of functional food, that is food that besides traditionally understood nutritional value may have a beneficial influence on the metabolism and health of consumers, thus reducing the risk of various lifestyle diseases such as atherosclerosis and coronary artery disease. The traditional method of enriching meat, milk or eggs with n-3 LCPUFA is the manipulation of the composition of animal diets. Huge progress in the development of genetic engineering techniques, for example transgenesis, has enabled the generation of many kinds of genetically modified animals. In recent years, one of the aims of animal transgenesis has been the modification of the lipid composition of meat and milk in order to improve the dietetic value of animal-origin products. This article reviews and discusses the data in the literature concerning studies where techniques of genetic engineering were used to create animal-origin products modified to contain health-promoting lipids. These studies are still at the laboratory stage, but their results have demonstrated that the transgenesis of pigs, cows, goats and fishes can be used in the future as efficient methods of production of healthy animal-origin food of high dietetic value. However, due to high costs and a low level of public acceptance, the introduction of this technology to commercial animal production and markets seems to be a distant prospect.

A Parallel Genetic Algorithm for Automated Electronic Circuit Design

Science.gov (United States)

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

2000-01-01

Parallelized versions of genetic algorithms (GAs) are popular primarily for three reasons: the GA is an inherently parallel algorithm, typical GA applications are very compute intensive, and powerful computing platforms, especially Beowulf-style computing clusters, are becoming more affordable and easier to implement. In addition, the low communication bandwidth required allows the use of inexpensive networking hardware such as standard office ethernet. In this paper we describe a parallel GA and its use in automated high-level circuit design. Genetic algorithms are a type of trial-and-error search technique that are guided by principles of Darwinian evolution. Just as the genetic material of two living organisms can intermix to produce offspring that are better adapted to their environment, GAs expose genetic material, frequently strings of 1s and Os, to the forces of artificial evolution: selection, mutation, recombination, etc. GAs start with a pool of randomly-generated candidate solutions which are then tested and scored with respect to their utility. Solutions are then bred by probabilistically selecting high quality parents and recombining their genetic representations to produce offspring solutions. Offspring are typically subjected to a small amount of random mutation. After a pool of offspring is produced, this process iterates until a satisfactory solution is found or an iteration limit is reached. Genetic algorithms have been applied to a wide variety of problems in many fields, including chemistry, biology, and many engineering disciplines. There are many styles of parallelism used in implementing parallel GAs. One such method is called the master-slave or processor farm approach. In this technique, slave nodes are used solely to compute fitness evaluations (the most time consuming part). The master processor collects fitness scores from the nodes and performs the genetic operators (selection, reproduction, variation, etc.). Because of dependency

Genetic diversity of six populations of red hybrid tilapia, using microsatellites genetic markers

Directory of Open Access Journals (Sweden)

Boris Briñez R.

2011-05-01

Full Text Available Objective. To determine and evaluate the genetic diversity of six populations of red hybrid tilapia, with the purpose to assess the potential benefit of a future breeding program conducted at the Research Center for Aquaculture (Ceniacua, Colombia. Material and methods. A total of 300 individuals, representing a wide genetic variability, were genotyped using a fluorescent microsatellite marker set of 5 gene-based SSRs in 6 different farms belonging to 4 States of Colombia. Results. The result showed that the mean number of alleles per locus per population was 8.367. The population 5 had the highest mean number of alleles with 9.6 alleles, followed by population 4 with 9.4 alleles, population 2 with 9.2, population 3 with 8.0, population 1 with 7.2 and population 6 with 6.8 alleles. The analysis of the distribution of genetic variation was (17.32% among population, while among individuals within populations was (28.55% and within individuals was high (54.12%. The standard diversity indices showed that population 4 was the more variable (mean He=0.837 followed by population 1 (mean He=0.728, population 3 (mean He=0.721, population 5 (mean He=0.705, population 2 (mean He=0.690, population 6 (mean He=0.586. Highly significant deviations from Hardy–Weinberg, exhibited all of the populations, mostly due to deficits of heterozygotes. Genotype frequencies at loci UNH 106 of population 5 and loci UNH 172 of population 6 were Hardy-Weinberg equilibrium (HWE. Conclusions. The results of this study, contribute to the genetic breeding program of Tilapia, conduced by the Research Center for Aquaculture. The Fst distance showed that the samples are differentiated genetically and it is possible to use at the beginning of the genetic program. However, it is recommended to introduce others individuals to the crossbreeding program.

Genetics in Relation to Biology.

Science.gov (United States)

Stewart, J. Bird

1987-01-01

Claims that most instruction dealing with genetics is limited to sex education and personal hygiene. Suggests that the biology curriculum should begin to deal with other issues related to genetics, including genetic normality, prenatal diagnoses, race, and intelligence. Predicts these topics will begin to appear in British examination programs.…

Preimplantation diagnosis of genetic diseases

Directory of Open Access Journals (Sweden)

Adiga S

2010-01-01

Full Text Available One of the landmarks in clinical genetics is prenatal diagnosis of genetic disorders. The recent advances in the field have made it possible to diagnose the genetic conditions in the embryos before implantation in a setting of in vitro fertilization. Polymerase chain reaction and fluorescence in situ hybridization are the two common techniques employed on a single or two cells obtained via embryo biopsy. The couple who seek in vitro fertilization may screen their embryos for aneuploidy and the couple at risk for a monogenic disorder but averse to abortion of the affected fetuses after prenatal diagnosis, are likely to be the best candidates to undergo this procedure. This article reviews the technique, indications, benefits, and limitations of pre-implantation genetic testing in clinical practice.

Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

Energy Technology Data Exchange (ETDEWEB)

Wichapa, Narong; Khokhajaikiat, Porntep

2017-07-01

Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

International Nuclear Information System (INIS)

Wichapa, Narong; Khokhajaikiat, Porntep

2017-01-01

Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

The use of automatic programming techniques for fault tolerant computing systems

Science.gov (United States)

Wild, C.

1985-01-01

It is conjectured that the production of software for ultra-reliable computing systems such as required by Space Station, aircraft, nuclear power plants and the like will require a high degree of automation as well as fault tolerance. In this paper, the relationship between automatic programming techniques and fault tolerant computing systems is explored. Initial efforts in the automatic synthesis of code from assertions to be used for error detection as well as the automatic generation of assertions and test cases from abstract data type specifications is outlined. Speculation on the ability to generate truly diverse designs capable of recovery from errors by exploring alternate paths in the program synthesis tree is discussed. Some initial thoughts on the use of knowledge based systems for the global detection of abnormal behavior using expectations and the goal-directed reconfiguration of resources to meet critical mission objectives are given. One of the sources of information for these systems would be the knowledge captured during the automatic programming process.

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.

Genetic stability evaluation of quercus suber l. somatic embryogenesis by rapd analysis

International Nuclear Information System (INIS)

Fernandes, P.; Costa, A.; Rocha, A.C.C.; Santos, C.

2011-01-01

A reliable protocol for adult Quercus suber L. somatic embryogenesis (SE) was developed recently. To evaluate the potential use of this protocol in cork oak forest breeding programs, it is essential to guarantee somatic embryos/emblings genetic stability. Random Amplification of Polymorphic DNA (RAPD) is currently used to assess somaclonal variation providing information on genetic variability of the micropropagation process. In this work, SE was induced from adult trees by growing leaf explants on MS medium supplemented with 2,4-D and zeatin. Embling conversion took place on MS medium without growth regulators. DNA from donor tree, somatic embryos and emblings was used to assess genetic variability by RAPD fingerprinting. Fourteen primers produced 165 genetic loci with high quality and reproducibility. Despite somatic embryos originated some poor quality PCR-profiles, replicable and excellent fingerprints were obtained for both donor plant and embling. Results presented no differences among regenerated emblings and donor plant. Hence, the SE protocol used did not induce, up to moment, any genetic variability, confirming data previously obtained with other molecular/genetic techniques, supporting that this protocol may be used to provide true-to-type plants from important forestry species. (author)

Prenatal screening and genetics

DEFF Research Database (Denmark)

Alderson, P; Aro, A R; Dragonas, T

2001-01-01

Although the term 'genetic screening' has been used for decades, this paper discusses how, in its most precise meaning, genetic screening has not yet been widely introduced. 'Prenatal screening' is often confused with 'genetic screening'. As we show, these terms have different meanings, and we...... examine definitions of the relevant concepts in order to illustrate this point. The concepts are i) prenatal, ii) genetic screening, iii) screening, scanning and testing, iv) maternal and foetal tests, v) test techniques and vi) genetic conditions. So far, prenatal screening has little connection...... with precisely defined genetics. There are benefits but also disadvantages in overstating current links between them in the term genetic screening. Policy making and professional and public understandings about screening could be clarified if the distinct meanings of prenatal screening and genetic screening were...

A Unique Technique to get Kaprekar Iteration in Linear Programming Problem

Science.gov (United States)

Sumathi, P.; Preethy, V.

2018-04-01

This paper explores about a frivolous number popularly known as Kaprekar constant and Kaprekar numbers. A large number of courses and the different classroom capacities with difference in study periods make the assignment between classrooms and courses complicated. An approach of getting the minimum value of number of iterations to reach the Kaprekar constant for four digit numbers and maximum value is also obtained through linear programming techniques.

Safe genetically engineered plants

International Nuclear Information System (INIS)

Rosellini, D; Veronesi, F

2007-01-01

The application of genetic engineering to plants has provided genetically modified plants (GMPs, or transgenic plants) that are cultivated worldwide on increasing areas. The most widespread GMPs are herbicide-resistant soybean and canola and insect-resistant corn and cotton. New GMPs that produce vaccines, pharmaceutical or industrial proteins, and fortified food are approaching the market. The techniques employed to introduce foreign genes into plants allow a quite good degree of predictability of the results, and their genome is minimally modified. However, some aspects of GMPs have raised concern: (a) control of the insertion site of the introduced DNA sequences into the plant genome and of its mutagenic effect; (b) presence of selectable marker genes conferring resistance to an antibiotic or an herbicide, linked to the useful gene; (c) insertion of undesired bacterial plasmid sequences; and (d) gene flow from transgenic plants to non-transgenic crops or wild plants. In response to public concerns, genetic engineering techniques are continuously being improved. Techniques to direct foreign gene integration into chosen genomic sites, to avoid the use of selectable genes or to remove them from the cultivated plants, to reduce the transfer of undesired bacterial sequences, and make use of alternative, safer selectable genes, are all fields of active research. In our laboratory, some of these new techniques are applied to alfalfa, an important forage plant. These emerging methods for plant genetic engineering are briefly reviewed in this work

Safe genetically engineered plants

Energy Technology Data Exchange (ETDEWEB)

Rosellini, D; Veronesi, F [Dipartimento di Biologia Vegetale e Biotecnologie Agroambientali e Zootecniche, Universita degli Studi di Perugia, Borgo XX giugno 74, 06121 Perugia (Italy)

2007-10-03

The application of genetic engineering to plants has provided genetically modified plants (GMPs, or transgenic plants) that are cultivated worldwide on increasing areas. The most widespread GMPs are herbicide-resistant soybean and canola and insect-resistant corn and cotton. New GMPs that produce vaccines, pharmaceutical or industrial proteins, and fortified food are approaching the market. The techniques employed to introduce foreign genes into plants allow a quite good degree of predictability of the results, and their genome is minimally modified. However, some aspects of GMPs have raised concern: (a) control of the insertion site of the introduced DNA sequences into the plant genome and of its mutagenic effect; (b) presence of selectable marker genes conferring resistance to an antibiotic or an herbicide, linked to the useful gene; (c) insertion of undesired bacterial plasmid sequences; and (d) gene flow from transgenic plants to non-transgenic crops or wild plants. In response to public concerns, genetic engineering techniques are continuously being improved. Techniques to direct foreign gene integration into chosen genomic sites, to avoid the use of selectable genes or to remove them from the cultivated plants, to reduce the transfer of undesired bacterial sequences, and make use of alternative, safer selectable genes, are all fields of active research. In our laboratory, some of these new techniques are applied to alfalfa, an important forage plant. These emerging methods for plant genetic engineering are briefly reviewed in this work.

Genetic diversity in Trichomonas vaginalis.

Science.gov (United States)

Meade, John C; Carlton, Jane M

2013-09-01

Recent advances in genetic characterisation of Trichomonas vaginalis isolates show that the extensive clinical variability in trichomoniasis and its disease sequelae are matched by significant genetic diversity in the organism itself, suggesting a connection between the genetic identity of isolates and their clinical manifestations. Indeed, a high degree of genetic heterogeneity in T vaginalis isolates has been observed using multiple genotyping techniques. A unique two-type population structure that is both local and global in distribution has been identified, and there is evidence of recombination within each group, although sexual recombination between the groups appears to be constrained. There is conflicting evidence in these studies for correlations between T vaginalis genetic identity and clinical presentation, metronidazole susceptibility, and the presence of T vaginalis virus, underscoring the need for adoption of a common standard for genotyping the parasite. Moving forward, microsatellite genotyping and multilocus sequence typing are the most robust techniques for future investigations of T vaginalis genotype-phenotype associations.

Improving the sterile sperm identification method for its implementation in the area-wide sterile insect technique program against Ceratitis capitata (Diptera: Tephritidae) in Spain

International Nuclear Information System (INIS)

Juan-Blasco, M.; Urbaneja, A.; San Andrés, V.; Sabater-Muñoz, B.; Castañera, P.

2014-01-01

The success of sterile males in area-wide sterile insect technique (aw-SIT) programs against Ceratitis capitata (Wiedemann) is currently measured by using indirect methods as the wild: sterile male ratio captured in monitoring traps. In the past decade, molecular techniques have been used to improve these methods. The development of a polymerase chain reaction-restriction fragment-length polymorphism- based method to identify the transfer of sterile sperm to wild females, the target of SIT, was considered a significant step in this direction. This method relies on identification of sperm by detecting the presence of Y chromosomes in spermathecae DNA extract complemented by the identification of the genetic origin of this sperm: Vienna-8 males or wild haplotype. However, the application of this protocol to aw-SIT programs is limited by handling time and personnel cost. The objective of this work was to obtain a high-throughput protocol to facilitate the routine measurement in a pest population of sterile sperm presence in wild females. The polymerase chain reactionrestriction fragment-length polymorphism markers previously developed were validated in Mediterranean fruit by samples collected from various locations worldwide. A laboratory protocol previously published was modified to allow for the analysis of more samples at the same time. Preservation methods and preservation times commonly used for Mediterranean fruit by female samples were assessed for their influence on the correct molecular detection of sterile sperm. This high-throughput methodology, as well as the results of sample management presented here, provide a robust, efficient, fast, and economical sterile sperm identification method ready to be used in all Mediterranean fruit by SIT programs. (author)

From observational to dynamic genetics

Directory of Open Access Journals (Sweden)

Claire M. A. Haworth

2014-01-01

Full Text Available Twin and family studies have shown that most traits are at least moderately heritable. But what are the implications of finding genetic influence for the design of intervention and prevention programs? For complex traits, heritability does not mean immutability, and research has shown that genetic influences can change with age, context and in response to behavioural and drug interventions. The most significant implications for intervention will come when we move from observational genetics to investigating dynamic genetics, including genetically sensitive interventions. Future interventions should be designed to overcome genetic risk and draw upon genetic strengths by changing the environment.

Genetic diversity and molecular characterization of Saccharomyces cerevisiae strains from winemaking environments

OpenAIRE

Schuller, Dorit Elisabeth

2004-01-01

Tese de doutoramento em Ciências The principal aim of the present work is to assess the genetic diversity of fermenting Saccharomyces cerevisiae strains found in vineyards belonging to the Vinho Verde Region in order to create a strain collection representing the region’s biodiversity wealth as a basis for future strain selection and improvement programs. Validation of molecular techniques for accurate genotyping is an indispensable prerequisite for biogeographical surveys. Molecular ty...

Management of insect pests: Nuclear and related molecular and genetic techniques

International Nuclear Information System (INIS)

1993-01-01

The conference was organized in eight sessions: opening, genetic engineering and molecular biology, genetics, operational programmes, F 1 sterility and insect behaviour, biocontrol, research and development on the tsetse fly, and quarantine. The 64 individual contributions have been indexed separately for INIS. Refs, figs and tabs

Selection on Optimal Haploid Value Increases Genetic Gain and Preserves More Genetic Diversity Relative to Genomic Selection.

Science.gov (United States)

Daetwyler, Hans D; Hayden, Matthew J; Spangenberg, German C; Hayes, Ben J

2015-08-01

Doubled haploids are routinely created and phenotypically selected in plant breeding programs to accelerate the breeding cycle. Genomic selection, which makes use of both phenotypes and genotypes, has been shown to further improve genetic gain through prediction of performance before or without phenotypic characterization of novel germplasm. Additional opportunities exist to combine genomic prediction methods with the creation of doubled haploids. Here we propose an extension to genomic selection, optimal haploid value (OHV) selection, which predicts the best doubled haploid that can be produced from a segregating plant. This method focuses selection on the haplotype and optimizes the breeding program toward its end goal of generating an elite fixed line. We rigorously tested OHV selection breeding programs, using computer simulation, and show that it results in up to 0.6 standard deviations more genetic gain than genomic selection. At the same time, OHV selection preserved a substantially greater amount of genetic diversity in the population than genomic selection, which is important to achieve long-term genetic gain in breeding populations. Copyright © 2015 by the Genetics Society of America.

Development of a Temperature Programmed Identification Technique to Characterize the Organic Sulphur Functional Groups in Coal

Directory of Open Access Journals (Sweden)

Moinuddin Ghauri

2017-06-01

Full Text Available The Temperature Programmed Reduction (TPR technique is employed for the characterisation of various organic sulphur functional groups in coal. The TPR technique is modified into the Temperature Programmed Identification technique to investigate whether this method can detect various functional groups corresponding to their reduction temperatures. Ollerton, Harworth, Silverdale, Prince of Wales coal and Mequinenza lignite were chosen for this study. High pressure oxydesulphurisation of the coal samples was also done. The characterization of various organic sulphur functional groups present in untreated and treated coal by the TPR method and later by the TPI method confirmed that these methods can identify the organic sulphur groups in coal and that the results based on total sulphur are comparable with those provided by standard analytical techniques. The analysis of the untreated and treated coal samples showed that the structural changes in the organic sulphur matrix due to a reaction can be determined.

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.

Techniques for detecting genetically modified crops and products ...

African Journals Online (AJOL)

The cultivation of genetically modified crops is becoming increasingly important; more traits are emerging and more acres than ever before are being planted with GM varieties. The release of GM crops and products in the markets worldwide has increased the regulatory need to monitor and verify the presence and the ...

An Equilibrium Chance-Constrained Multiobjective Programming Model with Birandom Parameters and Its Application to Inventory Problem

Directory of Open Access Journals (Sweden)

Zhimiao Tao

2013-01-01

Full Text Available An equilibrium chance-constrained multiobjective programming model with birandom parameters is proposed. A type of linear model is converted into its crisp equivalent model. Then a birandom simulation technique is developed to tackle the general birandom objective functions and birandom constraints. By embedding the birandom simulation technique, a modified genetic algorithm is designed to solve the equilibrium chance-constrained multiobjective programming model. We apply the proposed model and algorithm to a real-world inventory problem and show the effectiveness of the model and the solution method.

Genetic Engineering Workshop Report, 2010

Energy Technology Data Exchange (ETDEWEB)

Allen, J; Slezak, T

2010-11-03

The Lawrence Livermore National Laboratory (LLNL) Bioinformatics group has recently taken on a role in DTRA's Transformation Medical Technologies (TMT) program. The high-level goal of TMT is to accelerate the development of broad-spectrum countermeasures. To achieve this goal, there is a need to assess the genetic engineering (GE) approaches, potential application as well as detection and mitigation strategies. LLNL was tasked to coordinate a workshop to determine the scope of investments that DTRA should make to stay current with the rapid advances in genetic engineering technologies, so that accidental or malicious uses of GE technologies could be adequately detected and characterized. Attachment A is an earlier report produced by LLNL for TMT that provides some relevant background on Genetic Engineering detection. A workshop was held on September 23-24, 2010 in Springfield, Virginia. It was attended by a total of 55 people (see Attachment B). Twenty four (44%) of the attendees were academic researchers involved in GE or bioinformatics technology, 6 (11%) were from DTRA or the TMT program management, 7 (13%) were current TMT performers (including Jonathan Allen and Tom Slezak of LLNL who hosted the workshop), 11 (20%) were from other Federal agencies, and 7 (13%) were from industries that are involved in genetic engineering. Several attendees could be placed in multiple categories. There were 26 attendees (47%) who were from out of the DC area and received travel assistance through Invitational Travel Orders (ITOs). We note that this workshop could not have been as successful without the ability to invite experts from outside of the Beltway region. This workshop was an unclassified discussion of the science behind current genetic engineering capabilities. US citizenship was not required for attendance. While this may have limited some discussions concerning risk, we felt that it was more important for this first workshop to focus on the scientific state of

Airway Clearance Techniques (ACTs)

Medline Plus

Full Text Available ... decisions about your health care. CF Genetics: The Basics CF Mutations Video Series Find Out More About ... of Breathing Technique Airway Clearance Techniques Autogenic Drainage Basics of Lung Care Chest Physical Therapy Coughing and ...

LPmerge: an R package for merging genetic maps by linear programming.

Science.gov (United States)

Endelman, Jeffrey B; Plomion, Christophe

2014-06-01

Consensus genetic maps constructed from multiple populations are an important resource for both basic and applied research, including genome-wide association analysis, genome sequence assembly and studies of evolution. The LPmerge software uses linear programming to efficiently minimize the mean absolute error between the consensus map and the linkage maps from each population. This minimization is performed subject to linear inequality constraints that ensure the ordering of the markers in the linkage maps is preserved. When marker order is inconsistent between linkage maps, a minimum set of ordinal constraints is deleted to resolve the conflicts. LPmerge is on CRAN at http://cran.r-project.org/web/packages/LPmerge. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The use of genetic programming to develop a predictor of swash excursion on sandy beaches

OpenAIRE

M. Passarella; E. B. Goldstein; S. De Muro; G. Coco

2018-01-01

We use genetic programming (GP), a type of machine learning (ML) approach, to predict the total and infragravity swash excursion using previously published data sets that have been used extensively in swash prediction studies. Three previously published works with a range of new conditions are added to this data set to extend the range of measured swash conditions. Using this newly compiled data set we demonstrate that a ML approach can reduce the prediction errors compared ...

Three different applications of genetic algorithm (GA) search techniques on oil demand estimation

International Nuclear Information System (INIS)

Canyurt, Olcay Ersel; Oztuerk, Harun Kemal

2006-01-01

This present study develops three scenarios to analyze oil consumption and make future projections based on the Genetic algorithm (GA) notion, and examines the effect of the design parameters on the oil utilization values. The models developed in the non-linear form are applied to the oil demand of Turkey. The GA Oil Demand Estimation Model (GAODEM) is developed to estimate the future oil demand values based on Gross National Product (GNP), population, import, export, oil production, oil import and car, truck and bus sales figures. Among these models, the GA-PGOiTI model, which uses population, GNP, oil import, truck sales and import as design parameters/indicators, was found to provide the best fit solution with the observed data. It may be concluded that the proposed models can be used as alternative solution and estimation techniques for the future oil utilization values of any country

Pitfalls in genetic testing

DEFF Research Database (Denmark)

Djémié, Tania; Weckhuysen, Sarah; von Spiczak, Sarah

2016-01-01

BACKGROUND: Sanger sequencing, still the standard technique for genetic testing in most diagnostic laboratories and until recently widely used in research, is gradually being complemented by next-generation sequencing (NGS). No single mutation detection technique is however perfect in identifying...

Genetic diversity of pacu and piapara broodstocks in restocking programs in the rivers Paraná and Paranapanema (Brazil

Directory of Open Access Journals (Sweden)

Nelson Mauricio Lopera-Barrero

2016-09-01

Full Text Available The genetic diversity of Piaractus mesopotamicus (pacu and Leporinus elongatus (piapara broodstocks used in restocking programs in the rivers Paraná and Paranapanema is analyzed. One hundred and twenty specimens (two broodstocks of each species from fish ponds in Palotina PR Brazil and in Salto Grande SP Brazil were assessed. Ten primers produced 96 fragments, comprising 68 (70.83% and 94 (97.92% polymorphic fragments for P. mesopotamicus and L. elongatus broodstocks, respectively. Differences (p < 0.05 in the frequency of 15 and 27 fragments were detected for each species, without exclusive fragments. Shannon Index (0.347 - 0.572 and the percentage of polymorphic fragments (57.3% - 94.8% revealed high intra-population genetic variability for all broodstocks. Results of molecular variance analyses (AMOVA showed that most variations do not lie between the broodstocks but within each broodstock (89%. Genetic (0.088 and 0.142 and identity (0.916 and 0.868 distance rates demonstrated similarity between the broodstocks of each species, corroborated by Fst (0.1023 and 010.27 and Nm (4.18 and 4.33 rates, with a slight genetic difference due to genic flux. High intrapopulation genetic variability and similarity between the broodstocks of each species was also detected, proving a common ancestry.

Genetic parameters for oocyte number and embryo production within a bovine ovum pick-up-in vitro production embryo-production program.

Science.gov (United States)

Merton, J S; Ask, B; Onkundi, D C; Mullaart, E; Colenbrander, B; Nielen, M

2009-10-15

Genetic factors influencing the outcome of bovine ovum pick-up-in vitro production (OPU-IVP) and its relation to female fertility were investigated. For the first time, genetic parameters were estimated for the number of cumulus-oocyte complexes (Ncoc), quality of cumulus-oocyte complexes (Qcoc), number and proportion of cleaved embryos at Day 4 (Ncleav(D4), Pcleav(D4)), and number and proportion of total and transferable embryos at Day 7 of culture (Nemb(D7), Pemb(D7) and NTemb(D7), PTemb(D7), respectively). Data were recorded by CRV (formally Holland Genetics) from the OPU-IVP program from January 1995 to March 2006. Data were collected from 1508 Holstein female donors, both cows and pregnant virgin heifers, with a total of 18,702 OPU sessions. Data were analyzed with repeated-measure sire models with permanent environment effect using ASREML (Holstein Friesian). Estimates of heritability were 0.25 for Ncoc, 0.09 for Qcoc, 0.19 for Ncleav(D4), 0.21 for Nemb(D7), 0.16 for NTemb(D7), 0.07 for Pcleav(D4), 0.12 for Pemb(D7), and 0.10 for PTemb(D7). Genetic correlation between Ncoc and Qcoc was close to zero, whereas genetic correlations between Ncoc and the number of embryos were positive and moderate to high for Nemb(D7) (0.47), NTemb(D7) (0.52), and Ncleav(D4) (0.85). Genetic correlations between Ncoc and percentages of embryos (Pcleav(D4), Pemb(D7), and PTemb(D7)) were all close to zero. Phenotypic correlations were in line with genetic correlations. Genetic and phenotypic correlations between Qcoc and all other traits were not significant except for the phenotypic correlations between Qcoc and number of embryos, which were negative and low to moderate for Nemb(D7) (-0.20), NTemb(D7) (-0.24), and Ncleav(D4) (-0.43). Results suggest that cumulus-oocyte complex (COC) quality, based on cumulus investment, is independent from the total number of COCs collected via OPU and that in general, a higher number of COCs will lead to a higher number of embryos produced. The

Genetics educational needs in China: physicians' experience and knowledge of genetic testing.

Science.gov (United States)

Li, Jing; Xu, Tengda; Yashar, Beverly M

2015-09-01

The aims of this study were to explore the relationship between physicians' knowledge and utilization of genetic testing and to explore genetics educational needs in China. An anonymous survey about experience, attitudes, and knowledge of genetic testing was conducted among physicians affiliated with Peking Union Medical College Hospital during their annual health evaluation. A personal genetics knowledge score was developed and predictors of personal genetics knowledge score were evaluated. Sixty-four physicians (33% male) completed the survey. Fifty-eight percent of them had used genetic testing in their clinical practice. Using a 4-point scale, mean knowledge scores of six common genetic testing techniques ranged from 1.7 ± 0.9 to 2.4 ± 1.0, and the average personal genetics knowledge score was 2.1 ± 0.8. In regression analysis, significant predictors of higher personal genetics knowledge score were ordering of genetic testing, utilization of pedigrees, higher medical degree, and recent genetics training (P education. This study demonstrated a sizable gap between Chinese physicians' knowledge and utilization of genetic testing. Participants had high self-perceived genetics educational needs. Development of genetics educational platforms is both warranted and desired in China.Genet Med 17 9, 757-760.

Sex determination of Pohnpei Micronesian kingfishers using morphological and molecular genetic techniques

Science.gov (United States)

Kesler, Dylan C.; Lopes, I.F.; Haig, Susan M.

2006-01-01

Conservation-oriented studies of Micronesian Kingfishers (Todiramphus cinnamominus) have been hindered by a lack of basic natural history information, despite the status of the Guam subspecies (T. c. cinnamominus) as one of the most endangered species in the world. We used tissue samples and morphometric measures from museum specimens and wild-captured Pohnpei Micronesian Kingfishers (T. c. reichenbachii) to develop methods for sex determination. We present a modified molecular protocol and a discriminant function that yields the probability that a particular individual is male or female. Our results revealed that females were significantly larger than males, and the discriminant function correctly predicted sex in 73% (30/41) of the individuals. The sex of 86% (18/21) of individuals was correctly assigned when a moderate reliability threshold was set. Sex determination using molecular genetic techniques was more reliable than methods based on morphology. Our results will facilitate recovery efforts for the critically endangered Guam Micronesian Kingfisher and provide a basis for sex determination in the 11 other endangered congeners in the Pacific Basin.

Functional Programming in C# Classic Programming Techniques for Modern Projects

CERN Document Server

Sturm, Oliver

2011-01-01

Take advantage of the growing trend in functional programming. C# is the number-one language used by .NET developers and one of the most popular programming languages in the world. It has many built-in functional programming features, but most are complex and little understood. With the shift to functional programming increasing at a rapid pace, you need to know how to leverage your existing skills to take advantage of this trend. Functional Programming in C# leads you along a path that begins with the historic value of functional ideas. Inside, C# MVP and functional programming expert Oli

Symbolic regression via genetic programming for data driven derivation of confinement scaling laws without any assumption on their mathematical form

International Nuclear Information System (INIS)

Murari, A; Peluso, E; Gelfusa, M; Lupelli, I; Lungaroni, M; Gaudio, P

2015-01-01

Many measurements are required to control thermonuclear plasmas and to fully exploit them scientifically. In the last years JET has shown the potential to generate about 50 GB of data per shot. These amounts of data require more sophisticated data analysis methodologies to perform correct inference and various techniques have been recently developed in this respect. The present paper covers a new methodology to extract mathematical models directly from the data without any a priori assumption about their expression. The approach, based on symbolic regression via genetic programming, is exemplified using the data of the International Tokamak Physics Activity database for the energy confinement time. The best obtained scaling laws are not in power law form and suggest a revisiting of the extrapolation to ITER. Indeed the best non-power law scalings predict confinement times in ITER approximately between 2 and 3 s. On the other hand, more comprehensive and better databases are required to fully profit from the power of these new methods and to discriminate between the hundreds of thousands of models that they can generate. (paper)

Genetic risks and healthy choices: creating citizen-consumers of genetic services through empowerment and facilitation.

Science.gov (United States)

Harvey, Alison

2010-03-01

Genetic testing to identify susceptibility to a variety of common complex diseases is increasingly becoming available. In this article, focusing on the development of genetic susceptibility testing for diet-related disease, I examine the emergence of direct-to-the-consumer genetic testing services and the (re)configuration of healthcare provision, both within and outside the specialist genetics service, in the UK. I identify two key techniques within these practices: empowerment and facilitation. Using Foucauldian social theory, I show that empowerment and facilitation are being positioned as tools for the creation of citizen-consumers who will make appropriate dietary choices, based on the results of their genetic analysis. Through these techniques, individuals are transformed into properly entrepreneurial citizens who will, through judicious choices, act to maximise their 'vital capital' (their health) and the capital of the social body. I argue that the user of these services is not purely an economic figure, making rational choices as a consumer, but that her configuration as a citizen-consumer who avails herself of genetic information and services in a proper manner ensures that she is fit to contribute to the economic life of our present.

Transference of microsatellite markers from Eucalyptus spp to Acca sellowiana and the successful use of this technique in genetic characterization

Directory of Open Access Journals (Sweden)

Karine Louise dos Santos

2007-01-01

Full Text Available The pineapple guava (Acca sellowiana, known in portuguese as the goiabeira-serrana or "Feijoa", is a native fruit tree from southern Brazil and northern Uruguay that has commercial potential due to the quality and unique flavor of its fruits. Knowledge of genetic variability is an important tool in various steps of a breeding program, which can be facilitated by the use of molecular markers. The conservation of repeated sequences among related species permits the transferability of microsatellite markers from Eucalyptus spp. to A. sellowiana for testing. We used primers developed for Eucalyptus to characterize A. sellowiana accessions. Out of 404 primers tested, 180 amplified visible products and 38 were polymorphic. A total of 48 alleles were detected with ten Eucalyptus primer pairs against DNA from 119 A. sellowiana accessions. The mean expected heterozygosity among accessions was 0.64 and the mean observed heterozygosity 0.55. A high level of genetic diversity was also observed in the dendrogram, where the degree of genetic dissimilarity ranged from 0 to 65% among the 119 genotypes tested. This study demonstrates the possibility of transferring microsatellite markers between species of different genera in addition to evaluating the extent of genetic variability among plant accessions.

Genetics & sport: bioethical concerns.

Science.gov (United States)

Miah, Andy

2012-12-01

This paper provides an overview of the ethical issues pertaining to the use of genetic insights and techniques in sport. Initially, it considers a range of scientific findings that have stimulated debate about the ethical issues associated with genetics applied to sport. It also outlines some of the early policy responses to these discoveries from world leading sports organizations, along with knowledge about actual use of gene technologies in sport. Subsequently, it considers the challenges with distinguishing between therapeutic use and human enhancement within genetic science, which is a particularly important issue for the world of sport. Next, particular attention is given to the use of genetic information, which raises questions about the legitimacy and reliability of genetic tests, along with the potential public value of having DNA databanks to economize in health care. Finally, the ethics of gene transfer are considered, inviting questions into the values of sport and humanity. It argues that, while gene modification may seem conceptually similar to other forms of doping, the requirements upon athletes are such that new forms of enhancement become increasingly necessary to discover. Insofar as genetic science is able to create safer, more effective techniques of human modification, then it may be an appealing route through which to modify athletes to safeguard the future of elite sports as enterprises of human excellence.

GENETIC ALGORITHM BASED CONCEPT DESIGN TO OPTIMIZE NETWORK LOAD BALANCE

Directory of Open Access Journals (Sweden)

Ashish Jain

2012-07-01

Full Text Available Multiconstraints optimal network load balancing is an NP-hard problem and it is an important part of traffic engineering. In this research we balance the network load using classical method (brute force approach and dynamic programming is used but result shows the limitation of this method but at a certain level we recognized that the optimization of balanced network load with increased number of nodes and demands is intractable using the classical method because the solution set increases exponentially. In such case the optimization techniques like evolutionary techniques can employ for optimizing network load balance. In this paper we analyzed proposed classical algorithm and evolutionary based genetic approach is devise as well as proposed in this paper for optimizing the balance network load.

Integrating Genetic Studies of Nicotine Addiction into Public Health Practice: Stakeholder Views on Challenges, Barriers and Opportunities

Science.gov (United States)

Dingel, M.J.; Hicks, A.D.; Robinson, M.E.; Koenig, B.A.

2011-01-01

Objective: Will emerging genetic research strengthen tobacco control programs? In this empirical study, we interview stakeholders in tobacco control to illuminate debates about the role of genomics in public health. Methods: The authors performed open-ended interviews with 86 stakeholders from 5 areas of tobacco control: basic scientists, clinicians, tobacco prevention specialists, health payers, and pharmaceutical industry employees. Interviews were qualitatively analyzed using standard techniques. Results: The central tension is between the hope that an expanding genomic knowledge base will improve prevention and smoking cessation therapies and the fear that genetic research might siphon resources away from traditional and proven public health programs. While showing strong support for traditional public health approaches to tobacco control, stakeholders recognize weaknesses, specifically the difficulty of countering the powerful voice of the tobacco industry when mounting public campaigns and the problem of individuals who are resistant to treatment and continue smoking. Conclusions: In order for genetic research to be effectively translated into efforts to minimize the harm of smoking-related disease, the views of key stakeholders must be voiced and disagreements reconciled. Effective translation requires honest evaluation of both the strengths and limitations of genetic approaches. PMID:21757875

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

Science.gov (United States)

Taylan, Fatih

2011-04-01

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

High performance parallelism pearls 2 multicore and many-core programming approaches

CERN Document Server

Jeffers, Jim

2015-01-01

High Performance Parallelism Pearls Volume 2 offers another set of examples that demonstrate how to leverage parallelism. Similar to Volume 1, the techniques included here explain how to use processors and coprocessors with the same programming - illustrating the most effective ways to combine Xeon Phi coprocessors with Xeon and other multicore processors. The book includes examples of successful programming efforts, drawn from across industries and domains such as biomed, genetics, finance, manufacturing, imaging, and more. Each chapter in this edited work includes detailed explanations of t

Comparison of Bayesian clustering and edge detection methods for inferring boundaries in landscape genetics

Science.gov (United States)

Safner, T.; Miller, M.P.; McRae, B.H.; Fortin, M.-J.; Manel, S.

2011-01-01

Recently, techniques available for identifying clusters of individuals or boundaries between clusters using genetic data from natural populations have expanded rapidly. Consequently, there is a need to evaluate these different techniques. We used spatially-explicit simulation models to compare three spatial Bayesian clustering programs and two edge detection methods. Spatially-structured populations were simulated where a continuous population was subdivided by barriers. We evaluated the ability of each method to correctly identify boundary locations while varying: (i) time after divergence, (ii) strength of isolation by distance, (iii) level of genetic diversity, and (iv) amount of gene flow across barriers. To further evaluate the methods' effectiveness to detect genetic clusters in natural populations, we used previously published data on North American pumas and a European shrub. Our results show that with simulated and empirical data, the Bayesian spatial clustering algorithms outperformed direct edge detection methods. All methods incorrectly detected boundaries in the presence of strong patterns of isolation by distance. Based on this finding, we support the application of Bayesian spatial clustering algorithms for boundary detection in empirical datasets, with necessary tests for the influence of isolation by distance. ?? 2011 by the authors; licensee MDPI, Basel, Switzerland.

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...

Uranium exploration techniques

International Nuclear Information System (INIS)

Nichols, C.E.

1984-01-01

The subject is discussed under the headings: introduction (genetic description of some uranium deposits; typical concentrations of uranium in the natural environment); sedimentary host rocks (sandstones; tabular deposits; roll-front deposits; black shales); metamorphic host rocks (exploration techniques); geologic techniques (alteration features in sandstones; favourable features in metamorphic rocks); geophysical techniques (radiometric surveys; surface vehicle methods; airborne methods; input surveys); geochemical techniques (hydrogeochemistry; petrogeochemistry; stream sediment geochemistry; pedogeochemistry; emanometry; biogeochemistry); geochemical model for roll-front deposits; geologic model for vein-like deposits. (U.K.)

Improving feature ranking for biomarker discovery in proteomics mass spectrometry data using genetic programming

Science.gov (United States)

Ahmed, Soha; Zhang, Mengjie; Peng, Lifeng

2014-07-01

Feature selection on mass spectrometry (MS) data is essential for improving classification performance and biomarker discovery. The number of MS samples is typically very small compared with the high dimensionality of the samples, which makes the problem of biomarker discovery very hard. In this paper, we propose the use of genetic programming for biomarker detection and classification of MS data. The proposed approach is composed of two phases: in the first phase, feature selection and ranking are performed. In the second phase, classification is performed. The results show that the proposed method can achieve better classification performance and biomarker detection rate than the information gain- (IG) based and the RELIEF feature selection methods. Meanwhile, four classifiers, Naive Bayes, J48 decision tree, random forest and support vector machines, are also used to further test the performance of the top ranked features. The results show that the four classifiers using the top ranked features from the proposed method achieve better performance than the IG and the RELIEF methods. Furthermore, GP also outperforms a genetic algorithm approach on most of the used data sets.

Desktop Genetics.

Science.gov (United States)

Hough, Soren H; Ajetunmobi, Ayokunmi; Brody, Leigh; Humphryes-Kirilov, Neil; Perello, Edward

2016-11-01

Desktop Genetics is a bioinformatics company building a gene-editing platform for personalized medicine. The company works with scientists around the world to design and execute state-of-the-art clustered regularly interspaced short palindromic repeats (CRISPR) experiments. Desktop Genetics feeds the lessons learned about experimental intent, single-guide RNA design and data from international genomics projects into a novel CRISPR artificial intelligence system. We believe that machine learning techniques can transform this information into a cognitive therapeutic development tool that will revolutionize medicine.

A study on the optimization of radwaste treatment system: using goal programming

International Nuclear Information System (INIS)

Yang, Jin Yeong

1998-02-01

This study is concerned with the applications of linear goal programming techniques and artificial intelligence algorithm (fuzzy theory and genetic algorithm) to the analysis of management and operational problems in the radioactive processing system (RWPS). A typical RWPS is modeled as a linear functions to study and resolve the effects of conflicting objectives such as cost, limitation of released radioactivity to the environment, equipment utilization and total treatable radioactive waste volume before discharge and disposal. The developed model is validated and verified using actual data obtained from the RWPS at Kyoto University in Japan. The solution by goal programming would show the optimal operation point which is to maximize the total treatable radioactive waste volume and minimize the released radioactivity of liquid waste even under the restricted resources. But goal programming has a demerit that the target values are decided by decision maker arbitrarily. To complement the goal programming's demerit, the fuzzy set theory is introduced and the target values are analyzed by it. Genetic algorithm is combined with goal programming and the results by it is compared with that of goal programming only

Application of Artificial Intelligence (AI) Programming Techniques to Tactical Guidance for Fighter Aircraft

Science.gov (United States)

McManus, John W.; Goodrich, Kenneth H.

1989-01-01

A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within-Visual-Range (WVR) air combat engagements is discussed. The application of AI methods for development and implementation of the TDG is presented. The history of the Adaptive Maneuvering Logic (AML) program is traced and current versions of the AML program are compared and contrasted with the TDG system. The Knowledge-Based Systems (KBS) used by the TDG to aid in the decision-making process are outlined in detail and example rules are presented. The results of tests to evaluate the performance of the TDG versus a version of AML and versus human pilots in the Langley Differential Maneuvering Simulator (DMS) are presented. To date, these results have shown significant performance gains in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify than the updated FORTRAN AML programs.

Nurses' knowledge and educational needs regarding genetics.

Science.gov (United States)

Seven, Memnun; Akyüz, Aygül; Elbüken, Burcu; Skirton, Heather; Öztürk, Hatice

2015-03-01

Nurses now require a basic knowledge of genetics to provide patient care in a range of settings. To determine Turkish registered nurses' current knowledge and educational needs in relation to genetics. A descriptive, cross-sectional study. Turkish registered nurses working in a university hospital in Turkey were recruited. All registered nurses were invited to participate and 175 completed the study. The survey instrument, basic knowledge of health genetics, confidence in knowledge and the nurses' need for genetics education were used to collect data. The majority (81.1%, n=142) of participants indicated that genetics was not taught during their degree program, although 53.1% to 96% of respondents felt confident in defining different genetic concepts. The average genetics knowledge score was 6.89±1.99 of a possible 11 (range 0-11). The majority (70.3%) expressed a strong wish to attend a continuing nursing education program in genetics. The study shows that although Turkish nurses are not sufficiently knowledgeable to apply genetics in practice, they are willing to have more education to support their care of patients. Nurses need to have more education related to genetics in accordance with advances in human genetics to optimize health care. Copyright © 2014 Elsevier Ltd. All rights reserved.

Applying genetic algorithms for programming manufactoring cell tasks

Directory of Open Access Journals (Sweden)

Efredy Delgado

2005-05-01

Full Text Available This work was aimed for developing computational intelligence for scheduling a manufacturing cell's tasks, based manily on genetic algorithms. The manufacturing cell was modelled as beign a production-line; the makespan was calculated by using heuristics adapted from several libraries for genetic algorithms computed in C++ builder. Several problems dealing with small, medium and large list of jobs and machinery were resolved. The results were compared with other heuristics. The approach developed here would seem to be promising for future research concerning scheduling manufacturing cell tasks involving mixed batches.

Comparison the Impact of Spark Motor Program and Basketball Techniques on Improving Gross Motor Skills in Educable Intellectually Disabled Boys

Directory of Open Access Journals (Sweden)

Hashem Faal Moghanlo

2014-09-01

Full Text Available Background & objectives : Different types of practises are known for improving motor skills in intellectually disabled boys. The purpose of this study was to compar e the impact of spark motor program and basketball on improving of gross motor skills in this people.   Methods: In this semi-experimental study , from 98 educable intellectually disabled students who studied in special school in Urmia, 30 children ( age range of 9 to 13 years and IQ mean 64.4 were selected objectively and divided in three groups (2 experimental and 1 control based on pre - test. BOTMP was used as a measurement of motor ability. Selected motor program (Spark motor program including strengthening training, games, sports and basketball techniques was performed for 24 sessions. T-tests (dependent and co-variance were used to comparison of results.   Results: In Spark group after 24 sessions, there were significant effects on balance (p= 0.000, bilateral coordination (p=0.000 and strength (p=0.001. There was no significant effect in agility and speed (p= 0.343 in basketball techniques group after 24 sessions, there were significant effects in agility and speed (p= 0.001, balance (p= 0.000, bilateral coordination (p= 0.013 and strength (p= 0.007.   Conclusion: Based on the results of this study, it can be claimed that the Spark program and basketball techniques improve gross motor skills in educable intellectually disabled students. We also found a significant difference between the Spark program and basketball techniques efficacy on the improved skills. Furthermore, the efficacy of Spark program was significantly higher than basketball techniques (p<0.05.

Feline genetics: clinical applications and genetic testing.

Science.gov (United States)

Lyons, Leslie A

2010-11-01

DNA testing for domestic cat diseases and appearance traits is a rapidly growing asset for veterinary medicine. Approximately 33 genes contain 50 mutations that cause feline health problems or alterations in the cat's appearance. A variety of commercial laboratories can now perform cat genetic diagnostics, allowing both the veterinary clinician and the private owner to obtain DNA test results. DNA is easily obtained from a cat via a buccal swab with a standard cotton bud or cytological brush, allowing DNA samples to be easily sent to any laboratory in the world. The DNA test results identify carriers of the traits, predict the incidence of traits from breeding programs, and influence medical prognoses and treatments. An overall goal of identifying these genetic mutations is the correction of the defect via gene therapies and designer drug therapies. Thus, genetic testing is an effective preventative medicine and a potential ultimate cure. However, genetic diagnostic tests may still be novel for many veterinary practitioners and their application in the clinical setting needs to have the same scrutiny as any other diagnostic procedure. This article will review the genetic tests for the domestic cat, potential sources of error for genetic testing, and the pros and cons of DNA results in veterinary medicine. Highlighted are genetic tests specific to the individual cat, which are a part of the cat's internal genome. Copyright © 2010 Elsevier Inc. All rights reserved.

Cancer Genetics and Signaling | Center for Cancer Research

Science.gov (United States)

The Cancer, Genetics, and Signaling (CGS) Group at the National Cancer Institute at Frederick  offers a competitive postdoctoral training and mentoring program focusing on molecular and genetic aspects of cancer. The CGS Fellows Program is designed to attract and train exceptional postdoctoral fellows interested in pursuing independent research career tracks. CGS Fellows participate in a structured mentoring program designed for scientific and career development and transition to independent positions.

The Genetic Activity Profile database.

Science.gov (United States)

Waters, M D; Stack, H F; Garrett, N E; Jackson, M A

1991-12-01

A graphic approach termed a Genetic Activity Profile (GAP) has been developed to display a matrix of data on the genetic and related effects of selected chemical agents. The profiles provide a visual overview of the quantitative (doses) and qualitative (test results) data for each chemical. Either the lowest effective dose (LED) or highest ineffective dose (HID) is recorded for each agent and bioassay. Up to 200 different test systems are represented across the GAP. Bioassay systems are organized according to the phylogeny of the test organisms and the end points of genetic activity. The methodology for the production and evaluation of GAPs has been developed in collaboration with the International Agency for Research on Cancer. Data on individual chemicals have been compiled by IARC and by the U.S. Environmental Protection Agency. Data are available on 299 compounds selected from volumes 1-50 of the IARC Monographs and on 115 compounds identified as Superfund Priority Substances. Software to display the GAPs on an IBM-compatible personal computer is available from the authors. Structurally similar compounds frequently display qualitatively and quantitatively similar GAPs. By examining the patterns of GAPs of pairs and groups of chemicals, it is possible to make more informed decisions regarding the selection of test batteries to be used in evaluating chemical analogs. GAPs have provided useful data for the development of weight-of-evidence hazard ranking schemes. Also, some knowledge of the potential genetic activity of complex environmental mixtures may be gained from assessing the GAPs of component chemicals. The fundamental techniques and computer programs devised for the GAP database may be used to develop similar databases in other disciplines.

Plant breeding and genetics newsletter. No. 3

International Nuclear Information System (INIS)

1999-06-01

This third issue of the Plant Breeding and Genetics Newsletter highlights forthcoming events including regional (Afra) training course on 'molecular characterization of genetic biodiversity in traditional and neglected crops selected for improvement through mutation techniques' and seminar on 'mutation techniques and biotechnology for tropical and subtropical plant improvement in Asia and Pacific regions'. Status of existing co-ordinated and technical co-operation research projects is also summarized

Attitudes Toward Breast Cancer Genetic Testing in Five Special Population Groups.

Science.gov (United States)

Ramirez, Amelie G; Chalela, Patricia; Gallion, Kipling J; Muñoz, Edgar; Holden, Alan E; Burhansstipanov, Linda; Smith, Selina A; Wong-Kim, Evaon; Wyatt, Stephen W; Suarez, Lucina

2015-01-01

This study examined interest in and attitudes toward genetic testing in 5 different population groups. The survey included African American, Asian American, Latina, Native American, and Appalachian women with varying familial histories of breast cancer. A total of 49 women were interviewed in person. Descriptive and nonparametric statistical techniques were used to assess ethnic group differences. Overall, interest in testing was high. All groups endorsed more benefits than risks. There were group differences regarding endorsement of specific benefits and risks: testing to "follow doctor recommendations" (p=0.017), "concern for effects on family" (p=0.044), "distrust of modern medicine" (p=0.036), "cost" (p=0.025), and "concerns about communication of results to others" (p=0.032). There was a significant inverse relationship between interest and genetic testing cost (p<0.050), with the exception of Latinas, who showed the highest level of interest regardless of increasing cost. Cost may be an important barrier to obtaining genetic testing services, and participants would benefit by genetic counseling that incorporates the unique cultural values and beliefs of each group to create an individualized, culturally competent program. Further research about attitudes toward genetic testing is needed among Asian Americans, Native Americans, and Appalachians for whom data are severely lacking. Future study of the different Latina perceptions toward genetic testing are encouraged.

Public health genetic counselors: activities, skills, and sources of learning.

Science.gov (United States)

McWalter, Kirsty M; Sdano, Mallory R; Dave, Gaurav; Powell, Karen P; Callanan, Nancy

2015-06-01

Specialization within genetic counseling is apparent, with 29 primary specialties listed in the National Society of Genetic Counselors' 2012 Professional Status Survey (PSS). PSS results show a steady proportion of genetic counselors primarily involved in public health, yet do not identify all those performing public health activities. Little is known about the skills needed to perform activities outside of "traditional" genetic counselor roles and the expertise needed to execute those skills. This study aimed to identify genetic counselors engaging in public health activities, the skills used, and the most influential sources of learning for those skills. Participants (N = 155) reported involvement in several public health categories: (a) Education of Public and/or Health Care Providers (n = 80, 52 %), (b) Population-Based Screening Programs (n = 70, 45 %), (c) Lobbying/Public Policy (n = 62, 40 %), (d) Public Health Related Research (n = 47, 30 %), and (e) State Chronic Disease Programs (n = 12, 8 %). Regardless of category, "on the job" was the most common primary source of learning. Genetic counseling training program was the most common secondary source of learning. Results indicate that the number of genetic counselors performing public health activities is likely higher than PSS reports, and that those who may not consider themselves "public health genetic counselors" do participate in public health activities. Genetic counselors learn a diverse skill set in their training programs; some skills are directly applicable to public health genetics, while other public health skills require additional training and/or knowledge.

Adaptive sensor fusion using genetic algorithms

International Nuclear Information System (INIS)

Fitzgerald, D.S.; Adams, D.G.

1994-01-01

Past attempts at sensor fusion have used some form of Boolean logic to combine the sensor information. As an alteniative, an adaptive ''fuzzy'' sensor fusion technique is described in this paper. This technique exploits the robust capabilities of fuzzy logic in the decision process as well as the optimization features of the genetic algorithm. This paper presents a brief background on fuzzy logic and genetic algorithms and how they are used in an online implementation of adaptive sensor fusion

Nuclear techniques and in vitro culture for plant improvement

International Nuclear Information System (INIS)

1986-01-01

The continuous series of food shortages in many parts of the world have led scientists to consider the possibilities of using the new techniques to develop better varieties of plants. The basis for plant breeding is suitable genetic variability and mutation induction as the means to create additional variation. In vitro techniques are a relatively new tool in practical plant breeding. These Proceedings contain 62 papers and posters presented at the symposium, as well as excerpts from the discussions. The Symposium presentations are divided into the following sessions: Genetic variation from in vitro culture; Genetic stability of in vitro cultures; In vitro culture with application of mutagens; Haploids; In vitro mutant selection; Use of genetic variation derived by in vitro culture; In vitro techniques as aids in mutation breeding and Genetic engineering. A separate abstract is prepared for each of these papers and posters

Near infrared spectrometric technique for testing fruit quality: optimisation of regression models using genetic algorithms

Science.gov (United States)

Isingizwe Nturambirwe, J. Frédéric; Perold, Willem J.; Opara, Umezuruike L.

2016-02-01

Near infrared (NIR) spectroscopy has gained extensive use in quality evaluation. It is arguably one of the most advanced spectroscopic tools in non-destructive quality testing of food stuff, from measurement to data analysis and interpretation. NIR spectral data are interpreted through means often involving multivariate statistical analysis, sometimes associated with optimisation techniques for model improvement. The objective of this research was to explore the extent to which genetic algorithms (GA) can be used to enhance model development, for predicting fruit quality. Apple fruits were used, and NIR spectra in the range from 12000 to 4000 cm-1 were acquired on both bruised and healthy tissues, with different degrees of mechanical damage. GAs were used in combination with partial least squares regression methods to develop bruise severity prediction models, and compared to PLS models developed using the full NIR spectrum. A classification model was developed, which clearly separated bruised from unbruised apple tissue. GAs helped improve prediction models by over 10%, in comparison with full spectrum-based models, as evaluated in terms of error of prediction (Root Mean Square Error of Cross-validation). PLS models to predict internal quality, such as sugar content and acidity were developed and compared to the versions optimized by genetic algorithm. Overall, the results highlighted the potential use of GA method to improve speed and accuracy of fruit quality prediction.

Aquaculture-oriented genetic researches in abalone: Current status ...

African Journals Online (AJOL)

Hybridization, triploidization and genetic mapping were also briefly reviewed as aquaculture-oriented genetic techniques to improve growth and other commercially important traits. Cryopreservation and other biotechnologies potentially applicable on genetic improvement were also briefly mentioned as supporting tools for ...

APPLICATION OF OBJECT ORIENTED PROGRAMMING TECHNIQUES IN FRONT END COMPUTERS

International Nuclear Information System (INIS)

SKELLY, J.F.

1997-01-01

The Front End Computer (FEC) environment imposes special demands on software, beyond real time performance and robustness. FEC software must manage a diverse inventory of devices with individualistic timing requirements and hardware interfaces. It must implement network services which export device access to the control system at large, interpreting a uniform network communications protocol into the specific control requirements of the individual devices. Object oriented languages provide programming techniques which neatly address these challenges, and also offer benefits in terms of maintainability and flexibility. Applications are discussed which exhibit the use of inheritance, multiple inheritance and inheritance trees, and polymorphism to address the needs of FEC software

GAPscreener: An automatic tool for screening human genetic association literature in PubMed using the support vector machine technique

Directory of Open Access Journals (Sweden)

Khoury Muin J

2008-04-01

Full Text Available Abstract Background Synthesis of data from published human genetic association studies is a critical step in the translation of human genome discoveries into health applications. Although genetic association studies account for a substantial proportion of the abstracts in PubMed, identifying them with standard queries is not always accurate or efficient. Further automating the literature-screening process can reduce the burden of a labor-intensive and time-consuming traditional literature search. The Support Vector Machine (SVM, a well-established machine learning technique, has been successful in classifying text, including biomedical literature. The GAPscreener, a free SVM-based software tool, can be used to assist in screening PubMed abstracts for human genetic association studies. Results The data source for this research was the HuGE Navigator, formerly known as the HuGE Pub Lit database. Weighted SVM feature selection based on a keyword list obtained by the two-way z score method demonstrated the best screening performance, achieving 97.5% recall, 98.3% specificity and 31.9% precision in performance testing. Compared with the traditional screening process based on a complex PubMed query, the SVM tool reduced by about 90% the number of abstracts requiring individual review by the database curator. The tool also ascertained 47 articles that were missed by the traditional literature screening process during the 4-week test period. We examined the literature on genetic associations with preterm birth as an example. Compared with the traditional, manual process, the GAPscreener both reduced effort and improved accuracy. Conclusion GAPscreener is the first free SVM-based application available for screening the human genetic association literature in PubMed with high recall and specificity. The user-friendly graphical user interface makes this a practical, stand-alone application. The software can be downloaded at no charge.

Detecting high-order interactions of single nucleotide polymorphisms using genetic programming.

Science.gov (United States)

Nunkesser, Robin; Bernholt, Thorsten; Schwender, Holger; Ickstadt, Katja; Wegener, Ingo

2007-12-15

Not individual single nucleotide polymorphisms (SNPs), but high-order interactions of SNPs are assumed to be responsible for complex diseases such as cancer. Therefore, one of the major goals of genetic association studies concerned with such genotype data is the identification of these high-order interactions. This search is additionally impeded by the fact that these interactions often are only explanatory for a relatively small subgroup of patients. Most of the feature selection methods proposed in the literature, unfortunately, fail at this task, since they can either only identify individual variables or interactions of a low order, or try to find rules that are explanatory for a high percentage of the observations. In this article, we present a procedure based on genetic programming and multi-valued logic that enables the identification of high-order interactions of categorical variables such as SNPs. This method called GPAS cannot only be used for feature selection, but can also be employed for discrimination. In an application to the genotype data from the GENICA study, an association study concerned with sporadic breast cancer, GPAS is able to identify high-order interactions of SNPs leading to a considerably increased breast cancer risk for different subsets of patients that are not found by other feature selection methods. As an application to a subset of the HapMap data shows, GPAS is not restricted to association studies comprising several 10 SNPs, but can also be employed to analyze whole-genome data. Software can be downloaded from http://ls2-www.cs.uni-dortmund.de/~nunkesser/#Software

Development of new techniques of using irradiation in the genetic improvement of warm season grasses and an assessment of the genetic and cytogenetic effects. Progress report, November 1, 1977--October 31, 1978

International Nuclear Information System (INIS)

Hanna, W.W.; Burton, G.W.

1978-05-01

Progress is reported on plant breeding programs for the genetic improvement of warm season grasses using irradiation as a tool. Data are included from studies on alteration of the protein quantity and quality in pearl millet grain by irradiation and mutation breeding; the effects of nitrogen and genotype on pearl millet grain; the effects of seed size on quality in pearl millet; irradiation breeding of sterile triploid turf Bermuda grasses; irradiation breeding of sterile coastcross-1, a forage grass, to increase winter hardiness; use of irradiation to induce resistance to rust disease; and an economic assessment of irradiation-induced mutants for plant breeding programs

Improvement of ECM Techniques through Implementation of a Genetic Algorithm

National Research Council Canada - National Science Library

Townsend, James D

2008-01-01

This research effort develops the necessary interfaces between the radar signal processing components and an optimization routine, such as genetic algorithms, to develop Electronic Countermeasure (ECM...

Community Genetics: a new discipline and its application in Brazil

Directory of Open Access Journals (Sweden)

Antonio Sérgio Ramalho

Full Text Available Community genetics is a new discipline which aims to provide genetic services to the community as a whole. As a science, community genetics encompasses all research needed to develop and evaluate its application. There is no question that the development of community genetics is necessary in Brazil. The implementation of such programs in our country, especially for hemoglobinopathies, has been recommended by the World Health Organization and other international organizations. Apart from the need for and appeal of community genetics programs, some aspects require serious review. This article discusses various cultural, social, psychological, and economic factors that can make genetic screening an invasion of individual privacy

Community Genetics: a new discipline and its application in Brazil

Directory of Open Access Journals (Sweden)

Ramalho Antonio Sérgio

2000-01-01

Full Text Available Community genetics is a new discipline which aims to provide genetic services to the community as a whole. As a science, community genetics encompasses all research needed to develop and evaluate its application. There is no question that the development of community genetics is necessary in Brazil. The implementation of such programs in our country, especially for hemoglobinopathies, has been recommended by the World Health Organization and other international organizations. Apart from the need for and appeal of community genetics programs, some aspects require serious review. This article discusses various cultural, social, psychological, and economic factors that can make genetic screening an invasion of individual privacy

Flow discharge prediction in compound channels using linear genetic programming

Science.gov (United States)

Azamathulla, H. Md.; Zahiri, A.

2012-08-01

SummaryFlow discharge determination in rivers is one of the key elements in mathematical modelling in the design of river engineering projects. Because of the inundation of floodplains and sudden changes in river geometry, flow resistance equations are not applicable for compound channels. Therefore, many approaches have been developed for modification of flow discharge computations. Most of these methods have satisfactory results only in laboratory flumes. Due to the ability to model complex phenomena, the artificial intelligence methods have recently been employed for wide applications in various fields of water engineering. Linear genetic programming (LGP), a branch of artificial intelligence methods, is able to optimise the model structure and its components and to derive an explicit equation based on the variables of the phenomena. In this paper, a precise dimensionless equation has been derived for prediction of flood discharge using LGP. The proposed model was developed using published data compiled for stage-discharge data sets for 394 laboratories, and field of 30 compound channels. The results indicate that the LGP model has a better performance than the existing models.

Ocean acidification genetics - Genetics and genomics of response to ocean acidification

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — We are applying a variety of genetic tools to assess the response of our ocean resources to ocean acidification, including gene expression techniques, identification...

Recommended safety, reliability, quality assurance and management aerospace techniques with possible application by the DOE to the high-level radioactive waste repository program

International Nuclear Information System (INIS)

Bland, W.M. Jr.

1985-05-01

Aerospace SRQA and management techniques, principally those developed and used by the NASA Lyndon B. Johnson Space Center on the manned space flight programs, have been assessed for possible application by the DOE and the DOE-contractors to the high level radioactive waste repository program that results from the implementation of the NWPA of 1982. Those techniques believed to have the greatest potential for usefulness to the DOE and the DOE-contractors have been discussed in detail and are recommended to the DOE for adoption; discussion is provided for the manner in which this transfer of technology can be implemented. Six SRQA techniques and two management techniques are recommended for adoption by the DOE; included with the management techniques is a recommendation for the DOE to include a licensing interface with the NRC in the application of the milestone reviews technique. Three other techniques are recommended for study by the DOE for possible adaptation to the DOE program

gPGA: GPU Accelerated Population Genetics Analyses.

Directory of Open Access Journals (Sweden)

Chunbao Zhou

Full Text Available The isolation with migration (IM model is important for studies in population genetics and phylogeography. IM program applies the IM model to genetic data drawn from a pair of closely related populations or species based on Markov chain Monte Carlo (MCMC simulations of gene genealogies. But computational burden of IM program has placed limits on its application.With strong computational power, Graphics Processing Unit (GPU has been widely used in many fields. In this article, we present an effective implementation of IM program on one GPU based on Compute Unified Device Architecture (CUDA, which we call gPGA.Compared with IM program, gPGA can achieve up to 52.30X speedup on one GPU. The evaluation results demonstrate that it allows datasets to be analyzed effectively and rapidly for research on divergence population genetics. The software is freely available with source code at https://github.com/chunbaozhou/gPGA.

Genetic Sample Inventory

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This database archives genetic tissue samples from marine mammals collected primarily from the U.S. east coast. The collection includes samples from field programs,...

DETECTION OF MENDELIAN AND GENOTYPE FREQUENCY OF GROWTH HORMONE GENE IN ONGOLE CROSSBRED CATTLE MATED BY THE ARTIFICIAL INSEMINATION TECHNIQUE

Directory of Open Access Journals (Sweden)

U. Paputungan

2012-06-01

Full Text Available The objectives of this study were to detect the Mendelian mode inheritance of growth hormone (GH and to establish genotype frequency of GH gene in Ongole-crossbred cattle mated by the artificial insemination (AI technique. Total of 76 blood samples were collected from Ongole-crossbred cows and bulls (G0, and their progenies (G1 at the Tumaratas AI service center in North Sulawesi province, Indonesia. All blood samples were screened for the presence of GH locus using a PCR-RFLP method involving restricted enzyme Msp1 on 1.2 % of agarose gel. Data were analyzed using statistical program function in Excel XP. The results showed that GH locus using alleles of Msp1+ and Msp1- enzyme restriction in Ongole-crossbred cows and bulls was inherited to their Ongole-crossbred progenies following the Mendelian mode inheritance. This Mendelian inheritance generated by AI technique was not under genetic equilibrium for the Msp1 genotype frequencies in groups of G0 and G1. The breeding program using genotypes of bulls and cows (G0 for generating the genotype of GH Msp1 enzyme restriction by AI technique should be maintained to increase these various allele dispersion rates for breeding under genetic equilibrium of the Ongole-crossbred cattle population.

A genetic algorithm approach to recognition and data mining

Energy Technology Data Exchange (ETDEWEB)

Punch, W.F.; Goodman, E.D.; Min, Pei [Michigan State Univ., East Lansing, MI (United States)] [and others

1996-12-31

We review here our use of genetic algorithm (GA) and genetic programming (GP) techniques to perform {open_quotes}data mining,{close_quotes} the discovery of particular/important data within large datasets, by finding optimal data classifications using known examples. Our first experiments concentrated on the use of a K-nearest neighbor algorithm in combination with a GA. The GA selected weights for each feature so as to optimize knn classification based on a linear combination of features. This combined GA-knn approach was successfully applied to both generated and real-world data. We later extended this work by substituting a GP for the GA. The GP-knn could not only optimize data classification via linear combinations of features but also determine functional relationships among the features. This allowed for improved performance and new information on important relationships among features. We review the effectiveness of the overall approach on examples from biology and compare the effectiveness of the GA and GP.

The application of neutral network integrated with genetic algorithm and simulated annealing for the simulation of rare earths separation processes by the solvent extraction technique using EHEHPA agent

International Nuclear Information System (INIS)

Tran Ngoc Ha; Pham Thi Hong Ha

2003-01-01

In the present work, neutral network has been used for mathematically modeling equilibrium data of the mixture of two rare earth elements, namely Nd and Pr with PC88A agent. Thermo-genetic algorithm based on the idea of the genetic algorithm and the simulated annealing algorithm have been used in the training procedure of the neutral networks, giving better result in comparison with the traditional modeling approach. The obtained neutral network modeling the experimental data is further used in the computer program to simulate the solvent extraction process of two elements Nd and Pr. Based on this computer program, various optional schemes for the separation of Nd and Pr have been investigated and proposed. (author)

Application gives the technique the analytic tree in the evaluation the effectiveness programs to radiological protection

International Nuclear Information System (INIS)

Perez Gonzalez, F.; Perez Velazquez, R.S.; Fornet Rodriguez, O.; Mustelier Hechevarria, A.; Miller Clemente, A.

1998-01-01

In the work we develop the IAEA recommendations in the application the analytic tree as instrument for the evaluation the effectiveness the occupational radiological protection programs. Is reflected like it has been assimilated and converted that technique in daily work istruments in the evaluation process the security conditions in the institutions that apply the nuclear techniques with a view to its autorization on the part of the regulatory organ

Application of virtual reality technique to a radiation protection training program

International Nuclear Information System (INIS)

Hajek, Brian K.; Kang, Ki Doo; Shin, Yoo Jin; Lee, Yon Sik

2003-01-01

Using an Internet Virtual Reality (IVR) technique, a 3-dimensional (3-D) model for the radiation controlled area in a nuclear power plant was developed, and a feasibility study to develop a computational program to estimate radiation dose was performed. For this purpose, a pilot model with a dynamic function and bi-directional communication was developed. This model was enhanced from the existing 3-D single-directional communication. In this pilot model, a plant visitor needs to first pass a series of security checks. If the visitor enters the controlled area and approaches a radiation hazard area, alarms with a warning lamp will be initiated automatically. Throughout the test to connect this model from both domestic and international sites in various time zones, it has proven to perform well. Therefore, this model can be applied to broad fields as radiation protection procedures or radiation protection training with photographic data, and on-line dose assessment programs

Using GPS instruments and GIS techniques in data management for insect pest control programs

International Nuclear Information System (INIS)

2006-01-01

This interactive tutorial CD entitled 'Using GPS Instruments and GIS Techniques in Data Management for Insect Pest Control Programs' was developed by Micha silver of the Arava Development Co., Sapir, Israel, and includes step-by-step hands on lessons on the use of GPS/GIS in support of area-wide pest control operations

Genetic Manipulation of NK Cells for Cancer Immunotherapy: Techniques and Clinical Implications.

Science.gov (United States)

Carlsten, Mattias; Childs, Richard W

2015-01-01

Given their rapid and efficient capacity to recognize and kill tumor cells, natural killer (NK) cells represent a unique immune cell to genetically reprogram in an effort to improve the outcome of cell-based cancer immunotherapy. However, technical and biological challenges associated with gene delivery into NK cells have significantly tempered this approach. Recent advances in viral transduction and electroporation have now allowed detailed characterization of genetically modified NK cells and provided a better understanding for how these cells can be utilized in the clinic to optimize their capacity to induce tumor regression in vivo. Improving NK cell persistence in vivo via autocrine IL-2 and IL-15 stimulation, enhancing tumor targeting by silencing inhibitory NK cell receptors such as NKG2A, and redirecting tumor killing via chimeric antigen receptors, all represent approaches that hold promise in preclinical studies. This review focuses on available methods for genetic reprograming of NK cells and the advantages and challenges associated with each method. It also gives an overview of strategies for genetic reprograming of NK cells that have been evaluated to date and an outlook on how these strategies may be best utilized in clinical protocols. With the recent advances in our understanding of the complex biological networks that regulate the ability of NK cells to target and kill tumors in vivo, we foresee genetic engineering as an obligatory pathway required to exploit the full potential of NK-cell based immunotherapy in the clinic.

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.

Surrogate-Assisted Genetic Programming With Simplified Models for Automated Design of Dispatching Rules.

Science.gov (United States)

Nguyen, Su; Zhang, Mengjie; Tan, Kay Chen

2017-09-01

Automated design of dispatching rules for production systems has been an interesting research topic over the last several years. Machine learning, especially genetic programming (GP), has been a powerful approach to dealing with this design problem. However, intensive computational requirements, accuracy and interpretability are still its limitations. This paper aims at developing a new surrogate assisted GP to help improving the quality of the evolved rules without significant computational costs. The experiments have verified the effectiveness and efficiency of the proposed algorithms as compared to those in the literature. Furthermore, new simplification and visualisation approaches have also been developed to improve the interpretability of the evolved rules. These approaches have shown great potentials and proved to be a critical part of the automated design system.

A Computer Program for Simplifying Incompletely Specified Sequential Machines Using the Paull and Unger Technique

Science.gov (United States)

Ebersole, M. M.; Lecoq, P. E.

1968-01-01

This report presents a description of a computer program mechanized to perform the Paull and Unger process of simplifying incompletely specified sequential machines. An understanding of the process, as given in Ref. 3, is a prerequisite to the use of the techniques presented in this report. This process has specific application in the design of asynchronous digital machines and was used in the design of operational support equipment for the Mariner 1966 central computer and sequencer. A typical sequential machine design problem is presented to show where the Paull and Unger process has application. A description of the Paull and Unger process together with a description of the computer algorithms used to develop the program mechanization are presented. Several examples are used to clarify the Paull and Unger process and the computer algorithms. Program flow diagrams, program listings, and a program user operating procedures are included as appendixes.

Molecular markers to assess genetic diversity and mutant identifications in Jatropha curcas

International Nuclear Information System (INIS)

Azhar Mohamad; Yie Min Kwan; Fatin Mastura Derani; Abdul Rahim Harun

2010-01-01

Jatropha curcas (Linnaeus) belongs to the Euphorbiaceae family, is a multipurpose use, drought resistant and perennial plant. It is an economic important crop, which generates wide interest in understanding the genetic diversity of the species towards selection and breeding of superior genotypes. Jatropha accessions are closely related family species. Thus, better understanding of the effectiveness of the different DNA-based markers is an important step towards plant germplasm characterization and evaluation. It is becoming a prerequisite for more effective application of marker techniques in breeding programs. Inter-simple sequence repeats (ISSRs) has shown rapid, simple, reproducible and inexpensive means in molecular taxonomy, conservation breeding and genetic diversity analysis. These markers were used to understand diversity and differentiate amongst accessions of Jatropha population and mutant lines generated by acute gamma radiation. The ISSR for marker applications are essential to facilitate management, conservation and genetic improvement programs towards improvement of bio-diesel production and medication substances. A total of 62 ISSR primers were optimized for polymorphism evaluations on five foreign accessions (Africa, India, Myanmar, Indonesia, Thailand), nine local accessions and two mutants of Jatropha. Optimization was resulted 54 ISSR primers affirmative for the polymorphism evaluation study, which encountered 12 ISSR primers, showed significance polymorphism amongst the accessions and mutants. Marker derived from ISSR profiling is a powerful method for identification and molecular classification of Jatropha from accession to generated mutant varieties. (author)

The Potential of the Sterile Insect Technique and other Genetic Methods for Control of Malaria-Transmitting Mosquitoes. Report of a Consultants Meeting

International Nuclear Information System (INIS)

1996-01-01

This report updates information provided by a 1993 consultant group on the use of genetic methods for control of malaria-transmitting mosquitoes. Human malaria parasites of the genus Plasmodium are exclusively transmitted by mosquitoes of the genus Anopheles. Where these two groups co-exist, the transmission of the parasite to humans can create a major health problem. Malaria currently causes 2 million deaths world-wide and approximately 400 million clinical cases annually. There are ca. 15 major vector species and 30-40 vectors of lesser importance. This report considers the practicality of developing the sterile insect technique (SIT) or other genetic mechanisms in order to eradicate mosquito vectors from specific areas. This would interrupt transmission and eliminate malaria in those areas.

Protocols in human molecular genetics

National Research Council Canada - National Science Library

Mathew, Christopher G

1991-01-01

... sequences has led to the development of DNA fingerprinting. The application of these techniques to the study of the human genome has culminated in major advances such as the cloning of the cystic fibrosis gene, the construction of genetic linkage maps of each human chromosome, the mapping of many genes responsible for human inherited disorders, genet...

Knowledge of Genetics and Attitudes toward Genetic Testing among College Students in Saudi Arabia.

Science.gov (United States)

Olwi, Duaa; Merdad, Leena; Ramadan, Eman

2016-01-01

Genetic testing has been gradually permeating the practice of medicine. Health-care providers may be confronted with new genetic approaches that require genetically informed decisions which will be influenced by patients' knowledge of genetics and their attitudes toward genetic testing. This study assesses the knowledge of genetics and attitudes toward genetic testing among college students. A cross-sectional study was conducted using a multistage stratified sample of 920 senior college students enrolled at King Abdulaziz University, Saudi Arabia. Information regarding knowledge of genetics, attitudes toward genetic testing, and sociodemographic data were collected using a self-administered questionnaire. In general, students had a good knowledge of genetics but lacked some fundamentals of genetics. The majority of students showed positive attitudes toward genetic testing, but some students showed negative attitudes toward certain aspects of genetic testing such as resorting to abortion in the case of an untreatable major genetic defect in an unborn fetus. The main significant predictors of knowledge were faculty, gender, academic year, and some prior awareness of 'genetic testing'. The main significant predictors of attitudes were gender, academic year, grade point average, and some prior awareness of 'genetic testing'. The knowledge of genetics among college students was higher than has been reported in other studies, and the attitudes toward genetic testing were fairly positive. Genetics educational programs that target youths may improve knowledge of genetics and create a public perception that further supports genetic testing. © 2016 S. Karger AG, Basel.

Identifying genetic relatives without compromising privacy.

Science.gov (United States)

He, Dan; Furlotte, Nicholas A; Hormozdiari, Farhad; Joo, Jong Wha J; Wadia, Akshay; Ostrovsky, Rafail; Sahai, Amit; Eskin, Eleazar

2014-04-01

The development of high-throughput genomic technologies has impacted many areas of genetic research. While many applications of these technologies focus on the discovery of genes involved in disease from population samples, applications of genomic technologies to an individual's genome or personal genomics have recently gained much interest. One such application is the identification of relatives from genetic data. In this application, genetic information from a set of individuals is collected in a database, and each pair of individuals is compared in order to identify genetic relatives. An inherent issue that arises in the identification of relatives is privacy. In this article, we propose a method for identifying genetic relatives without compromising privacy by taking advantage of novel cryptographic techniques customized for secure and private comparison of genetic information. We demonstrate the utility of these techniques by allowing a pair of individuals to discover whether or not they are related without compromising their genetic information or revealing it to a third party. The idea is that individuals only share enough special-purpose cryptographically protected information with each other to identify whether or not they are relatives, but not enough to expose any information about their genomes. We show in HapMap and 1000 Genomes data that our method can recover first- and second-order genetic relationships and, through simulations, show that our method can identify relationships as distant as third cousins while preserving privacy.

Solving a multi-objective location routing problem for infectious waste disposal using hybrid goal programming and hybrid genetic algorithm

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Narong Wichapa

2018-01-01

Full Text Available Infectious waste disposal remains one of the most serious problems in the medical, social and environmental domains of almost every country. Selection of new suitable locations and finding the optimal set of transport routes for a fleet of vehicles to transport infectious waste material, location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Determining locations for infectious waste disposal is a difficult and complex process, because it requires combining both intangible and tangible factors. Additionally, it depends on several criteria and various regulations. This facility location problem for infectious waste disposal is complicated, and it cannot be addressed using any stand-alone technique. Based on a case study, 107 hospitals and 6 candidate municipalities in Upper-Northeastern Thailand, we considered criteria such as infrastructure, geology and social & environmental criteria, evaluating global priority weights using the fuzzy analytical hierarchy process (Fuzzy AHP. After that, a new multi-objective facility location problem model which hybridizes fuzzy AHP and goal programming (GP, namely the HGP model, was tested. Finally, the vehicle routing problem (VRP for a case study was formulated, and it was tested using a hybrid genetic algorithm (HGA which hybridizes the push forward insertion heuristic (PFIH, genetic algorithm (GA and three local searches including 2-opt, insertion-move and interexchange-move. The results show that both the HGP and HGA can lead to select new suitable locations and to find the optimal set of transport routes for vehicles delivering infectious waste material. The novelty of the proposed methodologies, HGP, is the simultaneous combination of relevant factors that are difficult to interpret and cost factors in order to determine new suitable locations, and HGA can be applied to determine the transport routes which provide a minimum number of vehicles

Efficient Feedforward Linearization Technique Using Genetic Algorithms for OFDM Systems

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García Paloma

2010-01-01

Full Text Available Feedforward is a linearization method that simultaneously offers wide bandwidth and good intermodulation distortion suppression; so it is a good choice for Orthogonal Frequency Division Multiplexing (OFDM systems. Feedforward structure consists of two loops, being necessary an accurate adjustment between them along the time, and when temperature, environmental, or operating changes are produced. Amplitude and phase imbalances of the circuit elements in both loops produce mismatched effects that lead to degrade its performance. A method is proposed to compensate these mismatches, introducing two complex coefficients calculated by means of a genetic algorithm. A full study is carried out to choose the optimal parameters of the genetic algorithm applied to wideband systems based on OFDM technologies, which are very sensitive to nonlinear distortions. The method functionality has been verified by means of simulation.

Genetic parameters in a Swine Population

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Dana Popa

2010-05-01

Full Text Available The estimation of the variance-covariance components is a very important step in animal breeding because these components are necessary for: estimation of the genetic parameters, prediction of the breeding value and design of animal breeding programs. The estimation of genetic parameters is the first step in the development of a swine breeding program, using artificial insemination. Various procedures exist for estimation of heritability. There are three major procedures used for estimating heritability: analysis of variance (ANOVA, parents-offspring regression and restricted maximum likelihood (REML. By using ANOVA methodology or regression method it is possible to obtain aberrant values of genetic parameters (negative or over unit value of heritability coefficient, for example which can not be interpreting because is out of biological limits.

Application of Fluorescence In Situ Hybridization (FISH) Technique for the Detection of Genetic Aberration in Medical Science

Science.gov (United States)

Ratan, Zubair Ahmed; Zaman, Sojib Bin; Haidere, Mohammad Faisal; Runa, Nusrat Jahan; Akter, Nasrin

2017-01-01

Fluorescence in situ hybridization (FISH) is a macromolecule recognition technique, which is considered as a new advent in the field of cytology. Initially, it was developed as a physical mapping tool to delineate genes within chromosomes. The accuracy and versatility of FISH were subsequently capitalized upon in biological and medical research. This visually appealing technique provides an intermediate degree of resolution between DNA analysis and chromosomal investigations. FISH consists of a hybridizing DNA probe, which can be labeled directly or indirectly. In the case of direct labeling, fluorescent nucleotides are used, while indirect labeling is incorporated with reporter molecules that are subsequently detected by fluorescent antibodies or other affinity molecules. FISH is applied to detect genetic abnormalities that include different characteristic gene fusions or the presence of an abnormal number of chromosomes in a cell or loss of a chromosomal region or a whole chromosome. It is also applied in different research applications, such as gene mapping or the identification of novel oncogenes. This article reviews the concept of FISH, its application, and its advantages in medical science.  PMID:28690958

A Robust Computational Technique for Model Order Reduction of Two-Time-Scale Discrete Systems via Genetic Algorithms

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Othman M. K. Alsmadi

2015-01-01

Full Text Available A robust computational technique for model order reduction (MOR of multi-time-scale discrete systems (single input single output (SISO and multi-input multioutput (MIMO is presented in this paper. This work is motivated by the singular perturbation of multi-time-scale systems where some specific dynamics may not have significant influence on the overall system behavior. The new approach is proposed using genetic algorithms (GA with the advantage of obtaining a reduced order model, maintaining the exact dominant dynamics in the reduced order, and minimizing the steady state error. The reduction process is performed by obtaining an upper triangular transformed matrix of the system state matrix defined in state space representation along with the elements of B, C, and D matrices. The GA computational procedure is based on maximizing the fitness function corresponding to the response deviation between the full and reduced order models. The proposed computational intelligence MOR method is compared to recently published work on MOR techniques where simulation results show the potential and advantages of the new approach.

Guidelines for collecting and maintaining archives for genetic monitoring

Science.gov (United States)

Jennifer A. Jackson; Linda Laikre; C. Scott Baker; Katherine C. Kendall; F. W. Allendorf; M. K. Schwartz

2011-01-01

Rapid advances in molecular genetic techniques and the statistical analysis of genetic data have revolutionized the way that populations of animals, plants and microorganisms can be monitored. Genetic monitoring is the practice of using molecular genetic markers to track changes in the abundance, diversity or distribution of populations, species or ecosystems over time...

Genetic engineering applied to agriculture has a long row to hoe.

Science.gov (United States)

Miller, Henry I

2018-01-02

In spite of the lack of scientific justification for skepticism about crops modified with molecular techniques of genetic engineering, they have been the most scrutinized agricultural products in human history. The assumption that "genetically engineered" or "genetically modified" is a meaningful - and dangerous - classification has led to excessive and dilatory regulation. The modern molecular techniques are an extension, or refinement, of older, less precise, less predictable methods of genetic modification, but as long as today's activists and regulators remain convinced that so called "GMOs" represent a distinct and dangerous category of research and products, genetic engineering will fall short of its potential.

Status of biotechnology with emphasis on molecular techniques for mutation breeding in the Philippines

Energy Technology Data Exchange (ETDEWEB)

Lapade, A.G.; Nazarea, T.Y.; Veluz, A.M.S.; Marbella, L.J.; Nato, A.Q.; Coloma, C.B. Jr.; Asencion, A.B. [Philippine Nuclear Research Institute, Commonwealth Avenue, Quezon (Philippines)

2002-02-01

This paper summarizes the status of biotechnology with emphasis on molecular techniques for plant breeding in the Philippines. Several molecular and in-vitro culture techniques are integrated in plant breeding for crop improvement at PNRI, UPLB, IRRI and PhilRice. At IRRI, PCR techniques, RFLP and RAPD, PCR techniques, RFLP and RAPD were developed to establish high density molecular maps, determine breadth and diversity of germplasm and characterize alien introgression. The molecular maps have identified DNA sequence of resistance genes of HYVs and NPTs to abiotic and biotic stresses, the major achievement is the development of high density molecular maps in rice with at least 2000 markers. The biotechnology program at PhilRice for varietal improvement includes: (1) utilization of molecular marker technology such gene mapping of desired traits in rice, analysis of genetic relationships of germplasm materials and breeding lines through DNA fingerprinting and genetic diversity studies and development and application of marker aided selection for disease resistance (RTD and BLB); (2) application of in-vitro techniques in the development of lines with tolerance to adverse conditions; (3) molecular cloning of important genes for RTD resistance; (4) genetic transformation for male sterility and resistance to sheath blight and stem borers; and (5) transfer of disease resistance from wild species to cultivated varieties. In IPB, molecular markers:microsatellites or SSR, AFLP and RGA are being used for mapping and diversity studies in coconut, mango, banana, mungbean, corn and tomato. Mutation breeding at PNRI using gamma radiation has resulted in the development of crop varieties with desirable traits. The use of AFLP coupled to PCR is being used to study polymorphism in plant variants of radiation-induced mutants of rice, pineapple and ornamentals. (author)

Preimplantation Genetic Diagnosis: The Situation in France and in Other European Countries.

Science.gov (United States)

Duguet, Anne-Marie; Boyer-Beviere, Bénédicte

2017-04-01

Preimplantation genetic diagnosis (PGD) relates exclusively to in vitro fertilisation techniques (IVF) that aim to prevent transmission of a serious genetic abnormality to the child. The genetic characteristics of the embryo created through IVF are analysed, and only the embryos free of the genetic abnormality are implanted in the womb. Performed worldwide since 1990, this technique has raised many legal and ethical debates due to the very wide variations of lawgiving between countries. This is shown by the report of the UNESCO IBC (2003), which described the techniques and the issues raised by preimplantation genetic diagnosis. In this article, the authors present the differences between prenatal diagnosis and preimplantation genetic diagnosis, the French legislation, then the range of legislation in Europe and finally the position of the European Court of Human Rights which sanctioned Italy and Latvia for refusing access to PGD.

Use of the analytical tree technique to develop a radiological protection program

International Nuclear Information System (INIS)

Domenech N, H.; Jova S, L.

1996-01-01

The results obtained by the Cuban Center for Radiological Protection and Hygiene by using an analytical tree technique to develop its general operational radiation protection program are presented. By the application of this method, some factors such as the organization of the radiation protection services, the provision of administrative requirements, the existing general laboratories requirements, the viability of resources and the current documentation was evaluated. Main components were considered such as: complete normative and regulatory documentation; automatic radiological protection data management; scope of 'on the-job'and radiological protection training for the personnel; previous radiological appraisal for the safety performance of the works and application of dose constrains for the personnel and the public. The detailed development of the program allowed to identify the basic aims to be achieved in its maintenance and improvement. (authors). 3 refs

Selected topics from classical bacterial genetics.

Science.gov (United States)

Raleigh, Elisabeth A; Elbing, Karen; Brent, Roger

2002-08-01

Current cloning technology exploits many facts learned from classical bacterial genetics. This unit covers those that are critical to understanding the techniques described in this book. Topics include antibiotics, the LAC operon, the F factor, nonsense suppressors, genetic markers, genotype and phenotype, DNA restriction, modification and methylation and recombination.

Estimating Typhoon Rainfall over Sea from SSM/I Satellite Data Using an Improved Genetic Programming

Science.gov (United States)

Yeh, K.; Wei, H.; Chen, L.; Liu, G.

2010-12-01

Estimating Typhoon Rainfall over Sea from SSM/I Satellite Data Using an Improved Genetic Programming Keh-Chia Yeha, Hsiao-Ping Weia,d, Li Chenb, and Gin-Rong Liuc a Department of Civil Engineering, National Chiao Tung University, Hsinchu, Taiwan, 300, R.O.C. b Department of Civil Engineering and Engineering Informatics, Chung Hua University, Hsinchu, Taiwan, 300, R.O.C. c Center for Space and Remote Sensing Research, National Central University, Tao-Yuan, Taiwan, 320, R.O.C. d National Science and Technology Center for Disaster Reduction, Taipei County, Taiwan, 231, R.O.C. Abstract This paper proposes an improved multi-run genetic programming (GP) and applies it to predict the rainfall using meteorological satellite data. GP is a well-known evolutionary programming and data mining method, used to automatically discover the complex relationships among nonlinear systems. The main advantage of GP is to optimize appropriate types of function and their associated coefficients simultaneously. This study makes an improvement to enhance escape ability from local optimums during the optimization procedure. The GP continuously runs several times by replacing the terminal nodes at the next run with the best solution at the current run. The current novel model improves GP, obtaining a highly nonlinear mathematical equation to estimate the rainfall. In the case study, this improved GP described above combining with SSM/I satellite data is employed to establish a suitable method for estimating rainfall at sea surface during typhoon periods. These estimated rainfalls are then verified with the data from four rainfall stations located at Peng-Jia-Yu, Don-Gji-Dao, Lan-Yu, and Green Island, which are four small islands around Taiwan. From the results, the improved GP can generate sophisticated and accurate nonlinear mathematical equation through two-run learning procedures which outperforms the traditional multiple linear regression, empirical equations and back-propagated network

Boolean Queries Optimization by Genetic Algorithms

Czech Academy of Sciences Publication Activity Database

Húsek, Dušan; Owais, S.S.J.; Krömer, P.; Snášel, Václav

2005-01-01

Roč. 15, - (2005), s. 395-409 ISSN 1210-0552 R&D Projects: GA AV ČR 1ET100300414 Institutional research plan: CEZ:AV0Z10300504 Keywords : evolutionary algorithms * genetic algorithms * genetic programming * information retrieval * Boolean query Subject RIV: BB - Applied Statistics, Operational Research

Genetic diversity of Colletotrichum gloeosporioides in Nigeria using ...

African Journals Online (AJOL)

fmodupe

2012-04-24

Apr 24, 2012 ... gloeosporioides isolates and was effective in establishing genetic relationships ... Key words: Anthracnose disease, pathotypes, genetic diversity, amplified ..... isolates to use in an anthracnose resistance screening program.

Monthly streamflow forecasting using continuous wavelet and multi-gene genetic programming combination

Science.gov (United States)

Hadi, Sinan Jasim; Tombul, Mustafa

2018-06-01

Streamflow is an essential component of the hydrologic cycle in the regional and global scale and the main source of fresh water supply. It is highly associated with natural disasters, such as droughts and floods. Therefore, accurate streamflow forecasting is essential. Forecasting streamflow in general and monthly streamflow in particular is a complex process that cannot be handled by data-driven models (DDMs) only and requires pre-processing. Wavelet transformation is a pre-processing technique; however, application of continuous wavelet transformation (CWT) produces many scales that cause deterioration in the performance of any DDM because of the high number of redundant variables. This study proposes multigene genetic programming (MGGP) as a selection tool. After the CWT analysis, it selects important scales to be imposed into the artificial neural network (ANN). A basin located in the southeast of Turkey is selected as case study to prove the forecasting ability of the proposed model. One month ahead downstream flow is used as output, and downstream flow, upstream, rainfall, temperature, and potential evapotranspiration with associated lags are used as inputs. Before modeling, wavelet coherence transformation (WCT) analysis was conducted to analyze the relationship between variables in the time-frequency domain. Several combinations were developed to investigate the effect of the variables on streamflow forecasting. The results indicated a high localized correlation between the streamflow and other variables, especially the upstream. In the models of the standalone layout where the data were entered to ANN and MGGP without CWT, the performance is found poor. In the best-scale layout, where the best scale of the CWT identified as the highest correlated scale is chosen and enters to ANN and MGGP, the performance increased slightly. Using the proposed model, the performance improved dramatically particularly in forecasting the peak values because of the inclusion

Local Genetic Correlation Gives Insights into the Shared Genetic Architecture of Complex Traits.

Science.gov (United States)

Shi, Huwenbo; Mancuso, Nicholas; Spendlove, Sarah; Pasaniuc, Bogdan

2017-11-02

Although genetic correlations between complex traits provide valuable insights into epidemiological and etiological studies, a precise quantification of which genomic regions disproportionately contribute to the genome-wide correlation is currently lacking. Here, we introduce ρ-HESS, a technique to quantify the correlation between pairs of traits due to genetic variation at a small region in the genome. Our approach requires GWAS summary data only and makes no distributional assumption on the causal variant effect sizes while accounting for linkage disequilibrium (LD) and overlapping GWAS samples. We analyzed large-scale GWAS summary data across 36 quantitative traits, and identified 25 genomic regions that contribute significantly to the genetic correlation among these traits. Notably, we find 6 genomic regions that contribute to the genetic correlation of 10 pairs of traits that show negligible genome-wide correlation, further showcasing the power of local genetic correlation analyses. Finally, we report the distribution of local genetic correlations across the genome for 55 pairs of traits that show putative causal relationships. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Genetics and ecology of colonization and mass rearing of Hawaiian fruit flies (Diptera: Tephritidae) for use in sterile insect control programs

International Nuclear Information System (INIS)

Saul, S.H.; McCombs, S.D.

1995-01-01

It is critical to maintain the genetic, physiological and behavioral competence of colonized populations of insect species, such as fruit flies, which are reared for release in sterile insect and other genetic control programs. Selective pressures associated with the mass rearing process affect this competence, but the underlying mechanisms of genetic change arc largely unknown. However, competence is often an operational goal achieved by manipulating environmental factors without possessing precise genetic knowledge of alleles and their marginal effects on the desired traits. One goal of this paper is to show that the precise genetic and statistical analysis of components that determine competence in a broad sense or fitness in the narrower ecological sense, is extremely difficult. We can gel contradictory results from the different methods for estimating genetic variation in tephritid populations. We observe low levels of allozyme variation, but high levels of recessive mutants in inbred populations. We propose that genetic variability may be maintained in colonized and mass reared laboratory populations by balanced lethal systems and that the introduction of fresh genetic material may reduce, not increase, fitness. We require rigorous and precise models of directional selection in the laboratory and selective forces in the natural environment to aid our understanding of dynamic changes in courtship and mating behavior under artificial conditions. We have chosen to examine the lek model as an example of an idea whose usefulness has yet to be determined by test ing and validation. The inclusion of lek forming ability in genetic models will be depen dent on rigorously establishing the validity of the lek model for each tephritid species

Intra-Day Trading System Design Based on the Integrated Model of Wavelet De-Noise and Genetic Programming

Directory of Open Access Journals (Sweden)

Hongguang Liu

2016-12-01

Full Text Available Technical analysis has been proved to be capable of exploiting short-term fluctuations in financial markets. Recent results indicate that the market timing approach beats many traditional buy-and-hold approaches in most of the short-term trading periods. Genetic programming (GP was used to generate short-term trade rules on the stock markets during the last few decades. However, few of the related studies on the analysis of financial time series with genetic programming considered the non-stationary and noisy characteristics of the time series. In this paper, to de-noise the original financial time series and to search profitable trading rules, an integrated method is proposed based on the Wavelet Threshold (WT method and GP. Since relevant information that affects the movement of the time series is assumed to be fully digested during the market closed periods, to avoid the jumping points of the daily or monthly data, in this paper, intra-day high-frequency time series are used to fully exploit the short-term forecasting advantage of technical analysis. To validate the proposed integrated approach, an empirical study is conducted based on the China Securities Index (CSI 300 futures in the emerging China Financial Futures Exchange (CFFEX market. The analysis outcomes show that the wavelet de-noise approach outperforms many comparative models.

On Gene Concepts and Teaching Genetics: Episodes from Classical Genetics

Science.gov (United States)

Burian, Richard M.

2013-02-01

This paper addresses the teaching of advanced high school courses or undergraduate courses for non-biology majors about genetics or history of genetics. It will probably be difficult to take the approach described here in a high school science course, although the general approach could help improve such courses. It would be ideal for a college course in history of genetics or a course designed to teach non-science majors how science works or the rudiments of the genetics in a way that will help them as citizens. The approach aims to teach the processes of discovery, correction, and validation by utilizing illustrative episodes from the history of genetics. The episodes are treated in way that should foster understanding of basic questions about genes, the sorts of techniques used to answer questions about the constitution and structure of genes, how they function, and what they determine, and some of the major biological disagreements that arose in dealing with these questions. The material covered here could be connected to social and political issues raised by genetics, but these connections are not surveyed here. As it is, to cover this much territory, the article is limited to four major episodes from Mendel's paper to the beginning of World War II. A sequel will deal with the molecularization of genetics and with molecular gene concepts through the Human Genome Project.

The retinoblastoma protein regulates hypoxia-inducible genetic programs, tumor cell invasiveness and neuroendocrine differentiation in prostate cancer cells

Science.gov (United States)

Labrecque, Mark P.; Takhar, Mandeep K.; Nason, Rebecca; Santacruz, Stephanie; Tam, Kevin J.; Massah, Shabnam; Haegert, Anne; Bell, Robert H.; Altamirano-Dimas, Manuel; Collins, Colin C.; Lee, Frank J.S.; Prefontaine, Gratien G.; Cox, Michael E.; Beischlag, Timothy V.

2016-01-01

Loss of tumor suppressor proteins, such as the retinoblastoma protein (Rb), results in tumor progression and metastasis. Metastasis is facilitated by low oxygen availability within the tumor that is detected by hypoxia inducible factors (HIFs). The HIF1 complex, HIF1α and dimerization partner the aryl hydrocarbon receptor nuclear translocator (ARNT), is the master regulator of the hypoxic response. Previously, we demonstrated that Rb represses the transcriptional response to hypoxia by virtue of its association with HIF1. In this report, we further characterized the role Rb plays in mediating hypoxia-regulated genetic programs by stably ablating Rb expression with retrovirally-introduced short hairpin RNA in LNCaP and 22Rv1 human prostate cancer cells. DNA microarray analysis revealed that loss of Rb in conjunction with hypoxia leads to aberrant expression of hypoxia-regulated genetic programs that increase cell invasion and promote neuroendocrine differentiation. For the first time, we have established a direct link between hypoxic tumor environments, Rb inactivation and progression to late stage metastatic neuroendocrine prostate cancer. Understanding the molecular pathways responsible for progression of benign prostate tumors to metastasized and lethal forms will aid in the development of more effective prostate cancer therapies. PMID:27015368

Genetic diversity and phylogenetic relationship in different genotypes of cotton for future breeding

Directory of Open Access Journals (Sweden)

Jehan

2017-11-01

Full Text Available Background: To make the plants well adapted and more resistant to diseases and other environmental stresses there is always a need to improve the quality of plant’s genome i.e. to increase its genetic diversity. Methods: In the present study six variety and six lines of cotton were investigated for their genetic diversity and phylogenetic relationship. For this purpose 35 different RAPD primers obtained from the Gene Link Technologies, USA were used. Results: Among 35 RAPD primers, 13 primers produced reproducible PCR bands while the rest failed to show any amplification product. Our results indicated that the total count of the reproducible bands was 670 and polymorphic loci were counted to be 442 which constitute 66% of total loci. Phylogenetic analysis revealed two major groups each consists of 7 and 5 genotypes respectively. Genotypes Lp1 and Tp4 were placed at maximum genetic distance and in separate groups and could be utilized for future cotton breeding. Conclusions: RAPD analysis is a cheaper and time saving technique for the determination of genetic diversity of different cotton genotypes. Cotton genotype Lp1 and Tp4 could be the best candidates for future breeding programs as both genotypes are genetically distant from each other.

Isozymes and the genetic resources of forest trees

Science.gov (United States)

A. H. D. Brown; G. F. Moran

1981-01-01

Genetic data are an essential prerequisite for analysing the genetic structure of tree populations. The isozyme technique is the best currently available method for obtaining such data. Despite several shortcomings, isozyme data directly evaluate the genetic resources of forest trees, and can thus be used to monitor and manipulate these resources. For example,...

Chapter VIII. Contributions of propagation techniques and genetic modification to breeding - genetic engineering for disease resistance

Science.gov (United States)

Genetic engineering offers an opportunity to develop flower bulb crops with resistance to fungal, viral, and bacterial pathogens. Several of the flower bulb crops, Lilium spp., Gladiolus, Zantedeschia, Muscari, Hyacinthus, Narcissus, Ornithogalum, Iris, and Alstroemeria, have been transformed with t...

Genomic evidence for the population genetic differentiation of Misgurnus anguillicaudatus in the Yangtze River basin of China.

Science.gov (United States)

Yi, Shaokui; Wang, Weimin; Zhou, Xiaoyun

2018-02-21

Misgurnus anguillicaudatus, an important aquatic species, is mainly distributed in the Yangtze River basin. To reveal the population genetic structure of M. anguillicaudatus distributed in the Yangtze River basin, genotyping by sequencing (GBS) technique was employed to detect the genome wide genetic variations of M. anguillicaudatus. A total of 30.03 Gb raw data were yielded from 70 samples collected from 15 geographic sites located in the Yangtze River basin. Subsequently, 2092 high quality SNPs were genotyped across these samples and used for a series of genetic analysis. The results of genetic analysis showed that high levels of genetic diversity were observed and the populations from upper reaches (UR) were significantly differentiated from the middle and lower reaches (MLR) of Yangtze River basin. Meanwhile, no significant isolation by distance was detected among the populations. Ecological factors (e.g. complicated topography and climatic environment) and anthropogenic factors (e.g. aquaculture and agriculture cultivation) might account for the genetic disconnectivity between UR and MLR populations. This study provided valuable genetic data for the future breeding program and also for the conversation and scientific utilization of those abundant genetic resources stored in the Yangtze River basin. Copyright © 2018 Elsevier Inc. All rights reserved.

Evaluation of genetic diversity in different Pakistani wheat land races

International Nuclear Information System (INIS)

Mahmood, T.; Siddiqua, A.; Rasheed, A.; Nazar, N.

2011-01-01

Wheat is one of the main sources of nutrition worldwide. Genetic improvement of the seed makes wheat a source of high quality flour for human consumption and for other industrial uses. With the help of molecular markers, the available germplasm of wheat can be assessed for future breeding programs. Therefore, the aim of the present work was to analyze the genetic diversity among 15 Pakistani wheat land races based on Random Amplified Polymorphism DNA (RAPD) markers. A total of 284 DNA fragments were amplified, ranging in size from 200bp to 1100bp by using six primers. The number of DNA fragments for each primer varied from 2 (OPC-6) to 9 (OPC-8) with an average of 6 fragments per primer. Out of 284 amplified products, 120 were monomorphic and 137 were polymorphic showing an average of 7.8% polymorphism per primer. One specific marker was detected both for OPC-1 and OPC-8, two for OPC-5, while no RAPD specific marker was detected for the remaining primers. The genetic similarity index values ranged from 0.36 to 0.93, with an average of 0.64. Maximum genetic similarity (91%) was observed between Sur bej and Khushkawa. On the contrary, minimum genetic similarity (32%) was observed in Khushkaba-1 and Khushkawa. The dendrogram resulting from the NTSYS cluster analysis showed that the studied genotypes are divided into two main clusters from the same node. The first cluster contained 13 land races, while the second cluster contained only 2 land races. The dendrogram clustered the genotypes into 5 groups and showed efficiency in identifying genetic variability. These results indicated the usefulness of RAPD technique in estimating the genetic diversity among wheat genetic resources. (author)

Genetic analysis of Schizosaccharomyces pombe

DEFF Research Database (Denmark)

Ekwall, Karl; Thon, Genevieve

2017-01-01

In this introduction we discuss some basic genetic tools and techniques that are used with the fission yeast Schizosaccharomyces pombe. Genes commonly used for selection or as reporters are discussed, with an emphasis on genes that permit counterselection, intragenic complementation, or colony......-color assays. S. pombe is most stable as a haploid organism. We describe its mating-type system, how to perform genetic crosses and methods for selecting and propagating diploids. We discuss the relative merits of tetrad dissection and random spore preparation in strain construction and genetic analyses...

Complex polarimetric and spectral techniques in diagnostics of blood plasma of patients with ovarian cancer as a preliminary stage molecular genetic screening

Science.gov (United States)

Grzegorzewski, B.; Peresunko, O. P.; Yermolenko, S. B.

2018-01-01

This work is devoted to the substantiation and selection of patients with ovarian cancer (OC) for the purpose of conducting expensive molecular genetic studies on genotyping. As diagnostic methods have been used ultraviolet spectrometry samples of blood plasma in the liquid state, infrared spectroscopy middle range (2,5 - 25 microns) dry residue of plasma polarization and laser diagnostic technique of thin histological sections of biological tissues. Obtained results showed that the use of spectrophotometry in the range of 1000-3000 cm-1 allowed to establish quantitative parameters of the plasma absorption rate of blood of patients in the third group in different ranges, which would allow in the future to conduct an express analysis of the patient's condition (procedure screening) for further molecular-genetic typing on BRCA I and II.

Genetic sexing of the Mediterranean fruit fly

International Nuclear Information System (INIS)

1990-01-01

In the early 1980s, it was recognized by the FAO and the IAEA that a genetic sexing method for the Mediterranean fruit fly (medfly) would greatly improve the efficacy of the medfly sterile insect technique (SIT) and reduce its costs. These Proceedings summarize the research and development findings of the Agency's co-operators in the co-ordinated research programme to develop a genetic sexing method for the medfly. Great progress has been made in many aspects of medfly genetics. including the development of a number of genetic sexing strains. Contents: Genetics, Cytogenetics and Population Genetics. Genetic Sexing of Ceratitis Capitata by Morphological, Biochemical and other means. Recommendations. Refs, figs and tabs

Genetic methods for area-wide management of Lepidopterous pests with emphasis on F1 sterility

International Nuclear Information System (INIS)

Ocampo, V.R.

1996-01-01

Enormous losses in the production and marketing of food and fiber are caused by larvae of Lepidoptera. Currently, large quantities of insecticides are used to combat these pests. Insecticide resistance, increasing concern over pesticide pollution, and the desire to effectively manage lepidopteran pests on an area-wide basis have motivated scientists to identify and develop new pest management tactics that are compatible with current IPM. Genetic methods have emerged as a promising control strategy for lepidopteran pests. Genetic control as a practical means of pest management was first successfully implemented by Knipling and colleagues in the USA during the 1960's with the sterile insect technique (SIT) program for the screwworm fly. SIT is not a readily adapted for use against Lepidoptera as against Diptera. Radiation-induced inherited sterility (or F 1 sterility) is generally considered the most promising genetic methods for large-scale suppression of lepidopteran populations. This papers discusses four genetic control methods that have been developed and the progress that has been made in integrating sterility with other IPM tactics. (author)

The use of recombinant DNA techniques to study radiation-induced damage, repair and genetic change in mammalian cells

International Nuclear Information System (INIS)

Thacker, J.

1986-01-01

A brief introduction is given to appropriate elements of recombinant DNA techniques and applications to problems in radiobiology are reviewed with illustrative detail. Examples are included of studies with both 254 nm ultraviolet light and ionizing radiation and the review progresses from the molecular analysis of DNA damage in vitro through to the nature of consequent cellular responses. The review is dealt with under the following headings: Molecular distribution of DNA damage, The use of DNA-mediated gene transfer to assess damage and repair, The DNA double strand break: use of restriction endonucleases to model radiation damage, Identification and cloning of DNA repair genes, Analysis of radiation-induced genetic change. (UK)

An Interactive Learning Environment for Teaching the Imperative and Object-Oriented Programming Techniques in Various Learning Contexts

Science.gov (United States)

Xinogalos, Stelios

The acquisition of problem-solving and programming skills in the era of knowledge society seems to be particularly important. Due to the intrinsic difficulty of acquiring such skills various educational tools have been developed. Unfortunately, most of these tools are not utilized. In this paper we present the programming microworlds Karel and objectKarel that support the procedural-imperative and Object-Oriented Programming (OOP) techniques and can be used for supporting the teaching and learning of programming in various learning contexts and audiences. The paper focuses on presenting the pedagogical features that are common to both environments and mainly on presenting the potential uses of these environments.

Problem solving with genetic algorithms and Splicer

Science.gov (United States)

Bayer, Steven E.; Wang, Lui

1991-01-01

Genetic algorithms are highly parallel, adaptive search procedures (i.e., problem-solving methods) loosely based on the processes of population genetics and Darwinian survival of the fittest. Genetic algorithms have proven useful in domains where other optimization techniques perform poorly. The main purpose of the paper is to discuss a NASA-sponsored software development project to develop a general-purpose tool for using genetic algorithms. The tool, called Splicer, can be used to solve a wide variety of optimization problems and is currently available from NASA and COSMIC. This discussion is preceded by an introduction to basic genetic algorithm concepts and a discussion of genetic algorithm applications.

The Analysis of Polyploid Genetic Data.

Science.gov (United States)

Meirmans, Patrick G; Liu, Shenglin; van Tienderen, Peter H

2018-03-16

Though polyploidy is an important aspect of the evolutionary genetics of both plants and animals, the development of population genetic theory of polyploids has seriously lagged behind that of diploids. This is unfortunate since the analysis of polyploid genetic data-and the interpretation of the results-requires even more scrutiny than with diploid data. This is because of several polyploidy-specific complications in segregation and genotyping such as tetrasomy, double reduction, and missing dosage information. Here, we review the theoretical and statistical aspects of the population genetics of polyploids. We discuss several widely used types of inferences, including genetic diversity, Hardy-Weinberg equilibrium, population differentiation, genetic distance, and detecting population structure. For each, we point out how the statistical approach, expected result, and interpretation differ between different ploidy levels. We also discuss for each type of inference what biases may arise from the polyploid-specific complications and how these biases can be overcome. From our overview, it is clear that the statistical toolbox that is available for the analysis of genetic data is flexible and still expanding. Modern sequencing techniques will soon be able to overcome some of the current limitations to the analysis of polyploid data, though the techniques are lagging behind those available for diploids. Furthermore, the availability of more data may aggravate the biases that can arise, and increase the risk of false inferences. Therefore, simulations such as we used throughout this review are an important tool to verify the results of analyses of polyploid genetic data.

Analysis of behavioral change techniques in community-led total sanitation programs.

Science.gov (United States)

Sigler, Rachel; Mahmoudi, Lyana; Graham, Jay Paul

2015-03-01

The lack of sanitation facilitates the spread of diarrheal diseases-a leading cause of child deaths worldwide. As of 2012, an estimated 1 billion people still practiced open defecation (OD). To address this issue, one behavioral change approach used is community-led total sanitation (CLTS). It is now applied in an estimated 66 countries worldwide, and many countries have adopted this approach as their main strategy for scaling up rural sanitation coverage. While it appears that many of the activities used in CLTS-that target community-level changes in sanitation behaviors instead of household-level changes-have evolved out of existing behavior change frameworks and techniques, it is less clear how these activities are adapted by different organizations and applied in different country contexts. The aims of this study are to (i) show which behavior change frameworks and techniques are the most common in CLTS interventions; (ii) describe how activities are implemented in CLTS interventions by region and context; and (3) determine which activities program implementers considered the most valuable in achieving open defecation free (ODF) status and sustaining it. The results indicate that a wide range of activities are conducted across the different programs and often go beyond standard CLTS activities. CLTS practitioners ranked follow-up and monitoring activities as the most important activities for achieving an ODF community, yet only 1 of 10 organizations conducted monitoring and follow-up throughout their project. Empirical studies are needed to determine which specific behavioral change activities are most effective at ending OD and sustaining it. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

High genetic diversity of Jatropha curcas assessed by ISSR.

Science.gov (United States)

Díaz, B G; Argollo, D M; Franco, M C; Nucci, S M; Siqueira, W J; de Laat, D M; Colombo, C A

2017-05-31

Jatropha curcas L. is a highly promising oilseed for sustainable production of biofuels and bio-kerosene due to its high oil content and excellent quality. However, it is a perennial and incipiently domesticated species with none stable cultivar created until now despite genetic breeding programs in progress in several countries. Knowledge of the genetic structure and diversity of the species is a necessary step for breeding programs. The molecular marker can be used as a tool for speed up the process. This study was carried out to assess genetic diversity of a germplasm bank represented by J. curcas accessions from different provenance beside interspecific hybrid and backcrosses generated by IAC breeding programs using inter-simple sequence repeat markers. The molecular study revealed 271 bands of which 98.9% were polymorphic with an average of 22.7 polymorphic bands per primer. Genetic diversity of the germplasm evaluated was slightly higher than other germplasm around the world and ranged from 0.55 to 0.86 with an average of 0.59 (Jaccard index). Cluster analysis (UPGMA) revealed no clear grouping as to the geographical origin of accessions, consistent with genetic structure analysis using the Structure software. For diversity analysis between groups, accessions were divided into eight groups by origin. Nei's genetic distance between groups was 0.14. The results showed the importance of Mexican accessions, congeneric wild species, and interspecific hybrids for conservation and development of new genotypes in breeding programs.

Laboratory colonisation and genetic bottlenecks in the tsetse fly Glossina pallidipes.

Directory of Open Access Journals (Sweden)

Marc Ciosi

2014-02-01

Full Text Available The IAEA colony is the only one available for mass rearing of Glossina pallidipes, a vector of human and animal African trypanosomiasis in eastern Africa. This colony is the source for Sterile Insect Technique (SIT programs in East Africa. The source population of this colony is unclear and its genetic diversity has not previously been evaluated and compared to field populations.We examined the genetic variation within and between the IAEA colony and its potential source populations in north Zimbabwe and the Kenya/Uganda border at 9 microsatellites loci to retrace the demographic history of the IAEA colony. We performed classical population genetics analyses and also combined historical and genetic data in a quantitative analysis using Approximate Bayesian Computation (ABC. There is no evidence of introgression from the north Zimbabwean population into the IAEA colony. Moreover, the ABC analyses revealed that the foundation and establishment of the colony was associated with a genetic bottleneck that has resulted in a loss of 35.7% of alleles and 54% of expected heterozygosity compared to its source population. Also, we show that tsetse control carried out in the 1990's is likely reduced the effective population size of the Kenya/Uganda border population.All the analyses indicate that the area of origin of the IAEA colony is the Kenya/Uganda border and that a genetic bottleneck was associated with the foundation and establishment of the colony. Genetic diversity associated with traits that are important for SIT may potentially have been lost during this genetic bottleneck which could lead to a suboptimal competitiveness of the colony males in the field. The genetic diversity of the colony is lower than that of field populations and so, studies using colony flies should be interpreted with caution when drawing general conclusions about G. pallidipes biology.

Novel Techniques and Their Wide Applications to Health Foods, Medical and Agricultural Biotechnology in Relation to Policy Making on Genetically Modified Crops and Foods

CERN Document Server

Baianu, I C; Lozano, P; Lin, H C

2004-01-01

Selected applications of novel techniques in Agricultural Biotechnology, Health Food formulations and Medical Biotechnology are being reviewed with the aim of unraveling future developments and policy changes that are likely to open new markets for Biotechnology and prevent the shrinking or closing of existing ones. Amongst the selected novel techniques with applications in both Agricultural and Medical Biotechnology are: immobilized bacterial cells and enzymes, microencapsulation and liposome production, genetic manipulation of microorganisms, development of novel vaccines from plants, epigenomics of mammalian cells and organisms, and biocomputational tools for molecular modeling related to disease and Bioinformatics. Both fundamental and applied aspects of the emerging new techniques are being discussed in relation to their anticipated, marked impact on future markets and present policy changes that are needed for success in either Agricultural or Medical Biotechnology. The novel techniques are illustrated ...

New techniques in quality assurance

International Nuclear Information System (INIS)

Fornicola, J.C.

1987-01-01

GPU Nuclear Corp. has a multifaceted quality assurance (QA) program. This program includes a comprehensive QA organization to help ensure its implementation. The QA organization employs various techniques in assuring quality at GPU Nuclear. These techniques not only include the typical QA/quality-control verification activities, i.e., QA engineering, quality control, and audits, but also include some new innovative techniques. Several new techniques have been developed for verifying activities. These techniques include monitoring and functional audits of safety systems. Several new techniques for assessing performance and adequacy and effectiveness of plant and QA programs, such as plant assessments and QA systems engineering evaluations, have also been developed. This paper provides an overview of these and other new techniques being employed by GPU Nuclear's QA organization

A method for digital image registration using a mathematical programming technique

Science.gov (United States)

Yao, S. S.

1973-01-01

A new algorithm based on a nonlinear programming technique to correct the geometrical distortions of one digital image with respect to another is discussed. This algorithm promises to be superior to existing ones in that it is capable of treating localized differential scaling, translational and rotational errors over the whole image plane. A series of piece-wise 'rubber-sheet' approximations are used, constrained in such a manner that a smooth approximation over the entire image can be obtained. The theoretical derivation is included. The result of using the algorithm to register four channel S065 Apollo IX digitized photography over Imperial Valley, California, is discussed in detail.

Genetic engineering technology for the improvement of the sterile insect technique. Proceedings of a final research co-ordination meeting

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-01-01

Since the beginning of the joint FAO/IAEA programme on the research and development of insect pest control methodology, emphasis has been placed on the basic and applied aspects of implementing the sterile insect technique (SIT). Special emphasis has always been directed at the assembly of technological progress into workable systems that can be implemented in developing countries. The general intention is to solve problems associated with insect pests that have an adverse impact on production of food and fibre. For several insect species SIT has proven to be a powerful method for control. This includes the New World screwworm fly (Cochliomyia hominivorox), the Mediterranean fruit fly (Ceratitis capitata), the melon fly (Bactrocera cucurbitae), the Queensland fruit fly (Bactrocera tryoni) and one tsetse fly species (Glossina austeni). Improvements of the SIT are possible, especially through the use of molecular techniques. The final report of the Co-ordinated Research Programme on ``Genetic Engineering Technology for the Improvement of the Sterile Insect Technique`` highlights the progress made towards the development of transformation systems for non-drosophilid insects and the research aimed at the identification and engineering of potential target genes or traits. Refs, figs, tabs.

Genetic engineering technology for the improvement of the sterile insect technique. Proceedings of a final research co-ordination meeting

International Nuclear Information System (INIS)

1998-01-01

Since the beginning of the joint FAO/IAEA programme on the research and development of insect pest control methodology, emphasis has been placed on the basic and applied aspects of implementing the sterile insect technique (SIT). Special emphasis has always been directed at the assembly of technological progress into workable systems that can be implemented in developing countries. The general intention is to solve problems associated with insect pests that have an adverse impact on production of food and fibre. For several insect species SIT has proven to be a powerful method for control. This includes the New World screwworm fly (Cochliomyia hominivorox), the Mediterranean fruit fly (Ceratitis capitata), the melon fly (Bactrocera cucurbitae), the Queensland fruit fly (Bactrocera tryoni) and one tsetse fly species (Glossina austeni). Improvements of the SIT are possible, especially through the use of molecular techniques. The final report of the Co-ordinated Research Programme on ''Genetic Engineering Technology for the Improvement of the Sterile Insect Technique'' highlights the progress made towards the development of transformation systems for non-drosophilid insects and the research aimed at the identification and engineering of potential target genes or traits

An investigation of genetic algorithms

International Nuclear Information System (INIS)

Douglas, S.R.

1995-04-01

Genetic algorithms mimic biological evolution by natural selection in their search for better individuals within a changing population. they can be used as efficient optimizers. This report discusses the developing field of genetic algorithms. It gives a simple example of the search process and introduces the concept of schema. It also discusses modifications to the basic genetic algorithm that result in species and niche formation, in machine learning and artificial evolution of computer programs, and in the streamlining of human-computer interaction. (author). 3 refs., 1 tab., 2 figs

Genetic counselling in the beta-thalassaemias

Directory of Open Access Journals (Sweden)

Adonis S. Ioannides

2013-03-01

Full Text Available The beta-thalassaemias are very important genetic disorders of haemoglobin synthesis and are amongst the commonest monogenic disorders. In view of the severity of beta-thalassaemia major, a number of screening programmes have been developed aimed at reducing the number of individuals born with the condition. Genetic counsellingplays a vital role in this process supporting the successful implementation of screening and delineating available options to at risk individuals. This review assesses the contribution of genetic counsellingat each stage of this process in the context of new diagnostic techniques and therapeutic options and discusses some of the more challenging aspects such as genotype/ phenotype correlation and coinheritance of other genetic conditions or genetic modifiers.

Determination of the genetic structure of remnant Morus boninensis Koidz. trees to establish a conservation program on the Bonin Islands, Japan

Directory of Open Access Journals (Sweden)

Nobushima Fuyuo

2006-10-01

Full Text Available Abstract Background Morus boninensis, is an endemic plant of the Bonin (Ogasawara Islands of Japan and is categorized as "critically endangered" in the Japanese red data book. However, little information is available about its ecological, evolutionary and genetic status, despite the urgent need for guidelines for the conservation of the species. Therefore, we adopted Moritz's MU concept, based on the species' current genetic structure, to define management units and to select mother tree candidates for seed orchards. Results Nearly all individuals of the species were genotyped on the basis of seven microsatellite markers. Genetic diversity levels in putative natural populations were higher than in putative man-made populations with the exception of those on Otouto-jima Island. This is because a limited number of maternal trees are likely to have been used for seed collection to establish the man-made populations. A model-based clustering analysis clearly distinguished individuals into nine clusters, with a large difference in genetic composition between the population on Otouto-jima Island, the putative natural populations and the putative man-made populations. The Otouto-jima population appeared to be genetically differentiated from the others; a finding that was also supported by pairwise FST and RST analysis. Although multiple clusters were detected in the putative man-made populations, the pattern of genetic diversity was monotonous in comparison to the natural populations. Conclusion The genotyping by microsatellite markers revealed strong genetic structures. Typically, artificial propagation of this species has ignored the genetic structure, relying only on seeds from Otouto-jima for replanting on other islands, because of a problem with inter-specific hybridization on Chichi-jima and Haha-jima Islands. However, this study demonstrates that we should be taking into consideration the genetic structure of the species when designing a

Determination of the genetic structure of remnant Morus boninensis Koidz. trees to establish a conservation program on the Bonin Islands, Japan.

Science.gov (United States)

Tani, Naoki; Yoshimaru, Hiroshi; Kawahara, Takayuki; Hoshi, Yoshio; Nobushima, Fuyuo; Yasui, Takaya

2006-10-11

Morus boninensis, is an endemic plant of the Bonin (Ogasawara) Islands of Japan and is categorized as "critically endangered" in the Japanese red data book. However, little information is available about its ecological, evolutionary and genetic status, despite the urgent need for guidelines for the conservation of the species. Therefore, we adopted Moritz's MU concept, based on the species' current genetic structure, to define management units and to select mother tree candidates for seed orchards. Nearly all individuals of the species were genotyped on the basis of seven microsatellite markers. Genetic diversity levels in putative natural populations were higher than in putative man-made populations with the exception of those on Otouto-jima Island. This is because a limited number of maternal trees are likely to have been used for seed collection to establish the man-made populations. A model-based clustering analysis clearly distinguished individuals into nine clusters, with a large difference in genetic composition between the population on Otouto-jima Island, the putative natural populations and the putative man-made populations. The Otouto-jima population appeared to be genetically differentiated from the others; a finding that was also supported by pairwise FST and RST analysis. Although multiple clusters were detected in the putative man-made populations, the pattern of genetic diversity was monotonous in comparison to the natural populations. The genotyping by microsatellite markers revealed strong genetic structures. Typically, artificial propagation of this species has ignored the genetic structure, relying only on seeds from Otouto-jima for replanting on other islands, because of a problem with inter-specific hybridization on Chichi-jima and Haha-jima Islands. However, this study demonstrates that we should be taking into consideration the genetic structure of the species when designing a propagation program for the conservation of this species.

Global Optimization of a Periodic System using a Genetic Algorithm

Science.gov (United States)

Stucke, David; Crespi, Vincent

2001-03-01

We use a novel application of a genetic algorithm global optimizatin technique to find the lowest energy structures for periodic systems. We apply this technique to colloidal crystals for several different stoichiometries of binary and trinary colloidal crystals. This application of a genetic algorithm is decribed and results of likely candidate structures are presented.

Multiobjective Genetic Algorithm applied to dengue control.

Science.gov (United States)

Florentino, Helenice O; Cantane, Daniela R; Santos, Fernando L P; Bannwart, Bettina F

2014-12-01

Dengue fever is an infectious disease caused by a virus of the Flaviridae family and transmitted to the person by a mosquito of the genus Aedes aegypti. This disease has been a global public health problem because a single mosquito can infect up to 300 people and between 50 and 100 million people are infected annually on all continents. Thus, dengue fever is currently a subject of research, whether in the search for vaccines and treatments for the disease or efficient and economical forms of mosquito control. The current study aims to study techniques of multiobjective optimization to assist in solving problems involving the control of the mosquito that transmits dengue fever. The population dynamics of the mosquito is studied in order to understand the epidemic phenomenon and suggest strategies of multiobjective programming for mosquito control. A Multiobjective Genetic Algorithm (MGA_DENGUE) is proposed to solve the optimization model treated here and we discuss the computational results obtained from the application of this technique. Copyright © 2014 Elsevier Inc. All rights reserved.

Training techniques for industry

International Nuclear Information System (INIS)

Jones, D.W.

1978-01-01

The advantages and disadvantages of commonly used training techniques in relation to cost-effective, prevention-oriented Quality Assurance are examined. Important questions are whether training techniques teach cost effectiveness and whether the techniques are, themselves, cost effective. To answer these questions, criteria for evaluating teaching techniques for cost effectiveness were developd, and then commonly used techniques are evaluated in terms of specific training program objectives. Motivation of personnel is also considered important to the success of a training program, and methods are outlined by which recognition of the academic quality of industrial training can be used as a motivational technique

Assessment of the genetic diversity and pattern of relationship of ...

African Journals Online (AJOL)

An understanding of the extent, distribution and patterns of genetic variation is useful for estimation of any possible loss of genetic diversity and assessment of genetic variability and its potential use in breeding programs, including establishment of heterotic groups. This study assessed patterns of genetic diversity and ...

Testing of chemicals for genetic activity with Saccharomyces cerevisiae: a report of the U. S. Environmental Protection Agency Gene-Tox Program

Energy Technology Data Exchange (ETDEWEB)

Zimmermann, F.K.; von Borstel, R.C.; von Halle, E.S.; Parry, J.M.; Siebert, D.; Zetterberg, G.; Barale, R.; Loprieno, N.

1984-01-01

This review article with over 200 references summarizes the results of mutation screening tests with 492 chemicals using saccharomyces cerevisiae as the test organism. In addition, an extensive description of S. cerevisiae as a test organism is given. Yeast can be used to study genetic effects both in mitotic and in meiotic cells because it can be cultured as a stable haploid or a stable diploid. The most commonly used genetic endpoint has been mitotic recombination either as mitotic crossing-over or mitotic gene conversion. Data were available on tests with 492 chemicals, of which 249 were positive, as reported in 173 articles or reports. The genetic test/carcinogenicity accuracy was 0.74, based on the carcinogen listing established in the gene-tox program. The yeast tests supplement the bacterial tests for detecting agents that act via radical formation, antibacterial drugs, and other chemicals interfering with chromosome segregation and recombination processes.

Routes for breaching and protecting genetic privacy

OpenAIRE

Erlich, Yaniv; Narayanan, Arvind

2013-01-01

We are entering an era of ubiquitous genetic information for research, clinical care and personal curiosity. Sharing these datasets is vital for progress in biomedical research. However, one growing concern is the ability to protect the genetic privacy of the data originators. Here, we present an overview of genetic privacy breaching strategies. We outline the principles of each technique, point to the underlying assumptions, and assess its technological complexity and maturati...

A Novel Idea for Optimizing Condition-Based Maintenance Using Genetic Algorithms and Continuous Event Simulation Techniques

Directory of Open Access Journals (Sweden)

Mansoor Ahmed Siddiqui

2017-01-01

Full Text Available Effective maintenance strategies are of utmost significance for system engineering due to their direct linkage with financial aspects and safety of the plants’ operation. At a point where the state of a system, for instance, level of its deterioration, can be constantly observed, a strategy based on condition-based maintenance (CBM may be affected; wherein upkeep of the system is done progressively on the premise of monitored state of the system. In this article, a multicomponent framework is considered that is continuously kept under observation. In order to decide an optimal deterioration stage for the said system, Genetic Algorithm (GA technique has been utilized that figures out when its preventive maintenance should be carried out. The system is configured into a multiobjective problem that is aimed at optimizing the two desired objectives, namely, profitability and accessibility. For the sake of reality, a prognostic model portraying the advancements of deteriorating system has been employed that will be based on utilization of continuous event simulation techniques. In this regard, Monte Carlo (MC simulation has been shortlisted as it can take into account a wide range of probable options that can help in reducing uncertainty. The inherent benefits proffered by the said simulation technique are fully utilized to display various elements of a deteriorating system working under stressed environment. The proposed synergic model (GA and MC is considered to be more effective due to the employment of “drop-by-drop approach” that permits successful drive of the related search process with regard to the best optimal solutions.

Genetic Diversity in Commercial Rapeseed (Brassica napus L. Varieties from Turkey as Revealed by RAPD

Directory of Open Access Journals (Sweden)

Özlem ÖZBEK

2013-02-01

Full Text Available In cultivated commercial crop species, genetic diversity tends to decrease because of the extensive breeding processes. Therefore, germplasm of commercial crop species, such as Brassica napus L. should be evaluated and the genotypes, which have higher genetic diversity index, should be addressed as potential parental cross materials in breeding programs. In this study, the genetic diversity was analysed by using randomly amplified polymorphic DNA analysis (RAPD technique in nine Turkish commercial rapeseed varieties. The RAPD primers (10-mer oligonucleotides produced 51 scorable loci, 31 loci of which were polymorphic (60.78% and 20 loci (39.22% were monomorphic The RAPD bands were scored as binary matrix data and were analysed using POPGENE version 1.32. At locus level, the values of genetic diversity within population (Hs and total (HT were 0.15 and 0.19 respectively. The genetic differentiation (GST and the gene flow (Nm values between the populations were 0.20 and 2.05 respectively. The mean number of alleles (na, the mean number of effective alleles (nae, and the mean value of genetic diversity (He were 2.00, 1.26, and 0.19 respectively. According to Pearson’s correlation, multiple regression and principal component analyses, eco-geographical conditions in combination had significant effect on genetic indices of commercial B. napus L. varieties were discussed.

Simplification of genotyping techniques of the ABO blood type experiment and exploration of population genetics.

Science.gov (United States)

Hu, Jian; Zhou, Yi-ren; Ding, Jia-lin; Wang, Zhi-yuan; Liu, Ling; Wang, Ye-kai; Lou, Hui-ling; Qiao, Shou-yi; Wu, Yan-hua

2017-05-20

The ABO blood type is one of the most common and widely used genetic traits in humans. Three glycosyltransferase-encoding gene alleles, I A , I B and i, produce three red blood cell surface antigens, by which the ABO blood type is classified. By using the ABO blood type experiment as an ideal case for genetics teaching, we can easily introduce to the students several genetic concepts, including multiple alleles, gene interaction, single nucleotide polymorphism (SNP) and gene evolution. Herein we have innovated and integrated our ABO blood type genetics experiments. First, in the section of Molecular Genetics, a new method of ABO blood genotyping was established: specific primers based on SNP sites were designed to distinguish three alleles through quantitative real-time PCR. Next, the experimental teaching method of Gene Evolution was innovated in the Population Genetics section: a gene-evolution software was developed to simulate the evolutionary tendency of the ABO genotype encoding alleles under diverse conditions. Our reform aims to extend the contents of genetics experiments, to provide additional teaching approaches, and to improve the learning efficiency of our students eventually.

GPU Pro advanced rendering techniques

CERN Document Server

Engel, Wolfgang

2010-01-01

This book covers essential tools and techniques for programming the graphics processing unit. Brought to you by Wolfgang Engel and the same team of editors who made the ShaderX series a success, this volume covers advanced rendering techniques, engine design, GPGPU techniques, related mathematical techniques, and game postmortems. A special emphasis is placed on handheld programming to account for the increased importance of graphics on mobile devices, especially the iPhone and iPod touch.Example programs and source code can be downloaded from the book's CRC Press web page. 

Whole genome amplification in preimplantation genetic diagnosis*

Science.gov (United States)

Zheng, Ying-ming; Wang, Ning; Li, Lei; Jin, Fan

2011-01-01

Preimplantation genetic diagnosis (PGD) refers to a procedure for genetically analyzing embryos prior to implantation, improving the chance of conception for patients at high risk of transmitting specific inherited disorders. This method has been widely used for a large number of genetic disorders since the first successful application in the early 1990s. Polymerase chain reaction (PCR) and fluorescent in situ hybridization (FISH) are the two main methods in PGD, but there are some inevitable shortcomings limiting the scope of genetic diagnosis. Fortunately, different whole genome amplification (WGA) techniques have been developed to overcome these problems. Sufficient DNA can be amplified and multiple tasks which need abundant DNA can be performed. Moreover, WGA products can be analyzed as a template for multi-loci and multi-gene during the subsequent DNA analysis. In this review, we will focus on the currently available WGA techniques and their applications, as well as the new technical trends from WGA products. PMID:21194180

The use of genetic programming in the analysis of quantitative gene expression profiles for identification of nodal status in bladder cancer

International Nuclear Information System (INIS)

Mitra, Anirban P; Almal, Arpit A; George, Ben; Fry, David W; Lenehan, Peter F; Pagliarulo, Vincenzo; Cote, Richard J; Datar, Ram H; Worzel, William P

2006-01-01

Previous studies on bladder cancer have shown nodal involvement to be an independent indicator of prognosis and survival. This study aimed at developing an objective method for detection of nodal metastasis from molecular profiles of primary urothelial carcinoma tissues. The study included primary bladder tumor tissues from 60 patients across different stages and 5 control tissues of normal urothelium. The entire cohort was divided into training and validation sets comprised of node positive and node negative subjects. Quantitative expression profiling was performed for a panel of 70 genes using standardized competitive RT-PCR and the expression values of the training set samples were run through an iterative machine learning process called genetic programming that employed an N-fold cross validation technique to generate classifier rules of limited complexity. These were then used in a voting algorithm to classify the validation set samples into those associated with or without nodal metastasis. The generated classifier rules using 70 genes demonstrated 81% accuracy on the validation set when compared to the pathological nodal status. The rules showed a strong predilection for ICAM1, MAP2K6 and KDR resulting in gene expression motifs that cumulatively suggested a pattern ICAM1>MAP2K6>KDR for node positive cases. Additionally, the motifs showed CDK8 to be lower relative to ICAM1, and ANXA5 to be relatively high by itself in node positive tumors. Rules generated using only ICAM1, MAP2K6 and KDR were comparably robust, with a single representative rule producing an accuracy of 90% when used by itself on the validation set, suggesting a crucial role for these genes in nodal metastasis. Our study demonstrates the use of standardized quantitative gene expression values from primary bladder tumor tissues as inputs in a genetic programming system to generate classifier rules for determining the nodal status. Our method also suggests the involvement of ICAM1, MAP2K6, KDR

Population genetics of commercial and feral honey bees in Western Australia.

Science.gov (United States)

Chapman, Nadine C; Lim, Julianne; Oldroyd, Benjamin P

2008-04-01

Due to the introduction of exotic honey bee (Apis mellifera L.) diseases in the eastern states, the borders of the state of Western Australia were closed to the import of bees for breeding and other purposes > 25 yr ago. To provide genetically improved stock for the industry, a closed population breeding program was established that now provides stock for the majority of Western Australian beekeepers. Given concerns that inbreeding may have resulted from the closed population breeding structure, we assessed the genetic diversity within and between the breeding lines by using microsatellite and mitochondrial markers. We found that the breeding population still maintains considerable genetic diversity, despite 25 yr of selective breeding. We also investigated the genetic distance of the closed population breeding program to that of beekeepers outside of the program, and the feral Western Australian honey bee population. The feral population is genetically distinct from the closed population, but not from the genetic stock maintained by beekeepers outside of the program. The honey bees of Western Australia show three mitotypes, originating from two subspecies: Apis mellifera ligustica (mitotypes C1 and M7b) and Apis mellifera iberica (mitotype M6). Only mitotypes C1 and M6 are present in the commercial populations. The feral population contains all three mitotypes.

Evaluating the Accreditation Council on Graduate Medical Education core clinical competencies: techniques and feasibility in a urology training program.

Science.gov (United States)

Miller, David C; Montie, James E; Faerber, Gary J

2003-10-01

We describe several traditional and novel techniques for teaching and evaluating the Accreditation Council on Graduate Medical Education (ACGME) core clinical competencies in a urology residency training program. The evolution and underpinnings of the ACGME Outcome Project were reviewed. Several publications related to the evaluation of clinical competencies as well as current assessment techniques at our institution were also analyzed. Several tools for the assessment of clinical competencies have been developed and refined in response to the ACGME Outcome project. Standardized patient encounters and expanded patient satisfaction surveys may prove useful with regard to assessing resident professionalism, patient care and communication skills. A feasible and possibly undervalued technique for evaluating a number of core competencies is the implementation of formal written appraisals of the nature and quality of resident performance at departmental conferences. The assessment of competency in practice based learning and systems based practice may be achieved through innovative exercises, such as practice guideline development, that assess the evidence for various urologic interventions as well as the financial and administrative aspects of such care. We describe several contemporary methods for teaching and evaluating the core clinical competencies in a urology training program. While the techniques described are neither comprehensive nor feasible for every program, they nevertheless provide an important starting point for a meaningful exchange of ideas in the urological graduate medical education community.

Human Genetic Engineering: A Survey of Student Value Stances

Science.gov (United States)

Wilson, Sara McCormack; And Others

1975-01-01

Assesses the values of high school and college students relative to human genetic engineering and recommends that biology educators explore instructional strategies merging human genetic information with value clarification techniques. (LS)

Detection of Genetically Modified Sugarcane by Using Terahertz Spectroscopy and Chemometrics

Science.gov (United States)

Liu, J.; Xie, H.; Zha, B.; Ding, W.; Luo, J.; Hu, C.

2018-03-01

A methodology is proposed to identify genetically modified sugarcane from non-genetically modified sugarcane by using terahertz spectroscopy and chemometrics techniques, including linear discriminant analysis (LDA), support vector machine-discriminant analysis (SVM-DA), and partial least squares-discriminant analysis (PLS-DA). The classification rate of the above mentioned methods is compared, and different types of preprocessing are considered. According to the experimental results, the best option is PLS-DA, with an identification rate of 98%. The results indicated that THz spectroscopy and chemometrics techniques are a powerful tool to identify genetically modified and non-genetically modified sugarcane.

Combining Diffusion Models and Macroeconomic Indicators with a Modified Genetic Programming Method: Implementation in Forecasting the Number of Mobile Telecommunications Subscribers in OECD Countries

Directory of Open Access Journals (Sweden)

Konstantinos Salpasaranis

2014-01-01

Full Text Available This paper proposes a modified Genetic Programming method for forecasting the mobile telecommunications subscribers’ population. The method constitutes an expansion of the hybrid Genetic Programming (hGP method improved by the introduction of diffusion models for technological forecasting purposes in the initial population, such as the Logistic, Gompertz, and Bass, as well as the Bi-Logistic and LogInLog. In addition, the aforementioned functions and models expand the function set of hGP. The application of the method in combination with macroeconomic indicators such as Gross Domestic Product per Capita (GDPpC and Consumer Prices Index (CPI leads to the creation of forecasting models and scenarios for medium- and long-term level of predictability. The forecasting module of the program has also been improved with the multi-levelled use of the statistical indices as fitness functions and model selection indices. The implementation of the modified-hGP in the datasets of mobile subscribers in the Organisation for Economic Cooperation and Development (OECD countries shows very satisfactory forecasting performance.

Privacy and confidentiality measures in genetic testing and counselling: arguing on genetic exceptionalism again?

Science.gov (United States)

Witt, Magdalena M; Witt, Michał P

2016-11-01

Medical confidentiality in clinical genetics poses an important question about its scope, which would be in line with professional ethics and simple honesty. It is already known that the maintenance of absolute anonymity, bearing in mind the current progress of genetic techniques, is virtually impossible. On the other hand, our insight into the information contained in the human genome is increasing. This mini-review presents the authors' standpoint regarding this complex and difficult issue.

Time-Delay System Identification Using Genetic Algorithm

DEFF Research Database (Denmark)

Yang, Zhenyu; Seested, Glen Thane

2013-01-01

Due to the unknown dead-time coefficient, the time-delay system identification turns to be a non-convex optimization problem. This paper investigates the identification of a simple time-delay system, named First-Order-Plus-Dead-Time (FOPDT), by using the Genetic Algorithm (GA) technique. The qual......Due to the unknown dead-time coefficient, the time-delay system identification turns to be a non-convex optimization problem. This paper investigates the identification of a simple time-delay system, named First-Order-Plus-Dead-Time (FOPDT), by using the Genetic Algorithm (GA) technique...

Genetic and nutrition development of indigenous chicken in Africa

DEFF Research Database (Denmark)

Khobondo, J O; Muasya, T K; Miyumo, S

2015-01-01

This review gives insights into genetic and feeding regime development for indigenous chicken genetic resources. We highlight and combine confirming evidence of genetic diversity and variability using morphological and molecular techniques. We further discuss previous past and current genetic...... requirement for indigenous chicken and report nutritive contents of various local feedstuffs under various production systems. Various conservation strategies for sustainable utilization are hereby reviewed...

Genetic privacy in sports: clearing the hurdles.

Science.gov (United States)

Callier, Shawneequa

2012-12-01

As genomic medicine continues to advance and inform clinical care, knowledge gained is likely to influence sports medicine and training practices. Susceptibility to injury, sudden cardiac failure, and other serious conditions may one day be tackled on a subclinical level through genetic testing programs. In addition, athletes may increasingly consider using genetic testing services to maximize their performance potential. This paper assesses the role of privacy and genetic discrimination laws that would apply to athletes who engage in genetic testing and the limits of these protections.

Future possibilities in migraine genetics

DEFF Research Database (Denmark)

Rudkjøbing, Laura Aviaja; Esserlind, Ann-Louise; Olesen, Jes

2012-01-01

Migraine with and without aura (MA and MO, respectively) have a strong genetic basis. Different approaches using linkage-, candidate gene- and genome-wide association studies have been explored, yielding limited results. This may indicate that the genetic component in migraine is due to rare...... variants; capturing these will require more detailed sequencing in order to be discovered. Next-generation sequencing (NGS) techniques such as whole exome and whole genome sequencing have been successful in finding genes in especially monogenic disorders. As the molecular genetics research progresses......, the technology will follow, rendering these approaches more applicable in the search for causative migraine genes in MO and MA. To date, no studies using NGS in migraine genetics have been published. In order to gain insight into the future possibilities of migraine genetics, we have looked at NGS studies...

Translocation-based genetic sexing system to enhance the sterile insect technique against the melon fly (Diptera: Tephritidae)

International Nuclear Information System (INIS)

McCombs, S.D.; Lee, S.G.; Saul, S.H.

1993-01-01

The autosomal recessive bubble wing (bw) mutant was used to construct a translocation-based genetic sex sorting system in the melon fly, Bactrocera cucurbitae (Coquillett). The translocation stock has females with the bubble wing phenotype that are unable to fly, but the males are wild-type and fly normally. The bubble wing translocation strain has lower egg hatch, larval viability, and eclosion rates than the wild-type strain. Expression of the bubble wing trait is temperature-dependent, with high expression of the trait in 92% of adults at 23°C but in only 15% of adults at 28°C. This translocation-based sex sorting system is the only method available for automatic separation of male and female melon flies in sterile insect release programs