On local search for bi-objective knapsack problems.

Science.gov (United States)

Liefooghe, Arnaud; Paquete, Luís; Figueira, José Rui

2013-01-01

In this article, a local search approach is proposed for three variants of the bi-objective binary knapsack problem, with the aim of maximizing the total profit and minimizing the total weight. First, an experimental study on a given structural property of connectedness of the efficient set is conducted. Based on this property, a local search algorithm is proposed and its performance is compared to exact algorithms in terms of runtime and quality metrics. The experimental results indicate that this simple local search algorithm is able to find a representative set of optimal solutions in most of the cases, and in much less time than exact algorithms.

Stochastic search in structural optimization - Genetic algorithms and simulated annealing

Science.gov (United States)

Hajela, Prabhat

1993-01-01

An account is given of illustrative applications of genetic algorithms and simulated annealing methods in structural optimization. The advantages of such stochastic search methods over traditional mathematical programming strategies are emphasized; it is noted that these methods offer a significantly higher probability of locating the global optimum in a multimodal design space. Both genetic-search and simulated annealing can be effectively used in problems with a mix of continuous, discrete, and integer design variables.

Complex Sequencing Problems and Local Search Heuristics

NARCIS (Netherlands)

Brucker, P.; Hurink, Johann L.; Osman, I.H.; Kelly, J.P.

1996-01-01

Many problems can be formulated as complex sequencing problems. We will present problems in flexible manufacturing that have such a formulation and apply local search methods like iterative improvement, simulated annealing and tabu search to solve these problems. Computational results are reported.

Integrating Conflict Driven Clause Learning to Local Search

Directory of Open Access Journals (Sweden)

Gilles Audenard

2009-10-01

Full Text Available This article introduces SatHyS (SAT HYbrid Solver, a novel hybrid approach for propositional satisfiability. It combines local search and conflict driven clause learning (CDCL scheme. Each time the local search part reaches a local minimum, the CDCL is launched. For SAT problems it behaves like a tabu list, whereas for UNSAT ones, the CDCL part tries to focus on minimum unsatisfiable sub-formula (MUS. Experimental results show good performances on many classes of SAT instances from the last SAT competitions.

Ant colony system (ACS with hybrid local search to solve vehicle routing problems

Directory of Open Access Journals (Sweden)

Suphan Sodsoon

2016-02-01

Full Text Available This research applied an Ant Colony System algorithm with a Hybrid Local Search to solve Vehicle Routing Problems (VRP from a single depot when the customers’ requirements are known. VRP is an NP-hard optimization problem and has usually been successfully solved optimum by heuristics. A fleet of vehicles of a specific capacity are used to serve a number of customers at minimum cost, without violating the constraints of vehicle capacity. There are meta-heuristic approaches to solve these problems, such as Simulated Annealing, Genetic Algorithm, Tabu Search and the Ant Colony System algorithm. In this case a hybrid local search was used (Cross-Exchange, Or-Opt and 2-Opt algorithm with an Ant Colony System algorithm. The Experimental Design was tested on 7 various problems from the data set online in the OR-Library. There are five different problems in which customers are randomly distributed with the depot in an approximately central location. The customers were grouped into clusters. The results are evaluated in terms of optimal routes using optimal distances. The experimental results are compared with those obtained from meta-heuristics and they show that the proposed method outperforms six meta-heuristics in the literature.

A genome-wide search for genes involved in type 2 diabetes in a recently genetically isolated population from the Netherlands

NARCIS (Netherlands)

Y.S. Aulchenko (Yurii); N. Vaessen (Norbert); P. Heutink (Peter); J. Pullen (Jan); P.J.L.M. Snijders (Pieter); A. Hofman (Albert); L.A. Sandkuijl (Lodewijk); J.J. Houwing-Duistermaat (Jeanine); S. Bennett (Simon); B.A. Oostra (Ben); C.M. van Duijn (Cornelia); M. Edwards (Mark)

2003-01-01

textabstractMultiple genes, interacting with the environment, contribute to the susceptibility to type 2 diabetes. We performed a genome-wide search to localize type 2 diabetes susceptibility genes in a recently genetically isolated population in the Netherlands. We identified 79 nuclear families

Local beam angle optimization with linear programming and gradient search

International Nuclear Information System (INIS)

Craft, David

2007-01-01

The optimization of beam angles in IMRT planning is still an open problem, with literature focusing on heuristic strategies and exhaustive searches on discrete angle grids. We show how a beam angle set can be locally refined in a continuous manner using gradient-based optimization in the beam angle space. The gradient is derived using linear programming duality theory. Applying this local search to 100 random initial angle sets of a phantom pancreatic case demonstrates the method, and highlights the many-local-minima aspect of the BAO problem. Due to this function structure, we recommend a search strategy of a thorough global search followed by local refinement at promising beam angle sets. Extensions to nonlinear IMRT formulations are discussed. (note)

Improved quantum-behaved particle swarm optimization with local search strategy

Directory of Open Access Journals (Sweden)

Maolong Xi

2017-03-01

Full Text Available Quantum-behaved particle swarm optimization, which was motivated by analysis of particle swarm optimization and quantum system, has shown compared performance in finding the optimal solutions for many optimization problems to other evolutionary algorithms. To address the problem of premature, a local search strategy is proposed to improve the performance of quantum-behaved particle swarm optimization. In proposed local search strategy, a super particle is presented which is a collection body of randomly selected particles’ dimension information in the swarm. The selected probability of particles in swarm is different and determined by their fitness values. To minimization problems, the fitness value of one particle is smaller; the selected probability is more and will contribute more information in constructing the super particle. In addition, in order to investigate the influence on algorithm performance with different local search space, four methods of computing the local search radius are applied in local search strategy and propose four variants of local search quantum-behaved particle swarm optimization. Empirical studies on a suite of well-known benchmark functions are undertaken in order to make an overall performance comparison among the proposed methods and other quantum-behaved particle swarm optimization. The simulation results show that the proposed quantum-behaved particle swarm optimization variants have better advantages over the original quantum-behaved particle swarm optimization.

The use of a genetic algorithm-based search strategy in geostatistics: application to a set of anisotropic piezometric head data

Science.gov (United States)

Abedini, M. J.; Nasseri, M.; Burn, D. H.

2012-04-01

In any geostatistical study, an important consideration is the choice of an appropriate, repeatable, and objective search strategy that controls the nearby samples to be included in the location-specific estimation procedure. Almost all geostatistical software available in the market puts the onus on the user to supply search strategy parameters in a heuristic manner. These parameters are solely controlled by geographical coordinates that are defined for the entire area under study, and the user has no guidance as to how to choose these parameters. The main thesis of the current study is that the selection of search strategy parameters has to be driven by data—both the spatial coordinates and the sample values—and cannot be chosen beforehand. For this purpose, a genetic-algorithm-based ordinary kriging with moving neighborhood technique is proposed. The search capability of a genetic algorithm is exploited to search the feature space for appropriate, either local or global, search strategy parameters. Radius of circle/sphere and/or radii of standard or rotated ellipse/ellipsoid are considered as the decision variables to be optimized by GA. The superiority of GA-based ordinary kriging is demonstrated through application to the Wolfcamp Aquifer piezometric head data. Assessment of numerical results showed that definition of search strategy parameters based on both geographical coordinates and sample values improves cross-validation statistics when compared with that based on geographical coordinates alone. In the case of a variable search neighborhood for each estimation point, optimization of local search strategy parameters for an elliptical support domain—the orientation of which is dictated by anisotropic axes—via GA was able to capture the dynamics of piezometric head in west Texas/New Mexico in an efficient way.

Inferring Mechanisms of Compensation from E-MAP and SGA Data Using Local Search Algorithms for Max Cut

Science.gov (United States)

Leiserson, Mark D. M.; Tatar, Diana; Cowen, Lenore J.; Hescott, Benjamin J.

A new method based on a mathematically natural local search framework for max cut is developed to uncover functionally coherent module and BPM motifs in high-throughput genetic interaction data. Unlike previous methods which also consider physical protein-protein interaction data, our method utilizes genetic interaction data only; this becomes increasingly important as high-throughput genetic interaction data is becoming available in settings where less is known about physical interaction data. We compare modules and BPMs obtained to previous methods and across different datasets. Despite needing no physical interaction information, the BPMs produced by our method are competitive with previous methods. Biological findings include a suggested global role for the prefoldin complex and a SWR subcomplex in pathway buffering in the budding yeast interactome.

Simulation Optimization by Genetic Search: A Comprehensive Study with Applications to Production Management

National Research Council Canada - National Science Library

Yunker, James

2003-01-01

In this report, a relatively new simulation optimization technique, the genetic search, is compared to two more established simulation techniques-the pattern search and the response surface methodology search...

Locality in Generic Instance Search from One Example

NARCIS (Netherlands)

Tao, R.; Gavves, E.; Snoek, C.G.M.; Smeulders, A.W.M.

2014-01-01

This paper aims for generic instance search from a single example. Where the state-of-the-art relies on global image representation for the search, we proceed by including locality at all steps of the method. As the first novelty, we consider many boxes per database image as candidate targets to

A search for symmetries in the genetic code

International Nuclear Information System (INIS)

Hornos, J.E.M.; Hornos, Y.M.M.

1991-01-01

A search for symmetries based on the classification theorem of Cartan for the compact simple Lie algebras is performed to verify to what extent the genetic code is a manifestation of some underlying symmetry. An exact continuous symmetry group cannot be found to reproduce the present, universal code. However a unique approximate symmetry group is compatible with codon assignment for the fundamental amino acids and the termination codon. In order to obtain the actual genetic code, the symmetry must be slightly broken. (author). 27 refs, 3 figs, 6 tabs

State-of-the-Art Review on Relevance of Genetic Algorithm to Internet Web Search

Directory of Open Access Journals (Sweden)

Kehinde Agbele

2012-01-01

Full Text Available People use search engines to find information they desire with the aim that their information needs will be met. Information retrieval (IR is a field that is concerned primarily with the searching and retrieving of information in the documents and also searching the search engine, online databases, and Internet. Genetic algorithms (GAs are robust, efficient, and optimizated methods in a wide area of search problems motivated by Darwin’s principles of natural selection and survival of the fittest. This paper describes information retrieval systems (IRS components. This paper looks at how GAs can be applied in the field of IR and specifically the relevance of genetic algorithms to internet web search. Finally, from the proposals surveyed it turns out that GA is applied to diverse problem fields of internet web search.

A Local Search Modeling for Constrained Optimum Paths Problems (Extended Abstract

Directory of Open Access Journals (Sweden)

Quang Dung Pham

2009-10-01

Full Text Available Constrained Optimum Path (COP problems appear in many real-life applications, especially on communication networks. Some of these problems have been considered and solved by specific techniques which are usually difficult to extend. In this paper, we introduce a novel local search modeling for solving some COPs by local search. The modeling features the compositionality, modularity, reuse and strengthens the benefits of Constrained-Based Local Search. We also apply the modeling to the edge-disjoint paths problem (EDP. We show that side constraints can easily be added in the model. Computational results show the significance of the approach.

Modernizing quantum annealing using local searches

International Nuclear Information System (INIS)

Chancellor, Nicholas

2017-01-01

I describe how real quantum annealers may be used to perform local (in state space) searches around specified states, rather than the global searches traditionally implemented in the quantum annealing algorithm (QAA). Such protocols will have numerous advantages over simple quantum annealing. By using such searches the effect of problem mis-specification can be reduced, as only energy differences between the searched states will be relevant. The QAA is an analogue of simulated annealing, a classical numerical technique which has now been superseded. Hence, I explore two strategies to use an annealer in a way which takes advantage of modern classical optimization algorithms. Specifically, I show how sequential calls to quantum annealers can be used to construct analogues of population annealing and parallel tempering which use quantum searches as subroutines. The techniques given here can be applied not only to optimization, but also to sampling. I examine the feasibility of these protocols on real devices and note that implementing such protocols should require minimal if any change to the current design of the flux qubit-based annealers by D-Wave Systems Inc. I further provide proof-of-principle numerical experiments based on quantum Monte Carlo that demonstrate simple examples of the discussed techniques. (paper)

Toward an automaton Constraint for Local Search

Directory of Open Access Journals (Sweden)

Jun He

2009-10-01

Full Text Available We explore the idea of using finite automata to implement new constraints for local search (this is already a successful technique in constraint-based global search. We show how it is possible to maintain incrementally the violations of a constraint and its decision variables from an automaton that describes a ground checker for that constraint. We establish the practicality of our approach idea on real-life personnel rostering problems, and show that it is competitive with the approach of [Pralong, 2007].

Search-free license plate localization based on saliency and local variance estimation

Science.gov (United States)

Safaei, Amin; Tang, H. L.; Sanei, S.

2015-02-01

In recent years, the performance and accuracy of automatic license plate number recognition (ALPR) systems have greatly improved, however the increasing number of applications for such systems have made ALPR research more challenging than ever. The inherent computational complexity of search dependent algorithms remains a major problem for current ALPR systems. This paper proposes a novel search-free method of localization based on the estimation of saliency and local variance. Gabor functions are then used to validate the choice of candidate license plate. The algorithm was applied to three image datasets with different levels of complexity and the results compared with a number of benchmark methods, particularly in terms of speed. The proposed method outperforms the state of the art methods and can be used for real time applications.

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.

the search for local government autonomy in nigeria

African Journals Online (AJOL)

RAYAN_

autonomous. Keywords: Search, local government, autonomy, pathways and realization .... time. 6 There were, for instance, the Native Authority Ordinance, the Native Revenue .... Construction and maintenance of primary schools; and e.

Searching LOGIN, the Local Government Information Network.

Science.gov (United States)

Jack, Robert F.

1984-01-01

Describes a computer-based information retrieval and electronic messaging system produced by Control Data Corporation now being used by government agencies and other organizations. Background of Local Government Information Network (LOGIN), database structure, types of LOGIN units, searching LOGIN (intersect, display, and list commands), and how…

Local search heuristics for the probabilistic dial-a-ride problem

DEFF Research Database (Denmark)

Ho, Sin C.; Haugland, Dag

2011-01-01

evaluation procedure in a pure local search heuristic and in a tabu search heuristic. The quality of the solutions obtained by the two heuristics have been compared experimentally. Computational results confirm that our neighborhood evaluation technique is much faster than the straightforward one...

On the Use of Local Search in the Evolution of Neural Networks for the Diagnosis of Breast Cancer

Directory of Open Access Journals (Sweden)

Agam Gupta

2015-07-01

Full Text Available With the advancement in the field of Artificial Intelligence, there have been considerable efforts to develop technologies for pattern recognition related to medical diagnosis. Artificial Neural Networks (ANNs, a significant piece of Artificial Intelligence forms the base for most of the marvels in the former field. However, ANNs face the problem of premature convergence at a local minimum and inability to set hyper-parameters (like the number of neurons, learning rate, etc. while using Back Propagation Algorithm (BPA. In this paper, we have used the Genetic Algorithm (GA for the evolution of the ANN, which overcomes the limitations of the BPA. Since GA alone cannot fit for a high-dimensional, complex and multi-modal optimization landscape of the ANN, BPA is used as a local search algorithm to aid the evolution. The contributions of GA and BPA in the resultant approach are adjudged to determine the magnitude of local search necessary for optimization, striking a clear balance between exploration and exploitation in the evolution. The algorithm was applied to deal with the problem of Breast Cancer diagnosis. Results showed that under optimal settings, hybrid algorithm performs better than BPA or GA alone.

Performance of genetic algorithms in search for water splitting perovskites

DEFF Research Database (Denmark)

Jain, A.; Castelli, Ivano Eligio; Hautier, G.

2013-01-01

We examine the performance of genetic algorithms (GAs) in uncovering solar water light splitters over a space of almost 19,000 perovskite materials. The entire search space was previously calculated using density functional theory to determine solutions that fulfill constraints on stability, band...

Stochastic local search foundations and applications

CERN Document Server

Hoos, Holger H; Stutzle, Thomas

2004-01-01

Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems in many areas of computer science and operations research, including propositional satisfiability, constraint satisfaction, routing, and scheduling. SLS algorithms have also become increasingly popular for solving challenging combinatorial problems in many application areas, such as e-commerce and bioinformatics. Hoos and Stützle offer the first systematic and unified treatment of SLS algorithms. In this groundbreaking new book, they examine the general concepts and specific instances of SLS algorithms and carefully consider their development, analysis and application. The discussion focuses on the most successful SLS methods and explores their underlying principles, properties, and features. This book gives hands-on experience with some of the most widely used search techniques, and provides readers with the necessary understanding and skills to use this powerful too...

A local search heuristic for the Multi-Commodity k-splittable Maximum Flow Problem

DEFF Research Database (Denmark)

Gamst, Mette

2014-01-01

, a local search heuristic for solving the problem is proposed. The heuristic is an iterative shortest path procedure on a reduced graph combined with a local search procedure to modify certain path flows and prioritize the different commodities. The heuristic is tested on benchmark instances from...

Local weather is associated with rates of online searches for musculoskeletal pain symptoms.

Directory of Open Access Journals (Sweden)

Scott Telfer

Full Text Available Weather conditions are commonly believed to influence musculoskeletal pain, however the evidence for this is mixed. This study aimed to examine the relationship between local meteorological conditions and online search trends for terms related to knee pain, hip pain, and arthritis. Five years of relative online search volumes for these terms were obtained for the 50 most populous cities in the contiguous United States, along with corresponding local weather data for temperature, relative humidity, barometric pressure, and precipitation. Methods from the climate econometrics literature were used to assess the casual impact of these meteorological variables on the relative volumes of searches for pain. For temperatures between -5°C and 30°C, search volumes for hip pain increased by 12 index points, and knee pain increased by 18 index points. Precipitation had a negative effect on search volumes for these terms. At temperatures >30°C, search volumes for arthritis related pain decreased by 7 index points. These patterns were not seen for pain searches unrelated to the musculoskeletal system. In summary, selected local weather conditions are significantly associated with online search volumes for specific musculoskeletal pain symptoms. We believe the predominate driver for this to be the relative changes in physical activity levels associated with meteorological conditions.

Improved Particle Swarm Optimization with a Collective Local Unimodal Search for Continuous Optimization Problems

Science.gov (United States)

Arasomwan, Martins Akugbe; Adewumi, Aderemi Oluyinka

2014-01-01

A new local search technique is proposed and used to improve the performance of particle swarm optimization algorithms by addressing the problem of premature convergence. In the proposed local search technique, a potential particle position in the solution search space is collectively constructed by a number of randomly selected particles in the swarm. The number of times the selection is made varies with the dimension of the optimization problem and each selected particle donates the value in the location of its randomly selected dimension from its personal best. After constructing the potential particle position, some local search is done around its neighbourhood in comparison with the current swarm global best position. It is then used to replace the global best particle position if it is found to be better; otherwise no replacement is made. Using some well-studied benchmark problems with low and high dimensions, numerical simulations were used to validate the performance of the improved algorithms. Comparisons were made with four different PSO variants, two of the variants implement different local search technique while the other two do not. Results show that the improved algorithms could obtain better quality solution while demonstrating better convergence velocity and precision, stability, robustness, and global-local search ability than the competing variants. PMID:24723827

Tunnel Vision: Local Behavioral Influences on Consumer Decisions in Product Search

NARCIS (Netherlands)

G. Häubl (Gerald); B.G.C. Dellaert (Benedict); A.C.D. Donkers (Bas)

2010-01-01

textabstractWe introduce and test a behavioral model of consumer product search that extends a baseline normative model of sequential search by incorporating nonnormative influences that are local in the sense that they reflect consumers' undue sensitivity to recently encountered alternatives. We

Local search for Steiner tree problems in graphs

NARCIS (Netherlands)

Verhoeven, M.G.A.; Severens, M.E.M.; Aarts, E.H.L.; Rayward-Smith, V.J.; Reeves, C.R.; Smith, G.D.

1996-01-01

We present a local search algorithm for the Steiner tree problem in graphs, which uses a neighbourhood in which paths in a steiner tree are exchanged. The exchange function of this neigbourhood is based on multiple-source shortest path algorithm. We present computational results for a known

Neurophysiological correlates of relatively enhanced local visual search in autistic adolescents.

Science.gov (United States)

Manjaly, Zina M; Bruning, Nicole; Neufang, Susanne; Stephan, Klaas E; Brieber, Sarah; Marshall, John C; Kamp-Becker, Inge; Remschmidt, Helmut; Herpertz-Dahlmann, Beate; Konrad, Kerstin; Fink, Gereon R

2007-03-01

Previous studies found normal or even superior performance of autistic patients on visuospatial tasks requiring local search, like the Embedded Figures Task (EFT). A well-known interpretation of this is "weak central coherence", i.e. autistic patients may show a reduced general ability to process information in its context and may therefore have a tendency to favour local over global aspects of information processing. An alternative view is that the local processing advantage in the EFT may result from a relative amplification of early perceptual processes which boosts processing of local stimulus properties but does not affect processing of global context. This study used functional magnetic resonance imaging (fMRI) in 12 autistic adolescents (9 Asperger and 3 high-functioning autistic patients) and 12 matched controls to help distinguish, on neurophysiological grounds, between these two accounts of EFT performance in autistic patients. Behaviourally, we found autistic individuals to be unimpaired during the EFT while they were significantly worse at performing a closely matched control task with minimal local search requirements. The fMRI results showed that activations specific for the local search aspects of the EFT were left-lateralised in parietal and premotor areas for the control group (as previously demonstrated for adults), whereas for the patients these activations were found in right primary visual cortex and bilateral extrastriate areas. These results suggest that enhanced local processing in early visual areas, as opposed to impaired processing of global context, is characteristic for performance of the EFT by autistic patients.

Simulation to Support Local Search in Trajectory Optimization Planning

Science.gov (United States)

Morris, Robert A.; Venable, K. Brent; Lindsey, James

2012-01-01

NASA and the international community are investing in the development of a commercial transportation infrastructure that includes the increased use of rotorcraft, specifically helicopters and civil tilt rotors. However, there is significant concern over the impact of noise on the communities surrounding the transportation facilities. One way to address the rotorcraft noise problem is by exploiting powerful search techniques coming from artificial intelligence coupled with simulation and field tests to design low-noise flight profiles which can be tested in simulation or through field tests. This paper investigates the use of simulation based on predictive physical models to facilitate the search for low-noise trajectories using a class of automated search algorithms called local search. A novel feature of this approach is the ability to incorporate constraints directly into the problem formulation that addresses passenger safety and comfort.

Medical image segmentation using genetic algorithms.

Science.gov (United States)

Maulik, Ujjwal

2009-03-01

Genetic algorithms (GAs) have been found to be effective in the domain of medical image segmentation, since the problem can often be mapped to one of search in a complex and multimodal landscape. The challenges in medical image segmentation arise due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. The resulting search space is therefore often noisy with a multitude of local optima. Not only does the genetic algorithmic framework prove to be effective in coming out of local optima, it also brings considerable flexibility into the segmentation procedure. In this paper, an attempt has been made to review the major applications of GAs to the domain of medical image segmentation.

An Enhanced Differential Evolution with Elite Chaotic Local Search

Directory of Open Access Journals (Sweden)

Zhaolu Guo

2015-01-01

Full Text Available Differential evolution (DE is a simple yet efficient evolutionary algorithm for real-world engineering problems. However, its search ability should be further enhanced to obtain better solutions when DE is applied to solve complex optimization problems. This paper presents an enhanced differential evolution with elite chaotic local search (DEECL. In DEECL, it utilizes a chaotic search strategy based on the heuristic information from the elite individuals to promote the exploitation power. Moreover, DEECL employs a simple and effective parameter adaptation mechanism to enhance the robustness. Experiments are conducted on a set of classical test functions. The experimental results show that DEECL is very competitive on the majority of the test functions.

Initialization and Restart in Stochastic Local Search: Computing a Most Probable Explanation in Bayesian Networks

Science.gov (United States)

Mengshoel, Ole J.; Wilkins, David C.; Roth, Dan

2010-01-01

For hard computational problems, stochastic local search has proven to be a competitive approach to finding optimal or approximately optimal problem solutions. Two key research questions for stochastic local search algorithms are: Which algorithms are effective for initialization? When should the search process be restarted? In the present work we investigate these research questions in the context of approximate computation of most probable explanations (MPEs) in Bayesian networks (BNs). We introduce a novel approach, based on the Viterbi algorithm, to explanation initialization in BNs. While the Viterbi algorithm works on sequences and trees, our approach works on BNs with arbitrary topologies. We also give a novel formalization of stochastic local search, with focus on initialization and restart, using probability theory and mixture models. Experimentally, we apply our methods to the problem of MPE computation, using a stochastic local search algorithm known as Stochastic Greedy Search. By carefully optimizing both initialization and restart, we reduce the MPE search time for application BNs by several orders of magnitude compared to using uniform at random initialization without restart. On several BNs from applications, the performance of Stochastic Greedy Search is competitive with clique tree clustering, a state-of-the-art exact algorithm used for MPE computation in BNs.

Optimal Refueling Pattern Search for a CANDU Reactor Using a Genetic Algorithm

International Nuclear Information System (INIS)

Quang Binh, DO; Gyuhong, ROH; Hangbok, CHOI

2006-01-01

This paper presents the results from the application of genetic algorithms to a refueling optimization of a Canada deuterium uranium (CANDU) reactor. This work aims at making a mathematical model of the refueling optimization problem including the objective function and constraints and developing a method based on genetic algorithms to solve the problem. The model of the optimization problem and the proposed method comply with the key features of the refueling strategy of the CANDU reactor which adopts an on-power refueling operation. In this study, a genetic algorithm combined with an elitism strategy was used to automatically search for the refueling patterns. The objective of the optimization was to maximize the discharge burn-up of the refueling bundles, minimize the maximum channel power, or minimize the maximum change in the zone controller unit (ZCU) water levels. A combination of these objectives was also investigated. The constraints include the discharge burn-up, maximum channel power, maximum bundle power, channel power peaking factor and the ZCU water level. A refueling pattern that represents the refueling rate and channels was coded by a one-dimensional binary chromosome, which is a string of binary numbers 0 and 1. A computer program was developed in FORTRAN 90 running on an HP 9000 workstation to conduct the search for the optimal refueling patterns for a CANDU reactor at the equilibrium state. The results showed that it was possible to apply genetic algorithms to automatically search for the refueling channels of the CANDU reactor. The optimal refueling patterns were compared with the solutions obtained from the AUTOREFUEL program and the results were consistent with each other. (authors)

Chapter 51: How to Build a Simple Cone Search Service Using a Local Database

Science.gov (United States)

Kent, B. R.; Greene, G. R.

The cone search service protocol will be examined from the server side in this chapter. A simple cone search service will be setup and configured locally using MySQL. Data will be read into a table, and the Java JDBC will be used to connect to the database. Readers will understand the VO cone search specification and how to use it to query a database on their local systems and return an XML/VOTable file based on an input of RA/DEC coordinates and a search radius. The cone search in this example will be deployed as a Java servlet. The resulting cone search can be tested with a verification service. This basic setup can be used with other languages and relational databases.

Predictive Feature Selection for Genetic Policy Search

Science.gov (United States)

2014-05-22

limited manual intervention are becoming increasingly desirable as more complex tasks in dynamic and high- tempo environments are explored. Reinforcement...states in many domains causes features relevant to the reward variations to be overlooked, which hinders the policy search. 3.4 Parameter Selection PFS...the current feature subset. This local minimum may be “deceptive,” meaning that it does not clearly lead to the global optimal policy ( Goldberg and

Permanent neonatal diabetes mellitus: prevalence and genetic diagnosis in the SEARCH for Diabetes in Youth Study.

Science.gov (United States)

Kanakatti Shankar, Roopa; Pihoker, Catherine; Dolan, Lawrence M; Standiford, Debra; Badaru, Angela; Dabelea, Dana; Rodriguez, Beatriz; Black, Mary Helen; Imperatore, Giuseppina; Hattersley, Andrew; Ellard, Sian; Gilliam, Lisa K

2013-05-01

Neonatal diabetes mellitus (NDM) is defined as diabetes with onset before 6 months of age. Nearly half of individuals with NDM are affected by permanent neonatal diabetes mellitus (PNDM). Mutations in KATP channel genes (KCNJ11, ABCC8) and the insulin gene (INS) are the most common causes of PNDM. To estimate the prevalence of PNDM among SEARCH for Diabetes in Youth (SEARCH) study participants (2001-2008) and to identify the genetic mutations causing PNDM. SEARCH is a multicenter population-based study of diabetes in youth diabetes before 6 months of age were invited for genetic testing for mutations in the KCNJ11, ABCC8, and INS genes. Of the 15,829 SEARCH participants with diabetes, 39 were diagnosed before 6 months of age. Thirty-five of them had PNDM (0.22% of all diabetes cases in SEARCH), 3 had transient neonatal diabetes that had remitted by 18 months and 1 was unknown. The majority of them (66.7%) had a clinical diagnosis of type1 diabetes by their health care provider. Population prevalence of PNDM in youth US based on the frequency of PNDM in SEARCH. Patients with NDM are often misclassified as having type1 diabetes. Widespread education is essential to encourage appropriate genetic testing and treatment of NDM. © 2012 John Wiley & Sons A/S.

Localized saddle-point search and application to temperature-accelerated dynamics

Energy Technology Data Exchange (ETDEWEB)

Shim, Yunsic; Amar, Jacques G. [Department of Physics and Astronomy, University of Toledo, Toledo, Ohio 43606 (United States); Callahan, Nathan B. [Department of Physics and Astronomy, University of Toledo, Toledo, Ohio 43606 (United States); Department of Physics, Indiana University, Bloomington, Indiana 47405 (United States)

2013-03-07

We present a method for speeding up temperature-accelerated dynamics (TAD) simulations by carrying out a localized saddle-point (LSAD) search. In this method, instead of using the entire system to determine the energy barriers of activated processes, the calculation is localized by only including a small chunk of atoms around the atoms directly involved in the transition. Using this method, we have obtained N-independent scaling for the computational cost of the saddle-point search as a function of system size N. The error arising from localization is analyzed using a variety of model systems, including a variety of activated processes on Ag(100) and Cu(100) surfaces, as well as multiatom moves in Cu radiation damage and metal heteroepitaxial growth. Our results show significantly improved performance of TAD with the LSAD method, for the case of Ag/Ag(100) annealing and Cu/Cu(100) growth, while maintaining a negligibly small error in energy barriers.

Genetic variability in local Brazilian horse lines using microsatellite markers.

Science.gov (United States)

Silva, A C M; Paiva, S R; Albuquerque, M S M; Egito, A A; Santos, S A; Lima, F C; Castro, S T; Mariante, A S; Correa, P S; McManus, C M

2012-04-10

Genetic variability at 11 microsatellite markers was analyzed in five naturalized/local Brazilian horse breeds or genetic groups. Blood samples were collected from 328 animals of the breeds Campeira (Santa Catarina State), Lavradeira (Roraima State), Pantaneira (Pantanal Mato-Grossense), Mangalarga Marchador (Minas Gerais State), as well as the genetic group Baixadeiro (Maranhão State), and the exotic breeds English Thoroughbred and Arab. We found significant genetic variability within evaluated microsatellite loci, with observed heterozygosis varying between 0.426 and 0.768 and polymorphism information content values of 0.751 to 0.914. All breeds showed high inbreeding coefficients and were not in Hardy-Weinberg equilibrium. The smallest genetic distance was seen between the Pantaneira and Arab breeds. The principal component analyzes and Bayesian approach demonstrated that the exotic breeds have had a significant influence on the genetic formation of the local breeds, with introgression of English Throroughbred in Pantaneira and Lavradeira, as well as genetic proximity between the Arab, Pantaneira and Mangalarga Marchador populations. This study shows the need to conserve traits acquired by naturalized horse breeds over centuries of natural selection in Brazil due to the genetic uniqueness of each group, suggesting a reduced gene flow between them. These results reinforce the need to include these herds in animal genetic resource conservation programs to maximize the genetic variability and conserve useful allele combinations.

Multi-agent search for source localization in a turbulent medium

International Nuclear Information System (INIS)

Hajieghrary, Hadi; Hsieh, M. Ani; Schwartz, Ira B.

2016-01-01

We extend the gradient-less search strategy referred to as “infotaxis” to a distributed multi-agent system. “Infotaxis” is a search strategy that uses sporadic sensor measurements to determine the source location of materials dispersed in a turbulent medium. In this work, we leverage the spatio-temporal sensing capabilities of a mobile sensing agents to optimize the time spent finding and localizing the position of the source using a multi-agent collaborative search strategy. Our results suggest that the proposed multi-agent collaborative search strategy leverages the team's ability to obtain simultaneous measurements at different locations to speed up the search process. We present a multi-agent collaborative “infotaxis” strategy that uses the relative entropy of the system to synthesize a suitable search strategy for the team. The result is a collaborative information theoretic search strategy that results in control actions that maximize the information gained by the team, and improves estimates of the source position. - Highlights: • We extend the gradient-less infotaxis search strategy to a distributed multi-agent system. • Leveraging the spatio-temporal sensing capabilities of a team of mobile sensing agents speeds up the search process. • The resulting information theoretic search strategy maximizes the information gained and improves the estimate of the source position.

An Effective Cuckoo Search Algorithm for Node Localization in Wireless Sensor Network.

Science.gov (United States)

Cheng, Jing; Xia, Linyuan

2016-08-31

Localization is an essential requirement in the increasing prevalence of wireless sensor network (WSN) applications. Reducing the computational complexity, communication overhead in WSN localization is of paramount importance in order to prolong the lifetime of the energy-limited sensor nodes and improve localization performance. This paper proposes an effective Cuckoo Search (CS) algorithm for node localization. Based on the modification of step size, this approach enables the population to approach global optimal solution rapidly, and the fitness of each solution is employed to build mutation probability for avoiding local convergence. Further, the approach restricts the population in the certain range so that it can prevent the energy consumption caused by insignificant search. Extensive experiments were conducted to study the effects of parameters like anchor density, node density and communication range on the proposed algorithm with respect to average localization error and localization success ratio. In addition, a comparative study was conducted to realize the same localization task using the same network deployment. Experimental results prove that the proposed CS algorithm can not only increase convergence rate but also reduce average localization error compared with standard CS algorithm and Particle Swarm Optimization (PSO) algorithm.

Comparison of genetic algorithm and harmony search for generator maintenance scheduling

International Nuclear Information System (INIS)

Khan, L.; Mumtaz, S.; Khattak, A.

2012-01-01

GMS (Generator Maintenance Scheduling) ranks very high in decision making of power generation management. Generators maintenance schedule decides the time period of maintenance tasks and a reliable reserve margin is also maintained during this time period. In this paper, a comparison of GA (Genetic Algorithm) and US (Harmony Search) algorithm is presented to solve generators maintenance scheduling problem for WAPDA (Water And Power Development Authority) Pakistan. GA is a search procedure, which is used in search problems to compute exact and optimized solution. GA is considered as global search heuristic technique. HS algorithm is quite efficient, because the convergence rate of this algorithm is very fast. HS algorithm is based on the concept of music improvisation process of searching for a perfect state of harmony. The two algorithms generate feasible and optimal solutions and overcome the limitations of the conventional methods including extensive computational effort, which increases exponentially as the size of the problem increases. The proposed methods are tested, validated and compared on the WAPDA electric system. (author)

Bilayer Local Search Enhanced Particle Swarm Optimization for the Capacitated Vehicle Routing Problem

Directory of Open Access Journals (Sweden)

A. K. M. Foysal Ahmed

2018-03-01

Full Text Available The classical capacitated vehicle routing problem (CVRP is a very popular combinatorial optimization problem in the field of logistics and supply chain management. Although CVRP has drawn interests of many researchers, no standard way has been established yet to obtain best known solutions for all the different problem sets. We propose an efficient algorithm Bilayer Local Search-based Particle Swarm Optimization (BLS-PSO along with a novel decoding method to solve CVRP. Decoding method is important to relate the encoded particle position to a feasible CVRP solution. In bilayer local search, one layer of local search is for the whole population in any iteration whereas another one is applied only on the pool of the best particles generated in different generations. Such searching strategies help the BLS-PSO to perform better than the existing proposals by obtaining best known solutions for most of the existing benchmark problems within very reasonable computational time. Computational results also show that the performance achieved by the proposed algorithm outperforms other PSO-based approaches.

Wayward Relations: Novel Searches of the Donor-Conceived for Genetic Kinship.

Science.gov (United States)

Klotz, Maren

2016-01-01

Searching and finding supposedly anonymous sperm donors or half-siblings by diverting direct-to-consumer genetic testing is a novel phenomenon. I refer to such new forms of kinship as 'wayward relations,' because they are often officially unintended and do not correspond to established kinship roles. Drawing on data mostly from the United Kingdom, Germany and the United States, I argue that wayward relations are a highly contemporary means of asserting agency in a technological world characterized by tensions over knowledge acquisition. I make the case that such relations reaffirm the genetic grounding of kinship, but do not displace other ways of relating--they are complementary not colonizing. Wayward relations challenge the gate-keeper status of fertility clinics and regulators over genetic knowledge and classical notions of privacy.

Constraint-based local search for container stowage slot planning

DEFF Research Database (Denmark)

Pacino, Dario; Jensen, Rune Møller; Bebbington, Tom

2012-01-01

-sea vessels. This paper describes the constrained-based local search algorithm used in the second phase of this approach where individual containers are assigned to slots in each bay section. The algorithm can solve this problem in an average of 0.18 seconds per bay, corresponding to a 20 seconds runtime...

NSGA-II Algorithm with a Local Search Strategy for Multiobjective Optimal Design of Dry-Type Air-Core Reactor

Directory of Open Access Journals (Sweden)

Chengfen Zhang

2015-01-01

Full Text Available Dry-type air-core reactor is now widely applied in electrical power distribution systems, for which the optimization design is a crucial issue. In the optimization design problem of dry-type air-core reactor, the objectives of minimizing the production cost and minimizing the operation cost are both important. In this paper, a multiobjective optimal model is established considering simultaneously the two objectives of minimizing the production cost and minimizing the operation cost. To solve the multi-objective optimization problem, a memetic evolutionary algorithm is proposed, which combines elitist nondominated sorting genetic algorithm version II (NSGA-II with a local search strategy based on the covariance matrix adaptation evolution strategy (CMA-ES. NSGA-II can provide decision maker with flexible choices among the different trade-off solutions, while the local-search strategy, which is applied to nondominated individuals randomly selected from the current population in a given generation and quantity, can accelerate the convergence speed. Furthermore, another modification is that an external archive is set in the proposed algorithm for increasing the evolutionary efficiency. The proposed algorithm is tested on a dry-type air-core reactor made of rectangular cross-section litz-wire. Simulation results show that the proposed algorithm has high efficiency and it converges to a better Pareto front.

A Group Theoretic Approach to Metaheuristic Local Search for Partitioning Problems

Science.gov (United States)

2005-05-01

Tabu Search. Mathematical and Computer Modeling 39: 599-616. 107 Daskin , M.S., E. Stern. 1981. A Hierarchical Objective Set Covering Model for EMS... A Group Theoretic Approach to Metaheuristic Local Search for Partitioning Problems by Gary W. Kinney Jr., B.G.S., M.S. Dissertation Presented to the...DISTRIBUTION STATEMENT A Approved for Public Release Distribution Unlimited The University of Texas at Austin May, 2005 20050504 002 REPORT

Neurophysiological correlates of relatively enhanced local visual search in autistic adolescents

OpenAIRE

Manjaly, Zina M.; Bruning, Nicole; Neufang, Susanne; Stephan, Klaas E.; Brieber, Sarah; Marshall, John C.; Kamp-Becker, Inge; Remschmidt, Helmut; Herpertz-Dahlmann, Beate; Konrad, Kerstin; Fink, Gereon R.

2007-01-01

Previous studies found normal or even superior performance of autistic patients on visuospatial tasks requiring local search, like the Embedded Figures Task (EFT). A well-known interpretation of this is ?weak central coherence?, i.e. autistic patients may show a reduced general ability to process information in its context and may therefore have a tendency to favour local over global aspects of information processing. An alternative view is that the local processing advantage in the EFT may r...

Greedy Local Search and Vertex Cover in Sparse Random Graphs

DEFF Research Database (Denmark)

Witt, Carsten

2009-01-01

. This work starts with a rigorous explanation for this claim based on the refined analysis of the Karp-Sipser algorithm by Aronson et al. Subsequently, theoretical supplements are given to experimental studies of search heuristics on random graphs. For c 1, a greedy and randomized local-search heuristic...... finds an optimal cover in polynomial time with a probability arbitrarily close to 1. This behavior relies on the absence of a giant component. As an additional insight into the randomized search, it is shown that the heuristic fails badly also on graphs consisting of a single tree component of maximum......Recently, various randomized search heuristics have been studied for the solution of the minimum vertex cover problem, in particular for sparse random instances according to the G(n, c/n) model, where c > 0 is a constant. Methods from statistical physics suggest that the problem is easy if c

Power law-based local search in spider monkey optimisation for lower order system modelling

Science.gov (United States)

Sharma, Ajay; Sharma, Harish; Bhargava, Annapurna; Sharma, Nirmala

2017-01-01

The nature-inspired algorithms (NIAs) have shown efficiency to solve many complex real-world optimisation problems. The efficiency of NIAs is measured by their ability to find adequate results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This paper presents a solution for lower order system modelling using spider monkey optimisation (SMO) algorithm to obtain a better approximation for lower order systems and reflects almost original higher order system's characteristics. Further, a local search strategy, namely, power law-based local search is incorporated with SMO. The proposed strategy is named as power law-based local search in SMO (PLSMO). The efficiency, accuracy and reliability of the proposed algorithm is tested over 20 well-known benchmark functions. Then, the PLSMO algorithm is applied to solve the lower order system modelling problem.

Iterated local search and record-to-record travel applied to the fixed charge transportation problem

DEFF Research Database (Denmark)

Andersen, Jeanne; Klose, Andreas

The fixed charge transportation problem (FCTP) is a well-known and difficult optimization problem with lots of applications in logistics. It consists in finding a minimum cost network flow from a set of suppliers to a set of customers. Beside costs proportional to quantities transported......, transportation costs do, however, include a fixed charge. Iterated local search and record-to-record travel are both simple local search based meta-heuristics that, to our knowledge, not yet have been applied to the FCTP. In this paper, we apply both types of search strategies and combine them into a single...

Genetic relationships among Vietnamese local pigs investigated using genome-wide SNP markers.

Science.gov (United States)

Ishihara, S; Arakawa, A; Taniguchi, M; Luu, Q M; Pham, D L; Nguyen, B V; Mikawa, S; Kikuchi, K

2018-02-01

Vietnam is one of the most important countries for pig domestication, and a total of 26 local breeds have been reported. In the present study, genetic relationships among the various pig breeds were investigated using 90 samples collected from local pigs (15 breeds) in 15 distantly separated, distinct areas of the country and six samples from Landrace pigs in Hanoi as an out-group of a common Western breed. All samples were genotyped using the Illumina Porcine SNP60 v2 Genotyping BeadChip. We used 15 160-15 217 SNPs that showed a high degree of polymorphism in the Vietnamese breeds for identifying genetic relationships among the Vietnamese breeds. Principal components analysis showed that most pigs indigenous to Vietnam formed clusters correlated with their original geographic locations. Some Vietnamese breeds formed a cluster that was genetically related to the Western breed Landrace, suggesting the possibility of crossbreeding. These findings will be useful for the conservation and management of Vietnamese local pig breeds. © 2018 Stichting International Foundation for Animal Genetics.

Automatic multi-cycle reload design of pressurized water reactor using particle swarm optimization algorithm and local search

International Nuclear Information System (INIS)

Lin, Chaung; Hung, Shao-Chun

2013-01-01

Highlights: • An automatic multi-cycle core reload design tool, which searches the fresh fuel assembly composition, is developed. • The search method adopts particle swarm optimization and local search. • The design objectives are to achieve required cycle energy, minimum fuel cost, and the satisfactory constraints. • The constraints include the hot zero power moderator temperature coefficient and the hot channel factor. - Abstract: An automatic multi-cycle core reload design tool, which searches the fresh fuel assembly composition, is developed using particle swarm optimization and local search. The local search uses heuristic rules to change the current search result a little so that the result can be improved. The composition of the fresh fuel assemblies should provide the required cycle energy and satisfy the constraints, such as the hot zero power moderator temperature coefficient and the hot channel factor. Instead of designing loading pattern for each FA composition during search process, two fixed loading patterns are used to calculate the core status and the better fitness function value is used in the search process. The fitness function contains terms which reflect the design objectives such as cycle energy, constraints, and fuel cost. The results show that the developed tool can achieve the desire objective

Patterns of genetic diversity of local pig populations in the State of Pernambuco, Brazil

Directory of Open Access Journals (Sweden)

Elizabete Cristina da Silva

2011-08-01

Full Text Available This study estimated the genetic diversity and structure of 12 genetic groups (GG of locally adapted and specialized pigs in the state of Pernambuco using 22 microsatellite markers. Nine locally adapted breeds (Baé, Caruncho, Canastra, Canastrão, Mamelado, Moura, Nilo, Piau and UDB (Undefined Breed and 3 specialized breeds (Duroc, Landrace and Large White, totaling 190 animals, were analyzed. The Analysis of Molecular Variance (AMOVA showed that 3.2% of the total variation was due to differences between genetic groups, and 3.6% to differences between local and commercial pigs. One hundred and ninety eight alleles were identified and apart from the Large White breed, all GG presented Hardy-Weinberg Equilibrium deviations for some loci. The total and effective allele means were lower for Duroc (3.65 and 3.01 and higher for UDB (8.89 and 4.53 and Canastra (8.61 and 4.58. Using Nei's standard genetic distance and the UPGMA method, it was possible to observe that the Landrace breed was grouped with the local genetic groups Canastra, Moura, Canastrão, Baé and Caruncho. Due to the complex admixture pattern, the genetic variability of the 12 genetic groups can be analyzed by distributing the individuals into two populations as demonstrated by a Bayesian analysis, corroborating the results from AMOVA, which revealed a low level of genetic differentiation between the inferred populations.

Research and Applications of Shop Scheduling Based on Genetic Algorithms

Directory of Open Access Journals (Sweden)

Hang ZHAO

Full Text Available ABSTRACT Shop Scheduling is an important factor affecting the efficiency of production, efficient scheduling method and a research and application for optimization technology play an important role for manufacturing enterprises to improve production efficiency, reduce production costs and many other aspects. Existing studies have shown that improved genetic algorithm has solved the limitations that existed in the genetic algorithm, the objective function is able to meet customers' needs for shop scheduling, and the future research should focus on the combination of genetic algorithm with other optimized algorithms. In this paper, in order to overcome the shortcomings of early convergence of genetic algorithm and resolve local minimization problem in search process,aiming at mixed flow shop scheduling problem, an improved cyclic search genetic algorithm is put forward, and chromosome coding method and corresponding operation are given.The operation has the nature of inheriting the optimal individual ofthe previous generation and is able to avoid the emergence of local minimum, and cyclic and crossover operation and mutation operation can enhance the diversity of the population and then quickly get the optimal individual, and the effectiveness of the algorithm is validated. Experimental results show that the improved algorithm can well avoid the emergency of local minimum and is rapid in convergence.

A New Improved Quantum Evolution Algorithm with Local Search Procedure for Capacitated Vehicle Routing Problem

Directory of Open Access Journals (Sweden)

Ligang Cui

2013-01-01

Full Text Available The capacitated vehicle routing problem (CVRP is the most classical vehicle routing problem (VRP; many solution techniques are proposed to find its better answer. In this paper, a new improved quantum evolution algorithm (IQEA with a mixed local search procedure is proposed for solving CVRPs. First, an IQEA with a double chain quantum chromosome, new quantum rotation schemes, and self-adaptive quantum Not gate is constructed to initialize and generate feasible solutions. Then, to further strengthen IQEA's searching ability, three local search procedures 1-1 exchange, 1-0 exchange, and 2-OPT, are adopted. Experiments on a small case have been conducted to analyze the sensitivity of main parameters and compare the performances of the IQEA with different local search strategies. Together with results from the testing of CVRP benchmarks, the superiorities of the proposed algorithm over the PSO, SR-1, and SR-2 have been demonstrated. At last, a profound analysis of the experimental results is presented and some suggestions on future researches are given.

Local Climate Heterogeneity Shapes Population Genetic Structure of Two Undifferentiated Insular Scutellaria Species.

Science.gov (United States)

Hsiung, Huan-Yi; Huang, Bing-Hong; Chang, Jui-Tse; Huang, Yao-Moan; Huang, Chih-Wei; Liao, Pei-Chun

2017-01-01

Spatial climate heterogeneity may not only affect adaptive gene frequencies but could also indirectly shape the genetic structure of neutral loci by impacting demographic dynamics. In this study, the effect of local climate on population genetic variation was tested in two phylogenetically close Scutellaria species in Taiwan. Scutellaria taipeiensis , which was originally assumed to be an endemic species of Taiwan Island, is shown to be part of the widespread species S. barbata based on the overlapping ranges of genetic variation and climatic niches as well as their morphological similarity. Rejection of the scenario of "early divergence with secondary contact" and the support for multiple origins of populations of S. taipeiensis from S. barbata provide strong evolutionary evidence for a taxonomic revision of the species combination. Further tests of a climatic effect on genetic variation were conducted. Regression analyses show nonlinear correlations among any pair of geographic, climatic, and genetic distances. However, significantly, the bioclimatic variables that represent the precipitation from late summer to early autumn explain roughly 13% of the genetic variation of our sampled populations. These results indicate that spatial differences of precipitation in the typhoon season may influence the regeneration rate and colonization rate of local populations. The periodic typhoon episodes explain the significant but nonlinear influence of climatic variables on population genetic differentiation. Although, the climatic difference does not lead to species divergence, the local climate variability indeed impacts the spatial genetic distribution at the population level.

A Particle Swarm Optimization-Based Approach with Local Search for Predicting Protein Folding.

Science.gov (United States)

Yang, Cheng-Hong; Lin, Yu-Shiun; Chuang, Li-Yeh; Chang, Hsueh-Wei

2017-10-01

The hydrophobic-polar (HP) model is commonly used for predicting protein folding structures and hydrophobic interactions. This study developed a particle swarm optimization (PSO)-based algorithm combined with local search algorithms; specifically, the high exploration PSO (HEPSO) algorithm (which can execute global search processes) was combined with three local search algorithms (hill-climbing algorithm, greedy algorithm, and Tabu table), yielding the proposed HE-L-PSO algorithm. By using 20 known protein structures, we evaluated the performance of the HE-L-PSO algorithm in predicting protein folding in the HP model. The proposed HE-L-PSO algorithm exhibited favorable performance in predicting both short and long amino acid sequences with high reproducibility and stability, compared with seven reported algorithms. The HE-L-PSO algorithm yielded optimal solutions for all predicted protein folding structures. All HE-L-PSO-predicted protein folding structures possessed a hydrophobic core that is similar to normal protein folding.

Genetic diversity measures of local European beef cattle breeds for conservation purposes

Directory of Open Access Journals (Sweden)

Pereira Albano

2001-05-01

Full Text Available Abstract This study was undertaken to determine the genetic structure, evolutionary relationships, and the genetic diversity among 18 local cattle breeds from Spain, Portugal, and France using 16 microsatellites. Heterozygosities, estimates of Fst, genetic distances, multivariate and diversity analyses, and assignment tests were performed. Heterozygosities ranged from 0.54 in the Pirenaica breed to 0.72 in the Barrosã breed. Seven percent of the total genetic variability can be attributed to differences among breeds (mean Fst = 0.07; P

Numeral eddy current sensor modelling based on genetic neural network

International Nuclear Information System (INIS)

Yu Along

2008-01-01

This paper presents a method used to the numeral eddy current sensor modelling based on the genetic neural network to settle its nonlinear problem. The principle and algorithms of genetic neural network are introduced. In this method, the nonlinear model parameters of the numeral eddy current sensor are optimized by genetic neural network (GNN) according to measurement data. So the method remains both the global searching ability of genetic algorithm and the good local searching ability of neural network. The nonlinear model has the advantages of strong robustness, on-line modelling and high precision. The maximum nonlinearity error can be reduced to 0.037% by using GNN. However, the maximum nonlinearity error is 0.075% using the least square method

Efficient Top-k Locality Search for Co-located Spatial Web Objects

DEFF Research Database (Denmark)

Qu, Qiang; Liu, Siyuan; Yang, Bin

2014-01-01

In step with the web being used widely by mobile users, user location is becoming an essential signal in services, including local intent search. Given a large set of spatial web objects consisting of a geographical location and a textual description (e.g., online business directory entries of re...

Genetic Diversity of Local and Introduced Sweet Potato [Ipomoea ...

African Journals Online (AJOL)

This study was therefore conducted to estimate the genetic diversity of 114 Sweet potato [Ipomoea batatas (L.) Lam] accessions obtained from Nigeria, Asia, Latin America and Local collections along with two improved varieties. Accessions were planted in 2012/13 cropping season at Haramaya University, eastern Ethiopia ...

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

Science.gov (United States)

Liu, Hua-Long; Liu, Hua-Dong

2014-10-01

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

Constraint-Based Local Search for Constrained Optimum Paths Problems

Science.gov (United States)

Pham, Quang Dung; Deville, Yves; van Hentenryck, Pascal

Constrained Optimum Path (COP) problems arise in many real-life applications and are ubiquitous in communication networks. They have been traditionally approached by dedicated algorithms, which are often hard to extend with side constraints and to apply widely. This paper proposes a constraint-based local search (CBLS) framework for COP applications, bringing the compositionality, reuse, and extensibility at the core of CBLS and CP systems. The modeling contribution is the ability to express compositional models for various COP applications at a high level of abstraction, while cleanly separating the model and the search procedure. The main technical contribution is a connected neighborhood based on rooted spanning trees to find high-quality solutions to COP problems. The framework, implemented in COMET, is applied to Resource Constrained Shortest Path (RCSP) problems (with and without side constraints) and to the edge-disjoint paths problem (EDP). Computational results show the potential significance of the approach.

Genetic evolutionary taboo search for optimal marker placement in infrared patient setup

International Nuclear Information System (INIS)

Riboldi, M; Baroni, G; Spadea, M F; Tagaste, B; Garibaldi, C; Cambria, R; Orecchia, R; Pedotti, A

2007-01-01

In infrared patient setup adequate selection of the external fiducial configuration is required for compensating inner target displacements (target registration error, TRE). Genetic algorithms (GA) and taboo search (TS) were applied in a newly designed approach to optimal marker placement: the genetic evolutionary taboo search (GETS) algorithm. In the GETS paradigm, multiple solutions are simultaneously tested in a stochastic evolutionary scheme, where taboo-based decision making and adaptive memory guide the optimization process. The GETS algorithm was tested on a group of ten prostate patients, to be compared to standard optimization and to randomly selected configurations. The changes in the optimal marker configuration, when TRE is minimized for OARs, were specifically examined. Optimal GETS configurations ensured a 26.5% mean decrease in the TRE value, versus 19.4% for conventional quasi-Newton optimization. Common features in GETS marker configurations were highlighted in the dataset of ten patients, even when multiple runs of the stochastic algorithm were performed. Including OARs in TRE minimization did not considerably affect the spatial distribution of GETS marker configurations. In conclusion, the GETS algorithm proved to be highly effective in solving the optimal marker placement problem. Further work is needed to embed site-specific deformation models in the optimization process

Genetic structure among the local chicken ecotypes of Tanzania ...

African Journals Online (AJOL)

A study was conducted to evaluate the genetic structure of local chicken ecotypes of Tanzania using 20 polymorphic microsatellite DNA markers. A standard PCR was followed by manual genotyping (6% native polyacrylamide gel visualized by silver staining). Phylogenetic analysis of 13 individuals from each of the nine ...

Enhanced Approximate Nearest Neighbor via Local Area Focused Search.

Energy Technology Data Exchange (ETDEWEB)

Gonzales, Antonio [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Blazier, Nicholas Paul [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-02-01

Approximate Nearest Neighbor (ANN) algorithms are increasingly important in machine learning, data mining, and image processing applications. There is a large family of space- partitioning ANN algorithms, such as randomized KD-Trees, that work well in practice but are limited by an exponential increase in similarity comparisons required to optimize recall. Additionally, they only support a small set of similarity metrics. We present Local Area Fo- cused Search (LAFS), a method that enhances the way queries are performed using an existing ANN index. Instead of a single query, LAFS performs a number of smaller (fewer similarity comparisons) queries and focuses on a local neighborhood which is refined as candidates are identified. We show that our technique improves performance on several well known datasets and is easily extended to general similarity metrics using kernel projection techniques.

Genetic search for an optimal power flow solution from a high density cluster

Energy Technology Data Exchange (ETDEWEB)

Amarnath, R.V. [Hi-Tech College of Engineering and Technology, Hyderabad (India); Ramana, N.V. [JNTU College of Engineering, Jagityala (India)

2008-07-01

This paper proposed a novel method to solve optimal power flow (OPF) problems. The method is based on a genetic algorithm (GA) search from a High Density Cluster (GAHDC). The algorithm of the proposed method includes 3 stages, notably (1) a suboptimal solution is obtained via a conventional analytical method, (2) a high density cluster, which consists of other suboptimal data points from the first stage, is formed using a density-based cluster algorithm, and (3) a genetic algorithm based search is carried out for the exact optimal solution from a low population sized, high density cluster. The final optimal solution thoroughly satisfies the well defined fitness function. A standard IEEE 30-bus test system was considered for the simulation study. Numerical results were presented and compared with the results of other approaches. It was concluded that although there is not much difference in numerical values, the proposed method has the advantage of minimal computational effort and reduced CPU time. As such, the method would be suitable for online applications such as the present Optimal Power Flow problem. 24 refs., 2 tabs., 4 figs.

A Dedicated Genetic Algorithm for Localization of Moving Magnetic Objects

Directory of Open Access Journals (Sweden)

Roger Alimi

2015-09-01

Full Text Available A dedicated Genetic Algorithm (GA has been developed to localize the trajectory of ferromagnetic moving objects within a bounded perimeter. Localization of moving ferromagnetic objects is an important tool because it can be employed in situations when the object is obscured. This work is innovative for two main reasons: first, the GA has been tuned to provide an accurate and fast solution to the inverse magnetic field equations problem. Second, the algorithm has been successfully tested using real-life experimental data. Very accurate trajectory localization estimations were obtained over a wide range of scenarios.

Genetic structure of local populations of Lutzomyia longipalpis (Diptera: Psychodidae) in central Colombia.

Science.gov (United States)

Munstermann, L E; Morrison, A C; Ferro, C; Pardo, R; Torres, M

1998-01-01

Lutzomyia longipalpis (Lutz & Neiva), the sand fly vector of American visceral leishmaniasis in the New World tropics, has a broad but discontinuous geographical distribution from southern Mexico to Argentina. A baseline for population genetic structure and genetic variability for this species was obtained by analyzing 5 local, peridomestic populations at the approximate center of its distribution, the Magdalena River Valley of central Colombia. Three populations of L. longipalpis from El Callejón, a small rural community, were compared with 2 populations from neighboring areas 12 and 25 km distant for genetic variation at 15 isoenzyme loci. The mean heterozygosity ranged from 11 to 16%, with 1.2 to 2.3 alleles detected per locus. Nei's genetic distances among the populations were very low, ranging from 0.001 to 0.007. Gene flow estimates based on FST indicated high levels of gene flow among local L. longipalpis populations, with minimal population substructuring.

2nd International Conference on Harmony Search Algorithm

CERN Document Server

Geem, Zong

2016-01-01

The Harmony Search Algorithm (HSA) is one of the most well-known techniques in the field of soft computing, an important paradigm in the science and engineering community.  This volume, the proceedings of the 2nd International Conference on Harmony Search Algorithm 2015 (ICHSA 2015), brings together contributions describing the latest developments in the field of soft computing with a special focus on HSA techniques. It includes coverage of new methods that have potentially immense application in various fields. Contributed articles cover aspects of the following topics related to the Harmony Search Algorithm: analytical studies; improved, hybrid and multi-objective variants; parameter tuning; and large-scale applications.  The book also contains papers discussing recent advances on the following topics: genetic algorithms; evolutionary strategies; the firefly algorithm and cuckoo search; particle swarm optimization and ant colony optimization; simulated annealing; and local search techniques.   This book ...

Genetic variability of Indonesian local chili pepper: The facts

Science.gov (United States)

Arumingtyas, Estri Laras; Kusnadi, Joni; Sari, Dewi Ratih Tirto; Ratih, Nursita

2017-11-01

Chili pepper (Capsicum frutescens) is one species of Solanaceae family that is very popular in Indonesia and some other tropical countries because of its pungency. Chili pepper is an important spice in Indonesia and is also eaten fresh as a pickle to increase appetite. In Indonesia, there are various local names for chili pepper includingcabai, cengek, lombok, pedesan etc. These varied local names represent the various morphological shapes of the chili pepper fruit. We have investigated the variability of some chili cultivars based on morphological characteristics, molecular markers, pungency, and capsaicin content. Some biological facts, such as the tendency of chili pepper to outbreed, have also been found. In this paper, the source of variability and the possible mechanism of increasing genetic variability of Indonesian local chili pepper are also discussed.

Three hybridization models based on local search scheme for job shop scheduling problem

Science.gov (United States)

Balbi Fraga, Tatiana

2015-05-01

This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.

Local-regional control in breast cancer patients with a possible genetic predisposition

International Nuclear Information System (INIS)

Freedman, Laura M.; Buchholz, Thomas A.; Thames, Howard D.; Strom, Eric A.; McNeese, Marsha D.; Hortobagyi, Gabriel N.; Singletary, S. Eva; Heaton, Keith M.; Hunt, Kelly K.

2000-01-01

Purpose: Local control rates for breast cancer in genetically predisposed women are poorly defined. Because such a small percentage of breast cancer patients have proven germline mutations, surrogates, such as a family history for breast cancer, have been used to examine this issue. The purpose of this study was to evaluate local-regional control following breast conservation therapy (BCT) in patients with bilateral breast cancer and a breast cancer family history. Methods and Materials: We retrospectively reviewed records of all 58 patients with bilateral breast cancer and a breast cancer family history treated in our institution between 1959 and 1998. The primary surgical treatment was a breast-conserving procedure in 55 of the 116 breast cancer cases and a mastectomy in 61. The median follow-up was 68 months for the BCT patients and 57 months for the mastectomy-treated patients. Results: Eight local-regional recurrences occurred in the 55 cases treated with BCT, resulting in 5- and 10-year actuarial local-regional control rates of 86% and 76%, respectively. In the nine cases that did not receive radiation as a component of their BCT, four developed local-regional recurrences (5- and 10-year local-regional control rates of BCT without radiation: 49% and 49%). The 5- and 10-year actuarial local-regional control rates for the 46 cases treated with BCT and radiation were 94% and 83%, respectively. In these cases, there were two late local recurrences, developing at 8 years and 9 years, respectively. A log rank comparison of radiation versus no radiation actuarial data was significant at p = 0.009. In the cases treated with BCT, a multivariate analysis of radiation use, patient age, degree of family history, margin status, and stage revealed that only the use of radiation was associated with improved local control (Cox regression analysis p = 0.021). The 10-year actuarial rates of local-regional control following mastectomy with and without radiation were 91% and 89

Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining.

Science.gov (United States)

Salehi, Mojtaba; Bahreininejad, Ardeshir

2011-08-01

Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously.

A GPU Implementation of Local Search Operators for Symmetric Travelling Salesman Problem

Directory of Open Access Journals (Sweden)

Juraj Fosin

2013-06-01

Full Text Available The Travelling Salesman Problem (TSP is one of the most studied combinatorial optimization problem which is significant in many practical applications in transportation problems. The TSP problem is NP-hard problem and requires large computation power to be solved by the exact algorithms. In the past few years, fast development of general-purpose Graphics Processing Units (GPUs has brought huge improvement in decreasing the applications’ execution time. In this paper, we implement 2-opt and 3-opt local search operators for solving the TSP on the GPU using CUDA. The novelty presented in this paper is a new parallel iterated local search approach with 2-opt and 3-opt operators for symmetric TSP, optimized for the execution on GPUs. With our implementation large TSP problems (up to 85,900 cities can be solved using the GPU. We will show that our GPU implementation can be up to 20x faster without losing quality for all TSPlib problems as well as for our CRO TSP problem.

From Genetics to Genetic Algorithms

Indian Academy of Sciences (India)

Genetic algorithms (GAs) are computational optimisation schemes with an ... The algorithms solve optimisation problems ..... Genetic Algorithms in Search, Optimisation and Machine. Learning, Addison-Wesley Publishing Company, Inc. 1989.

High and distinct range-edge genetic diversity despite local bottlenecks.

Directory of Open Access Journals (Sweden)

Jorge Assis

Full Text Available The genetic consequences of living on the edge of distributional ranges have been the subject of a largely unresolved debate. Populations occurring along persistent low latitude ranges (rear-edge are expected to retain high and unique genetic diversity. In contrast, currently less favourable environmental conditions limiting population size at such range-edges may have caused genetic erosion that prevails over past historical effects, with potential consequences on reducing future adaptive capacity. The present study provides an empirical test of whether population declines towards a peripheral range might be reflected on decreasing diversity and increasing population isolation and differentiation. We compare population genetic differentiation and diversity with trends in abundance along a latitudinal gradient towards the peripheral distribution range of Saccorhiza polyschides, a large brown seaweed that is the main structural species of kelp forests in SW Europe. Signatures of recent bottleneck events were also evaluated to determine whether the recently recorded distributional shifts had a negative influence on effective population size. Our findings show decreasing population density and increasing spatial fragmentation and local extinctions towards the southern edge. Genetic data revealed two well supported groups with a central contact zone. As predicted, higher differentiation and signs of bottlenecks were found at the southern edge region. However, a decrease in genetic diversity associated with this pattern was not verified. Surprisingly, genetic diversity increased towards the edge despite bottlenecks and much lower densities, suggesting that extinctions and recolonizations have not strongly reduced diversity or that diversity might have been even higher there in the past, a process of shifting genetic baselines.

Genetic diversity and phylogenetic relationship of Indonesian Local goats using microsatellite DNA markers

Directory of Open Access Journals (Sweden)

M Syamsul Arifin Zein

2012-03-01

Full Text Available Genetic diversity is important information in the process of conservation and sustainable utilization of animal genetic resources. Thirteen microsatellite markers were used to estimate the degree of genetic diversity on five Indonesian local goats. Results showed the highest average allele diversity present in the locus MAF70 (5.6 ± 2.9, and the lowest was in the locus MAF035 (1.6 ± 0.6, the average number of alleles per locus was 6 ± 2.3. The lowest average alleles diversity present was in the Gembrong goat (2.2 ± 1.1 and the highest was in the Jawarandu goat (4.9 ± 2.2. There is a unique alleles at loci MCM527 and present in all Indonesian local goat with the highest allele frequency on Peranakan Etawa (37.2% and lowest in Gembrong goat (7.9%. H0 ranged from 0.372 ± 0.173 (Gembrong to 0.540 ± 0.204 (Peranakan Etawa, and HE ranging from 0.249 ± 0.196 (Gembrong to 0.540 ± 0.212 (Peranakan Etawa.The genetic differentiation for inbreeding among population (FIS, within population (FIT, and average genetic differention (FST were 0,0208 (2,08%, 0,1532 (15,32%, and 0,1352 (13,52%, respectively. Locus ILSTS029, BMS1494, MAF035 and INRA0132 had a low PIC value (PIC 0.5. Phylogenetic relationship was consistent with the history of its development based on Kacang goat except was for Gembrong Goat. This research information can be used for conservation strategies and breeding programs on each population of Indonesian local goat.

Genetic characterization of local Criollo pig breeds from the Americas using microsatellite markers.

Science.gov (United States)

Revidatti, M A; Delgado Bermejo, J V; Gama, L T; Landi Periati, V; Ginja, C; Alvarez, L A; Vega-Pla, J L; Martínez, A M

2014-11-01

Little is known about local Criollo pig genetic resources and relationships among the various populations. In this paper, genetic diversity and relationships among 17 Criollo pig populations from 11 American countries were assessed with 24 microsatellite markers. Heterozygosities, F-statistics, and genetic distances were estimated, and multivariate, genetic structure and admixture analyses were performed. The overall means for genetic variability parameters based on the 24 microsatellite markers were the following: mean number of alleles per locus of 6.25 ± 2.3; effective number of alleles per locus of 3.33 ± 1.56; allelic richness per locus of 4.61 ± 1.37; expected and observed heterozygosity of 0.62 ± 0.04 and 0.57 ± 0.02, respectively; within-population inbreeding coefficient of 0.089; and proportion of genetic variability accounted for by differences among breeds of 0.11 ± 0.01. Genetic differences were not significantly associated with the geographical location to which breeds were assigned or their country of origin. Still, the NeighborNet dendrogram depicted the clustering by geographic origin of several South American breeds (Criollo Boliviano, Criollo of northeastern Argentina wet, and Criollo of northeastern Argentina dry), but some unexpected results were also observed, such as the grouping of breeds from countries as distant as El Salvador, Mexico, Ecuador, and Cuba. The results of genetic structure and admixture analyses indicated that the most likely number of ancestral populations was 11, and most breeds clustered separately when this was the number of predefined populations, with the exception of some closely related breeds that shared the same cluster and others that were admixed. These results indicate that Criollo pigs represent important reservoirs of pig genetic diversity useful for local development as well as for the pig industry.

A reduced-cost iterated local search heuristic for the fixed-charge transportation problem

NARCIS (Netherlands)

Buson, Erika; Roberti, Roberto; Toth, Paolo

2014-01-01

The fixed-charge transportation problem (FCTP) is a generalization of the transportation problem where an additional fixed cost is paid for sending a flow from an origin to a destination. We propose an iterated local search heuristic based on the utilization of reduced costs for guiding the restart

Local environment but not genetic differentiation influences biparental care in ten plover populations.

Directory of Open Access Journals (Sweden)

Orsolya Vincze

Full Text Available Social behaviours are highly variable between species, populations and individuals. However, it is contentious whether behavioural variations are primarily moulded by the environment, caused by genetic differences, or a combination of both. Here we establish that biparental care, a complex social behaviour that involves rearing of young by both parents, differs between closely related populations, and then test two potential sources of variation in parental behaviour between populations: ambient environment and genetic differentiation. We use 2904 hours behavioural data from 10 geographically distinct Kentish (Charadrius alexandrinus and snowy plover (C. nivosus populations in America, Europe, the Middle East and North Africa to test these two sources of behavioural variation. We show that local ambient temperature has a significant influence on parental care: with extreme heat (above 40 °C total incubation (i.e. % of time the male or female incubated the nest increased, and female share (% female share of incubation decreased. By contrast, neither genetic differences between populations, nor geographic distances predicted total incubation or female's share of incubation. These results suggest that the local environment has a stronger influence on a social behaviour than genetic differentiation, at least between populations of closely related species.

searchSCF: Using MongoDB to Enable Richer Searches of Locally Hosted Science Data Repositories

Science.gov (United States)

Knosp, B.

2016-12-01

Science teams today are in the unusual position of almost having too much data available to them. Modern sensors and models are capable of outputting terabytes of data per day, which can make it difficult to find specific subsets of data. The sheer size of files can also make it time consuming to retrieve this big data from national data archive centers. Thus, many science teams choose to store what data they can on their local systems, but they are not always equipped with tools to help them intelligently organize and search their data. In its local data repository, the Aura Microwave Limb Sounder (MLS) science team at NASA's Jet Propulsion Laboratory has collected over 300TB of atmospheric science data from 71 missions/models that aid in validation, algorithm development, and research activities. When the project began, the team developed a MySQL database to aid in data queries, but this database was only designed to keep track of MLS and a few ancillary data sets, leving much of the data uncatalogued. The team has also seen database query time rise over the life of the mission. Even though the MLS science team's data holdings are not the size of a national data center's, team members still need tools to help them discover and utilize the data that they have on-hand. Over the past year, members of the science team have been looking for solutions to (1) store information on all the data sets they have collected in a single database, (2) store more metadata about each data file, (3) develop queries that can find relationships among these disparate data types, and (4) plug any new functions developed around this database into existing analysis, visualization, and web tools, transparently to users. In this presentation, I will discuss the searchSCF package that is currently under development. This package includes a NoSQL database management system (MongoDB) and a set of Python tools that both ingests data into the database and supports user queries. I will also

Constraint Programming based Local Search for the Vehicle Routing Problem with Time Windows

OpenAIRE

Sala Reixach, Joan

2012-01-01

El projecte es centra en el "Vehicle Routing Problem with Time Windows". Explora i testeja un mètode basat en una formulació del problema en termes de programació de restriccions. Implementa un mètode de cerca local amb la capacitat de fer grans moviments anomenat "Large Neighbourhood Search".

Iterated Local Search Algorithm with Strategic Oscillation for School Bus Routing Problem with Bus Stop Selection

Directory of Open Access Journals (Sweden)

Mohammad Saied Fallah Niasar

2017-02-01

Full Text Available he school bus routing problem (SBRP represents a variant of the well-known vehicle routing problem. The main goal of this study is to pick up students allocated to some bus stops and generate routes, including the selected stops, in order to carry students to school. In this paper, we have proposed a simple but effective metaheuristic approach that employs two features: first, it utilizes large neighborhood structures for a deeper exploration of the search space; second, the proposed heuristic executes an efficient transition between the feasible and infeasible portions of the search space. Exploration of the infeasible area is controlled by a dynamic penalty function to convert the unfeasible solution into a feasible one. Two metaheuristics, called N-ILS (a variant of the Nearest Neighbourhood with Iterated Local Search algorithm and I-ILS (a variant of Insertion with Iterated Local Search algorithm are proposed to solve SBRP. Our experimental procedure is based on the two data sets. The results show that N-ILS is able to obtain better solutions in shorter computing times. Additionally, N-ILS appears to be very competitive in comparison with the best existing metaheuristics suggested for SBRP

Local Path Planning of Driverless Car Navigation Based on Jump Point Search Method Under Urban Environment

Directory of Open Access Journals (Sweden)

Kaijun Zhou

2017-09-01

Full Text Available The Jump Point Search (JPS algorithm is adopted for local path planning of the driverless car under urban environment, and it is a fast search method applied in path planning. Firstly, a vector Geographic Information System (GIS map, including Global Positioning System (GPS position, direction, and lane information, is built for global path planning. Secondly, the GIS map database is utilized in global path planning for the driverless car. Then, the JPS algorithm is adopted to avoid the front obstacle, and to find an optimal local path for the driverless car in the urban environment. Finally, 125 different simulation experiments in the urban environment demonstrate that JPS can search out the optimal and safety path successfully, and meanwhile, it has a lower time complexity compared with the Vector Field Histogram (VFH, the Rapidly Exploring Random Tree (RRT, A*, and the Probabilistic Roadmaps (PRM algorithms. Furthermore, JPS is validated usefully in the structured urban environment.

A Rule-Based Local Search Algorithm for General Shift Design Problems in Airport Ground Handling

DEFF Research Database (Denmark)

Clausen, Tommy

We consider a generalized version of the shift design problem where shifts are created to cover a multiskilled demand and fit the parameters of the workforce. We present a collection of constraints and objectives for the generalized shift design problem. A local search solution framework with mul......We consider a generalized version of the shift design problem where shifts are created to cover a multiskilled demand and fit the parameters of the workforce. We present a collection of constraints and objectives for the generalized shift design problem. A local search solution framework...... with multiple neighborhoods and a loosely coupled rule engine based on simulated annealing is presented. Computational experiments on real-life data from various airport ground handling organization show the performance and flexibility of the proposed algorithm....

Collinearity Impairs Local Element Visual Search

Science.gov (United States)

Jingling, Li; Tseng, Chia-Huei

2013-01-01

In visual searches, stimuli following the law of good continuity attract attention to the global structure and receive attentional priority. Also, targets that have unique features are of high feature contrast and capture attention in visual search. We report on a salient global structure combined with a high orientation contrast to the…

Evacuation route planning during nuclear emergency using genetic algorithm

International Nuclear Information System (INIS)

Suman, Vitisha; Sarkar, P.K.

2012-01-01

In nuclear industry the routing in case of any emergency is a cause of concern and of great importance. Even the smallest of time saved in the affected region saves a huge amount of otherwise received dose. Genetic algorithm an optimization technique has great ability to search for the optimal path from the affected region to a destination station in a spatially addressed problem. Usually heuristic algorithms are used to carry out these types of search strategy, but due to the lack of global sampling in the feasible solution space, these algorithms have considerable possibility of being trapped into local optima. Routing problems mainly are search problems for finding the shortest distance within a time limit to cover the required number of stations taking care of the traffics, road quality, population size etc. Lack of any formal mechanisms to help decision-makers explore the solution space of their problem and thereby challenges their assumptions about the number and range of options available. The Genetic Algorithm provides a way to optimize a multi-parameter constrained problem with an ease. Here use of Genetic Algorithm to generate a range of options available and to search a solution space and selectively focus on promising combinations of criteria makes them ideally suited to such complex spatial decision problems. The emergency response and routing can be made efficient, in accessing the closest facilities and determining the shortest route using genetic algorithm. The accuracy and care in creating database can be used to improve the result of the final output. The Genetic algorithm can be used to improve the accuracy of result on the basis of distance where other algorithm cannot be obtained. The search space can be utilized to its great extend

Stochastic Local Search for Core Membership Checking in Hedonic Games

Science.gov (United States)

Keinänen, Helena

Hedonic games have emerged as an important tool in economics and show promise as a useful formalism to model multi-agent coalition formation in AI as well as group formation in social networks. We consider a coNP-complete problem of core membership checking in hedonic coalition formation games. No previous algorithms to tackle the problem have been presented. In this work, we overcome this by developing two stochastic local search algorithms for core membership checking in hedonic games. We demonstrate the usefulness of the algorithms by showing experimentally that they find solutions efficiently, particularly for large agent societies.

Windows .NET Network Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST

Directory of Open Access Journals (Sweden)

Oliver Melvin J

2005-04-01

Full Text Available Abstract Background BLAST is one of the most common and useful tools for Genetic Research. This paper describes a software application we have termed Windows .NET Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST, which enhances the BLAST utility by improving usability, fault recovery, and scalability in a Windows desktop environment. Our goal was to develop an easy to use, fault tolerant, high-throughput BLAST solution that incorporates a comprehensive BLAST result viewer with curation and annotation functionality. Results W.ND-BLAST is a comprehensive Windows-based software toolkit that targets researchers, including those with minimal computer skills, and provides the ability increase the performance of BLAST by distributing BLAST queries to any number of Windows based machines across local area networks (LAN. W.ND-BLAST provides intuitive Graphic User Interfaces (GUI for BLAST database creation, BLAST execution, BLAST output evaluation and BLAST result exportation. This software also provides several layers of fault tolerance and fault recovery to prevent loss of data if nodes or master machines fail. This paper lays out the functionality of W.ND-BLAST. W.ND-BLAST displays close to 100% performance efficiency when distributing tasks to 12 remote computers of the same performance class. A high throughput BLAST job which took 662.68 minutes (11 hours on one average machine was completed in 44.97 minutes when distributed to 17 nodes, which included lower performance class machines. Finally, there is a comprehensive high-throughput BLAST Output Viewer (BOV and Annotation Engine components, which provides comprehensive exportation of BLAST hits to text files, annotated fasta files, tables, or association files. Conclusion W.ND-BLAST provides an interactive tool that allows scientists to easily utilizing their available computing resources for high throughput and comprehensive sequence analyses. The install package for W.ND-BLAST is

Limited Pollen Dispersal Contributes to Population Genetic Structure but Not Local Adaptation in Quercus oleoides Forests of Costa Rica.

Directory of Open Access Journals (Sweden)

Nicholas John Deacon

Full Text Available Quercus oleoides Cham. and Schlect., tropical live oak, is a species of conservation importance in its southern range limit of northwestern Costa Rica. It occurs in high-density stands across a fragmented landscape spanning a contrasting elevation and precipitation gradient. We examined genetic diversity and spatial genetic structure in this geographically isolated and genetically distinct population. We characterized population genetic diversity at 11 nuclear microsatellite loci in 260 individuals from 13 sites. We monitored flowering time at 10 sites, and characterized the local environment in order to compare observed spatial genetic structure to hypotheses of isolation-by-distance and isolation-by-environment. Finally, we quantified pollen dispersal distances and tested for local adaptation through a reciprocal transplant experiment in order to experimentally address these hypotheses.High genetic diversity is maintained in the population and the genetic variation is significantly structured among sampled sites. We identified 5 distinct genetic clusters and average pollen dispersal predominately occurred over short distances. Differences among sites in flowering phenology and environmental factors, however, were not strictly associated with genetic differentiation. Growth and survival of upland and lowland progeny in their native and foreign environments was expected to exhibit evidence of local adaptation due to the more extreme dry season in the lowlands. Seedlings planted in the lowland garden experienced much higher mortality than seedlings in the upland garden, but we did not identify evidence for local adaptation.Overall, this study indicates that the Costa Rican Q. oleoides population has a rich population genetic history. Despite environmental heterogeneity and habitat fragmentation, isolation-by-distance and isolation-by-environment alone do not explain spatial genetic structure. These results add to studies of genetic structure by

Limited Pollen Dispersal Contributes to Population Genetic Structure but Not Local Adaptation in Quercus oleoides Forests of Costa Rica.

Science.gov (United States)

Deacon, Nicholas John; Cavender-Bares, Jeannine

2015-01-01

Quercus oleoides Cham. and Schlect., tropical live oak, is a species of conservation importance in its southern range limit of northwestern Costa Rica. It occurs in high-density stands across a fragmented landscape spanning a contrasting elevation and precipitation gradient. We examined genetic diversity and spatial genetic structure in this geographically isolated and genetically distinct population. We characterized population genetic diversity at 11 nuclear microsatellite loci in 260 individuals from 13 sites. We monitored flowering time at 10 sites, and characterized the local environment in order to compare observed spatial genetic structure to hypotheses of isolation-by-distance and isolation-by-environment. Finally, we quantified pollen dispersal distances and tested for local adaptation through a reciprocal transplant experiment in order to experimentally address these hypotheses. High genetic diversity is maintained in the population and the genetic variation is significantly structured among sampled sites. We identified 5 distinct genetic clusters and average pollen dispersal predominately occurred over short distances. Differences among sites in flowering phenology and environmental factors, however, were not strictly associated with genetic differentiation. Growth and survival of upland and lowland progeny in their native and foreign environments was expected to exhibit evidence of local adaptation due to the more extreme dry season in the lowlands. Seedlings planted in the lowland garden experienced much higher mortality than seedlings in the upland garden, but we did not identify evidence for local adaptation. Overall, this study indicates that the Costa Rican Q. oleoides population has a rich population genetic history. Despite environmental heterogeneity and habitat fragmentation, isolation-by-distance and isolation-by-environment alone do not explain spatial genetic structure. These results add to studies of genetic structure by examining a common

Nigerian Journal of Genetics: Advanced Search

African Journals Online (AJOL)

Search tips: Search terms are case-insensitive; Common words are ignored; By default only articles containing all terms in the query are returned (i.e., AND is implied); Combine multiple words with OR to find articles containing either term; e.g., education OR research; Use parentheses to create more complex queries; e.g., ...

A hybrid genetic algorithm for the distributed permutation flowshop scheduling problem

Directory of Open Access Journals (Sweden)

Jian Gao

2011-08-01

Full Text Available Distributed Permutation Flowshop Scheduling Problem (DPFSP is a newly proposed scheduling problem, which is a generalization of classical permutation flow shop scheduling problem. The DPFSP is NP-hard in general. It is in the early stages of studies on algorithms for solving this problem. In this paper, we propose a GA-based algorithm, denoted by GA_LS, for solving this problem with objective to minimize the maximum completion time. In the proposed GA_LS, crossover and mutation operators are designed to make it suitable for the representation of DPFSP solutions, where the set of partial job sequences is employed. Furthermore, GA_LS utilizes an efficient local search method to explore neighboring solutions. The local search method uses three proposed rules that move jobs within a factory or between two factories. Intensive experiments on the benchmark instances, extended from Taillard instances, are carried out. The results indicate that the proposed hybrid genetic algorithm can obtain better solutions than all the existing algorithms for the DPFSP, since it obtains better relative percentage deviation and differences of the results are also statistically significant. It is also seen that best-known solutions for most instances are updated by our algorithm. Moreover, we also show the efficiency of the GA_LS by comparing with similar genetic algorithms with the existing local search methods.

Multiobjective pressurized water reactor reload core design by nondominated genetic algorithm search

International Nuclear Information System (INIS)

Parks, G.T.

1996-01-01

The design of pressurized water reactor reload cores is not only a formidable optimization problem but also, in many instances, a multiobjective problem. A genetic algorithm (GA) designed to perform true multiobjective optimization on such problems is described. Genetic algorithms simulate natural evolution. They differ from most optimization techniques by searching from one group of solutions to another, rather than from one solution to another. New solutions are generated by breeding from existing solutions. By selecting better (in a multiobjective sense) solutions as parents more often, the population can be evolved to reveal the trade-off surface between the competing objectives. An example illustrating the effectiveness of this novel method is presented and analyzed. It is found that in solving a reload design problem the algorithm evaluates a similar number of loading patterns to other state-of-the-art methods, but in the process reveals much more information about the nature of the problem being solved. The actual computational cost incurred depends on the core simulator used; the GA itself is code independent

Improved Genetic Algorithm Based on the Cooperation of Elite and Inverse-elite

Science.gov (United States)

Kanakubo, Masaaki; Hagiwara, Masafumi

In this paper, we propose an improved genetic algorithm based on the combination of Bee system and Inverse-elitism, both are effective strategies for the improvement of GA. In the Bee system, in the beginning, each chromosome tries to find good solution individually as global search. When some chromosome is regarded as superior one, the other chromosomes try to find solution around there. However, since chromosomes for global search are generated randomly, Bee system lacks global search ability. On the other hand, in the Inverse-elitism, an inverse-elite whose gene values are reversed from the corresponding elite is produced. This strategy greatly contributes to diversification of chromosomes, but it lacks local search ability. In the proposed method, the Inverse-elitism with Pseudo-simplex method is employed for global search of Bee system in order to strengthen global search ability. In addition, it also has strong local search ability. The proposed method has synergistic effects of the three strategies. We confirmed validity and superior performance of the proposed method by computer simulations.

A Framework for Similarity Search with Space-Time Tradeoffs using Locality Sensitive Filtering

DEFF Research Database (Denmark)

Christiani, Tobias Lybecker

2017-01-01

that satisfies certain locality-sensitivity properties, we can construct a dynamic data structure that solves the approximate near neighbor problem in $d$-dimensional space with query time $dn^{\\rho_q + o(1)}$, update time $dn^{\\rho_u + o(1)}$, and space usage $dn + n^{1 + \\rho_u + o(1)}$ where $n$ denotes......We present a framework for similarity search based on Locality-Sensitive Filtering~(LSF),generalizing the Indyk-Motwani (STOC 1998) Locality-Sensitive Hashing~(LSH) framework to support space-time tradeoffs. Given a family of filters, defined as a distribution over pairs of subsets of space...... the number of points in the data structure.The space-time tradeoff is tied to the tradeoff between query time and update time (insertions/deletions), controlled by the exponents $\\rho_q, \\rho_u$ that are determined by the filter family. \\\\ Locality-sensitive filtering was introduced by Becker et al. (SODA...

Population genetics models of local ancestry.

Science.gov (United States)

Gravel, Simon

2012-06-01

Migrations have played an important role in shaping the genetic diversity of human populations. Understanding genomic data thus requires careful modeling of historical gene flow. Here we consider the effect of relatively recent population structure and gene flow and interpret genomes of individuals that have ancestry from multiple source populations as mosaics of segments originating from each population. This article describes general and tractable models for local ancestry patterns with a focus on the length distribution of continuous ancestry tracts and the variance in total ancestry proportions among individuals. The models offer improved agreement with Wright-Fisher simulation data when compared to the state-of-the art and can be used to infer time-dependent migration rates from multiple populations. Considering HapMap African-American (ASW) data, we find that a model with two distinct phases of "European" gene flow significantly improves the modeling of both tract lengths and ancestry variances.

Searching for full power control rod patterns in a boiling water reactor using genetic algorithms

Energy Technology Data Exchange (ETDEWEB)

Montes, Jose Luis [Departamento Sistemas Nucleares, ININ, Carr. Mexico-Toluca Km. 36.5, Ocoyoacac, Edo. de Mexico (Mexico)]. E-mail: jlmt@nuclear.inin.mx; Ortiz, Juan Jose [Departamento Sistemas Nucleares, ININ, Carr. Mexico-Toluca Km. 36.5, Ocoyoacac, Edo. de Mexico (Mexico)]. E-mail: jjortiz@nuclear.inin.mx; Requena, Ignacio [Departamento Ciencias Computacion e I.A. ETSII, Informatica, Universidad de Granada, C. Daniel Saucedo Aranda s/n. 18071 Granada (Spain)]. E-mail: requena@decsai.ugr.es; Perusquia, Raul [Departamento Sistemas Nucleares, ININ, Carr. Mexico-Toluca Km. 36.5, Ocoyoacac, Edo. de Mexico (Mexico)]. E-mail: rpc@nuclear.inin.mx

2004-11-01

One of the most important questions related to both safety and economic aspects in a nuclear power reactor operation, is without any doubt its reactivity control. During normal operation of a boiling water reactor, the reactivity control of its core is strongly determined by control rods patterns efficiency. In this paper, GACRP system is proposed based on the concepts of genetic algorithms for full power control rod patterns search. This system was carried out using LVNPP transition cycle characteristics, being applied too to an equilibrium cycle. Several operation scenarios, including core water flow variation throughout the cycle and different target axial power distributions, are considered. Genetic algorithm fitness function includes reactor security parameters, such as MLHGR, MCPR, reactor k{sub eff} and axial power density.

A local search for a graph clustering problem

Science.gov (United States)

Navrotskaya, Anna; Il'ev, Victor

2016-10-01

In the clustering problems one has to partition a given set of objects (a data set) into some subsets (called clusters) taking into consideration only similarity of the objects. One of most visual formalizations of clustering is graph clustering, that is grouping the vertices of a graph into clusters taking into consideration the edge structure of the graph whose vertices are objects and edges represent similarities between the objects. In the graph k-clustering problem the number of clusters does not exceed k and the goal is to minimize the number of edges between clusters and the number of missing edges within clusters. This problem is NP-hard for any k ≥ 2. We propose a polynomial time (2k-1)-approximation algorithm for graph k-clustering. Then we apply a local search procedure to the feasible solution found by this algorithm and hold experimental research of obtained heuristics.

Earthquake—explosion discrimination using genetic algorithm-based boosting approach

Science.gov (United States)

Orlic, Niksa; Loncaric, Sven

2010-02-01

An important and challenging problem in seismic data processing is to discriminate between natural seismic events such as earthquakes and artificial seismic events such as explosions. Many automatic techniques for seismogram classification have been proposed in the literature. Most of these methods have a similar approach to seismogram classification: a predefined set of features based on ad-hoc feature selection criteria is extracted from the seismogram waveform or spectral data and these features are used for signal classification. In this paper we propose a novel approach for seismogram classification. A specially formulated genetic algorithm has been employed to automatically search for a near-optimal seismogram feature set, instead of using ad-hoc feature selection criteria. A boosting method is added to the genetic algorithm when searching for multiple features in order to improve classification performance. A learning set of seismogram data is used by the genetic algorithm to discover a near-optimal feature set. The feature set identified by the genetic algorithm is then used for seismogram classification. The described method is developed to classify seismograms in two groups, whereas a brief overview of method extension for multiple group classification is given. For method verification, a learning set consisting of 40 local earthquake seismograms and 40 explosion seismograms was used. The method was validated on seismogram set consisting of 60 local earthquake seismograms and 60 explosion seismograms, with correct classification of 85%.

An Improved Chaos Genetic Algorithm for T-Shaped MIMO Radar Antenna Array Optimization

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Xin Fu

2014-01-01

Full Text Available In view of the fact that the traditional genetic algorithm easily falls into local optimum in the late iterations, an improved chaos genetic algorithm employed chaos theory and genetic algorithm is presented to optimize the low side-lobe for T-shaped MIMO radar antenna array. The novel two-dimension Cat chaotic map has been put forward to produce its initial population, improving the diversity of individuals. The improved Tent map is presented for groups of individuals of a generation with chaos disturbance. Improved chaotic genetic algorithm optimization model is established. The algorithm presented in this paper not only improved the search precision, but also avoids effectively the problem of local convergence and prematurity. For MIMO radar, the improved chaos genetic algorithm proposed in this paper obtains lower side-lobe level through optimizing the exciting current amplitude. Simulation results show that the algorithm is feasible and effective. Its performance is superior to the traditional genetic algorithm.

The genetic basis of local adaptation for pathogenic fungi in agricultural ecosystems.

Science.gov (United States)

Croll, Daniel; McDonald, Bruce A

2017-04-01

Local adaptation plays a key role in the evolutionary trajectory of host-pathogen interactions. However, the genetic architecture of local adaptation in host-pathogen systems is poorly understood. Fungal plant pathogens in agricultural ecosystems provide highly tractable models to quantify phenotypes and map traits to corresponding genomic loci. The outcome of crop-pathogen interactions is thought to be governed largely by gene-for-gene interactions. However, recent studies showed that virulence can be governed by quantitative trait loci and that many abiotic factors contribute to the outcome of the interaction. After introducing concepts of local adaptation and presenting examples from wild plant pathosystems, we focus this review on a major pathogen of wheat, Zymoseptoria tritici, to show how a multitude of traits can affect local adaptation. Zymoseptoria tritici adapted to different thermal environments across its distribution range, indicating that thermal adaptation may limit effective dispersal to different climates. The application of fungicides led to the rapid evolution of multiple, independent resistant populations. The degree of colony melanization showed strong pleiotropic effects with other traits, including trade-offs with colony growth rates and fungicide sensitivity. The success of the pathogen on its host can be assessed quantitatively by counting pathogen reproductive structures and measuring host damage based on necrotic lesions. Interestingly, these two traits can be weakly correlated and depend both on host and pathogen genotypes. Quantitative trait mapping studies showed that the genetic architecture of locally adapted traits varies from single loci with large effects to many loci with small individual effects. We discuss how local adaptation could hinder or accelerate the development of epidemics in agricultural ecosystems. © 2016 John Wiley & Sons Ltd.

Compositional searching of CpG islands in the human genome

Science.gov (United States)

Luque-Escamilla, Pedro Luis; Martínez-Aroza, José; Oliver, José L.; Gómez-Lopera, Juan Francisco; Román-Roldán, Ramón

2005-06-01

We report on an entropic edge detector based on the local calculation of the Jensen-Shannon divergence with application to the search for CpG islands. CpG islands are pieces of the genome related to gene expression and cell differentiation, and thus to cancer formation. Searching for these CpG islands is a major task in genetics and bioinformatics. Some algorithms have been proposed in the literature, based on moving statistics in a sliding window, but its size may greatly influence the results. The local use of Jensen-Shannon divergence is a completely different strategy: the nucleotide composition inside the islands is different from that in their environment, so a statistical distance—the Jensen-Shannon divergence—between the composition of two adjacent windows may be used as a measure of their dissimilarity. Sliding this double window over the entire sequence allows us to segment it compositionally. The fusion of those segments into greater ones that satisfy certain identification criteria must be achieved in order to obtain the definitive results. We find that the local use of Jensen-Shannon divergence is very suitable in processing DNA sequences for searching for compositionally different structures such as CpG islands, as compared to other algorithms in literature.

Comparison of a constraint directed search to a genetic algorithm in a scheduling application

International Nuclear Information System (INIS)

Abbott, L.

1993-01-01

Scheduling plutonium containers for blending is a time-intensive operation. Several constraints must be taken into account; including the number of containers in a dissolver run, the size of each dissolver run, and the size and target purity of the blended mixture formed from these runs. Two types of algorithms have been used to solve this problem: a constraint directed search and a genetic algorithm. This paper discusses the implementation of these two different approaches to the problem and the strengths and weaknesses of each algorithm

A Hybrid Genetic Programming Algorithm for Automated Design of Dispatching Rules.

Science.gov (United States)

Nguyen, Su; Mei, Yi; Xue, Bing; Zhang, Mengjie

2018-06-04

Designing effective dispatching rules for production systems is a difficult and timeconsuming task if it is done manually. In the last decade, the growth of computing power, advanced machine learning, and optimisation techniques has made the automated design of dispatching rules possible and automatically discovered rules are competitive or outperform existing rules developed by researchers. Genetic programming is one of the most popular approaches to discovering dispatching rules in the literature, especially for complex production systems. However, the large heuristic search space may restrict genetic programming from finding near optimal dispatching rules. This paper develops a new hybrid genetic programming algorithm for dynamic job shop scheduling based on a new representation, a new local search heuristic, and efficient fitness evaluators. Experiments show that the new method is effective regarding the quality of evolved rules. Moreover, evolved rules are also significantly smaller and contain more relevant attributes.

Preservation of the genetic diversity of a local common carp in the agricultural heritage rice–fish system

Science.gov (United States)

Ren, Weizheng; Hu, Liangliang; Guo, Liang; Zhang, Jian; Tang, Lu; Zhang, Entao; Zhang, Jiaen; Luo, Shiming; Tang, Jianjun; Chen, Xin

2018-01-01

We examined how traditional farmers preserve the genetic diversity of a local common carp (Cyprinus carpio), which is locally referred to as “paddy field carp” (PF-carp), in a “globally important agricultural heritage system” (GIAHS), i.e., the 1,200-y-old rice–fish coculture system in Zhejiang Province, China. Our molecular and morphological analysis showed that the PF-carp has changed into a distinct local population with higher genetic diversity and diverse color types. Within this GIAHS region, PF-carps exist as a continuous metapopulation, although three genetic groups could be identified by microsatellite markers. Thousands of small farmer households interdependently obtained fry and parental carps for their own rice–fish production, resulting in a high gene flow and large numbers of parent carps distributing in a mosaic pattern in the region. Landscape genetic analysis indicated that farmers’ connectivity was one of the major factors that shaped this genetic pattern. Population viability analysis further revealed that the numbers of these interconnected small farmer households and their connection intensity affect the carps’ inherent genetic diversity. The practice of mixed culturing of carps with diverse color types helped to preserve a wide range of genetic resources in the paddy field. This widespread traditional practice increases fish yield and resource use, which, in return, encourages famers to continue their practice of selecting and conserving diverse color types of PF-carp. Our results suggested that traditional farmers secure the genetic diversity of PF-carp and its viability over generations in this region through interdependently incubating and mixed-culturing practices within the rice−fish system. PMID:29295926

Nonlinear inversion of potential-field data using a hybrid-encoding genetic algorithm

Science.gov (United States)

Chen, C.; Xia, J.; Liu, J.; Feng, G.

2006-01-01

Using a genetic algorithm to solve an inverse problem of complex nonlinear geophysical equations is advantageous because it does not require computer gradients of models or "good" initial models. The multi-point search of a genetic algorithm makes it easier to find the globally optimal solution while avoiding falling into a local extremum. As is the case in other optimization approaches, the search efficiency for a genetic algorithm is vital in finding desired solutions successfully in a multi-dimensional model space. A binary-encoding genetic algorithm is hardly ever used to resolve an optimization problem such as a simple geophysical inversion with only three unknowns. The encoding mechanism, genetic operators, and population size of the genetic algorithm greatly affect search processes in the evolution. It is clear that improved operators and proper population size promote the convergence. Nevertheless, not all genetic operations perform perfectly while searching under either a uniform binary or a decimal encoding system. With the binary encoding mechanism, the crossover scheme may produce more new individuals than with the decimal encoding. On the other hand, the mutation scheme in a decimal encoding system will create new genes larger in scope than those in the binary encoding. This paper discusses approaches of exploiting the search potential of genetic operations in the two encoding systems and presents an approach with a hybrid-encoding mechanism, multi-point crossover, and dynamic population size for geophysical inversion. We present a method that is based on the routine in which the mutation operation is conducted in the decimal code and multi-point crossover operation in the binary code. The mix-encoding algorithm is called the hybrid-encoding genetic algorithm (HEGA). HEGA provides better genes with a higher probability by a mutation operator and improves genetic algorithms in resolving complicated geophysical inverse problems. Another significant

A SOUND SOURCE LOCALIZATION TECHNIQUE TO SUPPORT SEARCH AND RESCUE IN LOUD NOISE ENVIRONMENTS

Science.gov (United States)

Yoshinaga, Hiroshi; Mizutani, Koichi; Wakatsuki, Naoto

At some sites of earthquakes and other disasters, rescuers search for people buried under rubble by listening for the sounds which they make. Thus developing a technique to localize sound sources amidst loud noise will support such search and rescue operations. In this paper, we discuss an experiment performed to test an array signal processing technique which searches for unperceivable sound in loud noise environments. Two speakers simultaneously played a noise of a generator and a voice decreased by 20 dB (= 1/100 of power) from the generator noise at an outdoor space where cicadas were making noise. The sound signal was received by a horizontally set linear microphone array 1.05 m in length and consisting of 15 microphones. The direction and the distance of the voice were computed and the sound of the voice was extracted and played back as an audible sound by array signal processing.

On the Runtime of Randomized Local Search and Simple Evolutionary Algorithms for Dynamic Makespan Scheduling

DEFF Research Database (Denmark)

Neumann, Frank; Witt, Carsten

2015-01-01

combinatorial optimization problem, namely makespan scheduling. We study the model of a strong adversary which is allowed to change one job at regular intervals. Furthermore, we investigate the setting of random changes. Our results show that randomized local search and a simple evolutionary algorithm are very...

Estimation of genetic parameters for milk traits in Romanian local sheep breed

Directory of Open Access Journals (Sweden)

Pelmus RS

2014-03-01

Full Text Available Objective. Estimate the genetic parameters for milk traits in a Romanian local sheep population Teleorman Black Head. Material and methods. Records of 262 sheep belonging to 17 rams and 139 ewes were used in the study. The following traits were investigated: milk yield, fat yield, protein yield, fat percentage and protein percentage. The genetic parameters were estimated using the Restricted Maximum Likelihood method, with a model including maternal effects. Results. The results from our study revealed that direct heritability estimates were moderate for milk yield (0.449, fat yield (0.442, protein yield (0.386 while for protein percentage (0.708 and fat percentage (0.924 were high. The high direct and maternal genetic correlation was between milk yield and protein yield (0.979, 0.973 and between protein yield and fat yield (0.952, 0.913 while the phenotypic correlation between the milk yield and fat yield (0.968, the milk yield and protein yield (0.967, fat yield and protein yield (0.936 was high and positive. Conclusions. The genetic parameters are important in selection program on this breed for genetic improvement.

Real-Time Ligand Binding Pocket Database Search Using Local Surface Descriptors

Science.gov (United States)

Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

2010-01-01

Due to the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of a particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two dimensional pseudo-Zernike moments or the 3D Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark study employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed. PMID:20455259

Genetic algorithms

Science.gov (United States)

Wang, Lui; Bayer, Steven E.

1991-01-01

Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.

Genetic diversity of five local Swedish chicken breeds detected by microsatellite markers.

Directory of Open Access Journals (Sweden)

Abiye Shenkut Abebe

Full Text Available This study aimed at investigating the genetic diversity, relationship and population structure of 110 local Swedish chickens derived from five breeds (Gotlandshöna, Hedemorahöna, Öländsk dvärghöna, Skånsk blommehöna, and Bohuslän- Dals svarthöna, in the rest of the paper the shorter name Svarthöna is used using 24 microsatellite markers. In total, one hundred thirteen alleles were detected in all populations, with a mean of 4.7 alleles per locus. For the five chicken breeds, the observed and expected heterozygosity ranged from 0.225 to 0.408 and from 0.231 to 0.515, with the lowest scores for the Svarthöna and the highest scores for the Skånsk blommehöna breeds, respectively. Similarly, the average within breed molecular kinship varied from 0.496 to 0.745, showing high coancestry, with Skånsk blommehöna having the lowest and Svarthöna the highest coancestry. Furthermore, all breeds showed significant deviations from Hardy-Weinberg expectations. Across the five breeds, the global heterozygosity deficit (FIT was 0.545, population differentiation index (FST was 0.440, and the global inbreeding of individuals within breed (FIS was 0.187. The phylogenetic relationships of chickens were examined using neighbor-joining trees constructed at the level of breeds and individual samples. The neighbor-joining tree constructed at breed level revealed two main clusters, with Hedemorahöna and Öländsk dvärghöna breeds in one cluster, and Gotlandshöna and Svarthöna breeds in the second cluster leaving the Skånsk blommehöna in the middle. Based on the results of the STRUCTURE analysis, the most likely number of clustering of the five breeds was at K = 4, with Hedemorahöna, Gotlandshöna and Svarthöna breeds forming their own distinct clusters, while Öländsk dvärghöna and Skånsk blommehöna breeds clustered together. Losses in the overall genetic diversity of local Swedish chickens due to breeds extinction varied from -1.46% to -6

A Local and Global Search Combined Particle Swarm Optimization Algorithm and Its Convergence Analysis

Directory of Open Access Journals (Sweden)

Weitian Lin

2014-01-01

Full Text Available Particle swarm optimization algorithm (PSOA is an advantage optimization tool. However, it has a tendency to get stuck in a near optimal solution especially for middle and large size problems and it is difficult to improve solution accuracy by fine-tuning parameters. According to the insufficiency, this paper researches the local and global search combine particle swarm algorithm (LGSCPSOA, and its convergence and obtains its convergence qualification. At the same time, it is tested with a set of 8 benchmark continuous functions and compared their optimization results with original particle swarm algorithm (OPSOA. Experimental results indicate that the LGSCPSOA improves the search performance especially on the middle and large size benchmark functions significantly.

Expectations and experiences of gamete donors and donor-conceived adults searching for genetic relatives using DNA linking through a voluntary register.

Science.gov (United States)

van den Akker, O B A; Crawshaw, M A; Blyth, E D; Frith, L J

2015-01-01

What are the experiences of donor-conceived adults and donors who are searching for a genetic link through the use of a DNA-based voluntary register service? Donor-conceived adults and donors held positive beliefs about their search and although some concerns in relation to finding a genetically linked relative were reported, these were not a barrier to searching. Research with donor-conceived people has consistently identified their interest in learning about-and in some cases making contact with-their donor and other genetic relatives. However, donor-conceived individuals or donors rarely have the opportunity to act on these desires. A questionnaire was administered for online completion using Bristol Online Surveys. The survey was live for 3 months and responses were collected anonymously. The survey was completed by 65 donor-conceived adults, 21 sperm donors and 5 oocyte donors who had registered with a DNA-based voluntary contact register in the UK. The questionnaire included socio-demographic questions, questions specifically developed for the purposes of this study and the standardized Aspects of Identity Questionnaire (AIQ). Motivations for searching for genetic relatives were varied, with the most common reasons being curiosity and passing on information. Overall, participants who were already linked and those awaiting a link were positive about being linked and valued access to a DNA-based register. Collective identity (reflecting self-defining feelings of continuity and uniqueness), as assessed by the AIQ, was significantly lower for donor-conceived adults when compared with the donor groups (P 0.05) for donor-conceived adults. Participants were members of a UK DNA-based registry which is unique. It was therefore not possible to determine how representative participants were of those who did not register for the service, those in other countries or of those who do not seek information exchange or contact. This is the first survey exploring the

Genetic Localization of Foraging (For): A Major Gene for Larval Behavior in Drosophila Melanogaster

OpenAIRE

de-Belle, J. S.; Hilliker, A. J.; Sokolowski, M. B.

1989-01-01

Localizing genes for quantitative traits by conventional recombination mapping is a formidable challenge because environmental variation, minor genes, and genetic markers have modifying effects on continuously varying phenotypes. We describe ``lethal tagging,'' a method used in conjunction with deficiency mapping for localizing major genes associated with quantitative traits. Rover/sitter is a naturally occurring larval foraging polymorphism in Drosophila melanogaster which has a polygenic pa...

Parameter estimation for chaotic systems using a hybrid adaptive cuckoo search with simulated annealing algorithm

Energy Technology Data Exchange (ETDEWEB)

Sheng, Zheng, E-mail: 19994035@sina.com [College of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101 (China); Wang, Jun; Zhou, Bihua [National Defense Key Laboratory on Lightning Protection and Electromagnetic Camouflage, PLA University of Science and Technology, Nanjing 210007 (China); Zhou, Shudao [College of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101 (China); Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044 (China)

2014-03-15

This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented to tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm.

Parameter estimation for chaotic systems using a hybrid adaptive cuckoo search with simulated annealing algorithm

International Nuclear Information System (INIS)

Sheng, Zheng; Wang, Jun; Zhou, Bihua; Zhou, Shudao

2014-01-01

This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented to tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm

Interactive searching of facial image databases

Science.gov (United States)

Nicholls, Robert A.; Shepherd, John W.; Shepherd, Jean

1995-09-01

A set of psychological facial descriptors has been devised to enable computerized searching of criminal photograph albums. The descriptors have been used to encode image databased of up to twelve thousand images. Using a system called FACES, the databases are searched by translating a witness' verbal description into corresponding facial descriptors. Trials of FACES have shown that this coding scheme is more productive and efficient than searching traditional photograph albums. An alternative method of searching the encoded database using a genetic algorithm is currenly being tested. The genetic search method does not require the witness to verbalize a description of the target but merely to indicate a degree of similarity between the target and a limited selection of images from the database. The major drawback of FACES is that is requires a manual encoding of images. Research is being undertaken to automate the process, however, it will require an algorithm which can predict human descriptive values. Alternatives to human derived coding schemes exist using statistical classifications of images. Since databases encoded using statistical classifiers do not have an obvious direct mapping to human derived descriptors, a search method which does not require the entry of human descriptors is required. A genetic search algorithm is being tested for such a purpose.

Hitting times of local and global optima in genetic algorithms with very high selection pressure

Directory of Open Access Journals (Sweden)

Eremeev Anton V.

2017-01-01

Full Text Available The paper is devoted to upper bounds on the expected first hitting times of the sets of local or global optima for non-elitist genetic algorithms with very high selection pressure. The results of this paper extend the range of situations where the upper bounds on the expected runtime are known for genetic algorithms and apply, in particular, to the Canonical Genetic Algorithm. The obtained bounds do not require the probability of fitness-decreasing mutation to be bounded by a constant which is less than one.

Harmony Search for Balancing Two-sided Assembly Lines

Directory of Open Access Journals (Sweden)

Hindriyanto Dwi Purnomo

2012-01-01

Full Text Available Two-sided assembly lines balancing problems are important problem for large-sized products such as cars and buses, in which, tasks operations can be performed in the two sides of the line. In this paper, Harmony Search algorithm is proposed to solve two-sided assembly lines balancing problems type-I (TALBP-I. The proposed method adopts the COMSOAL heuristic and specific features of TALBP in the Harmony operators – the harmony memory consideration, random selection and pitch adjustment – in order to maintain the local and global search. The proposed method is evaluated based on 6 benchmark problems that are commonly used in TALBP. The experiment results show that the proposed method work well and produces better solution than the heuristic method and genetic algorithm.

Comparison tomography relocation hypocenter grid search and guided grid search method in Java island

International Nuclear Information System (INIS)

Nurdian, S. W.; Adu, N.; Palupi, I. R.; Raharjo, W.

2016-01-01

The main data in this research is earthquake data recorded from 1952 to 2012 with 9162 P wave and 2426 events are recorded by 30 stations located around Java island. Relocation hypocenter processed using grid search and guidded grid search method. Then the result of relocation hypocenter become input for tomography pseudo bending inversion process. It can be used to identification the velocity distribution in subsurface. The result of relocation hypocenter by grid search and guided grid search method after tomography process shown in locally and globally. In locally area grid search method result is better than guided grid search according to geological reseach area. But in globally area the result of guided grid search method is better for a broad area because the velocity variation is more diverse than the other one and in accordance with local geological research conditions. (paper)

An efficient implementation of maximum likelihood identification of LTI state-space models by local gradient search

NARCIS (Netherlands)

Bergboer, N.H.; Verdult, V.; Verhaegen, M.H.G.

2002-01-01

We present a numerically efficient implementation of the nonlinear least squares and maximum likelihood identification of multivariable linear time-invariant (LTI) state-space models. This implementation is based on a local parameterization of the system and a gradient search in the resulting

Global search in photoelectron diffraction structure determination using genetic algorithms

Energy Technology Data Exchange (ETDEWEB)

Viana, M L [Departamento de Fisica, Icex, UFMG, Belo Horizonte, Minas Gerais (Brazil); Muino, R Diez [Donostia International Physics Center DIPC, Paseo Manuel de Lardizabal 4, 20018 San Sebastian (Spain); Soares, E A [Departamento de Fisica, Icex, UFMG, Belo Horizonte, Minas Gerais (Brazil); Hove, M A Van [Department of Physics and Materials Science, City University of Hong Kong, Hong Kong (China); Carvalho, V E de [Departamento de Fisica, Icex, UFMG, Belo Horizonte, Minas Gerais (Brazil)

2007-11-07

Photoelectron diffraction (PED) is an experimental technique widely used to perform structural determinations of solid surfaces. Similarly to low-energy electron diffraction (LEED), structural determination by PED requires a fitting procedure between the experimental intensities and theoretical results obtained through simulations. Multiple scattering has been shown to be an effective approach for making such simulations. The quality of the fit can be quantified through the so-called R-factor. Therefore, the fitting procedure is, indeed, an R-factor minimization problem. However, the topography of the R-factor as a function of the structural and non-structural surface parameters to be determined is complex, and the task of finding the global minimum becomes tough, particularly for complex structures in which many parameters have to be adjusted. In this work we investigate the applicability of the genetic algorithm (GA) global optimization method to this problem. The GA is based on the evolution of species, and makes use of concepts such as crossover, elitism and mutation to perform the search. We show results of its application in the structural determination of three different systems: the Cu(111) surface through the use of energy-scanned experimental curves; the Ag(110)-c(2 x 2)-Sb system, in which a theory-theory fit was performed; and the Ag(111) surface for which angle-scanned experimental curves were used. We conclude that the GA is a highly efficient method to search for global minima in the optimization of the parameters that best fit the experimental photoelectron diffraction intensities to the theoretical ones.

Spatial difference in genetic variation for fenitrothion tolerance between local populations of Daphnia galeata in Lake Kasumigaura, Japan.

Science.gov (United States)

Mano, Hiroyuki; Tanaka, Yoshinari

2017-12-01

This study examines the spatial difference in genetic variation for tolerance to a pesticide, fenitrothion, in Daphnia galeata at field sites in Lake Kasumigaura, Japan. We estimated genetic values of isofemale lines established from dormant eggs of D. galeata collected from field sampling sites with the toxicant threshold model applied using acute toxicity. We compared genetic values and variances and broad-sense heritability across different sites in the lake. Results showed that the mean tolerance values to fenitrothion did not differ spatially. The variance in genetic value and heritability of fenitrothion tolerance significantly differed between sampling sites, revealing that long-term ecological risk of fenitrothion may differ between local populations in the lake. These results have implications for aquatic toxicology research, suggesting that differences in genetic variation of tolerance to a chemical among local populations must be considered for understanding the long-term ecological risks of the chemical over a large geographic area.

Reactive searching and infotaxis in odor source localization.

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Nicole Voges

2014-10-01

Full Text Available Male moths aiming to locate pheromone-releasing females rely on stimulus-adapted search maneuvers complicated by a discontinuous distribution of pheromone patches. They alternate sequences of upwind surge when perceiving the pheromone and cross- or downwind casting when the odor is lost. We compare four search strategies: three reactive versus one cognitive. The former consist of pre-programmed movement sequences triggered by pheromone detections while the latter uses Bayesian inference to build spatial probability maps. Based on the analysis of triphasic responses of antennal lobe neurons (On, inhibition, Off, we propose three reactive strategies. One combines upwind surge (representing the On response to a pheromone detection and spiral casting, only. The other two additionally include crosswind (zigzag casting representing the Off phase. As cognitive strategy we use the infotaxis algorithm which was developed for searching in a turbulent medium. Detection events in the electroantennogram of a moth attached to a robot indirectly control this cyborg, depending on the strategy in use. The recorded trajectories are analyzed with regard to success rates, efficiency, and other features. In addition, we qualitatively compare our robotic trajectories to behavioral search paths. Reactive searching is more efficient (yielding shorter trajectories for higher pheromone doses whereas cognitive searching works better for lower doses. With respect to our experimental conditions (2 m from starting position to pheromone source, reactive searching with crosswind zigzag yields the shortest trajectories (for comparable success rates. Assuming that the neuronal Off response represents a short-term memory, zigzagging is an efficient movement to relocate a recently lost pheromone plume. Accordingly, such reactive strategies offer an interesting alternative to complex cognitive searching.

Reactive searching and infotaxis in odor source localization.

Science.gov (United States)

Voges, Nicole; Chaffiol, Antoine; Lucas, Philippe; Martinez, Dominique

2014-10-01

Male moths aiming to locate pheromone-releasing females rely on stimulus-adapted search maneuvers complicated by a discontinuous distribution of pheromone patches. They alternate sequences of upwind surge when perceiving the pheromone and cross- or downwind casting when the odor is lost. We compare four search strategies: three reactive versus one cognitive. The former consist of pre-programmed movement sequences triggered by pheromone detections while the latter uses Bayesian inference to build spatial probability maps. Based on the analysis of triphasic responses of antennal lobe neurons (On, inhibition, Off), we propose three reactive strategies. One combines upwind surge (representing the On response to a pheromone detection) and spiral casting, only. The other two additionally include crosswind (zigzag) casting representing the Off phase. As cognitive strategy we use the infotaxis algorithm which was developed for searching in a turbulent medium. Detection events in the electroantennogram of a moth attached to a robot indirectly control this cyborg, depending on the strategy in use. The recorded trajectories are analyzed with regard to success rates, efficiency, and other features. In addition, we qualitatively compare our robotic trajectories to behavioral search paths. Reactive searching is more efficient (yielding shorter trajectories) for higher pheromone doses whereas cognitive searching works better for lower doses. With respect to our experimental conditions (2 m from starting position to pheromone source), reactive searching with crosswind zigzag yields the shortest trajectories (for comparable success rates). Assuming that the neuronal Off response represents a short-term memory, zigzagging is an efficient movement to relocate a recently lost pheromone plume. Accordingly, such reactive strategies offer an interesting alternative to complex cognitive searching.

Genome-wide single-generation signatures of local selection in the panmictic European eel

DEFF Research Database (Denmark)

Pujolar, J. M.; Jacobsen, M. W.; Als, Thomas Damm

2014-01-01

Next-generation sequencing and the collection of genome-wide data allow identifying adaptive variation and footprints of directional selection. Using a large SNP data set from 259 RAD-sequenced European eel individuals (glass eels) from eight locations between 34 and 64oN, we examined the patterns...... of genome-wide genetic diversity across locations. We tested for local selection by searching for increased population differentiation using FST-based outlier tests and by testing for significant associations between allele frequencies and environmental variables. The overall low genetic differentiation...... with single-generation signatures of spatially varying selection acting on glass eels. After screening 50 354 SNPs, a total of 754 potentially locally selected SNPs were identified. Candidate genes for local selection constituted a wide array of functions, including calcium signalling, neuroactive ligand...

Noise genetics: inferring protein function by correlating phenotype with protein levels and localization in individual human cells.

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Shlomit Farkash-Amar

2014-03-01

Full Text Available To understand gene function, genetic analysis uses large perturbations such as gene deletion, knockdown or over-expression. Large perturbations have drawbacks: they move the cell far from its normal working point, and can thus be masked by off-target effects or compensation by other genes. Here, we offer a complementary approach, called noise genetics. We use natural cell-cell variations in protein level and localization, and correlate them to the natural variations of the phenotype of the same cells. Observing these variations is made possible by recent advances in dynamic proteomics that allow measuring proteins over time in individual living cells. Using motility of human cancer cells as a model system, and time-lapse microscopy on 566 fluorescently tagged proteins, we found 74 candidate motility genes whose level or localization strongly correlate with motility in individual cells. We recovered 30 known motility genes, and validated several novel ones by mild knockdown experiments. Noise genetics can complement standard genetics for a variety of phenotypes.

Genetics Home Reference

Science.gov (United States)

... Page Search Home Health Conditions Genes Chromosomes & mtDNA Resources Help Me Understand Genetics Share: Email Facebook Twitter Genetics Home Reference provides consumer-friendly information about the effects of genetic variation on human health. Health Conditions More than 1,200 health ...

An Efficient Two-Objective Hybrid Local Search Algorithm for Solving the Fuel Consumption Vehicle Routing Problem

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Weizhen Rao

2016-01-01

Full Text Available The classical model of vehicle routing problem (VRP generally minimizes either the total vehicle travelling distance or the total number of dispatched vehicles. Due to the increased importance of environmental sustainability, one variant of VRPs that minimizes the total vehicle fuel consumption has gained much attention. The resulting fuel consumption VRP (FCVRP becomes increasingly important yet difficult. We present a mixed integer programming model for the FCVRP, and fuel consumption is measured through the degree of road gradient. Complexity analysis of FCVRP is presented through analogy with the capacitated VRP. To tackle the FCVRP’s computational intractability, we propose an efficient two-objective hybrid local search algorithm (TOHLS. TOHLS is based on a hybrid local search algorithm (HLS that is also used to solve FCVRP. Based on the Golden CVRP benchmarks, 60 FCVRP instances are generated and tested. Finally, the computational results show that the proposed TOHLS significantly outperforms the HLS.

The Parameters Optimization of MCR-WPT System Based on the Improved Genetic Simulated Annealing Algorithm

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Sheng Lu

2015-01-01

Full Text Available To solve the problem of parameter selection during the design of magnetically coupled resonant wireless power transmission system (MCR-WPT, this paper proposed an improved genetic simulated annealing algorithm. Firstly, the equivalent circuit of the system is analysis in this study and a nonlinear programming mathematical model is built. Secondly, in place of the penalty function method in the genetic algorithm, the selection strategy based on the distance between individuals is adopted to select individual. In this way, it reduces the excess empirical parameters. Meanwhile, it can improve the convergence rate and the searching ability by calculating crossover probability and mutation probability according to the variance of population’s fitness. At last, the simulated annealing operator is added to increase local search ability of the method. The simulation shows that the improved method can break the limit of the local optimum solution and get the global optimum solution faster. The optimized system can achieve the practical requirements.

Automatic fuel lattice design in a boiling water reactor using a particle swarm optimization algorithm and local search

International Nuclear Information System (INIS)

Lin Chaung; Lin, Tung-Hsien

2012-01-01

Highlights: ► The automatic procedure was developed to design the radial enrichment and gadolinia (Gd) distribution of fuel lattice. ► The method is based on a particle swarm optimization algorithm and local search. ► The design goal were to achieve the minimum local peaking factor. ► The number of fuel pins with Gd and Gd concentration are fixed to reduce search complexity. ► In this study, three axial sections are design and lattice performance is calculated using CASMO-4. - Abstract: The axial section of fuel assembly in a boiling water reactor (BWR) consists of five or six different distributions; this requires a radial lattice design. In this study, an automatic procedure based on a particle swarm optimization (PSO) algorithm and local search was developed to design the radial enrichment and gadolinia (Gd) distribution of the fuel lattice. The design goals were to achieve the minimum local peaking factor (LPF), and to come as close as possible to the specified target average enrichment and target infinite multiplication factor (k ∞ ), in which the number of fuel pins with Gd and Gd concentration are fixed. In this study, three axial sections are designed, and lattice performance is calculated using CASMO-4. Finally, the neutron cross section library of the designed lattice is established by CMSLINK; the core status during depletion, such as thermal limits, cold shutdown margin and cycle length, are then calculated using SIMULATE-3 in order to confirm that the lattice design satisfies the design requirements.

Scalable unit commitment by memory-bounded ant colony optimization with A{sup *} local search

Energy Technology Data Exchange (ETDEWEB)

Saber, Ahmed Yousuf; Alshareef, Abdulaziz Mohammed [Department of Electrical and Computer Engineering, King Abdulaziz University, P.O. Box 80204, Jeddah 21589 (Saudi Arabia)

2008-07-15

Ant colony optimization (ACO) is successfully applied in optimization problems. Performance of the basic ACO for small problems with moderate dimension and searching space is satisfactory. As the searching space grows exponentially in the large-scale unit commitment problem, the basic ACO is not applicable for the vast size of pheromone matrix of ACO in practical time and physical computer-memory limit. However, memory-bounded methods prune the least-promising nodes to fit the system in computer memory. Therefore, the authors propose memory-bounded ant colony optimization (MACO) in this paper for the scalable (no restriction for system size) unit commitment problem. This MACO intelligently solves the limitation of computer memory, and does not permit the system to grow beyond a bound on memory. In the memory-bounded ACO implementation, A{sup *} heuristic is introduced to increase local searching ability and probabilistic nearest neighbor method is applied to estimate pheromone intensity for the forgotten value. Finally, the benchmark data sets and existing methods are used to show the effectiveness of the proposed method. (author)

A Local Search Algorithm for the Flow Shop Scheduling Problem with Release Dates

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Tao Ren

2015-01-01

Full Text Available This paper discusses the flow shop scheduling problem to minimize the makespan with release dates. By resequencing the jobs, a modified heuristic algorithm is obtained for handling large-sized problems. Moreover, based on some properties, a local search scheme is provided to improve the heuristic to gain high-quality solution for moderate-sized problems. A sequence-independent lower bound is presented to evaluate the performance of the algorithms. A series of simulation results demonstrate the effectiveness of the proposed algorithms.

Local Search Approaches in Stable Matching Problems

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Toby Walsh

2013-10-01

Full Text Available The stable marriage (SM problem has a wide variety of practical applications, ranging from matching resident doctors to hospitals, to matching students to schools or, more generally, to any two-sided market. In the classical formulation, n men and n women express their preferences (via a strict total order over the members of the other sex. Solving an SM problem means finding a stable marriage where stability is an envy-free notion: no man and woman who are not married to each other would both prefer each other to their partners or to being single. We consider both the classical stable marriage problem and one of its useful variations (denoted SMTI (Stable Marriage with Ties and Incomplete lists where the men and women express their preferences in the form of an incomplete preference list with ties over a subset of the members of the other sex. Matchings are permitted only with people who appear in these preference lists, and we try to find a stable matching that marries as many people as possible. Whilst the SM problem is polynomial to solve, the SMTI problem is NP-hard. We propose to tackle both problems via a local search approach, which exploits properties of the problems to reduce the size of the neighborhood and to make local moves efficiently. We empirically evaluate our algorithm for SM problems by measuring its runtime behavior and its ability to sample the lattice of all possible stable marriages. We evaluate our algorithm for SMTI problems in terms of both its runtime behavior and its ability to find a maximum cardinality stable marriage. Experimental results suggest that for SM problems, the number of steps of our algorithm grows only as O(n log(n, and that it samples very well the set of all stable marriages. It is thus a fair and efficient approach to generate stable marriages. Furthermore, our approach for SMTI problems is able to solve large problems, quickly returning stable matchings of large and often optimal size, despite the

Locally targeted ecosynthesis: a proactive in situ search for extant life on other worlds.

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Schulze-Makuch, Dirk; Fairén, Alberto G; Davila, Alfonso

2013-07-01

The Viking landers conducted the only life-detection mission outside Earth nearly 40 years ago. We believe it is time to resume this proactive search for life and propose a new approach based on Locally Targeted Ecosynthesis (LoTE) missions: the engineering of local habitable hotspots on planetary surfaces to reveal any subdued biosphere and enhance the expression of its biological activity. LoTE missions are based on a minimum set of assumptions about life, namely, the need for liquid solvents, energy sources, and nutrients, and the limits imposed by UV and ionizing radiation. The most promising destinations for LoTE missions are Mars and Saturn's moon Titan. We describe two LoTE mission concepts that would enhance the unique environmental conditions on Mars and Titan to reveal a subdued biosphere easily detectable with conventional instruments by supplying biologically essential yet critically limited compounds and by engineering local habitable conditions.

Rapid recovery of genetic diversity of dogwhelk (Nucella lapillus L.) populations after local extinction and recolonization contradicts predictions from life-history characteristics.

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Colson, I; Hughes, R N

2004-08-01

The dogwhelk Nucella lapillus is a predatory marine gastropod populating North Atlantic rocky shores. As with many other gastropod species, N. lapillus was affected by tributyltin (TBT) pollution during the 1970s and 1980s, when local populations became extinct. After a partial ban on TBT in the United Kingdom in 1987, vacant sites have been recolonized. N. lapillus lacks a planktonic larval stage and is therefore expected to have limited dispersal ability. Relatively fast recolonization of some sites, however, contradicts this assumption. We compared levels of genetic diversity and genetic structuring between recolonized sites and sites that showed continuous population at three localities across the British Isles. No significant genetic effects of extinction/recolonization events were observed in SW Scotland and NE England. In SW England we observed a decrease in genetic diversity and an increase in genetic structure in recolonized populations. This last result could be an artefact, however, due to the superposition of other local factors influencing the genetic structuring of dogwhelk populations. We conclude that recolonization of vacant sites was accomplished by a relatively high number of individuals originating from several source populations (the 'migrant-pool' model of recolonization), implying that movements are more widespread than expected on the basis of development mode alone. Comparison with published data on genetic structure of marine organisms with contrasted larval dispersal supports this hypothesis. Our results also stress the importance of local factors (geographical or ecological) in determining genetic structure of dogwhelk populations. Copyright 2004 Blackwell Publishing Ltd

All about Genetics (For Parents)

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... Videos for Educators Search English Español All About Genetics KidsHealth / For Parents / All About Genetics What's in ... the way they pick up special laboratory dyes. Genetic Problems Errors in the genetic code or "gene ...

Prenatal Genetic Counseling (For Parents)

Science.gov (United States)

... Videos for Educators Search English Español Prenatal Genetic Counseling KidsHealth / For Parents / Prenatal Genetic Counseling What's in ... can they help your family? What Is Genetic Counseling? Genetic counseling is the process of: evaluating family ...

Automatic boiling water reactor control rod pattern design using particle swarm optimization algorithm and local search

Energy Technology Data Exchange (ETDEWEB)

Wang, Cheng-Der, E-mail: jdwang@iner.gov.tw [Nuclear Engineering Division, Institute of Nuclear Energy Research, No. 1000, Wenhua Rd., Jiaan Village, Longtan Township, Taoyuan County 32546, Taiwan, ROC (China); Lin, Chaung [National Tsing Hua University, Department of Engineering and System Science, 101, Section 2, Kuang Fu Road, Hsinchu 30013, Taiwan (China)

2013-02-15

Highlights: ► The PSO algorithm was adopted to automatically design a BWR CRP. ► The local search procedure was added to improve the result of PSO algorithm. ► The results show that the obtained CRP is the same good as that in the previous work. -- Abstract: This study developed a method for the automatic design of a boiling water reactor (BWR) control rod pattern (CRP) using the particle swarm optimization (PSO) algorithm. The PSO algorithm is more random compared to the rank-based ant system (RAS) that was used to solve the same BWR CRP design problem in the previous work. In addition, the local search procedure was used to make improvements after PSO, by adding the single control rod (CR) effect. The design goal was to obtain the CRP so that the thermal limits and shutdown margin would satisfy the design requirement and the cycle length, which is implicitly controlled by the axial power distribution, would be acceptable. The results showed that the same acceptable CRP found in the previous work could be obtained.

A Comparison of Local Search Methods for the Multicriteria Police Districting Problem on Graph

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F. Liberatore

2016-01-01

Full Text Available In the current economic climate, law enforcement agencies are facing resource shortages. The effective and efficient use of scarce resources is therefore of the utmost importance to provide a high standard public safety service. Optimization models specifically tailored to the necessity of police agencies can help to ameliorate their use. The Multicriteria Police Districting Problem (MC-PDP on a graph concerns the definition of sound patrolling sectors in a police district. The objective of this problem is to partition a graph into convex and continuous subsets, while ensuring efficiency and workload balance among the subsets. The model was originally formulated in collaboration with the Spanish National Police Corps. We propose for its solution three local search algorithms: a Simple Hill Climbing, a Steepest Descent Hill Climbing, and a Tabu Search. To improve their diversification capabilities, all the algorithms implement a multistart procedure, initialized by randomized greedy solutions. The algorithms are empirically tested on a case study on the Central District of Madrid. Our experiments show that the solutions identified by the novel Tabu Search outperform the other algorithms. Finally, research guidelines for future developments on the MC-PDP are given.

A genetic algorithm approach to optimization for the radiological worker allocation problem

International Nuclear Information System (INIS)

Yan Chen; Masakuni Narita; Masashi Tsuji; Sangduk Sa

1996-01-01

The worker allocation optimization problem in radiological facilities inevitably involves various types of requirements and constraints relevant to radiological protection and labor management. Some of these goals and constraints are not amenable to a rigorous mathematical formulation. Conventional methods for this problem rely heavily on sophisticated algebraic or numerical algorithms, which cause difficulties in the search for optimal solutions in the search space of worker allocation optimization problems. Genetic algorithms (GAB) are stochastic search algorithms introduced by J. Holland in the 1970s based on ideas and techniques from genetic and evolutionary theories. The most striking characteristic of GAs is the large flexibility allowed in the formulation of the optimal problem and the process of the search for the optimal solution. In the formulation, it is not necessary to define the optimal problem in rigorous mathematical terms, as required in the conventional methods. Furthermore, by designing a model of evolution for the optimal search problem, the optimal solution can be sought efficiently with computational simple manipulations without highly complex mathematical algorithms. We reported a GA approach to the worker allocation problem in radiological facilities in the previous study. In this study, two types of hard constraints were employed to reduce the huge search space, where the optimal solution is sought in such a way as to satisfy as many of soft constraints as possible. It was demonstrated that the proposed evolutionary method could provide the optimal solution efficiently compared with conventional methods. However, although the employed hard constraints could localize the search space into a very small region, it brought some complexities in the designed genetic operators and demanded additional computational burdens. In this paper, we propose a simplified evolutionary model with less restrictive hard constraints and make comparisons between

Search of molecular ground state via genetic algorithm: Implementation on a hybrid SIMD-MIMD platform

International Nuclear Information System (INIS)

Pucello, N.; D'Agostino, G.; Pisacane, F.

1997-01-01

A genetic algorithm for the optimization of the ground-state structure of a metallic cluster has been developed and ported on a SIMD-MIMD parallel platform. The SIMD part of the parallel platform is represented by a Quadrics/APE100 consisting of 512 floating point units, while the MIMD part is formed by a cluster of workstations. The proposed algorithm is composed by a part where the genetic operators are applied to the elements of the population and a part which performs a further local relaxation and the fitness calculation via Molecular Dynamics. These parts have been implemented on the MIMD and on the SIMD part, respectively. Results have been compared to those generated by using Simulated Annealing

Genetics in eating disorders: extending the boundaries of research

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Andréa Poyastro Pinheiro

2006-09-01

Full Text Available OBJECTIVE: To review the recent literature relevant to genetic research in eating disorders and to discuss unique issues which are crucial for the development of a genetic research project in eating disorders in Brazil. METHOD: A computer literature review was conducted in the Medline database between 1984 and may 2005 with the search terms "eating disorders", "anorexia nervosa", "bulimia nervosa", "binge eating disorder", "family", "twin" and "molecular genetic" studies. RESULTS: Current research findings suggest a substantial influence of genetic factors on the liability to anorexia nervosa and bulimia nervosa. Genetic research with admixed populations should take into consideration sample size, density of genotyping and population stratification. Through admixture mapping it is possible to study the genetic structure of admixed human populations to localize genes that underlie ethnic variation in diseases or traits of interest. CONCLUSIONS: The development of a major collaborative genetics initiative of eating disorders in Brazil and South America would represent a realistic possibility of studying the genetics of eating disorders in the context of inter ethnic groups, and also integrate a new perspective on the biological etiology of eating disorders.

Genetic diversity of Echinococcus multilocularis on a local scale.

Science.gov (United States)

Knapp, J; Guislain, M-H; Bart, J M; Raoul, F; Gottstein, B; Giraudoux, P; Piarroux, R

2008-05-01

Echinococcusmultilocularis is the causative agent of human Alveolar Echinococcosis (AE), and it is one of the most lethal zoonotic infections in the Northern Hemisphere. In France, the eastern and central regions are endemic areas; Franche-Comté, Lorraine and Auvergne are particularly contaminated. Recently, several human cases were recorded in the French Ardennes area, a region adjacent to the western border of the E. multilocularis range in France. A previous study in this focus described a prevalence of over 50% of the parasite in red foxes. The present study investigated the genetic diversity of adult worms collected from foxes in a 900km(2) area in the Ardennes. Instead of a conventional mitochondrial target (ATP6), two microsatellite targets (EmsB and NAK1) were used. A total of 140 adult worms isolated from 25 red foxes were genotyped. After hierarchical clustering analyses, the EmsB target enabled us to distinguish two main assemblages, each divided into sub-groups, yielding the differentiation of six clusters or assemblage profiles. Thirteen foxes (52% of the foxes) each harbored worms from at least two different assemblage profiles, suggesting they had become infected by several sources. Using the NAK1 target, we identified 3 alleles, two found in association with the two EmsB assemblages. With the NAK1 target, we investigated the parasite breeding system and the possible causes of genetic diversification. Only one fox harbored hybrid worms, indicative of a possible (and rare) occurrence of recombination, although multiple infections have been observed in foxes. These results confirm the usefulness of microsatellite targets for assessing genetic polymorphism in a geographically restricted local range.

A hybrid search algorithm for swarm robots searching in an unknown environment.

Science.gov (United States)

Li, Shoutao; Li, Lina; Lee, Gordon; Zhang, Hao

2014-01-01

This paper proposes a novel method to improve the efficiency of a swarm of robots searching in an unknown environment. The approach focuses on the process of feeding and individual coordination characteristics inspired by the foraging behavior in nature. A predatory strategy was used for searching; hence, this hybrid approach integrated a random search technique with a dynamic particle swarm optimization (DPSO) search algorithm. If a search robot could not find any target information, it used a random search algorithm for a global search. If the robot found any target information in a region, the DPSO search algorithm was used for a local search. This particle swarm optimization search algorithm is dynamic as all the parameters in the algorithm are refreshed synchronously through a communication mechanism until the robots find the target position, after which, the robots fall back to a random searching mode. Thus, in this searching strategy, the robots alternated between two searching algorithms until the whole area was covered. During the searching process, the robots used a local communication mechanism to share map information and DPSO parameters to reduce the communication burden and overcome hardware limitations. If the search area is very large, search efficiency may be greatly reduced if only one robot searches an entire region given the limited resources available and time constraints. In this research we divided the entire search area into several subregions, selected a target utility function to determine which subregion should be initially searched and thereby reduced the residence time of the target to improve search efficiency.

Local literature bias in genetic epidemiology: an empirical evaluation of the Chinese literature.

Directory of Open Access Journals (Sweden)

Zhenglun Pan

2005-12-01

Full Text Available BACKGROUND: Postulated epidemiological associations are subject to several biases. We evaluated whether the Chinese literature on human genome epidemiology may offer insights on the operation of selective reporting and language biases. METHODS AND FINDINGS: We targeted 13 gene-disease associations, each already assessed by meta-analyses, including at least 15 non-Chinese studies. We searched the Chinese Journal Full-Text Database for additional Chinese studies on the same topics. We identified 161 Chinese studies on 12 of these gene-disease associations; only 20 were PubMed-indexed (seven English full-text. Many studies (14-35 per topic were available for six topics, covering diseases common in China. With one exception, the first Chinese study appeared with a time lag (2-21 y after the first non-Chinese study on the topic. Chinese studies showed significantly more prominent genetic effects than non-Chinese studies, and 48% were statistically significant per se, despite their smaller sample size (median sample size 146 versus 268, p < 0.001. The largest genetic effects were often seen in PubMed-indexed Chinese studies (65% statistically significant per se. Non-Chinese studies of Asian-descent populations (27% significant per se also tended to show somewhat more prominent genetic effects than studies of non-Asian descent (17% significant per se. CONCLUSION: Our data provide evidence for the interplay of selective reporting and language biases in human genome epidemiology. These biases may not be limited to the Chinese literature and point to the need for a global, transparent, comprehensive outlook in molecular population genetics and epidemiologic studies in general.

Genetic algorithm enhanced by machine learning in dynamic aperture optimization

Science.gov (United States)

Li, Yongjun; Cheng, Weixing; Yu, Li Hua; Rainer, Robert

2018-05-01

With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given "elite" status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitness of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. The machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.

A novel pseudoderivative-based mutation operator for real-coded adaptive genetic algorithms [v2; ref status: indexed, http://f1000r.es/1td

Directory of Open Access Journals (Sweden)

Maxinder S Kanwal

2013-11-01

Full Text Available Recent development of large databases, especially those in genetics and proteomics, is pushing the development of novel computational algorithms that implement rapid and accurate search strategies. One successful approach has been to use artificial intelligence and methods, including pattern recognition (e.g. neural networks and optimization techniques (e.g. genetic algorithms. The focus of this paper is on optimizing the design of genetic algorithms by using an adaptive mutation rate that is derived from comparing the fitness values of successive generations. We propose a novel pseudoderivative-based mutation rate operator designed to allow a genetic algorithm to escape local optima and successfully continue to the global optimum. Once proven successful, this algorithm can be implemented to solve real problems in neurology and bioinformatics. As a first step towards this goal, we tested our algorithm on two 3-dimensional surfaces with multiple local optima, but only one global optimum, as well as on the N-queens problem, an applied problem in which the function that maps the curve is implicit. For all tests, the adaptive mutation rate allowed the genetic algorithm to find the global optimal solution, performing significantly better than other search methods, including genetic algorithms that implement fixed mutation rates.

Searching for globally optimal functional forms for interatomic potentials using genetic programming with parallel tempering.

Science.gov (United States)

Slepoy, A; Peters, M D; Thompson, A P

2007-11-30

Molecular dynamics and other molecular simulation methods rely on a potential energy function, based only on the relative coordinates of the atomic nuclei. Such a function, called a force field, approximately represents the electronic structure interactions of a condensed matter system. Developing such approximate functions and fitting their parameters remains an arduous, time-consuming process, relying on expert physical intuition. To address this problem, a functional programming methodology was developed that may enable automated discovery of entirely new force-field functional forms, while simultaneously fitting parameter values. The method uses a combination of genetic programming, Metropolis Monte Carlo importance sampling and parallel tempering, to efficiently search a large space of candidate functional forms and parameters. The methodology was tested using a nontrivial problem with a well-defined globally optimal solution: a small set of atomic configurations was generated and the energy of each configuration was calculated using the Lennard-Jones pair potential. Starting with a population of random functions, our fully automated, massively parallel implementation of the method reproducibly discovered the original Lennard-Jones pair potential by searching for several hours on 100 processors, sampling only a minuscule portion of the total search space. This result indicates that, with further improvement, the method may be suitable for unsupervised development of more accurate force fields with completely new functional forms. Copyright (c) 2007 Wiley Periodicals, Inc.

The Cellular Differential Evolution Based on Chaotic Local Search

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Qingfeng Ding

2015-01-01

Full Text Available To avoid immature convergence and tune the selection pressure in the differential evolution (DE algorithm, a new differential evolution algorithm based on cellular automata and chaotic local search (CLS or ccDE is proposed. To balance the exploration and exploitation tradeoff of differential evolution, the interaction among individuals is limited in cellular neighbors instead of controlling parameters in the canonical DE. To improve the optimizing performance of DE, the CLS helps by exploring a large region to avoid immature convergence in the early evolutionary stage and exploiting a small region to refine the final solutions in the later evolutionary stage. What is more, to improve the convergence characteristics and maintain the population diversity, the binomial crossover operator in the canonical DE may be instead by the orthogonal crossover operator without crossover rate. The performance of ccDE is widely evaluated on a set of 14 bound constrained numerical optimization problems compared with the canonical DE and several DE variants. The simulation results show that ccDE has better performances in terms of convergence rate and solution accuracy than other optimizers.

Common Genetic Components of Obesity Traits and Serum Leptin

DEFF Research Database (Denmark)

Hasselbalch, Ann L; Benyamin, Beben; Visscher, Peter M

2008-01-01

To estimate common and distinct genetic influences on a panel of obesity-related traits and serum leptin level in adults. In a cross-sectional study of 625 Danish, adult, healthy, monozygotic, and same-sex dizygotic twin pairs of both genders, we carried out detailed anthropometry (height, weight...... components, which suggests that it is important to distinguish between the different phenotypes in the search for genes involved in the development of obesity.Obesity (2008) doi:10.1038/oby.2008.440........ For leptin vs. the various measures of overall and local fatness the correlations ranged from 0.54 to 0.74 in men and from 0.48 to 0.75 in women. All correlations were significantly different genetic...

Policy implications for familial searching

OpenAIRE

Kim, Joyce; Mammo, Danny; Siegel, Marni B; Katsanis, Sara H

2011-01-01

Abstract In the United States, several states have made policy decisions regarding whether and how to use familial searching of the Combined DNA Index System (CODIS) database in criminal investigations. Familial searching pushes DNA typing beyond merely identifying individuals to detecting genetic relatedness, an application previously reserved for missing persons identifications and custody battles. The intentional search of CODIS for partial matches to an item of evidence offers law enforce...

Genetics in endocrinology: genetic variation in deiodinases: a systematic review of potential clinical effects in humans.

Science.gov (United States)

Verloop, Herman; Dekkers, Olaf M; Peeters, Robin P; Schoones, Jan W; Smit, Johannes W A

2014-09-01

Iodothyronine deiodinases represent a family of selenoproteins involved in peripheral and local homeostasis of thyroid hormone action. Deiodinases are expressed in multiple organs and thyroid hormone affects numerous biological systems, thus genetic variation in deiodinases may affect multiple clinical endpoints. Interest in clinical effects of genetic variation in deiodinases has clearly increased. We aimed to provide an overview for the role of deiodinase polymorphisms in human physiology and morbidity. In this systematic review, studies evaluating the relationship between deiodinase polymorphisms and clinical parameters in humans were eligible. No restrictions on publication date were imposed. The following databases were searched up to August 2013: Pubmed, EMBASE (OVID-version), Web of Science, COCHRANE Library, CINAHL (EbscoHOST-version), Academic Search Premier (EbscoHOST-version), and ScienceDirect. Deiodinase physiology at molecular and tissue level is described, and finally the role of these polymorphisms in pathophysiological conditions is reviewed. Deiodinase type 1 (D1) polymorphisms particularly show moderate-to-strong relationships with thyroid hormone parameters, IGF1 production, and risk for depression. D2 variants correlate with thyroid hormone levels, insulin resistance, bipolar mood disorder, psychological well-being, mental retardation, hypertension, and risk for osteoarthritis. D3 polymorphisms showed no relationship with inter-individual variation in serum thyroid hormone parameters. One D3 polymorphism was associated with risk for osteoarthritis. Genetic deiodinase profiles only explain a small proportion of inter-individual variations in serum thyroid hormone levels. Evidence suggests a role of genetic deiodinase variants in certain pathophysiological conditions. The value for determination of deiodinase polymorphism in clinical practice needs further investigation. © 2014 European Society of Endocrinology.

Cloud Computing Task Scheduling Based on Cultural Genetic Algorithm

Directory of Open Access Journals (Sweden)

Li Jian-Wen

2016-01-01

Full Text Available The task scheduling strategy based on cultural genetic algorithm(CGA is proposed in order to improve the efficiency of task scheduling in the cloud computing platform, which targets at minimizing the total time and cost of task scheduling. The improved genetic algorithm is used to construct the main population space and knowledge space under cultural framework which get independent parallel evolution, forming a mechanism of mutual promotion to dispatch the cloud task. Simultaneously, in order to prevent the defects of the genetic algorithm which is easy to fall into local optimum, the non-uniform mutation operator is introduced to improve the search performance of the algorithm. The experimental results show that CGA reduces the total time and lowers the cost of the scheduling, which is an effective algorithm for the cloud task scheduling.

Acoustic Impedance Inversion of Seismic Data Using Genetic Algorithm

Science.gov (United States)

Eladj, Said; Djarfour, Noureddine; Ferahtia, Djalal; Ouadfeul, Sid-Ali

2013-04-01

The inversion of seismic data can be used to constrain estimates of the Earth's acoustic impedance structure. This kind of problem is usually known to be non-linear, high-dimensional, with a complex search space which may be riddled with many local minima, and results in irregular objective functions. We investigate here the performance and the application of a genetic algorithm, in the inversion of seismic data. The proposed algorithm has the advantage of being easily implemented without getting stuck in local minima. The effects of population size, Elitism strategy, uniform cross-over and lower mutation are examined. The optimum solution parameters and performance were decided as a function of the testing error convergence with respect to the generation number. To calculate the fitness function, we used L2 norm of the sample-to-sample difference between the reference and the inverted trace. The cross-over probability is of 0.9-0.95 and mutation has been tested at 0.01 probability. The application of such a genetic algorithm to synthetic data shows that the inverted acoustic impedance section was efficient. Keywords: Seismic, Inversion, acoustic impedance, genetic algorithm, fitness functions, cross-over, mutation.

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

Locally adapted fish populations maintain small-scale genetic differentiation despite perturbation by a catastrophic flood event.

Science.gov (United States)

Plath, Martin; Hermann, Bernd; Schröder, Christiane; Riesch, Rüdiger; Tobler, Michael; García de León, Francisco J; Schlupp, Ingo; Tiedemann, Ralph

2010-08-23

Local adaptation to divergent environmental conditions can promote population genetic differentiation even in the absence of geographic barriers and hence, lead to speciation. Perturbations by catastrophic events, however, can distort such parapatric ecological speciation processes. Here, we asked whether an exceptionally strong flood led to homogenization of gene pools among locally adapted populations of the Atlantic molly (Poecilia mexicana, Poeciliidae) in the Cueva del Azufre system in southern Mexico, where two strong environmental selection factors (darkness within caves and/or presence of toxic H2S in sulfidic springs) drive the diversification of P. mexicana. Nine nuclear microsatellites as well as heritable female life history traits (both as a proxy for quantitative genetics and for trait divergence) were used as markers to compare genetic differentiation, genetic diversity, and especially population mixing (immigration and emigration) before and after the flood. Habitat type (i.e., non-sulfidic surface, sulfidic surface, or sulfidic cave), but not geographic distance was the major predictor of genetic differentiation. Before and after the flood, each habitat type harbored a genetically distinct population. Only a weak signal of individual dislocation among ecologically divergent habitat types was uncovered (with the exception of slightly increased dislocation from the Cueva del Azufre into the sulfidic creek, El Azufre). By contrast, several lines of evidence are indicative of increased flood-induced dislocation within the same habitat type, e.g., between different cave chambers of the Cueva del Azufre. The virtual absence of individual dislocation among ecologically different habitat types indicates strong natural selection against migrants. Thus, our current study exemplifies that ecological speciation in this and other systems, in which extreme environmental factors drive speciation, may be little affected by temporary perturbations, as adaptations

Parallel local search for solving Constraint Problems on the Cell Broadband Engine (Preliminary Results

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Salvator Abreu

2009-10-01

Full Text Available We explore the use of the Cell Broadband Engine (Cell/BE for short for combinatorial optimization applications: we present a parallel version of a constraint-based local search algorithm that has been implemented on a multiprocessor BladeCenter machine with twin Cell/BE processors (total of 16 SPUs per blade. This algorithm was chosen because it fits very well the Cell/BE architecture and requires neither shared memory nor communication between processors, while retaining a compact memory footprint. We study the performance on several large optimization benchmarks and show that this achieves mostly linear time speedups, even sometimes super-linear. This is possible because the parallel implementation might explore simultaneously different parts of the search space and therefore converge faster towards the best sub-space and thus towards a solution. Besides getting speedups, the resulting times exhibit a much smaller variance, which benefits applications where a timely reply is critical.

Genetic particle swarm parallel algorithm analysis of optimization arrangement on mistuned blades

Science.gov (United States)

Zhao, Tianyu; Yuan, Huiqun; Yang, Wenjun; Sun, Huagang

2017-12-01

This article introduces a method of mistuned parameter identification which consists of static frequency testing of blades, dichotomy and finite element analysis. A lumped parameter model of an engine bladed-disc system is then set up. A bladed arrangement optimization method, namely the genetic particle swarm optimization algorithm, is presented. It consists of a discrete particle swarm optimization and a genetic algorithm. From this, the local and global search ability is introduced. CUDA-based co-evolution particle swarm optimization, using a graphics processing unit, is presented and its performance is analysed. The results show that using optimization results can reduce the amplitude and localization of the forced vibration response of a bladed-disc system, while optimization based on the CUDA framework can improve the computing speed. This method could provide support for engineering applications in terms of effectiveness and efficiency.

Visualization of local Ca2+ dynamics with genetically encoded bioluminescent reporters.

Science.gov (United States)

Rogers, Kelly L; Stinnakre, Jacques; Agulhon, Cendra; Jublot, Delphine; Shorte, Spencer L; Kremer, Eric J; Brûlet, Philippe

2005-02-01

Measurements of local Ca2+ signalling at different developmental stages and/or in specific cell types is important for understanding aspects of brain functioning. The use of light excitation in fluorescence imaging can cause phototoxicity, photobleaching and auto-fluorescence. In contrast, bioluminescence does not require the input of radiative energy and can therefore be measured over long periods, with very high temporal resolution. Aequorin is a genetically encoded Ca(2+)-sensitive bioluminescent protein, however, its low quantum yield prevents dynamic measurements of Ca2+ responses in single cells. To overcome this limitation, we recently reported the bi-functional Ca2+ reporter gene, GFP-aequorin (GA), which was developed specifically to improve the light output and stability of aequorin chimeras [V. Baubet, et al., (2000) PNAS, 97, 7260-7265]. In the current study, we have genetically targeted GA to different microdomains important in synaptic transmission, including to the mitochondrial matrix, endoplasmic reticulum, synaptic vesicles and to the postsynaptic density. We demonstrate that these reporters enable 'real-time' measurements of subcellular Ca2+ changes in single mammalian neurons using bioluminescence. The high signal-to-noise ratio of these reporters is also important in that it affords the visualization of Ca2+ dynamics in cell-cell communication in neuronal cultures and tissue slices. Further, we demonstrate the utility of this approach in ex-vivo preparations of mammalian retina, a paradigm in which external light input should be controlled. This represents a novel molecular imaging approach for non-invasive monitoring of local Ca2+ dynamics and cellular communication in tissue or whole animal studies.

Genetic algorithm optimization of atomic clusters

International Nuclear Information System (INIS)

Morris, J.R.; Deaven, D.M.; Ho, K.M.; Wang, C.Z.; Pan, B.C.; Wacker, J.G.; Turner, D.E.; Iowa State Univ., Ames, IA

1996-01-01

The authors have been using genetic algorithms to study the structures of atomic clusters and related problems. This is a problem where local minima are easy to locate, but barriers between the many minima are large, and the number of minima prohibit a systematic search. They use a novel mating algorithm that preserves some of the geometrical relationship between atoms, in order to ensure that the resultant structures are likely to inherit the best features of the parent clusters. Using this approach, they have been able to find lower energy structures than had been previously obtained. Most recently, they have been able to turn around the building block idea, using optimized structures from the GA to learn about systematic structural trends. They believe that an effective GA can help provide such heuristic information, and (conversely) that such information can be introduced back into the algorithm to assist in the search process

Modified harmony search

Science.gov (United States)

Mohamed, Najihah; Lutfi Amri Ramli, Ahmad; Majid, Ahmad Abd; Piah, Abd Rahni Mt

2017-09-01

A metaheuristic algorithm, called Harmony Search is quite highly applied in optimizing parameters in many areas. HS is a derivative-free real parameter optimization algorithm, and draws an inspiration from the musical improvisation process of searching for a perfect state of harmony. Propose in this paper Modified Harmony Search for solving optimization problems, which employs a concept from genetic algorithm method and particle swarm optimization for generating new solution vectors that enhances the performance of HS algorithm. The performances of MHS and HS are investigated on ten benchmark optimization problems in order to make a comparison to reflect the efficiency of the MHS in terms of final accuracy, convergence speed and robustness.

Keep Searching and You’ll Find

DEFF Research Database (Denmark)

Laursen, Keld

2012-01-01

This article critically reviews and synthesizes the contributions found in theoretical and empirical studies of firm-level innovation search processes. It explores the advantages and disadvantages of local and non-local search, discusses organizational responses, and identifies potential exogenous...... different search strategies, but end up with very similar technological profiles in fast-growing technologies. The article concludes by highlighting what we have learnt from the literature and suggesting some new avenues for research....

Hybridizing Evolutionary Algorithms with Opportunistic Local Search

DEFF Research Database (Denmark)

Gießen, Christian

2013-01-01

There is empirical evidence that memetic algorithms (MAs) can outperform plain evolutionary algorithms (EAs). Recently the first runtime analyses have been presented proving the aforementioned conjecture rigorously by investigating Variable-Depth Search, VDS for short (Sudholt, 2008). Sudholt...

Approximate k-NN delta test minimization method using genetic algorithms: Application to time series

CERN Document Server

Mateo, F; Gadea, Rafael; Sovilj, Dusan

2010-01-01

In many real world problems, the existence of irrelevant input variables (features) hinders the predictive quality of the models used to estimate the output variables. In particular, time series prediction often involves building large regressors of artificial variables that can contain irrelevant or misleading information. Many techniques have arisen to confront the problem of accurate variable selection, including both local and global search strategies. This paper presents a method based on genetic algorithms that intends to find a global optimum set of input variables that minimize the Delta Test criterion. The execution speed has been enhanced by substituting the exact nearest neighbor computation by its approximate version. The problems of scaling and projection of variables have been addressed. The developed method works in conjunction with MATLAB's Genetic Algorithm and Direct Search Toolbox. The goodness of the proposed methodology has been evaluated on several popular time series examples, and also ...

Hooke–Jeeves Method-used Local Search in a Hybrid Global Optimization Algorithm

Directory of Open Access Journals (Sweden)

V. D. Sulimov

2014-01-01

Full Text Available Modern methods for optimization investigation of complex systems are based on development and updating the mathematical models of systems because of solving the appropriate inverse problems. Input data desirable for solution are obtained from the analysis of experimentally defined consecutive characteristics for a system or a process. Causal characteristics are the sought ones to which equation coefficients of mathematical models of object, limit conditions, etc. belong. The optimization approach is one of the main ones to solve the inverse problems. In the main case it is necessary to find a global extremum of not everywhere differentiable criterion function. Global optimization methods are widely used in problems of identification and computation diagnosis system as well as in optimal control, computing to-mography, image restoration, teaching the neuron networks, other intelligence technologies. Increasingly complicated systems of optimization observed during last decades lead to more complicated mathematical models, thereby making solution of appropriate extreme problems significantly more difficult. A great deal of practical applications may have the problem con-ditions, which can restrict modeling. As a consequence, in inverse problems the criterion functions can be not everywhere differentiable and noisy. Available noise means that calculat-ing the derivatives is difficult and unreliable. It results in using the optimization methods without calculating the derivatives.An efficiency of deterministic algorithms of global optimization is significantly restrict-ed by their dependence on the extreme problem dimension. When the number of variables is large they use the stochastic global optimization algorithms. As stochastic algorithms yield too expensive solutions, so this drawback restricts their applications. Developing hybrid algo-rithms that combine a stochastic algorithm for scanning the variable space with deterministic local search

Virus evolutionary genetic algorithm for task collaboration of logistics distribution

Science.gov (United States)

Ning, Fanghua; Chen, Zichen; Xiong, Li

2005-12-01

In order to achieve JIT (Just-In-Time) level and clients' maximum satisfaction in logistics collaboration, a Virus Evolutionary Genetic Algorithm (VEGA) was put forward under double constraints of logistics resource and operation sequence. Based on mathematic description of a multiple objective function, the algorithm was designed to schedule logistics tasks with different due dates and allocate them to network members. By introducing a penalty item, make span and customers' satisfaction were expressed in fitness function. And a dynamic adaptive probability of infection was used to improve performance of local search. Compared to standard Genetic Algorithm (GA), experimental result illustrates the performance superiority of VEGA. So the VEGA can provide a powerful decision-making technique for optimizing resource configuration in logistics network.

Optimization of Multiple Traveling Salesman Problem Based on Simulated Annealing Genetic Algorithm

Directory of Open Access Journals (Sweden)

Xu Mingji

2017-01-01

Full Text Available It is very effective to solve the multi variable optimization problem by using hierarchical genetic algorithm. This thesis analyzes both advantages and disadvantages of hierarchical genetic algorithm and puts forward an improved simulated annealing genetic algorithm. The new algorithm is applied to solve the multiple traveling salesman problem, which can improve the performance of the solution. First, it improves the design of chromosomes hierarchical structure in terms of redundant hierarchical algorithm, and it suggests a suffix design of chromosomes; Second, concerning to some premature problems of genetic algorithm, it proposes a self-identify crossover operator and mutation; Third, when it comes to the problem of weak ability of local search of genetic algorithm, it stretches the fitness by mixing genetic algorithm with simulated annealing algorithm. Forth, it emulates the problems of N traveling salesmen and M cities so as to verify its feasibility. The simulation and calculation shows that this improved algorithm can be quickly converged to a best global solution, which means the algorithm is encouraging in practical uses.

Predicting the severity of nuclear power plant transients using nearest neighbors modeling optimized by genetic algorithms on a parallel computer

International Nuclear Information System (INIS)

Lin, J.; Bartal, Y.; Uhrig, R.E.

1995-01-01

The importance of automatic diagnostic systems for nuclear power plants (NPPs) has been discussed in numerous studies, and various such systems have been proposed. None of those systems were designed to predict the severity of the diagnosed scenario. A classification and severity prediction system for NPP transients is developed. The system is based on nearest neighbors modeling, which is optimized using genetic algorithms. The optimization process is used to determine the most important variables for each of the transient types analyzed. An enhanced version of the genetic algorithms is used in which a local downhill search is performed to further increase the accuracy achieved. The genetic algorithms search was implemented on a massively parallel supercomputer, the KSR1-64, to perform the analysis in a reasonable time. The data for this study were supplied by the high-fidelity simulator of the San Onofre unit 1 pressurized water reactor

Control of Disease Induced by Tospoviruses in Tomato: An Update of the Genetic Approach

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J. Cebolla-Cornejo

2003-12-01

Full Text Available Advances in the search for genetic resistance to tospoviruses affecting tomato crops are reviewed. The economic losses caused by Tomato spotted wilt tospovirus (TSWV, the great number of hosts it affects and its wide distribution around the world has made TSWV one of the ten most important plant viruses. Other viruses in or related to the same genus also cause severe damage, although their presence in the world is much more localized. Due to the limited effectiveness of physical, chemical and biological control methods, the use of genetic resistance for control is the best management strategy on a medium-long term basis. Given the relative ease with which new TSWV isolates that overcome existing genetic resistance are generated, it is of prime importance to continue the search for new sources of resistance, as well as to promote a better exploitation of available ones. A better understanding of the mechanisms causing resistance and of their genetic control, as well as the identification of molecular markers linked to resistance genes, would enable the pyramiding of different resistance genes. This would be a positive contribution to the development of a greater and more durable resistance. It is also necessary to further the study of genetic resistance to other viruses of the genus Tospovirus, as globalisation can speed up their distribution throughout the world.

Searching of fuel recharges by means of genetic algorithms and neural networks in BWRs

International Nuclear Information System (INIS)

Ortiz S, J.J.; Montes T, J.L.; Castillo M, J.A.; Perusquia del C, R.

2004-01-01

In this work improvements to the systems RENOR and RECOPIA are presented, that were developed to optimize fuel recharges in boiling water reactors. The RENOR system is based on a Multi state recurrent neural network while RECOPIA is based on a Genetic Algorithm. In the new versions of these systems there is incorporate the execution of the Turned off Margin in Cold and the Excess of Reactivity in Hot. The new systems were applied to an operation cycle of the Unit 1 of the Nuclear Power station of Laguna Verde. The recharges of fuel obtained by both methods are compared among if being observed that RENOR has better performance that RECOPIA, due to the nature of its search process. RECOPIA requires of approximately 1.4 times more time that RENOR to find a satisfactory recharge of fuel. (Author)

Search on Rugged Landscapes

DEFF Research Database (Denmark)

Billinger, Stephan; Stieglitz, Nils; Schumacher, Terry

2014-01-01

This paper presents findings from a laboratory experiment on human decision-making in a complex combinatorial task. We find strong evidence for a behavioral model of adaptive search. Success narrows down search to the neighborhood of the status quo, while failure promotes gradually more explorative...... for local improvements too early. We derive stylized decision rules that generate the search behavior observed in the experiment and discuss the implications of our findings for individual decision-making and organizational search....

Inclusion of the fitness sharing technique in an evolutionary algorithm to analyze the fitness landscape of the genetic code adaptability.

Science.gov (United States)

Santos, José; Monteagudo, Ángel

2017-03-27

The canonical code, although prevailing in complex genomes, is not universal. It was shown the canonical genetic code superior robustness compared to random codes, but it is not clearly determined how it evolved towards its current form. The error minimization theory considers the minimization of point mutation adverse effect as the main selection factor in the evolution of the code. We have used simulated evolution in a computer to search for optimized codes, which helps to obtain information about the optimization level of the canonical code in its evolution. A genetic algorithm searches for efficient codes in a fitness landscape that corresponds with the adaptability of possible hypothetical genetic codes. The lower the effects of errors or mutations in the codon bases of a hypothetical code, the more efficient or optimal is that code. The inclusion of the fitness sharing technique in the evolutionary algorithm allows the extent to which the canonical genetic code is in an area corresponding to a deep local minimum to be easily determined, even in the high dimensional spaces considered. The analyses show that the canonical code is not in a deep local minimum and that the fitness landscape is not a multimodal fitness landscape with deep and separated peaks. Moreover, the canonical code is clearly far away from the areas of higher fitness in the landscape. Given the non-presence of deep local minima in the landscape, although the code could evolve and different forces could shape its structure, the fitness landscape nature considered in the error minimization theory does not explain why the canonical code ended its evolution in a location which is not an area of a localized deep minimum of the huge fitness landscape.

Journal of Genetics | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Journals; Journal of Genetics; Volume 80; Issue 1. Testing quantum dynamics in genetic information processing ... Keywords. assembly; computation; database search; DNA replication; genetic information; nucleotide base; polymerase enzyme; quantum coherence; quantum mechanics; quantum superposition.

Networking in autism: leveraging genetic, biomarker and model system findings in the search for new treatments.

Science.gov (United States)

Veenstra-VanderWeele, Jeremy; Blakely, Randy D

2012-01-01

Autism Spectrum Disorder (ASD) is a common neurodevelopmental disorder affecting approximately 1% of children. ASD is defined by core symptoms in two domains: negative symptoms of impairment in social and communication function, and positive symptoms of restricted and repetitive behaviors. Available treatments are inadequate for treating both core symptoms and associated conditions. Twin studies indicate that ASD susceptibility has a large heritable component. Genetic studies have identified promising leads, with converging insights emerging from single-gene disorders that bear ASD features, with particular interest in mammalian target of rapamycin (mTOR)-linked synaptic plasticity mechanisms. Mouse models of these disorders are revealing not only opportunities to model behavioral perturbations across species, but also evidence of postnatal rescue of brain and behavioral phenotypes. An intense search for ASD biomarkers has consistently pointed to elevated platelet serotonin (5-HT) levels and a surge in brain growth in the first 2 years of life. Following a review of the diversity of ASD phenotypes and its genetic origins and biomarkers, we discuss opportunities for translation of these findings into novel ASD treatments, focusing on mTor- and 5-HT-signaling pathways, and their possible intersection. Paralleling the progress made in understanding the root causes of rare genetic syndromes that affect cognitive development, we anticipate progress in models systems using bona fide ASD-associated molecular changes that have the potential to accelerate the development of ASD diagnostics and therapeutics.

An Extended Genetic Algorithm for Distributed Integration of Fuzzy Process Planning and Scheduling

Directory of Open Access Journals (Sweden)

Shuai Zhang

2016-01-01

Full Text Available The distributed integration of process planning and scheduling (DIPPS aims to simultaneously arrange the two most important manufacturing stages, process planning and scheduling, in a distributed manufacturing environment. Meanwhile, considering its advantage corresponding to actual situation, the triangle fuzzy number (TFN is adopted in DIPPS to represent the machine processing and transportation time. In order to solve this problem and obtain the optimal or near-optimal solution, an extended genetic algorithm (EGA with innovative three-class encoding method, improved crossover, and mutation strategies is proposed. Furthermore, a local enhancement strategy featuring machine replacement and order exchange is also added to strengthen the local search capability on the basic process of genetic algorithm. Through the verification of experiment, EGA achieves satisfactory results all in a very short period of time and demonstrates its powerful performance in dealing with the distributed integration of fuzzy process planning and scheduling (DIFPPS.

The impact of local extinction on genetic structure of wild populations of lima beans (Phaseolus lunatus in the Central Valley of Costa Rica: consequences for the conservation of plant genetic resources

Directory of Open Access Journals (Sweden)

Daniel Barrantes

2008-09-01

Full Text Available Plant populations may experience local extinction and at the same time new populations may appear in nearby suitable locations. Species may also colonize the same site on multiple occasions. Here, we examined the impact of local extinction and recolonization on the genetic structure of wild populations of lima beans (Phaseolus lunatus in the Central valley of Costa Rica. We compared genetic diversity from the samples taken from the populations before and after extinction at 13 locations using microsatellite markers. Locations were classified according to the occurrence of extinction episodes during the previous five years into three groups: 1 populations that experienced extinction for more than one year, and were later recolonized (recolonized, 2 populations that did not experience local extinction (control, and 3 populations that did not experience local extinction during the study, but were cut to experimentally simulate extinction (experimental. Our data did not show a clear tendency in variation in allele frequencies, expected heterozygosity, and effective number of alleles within and between groups of populations. However, we found that the level of genetic differentiation between samples collected at different times at the same location was different in the three groups of populations. Recolonized locations showed the highest level of genetic differentiation (mean Fst= 0.2769, followed by control locations (mean Fst= 0.0576 and experimental locations (mean Fst= 0.0189. Similar findings were observed for Nei’s genetic distance between samples (di,j= 0.1786, 0.0400, and 0.0037, respectively. Our results indicate that genetic change in lima beans depends on the duration and frequency of local extinction episodes. These findings also showed that control populations are not in equilibrium. Implications of these results for the establishment of conservation strategies of genetic resources of lima beans are discussed. Rev. Biol. Trop. 56 (3

Analysis of genetic and cultural conservation value of three indigenous Croatian cattle breeds in a local and global context.

Science.gov (United States)

Ramljak, J; Ivanković, A; Veit-Kensch, C E; Förster, M; Medugorac, I

2011-02-01

It is widely accepted that autochthonous cattle breeds can be important genetic resources for unforeseeable environmental conditions in the future. Apart from that, they often represent local culture and tradition and thus assist in the awareness of ethnic identity of a country. In Croatia, there are only three indigenous cattle breeds, Croatian Buša, Slavonian Syrmian Podolian and Istrian Cattle. All of them are threatened but specialized in a particular habitat and production system. We analysed 93 microsatellites in 51 animals of each breed to get thorough information about genetic diversity and population structure. We further set them within an existing frame of additional 16 breeds that have been genotyped for the same marker set and cover a geographical area from the domestication centre near Anatolia, through the Balkan and alpine regions, to the north-west of Europe. The cultural value was evaluated regarding the role in landscape, gastronomy, folklore and handicraft. The overall results recognize Croatian Buša being partly admixed but harbouring an enormous genetic diversity comparable with other traditional unselected Buša breeds in the Anatolian and Balkan areas. The Podolian cattle showed the lowest genetic diversity at the highest genetic distance to all remaining breeds but are playing an important role as part of the cultural landscape and thus contribute to the tourist industry. The genetic diversity of the Istrian cattle was found in the middle range of this study. It is already included in the tourist industry as a local food speciality. Current and future conservation strategies are discussed. © 2010 Blackwell Verlag GmbH.

Genebanks: a comparison of eight proposed international genetic databases.

Science.gov (United States)

Austin, Melissa A; Harding, Sarah; McElroy, Courtney

2003-01-01

To identify and compare population-based genetic databases, or "genebanks", that have been proposed in eight international locations between 1998 and 2002. A genebank can be defined as a stored collection of genetic samples in the form of blood or tissue, that can be linked with medical and genealogical or lifestyle information from a specific population, gathered using a process of generalized consent. Genebanks were identified by searching Medline and internet search engines with key words such as "genetic database" and "biobank" and by reviewing literature on previously identified databases such as the deCode project. Collection of genebank characteristics was by an electronic and literature search, augmented by correspondence with informed individuals. The proposed genebanks are located in Iceland, the United Kingdom, Estonia, Latvia, Sweden, Singapore, the Kingdom of Tonga, and Quebec, Canada. Comparisons of the genebanks were based on the following criteria: genebank location and description of purpose, role of government, commercial involvement, consent and confidentiality procedures, opposition to the genebank, and current progress. All of the groups proposing the genebanks plan to search for susceptibility genes for complex diseases while attempting to improve public health and medical care in the region and, in some cases, stimulating the local economy through expansion of the biotechnology sector. While all of the identified plans share these purposes, they differ in many aspects, including funding, subject participation, and organization. The balance of government and commercial involvement in the development of each project varies. Genetic samples and health information will be collected from participants and coded in all of the genebanks, but consent procedures range from presumed consent of the entire eligible population to recruitment of volunteers with informed consent. Issues regarding confidentiality and consent have resulted in opposition to

SoftSearch: integration of multiple sequence features to identify breakpoints of structural variations.

Directory of Open Access Journals (Sweden)

Steven N Hart

Full Text Available BACKGROUND: Structural variation (SV represents a significant, yet poorly understood contribution to an individual's genetic makeup. Advanced next-generation sequencing technologies are widely used to discover such variations, but there is no single detection tool that is considered a community standard. In an attempt to fulfil this need, we developed an algorithm, SoftSearch, for discovering structural variant breakpoints in Illumina paired-end next-generation sequencing data. SoftSearch combines multiple strategies for detecting SV including split-read, discordant read-pair, and unmated pairs. Co-localized split-reads and discordant read pairs are used to refine the breakpoints. RESULTS: We developed and validated SoftSearch using real and synthetic datasets. SoftSearch's key features are 1 not requiring secondary (or exhaustive primary alignment, 2 portability into established sequencing workflows, and 3 is applicable to any DNA-sequencing experiment (e.g. whole genome, exome, custom capture, etc.. SoftSearch identifies breakpoints from a small number of soft-clipped bases from split reads and a few discordant read-pairs which on their own would not be sufficient to make an SV call. CONCLUSIONS: We show that SoftSearch can identify more true SVs by combining multiple sequence features. SoftSearch was able to call clinically relevant SVs in the BRCA2 gene not reported by other tools while offering significantly improved overall performance.

Two Search Techniques within a Human Pedigree Database

OpenAIRE

Gersting, J. M.; Conneally, P. M.; Rogers, K.

1982-01-01

This paper presents the basic features of two search techniques from MEGADATS-2 (MEdical Genetics Acquisition and DAta Transfer System), a system for collecting, storing, retrieving and plotting human family pedigrees. The individual search provides a quick method for locating an individual in the pedigree database. This search uses a modified soundex coding and an inverted file structure based on a composite key. The navigational search uses a set of pedigree traversal operations (individual...

Parallel Genetic Algorithms for calibrating Cellular Automata models: Application to lava flows

International Nuclear Information System (INIS)

D'Ambrosio, D.; Spataro, W.; Di Gregorio, S.; Calabria Univ., Cosenza; Crisci, G.M.; Rongo, R.; Calabria Univ., Cosenza

2005-01-01

Cellular Automata are highly nonlinear dynamical systems which are suitable far simulating natural phenomena whose behaviour may be specified in terms of local interactions. The Cellular Automata model SCIARA, developed far the simulation of lava flows, demonstrated to be able to reproduce the behaviour of Etnean events. However, in order to apply the model far the prediction of future scenarios, a thorough calibrating phase is required. This work presents the application of Genetic Algorithms, general-purpose search algorithms inspired to natural selection and genetics, far the parameters optimisation of the model SCIARA. Difficulties due to the elevated computational time suggested the adoption a Master-Slave Parallel Genetic Algorithm far the calibration of the model with respect to the 2001 Mt. Etna eruption. Results demonstrated the usefulness of the approach, both in terms of computing time and quality of performed simulations

Local genetic diversity of sorghum in a village in northern Cameroon: structure and dynamics of landraces.

Science.gov (United States)

Barnaud, Adeline; Deu, Monique; Garine, Eric; McKey, Doyle; Joly, Hélène I

2007-01-01

We present the first study of patterns of genetic diversity of sorghum landraces at the local scale. Understanding landrace diversity aids in deciphering evolutionary forces under domestication, and has applications in the conservation of genetic resources and their use in breeding programs. Duupa farmers in a village in Northern Cameroon distinguished 59 named sorghum taxa, representing 46 landraces. In each field, seeds are sown as a mixture of landraces (mean of 12 landraces per field), giving the potential for extensive gene flow. What level of genetic diversity underlies the great morphological diversity observed among landraces? Given the potential for gene flow, how well defined genetically is each landrace? To answer these questions, we recorded spatial patterns of planting and farmers' perceptions of landraces, and characterized 21 landraces using SSR markers. Analysis using distance and clustering methods grouped the 21 landraces studied into four clusters. These clusters correspond to functionally and ecologically distinct groups of landraces. Within-landrace genetic variation accounted for 30% of total variation. The average F(is) over landraces was 0.68, suggesting high inbreeding within landraces. Differentiation among landraces was substantial and significant (F(st) = 0.36). Historical factors, variation in breeding systems, and farmers' practices all affected patterns of genetic variation. Farmers' practices are key to the maintenance, despite gene flow, of landraces with different combinations of agronomically and ecologically pertinent traits. They must be taken into account in strategies of conservation and use of genetic resources.

Real-Coded Quantum-Inspired Genetic Algorithm-Based BP Neural Network Algorithm

Directory of Open Access Journals (Sweden)

Jianyong Liu

2015-01-01

Full Text Available The method that the real-coded quantum-inspired genetic algorithm (RQGA used to optimize the weights and threshold of BP neural network is proposed to overcome the defect that the gradient descent method makes the algorithm easily fall into local optimal value in the learning process. Quantum genetic algorithm (QGA is with good directional global optimization ability, but the conventional QGA is based on binary coding; the speed of calculation is reduced by the coding and decoding processes. So, RQGA is introduced to explore the search space, and the improved varied learning rate is adopted to train the BP neural network. Simulation test shows that the proposed algorithm is effective to rapidly converge to the solution conformed to constraint conditions.

Local topography shapes fine-scale spatial genetic structure in the Arkansas Valley evening primrose, Oenothera harringtonii (Onagraceae).

Science.gov (United States)

Rhodes, Matthew K; Fant, Jeremie B; Skogen, Krissa A

2014-01-01

Identifying factors that shape the spatial distribution of genetic variation is crucial to understanding many population- and landscape-level processes. In this study, we explore fine-scale spatial genetic structure in Oenothera harringtonii (Onagraceae), an insect-pollinated, gravity-dispersed herb endemic to the grasslands of south-central and southeastern Colorado, USA. We genotyped 315 individuals with 11 microsatellite markers and utilized a combination of spatial autocorrelation analyses and landscape genetic models to relate life history traits and landscape features to dispersal processes. Spatial genetic structure was consistent with theoretical expectations of isolation by distance, but this pattern was weak (Sp = 0.00374). Anisotropic analyses indicated that spatial genetic structure was markedly directional, in this case consistent with increased dispersal along prominent slopes. Landscape genetic models subsequently confirmed that spatial genetic variation was significantly influenced by local topographic heterogeneity, specifically that geographic distance, elevation and aspect were important predictors of spatial genetic structure. Among these variables, geographic distance was ~68% more important than elevation in describing spatial genetic variation, and elevation was ~42% more important than aspect after removing the effect of geographic distance. From these results, we infer a mechanism of hydrochorous seed dispersal along major drainages aided by seasonal monsoon rains. Our findings suggest that landscape features may shape microevolutionary processes at much finer spatial scales than typically considered, and stress the importance of considering how particular dispersal vectors are influenced by their environmental context. © The American Genetic Association 2014. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Genetics and epigenetics of obesity

OpenAIRE

Herrera, Blanca M.; Keildson, Sarah; Lindgren, Cecilia M.

2011-01-01

Obesity results from interactions between environmental and genetic factors. Despite a relatively high heritability of common, non-syndromic obesity (40?70%), the search for genetic variants contributing to susceptibility has been a challenging task. Genome wide association (GWA) studies have dramatically changed the pace of detection of common genetic susceptibility variants. To date, more than 40 genetic variants have been associated with obesity and fat distribution. However, since these v...

Estimating detection rates for the LIGO-Virgo search for gravitational-wave burst counterparts to gamma-ray bursts using inferred local GRB rates

International Nuclear Information System (INIS)

Leonor, I; Frey, R; Sutton, P J; Jones, G; Marka, S; Marka, Z

2009-01-01

One of the ongoing searches performed using the LIGO-Virgo network of gravitational-wave interferometers is the search for gravitational-wave burst (GWB) counterparts to gamma-ray bursts (GRBs). This type of analysis makes use of GRB time and position information from gamma-ray satellite detectors to trigger the GWB search, and the GWB detection rates possible for such an analysis thus strongly depend on the GRB detection efficiencies of the satellite detectors. Using local GRB rate densities inferred from observations which are found in the science literature, we calculate estimates of the GWB detection rates for different configurations of the LIGO-Virgo network for this type of analysis.

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

Directory of Open Access Journals (Sweden)

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

Cultural-Based Genetic Tabu Algorithm for Multiobjective Job Shop Scheduling

Directory of Open Access Journals (Sweden)

Yuzhen Yang

2014-01-01

Full Text Available The job shop scheduling problem, which has been dealt with by various traditional optimization methods over the decades, has proved to be an NP-hard problem and difficult in solving, especially in the multiobjective field. In this paper, we have proposed a novel quadspace cultural genetic tabu algorithm (QSCGTA to solve such problem. This algorithm provides a different structure from the original cultural algorithm in containing double brief spaces and population spaces. These spaces deal with different levels of populations globally and locally by applying genetic and tabu searches separately and exchange information regularly to make the process more effective towards promising areas, along with modified multiobjective domination and transform functions. Moreover, we have presented a bidirectional shifting for the decoding process of job shop scheduling. The computational results we presented significantly prove the effectiveness and efficiency of the cultural-based genetic tabu algorithm for the multiobjective job shop scheduling problem.

Application of Hybrid Genetic Algorithm Routine in Optimizing Food and Bioengineering Processes

Directory of Open Access Journals (Sweden)

Jaya Shankar Tumuluru

2016-11-01

Full Text Available Optimization is a crucial step in the analysis of experimental results. Deterministic methods only converge on local optimums and require exponentially more time as dimensionality increases. Stochastic algorithms are capable of efficiently searching the domain space; however convergence is not guaranteed. This article demonstrates the novelty of the hybrid genetic algorithm (HGA, which combines both stochastic and deterministic routines for improved optimization results. The new hybrid genetic algorithm developed is applied to the Ackley benchmark function as well as case studies in food, biofuel, and biotechnology processes. For each case study, the hybrid genetic algorithm found a better optimum candidate than reported by the sources. In the case of food processing, the hybrid genetic algorithm improved the anthocyanin yield by 6.44%. Optimization of bio-oil production using HGA resulted in a 5.06% higher yield. In the enzyme production process, HGA predicted a 0.39% higher xylanase yield. Hybridization of the genetic algorithm with a deterministic algorithm resulted in an improved optimum compared to statistical methods.

A search for extragalactic pulsars in the local group galaxies IC 10 and Barnard’s galaxy

International Nuclear Information System (INIS)

Al Noori, H; Roberts, M S E; Champion, D; McLaughlin, M; Ransom, Scott; Ray, P S

2017-01-01

As of today, more than 2500 pulsars have been found, nearly all in the Milky Way, with the exception of ∼28 pulsars in the Small and Large Magellanic Clouds. However, there have been few published attempts to search for pulsars deeper in our Galactic neighborhood. Two of the more promising Local Group galaxies are IC 10 and NGC 6822 (also known as Barnard’s Galaxy) due to their relatively high star formation rate and their proximity to our galaxy. IC 10 in particular, holds promise as it is the closest starburst galaxy to us and harbors an unusually high number of Wolf-Rayet stars, implying the presence of many neutron stars. We observed IC 10 and NGC 6822 at 820 MHz with the Green Bank Telescope for ∼15 and 5 hours respectively, and put a strong upper limit of 0.1 mJy on pulsars in either of the two galaxies. We also performed single pulse searches of both galaxies with no firm detections. (paper)

An Improved Genetic Algorithm for Single-Machine Inverse Scheduling Problem

Directory of Open Access Journals (Sweden)

Jianhui Mou

2014-01-01

Full Text Available The goal of the scheduling is to arrange operations on suitable machines with optimal sequence for corresponding objectives. In order to meet market requirements, scheduling systems must own enough flexibility against uncertain events. These events can change production status or processing parameters, even causing the original schedule to no longer be optimal or even to be infeasible. Traditional scheduling strategies, however, cannot cope with these cases. Therefore, a new idea of scheduling called inverse scheduling has been proposed. In this paper, the inverse scheduling with weighted completion time (SMISP is considered in a single-machine shop environment. In this paper, an improved genetic algorithm (IGA with a local searching strategy is proposed. To improve the performance of IGA, efficient encoding scheme, fitness evaluation mechanism, feasible initialization methods, and a local search procedure have been employed in the paper. Because of the local improving method, the proposed IGA can balance its exploration ability and exploitation ability. We adopt 27 instances to verify the effectiveness of the proposed algorithm. The experimental results illustrated that the proposed algorithm can generate satisfactory solutions. This approach also has been applied to solve the scheduling problem in the real Chinese shipyard and can bring some benefits.

Multivariate analysis in a genetic divergence study of Psidium guajava.

Science.gov (United States)

Nogueira, A M; Ferreira, M F S; Guilhen, J H S; Ferreira, A

2014-12-18

The family Myrtaceae is widespread in the Atlantic Forest and is well-represented in the Espírito Santo State in Brazil. In the genus Psidium of this family, guava (Psidium guajava L.) is the most economically important species. Guava is widely cultivated in tropical and subtropical countries; however, the widespread cultivation of only a small number of guava tree cultivars may cause the genetic vulnerability of this crop, making the search for promising genotypes in natural populations important for breeding programs and conservation. In this study, the genetic diversity of 66 guava trees sampled in the southern region of Espírito Santo and in Caparaó, MG, Brazil were evaluated. A total of 28 morphological descriptors (11 quantitative and 17 multicategorical) and 18 microsatellite markers were used. Principal component, discriminant and cluster analyses, descriptive analyses, and genetic diversity analyses using simple sequence repeats were performed. Discrimination of accessions using molecular markers resulted in clustering of genotypes of the same origin, which was not observed using morphological data. Genetic diversity was detected between and within the localities evaluated, regardless of the methodology used. Genetic differentiation among the populations using morphological and molecular data indicated the importance of the study area for species conservation, genetic erosion estimation, and exploitation in breeding programs.

Optimized hyperspectral band selection using hybrid genetic algorithm and gravitational search algorithm

Science.gov (United States)

Zhang, Aizhu; Sun, Genyun; Wang, Zhenjie

2015-12-01

The serious information redundancy in hyperspectral images (HIs) cannot contribute to the data analysis accuracy, instead it require expensive computational resources. Consequently, to identify the most useful and valuable information from the HIs, thereby improve the accuracy of data analysis, this paper proposed a novel hyperspectral band selection method using the hybrid genetic algorithm and gravitational search algorithm (GA-GSA). In the proposed method, the GA-GSA is mapped to the binary space at first. Then, the accuracy of the support vector machine (SVM) classifier and the number of selected spectral bands are utilized to measure the discriminative capability of the band subset. Finally, the band subset with the smallest number of spectral bands as well as covers the most useful and valuable information is obtained. To verify the effectiveness of the proposed method, studies conducted on an AVIRIS image against two recently proposed state-of-the-art GSA variants are presented. The experimental results revealed the superiority of the proposed method and indicated that the method can indeed considerably reduce data storage costs and efficiently identify the band subset with stable and high classification precision.

Dark matter searches with Cherenkov telescopes: nearby dwarf galaxies or local galaxy clusters?

Energy Technology Data Exchange (ETDEWEB)

Sánchez-Conde, Miguel A. [SLAC National Laboratory and Kavli Institute for Particle Astrophysics and Cosmology, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States); Cannoni, Mirco; Gómez, Mario E. [Dpto. Física Aplicada, Facultad de Ciencias Experimentales, Universidad de Huelva, 21071 Huelva (Spain); Zandanel, Fabio; Prada, Francisco, E-mail: masc@stanford.edu, E-mail: mirco.cannoni@dfa.uhu.es, E-mail: fabio@iaa.es, E-mail: mario.gomez@dfa.uhu.es, E-mail: fprada@iaa.es [Instituto de Astrofísica de Andalucía (CSIC), E-18008, Granada (Spain)

2011-12-01

In this paper, we compare dwarf galaxies and galaxy clusters in order to elucidate which object class is the best target for gamma-ray DM searches with imaging atmospheric Cherenkov telescopes (IACTs). We have built a mixed dwarfs+clusters sample containing some of the most promising nearby dwarf galaxies (Draco, Ursa Minor, Wilman 1 and Segue 1) and local galaxy clusters (Perseus, Coma, Ophiuchus, Virgo, Fornax, NGC 5813 and NGC 5846), and then compute their DM annihilation flux profiles by making use of the latest modeling of their DM density profiles. We also include in our calculations the effect of DM substructure. Willman 1 appears as the best candidate in the sample. However, its mass modeling is still rather uncertain, so probably other candidates with less uncertainties and quite similar fluxes, namely Ursa Minor and Segue 1, might be better options. As for galaxy clusters, Virgo represents the one with the highest flux. However, its large spatial extension can be a serious handicap for IACT observations and posterior data analysis. Yet, other local galaxy cluster candidates with more moderate emission regions, such as Perseus, may represent good alternatives. After comparing dwarfs and clusters, we found that the former exhibit annihilation flux profiles that, at the center, are roughly one order of magnitude higher than those of clusters, although galaxy clusters can yield similar, or even higher, integrated fluxes for the whole object once substructure is taken into account. Even when any of these objects are strictly point-like according to the properties of their annihilation signals, we conclude that dwarf galaxies are best suited for observational strategies based on the search of point-like sources, while galaxy clusters represent best targets for analyses that can deal with rather extended emissions. Finally, we study the detection prospects for present and future IACTs in the framework of the constrained minimal supersymmetric standard model. We

Dark Matter Searches with Cherenkov Telescopes: Nearby Dwarf Galaxies or Local Galaxy Clusters?

Energy Technology Data Exchange (ETDEWEB)

Sanchez-Conde, Miguel A.; /KIPAC, Menlo Park /SLAC /IAC, La Laguna /Laguna U., Tenerife; Cannoni, Mirco; /Huelva U.; Zandanel, Fabio; /IAA, Granada; Gomez, Mario E.; /Huelva U.; Prada, Francisco; /IAA, Granada

2012-06-06

In this paper, we compare dwarf galaxies and galaxy clusters in order to elucidate which object class is the best target for gamma-ray DM searches with imaging atmospheric Cherenkov telescopes (IACTs). We have built a mixed dwarfs+clusters sample containing some of the most promising nearby dwarf galaxies (Draco, Ursa Minor, Wilman 1 and Segue 1) and local galaxy clusters (Perseus, Coma, Ophiuchus, Virgo, Fornax, NGC 5813 and NGC 5846), and then compute their DM annihilation flux profiles by making use of the latest modeling of their DM density profiles. We also include in our calculations the effect of DM substructure. Willman 1 appears as the best candidate in the sample. However, its mass modeling is still rather uncertain, so probably other candidates with less uncertainties and quite similar fluxes, namely Ursa Minor and Segue 1, might be better options. As for galaxy clusters, Virgo represents the one with the highest flux. However, its large spatial extension can be a serious handicap for IACT observations and posterior data analysis. Yet, other local galaxy cluster candidates with more moderate emission regions, such as Perseus, may represent good alternatives. After comparing dwarfs and clusters, we found that the former exhibit annihilation flux profiles that, at the center, are roughly one order of magnitude higher than those of clusters, although galaxy clusters can yield similar, or even higher, integrated fluxes for the whole object once substructure is taken into account. Even when any of these objects are strictly point-like according to the properties of their annihilation signals, we conclude that dwarf galaxies are best suited for observational strategies based on the search of point-like sources, while galaxy clusters represent best targets for analyses that can deal with rather extended emissions. Finally, we study the detection prospects for present and future IACTs in the framework of the constrained minimal supersymmetric standard model. We

Search and optimization by metaheuristics techniques and algorithms inspired by nature

CERN Document Server

Du, Ke-Lin

2016-01-01

This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones. An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material. Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computin...

Iterated local search algorithm for solving the orienteering problem with soft time windows.

Science.gov (United States)

Aghezzaf, Brahim; Fahim, Hassan El

2016-01-01

In this paper we study the orienteering problem with time windows (OPTW) and the impact of relaxing the time windows on the profit collected by the vehicle. The way of relaxing time windows adopted in the orienteering problem with soft time windows (OPSTW) that we study in this research is a late service relaxation that allows linearly penalized late services to customers. We solve this problem heuristically by considering a hybrid iterated local search. The results of the computational study show that the proposed approach is able to achieve promising solutions on the OPTW test instances available in the literature, one new best solution is found. On the newly generated test instances of the OPSTW, the results show that the profit collected by the OPSTW is better than the profit collected by the OPTW.

A grand canonical genetic algorithm for the prediction of multi-component phase diagrams and testing of empirical potentials

International Nuclear Information System (INIS)

Tipton, William W; Hennig, Richard G

2013-01-01

We present an evolutionary algorithm which predicts stable atomic structures and phase diagrams by searching the energy landscape of empirical and ab initio Hamiltonians. Composition and geometrical degrees of freedom may be varied simultaneously. We show that this method utilizes information from favorable local structure at one composition to predict that at others, achieving far greater efficiency of phase diagram prediction than a method which relies on sampling compositions individually. We detail this and a number of other efficiency-improving techniques implemented in the genetic algorithm for structure prediction code that is now publicly available. We test the efficiency of the software by searching the ternary Zr–Cu–Al system using an empirical embedded-atom model potential. In addition to testing the algorithm, we also evaluate the accuracy of the potential itself. We find that the potential stabilizes several correct ternary phases, while a few of the predicted ground states are unphysical. Our results suggest that genetic algorithm searches can be used to improve the methodology of empirical potential design. (paper)

A grand canonical genetic algorithm for the prediction of multi-component phase diagrams and testing of empirical potentials.

Science.gov (United States)

Tipton, William W; Hennig, Richard G

2013-12-11

We present an evolutionary algorithm which predicts stable atomic structures and phase diagrams by searching the energy landscape of empirical and ab initio Hamiltonians. Composition and geometrical degrees of freedom may be varied simultaneously. We show that this method utilizes information from favorable local structure at one composition to predict that at others, achieving far greater efficiency of phase diagram prediction than a method which relies on sampling compositions individually. We detail this and a number of other efficiency-improving techniques implemented in the genetic algorithm for structure prediction code that is now publicly available. We test the efficiency of the software by searching the ternary Zr-Cu-Al system using an empirical embedded-atom model potential. In addition to testing the algorithm, we also evaluate the accuracy of the potential itself. We find that the potential stabilizes several correct ternary phases, while a few of the predicted ground states are unphysical. Our results suggest that genetic algorithm searches can be used to improve the methodology of empirical potential design.

Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search Algorithms

Directory of Open Access Journals (Sweden)

Anongrit Kangrang

2018-01-01

Full Text Available Optimal rule curves are necessary guidelines in the reservoir operation that have been used to assess performance of any reservoir to satisfy water supply, irrigation, industrial, hydropower, and environmental conservation requirements. This study applied the conditional genetic algorithm (CGA and the conditional tabu search algorithm (CTSA technique to connect with the reservoir simulation model in order to search optimal reservoir rule curves. The Ubolrat Reservoir located in the northeast region of Thailand was an illustrative application including historic monthly inflow, future inflow generated by the SWAT hydrological model using 50-year future climate data from the PRECIS regional climate model in case of B2 emission scenario by IPCC SRES, water demand, hydrologic data, and physical reservoir data. The future and synthetic inflow data of reservoirs were used to simulate reservoir system for evaluating water situation. The situations of water shortage and excess water were shown in terms of frequency magnitude and duration. The results have shown that the optimal rule curves from CGA and CTSA connected with the simulation model can mitigate drought and flood situations than the existing rule curves. The optimal future rule curves were more suitable for future situations than the other rule curves.

Enhancements to Constrained Novelty Search: Two-Population Novelty Search for Generating Game Content

DEFF Research Database (Denmark)

Liapis, Antonios; Yannakakis, Georgios N.; Togelius, Julian

2013-01-01

pop genetic algorithm. These algorithms are applied to the problem of creating diverse and feasible game levels, representative of a large class of important problems in procedural content generation for games. Results show that the new algorithms under certain conditions can produce larger and more...... diverse sets of feasible strategy game maps than existing algorithms. However, the best algorithm is contingent on the particularities of the search space and the genetic operators used. It is also shown that the proposed enhancement of offspring boosting increases performance in all cases....

Genetic Structure and Molecular Diversity of Cacao Plants Established as Local Varieties for More than Two Centuries: The Genetic History of Cacao Plantations in Bahia, Brazil.

Science.gov (United States)

Santos, Elisa S L; Cerqueira-Silva, Carlos Bernard M; Mori, Gustavo M; Ahnert, Dário; Mello, Durval L N; Pires, José Luis; Corrêa, Ronan X; de Souza, Anete P

2015-01-01

Bahia is the most important cacao-producing state in Brazil, which is currently the sixth-largest country worldwide to produce cacao seeds. In the eighteenth century, the Comum, Pará and Maranhão varieties of cacao were introduced into southern Bahia, and their descendants, which are called 'Bahian cacao' or local Bahian varieties, have been cultivated for over 200 years. Comum plants have been used to start plantations in African countries and extended as far as countries in South Asia and Oceania. In Brazil, two sets of clones selected from Bahian varieties and their mutants, the Agronomic Institute of East (SIAL) and Bahian Cacao Institute (SIC) series, represent the diversity of Bahian cacao in germplasm banks. Because the genetic diversity of Bahian varieties, which is essential for breeding programs, remains unknown, the objective of this work was to assess the genetic structure and diversity of local Bahian varieties collected from farms and germplasm banks. To this end, 30 simple sequence repeat (SSR) markers were used to genotype 279 cacao plants from germplasm and local farms. The results facilitated the identification of 219 cacao plants of Bahian origin, and 51 of these were SIAL or SIC clones. Bahian cacao showed low genetic diversity. It could be verified that SIC and SIAL clones do not represent the true diversity of Bahian cacao, with the greatest amount of diversity found in cacao trees on the farms. Thus, a core collection to aid in prioritizing the plants to be sampled for Bahian cacao diversity is suggested. These results provide information that can be used to conserve Bahian cacao plants and applied in breeding programs to obtain more productive Bahian cacao with superior quality and tolerance to major diseases in tropical cacao plantations worldwide.

Bayesian inference for the genetic control of water deficit tolerance in spring wheat by stochastic search variable selection.

Science.gov (United States)

Safari, Parviz; Danyali, Syyedeh Fatemeh; Rahimi, Mehdi

2018-06-02

Drought is the main abiotic stress seriously influencing wheat production. Information about the inheritance of drought tolerance is necessary to determine the most appropriate strategy to develop tolerant cultivars and populations. In this study, generation means analysis to identify the genetic effects controlling grain yield inheritance in water deficit and normal conditions was considered as a model selection problem in a Bayesian framework. Stochastic search variable selection (SSVS) was applied to identify the most important genetic effects and the best fitted models using different generations obtained from two crosses applying two water regimes in two growing seasons. The SSVS is used to evaluate the effect of each variable on the dependent variable via posterior variable inclusion probabilities. The model with the highest posterior probability is selected as the best model. In this study, the grain yield was controlled by the main effects (additive and non-additive effects) and epistatic. The results demonstrate that breeding methods such as recurrent selection and subsequent pedigree method and hybrid production can be useful to improve grain yield.

High local genetic diversity of canine parvovirus from Ecuador.

Science.gov (United States)

Aldaz, Jaime; García-Díaz, Juan; Calleros, Lucía; Sosa, Katia; Iraola, Gregorio; Marandino, Ana; Hernández, Martín; Panzera, Yanina; Pérez, Ruben

2013-09-27

Canine parvovirus (CPV) comprises three antigenic variants (2a, 2b, and 2c) that are distributed globally with different frequencies and levels of genetic variability. CPVs from central Ecuador were herein analyzed to characterize the strains and to provide new insights into local viral diversity, evolution, and pathogenicity. Variant prevalence was analyzed by PCR and partial sequencing for 53 CPV-positive samples collected during 2011 and 2012. The full-length VP2 gene was sequenced in 24 selected strains and a maximum-likelihood phylogenetic tree was constructed using both Ecuadorian and worldwide strains. Ecuadorian CPVs have a remarkable genetic diversity that includes the circulation of all three variants and the existence of different evolutionary groups or lineages. CPV-2c was the most prevalent variant (54.7%), confirming the spread of this variant in America. Ecuadorian CPV-2c strains clustered in two lineages, which represent the first evidence of polyphyletic CPV-2c circulating in South America. CPV-2a strains constituted 41.5% of the samples and clustered in a single lineage. The two detected CPV-2b strains (3.8%) were clearly polyphyletic and appeared related to Ecuadorian CPV-2a or foreign CPV-2b strains. Besides the substitution at residue 426 that is used to identify the variants, two amino acid changes occurred in Ecuadorian strains: Val139Iso and Thr440Ser. Ser(440) occurred in a biologically relevant domain of VP2 and is here described for the first time in CPV. The associations of Ecuadorian CPV-2c and CPV-2a with clinical symptoms indicate that dull mentation, hemorrhagic gastroenteritis and hypothermia occurred more frequently in infection with CPV-2c than with CPV-2a. Copyright © 2013 Elsevier B.V. All rights reserved.

Genetics Home Reference: nonsyndromic hearing loss

Science.gov (United States)

... Centre for Genetics Education (Australia) Disease InfoSearch: Deafness Harvard Medical School Center for Hereditary Deafness Hereditary Hearing ... Available from http://www.ncbi.nlm.nih.gov/books/NBK1434/ Citation on ... Bulletins Genetics Home Reference Celebrates Its 15th Anniversary ...

Development of an improved genetic algorithm and its application in the optimal design of ship nuclear power system

International Nuclear Information System (INIS)

Jia Baoshan; Yu Jiyang; You Songbo

2005-01-01

This article focuses on the development of an improved genetic algorithm and its application in the optimal design of the ship nuclear reactor system, whose goal is to find a combination of system parameter values that minimize the mass or volume of the system given the power capacity requirement and safety criteria. An improved genetic algorithm (IGA) was developed using an 'average fitness value' grouping + 'specified survival probability' rank selection method and a 'separate-recombine' duplication operator. Combining with a simulated annealing algorithm (SAA) that continues the local search after the IGA reaches a satisfactory point, the algorithm gave satisfactory optimization results from both search efficiency and accuracy perspectives. This IGA-SAA algorithm successfully solved the design optimization problem of ship nuclear power system. It is an advanced and efficient methodology that can be applied to the similar optimization problems in other areas. (authors)

Application of artificial intelligence to search ground-state geometry of clusters

International Nuclear Information System (INIS)

Lemes, Mauricio Ruv; Marim, L.R.; Dal Pino, A. Jr.

2002-01-01

We introduce a global optimization procedure, the neural-assisted genetic algorithm (NAGA). It combines the power of an artificial neural network (ANN) with the versatility of the genetic algorithm. This method is suitable to solve optimization problems that depend on some kind of heuristics to limit the search space. If a reasonable amount of data is available, the ANN can 'understand' the problem and provide the genetic algorithm with a selected population of elements that will speed up the search for the optimum solution. We tested the method in a search for the ground-state geometry of silicon clusters. We trained the ANN with information about the geometry and energetics of small silicon clusters. Next, the ANN learned how to restrict the configurational space for larger silicon clusters. For Si 10 and Si 20 , we noticed that the NAGA is at least three times faster than the 'pure' genetic algorithm. As the size of the cluster increases, it is expected that the gain in terms of time will increase as well

A Moderate Redshift Supernova Search Program

Science.gov (United States)

Adams, M. T.; Wheeler, J. C.; Ward, M.; Wren, W. R.; Schmidt, B. P.

1995-12-01

We report on a recently initiated supernova (SN) search program using the McDonald Observatory 0.76m telescope and Prime Focus Camera (PFC). This SN search program takes advantage of the PFC's 42.6 x 42.6 arcmin FOV to survey moderate redshift Abell clusters in single Kron-Cousins R-band images. Our scientific goal is to discover and provide quality BVRI photometric follow-up, to R \\ +21, for a significant SNe sample at 0.03 group (Perlmutter et al 1995, ApJ, 440, L41), and the High Redshift SN Search Team (Schmidt et al 1995, Aiguiblava NATO ASI Proceedings). The McDonald SN search program includes a sample of the Abell clusters used by Lauer and Postman (1994, ApJ, 425, 418) to analyze Local Group motion. SNe discovered in these clusters contribute to the resolution of the Local Group motion controversy. We present an overview of the McDonald Observatory supernova search program, and discuss recent results.

Spatial correlation genetic algorithm for fractal image compression

International Nuclear Information System (INIS)

Wu, M.-S.; Teng, W.-C.; Jeng, J.-H.; Hsieh, J.-G.

2006-01-01

Fractal image compression explores the self-similarity property of a natural image and utilizes the partitioned iterated function system (PIFS) to encode it. This technique is of great interest both in theory and application. However, it is time-consuming in the encoding process and such drawback renders it impractical for real time applications. The time is mainly spent on the search for the best-match block in a large domain pool. In this paper, a spatial correlation genetic algorithm (SC-GA) is proposed to speed up the encoder. There are two stages for the SC-GA method. The first stage makes use of spatial correlations in images for both the domain pool and the range pool to exploit local optima. The second stage is operated on the whole image to explore more adequate similarities if the local optima are not satisfied. With the aid of spatial correlation in images, the encoding time is 1.5 times faster than that of traditional genetic algorithm method, while the quality of the retrieved image is almost the same. Moreover, about half of the matched blocks come from the correlated space, so fewer bits are required to represent the fractal transform and therefore the compression ratio is also improved

Modification site localization scoring integrated into a search engine.

Science.gov (United States)

Baker, Peter R; Trinidad, Jonathan C; Chalkley, Robert J

2011-07-01

Large proteomic data sets identifying hundreds or thousands of modified peptides are becoming increasingly common in the literature. Several methods for assessing the reliability of peptide identifications both at the individual peptide or data set level have become established. However, tools for measuring the confidence of modification site assignments are sparse and are not often employed. A few tools for estimating phosphorylation site assignment reliabilities have been developed, but these are not integral to a search engine, so require a particular search engine output for a second step of processing. They may also require use of a particular fragmentation method and are mostly only applicable for phosphorylation analysis, rather than post-translational modifications analysis in general. In this study, we present the performance of site assignment scoring that is directly integrated into the search engine Protein Prospector, which allows site assignment reliability to be automatically reported for all modifications present in an identified peptide. It clearly indicates when a site assignment is ambiguous (and if so, between which residues), and reports an assignment score that can be translated into a reliability measure for individual site assignments.

Genetic variability, local selection and demographic history: genomic evidence of evolving towards allopatric speciation in Asian seabass.

Science.gov (United States)

Wang, Le; Wan, Zi Yi; Lim, Huan Sein; Yue, Gen Hua

2016-08-01

Genomewide analysis of genetic divergence is critically important in understanding the genetic processes of allopatric speciation. We sequenced RAD tags of 131 Asian seabass individuals of six populations from South-East Asia and Australia/Papua New Guinea. Using 32 433 SNPs, we examined the genetic diversity and patterns of population differentiation across all the populations. We found significant evidence of genetic heterogeneity between South-East Asian and Australian/Papua New Guinean populations. The Australian/Papua New Guinean populations showed a rather lower level of genetic diversity. FST and principal components analysis revealed striking divergence between South-East Asian and Australian/Papua New Guinean populations. Interestingly, no evidence of contemporary gene flow was observed. The demographic history was further tested based on the folded joint site frequency spectrum. The scenario of ancient migration with historical population size changes was suggested to be the best fit model to explain the genetic divergence of Asian seabass between South-East Asia and Australia/Papua New Guinea. This scenario also revealed that Australian/Papua New Guinean populations were founded by ancestors from South-East Asia during mid-Pleistocene and were completely isolated from the ancestral population after the last glacial retreat. We also detected footprints of local selection, which might be related to differential ecological adaptation. The ancient gene flow was examined and deemed likely insufficient to counteract the genetic differentiation caused by genetic drift. The observed genomic pattern of divergence conflicted with the 'genomic islands' scenario. Altogether, Asian seabass have likely been evolving towards allopatric speciation since the split from the ancestral population during mid-Pleistocene. © 2016 John Wiley & Sons Ltd.

Reactor controller design using genetic algorithms with simulated annealing

International Nuclear Information System (INIS)

Erkan, K.; Buetuen, E.

2000-01-01

This chapter presents a digital control system for ITU TRIGA Mark-II reactor using genetic algorithms with simulated annealing. The basic principles of genetic algorithms for problem solving are inspired by the mechanism of natural selection. Natural selection is a biological process in which stronger individuals are likely to be winners in a competing environment. Genetic algorithms use a direct analogy of natural evolution. Genetic algorithms are global search techniques for optimisation but they are poor at hill-climbing. Simulated annealing has the ability of probabilistic hill-climbing. Thus, the two techniques are combined here to get a fine-tuned algorithm that yields a faster convergence and a more accurate search by introducing a new mutation operator like simulated annealing or an adaptive cooling schedule. In control system design, there are currently no systematic approaches to choose the controller parameters to obtain the desired performance. The controller parameters are usually determined by test and error with simulation and experimental analysis. Genetic algorithm is used automatically and efficiently searching for a set of controller parameters for better performance. (orig.)

[Quality assurance in human genetic testing].

Science.gov (United States)

Stuhrmann-Spangenberg, Manfred

2015-02-01

Advances in technical developments of genetic diagnostics for more than 50 years, as well as the fact that human genetic testing is usually performed only once in a lifetime, with additional impact for blood relatives, are determining the extraordinary importance of quality assurance in human genetic testing. Abidance of laws, directives, and guidelines plays a major role. This article aims to present the major laws, directives, and guidelines with respect to quality assurance of human genetic testing, paying careful attention to internal and external quality assurance. The information on quality assurance of human genetic testing was obtained through a web-based search of the web pages that are referred to in this article. Further information was retrieved from publications in the German Society of Human Genetics and through a PubMed-search using term quality + assurance + genetic + diagnostics. The most important laws, directives, and guidelines for quality assurance of human genetic testing are the gene diagnostics law (GenDG), the directive of the Federal Medical Council for quality control of clinical laboratory analysis (RiliBÄK), and the S2K guideline for human genetic diagnostics and counselling. In addition, voluntary accreditation under DIN EN ISO 15189:2013 offers a most recommended contribution towards quality assurance of human genetic testing. Legal restraints on quality assurance of human genetic testing as mentioned in § 5 GenDG are fulfilled once RiliBÄK requirements are followed.

Evolutionary Cellular Automata for Image Segmentation and Noise Filtering Using Genetic Algorithms

Directory of Open Access Journals (Sweden)

Sihem SLATNIA

2011-01-01

Full Text Available We use an evolutionary process to seek a specialized set of rules among a wide range of rules to be used by Cellular Automata (CA for a range of tasks,extracting edges in a given gray or colour image, noise filtering applied to black-white image. This is the best set of local rules determine the future state of CA in an asynchronous way. The Genetic Algorithm (GA is applied to search the best CA rules that can realize the best edge detection and noise filtering.

Evolutionary Cellular Automata for Image Segmentation and Noise Filtering Using Genetic Algorithms

Directory of Open Access Journals (Sweden)

Okba Kazar

2011-01-01

Full Text Available We use an evolutionary process to seek a specialized set of rules among a wide range of rules to be used by Cellular Automata (CA for a range of tasks, extracting edges in a given gray or colour image, noise filtering applied to black-white image. This is the best set of local rules determine the future state of CA in an asynchronous way. The Genetic Algorithm (GA is applied to search the best CA rules that can realize the best edge detection and noise filtering.

HUBBLE SPACE TELESCOPE SNAPSHOT SEARCH FOR PLANETARY NEBULAE IN GLOBULAR CLUSTERS OF THE LOCAL GROUP

Energy Technology Data Exchange (ETDEWEB)

Bond, Howard E., E-mail: heb11@psu.edu [Department of Astronomy and Astrophysics, Pennsylvania State University, University Park, PA 16802 (United States)

2015-04-15

Single stars in ancient globular clusters (GCs) are believed incapable of producing planetary nebulae (PNs), because their post-asymptotic-giant-branch evolutionary timescales are slower than the dissipation timescales for PNs. Nevertheless, four PNs are known in Galactic GCs. Their existence likely requires more exotic evolutionary channels, including stellar mergers and common-envelope binary interactions. I carried out a snapshot imaging search with the Hubble Space Telescope (HST) for PNs in bright Local Group GCs outside the Milky Way. I used a filter covering the 5007 Å nebular emission line of [O iii], and another one in the nearby continuum, to image 66 GCs. Inclusion of archival HST frames brought the total number of extragalactic GCs imaged at 5007 Å to 75, whose total luminosity slightly exceeds that of the entire Galactic GC system. I found no convincing PNs in these clusters, aside from one PN in a young M31 cluster misclassified as a GC, and two PNs at such large angular separations from an M31 GC that membership is doubtful. In a ground-based spectroscopic survey of 274 old GCs in M31, Jacoby et al. found three candidate PNs. My HST images of one of them suggest that the [O iii] emission actually arises from ambient interstellar medium rather than a PN; for the other two candidates, there are broadband archival UV HST images that show bright, blue point sources that are probably the PNs. In a literature search, I also identified five further PN candidates lying near old GCs in M31, for which follow-up observations are necessary to confirm their membership. The rates of incidence of PNs are similar, and small but nonzero, throughout the GCs of the Local Group.

Disease and genetic contributions toward local tissue volume disturbances in schizophrenia: a tensor-based morphometry study.

Science.gov (United States)

Yang, Yaling; Nuechterlein, Keith H; Phillips, Owen R; Gutman, Boris; Kurth, Florian; Dinov, Ivo; Thompson, Paul M; Asarnow, Robert F; Toga, Arthur W; Narr, Katherine L

2012-09-01

Structural brain deficits, especially frontotemporal volume reduction and ventricular enlargement, have been repeatedly reported in patients with schizophrenia. However, it remains unclear whether brain structural deformations may be attributable to disease-related or genetic factors. In this study, the structural magnetic resonance imaging data of 48 adult-onset schizophrenia patients, 65 first-degree nonpsychotic relatives of schizophrenia patients, 27 community comparison (CC) probands, and 73 CC relatives were examined using tensor-based morphometry (TBM) to isolate global and localized differences in tissue volume across the entire brain between groups. We found brain tissue contractions most prominently in frontal and temporal regions and expansions in the putamen/pallidum, and lateral and third ventricles in schizophrenia patients when compared with unrelated CC probands. Results were similar, though less prominent when patients were compared with their nonpsychotic relatives. Structural deformations observed in unaffected patient relatives compared to age-similar CC relatives were suggestive of schizophrenia-related genetic liability and were pronounced in the putamen/pallidum and medial temporal regions. Schizophrenia and genetic liability effects for the putamen/pallidum were confirmed by regions-of-interest analysis. In conclusion, TBM findings complement reports of frontal, temporal, and ventricular dysmorphology in schizophrenia and further indicate that putamen/pallidum enlargements, originally linked mainly with medication exposure in early studies, also reflect a genetic predisposition for schizophrenia. Thus, brain deformation profiles revealed in this study may help to clarify the role of specific genetic or environmental risk factors toward altered brain morphology in schizophrenia.

Optimizing heliostat positions with local search metaheuristics using a ray tracing optical model

Science.gov (United States)

Reinholz, Andreas; Husenbeth, Christof; Schwarzbözl, Peter; Buck, Reiner

2017-06-01

The life cycle costs of solar tower power plants are mainly determined by the investment costs of its construction. Significant parts of these investment costs are used for the heliostat field. Therefore, an optimized placement of the heliostats gaining the maximal annual power production has a direct impact on the life cycle costs revenue ratio. We present a two level local search method implemented in MATLAB utilizing the Monte Carlo raytracing software STRAL [1] for the evaluation of the annual power output for a specific weighted annual time scheme. The algorithm was applied to a solar tower power plant (PS10) with 624 heliostats. Compared to former work of Buck [2], we were able to improve both runtime of the algorithm and quality of the output solutions significantly. Using the same environment for both algorithms, we were able to reach Buck's best solution with a speed up factor of about 20.

Registration of TLS and MLS Point Cloud Combining Genetic Algorithm with ICP

Directory of Open Access Journals (Sweden)

YAN Li

2018-04-01

Full Text Available Large scene point cloud can be quickly acquired by mobile laser scanning (MLS technology,which needs to be supplemented by terrestrial laser scanning (TLS point cloud because of limited field of view and occlusion.MLS and TLS point cloud are located in geodetic coordinate system and local coordinate system respectively.This paper proposes an automatic registration method combined genetic algorithm (GA and iterative closed point ICP to achieve a uniform coordinate reference frame.The local optimizer is utilized in ICP.The efficiency of ICP is higher than that of GA registration,but it depends on a initial solution.GA is a global optimizer,but it's inefficient.The combining strategy is that ICP is enabled to complete the registration when the GA tends to local search.The rough position measured by a built-in GPS of a terrestrial laser scanner is used in the GA registration to limit its optimizing search space.To improve the GA registration accuracy,a maximum registration model called normalized sum of matching scores (NSMS is presented.The results for measured data show that the NSMS model is effective,the root mean square error (RMSE of GA registration is 1~5 cm and the registration efficiency can be improved by about 50% combining GA with ICP.

Stochastic search techniques for post-fault restoration of electrical ...

Indian Academy of Sciences (India)

Three stochastic search techniques have been used to find the optimal sequence of operations required to restore supply in an electrical distribution system on the occurrence of a fault. The three techniques are the genetic algorithm,simulated annealing and the tabu search. The performance of these techniques has been ...

Environmental and Genetic Factors Regulating Localization of the Plant Plasma Membrane H+-ATPase.

Science.gov (United States)

Haruta, Miyoshi; Tan, Li Xuan; Bushey, Daniel B; Swanson, Sarah J; Sussman, Michael R

2018-01-01

A P-type H + -ATPase is the primary transporter that converts ATP to electrochemical energy at the plasma membrane of higher plants. Its product, the proton-motive force, is composed of an electrical potential and a pH gradient. Many studies have demonstrated that this proton-motive force not only drives the secondary transporters required for nutrient uptake, but also plays a direct role in regulating cell expansion. Here, we have generated a transgenic Arabidopsis ( Arabidopsis thaliana ) plant expressing H + -ATPase isoform 2 (AHA2) that is translationally fused with a fluorescent protein and examined its cellular localization by live-cell microscopy. Using a 3D imaging approach with seedlings grown for various times under a variety of light intensities, we demonstrate that AHA2 localization at the plasma membrane of root cells requires light. In dim light conditions, AHA2 is found in intracellular compartments, in addition to the plasma membrane. This localization profile was age-dependent and specific to cell types found in the transition zone located between the meristem and elongation zones. The accumulation of AHA2 in intracellular compartments is consistent with reduced H + secretion near the transition zone and the suppression of root growth. By examining AHA2 localization in a knockout mutant of a receptor protein kinase, FERONIA, we found that the intracellular accumulation of AHA2 in the transition zone is dependent on a functional FERONIA-dependent inhibitory response in root elongation. Overall, this study provides a molecular underpinning for understanding the genetic, environmental, and developmental factors influencing root growth via localization of the plasma membrane H + -ATPase. © 2018 American Society of Plant Biologists. All Rights Reserved.

D-score: a search engine independent MD-score.

Science.gov (United States)

Vaudel, Marc; Breiter, Daniela; Beck, Florian; Rahnenführer, Jörg; Martens, Lennart; Zahedi, René P

2013-03-01

While peptides carrying PTMs are routinely identified in gel-free MS, the localization of the PTMs onto the peptide sequences remains challenging. Search engine scores of secondary peptide matches have been used in different approaches in order to infer the quality of site inference, by penalizing the localization whenever the search engine similarly scored two candidate peptides with different site assignments. In the present work, we show how the estimation of posterior error probabilities for peptide candidates allows the estimation of a PTM score called the D-score, for multiple search engine studies. We demonstrate the applicability of this score to three popular search engines: Mascot, OMSSA, and X!Tandem, and evaluate its performance using an already published high resolution data set of synthetic phosphopeptides. For those peptides with phosphorylation site inference uncertainty, the number of spectrum matches with correctly localized phosphorylation increased by up to 25.7% when compared to using Mascot alone, although the actual increase depended on the fragmentation method used. Since this method relies only on search engine scores, it can be readily applied to the scoring of the localization of virtually any modification at no additional experimental or in silico cost. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Inversion for Refractivity Parameters Using a Dynamic Adaptive Cuckoo Search with Crossover Operator Algorithm.

Science.gov (United States)

Zhang, Zhihua; Sheng, Zheng; Shi, Hanqing; Fan, Zhiqiang

2016-01-01

Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS) algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO). Rechenberg's 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter.

Forecasting nonlinear chaotic time series with function expression method based on an improved genetic-simulated annealing algorithm.

Science.gov (United States)

Wang, Jun; Zhou, Bi-hua; Zhou, Shu-dao; Sheng, Zheng

2015-01-01

The paper proposes a novel function expression method to forecast chaotic time series, using an improved genetic-simulated annealing (IGSA) algorithm to establish the optimum function expression that describes the behavior of time series. In order to deal with the weakness associated with the genetic algorithm, the proposed algorithm incorporates the simulated annealing operation which has the strong local search ability into the genetic algorithm to enhance the performance of optimization; besides, the fitness function and genetic operators are also improved. Finally, the method is applied to the chaotic time series of Quadratic and Rossler maps for validation. The effect of noise in the chaotic time series is also studied numerically. The numerical results verify that the method can forecast chaotic time series with high precision and effectiveness, and the forecasting precision with certain noise is also satisfactory. It can be concluded that the IGSA algorithm is energy-efficient and superior.

Search for heavy resonances decaying to top quarks (and related searches)

CERN Document Server

Haley, Joseph; The ATLAS collaboration

2017-01-01

Searches for new resonances that decay either to pairs of top quarks or a top and a b-quark will be presented. The searches are performed with the ATLAS experiment at the LHC using proton-proton collision data collected in 2015 and 2016 with a centre-of-mass energy of 13 TeV. The invariant mass spectrum of hypothetical resonances are examined for local excesses or deficits that are inconsistent with the Standard Model prediction.​

Collective search by ants in microgravity

Directory of Open Access Journals (Sweden)

Stefanie M. Countryman

2015-03-01

Full Text Available The problem of collective search is a tradeoff between searching thoroughly and covering as much area as possible. This tradeoff depends on the density of searchers. Solutions to the problem of collective search are currently of much interest in robotics and in the study of distributed algorithms, for example to design ways that without central control robots can use local information to perform search and rescue operations. Ant colonies operate without central control. Because they can perceive only local, mostly chemical and tactile cues, they must search collectively to find resources and to monitor the colony's environment. Examining how ants in diverse environments solve the problem of collective search can elucidate how evolution has led to diverse forms of collective behavior. An experiment on the International Space Station in January 2014 examined how ants (Tetramorium caespitum perform collective search in microgravity. In the ISS experiment, the ants explored a small arena in which a barrier was lowered to increase the area and thus lower ant density. In microgravity, relative to ground controls, ants explored the area less thoroughly and took more convoluted paths. It appears that the difficulty of holding on to the surface interfered with the ants’ ability to search collectively. Ants frequently lost contact with the surface, but showed a remarkable ability to regain contact with the surface.

Local search for optimal global map generation using mid-decadal landsat images

Science.gov (United States)

Khatib, L.; Gasch, J.; Morris, Robert; Covington, S.

2007-01-01

NASA and the US Geological Survey (USGS) are seeking to generate a map of the entire globe using Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor data from the "mid-decadal" period of 2004 through 2006. The global map is comprised of thousands of scene locations and, for each location, tens of different images of varying quality to chose from. Furthermore, it is desirable for images of adjacent scenes be close together in time of acquisition, to avoid obvious discontinuities due to seasonal changes. These characteristics make it desirable to formulate an automated solution to the problem of generating the complete map. This paper formulates a Global Map Generator problem as a Constraint Optimization Problem (GMG-COP) and describes an approach to solving it using local search. Preliminary results of running the algorithm on image data sets are summarized. The results suggest a significant improvement in map quality using constraint-based solutions. Copyright ?? 2007, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

DNA markers reveal genetic structure and localized diversity of ...

African Journals Online (AJOL)

uqhdesma

2016-10-12

Oct 12, 2016 ... STRUCTURE analysis revealed 4 clusters of genetically ..... 10000 cycles and 50000 Markov Chain Monte Carlo (MCMC) iterations and 10 replicate runs performed for each K value to ..... WL, Lee M, Porter K (2000). Genetic ...

SpolSimilaritySearch - A web tool to compare and search similarities between spoligotypes of Mycobacterium tuberculosis complex.

Science.gov (United States)

Couvin, David; Zozio, Thierry; Rastogi, Nalin

2017-07-01

Spoligotyping is one of the most commonly used polymerase chain reaction (PCR)-based methods for identification and study of genetic diversity of Mycobacterium tuberculosis complex (MTBC). Despite its known limitations if used alone, the methodology is particularly useful when used in combination with other methods such as mycobacterial interspersed repetitive units - variable number of tandem DNA repeats (MIRU-VNTRs). At a worldwide scale, spoligotyping has allowed identification of information on 103,856 MTBC isolates (corresponding to 98049 clustered strains plus 5807 unique isolates from 169 countries of patient origin) contained within the SITVIT2 proprietary database of the Institut Pasteur de la Guadeloupe. The SpolSimilaritySearch web-tool described herein (available at: http://www.pasteur-guadeloupe.fr:8081/SpolSimilaritySearch) incorporates a similarity search algorithm allowing users to get a complete overview of similar spoligotype patterns (with information on presence or absence of 43 spacers) in the aforementioned worldwide database. This tool allows one to analyze spread and evolutionary patterns of MTBC by comparing similar spoligotype patterns, to distinguish between widespread, specific and/or confined patterns, as well as to pinpoint patterns with large deleted blocks, which play an intriguing role in the genetic epidemiology of M. tuberculosis. Finally, the SpolSimilaritySearch tool also provides with the country distribution patterns for each queried spoligotype. Copyright © 2017 Elsevier Ltd. All rights reserved.

Generalised Adaptive Harmony Search: A Comparative Analysis of Modern Harmony Search

Directory of Open Access Journals (Sweden)

Jaco Fourie

2013-01-01

Full Text Available Harmony search (HS was introduced in 2001 as a heuristic population-based optimisation algorithm. Since then HS has become a popular alternative to other heuristic algorithms like simulated annealing and particle swarm optimisation. However, some flaws, like the need for parameter tuning, were identified and have been a topic of study for much research over the last 10 years. Many variants of HS were developed to address some of these flaws, and most of them have made substantial improvements. In this paper we compare the performance of three recent HS variants: exploratory harmony search, self-adaptive harmony search, and dynamic local-best harmony search. We compare the accuracy of these algorithms, using a set of well-known optimisation benchmark functions that include both unimodal and multimodal problems. Observations from this comparison led us to design a novel hybrid that combines the best attributes of these modern variants into a single optimiser called generalised adaptive harmony search.

Genetic Learning Particle Swarm Optimization.

Science.gov (United States)

Gong, Yue-Jiao; Li, Jing-Jing; Zhou, Yicong; Li, Yun; Chung, Henry Shu-Hung; Shi, Yu-Hui; Zhang, Jun

2016-10-01

Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This observation recently leads to hybridizing PSO with GA for performance enhancement. However, existing work uses a mechanistic parallel superposition and research has shown that construction of superior exemplars in PSO is more effective. Hence, this paper first develops a new framework so as to organically hybridize PSO with another optimization technique for "learning." This leads to a generalized "learning PSO" paradigm, the *L-PSO. The paradigm is composed of two cascading layers, the first for exemplar generation and the second for particle updates as per a normal PSO algorithm. Using genetic evolution to breed promising exemplars for PSO, a specific novel *L-PSO algorithm is proposed in the paper, termed genetic learning PSO (GL-PSO). In particular, genetic operators are used to generate exemplars from which particles learn and, in turn, historical search information of particles provides guidance to the evolution of the exemplars. By performing crossover, mutation, and selection on the historical information of particles, the constructed exemplars are not only well diversified, but also high qualified. Under such guidance, the global search ability and search efficiency of PSO are both enhanced. The proposed GL-PSO is tested on 42 benchmark functions widely adopted in the literature. Experimental results verify the effectiveness, efficiency, robustness, and scalability of the GL-PSO.

Local adaptation and pronounced genetic differentiation in an extremophile fish, Poecilia mexicana, inhabiting a Mexican cave with toxic hydrogen sulphide.

Science.gov (United States)

Plath, M; Hauswaldt, J S; Moll, K; Tobler, M; García De León, F J; Schlupp, I; Tiedemann, R

2007-03-01

We investigated genetic differentiation and migration patterns in a small livebearing fish, Poecilia mexicana, inhabiting a sulfidic Mexican limestone cave (Cueva del Azufre). We examined fish from three different cave chambers, the sulfidic surface creek draining the cave (El Azufre) and a nearby surface creek without the toxic hydrogen sulphide (Arroyo Cristal). Using microsatellite analysis of 10 unlinked loci, we found pronounced genetic differentiation among the three major habitats: Arroyo Cristal, El Azufre and the cave. Genetic differentiation was also found within the cave between different pools. An estimation of first-generation migrants suggests that (i) migration is unidirectional, out of the cave, and (ii) migration among different cave chambers occurs to some extent. We investigated if the pattern of genetic differentiation is also reflected in a morphological trait, eye size. Relatively large eyes were found in surface habitats, small eyes in the anterior cave chambers, and the smallest eyes were detected in the innermost cave chamber (XIII). This pattern shows some congruence with a previously proposed morphocline in eye size. However, our data do not support the proposed mechanism for this morphocline, namely that it would be maintained by migration from both directions into the middle cave chambers. This would have led to an increased variance in eye size in the middle cave chambers, which we did not find. Restricted gene flow between the cave and the surface can be explained by local adaptations to extreme environmental conditions, namely H2S and absence of light. Within the cave system, habitat properties are patchy, and genetic differentiation between cave chambers despite migration could indicate local adaptation at an even smaller scale.

Computer-aided diagnostic scheme for the detection of lung nodules on chest radiographs: Localized search method based on anatomical classification

International Nuclear Information System (INIS)

Shiraishi, Junji; Li Qiang; Suzuki, Kenji; Engelmann, Roger; Doi, Kunio

2006-01-01

We developed an advanced computer-aided diagnostic (CAD) scheme for the detection of various types of lung nodules on chest radiographs intended for implementation in clinical situations. We used 924 digitized chest images (992 noncalcified nodules) which had a 500x500 matrix size with a 1024 gray scale. The images were divided randomly into two sets which were used for training and testing of the computerized scheme. In this scheme, the lung field was first segmented by use of a ribcage detection technique, and then a large search area (448x448 matrix size) within the chest image was automatically determined by taking into account the locations of a midline and a top edge of the segmented ribcage. In order to detect lung nodule candidates based on a localized search method, we divided the entire search area into 7x7 regions of interest (ROIs: 64x64 matrix size). In the next step, each ROI was classified anatomically into apical, peripheral, hilar, and diaphragm/heart regions by use of its image features. Identification of lung nodule candidates and extraction of image features were applied for each localized region (128x128 matrix size), each having its central part (64x64 matrix size) located at a position corresponding to a ROI that was classified anatomically in the previous step. Initial candidates were identified by use of the nodule-enhanced image obtained with the average radial-gradient filtering technique, in which the filter size was varied adaptively depending on the location and the anatomical classification of the ROI. We extracted 57 image features from the original and nodule-enhanced images based on geometric, gray-level, background structure, and edge-gradient features. In addition, 14 image features were obtained from the corresponding locations in the contralateral subtraction image. A total of 71 image features were employed for three sequential artificial neural networks (ANNs) in order to reduce the number of false-positive candidates. All

Genetic and family counselling for schizophrenia: Where do we ...

African Journals Online (AJOL)

Background: Recent genetic findings have led to profound changes in genetic and family counselling for schizophrenia patients and their families. Objectives: The article gives an overview of the present knowledge regarding the genetic and family counselling for schizophrenia. Method: Literature searches were performed ...

Deep-Sea Astronomy: Searching for Signals of Recent Nucleosynthesis in the Local Universe with AMS

International Nuclear Information System (INIS)

Feige, J.

2012-01-01

Stars with masses larger than 8 Msun end their life in a supernova (SN) explosion. The nuclides, which are created in the late burning phases of such stars and also during the explosion are ejected and entrained in the SN-shell. This material expands rapidly into the surrounding interstellar medium. Such events happened in the recent history in our solar neighborhood and led to the formation of the Local Bubble, characterized as a hot void embedding our solar system. Minute traces of close-by SN ejects might be found in terrestrial archives and can potentially be detected by accelerator mass spectrometry (AMS). I will report on the search for SN-ejected long-lived radionuclides in two deep-sea sediment cores from the Indian Ocean. (author)

High-precision approach to localization scheme of visible light communication based on artificial neural networks and modified genetic algorithms

Science.gov (United States)

Guan, Weipeng; Wu, Yuxiang; Xie, Canyu; Chen, Hao; Cai, Ye; Chen, Yingcong

2017-10-01

An indoor positioning algorithm based on visible light communication (VLC) is presented. This algorithm is used to calculate a three-dimensional (3-D) coordinate of an indoor optical wireless environment, which includes sufficient orders of multipath reflections from reflecting surfaces of the room. Leveraging the global optimization ability of the genetic algorithm (GA), an innovative framework for 3-D position estimation based on a modified genetic algorithm is proposed. Unlike other techniques using VLC for positioning, the proposed system can achieve indoor 3-D localization without making assumptions about the height or acquiring the orientation angle of the mobile terminal. Simulation results show that an average localization error of less than 1.02 cm can be achieved. In addition, in most VLC-positioning systems, the effect of reflection is always neglected and its performance is limited by reflection, which makes the results not so accurate for a real scenario and the positioning errors at the corners are relatively larger than other places. So, we take the first-order reflection into consideration and use artificial neural network to match the model of a nonlinear channel. The studies show that under the nonlinear matching of direct and reflected channels the average positioning errors of four corners decrease from 11.94 to 0.95 cm. The employed algorithm is emerged as an effective and practical method for indoor localization and outperform other existing indoor wireless localization approaches.

Ringed Seal Search for Global Optimization via a Sensitive Search Model.

Directory of Open Access Journals (Sweden)

Younes Saadi

Full Text Available The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS is introduced. It is inspired by the natural behavior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emitted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and validations were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of convergence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive and exploitation (intensive of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be

A Local and Global Search Combine Particle Swarm Optimization Algorithm for Job-Shop Scheduling to Minimize Makespan

Directory of Open Access Journals (Sweden)

Zhigang Lian

2010-01-01

Full Text Available The Job-shop scheduling problem (JSSP is a branch of production scheduling, which is among the hardest combinatorial optimization problems. Many different approaches have been applied to optimize JSSP, but for some JSSP even with moderate size cannot be solved to guarantee optimality. The original particle swarm optimization algorithm (OPSOA, generally, is used to solve continuous problems, and rarely to optimize discrete problems such as JSSP. In OPSOA, through research I find that it has a tendency to get stuck in a near optimal solution especially for middle and large size problems. The local and global search combine particle swarm optimization algorithm (LGSCPSOA is used to solve JSSP, where particle-updating mechanism benefits from the searching experience of one particle itself, the best of all particles in the swarm, and the best of particles in neighborhood population. The new coding method is used in LGSCPSOA to optimize JSSP, and it gets all sequences are feasible solutions. Three representative instances are made computational experiment, and simulation shows that the LGSCPSOA is efficacious for JSSP to minimize makespan.

Adaptive switching gravitational search algorithm: an attempt to ...

Indian Academy of Sciences (India)

Nor Azlina Ab Aziz

An adaptive gravitational search algorithm (GSA) that switches between synchronous and ... genetic algorithm (GA), bat-inspired algorithm (BA) and grey wolf optimizer (GWO). ...... heuristic with applications in applied electromagnetics. Prog.

Human genetic factors in tuberculosis: an update.

Science.gov (United States)

van Tong, Hoang; Velavan, Thirumalaisamy P; Thye, Thorsten; Meyer, Christian G

2017-09-01

Tuberculosis (TB) is a major threat to human health, especially in many developing countries. Human genetic variability has been recognised to be of great relevance in host responses to Mycobacterium tuberculosis infection and in regulating both the establishment and the progression of the disease. An increasing number of candidate gene and genome-wide association studies (GWAS) have focused on human genetic factors contributing to susceptibility or resistance to TB. To update previous reviews on human genetic factors in TB we searched the MEDLINE database and PubMed for articles from 1 January 2014 through 31 March 2017 and reviewed the role of human genetic variability in TB. Search terms applied in various combinations were 'tuberculosis', 'human genetics', 'candidate gene studies', 'genome-wide association studies' and 'Mycobacterium tuberculosis'. Articles in English retrieved and relevant references cited in these articles were reviewed. Abstracts and reports from meetings were also included. This review provides a recent summary of associations of polymorphisms of human genes with susceptibility/resistance to TB. © 2017 John Wiley & Sons Ltd.

PMD2HD--a web tool aligning a PubMed search results page with the local German Cancer Research Centre library collection.

Science.gov (United States)

Bohne-Lang, Andreas; Lang, Elke; Taube, Anke

2005-06-27

Web-based searching is the accepted contemporary mode of retrieving relevant literature, and retrieving as many full text articles as possible is a typical prerequisite for research success. In most cases only a proportion of references will be directly accessible as digital reprints through displayed links. A large number of references, however, have to be verified in library catalogues and, depending on their availability, are accessible as print holdings or by interlibrary loan request. The problem of verifying local print holdings from an initial retrieval set of citations can be solved using Z39.50, an ANSI protocol for interactively querying library information systems. Numerous systems include Z39.50 interfaces and therefore can process Z39.50 interactive requests. However, the programmed query interaction command structure is non-intuitive and inaccessible to the average biomedical researcher. For the typical user, it is necessary to implement the protocol within a tool that hides and handles Z39.50 syntax, presenting a comfortable user interface. PMD2HD is a web tool implementing Z39.50 to provide an appropriately functional and usable interface to integrate into the typical workflow that follows an initial PubMed literature search, providing users with an immediate asset to assist in the most tedious step in literature retrieval, checking for subscription holdings against a local online catalogue. PMD2HD can facilitate literature access considerably with respect to the time and cost of manual comparisons of search results with local catalogue holdings. The example presented in this article is related to the library system and collections of the German Cancer Research Centre. However, the PMD2HD software architecture and use of common Z39.50 protocol commands allow for transfer to a broad range of scientific libraries using Z39.50-compatible library information systems.

Inversion for Refractivity Parameters Using a Dynamic Adaptive Cuckoo Search with Crossover Operator Algorithm

Directory of Open Access Journals (Sweden)

Zhihua Zhang

2016-01-01

Full Text Available Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO. Rechenberg’s 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter.

Policy implications for familial searching.

Science.gov (United States)

Kim, Joyce; Mammo, Danny; Siegel, Marni B; Katsanis, Sara H

2011-11-01

In the United States, several states have made policy decisions regarding whether and how to use familial searching of the Combined DNA Index System (CODIS) database in criminal investigations. Familial searching pushes DNA typing beyond merely identifying individuals to detecting genetic relatedness, an application previously reserved for missing persons identifications and custody battles. The intentional search of CODIS for partial matches to an item of evidence offers law enforcement agencies a powerful tool for developing investigative leads, apprehending criminals, revitalizing cold cases and exonerating wrongfully convicted individuals. As familial searching involves a range of logistical, social, ethical and legal considerations, states are now grappling with policy options for implementing familial searching to balance crime fighting with its potential impact on society. When developing policies for familial searching, legislators should take into account the impact of familial searching on select populations and the need to minimize personal intrusion on relatives of individuals in the DNA database. This review describes the approaches used to narrow a suspect pool from a partial match search of CODIS and summarizes the economic, ethical, logistical and political challenges of implementing familial searching. We examine particular US state policies and the policy options adopted to address these issues. The aim of this review is to provide objective background information on the controversial approach of familial searching to inform policy decisions in this area. Herein we highlight key policy options and recommendations regarding effective utilization of familial searching that minimize harm to and afford maximum protection of US citizens.

A matter of timing: identifying significant multi-dose radiotherapy improvements by numerical simulation and genetic algorithm search.

Directory of Open Access Journals (Sweden)

Simon D Angus

Full Text Available Multi-dose radiotherapy protocols (fraction dose and timing currently used in the clinic are the product of human selection based on habit, received wisdom, physician experience and intra-day patient timetabling. However, due to combinatorial considerations, the potential treatment protocol space for a given total dose or treatment length is enormous, even for relatively coarse search; well beyond the capacity of traditional in-vitro methods. In constrast, high fidelity numerical simulation of tumor development is well suited to the challenge. Building on our previous single-dose numerical simulation model of EMT6/Ro spheroids, a multi-dose irradiation response module is added and calibrated to the effective dose arising from 18 independent multi-dose treatment programs available in the experimental literature. With the developed model a constrained, non-linear, search for better performing cadidate protocols is conducted within the vicinity of two benchmarks by genetic algorithm (GA techniques. After evaluating less than 0.01% of the potential benchmark protocol space, candidate protocols were identified by the GA which conferred an average of 9.4% (max benefit 16.5% and 7.1% (13.3% improvement (reduction on tumour cell count compared to the two benchmarks, respectively. Noticing that a convergent phenomenon of the top performing protocols was their temporal synchronicity, a further series of numerical experiments was conducted with periodic time-gap protocols (10 h to 23 h, leading to the discovery that the performance of the GA search candidates could be replicated by 17-18 h periodic candidates. Further dynamic irradiation-response cell-phase analysis revealed that such periodicity cohered with latent EMT6/Ro cell-phase temporal patterning. Taken together, this study provides powerful evidence towards the hypothesis that even simple inter-fraction timing variations for a given fractional dose program may present a facile, and highly cost

A matter of timing: identifying significant multi-dose radiotherapy improvements by numerical simulation and genetic algorithm search.

Science.gov (United States)

Angus, Simon D; Piotrowska, Monika Joanna

2014-01-01

Multi-dose radiotherapy protocols (fraction dose and timing) currently used in the clinic are the product of human selection based on habit, received wisdom, physician experience and intra-day patient timetabling. However, due to combinatorial considerations, the potential treatment protocol space for a given total dose or treatment length is enormous, even for relatively coarse search; well beyond the capacity of traditional in-vitro methods. In constrast, high fidelity numerical simulation of tumor development is well suited to the challenge. Building on our previous single-dose numerical simulation model of EMT6/Ro spheroids, a multi-dose irradiation response module is added and calibrated to the effective dose arising from 18 independent multi-dose treatment programs available in the experimental literature. With the developed model a constrained, non-linear, search for better performing cadidate protocols is conducted within the vicinity of two benchmarks by genetic algorithm (GA) techniques. After evaluating less than 0.01% of the potential benchmark protocol space, candidate protocols were identified by the GA which conferred an average of 9.4% (max benefit 16.5%) and 7.1% (13.3%) improvement (reduction) on tumour cell count compared to the two benchmarks, respectively. Noticing that a convergent phenomenon of the top performing protocols was their temporal synchronicity, a further series of numerical experiments was conducted with periodic time-gap protocols (10 h to 23 h), leading to the discovery that the performance of the GA search candidates could be replicated by 17-18 h periodic candidates. Further dynamic irradiation-response cell-phase analysis revealed that such periodicity cohered with latent EMT6/Ro cell-phase temporal patterning. Taken together, this study provides powerful evidence towards the hypothesis that even simple inter-fraction timing variations for a given fractional dose program may present a facile, and highly cost-effecitive means

Solving a chemical batch scheduling problem by local search

NARCIS (Netherlands)

Brucker, P.; Hurink, Johann L.

1999-01-01

A chemical batch scheduling problem is modelled in two different ways as a discrete optimization problem. Both models are used to solve the batch scheduling problem in a two-phase tabu search procedure. The method is tested on real-world data.

Genetics and human rights. Two histories: Restoring genetic identity after forced disappearance and identity suppression in Argentina and after compulsory isolation for leprosy in Brazil

Science.gov (United States)

Penchaszadeh, Victor B.; Schuler-Faccini, Lavinia

2014-01-01

Over the past three decades, there has been an accelerated development of genetic technology, leading to its use in human genetic identification for many purposes. Additionally, it has been made explicit that identity is a fundamental human right. A number of historical circumstances have connected these developments. Personal identity is increasingly associated with the preservation and defense of human rights and is a tool to repair the violation of these rights, particularly the right to identity. In this article, we report the use of genetics to support the right to identity in two historical circumstances. First, we report the search, localization, DNA testing and genetic identification of 110 individuals who were appropriated as babies by the Argentine military dictatorship of 1976–1983 in the context of savage repression and egregious violations of human rights, including forced disappearance and suppression of identity. Second, we report on the repair of right-to-identity violations of hundreds of individuals that occurred during the process of compulsory isolation of patients with leprosy in Brazil through the Program “Reencontro”, which has led to the genetic identification of 158 pairs of individuals who previously did not have proof that they were siblings. The high value placed on genetic identification by victims of identity suppression did not counter the prevailing view that genetic factors were not more important than other factors (social, emotional, educational, cultural, spiritual) in determining the complex phenomenon of personal identity. The use of genetic identification as a tool to redress and repair human rights violations is a novel application of human genetics for the benefit of mankind. PMID:24764764

Genetics and human rights. Two histories: Restoring genetic identity after forced disappearance and identity suppression in Argentina and after compulsory isolation for leprosy in Brazil.

Science.gov (United States)

Penchaszadeh, Victor B; Schuler-Faccini, Lavinia

2014-03-01

Over the past three decades, there has been an accelerated development of genetic technology, leading to its use in human genetic identification for many purposes. Additionally, it has been made explicit that identity is a fundamental human right. A number of historical circumstances have connected these developments. Personal identity is increasingly associated with the preservation and defense of human rights and is a tool to repair the violation of these rights, particularly the right to identity. In this article, we report the use of genetics to support the right to identity in two historical circumstances. First, we report the search, localization, DNA testing and genetic identification of 110 individuals who were appropriated as babies by the Argentine military dictatorship of 1976-1983 in the context of savage repression and egregious violations of human rights, including forced disappearance and suppression of identity. Second, we report on the repair of right-to-identity violations of hundreds of individuals that occurred during the process of compulsory isolation of patients with leprosy in Brazil through the Program "Reencontro", which has led to the genetic identification of 158 pairs of individuals who previously did not have proof that they were siblings. The high value placed on genetic identification by victims of identity suppression did not counter the prevailing view that genetic factors were not more important than other factors (social, emotional, educational, cultural, spiritual) in determining the complex phenomenon of personal identity. The use of genetic identification as a tool to redress and repair human rights violations is a novel application of human genetics for the benefit of mankind.

Genetics and human rights: Two histories: restoring genetic identity after forced disappearance and identity suppression in Argentina and after compulsory isolation for leprosy in Brazil

Directory of Open Access Journals (Sweden)

Victor B. Penchaszadeh

2014-01-01

Full Text Available Over the past three decades, there has been an accelerated development of genetic technology, leading to its use in human genetic identification for many purposes. Additionally, it has been made explicit that identity is a fundamental human right. A number of historical circumstances have connected these developments. Personal identity is increasingly associated with the preservation and defense of human rights and is a tool to repair the violation of these rights, particularly the right to identity. In this article, we report the use of genetics to support the right to identity in two historical circumstances. First, we report the search, localization, DNA testing and genetic identification of 110 individuals who were appropriated as babies by the Argentine military dictatorship of 1976-1983 in the context of savage repression and egregious violations of human rights, including forced disappearance and suppression of identity. Second, we report on the repair of right-to-identity violations of hundreds of individuals that occurred during the process of compulsory isolation of patients with leprosy in Brazil through the Program "Reencontro", which has led to the genetic identification of 158 pairs of individuals who previously did not have proof that they were siblings. The high value placed on genetic identification by victims of identity suppression did not counter the prevailing view that genetic factors were not more important than other factors (social, emotional, educational, cultural, spiritual in determining the complex phenomenon of personal identity. The use of genetic identification as a tool to redress and repair human rights violations is a novel application of human genetics for the benefit of mankind.

Properties of global- and local-ancestry adjustments in genetic association tests in admixed populations.

Science.gov (United States)

Martin, Eden R; Tunc, Ilker; Liu, Zhi; Slifer, Susan H; Beecham, Ashley H; Beecham, Gary W

2018-03-01

Population substructure can lead to confounding in tests for genetic association, and failure to adjust properly can result in spurious findings. Here we address this issue of confounding by considering the impact of global ancestry (average ancestry across the genome) and local ancestry (ancestry at a specific chromosomal location) on regression parameters and relative power in ancestry-adjusted and -unadjusted models. We examine theoretical expectations under different scenarios for population substructure; applying different regression models, verifying and generalizing using simulations, and exploring the findings in real-world admixed populations. We show that admixture does not lead to confounding when the trait locus is tested directly in a single admixed population. However, if there is more complex population structure or a marker locus in linkage disequilibrium (LD) with the trait locus is tested, both global and local ancestry can be confounders. Additionally, we show the genotype parameters of adjusted and unadjusted models all provide tests for LD between the marker and trait locus, but in different contexts. The local ancestry adjusted model tests for LD in the ancestral populations, while tests using the unadjusted and the global ancestry adjusted models depend on LD in the admixed population(s), which may be enriched due to different ancestral allele frequencies. Practically, this implies that global-ancestry adjustment should be used for screening, but local-ancestry adjustment may better inform fine mapping and provide better effect estimates at trait loci. © 2017 WILEY PERIODICALS, INC.

Increased fire frequency promotes stronger spatial genetic structure and natural selection at regional and local scales in Pinus halepensis Mill.

Science.gov (United States)

Budde, Katharina B; González-Martínez, Santiago C; Navascués, Miguel; Burgarella, Concetta; Mosca, Elena; Lorenzo, Zaida; Zabal-Aguirre, Mario; Vendramin, Giovanni G; Verdú, Miguel; Pausas, Juli G; Heuertz, Myriam

2017-04-01

The recurrence of wildfires is predicted to increase due to global climate change, resulting in severe impacts on biodiversity and ecosystem functioning. Recurrent fires can drive plant adaptation and reduce genetic diversity; however, the underlying population genetic processes have not been studied in detail. In this study, the neutral and adaptive evolutionary effects of contrasting fire regimes were examined in the keystone tree species Pinus halepensis Mill. (Aleppo pine), a fire-adapted conifer. The genetic diversity, demographic history and spatial genetic structure were assessed at local (within-population) and regional scales for populations exposed to different crown fire frequencies. Eight natural P. halepensis stands were sampled in the east of the Iberian Peninsula, five of them in a region exposed to frequent crown fires (HiFi) and three of them in an adjacent region with a low frequency of crown fires (LoFi). Samples were genotyped at nine neutral simple sequence repeats (SSRs) and at 251 single nucleotide polymorphisms (SNPs) from coding regions, some of them potentially important for fire adaptation. Fire regime had no effects on genetic diversity or demographic history. Three high-differentiation outlier SNPs were identified between HiFi and LoFi stands, suggesting fire-related selection at the regional scale. At the local scale, fine-scale spatial genetic structure (SGS) was overall weak as expected for a wind-pollinated and wind-dispersed tree species. HiFi stands displayed a stronger SGS than LoFi stands at SNPs, which probably reflected the simultaneous post-fire recruitment of co-dispersed related seeds. SNPs with exceptionally strong SGS, a proxy for microenvironmental selection, were only reliably identified under the HiFi regime. An increasing fire frequency as predicted due to global change can promote increased SGS with stronger family structures and alter natural selection in P. halepensis and in plants with similar life history traits

Generation of Compliant Mechanisms using Hybrid Genetic Algorithm

Science.gov (United States)

Sharma, D.; Deb, K.

2014-10-01

Compliant mechanism is a single piece elastic structure which can deform to perform the assigned task. In this work, compliant mechanisms are evolved using a constraint based bi-objective optimization formulation which requires one user defined parameter ( η). This user defined parameter limits a gap between a desired path and an actual path traced by the compliant mechanism. The non-linear and discrete optimization problems are solved using the hybrid Genetic Algorithm (GA) wherein domain specific initialization, two-dimensional crossover operator and repairing techniques are adopted. A bit-wise local search method is used with elitist non-dominated sorting genetic algorithm to further refine the compliant mechanisms. Parallel computations are performed on the master-slave architecture to reduce the computation time. A parametric study is carried out for η value which suggests a range to evolve topologically different compliant mechanisms. The applied and boundary conditions to the compliant mechanisms are considered the variables that are evolved by the hybrid GA. The post-analysis of results unveils that the complaint mechanisms are always supported at unique location that can evolve the non-dominated solutions.

Gaussian variable neighborhood search for the file transfer scheduling problem

Directory of Open Access Journals (Sweden)

Dražić Zorica

2016-01-01

Full Text Available This paper presents new modifications of Variable Neighborhood Search approach for solving the file transfer scheduling problem. To obtain better solutions in a small neighborhood of a current solution, we implement two new local search procedures. As Gaussian Variable Neighborhood Search showed promising results when solving continuous optimization problems, its implementation in solving the discrete file transfer scheduling problem is also presented. In order to apply this continuous optimization method to solve the discrete problem, mapping of uncountable set of feasible solutions into a finite set is performed. Both local search modifications gave better results for the large size instances, as well as better average performance for medium and large size instances. One local search modification achieved significant acceleration of the algorithm. The numerical experiments showed that the results obtained by Gaussian modifications are comparable with the results obtained by standard VNS based algorithms, developed for combinatorial optimization. In some cases Gaussian modifications gave even better results. [Projekat Ministarstava nauke Republike Srbije, br. 174010

The Search for Symmetries in the Genetic Code:

Science.gov (United States)

Antoneli, Fernando; Forger, Michael; Hornos, José Eduardo M.

We give a full classification of the possible schemes for obtaining the distribution of multiplets observed in the standard genetic code by symmetry breaking in the context of finite groups, based on an extended notion of partial symmetry breaking that incorporates the intuitive idea of "freezing" first proposed by Francis Crick, which is given a precise mathematical meaning.

Approximation algorithms for a genetic diagnostics problem.

Science.gov (United States)

Kosaraju, S R; Schäffer, A A; Biesecker, L G

1998-01-01

We define and study a combinatorial problem called WEIGHTED DIAGNOSTIC COVER (WDC) that models the use of a laboratory technique called genotyping in the diagnosis of an important class of chromosomal aberrations. An optimal solution to WDC would enable us to define a genetic assay that maximizes the diagnostic power for a specified cost of laboratory work. We develop approximation algorithms for WDC by making use of the well-known problem SET COVER for which the greedy heuristic has been extensively studied. We prove worst-case performance bounds on the greedy heuristic for WDC and for another heuristic we call directional greedy. We implemented both heuristics. We also implemented a local search heuristic that takes the solutions obtained by greedy and dir-greedy and applies swaps until they are locally optimal. We report their performance on a real data set that is representative of the options that a clinical geneticist faces for the real diagnostic problem. Many open problems related to WDC remain, both of theoretical interest and practical importance.

Genetic algorithm with small population size for search feasible control parameters for parallel hybrid electric vehicles

Directory of Open Access Journals (Sweden)

Yu-Huei Cheng

2017-11-01

Full Text Available The control strategy is a major unit in hybrid electric vehicles (HEVs. In order to provide suitable control parameters for reducing fuel consumptions and engine emissions while maintaining vehicle performance requirements, the genetic algorithm (GA with small population size is applied to search for feasible control parameters in parallel HEVs. The electric assist control strategy (EACS is used as the fundamental control strategy of parallel HEVs. The dynamic performance requirements stipulated in the Partnership for a New Generation of Vehicles (PNGV is considered to maintain the vehicle performance. The known ADvanced VehIcle SimulatOR (ADVISOR is used to simulate a specific parallel HEV with urban dynamometer driving schedule (UDDS. Five population sets with size 5, 10, 15, 20, and 25 are used in the GA. The experimental results show that the GA with population size of 25 is the best for selecting feasible control parameters in parallel HEVs.

Dynamic Search and Working Memory in Social Recall

Science.gov (United States)

Hills, Thomas T.; Pachur, Thorsten

2012-01-01

What are the mechanisms underlying search in social memory (e.g., remembering the people one knows)? Do the search mechanisms involve dynamic local-to-global transitions similar to semantic search, and are these transitions governed by the general control of attention, associated with working memory span? To find out, we asked participants to…

Optimization of redundancy by using genetic algorithm for reliability of plant protection system

International Nuclear Information System (INIS)

Yoo, D. W.; Seong, S. H.; Kim, D. H.; Park, H. Y.; Gu, I. S.

2000-01-01

The design and development of a reliable protection system has been becoming a key issue in industry field because the reliability of system is considered as an important factor to perform the system's function successfully. Plant Protection System(PPS) guarantees the safety of plant by accident detection and control action against the transient conditions of plant. This paper presents the analysis of PPS reliability and the formal problem statement about optimal redundancy based on the reliability of PPS. And the optimization problem is solved by genetic algorithm. The genetic algorithm is a useful tool to solve the problems, in the case of large searching, complex gradient, existence local minimum. The effectiveness of the proposed optimization technique is proved by the target reliability of one channel of PPS, using the failure rate based on the MIL-HDBK-217

Phenylketonuria Genetic Screening Simulation

Science.gov (United States)

Erickson, Patti

2012-01-01

After agreeing to host over 200 students on a daylong genetics field trip, the author needed an easy-to-prepare genetics experiment to accompany the DNA-necklace and gel-electrophoresis activities already planned. One of the student's mothers is a pediatric physician at the local hospital, and she suggested exploring genetic-disease screening…

Heritability and genetics of lipid metabolism

DEFF Research Database (Denmark)

Fenger, Mogens

2007-01-01

In this article, the concept of heritability and genetic effect will be reviewed and our current knowledge of the genetics of lipid metabolism summarized. The concepts of polygenic conditions and epistasis are discussed at length, and an effort is made to put the biological processes in context...... in the search for genetic factors influencing the metabolic pathways. Particular physiological heterogeneity is addressed and procedures to handle this complex issue are suggested....

A search for genetic effects of atomic bomb radiation on the growth and development of the F1 generation, 1

International Nuclear Information System (INIS)

Furusho, Toshiyuki; Otake, Masanori.

1978-10-01

In a search for possible genetic effects of atomic bomb radiation on the growth and development of offspring of A-bomb survivors a survey was made in 1965 on approximately 200,000 children of all primary schools, junior high schools, and senior high schools in the cities of Hiroshima and Nagasaki. Of the collected data, those pertaining to senior high school students 15 to 17 years of age of Hiroshima City were analyzed to determine if there was any genetic effect of A-bomb radiation on stature. Comparisons were made with regard to the mean stature and variance of the offspring and the covariance and correlation between one parent or the sum for both parents and offspring for the exposed group and the nonexposed group. The observed differences included those with both positive and negative signs, but none were statistically significant nor did they demonstrate any specific tendency. A comparison was made with a similar study reported by Neel and Schull. Furthermore, estimation of the regression coefficients of the mean stature, variance, covariance, and correlation between one parent or the sum for both parents and offspring by parental radiation dose also did not show any specific tendency. Though the genetic effects of A-bomb radiation on stature could not be accurately estimated in the current series of analyses, the stature data of 6- to 14-year-old children in Hiroshima and those of 6- to 17-year-old children in Nagasaki Will soon be studied, which should permit a more comprehensive and extensive analysis and evaluation of the possible genetic effects of radiation on stature. (author)

Comparison of genetic algorithms with conjugate gradient methods

Science.gov (United States)

Bosworth, J. L.; Foo, N. Y.; Zeigler, B. P.

1972-01-01

Genetic algorithms for mathematical function optimization are modeled on search strategies employed in natural adaptation. Comparisons of genetic algorithms with conjugate gradient methods, which were made on an IBM 1800 digital computer, show that genetic algorithms display superior performance over gradient methods for functions which are poorly behaved mathematically, for multimodal functions, and for functions obscured by additive random noise. Genetic methods offer performance comparable to gradient methods for many of the standard functions.

Theory of Randomized Search Heuristics in Combinatorial Optimization

DEFF Research Database (Denmark)

The rigorous mathematical analysis of randomized search heuristics(RSHs) with respect to their expected runtime is a growing research area where many results have been obtained in recent years. This class of heuristics includes well-known approaches such as Randomized Local Search (RLS), the Metr......The rigorous mathematical analysis of randomized search heuristics(RSHs) with respect to their expected runtime is a growing research area where many results have been obtained in recent years. This class of heuristics includes well-known approaches such as Randomized Local Search (RLS...... analysis of randomized algorithms to RSHs. Mostly, the expected runtime of RSHs on selected problems is analzyed. Thereby, we understand why and when RSHs are efficient optimizers and, conversely, when they cannot be efficient. The tutorial will give an overview on the analysis of RSHs for solving...

Effect of non-local equilibrium on minimal thermal resistance porous layered systems

International Nuclear Information System (INIS)

Leblond, Genevieve; Gosselin, Louis

2008-01-01

In this paper, the cooling of a heat-generating surface by a stacking of porous media (e.g., metallic foam) through which fluid flows parallel to the surface is considered. A two-temperature model is proposed to account for non-local thermal equilibrium (non-LTE). A scale analysis is performed to determine temperatures profiles in the boundary layer regime. The hot spot temperature is minimized with respect to the three design variables of each layer: porosity, pore diameter, and material. Global cost and mass are constrained. The optimization is performed with a hybrid genetic algorithm (GA) including local search to enhance convergence and repeatability. Results demonstrate that the optimized stacks do not operate in LTE. Therefore, we show that assuming LTE might result in underestimation of the hot spot temperature, and into different final designs as well

A Sustainable City Planning Algorithm Based on TLBO and Local Search

Science.gov (United States)

Zhang, Ke; Lin, Li; Huang, Xuanxuan; Liu, Yiming; Zhang, Yonggang

2017-09-01

Nowadays, how to design a city with more sustainable features has become a center problem in the field of social development, meanwhile it has provided a broad stage for the application of artificial intelligence theories and methods. Because the design of sustainable city is essentially a constraint optimization problem, the swarm intelligence algorithm of extensive research has become a natural candidate for solving the problem. TLBO (Teaching-Learning-Based Optimization) algorithm is a new swarm intelligence algorithm. Its inspiration comes from the “teaching” and “learning” behavior of teaching class in the life. The evolution of the population is realized by simulating the “teaching” of the teacher and the student “learning” from each other, with features of less parameters, efficient, simple thinking, easy to achieve and so on. It has been successfully applied to scheduling, planning, configuration and other fields, which achieved a good effect and has been paid more and more attention by artificial intelligence researchers. Based on the classical TLBO algorithm, we propose a TLBO_LS algorithm combined with local search. We design and implement the random generation algorithm and evaluation model of urban planning problem. The experiments on the small and medium-sized random generation problem showed that our proposed algorithm has obvious advantages over DE algorithm and classical TLBO algorithm in terms of convergence speed and solution quality.

SS-Wrapper: a package of wrapper applications for similarity searches on Linux clusters

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Lefkowitz Elliot J

2004-10-01

Full Text Available Abstract Background Large-scale sequence comparison is a powerful tool for biological inference in modern molecular biology. Comparing new sequences to those in annotated databases is a useful source of functional and structural information about these sequences. Using software such as the basic local alignment search tool (BLAST or HMMPFAM to identify statistically significant matches between newly sequenced segments of genetic material and those in databases is an important task for most molecular biologists. Searching algorithms are intrinsically slow and data-intensive, especially in light of the rapid growth of biological sequence databases due to the emergence of high throughput DNA sequencing techniques. Thus, traditional bioinformatics tools are impractical on PCs and even on dedicated UNIX servers. To take advantage of larger databases and more reliable methods, high performance computation becomes necessary. Results We describe the implementation of SS-Wrapper (Similarity Search Wrapper, a package of wrapper applications that can parallelize similarity search applications on a Linux cluster. Our wrapper utilizes a query segmentation-search (QS-search approach to parallelize sequence database search applications. It takes into consideration load balancing between each node on the cluster to maximize resource usage. QS-search is designed to wrap many different search tools, such as BLAST and HMMPFAM using the same interface. This implementation does not alter the original program, so newly obtained programs and program updates should be accommodated easily. Benchmark experiments using QS-search to optimize BLAST and HMMPFAM showed that QS-search accelerated the performance of these programs almost linearly in proportion to the number of CPUs used. We have also implemented a wrapper that utilizes a database segmentation approach (DS-BLAST that provides a complementary solution for BLAST searches when the database is too large to fit into

SS-Wrapper: a package of wrapper applications for similarity searches on Linux clusters.

Science.gov (United States)

Wang, Chunlin; Lefkowitz, Elliot J

2004-10-28

Large-scale sequence comparison is a powerful tool for biological inference in modern molecular biology. Comparing new sequences to those in annotated databases is a useful source of functional and structural information about these sequences. Using software such as the basic local alignment search tool (BLAST) or HMMPFAM to identify statistically significant matches between newly sequenced segments of genetic material and those in databases is an important task for most molecular biologists. Searching algorithms are intrinsically slow and data-intensive, especially in light of the rapid growth of biological sequence databases due to the emergence of high throughput DNA sequencing techniques. Thus, traditional bioinformatics tools are impractical on PCs and even on dedicated UNIX servers. To take advantage of larger databases and more reliable methods, high performance computation becomes necessary. We describe the implementation of SS-Wrapper (Similarity Search Wrapper), a package of wrapper applications that can parallelize similarity search applications on a Linux cluster. Our wrapper utilizes a query segmentation-search (QS-search) approach to parallelize sequence database search applications. It takes into consideration load balancing between each node on the cluster to maximize resource usage. QS-search is designed to wrap many different search tools, such as BLAST and HMMPFAM using the same interface. This implementation does not alter the original program, so newly obtained programs and program updates should be accommodated easily. Benchmark experiments using QS-search to optimize BLAST and HMMPFAM showed that QS-search accelerated the performance of these programs almost linearly in proportion to the number of CPUs used. We have also implemented a wrapper that utilizes a database segmentation approach (DS-BLAST) that provides a complementary solution for BLAST searches when the database is too large to fit into the memory of a single node. Used together

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.

Recent advances in understanding the genetic resources of sheep breeds locally-adapted to the UK uplands : opportunities they offer for sustainable productivity.

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Dianna eBowles

2015-02-01

Full Text Available Locally adapted breeds of livestock are of considerable interest since they represent potential reservoirs of adaptive fitness traits that may contribute to the future of sustainable productivity in a changing climate.Recent research, involving three hill sheep breeds geographically concentrated in the northern uplands of the UK has revealed the extent of their genetic diversity from one another and from other breeds. Results from the use of SNPs, microsatellites and retrovirus insertions are reviewed in the context of related studies on sheep breeds world-wide to highlight opportunities offered by the genetic resources of locally adapted hill breeds. One opportunity concerns reduced susceptibility to Maedi-Visna, a lentivirus with massive impacts on sheep health and productivity globally. In contrast to many mainstream breeds used in farming, each of the hill breeds analysed are likely to be far less susceptible to the disease threat. A different opportunity, relating specifically to the Herdwick breed, is the extent to which the genome of the breed has retained primitive features, no longer present in other mainland breeds of sheep in the UK and offering a new route for discovering unique genetic traits of use to agriculture.

Instrument design and optimization using genetic algorithms

International Nuclear Information System (INIS)

Hoelzel, Robert; Bentley, Phillip M.; Fouquet, Peter

2006-01-01

This article describes the design of highly complex physical instruments by using a canonical genetic algorithm (GA). The procedure can be applied to all instrument designs where performance goals can be quantified. It is particularly suited to the optimization of instrument design where local optima in the performance figure of merit are prevalent. Here, a GA is used to evolve the design of the neutron spin-echo spectrometer WASP which is presently being constructed at the Institut Laue-Langevin, Grenoble, France. A comparison is made between this artificial intelligence approach and the traditional manual design methods. We demonstrate that the search of parameter space is more efficient when applying the genetic algorithm, and the GA produces a significantly better instrument design. Furthermore, it is found that the GA increases flexibility, by facilitating the reoptimization of the design after changes in boundary conditions during the design phase. The GA also allows the exploration of 'nonstandard' magnet coil geometries. We conclude that this technique constitutes a powerful complementary tool for the design and optimization of complex scientific apparatus, without replacing the careful thought processes employed in traditional design methods

Instrument design and optimization using genetic algorithms

Science.gov (United States)

Hölzel, Robert; Bentley, Phillip M.; Fouquet, Peter

2006-10-01

This article describes the design of highly complex physical instruments by using a canonical genetic algorithm (GA). The procedure can be applied to all instrument designs where performance goals can be quantified. It is particularly suited to the optimization of instrument design where local optima in the performance figure of merit are prevalent. Here, a GA is used to evolve the design of the neutron spin-echo spectrometer WASP which is presently being constructed at the Institut Laue-Langevin, Grenoble, France. A comparison is made between this artificial intelligence approach and the traditional manual design methods. We demonstrate that the search of parameter space is more efficient when applying the genetic algorithm, and the GA produces a significantly better instrument design. Furthermore, it is found that the GA increases flexibility, by facilitating the reoptimization of the design after changes in boundary conditions during the design phase. The GA also allows the exploration of "nonstandard" magnet coil geometries. We conclude that this technique constitutes a powerful complementary tool for the design and optimization of complex scientific apparatus, without replacing the careful thought processes employed in traditional design methods.

Optimal Point-to-Point Trajectory Tracking of Redundant Manipulators using Generalized Pattern Search

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Thi Rein Myo

2008-11-01

Full Text Available Optimal point-to-point trajectory planning for planar redundant manipulator is considered in this study. The main objective is to minimize the sum of the position error of the end-effector at each intermediate point along the trajectory so that the end-effector can track the prescribed trajectory accurately. An algorithm combining Genetic Algorithm and Pattern Search as a Generalized Pattern Search GPS is introduced to design the optimal trajectory. To verify the proposed algorithm, simulations for a 3-D-O-F planar manipulator with different end-effector trajectories have been carried out. A comparison between the Genetic Algorithm and the Generalized Pattern Search shows that The GPS gives excellent tracking performance.

A Practical, Robust and Fast Method for Location Localization in Range-Based Systems.

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Huang, Shiping; Wu, Zhifeng; Misra, Anil

2017-12-11

Location localization technology is used in a number of industrial and civil applications. Real time location localization accuracy is highly dependent on the quality of the distance measurements and efficiency of solving the localization equations. In this paper, we provide a novel approach to solve the nonlinear localization equations efficiently and simultaneously eliminate the bad measurement data in range-based systems. A geometric intersection model was developed to narrow the target search area, where Newton's Method and the Direct Search Method are used to search for the unknown position. Not only does the geometric intersection model offer a small bounded search domain for Newton's Method and the Direct Search Method, but also it can self-correct bad measurement data. The Direct Search Method is useful for the coarse localization or small target search domain, while the Newton's Method can be used for accurate localization. For accurate localization, by utilizing the proposed Modified Newton's Method (MNM), challenges of avoiding the local extrema, singularities, and initial value choice are addressed. The applicability and robustness of the developed method has been demonstrated by experiments with an indoor system.

Genetic architecture of the Delis-Kaplan Executive Function System Trail Making Test: evidence for distinct genetic influences on executive function.

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Vasilopoulos, Terrie; Franz, Carol E; Panizzon, Matthew S; Xian, Hong; Grant, Michael D; Lyons, Michael J; Toomey, Rosemary; Jacobson, Kristen C; Kremen, William S

2012-03-01

To examine how genes and environments contribute to relationships among Trail Making Test (TMT) conditions and the extent to which these conditions have unique genetic and environmental influences. Participants included 1,237 middle-aged male twins from the Vietnam Era Twin Study of Aging. The Delis-Kaplan Executive Function System TMT included visual searching, number and letter sequencing, and set-shifting components. Phenotypic correlations among TMT conditions ranged from 0.29 to 0.60, and genes accounted for the majority (58-84%) of each correlation. Overall heritability ranged from 0.34 to 0.62 across conditions. Phenotypic factor analysis suggested a single factor. In contrast, genetic models revealed a single common genetic factor but also unique genetic influences separate from the common factor. Genetic variance (i.e., heritability) of number and letter sequencing was completely explained by the common genetic factor while unique genetic influences separate from the common factor accounted for 57% and 21% of the heritabilities of visual search and set shifting, respectively. After accounting for general cognitive ability, unique genetic influences accounted for 64% and 31% of those heritabilities. A common genetic factor, most likely representing a combination of speed and sequencing, accounted for most of the correlation among TMT 1-4. Distinct genetic factors, however, accounted for a portion of variance in visual scanning and set shifting. Thus, although traditional phenotypic shared variance analysis techniques suggest only one general factor underlying different neuropsychological functions in nonpatient populations, examining the genetic underpinnings of cognitive processes with twin analysis can uncover more complex etiological processes.

Genetic susceptibility of periodontitis

NARCIS (Netherlands)

Laine, M.L.; Crielaard, W.; Loos, B.G.

2012-01-01

In this systematic review, we explore and summarize the peer-reviewed literature on putative genetic risk factors for susceptibility to aggressive and chronic periodontitis. A comprehensive literature search on the PubMed database was performed using the keywords ‘periodontitis’ or ‘periodontal

Genetic modification of neurons to express bevacizumab for local anti-angiogenesis treatment of glioblastoma.

Science.gov (United States)

Hicks, Martin J; Funato, Kosuke; Wang, Lan; Aronowitz, Eric; Dyke, Jonathan P; Ballon, Douglas J; Havlicek, David F; Frenk, Esther Z; De, Bishnu P; Chiuchiolo, Maria J; Sondhi, Dolan; Hackett, Neil R; Kaminsky, Stephen M; Tabar, Viviane; Crystal, Ronald G

2015-01-01

The median survival of glioblastoma multiforme (GBM) is approximately 1 year. Following surgical removal, systemic therapies are limited by the blood-brain barrier. To circumvent this, we developed a method to modify neurons with the genetic sequence for therapeutic monoclonal antibodies using adeno-associated virus (AAV) gene transfer vectors, directing persistent, local expression in the tumor milieu. The human U87MG GBM cell line or patient-derived early passage GBM cells were administered to the striatum of NOD/SCID immunodeficient mice. AAVrh.10BevMab, an AAVrh.10-based vector coding for bevacizumab (Avastin), an anti-human vascular endothelial growth factor (VEGF) monoclonal antibody, was delivered to the area of the GBM xenograft. Localized expression of bevacizumab was demonstrated by quantitative PCR, ELISA and western blotting. Immunohistochemistry showed that bevacizumab was expressed in neurons. Concurrent administration of AAVrh.10BevMab with the U87MG tumor reduced tumor blood vessel density and tumor volume, and increased survival. Administration of AAVrh.10BevMab 1 week after U87MG xenograft reduced growth and increased survival. Studies with patient-derived early passage GBM primary cells showed a reduction in primary tumor burden with an increased survival. These data support the strategy of AAV-mediated central nervous system gene therapy to treat GBM, overcoming the blood-brain barrier through local, persistent delivery of an anti-angiogenesis monoclonal antibody.

Dynamic Demand-Capacity Balancing for Air Traffic Management Using Constraint-Based Local Search: First Results

Directory of Open Access Journals (Sweden)

Farshid Hassani Bijarbooneh

2009-10-01

Full Text Available Using constraint-based local search, we effectively model and efficiently solve the problem of balancing the traffic demands on portions of the European airspace while ensuring that their capacity constraints are satisfied. The traffic demand of a portion of airspace is the hourly number of flights planned to enter it, and its capacity is the upper bound on this number under which air-traffic controllers can work. Currently, the only form of demand-capacity balancing we allow is ground holding, that is the changing of the take-off times of not yet airborne flights. Experiments with projected European flight plans of the year 2030 show that already this first form of demand-capacity balancing is feasible without incurring too much total delay and that it can lead to a significantly better demand-capacity balance.

Information-Fusion Methods Based Simultaneous Localization and Mapping for Robot Adapting to Search and Rescue Postdisaster Environments

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Hongling Wang

2018-01-01

Full Text Available The first application of utilizing unique information-fusion SLAM (IF-SLAM methods is developed for mobile robots performing simultaneous localization and mapping (SLAM adapting to search and rescue (SAR environments in this paper. Several fusion approaches, parallel measurements filtering, exploration trajectories fusing, and combination sensors’ measurements and mobile robots’ trajectories, are proposed. The novel integration particle filter (IPF and optimal improved EKF (IEKF algorithms are derived for information-fusion systems to perform SLAM task in SAR scenarios. The information-fusion architecture consists of multirobots and multisensors (MAM; multiple robots mount on-board laser range finder (LRF sensors, localization sonars, gyro odometry, Kinect-sensor, RGB-D camera, and other proprioceptive sensors. This information-fusion SLAM (IF-SLAM is compared with conventional methods, which indicates that fusion trajectory is more consistent with estimated trajectories and real observation trajectories. The simulations and experiments of SLAM process are conducted in both cluttered indoor environment and outdoor collapsed unstructured scenario, and experimental results validate the effectiveness of the proposed information-fusion methods in improving SLAM performances adapting to SAR scenarios.

Genetics Home Reference: Williams syndrome

Science.gov (United States)

... do well on tasks that involve spoken language, music, and learning by repetition (rote memorization). Affected individuals ... Resources (5 links) Disease InfoSearch: Williams syndrome Genetic Science Learning Center, University of Utah MalaCards: williams-beuren ...

A hybrid guided neighborhood search for the disjunctively constrained knapsack problem

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Mhand Hifi

2015-12-01

Full Text Available In this paper, we investigate the use of a hybrid guided neighborhood search for solving the disjunctively constrained knapsack problem. The studied problem may be viewed as a combination of two NP-hard combinatorial optimization problems: the weighted-independent set and the classical binary knapsack. The proposed algorithm is a hybrid approach that combines both deterministic and random local searches. The deterministic local search is based on a descent method, where both building and exploring procedures are alternatively used for improving the solution at hand. In order to escape from a local optima, a random local search strategy is introduced which is based on a modified ant colony optimization system. During the search process, the ant colony optimization system tries to diversify and to enhance the solutions using some informations collected from the previous iterations. Finally, the proposed algorithm is computationally analyzed on a set of benchmark instances available in the literature. The provided results are compared to those realized by both the Cplex solver and a recent algorithm of the literature. The computational part shows that the obtained results improve most existing solution values.

A search for genetic effects of atomic bomb radiation on the growth and development of the F1 generation, 3

International Nuclear Information System (INIS)

Furusho, Toshiyuki; Otake, Masanori.

1980-02-01

In a search for possible genetic effects of atomic bomb radiation on the stature of the offspring of A-bomb survivors a comparative study has been made of junior high school students 12 to 14 years of age born in Hiroshima to exposed and nonexposed parents. The mean stature and variance of the offspring and the covariance and correlation between one parent or the sum for both parents and their children were compared. The observed differences were both positive and negative in sign, and only a few were statistically significant. No clear tendency was demonstrated. When one parent was exposed, seven variance values of the offspring were statistically significant and six were positive in sign. Regression analyses of the mean stature and variance of the offspring, or the covariance, and correlation between one parent or the sum for both parents and their offspring by parental radiation dose revealed no clear effects of exposure. Only a very few of the regression coefficients were significantly different from zero. While genetic effects of A-bomb radiation on the stature of the children of exposed parents cannot be ruled out by this study, neither can such effects be unequivocally demonstrated. (author)

Genetics Home Reference: congenital hyperinsulinism

Science.gov (United States)

... Topic: Hypoglycemia Health Topic: Metabolic Disorders Genetic and Rare Diseases Information Center (1 link) Congenital hyperinsulinism Educational Resources (7 links) Boston Children's Hospital: Hypoglycemia and Low Blood Sugar in Children Cook Children's Hospital (PDF) Disease InfoSearch: ...

Searching for preeclampsia genes : the current position

NARCIS (Netherlands)

Lachmeijer, AMA; Dekker, GA; Pals, G; Aarnoudse, JG; ten Kate, LP; Arngrimsson, R

2002-01-01

Although there is substantial evidence that preeclampsia has a genetic background, the complexity of the processes involved and the fact that preeclampsia is a maternal-fetal phenomenon does not make the search for the molecular basis of preeclampsia genes easy. It is possible that the single

Poa secunda local collections and commercial releases: A genotypic evaluation.

Directory of Open Access Journals (Sweden)

Alanna N Shaw

Full Text Available The genetics of native plants influence the success of ecological restoration, yet genetic variability of local seed collections and commercial seed releases remains unclear for most taxa. Poa secunda, a common native grass species in Intermountain West grasslands and a frequent component of restoration seed mixes, is one such species. Here, we evaluate the genetic variation of local Poa secunda collections in the context of wild populations and commercial seed releases. We evaluated AFLP markers for seven Poa secunda collections made over a 4000-hectare area and four commercial releases (High Plains, MT-1, Opportunity, and Sherman. We compare the genetic distance and distribution of genetic variation within and between local collections and commercial releases. The extent and patterns of genetic variation in our local collections indicate subtle site differences with most variation occurring within rather than between collections. Identical genetic matches were usually, but not always, found within 5 m2 collection sites. Our results suggest that the genetic variation in two Poa secunda releases (High Plains and MT-1 is similar to our local collections. Our results affirm that guidelines for Poa secunda seed collection should follow recommendations for selfing species, by collecting from many sites over large individual sites.

Application of Genetic Algorithms in Seismic Tomography

Science.gov (United States)

Soupios, Pantelis; Akca, Irfan; Mpogiatzis, Petros; Basokur, Ahmet; Papazachos, Constantinos

2010-05-01

application of hybrid genetic algorithms in seismic tomography is examined and the efficiency of least squares and genetic methods as representative of the local and global optimization, respectively, is presented and evaluated. The robustness of both optimization methods has been tested and compared for the same source-receiver geometry and characteristics of the model structure (anomalies, etc.). A set of seismic refraction synthetic (noise free) data was used for modeling. Specifically, cross-well, down-hole and typical refraction studies using 24 geophones and 5 shoots were used to confirm the applicability of the genetic algorithms in seismic tomography. To solve the forward modeling and estimate the traveltimes, the revisited ray bending method was used supplemented by an approximate computation of the first Fresnel volume. The root mean square (rms) error as the misfit function was used and calculated for the entire random velocity model for each generation. After the end of each generation and based on the misfit of the individuals (velocity models), the selection, crossover and mutation (typical process steps of genetic algorithms) were selected continuing the evolution theory and coding the new generation. To optimize the computation time, since the whole procedure is quite time consuming, the Matlab Distributed Computing Environment (MDCE) was used in a multicore engine. During the tests, we noticed that the fast convergence that the algorithm initially exhibits (first 5 generations) is followed by progressively slower improvements of the reconstructed velocity models. Thus, to improve the final tomographic models, a hybrid genetic algorithm (GA) approach was adopted by combining the GAs with a local optimization method after several generations, on the basis of the convergence of the resulting models. This approach is shown to be efficient, as it directs the solution search towards a model region close to the global minimum solution.

Optimal planning approaches with multiple impulses for rendezvous based on hybrid genetic algorithm and control method

Directory of Open Access Journals (Sweden)

JingRui Zhang

2015-03-01

Full Text Available In this article, we focus on safe and effective completion of a rendezvous and docking task by looking at planning approaches and control with fuel-optimal rendezvous for a target spacecraft running on a near-circular reference orbit. A variety of existent practical path constraints are considered, including the constraints of field of view, impulses, and passive safety. A rendezvous approach is calculated by using a hybrid genetic algorithm with those constraints. Furthermore, a control method of trajectory tracking is adopted to overcome the external disturbances. Based on Clohessy–Wiltshire equations, we first construct the mathematical model of optimal planning approaches of multiple impulses with path constraints. Second, we introduce the principle of hybrid genetic algorithm with both stronger global searching ability and local searching ability. We additionally explain the application of this algorithm in the problem of trajectory planning. Then, we give three-impulse simulation examples to acquire an optimal rendezvous trajectory with the path constraints presented in this article. The effectiveness and applicability of the tracking control method are verified with the optimal trajectory above as control objective through the numerical simulation.

Global OpenSearch

Science.gov (United States)

Newman, D. J.; Mitchell, A. E.

2015-12-01

At AGU 2014, NASA EOSDIS demonstrated a case-study of an OpenSearch framework for Earth science data discovery. That framework leverages the IDN and CWIC OpenSearch API implementations to provide seamless discovery of data through the 'two-step' discovery process as outlined by the Federation for Earth Sciences (ESIP) OpenSearch Best Practices. But how would an Earth Scientist leverage this framework and what are the benefits? Using a client that understands the OpenSearch specification and, for further clarity, the various best practices and extensions, a scientist can discovery a plethora of data not normally accessible either by traditional methods (NASA Earth Data Search, Reverb, etc) or direct methods (going to the source of the data) We will demonstrate, via the CWICSmart web client, how an earth scientist can access regional data on a regional phenomena in a uniform and aggregated manner. We will demonstrate how an earth scientist can 'globalize' their discovery. You want to find local data on 'sea surface temperature of the Indian Ocean'? We can help you with that. 'European meteorological data'? Yes. 'Brazilian rainforest satellite imagery'? That too. CWIC allows you to get earth science data in a uniform fashion from a large number of disparate, world-wide agencies. This is what we mean by Global OpenSearch.

Environmental and Genetic Factors Regulating Localization of the Plant Plasma Membrane H+-ATPase1[OPEN

Science.gov (United States)

Tan, Li Xuan; Bushey, Daniel B.; Swanson, Sarah J.

2018-01-01

A P-type H+-ATPase is the primary transporter that converts ATP to electrochemical energy at the plasma membrane of higher plants. Its product, the proton-motive force, is composed of an electrical potential and a pH gradient. Many studies have demonstrated that this proton-motive force not only drives the secondary transporters required for nutrient uptake, but also plays a direct role in regulating cell expansion. Here, we have generated a transgenic Arabidopsis (Arabidopsis thaliana) plant expressing H+-ATPase isoform 2 (AHA2) that is translationally fused with a fluorescent protein and examined its cellular localization by live-cell microscopy. Using a 3D imaging approach with seedlings grown for various times under a variety of light intensities, we demonstrate that AHA2 localization at the plasma membrane of root cells requires light. In dim light conditions, AHA2 is found in intracellular compartments, in addition to the plasma membrane. This localization profile was age-dependent and specific to cell types found in the transition zone located between the meristem and elongation zones. The accumulation of AHA2 in intracellular compartments is consistent with reduced H+ secretion near the transition zone and the suppression of root growth. By examining AHA2 localization in a knockout mutant of a receptor protein kinase, FERONIA, we found that the intracellular accumulation of AHA2 in the transition zone is dependent on a functional FERONIA-dependent inhibitory response in root elongation. Overall, this study provides a molecular underpinning for understanding the genetic, environmental, and developmental factors influencing root growth via localization of the plasma membrane H+-ATPase. PMID:29042459

An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm.

Science.gov (United States)

Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

2015-01-01

Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.

An Adaptive Image Enhancement Technique by Combining Cuckoo Search and Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Zhiwei Ye

2015-01-01

Full Text Available Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.

Where genetic algorithms excel.

Science.gov (United States)

Baum, E B; Boneh, D; Garrett, C

2001-01-01

We analyze the performance of a genetic algorithm (GA) we call Culling, and a variety of other algorithms, on a problem we refer to as the Additive Search Problem (ASP). We show that the problem of learning the Ising perceptron is reducible to a noisy version of ASP. Noisy ASP is the first problem we are aware of where a genetic-type algorithm bests all known competitors. We generalize ASP to k-ASP to study whether GAs will achieve "implicit parallelism" in a problem with many more schemata. GAs fail to achieve this implicit parallelism, but we describe an algorithm we call Explicitly Parallel Search that succeeds. We also compute the optimal culling point for selective breeding, which turns out to be independent of the fitness function or the population distribution. We also analyze a mean field theoretic algorithm performing similarly to Culling on many problems. These results provide insight into when and how GAs can beat competing methods.

Genetics of allergy and bronchial hyperresponsiveness

NARCIS (Netherlands)

Howard, TD; Wiesch, DG; Koppelman, GH; Postma, DS; Meyers, DA; Bleecker, ER

Allergy and asthma are closely related complex diseases caused by a combination of both genetic and environmental influences. Two common genetic approaches, candidate gene studies and genome-wide screens, have been used to localize and evaluate potential genetic factors that confer susceptibility or

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...

Scientific discovery using genetic programming

DEFF Research Database (Denmark)

Keijzer, Maarten

2001-01-01

programming paradigm. The induction of mathematical expressions based on data is called symbolic regression. In this work, genetic programming is extended to not just fit the data i.e., get the numbers right, but also to get the dimensions right. For this units of measurement are used. The main contribution......Genetic Programming is capable of automatically inducing symbolic computer programs on the basis of a set of examples or their performance in a simulation. Mathematical expressions are a well-defined subset of symbolic computer programs and are also suitable for optimization using the genetic...... in this work can be summarized as: The symbolic expressions produced by genetic programming can be made suitable for analysis and interpretation by using units of measurements to guide or restrict the search. To achieve this, the following has been accomplished: A standard genetic programming system...

PLAST: parallel local alignment search tool for database comparison

Directory of Open Access Journals (Sweden)

Lavenier Dominique

2009-10-01

Full Text Available Abstract Background Sequence similarity searching is an important and challenging task in molecular biology and next-generation sequencing should further strengthen the need for faster algorithms to process such vast amounts of data. At the same time, the internal architecture of current microprocessors is tending towards more parallelism, leading to the use of chips with two, four and more cores integrated on the same die. The main purpose of this work was to design an effective algorithm to fit with the parallel capabilities of modern microprocessors. Results A parallel algorithm for comparing large genomic banks and targeting middle-range computers has been developed and implemented in PLAST software. The algorithm exploits two key parallel features of existing and future microprocessors: the SIMD programming model (SSE instruction set and the multithreading concept (multicore. Compared to multithreaded BLAST software, tests performed on an 8-processor server have shown speedup ranging from 3 to 6 with a similar level of accuracy. Conclusion A parallel algorithmic approach driven by the knowledge of the internal microprocessor architecture allows significant speedup to be obtained while preserving standard sensitivity for similarity search problems.

Local ancestry transitions modify snp-trait associations.

Science.gov (United States)

Fish, Alexandra E; Crawford, Dana C; Capra, John A; Bush, William S

2018-01-01

Genomic maps of local ancestry identify ancestry transitions - points on a chromosome where recent recombination events in admixed individuals have joined two different ancestral haplotypes. These events bring together alleles that evolved within separate continential populations, providing a unique opportunity to evaluate the joint effect of these alleles on health outcomes. In this work, we evaluate the impact of genetic variants in the context of nearby local ancestry transitions within a sample of nearly 10,000 adults of African ancestry with traits derived from electronic health records. Genetic data was located using the Metabochip, and used to derive local ancestry. We develop a model that captures the effect of both single variants and local ancestry, and use it to identify examples where local ancestry transitions significantly interact with nearby variants to influence metabolic traits. In our most compelling example, we find that the minor allele of rs16890640 occuring on a European background with a downstream local ancestry transition to African ancestry results in significantly lower mean corpuscular hemoglobin and volume. This finding represents a new way of discovering genetic interactions, and is supported by molecular data that suggest changes to local ancestry may impact local chromatin looping.

Balancing Inverted Pendulum by Angle Sensing Using Fuzzy Logic Supervised PID Controller Optimized by Genetic Algorithm

Directory of Open Access Journals (Sweden)

Ashutosh K. AGARWAL

2011-10-01

Full Text Available Genetic algorithms are robust search techniques based on the principles of evolution. A genetic algorithm maintains a population of encoded solutions and guides the population towards the optimum solution. This important property of genetic algorithm is used in this paper to stabilize the Inverted pendulum system. This paper highlights the application and stability of inverted pendulum using PID controller with fuzzy logic genetic algorithm supervisor . There are a large number of well established search techniques in use within the information technology industry. We propose a method to control inverted pendulum steady state error and overshoot using genetic algorithm technique.

Study on Multi-stage Logistics System Design Problem with Inventory Considering Demand Change by Hybrid Genetic Algorithm

Science.gov (United States)

Inoue, Hisaki; Gen, Mitsuo

The logistics model used in this study is 3-stage model employed by an automobile company, which aims to solve traffic problems at a total minimum cost. Recently, research on the metaheuristics method has advanced as an approximate means for solving optimization problems like this model. These problems can be solved using various methods such as the genetic algorithm (GA), simulated annealing, and tabu search. GA is superior in robustness and adjustability toward a change in the structure of these problems. However, GA has a disadvantage in that it has a slightly inefficient search performance because it carries out a multi-point search. A hybrid GA that combines another method is attracting considerable attention since it can compensate for a fault to a partial solution that early convergence gives a bad influence on a result. In this study, we propose a novel hybrid random key-based GA(h-rkGA) that combines local search and parameter tuning of crossover rate and mutation rate; h-rkGA is an improved version of the random key-based GA (rk-GA). We attempted comparative experiments with spanning tree-based GA, priority based GA and random key-based GA. Further, we attempted comparative experiments with “h-GA by only local search” and “h-GA by only parameter tuning”. We reported the effectiveness of the proposed method on the basis of the results of these experiments.

Mapping the regional influence of genetics on brain structure variability--a tensor-based morphometry study.

Science.gov (United States)

Brun, Caroline C; Leporé, Natasha; Pennec, Xavier; Lee, Agatha D; Barysheva, Marina; Madsen, Sarah K; Avedissian, Christina; Chou, Yi-Yu; de Zubicaray, Greig I; McMahon, Katie L; Wright, Margaret J; Toga, Arthur W; Thompson, Paul M

2009-10-15

Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8+/-1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.

Adiabatic quantum search algorithm for structured problems

International Nuclear Information System (INIS)

Roland, Jeremie; Cerf, Nicolas J.

2003-01-01

The study of quantum computation has been motivated by the hope of finding efficient quantum algorithms for solving classically hard problems. In this context, quantum algorithms by local adiabatic evolution have been shown to solve an unstructured search problem with a quadratic speedup over a classical search, just as Grover's algorithm. In this paper, we study how the structure of the search problem may be exploited to further improve the efficiency of these quantum adiabatic algorithms. We show that by nesting a partial search over a reduced set of variables into a global search, it is possible to devise quantum adiabatic algorithms with a complexity that, although still exponential, grows with a reduced order in the problem size

Dark matter searches at the Canfranc tunnel

International Nuclear Information System (INIS)

Sarsa, M.L.; Avignone, F.T.; Brodzinski, R.L.; Cerezo, E.; Collar, J.I.; Garcia, E.; Reeves, J.H.; Miley, H.S.; Morales, A.; Morales, J.; Nunez-Lagos, R.; Ortiz de Solorzano, A.; Puimedon, J.; Saenz, C.; Salinas, A.; Villar, J.A.

1994-01-01

Results of an on-going search for particle dark matter with a germanium detector at the Canfranc tunnel are reported. Contour limits for cross-sections, masses and local halo densities of particles interacting through spin-independent interactions are presented. Preliminary results and prospects of a search for timing modulation of the signal are also reported. ((orig.))

Characterization of local goat breeds using RAP-DNA markers

Science.gov (United States)

Al-Barzinji, Yousif M. S.; Hamad, Aram O.

2017-09-01

The present study was conducted on different colors of local goat breeds. A number of 216 does were sampled from the seven groups. Genomic DNA was extracted from the blood samples. From the twenty used RAPD primers 12 of them were amplified, and presence of bands. The total fragment number of 12 primers over all the goat breed samples was 485 fragments. Out of the 485 fragments, 90 of them were Polymorphic fragments numbers (PFN). From all bands obtained, 20 of them possessed unique bands. The highest unique band was found in locus RAP 6 which has 4 unique bands, three of them in the Maraz Brown and one in the local Koor. Nei's gene diversity and Shanon's information index in this study were averaged 0.38 and 0.60, respectively. The genetic distance among several goat breeds ranged from 9.11 to 43.33%. The highest genetic distance 43.33% recorded between Maraz goat and other goat breeds and between local Koor and other goat (except Maraz goats) breeds (37.79%). However, the lowest genetic distance recorded between local white and Pnok. The distance between (local Black and Pnok) and (local Black and local white) was 22.75%. In conclusions, the high distance among these goat breeds, polymorphism and high numbers of unique bands found in present study indicates that these goat breeds have the required amount of genetic variation to made genetic improvement. This study helps us to clarify the image of the genetic diversity of the local goat breeds and the breeders can used it for mating system when need to make the crossing among these goat breeds.

The search for viable local government system in Nigeria: an ...

African Journals Online (AJOL)

The history of the Nigerian local government system has been one long episode of trails and errors aimed at achieving viable local government institution without much success. Local government in the country began its long series of reforms from the colonial period when the colonial government attempted to ...

Foraging in Semantic Fields: How We Search Through Memory.

Science.gov (United States)

Hills, Thomas T; Todd, Peter M; Jones, Michael N

2015-07-01

When searching for concepts in memory--as in the verbal fluency task of naming all the animals one can think of--people appear to explore internal mental representations in much the same way that animals forage in physical space: searching locally within patches of information before transitioning globally between patches. However, the definition of the patches being searched in mental space is not well specified. Do we search by activating explicit predefined categories (e.g., pets) and recall items from within that category (categorical search), or do we activate and recall a connected sequence of individual items without using categorical information, with each item recalled leading to the retrieval of an associated item in a stream (associative search), or both? Using semantic representations in a search of associative memory framework and data from the animal fluency task, we tested competing hypotheses based on associative and categorical search models. Associative, but not categorical, patch transitions took longer to make than position-matched productions, suggesting that categorical transitions were not true transitions. There was also clear evidence of associative search even within categorical patch boundaries. Furthermore, most individuals' behavior was best explained by an associative search model without the addition of categorical information. Thus, our results support a search process that does not use categorical information, but for which patch boundaries shift with each recall and local search is well described by a random walk in semantic space, with switches to new regions of the semantic space when the current region is depleted. Copyright © 2015 Cognitive Science Society, Inc.

Genetic aspects of pathological gambling: a complex disorder with shared genetic vulnerabilities.

Science.gov (United States)

Lobo, Daniela S S; Kennedy, James L

2009-09-01

To summarize and discuss findings from genetic studies conducted on pathological gambling (PG). Searches were conducted on PubMed and PsychInfo databases using the keywords: 'gambling and genes', 'gambling and family' and 'gambling and genetics', yielding 18 original research articles investigating the genetics of PG. Twin studies using the Vietnam Era Twin Registry have found that: (i) the heritability of PG is estimated to be 50-60%; (ii) PG and subclinical PG are a continuum of the same disorder; (iii) PG shares genetic vulnerability factors with antisocial behaviours, alcohol dependence and major depressive disorder; (iv) genetic factors underlie the association between exposure to traumatic life-events and PG. Molecular genetic investigations on PG are at an early stage and published studies have reported associations with genes involved in the brain's reward and impulse control systems. Despite the paucity of studies in this area, published studies have provided considerable evidence of the influence of genetic factors on PG and its complex interaction with other psychiatric disorders and environmental factors. The next step would be to investigate the association and interaction of these variables in larger molecular genetic studies with subphenotypes that underlie PG. Results from family and genetic investigations corroborate further the importance of understanding the biological underpinnings of PG in the development of more specific treatment and prevention strategies.

Application of Neural Networks to Higgs Boson Search

Czech Academy of Sciences Publication Activity Database

Hakl, František; Hlaváček, M.; Kalous, R.

2003-01-01

Roč. 502, - (2003), s. 489-491 ISSN 0168-9002 R&D Projects: GA MPO RP-4210/69/97 Institutional research plan: AV0Z1030915 Keywords : neural network s * Higgs search * genetic optimization Subject RIV: BA - General Mathematics Impact factor: 1.166, year: 2003

Optimum energy re-establishment in distribution systems: a comparison between the search performance using fuzzy heuristics and genetic algorithms; Restabelecimento otimo de energia em sistemas de distribuicao: uma comparacao entre o desempenho de busca com heuristica fuzzy e algoritmos geneticos

Energy Technology Data Exchange (ETDEWEB)

Delbem, Alexandre C.B.; Bretas, Newton G. [Sao Paulo Univ., Sao Carlos, SP (Brazil). Dept. de Engenharia Eletrica; Carvalho, Andre C.P.L.F. [Sao Paulo Univ., Sao Carlos, SP (Brazil). Dept. de Ciencias de Computacao e Estatistica

1996-11-01

A search approach using fuzzy heuristics and a neural network parameter was developed for service restoration of a distribution system. The goal was to restore energy for an un-faulted zone after a fault had been identified and isolated. The restoration plan must be carried out in a very short period. However, the combinatorial feature of the problem constrained the application of automatic energy restoration planners. To overcome this problem, an heuristic search approach using fuzzy heuristics was proposed. As a result, a genetic algorithm approach was developed to achieve the optimal energy restoration plan. The effectiveness of these approaches were tested in a simplified distribution system based on the complex distribution system of Sao Carlos city, Sao Paulo State - southeast Brazil. It was noticed that the genetic algorithm provided better performance than the fuzzy heuristic search in this problem. 11 refs., 10 figs.

A Genetic Algorithms Based Approach for Identification of Escherichia coli Fed-batch Fermentation

Directory of Open Access Journals (Sweden)

Olympia Roeva

2004-10-01

Full Text Available This paper presents the use of genetic algorithms for identification of Escherichia coli fed-batch fermentation process. Genetic algorithms are a directed random search technique, based on the mechanics of natural selection and natural genetics, which can find the global optimal solution in complex multidimensional search space. The dynamic behavior of considered process has known nonlinear structure, described with a system of deterministic nonlinear differential equations according to the mass balance. The parameters of the model are estimated using genetic algorithms. Simulation examples for demonstration of the effectiveness and robustness of the proposed identification scheme are included. As a result, the model accurately predicts the process of cultivation of E. coli.

Genetic diversity and landscape genetic structure of otter (Lutra lutra) populations in Europe

DEFF Research Database (Denmark)

Mucci, Nadia; Arrendal, Johanna; Ansorge, Hermann

2010-01-01

Eurasian otter populations strongly declined and partially disappeared due to global and local causes (habitat destruction, water pollution, human persecution) in parts of their continental range. Conservation strategies, based on reintroduction projects or restoration of dispersal corridors...... and landscape genetic analyses however indicate that local populations are genetically differentiated, perhaps as consequence of post-glacial demographic fluctuations and recent isolation. These results delineate a framework that should be used for implementing conservation programs in Europe, particularly...

Genetic analysis of the isolated Faroe Islands reveals SORCS3 as a potential multiple sclerosis risk gene

DEFF Research Database (Denmark)

Binzer, Stefanie; Stenager, Egon; Binzer, Michael

2016-01-01

BACKGROUND: In search of the missing heritability in multiple sclerosis (MS), additional approaches adding to the genetic discoveries of large genome-wide association studies are warranted. OBJECTIVE: The objective of this research paper is to search for rare genetic MS risk variants...... in the genetically homogenous population of the isolated Faroe Islands. METHODS: Twenty-nine Faroese MS cases and 28 controls were genotyped with the HumanOmniExpressExome-chip. The individuals make up 1596 pair-combinations in which we searched for identical-by-descent shared segments using the PLINK...... of neurotrophin factors and involvement in glutamate homeostasis. Although additional work is needed to scrutinise the genetic effect of the SORCS3-covering haplotype, this study suggests that SORCS3 may also be important in MS pathogenesis....

Pareto Optimization of a Half Car Passive Suspension Model Using a Novel Multiobjective Heat Transfer Search Algorithm

OpenAIRE

Savsani, Vimal; Patel, Vivek; Gadhvi, Bhargav; Tawhid, Mohamed

2017-01-01

Most of the modern multiobjective optimization algorithms are based on the search technique of genetic algorithms; however the search techniques of other recently developed metaheuristics are emerging topics among researchers. This paper proposes a novel multiobjective optimization algorithm named multiobjective heat transfer search (MOHTS) algorithm, which is based on the search technique of heat transfer search (HTS) algorithm. MOHTS employs the elitist nondominated sorting and crowding dis...

Optimal filter design with progressive genetic algorithm for local damage detection in rolling bearings

Science.gov (United States)

Wodecki, Jacek; Michalak, Anna; Zimroz, Radoslaw

2018-03-01

Harsh industrial conditions present in underground mining cause a lot of difficulties for local damage detection in heavy-duty machinery. For vibration signals one of the most intuitive approaches of obtaining signal with expected properties, such as clearly visible informative features, is prefiltration with appropriately prepared filter. Design of such filter is very broad field of research on its own. In this paper authors propose a novel approach to dedicated optimal filter design using progressive genetic algorithm. Presented method is fully data-driven and requires no prior knowledge of the signal. It has been tested against a set of real and simulated data. Effectiveness of operation has been proven for both healthy and damaged case. Termination criterion for evolution process was developed, and diagnostic decision making feature has been proposed for final result determinance.

On Generating Optimal Signal Probabilities for Random Tests: A Genetic Approach

Directory of Open Access Journals (Sweden)

M. Srinivas

1996-01-01

Full Text Available Genetic Algorithms are robust search and optimization techniques. A Genetic Algorithm based approach for determining the optimal input distributions for generating random test vectors is proposed in the paper. A cost function based on the COP testability measure for determining the efficacy of the input distributions is discussed. A brief overview of Genetic Algorithms (GAs and the specific details of our implementation are described. Experimental results based on ISCAS-85 benchmark circuits are presented. The performance of our GAbased approach is compared with previous results. While the GA generates more efficient input distributions than the previous methods which are based on gradient descent search, the overheads of the GA in computing the input distributions are larger.

Optimal hydrogenerator governor tuning with a genetic algorithm

International Nuclear Information System (INIS)

Lansberry, J.E.; Wozniak, L.; Goldberg, D.E.

1992-01-01

Many techniques exist for developing optimal controllers. This paper investigates genetic algorithms as a means of finding optimal solutions over a parameter space. In particular, the genetic algorithm is applied to optimal tuning of a governor for a hydrogenerator plant. Analog and digital simulation methods are compared for use in conjunction with the genetic algorithm optimization process. It is shown that analog plant simulation provides advantages in speed over digital plant simulation. This speed advantage makes application of the genetic algorithm in an actual plant environment feasible. Furthermore, the genetic algorithm is shown to possess the ability to reject plant noise and other system anomalies in its search for optimizing solutions

Basics on Genes and Genetic Disorders

Science.gov (United States)

... for Educators Search English Español The Basics on Genes and Genetic Disorders KidsHealth / For Teens / The Basics ... such as treating health problems. What Is a Gene? To understand how genes work, let's review some ...

Search and localization of orphan sources

International Nuclear Information System (INIS)

Gayral, J.-P.

2001-01-01

The control of all radioactive materials should be a major and permanent concern of every state. This paper outlines some of the steps which should be taken in order to detect and localize orphan sources. Two of them are of great importance to any state wishing to resolve the orphan source problem. The first one is to analyse the situation and the second is to establish a strategy before taking action. It is the responsibility of the state to work on the first step; but for the second one it can draw on the advice of the IAEA specialists with experience grained from a variety of situations

Feature Selection for Object-Based Classification of High-Resolution Remote Sensing Images Based on the Combination of a Genetic Algorithm and Tabu Search

Directory of Open Access Journals (Sweden)

Lei Shi

2018-01-01

Full Text Available In object-based image analysis of high-resolution images, the number of features can reach hundreds, so it is necessary to perform feature reduction prior to classification. In this paper, a feature selection method based on the combination of a genetic algorithm (GA and tabu search (TS is presented. The proposed GATS method aims to reduce the premature convergence of the GA by the use of TS. A prematurity index is first defined to judge the convergence situation during the search. When premature convergence does take place, an improved mutation operator is executed, in which TS is performed on individuals with higher fitness values. As for the other individuals with lower fitness values, mutation with a higher probability is carried out. Experiments using the proposed GATS feature selection method and three other methods, a standard GA, the multistart TS method, and ReliefF, were conducted on WorldView-2 and QuickBird images. The experimental results showed that the proposed method outperforms the other methods in terms of the final classification accuracy.

Feature Selection for Object-Based Classification of High-Resolution Remote Sensing Images Based on the Combination of a Genetic Algorithm and Tabu Search

Science.gov (United States)

Shi, Lei; Wan, Youchuan; Gao, Xianjun

2018-01-01

In object-based image analysis of high-resolution images, the number of features can reach hundreds, so it is necessary to perform feature reduction prior to classification. In this paper, a feature selection method based on the combination of a genetic algorithm (GA) and tabu search (TS) is presented. The proposed GATS method aims to reduce the premature convergence of the GA by the use of TS. A prematurity index is first defined to judge the convergence situation during the search. When premature convergence does take place, an improved mutation operator is executed, in which TS is performed on individuals with higher fitness values. As for the other individuals with lower fitness values, mutation with a higher probability is carried out. Experiments using the proposed GATS feature selection method and three other methods, a standard GA, the multistart TS method, and ReliefF, were conducted on WorldView-2 and QuickBird images. The experimental results showed that the proposed method outperforms the other methods in terms of the final classification accuracy. PMID:29581721

Allotment of aircraft spare parts using genetic alorithms

Directory of Open Access Journals (Sweden)

Batchoun Pascale

2003-01-01

Full Text Available In this paper we attempt to determine the optimal allocation of aircraft parts used as spares for replacement of defective parts on-board of a departing flight. In order to minimize the cost of delay caused by unexpected failure, Genetic algorithms (GAs are used to allocate the initial quantity of parts among the airports. GAs are a class of adaptive search procedures, that distinguish themselves from other optimization techniques by the use of concepts from population genetics to guide the search. Problem-specific knowledge is incorporated into the problem and efficient parameters are identified and tested for the task of optimizing the allocation of parts. The approach is illustrated by numerical results.

[Investigation of the publishing and using status of college genetics textbooks in China].

Science.gov (United States)

Chen, Xiwen; Chen, Defu

2014-04-01

Using Wenjin Search of the National Library of China, it was found that 895 genetics textbooks for Chinese colleges, including 588 (67.5%) theoretical books, 122 (13.6%) experimental books and 185 (20.7%) teaching reference books, have been published since College Entrance Examination resumed. Most of these books belong to medical genetics, followed by general genetics, while the books on plant genetics, animal genetics or microbial genetics are relatively few. In these search results, 91 had the same name of Medical Genetics, professor Ji Zuo is the most productive author, who edited 9 genetics textbooks, and Science Press Ltd. is the most productive press, which published 179 (20%) genetics textbooks. The questionnaire survey showed that "Genetics" (Second Edition) edited by Zhuohua Dai is the most widely used textbooks in the Chinese colleges, while the mainly used experimental books are the handouts or self-edited textbooks. Finally, we analyzed the problems currently existed in the textbooks, such as slowly updating cycle, less supports, lots of books with the same name, lack of scientific stories, very rare and unique illustrations, too full printed pages, and also provided the proposed solution.

Identifying Interacting Genetic Variations by Fish-Swarm Logic Regression

Science.gov (United States)

Yang, Aiyuan; Yan, Chunxia; Zhu, Feng; Zhao, Zhongmeng; Cao, Zhi

2013-01-01

Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR) is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR), which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds. PMID:23984382

Identifying Interacting Genetic Variations by Fish-Swarm Logic Regression

Directory of Open Access Journals (Sweden)

Xuanping Zhang

2013-01-01

Full Text Available Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR, which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds.

An efficient genetic algorithm for maximum coverage deployment in wireless sensor networks.

Science.gov (United States)

Yoon, Yourim; Kim, Yong-Hyuk

2013-10-01

Sensor networks have a lot of applications such as battlefield surveillance, environmental monitoring, and industrial diagnostics. Coverage is one of the most important performance metrics for sensor networks since it reflects how well a sensor field is monitored. In this paper, we introduce the maximum coverage deployment problem in wireless sensor networks and analyze the properties of the problem and its solution space. Random deployment is the simplest way to deploy sensor nodes but may cause unbalanced deployment and therefore, we need a more intelligent way for sensor deployment. We found that the phenotype space of the problem is a quotient space of the genotype space in a mathematical view. Based on this property, we propose an efficient genetic algorithm using a novel normalization method. A Monte Carlo method is adopted to design an efficient evaluation function, and its computation time is decreased without loss of solution quality using a method that starts from a small number of random samples and gradually increases the number for subsequent generations. The proposed genetic algorithms could be further improved by combining with a well-designed local search. The performance of the proposed genetic algorithm is shown by a comparative experimental study. When compared with random deployment and existing methods, our genetic algorithm was not only about twice faster, but also showed significant performance improvement in quality.

On the network-based emulation of human visual search

NARCIS (Netherlands)

Gerrissen, J.F.

1991-01-01

We describe the design of a computer emulator of human visual search. The emulator mechanism is eventually meant to support ergonomic assessment of the effect of display structure and protocol on search performance. As regards target identification and localization, it mimics a number of

Accelerated Profile HMM Searches.

Directory of Open Access Journals (Sweden)

Sean R Eddy

2011-10-01

Full Text Available Profile hidden Markov models (profile HMMs and probabilistic inference methods have made important contributions to the theory of sequence database homology search. However, practical use of profile HMM methods has been hindered by the computational expense of existing software implementations. Here I describe an acceleration heuristic for profile HMMs, the "multiple segment Viterbi" (MSV algorithm. The MSV algorithm computes an optimal sum of multiple ungapped local alignment segments using a striped vector-parallel approach previously described for fast Smith/Waterman alignment. MSV scores follow the same statistical distribution as gapped optimal local alignment scores, allowing rapid evaluation of significance of an MSV score and thus facilitating its use as a heuristic filter. I also describe a 20-fold acceleration of the standard profile HMM Forward/Backward algorithms using a method I call "sparse rescaling". These methods are assembled in a pipeline in which high-scoring MSV hits are passed on for reanalysis with the full HMM Forward/Backward algorithm. This accelerated pipeline is implemented in the freely available HMMER3 software package. Performance benchmarks show that the use of the heuristic MSV filter sacrifices negligible sensitivity compared to unaccelerated profile HMM searches. HMMER3 is substantially more sensitive and 100- to 1000-fold faster than HMMER2. HMMER3 is now about as fast as BLAST for protein searches.

Nature-inspired novel Cuckoo Search Algorithm for genome ...

Indian Academy of Sciences (India)

compared their results with other methods such as the genetic algorithm. ... It is a population-based search procedure used as an optimization tool, in ... In this section, the problem formulation, fitness evaluation, flowchart and implementation of the ..... Machine Learning 21: 11–33 ... Numerical Optimization 1: 330–343.

A "Hands on" Strategy for Teaching Genetic Algorithms to Undergraduates

Science.gov (United States)

Venables, Anne; Tan, Grace

2007-01-01

Genetic algorithms (GAs) are a problem solving strategy that uses stochastic search. Since their introduction (Holland, 1975), GAs have proven to be particularly useful for solving problems that are "intractable" using classical methods. The language of genetic algorithms (GAs) is heavily laced with biological metaphors from evolutionary…

White Matter Lesion Progression: Genome-Wide Search for Genetic Influences

NARCIS (Netherlands)

E. Hofer (Edith); M. Cavalieri (Margherita); J.C. Bis (Joshua); C. DeCarli (Charles); M. Fornage (Myriam); S. Sigurdsson (Sigurdur); V. Srikanth (Velandai); S. Trompet (Stella); B.F.J. Verhaaren (Benjamin); C. Wolf (Christiane); Q. Yang (Qiong Fang); H.H.H. Adams (Hieab); P. Amouyel (Philippe); A. Beiser (Alexa); B.M. Buckley (Brendan M.); M. Callisaya (Michele); G. Chauhan (Ganesh); A.J.M. De Craen (Anton J. M.); C. Dufouil (Carole); C.M. van Duijn (Cornelia); I. Ford; P. Freudenberger (Paul); R.F. Gottesman (Rebecca); V. Gudnason (Vilmundur); G. Heiss (Gerardo); A. Hofman (Albert); T. Lumley (Thomas); O. Martinez (Oliver); B. Mazoyer (Bernard); C. Moran (Chris); W.J. Niessen (Wiro); T.G. Phan (Thanh); B.M. Psaty (Bruce); C.L. Satizabal (Claudia L.); N. Sattar (Naveed); S. Schilling (Sabrina); D.K. Shibata (Dean); P.E. Slagboom (Eline); G.D. Smith; D.J. Stott (David. J.); K.D. Taylor (Kent); R. Thomson (Russell); A.M. Töglhofer (Anna Maria); C. Tzourio (Christophe); M.A. van Buchem (Mark); J. Wang (Jing); R.G.J. Westendorp (Rudi); B. Gwen Windham; M.W. Vernooij (Meike); A.P. Zijdenbos; R.J. Beare (Richard); S. Debette (Stéphanie); M.A. Ikram (Arfan); J.W. Jukema (Jan Wouter); L.J. Launer (Lenore); W.T. Longstreth Jr; T.H. Mosley (Thomas H.); S. Seshadri (Sudha); R. Schmidt (Reinhold); R. Schmidt (Reinhold)

2015-01-01

textabstractBackground and Purpose-White matter lesion (WML) progression on magnetic resonance imaging is related to cognitive decline and stroke, but its determinants besides baseline WML burden are largely unknown. Here, we estimated heritability of WML progression, and sought common genetic

Oceanographic Currents and Local Ecological Knowledge Indicate, and Genetics Does Not Refute, a Contemporary Pattern of Larval Dispersal for The Ornate Spiny Lobster, Panulirus ornatus in the South-East Asian Archipelago.

Directory of Open Access Journals (Sweden)

Hoc Tan Dao

Full Text Available Here we utilize a combination of genetic data, oceanographic data, and local ecological knowledge to assess connectivity patterns of the ornate spiny lobster Panulirus ornatus (Fabricius, 1798 in the South-East Asian archipelago from Vietnam to Australia. Partial mitochondrial DNA control region and 10 polymorphic microsatellites did not detect genetic structure of 216 wild P. ornatus samples from Australia, Indonesia and Vietnam. Analyses show no evidence for genetic differentiation among populations (mtDNA control region sequences ΦST = -0.008; microsatellite loci FST = 0.003. A lack of evidence for regional or localized mtDNA haplotype clusters, or geographic clusters of microsatellite genotypes, reveals a pattern of high gene flow in P. ornatus throughout the South-East Asian Archipelago. This lack of genetic structure may be due to the oceanography-driven connectivity of the pelagic lobster larvae between spawning grounds in Papua New Guinea, the Philippines and, possibly, Indonesia. The connectivity cycle necessitates three generations. The lack of genetic structure of P. ornatus population in the South-East Asian archipelago has important implications for the sustainable management of this lobster in that the species within the region needs to be managed as one genetic stock.

A theoretical analysis of population genetics of plants on restored habitats

Energy Technology Data Exchange (ETDEWEB)

Bogoliubov, A.G. [Botanical Institute, Russian Academy of Science, St. Petersburg (Russian Federation); Loehle, C. [Argonne National Lab., IL (United States)

1995-02-01

Seed and propagules used for habitat restoration are not likely to be closely adapted to local site conditions. Rapid changes of genotypes frequencies on local microsites and/or microevolution would allow plants to become better adapted to a site. These same factors would help to maintain genetic diversity and ensure the survival of small endangered populations. We used population genetics models to examine the selection of genotypes during establishment on restored sites. Vegetative spread was shown to affect selection and significantly reduce genetic diversity. To study general microevolution, we linked a model of resource usage with a genetics model and analyzed competition between genotypes. A complex suite of feasible ecogenetic states was shown to result. The state actually resulting would depend strongly on initial conditions. This analysis indicated that genetic structure can vary locally and can produce overall genetic variability that is not simply the result of microsite adaptations. For restoration activities, the implication is that small differences in seed source could lead to large differences in local genetic structure after selection.

A theoretical analysis of population genetics of plants on restored habitats

Energy Technology Data Exchange (ETDEWEB)

Bogoliubov, A.G. [Russian Academy of Science, St. Petersburg (Russian Federation). Botanical Inst.; Loehle, C. [Argonne National Lab., IL (United States). Environmental Research Div.

1997-07-01

Seed and propagules used for habitat restoration are not likely to be closely adapted to local site conditions. Rapid changes of genotypes frequencies on local microsites and/or microevolution would allow plants to become better adapted to a site. These same factors would help to maintain genetic diversity and ensure the survival of small endangered populations. The authors used population genetics models to examine the selection of genotypes during establishment on restored sites. Vegetative spread was shown to affect selection and significantly reduce genetic diversity. To study general microevolution, the authors linked a model of resource usage with a genetics model and analyzed competition between genotypes. A complex suite of feasible ecogenetic states was shown to result. The state actually resulting would depend strongly on initial conditions. This analysis indicated that genetic structure can vary locally and can produce overall genetic variability that is not simply the result of microsite adaptations. For restoration activities, the implication is that small differences in seed source could lead to large differences in local genetic structure after selection.

Characteristic sounds facilitate visual search.

Science.gov (United States)

Iordanescu, Lucica; Guzman-Martinez, Emmanuel; Grabowecky, Marcia; Suzuki, Satoru

2008-06-01

In a natural environment, objects that we look for often make characteristic sounds. A hiding cat may meow, or the keys in the cluttered drawer may jingle when moved. Using a visual search paradigm, we demonstrated that characteristic sounds facilitated visual localization of objects, even when the sounds carried no location information. For example, finding a cat was faster when participants heard a meow sound. In contrast, sounds had no effect when participants searched for names rather than pictures of objects. For example, hearing "meow" did not facilitate localization of the word cat. These results suggest that characteristic sounds cross-modally enhance visual (rather than conceptual) processing of the corresponding objects. Our behavioral demonstration of object-based cross-modal enhancement complements the extensive literature on space-based cross-modal interactions. When looking for your keys next time, you might want to play jingling sounds.

Genetics education in the nursing profession: literature review.

Science.gov (United States)

Burke, Sarah; Kirk, Maggie

2006-04-01

This paper reports a literature review exploring genetics education for nursing professionals. The aim was to contribute to the debate about the future direction of such education. Advances in genetics science and technology have profound implications for health care and the growing importance and relevance of genetics for everyday nursing practice is increasingly recognized. A search was conducted in February 2005 using the CINAHL and Google Scholar databases and the keywords nurse, midwife, health visitor, education and genetics. Papers were included if they were published in English between 1994 and 2005 and included empirical data about genetics education in nursing. In addition, attempts were made to access the grey literature, with requests for information on research, for example, to members of the Association of Genetic Nurses and Counsellors and searches of relevant websites. Agreement on the relevance of genetics for nursing practice is extensive. Empirical evidence of the learning needs of practitioners highlights widespread deficits in knowledge and skills, and low confidence levels. Provision of nursing education in genetics is patchy and insubstantial across a number of countries, further hampered by lack of strategic development. Significant progress has been made in the identification of learning outcomes for nurses. Research on the delivery of genetics education is limited, but the role of skills-based training, use of clinical scenarios, and importance of assessment have all been identified as factors that can promote learning. Whilst areas of good performance were revealed, many studies identified gaps in professional competence and/or education. New initiatives are underway to support genetics education and its integration into professional practice, but further research is needed on the most effective forms of educational delivery, and an international collaborative approach to this should be considered.

Detecting authorized and unauthorized genetically modified organisms containing vip3A by real-time PCR and next-generation sequencing.

Science.gov (United States)

Liang, Chanjuan; van Dijk, Jeroen P; Scholtens, Ingrid M J; Staats, Martijn; Prins, Theo W; Voorhuijzen, Marleen M; da Silva, Andrea M; Arisi, Ana Carolina Maisonnave; den Dunnen, Johan T; Kok, Esther J

2014-04-01

The growing number of biotech crops with novel genetic elements increasingly complicates the detection of genetically modified organisms (GMOs) in food and feed samples using conventional screening methods. Unauthorized GMOs (UGMOs) in food and feed are currently identified through combining GMO element screening with sequencing the DNA flanking these elements. In this study, a specific and sensitive qPCR assay was developed for vip3A element detection based on the vip3Aa20 coding sequences of the recently marketed MIR162 maize and COT102 cotton. Furthermore, SiteFinding-PCR in combination with Sanger, Illumina or Pacific BioSciences (PacBio) sequencing was performed targeting the flanking DNA of the vip3Aa20 element in MIR162. De novo assembly and Basic Local Alignment Search Tool searches were used to mimic UGMO identification. PacBio data resulted in relatively long contigs in the upstream (1,326 nucleotides (nt); 95 % identity) and downstream (1,135 nt; 92 % identity) regions, whereas Illumina data resulted in two smaller contigs of 858 and 1,038 nt with higher sequence identity (>99 % identity). Both approaches outperformed Sanger sequencing, underlining the potential for next-generation sequencing in UGMO identification.

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)

Low genetic diversity and local adaptive divergence of Dracaena cambodiana (Liliaceae) populations associated with historical population bottlenecks and natural selection: an endangered long-lived tree endemic to Hainan Island, China.

Science.gov (United States)

Zheng, D-J; Xie, L-S; Zhu, J-H; Zhang, Z-L

2012-09-01

Historical population bottlenecks and natural selection have important effects on the current genetic diversity and structure of long-lived trees. Dracaena cambodiana is an endangered, long-lived tree endemic to Hainan Island, China. Our field investigations showed that only 10 populations remain on Hainan Island and that almost all have been seriously isolated and grow in distinct habitats. A considerable amount of genetic variation at the species level, but little variation at the population level, and a high level of genetic differentiation among the populations with limited gene flow in D. cambodiana were detected using inter-simple sequence repeat (ISSR) and random amplified polymorphic DNA (RAPD) analyses. No significant correlation was found between genetic diversity and actual population size, as the genetic diversities were similar regardless of population size. The Mantel test revealed that there was no correlation between genetic and geographic distances among the 10 populations. The UPGMA, PCoA and Bayesian analyses showed that local adaptive divergence has occurred among the D. cambodiana populations, which was further supported by habitat-private fragments. We suggest that the current genetic diversity and population differentiation of D. cambodiana resulted from historical population bottlenecks and natural selection followed by historical isolation. However, the lack of natural regeneration of D. cambodiana indicates that former local adaptations with low genetic diversity may have been genetically weak and are unable to adapt to the current ecological environments. © 2012 German Botanical Society and The Royal Botanical Society of the Netherlands.

Contribution of genetics to ecological restoration.

Science.gov (United States)

Mijangos, Jose Luis; Pacioni, Carlo; Spencer, Peter B S; Craig, Michael D

2015-01-01

Ecological restoration of degraded ecosystems has emerged as a critical tool in the fight to reverse and ameliorate the current loss of biodiversity and ecosystem services. Approaches derived from different genetic disciplines are extending the theoretical and applied frameworks on which ecological restoration is based. We performed a search of scientific articles and identified 160 articles that employed a genetic approach within a restoration context to shed light on the links between genetics and restoration. These articles were then classified on whether they examined association between genetics and fitness or the application of genetics in demographic studies, and on the way the studies informed restoration practice. Although genetic research in restoration is rapidly growing, we found that studies could make better use of the extensive toolbox developed by applied fields in genetics. Overall, 41% of reviewed studies used genetic information to evaluate or monitor restoration, and 59% provided genetic information to guide prerestoration decision-making processes. Reviewed studies suggest that restoration practitioners often overlook the importance of including genetic aspects within their restoration goals. Even though there is a genetic basis influencing the provision of ecosystem services, few studies explored this relationship. We provide a view of research gaps, future directions and challenges in the genetics of restoration. © 2014 John Wiley & Sons Ltd.

Search for heavy resonances decaying to top quarks

CERN Document Server

D'Auria, Saverio; The ATLAS collaboration

2017-01-01

Searches for new resonances that decay either to pairs of top quarks or a top and a b-quark are presented. The searches are performed with the ATLAS experiment at the LHC using proton-proton collision data. The invariant mass spectrum of hypothetical resonances are examined for local excesses or deficits that are inconsistent with the Standard Model prediction.

Feed-Forward Neural Networks and Minimal Search Space Learning

Czech Academy of Sciences Publication Activity Database

Neruda, Roman

2005-01-01

Roč. 4, č. 12 (2005), s. 1867-1872 ISSN 1109-2750 R&D Projects: GA ČR GA201/05/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : search space * feed-forward networks * genetic algorithm s Subject RIV: BA - General Mathematics

An Update on Genetic and Serotoneric Biomarker Findings in Bulimia Nervosa

DEFF Research Database (Denmark)

Sjögren, Magnus

2017-01-01

support in understanding the pathophysiology of BN, and potentially in diagnosing, and monitoring of effects of treatment. This review describes genetic and serotonergic biomarkers for BN. Method: A literature search using PUBMED (20 June 2017) was done using the following search terms: 1) “Bulimia...

Graphical models for genetic analyses

DEFF Research Database (Denmark)

Lauritzen, Steffen Lilholt; Sheehan, Nuala A.

2003-01-01

This paper introduces graphical models as a natural environment in which to formulate and solve problems in genetics and related areas. Particular emphasis is given to the relationships among various local computation algorithms which have been developed within the hitherto mostly separate areas...... of graphical models and genetics. The potential of graphical models is explored and illustrated through a number of example applications where the genetic element is substantial or dominating....

Delay-independent stability of genetic regulatory networks.

Science.gov (United States)

Wu, Fang-Xiang

2011-11-01

Genetic regulatory networks can be described by nonlinear differential equations with time delays. In this paper, we study both locally and globally delay-independent stability of genetic regulatory networks, taking messenger ribonucleic acid alternative splicing into consideration. Based on nonnegative matrix theory, we first develop necessary and sufficient conditions for locally delay-independent stability of genetic regulatory networks with multiple time delays. Compared to the previous results, these conditions are easy to verify. Then we develop sufficient conditions for global delay-independent stability for genetic regulatory networks. Compared to the previous results, this sufficient condition is less conservative. To illustrate theorems developed in this paper, we analyze delay-independent stability of two genetic regulatory networks: a real-life repressilatory network with three genes and three proteins, and a synthetic gene regulatory network with five genes and seven proteins. The simulation results show that the theorems developed in this paper can effectively determine the delay-independent stability of genetic regulatory networks.

Model parameters estimation and sensitivity by genetic algorithms

International Nuclear Information System (INIS)

Marseguerra, Marzio; Zio, Enrico; Podofillini, Luca

2003-01-01

In this paper we illustrate the possibility of extracting qualitative information on the importance of the parameters of a model in the course of a Genetic Algorithms (GAs) optimization procedure for the estimation of such parameters. The Genetic Algorithms' search of the optimal solution is performed according to procedures that resemble those of natural selection and genetics: an initial population of alternative solutions evolves within the search space through the four fundamental operations of parent selection, crossover, replacement, and mutation. During the search, the algorithm examines a large amount of solution points which possibly carries relevant information on the underlying model characteristics. A possible utilization of this information amounts to create and update an archive with the set of best solutions found at each generation and then to analyze the evolution of the statistics of the archive along the successive generations. From this analysis one can retrieve information regarding the speed of convergence and stabilization of the different control (decision) variables of the optimization problem. In this work we analyze the evolution strategy followed by a GA in its search for the optimal solution with the aim of extracting information on the importance of the control (decision) variables of the optimization with respect to the sensitivity of the objective function. The study refers to a GA search for optimal estimates of the effective parameters in a lumped nuclear reactor model of literature. The supporting observation is that, as most optimization procedures do, the GA search evolves towards convergence in such a way to stabilize first the most important parameters of the model and later those which influence little the model outputs. In this sense, besides estimating efficiently the parameters values, the optimization approach also allows us to provide a qualitative ranking of their importance in contributing to the model output. The

Genetic architecture of local adaptation in lunar and diurnal emergence times of the marine midge Clunio marinus (Chironomidae, Diptera).

Science.gov (United States)

Kaiser, Tobias S; Heckel, David G

2012-01-01

Circadian rhythms pre-adapt the physiology of most organisms to predictable daily changes in the environment. Some marine organisms also show endogenous circalunar rhythms. The genetic basis of the circalunar clock and its interaction with the circadian clock is unknown. Both clocks can be studied in the marine midge Clunio marinus (Chironomidae, Diptera), as different populations have different local adaptations in their lunar and diurnal rhythms of adult emergence, which can be analyzed by crossing experiments. We investigated the genetic basis of population variation in clock properties by constructing the first genetic linkage map for this species, and performing quantitative trait locus (QTL) analysis on variation in both lunar and diurnal timing. The genome has a genetic length of 167-193 centimorgans based on a linkage map using 344 markers, and a physical size of 95-140 megabases estimated by flow cytometry. Mapping the sex determining locus shows that females are the heterogametic sex, unlike most other Chironomidae. We identified two QTL each for lunar emergence time and diurnal emergence time. The distribution of QTL confirms a previously hypothesized genetic basis to a correlation of lunar and diurnal emergence times in natural populations. Mapping of clock genes and light receptors identified ciliary opsin 2 (cOps2) as a candidate to be involved in both lunar and diurnal timing; cryptochrome 1 (cry1) as a candidate gene for lunar timing; and two timeless (tim2, tim3) genes as candidate genes for diurnal timing. This QTL analysis of lunar rhythmicity, the first in any species, provides a unique entree into the molecular analysis of the lunar clock.

Evolving temporal association rules with genetic algorithms

OpenAIRE

Matthews, Stephen G.; Gongora, Mario A.; Hopgood, Adrian A.

2010-01-01

A novel framework for mining temporal association rules by discovering itemsets with a genetic algorithm is introduced. Metaheuristics have been applied to association rule mining, we show the efficacy of extending this to another variant - temporal association rule mining. Our framework is an enhancement to existing temporal association rule mining methods as it employs a genetic algorithm to simultaneously search the rule space and temporal space. A methodology for validating the ability of...

Quantum-circuit model of Hamiltonian search algorithms

International Nuclear Information System (INIS)

Roland, Jeremie; Cerf, Nicolas J.

2003-01-01

We analyze three different quantum search algorithms, namely, the traditional circuit-based Grover's algorithm, its continuous-time analog by Hamiltonian evolution, and the quantum search by local adiabatic evolution. We show that these algorithms are closely related in the sense that they all perform a rotation, at a constant angular velocity, from a uniform superposition of all states to the solution state. This makes it possible to implement the two Hamiltonian-evolution algorithms on a conventional quantum circuit, while keeping the quadratic speedup of Grover's original algorithm. It also clarifies the link between the adiabatic search algorithm and Grover's algorithm

[Genetic diversity and mating system Pinus brutia var. Stankewiczii sukacz. in small localities of Sudak (Crimea)].

Science.gov (United States)

Korshikov, I I; Kalafat, L A; Milchevskaya, Ya G

2015-01-01

A comparative analysis of genetic variation at 12 polymorphic isozyme loci, and the mating system has been carried out in mature trees and their seed progeny in three small localities of Pinus brutia var. stankewiczii Sukacz. near the town of Sudak--settlement of Novyi Svet in the Crimea. We found that embryos maintain the same allelic diversity as mother plants but their observed heterozygosity is lower on the average by 37.4%. The significant deviation of genotype distribution from the theoretically expected ratios caused by the deficiency of heterozygotes was observed at 8 out of 12 loci. Multilocus estimate of outcrossing rate (t(m)) in populations varied from 68.9 to 94.9% making on the average 80.7%.

BRAD, the genetics and genomics database for Brassica plants

Directory of Open Access Journals (Sweden)

Li Pingxia

2011-10-01

Full Text Available Abstract Background Brassica species include both vegetable and oilseed crops, which are very important to the daily life of common human beings. Meanwhile, the Brassica species represent an excellent system for studying numerous aspects of plant biology, specifically for the analysis of genome evolution following polyploidy, so it is also very important for scientific research. Now, the genome of Brassica rapa has already been assembled, it is the time to do deep mining of the genome data. Description BRAD, the Brassica database, is a web-based resource focusing on genome scale genetic and genomic data for important Brassica crops. BRAD was built based on the first whole genome sequence and on further data analysis of the Brassica A genome species, Brassica rapa (Chiifu-401-42. It provides datasets, such as the complete genome sequence of B. rapa, which was de novo assembled from Illumina GA II short reads and from BAC clone sequences, predicted genes and associated annotations, non coding RNAs, transposable elements (TE, B. rapa genes' orthologous to those in A. thaliana, as well as genetic markers and linkage maps. BRAD offers useful searching and data mining tools, including search across annotation datasets, search for syntenic or non-syntenic orthologs, and to search the flanking regions of a certain target, as well as the tools of BLAST and Gbrowse. BRAD allows users to enter almost any kind of information, such as a B. rapa or A. thaliana gene ID, physical position or genetic marker. Conclusion BRAD, a new database which focuses on the genetics and genomics of the Brassica plants has been developed, it aims at helping scientists and breeders to fully and efficiently use the information of genome data of Brassica plants. BRAD will be continuously updated and can be accessed through http://brassicadb.org.

Using probability modelling and genetic parentage assignment to test the role of local mate availability in mating system variation.

Science.gov (United States)

Blyton, Michaela D J; Banks, Sam C; Peakall, Rod; Lindenmayer, David B

2012-02-01

The formal testing of mating system theories with empirical data is important for evaluating the relative importance of different processes in shaping mating systems in wild populations. Here, we present a generally applicable probability modelling framework to test the role of local mate availability in determining a population's level of genetic monogamy. We provide a significance test for detecting departures in observed mating patterns from model expectations based on mate availability alone, allowing the presence and direction of behavioural effects to be inferred. The assessment of mate availability can be flexible and in this study it was based on population density, sex ratio and spatial arrangement. This approach provides a useful tool for (1) isolating the effect of mate availability in variable mating systems and (2) in combination with genetic parentage analyses, gaining insights into the nature of mating behaviours in elusive species. To illustrate this modelling approach, we have applied it to investigate the variable mating system of the mountain brushtail possum (Trichosurus cunninghami) and compared the model expectations with the outcomes of genetic parentage analysis over an 18-year study. The observed level of monogamy was higher than predicted under the model. Thus, behavioural traits, such as mate guarding or selective mate choice, may increase the population level of monogamy. We show that combining genetic parentage data with probability modelling can facilitate an improved understanding of the complex interactions between behavioural adaptations and demographic dynamics in driving mating system variation. © 2011 Blackwell Publishing Ltd.

The star formation histories of local group dwarf galaxies. II. Searching for signatures of reionization

Energy Technology Data Exchange (ETDEWEB)

Weisz, Daniel R. [Department of Astronomy, University of California at Santa Cruz, 1156 High Street, Santa Cruz, CA 95064 (United States); Dolphin, Andrew E. [Raytheon Company, 1151 East Hermans Road, Tucson, AZ 85756 (United States); Skillman, Evan D. [Minnesota Institute for Astrophysics, University of Minnesota, 116 Church Street SE, Minneapolis, MN 55455 (United States); Holtzman, Jon [Department of Astronomy, New Mexico State University, Box 30001, 1320 Frenger Street, Las Cruces, NM 88003 (United States); Gilbert, Karoline M.; Dalcanton, Julianne J.; Williams, Benjamin F., E-mail: drw@ucsc.edu [Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195 (United States)

2014-07-10

We search for signatures of reionization in the star formation histories (SFHs) of 38 Local Group dwarf galaxies (10{sup 4} < M{sub *} < 10{sup 9} M{sub ☉}). The SFHs are derived from color-magnitude diagrams using archival Hubble Space Telescope/Wide Field Planetary Camera 2 imaging. Only five quenched galaxies (And V, And VI, And XIII, Leo IV, and Hercules) are consistent with forming the bulk of their stars before reionization, when full uncertainties are considered. Observations of 13 of the predicted 'true fossils' identified by Bovill and Ricotti show that only two (Hercules and Leo IV) indicate star formation quenched by reionization. However, both are within the virial radius of the Milky Way and evidence of tidal disturbance complicates this interpretation. We argue that the late-time gas capture scenario posited by Ricotti for the low mass, gas-rich, and star-forming fossil candidate Leo T is observationally indistinguishable from simple gas retention. Given the ambiguity between environmental effects and reionization, the best reionization fossil candidates are quenched low mass field galaxies (e.g., KKR 25).

New technique for global solar radiation forecasting by simulated annealing and genetic algorithms using

International Nuclear Information System (INIS)

Tolabi, H.B.; Ayob, S.M.

2014-01-01

In this paper, a novel approach based on simulated annealing algorithm as a meta-heuristic method is implemented in MATLAB software to estimate the monthly average daily global solar radiation on a horizontal surface for six different climate cities of Iran. A search method based on genetic algorithm is applied to accelerate problem solving. Results show that simulated annealing based on genetic algorithm search is a suitable method to find the global solar radiation. (author)

A search asymmetry reversed by figure-ground assignment.

Science.gov (United States)

Humphreys, G W; Müller, H

2000-05-01

We report evidence demonstrating that a search asymmetry favoring concave over convex targets can be reversed by altering the figure-ground assignment of edges in shapes. Visual search for a concave target among convex distractors is faster than search for a convex target among concave distractors (a search asymmetry). By using shapes with ambiguous local figure-ground relations, we demonstrated that search can be efficient (with search slopes around 10 ms/item) or inefficient (with search slopes around 30-40 ms/item) with the same stimuli, depending on whether edges are assigned to concave or convex "figures." This assignment process can operate in a top-down manner, according to the task set. The results suggest that attention is allocated to spatial regions following the computation of figure-ground relations in parallel across the elements present. This computation can also be modulated by top-down processes.

Utilization of a radiology-centric search engine.

Science.gov (United States)

Sharpe, Richard E; Sharpe, Megan; Siegel, Eliot; Siddiqui, Khan

2010-04-01

Internet-based search engines have become a significant component of medical practice. Physicians increasingly rely on information available from search engines as a means to improve patient care, provide better education, and enhance research. Specialized search engines have emerged to more efficiently meet the needs of physicians. Details about the ways in which radiologists utilize search engines have not been documented. The authors categorized every 25th search query in a radiology-centric vertical search engine by radiologic subspecialty, imaging modality, geographic location of access, time of day, use of abbreviations, misspellings, and search language. Musculoskeletal and neurologic imagings were the most frequently searched subspecialties. The least frequently searched were breast imaging, pediatric imaging, and nuclear medicine. Magnetic resonance imaging and computed tomography were the most frequently searched modalities. A majority of searches were initiated in North America, but all continents were represented. Searches occurred 24 h/day in converted local times, with a majority occurring during the normal business day. Misspellings and abbreviations were common. Almost all searches were performed in English. Search engine utilization trends are likely to mirror trends in diagnostic imaging in the region from which searches originate. Internet searching appears to function as a real-time clinical decision-making tool, a research tool, and an educational resource. A more thorough understanding of search utilization patterns can be obtained by analyzing phrases as actually entered as well as the geographic location and time of origination. This knowledge may contribute to the development of more efficient and personalized search engines.

Genetic theory – a suggested cupping therapy mechanism of action

OpenAIRE

Shaban , Tamer; Ravalia , Munir

2017-01-01

The Cupping Therapy mechanism of action is not clear. Cupping may increase local blood circulation, and may have an immunomodulation effect. Local and systemic effects of Cupping Therapy were reported. Genetic expression is a physiological process that regulates body functions. Genetic modulation is a reported acupuncture effect. In this article, the authors suggest genetic modulation theory as one of the possible mechanisms of action of cupping therapy.

An Iterated Tabu Search Approach for the Clique Partitioning Problem

Directory of Open Access Journals (Sweden)

Gintaras Palubeckis

2014-01-01

all cliques induced by the subsets is as small as possible. We develop an iterated tabu search (ITS algorithm for solving this problem. The proposed algorithm incorporates tabu search, local search, and solution perturbation procedures. We report computational results on CPP instances of size up to 2000 vertices. Performance comparisons of ITS against state-of-the-art methods from the literature demonstrate the competitiveness of our approach.

Genetic diversity in a population of rhinoclemmys nasuta (Testudines: Geoemydidae) associated with an insular locality in the Choco biogeographic region

International Nuclear Information System (INIS)

Castillo Cutiva, Leslie Anais; Giraldo, Alan; Barreto, Guillermo

2014-01-01

Characterization of the genetic diversity of Rhinoclemmys nasuta population inhabits Isla Palma (Malaga Bay, Valle del Cauca) was carried out using three microsatellite systems (cm72, cm58 and cm"3). In this locality, individuals of R. nasuta are widely distributed in the inland streams and creeks system. 100 to 200 ml of peripheral blood was taken off from ten turtles in five streams of the island, preserving samples in a 0.5 m EDTA. DNA was extracted using salting-out and chelex solution techniques. PCR amplified products were visualized and measured in polyacrylamide gels stained with silver nitrate. successful amplification products were obtained for all systems analyzed, two of which (cm72 and cm3) were found to be monomorphic, while the system cm58 had a high pic (0.698) allowing to estimate the genetic diversity of this population. The observed heterozygosity was low (ho = 0.26) and inbreeding indices fis and fit were high (0.67857 and 0.67881), indicating an excess of homozygotes in each of the rivers and for the all population. The molecular analysis of variance suggested that there is no difference in genetic structure of the population (FST = 0.00075, p= 0.95112). Therefore, the results suggest that the genetic diversity of R. nasutapopulation in Isla Palma was low and exhibited a highly inbred index.

The population genomic landscape of human genetic structure, admixture history and local adaptation in Peninsular Malaysia.

Science.gov (United States)

Deng, Lian; Hoh, Boon Peng; Lu, Dongsheng; Fu, Ruiqing; Phipps, Maude E; Li, Shilin; Nur-Shafawati, Ab Rajab; Hatin, Wan Isa; Ismail, Endom; Mokhtar, Siti Shuhada; Jin, Li; Zilfalil, Bin Alwi; Marshall, Christian R; Scherer, Stephen W; Al-Mulla, Fahd; Xu, Shuhua

2014-09-01

Peninsular Malaysia is a strategic region which might have played an important role in the initial peopling and subsequent human migrations in Asia. However, the genetic diversity and history of human populations--especially indigenous populations--inhabiting this area remain poorly understood. Here, we conducted a genome-wide study using over 900,000 single nucleotide polymorphisms (SNPs) in four major Malaysian ethnic groups (MEGs; Malay, Proto-Malay, Senoi and Negrito), and made comparisons of 17 world-wide populations. Our data revealed that Peninsular Malaysia has greater genetic diversity corresponding to its role as a contact zone of both early and recent human migrations in Asia. However, each single Orang Asli (indigenous) group was less diverse with a smaller effective population size (N(e)) than a European or an East Asian population, indicating a substantial isolation of some duration for these groups. All four MEGs were genetically more similar to Asian populations than to other continental groups, and the divergence time between MEGs and East Asian populations (12,000--6,000 years ago) was also much shorter than that between East Asians and Europeans. Thus, Malaysian Orang Asli groups, despite their significantly different features, may share a common origin with the other Asian groups. Nevertheless, we identified traces of recent gene flow from non-Asians to MEGs. Finally, natural selection signatures were detected in a batch of genes associated with immune response, human height, skin pigmentation, hair and facial morphology and blood pressure in MEGs. Notable examples include SYN3 which is associated with human height in all Orang Asli groups, a height-related gene (PNPT1) and two blood pressure-related genes (CDH13 and PAX5) in Negritos. We conclude that a long isolation period, subsequent gene flow and local adaptations have jointly shaped the genetic architectures of MEGs, and this study provides insight into the peopling and human migration

Genetics Home Reference: optic atrophy type 1

Science.gov (United States)

... Nerve Atrophy Encyclopedia: Visual Acuity Test Health Topic: Color Blindness Health Topic: Optic Nerve Disorders Genetic and Rare ... Disease InfoSearch: Optic atrophy 1 Kids Health: What's Color Blindness? MalaCards: autosomal dominant optic atrophy, classic form Merck ...

Hybridisations of Variable Neighbourhood Search and Modified Simplex Elements to Harmony Search and Shuffled Frog Leaping Algorithms for Process Optimisations

Science.gov (United States)

Aungkulanon, P.; Luangpaiboon, P.

2010-10-01

Nowadays, the engineering problem systems are large and complicated. An effective finite sequence of instructions for solving these problems can be categorised into optimisation and meta-heuristic algorithms. Though the best decision variable levels from some sets of available alternatives cannot be done, meta-heuristics is an alternative for experience-based techniques that rapidly help in problem solving, learning and discovery in the hope of obtaining a more efficient or more robust procedure. All meta-heuristics provide auxiliary procedures in terms of their own tooled box functions. It has been shown that the effectiveness of all meta-heuristics depends almost exclusively on these auxiliary functions. In fact, the auxiliary procedure from one can be implemented into other meta-heuristics. Well-known meta-heuristics of harmony search (HSA) and shuffled frog-leaping algorithms (SFLA) are compared with their hybridisations. HSA is used to produce a near optimal solution under a consideration of the perfect state of harmony of the improvisation process of musicians. A meta-heuristic of the SFLA, based on a population, is a cooperative search metaphor inspired by natural memetics. It includes elements of local search and global information exchange. This study presents solution procedures via constrained and unconstrained problems with different natures of single and multi peak surfaces including a curved ridge surface. Both meta-heuristics are modified via variable neighbourhood search method (VNSM) philosophy including a modified simplex method (MSM). The basic idea is the change of neighbourhoods during searching for a better solution. The hybridisations proceed by a descent method to a local minimum exploring then, systematically or at random, increasingly distant neighbourhoods of this local solution. The results show that the variant of HSA with VNSM and MSM seems to be better in terms of the mean and variance of design points and yields.

Pulses of movement across the sea ice: population connectivity and temporal genetic structure in the arctic fox.

Science.gov (United States)

Norén, Karin; Carmichael, Lindsey; Fuglei, Eva; Eide, Nina E; Hersteinsson, Pall; Angerbjörn, Anders

2011-08-01

Lemmings are involved in several important functions in the Arctic ecosystem. The Arctic fox (Vulpes lagopus) can be divided into two discrete ecotypes: "lemming foxes" and "coastal foxes". Crashes in lemming abundance can result in pulses of "lemming fox" movement across the Arctic sea ice and immigration into coastal habitats in search for food. These pulses can influence the genetic structure of the receiving population. We have tested the impact of immigration on the genetic structure of the "coastal fox" population in Svalbard by recording microsatellite variation in seven loci for 162 Arctic foxes sampled during the summer and winter over a 5-year period. Genetic heterogeneity and temporal genetic shifts, as inferred by STRUCTURE simulations and deviations from Hardy-Weinberg proportions, respectively, were recorded. Maximum likelihood estimates of movement as well as STRUCTURE simulations suggested that both immigration and genetic mixture are higher in Svalbard than in the neighbouring "lemming fox" populations. The STRUCTURE simulations and AMOVA revealed there are differences in genetic composition of the population between summer and winter seasons, indicating that immigrants are not present in the reproductive portion of the Svalbard population. Based on these results, we conclude that Arctic fox population structure varies with time and is influenced by immigration from neighbouring populations. The lemming cycle is likely an important factor shaping Arctic fox movement across sea ice and the subsequent population genetic structure, but is also likely to influence local adaptation to the coastal habitat and the prevalence of diseases.

Diphoton searches in ATLAS

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00213273; The ATLAS collaboration

2016-01-01

Searches for new resonances decaying into two photons in the ATLAS experiment at the LHC are described. The analysis is based on $pp$ collision data corresponding to an integrated luminosity of 3.2 fb$^{-1}$ at $\\sqrt{s}$ = 13 TeV recorded in 2015. Two different searches are performed, one targeted for a spin-2 particle, using Randall-Sundrum graviton states as a benchmark model, and one optimized for a spin-0 particle. The most significant deviation from the background predictions is observed at a diphoton invariant mass around 750 GeV with local significances of 3.6 and 3.9 standard deviations in the searches optimized for a spin-2 and spin-0 particle, respectively. The global significances are estimated to be 1.8 and 2.0 standard deviations. The consistency between the data collected at 13 TeV and 8 TeV is also evaluated. Limits on the production cross-section for the two benchmark resonances are reported.

Efficient Topological Localization Using Global and Local Feature Matching

Directory of Open Access Journals (Sweden)

Junqiu Wang

2013-03-01

Full Text Available We present an efficient vision-based global topological localization approach in which different image features are used in a coarse-to-fine matching framework. Orientation Adjacency Coherence Histogram (OACH, a novel image feature, is proposed to improve the coarse localization. The coarse localization results are taken as inputs for the fine localization which is carried out by matching Harris-Laplace interest points characterized by the SIFT descriptor. The computation of OACHs and interest points is efficient due to the fact that these features are computed in an integrated process. The matching of local features is improved by using approximate nearest neighbor searching technique. We have implemented and tested the localization system in real environments. The experimental results demonstrate that our approach is efficient and reliable in both indoor and outdoor environments. This work has also been compared with previous works. The comparison results show that our approach has better performance with higher correct ratio and lower computational complexity.

Genetic causes of congenital brain malformations in epilepsy patients

DEFF Research Database (Denmark)

Møller, Rikke Steensbjerre

2008-01-01

The search for genetic causes of congenital brain malformations, severe epilepsy and mental retardation plays an important role in neuropediatrics and neurology. Disclosure of the aetiology of the intellectual disabilities, seizures and the underlying brain malformation may be of psychological va...... genes for developmental brain defects. The overall aim of the present study has been to identify new candidate genes or predisposing factors involved in congenital brain malformations in epilepsy patients.......The search for genetic causes of congenital brain malformations, severe epilepsy and mental retardation plays an important role in neuropediatrics and neurology. Disclosure of the aetiology of the intellectual disabilities, seizures and the underlying brain malformation may be of psychological...... value for the family, and it is essential for proper genetic counselling. The human brain is one of the most complex structures known, and probably many of the 25.000- 30.000 genes that comprise the human genome are involved in its development, which means that thousands of genes could be candidate...

Classification and learning using genetic algorithms applications in Bioinformatics and Web Intelligence

CERN Document Server

Bandyopadhyay, Sanghamitra

2007-01-01

This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. It examines how a search technique, the genetic algorithm, can be used for pattern classification mainly through approximating decision boundaries. Coverage also demonstrates the effectiveness of the genetic classifiers vis-à-vis several widely used classifiers, including neural networks.

Pareto Optimization of a Half Car Passive Suspension Model Using a Novel Multiobjective Heat Transfer Search Algorithm

Directory of Open Access Journals (Sweden)

Vimal Savsani

2017-01-01

Full Text Available Most of the modern multiobjective optimization algorithms are based on the search technique of genetic algorithms; however the search techniques of other recently developed metaheuristics are emerging topics among researchers. This paper proposes a novel multiobjective optimization algorithm named multiobjective heat transfer search (MOHTS algorithm, which is based on the search technique of heat transfer search (HTS algorithm. MOHTS employs the elitist nondominated sorting and crowding distance approach of an elitist based nondominated sorting genetic algorithm-II (NSGA-II for obtaining different nondomination levels and to preserve the diversity among the optimal set of solutions, respectively. The capability in yielding a Pareto front as close as possible to the true Pareto front of MOHTS has been tested on the multiobjective optimization problem of the vehicle suspension design, which has a set of five second-order linear ordinary differential equations. Half car passive ride model with two different sets of five objectives is employed for optimizing the suspension parameters using MOHTS and NSGA-II. The optimization studies demonstrate that MOHTS achieves the better nondominated Pareto front with the widespread (diveresed set of optimal solutions as compared to NSGA-II, and further the comparison of the extreme points of the obtained Pareto front reveals the dominance of MOHTS over NSGA-II, multiobjective uniform diversity genetic algorithm (MUGA, and combined PSO-GA based MOEA.

Hybrid Firefly Variants Algorithm for Localization Optimization in WSN

Directory of Open Access Journals (Sweden)

P. SrideviPonmalar

2017-01-01

Full Text Available Localization is one of the key issues in wireless sensor networks. Several algorithms and techniques have been introduced for localization. Localization is a procedural technique of estimating the sensor node location. In this paper, a novel three hybrid algorithms based on firefly is proposed for localization problem. Hybrid Genetic Algorithm-Firefly Localization Algorithm (GA-FFLA, Hybrid Differential Evolution-Firefly Localization Algorithm (DE-FFLA and Hybrid Particle Swarm Optimization -Firefly Localization Algorithm (PSO-FFLA are analyzed, designed and implemented to optimize the localization error. The localization algorithms are compared based on accuracy of estimation of location, time complexity and iterations required to achieve the accuracy. All the algorithms have hundred percent estimation accuracy but with variations in the number of firefliesr requirements, variation in time complexity and number of iteration requirements. Keywords: Localization; Genetic Algorithm; Differential Evolution; Particle Swarm Optimization

Communicating genetics and smoking through social media: are we there yet?

Science.gov (United States)

de Viron, Sylviane; Suggs, L Suzanne; Brand, Angela; Van Oyen, Herman

2013-09-09

Social media is a recent source of health information that could disseminate new scientific research, such as the genetics of smoking. The objectives were (1) to evaluate the availability of genetic information about smoking on different social media platforms (ie, YouTube, Facebook, and Twitter) and (2) to assess the type and the content of the information displayed on the social media as well as the profile of people publishing this information. We screened posts on YouTube, Facebook, and Twitter with the terms "smoking" and "genetic" at two time points (September 18, 2012, and May 7, 2013). The first 100 posts were reviewed for each media for the time points. Google was searched during Time 2 as an indicator of available information on the Web and the other social media that discussed genetics and smoking. The source of information, the country of the publisher, characteristics of the posts, and content of the posts were extracted. On YouTube, Facebook, and Twitter, 31, 0, and 84 posts, respectively, were included. Posts were mostly based on smoking-related diseases, referred to scientific publications, and were largely from the United States. From the Google search, most results were scientific databases. Six scientific publications referred to within the Google search were also retrieved on either YouTube or Twitter. Despite the importance of public understanding of smoking and genetics, and the high use of social media, little information on this topic is actually present on social media. Therefore, there is a need to monitor the information that is there and to evaluate the population's understanding of the information related to genetics and smoking that is displayed on social media.

Quantum Search and Beyond

Science.gov (United States)

2008-07-02

mechanics leads to non-local paradoxical effects (physicists sometimes call this "spooky action at a distance"). Spatial searching is the problem where...resource of EPR pairs, and that they use the states |0L〉 = |00〉+ |11〉 (|1L〉 = |00〉 − |11〉) to encode a logical zero (one). Note that each of them can set

Phenotypic variance explained by local ancestry in admixed African Americans.

Science.gov (United States)

Shriner, Daniel; Bentley, Amy R; Doumatey, Ayo P; Chen, Guanjie; Zhou, Jie; Adeyemo, Adebowale; Rotimi, Charles N

2015-01-01

We surveyed 26 quantitative traits and disease outcomes to understand the proportion of phenotypic variance explained by local ancestry in admixed African Americans. After inferring local ancestry as the number of African-ancestry chromosomes at hundreds of thousands of genotyped loci across all autosomes, we used a linear mixed effects model to estimate the variance explained by local ancestry in two large independent samples of unrelated African Americans. We found that local ancestry at major and polygenic effect genes can explain up to 20 and 8% of phenotypic variance, respectively. These findings provide evidence that most but not all additive genetic variance is explained by genetic markers undifferentiated by ancestry. These results also inform the proportion of health disparities due to genetic risk factors and the magnitude of error in association studies not controlling for local ancestry.

MIP Models and Hybrid Algorithms for Simultaneous Job Splitting and Scheduling on Unrelated Parallel Machines

Science.gov (United States)

Ozmutlu, H. Cenk

2014-01-01

We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms. PMID:24977204

MIP models and hybrid algorithms for simultaneous job splitting and scheduling on unrelated parallel machines.

Science.gov (United States)

Eroglu, Duygu Yilmaz; Ozmutlu, H Cenk

2014-01-01

We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms.

The search for local government autonomy in Nigeria: legal and ...

African Journals Online (AJOL)

This article examines the status of the local government under the tripartite governmental system in Nigeria that has been in operation since 1979. It reviews the various reforms that the administration of local government has gone through from the colonial era till 1999 when the extant Constitution of Nigeria came into force.

Exploration of Stellarator Configuration Space with Global Search Methods

International Nuclear Information System (INIS)

Mynick, H.E.; Pomphrey, N.; Ethier, S.

2001-01-01

An exploration of stellarator configuration space z for quasi-axisymmetric stellarator (QAS) designs is discussed, using methods which provide a more global view of that space. To this end, we have implemented a ''differential evolution'' (DE) search algorithm in an existing stellarator optimizer, which is much less prone to become trapped in local, suboptimal minima of the cost function chi than the local search methods used previously. This search algorithm is complemented by mapping studies of chi over z aimed at gaining insight into the results of the automated searches. We find that a wide range of the attractive QAS configurations previously found fall into a small number of classes, with each class corresponding to a basin of chi(z). We develop maps on which these earlier stellarators can be placed, the relations among them seen, and understanding gained into the physics differences between them. It is also found that, while still large, the region of z space containing practically realizable QAS configurations is much smaller than earlier supposed

Genetics Home Reference: atypical hemolytic-uremic syndrome

Science.gov (United States)

... Kidney Diseases: Kidney Failure: Choosing a Treatment That's Right for You Educational Resources (6 links) Disease InfoSearch: Hemolytic uremic syndrome, atypical MalaCards: genetic atypical hemolytic-uremic syndrome Merck Manual Consumer Version: Overview of Anemia Merck Manual Consumer Version: ...

Black-Box Search by Unbiased Variation

DEFF Research Database (Denmark)

Lehre, Per Kristian; Witt, Carsten

2012-01-01

The complexity theory for black-box algorithms, introduced by Droste, Jansen, and Wegener (Theory Comput. Syst. 39:525–544, 2006), describes common limits on the efficiency of a broad class of randomised search heuristics. There is an obvious trade-off between the generality of the black-box model...... and the strength of the bounds that can be proven in such a model. In particular, the original black-box model provides for well-known benchmark problems relatively small lower bounds, which seem unrealistic in certain cases and are typically not met by popular search heuristics.In this paper, we introduce a more...... restricted black-box model for optimisation of pseudo-Boolean functions which we claim captures the working principles of many randomised search heuristics including simulated annealing, evolutionary algorithms, randomised local search, and others. The key concept worked out is an unbiased variation operator...

A Molecular Genetic Basis Explaining Altered Bacterial Behavior in Space.

Directory of Open Access Journals (Sweden)

Luis Zea

Full Text Available Bacteria behave differently in space, as indicated by reports of reduced lag phase, higher final cell counts, enhanced biofilm formation, increased virulence, and reduced susceptibility to antibiotics. These phenomena are theorized, at least in part, to result from reduced mass transport in the local extracellular environment, where movement of molecules consumed and excreted by the cell is limited to diffusion in the absence of gravity-dependent convection. However, to date neither empirical nor computational approaches have been able to provide sufficient evidence to confirm this explanation. Molecular genetic analysis findings, conducted as part of a recent spaceflight investigation, support the proposed model. This investigation indicated an overexpression of genes associated with starvation, the search for alternative energy sources, increased metabolism, enhanced acetate production, and other systematic responses to acidity-all of which can be associated with reduced extracellular mass transport.

A Molecular Genetic Basis Explaining Altered Bacterial Behavior in Space

Science.gov (United States)

Prasad, Nripesh; Levy, Shawn E.; Stodieck, Louis; Jones, Angela; Shrestha, Shristi; Klaus, David

2016-01-01

Bacteria behave differently in space, as indicated by reports of reduced lag phase, higher final cell counts, enhanced biofilm formation, increased virulence, and reduced susceptibility to antibiotics. These phenomena are theorized, at least in part, to result from reduced mass transport in the local extracellular environment, where movement of molecules consumed and excreted by the cell is limited to diffusion in the absence of gravity-dependent convection. However, to date neither empirical nor computational approaches have been able to provide sufficient evidence to confirm this explanation. Molecular genetic analysis findings, conducted as part of a recent spaceflight investigation, support the proposed model. This investigation indicated an overexpression of genes associated with starvation, the search for alternative energy sources, increased metabolism, enhanced acetate production, and other systematic responses to acidity—all of which can be associated with reduced extracellular mass transport. PMID:27806055

Genome-Wide Search for Quantitative Trait Loci Controlling Important Plant and Flower Traits in Petunia Using an Interspecific Recombinant Inbred Population of Petunia axillaris and Petunia exserta.

Science.gov (United States)

Cao, Zhe; Guo, Yufang; Yang, Qian; He, Yanhong; Fetouh, Mohammed; Warner, Ryan M; Deng, Zhanao

2018-05-15

A major bottleneck in plant breeding has been the much limited genetic base and much reduced genetic diversity in domesticated, cultivated germplasm. Identification and utilization of favorable gene loci or alleles from wild or progenitor species can serve as an effective approach to increasing genetic diversity and breaking this bottleneck in plant breeding. This study was conducted to identify quantitative trait loci (QTL) in wild or progenitor petunia species that can be used to improve important horticultural traits in garden petunia. An F 7 recombinant inbred population derived between Petunia axillaris and P. exserta was phenotyped for plant height, plant spread, plant size, flower counts, flower diameter, flower length, and days to anthesis, in Florida in two consecutive years. Transgressive segregation was observed for all seven traits in both years. The broad-sense heritability estimates for the traits ranged from 0.20 (days to anthesis) to 0.62 (flower length). A genome-wide genetic linkage map consisting 368 single nucleotide polymorphism bins and extending over 277 cM was searched to identify QTL for these traits. Nineteen QTL were identified and localized to five linkage groups. Eleven of the loci were identified consistently in both years; several loci explained up to 34.0% and 24.1% of the phenotypic variance for flower length and flower diameter, respectively. Multiple loci controlling different traits are co-localized in four intervals in four linkage groups. These intervals contain desirable alleles that can be introgressed into commercial petunia germplasm to expand the genetic base and improve plant performance and flower characteristics in petunia. Copyright © 2018, G3: Genes, Genomes, Genetics.

Genetic diversity of four protected indigenous chicken breeds in ...

African Journals Online (AJOL)

joining method. Its topology reflects the general pattern of genetic differentiation among the four chicken breeds. The results also showed high genetic diversity and genetic variation among all the breeds. The information about the four local ...

Genetic algorithm based on qubits and quantum gates

International Nuclear Information System (INIS)

Silva, Joao Batista Rosa; Ramos, Rubens Viana

2003-01-01

Full text: Genetic algorithm, a computational technique based on the evolution of the species, in which a possible solution of the problem is coded in a binary string, called chromosome, has been used successfully in several kinds of problems, where the search of a minimal or a maximal value is necessary, even when local minima are present. A natural generalization of a binary string is a qubit string. Hence, it is possible to use the structure of a genetic algorithm having a sequence of qubits as a chromosome and using quantum operations in the reproduction in order to find the best solution in some problems of quantum information. For example, given a unitary matrix U what is the pair of qubits that, when applied at the input, provides the output state with maximal entanglement? In order to solve this problem, a population of chromosomes of two qubits was created. The crossover was performed applying the quantum gates CNOT and SWAP at the pair of qubits, while the mutation was performed applying the quantum gates Hadamard, Z and Not in a single qubit. The result was compared with a classical genetic algorithm used to solve the same problem. A hundred simulations using the same U matrix was performed. Both algorithms, hereafter named by CGA (classical) and QGA (using qu bits), reached good results close to 1 however, the number of generations needed to find the best result was lower for the QGA. Another problem where the QGA can be useful is in the calculation of the relative entropy of entanglement. We have tested our algorithm using 100 pure states chosen randomly. The stop criterion used was the error lower than 0.01. The main advantages of QGA are its good precision, robustness and very easy implementation. The main disadvantage is its low velocity, as happen for all kind of genetic algorithms. (author)

Born to fight? Genetics and combat sports

Directory of Open Access Journals (Sweden)

Emerson Franchini

2014-02-01

Full Text Available Recently, the influence of genetics on sports performance has received increased attention from many researchers. In combat sports, some investigations have also been conducted. This article’s main objective was to review the representation of specific gene polymorphisms in combat sports athletes compared to controls. The following databases were searched: PubMed, Web of Science and SportDiscus. The terms used in this search involved combat sports (boxing, karate, judo, mixed martial arts, taekwondo and wrestling, genes, genetics and candidate genes. Articles published until November 2013 were included if combat sports athletes were considered as a single group (i.e., not mixed with athletes of other sports. Seven studies were found, with two presenting no difference between combat sports athletes and controls, two presenting higher frequencies of candidate genes related to a more endurance-related profile compared to controls, and three where a more power-related gene overrepresentation was found in comparison to controls. Taken together, the initial studies about the genetic characteristics of combat sports athletes are controversial, which is probably due to the mixed (aerobic and anaerobic characteristic and to the multifactorial performance determinants of these sports.

Genetic studies and a search for molecular markers that are linked ...

African Journals Online (AJOL)

SERVER

Instead, linkage analysis resulted in the construction of a molecular marker linkage map consisting of 45 ..... This limits the application of this marker type, particularly in ... primer design when one uses RAPDs. .... Concepts of Genetics. Fourth.

A modified gravitational search algorithm based on a non-dominated sorting genetic approach for hydro-thermal-wind economic emission dispatching

International Nuclear Information System (INIS)

Chen, Fang; Zhou, Jianzhong; Wang, Chao; Li, Chunlong; Lu, Peng

2017-01-01

Wind power is a type of clean and renewable energy, and reasonable utilization of wind power is beneficial to environmental protection and economic development. Therefore, a short-term hydro-thermal-wind economic emission dispatching (SHTW-EED) problem is presented in this paper. The proposed problem aims to distribute the load among hydro, thermal and wind power units to simultaneously minimize economic cost and pollutant emission. To solve the SHTW-EED problem with complex constraints, a modified gravitational search algorithm based on the non-dominated sorting genetic algorithm-III (MGSA-NSGA-III) is proposed. In the proposed MGSA-NSGA-III, a non-dominated sorting approach, reference-point based selection mechanism and chaotic mutation strategy are applied to improve the evolutionary process of the original gravitational search algorithm (GSA) and maintain the distribution diversity of Pareto optimal solutions. Moreover, a parallel computing strategy is introduced to improve the computational efficiency. Finally, the proposed MGSA-NSGA-III is applied to a typical hydro-thermal-wind system to verify its feasibility and effectiveness. The simulation results indicate that the proposed algorithm can obtain low economic cost and small pollutant emission when dealing with the SHTW-EED problem. - Highlights: • A hybrid algorithm is proposed to handle hydro-thermal-wind power dispatching. • Several improvement strategies are applied to the algorithm. • A parallel computing strategy is applied to improve computational efficiency. • Two cases are analyzed to verify the efficiency of the optimize mode.

Genomic multiple sequence alignments: refinement using a genetic algorithm

Directory of Open Access Journals (Sweden)

Lefkowitz Elliot J

2005-08-01

Full Text Available Abstract Background Genomic sequence data cannot be fully appreciated in isolation. Comparative genomics – the practice of comparing genomic sequences from different species – plays an increasingly important role in understanding the genotypic differences between species that result in phenotypic differences as well as in revealing patterns of evolutionary relationships. One of the major challenges in comparative genomics is producing a high-quality alignment between two or more related genomic sequences. In recent years, a number of tools have been developed for aligning large genomic sequences. Most utilize heuristic strategies to identify a series of strong sequence similarities, which are then used as anchors to align the regions between the anchor points. The resulting alignment is globally correct, but in many cases is suboptimal locally. We describe a new program, GenAlignRefine, which improves the overall quality of global multiple alignments by using a genetic algorithm to improve local regions of alignment. Regions of low quality are identified, realigned using the program T-Coffee, and then refined using a genetic algorithm. Because a better COFFEE (Consistency based Objective Function For alignmEnt Evaluation score generally reflects greater alignment quality, the algorithm searches for an alignment that yields a better COFFEE score. To improve the intrinsic slowness of the genetic algorithm, GenAlignRefine was implemented as a parallel, cluster-based program. Results We tested the GenAlignRefine algorithm by running it on a Linux cluster to refine sequences from a simulation, as well as refine a multiple alignment of 15 Orthopoxvirus genomic sequences approximately 260,000 nucleotides in length that initially had been aligned by Multi-LAGAN. It took approximately 150 minutes for a 40-processor Linux cluster to optimize some 200 fuzzy (poorly aligned regions of the orthopoxvirus alignment. Overall sequence identity increased only

A Swarm Optimization Genetic Algorithm Based on Quantum-Behaved Particle Swarm Optimization.

Science.gov (United States)

Sun, Tao; Xu, Ming-Hai

2017-01-01

Quantum-behaved particle swarm optimization (QPSO) algorithm is a variant of the traditional particle swarm optimization (PSO). The QPSO that was originally developed for continuous search spaces outperforms the traditional PSO in search ability. This paper analyzes the main factors that impact the search ability of QPSO and converts the particle movement formula to the mutation condition by introducing the rejection region, thus proposing a new binary algorithm, named swarm optimization genetic algorithm (SOGA), because it is more like genetic algorithm (GA) than PSO in form. SOGA has crossover and mutation operator as GA but does not need to set the crossover and mutation probability, so it has fewer parameters to control. The proposed algorithm was tested with several nonlinear high-dimension functions in the binary search space, and the results were compared with those from BPSO, BQPSO, and GA. The experimental results show that SOGA is distinctly superior to the other three algorithms in terms of solution accuracy and convergence.

Journal of Genetics | Indian Academy of Sciences

Indian Academy of Sciences (India)

Journal of Genetics. Current Issue : Vol. 97, Issue 1 · Current Issue Volume 97 | Issue 1. March 2018. Home · Volumes & Issues · Online Resources · Special Issues · Forthcoming Articles · Search · Editorial Board · Information for Authors · Subscription ...

Journal of Genetics | Indian Academy of Sciences

Indian Academy of Sciences (India)

Journal of Genetics. Current Issue : Vol. 97, Issue 1. Current Issue Volume 97 | Issue 1. March 2018. Home · Volumes & Issues · Online Resources · Special Issues · Forthcoming Articles · Search · Editorial Board · Information for Authors · Subscription ...

Estimation of loss of genetic diversity in modern Japanese cultivars by comparison of diverse genetic resources in Asian pear (Pyrus spp.).

Science.gov (United States)

Nishio, Sogo; Takada, Norio; Saito, Toshihiro; Yamamoto, Toshiya; Iketani, Hiroyuki

2016-06-14

Pears (Pyrus spp.) are one of the most important fruit crops in temperate regions. Japanese pear breeding has been carried out for over 100 years, working to release new cultivars that have good fruit quality and other desirable traits. Local cultivar 'Nijisseiki' and its relatives, which have excellent fruit texture, have been repeatedly used as parents in the breeding program. This strategy has led to inbreeding within recent cultivars and selections. To avoid inbreeding depression, we need to clarify the degree of inbreeding among crossbred cultivars and to introgress genetic resources that are genetically different from modern cultivars and selections. The objective of the present study was to clarify the genetic relatedness between modern Japanese pear cultivars and diverse Asian pear genetic resources. We genotyped 207 diverse accessions by using 19 simple sequence repeat (SSR) markers. The heterozygosity and allelic richness of modern cultivars was obviously decreased compared with that of wild individuals, Chinese pear cultivars, and local cultivars. In analyses using Structure software, the 207 accessions were classified into four clusters (K = 4): one consisting primarily of wild individuals, one of Chinese pear cultivars, one of local cultivars from outside the Kanto region, and one containing both local cultivars from the Kanto region and crossbred cultivars. The results of principal coordinate analysis (PCoA) were similar to those from the Structure analysis. Wild individuals and Chinese pears appeared to be distinct from other groups, and crossbred cultivars became closer to 'Nijisseiki' as the year of release became more recent. Both Structure and PCoA results suggest that the modern Japanese pear cultivars are genetically close to local cultivars that originated in the Kanto region, and that the genotypes of the modern cultivars were markedly biased toward 'Nijisseiki'. Introgression of germplasm from Chinese pear and wild individuals that are

Systems Biology Genetic Approach Identifies Serotonin Pathway as a Possible Target for Obstructive Sleep Apnea: Results from a Literature Search Review

Directory of Open Access Journals (Sweden)

Ram Jagannathan

2017-01-01

Full Text Available Rationale. Overall validity of existing genetic biomarkers in the diagnosis of obstructive sleep apnea (OSA remains unclear. The objective of this systematic genetic study is to identify “novel” biomarkers for OSA using systems biology approach. Methods. Candidate genes for OSA were extracted from PubMed, MEDLINE, and Embase search engines and DisGeNET database. The gene ontology (GO analyses and candidate genes prioritization were performed using Enrichr tool. Genes pertaining to the top 10 pathways were extracted and used for Ingenuity Pathway Analysis. Results. In total, we have identified 153 genes. The top 10 pathways associated with OSA include (i serotonin receptor interaction, (ii pathways in cancer, (iii AGE-RAGE signaling in diabetes, (iv infectious diseases, (v serotonergic synapse, (vi inflammatory bowel disease, (vii HIF-1 signaling pathway, (viii PI3-AKT signaling pathway, (ix regulation lipolysis in adipocytes, and (x rheumatoid arthritis. After removing the overlapping genes, we have identified 23 candidate genes, out of which >30% of the genes were related to the genes involved in the serotonin pathway. Among these 4 serotonin receptors SLC6A4, HTR2C, HTR2A, and HTR1B were strongly associated with OSA. Conclusions. This preliminary report identifies several potential candidate genes associated with OSA and also describes the possible regulatory mechanisms.

Contributions from cognitive neuroscience to understanding functional mechanisms of visual search.

NARCIS (Netherlands)

Humphreys, G.W.; Hodsoll, J.; Olivers, C.N.L.; Yoon, E.Y.

2006-01-01

We argue that cognitive neuroscience can contribute not only information about the neural localization of processes underlying visual search, but also information about the functional nature of these processes. First we present an overview of recent work on whether search for form - colour

A binary mixed integer coded genetic algorithm for multi-objective optimization of nuclear research reactor fuel reloading

Energy Technology Data Exchange (ETDEWEB)

Binh, Do Quang [University of Technical Education Ho Chi Minh City (Viet Nam); Huy, Ngo Quang [University of Industry Ho Chi Minh City (Viet Nam); Hai, Nguyen Hoang [Centre for Research and Development of Radiation Technology, Ho Chi Minh City (Viet Nam)

2014-12-15

This paper presents a new approach based on a binary mixed integer coded genetic algorithm in conjunction with the weighted sum method for multi-objective optimization of fuel loading patterns for nuclear research reactors. The proposed genetic algorithm works with two types of chromosomes: binary and integer chromosomes, and consists of two types of genetic operators: one working on binary chromosomes and the other working on integer chromosomes. The algorithm automatically searches for the most suitable weighting factors of the weighting function and the optimal fuel loading patterns in the search process. Illustrative calculations are implemented for a research reactor type TRIGA MARK II loaded with the Russian VVR-M2 fuels. Results show that the proposed genetic algorithm can successfully search for both the best weighting factors and a set of approximate optimal loading patterns that maximize the effective multiplication factor and minimize the power peaking factor while satisfying operational and safety constraints for the research reactor.

A binary mixed integer coded genetic algorithm for multi-objective optimization of nuclear research reactor fuel reloading

International Nuclear Information System (INIS)

Binh, Do Quang; Huy, Ngo Quang; Hai, Nguyen Hoang

2014-01-01

This paper presents a new approach based on a binary mixed integer coded genetic algorithm in conjunction with the weighted sum method for multi-objective optimization of fuel loading patterns for nuclear research reactors. The proposed genetic algorithm works with two types of chromosomes: binary and integer chromosomes, and consists of two types of genetic operators: one working on binary chromosomes and the other working on integer chromosomes. The algorithm automatically searches for the most suitable weighting factors of the weighting function and the optimal fuel loading patterns in the search process. Illustrative calculations are implemented for a research reactor type TRIGA MARK II loaded with the Russian VVR-M2 fuels. Results show that the proposed genetic algorithm can successfully search for both the best weighting factors and a set of approximate optimal loading patterns that maximize the effective multiplication factor and minimize the power peaking factor while satisfying operational and safety constraints for the research reactor.

The control of male fertility by spermatid-specific factors: searching for contraceptive targets from spermatozoon's head to tail

Science.gov (United States)

Chen, Su-Ren; Batool, Aalia; Wang, Yu-Qian; Hao, Xiao-Xia; Chang, Chawn-Shang; Cheng, C Yan; Liu, Yi-Xun

2016-01-01

Male infertility due to abnormal spermatozoa has been reported in both animals and humans, but its pathogenic causes, including genetic abnormalities, remain largely unknown. On the other hand, contraceptive options for men are limited, and a specific, reversible and safe method of male contraception has been a long-standing quest in medicine. Some progress has recently been made in exploring the effects of spermatid-specifical genetic factors in controlling male fertility. A comprehensive search of PubMed for articles and reviews published in English before July 2016 was carried out using the search terms ‘spermiogenesis failure', ‘globozoospermia', ‘spermatid-specific', ‘acrosome', ‘infertile', ‘manchette', ‘sperm connecting piece', ‘sperm annulus', ‘sperm ADAMs', ‘flagellar abnormalities', ‘sperm motility loss', ‘sperm ion exchanger' and ‘contraceptive targets'. Importantly, we have opted to focus on articles regarding spermatid-specific factors. Genetic studies to define the structure and physiology of sperm have shown that spermatozoa appear to be one of the most promising contraceptive targets. Here we summarize how these spermatid-specific factors regulate spermiogenesis and categorize them according to their localization and function from spermatid head to tail (e.g., acrosome, manchette, head-tail conjunction, annulus, principal piece of tail). In addition, we emphatically introduce small-molecule contraceptives, such as BRDT and PPP3CC/PPP3R2, which are currently being developed to target spermatogenic-specific proteins. We suggest that blocking the differentiation of haploid germ cells, which rarely affects early spermatogenic cell types and the testicular microenvironment, is a better choice than spermatogenic-specific proteins. The studies described here provide valuable information regarding the genetic and molecular defects causing male mouse infertility to improve our understanding of the importance of spermatid

BLAST and FASTA similarity searching for multiple sequence alignment.

Science.gov (United States)

Pearson, William R

2014-01-01

BLAST, FASTA, and other similarity searching programs seek to identify homologous proteins and DNA sequences based on excess sequence similarity. If two sequences share much more similarity than expected by chance, the simplest explanation for the excess similarity is common ancestry-homology. The most effective similarity searches compare protein sequences, rather than DNA sequences, for sequences that encode proteins, and use expectation values, rather than percent identity, to infer homology. The BLAST and FASTA packages of sequence comparison programs provide programs for comparing protein and DNA sequences to protein databases (the most sensitive searches). Protein and translated-DNA comparisons to protein databases routinely allow evolutionary look back times from 1 to 2 billion years; DNA:DNA searches are 5-10-fold less sensitive. BLAST and FASTA can be run on popular web sites, but can also be downloaded and installed on local computers. With local installation, target databases can be customized for the sequence data being characterized. With today's very large protein databases, search sensitivity can also be improved by searching smaller comprehensive databases, for example, a complete protein set from an evolutionarily neighboring model organism. By default, BLAST and FASTA use scoring strategies target for distant evolutionary relationships; for comparisons involving short domains or queries, or searches that seek relatively close homologs (e.g. mouse-human), shallower scoring matrices will be more effective. Both BLAST and FASTA provide very accurate statistical estimates, which can be used to reliably identify protein sequences that diverged more than 2 billion years ago.

DataGenno: building a new tool to bridge molecular and clinical genetics

Directory of Open Access Journals (Sweden)

Fabricio F Costa

2011-03-01

Full Text Available Fabricio F Costa1,2, Luciano S Foly1, Marcelo P Coutinho11DataGenno Interactive Research Ltd., Itaperuna, Rio de Janeiro, Brazil; 2Cancer Biology and Epigenomics Program, Children's Memorial Research Center, Northwestern University's Feinberg School of Medicine, Chicago, IL, USAAbstract: Clinical genetics is one of the most challenging fields in medicine, with thousands of children born every year with congenital defects that have no satisfactory diagnosis. There are more than 6,000 known single-gene disorders that can cause birth defects or diseases in approximately 1 in every 200 births. Clinical and molecular information on genetic diseases and syndromes are widespread in the literature, and there are few databases combining this information. Therefore, it is very challenging for health care professionals and researchers to translate the latest advances in science and medicine into effective clinical interventions and new treatments. In order to overcome this obstacle and promote networking, we are building DataGenno, an online medical and scientific portal. DataGenno has been developed to be a source of information on genetic diseases and syndromes for the needs of all heath care professionals and researchers. Our database will be able to integrate both clinical and molecular aspects of genetic diseases in a fully interactive environment. DataGenno’s system already contains clinical and molecular information for 300 diseases, with approximately 6,000 signs and symptoms of these diseases in a database combined with a search engine. Our main goal is to cover all genetic diseases described to date, providing not only clinical information such as morphological and anatomical features but also the most comprehensive molecular genetics/genomics features and available testing information. We are also developing ways to connect DataGenno’s portal with Electronic Health Records in order to improve the efficiency of patient care. Additionally

Technical Update: Preimplantation Genetic Diagnosis and Screening.

Science.gov (United States)

Dahdouh, Elias M; Balayla, Jacques; Audibert, François; Wilson, R Douglas; Audibert, François; Brock, Jo-Ann; Campagnolo, Carla; Carroll, June; Chong, Karen; Gagnon, Alain; Johnson, Jo-Ann; MacDonald, William; Okun, Nanette; Pastuck, Melanie; Vallée-Pouliot, Karine

2015-05-01

To update and review the techniques and indications of preimplantation genetic diagnosis (PGD) and preimplantation genetic screening (PGS). Discussion about the genetic and technical aspects of preimplantation reproductive techniques, particularly those using new cytogenetic technologies and embryo-stage biopsy. Clinical outcomes of reproductive techniques following the use of PGD and PGS are included. This update does not discuss in detail the adverse outcomes that have been recorded in association with assisted reproductive technologies. Published literature was retrieved through searches of The Cochrane Library and Medline in April 2014 using appropriate controlled vocabulary (aneuploidy, blastocyst/physiology, genetic diseases, preimplantation diagnosis/methods, fertilization in vitro) and key words (e.g., preimplantation genetic diagnosis, preimplantation genetic screening, comprehensive chromosome screening, aCGH, SNP microarray, qPCR, and embryo selection). Results were restricted to systematic reviews, randomized controlled trials/controlled clinical trials, and observational studies published from 1990 to April 2014. There were no language restrictions. Searches were updated on a regular basis and incorporated in the update to January 2015. Additional publications were identified from the bibliographies of retrieved articles. Grey (unpublished) literature was identified through searching the websites of health technology assessment and health technology-related agencies, clinical practice guideline collections, clinical trial registries, and national and international medical specialty societies. The quality of evidence in this document was rated using the criteria described in the Report of the Canadian Task Force on Preventive Health Care. (Table 1) BENEFITS, HARMS, AND COSTS: This update will educate readers about new preimplantation genetic concepts, directions, and technologies. The major harms and costs identified are those of assisted reproductive

Managing genetic diversity and society needs

Directory of Open Access Journals (Sweden)

Arthur da Silva Mariante

2008-07-01

Full Text Available Most livestock are not indigenous to Brazil. Several animal species were considered domesticated in the pre-colonial period, since the indigenous people manage them as would be typical of European livestock production. For over 500 years there have been periodic introductions resulting in the wide range of genetic diversity that for centuries supported domestic animal production in the country. Even though these naturalized breeds have acquired adaptive traits after centuries of natural selection, they have been gradually replaced by exotic breeds, to such an extent, that today they are in danger of extinction To avoid further loss of this important genetic material, in 1983 Embrapa Genetic Resources and Biotechnology decided to include conservation of animal genetic resources among its priorities. In this paper we describe the effort to genetically characterize these populations, as a tool to ensure their genetic variability. To effectively save the threatened local breeds of livestock it is important to find a niche market for each one, reinserting them in production systems. They have to be utilized in order to be conserved. And there is no doubt that due to their adaptive traits, the Brazilian local breeds of livestock can play an important role in animal production, to meet society needs.

Efficient algorithms for multidimensional global optimization in genetic mapping of complex traits

Directory of Open Access Journals (Sweden)

Kajsa Ljungberg

2010-10-01

Full Text Available Kajsa Ljungberg1, Kateryna Mishchenko2, Sverker Holmgren11Division of Scientific Computing, Department of Information Technology, Uppsala University, Uppsala, Sweden; 2Department of Mathematics and Physics, Mälardalen University College, Västerås, SwedenAbstract: We present a two-phase strategy for optimizing a multidimensional, nonconvex function arising during genetic mapping of quantitative traits. Such traits are believed to be affected by multiple so called QTL, and searching for d QTL results in a d-dimensional optimization problem with a large number of local optima. We combine the global algorithm DIRECT with a number of local optimization methods that accelerate the final convergence, and adapt the algorithms to problem-specific features. We also improve the evaluation of the QTL mapping objective function to enable exploitation of the smoothness properties of the optimization landscape. Our best two-phase method is demonstrated to be accurate in at least six dimensions and up to ten times faster than currently used QTL mapping algorithms.Keywords: global optimization, QTL mapping, DIRECT 

IN SITU COMPARISON OF TREE-RING RESPONSES TO CLIMATE AND POPULATION GENETICS: THE NEED TO CONTROL FOR LOCAL CLIMATE AND SITE VARIABLES

Directory of Open Access Journals (Sweden)

Johann Mathias Housset

2016-10-01

Full Text Available Tree species responses to climate change will be greatly influenced by their evolutionary potential and their phenotypic plasticity. Investigating tree-rings responses to climate and population genetics at the regional scale is therefore crucial in assessing the tree behaviour to climate change. This study combined in situ dendroclimatology and population genetics over a latitudinal gradient and compared the variations between the two at the intra- and inter-population levels. This approach was applied on the northern marginal populations of Thuja occidentalis (eastern white-cedar in the Canadian boreal forest. We aimed first to assess the radial growth variability (response functional trait within populations across the gradient and to compare it with the genetic diversity (microsatellites. Second, we investigated the variability in the growth response to climate at the regional scale through the radial growth-climate relationships, and tested its correlation with environmental variables and population genetic structure. Model selection based on the Akaike Information Criteria revealed that the growth synchronicity between pairs of trees of a population covariates with both the genetic diversity of this population and the amount of precipitation (inverse correlation, although these variables only explained a small fraction of the observed variance. At the regional scale, variance partitioning and partial redundancy analysis indicate that the growth response to climate was greatly modulated by stand environmental variables, suggesting predominant plastic variations in growth-response to climate. Combining in situ dendroclimatology and population genetics is a promising way to investigate species’ response capacity to climate change in natural stands. We stress the need to control for local climate and site conditions effects on dendroclimatic response to climate to avoid misleading conclusions regarding the associations with genetic variables.

Locating hazardous gas leaks in the atmosphere via modified genetic, MCMC and particle swarm optimization algorithms

Science.gov (United States)

Wang, Ji; Zhang, Ru; Yan, Yuting; Dong, Xiaoqiang; Li, Jun Ming

2017-05-01

Hazardous gas leaks in the atmosphere can cause significant economic losses in addition to environmental hazards, such as fires and explosions. A three-stage hazardous gas leak source localization method was developed that uses movable and stationary gas concentration sensors. The method calculates a preliminary source inversion with a modified genetic algorithm (MGA) and has the potential to crossover with eliminated individuals from the population, following the selection of the best candidate. The method then determines a search zone using Markov Chain Monte Carlo (MCMC) sampling, utilizing a partial evaluation strategy. The leak source is then accurately localized using a modified guaranteed convergence particle swarm optimization algorithm with several bad-performing individuals, following selection of the most successful individual with dynamic updates. The first two stages are based on data collected by motionless sensors, and the last stage is based on data from movable robots with sensors. The measurement error adaptability and the effect of the leak source location were analyzed. The test results showed that this three-stage localization process can localize a leak source within 1.0 m of the source for different leak source locations, with measurement error standard deviation smaller than 2.0.

A meta-heuristic cuckoo search and eigen permutation approach for ...

Indian Academy of Sciences (India)

Akhilesh Kumar Gupta

2018-04-17

Apr 17, 2018 ... system (HOS) into a simplified lower order model of rea- sonable accuracy by ..... dom walk whose flight step length is dependent on a power law formula often ..... In: IEEE International Conference on Electric. Power and Energy ... hybrid cuckoo search and genetic algorithm for reliability– redundancy ...

A novel directional asymmetric sampling search algorithm for fast block-matching motion estimation

Science.gov (United States)

Li, Yue-e.; Wang, Qiang

2011-11-01

This paper proposes a novel directional asymmetric sampling search (DASS) algorithm for video compression. Making full use of the error information (block distortions) of the search patterns, eight different direction search patterns are designed for various situations. The strategy of local sampling search is employed for the search of big-motion vector. In order to further speed up the search, early termination strategy is adopted in procedure of DASS. Compared to conventional fast algorithms, the proposed method has the most satisfactory PSNR values for all test sequences.

Role of Genetics in the Etiology of Autistic Spectrum Disorder: Towards a Hierarchical Diagnostic Strategy.

Science.gov (United States)

Robert, Cyrille; Pasquier, Laurent; Cohen, David; Fradin, Mélanie; Canitano, Roberto; Damaj, Léna; Odent, Sylvie; Tordjman, Sylvie

2017-03-12

Progress in epidemiological, molecular and clinical genetics with the development of new techniques has improved knowledge on genetic syndromes associated with autism spectrum disorder (ASD). The objective of this article is to show the diversity of genetic disorders associated with ASD (based on an extensive review of single-gene disorders, copy number variants, and other chromosomal disorders), and consequently to propose a hierarchical diagnostic strategy with a stepwise evaluation, helping general practitioners/pediatricians and child psychiatrists to collaborate with geneticists and neuropediatricians, in order to search for genetic disorders associated with ASD. The first step is a clinical investigation involving: (i) a child psychiatric and psychological evaluation confirming autism diagnosis from different observational sources and assessing autism severity; (ii) a neuropediatric evaluation examining neurological symptoms and developmental milestones; and (iii) a genetic evaluation searching for dysmorphic features and malformations. The second step involves laboratory and if necessary neuroimaging and EEG studies oriented by clinical results based on clinical genetic and neuropediatric examinations. The identification of genetic disorders associated with ASD has practical implications for diagnostic strategies, early detection or prevention of co-morbidity, specific treatment and follow up, and genetic counseling.

Role of Genetics in the Etiology of Autistic Spectrum Disorder: Towards a Hierarchical Diagnostic Strategy

Science.gov (United States)

Robert, Cyrille; Pasquier, Laurent; Cohen, David; Fradin, Mélanie; Canitano, Roberto; Damaj, Léna; Odent, Sylvie; Tordjman, Sylvie

2017-01-01

Progress in epidemiological, molecular and clinical genetics with the development of new techniques has improved knowledge on genetic syndromes associated with autism spectrum disorder (ASD). The objective of this article is to show the diversity of genetic disorders associated with ASD (based on an extensive review of single-gene disorders, copy number variants, and other chromosomal disorders), and consequently to propose a hierarchical diagnostic strategy with a stepwise evaluation, helping general practitioners/pediatricians and child psychiatrists to collaborate with geneticists and neuropediatricians, in order to search for genetic disorders associated with ASD. The first step is a clinical investigation involving: (i) a child psychiatric and psychological evaluation confirming autism diagnosis from different observational sources and assessing autism severity; (ii) a neuropediatric evaluation examining neurological symptoms and developmental milestones; and (iii) a genetic evaluation searching for dysmorphic features and malformations. The second step involves laboratory and if necessary neuroimaging and EEG studies oriented by clinical results based on clinical genetic and neuropediatric examinations. The identification of genetic disorders associated with ASD has practical implications for diagnostic strategies, early detection or prevention of co-morbidity, specific treatment and follow up, and genetic counseling. PMID:28287497

Genetics and epigenetics of obesity.

Science.gov (United States)

Herrera, Blanca M; Keildson, Sarah; Lindgren, Cecilia M

2011-05-01

Obesity results from interactions between environmental and genetic factors. Despite a relatively high heritability of common, non-syndromic obesity (40-70%), the search for genetic variants contributing to susceptibility has been a challenging task. Genome wide association (GWA) studies have dramatically changed the pace of detection of common genetic susceptibility variants. To date, more than 40 genetic variants have been associated with obesity and fat distribution. However, since these variants do not fully explain the heritability of obesity, other forms of variation, such as epigenetics marks, must be considered. Epigenetic marks, or "imprinting", affect gene expression without actually changing the DNA sequence. Failures in imprinting are known to cause extreme forms of obesity (e.g. Prader-Willi syndrome), but have also been convincingly associated with susceptibility to obesity. Furthermore, environmental exposures during critical developmental periods can affect the profile of epigenetic marks and result in obesity. We review the most recent evidence for genetic and epigenetic mechanisms involved in the susceptibility and development of obesity. Only a comprehensive understanding of the underlying genetic and epigenetic mechanisms, and the metabolic processes they govern, will allow us to manage, and eventually prevent, obesity. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Near-Optimal Resource Allocation in Cooperative Cellular Networks Using Genetic Algorithms

OpenAIRE

Luo, Zihan; Armour, Simon; McGeehan, Joe

2015-01-01

This paper shows how a genetic algorithm can be used as a method of obtaining the near-optimal solution of the resource block scheduling problem in a cooperative cellular network. An exhaustive search is initially implementedto guarantee that the optimal result, in terms of maximizing the bandwidth efficiency of the overall network, is found, and then the genetic algorithm with the properly selected termination conditions is used in the same network. The simulation results show that the genet...

Search for heavy resonances decaying to top quarks

CERN Document Server

Anders, Christoph Falk; The ATLAS collaboration

2018-01-01

Searches for new resonances that decay either to pairs of top quarks or a top and a b-quark will be presented. The searches are performed with the ATLAS experiment at the LHC using proton-proton collision data collected in 2015 and 2016 with a centre-of-mass energy of 13 TeV. The invariant mass spectrum of hypothetical resonances are examined for local excesses or deficits that are inconsistent with the Standard Model prediction.

Search for heavy resonances decaying to top quarks

CERN Document Server

D'Auria, Saverio; The ATLAS collaboration

2017-01-01

Searches for new resonances that decay either to pairs of top quarks or a top and a b-quark will be presented. The searches are performed with the ATLAS experiment at the LHC using proton-proton collision data collected in 2015 and 2016 with a centre-of-mass energy of 13 TeV. The invariant mass spectrum of hypothetical resonances are examined for local excesses or deficits that are inconsistent with the Standard Model prediction.

Systematic Search for Gene-Gene Interaction Effect on Prostate Cancer Risk

Science.gov (United States)

2013-07-01

Systematic Search for Gene-Gene Interaction 5a. CONTRACT NUMBER Effect on Prostate Cancer Risk 5b. GRANT NUMBER W81XWH-09-1-0488 5c. PROGRAM...Supported by this grant ) 1. Tao S, Wang Z, Feng J, Hsu FC, Jin G, Kin ST, Zhang Z, Gronberg H, Zheng, SL, Isaacs WB, XU J, Sun J. A Genome-Wide Search for...order interactions among estrogen- metabolism genes in sporadic breast cancer. Am J Hum Genet, 69, 138-47. 48. Marchini, J., Donnelly, P. and Cardon