Multi-objective optimization of an industrial penicillin V bioreactor train using non-dominated sorting genetic algorithm.

Science.gov (United States)

Lee, Fook Choon; Rangaiah, Gade Pandu; Ray, Ajay Kumar

2007-10-15

Bulk of the penicillin produced is used as raw material for semi-synthetic penicillin (such as amoxicillin and ampicillin) and semi-synthetic cephalosporins (such as cephalexin and cefadroxil). In the present paper, an industrial penicillin V bioreactor train is optimized for multiple objectives simultaneously. An industrial train, comprising a bank of identical bioreactors, is run semi-continuously in a synchronous fashion. The fermentation taking place in a bioreactor is modeled using a morphologically structured mechanism. For multi-objective optimization for two and three objectives, the elitist non-dominated sorting genetic algorithm (NSGA-II) is chosen. Instead of a single optimum as in the traditional optimization, a wide range of optimal design and operating conditions depicting trade-offs of key performance indicators such as batch cycle time, yield, profit and penicillin concentration, is successfully obtained. The effects of design and operating variables on the optimal solutions are discussed in detail. Copyright 2007 Wiley Periodicals, Inc.

Single-gene testing combined with single nucleotide polymorphism microarray preimplantation genetic diagnosis for aneuploidy: a novel approach in optimizing pregnancy outcome.

Science.gov (United States)

Brezina, Paul R; Benner, Andrew; Rechitsky, Svetlana; Kuliev, Anver; Pomerantseva, Ekaterina; Pauling, Dana; Kearns, William G

2011-04-01

To describe a method of amplifying DNA from blastocyst trophectoderm cells (two or three cells) and simultaneously performing 23-chromosome single nucleotide polymorphism microarrays and single-gene preimplantation genetic diagnosis. Case report. IVF clinic and preimplantation genetic diagnostic centers. A 36-year-old woman, gravida 2, para 1011, and her husband who both were carriers of GM(1) gangliosidosis. The couple wished to proceed with microarray analysis for aneuploidy detection coupled with DNA sequencing for GM(1) gangliosidosis. An IVF cycle was performed. Ten blastocyst-stage embryos underwent trophectoderm biopsy. Twenty-three-chromosome microarray analysis for aneuploidy and specific DNA sequencing for GM(1) gangliosidosis mutations were performed. Viable pregnancy. After testing, elective single embryo transfer was performed followed by an intrauterine pregnancy with documented fetal cardiac activity by ultrasound. Twenty-three-chromosome microarray analysis for aneuploidy detection and single-gene evaluation via specific DNA sequencing and linkage analysis are used for preimplantation diagnosis for single-gene disorders and aneuploidy. Because of the minimal amount of genetic material obtained from the day 3 to 5 embryos (up to 6 pg), these modalities have been used in isolation of each other. The use of preimplantation genetic diagnosis for aneuploidy coupled with testing for single-gene disorders via trophectoderm biopsy is a novel approach to maximize pregnancy outcomes. Although further investigation is warranted, preimplantation genetic diagnosis for aneuploidy and single-gene testing seem destined to be used increasingly to optimize ultimate pregnancy success. Copyright © 2011 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Crystal Genetics, Inc.

Science.gov (United States)

Kermani, Bahram G

2016-07-01

Crystal Genetics, Inc. is an early-stage genetic test company, focused on achieving the highest possible clinical-grade accuracy and comprehensiveness for detecting germline (e.g., in hereditary cancer) and somatic (e.g., in early cancer detection) mutations. Crystal's mission is to significantly improve the health status of the population, by providing high accuracy, comprehensive, flexible and affordable genetic tests, primarily in cancer. Crystal's philosophy is that when it comes to detecting mutations that are strongly correlated with life-threatening diseases, the detection accuracy of every single mutation counts: a single false-positive error could cause severe anxiety for the patient. And, more importantly, a single false-negative error could potentially cost the patient's life. Crystal's objective is to eliminate both of these error types.

Genetic algorithms and fuzzy multiobjective optimization

CERN Document Server

Sakawa, Masatoshi

2002-01-01

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

Genetic Mapping in Mice Reveals the Involvement of Pcdh9 in Long-Term Social and Object Recognition and Sensorimotor Development.

Science.gov (United States)

Bruining, Hilgo; Matsui, Asuka; Oguro-Ando, Asami; Kahn, René S; Van't Spijker, Heleen M; Akkermans, Guus; Stiedl, Oliver; van Engeland, Herman; Koopmans, Bastijn; van Lith, Hein A; Oppelaar, Hugo; Tieland, Liselotte; Nonkes, Lourens J; Yagi, Takeshi; Kaneko, Ryosuke; Burbach, J Peter H; Yamamoto, Nobuhiko; Kas, Martien J

2015-10-01

Quantitative genetic analysis of basic mouse behaviors is a powerful tool to identify novel genetic phenotypes contributing to neurobehavioral disorders. Here, we analyzed genetic contributions to single-trial, long-term social and nonsocial recognition and subsequently studied the functional impact of an identified candidate gene on behavioral development. Genetic mapping of single-trial social recognition was performed in chromosome substitution strains, a sophisticated tool for detecting quantitative trait loci (QTL) of complex traits. Follow-up occurred by generating and testing knockout (KO) mice of a selected QTL candidate gene. Functional characterization of these mice was performed through behavioral and neurological assessments across developmental stages and analyses of gene expression and brain morphology. Chromosome substitution strain 14 mapping studies revealed an overlapping QTL related to long-term social and object recognition harboring Pcdh9, a cell-adhesion gene previously associated with autism spectrum disorder. Specific long-term social and object recognition deficits were confirmed in homozygous (KO) Pcdh9-deficient mice, while heterozygous mice only showed long-term social recognition impairment. The recognition deficits in KO mice were not associated with alterations in perception, multi-trial discrimination learning, sociability, behavioral flexibility, or fear memory. Rather, KO mice showed additional impairments in sensorimotor development reflected by early touch-evoked biting, rotarod performance, and sensory gating deficits. This profile emerged with structural changes in deep layers of sensory cortices, where Pcdh9 is selectively expressed. This behavior-to-gene study implicates Pcdh9 in cognitive functions required for long-term social and nonsocial recognition. This role is supported by the involvement of Pcdh9 in sensory cortex development and sensorimotor phenotypes. Copyright © 2015 Society of Biological Psychiatry. Published

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.

Reliability of a single objective measure in assessing sleepiness.

Science.gov (United States)

Sunwoo, Bernie Y; Jackson, Nicholas; Maislin, Greg; Gurubhagavatula, Indira; George, Charles F; Pack, Allan I

2012-01-01

To evaluate reliability of single objective tests in assessing sleepiness. Subjects who completed polysomnography underwent a 4-nap multiple sleep latency test (MSLT) the following day. Prior to each nap opportunity on MSLT, subjects performed the psychomotor vigilance test (PVT) and divided attention driving task (DADT). Results of single versus multiple test administrations were compared using the intraclass correlation coefficient (ICC) and adjusted for test administration order effects to explore time of day effects. Measures were explored as continuous and binary (i.e., impaired or not impaired). Community-based sample evaluated at a tertiary, university-based sleep center. 372 adult commercial vehicle operators oversampled for increased obstructive sleep apnea risk. N/A. AS CONTINUOUS MEASURES, ICC WERE AS FOLLOWS: MSLT 0.45, PVT median response time 0.69, PVT number of lapses 0.51, 10-min DADT tracking error 0.87, 20-min DADT tracking error 0.90. Based on binary outcomes, ICC were: MSLT 0.63, PVT number of lapses 0.85, 10-min DADT 0.95, 20-min DADT 0.96. Statistically significant time of day effects were seen in both the MSLT and PVT but not the DADT. Correlation between ESS and different objective tests was strongest for MSLT, range [-0.270 to -0.195] and persisted across all time points. Single DADT and PVT administrations are reliable measures of sleepiness. A single MSLT administration can reasonably discriminate individuals with MSL < 8 minutes. These results support the use of a single administration of some objective tests of sleepiness when performed under controlled conditions in routine clinical care.

Subjective versus objective risk in genetic counseling for hereditary breast and/or ovarian cancers

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Sperduti Isabella

2009-12-01

Full Text Available Abstract Background Despite the fact that genetic counseling in oncology provides information regarding objective risks, it can be found a contrast between the subjective and objective risk. The aims of this study were to evaluate the accuracy of the perceived risk compared to the objective risk estimated by the BRCApro computer model and to evaluate any associations between medical, demographic and psychological variables and the accuracy of risk perception. Methods 130 subjects were given medical-demographic file, Cancer and Genetic Risk Perception, Hospital Anxiety-Depression Scale. It was also computed an objective evaluation of the risk by the BRCApro model. Results The subjective risk was significantly higher than objective risk. The risk of tumour was overestimated by 56%, and the genetic risk by 67%. The subjects with less cancer affected relatives significantly overestimated their risk of being mutation carriers and made a more innacurate estimation than high risk subjects. Conclusion The description of this sample shows: general overestimation of the risk, inaccurate perception compared to BRCApro calculation and a more accurate estimation in those subjects with more cancer affected relatives (high risk subjects. No correlation was found between the levels of perception of risk and anxiety and depression. Based on our findings, it is worth pursuing improved communication strategies about the actual cancer and genetic risk, especially for subjects at "intermediate and slightly increased risk" of developing an hereditary breast and/or ovarian cancer or of being mutation carrier.

Feature Selection using Multi-objective Genetic Algorith m: A Hybrid Approach

OpenAIRE

Ahuja, Jyoti; GJUST - Guru Jambheshwar University of Sciecne and Technology; Ratnoo, Saroj Dahiya; GJUST - Guru Jambheshwar University of Sciecne and Technology

2015-01-01

Feature selection is an important pre-processing task for building accurate and comprehensible classification models. Several researchers have applied filter, wrapper or hybrid approaches using genetic algorithms which are good candidates for optimization problems that involve large search spaces like in the case of feature selection. Moreover, feature selection is an inherently multi-objective problem with many competing objectives involving size, predictive power and redundancy of the featu...

Multi-objective engineering design using preferences

Science.gov (United States)

Sanchis, J.; Martinez, M.; Blasco, X.

2008-03-01

System design is a complex task when design parameters have to satisy a number of specifications and objectives which often conflict with those of others. This challenging problem is called multi-objective optimization (MOO). The most common approximation consists in optimizing a single cost index with a weighted sum of objectives. However, once weights are chosen the solution does not guarantee the best compromise among specifications, because there is an infinite number of solutions. A new approach can be stated, based on the designer's experience regarding the required specifications and the associated problems. This valuable information can be translated into preferences for design objectives, and will lead the search process to the best solution in terms of these preferences. This article presents a new method, which enumerates these a priori objective preferences. As a result, a single objective is built automatically and no weight selection need be performed. Problems occuring because of the multimodal nature of the generated single cost index are managed with genetic algorithms (GAs).

Multi-objective optimization of an underwater compressed air energy storage system using genetic algorithm

International Nuclear Information System (INIS)

Cheung, Brian C.; Carriveau, Rupp; Ting, David S.K.

2014-01-01

This paper presents the findings from a multi-objective genetic algorithm optimization study on the design parameters of an underwater compressed air energy storage system (UWCAES). A 4 MWh UWCAES system was numerically simulated and its energy, exergy, and exergoeconomics were analysed. Optimal system configurations were determined that maximized the UWCAES system round-trip efficiency and operating profit, and minimized the cost rate of exergy destruction and capital expenditures. The optimal solutions obtained from the multi-objective optimization model formed a Pareto-optimal front, and a single preferred solution was selected using the pseudo-weight vector multi-criteria decision making approach. A sensitivity analysis was performed on interest rates to gauge its impact on preferred system designs. Results showed similar preferred system designs for all interest rates in the studied range. The round-trip efficiency and operating profit of the preferred system designs were approximately 68.5% and $53.5/cycle, respectively. The cost rate of the system increased with interest rates. - Highlights: • UWCAES system configurations were developed using multi-objective optimization. • System was optimized for energy efficiency, exergy, and exergoeconomics • Pareto-optimal solution surfaces were developed at different interest rates. • Similar preferred system configurations were found at all interest rates studied

A multi-objective genetic approach to domestic load scheduling in an energy management system

International Nuclear Information System (INIS)

Soares, Ana; Antunes, Carlos Henggeler; Oliveira, Carlos; Gomes, Álvaro

2014-01-01

In this paper a multi-objective genetic algorithm is used to solve a multi-objective model to optimize the time allocation of domestic loads within a planning period of 36 h, in a smart grid context. The management of controllable domestic loads is aimed at minimizing the electricity bill and the end-user’s dissatisfaction concerning two different aspects: the preferred time slots for load operation and the risk of interruption of the energy supply. The genetic algorithm is similar to the Elitist NSGA-II (Nondominated Sorting Genetic Algorithm II), in which some changes have been introduced to adapt it to the physical characteristics of the load scheduling problem and improve usability of results. The mathematical model explicitly considers economical, technical, quality of service and comfort aspects. Illustrative results are presented and the characteristics of different solutions are analyzed. - Highlights: • A genetic algorithm similar to the NSGA-II is used to solve a multi-objective model. • The optimized time allocation of domestic loads in a smart grid context is achieved. • A variable preference profile for the operation of the managed loads is included. • A safety margin is used to account for the quality of the energy services provided. • A non-dominated front with the solutions in the two-objective space is obtained

Linear and ultrafast nonlinear plasmonics of single nano-objects

Science.gov (United States)

Crut, Aurélien; Maioli, Paolo; Vallée, Fabrice; Del Fatti, Natalia

2017-03-01

Single-particle optical investigations have greatly improved our understanding of the fundamental properties of nano-objects, avoiding the spurious inhomogeneous effects that affect ensemble experiments. Correlation with high-resolution imaging techniques providing morphological information (e.g. electron microscopy) allows a quantitative interpretation of the optical measurements by means of analytical models and numerical simulations. In this topical review, we first briefly recall the principles underlying some of the most commonly used single-particle optical techniques: near-field, dark-field, spatial modulation and photothermal microscopies/spectroscopies. We then focus on the quantitative investigation of the surface plasmon resonance (SPR) of metallic nano-objects using linear and ultrafast optical techniques. While measured SPR positions and spectral areas are found in good agreement with predictions based on Maxwell’s equations, SPR widths are strongly influenced by quantum confinement (or, from a classical standpoint, surface-induced electron scattering) and, for small nano-objects, cannot be reproduced using the dielectric functions of bulk materials. Linear measurements on single nano-objects (silver nanospheres and gold nanorods) allow a quantification of the size and geometry dependences of these effects in confined metals. Addressing the ultrafast response of an individual nano-object is also a powerful tool to elucidate the physical mechanisms at the origin of their optical nonlinearities, and their electronic, vibrational and thermal relaxation processes. Experimental investigations of the dynamical response of gold nanorods are shown to be quantitatively modeled in terms of modifications of the metal dielectric function enhanced by plasmonic effects. Ultrafast spectroscopy can also be exploited to unveil hidden physical properties of more complex nanosystems. In this context, two-color femtosecond pump-probe experiments performed on individual

A probabilistic multi objective CLSC model with Genetic algorithm-ε_Constraint approach

Directory of Open Access Journals (Sweden)

Alireza TaheriMoghadam

2014-05-01

Full Text Available In this paper an uncertain multi objective closed-loop supply chain is developed. The first objective function is maximizing the total profit. The second objective function is minimizing the use of row materials. In the other word, the second objective function is maximizing the amount of remanufacturing and recycling. Genetic algorithm is used for optimization and for finding the pareto optimal line, Epsilon-constraint method is used. Finally a numerical example is solved with proposed approach and performance of the model is evaluated in different sizes. The results show that this approach is effective and useful for managerial decisions.

Optimal power system generation scheduling by multi-objective genetic algorithms with preferences

International Nuclear Information System (INIS)

Zio, E.; Baraldi, P.; Pedroni, N.

2009-01-01

Power system generation scheduling is an important issue both from the economical and environmental safety viewpoints. The scheduling involves decisions with regards to the units start-up and shut-down times and to the assignment of the load demands to the committed generating units for minimizing the system operation costs and the emission of atmospheric pollutants. As many other real-world engineering problems, power system generation scheduling involves multiple, conflicting optimization criteria for which there exists no single best solution with respect to all criteria considered. Multi-objective optimization algorithms, based on the principle of Pareto optimality, can then be designed to search for the set of nondominated scheduling solutions from which the decision-maker (DM) must a posteriori choose the preferred alternative. On the other hand, often, information is available a priori regarding the preference values of the DM with respect to the objectives. When possible, it is important to exploit this information during the search so as to focus it on the region of preference of the Pareto-optimal set. In this paper, ways are explored to use this preference information for driving a multi-objective genetic algorithm towards the preferential region of the Pareto-optimal front. Two methods are considered: the first one extends the concept of Pareto dominance by biasing the chromosome replacement step of the algorithm by means of numerical weights that express the DM' s preferences; the second one drives the search algorithm by changing the shape of the dominance region according to linear trade-off functions specified by the DM. The effectiveness of the proposed approaches is first compared on a case study of literature. Then, a nonlinear, constrained, two-objective power generation scheduling problem is effectively tackled

Optimization of Combined Thermal and Electrical Behavior of Power Converters Using Multi-Objective Genetic Algorithms

NARCIS (Netherlands)

Malyna, D.V.; Duarte, J.L.; Hendrix, M.A.M.; Horck, van F.B.M.

2007-01-01

A practical example of power electronic converter synthesis is presented, where a multi-objective genetic algorithm, namely non-dominated sorting genetic algorithm (NSGA-II) is used. The optimization algorithm takes an experimentally-derived thermal model for the converter into account. Experimental

Single-trial multisensory memories affect later auditory and visual object discrimination.

Science.gov (United States)

Thelen, Antonia; Talsma, Durk; Murray, Micah M

2015-05-01

Multisensory memory traces established via single-trial exposures can impact subsequent visual object recognition. This impact appears to depend on the meaningfulness of the initial multisensory pairing, implying that multisensory exposures establish distinct object representations that are accessible during later unisensory processing. Multisensory contexts may be particularly effective in influencing auditory discrimination, given the purportedly inferior recognition memory in this sensory modality. The possibility of this generalization and the equivalence of effects when memory discrimination was being performed in the visual vs. auditory modality were at the focus of this study. First, we demonstrate that visual object discrimination is affected by the context of prior multisensory encounters, replicating and extending previous findings by controlling for the probability of multisensory contexts during initial as well as repeated object presentations. Second, we provide the first evidence that single-trial multisensory memories impact subsequent auditory object discrimination. Auditory object discrimination was enhanced when initial presentations entailed semantically congruent multisensory pairs and was impaired after semantically incongruent multisensory encounters, compared to sounds that had been encountered only in a unisensory manner. Third, the impact of single-trial multisensory memories upon unisensory object discrimination was greater when the task was performed in the auditory vs. visual modality. Fourth, there was no evidence for correlation between effects of past multisensory experiences on visual and auditory processing, suggestive of largely independent object processing mechanisms between modalities. We discuss these findings in terms of the conceptual short term memory (CSTM) model and predictive coding. Our results suggest differential recruitment and modulation of conceptual memory networks according to the sensory task at hand. Copyright �

3D high- and super-resolution imaging using single-objective SPIM.

Science.gov (United States)

Galland, Remi; Grenci, Gianluca; Aravind, Ajay; Viasnoff, Virgile; Studer, Vincent; Sibarita, Jean-Baptiste

2015-07-01

Single-objective selective-plane illumination microscopy (soSPIM) is achieved with micromirrored cavities combined with a laser beam-steering unit installed on a standard inverted microscope. The illumination and detection are done through the same objective. soSPIM can be used with standard sample preparations and features high background rejection and efficient photon collection, allowing for 3D single-molecule-based super-resolution imaging of whole cells or cell aggregates. Using larger mirrors enabled us to broaden the capabilities of our system to image Drosophila embryos.

Methodology for single-cell genetic analysis of planktonic foraminifera for studies of protist diversity and evolution

Directory of Open Access Journals (Sweden)

Agnes Katharina Maria Weiner

2016-12-01

Full Text Available Single-cell genetic analysis is an essential method to investigate the biodiversity and evolutionary ecology of marine protists. In protist groups that do not reproduce under laboratory conditions, this approach provides the only means to directly associate molecular sequences with cell morphology. The resulting unambiguous taxonomic identification of the DNA sequences is a prerequisite for barcoding and analyses of environmental metagenomic data. Extensive single-cell genetic studies have been carried out on planktonic foraminifera over the past 20 years to elucidate their phylogeny, cryptic diversity, biogeography and the relationship between genetic and morphological variability. In the course of these investigations, it has become evident that genetic analysis at the individual specimen level is confronted by innumerable challenges ranging from the negligible amount of DNA present in the single cell to the substantial amount of DNA contamination introduced by endosymbionts or food particles. Consequently, a range of methods has been developed and applied throughout the years for the genetic analysis of planktonic foraminifera in order to enhance DNA amplification success rates. Yet, the description of these methods in the literature rarely occurred with equivalent levels of detail and the different approaches have never been compared in terms of their efficiency and reproducibility. Here, aiming at a standardization of methods, we provide a comprehensive review of all methods that have been employed for the single-cell genetic analysis of planktonic foraminifera. We compile data on success rates of DNA amplification and use these to evaluate the effects of key parameters associated with the methods of sample collection, storage and extraction of single-cell DNA. We show that the chosen methods influence the success rates of single-cell genetic studies, but the differences between them are not sufficient to hinder comparisons between studies

Multi-objective optimization of water supply network rehabilitation with non-dominated sorting Genetic Algorithm-Ⅱ

Institute of Scientific and Technical Information of China (English)

Xi JIN; Jie ZHANG; Jin-liang GAO; Wen-yan WU

2008-01-01

Through the transformation of hydraulic constraints into the objective functions associated with a water supply network rehabilitation problem, a non-dominated sorting Genetic Aigorithm-Ⅱ (NSGA-Ⅱ) can be used to solve the altered multi-objective optimization model. The introduction of NSGA-Ⅱ into water supply network optimal rehabilitation problem solves the conflict between one fitness value of standard genetic algorithm (SGA) and multi-objectives of rehabilitation problem. And the uncertainties brought by using weight coefficients or punish functions in conventional methods are controlled. And also by introduction of artificial inducement mutation (AIM) operation, the convergence speed of population is accelerated; this operation not only improves the convergence speed, but also improves the rationality and feasibility of solutions.

Multi-objective genetic optimization of linear construction projects

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Fatma A. Agrama

2012-08-01

Full Text Available In the real world, the majority cases of optimization problems, met by engineers, are composed of several conflicting objectives. This paper presents an approach for a multi-objective optimization model for scheduling linear construction projects. Linear construction projects have many identical units wherein activities repeat from one unit to another. Highway, pipeline, and tunnels are good examples that exhibit repetitive characteristics. These projects represent a large portion of the construction industry. The present model enables construction planners to generate optimal/near-optimal construction plans that minimize project duration, total work interruptions, and total number of crews. Each of these plans identifies, from a set of feasible alternatives, optimal crew synchronization for each activity and activity interruptions at each unit. This model satisfies the following aspects: (1 it is based on the line of balance technique; (2 it considers non-serial typical activities networks with finish–start relationship and both lag or overlap time between activities is allowed; (3 it utilizes a multi-objective genetic algorithms approach; (4 it is developed as a spreadsheet template that is easy to use. Details of the model with visual charts are presented. An application example is analyzed to illustrate the use of the model and demonstrate its capabilities in optimizing the scheduling of linear construction projects.

Improving Genetic Evaluation of Litter Size Using a Single-step Model

DEFF Research Database (Denmark)

Guo, Xiangyu; Christensen, Ole Fredslund; Ostersen, Tage

A recently developed single-step method allows genetic evaluation based on information from phenotypes, pedigree and markers simultaneously. This paper compared reliabilities of predicted breeding values obtained from single-step method and the traditional pedigree-based method for two litter size...... traits, total number of piglets born (TNB), and litter size at five days after birth (Ls 5) in Danish Landrace and Yorkshire pigs. The results showed that the single-step method combining phenotypic and genotypic information provided more accurate predictions than the pedigree-based method, not only...

Makeup of the genetic correlation between milk production traits using genome-wide single nucleotide polymorphism information.

Science.gov (United States)

van Binsbergen, R; Veerkamp, R F; Calus, M P L

2012-04-01

The correlated responses between traits may differ depending on the makeup of genetic covariances, and may differ from the predictions of polygenic covariances. Therefore, the objective of the present study was to investigate the makeup of the genetic covariances between the well-studied traits: milk yield, fat yield, protein yield, and their percentages in more detail. Phenotypic records of 1,737 heifers of research farms in 4 different countries were used after homogenizing and adjusting for management effects. All cows had a genotype for 37,590 single nucleotide polymorphisms (SNP). A bayesian stochastic search variable selection model was used to estimate the SNP effects for each trait. About 0.5 to 1.0% of the SNP had a significant effect on 1 or more traits; however, the SNP without a significant effect explained most of the genetic variances and covariances of the traits. Single nucleotide polymorphism correlations differed from the polygenic correlations, but only 10 regions were found with an effect on multiple traits; in 1 of these regions the DGAT1 gene was previously reported with an effect on multiple traits. This region explained up to 41% of the variances of 4 traits and explained a major part of the correlation between fat yield and fat percentage and contributes to asymmetry in correlated response between fat yield and fat percentage. Overall, for the traits in this study, the infinitesimal model is expected to be sufficient for the estimation of the variances and covariances. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Removing defocused objects from single focal plane scans of cytological slides

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David Friedrich

2016-01-01

Full Text Available Background: Virtual microscopy and automated processing of cytological slides are more challenging compared to histological slides. Since cytological slides exhibit a three-dimensional surface and the required microscope objectives with high resolution have a low depth of field, these cannot capture all objects of a single field of view in focus. One solution would be to scan multiple focal planes; however, the increase in processing time and storage requirements are often prohibitive for clinical routine. Materials and Methods: In this paper, we show that it is a reasonable trade-off to scan a single focal plane and automatically reject defocused objects from the analysis. To this end, we have developed machine learning solutions for the automated identification of defocused objects. Our approach includes creating novel features, systematically optimizing their parameters, selecting adequate classifier algorithms, and identifying the correct decision boundary between focused and defocused objects. We validated our approach for computer-assisted DNA image cytometry. Results and Conclusions: We reach an overall sensitivity of 96.08% and a specificity of 99.63% for identifying defocused objects. Applied on ninety cytological slides, the developed classifiers automatically removed 2.50% of the objects acquired during scanning, which otherwise would have interfered the examination. Even if not all objects are acquired in focus, computer-assisted DNA image cytometry still identified more diagnostically or prognostically relevant objects compared to manual DNA image cytometry. At the same time, the workload for the expert is reduced dramatically.

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

Science.gov (United States)

Rai, Man Mohan

2006-01-01

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more

Multi-objective optimization in systematic conservation planning and the representation of genetic variability among populations.

Science.gov (United States)

Schlottfeldt, S; Walter, M E M T; Carvalho, A C P L F; Soares, T N; Telles, M P C; Loyola, R D; Diniz-Filho, J A F

2015-06-18

Biodiversity crises have led scientists to develop strategies for achieving conservation goals. The underlying principle of these strategies lies in systematic conservation planning (SCP), in which there are at least 2 conflicting objectives, making it a good candidate for multi-objective optimization. Although SCP is typically applied at the species level (or hierarchically higher), it can be used at lower hierarchical levels, such as using alleles as basic units for analysis, for conservation genetics. Here, we propose a method of SCP using a multi-objective approach. We used non-dominated sorting genetic algorithm II in order to identify the smallest set of local populations of Dipteryx alata (baru) (a Brazilian Cerrado species) for conservation, representing the known genetic diversity and using allele frequency information associated with heterozygosity and Hardy-Weinberg equilibrium. We worked in 3 variations for the problem. First, we reproduced a previous experiment, but using a multi-objective approach. We found that the smallest set of populations needed to represent all alleles under study was 7, corroborating the results of the previous study, but with more distinct solutions. In the 2nd and 3rd variations, we performed simultaneous optimization of 4 and 5 objectives, respectively. We found similar but refined results for 7 populations, and a larger portfolio considering intra-specific diversity and persistence with populations ranging from 8-22. This is the first study to apply multi-objective algorithms to an SCP problem using alleles at the population level as basic units for analysis.

Genetic influence on prolonged gestation

DEFF Research Database (Denmark)

Laursen, Maja; Bille, Camilla; Olesen, Annette Wind

2004-01-01

OBJECTIVE: The purpose of this study was to test a possible genetic component to prolonged gestation. STUDY DESIGN: The gestational duration of single, first pregnancies by both female and male twins was obtained by linking the Danish Twin Registry, The Danish Civil Registration System, and the D...... factors. CONCLUSION: Maternal genes influence prolonged gestation. However, a substantial paternal genetic influence through the fetus was not found....

Personalized Genetic Risk Counseling to Motivate Diabetes Prevention

OpenAIRE

Grant, Richard W.; O’Brien, Kelsey E.; Waxler, Jessica L.; Vassy, Jason L.; Delahanty, Linda M.; Bissett, Laurie G.; Green, Robert C.; Stember, Katherine G.; Guiducci, Candace; Park, Elyse R.; Florez, Jose C.; Meigs, James B.

2012-01-01

OBJECTIVE To examine whether diabetes genetic risk testing and counseling can improve diabetes prevention behaviors. RESEARCH DESIGN AND METHODS We conducted a randomized trial of diabetes genetic risk counseling among overweight patients at increased phenotypic risk for type 2 diabetes. Participants were randomly allocated to genetic testing versus no testing. Genetic risk was calculated by summing 36 single nucleotide polymorphisms associated with type 2 diabetes. Participants in the top an...

Validity of single-cycle objective functions for multicycle reload design optimization

International Nuclear Information System (INIS)

Kropaczek, D.J.; McElroy, J.; Turinsky, P.J.

1993-01-01

Beyond the equilibrium cycle scoping calculations used for determining numbers of feed assemblies and enrichment estimates, multicycle reload design currently consists of stagewise optimization of single-cycle core loading patterns, typically extending over a short-term planning horizon of perhaps three reload cycles. Particularly in transition cycles, however, optimizing a loading pattern over a single cycle for a stated objective, such as minimum core leakage, may have an adverse impact on subsequent cycles. The penalties paid may be in the form of reduced thermal margin or an increase in feed enrichment due to insufficient reactivity carryover from the open-quotes optimizedclose quotes cycle. In view of current practices, a study was performed that examined the behavior of the loading pattern as a function of the objective functions selected as implemented in the stagewise optimization of single-cycle core loading patterns from initial transition cycle through equilibrium using the FORMOSA-P code. The objective functions studied were region average discharge burnup maximization (with enrichment search) and feed enrichment minimization. It is noted at the beginning that the maximization of region average discharge has no meaning for the equilibrium cycle because region average discharge burnup is explicitly set by the feed size and cycle length independent of the loading pattern. In the nonequilibrium cycle, however, it was reasoned that this objective would provide the maximum reactivity carryover throughout the transition and thus have a direct effect on minimizing the multicycle levelized fuel cost

Multi-objective compared to single-objective optimization with application to model validation and uncertainty quantification

Energy Technology Data Exchange (ETDEWEB)

Schulze-Riegert, R.; Krosche, M.; Stekolschikov, K. [Scandpower Petroleum Technology GmbH, Hamburg (Germany); Fahimuddin, A. [Technische Univ. Braunschweig (Germany)

2007-09-13

History Matching in Reservoir Simulation, well location and production optimization etc. is generally a multi-objective optimization problem. The problem statement of history matching for a realistic field case includes many field and well measurements in time and type, e.g. pressure measurements, fluid rates, events such as water and gas break-throughs, etc. Uncertainty parameters modified as part of the history matching process have varying impact on the improvement of the match criteria. Competing match criteria often reduce the likelihood of finding an acceptable history match. It is an engineering challenge in manual history matching processes to identify competing objectives and to implement the changes required in the simulation model. In production optimization or scenario optimization the focus on one key optimization criterion such as NPV limits the identification of alternatives and potential opportunities, since multiple objectives are summarized in a predefined global objective formulation. Previous works primarily focus on a specific optimization method. Few works actually concentrate on the objective formulation and multi-objective optimization schemes have not yet been applied to reservoir simulations. This paper presents a multi-objective optimization approach applicable to reservoir simulation. It addresses the problem of multi-objective criteria in a history matching study and presents analysis techniques identifying competing match criteria. A Pareto-Optimizer is discussed and the implementation of that multi-objective optimization scheme is applied to a case study. Results are compared to a single-objective optimization method. (orig.)

Embryo genome profiling by single-cell sequencing for preimplantation genetic diagnosis in a β-thalassemia family

DEFF Research Database (Denmark)

Xu, Yanwen; Chen, Shengpei; Yin, Xuyang

2015-01-01

for a β-thalassemia-carrier couple to have a healthy second baby. We carried out sequencing for single blastomere cells and the family trio and further developed the analysis pipeline, including recovery of the missing alleles, removal of the majority of errors, and phasing of the embryonic genome...... leukocyte antigen matching tests. CONCLUSIONS: This retrospective study in a β-thalassemia family demonstrates a method for embryo genome recovery through single-cell sequencing, which permits detection of genetic variations in preimplantation genetic diagnosis. It shows the potential of single...

Genetic mapping in mice reveals the involvement of Pcdh9 in long-term social and object recognition and sensorimotor development

NARCIS (Netherlands)

Bruining, Hilgo; Matsui, Asuka; Oguro-Ando, Asami; Kahn, René S.; Van'T Spijker, Heleen M.; Akkermans, Guus; Stiedl, Oliver; Van Engeland, Herman; Koopmans, Bastijn; Van Lith, Hein A.; Oppelaar, Hugo; Tieland, Liselotte; Nonkes, Lourens J.; Yagi, Takeshi; Kaneko, Ryosuke; Burbach, J. Peter H; Yamamoto, Nobuhiko; Kas, Martien J.

2015-01-01

Background Quantitative genetic analysis of basic mouse behaviors is a powerful tool to identify novel genetic phenotypes contributing to neurobehavioral disorders. Here, we analyzed genetic contributions to single-trial, long-term social and nonsocial recognition and subsequently studied the

Genetic Mapping in Mice Reveals the Involvement of Pcdh9 in Long-Term Social and Object Recognition and Sensorimotor Development

NARCIS (Netherlands)

Bruining, Hilgo; Matsui, Asuka; Oguro-Ando, Asami; Kahn, René S; Van't Spijker, Heleen M; Akkermans, Guus; Stiedl, Oliver; van Engeland, Herman; Koopmans, Bastijn; van Lith, Hein A; Oppelaar, Hugo; Tieland, Liselotte; Nonkes, Lourens J; Yagi, Takeshi; Kaneko, Ryosuke; Burbach, J Peter H; Yamamoto, Nobuhiko; Kas, Martien J

2015-01-01

BACKGROUND: Quantitative genetic analysis of basic mouse behaviors is a powerful tool to identify novel genetic phenotypes contributing to neurobehavioral disorders. Here, we analyzed genetic contributions to single-trial, long-term social and nonsocial recognition and subsequently studied the

Multi-objective optimal design of sandwich panels using a genetic algorithm

Science.gov (United States)

Xu, Xiaomei; Jiang, Yiping; Pueh Lee, Heow

2017-10-01

In this study, an optimization problem concerning sandwich panels is investigated by simultaneously considering the two objectives of minimizing the panel mass and maximizing the sound insulation performance. First of all, the acoustic model of sandwich panels is discussed, which provides a foundation to model the acoustic objective function. Then the optimization problem is formulated as a bi-objective programming model, and a solution algorithm based on the non-dominated sorting genetic algorithm II (NSGA-II) is provided to solve the proposed model. Finally, taking an example of a sandwich panel that is expected to be used as an automotive roof panel, numerical experiments are carried out to verify the effectiveness of the proposed model and solution algorithm. Numerical results demonstrate in detail how the core material, geometric constraints and mechanical constraints impact the optimal designs of sandwich panels.

Identifying groups of critical edges in a realistic electrical network by multi-objective genetic algorithms

International Nuclear Information System (INIS)

Zio, E.; Golea, L.R.; Rocco S, C.M.

2012-01-01

In this paper, an analysis of the vulnerability of the Italian high-voltage (380 kV) electrical transmission network (HVIET) is carried out for the identification of the groups of links (or edges, or arcs) most critical considering the network structure and flow. Betweenness centrality and network connection efficiency variations are considered as measures of the importance of the network links. The search of the most critical ones is carried out within a multi-objective optimization problem aimed at the maximization of the importance of the groups and minimization of their dimension. The problem is solved using a genetic algorithm. The analysis is based only on information on the topology of the network and leads to the identification of the most important single component, couples of components, triplets and so forth. The comparison of the results obtained with those reported by previous analyses indicates that the proposed approach provides useful complementary information.

Compatibility of pedigree-based and marker-based relationship matrices for single-step genetic evaluation

DEFF Research Database (Denmark)

Christensen, Ole Fredslund

2012-01-01

Single-step methods for genomic prediction have recently become popular because they are conceptually simple and in practice such a method can completely replace a pedigree-based method for routine genetic evaluation. An issue with single-step methods is compatibility between the marker-based rel...

Combining features from ERP components in single-trial EEG for discriminating four-category visual objects

Science.gov (United States)

Wang, Changming; Xiong, Shi; Hu, Xiaoping; Yao, Li; Zhang, Jiacai

2012-10-01

Categorization of images containing visual objects can be successfully recognized using single-trial electroencephalograph (EEG) measured when subjects view images. Previous studies have shown that task-related information contained in event-related potential (ERP) components could discriminate two or three categories of object images. In this study, we investigated whether four categories of objects (human faces, buildings, cats and cars) could be mutually discriminated using single-trial EEG data. Here, the EEG waveforms acquired while subjects were viewing four categories of object images were segmented into several ERP components (P1, N1, P2a and P2b), and then Fisher linear discriminant analysis (Fisher-LDA) was used to classify EEG features extracted from ERP components. Firstly, we compared the classification results using features from single ERP components, and identified that the N1 component achieved the highest classification accuracies. Secondly, we discriminated four categories of objects using combining features from multiple ERP components, and showed that combination of ERP components improved four-category classification accuracies by utilizing the complementarity of discriminative information in ERP components. These findings confirmed that four categories of object images could be discriminated with single-trial EEG and could direct us to select effective EEG features for classifying visual objects.

Multi-objective genetic algorithm based innovative wind farm layout optimization method

International Nuclear Information System (INIS)

Chen, Ying; Li, Hua; He, Bang; Wang, Pengcheng; Jin, Kai

2015-01-01

Highlights: • Innovative optimization procedures for both regular and irregular shape wind farm. • Using real wind condition and commercial wind turbine parameters. • Using multiple-objective genetic algorithm optimization method. • Optimize the selection of different wind turbine types and their hub heights. - Abstract: Layout optimization has become one of the critical approaches to increase power output and decrease total cost of a wind farm. Previous researches have applied intelligent algorithms to optimizing the wind farm layout. However, those wind conditions used in most of previous research are simplified and not accurate enough to match the real world wind conditions. In this paper, the authors propose an innovative optimization method based on multi-objective genetic algorithm, and test it with real wind condition and commercial wind turbine parameters. Four case studies are conducted to investigate the number of wind turbines needed in the given wind farm. Different cost models are also considered in the case studies. The results clearly demonstrate that the new method is able to optimize the layout of a given wind farm with real commercial data and wind conditions in both regular and irregular shapes, and achieve a better result by selecting different type and hub height wind turbines.

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.

A versatile nanotechnology to connect individual nano-objects for the fabrication of hybrid single-electron devices

International Nuclear Information System (INIS)

Bernand-Mantel, A; Bouzehouane, K; Seneor, P; Fusil, S; Deranlot, C; Petroff, F; Fert, A; Brenac, A; Notin, L; Morel, R

2010-01-01

We report on the high yield connection of single nano-objects as small as a few nanometres in diameter to separately elaborated metallic electrodes, using a 'table-top' nanotechnology. Single-electron transport measurements validate that transport occurs through a single nano-object. The vertical geometry of the device natively allows an independent choice of materials for each electrode and the nano-object. In addition ferromagnetic materials can be used without encountering oxidation problems. The possibility of elaborating such hybrid nanodevices opens new routes for the democratization of spintronic studies in low dimensions.

Combinations of Genetic Data Present in Bipolar Patients, but Absent in Control Persons

DEFF Research Database (Denmark)

Mellerup, E; Andreassen, OA; Bennike, B.

2015-01-01

The main objective of the study was to find combinations of genetic variants significantly associated with bipolar disorder. In a previous study of bipolar disorder, combinations of three single nucleotide polymorphism (SNP) genotypes taken from 803 SNPs were analyzed, and four clusters of combin......The main objective of the study was to find combinations of genetic variants significantly associated with bipolar disorder. In a previous study of bipolar disorder, combinations of three single nucleotide polymorphism (SNP) genotypes taken from 803 SNPs were analyzed, and four clusters...

Optimum analysis of pavement maintenance using multi-objective genetic algorithms

Directory of Open Access Journals (Sweden)

Amr A. Elhadidy

2015-04-01

Full Text Available Road network expansion in Egypt is considered as a vital issue for the development of the country. This is done while upgrading current road networks to increase the safety and efficiency. A pavement management system (PMS is a set of tools or methods that assist decision makers in finding optimum strategies for providing and maintaining pavements in a serviceable condition over a given period of time. A multi-objective optimization problem for pavement maintenance and rehabilitation strategies on network level is discussed in this paper. A two-objective optimization model considers minimum action costs and maximum condition for used road network. In the proposed approach, Markov-chain models are used for predicting the performance of road pavement and to calculate the expected decline at different periods of time. A genetic-algorithm-based procedure is developed for solving the multi-objective optimization problem. The model searched for the optimum maintenance actions at adequate time to be implemented on an appropriate pavement. Based on the computing results, the Pareto optimal solutions of the two-objective optimization functions are obtained. From the optimal solutions represented by cost and condition, a decision maker can easily obtain the information of the maintenance and rehabilitation planning with minimum action costs and maximum condition. The developed model has been implemented on a network of roads and showed its ability to derive the optimal solution.

Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers.

Directory of Open Access Journals (Sweden)

Guosheng Su

Full Text Available Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1 a simple additive genetic model (MA, 2 a model including both additive and additive by additive epistatic genetic effects (MAE, 3 a model including both additive and dominance genetic effects (MAD, and 4 a full model including all three genetic components (MAED. Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions.

Tabletop single-shot extreme ultraviolet Fourier transform holography of an extended object.

Science.gov (United States)

Malm, Erik B; Monserud, Nils C; Brown, Christopher G; Wachulak, Przemyslaw W; Xu, Huiwen; Balakrishnan, Ganesh; Chao, Weilun; Anderson, Erik; Marconi, Mario C

2013-04-22

We demonstrate single and multi-shot Fourier transform holography with the use of a tabletop extreme ultraviolet laser. The reference wave was produced by a Fresnel zone plate with a central opening that allowed the incident beam to illuminate the sample directly. The high reference wave intensity allows for larger objects to be imaged compared to mask-based lensless Fourier transform holography techniques. We obtain a spatial resolution of 169 nm from a single laser pulse and a resolution of 128 nm from an accumulation of 20 laser pulses for an object ~11x11μm(2) in size. This experiment utilized a tabletop extreme ultraviolet laser that produces a highly coherent ~1.2 ns laser pulse at 46.9 nm wavelength.

Single-objective vs. multi-objective autocalibration in modelling total suspended solids and phosphorus in a small agricultural watershed with SWAT.

Science.gov (United States)

Rasolomanana, Santatriniaina Denise; Lessard, Paul; Vanrolleghem, Peter A

2012-01-01

To obtain greater precision in modelling small agricultural watersheds, a shorter simulation time step is beneficial. A daily time step better represents the dynamics of pollutants in the river and provides more realistic simulation results. However, with a daily evaluation performance, good fits are rarely obtained. With the Shuffled Complex Evolution (SCE) method embedded in the Soil and Water Assessment Tool (SWAT), two calibration approaches are available, single-objective or multi-objective optimization. The goal of the present study is to evaluate which approach can improve the daily performance with SWAT, in modelling flow (Q), total suspended solids (TSS) and total phosphorus (TP). The influence of weights assigned to the different variables included in the objective function has also been tested. The results showed that: (i) the model performance depends not only on the choice of calibration approach, but essentially on the influential parameters; (ii) the multi-objective calibration estimating at once all parameters related to all measured variables is the best approach to model Q, TSS and TP; (iii) changing weights does not improve model performance; and (iv) with a single-objective optimization, an excellent water quality modelling performance may hide a loss of performance of predicting flows and unbalanced internal model components.

An improved fast and elitist multi-objective genetic algorithm-ANSGA-II for multi-objective optimization of inverse radiotherapy treatment planning

International Nuclear Information System (INIS)

Cao Ruifen; Li Guoli; Song Gang; Zhao Pan; Lin Hui; Wu Aidong; Huang Chenyu; Wu Yican

2007-01-01

Objective: To provide a fast and effective multi-objective optimization algorithm for inverse radiotherapy treatment planning system. Methods: Non-dominated Sorting Genetic Algorithm-NSGA-II is a representative of multi-objective evolutionary optimization algorithms and excels the others. The paper produces ANSGA-II that makes use of advantage of NSGA-II, and uses adaptive crossover and mutation to improve its flexibility; according the character of inverse radiotherapy treatment planning, the paper uses the pre-known knowledge to generate individuals of every generation in the course of optimization, which enhances the convergent speed and improves efficiency. Results: The example of optimizing average dose of a sheet of CT, including PTV, OAR, NT, proves the algorithm could find satisfied solutions in several minutes. Conclusions: The algorithm could provide clinic inverse radiotherapy treatment planning system with selection of optimization algorithms. (authors)

Personalized Genetic Risk Counseling to Motivate Diabetes Prevention: A randomized trial

OpenAIRE

Grant, Richard W.; O’Brien, Kelsey E.; Waxler, Jessica L.; Vassy, Jason L.; Delahanty, Linda M.; Bissett, Laurie G.; Green, Robert C.; Stember, Katherine G.; Guiducci, Candace; Park, Elyse R.; Florez, Jose C.; Meigs, James B.

2013-01-01

OBJECTIVE To examine whether diabetes genetic risk testing and counseling can improve diabetes prevention behaviors. RESEARCH DESIGN AND METHODS We conducted a randomized trial of diabetes genetic risk counseling among overweight patients at increased phenotypic risk for type 2 diabetes. Participants were randomly allocated to genetic testing versus no testing. Genetic risk was calculated by summing 36 single nucleotide polymorphisms associated with type 2 diabetes. Participants in the top an...

From tomography to FWI with a single objective function

KAUST Repository

Alkhalifah, Tariq Ali

2013-06-10

Reflections in our seismic data induce serious nonlinear behavior in the objective function of full waveform inversion (FWI). Thus, without a good initial velocity model, that can produce the reflections within a cycle of the frequency used in the inversion, convergence to the solution becomes hard. Such velocity models are usually extracted from migration velocity analysis or traveltime tomography, among other means, that are not guaranteed to adhere to the FWI requirements. As such, we promote an objective function based on the misfit in the instantaneous traveltime between the observed and modeled data. This phase based attribute of the wavefield, along with its phase unwrapping features, provide a frequency dependent traveltime function. With strong damping of the of the synthetic, potentially low frequency, data, this attribute admits first arrival traveltime that could be compared with picked ones from the observed data, like in wave equation tomography. As we relax the damping on the synthetic and observed data, the objective function measures the misfit in the phase, however unwrapped in an FWI type inversion. It, thus, provides a single objective function and a natural transition from traveltime tomography to full waveform inversion. A Marmousi example demonstrates the effectiveness of the approach.

Multiplicative mixing of object identity and image attributes in single inferior temporal neurons.

Science.gov (United States)

Ratan Murty, N Apurva; Arun, S P

2018-04-03

Object recognition is challenging because the same object can produce vastly different images, mixing signals related to its identity with signals due to its image attributes, such as size, position, rotation, etc. Previous studies have shown that both signals are present in high-level visual areas, but precisely how they are combined has remained unclear. One possibility is that neurons might encode identity and attribute signals multiplicatively so that each can be efficiently decoded without interference from the other. Here, we show that, in high-level visual cortex, responses of single neurons can be explained better as a product rather than a sum of tuning for object identity and tuning for image attributes. This subtle effect in single neurons produced substantially better population decoding of object identity and image attributes in the neural population as a whole. This property was absent both in low-level vision models and in deep neural networks. It was also unique to invariances: when tested with two-part objects, neural responses were explained better as a sum than as a product of part tuning. Taken together, our results indicate that signals requiring separate decoding, such as object identity and image attributes, are combined multiplicatively in IT neurons, whereas signals that require integration (such as parts in an object) are combined additively. Copyright © 2018 the Author(s). Published by PNAS.

Dandelion (Taraxacum Officinale Wigg. S.L. Is A Convenient Object For Genetic Monitoring Of Environmental Pollution

Directory of Open Access Journals (Sweden)

Nina V Reutova

2006-09-01

Full Text Available It is proposed to use dandelion (Taraxacum officinale Wigg. s.l. for testing of mutagenic effects of environmental pollutants. This widespread species is convenient for genetic monitoring. It is sensitive to various types of pollutants (heavy metals, products of combustion and processing of oil. T. officinale appeared to be a convenient, simple in using and inexpensive object for genetic monitoring of environmental pollution. anaphase-telophase method is recomended for this purpose.

Single nucleotide polymorphisms for assessing genetic diversity in castor bean (Ricinus communis

Directory of Open Access Journals (Sweden)

Rabinowicz Pablo D

2010-01-01

Full Text Available Abstract Background Castor bean (Ricinus communis is an agricultural crop and garden ornamental that is widely cultivated and has been introduced worldwide. Understanding population structure and the distribution of castor bean cultivars has been challenging because of limited genetic variability. We analyzed the population genetics of R. communis in a worldwide collection of plants from germplasm and from naturalized populations in Florida, U.S. To assess genetic diversity we conducted survey sequencing of the genomes of seven diverse cultivars and compared the data to a reference genome assembly of a widespread cultivar (Hale. We determined the population genetic structure of 676 samples using single nucleotide polymorphisms (SNPs at 48 loci. Results Bayesian clustering indicated five main groups worldwide and a repeated pattern of mixed genotypes in most countries. High levels of population differentiation occurred between most populations but this structure was not geographically based. Most molecular variance occurred within populations (74% followed by 22% among populations, and 4% among continents. Samples from naturalized populations in Florida indicated significant population structuring consistent with local demes. There was significant population differentiation for 56 of 78 comparisons in Florida (pairwise population ϕPT values, p Conclusion Low levels of genetic diversity and mixing of genotypes have led to minimal geographic structuring of castor bean populations worldwide. Relatively few lineages occur and these are widely distributed. Our approach of determining population genetic structure using SNPs from genome-wide comparisons constitutes a framework for high-throughput analyses of genetic diversity in plants, particularly in species with limited genetic diversity.

Multi-Objective Optimization of a Turbofan for an Advanced, Single-Aisle Transport

Science.gov (United States)

Berton, Jeffrey J.; Guynn, Mark D.

2012-01-01

Considerable interest surrounds the design of the next generation of single-aisle commercial transports in the Boeing 737 and Airbus A320 class. Aircraft designers will depend on advanced, next-generation turbofan engines to power these airplanes. The focus of this study is to apply single- and multi-objective optimization algorithms to the conceptual design of ultrahigh bypass turbofan engines for this class of aircraft, using NASA s Subsonic Fixed Wing Project metrics as multidisciplinary objectives for optimization. The independent design variables investigated include three continuous variables: sea level static thrust, wing reference area, and aerodynamic design point fan pressure ratio, and four discrete variables: overall pressure ratio, fan drive system architecture (i.e., direct- or gear-driven), bypass nozzle architecture (i.e., fixed- or variable geometry), and the high- and low-pressure compressor work split. Ramp weight, fuel burn, noise, and emissions are the parameters treated as dependent objective functions. These optimized solutions provide insight to the ultrahigh bypass engine design process and provide information to NASA program management to help guide its technology development efforts.

Comprehensive genetic assessment of the human embryo: can empiric application of microarray comparative genomic hybridization reduce multiple gestation rate by single fresh blastocyst transfer?

Science.gov (United States)

Sills, Eric Scott; Yang, Zhihong; Walsh, David J; Salem, Shala A

2012-09-01

The unacceptable multiple gestation rate currently associated with in vitro fertilization (IVF) would be substantially alleviated if the routine practice of transferring more than one embryo were reconsidered. While transferring a single embryo is an effective method to reduce the clinical problem of multiple gestation, rigid adherence to this approach has been criticized for negatively impacting clinical pregnancy success in IVF. In general, single embryo transfer is viewed cautiously by IVF patients although greater acceptance would result from a more effective embryo selection method. Selection of one embryo for fresh transfer on the basis of chromosomal normalcy should achieve the dual objective of maintaining satisfactory clinical pregnancy rates and minimizing the multiple gestation problem, because embryo aneuploidy is a major contributing factor in implantation failure and miscarriage in IVF. The initial techniques for preimplantation genetic screening unfortunately lacked sufficient sensitivity and did not yield the expected results in IVF. However, newer molecular genetic methods could be incorporated with standard IVF to bring the goal of single embryo transfer within reach. Aiming to make multiple embryo transfers obsolete and unnecessary, and recognizing that array comparative genomic hybridization (aCGH) will typically require an additional 12 h of laboratory time to complete, we propose adopting aCGH for mainstream use in clinical IVF practice. As aCGH technology continues to develop and becomes increasingly available at lower cost, it may soon be considered unusual for IVF laboratories to select a single embryo for fresh transfer without regard to its chromosomal competency. In this report, we provide a rationale supporting aCGH as the preferred methodology to provide a comprehensive genetic assessment of the single embryo before fresh transfer in IVF. The logistics and cost of integrating aCGH with IVF to enable fresh embryo transfer are also

Development and amplification of multiple co-dominant genetic markers from single spores of arbuscular mycorrhizal fungi by nested multiplex PCR

DEFF Research Database (Denmark)

Holtgrewe-Stukenbrock, Eva; Rosendahl, Søren

2005-01-01

Multiple co-dominant genetic markers from single spores of the arbuscular mycorrhizal (AM) fungi Glomus mosseae, Glomus caledonium, and Glomus geosporum were amplified by nested multiplex PCR using a combination of primers for simultaneous amplification of five loci in one PCR. Subsequently, each...... marker was amplified separately in nested PCR using specific primers. Polymorphic loci within the three putative single copy genes GmFOX2, GmTOR2, and GmGIN1 were characterized by sequencing and single strand conformation polymorphisms (SSCP). Primers specific for the LSU rDNA D2 region were included...... are homokaryotic. All isolates of G. mosseae had unique genotypes. The amplification of multiple co-dominant genetic markers from single spores by the nested multiplex PCR approach provides an important tool for future studies of AM fungi population genetics and evolution....

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

Directory of Open Access Journals (Sweden)

Maryam Mousavi

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

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

Science.gov (United States)

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

2017-01-01

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

Modeling of genetic gain for single traits from marker-assisted seedling selection in clonally propagated crops

Science.gov (United States)

Ru, Sushan; Hardner, Craig; Carter, Patrick A; Evans, Kate; Main, Dorrie; Peace, Cameron

2016-01-01

Seedling selection identifies superior seedlings as candidate cultivars based on predicted genetic potential for traits of interest. Traditionally, genetic potential is determined by phenotypic evaluation. With the availability of DNA tests for some agronomically important traits, breeders have the opportunity to include DNA information in their seedling selection operations—known as marker-assisted seedling selection. A major challenge in deploying marker-assisted seedling selection in clonally propagated crops is a lack of knowledge in genetic gain achievable from alternative strategies. Existing models based on additive effects considering seed-propagated crops are not directly relevant for seedling selection of clonally propagated crops, as clonal propagation captures all genetic effects, not just additive. This study modeled genetic gain from traditional and various marker-based seedling selection strategies on a single trait basis through analytical derivation and stochastic simulation, based on a generalized seedling selection scheme of clonally propagated crops. Various trait-test scenarios with a range of broad-sense heritability and proportion of genotypic variance explained by DNA markers were simulated for two populations with different segregation patterns. Both derived and simulated results indicated that marker-based strategies tended to achieve higher genetic gain than phenotypic seedling selection for a trait where the proportion of genotypic variance explained by marker information was greater than the broad-sense heritability. Results from this study provides guidance in optimizing genetic gain from seedling selection for single traits where DNA tests providing marker information are available. PMID:27148453

Global shape optimization of airfoil using multi-objective genetic algorithm

International Nuclear Information System (INIS)

Lee, Ju Hee; Lee, Sang Hwan; Park, Kyoung Woo

2005-01-01

The shape optimization of an airfoil has been performed for an incompressible viscous flow. In this study, Pareto frontier sets, which are global and non-dominated solutions, can be obtained without various weighting factors by using the multi-objective genetic algorithm. An NACA0012 airfoil is considered as a baseline model, and the profile of the airfoil is parameterized and rebuilt with four Bezier curves. Two curves, from leading to maximum thickness, are composed of five control points and the rest, from maximum thickness to tailing edge, are composed of four control points. There are eighteen design variables and two objective functions such as the lift and drag coefficients. A generation is made up of forty-five individuals. After fifteenth evolutions, the Pareto individuals of twenty can be achieved. One Pareto, which is the best of the reduction of the drag force, improves its drag to 13% and lift-drag ratio to 2%. Another Pareto, however, which is focused on increasing the lift force, can improve its lift force to 61%, while sustaining its drag force, compared to those of the baseline model

Global shape optimization of airfoil using multi-objective genetic algorithm

Energy Technology Data Exchange (ETDEWEB)

Lee, Ju Hee; Lee, Sang Hwan [Hanyang Univ., Seoul (Korea, Republic of); Park, Kyoung Woo [Hoseo Univ., Asan (Korea, Republic of)

2005-10-01

The shape optimization of an airfoil has been performed for an incompressible viscous flow. In this study, Pareto frontier sets, which are global and non-dominated solutions, can be obtained without various weighting factors by using the multi-objective genetic algorithm. An NACA0012 airfoil is considered as a baseline model, and the profile of the airfoil is parameterized and rebuilt with four Bezier curves. Two curves, from leading to maximum thickness, are composed of five control points and the rest, from maximum thickness to tailing edge, are composed of four control points. There are eighteen design variables and two objective functions such as the lift and drag coefficients. A generation is made up of forty-five individuals. After fifteenth evolutions, the Pareto individuals of twenty can be achieved. One Pareto, which is the best of the reduction of the drag force, improves its drag to 13% and lift-drag ratio to 2%. Another Pareto, however, which is focused on increasing the lift force, can improve its lift force to 61%, while sustaining its drag force, compared to those of the baseline model.

Multi-objective thermodynamic optimization of combined Brayton and inverse Brayton cycles using genetic algorithms

International Nuclear Information System (INIS)

Besarati, S.M.; Atashkari, K.; Jamali, A.; Hajiloo, A.; Nariman-zadeh, N.

2010-01-01

This paper presents a simultaneous optimization study of two outputs performance of a previously proposed combined Brayton and inverse Brayton cycles. It has been carried out by varying the upper cycle pressure ratio, the expansion pressure of the bottom cycle and using variable, above atmospheric, bottom cycle inlet pressure. Multi-objective genetic algorithms are used for Pareto approach optimization of the cycle outputs. The two important conflicting thermodynamic objectives that have been considered in this work are net specific work (w s ) and thermal efficiency (η th ). It is shown that some interesting features among optimal objective functions and decision variables involved in the Baryton and inverse Brayton cycles can be discovered consequently.

Makeup of the genetic correlation between milk production traits using genome-wide single nucleotide polymorphism information

NARCIS (Netherlands)

Binsbergen, van R.; Veerkamp, R.F.; Calus, M.P.L.

2012-01-01

The correlated responses between traits may differ depending on the makeup of genetic covariances, and may differ from the predictions of polygenic covariances Therefore, the objective of the present study was to investigate the makeup of the genetic covariances between the well-studied traits: milk

A modified genetic algorithm for time and cost optimization of an additive manufacturing single-machine scheduling

Directory of Open Access Journals (Sweden)

M. Fera

2018-09-01

Full Text Available Additive Manufacturing (AM is a process of joining materials to make objects from 3D model data, usually layer by layer, as opposed to subtractive manufacturing methodologies. Selective Laser Melting, commercially known as Direct Metal Laser Sintering (DMLS®, is the most diffused additive process in today’s manufacturing industry. Introduction of a DMLS® machine in a production department has remarkable effects not only on industrial design but also on production planning, for example, on machine scheduling. Scheduling for a traditional single machine can employ consolidated models. Scheduling of an AM machine presents new issues because it must consider the capability of producing different geometries, simultaneously. The aim of this paper is to provide a mathematical model for an AM/SLM machine scheduling. The complexity of the model is NP-HARD, so possible solutions must be found by metaheuristic algorithms, e.g., Genetic Algorithms. Genetic Algorithms solve sequential optimization problems by handling vectors; in the present paper, we must modify them to handle a matrix. The effectiveness of the proposed algorithms will be tested on a test case formed by a 30 Part Number production plan with a high variability in complexity, distinct due dates and low production volumes.

Linking transcriptional and genetic tumor heterogeneity through allele analysis of single-cell RNA-seq data.

Science.gov (United States)

Fan, Jean; Lee, Hae-Ock; Lee, Soohyun; Ryu, Da-Eun; Lee, Semin; Xue, Catherine; Kim, Seok Jin; Kim, Kihyun; Barkas, Nikolas; Park, Peter J; Park, Woong-Yang; Kharchenko, Peter V

2018-06-13

Characterization of intratumoral heterogeneity is critical to cancer therapy, as presence of phenotypically diverse cell populations commonly fuels relapse and resistance to treatment. Although genetic variation is a well-studied source of intratumoral heterogeneity, the functional impact of most genetic alterations remains unclear. Even less understood is the relative importance of other factors influencing heterogeneity, such as epigenetic state or tumor microenvironment. To investigate the relationship between genetic and transcriptional heterogeneity in a context of cancer progression, we devised a computational approach called HoneyBADGER to identify copy number variation and loss-of-heterozygosity in individual cells from single-cell RNA-sequencing data. By integrating allele and normalized expression information, HoneyBADGER is able to identify and infer the presence of subclone-specific alterations in individual cells and reconstruct underlying subclonal architecture. Examining several tumor types, we show that HoneyBADGER is effective at identifying deletion, amplifications, and copy-neutral loss-of-heterozygosity events, and is capable of robustly identifying subclonal focal alterations as small as 10 megabases. We further apply HoneyBADGER to analyze single cells from a progressive multiple myeloma patient to identify major genetic subclones that exhibit distinct transcriptional signatures relevant to cancer progression. Surprisingly, other prominent transcriptional subpopulations within these tumors did not line up with the genetic subclonal structure, and were likely driven by alternative, non-clonal mechanisms. These results highlight the need for integrative analysis to understand the molecular and phenotypic heterogeneity in cancer. Published by Cold Spring Harbor Laboratory Press.

Time-domain single-source integral equations for analyzing scattering from homogeneous penetrable objects

KAUST Repository

Valdé s, Felipe; Andriulli, Francesco P.; Bagci, Hakan; Michielssen, Eric

2013-01-01

Single-source time-domain electric-and magnetic-field integral equations for analyzing scattering from homogeneous penetrable objects are presented. Their temporal discretization is effected by using shifted piecewise polynomial temporal basis

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

Science.gov (United States)

Valles Sosa, Claudia Evangelina

Bioenergy has become an important alternative source of energy to alleviate the reliance on petroleum energy. Bioenergy offers diminishing climate change by reducing Green House Gas Emissions, as well as providing energy security and enhancing rural development. The Energy Independence and Security Act mandate the use of 21 billion gallons of advanced biofuels including 16 billion gallons of cellulosic biofuels by the year 2022. It is clear that Biomass can make a substantial contribution to supply future energy demand in a sustainable way. However, the supply of sustainable energy is one of the main challenges that mankind will face over the coming decades. For instance, many logistical challenges will be faced in order to provide an efficient and reliable supply of quality feedstock to biorefineries. 700 million tons of biomass will be required to be sustainably delivered to biorefineries annually to meet the projected use of biofuels by the year of 2022. Approaching this complex logistic problem as a multi-commodity network flow structure, the present work proposes the use of a genetic algorithm as a single objective optimization problem that considers the maximization of profit and the present work also proposes the use of a Multiple Objective Evolutionary Algorithm to simultaneously maximize profit while minimizing global warming potential. Most transportation optimization problems available in the literature have mostly considered the maximization of profit or the minimization of total travel time as potential objectives to be optimized. However, on this research work, we take a more conscious and sustainable approach for this logistic problem. Planners are increasingly expected to adopt a multi-disciplinary approach, especially due to the rising importance of environmental stewardship. The role of a transportation planner and designer is shifting from simple economic analysis to promoting sustainability through the integration of environmental objectives. To

Multi-Objective Optimization Design for a Hybrid Energy System Using the Genetic Algorithm

Directory of Open Access Journals (Sweden)

Myeong Jin Ko

2015-04-01

Full Text Available To secure a stable energy supply and bring renewable energy to buildings within a reasonable cost range, a hybrid energy system (HES that integrates both fossil fuel energy systems (FFESs and new and renewable energy systems (NRESs needs to be designed and applied. This paper presents a methodology to optimize a HES consisting of three types of NRESs and six types of FFESs while simultaneously minimizing life cycle cost (LCC, maximizing penetration of renewable energy and minimizing annual greenhouse gas (GHG emissions. An elitist non-dominated sorting genetic algorithm is utilized for multi-objective optimization. As an example, we have designed the optimal configuration and sizing for a HES in an elementary school. The evolution of Pareto-optimal solutions according to the variation in the economic, technical and environmental objective functions through generations is discussed. The pair wise trade-offs among the three objectives are also examined.

Genetic risk scores and number of autoantibodies in patients with rheumatoid arthritis

NARCIS (Netherlands)

Maehlen, Marthe T.; Olsen, Inge C.; Andreassen, Bettina K.; Viken, Marte K.; Jiang, Xia; Alfredsson, Lars; Kallberg, Henrik; Brynedal, Boel; Kurreeman, Fina; Daha, Nina; Toes, Rene; Zhernakova, Alexandra; Gutierrez-Achury, Javier; de Bakker, Paul I. W.; Martin, Javier; Teruel, Maria; Gonzalez-Gay, Miguel A.; Rodriguez-Rodriguez, Luis; Balsa, Alejandro; Uhlig, Till; Kvien, Tore K.; Lie, Benedicte A.

Objective Certain HLA-DRB1 alleles and single-nucleotide polymorphisms (SNPs) are associated with rheumatoid arthritis (RA). Our objective was to examine the combined effect of these associated variants, calculated as a cumulative genetic risk score (GRS) on RA predisposition, as well as the number

Genetic risk scores and number of autoantibodies in patients with rheumatoid arthritis

NARCIS (Netherlands)

Maehlen, Marthe T; Olsen, Inge C; Andreassen, Bettina K; Viken, Marte K; Jiang, Xia; Alfredsson, Lars; Källberg, Henrik; Brynedal, Boel; Kurreeman, Fina; Daha, Nina; Toes, Rene; Zhernakova, Alexandra; Gutierrez-Achury, Javier; de Bakker, Paul I W; Martin, Javier; Teruel, María; Gonzalez-Gay, Miguel A; Rodríguez-Rodríguez, Luis; Balsa, Alejandro; Uhlig, Till; Kvien, Tore K; Lie, Benedicte A

OBJECTIVE: Certain HLA-DRB1 alleles and single-nucleotide polymorphisms (SNPs) are associated with rheumatoid arthritis (RA). Our objective was to examine the combined effect of these associated variants, calculated as a cumulative genetic risk score (GRS) on RA predisposition, as well as the number

Intersection signal control multi-objective optimization based on genetic algorithm

Directory of Open Access Journals (Sweden)

Zhanhong Zhou

2014-04-01

Full Text Available A signal control intersection increases not only vehicle delay, but also vehicle emissions and fuel consumption in that area. Because more and more fuel and air pollution problems arise recently, an intersection signal control optimization method which aims at reducing vehicle emissions, fuel consumption and vehicle delay is required heavily. This paper proposed a signal control multi-object optimization method to reduce vehicle emissions, fuel consumption and vehicle delay simultaneously at an intersection. The optimization method combined the Paramics microscopic traffic simulation software, Comprehensive Modal Emissions Model (CMEM, and genetic algorithm. An intersection in Haizhu District, Guangzhou, was taken for a case study. The result of the case study shows the optimal timing scheme obtained from this method is better than the Webster timing scheme.

Combinations of Genetic Variants Occurring Exclusively in Patients

DEFF Research Database (Denmark)

Mellerup, Erling Thyge; Møller, Gert Lykke

2017-01-01

The main objective of the study was to find genetic variants that in combination are significantly associated with bipolar disorder. In previous studies of bipolar disorder, combinations of three and four single nucleotide polymorphisms (SNP) genotypes taken from 803 SNPs were analyzed, and five ...

A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

Science.gov (United States)

Ingram, James N; Howard, Ian S; Flanagan, J Randall; Wolpert, Daniel M

2011-09-01

Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics

A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

Directory of Open Access Journals (Sweden)

James N Ingram

2011-09-01

Full Text Available Motor learning has been extensively studied using dynamic (force-field perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar

Resonance assignment of the NMR spectra of disordered proteins using a multi-objective non-dominated sorting genetic algorithm

International Nuclear Information System (INIS)

Yang, Yu; Fritzsching, Keith J.; Hong, Mei

2013-01-01

A multi-objective genetic algorithm is introduced to predict the assignment of protein solid-state NMR (SSNMR) spectra with partial resonance overlap and missing peaks due to broad linewidths, molecular motion, and low sensitivity. This non-dominated sorting genetic algorithm II (NSGA-II) aims to identify all possible assignments that are consistent with the spectra and to compare the relative merit of these assignments. Our approach is modeled after the recently introduced Monte-Carlo simulated-annealing (MC/SA) protocol, with the key difference that NSGA-II simultaneously optimizes multiple assignment objectives instead of searching for possible assignments based on a single composite score. The multiple objectives include maximizing the number of consistently assigned peaks between multiple spectra (“good connections”), maximizing the number of used peaks, minimizing the number of inconsistently assigned peaks between spectra (“bad connections”), and minimizing the number of assigned peaks that have no matching peaks in the other spectra (“edges”). Using six SSNMR protein chemical shift datasets with varying levels of imperfection that was introduced by peak deletion, random chemical shift changes, and manual peak picking of spectra with moderately broad linewidths, we show that the NSGA-II algorithm produces a large number of valid and good assignments rapidly. For high-quality chemical shift peak lists, NSGA-II and MC/SA perform similarly well. However, when the peak lists contain many missing peaks that are uncorrelated between different spectra and have chemical shift deviations between spectra, the modified NSGA-II produces a larger number of valid solutions than MC/SA, and is more effective at distinguishing good from mediocre assignments by avoiding the hazard of suboptimal weighting factors for the various objectives. These two advantages, namely diversity and better evaluation, lead to a higher probability of predicting the correct

Resonance assignment of the NMR spectra of disordered proteins using a multi-objective non-dominated sorting genetic algorithm.

Science.gov (United States)

Yang, Yu; Fritzsching, Keith J; Hong, Mei

2013-11-01

A multi-objective genetic algorithm is introduced to predict the assignment of protein solid-state NMR (SSNMR) spectra with partial resonance overlap and missing peaks due to broad linewidths, molecular motion, and low sensitivity. This non-dominated sorting genetic algorithm II (NSGA-II) aims to identify all possible assignments that are consistent with the spectra and to compare the relative merit of these assignments. Our approach is modeled after the recently introduced Monte-Carlo simulated-annealing (MC/SA) protocol, with the key difference that NSGA-II simultaneously optimizes multiple assignment objectives instead of searching for possible assignments based on a single composite score. The multiple objectives include maximizing the number of consistently assigned peaks between multiple spectra ("good connections"), maximizing the number of used peaks, minimizing the number of inconsistently assigned peaks between spectra ("bad connections"), and minimizing the number of assigned peaks that have no matching peaks in the other spectra ("edges"). Using six SSNMR protein chemical shift datasets with varying levels of imperfection that was introduced by peak deletion, random chemical shift changes, and manual peak picking of spectra with moderately broad linewidths, we show that the NSGA-II algorithm produces a large number of valid and good assignments rapidly. For high-quality chemical shift peak lists, NSGA-II and MC/SA perform similarly well. However, when the peak lists contain many missing peaks that are uncorrelated between different spectra and have chemical shift deviations between spectra, the modified NSGA-II produces a larger number of valid solutions than MC/SA, and is more effective at distinguishing good from mediocre assignments by avoiding the hazard of suboptimal weighting factors for the various objectives. These two advantages, namely diversity and better evaluation, lead to a higher probability of predicting the correct assignment for a

Multi-objective optimal design of magnetorheological engine mount based on an improved non-dominated sorting genetic algorithm

Science.gov (United States)

Zheng, Ling; Duan, Xuwei; Deng, Zhaoxue; Li, Yinong

2014-03-01

A novel flow-mode magneto-rheological (MR) engine mount integrated a diaphragm de-coupler and the spoiler plate is designed and developed to isolate engine and the transmission from the chassis in a wide frequency range and overcome the stiffness in high frequency. A lumped parameter model of the MR engine mount in single degree of freedom system is further developed based on bond graph method to predict the performance of the MR engine mount accurately. The optimization mathematical model is established to minimize the total of force transmissibility over several frequency ranges addressed. In this mathematical model, the lumped parameters are considered as design variables. The maximum of force transmissibility and the corresponding frequency in low frequency range as well as individual lumped parameter are limited as constraints. The multiple interval sensitivity analysis method is developed to select the optimized variables and improve the efficiency of optimization process. An improved non-dominated sorting genetic algorithm (NSGA-II) is used to solve the multi-objective optimization problem. The synthesized distance between the individual in Pareto set and the individual in possible set in engineering is defined and calculated. A set of real design parameters is thus obtained by the internal relationship between the optimal lumped parameters and practical design parameters for the MR engine mount. The program flowchart for the improved non-dominated sorting genetic algorithm (NSGA-II) is given. The obtained results demonstrate the effectiveness of the proposed optimization approach in minimizing the total of force transmissibility over several frequency ranges addressed.

Analysis and optimization with ecological objective function of irreversible single resonance energy selective electron heat engines

International Nuclear Information System (INIS)

Zhou, Junle; Chen, Lingen; Ding, Zemin; Sun, Fengrui

2016-01-01

Ecological performance of a single resonance ESE heat engine with heat leakage is conducted by applying finite time thermodynamics. By introducing Nielsen function and numerical calculations, expressions about power output, efficiency, entropy generation rate and ecological objective function are derived; relationships between ecological objective function and power output, between ecological objective function and efficiency as well as between power output and efficiency are demonstrated; influences of system parameters of heat leakage, boundary energy and resonance width on the optimal performances are investigated in detail; a specific range of boundary energy is given as a compromise to make ESE heat engine system work at optimal operation regions. Comparing performance characteristics with different optimization objective functions, the significance of selecting ecological objective function as the design objective is clarified specifically: when changing the design objective from maximum power output into maximum ecological objective function, the improvement of efficiency is 4.56%, while the power output drop is only 2.68%; when changing the design objective from maximum efficiency to maximum ecological objective function, the improvement of power output is 229.13%, and the efficiency drop is only 13.53%. - Highlights: • An irreversible single resonance energy selective electron heat engine is studied. • Heat leakage between two reservoirs is considered. • Power output, efficiency and ecological objective function are derived. • Optimal performance comparison for three objective functions is carried out.

Optical encryption of multiple three-dimensional objects based on multiple interferences and single-pixel digital holography

Science.gov (United States)

Wang, Ying; Liu, Qi; Wang, Jun; Wang, Qiong-Hua

2018-03-01

We present an optical encryption method of multiple three-dimensional objects based on multiple interferences and single-pixel digital holography. By modifying the Mach–Zehnder interferometer, the interference of the multiple objects beams and the one reference beam is used to simultaneously encrypt multiple objects into a ciphertext. During decryption, each three-dimensional object can be decrypted independently without having to decrypt other objects. Since the single-pixel digital holography based on compressive sensing theory is introduced, the encrypted data of this method is effectively reduced. In addition, recording fewer encrypted data can greatly reduce the bandwidth of network transmission. Moreover, the compressive sensing essentially serves as a secret key that makes an intruder attack invalid, which means that the system is more secure than the conventional encryption method. Simulation results demonstrate the feasibility of the proposed method and show that the system has good security performance. Project supported by the National Natural Science Foundation of China (Grant Nos. 61405130 and 61320106015).

Clonal diversity and population genetic structure of arbuscular mycorrhizal fungi (Glomus spp.) studied by multilocus genotyping of single spores

DEFF Research Database (Denmark)

Holtgrewe-Stukenbrock, Eva; Rosendahl, Søren

2005-01-01

A nested multiplex PCR (polymerase chain reaction) approach was used for multilocus genotyping of arbuscular mycorrhizal fungal populations. This method allowed us to amplify multiple loci from Glomus single spores in a single PCR amplification. Variable introns in the two protein coding genes Gm......FOX2 and GmTOR2 were applied as codominant genetic markers together with the LSU rDNA.   Genetic structure of Glomus spp. populations from an organically and a conventionally cultured field were compared by hierarchical sampling of spores from four plots in each field. Multilocus genotypes were...

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.

Pre-natal genetic counselling in a resource limited country - a single center geneticist's perspectives

International Nuclear Information System (INIS)

Afroze, B.; Jehan, F.

2014-01-01

Objective: To assess the needs related to prenatal genetic counselling in a developing country. Methods: The prospective observational study was conducted at the Prenatal-Genetic Counselling Clinic of Aga Khan University Hospital, Karachi, from October 2007 to September 2010. In-depth interviews were conducted and the data was stored in the form of patient charts. Information was then extracted from the charts and entered into a structured questionnaire. Results: Of the 93 couples in the study, 49(53%) were in the self-referral group and 44(47%) were in the physician-referral group. Diagnosis was not given for previously affected children by the paediatrician or by obstetrician for recurrent miscarriages in 68(73%)cases. Besides, 20(22%) couples had voluntarily terminated a pregnancy without any tests because of the fear of having a diseased child. Eleven (12%) couples were looking for amniocentensis or chorionic villus sampling. Death in previous children was the main reason to seek genetic counselling and was seen in 57(61%) couples. Consanguinity was seen in 77(83%) couples. Conclusion: A clear deficiency of knowledge of genetics was seen among the non-genetic healthcare providers. Demand of antenatal genetic testing among the public was also seen, highlighting the need of diagnostic facility for genetic and metabolic disorders. However, this needs to be explored in the context of the existing healthcare infrastructure. (author)

Designing optimal degradation tests via multi-objective genetic algorithms

International Nuclear Information System (INIS)

Marseguerra, Marzio; Zio, Enrico; Cipollone, Maurizio

2003-01-01

The experimental determination of the failure time probability distribution of highly reliable components, such as those used in nuclear and aerospace applications, is intrinsically difficult due to the lack, or scarce significance, of failure data which can be collected during the relatively short test periods. A possibility to overcome this difficulty is to resort to the so-called degradation tests, in which measurements of components' degradation are used to infer the failure time distribution. To design such tests, parameters like the number of tests to be run, their frequency and duration, must be set so as to obtain an accurate estimate of the distribution statistics, under the existing limitations of budget. The optimisation problem which results is a non-linear one. In this work, we propose a method, based on multi-objective genetic algorithms for determining the values of the test parameters which optimise both the accuracy in the estimate of the failure time distribution percentiles and the testing costs. The method has been validated on a degradation model of literature

Covering chemical diversity of genetically-modified tomatoes using metabolomics for objective substantial equivalence assessment.

Directory of Open Access Journals (Sweden)

Miyako Kusano

Full Text Available As metabolomics can provide a biochemical snapshot of an organism's phenotype it is a promising approach for charting the unintended effects of genetic modification. A critical obstacle for this application is the inherently limited metabolomic coverage of any single analytical platform. We propose using multiple analytical platforms for the direct acquisition of an interpretable data set of estimable chemical diversity. As an example, we report an application of our multi-platform approach that assesses the substantial equivalence of tomatoes over-expressing the taste-modifying protein miraculin. In combination, the chosen platforms detected compounds that represent 86% of the estimated chemical diversity of the metabolites listed in the LycoCyc database. Following a proof-of-safety approach, we show that % had an acceptable range of variation while simultaneously indicating a reproducible transformation-related metabolic signature. We conclude that multi-platform metabolomics is an approach that is both sensitive and robust and that it constitutes a good starting point for characterizing genetically modified organisms.

Covering Chemical Diversity of Genetically-Modified Tomatoes Using Metabolomics for Objective Substantial Equivalence Assessment

Science.gov (United States)

Hirai, Tadayoshi; Oikawa, Akira; Matsuda, Fumio; Fukushima, Atsushi; Arita, Masanori; Watanabe, Shin; Yano, Megumu; Hiwasa-Tanase, Kyoko; Ezura, Hiroshi; Saito, Kazuki

2011-01-01

As metabolomics can provide a biochemical snapshot of an organism's phenotype it is a promising approach for charting the unintended effects of genetic modification. A critical obstacle for this application is the inherently limited metabolomic coverage of any single analytical platform. We propose using multiple analytical platforms for the direct acquisition of an interpretable data set of estimable chemical diversity. As an example, we report an application of our multi-platform approach that assesses the substantial equivalence of tomatoes over-expressing the taste-modifying protein miraculin. In combination, the chosen platforms detected compounds that represent 86% of the estimated chemical diversity of the metabolites listed in the LycoCyc database. Following a proof-of-safety approach, we show that % had an acceptable range of variation while simultaneously indicating a reproducible transformation-related metabolic signature. We conclude that multi-platform metabolomics is an approach that is both sensitive and robust and that it constitutes a good starting point for characterizing genetically modified organisms. PMID:21359231

Objective quantification of the tinnitus decompensation by synchronization measures of auditory evoked single sweeps.

Science.gov (United States)

Strauss, Daniel J; Delb, Wolfgang; D'Amelio, Roberto; Low, Yin Fen; Falkai, Peter

2008-02-01

Large-scale neural correlates of the tinnitus decompensation might be used for an objective evaluation of therapies and neurofeedback based therapeutic approaches. In this study, we try to identify large-scale neural correlates of the tinnitus decompensation using wavelet phase stability criteria of single sweep sequences of late auditory evoked potentials as synchronization stability measure. The extracted measure provided an objective quantification of the tinnitus decompensation and allowed for a reliable discrimination between a group of compensated and decompensated tinnitus patients. We provide an interpretation for our results by a neural model of top-down projections based on the Jastreboff tinnitus model combined with the adaptive resonance theory which has not been applied to model tinnitus so far. Using this model, our stability measure of evoked potentials can be linked to the focus of attention on the tinnitus signal. It is concluded that the wavelet phase stability of late auditory evoked potential single sweeps might be used as objective tinnitus decompensation measure and can be interpreted in the framework of the Jastreboff tinnitus model and adaptive resonance theory.

Single prolonged stress impairs social and object novelty recognition in rats.

Science.gov (United States)

Eagle, Andrew L; Fitzpatrick, Chris J; Perrine, Shane A

2013-11-01

Posttraumatic stress disorder (PTSD) results from exposure to a traumatic event and manifests as re-experiencing, arousal, avoidance, and negative cognition/mood symptoms. Avoidant symptoms, as well as the newly defined negative cognitions/mood, are a serious complication leading to diminished interest in once important or positive activities, such as social interaction; however, the basis of these symptoms remains poorly understood. PTSD patients also exhibit impaired object and social recognition, which may underlie the avoidance and symptoms of negative cognition, such as social estrangement or diminished interest in activities. Previous studies have demonstrated that single prolonged stress (SPS), models PTSD phenotypes, including impairments in learning and memory. Therefore, it was hypothesized that SPS would impair social and object recognition memory. Male Sprague Dawley rats were exposed to SPS then tested in the social choice test (SCT) or novel object recognition test (NOR). These tests measure recognition of novelty over familiarity, a natural preference of rodents. Results show that SPS impaired preference for both social and object novelty. In addition, SPS impairment in social recognition may be caused by impaired behavioral flexibility, or an inability to shift behavior during the SCT. These results demonstrate that traumatic stress can impair social and object recognition memory, which may underlie certain avoidant symptoms or negative cognition in PTSD and be related to impaired behavioral flexibility. Copyright © 2013 Elsevier B.V. All rights reserved.

Understanding of BRCA1/2 genetic tests results: the importance of objective and subjective numeracy.

Science.gov (United States)

Hanoch, Yaniv; Miron-Shatz, Talya; Rolison, Jonathan J; Ozanne, Elissa

2014-10-01

The majority of women (71%) who undergo BRCA1/2 testing-designed to identify genetic mutations associated with increased risk of cancer-receive results that are termed 'ambiguous' or 'uninformative negative'. How women interpret these results and the association with numerical ability was examined. In this study, 477 women at increased risk for breast and ovarian cancer were recruited via the Cancer Genetics Network. They were presented with information about the four different possible BRCA1/2 test results-positive, true negative, ambiguous and uninformative negative-and asked to indicate which of six options represents the best response. Participants were then asked which treatment options they thought a woman receiving the results should discuss with her doctor. Finally, participants completed measures of objective and subjective numeracy. Almost all of the participants correctly interpreted the positive and negative BRCA1/2 genetic test results. However, they encountered difficulties interpreting the uninformative and ambiguous BRCA1/2 genetic test results. Participants were almost equally likely to think either that the woman had learned nothing from the test result or that she was as likely to develop cancer as the average woman. Highly numerate participants were more likely to correctly interpret inconclusive test results (ambiguous, OR = 1.62; 95% CI [1.28, 2.07]; p psychological ramifications of genetic testing, healthcare professionals should consider devoting extra effort to ensuring proper comprehension of ambiguous and uninformative negative test results by women. Copyright © 2014 John Wiley & Sons, Ltd.

Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method

Science.gov (United States)

Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan

2017-05-01

In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability.

The Formation of Optimal Portfolio of Mutual Shares Funds using Multi-Objective Genetic Algorithm

Directory of Open Access Journals (Sweden)

Yandra Arkeman

2013-09-01

Full Text Available Investments in financial assets have become a trend in the globalization era, especially the investment in mutual fund shares. Investors who want to invest in stock mutual funds can set up an investment portfolio in order to generate a minimal risk and maximum return. In this study the authors used the Multi-Objective Genetic Algorithm Non-dominated Sorting II (MOGA NSGA-II technique with the Markowitz portfolio principle to find the best portfolio from several mutual funds. The data used are 10 company stock mutual funds with a period of 12 months, 24 months and 36 months. The genetic algorithm parameters used are crossover probability of 0.65, mutation probability of 0.05, Generation 400 and a population numbering 20 individuals. The study produced a combination of the best portfolios for the period of 24 months with a computing time of 63,289 seconds.

From Single- to Multi-Objective Auto-Tuning of Programs: Advantages and Implications

Directory of Open Access Journals (Sweden)

Juan Durillo

2014-01-01

Full Text Available Automatic tuning (auto-tuning of software has emerged in recent years as a promising method that tries to automatically adapt the behaviour of a program to attain different performance objectives on a given computing system. This method is gaining momentum due to the increasing complexity of modern multicore-based hardware architectures. Many solutions to auto-tuning have been explored ranging from simple random search to more sophisticate methods like machine learning or evolutionary search. To this day, it is still unclear whether these approaches are general enough to encompass all the complexities of the problem (e.g. search space, parameters influencing the search space, input data sensitivity, etc., or which approach is best suited for a given problem. Furthermore, the growing interest in auto-tuning a program for several objectives is increasing this confusion even further. The goal of this paper is to formally describe the problem addressed by auto-tuning programs and review existing solutions highlighting the advantages and drawbacks of different techniques for single-objective as well as multi-objective auto-tuning approaches.

Effect of genetic homogeneity on behavioural variability in an object recognition test in cloned Göttingen minipigs

DEFF Research Database (Denmark)

Søndergaard, Lene Vammen; Herskin, Mette S.; Ladewig, Jan

2012-01-01

effects of genetic homogeneity on variability of cloned minipigs compared with non-cloned controls regarding behavioural variables in a cognitive test, namely the spontaneous object recognition test. Significant differences in the variability between the cloned and control pigs were found in five out...... was numerically greater for the control group compared to the cloned group, indicating that variation may be less in cloned animals, but not demonstrable with the small group size of the present study (n = 6 for each of the two groups tested). Overall, this study failed to show unambiguously that variability......The number of animals used in research should be limited as much as possible. Among cloned animals, genetic variation is minimal and to the extent that behaviour is genetically determined inter-individual variability is expected to be higher among naturally bred animals. However, the cloning...

Assessment of Genetic Diversity in Faba Bean Based on Single Nucleotide Polymorphism

Directory of Open Access Journals (Sweden)

Sukhjiwan Kaur

2014-01-01

Full Text Available Detection of genetic diversity is important for characterisation of crop plant collections in order to detect the presence of valuable trait variation for use in breeding programs. A collection of faba bean (Vicia faba L. genotypes was evaluated for intra- and inter-population diversity using a set of 768 genome-wide distributed single nucleotide polymorphism (SNP markers, of which 657 obtained successful amplification and detected polymorphisms. Gene diversity and polymorphism information content (PIC values varied between 0.022–0.500 and 0.023–1.00, with averages of 0.363 and 0.287, respectively. The genetic structure of the germplasm collection was analysed and a neighbour-joining (NJ dendrogram was constructed. The faba bean accessions grouped into two major groups, with several additional smaller sub-groups, predominantly on the basis of geographical origin. These results were further supported by principal co-ordinate analysis (PCoA, deriving two major groupings which were differentiated on the basis of site of origin and pedigree relationships. In general, high levels of heterozygosity were observed, presumably due to the partially allogamous nature of the species. The results will facilitate targeted crossing strategies in future faba bean breeding programs in order to achieve genetic gain.

Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method.

Science.gov (United States)

Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan

2017-05-01

In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability. Copyright © 2017 Elsevier B.V. All rights reserved.

Probing optimal measurement configuration for optical scatterometry by the multi-objective genetic algorithm

Science.gov (United States)

Chen, Xiuguo; Gu, Honggang; Jiang, Hao; Zhang, Chuanwei; Liu, Shiyuan

2018-04-01

Measurement configuration optimization (MCO) is a ubiquitous and important issue in optical scatterometry, whose aim is to probe the optimal combination of measurement conditions, such as wavelength, incidence angle, azimuthal angle, and/or polarization directions, to achieve a higher measurement precision for a given measuring instrument. In this paper, the MCO problem is investigated and formulated as a multi-objective optimization problem, which is then solved by the multi-objective genetic algorithm (MOGA). The case study on the Mueller matrix scatterometry for the measurement of a Si grating verifies the feasibility of the MOGA in handling the MCO problem in optical scatterometry by making a comparison with the Monte Carlo simulations. Experiments performed at the achieved optimal measurement configuration also show good agreement between the measured and calculated best-fit Mueller matrix spectra. The proposed MCO method based on MOGA is expected to provide a more general and practical means to solve the MCO problem in the state-of-the-art optical scatterometry.

Application of multi-objective optimization based on genetic algorithm for sustainable strategic supplier selection under fuzzy environment

Energy Technology Data Exchange (ETDEWEB)

Hashim, M.; Nazam, M.; Yao, L.; Baig, S.A.; Abrar, M.; Zia-ur-Rehman, M.

2017-07-01

The incorporation of environmental objective into the conventional supplier selection practices is crucial for corporations seeking to promote green supply chain management (GSCM). Challenges and risks associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. This paper aims to solve a Tetra “S” (SSSS) problem based on a fuzzy multi-objective optimization with genetic algorithm in a holistic supply chain environment. In this empirical study, a mathematical model with fuzzy coefficients is considered for sustainable strategic supplier selection (SSSS) problem and a corresponding model is developed to tackle this problem. Design/methodology/approach: Sustainable strategic supplier selection (SSSS) decisions are typically multi-objectives in nature and it is an important part of green production and supply chain management for many firms. The proposed uncertain model is transferred into deterministic model by applying the expected value mesurement (EVM) and genetic algorithm with weighted sum approach for solving the multi-objective problem. This research focus on a multi-objective optimization model for minimizing lean cost, maximizing sustainable service and greener product quality level. Finally, a mathematical case of textile sector is presented to exemplify the effectiveness of the proposed model with a sensitivity analysis. Findings: This study makes a certain contribution by introducing the Tetra ‘S’ concept in both the theoretical and practical research related to multi-objective optimization as well as in the study of sustainable strategic supplier selection (SSSS) under uncertain environment. Our results suggest that decision makers tend to select strategic supplier first then enhance the sustainability. Research limitations/implications: Although the fuzzy expected value model (EVM) with fuzzy coefficients constructed in present research should be helpful for solving real world

Application of multi-objective optimization based on genetic algorithm for sustainable strategic supplier selection under fuzzy environment

Directory of Open Access Journals (Sweden)

Muhammad Hashim

2017-05-01

Full Text Available Purpose:  The incorporation of environmental objective into the conventional supplier selection practices is crucial for corporations seeking to promote green supply chain management (GSCM. Challenges and risks associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. This paper aims to solve a Tetra “S” (SSSS problem based on a fuzzy multi-objective optimization with genetic algorithm in a holistic supply chain environment. In this empirical study, a mathematical model with fuzzy coefficients is considered for sustainable strategic supplier selection (SSSS problem and a corresponding model is developed to tackle this problem. Design/methodology/approach: Sustainable strategic supplier selection (SSSS decisions are typically multi-objectives in nature and it is an important part of green production and supply chain management for many firms. The proposed uncertain model is transferred into deterministic model by applying the expected value mesurement (EVM and genetic algorithm with weighted sum approach for solving the multi-objective problem. This research focus on a multi-objective optimization model for minimizing lean cost, maximizing sustainable service and greener product quality level. Finally, a mathematical case of textile sector is presented to exemplify the effectiveness of the proposed model with a sensitivity analysis. Findings: This study makes a certain contribution by introducing the Tetra ‘S’ concept in both the theoretical and practical research related to multi-objective optimization as well as in the study of sustainable strategic supplier selection (SSSS under uncertain environment. Our results suggest that decision makers tend to select strategic supplier first then enhance the sustainability. Research limitations/implications: Although the fuzzy expected value model (EVM with fuzzy coefficients constructed in present research should be helpful for

Application of multi-objective optimization based on genetic algorithm for sustainable strategic supplier selection under fuzzy environment

International Nuclear Information System (INIS)

Hashim, M.; Nazam, M.; Yao, L.; Baig, S.A.; Abrar, M.; Zia-ur-Rehman, M.

2017-01-01

The incorporation of environmental objective into the conventional supplier selection practices is crucial for corporations seeking to promote green supply chain management (GSCM). Challenges and risks associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. This paper aims to solve a Tetra “S” (SSSS) problem based on a fuzzy multi-objective optimization with genetic algorithm in a holistic supply chain environment. In this empirical study, a mathematical model with fuzzy coefficients is considered for sustainable strategic supplier selection (SSSS) problem and a corresponding model is developed to tackle this problem. Design/methodology/approach: Sustainable strategic supplier selection (SSSS) decisions are typically multi-objectives in nature and it is an important part of green production and supply chain management for many firms. The proposed uncertain model is transferred into deterministic model by applying the expected value mesurement (EVM) and genetic algorithm with weighted sum approach for solving the multi-objective problem. This research focus on a multi-objective optimization model for minimizing lean cost, maximizing sustainable service and greener product quality level. Finally, a mathematical case of textile sector is presented to exemplify the effectiveness of the proposed model with a sensitivity analysis. Findings: This study makes a certain contribution by introducing the Tetra ‘S’ concept in both the theoretical and practical research related to multi-objective optimization as well as in the study of sustainable strategic supplier selection (SSSS) under uncertain environment. Our results suggest that decision makers tend to select strategic supplier first then enhance the sustainability. Research limitations/implications: Although the fuzzy expected value model (EVM) with fuzzy coefficients constructed in present research should be helpful for solving real world

Multi-objective optimization design of air distribution of grate cooler by entropy generation minimization and genetic algorithm

International Nuclear Information System (INIS)

Shao, Wei; Cui, Zheng; Cheng, Lin

2016-01-01

Highlights: • A multi-objective optimization model of air distribution of grate cooler by genetic algorithm is proposed. • Pareto Front is obtained and validated by comparing with operating data. • Optimal schemes are compared and selected by engineering background. • Total power consumption after optimization decreases 61.10%. • Thickness of clinker on three grate plates is thinner. - Abstract: The cooling air distributions of grate cooler exercise a great influence on the clinker cooling efficiency and power consumption of cooling fans. A multi-objective optimization model of air distributions of grate cooler with cross-flow heat exchanger analogy is proposed in this paper. Firstly, thermodynamic and flow models of clinker cooling process is carried out. Then based on entropy generation minimization analysis, modified entropy generation numbers caused by heat transfer and pressure drop are chosen as objective functions respectively which optimized by genetic algorithm. The design variables are superficial velocities of air chambers and thicknesses of clinker layers on different grate plates. A set of Pareto optimal solutions which two objectives are optimized simultaneously is achieved. Scattered distributions of design variables resulting in the conflict between two objectives are brought out. The final optimal air distribution and thicknesses of clinker layers are selected from the Pareto optimal solutions based on power consumption of cooling fans minimization and validated by measurements. Compared with actual operating scheme, the total air volumes of optimized schemes decrease 2.4%, total power consumption of cooling fans decreases 61.1% and the outlet temperature of clinker decreases 122.9 °C which shows a remarkable energy-saving effect on energy consumption.

A calderón-preconditioned single source combined field integral equation for analyzing scattering from homogeneous penetrable objects

KAUST Repository

Valdé s, Felipe; Andriulli, Francesco P.; Bagci, Hakan; Michielssen, Eric

2011-01-01

A new regularized single source equation for analyzing scattering from homogeneous penetrable objects is presented. The proposed equation is a linear combination of a Calderón-preconditioned single source electric field integral equation and a

A Single Unexpected Change in Target- but Not Distractor Motion Impairs Multiple Object Tracking

Directory of Open Access Journals (Sweden)

Hauke S. Meyerhoff

2013-02-01

Full Text Available Recent research addresses the question whether motion information of multiple objects contributes to maintaining a selection of objects across a period of motion. Here, we investigate whether target and/or distractor motion information is used during attentive tracking. We asked participants to track four objects and changed either the motion direction of targets, the motion direction of distractors, neither, or both during a brief flash in the middle of a tracking interval. We observed that a single direction change of targets is sufficient to impair tracking performance. In contrast, changing the motion direction of distractors had no effect on performance. This indicates that target- but not distractor motion information is evaluated during tracking.

Genetic effects of high LET radiations

International Nuclear Information System (INIS)

Grahn, D.; Garriott, M.L.; Farrington, B.H.; Lee, C.H.; Russell, J.J.

1981-01-01

The objectives of this project are: (1) to assess genetic hazards from testicular burdens of 239 Pu and determine its retention and microdistribution in the testis; (2) to compare effects of 239 Pu with single, weekly, and continuous 60 Co gamma irradiation and single and weekly fission neutron irradiation to develop a basis for estimating relative biological effectiveness (RBE); and (3) to develop detailed dose-response data for genetic end points of concern at low doses of neutrons and gamma rays. Comparatively short-term genetic end points are used, namely: (1) the dominant lethal mutation rate in premeiotic and postmeiotic cell stages; (2) the frequency of abnormal sperm head morphology measured at various times after irradiation; and (3) the frequency of reciprocal chromosome translocations induced in spermatogonia and measured at first meiotic metaphase. Male hybrid B6CF 1 mice, 120 days old, are used for all studies. Measures of the retention, microdistributionand pollutant related changes. Assessment of human risk associated with nuclearing collective dose commitment will result in more attention being paid to potential releases of radionuclides at relatively short times after disposal

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

OpenAIRE

Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of tra...

Clinical and Genetic Associations of Objectively Identified Interstitial Changes in Smokers.

Science.gov (United States)

Ash, Samuel Y; Harmouche, Rola; Putman, Rachel K; Ross, James C; Diaz, Alejandro A; Hunninghake, Gary M; Onieva Onieva, Jorge; Martinez, Fernando J; Choi, Augustine M; Lynch, David A; Hatabu, Hiroto; Rosas, Ivan O; San Jose Estepar, Raul; Washko, George R

2017-10-01

Smoking-related lung injury may manifest on CT scans as both emphysema and interstitial changes. We have developed an automated method to quantify interstitial changes and hypothesized that this measurement would be associated with lung function, quality of life, mortality, and a mucin 5B (MUC5B) polymorphism. Using CT scans from the Genetic Epidemiology of COPD Study, we objectively labeled lung parenchyma as a tissue subtype. We calculated the percentage of the lung occupied by interstitial subtypes. A total of 8,345 participants had clinical and CT scanning data available. A 5% absolute increase in interstitial changes was associated with an absolute decrease in FVC % predicted of 2.47% (P percentage of lung with interstitial changes. Objective interstitial changes on CT scans were associated with impaired lung function, worse quality of life, increased mortality, and more copies of a MUC5B promoter polymorphism, suggesting that these changes may be a marker of susceptibility to smoking-related lung injury, detectable even in those who are healthy by other measures. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Mutation Scanning in a Single and a Stacked Genetically Modified (GM) Event by Real-Time PCR and High Resolution Melting (HRM) Analysis

Science.gov (United States)

Ben Ali, Sina-Elisabeth; Madi, Zita Erika; Hochegger, Rupert; Quist, David; Prewein, Bernhard; Haslberger, Alexander G.; Brandes, Christian

2014-01-01

Genetic mutations must be avoided during the production and use of seeds. In the European Union (EU), Directive 2001/18/EC requires any DNA construct introduced via transformation to be stable. Establishing genetic stability is critical for the approval of genetically modified organisms (GMOs). In this study, genetic stability of two GMOs was examined using high resolution melting (HRM) analysis and real-time polymerase chain reaction (PCR) employing Scorpion primers for amplification. The genetic variability of the transgenic insert and that of the flanking regions in a single oilseed rape variety (GT73) and a stacked maize (MON88017 × MON810) was studied. The GT73 and the 5' region of MON810 showed no instabilities in the examined regions. However; two out of 100 analyzed samples carried a heterozygous point mutation in the 3' region of MON810 in the stacked variety. These results were verified by direct sequencing of the amplified PCR products as well as by sequencing of cloned PCR fragments. The occurrence of the mutation suggests that the 5' region is more suitable than the 3' region for the quantification of MON810. The identification of the single nucleotide polymorphism (SNP) in a stacked event is in contrast to the results of earlier studies of the same MON810 region in a single event where no DNA polymorphism was found. PMID:25365178

Multi Objective Optimization Using Genetic Algorithm of a Pneumatic Connector

Science.gov (United States)

Salaam, HA; Taha, Zahari; Ya, TMYS Tuan

2018-03-01

The concept of sustainability was first introduced by Dr Harlem Brutland in the 1980’s promoting the need to preserve today’s natural environment for the sake of future generations. Based on this concept, John Elkington proposed an approach to measure sustainability known as Triple Bottom Line (TBL). There are three evaluation criteria’s involved in the TBL approach; namely economics, environmental integrity and social equity. In manufacturing industry the manufacturing costs measure the economic sustainability of a company in a long term. Environmental integrity is a measure of the impact of manufacturing activities on the environment. Social equity is complicated to evaluate; but when the focus is at the production floor level, the production operator health can be considered. In this paper, the TBL approach is applied in the manufacturing of a pneumatic nipple hose. The evaluation criteria used are manufacturing costs, environmental impact, ergonomics impact and also energy used for manufacturing. This study involves multi objective optimization by using genetic algorithm of several possible alternatives for material used in the manufacturing of the pneumatic nipple.

Single and multiple object tracking using log-euclidean Riemannian subspace and block-division appearance model.

Science.gov (United States)

Hu, Weiming; Li, Xi; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen; Zhang, Zhongfei

2012-12-01

Object appearance modeling is crucial for tracking objects, especially in videos captured by nonstationary cameras and for reasoning about occlusions between multiple moving objects. Based on the log-euclidean Riemannian metric on symmetric positive definite matrices, we propose an incremental log-euclidean Riemannian subspace learning algorithm in which covariance matrices of image features are mapped into a vector space with the log-euclidean Riemannian metric. Based on the subspace learning algorithm, we develop a log-euclidean block-division appearance model which captures both the global and local spatial layout information about object appearances. Single object tracking and multi-object tracking with occlusion reasoning are then achieved by particle filtering-based Bayesian state inference. During tracking, incremental updating of the log-euclidean block-division appearance model captures changes in object appearance. For multi-object tracking, the appearance models of the objects can be updated even in the presence of occlusions. Experimental results demonstrate that the proposed tracking algorithm obtains more accurate results than six state-of-the-art tracking algorithms.

From tomography to full-waveform inversion with a single objective function

KAUST Repository

Alkhalifah, Tariq Ali

2014-02-17

In full-waveform inversion (FWI), a gradient-based update of the velocity model requires an initial velocity that produces synthetic data that are within a half-cycle, everywhere, from the field data. Such initial velocity models are usually extracted from migration velocity analysis or traveltime tomography, among other means, and are not guaranteed to adhere to the FWI requirements for an initial velocity model. As such, we evaluated an objective function based on the misfit in the instantaneous traveltime between the observed and modeled data. This phase-based attribute of the wavefield, along with its phase unwrapping characteristics, provided a frequency-dependent traveltime function that was easy to use and quantify, especially compared to conventional phase representation. With a strong Laplace damping of the modeled, potentially low-frequency, data along the time axis, this attribute admitted a first-arrival traveltime that could be compared with picked ones from the observed data, such as in wave equation tomography (WET). As we relax the damping on the synthetic and observed data, the objective function measures the misfit in the phase, however unwrapped. It, thus, provided a single objective function for a natural transition from WET to FWI. A Marmousi example demonstrated the effectiveness of the approach.

Multi-objective genetic algorithm optimization of 2D- and 3D-Pareto fronts for vibrational quantum processes

International Nuclear Information System (INIS)

Gollub, C; De Vivie-Riedle, R

2009-01-01

A multi-objective genetic algorithm is applied to optimize picosecond laser fields, driving vibrational quantum processes. Our examples are state-to-state transitions and unitary transformations. The approach allows features of the shaped laser fields and of the excitation mechanisms to be controlled simultaneously with the quantum yield. Within the parameter range accessible to the experiment, we focus on short pulse durations and low pulse energies to optimize preferably robust laser fields. Multidimensional Pareto fronts for these conflicting objectives could be constructed. Comparison with previous work showed that the solutions from Pareto optimizations and from optimal control theory match very well.

Design of a hybrid double-sideband/single-sideband (schlieren) objective aperture suitable for electron microscopy

Energy Technology Data Exchange (ETDEWEB)

Buijsse, Bart; Laarhoven, Frank M.H.M. van [FEI Company, PO Box 80066, 5600 KA Eindhoven (Netherlands); Schmid, Andreas K.; Cambie, Rossana; Cabrini, Stefano; Jin, Jian [Lawrence Berkeley National Laboratory, University of California, Berkeley, CA 94720 (United States); Glaeser, Robert M., E-mail: rmglaeser@lbl.gov [Lawrence Berkeley National Laboratory, University of California, Berkeley, CA 94720 (United States)

2011-12-15

A novel design is described for an aperture that blocks a half-plane of the electron diffraction pattern out to a desired scattering angle, and then - except for a narrow support beam - transmits all of the scattered electrons beyond that angle. Our proposed tulip-shaped design is thus a hybrid between the single-sideband (ssb) aperture, which blocks a full half-plane of the diffraction pattern, and the conventional (i.e. fully open) double-sideband (dsb) aperture. The benefits of this hybrid design include the fact that such an aperture allows one to obtain high-contrast images of weak-phase objects with the objective lens set to Scherzer defocus. We further demonstrate that such apertures can be fabricated from thin-foil materials by milling with a focused ion beam (FIB), and that such apertures are fully compatible with the requirements of imaging out to a resolution of at least 0.34 nm. As is known from earlier work with single-sideband apertures, however, the edge of such an aperture can introduce unwanted, electrostatic phase shifts due to charging. The principal requirement for using such an aperture in a routine data-collection mode is thus to discover appropriate materials, protocols for fabrication and processing and conditions of use such that the hybrid aperture remains free of charging over long periods of time. -- Highlights: Black-Right-Pointing-Pointer New objective-aperture design is proposed for imaging weak-phase objects. Black-Right-Pointing-Pointer Design produces single-sideband contrast at low spatial frequencies. Black-Right-Pointing-Pointer Design also retains Scherzer-defocus phase contrast at higher resolution. Black-Right-Pointing-Pointer Proof-of-concept results are presented for microfabricated apertures. Black-Right-Pointing-Pointer Charging of such apertures during use remains an experimental challenge.

Simultaneous positioning and orientation of a single nano-object by flow control: theory and simulations

International Nuclear Information System (INIS)

Mathai, Pramod P; Berglund, Andrew J; Alexander Liddle, J; Shapiro, Benjamin A

2011-01-01

In this paper, we theoretically describe a method to simultaneously control both the position and orientation of single nano-objects in fluids by precisely controlling the flow around them. We develop and simulate a control law that uses electro-osmotic flow (EOF) actuation to translate and rotate rigid nano-objects in two spatial dimensions. Using EOF to control nano-objects offers advantages as compared to other approaches: a wide class of objects can be manipulated (no magnetic or electric dipole moments are needed), the object can be controlled over a long range (>100 μm) with sub-micrometer accuracy, and control may be achieved with simple polydimethylsiloxane (PDMS) devices. We demonstrate the theory and numerical solutions that will enable deterministic control of the position and orientation of a nano-object in solution, which can be used, for example, to integrate nanostructures in circuits and orient sensors to probe living cells.

Genetic and biochemical identification of a novel single-stranded DNA binding complex in Haloferax volcanii

Directory of Open Access Journals (Sweden)

Amy eStroud

2012-06-01

Full Text Available Single-stranded DNA binding proteins play an essential role in DNA replication and repair. They use oligosaccharide-binding folds, a five-stranded ß-sheet coiled into a closed barrel, to bind to single-stranded DNA thereby protecting and stabilizing the DNA. In eukaryotes the single-stranded DNA binding protein is known as replication protein A (RPA and consists of three distinct subunits that function as a heterotrimer. The bacterial homolog is termed single-stranded DNA-binding protein (SSB and functions as a homotetramer. In the archaeon Haloferax volcanii there are three genes encoding homologs of RPA. Two of the rpa genes (rpa1 and rpa3 exist in operons with a novel gene specific to Euryarchaeota, this gene encodes a protein that we have termed rpa-associated protein (RPAP. The rpap genes encode proteins belonging to COG3390 group and feature oligosaccharide-binding folds, suggesting that they might cooperate with RPA in binding to single-stranded DNA. Our genetic analysis showed that rpa1 and rpa3 deletion mutants have differing phenotypes; only ∆rpa3 strains are hypersensitive to DNA damaging agents. Deletion of the rpa3-associated gene rpap3 led to similar levels of DNA damage sensitivity, as did deletion of the rpa3 operon, suggesting that RPA3 and RPAP3 function in the same pathway. Protein pull-downs involving recombinant hexahistidine-tagged RPAs showed that RPA3 co-purifies with RPAP3, and RPA1 co-purifies with RPAP1. This indicates that the RPAs interact only with their respective associated proteins; this was corroborated by the inability to construct rpa1 rpap3 and rpa3 rpap1 double mutants. This is the first report investigating the individual function of the archaeal COG3390 RPA-associated proteins. We have shown genetically and biochemically that the RPAPs interact with their respective RPAs, and have uncovered a novel single-stranded DNA binding complex that is unique to Euryarchaeota.

Time-domain single-source integral equations for analyzing scattering from homogeneous penetrable objects

KAUST Repository

Valdés, Felipe

2013-03-01

Single-source time-domain electric-and magnetic-field integral equations for analyzing scattering from homogeneous penetrable objects are presented. Their temporal discretization is effected by using shifted piecewise polynomial temporal basis functions and a collocation testing procedure, thus allowing for a marching-on-in-time (MOT) solution scheme. Unlike dual-source formulations, single-source equations involve space-time domain operator products, for which spatial discretization techniques developed for standalone operators do not apply. Here, the spatial discretization of the single-source time-domain integral equations is achieved by using the high-order divergence-conforming basis functions developed by Graglia alongside the high-order divergence-and quasi curl-conforming (DQCC) basis functions of Valdés The combination of these two sets allows for a well-conditioned mapping from div-to curl-conforming function spaces that fully respects the space-mapping properties of the space-time operators involved. Numerical results corroborate the fact that the proposed procedure guarantees accuracy and stability of the MOT scheme. © 2012 IEEE.

Using genetic algorithm and TOPSIS for Xinanjiang model calibration with a single procedure

Science.gov (United States)

Cheng, Chun-Tian; Zhao, Ming-Yan; Chau, K. W.; Wu, Xin-Yu

2006-01-01

Genetic Algorithm (GA) is globally oriented in searching and thus useful in optimizing multiobjective problems, especially where the objective functions are ill-defined. Conceptual rainfall-runoff models that aim at predicting streamflow from the knowledge of precipitation over a catchment have become a basic tool for flood forecasting. The parameter calibration of a conceptual model usually involves the multiple criteria for judging the performances of observed data. However, it is often difficult to derive all objective functions for the parameter calibration problem of a conceptual model. Thus, a new method to the multiple criteria parameter calibration problem, which combines GA with TOPSIS (technique for order performance by similarity to ideal solution) for Xinanjiang model, is presented. This study is an immediate further development of authors' previous research (Cheng, C.T., Ou, C.P., Chau, K.W., 2002. Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall-runoff model calibration. Journal of Hydrology, 268, 72-86), whose obvious disadvantages are to split the whole procedure into two parts and to become difficult to integrally grasp the best behaviors of model during the calibration procedure. The current method integrates the two parts of Xinanjiang rainfall-runoff model calibration together, simplifying the procedures of model calibration and validation and easily demonstrated the intrinsic phenomenon of observed data in integrity. Comparison of results with two-step procedure shows that the current methodology gives similar results to the previous method, is also feasible and robust, but simpler and easier to apply in practice.

Solving multi-objective job shop scheduling problems using a non-dominated sorting genetic algorithm

Science.gov (United States)

Piroozfard, Hamed; Wong, Kuan Yew

2015-05-01

The efforts of finding optimal schedules for the job shop scheduling problems are highly important for many real-world industrial applications. In this paper, a multi-objective based job shop scheduling problem by simultaneously minimizing makespan and tardiness is taken into account. The problem is considered to be more complex due to the multiple business criteria that must be satisfied. To solve the problem more efficiently and to obtain a set of non-dominated solutions, a meta-heuristic based non-dominated sorting genetic algorithm is presented. In addition, task based representation is used for solution encoding, and tournament selection that is based on rank and crowding distance is applied for offspring selection. Swapping and insertion mutations are employed to increase diversity of population and to perform intensive search. To evaluate the modified non-dominated sorting genetic algorithm, a set of modified benchmarking job shop problems obtained from the OR-Library is used, and the results are considered based on the number of non-dominated solutions and quality of schedules obtained by the algorithm.

hamlet, a binary genetic switch between single- and multiple- dendrite neuron morphology.

Science.gov (United States)

Moore, Adrian W; Jan, Lily Yeh; Jan, Yuh Nung

2002-08-23

The dendritic morphology of neurons determines the number and type of inputs they receive. In the Drosophila peripheral nervous system (PNS), the external sensory (ES) neurons have a single nonbranched dendrite, whereas the lineally related multidendritic (MD) neurons have extensively branched dendritic arbors. We report that hamlet is a binary genetic switch between these contrasting morphological types. In hamlet mutants, ES neurons are converted to an MD fate, whereas ectopic hamlet expression in MD precursors results in transformation of MD neurons into ES neurons. Moreover, hamlet expression induced in MD neurons undergoing dendrite outgrowth drastically reduces arbor branching.

Effects of Implied Motion and Facing Direction on Positional Preferences in Single-Object Pictures.

Science.gov (United States)

Palmer, Stephen E; Langlois, Thomas A

2017-07-01

Palmer, Gardner, and Wickens studied aesthetic preferences for pictures of single objects and found a strong inward bias: Right-facing objects were preferred left-of-center and left-facing objects right-of-center. They found no effect of object motion (people and cars showed the same inward bias as chairs and teapots), but the objects were not depicted as moving. Here we measured analogous inward biases with objects depicted as moving with an implied direction and speed by having participants drag-and-drop target objects into the most aesthetically pleasing position. In Experiment 1, human figures were shown diving or falling while moving forward or backward. Aesthetic biases were evident for both inward-facing and inward-moving figures, but the motion-based bias dominated so strongly that backward divers or fallers were preferred moving inward but facing outward. Experiment 2 investigated implied speed effects using images of humans, horses, and cars moving at different speeds (e.g., standing, walking, trotting, and galloping horses). Inward motion or facing biases were again present, and differences in their magnitude due to speed were evident. Unexpectedly, faster moving objects were generally preferred closer to frame center than slower moving objects. These results are discussed in terms of the combined effects of prospective, future-oriented biases, and retrospective, past-oriented biases.

Multilocus genetic models of handedness closely resemble single-locus models in explaining family data and are compatible with genome-wide association studies.

Science.gov (United States)

McManus, I C; Davison, Angus; Armour, John A L

2013-06-01

Right- and left-handedness run in families, show greater concordance in monozygotic than dizygotic twins, and are well described by single-locus Mendelian models. Here we summarize a large genome-wide association study (GWAS) that finds no significant associations with handedness and is consistent with a meta-analysis of GWASs. The GWAS had 99% power to detect a single locus using the conventional criterion of P < 5 × 10(-8) for the single locus models of McManus and Annett. The strong conclusion is that handedness is not controlled by a single genetic locus. A consideration of the genetic architecture of height, primary ciliary dyskinesia, and intelligence suggests that handedness inheritance can be explained by a multilocus variant of the McManus DC model, classical effects on family and twins being barely distinguishable from the single locus model. Based on the ENGAGE meta-analysis of GWASs, we estimate at least 40 loci are involved in determining handedness. © 2013 New York Academy of Sciences.

Potential Implications of Research on Genetic or Heritable Contributions to Pedophilia for the Objectives of Criminal Law

Science.gov (United States)

Berryessa, Colleen M.

2015-01-01

In recent years, there has been increasing scientific research on possible genetic or heritable influences to the etiology of pedophilia, driven by national and public concerns about better understanding the disorder in order to reduce children’s vulnerabilities to pedophilic and child sex offenders. This research has corresponded to growing academic dialogue on how advances in genetic research, especially concerning the causes and development of particular mental disorders or behaviors, may affect traditional practices of criminal law and how the justice system views, manages, and adjudicates different types of criminal behavior and offenders. This paper strives to supplement this dialogue by exploring several of the many possible effects and implications of research surrounding genetic or heritable contributions to pedophilia for the five widely accepted objectives that enforce and regulate the punishment of criminal law. These include retribution, incapacitation, deterrence, rehabilitation, and restoration. Although still currently in early stages, genetic and heritability research on the etiology of pedophilia may have the potential moving forward to influence the current and established punitive methods and strategies of how the justice system perceives, adjudicates, regulates, and punishes pedophilic and sex offenders, as well as how to best prevent sexual offending against children by pedophilic offenders in the future. PMID:25557668

Unraveling the genetic architecture of environmental variance of somatic cell score using high-density single nucleotide polymorphism and cow data from experimental farms

NARCIS (Netherlands)

Mulder, H.A.; Crump, R.E.; Calus, M.P.L.; Veerkamp, R.F.

2013-01-01

In recent years, it has been shown that not only is the phenotype under genetic control, but also the environmental variance. Very little, however, is known about the genetic architecture of environmental variance. The main objective of this study was to unravel the genetic architecture of the mean

Genetic modification and genetic determinism

Science.gov (United States)

Resnik, David B; Vorhaus, Daniel B

2006-01-01

In this article we examine four objections to the genetic modification of human beings: the freedom argument, the giftedness argument, the authenticity argument, and the uniqueness argument. We then demonstrate that each of these arguments against genetic modification assumes a strong version of genetic determinism. Since these strong deterministic assumptions are false, the arguments against genetic modification, which assume and depend upon these assumptions, are therefore unsound. Serious discussion of the morality of genetic modification, and the development of sound science policy, should be driven by arguments that address the actual consequences of genetic modification for individuals and society, not by ones propped up by false or misleading biological assumptions. PMID:16800884

Genetic modification and genetic determinism

Directory of Open Access Journals (Sweden)

Vorhaus Daniel B

2006-06-01

Full Text Available Abstract In this article we examine four objections to the genetic modification of human beings: the freedom argument, the giftedness argument, the authenticity argument, and the uniqueness argument. We then demonstrate that each of these arguments against genetic modification assumes a strong version of genetic determinism. Since these strong deterministic assumptions are false, the arguments against genetic modification, which assume and depend upon these assumptions, are therefore unsound. Serious discussion of the morality of genetic modification, and the development of sound science policy, should be driven by arguments that address the actual consequences of genetic modification for individuals and society, not by ones propped up by false or misleading biological assumptions.

Barack Obama Blindness (BOB): Absence of Visual Awareness to a Single Object.

Science.gov (United States)

Persuh, Marjan; Melara, Robert D

2016-01-01

In two experiments, we evaluated whether a perceiver's prior expectations could alone obliterate his or her awareness of a salient visual stimulus. To establish expectancy, observers first made a demanding visual discrimination on each of three baseline trials. Then, on a fourth, critical trial, a single, salient and highly visible object appeared in full view at the center of the visual field and in the absence of any competing visual input. Surprisingly, fully half of the participants were unaware of the solitary object in front of their eyes. Dramatically, observers were blind even when the only stimulus on display was the face of U.S. President Barack Obama. We term this novel, counterintuitive phenomenon, Barack Obama Blindness (BOB). Employing a method that rules out putative memory effects by probing awareness immediately after presentation of the critical stimulus, we demonstrate that the BOB effect is a true failure of conscious vision.

Genetic algorithm-based optimization of testing and maintenance under uncertain unavailability and cost estimation: A survey of strategies for harmonizing evolution and accuracy

International Nuclear Information System (INIS)

Villanueva, J.F.; Sanchez, A.I.; Carlos, S.; Martorell, S.

2008-01-01

This paper presents the results of a survey to show the applicability of an approach based on a combination of distribution-free tolerance interval and genetic algorithms for testing and maintenance optimization of safety-related systems based on unavailability and cost estimation acting as uncertain decision criteria. Several strategies have been checked using a combination of Monte Carlo (simulation)--genetic algorithm (search-evolution). Tolerance intervals for the unavailability and cost estimation are obtained to be used by the genetic algorithms. Both single- and multiple-objective genetic algorithms are used. In general, it is shown that the approach is a robust, fast and powerful tool that performs very favorably in the face of noise in the output (i.e. uncertainty) and it is able to find the optimum over a complicated, high-dimensional nonlinear space in a tiny fraction of the time required for enumeration of the decision space. This approach reduces the computational effort by means of providing appropriate balance between accuracy of simulation and evolution; however, negative effects are also shown when a not well-balanced accuracy-evolution couple is used, which can be avoided or mitigated with the use of a single-objective genetic algorithm or the use of a multiple-objective genetic algorithm with additional statistical information

A Method for Interactive 3D Reconstruction of Piecewise Planar Objects from Single Images

OpenAIRE

Sturm , Peter; Maybank , Steve

1999-01-01

International audience; We present an approach for 3D reconstruction of objects from a single image. Obviously, constraints on the 3D structure are needed to perform this task. Our approach is based on user-provided coplanarity, perpendicularity and parallelism constraints. These are used to calibrate the image and perform 3D reconstruction. The method is described in detail and results are provided.

Estimates for Genetic Variance Components in Reciprocal Recurrent Selection in Populations Derived from Maize Single-Cross Hybrids

Directory of Open Access Journals (Sweden)

Matheus Costa dos Reis

2014-01-01

Full Text Available This study was carried out to obtain the estimates of genetic variance and covariance components related to intra- and interpopulation in the original populations (C0 and in the third cycle (C3 of reciprocal recurrent selection (RRS which allows breeders to define the best breeding strategy. For that purpose, the half-sib progenies of intrapopulation (P11 and P22 and interpopulation (P12 and P21 from populations 1 and 2 derived from single-cross hybrids in the 0 and 3 cycles of the reciprocal recurrent selection program were used. The intra- and interpopulation progenies were evaluated in a 10×10 triple lattice design in two separate locations. The data for unhusked ear weight (ear weight without husk and plant height were collected. All genetic variance and covariance components were estimated from the expected mean squares. The breakdown of additive variance into intrapopulation and interpopulation additive deviations (στ2 and the covariance between these and their intrapopulation additive effects (CovAτ found predominance of the dominance effect for unhusked ear weight. Plant height for these components shows that the intrapopulation additive effect explains most of the variation. Estimates for intrapopulation and interpopulation additive genetic variances confirm that populations derived from single-cross hybrids have potential for recurrent selection programs.

Single-Grasp Object Classification and Feature Extraction with Simple Robot Hands and Tactile Sensors.

Science.gov (United States)

Spiers, Adam J; Liarokapis, Minas V; Calli, Berk; Dollar, Aaron M

2016-01-01

Classical robotic approaches to tactile object identification often involve rigid mechanical grippers, dense sensor arrays, and exploratory procedures (EPs). Though EPs are a natural method for humans to acquire object information, evidence also exists for meaningful tactile property inference from brief, non-exploratory motions (a 'haptic glance'). In this work, we implement tactile object identification and feature extraction techniques on data acquired during a single, unplanned grasp with a simple, underactuated robot hand equipped with inexpensive barometric pressure sensors. Our methodology utilizes two cooperating schemes based on an advanced machine learning technique (random forests) and parametric methods that estimate object properties. The available data is limited to actuator positions (one per two link finger) and force sensors values (eight per finger). The schemes are able to work both independently and collaboratively, depending on the task scenario. When collaborating, the results of each method contribute to the other, improving the overall result in a synergistic fashion. Unlike prior work, the proposed approach does not require object exploration, re-grasping, grasp-release, or force modulation and works for arbitrary object start positions and orientations. Due to these factors, the technique may be integrated into practical robotic grasping scenarios without adding time or manipulation overheads.

Choice of genetic resources needed for achievement of relevant breeding objectives

International Nuclear Information System (INIS)

Murty, B.R.

1984-01-01

The author points out the importance of exploration, conservation and documentation of genetic resources and reviews the current status of utilization of available genetic resources and the present breeding strategies

Barack Obama Blindness (BOB: Absence of visual awareness to a single object

Directory of Open Access Journals (Sweden)

Marjan ePersuh

2016-03-01

Full Text Available In two experiments we evaluated whether a perceiver’s prior expectations could alone obliterate his or her awareness of a salient visual stimulus. To establish expectancy, observers first made a demanding visual discrimination on each of three baseline trials. Then, on a fourth, critical trial, a single, salient and highly visible object appeared in full view at the center of the visual field and in the absence of any competing visual input. Surprisingly, fully half of the participants were unaware of the solitary object in front of their eyes. Dramatically, observers were blind even when the only stimulus on display was the face of U.S. President Barack Obama. We term this novel, counterintuitive phenomenon, Barack Obama Blindness (BOB. Employing a method that rules out putative memory effects by probing awareness immediately after presentation of the critical stimulus, we demonstrate that the BOB effect is a true failure of conscious vision.

Neural evidence for competition-mediated suppression in the perception of a single object.

Science.gov (United States)

Cacciamani, Laura; Scalf, Paige E; Peterson, Mary A

2015-11-01

Multiple objects compete for representation in visual cortex. Competition may also underlie the perception of a single object. Computational models implement object perception as competition between units on opposite sides of a border. The border is assigned to the winning side, which is perceived as an object (or "figure"), whereas the other side is perceived as a shapeless ground. Behavioral experiments suggest that the ground is inhibited to a degree that depends on the extent to which it competed for object status, and that this inhibition is relayed to low-level brain areas. Here, we used fMRI to assess activation for ground regions of task-irrelevant novel silhouettes presented in the left or right visual field (LVF or RVF) while participants performed a difficult task at fixation. Silhouettes were designed so that the insides would win the competition for object status. The outsides (grounds) suggested portions of familiar objects in half of the silhouettes and novel objects in the other half. Because matches to object memories affect the competition, these two types of silhouettes operationalized, respectively, high competition and low competition from the grounds. The results showed that activation corresponding to ground regions was reduced for high- versus low-competition silhouettes in V4, where receptive fields (RFs) are large enough to encompass the familiar objects in the grounds, and in V1/V2, where RFs are much smaller. These results support a theory of object perception involving competition-mediated ground suppression and feedback from higher to lower levels. This pattern of results was observed in the left hemisphere (RVF), but not in the right hemisphere (LVF). One explanation of the lateralized findings is that task-irrelevant silhouettes in the RVF captured attention, allowing us to observe these effects, whereas those in the LVF did not. Experiment 2 provided preliminary behavioral evidence consistent with this possibility. Copyright �

A Case Study: Optimal Stage Gauge NetworkUsing Multi Objective Genetic Algorithm

Science.gov (United States)

Joo, H. J.; Han, D.; Jung, J.; Kim, H. S.

2017-12-01

Recently, the possibility of occurrence of localized strong heavy rainfall due to climate change is increasing and flood damage is also increasing trend in Korea. Therefore we need more precise hydrologic analysis for preparing alternatives or measures for flood reduction by considering climate conditions which we have difficulty in the prediction. To do this, obtaining reliable hydrologic data, for an example, stage data, is very important. However, the existing stage gauge stations are scattered around the country, making it difficult to maintain them in a stable manner, and subsequently hard to acquire the hydrologic data that could be used for reflecting the localized hydrologic characteristics. In order to overcome such restrictions, this paper not only aims to establish a plan to acquire the water stage data in a constant and proper manner by using limited manpower and costs, but also establishes the fundamental technology for acquiring the water level observation data or the stage data. For that, this paper identifies the current status of the stage gauge stations installed in the Chung-Ju dam in Han river, Korea and extract the factors related to the division and characteristics of basins. Then, the obtained factors are used to develop the representative unit hydrograph that shows the characteristics of flow. After that, the data are converted into the probability density function and the stations at individual basins are selected by using the entropy theory. In last step, we establish the optimized stage gauge network by the location of the stage station and grade using the Multi Objective Genetic Algorithm(MOGA) technique that takes into account for the combinations of the number of the stations. It is expected that this paper can help establish an optimal observational network of stage guages as it can be applied usefully not only for protecting against floods in a stable manner, but also for acquiring the hydrologic data in an efficient manner. Keywords

Sustainable Scheduling of Cloth Production Processes by Multi-Objective Genetic Algorithm with Tabu-Enhanced Local Search

Directory of Open Access Journals (Sweden)

Rui Zhang

2017-09-01

Full Text Available The dyeing of textile materials is the most critical process in cloth production because of the strict technological requirements. In addition to the technical aspect, there have been increasing concerns over how to minimize the negative environmental impact of the dyeing industry. The emissions of pollutants are mainly caused by frequent cleaning operations which are necessary for initializing the dyeing equipment, as well as idled production capacity which leads to discharge of unconsumed chemicals. Motivated by these facts, we propose a methodology to reduce the pollutant emissions by means of systematic production scheduling. Firstly, we build a three-objective scheduling model that incorporates both the traditional tardiness objective and the environmentally-related objectives. A mixed-integer programming formulation is also provided to accurately define the problem. Then, we present a novel solution method for the sustainable scheduling problem, namely, a multi-objective genetic algorithm with tabu-enhanced iterated greedy local search strategy (MOGA-TIG. Finally, we conduct extensive computational experiments to investigate the actual performance of the MOGA-TIG. Based on a fair comparison with two state-of-the-art multi-objective optimizers, it is concluded that the MOGA-TIG is able to achieve satisfactory solution quality within tight computational time budget for the studied scheduling problem.

Identification of Auditory Object-Specific Attention from Single-Trial Electroencephalogram Signals via Entropy Measures and Machine Learning

Directory of Open Access Journals (Sweden)

Yun Lu

2018-05-01

Full Text Available Existing research has revealed that auditory attention can be tracked from ongoing electroencephalography (EEG signals. The aim of this novel study was to investigate the identification of peoples’ attention to a specific auditory object from single-trial EEG signals via entropy measures and machine learning. Approximate entropy (ApEn, sample entropy (SampEn, composite multiscale entropy (CmpMSE and fuzzy entropy (FuzzyEn were used to extract the informative features of EEG signals under three kinds of auditory object-specific attention (Rest, Auditory Object1 Attention (AOA1 and Auditory Object2 Attention (AOA2. The linear discriminant analysis and support vector machine (SVM, were used to construct two auditory attention classifiers. The statistical results of entropy measures indicated that there were significant differences in the values of ApEn, SampEn, CmpMSE and FuzzyEn between Rest, AOA1 and AOA2. For the SVM-based auditory attention classifier, the auditory object-specific attention of Rest, AOA1 and AOA2 could be identified from EEG signals using ApEn, SampEn, CmpMSE and FuzzyEn as features and the identification rates were significantly different from chance level. The optimal identification was achieved by the SVM-based auditory attention classifier using CmpMSE with the scale factor τ = 10. This study demonstrated a novel solution to identify the auditory object-specific attention from single-trial EEG signals without the need to access the auditory stimulus.

Genetic analysis of glucosinolate variability in broccoli florets using genome-anchored single nucleotide polymorphisms.

Science.gov (United States)

Brown, Allan F; Yousef, Gad G; Reid, Robert W; Chebrolu, Kranthi K; Thomas, Aswathy; Krueger, Christopher; Jeffery, Elizabeth; Jackson, Eric; Juvik, John A

2015-07-01

The identification of genetic factors influencing the accumulation of individual glucosinolates in broccoli florets provides novel insight into the regulation of glucosinolate levels in Brassica vegetables and will accelerate the development of vegetables with glucosinolate profiles tailored to promote human health. Quantitative trait loci analysis of glucosinolate (GSL) variability was conducted with a B. oleracea (broccoli) mapping population, saturated with single nucleotide polymorphism markers from a high-density array designed for rapeseed (Brassica napus). In 4 years of analysis, 14 QTLs were associated with the accumulation of aliphatic, indolic, or aromatic GSLs in floret tissue. The accumulation of 3-carbon aliphatic GSLs (2-propenyl and 3-methylsulfinylpropyl) was primarily associated with a single QTL on C05, but common regulation of 4-carbon aliphatic GSLs was not observed. A single locus on C09, associated with up to 40 % of the phenotypic variability of 2-hydroxy-3-butenyl GSL over multiple years, was not associated with the variability of precursor compounds. Similarly, QTLs on C02, C04, and C09 were associated with 4-methylsulfinylbutyl GSL concentration over multiple years but were not significantly associated with downstream compounds. Genome-specific SNP markers were used to identify candidate genes that co-localized to marker intervals and previously sequenced Brassica oleracea BAC clones containing known GSL genes (GSL-ALK, GSL-PRO, and GSL-ELONG) were aligned to the genomic sequence, providing support that at least three of our 14 QTLs likely correspond to previously identified GSL loci. The results demonstrate that previously identified loci do not fully explain GSL variation in broccoli. The identification of additional genetic factors influencing the accumulation of GSL in broccoli florets provides novel insight into the regulation of GSL levels in Brassicaceae and will accelerate development of vegetables with modified or enhanced GSL

Channels as Objects in Concurrent Object-Oriented Programming

Directory of Open Access Journals (Sweden)

Joana Campos

2011-10-01

Full Text Available There is often a sort of a protocol associated to each class, stating when and how certain methods should be called. Given that this protocol is, if at all, described in the documentation accompanying the class, current mainstream object-oriented languages cannot provide for the verification of client code adherence against the sought class behaviour. We have defined a class-based concurrent object-oriented language that formalises such protocols in the form of usage types. Usage types are attached to class definitions, allowing for the specification of (1 the available methods, (2 the tests clients must perform on the result of methods, and (3 the object status - linear or shared - all of which depend on the object's state. Our work extends the recent approach on modular session types by eliminating channel operations, and defining the method call as the single communication primitive in both sequential and concurrent settings. In contrast to previous works, we define a single category for objects, instead of distinct categories for linear and for shared objects, and let linear objects evolve into shared ones. We introduce a standard sync qualifier to prevent thread interference in certain operations on shared objects. We formalise the language syntax, the operational semantics, and a type system that enforces by static typing that methods are called only when available, and by a single client if so specified in the usage type. We illustrate the language via a complete example.

Multi-objective optimization of design and testing of safety instrumented systems with MooN voting architectures using a genetic algorithm

International Nuclear Information System (INIS)

Torres-Echeverría, A.C.; Martorell, S.; Thompson, H.A.

2012-01-01

This paper presents the optimization of design and test policies of safety instrumented systems using MooN voting redundancies by a multi-objective genetic algorithm. The objectives to optimize are the Average Probability of Dangerous Failure on Demand, which represents the system safety integrity, the Spurious Trip Rate and the Lifecycle Cost. In this way safety, reliability and cost are included. This is done by using novel models of time-dependent probability of failure on demand and spurious trip rate, recently published by the authors. These models are capable of delivering the level of modeling detail required by the standard IEC 61508. Modeling includes common cause failure and diagnostic coverage. The Probability of Failure on Demand model also permits to quantify results with changing testing strategies. The optimization is performed using the multi-objective Genetic Algorithm NSGA-II. This allows weighting of the trade-offs between the three objectives and, thus, implementation of safety systems that keep a good balance between safety, reliability and cost. The complete methodology is applied to two separate case studies, one for optimization of system design with redundancy allocation and component selection and another for optimization of testing policies. Both optimization cases are performed for both systems with MooN redundancies and systems with only parallel redundancies. Their results are compared, demonstrating how introducing MooN architectures presents a significant improvement for the optimization process.

Object-based attention: strength of object representation and attentional guidance.

Science.gov (United States)

Shomstein, Sarah; Behrmann, Marlene

2008-01-01

Two or more features belonging to a single object are identified more quickly and more accurately than are features belonging to different objects--a finding attributed to sensory enhancement of all features belonging to an attended or selected object. However, several recent studies have suggested that this "single-object advantage" may be a product of probabilistic and configural strategic prioritizations rather than of object-based perceptual enhancement per se, challenging the underlying mechanism that is thought to give rise to object-based attention. In the present article, we further explore constraints on the mechanisms of object-based selection by examining the contribution of the strength of object representations to the single-object advantage. We manipulated factors such as exposure duration (i.e., preview time) and salience of configuration (i.e., objects). Varying preview time changes the magnitude of the object-based effect, so that if there is ample time to establish an object representation (i.e., preview time of 1,000 msec), then both probability and configuration (i.e., objects) guide attentional selection. If, however, insufficient time is provided to establish a robust object-based representation, then only probabilities guide attentional selection. Interestingly, at a short preview time of 200 msec, when the two objects were sufficiently different from each other (i.e., different colors), both configuration and probability guided attention selection. These results suggest that object-based effects can be explained both in terms of strength of object representations (established at longer exposure durations and by pictorial cues) and probabilistic contingencies in the visual environment.

Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control

Science.gov (United States)

Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.

2015-01-01

The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.

Optimizing multiple sequence alignments using a genetic algorithm based on three objectives: structural information, non-gaps percentage and totally conserved columns.

Science.gov (United States)

Ortuño, Francisco M; Valenzuela, Olga; Rojas, Fernando; Pomares, Hector; Florido, Javier P; Urquiza, Jose M; Rojas, Ignacio

2013-09-01

Multiple sequence alignments (MSAs) are widely used approaches in bioinformatics to carry out other tasks such as structure predictions, biological function analyses or phylogenetic modeling. However, current tools usually provide partially optimal alignments, as each one is focused on specific biological features. Thus, the same set of sequences can produce different alignments, above all when sequences are less similar. Consequently, researchers and biologists do not agree about which is the most suitable way to evaluate MSAs. Recent evaluations tend to use more complex scores including further biological features. Among them, 3D structures are increasingly being used to evaluate alignments. Because structures are more conserved in proteins than sequences, scores with structural information are better suited to evaluate more distant relationships between sequences. The proposed multiobjective algorithm, based on the non-dominated sorting genetic algorithm, aims to jointly optimize three objectives: STRIKE score, non-gaps percentage and totally conserved columns. It was significantly assessed on the BAliBASE benchmark according to the Kruskal-Wallis test (P algorithm also outperforms other aligners, such as ClustalW, Multiple Sequence Alignment Genetic Algorithm (MSA-GA), PRRP, DIALIGN, Hidden Markov Model Training (HMMT), Pattern-Induced Multi-sequence Alignment (PIMA), MULTIALIGN, Sequence Alignment Genetic Algorithm (SAGA), PILEUP, Rubber Band Technique Genetic Algorithm (RBT-GA) and Vertical Decomposition Genetic Algorithm (VDGA), according to the Wilcoxon signed-rank test (P 0.05) with the advantage of being able to use less structures. Structural information is included within the objective function to evaluate more accurately the obtained alignments. The source code is available at http://www.ugr.es/~fortuno/MOSAStrE/MO-SAStrE.zip.

Single-Event Transgene Product Levels Predict Levels in Genetically Modified Breeding Stacks.

Science.gov (United States)

Gampala, Satyalinga Srinivas; Fast, Brandon J; Richey, Kimberly A; Gao, Zhifang; Hill, Ryan; Wulfkuhle, Bryant; Shan, Guomin; Bradfisch, Greg A; Herman, Rod A

2017-09-13

The concentration of transgene products (proteins and double-stranded RNA) in genetically modified (GM) crop tissues is measured to support food, feed, and environmental risk assessments. Measurement of transgene product concentrations in breeding stacks of previously assessed and approved GM events is required by many regulatory authorities to evaluate unexpected transgene interactions that might affect expression. Research was conducted to determine how well concentrations of transgene products in single GM events predict levels in breeding stacks composed of these events. The concentrations of transgene products were compared between GM maize, soybean, and cotton breeding stacks (MON-87427 × MON-89034 × DAS-Ø15Ø7-1 × MON-87411 × DAS-59122-7 × DAS-40278-9 corn, DAS-81419-2 × DAS-44406-6 soybean, and DAS-21023-5 × DAS-24236-5 × SYN-IR102-7 × MON-88913-8 × DAS-81910-7 cotton) and their component single events (MON-87427, MON-89034, DAS-Ø15Ø7-1, MON-87411, DAS-59122-7, and DAS-40278-9 corn, DAS-81419-2, and DAS-44406-6 soybean, and DAS-21023-5, DAS-24236-5, SYN-IR102-7, MON-88913-8, and DAS-81910-7 cotton). Comparisons were made within a crop and transgene product across plant tissue types and were also made across transgene products in each breeding stack for grain/seed. Scatter plots were generated comparing expression in the stacks to their component events, and the percent of variability accounted for by the line of identity (y = x) was calculated (coefficient of identity, I 2 ). Results support transgene concentrations in single events predicting similar concentrations in breeding stacks containing the single events. Therefore, food, feed, and environmental risk assessments based on concentrations of transgene products in single GM events are generally applicable to breeding stacks composed of these events.

Thermo-economic and environmental analyses based multi-objective optimization of vapor compression–absorption cascaded refrigeration system using NSGA-II technique

International Nuclear Information System (INIS)

Jain, Vaibhav; Sachdeva, Gulshan; Kachhwaha, Surendra Singh; Patel, Bhavesh

2016-01-01

Highlights: • It addresses multi-objective optimization study on cascaded refrigeration system. • Cascaded system is a promising decarburizing and energy efficient technology. • NSGA-II technique is used for multi-objective optimization. • Total annual product cost and irreversibility rate are simultaneously optimized. - Abstract: Present work optimizes the performance of 170 kW vapor compression–absorption cascaded refrigeration system (VCACRS) based on combined thermodynamic, economic and environmental parameters using Non-dominated Sort Genetic Algorithm-II (NSGA-II) technique. Two objective functions including the total irreversibility rate (as a thermodynamic criterion) and the total product cost (as an economic criterion) of the system are considered simultaneously for multi-objective optimization of VCACRS. The capital and maintenance costs of the system components, the operational cost, and the penalty cost due to CO_2 emission are included in the total product cost of the system. Three optimized systems including a single-objective thermodynamic optimized, a single-objective economic optimized and a multi-objective optimized are analyzed and compared. The results showed that the multi-objective design considers the combined thermodynamic and total product cost criteria better than the two individual single-objective thermodynamic and total product cost optimized designs.

Family-based analysis of genetic variation underlying psychosis-inducing effects of cannabis : Sibling analysis and proband follow-up

NARCIS (Netherlands)

van Winkel, Ruud; Wiersma, Durk

Context: Individual differences exist in sensitivity to the psychotomimetic effect of cannabis; the molecular genetic basis underlying differential sensitivity remains elusive. Objective: To investigate whether selected schizophrenia candidate single-nucleotide polymorphisms (SNPs) moderate effects

Philosophy of race meets population genetics.

Science.gov (United States)

Spencer, Quayshawn

2015-08-01

In this paper, I respond to four common semantic and metaphysical objections that philosophers of race have launched at scholars who interpret recent human genetic clustering results in population genetics as evidence for biological racial realism. I call these objections 'the discreteness objection', 'the visibility objection', 'the very important objection', and 'the objectively real objection.' After motivating each objection, I show that each one stems from implausible philosophical assumptions about the relevant meaning of 'race' or the nature of biological racial realism. In order to be constructive, I end by offering some advice for how we can productively critique attempts to defend biological racial realism based on recent human genetic clustering results. I also offer a clarification of the relevant human-population genetic research. Copyright © 2015 Elsevier Ltd. All rights reserved.

Subjective and Objective Quality Assessment of Single-Channel Speech Separation Algorithms

DEFF Research Database (Denmark)

Mowlaee, Pejman; Saeidi, Rahim; Christensen, Mads Græsbøll

2012-01-01

Previous studies on performance evaluation of single-channel speech separation (SCSS) algorithms mostly focused on automatic speech recognition (ASR) accuracy as their performance measure. Assessing the separated signals by different metrics other than this has the benefit that the results...... are expected to carry on to other applications beyond ASR. In this paper, in addition to conventional speech quality metrics (PESQ and SNRloss), we also evaluate the separation systems output using different source separation metrics: blind source separation evaluation (BSS EVAL) and perceptual evaluation...... that PESQ and PEASS quality metrics predict well the subjective quality of separated signals obtained by the separation systems. From the results it is observed that the short-time objective intelligibility (STOI) measure predict the speech intelligibility results....

Intra-observer agreement in single and joint double readings of contrast-enhanced breast MRI screening for women with high genetic breast cancer risks

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Hugo C

2013-04-01

Full Text Available Objectives: To examine intra-observer reliability (IR for lesion detection on contrast-enhanced breast magnetic resonance images (MRI for screening women at high risk of breast cancer in single and joint double readings, without case selection. Methods: Contrast-enhanced breast MRIs were interpreted twice by the same independent reader and twice in joint readings. IR was assessed for lesion detection, normal MRI identification, mass, non-mass like enhancements (NMLE and focus characterisation, and BI-RADS assessment. Results: MRI examinations for 124 breasts, 65 women (mean age 43.4y were retrospectively reviewed with 110 lesions identified. Abnormal BIRADS (3-5 classifications were found for 52.3% in single readings and 58.5% in joint readings. Seven biopsies were performed for 4 histologically confirmed cancers. IR for BI-RADS classifications was good for single (0.63, 95% CI: 0.49-0.77, and joint readings (0.77, 95% CI: 0.61-0.93. IR for background parenchymal enhancement (BPE was moderate across single (0.53, 95% CI: 0.40-0.65 and joint readings (0.44, 95% CI: 0.33-0.56. IR for BI-RADS category according to each enhancement was poor for single (0.27, 95% CI: 0.10-0.44, and higher for joint readings, (0.58, 95% CI: 0.43-0.72. Conclusions: IR in BI-RADS breast assessments or BI-RADS lesion assessments are better with joint reading in screening for women with high genetic risks, in particular for abnormal MRI (BI-RADS 3, 4 and 5.

Temporal Genetic Variance and Propagule-Driven Genetic Structure Characterize Naturalized Rainbow Trout (Oncorhynchus mykiss) from a Patagonian Lake Impacted by Trout Farming.

Science.gov (United States)

Benavente, Javiera N; Seeb, Lisa W; Seeb, James E; Arismendi, Ivan; Hernández, Cristián E; Gajardo, Gonzalo; Galleguillos, Ricardo; Cádiz, Maria I; Musleh, Selim S; Gomez-Uchida, Daniel

2015-01-01

Knowledge about the genetic underpinnings of invasions-a theme addressed by invasion genetics as a discipline-is still scarce amid well documented ecological impacts of non-native species on ecosystems of Patagonia in South America. One of the most invasive species in Patagonia's freshwater systems and elsewhere is rainbow trout (Oncorhynchus mykiss). This species was introduced to Chile during the early twentieth century for stocking and promoting recreational fishing; during the late twentieth century was reintroduced for farming purposes and is now naturalized. We used population- and individual-based inference from single nucleotide polymorphisms (SNPs) to illuminate three objectives related to the establishment and naturalization of Rainbow Trout in Lake Llanquihue. This lake has been intensively used for trout farming during the last three decades. Our results emanate from samples collected from five inlet streams over two seasons, winter and spring. First, we found that significant intra- population (temporal) genetic variance was greater than inter-population (spatial) genetic variance, downplaying the importance of spatial divergence during the process of naturalization. Allele frequency differences between cohorts, consistent with variation in fish length between spring and winter collections, might explain temporal genetic differences. Second, individual-based Bayesian clustering suggested that genetic structure within Lake Llanquihue was largely driven by putative farm propagules found at one single stream during spring, but not in winter. This suggests that farm broodstock might migrate upstream to breed during spring at that particular stream. It is unclear whether interbreeding has occurred between "pure" naturalized and farm trout in this and other streams. Third, estimates of the annual number of breeders (Nb) were below 73 in half of the collections, suggestive of genetically small and recently founded populations that might experience substantial

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.

Science.gov (United States)

Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.

Single strand conformation polymorphism based SNP and Indel markers for genetic mapping and synteny analysis of common bean (Phaseolus vulgaris L.

Directory of Open Access Journals (Sweden)

Gómez Marcela

2009-12-01

Full Text Available Abstract Background Expressed sequence tags (ESTs are an important source of gene-based markers such as those based on insertion-deletions (Indels or single-nucleotide polymorphisms (SNPs. Several gel based methods have been reported for the detection of sequence variants, however they have not been widely exploited in common bean, an important legume crop of the developing world. The objectives of this project were to develop and map EST based markers using analysis of single strand conformation polymorphisms (SSCPs, to create a transcript map for common bean and to compare synteny of the common bean map with sequenced chromosomes of other legumes. Results A set of 418 EST based amplicons were evaluated for parental polymorphisms using the SSCP technique and 26% of these presented a clear conformational or size polymorphism between Andean and Mesoamerican genotypes. The amplicon based markers were then used for genetic mapping with segregation analysis performed in the DOR364 × G19833 recombinant inbred line (RIL population. A total of 118 new marker loci were placed into an integrated molecular map for common bean consisting of 288 markers. Of these, 218 were used for synteny analysis and 186 presented homology with segments of the soybean genome with an e-value lower than 7 × 10-12. The synteny analysis with soybean showed a mosaic pattern of syntenic blocks with most segments of any one common bean linkage group associated with two soybean chromosomes. The analysis with Medicago truncatula and Lotus japonicus presented fewer syntenic regions consistent with the more distant phylogenetic relationship between the galegoid and phaseoloid legumes. Conclusion The SSCP technique is a useful and inexpensive alternative to other SNP or Indel detection techniques for saturating the common bean genetic map with functional markers that may be useful in marker assisted selection. In addition, the genetic markers based on ESTs allowed the construction

Single strand conformation polymorphism based SNP and Indel markers for genetic mapping and synteny analysis of common bean (Phaseolus vulgaris L.).

Science.gov (United States)

Galeano, Carlos H; Fernández, Andrea C; Gómez, Marcela; Blair, Matthew W

2009-12-23

Expressed sequence tags (ESTs) are an important source of gene-based markers such as those based on insertion-deletions (Indels) or single-nucleotide polymorphisms (SNPs). Several gel based methods have been reported for the detection of sequence variants, however they have not been widely exploited in common bean, an important legume crop of the developing world. The objectives of this project were to develop and map EST based markers using analysis of single strand conformation polymorphisms (SSCPs), to create a transcript map for common bean and to compare synteny of the common bean map with sequenced chromosomes of other legumes. A set of 418 EST based amplicons were evaluated for parental polymorphisms using the SSCP technique and 26% of these presented a clear conformational or size polymorphism between Andean and Mesoamerican genotypes. The amplicon based markers were then used for genetic mapping with segregation analysis performed in the DOR364 x G19833 recombinant inbred line (RIL) population. A total of 118 new marker loci were placed into an integrated molecular map for common bean consisting of 288 markers. Of these, 218 were used for synteny analysis and 186 presented homology with segments of the soybean genome with an e-value lower than 7 x 10-12. The synteny analysis with soybean showed a mosaic pattern of syntenic blocks with most segments of any one common bean linkage group associated with two soybean chromosomes. The analysis with Medicago truncatula and Lotus japonicus presented fewer syntenic regions consistent with the more distant phylogenetic relationship between the galegoid and phaseoloid legumes. The SSCP technique is a useful and inexpensive alternative to other SNP or Indel detection techniques for saturating the common bean genetic map with functional markers that may be useful in marker assisted selection. In addition, the genetic markers based on ESTs allowed the construction of a transcript map and given their high conservation

Unraveling the genetic architecture of environmental variance of somatic cell score using high-density single nucleotide polymorphism and cow data from experimental farms.

Science.gov (United States)

Mulder, H A; Crump, R E; Calus, M P L; Veerkamp, R F

2013-01-01

In recent years, it has been shown that not only is the phenotype under genetic control, but also the environmental variance. Very little, however, is known about the genetic architecture of environmental variance. The main objective of this study was to unravel the genetic architecture of the mean and environmental variance of somatic cell score (SCS) by identifying genome-wide associations for mean and environmental variance of SCS in dairy cows and by quantifying the accuracy of genome-wide breeding values. Somatic cell score was used because previous research has shown that the environmental variance of SCS is partly under genetic control and reduction of the variance of SCS by selection is desirable. In this study, we used 37,590 single nucleotide polymorphism (SNP) genotypes and 46,353 test-day records of 1,642 cows at experimental research farms in 4 countries in Europe. We used a genomic relationship matrix in a double hierarchical generalized linear model to estimate genome-wide breeding values and genetic parameters. The estimated mean and environmental variance per cow was used in a Bayesian multi-locus model to identify SNP associated with either the mean or the environmental variance of SCS. Based on the obtained accuracy of genome-wide breeding values, 985 and 541 independent chromosome segments affecting the mean and environmental variance of SCS, respectively, were identified. Using a genomic relationship matrix increased the accuracy of breeding values relative to using a pedigree relationship matrix. In total, 43 SNP were significantly associated with either the mean (22) or the environmental variance of SCS (21). The SNP with the highest Bayes factor was on chromosome 9 (Hapmap31053-BTA-111664) explaining approximately 3% of the genetic variance of the environmental variance of SCS. Other significant SNP explained less than 1% of the genetic variance. It can be concluded that fewer genomic regions affect the environmental variance of SCS than the

Design optimization of shell-and-tube heat exchangers using single objective and multiobjective particle swarm optimization

International Nuclear Information System (INIS)

Elsays, Mostafa A.; Naguib Aly, M; Badawi, Alya A.

2010-01-01

The Particle Swarm Optimization (PSO) algorithm is used to optimize the design of shell-and-tube heat exchangers and determine the optimal feasible solutions so as to eliminate trial-and-error during the design process. The design formulation takes into account the area and the total annual cost of heat exchangers as two objective functions together with operating as well as geometrical constraints. The Nonlinear Constrained Single Objective Particle Swarm Optimization (NCSOPSO) algorithm is used to minimize and find the optimal feasible solution for each of the nonlinear constrained objective functions alone, respectively. Then, a novel Nonlinear Constrained Mult-objective Particle Swarm Optimization (NCMOPSO) algorithm is used to minimize and find the Pareto optimal solutions for both of the nonlinear constrained objective functions together. The experimental results show that the two algorithms are very efficient, fast and can find the accurate optimal feasible solutions of the shell and tube heat exchangers design optimization problem. (orig.)

Perception of Animacy from the Motion of a Single Sound Object.

Science.gov (United States)

Nielsen, Rasmus Høll; Vuust, Peter; Wallentin, Mikkel

2015-02-01

Research in the visual modality has shown that the presence of certain dynamics in the motion of an object has a strong effect on whether or not the entity is perceived as animate. Cues for animacy are, among others, self-propelled motion and direction changes that are seemingly not caused by entities external to, or in direct contact with, the moving object. The present study aimed to extend this research into the auditory domain by determining if similar dynamics could influence the perceived animacy of a sound source. In two experiments, participants were presented with single, synthetically generated 'mosquito' sounds moving along trajectories in space, and asked to rate how certain they were that each sound-emitting entity was alive. At a random point on a linear motion trajectory, the sound source would deviate from its initial path and speed. Results confirm findings from the visual domain that a change in the velocity of motion is positively correlated with perceived animacy, and changes in direction were found to influence animacy judgment as well. This suggests that an ability to facilitate and sustain self-movement is perceived as a living quality not only in the visual domain, but in the auditory domain as well. © 2015 SAGE Publications.

Dynamic Non-Rigid Objects Reconstruction with a Single RGB-D Sensor

Directory of Open Access Journals (Sweden)

Sen Wang

2018-03-01

Full Text Available This paper deals with the 3D reconstruction problem for dynamic non-rigid objects with a single RGB-D sensor. It is a challenging task as we consider the almost inevitable accumulation error issue in some previous sequential fusion methods and also the possible failure of surface tracking in a long sequence. Therefore, we propose a global non-rigid registration framework and tackle the drifting problem via an explicit loop closure. Our novel scheme starts with a fusion step to get multiple partial scans from the input sequence, followed by a pairwise non-rigid registration and loop detection step to obtain correspondences between neighboring partial pieces and those pieces that form a loop. Then, we perform a global registration procedure to align all those pieces together into a consistent canonical space as guided by those matches that we have established. Finally, our proposed model-update step helps fixing potential misalignments that still exist after the global registration. Both geometric and appearance constraints are enforced during our alignment; therefore, we are able to get the recovered model with accurate geometry as well as high fidelity color maps for the mesh. Experiments on both synthetic and various real datasets have demonstrated the capability of our approach to reconstruct complete and watertight deformable objects.

[Cloning goat producing human lactoferrin with genetically modified donor cells selected by single or dual markers].

Science.gov (United States)

An, Liyou; Yuan, Yuguo; Yu, Baoli; Yang, Tingjia; Cheng, Yong

2012-12-01

We compared the efficiency of cloning goat using human lactoferrin (hLF) with genetically modified donor cells marked by single (Neo(r)) or double (Neo(r)/GFP) markers. Single marker expression vector (pBLC14) or dual markers expression vector (pAPLM) was delivered to goat fetal fibroblasts (GFF), and then the transgenic GFF was used as donor cells to produce transgenic goats. Respectively, 58.8% (20/34) and 86.7% (26/30) resistant cell lines confirmed the transgenic integration by PCR. Moreover, pAPLM cells lines were subcultured with several passages, only 20% (6/30) cell lines was observed fluorescence from each cell during the cell passage. Somatic cell nuclear transfer using the donor cells harbouring pBLC14 or pAPLM construct, resulting in a total of 806 reconstructed embryos, a pregnancy rate at 35 d (53.8%, 39.1%) and 60 d (26.9%, 21.7%), and an offspring birth rate (1.9%, 1.4%) with 5 and 7 newborn cloned goats, respectively. Transgene was confirmed by PCR and southern-blot in all cloned offspring. There were no significant differences at the reconstructed embryo fusion rates, pregnancy rates and the birth rate (P > 0.05) between single and double markers groups. The Neo(r)/GFP double markers could improve the reliability for accurately and efficiently selecting the genetically modified donor cells. No adverse effect was observed on the efficiency of transgenic goat production by SCNT using somatic cells transfected with double (Neo(r)/GFP) markers vector.

Multi-objective optimization of the control strategy of electric vehicle electro-hydraulic composite braking system with genetic algorithm

Directory of Open Access Journals (Sweden)

Zhang Fengjiao

2015-03-01

Full Text Available Optimization of the control strategy plays an important role in improving the performance of electric vehicles. In order to improve the braking stability and recover the braking energy, a multi-objective genetic algorithm is applied to optimize the key parameters in the control strategy of electric vehicle electro-hydraulic composite braking system. Various limitations are considered in the optimization process, and the optimization results are verified by a software simulation platform of electric vehicle regenerative braking system in typical brake conditions. The results show that optimization objectives achieved a good astringency, and the optimized control strategy can increase the brake energy recovery effectively under the condition of ensuring the braking stability.

Multi-objective optimization of combustion, performance and emission parameters in a jatropha biodiesel engine using Non-dominated sorting genetic algorithm-II

Science.gov (United States)

Dhingra, Sunil; Bhushan, Gian; Dubey, Kashyap Kumar

2014-03-01

The present work studies and identifies the different variables that affect the output parameters involved in a single cylinder direct injection compression ignition (CI) engine using jatropha biodiesel. Response surface methodology based on Central composite design (CCD) is used to design the experiments. Mathematical models are developed for combustion parameters (Brake specific fuel consumption (BSFC) and peak cylinder pressure (Pmax)), performance parameter brake thermal efficiency (BTE) and emission parameters (CO, NO x , unburnt HC and smoke) using regression techniques. These regression equations are further utilized for simultaneous optimization of combustion (BSFC, Pmax), performance (BTE) and emission (CO, NO x , HC, smoke) parameters. As the objective is to maximize BTE and minimize BSFC, Pmax, CO, NO x , HC, smoke, a multiobjective optimization problem is formulated. Nondominated sorting genetic algorithm-II is used in predicting the Pareto optimal sets of solution. Experiments are performed at suitable optimal solutions for predicting the combustion, performance and emission parameters to check the adequacy of the proposed model. The Pareto optimal sets of solution can be used as guidelines for the end users to select optimal combination of engine output and emission parameters depending upon their own requirements.

Rice genetic marker database: An identification of single nucleotide ...

African Journals Online (AJOL)

based genetic marker system to provide information about SNP and QTL markers in rice. The SNP marker database provides 7,227 SNP markers including location information on chromosomes by using genetic map. It allows users to access a ...

Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects.

Science.gov (United States)

Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao

2016-01-01

Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems.

Comparison of single nucleotide polymorphisms and microsatellites in non-invasive genetic monitoring of a wolf population

DEFF Research Database (Denmark)

Fabbri, Elena; Caniglia, R.; Mucci, Nadia

2012-01-01

Single nucleotide polymorphisms (SNPs) which represent the most widespread source of sequence variation in genomes, are becoming a routine application in several fields such as forensics, ecology and conservation genetics. Their use, requiring short amplifications, may allow a more efficient geno....... We evaluated the cost, laboratory effort and reliability of these different markers and discuss the possible future use of VeraCode, SNPlex and Fluidigm EP1 system in wild population monitoring....

Analysis of genetic diversity in Brown Swiss, Jersey and Holstein populations using genome-wide single nucleotide polymorphism markers

Directory of Open Access Journals (Sweden)

Melka Melkaye G

2012-03-01

Full Text Available Abstract Background Studies of genetic diversity are essential in understanding the extent of differentiation between breeds, and in designing successful diversity conservation strategies. The objective of this study was to evaluate the level of genetic diversity within and between North American Brown Swiss (BS, n = 900, Jersey (JE, n = 2,922 and Holstein (HO, n = 3,535 cattle, using genotyped bulls. GENEPOP and FSTAT software were used to evaluate the level of genetic diversity within each breed and between each pair of the three breeds based on genome-wide SNP markers (n = 50,972. Results Hardy-Weinberg equilibrium (HWE exact test within breeds showed a significant deviation from equilibrium within each population (P st indicated that the combination of BS and HO in an ideally amalgamated population had higher genetic diversity than the other pairs of breeds. Conclusion Results suggest that the three bull populations have substantially different gene pools. BS and HO show the largest gene differentiation and jointly the highest total expected gene diversity compared to when JE is considered. If the loss of genetic diversity within breeds worsens in the future, the use of crossbreeding might be an option to recover genetic diversity, especially for the breeds with small population size.

Induction of atherosclerosis in mice and hamsters without germline genetic engineering

DEFF Research Database (Denmark)

Bjørklund, Martin Mæng; Hollensen, Anne Kruse; Hagensen, Mette Kallestrup

2014-01-01

RATIONALE: Atherosclerosis can be achieved in animals by germline genetic engineering, leading to hypercholesterolemia, but such models are constrained to few species and strains, and they are difficult to combine with other powerful techniques involving genetic manipulation or variation. OBJECTIVE......: To develop a method for induction of atherosclerosis without germline genetic engineering. METHODS AND RESULTS: Recombinant adeno-associated viral vectors were engineered to encode gain-of-function proprotein convertase subtilisin/kexin type 9 mutants, and mice were given a single intravenous vector...... injection followed by high-fat diet feeding. Plasma proprotein convertase subtilisin/kexin type 9 and total cholesterol increased rapidly and were maintained at high levels, and after 12 weeks, mice had atherosclerotic lesions in the aorta. Histology of the aortic root showed progression of lesions...

Considering dominance in reduced single-step genomic evaluations.

Science.gov (United States)

Ertl, J; Edel, C; Pimentel, E C G; Emmerling, R; Götz, K-U

2018-06-01

Single-step models including dominance can be an enormous computational task and can even be prohibitive for practical application. In this study, we try to answer the question whether a reduced single-step model is able to estimate breeding values of bulls and breeding values, dominance deviations and total genetic values of cows with acceptable quality. Genetic values and phenotypes were simulated (500 repetitions) for a small Fleckvieh pedigree consisting of 371 bulls (180 thereof genotyped) and 553 cows (40 thereof genotyped). This pedigree was virtually extended for 2,407 non-genotyped daughters. Genetic values were estimated with the single-step model and with different reduced single-step models. Including more relatives of genotyped cows in the reduced single-step model resulted in a better agreement of results with the single-step model. Accuracies of genetic values were largest with single-step and smallest with reduced single-step when only the cows genotyped were modelled. The results indicate that a reduced single-step model is suitable to estimate breeding values of bulls and breeding values, dominance deviations and total genetic values of cows with acceptable quality. © 2018 Blackwell Verlag GmbH.

Functional characterization of an alkaline exonuclease and single strand annealing protein from the SXT genetic element of Vibrio cholerae

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Huang Jian-dong

2011-04-01

Full Text Available Abstract Background SXT is an integrating conjugative element (ICE originally isolated from Vibrio cholerae, the bacterial pathogen that causes cholera. It houses multiple antibiotic and heavy metal resistance genes on its ca. 100 kb circular double stranded DNA (dsDNA genome, and functions as an effective vehicle for the horizontal transfer of resistance genes within susceptible bacterial populations. Here, we characterize the activities of an alkaline exonuclease (S066, SXT-Exo and single strand annealing protein (S065, SXT-Bet encoded on the SXT genetic element, which share significant sequence homology with Exo and Bet from bacteriophage lambda, respectively. Results SXT-Exo has the ability to degrade both linear dsDNA and single stranded DNA (ssDNA molecules, but has no detectable endonuclease or nicking activities. Adopting a stable trimeric arrangement in solution, the exonuclease activities of SXT-Exo are optimal at pH 8.2 and essentially require Mn2+ or Mg2+ ions. Similar to lambda-Exo, SXT-Exo hydrolyzes dsDNA with 5'- to 3'-polarity in a highly processive manner, and digests DNA substrates with 5'-phosphorylated termini significantly more effectively than those lacking 5'-phosphate groups. Notably, the dsDNA exonuclease activities of both SXT-Exo and lambda-Exo are stimulated by the addition of lambda-Bet, SXT-Bet or a single strand DNA binding protein encoded on the SXT genetic element (S064, SXT-Ssb. When co-expressed in E. coli cells, SXT-Bet and SXT-Exo mediate homologous recombination between a PCR-generated dsDNA fragment and the chromosome, analogous to RecET and lambda-Bet/Exo. Conclusions The activities of the SXT-Exo protein are consistent with it having the ability to resect the ends of linearized dsDNA molecules, forming partially ssDNA substrates for the partnering SXT-Bet single strand annealing protein. As such, SXT-Exo and SXT-Bet may function together to repair or process SXT genetic elements within infected V

Genetic homogeneity of the invasive lionfish across the Northwestern Atlantic and the Gulf of Mexico based on Single Nucleotide Polymorphisms.

Science.gov (United States)

Pérez-Portela, R; Bumford, A; Coffman, B; Wedelich, S; Davenport, M; Fogg, A; Swenarton, M K; Coleman, F; Johnston, M A; Crawford, D L; Oleksiak, M F

2018-03-22

Despite the devastating impact of the lionfish (Pterois volitans) invasion on NW Atlantic ecosystems, little genetic information about the invasion process is available. We applied Genotyping by Sequencing techniques to identify 1,220 single nucleotide polymorphic sites (SNPs) from 162 lionfish samples collected between 2013 and 2015 from two areas chronologically identified as the first and last invaded areas in US waters: the east coast of Florida and the Gulf of Mexico. We used population genomic analyses, including phylogenetic reconstruction, Bayesian clustering, genetic distances, Discriminant Analyses of Principal Components, and coalescence simulations for detection of outlier SNPs, to understand genetic trends relevant to the lionfish's long-term persistence. We found no significant differences in genetic structure or diversity between the two areas (F ST p-values > 0.01, and t-test p-values > 0.05). In fact, our genomic analyses showed genetic homogeneity, with enough gene flow between the east coast of Florida and Gulf of Mexico to erase previous signals of genetic divergence detected between these areas, secondary spreading, and bottlenecks in the Gulf of Mexico. These findings suggest rapid genetic changes over space and time during the invasion, resulting in one panmictic population with no signs of divergence between areas due to local adaptation.

Genetics education for non-genetic health care professionals in the Netherlands

NARCIS (Netherlands)

Plass, Anne Marie C.; Baars, Marieke J. H.; Beemer, Frits A.; ten Kate, Leo P.

2006-01-01

OBJECTIVE: The aim of the present study was to investigate whether medical care providers in the Netherlands are adequately educated in genetics by collecting information about the current state of genetics education of non-genetics health care professionals. METHOD: The curricula of the 8

Face Validity of the Single Work Ability Item: Comparison with Objectively Measured Heart Rate Reserve over Several Days

Science.gov (United States)

Gupta, Nidhi; Jensen, Bjørn Søvsø; Søgaard, Karen; Carneiro, Isabella Gomes; Christiansen, Caroline Stordal; Hanisch, Christiana; Holtermann, Andreas

2014-01-01

Purpose: The purpose of this study was to investigate the face validity of the self-reported single item work ability with objectively measured heart rate reserve (%HRR) among blue-collar workers. Methods: We utilized data from 127 blue-collar workers (Female = 53; Male = 74) aged 18–65 years from the cross-sectional “New method for Objective Measurements of physical Activity in Daily living (NOMAD)” study. The workers reported their single item work ability and completed an aerobic capacity cycling test and objective measurements of heart rate reserve monitored with Actiheart for 3–4 days with a total of 5,810 h, including 2,640 working hours. Results: A significant moderate correlation between work ability and %HRR was observed among males (R = −0.33, P = 0.005), but not among females (R = 0.11, P = 0.431). In a gender-stratified multi-adjusted logistic regression analysis, males with high %HRR were more likely to report a reduced work ability compared to males with low %HRR [OR = 4.75, 95% confidence interval (95% CI) = 1.31 to 17.25]. However, this association was not found among females (OR = 0.26, 95% CI 0.03 to 2.16), and a significant interaction between work ability, %HRR and gender was observed (P = 0.03). Conclusions: The observed association between work ability and objectively measured %HRR over several days among male blue-collar workers supports the face validity of the single work ability item. It is a useful and valid measure of the relation between physical work demands and resources among male blue-collar workers. The contrasting association among females needs to be further investigated. PMID:24840350

Face Validity of the Single Work Ability Item: Comparison with Objectively Measured Heart Rate Reserve over Several Days

Directory of Open Access Journals (Sweden)

Nidhi Gupta

2014-05-01

Full Text Available Purpose: The purpose of this study was to investigate the face validity of the self-reported single item work ability with objectively measured heart rate reserve (%HRR among blue-collar workers. Methods: We utilized data from 127 blue-collar workers (Female = 53; Male = 74 aged 18–65 years from the cross-sectional “New method for Objective Measurements of physical Activity in Daily living (NOMAD” study. The workers reported their single item work ability and completed an aerobic capacity cycling test and objective measurements of heart rate reserve monitored with Actiheart for 3–4 days with a total of 5,810 h, including 2,640 working hours. Results: A significant moderate correlation between work ability and %HRR was observed among males (R = −0.33, P = 0.005, but not among females (R = 0.11, P = 0.431. In a gender-stratified multi-adjusted logistic regression analysis, males with high %HRR were more likely to report a reduced work ability compared to males with low %HRR [OR = 4.75, 95% confidence interval (95% CI = 1.31 to 17.25]. However, this association was not found among females (OR = 0.26, 95% CI 0.03 to 2.16, and a significant interaction between work ability, %HRR and gender was observed (P = 0.03. Conclusions: The observed association between work ability and objectively measured %HRR over several days among male blue-collar workers supports the face validity of the single work ability item. It is a useful and valid measure of the relation between physical work demands and resources among male blue-collar workers. The contrasting association among females needs to be further investigated.

Parallel Multi-Objective Genetic Algorithm for Short-Term Economic Environmental Hydrothermal Scheduling

Directory of Open Access Journals (Sweden)

Zhong-Kai Feng

2017-01-01

Full Text Available With the increasingly serious energy crisis and environmental pollution, the short-term economic environmental hydrothermal scheduling (SEEHTS problem is becoming more and more important in modern electrical power systems. In order to handle the SEEHTS problem efficiently, the parallel multi-objective genetic algorithm (PMOGA is proposed in the paper. Based on the Fork/Join parallel framework, PMOGA divides the whole population of individuals into several subpopulations which will evolve in different cores simultaneously. In this way, PMOGA can avoid the wastage of computational resources and increase the population diversity. Moreover, the constraint handling technique is used to handle the complex constraints in SEEHTS, and a selection strategy based on constraint violation is also employed to ensure the convergence speed and solution feasibility. The results from a hydrothermal system in different cases indicate that PMOGA can make the utmost of system resources to significantly improve the computing efficiency and solution quality. Moreover, PMOGA has competitive performance in SEEHTS when compared with several other methods reported in the previous literature, providing a new approach for the operation of hydrothermal systems.

Brief communication genotyping of Burkholderia pseudomallei revealed high genetic variability among isolates from a single population group

OpenAIRE

Zueter, Abdelrahman Mohammad; Rahman, Zaidah Abdul; Yean, Chan Yean; Harun, Azian

2015-01-01

Burkholderia pseudomallei is a soil dwelling Gram-negative bacteria predominates in Southeast Asia zone and the tropical part of Australia. Genetic diversity has been explored among various populations and environments worldwide. To date, little data is available on MLST profiling of clinical B. pseudomallei isolates in peninsular Malaysia. In this brief report, thirteen culture positive B. pseudomallei cases collected from a single population of Terengganu state in the Western Peninsular Mal...

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

Science.gov (United States)

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

2007-12-15

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

Multi-objective group scheduling optimization integrated with preventive maintenance

Science.gov (United States)

Liao, Wenzhu; Zhang, Xiufang; Jiang, Min

2017-11-01

This article proposes a single-machine-based integration model to meet the requirements of production scheduling and preventive maintenance in group production. To describe the production for identical/similar and different jobs, this integrated model considers the learning and forgetting effects. Based on machine degradation, the deterioration effect is also considered. Moreover, perfect maintenance and minimal repair are adopted in this integrated model. The multi-objective of minimizing total completion time and maintenance cost is taken to meet the dual requirements of delivery date and cost. Finally, a genetic algorithm is developed to solve this optimization model, and the computation results demonstrate that this integrated model is effective and reliable.

Selection of security system design via games of imperfect information and multi-objective genetic algorithm

International Nuclear Information System (INIS)

Lins, Isis Didier; Rêgo, Leandro Chaves; Moura, Márcio das Chagas

2013-01-01

This work analyzes the strategic interaction between a defender and an intelligent attacker by means of a game and reliability framework involving a multi-objective approach and imperfect information so as to support decision-makers in choosing efficiently designed security systems. A multi-objective genetic algorithm is used to determine the optimal security system's configurations representing the tradeoff between the probability of a successful defense and the acquisition and operational costs. Games with imperfect information are considered, in which the attacker has limited knowledge about the actual security system. The types of security alternatives are readily observable, but the number of redundancies actually implemented in each security subsystem is not known. The proposed methodology is applied to an illustrative example considering power transmission lines in the Northeast of Brazil, which are often targets for attackers who aims at selling the aluminum conductors. The empirical results show that the framework succeeds in handling this sort of strategic interaction. -- Highlights: ► Security components must have feasible costs and must be reliable. ► The optimal design of security systems considers a multi-objective approach. ► Games of imperfect information enable the choice of non-dominated configurations. ► MOGA, reliability and games support the entire defender's decision process. ► The selection of effective security systems may discourage attacker's actions

A Single Missense Mutation in 77% of Prostate Cancer Bone Metastases: Novel Opportunity for Genetic Biomarker and Novel Therapeutic Mitochondrial Target

Science.gov (United States)

2017-10-01

goal of this application is to identify targets for the treatment of androgen receptor null castration-resistant prostate cancer in in vitro and pre...AWARD NUMBER: W81XWH-16-1-0584 TITLE : A Single Missense Mutation in 77% of Prostate Cancer Bone Metastases: Novel Opportunity for Genetic...Missense Mutation in 77% of Prostate Cancer Bone Metastases: 5a. CONTRACT NUMBER A Single Missense Mutation in 77% of Prostate Cancer Bone Metastases

Genetic Particle Swarm Optimization–Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection

Science.gov (United States)

Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

2016-01-01

In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm. PMID:27483285

Genetic Particle Swarm Optimization-Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection.

Science.gov (United States)

Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

2016-07-30

In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm.

The role of auditory cortices in the retrieval of single-trial auditory-visual object memories.

Science.gov (United States)

Matusz, Pawel J; Thelen, Antonia; Amrein, Sarah; Geiser, Eveline; Anken, Jacques; Murray, Micah M

2015-03-01

Single-trial encounters with multisensory stimuli affect both memory performance and early-latency brain responses to visual stimuli. Whether and how auditory cortices support memory processes based on single-trial multisensory learning is unknown and may differ qualitatively and quantitatively from comparable processes within visual cortices due to purported differences in memory capacities across the senses. We recorded event-related potentials (ERPs) as healthy adults (n = 18) performed a continuous recognition task in the auditory modality, discriminating initial (new) from repeated (old) sounds of environmental objects. Initial presentations were either unisensory or multisensory; the latter entailed synchronous presentation of a semantically congruent or a meaningless image. Repeated presentations were exclusively auditory, thus differing only according to the context in which the sound was initially encountered. Discrimination abilities (indexed by d') were increased for repeated sounds that were initially encountered with a semantically congruent image versus sounds initially encountered with either a meaningless or no image. Analyses of ERPs within an electrical neuroimaging framework revealed that early stages of auditory processing of repeated sounds were affected by prior single-trial multisensory contexts. These effects followed from significantly reduced activity within a distributed network, including the right superior temporal cortex, suggesting an inverse relationship between brain activity and behavioural outcome on this task. The present findings demonstrate how auditory cortices contribute to long-term effects of multisensory experiences on auditory object discrimination. We propose a new framework for the efficacy of multisensory processes to impact both current multisensory stimulus processing and unisensory discrimination abilities later in time. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Genetic characterization of Anaplasma marginale strains from Tunisia using single and multiple gene typing reveals novel variants with an extensive genetic diversity.

Science.gov (United States)

Ben Said, Mourad; Ben Asker, Alaa; Belkahia, Hanène; Ghribi, Raoua; Selmi, Rachid; Messadi, Lilia

2018-05-12

Anaplasma marginale, which is responsible for bovine anaplasmosis in tropical and subtropical regions, is a tick-borne obligatory intraerythrocytic bacterium of cattle and wild ruminants. In Tunisia, information about the genetic diversity and the phylogeny of A. marginale strains are limited to the msp4 gene analysis. The purpose of this study is to investigate A. marginale isolates infecting 16 cattle located in different bioclimatic areas of northern Tunisia with single gene analysis and multilocus sequence typing methods on the basis of seven partial genes (dnaA, ftsZ, groEL, lipA, secY, recA and sucB). The single gene analysis confirmed the presence of different and novel heterogenic A. marginale strains infecting cattle from the north of Tunisia. The concatenated sequence analysis showed a phylogeographical resolution at the global level and that most of the Tunisian sequence types (STs) formed a separate cluster from a South African isolate and from all New World isolates and strains. By combining the characteristics of each single locus with those of the multi-loci scheme, these results provide a more detailed understanding on the diversity and the evolution of Tunisian A. marginale strains. Copyright © 2018 Elsevier GmbH. All rights reserved.

Optimization of a Turboprop UAV for Maximum Loiter and Specific Power Using Genetic Algorithm

Science.gov (United States)

Dinc, Ali

2016-09-01

In this study, a genuine code was developed for optimization of selected parameters of a turboprop engine for an unmanned aerial vehicle (UAV) by employing elitist genetic algorithm. First, preliminary sizing of a UAV and its turboprop engine was done, by the code in a given mission profile. Secondly, single and multi-objective optimization were done for selected engine parameters to maximize loiter duration of UAV or specific power of engine or both. In single objective optimization, as first case, UAV loiter time was improved with an increase of 17.5% from baseline in given boundaries or constraints of compressor pressure ratio and burner exit temperature. In second case, specific power was enhanced by 12.3% from baseline. In multi-objective optimization case, where previous two objectives are considered together, loiter time and specific power were increased by 14.2% and 9.7% from baseline respectively, for the same constraints.

Single Nucleotide Polymorphism Markers for Genetic Mapping in Drosophila melanogaster

OpenAIRE

Hoskins, Roger A.; Phan, Alexander C.; Naeemuddin, Mohammed; Mapa, Felipa A.; Ruddy, David A.; Ryan, Jessica J.; Young, Lynn M.; Wells, Trent; Kopczynski, Casey; Ellis, Michael C.

2001-01-01

For nearly a century, genetic analysis in Drosophila melanogaster has been a powerful tool for analyzing gene function, yet Drosophila lacks the molecular genetic mapping tools that recently have revolutionized human, mouse, and plant genetics. Here, we describe the systematic characterization of a dense set of molecular markers in Drosophila by using a sequence tagged site-based physical map of the genome. We identify 474 biallelic markers in standard laboratory strains of Drosophila that sp...

Multiple criteria decision-making process to derive consensus desired genetic gains for a dairy cattle breeding objective for diverse production systems.

Science.gov (United States)

Kariuki, C M; van Arendonk, J A M; Kahi, A K; Komen, H

2017-06-01

Dairy cattle industries contribute to food and nutrition security and are a source of income for numerous households in many developing countries. Selective breeding can enhance efficiency in these industries. Developing dairy industries are characterized by diverse production and marketing systems. In this paper, we use weighted goal aggregating procedure to derive consensus trait preferences for different producer categories and processors. We based the study on the dairy industry in Kenya. The analytic hierarchy process was used to derive individual preferences for milk yield (MY), calving interval (CIN), production lifetime (PLT), mature body weight (MBW), and fat yield (FY). Results show that classical classification of production systems into large-scale and smallholder systems does not capture all differences in trait preferences. These differences became apparent when classification was based on productivity at the individual animal level, with high and low intensity producers and processors as the most important groups. High intensity producers had highest preferences for PLT and MY, whereas low intensity producers had highest preference for CIN and PLT; processors preferred MY and FY the most. The highest disagreements between the groups were observed for FY, PLT, and MY. Individual and group preferences were aggregated into consensus preferences using weighted goal programming. Desired gains were obtained as a product of consensus preferences and percentage genetic gains (G%). These were 2.42, 0.22, 2.51, 0.15, and 0.87 for MY, CIN, PLT, MBW, and FY, respectively. Consensus preferences can be used to derive a single compromise breeding objective for situations where the same genetic resources are used in diverse production and marketing circumstances. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license

Reverse genetics with animal viruses. NSV reverse genetics

International Nuclear Information System (INIS)

Mebatsion, T.

2005-01-01

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

Systematic analysis of the heat exchanger arrangement problem using multi-objective genetic optimization

International Nuclear Information System (INIS)

Daróczy, László; Janiga, Gábor; Thévenin, Dominique

2014-01-01

A two-dimensional cross-flow tube bank heat exchanger arrangement problem with internal laminar flow is considered in this work. The objective is to optimize the arrangement of tubes and find the most favorable geometries, in order to simultaneously maximize the rate of heat exchange while obtaining a minimum pressure loss. A systematic study was performed involving a large number of simulations. The global optimization method NSGA-II was retained. A fully automatized in-house optimization environment was used to solve the problem, including mesh generation and CFD (computational fluid dynamics) simulations. The optimization was performed in parallel on a Linux cluster with a very good speed-up. The main purpose of this article is to illustrate and analyze a heat exchanger arrangement problem in its most general form and to provide a fundamental understanding of the structure of the Pareto front and optimal geometries. The considered conditions are particularly suited for low-power applications, as found in a growing number of practical systems in an effort toward increasing energy efficiency. For such a detailed analysis with more than 140 000 CFD-based evaluations, a design-of-experiment study involving a response surface would not be sufficient. Instead, all evaluations rely on a direct solution using a CFD solver. - Highlights: • Cross-flow tube bank heat exchanger arrangement problem. • A fully automatized multi-objective optimization based on genetic algorithm. • A systematic study involving a large number of CFD (computational fluid dynamics) simulations

Hydrologic Model Development and Calibration: Contrasting a Single- and Multi-Objective Approach for Comparing Model Performance

Science.gov (United States)

Asadzadeh, M.; Maclean, A.; Tolson, B. A.; Burn, D. H.

2009-05-01

Hydrologic model calibration aims to find a set of parameters that adequately simulates observations of watershed behavior, such as streamflow, or a state variable, such as snow water equivalent (SWE). There are different metrics for evaluating calibration effectiveness that involve quantifying prediction errors, such as the Nash-Sutcliffe (NS) coefficient and bias evaluated for the entire calibration period, on a seasonal basis, for low flows, or for high flows. Many of these metrics are conflicting such that the set of parameters that maximizes the high flow NS differs from the set of parameters that maximizes the low flow NS. Conflicting objectives are very likely when different calibration objectives are based on different fluxes and/or state variables (e.g., NS based on streamflow versus SWE). One of the most popular ways to balance different metrics is to aggregate them based on their importance and find the set of parameters that optimizes a weighted sum of the efficiency metrics. Comparing alternative hydrologic models (e.g., assessing model improvement when a process or more detail is added to the model) based on the aggregated objective might be misleading since it represents one point on the tradeoff of desired error metrics. To derive a more comprehensive model comparison, we solved a bi-objective calibration problem to estimate the tradeoff between two error metrics for each model. Although this approach is computationally more expensive than the aggregation approach, it results in a better understanding of the effectiveness of selected models at each level of every error metric and therefore provides a better rationale for judging relative model quality. The two alternative models used in this study are two MESH hydrologic models (version 1.2) of the Wolf Creek Research basin that differ in their watershed spatial discretization (a single Grouped Response Unit, GRU, versus multiple GRUs). The MESH model, currently under development by Environment

Oligonucleotide arrays vs. metaphase-comparative genomic hybridisation and BAC arrays for single-cell analysis: first applications to preimplantation genetic diagnosis for Robertsonian translocation carriers.

Science.gov (United States)

Ramos, Laia; del Rey, Javier; Daina, Gemma; García-Aragonés, Manel; Armengol, Lluís; Fernandez-Encinas, Alba; Parriego, Mònica; Boada, Montserrat; Martinez-Passarell, Olga; Martorell, Maria Rosa; Casagran, Oriol; Benet, Jordi; Navarro, Joaquima

2014-01-01

Comprehensive chromosome analysis techniques such as metaphase-Comparative Genomic Hybridisation (CGH) and array-CGH are available for single-cell analysis. However, while metaphase-CGH and BAC array-CGH have been widely used for Preimplantation Genetic Diagnosis, oligonucleotide array-CGH has not been used in an extensive way. A comparison between oligonucleotide array-CGH and metaphase-CGH has been performed analysing 15 single fibroblasts from aneuploid cell-lines and 18 single blastomeres from human cleavage-stage embryos. Afterwards, oligonucleotide array-CGH and BAC array-CGH were also compared analysing 16 single blastomeres from human cleavage-stage embryos. All three comprehensive analysis techniques provided broadly similar cytogenetic profiles; however, non-identical profiles appeared when extensive aneuploidies were present in a cell. Both array techniques provided an optimised analysis procedure and a higher resolution than metaphase-CGH. Moreover, oligonucleotide array-CGH was able to define extra segmental imbalances in 14.7% of the blastomeres and it better determined the specific unbalanced chromosome regions due to a higher resolution of the technique (≈ 20 kb). Applicability of oligonucleotide array-CGH for Preimplantation Genetic Diagnosis has been demonstrated in two cases of Robertsonian translocation carriers 45,XY,der(13;14)(q10;q10). Transfer of euploid embryos was performed in both cases and pregnancy was achieved by one of the couples. This is the first time that an oligonucleotide array-CGH approach has been successfully applied to Preimplantation Genetic Diagnosis for balanced chromosome rearrangement carriers.

Oligonucleotide arrays vs. metaphase-comparative genomic hybridisation and BAC arrays for single-cell analysis: first applications to preimplantation genetic diagnosis for Robertsonian translocation carriers.

Directory of Open Access Journals (Sweden)

Laia Ramos

Full Text Available Comprehensive chromosome analysis techniques such as metaphase-Comparative Genomic Hybridisation (CGH and array-CGH are available for single-cell analysis. However, while metaphase-CGH and BAC array-CGH have been widely used for Preimplantation Genetic Diagnosis, oligonucleotide array-CGH has not been used in an extensive way. A comparison between oligonucleotide array-CGH and metaphase-CGH has been performed analysing 15 single fibroblasts from aneuploid cell-lines and 18 single blastomeres from human cleavage-stage embryos. Afterwards, oligonucleotide array-CGH and BAC array-CGH were also compared analysing 16 single blastomeres from human cleavage-stage embryos. All three comprehensive analysis techniques provided broadly similar cytogenetic profiles; however, non-identical profiles appeared when extensive aneuploidies were present in a cell. Both array techniques provided an optimised analysis procedure and a higher resolution than metaphase-CGH. Moreover, oligonucleotide array-CGH was able to define extra segmental imbalances in 14.7% of the blastomeres and it better determined the specific unbalanced chromosome regions due to a higher resolution of the technique (≈ 20 kb. Applicability of oligonucleotide array-CGH for Preimplantation Genetic Diagnosis has been demonstrated in two cases of Robertsonian translocation carriers 45,XY,der(13;14(q10;q10. Transfer of euploid embryos was performed in both cases and pregnancy was achieved by one of the couples. This is the first time that an oligonucleotide array-CGH approach has been successfully applied to Preimplantation Genetic Diagnosis for balanced chromosome rearrangement carriers.

Oligonucleotide Arrays vs. Metaphase-Comparative Genomic Hybridisation and BAC Arrays for Single-Cell Analysis: First Applications to Preimplantation Genetic Diagnosis for Robertsonian Translocation Carriers

Science.gov (United States)

Ramos, Laia; del Rey, Javier; Daina, Gemma; García-Aragonés, Manel; Armengol, Lluís; Fernandez-Encinas, Alba; Parriego, Mònica; Boada, Montserrat; Martinez-Passarell, Olga; Martorell, Maria Rosa; Casagran, Oriol; Benet, Jordi; Navarro, Joaquima

2014-01-01

Comprehensive chromosome analysis techniques such as metaphase-Comparative Genomic Hybridisation (CGH) and array-CGH are available for single-cell analysis. However, while metaphase-CGH and BAC array-CGH have been widely used for Preimplantation Genetic Diagnosis, oligonucleotide array-CGH has not been used in an extensive way. A comparison between oligonucleotide array-CGH and metaphase-CGH has been performed analysing 15 single fibroblasts from aneuploid cell-lines and 18 single blastomeres from human cleavage-stage embryos. Afterwards, oligonucleotide array-CGH and BAC array-CGH were also compared analysing 16 single blastomeres from human cleavage-stage embryos. All three comprehensive analysis techniques provided broadly similar cytogenetic profiles; however, non-identical profiles appeared when extensive aneuploidies were present in a cell. Both array techniques provided an optimised analysis procedure and a higher resolution than metaphase-CGH. Moreover, oligonucleotide array-CGH was able to define extra segmental imbalances in 14.7% of the blastomeres and it better determined the specific unbalanced chromosome regions due to a higher resolution of the technique (≈20 kb). Applicability of oligonucleotide array-CGH for Preimplantation Genetic Diagnosis has been demonstrated in two cases of Robertsonian translocation carriers 45,XY,der(13;14)(q10;q10). Transfer of euploid embryos was performed in both cases and pregnancy was achieved by one of the couples. This is the first time that an oligonucleotide array-CGH approach has been successfully applied to Preimplantation Genetic Diagnosis for balanced chromosome rearrangement carriers. PMID:25415307

A hybrid, massively parallel implementation of a genetic algorithm for optimization of the impact performance of a metal/polymer composite plate

KAUST Repository

Narayanan, Kiran; Mora Cordova, Angel; Allsopp, Nicholas; El Sayed, Tamer S.

2012-01-01

A hybrid parallelization method composed of a coarse-grained genetic algorithm (GA) and fine-grained objective function evaluations is implemented on a heterogeneous computational resource consisting of 16 IBM Blue Gene/P racks, a single x86 cluster

The genetics of eye colours in an Italian population measured with an objective method for eye colour quantification

DEFF Research Database (Denmark)

Pietroni, C.; Andersen, J.D.; Johansen, P.

2013-01-01

Brown and blue eye colours are primarily explained by the single nucleotide polymorphism (SNP) HERC2 rs12913832. However, the genetics of eye colours that appear to be neither blue nor brown are not well understood. In this study, 230 unrelated Italian individuals were typed for 32 SNP loci...... in the iris region and calculated a Pixel Index of the Eye (PIE-score) that described the eye colours quantitatively. The PIE-score ranged from _1 to 1 (brown to blue). We investigated the association of the PIE-scores extracted from the eye images with the genotypes of the 32 pigmentary SNPs. We observed...

Long-term correction of obesity and diabetes in genetically obese mice by a single intramuscular injection of recombinant adeno-associated virus encoding mouse leptin

Science.gov (United States)

Murphy, John E.; Zhou, Shangzhen; Giese, Klaus; Williams, Lewis T.; Escobedo, Jaime A.; Dwarki, Varavani J.

1997-01-01

The ob/ob mouse is genetically deficient in leptin and exhibits a phenotype that includes obesity and non-insulin-dependent diabetes melitus. This phenotype closely resembles the morbid obesity seen in humans. In this study, we demonstrate that a single intramuscular injection of a recombinant adeno-associated virus (AAV) vector encoding mouse leptin (rAAV-leptin) in ob/ob mice leads to prevention of obesity and diabetes. The treated animals show normalization of metabolic abnormalities including hyperglycemia, insulin resistance, impaired glucose tolerance, and lethargy. The effects of a single injection have lasted through the 6-month course of the study. At all time points measured the circulating levels of leptin in the serum were similar to age-matched control C57 mice. These results demonstrate that maintenance of normal levels of leptin (2–5 ng/ml) in the circulation can prevent both the onset of obesity and associated non-insulin-dependent diabetes. Thus a single injection of a rAAV vector expressing a therapeutic gene can lead to complete and long-term correction of a genetic disorder. Our study demonstrates the long-term correction of a disease caused by a genetic defect and proves the feasibility of using rAAV-based vectors for the treatment of chronic disorders like obesity. PMID:9391128

Preimplantation Genetic Screening and Preimplantation Genetic Diagnosis.

Science.gov (United States)

Sullivan-Pyke, Chantae; Dokras, Anuja

2018-03-01

Preimplantation genetic testing encompasses preimplantation genetic screening (PGS) and preimplantation genetic diagnosis (PGD). PGS improves success rates of in vitro fertilization by ensuring the transfer of euploid embryos that have a higher chance of implantation and resulting in a live birth. PGD enables the identification of embryos with specific disease-causing mutations and transfer of unaffected embryos. The development of whole genome amplification and genomic tools, including single nucleotide polymorphism microarrays, comparative genomic hybridization microarrays, and next-generation sequencing, has led to faster, more accurate diagnoses that translate to improved pregnancy and live birth rates. Copyright © 2017 Elsevier Inc. All rights reserved.

Genetic heterogeneity of retinitis pigmentosa

OpenAIRE

Hartono, Hartono

2015-01-01

Genetic heterogeneity is a phenomenon in which a genetic disease can be transmitted by several modes of inheritance. The understanding of genetic heterogeneity is important in giving genetic counselling.The presence of genetic heterogeneity can be explained by the existence of:1.different mutant alleles at a single locus, and2.mutant alleles at different loci affecting the same enzyme or protein, or affecting different enzymes or proteins.To have an overall understanding of genetic heterogene...

[The Object Permanence Fallacy.] Commentary.

Science.gov (United States)

Bradley, Ben S.

1996-01-01

Suggests that Greenberg's challenge to the centrality of object permanence in developmental thinking reveals that developmentalists' theories about childhood speak about their own self-images. Notes that developmentalists have been guilty of not only the object permanence fallacy but also the genetic fallacy, or the mistaken belief that describing…

Multi objective multi refinery optimization with environmental and catastrophic failure effects objectives

Science.gov (United States)

Khogeer, Ahmed Sirag

2005-11-01

Petroleum refining is a capital-intensive business. With stringent environmental regulations on the processing industry and declining refining margins, political instability, increased risk of war and terrorist attacks in which refineries and fuel transportation grids may be targeted, higher pressures are exerted on refiners to optimize performance and find the best combination of feed and processes to produce salable products that meet stricter product specifications, while at the same time meeting refinery supply commitments and of course making profit. This is done through multi objective optimization. For corporate refining companies and at the national level, Intea-Refinery and Inter-Refinery optimization is the second step in optimizing the operation of the whole refining chain as a single system. Most refinery-wide optimization methods do not cover multiple objectives such as minimizing environmental impact, avoiding catastrophic failures, or enhancing product spec upgrade effects. This work starts by carrying out a refinery-wide, single objective optimization, and then moves to multi objective-single refinery optimization. The last step is multi objective-multi refinery optimization, the objectives of which are analysis of the effects of economic, environmental, product spec, strategic, and catastrophic failure. Simulation runs were carried out using both MATLAB and ASPEN PIMS utilizing nonlinear techniques to solve the optimization problem. The results addressed the need to debottleneck some refineries or transportation media in order to meet the demand for essential products under partial or total failure scenarios. They also addressed how importing some high spec products can help recover some of the losses and what is needed in order to accomplish this. In addition, the results showed nonlinear relations among local and global objectives for some refineries. The results demonstrate that refineries can have a local multi objective optimum that does not

Optimal design and management of chlorination in drinking water networks: a multi-objective approach using Genetic Algorithms and the Pareto optimality concept

Science.gov (United States)

Nouiri, Issam

2017-11-01

This paper presents the development of multi-objective Genetic Algorithms to optimize chlorination design and management in drinking water networks (DWN). Three objectives have been considered: the improvement of the chlorination uniformity (healthy objective), the minimization of chlorine booster stations number, and the injected chlorine mass (economic objectives). The problem has been dissociated in medium and short terms ones. The proposed methodology was tested on hypothetical and real DWN. Results proved the ability of the developed optimization tool to identify relationships between the healthy and economic objectives as Pareto fronts. The proposed approach was efficient in computing solutions ensuring better chlorination uniformity while requiring the weakest injected chlorine mass when compared to other approaches. For the real DWN studied, chlorination optimization has been crowned by great improvement of free-chlorine-dosing uniformity and by a meaningful chlorine mass reduction, in comparison with the conventional chlorination.

PRODUCT LIFECYCLE OPTIMISATION OF CAR CLIMATE CONTROLS USING ANALYTICAL HIERARCHICAL PROCESS (AHP ANALYSIS AND A MULTI-OBJECTIVE GROUPING GENETIC ALGORITHM (MOGGA

Directory of Open Access Journals (Sweden)

MICHAEL J. LEE

2016-01-01

Full Text Available A product’s lifecycle performance (e.g. assembly, outsourcing, maintenance and recycling can often be improved through modularity. However, modularisation under different and often conflicting lifecycle objectives is a complex problem that will ultimately require trade-offs. This paper presents a novel multi-objective modularity optimisation framework; the application of which is illustrated through the modularisation of a car climate control system. Central to the framework is a specially designed multi-objective grouping genetic algorithm (MOGGA that is able to generate a whole range of alternative product modularisations. Scenario analysis, using the principles of the analytical hierarchical process (AHP, is then carried out to explore the solution set and choose a suitable modular architecture that optimises the product lifecycle according to the company’s strategic vision.

Single-Cell Quantitative PCR: Advances and Potential in Cancer Diagnostics.

Science.gov (United States)

Ok, Chi Young; Singh, Rajesh R; Salim, Alaa A

2016-01-01

Tissues are heterogeneous in their components. If cells of interest are a minor population of collected tissue, it would be difficult to obtain genetic or genomic information of the interested cell population with conventional genomic DNA extraction from the collected tissue. Single-cell DNA analysis is important in the analysis of genetics of cell clonality, genetic anticipation, and single-cell DNA polymorphisms. Single-cell PCR using Single Cell Ampligrid/GeXP platform is described in this chapter.

Desktop Genetics

OpenAIRE

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

2016-01-01

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

Possible people, complaints, and the distinction between genetic planning and genetic engineering.

Science.gov (United States)

Delaney, James J

2011-07-01

Advances in the understanding of genetics have led to the belief that it may become possible to use genetic engineering to manipulate the DNA of humans at the embryonic stage to produce certain desirable traits. Although this currently cannot be done on a large scale, many people nevertheless object in principle to such practices. Most often, they argue that genetic enhancements would harm the children who were engineered, cause societal harms, or that the risks of perfecting the procedures are too high to proceed. However, many of these same people do not have serious objections to what is called 'genetic planning' procedures (such as the selection of sperm donors with desirable traits) that essentially have the same ends. The author calls the view that genetic engineering enhancements are impermissible while genetic planning enhancements are permissible the 'popular view', and argues that the typical reasons people give for the popular view fail to distinguish the two practices. This paper provides a principle that can salvage the popular view, which stresses that offspring from genetic engineering practices have grounds for complaint because they are identical to the pre-enhanced embryo, whereas offspring who are the result of genetic planning have no such grounds.

Energy-Efficient Scheduling Problem Using an Effective Hybrid Multi-Objective Evolutionary Algorithm

Directory of Open Access Journals (Sweden)

Lvjiang Yin

2016-12-01

Full Text Available Nowadays, manufacturing enterprises face the challenge of just-in-time (JIT production and energy saving. Therefore, study of JIT production and energy consumption is necessary and important in manufacturing sectors. Moreover, energy saving can be attained by the operational method and turn off/on idle machine method, which also increases the complexity of problem solving. Thus, most researchers still focus on small scale problems with one objective: a single machine environment. However, the scheduling problem is a multi-objective optimization problem in real applications. In this paper, a single machine scheduling model with controllable processing and sequence dependence setup times is developed for minimizing the total earliness/tardiness (E/T, cost, and energy consumption simultaneously. An effective multi-objective evolutionary algorithm called local multi-objective evolutionary algorithm (LMOEA is presented to tackle this multi-objective scheduling problem. To accommodate the characteristic of the problem, a new solution representation is proposed, which can convert discrete combinational problems into continuous problems. Additionally, a multiple local search strategy with self-adaptive mechanism is introduced into the proposed algorithm to enhance the exploitation ability. The performance of the proposed algorithm is evaluated by instances with comparison to other multi-objective meta-heuristics such as Nondominated Sorting Genetic Algorithm II (NSGA-II, Strength Pareto Evolutionary Algorithm 2 (SPEA2, Multiobjective Particle Swarm Optimization (OMOPSO, and Multiobjective Evolutionary Algorithm Based on Decomposition (MOEA/D. Experimental results demonstrate that the proposed LMOEA algorithm outperforms its counterparts for this kind of scheduling problems.

Multi-objective optimization of cooling air distributions of grate cooler with different clinker particles diameters and air chambers by genetic algorithm

International Nuclear Information System (INIS)

Shao, Wei; Cui, Zheng; Cheng, Lin

2017-01-01

Highlights: • A multi-objective optimization model of air distributions of grate cooler by genetic algorithm is proposed. • Optimal air distributions of different conditions are obtained and validated by measurements. • The most economic average diameters of clinker particles is 0.02 m. • The most economic amount of air chambers is 9. - Abstract: The paper proposes a multi-objective optimization model of cooling air distributions of grate cooler in cement plant based on convective heat transfer principle and entropy generation minimization analysis. The heat transfer and flow models of clinker cooling process are brought out at first. Then the modified entropy generation numbers caused by heat transfer and viscous dissipation are considered as objective functions respectively which are optimized by genetic algorithm simultaneously. The design variables are superficial velocities of air chambers and thicknesses of clinker layer on different grate plates. The model is verified by a set of Pareto optimal solutions and scattered distributions of design variables. Sensitive analysis of average diameters of clinker particles and amount of air chambers are carried out based on the optimization model. The optimal cooling air distributions are compared by heat recovered, energy consumption of cooling fans and heat efficiency of grate cooler. And all of them are selected from the Pareto optimal solutions based on energy consumption of cooling fans minimization. The results show that the most effective and economic average diameter of clinker particles is 0.02 m and the amount of air chambers is 9.

Linear Mixed Models in Statistical Genetics

NARCIS (Netherlands)

R. de Vlaming (Ronald)

2017-01-01

markdownabstractOne of the goals of statistical genetics is to elucidate the genetic architecture of phenotypes (i.e., observable individual characteristics) that are affected by many genetic variants (e.g., single-nucleotide polymorphisms; SNPs). A particular aim is to identify specific SNPs that

A calderón-preconditioned single source combined field integral equation for analyzing scattering from homogeneous penetrable objects

KAUST Repository

Valdés, Felipe

2011-06-01

A new regularized single source equation for analyzing scattering from homogeneous penetrable objects is presented. The proposed equation is a linear combination of a Calderón-preconditioned single source electric field integral equation and a single source magnetic field integral equation. The equation is immune to low-frequency and dense-mesh breakdown, and free from spurious resonances. Unlike dual source formulations, this equation involves operator products that cannot be discretized using standard procedures for discretizing standalone electric, magnetic, and combined field operators. Instead, the single source equation proposed here is discretized using a recently developed technique that achieves a well-conditioned mapping from div- to curl-conforming function spaces, thereby fully respecting the space mapping properties of the operators involved, and guaranteeing accuracy and stability. Numerical results show that the proposed equation and discretization technique give rise to rapidly convergent solutions. They also validate the equation\\'s resonant free character. © 2006 IEEE.

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

Science.gov (United States)

Valdés, Julio J; Barton, Alan J

2007-05-01

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

Accuracy of preimplantation genetic diagnosis (PGD) of single gene and chromosomal disorders

Energy Technology Data Exchange (ETDEWEB)

Verlinsky, Y.; Strom, C.; Rechitsky, S. [Reproductive Genetics Institute, Chicage, IL (United States)] [and others

1994-09-01

We have developed a polar body inferred approach for preconception diagnosis of single gene and chromosomal disorders. Preconception PCR or FISH analysis was performed in a total of 310 first polar bodies for the following genetic conditions: cystic fibrosis, hemophilia A, alpha-1-antitrypsin deficiency, Tay Sachs disease, retinitis pigmentosa and common chromosomal trisomies. An important advantage of this approach is the avoidance of sperm (DNA) contamination, which is the major problem of PGD. We are currently applying FISH analysis of biopsied blastomeres, in combination with PCR or separately, and have demonstrated a significant improvement of the accuracy of PGD of X-linked disorders at this stage. Our data have also demonstrated feasibility of the application of FISH technique for PGD of chromosomal disorders. It was possible to detect chromosomal non-disjunctions and chromatid malsegregations in the first meiotic division, as well as to evaluate chromosomal mutations originating from the second meiotic nondisjunction.

Woodland Mapping at Single-Tree Levels Using Object-Oriented Classification of Unmanned Aerial Vehicle (uav) Images

Science.gov (United States)

Chenari, A.; Erfanifard, Y.; Dehghani, M.; Pourghasemi, H. R.

2017-09-01

Remotely sensed datasets offer a reliable means to precisely estimate biophysical characteristics of individual species sparsely distributed in open woodlands. Moreover, object-oriented classification has exhibited significant advantages over different classification methods for delineation of tree crowns and recognition of species in various types of ecosystems. However, it still is unclear if this widely-used classification method can have its advantages on unmanned aerial vehicle (UAV) digital images for mapping vegetation cover at single-tree levels. In this study, UAV orthoimagery was classified using object-oriented classification method for mapping a part of wild pistachio nature reserve in Zagros open woodlands, Fars Province, Iran. This research focused on recognizing two main species of the study area (i.e., wild pistachio and wild almond) and estimating their mean crown area. The orthoimage of study area was consisted of 1,076 images with spatial resolution of 3.47 cm which was georeferenced using 12 ground control points (RMSE=8 cm) gathered by real-time kinematic (RTK) method. The results showed that the UAV orthoimagery classified by object-oriented method efficiently estimated mean crown area of wild pistachios (52.09±24.67 m2) and wild almonds (3.97±1.69 m2) with no significant difference with their observed values (α=0.05). In addition, the results showed that wild pistachios (accuracy of 0.90 and precision of 0.92) and wild almonds (accuracy of 0.90 and precision of 0.89) were well recognized by image segmentation. In general, we concluded that UAV orthoimagery can efficiently produce precise biophysical data of vegetation stands at single-tree levels, which therefore is suitable for assessment and monitoring open woodlands.

Optimal design of link systems using successive zooming genetic algorithm

Science.gov (United States)

Kwon, Young-Doo; Sohn, Chang-hyun; Kwon, Soon-Bum; Lim, Jae-gyoo

2009-07-01

Link-systems have been around for a long time and are still used to control motion in diverse applications such as automobiles, robots and industrial machinery. This study presents a procedure involving the use of a genetic algorithm for the optimal design of single four-bar link systems and a double four-bar link system used in diesel engine. We adopted the Successive Zooming Genetic Algorithm (SZGA), which has one of the most rapid convergence rates among global search algorithms. The results are verified by experiment and the Recurdyn dynamic motion analysis package. During the optimal design of single four-bar link systems, we found in the case of identical input/output (IO) angles that the initial and final configurations show certain symmetry. For the double link system, we introduced weighting factors for the multi-objective functions, which minimize the difference between output angles, providing balanced engine performance, as well as the difference between final output angle and the desired magnitudes of final output angle. We adopted a graphical method to select a proper ratio between the weighting factors.

Applications of genetic algorithms to optimization problems in the solvent extraction process for spent nuclear fuel

International Nuclear Information System (INIS)

Omori, Ryota, Sakakibara, Yasushi; Suzuki, Atsuyuki

1997-01-01

Applications of genetic algorithms (GAs) to optimization problems in the solvent extraction process for spent nuclear fuel are described. Genetic algorithms have been considered a promising tool for use in solving optimization problems in complicated and nonlinear systems because they require no derivatives of the objective function. In addition, they have the ability to treat a set of many possible solutions and consider multiple objectives simultaneously, so they can calculate many pareto optimal points on the trade-off curve between the competing objectives in a single iteration, which leads to small computing time. Genetic algorithms were applied to two optimization problems. First, process variables in the partitioning process were optimized using a weighted objective function. It was observed that the average fitness of a generation increased steadily as the generation proceeded and satisfactory solutions were obtained in all cases, which means that GAs are an appropriate method to obtain such an optimization. Secondly, GAs were applied to a multiobjective optimization problem in the co-decontamination process, and the trade-off curve between the loss of uranium and the solvent flow rate was successfully obtained. For both optimization problems, CPU time with the present method was estimated to be several tens of times smaller than with the random search method

Genetic specificity of face recognition.

Science.gov (United States)

Shakeshaft, Nicholas G; Plomin, Robert

2015-10-13

Specific cognitive abilities in diverse domains are typically found to be highly heritable and substantially correlated with general cognitive ability (g), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition. However, the genetic relationships between face recognition and other abilities (the extent to which they share a common genetic etiology) cannot be determined from phenotypic associations. In this, to our knowledge, first study of the genetic associations between face recognition and other domains, 2,000 18- and 19-year-old United Kingdom twins completed tests assessing their face recognition, object recognition, and general cognitive abilities. Results confirmed the substantial heritability of face recognition (61%), and multivariate genetic analyses found that most of this genetic influence is unique and not shared with other cognitive abilities.

Single Cell Oncogenesis

Science.gov (United States)

Lu, Xin

It is believed that cancer originates from a single cell that has gone through generations of evolution of genetic and epigenetic changes that associate with the hallmarks of cancer. In some cancers such as various types of leukemia, cancer is clonal. Yet in other cancers like glioblastoma (GBM), there is tremendous tumor heterogeneity that is likely to be caused by simultaneous evolution of multiple subclones within the same tissue. It is obvious that understanding how a single cell develops into a clonal tumor upon genetic alterations, at molecular and cellular levels, holds the key to the real appreciation of tumor etiology and ultimate solution for therapeutics. Surprisingly very little is known about the process of spontaneous tumorigenesis from single cells in human or vertebrate animal models. The main reason is the lack of technology to track the natural process of single cell changes from a homeostatic state to a progressively cancerous state. Recently, we developed a patented compound, photoactivatable (''caged'') tamoxifen analogue 4-OHC and associated technique called optochemogenetic switch (OCG switch), which we believe opens the opportunity to address this urgent biological as well as clinical question about cancer. We propose to combine OCG switch with genetically engineered mouse models of head and neck squamous cell carcinoma and high grade astrocytoma (including GBM) to study how single cells, when transformed through acute loss of tumor suppressor genes PTEN and TP53 and gain of oncogenic KRAS, can develop into tumor colonies with cellular and molecular heterogeneity in these tissues. The abstract is for my invited talk in session ``Beyond Darwin: Evolution in Single Cells'' 3/18/2016 11:15 AM.

Multi-objective approach in thermoenvironomic optimization of a benchmark cogeneration system

International Nuclear Information System (INIS)

Sayyaadi, Hoseyn

2009-01-01

Multi-objective optimization for designing of a benchmark cogeneration system known as CGAM cogeneration system has been performed. In optimization approach, the exergetic, economic and environmental aspects have been considered, simultaneously. The thermodynamic modeling has been implemented comprehensively while economic analysis conducted in accordance with the total revenue requirement (TRR) method. The results for the single objective thermoeconomic optimization have been compared with the previous studies in optimization of CGAM problem. In multi-objective optimization of the CGAM problem, the three objective functions including the exergetic efficiency, total levelized cost rate of the system product and the cost rate of environmental impact have been considered. The environmental impact objective function has been defined and expressed in cost terms. This objective has been integrated with the thermoeconomic objective to form a new unique objective function known as a thermoenvironomic objective function. The thermoenvironomic objective has been minimized while the exergetic objective has been maximized. One of the most suitable optimization techniques developed using a particular class of search algorithms known as multi-objective evolutionary algorithms (MOEAs) has been considered here. This approach which is developed based on the genetic algorithm has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of decision-making has been presented and a final optimal solution has been introduced. The sensitivity of the solutions to the interest rate and the fuel cost has been studied

A multiobjective approach to the genetic code adaptability problem.

Science.gov (United States)

de Oliveira, Lariza Laura; de Oliveira, Paulo S L; Tinós, Renato

2015-02-19

The organization of the canonical code has intrigued researches since it was first described. If we consider all codes mapping the 64 codes into 20 amino acids and one stop codon, there are more than 1.51×10(84) possible genetic codes. The main question related to the organization of the genetic code is why exactly the canonical code was selected among this huge number of possible genetic codes. Many researchers argue that the organization of the canonical code is a product of natural selection and that the code's robustness against mutations would support this hypothesis. In order to investigate the natural selection hypothesis, some researches employ optimization algorithms to identify regions of the genetic code space where best codes, according to a given evaluation function, can be found (engineering approach). The optimization process uses only one objective to evaluate the codes, generally based on the robustness for an amino acid property. Only one objective is also employed in the statistical approach for the comparison of the canonical code with random codes. We propose a multiobjective approach where two or more objectives are considered simultaneously to evaluate the genetic codes. In order to test our hypothesis that the multiobjective approach is useful for the analysis of the genetic code adaptability, we implemented a multiobjective optimization algorithm where two objectives are simultaneously optimized. Using as objectives the robustness against mutation with the amino acids properties polar requirement (objective 1) and robustness with respect to hydropathy index or molecular volume (objective 2), we found solutions closer to the canonical genetic code in terms of robustness, when compared with the results using only one objective reported by other authors. Using more objectives, more optimal solutions are obtained and, as a consequence, more information can be used to investigate the adaptability of the genetic code. The multiobjective approach

Error analysis of marker-based object localization using a single-plane XRII

International Nuclear Information System (INIS)

Habets, Damiaan F.; Pollmann, Steven I.; Yuan, Xunhua; Peters, Terry M.; Holdsworth, David W.

2009-01-01

The role of imaging and image guidance is increasing in surgery and therapy, including treatment planning and follow-up. Fluoroscopy is used for two-dimensional (2D) guidance or localization; however, many procedures would benefit from three-dimensional (3D) guidance or localization. Three-dimensional computed tomography (CT) using a C-arm mounted x-ray image intensifier (XRII) can provide high-quality 3D images; however, patient dose and the required acquisition time restrict the number of 3D images that can be obtained. C-arm based 3D CT is therefore limited in applications for x-ray based image guidance or dynamic evaluations. 2D-3D model-based registration, using a single-plane 2D digital radiographic system, does allow for rapid 3D localization. It is our goal to investigate - over a clinically practical range - the impact of x-ray exposure on the resulting range of 3D localization precision. In this paper it is assumed that the tracked instrument incorporates a rigidly attached 3D object with a known configuration of markers. A 2D image is obtained by a digital fluoroscopic x-ray system and corrected for XRII distortions (±0.035 mm) and mechanical C-arm shift (±0.080 mm). A least-square projection-Procrustes analysis is then used to calculate the 3D position using the measured 2D marker locations. The effect of x-ray exposure on the precision of 2D marker localization and on 3D object localization was investigated using numerical simulations and x-ray experiments. The results show a nearly linear relationship between 2D marker localization precision and the 3D localization precision. However, a significant amplification of error, nonuniformly distributed among the three major axes, occurs, and that is demonstrated. To obtain a 3D localization error of less than ±1.0 mm for an object with 20 mm marker spacing, the 2D localization precision must be better than ±0.07 mm. This requirement was met for all investigated nominal x-ray exposures at 28 cm FOV, and

Pathological mechanisms underlying single large‐scale mitochondrial DNA deletions

Science.gov (United States)

Rocha, Mariana C.; Rosa, Hannah S.; Grady, John P.; Blakely, Emma L.; He, Langping; Romain, Nadine; Haller, Ronald G.; Newman, Jane; McFarland, Robert; Ng, Yi Shiau; Gorman, Grainne S.; Schaefer, Andrew M.; Tuppen, Helen A.; Taylor, Robert W.

2018-01-01

Objective Single, large‐scale deletions in mitochondrial DNA (mtDNA) are a common cause of mitochondrial disease. This study aimed to investigate the relationship between the genetic defect and molecular phenotype to improve understanding of pathogenic mechanisms associated with single, large‐scale mtDNA deletions in skeletal muscle. Methods We investigated 23 muscle biopsies taken from adult patients (6 males/17 females with a mean age of 43 years) with characterized single, large‐scale mtDNA deletions. Mitochondrial respiratory chain deficiency in skeletal muscle biopsies was quantified by immunoreactivity levels for complex I and complex IV proteins. Single muscle fibers with varying degrees of deficiency were selected from 6 patient biopsies for determination of mtDNA deletion level and copy number by quantitative polymerase chain reaction. Results We have defined 3 “classes” of single, large‐scale deletion with distinct patterns of mitochondrial deficiency, determined by the size and location of the deletion. Single fiber analyses showed that fibers with greater respiratory chain deficiency harbored higher levels of mtDNA deletion with an increase in total mtDNA copy number. For the first time, we have demonstrated that threshold levels for complex I and complex IV deficiency differ based on deletion class. Interpretation Combining genetic and immunofluorescent assays, we conclude that thresholds for complex I and complex IV deficiency are modulated by the deletion of complex‐specific protein‐encoding genes. Furthermore, removal of mt‐tRNA genes impacts specific complexes only at high deletion levels, when complex‐specific protein‐encoding genes remain. These novel findings provide valuable insight into the pathogenic mechanisms associated with these mutations. Ann Neurol 2018;83:115–130 PMID:29283441

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.

Biokinetic model-based multi-objective optimization of Dunaliella tertiolecta cultivation using elitist non-dominated sorting genetic algorithm with inheritance.

Science.gov (United States)

Sinha, Snehal K; Kumar, Mithilesh; Guria, Chandan; Kumar, Anup; Banerjee, Chiranjib

2017-10-01

Algal model based multi-objective optimization using elitist non-dominated sorting genetic algorithm with inheritance was carried out for batch cultivation of Dunaliella tertiolecta using NPK-fertilizer. Optimization problems involving two- and three-objective functions were solved simultaneously. The objective functions are: maximization of algae-biomass and lipid productivity with minimization of cultivation time and cost. Time variant light intensity and temperature including NPK-fertilizer, NaCl and NaHCO 3 loadings are the important decision variables. Algal model involving Monod/Andrews adsorption kinetics and Droop model with internal nutrient cell quota was used for optimization studies. Sets of non-dominated (equally good) Pareto optimal solutions were obtained for the problems studied. It was observed that time variant optimal light intensity and temperature trajectories, including optimum NPK fertilizer, NaCl and NaHCO 3 concentration has significant influence to improve biomass and lipid productivity under minimum cultivation time and cost. Proposed optimization studies may be helpful to implement the control strategy in scale-up operation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimization of a Finned Shell and Tube Heat Exchanger Using a Multi-Objective Optimization Genetic Algorithm

Directory of Open Access Journals (Sweden)

Heidar Sadeghzadeh

2015-08-01

Full Text Available Heat transfer rate and cost significantly affect designs of shell and tube heat exchangers. From the viewpoint of engineering, an optimum design is obtained via maximum heat transfer rate and minimum cost. Here, an analysis of a radial, finned, shell and tube heat exchanger is carried out, considering nine design parameters: tube arrangement, tube diameter, tube pitch, tube length, number of tubes, fin height, fin thickness, baffle spacing ratio and number of fins per unit length of tube. The “Delaware modified” technique is used to determine heat transfer coefficients and the shell-side pressure drop. In this technique, the baffle cut is 20 percent and the baffle ratio limits range from 0.2 to 0.4. The optimization of the objective functions (maximum heat transfer rate and minimum total cost is performed using a non-dominated sorting genetic algorithm (NSGA-II, and compared against a one-objective algorithm, to find the best solutions. The results are depicted as a set of solutions on a Pareto front, and show that the heat transfer rate ranges from 3517 to 7075 kW. Also, the minimum and maximum objective functions are specified, allowing the designer to select the best points among these solutions based on requirements. Additionally, variations of shell-side pressure drop with total cost are depicted, and indicate that the pressure drop ranges from 3.8 to 46.7 kPa.

Alternatives and challenges in optimizing industrial safety using genetic algorithms

International Nuclear Information System (INIS)

Martorell, Sebastian; Sanchez, Ana; Carlos, Sofia; Serradell, Vicente

2004-01-01

Safety (S) improvement of industrial installations leans on the optimal allocation of designs that use more reliable equipment and testing and maintenance activities to assure a high level of reliability, availability and maintainability (RAM) for their safety-related systems. However, this also requires assigning a certain amount of resources (C) that are usually limited. Therefore, the decision-maker in this context faces in general a multiple-objective optimization problem (MOP) based on RAMS+C criteria where the parameters of design, testing and maintenance act as decision variables. Solutions to the MOP can be obtained by solving the problem directly, or by transforming it into several single-objective problems. A general framework for such MOP based on RAMS+C criteria is proposed in this paper. Then, problem formulation and fundamentals of two major groups of resolution alternatives are presented. Next, both alternatives are implemented in this paper using genetic algorithms (GAs), named single-objective GA and multi-objective GA, respectively, which are then used in the case of application to solve the problem of testing and maintenance optimization based on unavailability and cost criteria. The results show the capabilities and limitations of both approaches. Based on them, future challenges are identified in this field and guidelines provided for further research

Perceived genetic knowledge, attitudes towards genetic testing, and the relationship between these among patients with a chronic disease

NARCIS (Netherlands)

Morren, M.; Rijken, M.; Baanders, A.N.; Bensing, J.

2007-01-01

Objective: Genetics increasingly permeate everyday medicine. When patients want to make informed decisions about genetic testing, they require genetic knowledge. This study examined the genetic knowledge and attitudes of patients with chronic diseases, and the relationship between both. In addition,

Perceived genetic knowledge, attitudes toward genetic testing, and the relationship between these among patients with a chronic disease.

NARCIS (Netherlands)

Morren, M.; Rijken, M.; Baanders, A.N.; Bensing, J.

2007-01-01

OBJECTIVE: Genetics increasingly permeate everyday medicine. When patients want to make informed decisions about genetic testing, they require genetic knowledge. This study examined the genetic knowledge and attitudes of patients with chronic diseases, and the relationship between both. In addition,

Identification of single-copy orthologous genes between Physalis and Solanum lycopersicum and analysis of genetic diversity in Physalis using molecular markers.

Science.gov (United States)

Wei, Jingli; Hu, Xiaorong; Yang, Jingjing; Yang, Wencai

2012-01-01

The genus Physalis includes a number of commercially important edible and ornamental species. Its high nutritional value and potential medicinal properties leads to the increased commercial interest in the products of this genus worldwide. However, lack of molecular markers prevents the detailed study of genetics and phylogeny in Physalis, which limits the progress of breeding. In the present study, we compared the DNA sequences between Physalis and tomato, and attempted to analyze genetic diversity in Physalis using tomato markers. Blasting 23180 DNA sequences derived from Physalis against the International Tomato Annotation Group (ITAG) Release2.3 Predicted CDS (SL2.40) discovered 3356 single-copy orthologous genes between them. A total of 38 accessions from at least six species of Physalis were subjected to genetic diversity analysis using 97 tomato markers and 25 SSR markers derived from P. peruviana. Majority (73.2%) of tomato markers could amplify DNA fragments from at least one accession of Physalis. Diversity in Physalis at molecular level was also detected. The average Nei's genetic distance between accessions was 0.3806 with a range of 0.2865 to 0.7091. These results indicated Physalis and tomato had similarity at both molecular marker and DNA sequence levels. Therefore, the molecular markers developed in tomato can be used in genetic study in Physalis.

WOODLAND MAPPING AT SINGLE-TREE LEVELS USING OBJECT-ORIENTED CLASSIFICATION OF UNMANNED AERIAL VEHICLE (UAV IMAGES

Directory of Open Access Journals (Sweden)

A. Chenari

2017-09-01

Full Text Available Remotely sensed datasets offer a reliable means to precisely estimate biophysical characteristics of individual species sparsely distributed in open woodlands. Moreover, object-oriented classification has exhibited significant advantages over different classification methods for delineation of tree crowns and recognition of species in various types of ecosystems. However, it still is unclear if this widely-used classification method can have its advantages on unmanned aerial vehicle (UAV digital images for mapping vegetation cover at single-tree levels. In this study, UAV orthoimagery was classified using object-oriented classification method for mapping a part of wild pistachio nature reserve in Zagros open woodlands, Fars Province, Iran. This research focused on recognizing two main species of the study area (i.e., wild pistachio and wild almond and estimating their mean crown area. The orthoimage of study area was consisted of 1,076 images with spatial resolution of 3.47 cm which was georeferenced using 12 ground control points (RMSE=8 cm gathered by real-time kinematic (RTK method. The results showed that the UAV orthoimagery classified by object-oriented method efficiently estimated mean crown area of wild pistachios (52.09±24.67 m2 and wild almonds (3.97±1.69 m2 with no significant difference with their observed values (α=0.05. In addition, the results showed that wild pistachios (accuracy of 0.90 and precision of 0.92 and wild almonds (accuracy of 0.90 and precision of 0.89 were well recognized by image segmentation. In general, we concluded that UAV orthoimagery can efficiently produce precise biophysical data of vegetation stands at single-tree levels, which therefore is suitable for assessment and monitoring open woodlands.

Gene-based single nucleotide polymorphism markers for genetic and association mapping in common bean.

Science.gov (United States)

Galeano, Carlos H; Cortés, Andrés J; Fernández, Andrea C; Soler, Álvaro; Franco-Herrera, Natalia; Makunde, Godwill; Vanderleyden, Jos; Blair, Matthew W

2012-06-26

In common bean, expressed sequence tags (ESTs) are an underestimated source of gene-based markers such as insertion-deletions (Indels) or single-nucleotide polymorphisms (SNPs). However, due to the nature of these conserved sequences, detection of markers is difficult and portrays low levels of polymorphism. Therefore, development of intron-spanning EST-SNP markers can be a valuable resource for genetic experiments such as genetic mapping and association studies. In this study, a total of 313 new gene-based markers were developed at target genes. Intronic variation was deeply explored in order to capture more polymorphism. Introns were putatively identified after comparing the common bean ESTs with the soybean genome, and the primers were designed over intron-flanking regions. The intronic regions were evaluated for parental polymorphisms using the single strand conformational polymorphism (SSCP) technique and Sequenom MassARRAY system. A total of 53 new marker loci were placed on an integrated molecular map in the DOR364 × G19833 recombinant inbred line (RIL) population. The new linkage map was used to build a consensus map, merging the linkage maps of the BAT93 × JALO EEP558 and DOR364 × BAT477 populations. A total of 1,060 markers were mapped, with a total map length of 2,041 cM across 11 linkage groups. As a second application of the generated resource, a diversity panel with 93 genotypes was evaluated with 173 SNP markers using the MassARRAY-platform and KASPar technology. These results were coupled with previous SSR evaluations and drought tolerance assays carried out on the same individuals. This agglomerative dataset was examined, in order to discover marker-trait associations, using general linear model (GLM) and mixed linear model (MLM). Some significant associations with yield components were identified, and were consistent with previous findings. In short, this study illustrates the power of intron-based markers for linkage and association mapping in

Prediction and optimization of fuel cell performance using a multi-objective genetic algorithm

Energy Technology Data Exchange (ETDEWEB)

Marques Hobold, Gustavo [Laboratory of Energy Conversion Engineering and Technology, Federal University of Santa Catarina (Brazil); Washington University in St. Louis, MO 63130 (United States); Agarwal, Ramesh K. [Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, MO 63130 (United States)

2013-07-01

The attention that is currently being given to the emission of pollutant gases in the atmosphere has made the fuel cell (FC), an energy conversion device that cleanly converts chemical energy into electrical energy, a good alternative to other technologies that still use carbon-based fuels. The temperature plays an important role on the efficiency of an FC as it influences directly the humidity of the membrane, the reversible thermodynamic potential and the partial pressure of water; therefore the thermal control of the fuel cell is the focus of this paper. We present models for both high and low temperature fuel cells based on the solid-oxide fuel cell (SOFC) and the polymer electrolyte membrane fuel cell (PEMFC). A thermodynamic analysis is performed on the cells and the methods of controlling their temperature are discussed. The cell parameters are optimized for both high and low temperatures using a Java-based multi-objective genetic algorithm, which makes use of the logic of the biological theory of evolution to classify individual parameters based on a fitness function in order to maximize the power of the fuel cell. Applications to high and low temperature fuel cells are discussed.

Numerical correction of anti-symmetric aberrations in single HRTEM images of weakly scattering 2D-objects

International Nuclear Information System (INIS)

Lehtinen, Ossi; Geiger, Dorin; Lee, Zhongbo; Whitwick, Michael Brian; Chen, Ming-Wei; Kis, Andras; Kaiser, Ute

2015-01-01

Here, we present a numerical post-processing method for removing the effect of anti-symmetric residual aberrations in high-resolution transmission electron microscopy (HRTEM) images of weakly scattering 2D-objects. The method is based on applying the same aberrations with the opposite phase to the Fourier transform of the recorded image intensity and subsequently inverting the Fourier transform. We present the theoretical justification of the method, and its verification based on simulated images in the case of low-order anti-symmetric aberrations. Ultimately the method is applied to experimental hardware aberration-corrected HRTEM images of single-layer graphene and MoSe 2 resulting in images with strongly reduced residual low-order aberrations, and consequently improved interpretability. Alternatively, this method can be used to estimate by trial and error the residual anti-symmetric aberrations in HRTEM images of weakly scattering objects

Reproductive cloning combined with genetic modification.

Science.gov (United States)

Strong, C

2005-11-01

Although there is widespread opposition to reproductive cloning, some have argued that its use by infertile couples to have genetically related children would be ethically justifiable. Others have suggested that lesbian or gay couples might wish to use cloning to have genetically related children. Most of the main objections to human reproductive cloning are based on the child's lack of unique nuclear DNA. In the future, it may be possible safely to create children using cloning combined with genetic modifications, so that they have unique nuclear DNA. The genetic modifications could be aimed at giving such children genetic characteristics of both members of the couple concerned. Thus, cloning combined with genetic modification could be appealing to infertile, lesbian, or gay couples who seek genetically related children who have genetic characteristics of both members. In such scenarios, the various objections to human reproductive cloning that are based on the lack of genetic uniqueness would no longer be applicable. The author argues that it would be ethically justifiable for such couples to create children in this manner, assuming these techniques could be used safely.

Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

DEFF Research Database (Denmark)

Su, Guosheng; Christensen, Ole Fredslund; Ostersen, Tage

2012-01-01

of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects...

Multi-objective optimization of in-situ bioremediation of groundwater using a hybrid metaheuristic technique based on differential evolution, genetic algorithms and simulated annealing

Directory of Open Access Journals (Sweden)

Kumar Deepak

2015-12-01

Full Text Available Groundwater contamination due to leakage of gasoline is one of the several causes which affect the groundwater environment by polluting it. In the past few years, In-situ bioremediation has attracted researchers because of its ability to remediate the contaminant at its site with low cost of remediation. This paper proposed the use of a new hybrid algorithm to optimize a multi-objective function which includes the cost of remediation as the first objective and residual contaminant at the end of the remediation period as the second objective. The hybrid algorithm was formed by combining the methods of Differential Evolution, Genetic Algorithms and Simulated Annealing. Support Vector Machines (SVM was used as a virtual simulator for biodegradation of contaminants in the groundwater flow. The results obtained from the hybrid algorithm were compared with Differential Evolution (DE, Non Dominated Sorting Genetic Algorithm (NSGA II and Simulated Annealing (SA. It was found that the proposed hybrid algorithm was capable of providing the best solution. Fuzzy logic was used to find the best compromising solution and finally a pumping rate strategy for groundwater remediation was presented for the best compromising solution. The results show that the cost incurred for the best compromising solution is intermediate between the highest and lowest cost incurred for other non-dominated solutions.

Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity.

Science.gov (United States)

Zhong, Qing; Rüschoff, Jan H; Guo, Tiannan; Gabrani, Maria; Schüffler, Peter J; Rechsteiner, Markus; Liu, Yansheng; Fuchs, Thomas J; Rupp, Niels J; Fankhauser, Christian; Buhmann, Joachim M; Perner, Sven; Poyet, Cédric; Blattner, Miriam; Soldini, Davide; Moch, Holger; Rubin, Mark A; Noske, Aurelia; Rüschoff, Josef; Haffner, Michael C; Jochum, Wolfram; Wild, Peter J

2016-04-07

Recent large-scale genome analyses of human tissue samples have uncovered a high degree of genetic alterations and tumour heterogeneity in most tumour entities, independent of morphological phenotypes and histopathological characteristics. Assessment of genetic copy-number variation (CNV) and tumour heterogeneity by fluorescence in situ hybridization (ISH) provides additional tissue morphology at single-cell resolution, but it is labour intensive with limited throughput and high inter-observer variability. We present an integrative method combining bright-field dual-colour chromogenic and silver ISH assays with an image-based computational workflow (ISHProfiler), for accurate detection of molecular signals, high-throughput evaluation of CNV, expressive visualization of multi-level heterogeneity (cellular, inter- and intra-tumour heterogeneity), and objective quantification of heterogeneous genetic deletions (PTEN) and amplifications (19q12, HER2) in diverse human tumours (prostate, endometrial, ovarian and gastric), using various tissue sizes and different scanners, with unprecedented throughput and reproducibility.

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

Multi-objective genetic algorithm parameter estimation in a reduced nuclear reactor model

Energy Technology Data Exchange (ETDEWEB)

Marseguerra, M.; Zio, E.; Canetta, R. [Polytechnic of Milan, Dept. of Nuclear Engineering, Milano (Italy)

2005-07-01

The fast increase in computing power has rendered, and will continue to render, more and more feasible the incorporation of dynamics in the safety and reliability models of complex engineering systems. In particular, the Monte Carlo simulation framework offers a natural environment for estimating the reliability of systems with dynamic features. However, the time-integration of the dynamic processes may render the Monte Carlo simulation quite burdensome so that it becomes mandatory to resort to validated, simplified models of process evolution. Such models are typically based on lumped effective parameters whose values need to be suitably estimated so as to best fit to the available plant data. In this paper we propose a multi-objective genetic algorithm approach for the estimation of the effective parameters of a simplified model of nuclear reactor dynamics. The calibration of the effective parameters is achieved by best fitting the model responses of the quantities of interest to the actual evolution profiles. A case study is reported in which the real reactor is simulated by the QUAndry based Reactor Kinetics (Quark) code available from the Nuclear Energy Agency and the simplified model is based on the point kinetics approximation to describe the neutron balance in the core and on thermal equilibrium relations to describe the energy exchange between the different loops. (authors)

Multi-objective genetic algorithm parameter estimation in a reduced nuclear reactor model

International Nuclear Information System (INIS)

Marseguerra, M.; Zio, E.; Canetta, R.

2005-01-01

The fast increase in computing power has rendered, and will continue to render, more and more feasible the incorporation of dynamics in the safety and reliability models of complex engineering systems. In particular, the Monte Carlo simulation framework offers a natural environment for estimating the reliability of systems with dynamic features. However, the time-integration of the dynamic processes may render the Monte Carlo simulation quite burdensome so that it becomes mandatory to resort to validated, simplified models of process evolution. Such models are typically based on lumped effective parameters whose values need to be suitably estimated so as to best fit to the available plant data. In this paper we propose a multi-objective genetic algorithm approach for the estimation of the effective parameters of a simplified model of nuclear reactor dynamics. The calibration of the effective parameters is achieved by best fitting the model responses of the quantities of interest to the actual evolution profiles. A case study is reported in which the real reactor is simulated by the QUAndry based Reactor Kinetics (Quark) code available from the Nuclear Energy Agency and the simplified model is based on the point kinetics approximation to describe the neutron balance in the core and on thermal equilibrium relations to describe the energy exchange between the different loops. (authors)

[Application of single nucleotide polymorphism-microarray and target gene sequencing in the study of genetic etiology of children with unexplained intellectual disability or developmental delay].

Science.gov (United States)

Gao, Z J; Jiang, Q; Cheng, D Z; Yan, X X; Chen, Q; Xu, K M

2016-10-02

Objective: To evaluate the application of single nucleotide polymorphism (SNP)-microarray and target gene sequencing technology in the clinical molecular genetic diagnosis of unexplained intellectual disability(ID) or developmental delay (DD). Method: Patients with ID or DD were recruited in the Department of Neurology, Affiliated Children's Hospital of Capital Institute of Pediatrics between September 2015 and February 2016. The intellectual assessment of the patients was performed using 0-6-year-old pediatric examination table of neuropsychological development or Wechsler intelligence scale (>6 years). Patients with a DQ less than 49 or IQ less than 51 were included in this study. The patients were scanned by SNP-array for detection of genomic copy number variations (CNV), and the revealed genomic imbalance was confirmed by quantitative real time-PCR. Candidate gene mutation screening was carried out by target gene sequencing technology.Causal mutations or likely pathogenic variants were verified by polymerase chain reaction and direct sequencing. Result: There were 15 children with ID or DD enrolled, 9 males and 6 females. The age of these patients was 7 months-16 years and 9 months. SNP-array revealed that two of the 15 patients had genomic CNV. Both CNV were de novo micro deletions, one involved 11q24.1q25 and the other micro deletion located on 21q22.2q22.3. Both micro deletions were proved to have a clinical significance due to their association with ID, brain DD, unusual faces etc. by querying Decipher database. Thirteen patients with negative findings in SNP-array were consequently examined with target gene sequencing technology, genotype-phenotype correlation analysis and genetic analysis. Five patients were diagnosed with monogenic disorder, two were diagnosed with suspected genetic disorder and six were still negative. Conclusion: Sequential use of SNP-array and target gene sequencing technology can significantly increase the molecular genetic etiologic

Object-based warping: an illusory distortion of space within objects.

Science.gov (United States)

Vickery, Timothy J; Chun, Marvin M

2010-12-01

Visual objects are high-level primitives that are fundamental to numerous perceptual functions, such as guidance of attention. We report that objects warp visual perception of space in such a way that spatial distances within objects appear to be larger than spatial distances in ground regions. When two dots were placed inside a rectangular object, they appeared farther apart from one another than two dots with identical spacing outside of the object. To investigate whether this effect was object based, we measured the distortion while manipulating the structure surrounding the dots. Object displays were constructed with a single object, multiple objects, a partially occluded object, and an illusory object. Nonobject displays were constructed to be comparable to object displays in low-level visual attributes. In all cases, the object displays resulted in a more powerful distortion of spatial perception than comparable non-object-based displays. These results suggest that perception of space within objects is warped.

Production objectives and trait preferences of village poultry producers of Ethiopia: implications for designing breeding schemes utilizing indigenous chicken genetic resources.

Science.gov (United States)

Dana, Nigussie; van der Waaij, Liesbeth H; Dessie, Tadelle; van Arendonk, Johan A M

2010-10-01

To generate information essential for the implementation of breeding schemes suitable for village poultry producers in Ethiopia, a survey was conducted aimed at defining the socioeconomic characteristics of the production environments in different geographic regions, understanding the important functions of chickens, identifying farmers' choice of chicken breeds and the underlying factors that determine the choice of genetic stock used. The survey included both questionnaire survey and a participatory group discussion. A total of 225 households (45 households from each of five Woredas) were interviewed. The questionnaire was designed to collect data covering general information on village poultry production such as socio-management characteristics, production objectives, population structure, breed choice and trait preferences, market preferences of specific traits, and farmers' selection practices. The participatory farmers' discussions were designed to involve stakeholders in defining the breeding objective "traits" and deriving their relative importance in the production environment based on the different functions of chickens and "traits" identified in the interviews. The results showed that production of eggs for consumption is the principal function of chickens in most regions followed by the use as source of income and meat for home consumption. The production system in all geographic regions studied revealed similar features generally characterized by extensive scavenging management, absence of immunization programs, increased risk of exposure of birds to disease and predators, and reproduction entirely based on uncontrolled natural mating and hatching of eggs using broody hens. Farmers' ratings of indigenous chickens with respect to modern breeds showed the highest significance of the adaptive traits in general, and the superior merits of indigenous chickens to high yielding exotic breeds in particular. Adaptation to the production environment was the most

Genome-Wide Single-Nucleotide Polymorphisms Discovery and High-Density Genetic Map Construction in Cauliflower Using Specific-Locus Amplified Fragment Sequencing

Science.gov (United States)

Zhao, Zhenqing; Gu, Honghui; Sheng, Xiaoguang; Yu, Huifang; Wang, Jiansheng; Huang, Long; Wang, Dan

2016-01-01

Molecular markers and genetic maps play an important role in plant genomics and breeding studies. Cauliflower is an important and distinctive vegetable; however, very few molecular resources have been reported for this species. In this study, a novel, specific-locus amplified fragment (SLAF) sequencing strategy was employed for large-scale single nucleotide polymorphism (SNP) discovery and high-density genetic map construction in a double-haploid, segregating population of cauliflower. A total of 12.47 Gb raw data containing 77.92 M pair-end reads were obtained after processing and 6815 polymorphic SLAFs between the two parents were detected. The average sequencing depths reached 52.66-fold for the female parent and 49.35-fold for the male parent. Subsequently, these polymorphic SLAFs were used to genotype the population and further filtered based on several criteria to construct a genetic linkage map of cauliflower. Finally, 1776 high-quality SLAF markers, including 2741 SNPs, constituted the linkage map with average data integrity of 95.68%. The final map spanned a total genetic length of 890.01 cM with an average marker interval of 0.50 cM, and covered 364.9 Mb of the reference genome. The markers and genetic map developed in this study could provide an important foundation not only for comparative genomics studies within Brassica oleracea species but also for quantitative trait loci identification and molecular breeding of cauliflower. PMID:27047515

Object-Oriented Economic Power Dispatch of Electrical Power System with minimum pollution using a Genetic Algorithm

Directory of Open Access Journals (Sweden)

T. Bouktir

2005-06-01

Full Text Available This paper presents solution of optimal power flow (OPF problem of electrical power system via a genetic algorithm of real type. The objective is to minimize the total fuel cost of generation and environmental pollution caused by fossil based thermal generating units and also maintain an acceptable system performance in terms of limits on generator real and reactive power outputs, bus voltages, shunt capacitors/reactors, transformers tap-setting and power flow of transmission lines. CPU times can be reduced by decomposing the optimization constraints to active constraints that affect directly the cost function manipulated directly the GA, and passive constraints such as generator bus voltages and transformer tap setting maintained in their soft limits using a conventional constraint load flow. The algorithm was developed in an Object Oriented fashion, in the C++ programming language. This option satisfies the requirements of flexibility, extensibility, maintainability and data integrity. The economic power dispatch is applied to IEEE 30-bus model system (6-generator, 41-line and 20-load. The numerical results have demonstrate the effectiveness of the stochastic search algorithms because its can provide accurate dispatch solutions with reasonable time. Further analyses indicate that this method is effective for large-scale power systems.

Genetics in the art and art in genetics.

Science.gov (United States)

Bukvic, Nenad; Elling, John W

2015-01-15

"Healing is best accomplished when art and science are conjoined, when body and spirit are probed together", says Bernard Lown, in his book "The Lost Art of Healing". Art has long been a witness to disease either through diseases which affected artists or diseases afflicting objects of their art. In particular, artists have often portrayed genetic disorders and malformations in their work. Sometimes genetic disorders have mystical significance; other times simply have intrinsic interest. Recognizing genetic disorders is also an art form. From the very beginning of my work as a Medical Geneticist I have composed personal "algorithms" to piece together evidence of genetics syndromes and diseases from the observable signs and symptoms. In this paper we apply some 'gestalt' Genetic Syndrome Diagnostic algorithms to virtual patients found in some art masterpieces. In some the diagnosis is clear and in others the artists' depiction only supports a speculative differential diagnosis. Copyright © 2014 Elsevier B.V. All rights reserved.

Desktop Genetics.

Science.gov (United States)

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

2016-11-01

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

Genetic and Environmental Influences on Retinopathy of Prematurity

Science.gov (United States)

Ortega-Molina, J. M.; Anaya-Alaminos, R.; Uberos-Fernández, J.; Solans-Pérez de Larraya, A.; Chaves-Samaniego, M. J.; Salgado-Miranda, A.; Piñar-Molina, R.; Jerez-Calero, A.; García-Serrano, J. L.

2015-01-01

Objective. The goals were to isolate and study the genetic susceptibility to retinopathy of prematurity (ROP), as well as the gene-environment interaction established in this disease. Methods. A retrospective study (2000–2014) was performed about the heritability of retinopathy of prematurity in 257 infants who were born at a gestational age of ≤32 weeks. The ROP was studied and treated by a single pediatric ophthalmologist. A binary logistic regression analysis was completed between the presence or absence of ROP and the predictor variables. Results. Data obtained from 38 monozygotic twins, 66 dizygotic twins, and 153 of simple birth were analyzed. The clinical features of the cohorts of monozygotic and dizygotic twins were not significantly different. Genetic factors represented 72.8% of the variability in the stage of ROP, environmental factors 23.08%, and random factors 4.12%. The environmental variables representing the highest risk of ROP were the number of days of tracheal intubation (p < 0.001), postnatal weight gain (p = 0.001), and development of sepsis (p = 0.0014). Conclusion. The heritability of ROP was found to be 0.73. The environmental factors regulate and modify the expression of the genetic code. PMID:26089603

Analysis of the Multi Strategy Goal Programming for Micro-Grid Based on Dynamic ant Genetic Algorithm

Science.gov (United States)

Qiu, J. P.; Niu, D. X.

Micro-grid is one of the key technologies of the future energy supplies. Take economic planning. reliability, and environmental protection of micro grid as a basis for the analysis of multi-strategy objective programming problems for micro grid which contains wind power, solar power, and battery and micro gas turbine. Establish the mathematical model of each power generation characteristics and energy dissipation. and change micro grid planning multi-objective function under different operating strategies to a single objective model based on AHP method. Example analysis shows that in combination with dynamic ant mixed genetic algorithm can get the optimal power output of this model.

Detecting β-thalassaemia mutations from a single cell by PEP and RDB

Institute of Scientific and Technical Information of China (English)

YI Ping; LI Li; YAO Hong; ZHOU Yuan-guo; DENG Bing; CHEN Zhu-qin

2006-01-01

Objective:To evaluate the possibility of the technology involving PEP and RDB for detecting β-thalassaemia multipoint mutations from a single cell simultaneously. Methods: A set of allele specific oligonucleotide (ASO) probes used for detecting 8 familiar β-thalassaemia mutations (CD41-42, IVS- Ⅱ -654, CD17, TATA box nt-28, CD71-72, TATA box nt-29, CD26, IVS- Ⅰ -5) were immobilized on a strip of nylon membrane. The genome of a individual cell was amplified by primer extension preamplification (PEP) with the mixture of15-base random oligonucleotides. The aliquots from PEP were used to amplify the objective gene fractions of β-thalassaemia gene by nested or semi-nested PCR. The membrane was hybridized with the final amplified products and then treated with Streptavidin-HRP and color development.Results :Totally 30 lymphocytes were picked up from blood samples of 1 healthy female and 4 patients with known β-thalassaemia mutations respectively. Each single lymphocyte was lysed in the proteinase K buffer. The amplification efficacy was 94.0% and alle drop-out(ADO) rate was 8.0%. Revert dot blot (RDB) was applied to the final amplified products from the 5 participants. The results of diagnosis were the same to the expected, and their genotypes were N/N, CD17 (A→T)/N, IVS- Ⅱ -654(C→T)/CD17(A → T), CD41-42 (-CTTT)/N and TATA box nt-28 (A→G)/N, respectively. Conclusion: The technology involving PEP and RDB could detectmultiple β-thalassaemia mutations from a single cell simultaneously,and the research provides experimental evidences for the feasibility of applying PEP and DNA array technology to screening multiple genetic mutations from a single cell, and will be applied to preimplantation genetic diagnosis and non-invasive prenatal diagnosis for β-thalassaemia.

Identification of single-copy orthologous genes between Physalis and Solanum lycopersicum and analysis of genetic diversity in Physalis using molecular markers.

Directory of Open Access Journals (Sweden)

Jingli Wei

Full Text Available The genus Physalis includes a number of commercially important edible and ornamental species. Its high nutritional value and potential medicinal properties leads to the increased commercial interest in the products of this genus worldwide. However, lack of molecular markers prevents the detailed study of genetics and phylogeny in Physalis, which limits the progress of breeding. In the present study, we compared the DNA sequences between Physalis and tomato, and attempted to analyze genetic diversity in Physalis using tomato markers. Blasting 23180 DNA sequences derived from Physalis against the International Tomato Annotation Group (ITAG Release2.3 Predicted CDS (SL2.40 discovered 3356 single-copy orthologous genes between them. A total of 38 accessions from at least six species of Physalis were subjected to genetic diversity analysis using 97 tomato markers and 25 SSR markers derived from P. peruviana. Majority (73.2% of tomato markers could amplify DNA fragments from at least one accession of Physalis. Diversity in Physalis at molecular level was also detected. The average Nei's genetic distance between accessions was 0.3806 with a range of 0.2865 to 0.7091. These results indicated Physalis and tomato had similarity at both molecular marker and DNA sequence levels. Therefore, the molecular markers developed in tomato can be used in genetic study in Physalis.

Origin of new Brassica types from a single intergeneric hybrid ...

Indian Academy of Sciences (India)

Origin of new Brassica types from a single intergeneric hybrid between B. rapa and Orychophragmus ... The morphological and genetic divergence of these novel types derived from a single hybrid is probably due ... Journal of Genetics | News.

New perspectives on preimplantation genetic diagnosis and preimplantation genetic screening

Directory of Open Access Journals (Sweden)

Chun-Kai Chen

2014-06-01

Full Text Available Preimplantation genetic diagnosis is a procedure that involves the removal of one or more nuclei from oocytes (a polar body or embryos (blastomeres or trophectoderm cells in order to test for problems in genome sequence or chromosomes of the embryo prior to implantation. It provides new hope of having unaffected children, as well as avoiding the necessity of terminating an affected pregnancy for genetic parents who carry an affected gene or have balanced chromosomal status. Polymerase chain reaction-based molecular techniques are the methods used to detect gene defects with a known sequence and X-linked diseases. The indication for using this approach has expanded for couples who are prevented from having babies because they carry a serious genetic disorder to couples with conditions that are not immediately life threatening, such as cancer predisposition genes and Huntington disease. In addition, fluorescent in situ hybridization (FISH has been widely applied for the detection of chromosome abnormalities. FISH allows the evaluation of many chromosomes at the same time, up to 15 chromosome pairs in a single cell. Preimplantation genetic screening, defined as a test that screens for aneuploidy, has been most commonly used in situations of advanced maternal age, a history of recurrent miscarriage, a history of repeated implantation failure, or a severe male factor. Unfortunately, randomized controlled trials have as yet shown no benefit with respect to preimplantation genetic screening using cleavage stage biopsy, which is probably attributable to the high levels of mosaicism at early cleavage stages and the limitations of FISH. Recently, two main types of array-based technology combined with whole genome amplification have been developed for use in preimplantation genetic diagnosis; these are comparative genomic hybridization and single nucleotide polymorphism-based arrays. Both allow the analysis of all chromosomes, and the latter also allows

Review: domestic animal forensic genetics - biological evidence, genetic markers, analytical approaches and challenges.

Science.gov (United States)

Kanthaswamy, S

2015-10-01

This review highlights the importance of domestic animal genetic evidence sources, genetic testing, markers and analytical approaches as well as the challenges this field is facing in view of the de facto 'gold standard' human DNA identification. Because of the genetic similarity between humans and domestic animals, genetic analysis of domestic animal hair, saliva, urine, blood and other biological material has generated vital investigative leads that have been admitted into a variety of court proceedings, including criminal and civil litigation. Information on validated short tandem repeat, single nucleotide polymorphism and mitochondrial DNA markers and public access to genetic databases for forensic DNA analysis is becoming readily available. Although the fundamental aspects of animal forensic genetic testing may be reliable and acceptable, animal forensic testing still lacks the standardized testing protocols that human genetic profiling requires, probably because of the absence of monetary support from government agencies and the difficulty in promoting cooperation among competing laboratories. Moreover, there is a lack in consensus about how to best present the results and expert opinion to comply with court standards and bear judicial scrutiny. This has been the single most persistent challenge ever since the earliest use of domestic animal forensic genetic testing in a criminal case in the mid-1990s. Crime laboratory accreditation ensures that genetic test results have the courts' confidence. Because accreditation requires significant commitments of effort, time and resources, the vast majority of animal forensic genetic laboratories are not accredited nor are their analysts certified forensic examiners. The relevance of domestic animal forensic genetics in the criminal justice system is undeniable. However, further improvements are needed in a wide range of supporting resources, including standardized quality assurance and control protocols for sample

Genetic and Non-genetic Factors Associated WithConstipation in Cancer Patients Receiving Opioids

OpenAIRE

Laugsand, Eivor Alette; Skorpen, Frank; Kaasa, Stein; Sabatowski, Rainer; Strasser, Florian; Fayers, Peter; Klepstad, Pål

2015-01-01

Objectives: To examine whether the inter-individual variation in constipation among patients receiving opioids for cancer pain is associated with genetic or non-genetic factors. Methods: Cancer patients receiving opioids were included from 17 centers in 11 European countries. Intensity of constipation was reported by 1,568 patients on a four-point categorical scale. Non-genetic factors were included as covariates in stratified regression analyses on the association between constipation a...

Multi-Objective Optimization of Managed Aquifer Recharge.

Science.gov (United States)

Fatkhutdinov, Aybulat; Stefan, Catalin

2018-04-27

This study demonstrates the utilization of a multi-objective hybrid global/local optimization algorithm for solving managed aquifer recharge (MAR) design problems, in which the decision variables included spatial arrangement of water injection and abstraction wells and time-variant rates of pumping and injection. The objective of the optimization was to maximize the efficiency of the MAR scheme, which includes both quantitative and qualitative aspects. The case study used to demonstrate the capabilities of the proposed approach is based on a published report on designing a real MAR site with defined aquifer properties, chemical groundwater characteristics as well as quality and volumes of injected water. The demonstration problems include steady-state and transient scenarios. The steady-state scenario demonstrates optimization of spatial arrangement of multiple injection and recovery wells, whereas the transient scenario was developed with the purpose of finding optimal regimes of water injection and recovery at a single location. Both problems were defined as multi-objective problems. The scenarios were simulated by applying coupled numerical groundwater flow and solute transport models: MODFLOW-2005 and MT3D-USGS. The applied optimization method was a combination of global - the Non-Dominated Sorting Genetic Algorithm (NSGA-2), and local - the Nelder-Mead Downhill Simplex search algorithms. The analysis of the resulting Pareto optimal solutions led to the discovery of valuable patterns and dependencies between the decision variables, model properties and problem objectives. Additionally, the performance of the traditional global and the hybrid optimization schemes were compared. This article is protected by copyright. All rights reserved.

In-silico single nucleotide polymorphisms (SNP) mining of Sorghum ...

African Journals Online (AJOL)

Single nucleotide polymorphisms (SNPs) may be considered the ultimate genetic markers as they represent the finest resolution of a DNA sequence (a single nucleotide), and are generally abundant in populations with a low mutation rate. SNPs are important tools in studying complex genetic traits and genome evolution.

Genetics of osteoporosis

Energy Technology Data Exchange (ETDEWEB)

Urano, Tomohiko [Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655 (Japan); Inoue, Satoshi, E-mail: INOUE-GER@h.u-tokyo.ac.jp [Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655 (Japan); Department of Anti-Aging Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655 (Japan); Division of Gene Regulation and Signal Transduction, Research Center for Genomic Medicine, Saitama Medical University, Saitama (Japan)

2014-09-19

Highlights: • Single-nucleotide polymorphisms (SNPs) associated with osteoporosis were identified. • SNPs mapped close to or within VDR and ESR1 are associated with bone mineral density. • WNT signaling pathway plays a pivotal role in regulating bone mineral density. • Genetic studies will be useful for identification of new therapeutic targets. - Abstract: Osteoporosis is a skeletal disease characterized by low bone mineral density (BMD) and microarchitectural deterioration of bone tissue, which increases susceptibility to fractures. BMD is a complex quantitative trait with normal distribution and seems to be genetically controlled (in 50–90% of the cases), according to studies on twins and families. Over the last 20 years, candidate gene approach and genome-wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) that are associated with low BMD, osteoporosis, and osteoporotic fractures. These SNPs have been mapped close to or within genes including those encoding nuclear receptors and WNT-β-catenin signaling proteins. Understanding the genetics of osteoporosis will help identify novel candidates for diagnostic and therapeutic targets.

Integration trumps selection in object recognition

Science.gov (United States)

Saarela, Toni P.; Landy, Michael S.

2015-01-01

Summary Finding and recognizing objects is a fundamental task of vision. Objects can be defined by several “cues” (color, luminance, texture etc.), and humans can integrate sensory cues to improve detection and recognition [1–3]. Cortical mechanisms fuse information from multiple cues [4], and shape-selective neural mechanisms can display cue-invariance by responding to a given shape independent of the visual cue defining it [5–8]. Selective attention, in contrast, improves recognition by isolating a subset of the visual information [9]. Humans can select single features (red or vertical) within a perceptual dimension (color or orientation), giving faster and more accurate responses to items having the attended feature [10,11]. Attention elevates neural responses and sharpens neural tuning to the attended feature, as shown by studies in psychophysics and modeling [11,12], imaging [13–16], and single-cell and neural population recordings [17,18]. Besides single features, attention can select whole objects [19–21]. Objects are among the suggested “units” of attention because attention to a single feature of an object causes the selection of all of its features [19–21]. Here, we pit integration against attentional selection in object recognition. We find, first, that humans can integrate information near-optimally from several perceptual dimensions (color, texture, luminance) to improve recognition. They cannot, however, isolate a single dimension even when the other dimensions provide task-irrelevant, potentially conflicting information. For object recognition, it appears that there is mandatory integration of information from multiple dimensions of visual experience. The advantage afforded by this integration, however, comes at the expense of attentional selection. PMID:25802154

Integration trumps selection in object recognition.

Science.gov (United States)

Saarela, Toni P; Landy, Michael S

2015-03-30

Finding and recognizing objects is a fundamental task of vision. Objects can be defined by several "cues" (color, luminance, texture, etc.), and humans can integrate sensory cues to improve detection and recognition [1-3]. Cortical mechanisms fuse information from multiple cues [4], and shape-selective neural mechanisms can display cue invariance by responding to a given shape independent of the visual cue defining it [5-8]. Selective attention, in contrast, improves recognition by isolating a subset of the visual information [9]. Humans can select single features (red or vertical) within a perceptual dimension (color or orientation), giving faster and more accurate responses to items having the attended feature [10, 11]. Attention elevates neural responses and sharpens neural tuning to the attended feature, as shown by studies in psychophysics and modeling [11, 12], imaging [13-16], and single-cell and neural population recordings [17, 18]. Besides single features, attention can select whole objects [19-21]. Objects are among the suggested "units" of attention because attention to a single feature of an object causes the selection of all of its features [19-21]. Here, we pit integration against attentional selection in object recognition. We find, first, that humans can integrate information near optimally from several perceptual dimensions (color, texture, luminance) to improve recognition. They cannot, however, isolate a single dimension even when the other dimensions provide task-irrelevant, potentially conflicting information. For object recognition, it appears that there is mandatory integration of information from multiple dimensions of visual experience. The advantage afforded by this integration, however, comes at the expense of attentional selection. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effect of objective function on multi-objective inverse planning of radiation therapy

International Nuclear Information System (INIS)

Li Guoli; Wu Yican; Song Gang; Wang Shifang

2006-01-01

There are two kinds of objective functions in radiotherapy inverse planning: dose distribution-based and Dose-Volume Histogram (DVH)-based functions. The treatment planning in our days is still a trial and error process because the multi-objective problem is solved by transforming it into a single objective problem using a specific set of weights for each object. This work investigates the problem of objective function setting based on Pareto multi-optimization theory, and compares the effect on multi-objective inverse planning of those two kinds of objective functions including calculation time, converge speed, etc. The basis of objective function setting on inverse planning is discussed. (authors)

The Tourette International Collaborative Genetics (TIC Genetics) study, finding the genes causing Tourette syndrome : objectives and methods

NARCIS (Netherlands)

Dietrich, Andrea; Fernandez, Thomas V.; King, Robert A.; State, Matthew W.; Tischfield, Jay A.; Hoekstra, Pieter J.; Heiman, Gary A.

Tourette syndrome (TS) is a neuropsychiatric disorder characterized by recurrent motor and vocal tics, often accompanied by obsessive-compulsive disorder and/or attention-deficit/hyperactivity disorder. While the evidence for a genetic contribution is strong, its exact nature has yet to be clarified

Genetic and Non-genetic Factors Associated With Constipation in Cancer Patients Receiving Opioids

Science.gov (United States)

Laugsand, Eivor A; Skorpen, Frank; Kaasa, Stein; Sabatowski, Rainer; Strasser, Florian; Fayers, Peter; Klepstad, Pål

2015-01-01

Objectives: To examine whether the inter-individual variation in constipation among patients receiving opioids for cancer pain is associated with genetic or non-genetic factors. Methods: Cancer patients receiving opioids were included from 17 centers in 11 European countries. Intensity of constipation was reported by 1,568 patients on a four-point categorical scale. Non-genetic factors were included as covariates in stratified regression analyses on the association between constipation and 75 single-nucleotide polymorphisms (SNPs) within 15 candidate genes related to opioid- or constipation-signaling pathways (HTR3E, HTR4, HTR2A, TPH1, ADRA2A, CHRM3, TACR1, CCKAR, KIT, ARRB2, GHRL, ABCB1, COMT, OPRM1, and OPRD1). Results: The non-genetic factors significantly associated with constipation were type of laxative, mobility and place of care among patients receiving laxatives (N=806), in addition to Karnofsky performance status and presence of metastases among patients not receiving laxatives (N=762) (P<0.01). Age, gender, body mass index, cancer diagnosis, time on opioids, opioid dose, and type of opioid did not contribute to the inter-individual differences in constipation. Five SNPs, rs1800532 in TPH1, rs1799971 in OPRM1, rs4437575 in ABCB1, rs10802789 in CHRM3, and rs2020917 in COMT were associated with constipation (P<0.01). Only rs2020917 in COMT passed the Benjamini–Hochberg criterion for a 10% false discovery rate. Conclusions: Type of laxative, mobility, hospitalization, Karnofsky performance status, presence of metastases, and five SNPs within TPH1, OPRM1, ABCB1, CHRM3, and COMT may contribute to the variability in constipation among cancer patients treated with opioids. Knowledge of these factors may help to develop new therapies and to identify patients needing a more individualized approach to treatment. PMID:26087058

Genetic and Biochemical Identification of a Novel Single-Stranded DNA-Binding Complex in Haloferax volcanii.

Science.gov (United States)

Stroud, Amy; Liddell, Susan; Allers, Thorsten

2012-01-01

Single-stranded DNA (ssDNA)-binding proteins play an essential role in DNA replication and repair. They use oligonucleotide/oligosaccharide-binding (OB)-folds, a five-stranded β-sheet coiled into a closed barrel, to bind to ssDNA thereby protecting and stabilizing the DNA. In eukaryotes the ssDNA-binding protein (SSB) is known as replication protein A (RPA) and consists of three distinct subunits that function as a heterotrimer. The bacterial homolog is termed SSB and functions as a homotetramer. In the archaeon Haloferax volcanii there are three genes encoding homologs of RPA. Two of the rpa genes (rpa1 and rpa3) exist in operons with a novel gene specific to Euryarchaeota; this gene encodes a protein that we have termed RPA-associated protein (rpap). The rpap genes encode proteins belonging to COG3390 group and feature OB-folds, suggesting that they might cooperate with RPA in binding to ssDNA. Our genetic analysis showed that rpa1 and rpa3 deletion mutants have differing phenotypes; only Δrpa3 strains are hypersensitive to DNA damaging agents. Deletion of the rpa3-associated gene rpap3 led to similar levels of DNA damage sensitivity, as did deletion of the rpa3 operon, suggesting that RPA3 and RPAP3 function in the same pathway. Protein pull-downs involving recombinant hexahistidine-tagged RPAs showed that RPA3 co-purifies with RPAP3, and RPA1 co-purifies with RPAP1. This indicates that the RPAs interact only with their respective associated proteins; this was corroborated by the inability to construct rpa1 rpap3 and rpa3 rpap1 double mutants. This is the first report investigating the individual function of the archaeal COG3390 RPA-associated proteins (RPAPs). We have shown genetically and biochemically that the RPAPs interact with their respective RPAs, and have uncovered a novel single-stranded DNA-binding complex that is unique to Euryarchaeota.

PAIRS AND GROUPS OF GENETICALLY RELATED LONG-PERIOD COMETS AND PROPOSED IDENTITY OF THE MYSTERIOUS LICK OBJECT OF 1921

Energy Technology Data Exchange (ETDEWEB)

Sekanina, Zdenek [Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109 (United States); Kracht, Rainer, E-mail: Zdenek.Sekanina@jpl.nasa.gov, E-mail: R.Kracht@t-online.de [Ostlandring 53, D-25335 Elmshorn, Schleswig-Holstein (Germany)

2016-05-20

We present the history of investigation of the dynamical properties of pairs and groups of genetically related long-period comets (other than the Kreutz sungrazing system). Members of a comet pair or group move in nearly identical orbits, and their origin as fragments of a common parent comet is unquestionable. The only variable is the time of perihelion passage, which differs considerably from member to member owing primarily to an orbital-momentum increment acquired during breakup. Meter-per-second separation velocities account for gaps of years or tens of years, thanks to the orbital periods of many millennia. The physical properties of individual members may not at all be alike, as illustrated by the trio of C/1988 A1, C/1996 Q1, and C/2015 F3. We exploit orbital similarity to examine whether the enigmatic and as-yet-unidentified object discovered from the Lick Observatory near the Sun at sunset on 1921 August 7 happened to be a member of such a pair and to track down the long-period comet to which it might be genetically related. Our search shows that the Lick object, which could not be a Kreutz sungrazer, was likely a companion to comet C/1847 C1 (Hind), whose perihelion distance was ∼9 R {sub ⊙} and true orbital period was approximately 8300 yr. The gap of 74.4 yr between their perihelion times is consistent with a separation velocity of ∼1 m s{sup −1} which sets the fragments apart following the parent's breakup in a general proximity of perihelion during the previous return to the Sun in the seventh millennium BCE.

Multi-Objective Optimization of Grillages Applying the Genetic Algorithm

Directory of Open Access Journals (Sweden)

Darius Mačiūnas

2012-01-01

Full Text Available The article analyzes the optimization of grillage-type foundations seeking for the least possible reactive forces in the poles for a given number of poles and for the least possible bending moments of absolute values in the connecting beams of the grillage. Therefore, we suggest using a compromise objective function (to be minimized that consists of the maximum reactive force arising in all poles and the maximum bending moment of the absolute value in connecting beams; both components include the given weights. The variables of task design are pole positions under connecting beams. The optimization task is solved applying the algorithm containing all the initial data of the problem. Reactive forces and bending moments are calculated using an original program (finite element method is applied. This program is integrated into the optimization algorithm using the “black-box” principle. The “black-box” finite element program sends back the corresponding value of the objective function. Numerical experiments revealed the optimal quantity of points to compute bending moments. The obtained results show a certain ratio of weights in the objective function where the contribution of reactive forces and bending moments to the objective function are equivalent. This solution can serve as a pilot project for more detailed design.Article in Lithuanian

Genetic architecture of plasma adiponectin overlaps with the genetics of metabolic syndrome-related traits

NARCIS (Netherlands)

P. Henneman (Peter); Y.S. Aulchenko (Yurii); R.R. Frants (Rune); I.V. Zorkoltseva (Irina); M.C. Zillikens (Carola); M. Frölich (Marijke); B.A. Oostra (Ben); J.A.P. Willems van Dijk (Ko); P. Tikka-Kleemola (Päivi)

2010-01-01

textabstractOBJECTIVE - Adiponectin, a hormone secreted by adipose tissue, is of particular interest in metabolic syndrome, because it is inversely correlated with obesity and insulin sensitivity. However, it is not known to what extent the genetics of plasma adiponectin and the genetics of obesity

Genetic analyses of the human eye colours using a novel objective method for eye colour classification

DEFF Research Database (Denmark)

Andersen, Jeppe D.; Johansen, Peter; Harder, Stine

2013-01-01

In this study, we present a new objective method for measuring the eye colour on a continuous scale that allows researchers to associate genetic markers with different shades of eye colour. With the use of the custom designed software Digital Iris Analysis Tool (DIAT), the iris was automatically...... and TYR rs1393350) on the eye colour. We evaluated the two published prediction models for eye colour (IrisPlex [1] and Snipper[2]) and compared the predictions with the PIE-scores. We found good concordance with the prediction from individuals typed as HERC2 rs12913832 G. However, both methods had......-score ranged from −1 to 1 (brown to blue). The software eliminated the need for user based interpretation and qualitative eye colour categories. In 94% (570) of 605 analyzed eye images, the iris region was successfully extracted and a PIE-score was calculated. A very high correlation between the PIE...

The Design and Optimization of GaAs Single Solar Cells Using the Genetic Algorithm and Silvaco ATLAS

Directory of Open Access Journals (Sweden)

Kamal Attari

2017-01-01

Full Text Available Single-junction solar cells are the most available in the market and the most simple in terms of the realization and fabrication comparing to the other solar devices. However, these single-junction solar cells need more development and optimization for higher conversion efficiency. In addition to the doping densities and compromises between different layers and their best thickness value, the choice of the materials is also an important factor on improving the efficiency. In this paper, an efficient single-junction solar cell model of GaAs is presented and optimized. In the first step, an initial model was simulated and then the results were processed by an algorithm code. In this work, the proposed optimization method is a genetic search algorithm implemented in Matlab receiving ATLAS data to generate an optimum output power solar cell. Other performance parameters such as photogeneration rates, external quantum efficiency (EQE, and internal quantum efficiency (EQI are also obtained. The simulation shows that the proposed method provides significant conversion efficiency improvement of 29.7% under AM1.5G illumination. The other results were Jsc = 34.79 mA/cm2, Voc = 1 V, and fill factor (FF = 85%.

Accurate determination of genetic identity for a single cacao bean, using molecular markers with a nanofluidic system, ensures cocoa authentication.

Science.gov (United States)

Fang, Wanping; Meinhardt, Lyndel W; Mischke, Sue; Bellato, Cláudia M; Motilal, Lambert; Zhang, Dapeng

2014-01-15

Cacao (Theobroma cacao L.), the source of cocoa, is an economically important tropical crop. One problem with the premium cacao market is contamination with off-types adulterating raw premium material. Accurate determination of the genetic identity of single cacao beans is essential for ensuring cocoa authentication. Using nanofluidic single nucleotide polymorphism (SNP) genotyping with 48 SNP markers, we generated SNP fingerprints for small quantities of DNA extracted from the seed coat of single cacao beans. On the basis of the SNP profiles, we identified an assumed adulterant variety, which was unambiguously distinguished from the authentic beans by multilocus matching. Assignment tests based on both Bayesian clustering analysis and allele frequency clearly separated all 30 authentic samples from the non-authentic samples. Distance-based principle coordinate analysis further supported these results. The nanofluidic SNP protocol, together with forensic statistical tools, is sufficiently robust to establish authentication and to verify gourmet cacao varieties. This method shows significant potential for practical application.

A Single Transcriptome of a Green Toad (Bufo viridis Yields Candidate Genes for Sex Determination and -Differentiation and Non-Anonymous Population Genetic Markers.

Directory of Open Access Journals (Sweden)

Jörn F Gerchen

Full Text Available Large genome size, including immense repetitive and non-coding fractions, still present challenges for capacity, bioinformatics and thus affordability of whole genome sequencing in most amphibians. Here, we test the performance of a single transcriptome to understand whether it can provide a cost-efficient resource for species with large unknown genomes. Using RNA from six different tissues from a single Palearctic green toad (Bufo viridis specimen and Hiseq2000, we obtained 22,5 Mio reads and publish >100,000 unigene sequences. To evaluate efficacy and quality, we first use this data to identify green toad specific candidate genes, known from other vertebrates for their role in sex determination and differentiation. Of a list of 37 genes, the transcriptome yielded 32 (87%, many of which providing the first such data for this non-model anuran species. However, for many of these genes, only fragments could be retrieved. In order to allow also applications to population genetics, we further used the transcriptome for the targeted development of 21 non-anonymous microsatellites and tested them in genetic families and backcrosses. Eleven markers were specifically developed to be located on the B. viridis sex chromosomes; for eight markers we can indeed demonstrate sex-specific transmission in genetic families. Depending on phylogenetic distance, several markers, which are sex-linked in green toads, show high cross-amplification success across the anuran phylogeny, involving nine systematic anuran families. Our data support the view that single transcriptome sequencing (based on multiple tissues provides a reliable genomic resource and cost-efficient method for non-model amphibian species with large genome size and, despite limitations, should be considered as long as genome sequencing remains unaffordable for most species.

Multi-Objective Optimization of Squeeze Casting Process using Genetic Algorithm and Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Patel G.C.M.

2016-09-01

Full Text Available The near net shaped manufacturing ability of squeeze casting process requiresto set the process variable combinations at their optimal levels to obtain both aesthetic appearance and internal soundness of the cast parts. The aesthetic and internal soundness of cast parts deal with surface roughness and tensile strength those can readily put the part in service without the requirement of costly secondary manufacturing processes (like polishing, shot blasting, plating, hear treatment etc.. It is difficult to determine the levels of the process variable (that is, pressure duration, squeeze pressure, pouring temperature and die temperature combinations for extreme values of the responses (that is, surface roughness, yield strength and ultimate tensile strength due to conflicting requirements. In the present manuscript, three population based search and optimization methods, namely genetic algorithm (GA, particle swarm optimization (PSO and multi-objective particle swarm optimization based on crowding distance (MOPSO-CD methods have been used to optimize multiple outputs simultaneously. Further, validation test has been conducted for the optimal casting conditions suggested by GA, PSO and MOPSO-CD. The results showed that PSO outperformed GA with regard to computation time.

Molecular Genetic Characterization of Mutagenesis Using a Highly Sensitive Single-Stranded DNA Reporter System in Budding Yeast.

Science.gov (United States)

Chan, Kin

2018-01-01

Mutations are permanent alterations to the coding content of DNA. They are starting material for the Darwinian evolution of species by natural selection, which has yielded an amazing diversity of life on Earth. Mutations can also be the fundamental basis of serious human maladies, most notably cancers. In this chapter, I describe a highly sensitive reporter system for the molecular genetic analysis of mutagenesis, featuring controlled generation of long stretches of single-stranded DNA in budding yeast cells. This system is ~100- to ~1000-fold more susceptible to mutation than conventional double-stranded DNA reporters, and is well suited for generating large mutational datasets to investigate the properties of mutagens.

USING OF OBJECT-ORIENTED DESIGN PRINCIPLES IN ELECTRIC MACHINES DEVELOPMENT

Directory of Open Access Journals (Sweden)

N.N. Zablodskii

2016-03-01

Full Text Available Purpose. To develop the theoretical basis of electrical machines object-oriented design, mathematical models and software to improve their design synthesis, analysis and optimization. Methodology. We have applied object-oriented design theory in electric machines optimal design and mathematical modelling of electromagnetic transients and electromagnetic field distribution. We have correlated the simulated results with the experimental data obtained by means of the double-stator screw dryer with an external solid rotor, brushless turbo-generator exciter and induction motor with squirrel cage rotor. Results. We have developed object-oriented design methodology, transient mathematical modelling and electromagnetic field equations templates for cylindrical electrical machines, improved and remade Cartesian product and genetic optimization algorithms. This allows to develop electrical machines classifications models, included not only structure development but also parallel synthesis of mathematical models and design software, to improve electric machines efficiency and technical performance. Originality. For the first time, we have applied a new way of design and modelling of electrical machines, which is based on the basic concepts of the object-oriented analysis. For the first time is suggested to use a single class template for structural and system organization of electrical machines, invariant to their specific variety. Practical value. We have manufactured screw dryer for coil dust drying and mixing based on the performed object-oriented theory. We have developed object-oriented software for design and optimization of induction motor with squirrel cage rotor of AIR series and brushless turbo-generator exciter. The experimental studies have confirmed the adequacy of the developed object-oriented design methodology.

Single Cell Analysis of Dystrophin and SRY Gene by Using Whole Genome Amplification

Institute of Scientific and Technical Information of China (English)

徐晨明; 金帆; 黄荷凤; 陶冶; 叶英辉

2001-01-01

Objective To develop a reliable and sensitive method for detection of sex and multiloci of Duchenne muscular dystrophy (DMD) gene in single cell Materials & methods Whole genome of single cell were amplified by using 15-base random primers (primer extension preamplification, PEP), then a small aliquot of PEP product were analyzed by using locus-specific nest PCR amplification. The procedure was evaluated by detection dystrophin exons 8, 17, 19, 44, 45, 48 and human testis-determining gene (SRY)in single lymphocytes from known sources and single blastomeres from the couples with no family history of DMD.Results The amplification efficiency rate of six dystrophin exons from single lymphocytes and single blastomeres were 97. 2% (175/180) and 100% (60/60) respectively.Results of SRY showed that 100% (15/15) amplification in single male-derived lymphocytes and 0% (0/15) amplification in single female-derived lymphocytes. Conclusion The technique of single cell PEP-nest PCR for dystrophin exons 8, 17,19, 44, 45, 48 and SRY is highly specifc. PEP-nest PCR is suitable for Preimplantation genetic diagnosis (PGD) of DMD at single cell level.

Optimization of a novel carbon dioxide cogeneration system using artificial neural network and multi-objective genetic algorithm

International Nuclear Information System (INIS)

Jamali, Arash; Ahmadi, Pouria; Mohd Jaafar, Mohammad Nazri

2014-01-01

In this research study, a combined cycle based on the Brayton power cycle and the ejector expansion refrigeration cycle is proposed. The proposed cycle can provide heating, cooling and power simultaneously. One of the benefits of such a system is to be driven by low temperature heat sources and using CO 2 as working fluid. In order to enhance the understanding of the current work, a comprehensive parametric study and exergy analysis are conducted to determine the effects of the thermodynamic parameters on the system performance and the exergy destruction rate in the components. The suggested cycle can save the energy around 46% in comparison with a system producing cooling, power and hot water separately. On the other hand, to optimize a system to meet the load requirement, the surface area of the heat exchangers is determined and optimized. The results of this section can be used when a compact system is also an objective function. Along with a comprehensive parametric study and exergy analysis, a complete optimization study is carried out using a multi-objective evolutionary based genetic algorithm considering two different objective functions, heat exchangers size (to be minimized) and exergy efficiency (to be maximized). The Pareto front of the optimization problem and a correlation between exergy efficiency and total heat exchangers length is presented in order to predict the trend of optimized points. The suggested system can be a promising combined system for buildings and outland regions. - Highlights: •Energy and exergy analysis of a novel CHP system are reported. •A comprehensive parametric study is conducted to enhance the understanding of the system performance. •Apply a multi-objective optimization technique based on a code developed in the Matlab software program using an evolutionary algorithm

Genetic diagnosis of Duchenne and Becker muscular dystrophy using next-generation sequencing technology: comprehensive mutational search in a single platform.

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Lim, Byung Chan; Lee, Seungbok; Shin, Jong-Yeon; Kim, Jong-Il; Hwang, Hee; Kim, Ki Joong; Hwang, Yong Seung; Seo, Jeong-Sun; Chae, Jong Hee

2011-11-01

Duchenne muscular dystrophy or Becker muscular dystrophy might be a suitable candidate disease for application of next-generation sequencing in the genetic diagnosis because the complex mutational spectrum and the large size of the dystrophin gene require two or more analytical methods and have a high cost. The authors tested whether large deletions/duplications or small mutations, such as point mutations or short insertions/deletions of the dystrophin gene, could be predicted accurately in a single platform using next-generation sequencing technology. A custom solution-based target enrichment kit was designed to capture whole genomic regions of the dystrophin gene and other muscular-dystrophy-related genes. A multiplexing strategy, wherein four differently bar-coded samples were captured and sequenced together in a single lane of the Illumina Genome Analyser, was applied. The study subjects were 25 16 with deficient dystrophin expression without a large deletion/duplication and 9 with a known large deletion/duplication. Nearly 100% of the exonic region of the dystrophin gene was covered by at least eight reads with a mean read depth of 107. Pathogenic small mutations were identified in 15 of the 16 patients without a large deletion/duplication. Using these 16 patients as the standard, the authors' method accurately predicted the deleted or duplicated exons in the 9 patients with known mutations. Inclusion of non-coding regions and paired-end sequence analysis enabled accurate identification by increasing the read depth and providing information about the breakpoint junction. The current method has an advantage for the genetic diagnosis of Duchenne muscular dystrophy and Becker muscular dystrophy wherein a comprehensive mutational search may be feasible using a single platform.

Comparing multi-objective non-evolutionary NLPQL and evolutionary genetic algorithm optimization of a DI diesel engine: DoE estimation and creating surrogate model

International Nuclear Information System (INIS)

Navid, Ali; Khalilarya, Shahram; Taghavifar, Hadi

2016-01-01

Highlights: • NLPQL algorithm with Latin hypercube and multi-objective GA were applied on engine. • NLPQL converge to the best solution at RunID41, MOGA introduces at RunID84. • Deeper, more encircled design gives the lowest NOx, greater radius and deeper bowl the highest IMEP. • The maximum IMEP and minimum ISFC obtained with NLPQL, the lowest NOx with MOGA. - Abstract: This study is concerned with the application of two major kinds of optimization algorithms on the baseline diesel engine in the class of evolutionary and non-evolutionary algorithms. The multi-objective genetic algorithm and non-linear programming by quadratic Lagrangian (NLPQL) method have completely different functions in optimizing and finding the global optimal design. The design variables are injection angle, half spray cone angle, inner distance of the bowl wall, and the bowl radius, while the objectives include NOx emission, spray droplet diameter, indicated mean effective pressure (IMEP), and indicated specific fuel consumption (ISFC). The restrictions were set on the objectives to distinguish between feasible designs and infeasible designs to sort those cases that cannot fulfill the demands of diesel engine designers and emission control measures. It is found that a design with deeper bowl and more encircled shape (higher swirl motion) is more suitable for NO_x emission control, whereas designs with a bigger bowl radius, and closer inner wall distance of the bowl (Di) may lead to higher engine efficiency indices. Moreover, it was revealed that the NLPQL could rapidly search for the best design at Run ID 41 compared to genetic algorithm, which is able to find the global optima at last runs (ID 84). Both techniques introduce almost the same geometrical shape of the combustion chamber with a negligible contrast in the injection system.

CCLab--a multi-objective genetic algorithm based combinatorial library design software and an application for histone deacetylase inhibitor design.

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Fang, Guanghua; Xue, Mengzhu; Su, Mingbo; Hu, Dingyu; Li, Yanlian; Xiong, Bing; Ma, Lanping; Meng, Tao; Chen, Yuelei; Li, Jingya; Li, Jia; Shen, Jingkang

2012-07-15

The introduction of the multi-objective optimization has dramatically changed the virtual combinatorial library design, which can consider many objectives simultaneously, such as synthesis cost and drug-likeness, thus may increase positive rates of biological active compounds. Here we described a software called CCLab (Combinatorial Chemistry Laboratory) for combinatorial library design based on the multi-objective genetic algorithm. Tests of the convergence ability and the ratio to re-take the building blocks in the reference library were conducted to assess the software in silico, and then it was applied to a real case of designing a 5×6 HDAC inhibitor library. Sixteen compounds in the resulted library were synthesized, and the histone deactetylase (HDAC) enzymatic assays proved that 14 compounds showed inhibitory ratios more than 50% against tested 3 HDAC enzymes at concentration of 20 μg/mL, with IC(50) values of 3 compounds comparable to SAHA. These results demonstrated that the CCLab software could enhance the hit rates of the designed library and would be beneficial for medicinal chemists to design focused library in drug development (the software can be downloaded at: http://202.127.30.184:8080/drugdesign.html). Copyright © 2012 Elsevier Ltd. All rights reserved.

A hybrid non-dominated sorting genetic algorithm and its application on multi-objective optimal design of nuclear power plant

International Nuclear Information System (INIS)

Chen, Lei; Yan, Changqi; Liao, Yi; Song, Feifei; Jia, Zhen

2017-01-01

Highlights: • The optimization ability of NSGA-II is improved. • The design targets can be obvious optimized through optimization methodology. • Multi-objective optimization is implanted into the design of nuclear power plant. - Abstract: The design of nuclear component can be optimized by seeking out the best combination of article operational and structural parameters. Through multi-objective optimization, the optimized scheme can not only meets the design requirements, but also satisfies the safety regulations. In this work, a hybrid non-dominated sorting genetic algorithm is proposed, and its performance is verified by comparing it with its prototype and immune memory clone constraint multi-objective algorithm through four test-functions; the designs of the steam generator and the primary loop of Qinshan I nuclear power plant are optimized by the proposed algorithm. The results show that the algorithm outperforms the other two through overall evaluation; the reactor inlet temperature is an important parameter which influences the distribution of the Pareto optimal front; through optimization, the weight of the steam generator can be reduced by 16.5%, and the primary flow-rate can be reduced by 17.0%, the weight of the primary loop can be reduced by 11.4%, and the volume can be reduced by 9.8%.

Visualizing presynaptic calcium dynamics and vesicle fusion with a single genetically encoded reporter at individual synapses

Directory of Open Access Journals (Sweden)

Rachel E Jackson

2016-07-01

Full Text Available Synaptic transmission depends on the influx of calcium into the presynaptic compartment, which drives neurotransmitter release. Genetically encoded reporters are widely used tools to understand these processes, particularly pHluorin-based reporters that report vesicle exocytosis and endocytosis through pH dependent changes in fluorescence, and genetically encoded calcium indicators (GECIs that exhibit changes in fluorescence upon binding to calcium. The recent expansion of the color palette of available indicators has made it possible to image multiple probes simultaneously within a cell. We have constructed a single molecule reporter capable of concurrent imaging of both presynaptic calcium influx and exocytosis, by fusion of sypHy, the vesicle associated protein synaptophysin containing a GFP-based pHluorin sensor, with the red-shifted GECI R-GECO1. Due to the fixed stoichiometry of the two probes, the ratio of the two responses can also be measured, providing an all optical correlate of the calcium dependence of release. Here, we have characterized stimulus-evoked sypHy-RGECO responses of hippocampal synapses in vitro, exploring the effects of different stimulus strengths and frequencies as well as variations in external calcium concentrations. By combining live sypHy-RGECO imaging with post-hoc fixation and immunofluorescence, we have also investigated correlations between structural and functional properties of synapses.

Genetics of aggression.

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Anholt, Robert R H; Mackay, Trudy F C

2012-01-01

Aggression mediates competition for food, mating partners, and habitats and, among social animals, establishes stable dominance hierarchies. In humans, abnormal aggression is a hallmark of neuropsychiatric disorders and can be elicited by environmental factors acting on an underlying genetic susceptibility. Identifying the genetic architecture that predisposes to aggressive behavior in people is challenging because of difficulties in quantifying the phenotype, genetic heterogeneity, and uncontrolled environmental conditions. Studies on mice have identified single-gene mutations that result in hyperaggression, contingent on genetic background. These studies can be complemented by systems genetics approaches in Drosophila melanogaster, in which mutational analyses together with genome-wide transcript analyses, artificial selection studies, and genome-wide analysis of epistasis have revealed that a large segment of the genome contributes to the manifestation of aggressive behavior with widespread epistatic interactions. Comparative genomic analyses based on the principle of evolutionary conservation are needed to enable a complete dissection of the neurogenetic underpinnings of this universal fitness trait.

A genetic assessment of the English bulldog.

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Pedersen, Niels C; Pooch, Ashley S; Liu, Hongwei

2016-01-01

This study examines genetic diversity among 102 registered English Bulldogs used for breeding based on maternal and paternal haplotypes, allele frequencies in 33 highly polymorphic short tandem repeat (STR) loci on 25 chromosomes, STR-linked dog leukocyte antigen (DLA) class I and II haplotypes, and the number and size of genome-wide runs of homozygosity (ROH) determined from high density SNP arrays. The objective was to assess whether the breed retains enough genetic diversity to correct the genotypic and phenotypic abnormalities associated with poor health, to allow for the elimination of deleterious recessive mutations, or to make further phenotypic changes in body structure or coat. An additional 37 English bulldogs presented to the UC Davis Veterinary Clinical Services for health problems were also genetically compared with the 102 registered dogs based on the perception that sickly English bulldogs are products of commercial breeders or puppy-mills and genetically different and inferior. Four paternal haplotypes, with one occurring in 93 % of dogs, were identified using six Y-short tandem repeat (STR) markers. Three major and two minor matrilines were identified by mitochondrial D-loop sequencing. Heterozygosity was determined from allele frequencies at genomic loci; the average number of alleles per locus was 6.45, with only 2.7 accounting for a majority of the diversity. However, observed and expected heterozygosity values were nearly identical, indicating that the population as a whole was in Hardy-Weinberg equilibrium (HWE). However, internal relatedness (IR) and adjusted IR (IRVD) values demonstrated that a number of individuals were the offspring of parents that were either more inbred or outbred than the population as a whole. The diversity of DLA class I and II haplotypes was low, with only 11 identified DLA class I and nine class II haplotypes. Forty one percent of the breed shared a single DLA class I and 62 % a single class II haplotype. Nineteen

Phenotype variations affect genetic association studies of degenerative disc disease: conclusions of analysis of genetic association of 58 single nucleotide polymorphisms with highly specific phenotypes for disc degeneration in 332 subjects.

Science.gov (United States)

Rajasekaran, S; Kanna, Rishi Mugesh; Senthil, Natesan; Raveendran, Muthuraja; Cheung, Kenneth M C; Chan, Danny; Subramaniam, Sakthikanal; Shetty, Ajoy Prasad

2013-10-01

Although the influence of genetics on the process of disc degeneration is well recognized, in recently published studies, there is a wide variation in the race and selection criteria for such study populations. More importantly, the radiographic features of disc degeneration that are selected to represent the disc degeneration phenotype are variable in these studies. The study presented here evaluates the association between single nucleotide polymorphisms (SNPs) of candidate genes and three distinct radiographic features that can be defined as the degenerative disc disease (DDD) phenotype. The study objectives were to examine the allelic diversity of 58 SNPs related to 35 candidate genes related to lumbar DDD, to evaluate the association in a hitherto unevaluated ethnic Indian population that represents more than one-sixth of the world population, and to analyze how genetic associations can vary in the same study subjects with the choice of phenotype. A cross-sectional, case-control study of an ethnic Indian population was carried out. Fifty-eight SNPs in 35 potential candidate genes were evaluated in 342 subjects and the associations were analyzed against three highly specific markers for DDD, namely disc degeneration by Pfirrmann grading, end-plate damage evaluated by total end-plate damage score, and annular tears evaluated by disc herniations and hyperintense zones. Genotyping of cases and controls was performed on a genome-wide SNP array to identify potential associated disease loci. The results from the genome-wide SNP array were then used to facilitate SNP selection and genotype validation was conducted using Sequenom-based genotyping. Eleven of the 58 SNPs provided evidence of association with one of the phenotypes. For annular tears, rs1042631 SNP of AGC1 and rs467691 SNP of ADAMTS5 were highly significantly associated (p<.01) and SNPs in NGFB, IL1B, IL18RAP, and MMP10 were also significantly associated (p<.05). The rs4076018 SNP of NGFB was highly

New perspectives on preimplantation genetic diagnosis and preimplantation genetic screening.

Science.gov (United States)

Chen, Chun-Kai; Yu, Hsing-Tse; Soong, Yung-Kuei; Lee, Chyi-Long

2014-06-01

Preimplantation genetic diagnosis is a procedure that involves the removal of one or more nuclei from oocytes (a polar body) or embryos (blastomeres or trophectoderm cells) in order to test for problems in genome sequence or chromosomes of the embryo prior to implantation. It provides new hope of having unaffected children, as well as avoiding the necessity of terminating an affected pregnancy for genetic parents who carry an affected gene or have balanced chromosomal status. Polymerase chain reaction-based molecular techniques are the methods used to detect gene defects with a known sequence and X-linked diseases. The indication for using this approach has expanded for couples who are prevented from having babies because they carry a serious genetic disorder to couples with conditions that are not immediately life threatening, such as cancer predisposition genes and Huntington disease. In addition, fluorescent in situ hybridization (FISH) has been widely applied for the detection of chromosome abnormalities. FISH allows the evaluation of many chromosomes at the same time, up to 15 chromosome pairs in a single cell. Preimplantation genetic screening, defined as a test that screens for aneuploidy, has been most commonly used in situations of advanced maternal age, a history of recurrent miscarriage, a history of repeated implantation failure, or a severe male factor. Unfortunately, randomized controlled trials have as yet shown no benefit with respect to preimplantation genetic screening using cleavage stage biopsy, which is probably attributable to the high levels of mosaicism at early cleavage stages and the limitations of FISH. Recently, two main types of array-based technology combined with whole genome amplification have been developed for use in preimplantation genetic diagnosis; these are comparative genomic hybridization and single nucleotide polymorphism-based arrays. Both allow the analysis of all chromosomes, and the latter also allows the haplotype of

Brief communication genotyping of Burkholderia pseudomallei revealed high genetic variability among isolates from a single population group.

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Zueter, Abdelrahman Mohammad; Rahman, Zaidah Abdul; Yean, Chan Yean; Harun, Azian

2015-01-01

Burkholderia pseudomallei is a soil dwelling Gram-negative bacteria predominates in Southeast Asia zone and the tropical part of Australia. Genetic diversity has been explored among various populations and environments worldwide. To date, little data is available on MLST profiling of clinical B. pseudomallei isolates in peninsular Malaysia. In this brief report, thirteen culture positive B. pseudomallei cases collected from a single population of Terengganu state in the Western Peninsular Malaysia and were confirmed by In-house TTS1-PCR. Isolates were subjected for multi-locus sequence typing (MLST) to explore their genotypic diversity and to investigate for possible clonal clustering of a certain sequence type. Patient's clinical information was examined to investigate for clinical correlation among the different genotypes. In spite of small sample set, MLST results indicated predictive results; considerable genotypic diversity, predominance and novelty among B. pseudomallei collected over a single geographically-located population in Malaysia. Massive genotypic heterogeneity was observed; 8 different sequence types with predominance of sequence type 54 and discovery of two novel sequence types. However, no clear pathogenomic or organ tropism clonal relationships were predicted.

Genetic diversity of the critically endangered Verbascum davidoffii Murb. (Scrophulariaceae and implications for conservation

Directory of Open Access Journals (Sweden)

Petrova, G.

2016-12-01

Full Text Available Verbascum davidoffii Murb. (Scrophulariaceae, one of the rarest plant species in Bulgarian flora, is a local endemic, protected by the National Biodiversity Act, included in the Red List of vascular plants, as well as in the Red Data Book of Bulgaria with conservation status “Critically Endangered”. Its distribution is limited due to anthropogenic pressure, specific ecological requirements and low reproductive capability. In this study, we aimed to measure the genetic diversity level in the unique single world population of Verbascum davidoffii located in Pirin National Park, Bulgaria. We found high genetic diversity in the excitant population of the species. The present study indicates that the primary objective in conservation of Verbascum davidoffii is to preserve as much as possible of its evolutionary potential

Genetic consequences of trumpeter swan (Cygnus buccinator) reintroductions

Science.gov (United States)

Ransler, F.A.; Quinn, T.W.; Oyler-McCance, S.J.

2011-01-01

Relocation programs are often initiated to restore threatened species to previously occupied portions of their range. A primary challenge of restoration efforts is to translocate individuals in a way that prevents loss of genetic diversity and decreases differentiation relative to source populations-a challenge that becomes increasingly difficult when remnant populations of the species are already genetically depauperate. Trumpeter swans were previously extirpated in the entire eastern half of their range. Physical translocations of birds over the last 70 years have restored the species to portions of its historical range. Despite the long history of management, there has been little monitoring of the genetic outcomes of these restoration attempts. We assessed the consequences of this reintroduction program by comparing patterns of genetic variation at 17 microsatellite loci across four restoration flocks (three wild-released, one captive) and their source populations. We found that a wild-released population established from a single source displayed a trend toward reduced genetic diversity relative to and significant genetic differentiation from its source population, though small founder population effects may also explain this pattern. Wild-released flocks restored from multiple populations maintained source levels of genetic variation and lacked significant differentiation from at least one of their sources. Further, the flock originating from a single source revealed significantly lower levels of genetic variation than those established from multiple sources. The distribution of genetic variation in the captive flock was similar to its source. While the case of trumpeter swans provides evidence that restorations from multiple versus single source populations may better preserve natural levels of genetic diversity, more studies are needed to understand the general applicability of this management strategy. ?? 2010 Springer Science+Business Media B.V. (outside

One-single physical exercise session after object recognition learning promotes memory persistence through hippocampal noradrenergic mechanisms.

Science.gov (United States)

da Silva de Vargas, Liane; Neves, Ben-Hur Souto das; Roehrs, Rafael; Izquierdo, Iván; Mello-Carpes, Pâmela

2017-06-30

Previously we showed the involvement of the hippocampal noradrenergic system in the consolidation and persistence of object recognition (OR) memory. Here we show that one-single physical exercise session performed immediately after learning promotes OR memory persistence and increases norepinephrine levels in the hippocampus. Additionally, effects of exercise on memory are avoided by an intra-hippocampal beta-adrenergic antagonist infusion. Taken together, these results suggest that exercise effects on memory can be related to noradrenergic mechanisms and acute physical exercise can be a non-pharmacological intervention to assist memory consolidation and persistence, with few or no side effects. Copyright © 2017 Elsevier B.V. All rights reserved.

Genetic basis of a cognitive complexity metric.

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Narelle K Hansell

Full Text Available Relational complexity (RC is a metric reflecting capacity limitation in relational processing. It plays a crucial role in higher cognitive processes and is an endophenotype for several disorders. However, the genetic underpinnings of complex relational processing have not been investigated. Using the classical twin model, we estimated the heritability of RC and genetic overlap with intelligence (IQ, reasoning, and working memory in a twin and sibling sample aged 15-29 years (N = 787. Further, in an exploratory search for genetic loci contributing to RC, we examined associated genetic markers and genes in our Discovery sample and selected loci for replication in four independent samples (ALSPAC, LBC1936, NTR, NCNG, followed by meta-analysis (N>6500 at the single marker level. Twin modelling showed RC is highly heritable (67%, has considerable genetic overlap with IQ (59%, and is a major component of genetic covariation between reasoning and working memory (72%. At the molecular level, we found preliminary support for four single-marker loci (one in the gene DGKB, and at a gene-based level for the NPS gene, having influence on cognition. These results indicate that genetic sources influencing relational processing are a key component of the genetic architecture of broader cognitive abilities. Further, they suggest a genetic cascade, whereby genetic factors influencing capacity limitation in relational processing have a flow-on effect to more complex cognitive traits, including reasoning and working memory, and ultimately, IQ.

Real Objects Can Impede Conditional Reasoning but Augmented Objects Do Not.

Science.gov (United States)

Sato, Yuri; Sugimoto, Yutaro; Ueda, Kazuhiro

2018-03-01

In this study, Knauff and Johnson-Laird's (2002) visual impedance hypothesis (i.e., mental representations with irrelevant visual detail can impede reasoning) is applied to the domain of external representations and diagrammatic reasoning. We show that the use of real objects and augmented real (AR) objects can control human interpretation and reasoning about conditionals. As participants made inferences (e.g., an invalid one from "if P then Q" to "P"), they also moved objects corresponding to premises. Participants who moved real objects made more invalid inferences than those who moved AR objects and those who did not manipulate objects (there was no significant difference between the last two groups). Our results showed that real objects impeded conditional reasoning, but AR objects did not. These findings are explained by the fact that real objects may over-specify a single state that exists, while AR objects suggest multiple possibilities. Copyright © 2017 Cognitive Science Society, Inc.

Bi-objective branch-and-cut algorithms

DEFF Research Database (Denmark)

Gadegaard, Sune Lauth; Ehrgott, Matthias; Nielsen, Lars Relund

Most real-world optimization problems are of a multi-objective nature, involving objectives which are conflicting and incomparable. Solving a multi-objective optimization problem requires a method which can generate the set of rational compromises between the objectives. In this paper, we propose...... are strengthened by cutting planes. In addition, we suggest an extension of the branching strategy "Pareto branching''. Extensive computational results obtained for the bi-objective single source capacitated facility location problem prove the effectiveness of the algorithms....... and compares it to an upper bound set. The implicit bound set based algorithm, on the other hand, fathoms branching nodes by generating a single point on the lower bound set for each local nadir point. We outline several approaches for fathoming branching nodes and we propose an updating scheme for the lower...

Genomic single-nucleotide polymorphisms confirm that Gunnison and Greater sage-grouse are genetically well differentiated and that the Bi-State population is distinct

Science.gov (United States)

Oyler-McCance, Sara J.; Cornman, Robert S.; Jones, Kenneth L.; Fike, Jennifer

2015-01-01

Sage-grouse are iconic, declining inhabitants of sagebrush habitats in western North America, and their management depends on an understanding of genetic variation across the landscape. Two distinct species of sage-grouse have been recognized, Greater (Centrocercus urophasianus) and Gunnison sage-grouse (C. minimus), based on morphology, behavior, and variation at neutral genetic markers. A parapatric group of Greater Sage-Grouse along the border of California and Nevada ("Bi-State") is also genetically distinct at the same neutral genetic markers, yet not different in behavior or morphology. Because delineating taxonomic boundaries and defining conservation units is often difficult in recently diverged taxa and can be further complicated by highly skewed mating systems, we took advantage of new genomic methods that improve our ability to characterize genetic variation at a much finer resolution. We identified thousands of single-nucleotide polymorphisms (SNPs) among Gunnison, Greater, and Bi-State sage-grouse and used them to comprehensively examine levels of genetic diversity and differentiation among these groups. The pairwise multilocus fixation index (FST) was high (0.49) between Gunnison and Greater sage-grouse, and both principal coordinates analysis and model-based clustering grouped samples unequivocally by species. Standing genetic variation was lower within the Gunnison Sage-Grouse. The Bi-State population was also significantly differentiated from Greater Sage-Grouse, albeit more weakly (FST = 0.09), and genetic clustering results were consistent with reduced gene flow with Greater Sage-Grouse. No comparable genetic divisions were found within the Greater Sage-Grouse sample, which spanned the southern half of the range. Thus, we provide much stronger genetic evidence supporting the recognition of Gunnison Sage-Grouse as a distinct species with low genetic diversity. Further, our work confirms that the Bi-State population is differentiated from other

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.

Development and validation of concurrent preimplantation genetic diagnosis for single gene disorders and comprehensive chromosomal aneuploidy screening without whole genome amplification.

Science.gov (United States)

Zimmerman, Rebekah S; Jalas, Chaim; Tao, Xin; Fedick, Anastasia M; Kim, Julia G; Pepe, Russell J; Northrop, Lesley E; Scott, Richard T; Treff, Nathan R

2016-02-01

To develop a novel and robust protocol for multifactorial preimplantation genetic testing of trophectoderm biopsies using quantitative polymerase chain reaction (qPCR). Prospective and blinded. Not applicable. Couples indicated for preimplantation genetic diagnosis (PGD). None. Allele dropout (ADO) and failed amplification rate, genotyping consistency, chromosome screening success rate, and clinical outcomes of qPCR-based screening. The ADO frequency on a single cell from a fibroblast cell line was 1.64% (18/1,096). When two or more cells were tested, the ADO frequency dropped to 0.02% (1/4,426). The rate of amplification failure was 1.38% (55/4,000) overall, with 2.5% (20/800) for single cells and 1.09% (35/3,200) for samples that had two or more cells. Among 152 embryos tested in 17 cases by qPCR-based PGD and CCS, 100% were successfully given a diagnosis, with 0% ADO or amplification failure. Genotyping consistency with reference laboratory results was >99%. Another 304 embryos from 43 cases were included in the clinical application of qPCR-based PGD and CCS, for which 99.7% (303/304) of the embryos were given a definitive diagnosis, with only 0.3% (1/304) having an inconclusive result owing to recombination. In patients receiving a transfer with follow-up, the pregnancy rate was 82% (27/33). This study demonstrates that the use of qPCR for PGD testing delivers consistent and more reliable results than existing methods and that single gene disorder PGD can be run concurrently with CCS without the need for additional embryo biopsy or whole genome amplification. Copyright © 2016 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Genetic improvement of vegetables

International Nuclear Information System (INIS)

Jaramillo Vasquez, J.G.

2001-01-01

Some genetic bases of the improvement of vegetables are given. The objectives of the genetic improvement and the fundamental stages of this process are done. The sources of genetic variation are indicated and they are related the reproduction systems of the main horticultural species. It is analyzed the concept of genetic inheritance like base to determine the procedures more appropriate of improvement. The approaches are discussed, has more than enough phenotypic value, genetic action and genotypic variance; Equally the heredability concepts and value of improvement. The conventional methods of improvement are described, like they are: the introduction of species or varieties, the selection, the pure line, the pedigree method, the selection for families, the recurrent selection, the selection for unique seed, the haploids method, the selection for heterosis and the synthetic varieties

An Integrated Account of Generalization across Objects and Features

Science.gov (United States)

Kemp, Charles; Shafto, Patrick; Tenenbaum, Joshua B.

2012-01-01

Humans routinely make inductive generalizations about unobserved features of objects. Previous accounts of inductive reasoning often focus on inferences about a single object or feature: accounts of causal reasoning often focus on a single object with one or more unobserved features, and accounts of property induction often focus on a single…

Coronary artery disease-associated genetic variants and biomarkers of inflammation

DEFF Research Database (Denmark)

Christiansen, Morten Krogh; Larsen, Sanne Bøjet; Nyegaard, Mette

2017-01-01

score was calculated to assess the combined risk associated with all the genetic variants. A multiple linear regression model was used to assess associations between the genetic risk score, single SNPs, and the five inflammatory biomarkers. RESULTS:The minor allele (G) (CAD risk allele) of rs2075650......INTRODUCTION:Genetic constitution and inflammation both contribute to development of coronary artery disease (CAD). Several CAD-associated single-nucleotide polymorphisms (SNPs) have recently been identified, but their functions are largely unknown. We investigated the associations between CAD...

Discovery and mapping of a new expressed sequence tag-single nucleotide polymorphism and simple sequence repeat panel for large-scale genetic studies and breeding of Theobroma cacao L.

Science.gov (United States)

Allegre, Mathilde; Argout, Xavier; Boccara, Michel; Fouet, Olivier; Roguet, Yolande; Bérard, Aurélie; Thévenin, Jean Marc; Chauveau, Aurélie; Rivallan, Ronan; Clement, Didier; Courtois, Brigitte; Gramacho, Karina; Boland-Augé, Anne; Tahi, Mathias; Umaharan, Pathmanathan; Brunel, Dominique; Lanaud, Claire

2012-01-01

Theobroma cacao is an economically important tree of several tropical countries. Its genetic improvement is essential to provide protection against major diseases and improve chocolate quality. We discovered and mapped new expressed sequence tag-single nucleotide polymorphism (EST-SNP) and simple sequence repeat (SSR) markers and constructed a high-density genetic map. By screening 149 650 ESTs, 5246 SNPs were detected in silico, of which 1536 corresponded to genes with a putative function, while 851 had a clear polymorphic pattern across a collection of genetic resources. In addition, 409 new SSR markers were detected on the Criollo genome. Lastly, 681 new EST-SNPs and 163 new SSRs were added to the pre-existing 418 co-dominant markers to construct a large consensus genetic map. This high-density map and the set of new genetic markers identified in this study are a milestone in cocoa genomics and for marker-assisted breeding. The data are available at http://tropgenedb.cirad.fr. PMID:22210604

Ultrasensitive Single Fluorescence-Labeled Probe-Mediated Single Universal Primer-Multiplex-Droplet Digital Polymerase Chain Reaction for High-Throughput Genetically Modified Organism Screening.

Science.gov (United States)

Niu, Chenqi; Xu, Yuancong; Zhang, Chao; Zhu, Pengyu; Huang, Kunlun; Luo, Yunbo; Xu, Wentao

2018-05-01

As genetically modified (GM) technology develops and genetically modified organisms (GMOs) become more available, GMOs face increasing regulations and pressure to adhere to strict labeling guidelines. A singleplex detection method cannot perform the high-throughput analysis necessary for optimal GMO detection. Combining the advantages of multiplex detection and droplet digital polymerase chain reaction (ddPCR), a single universal primer-multiplex-ddPCR (SUP-M-ddPCR) strategy was proposed for accurate broad-spectrum screening and quantification. The SUP increases efficiency of the primers in PCR and plays an important role in establishing a high-throughput, multiplex detection method. Emerging ddPCR technology has been used for accurate quantification of nucleic acid molecules without a standard curve. Using maize as a reference point, four heterologous sequences ( 35S, NOS, NPTII, and PAT) were selected to evaluate the feasibility and applicability of this strategy. Surprisingly, these four genes cover more than 93% of the transgenic maize lines and serve as preliminary screening sequences. All screening probes were labeled with FAM fluorescence, which allows the signals from the samples with GMO content and those without to be easily differentiated. This fiveplex screening method is a new development in GMO screening. Utilizing an optimal amplification assay, the specificity, limit of detection (LOD), and limit of quantitation (LOQ) were validated. The LOD and LOQ of this GMO screening method were 0.1% and 0.01%, respectively, with a relative standard deviation (RSD) < 25%. This method could serve as an important tool for the detection of GM maize from different processed, commercially available products. Further, this screening method could be applied to other fields that require reliable and sensitive detection of DNA targets.

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

Science.gov (United States)

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.

CRY2 genetic variants associate with dysthymia.

Directory of Open Access Journals (Sweden)

Leena Kovanen

Full Text Available People with mood disorders often have disruptions in their circadian rhythms. Recent molecular genetics has linked circadian clock genes to mood disorders. Our objective was to study two core circadian clock genes, CRY1 and CRY2 as well as TTC1 that interacts with CRY2, in relation to depressive and anxiety disorders. Of these three genes, 48 single-nucleotide polymorphisms (SNPs whose selection was based on the linkage disequilibrium and potential functionality were genotyped in 5910 individuals from a nationwide population-based sample. The diagnoses of major depressive disorder, dysthymia and anxiety disorders were assessed with a structured interview (M-CIDI. In addition, the participants filled in self-report questionnaires on depressive and anxiety symptoms. Logistic and linear regression models were used to analyze the associations of the SNPs with the phenotypes. Four CRY2 genetic variants (rs10838524, rs7121611, rs7945565, rs1401419 associated significantly with dysthymia (false discovery rate q<0.05. This finding together with earlier CRY2 associations with winter depression and with bipolar type 1 disorder supports the view that CRY2 gene has a role in mood disorders.

Ethical and legal issues arising from complex genetic disorders. DOE final report

Energy Technology Data Exchange (ETDEWEB)

Andrews, Lori

2002-10-09

The project analyzed the challenges raised by complex genetic disorders in genetic counselling, for clinical practice, for public health, for quality assurance, and for protection against discrimination. The research found that, in some settings, solutions created in the context of single gene disorders are more difficult to apply to complex disorders. In other settings, the single gene solutions actually backfired and created additional problems when applied to complex genetic disorders. The literature of five common, complex genetic disorders--Alzheimer's, asthma, coronary heart disease, diabetes, and psychiatric illnesses--was evaluated in depth.

Effect of inclusion or non-inclusion of short lactations and cow and/or dam genetic group on genetic evaluation of Girolando dairy cattle.

Science.gov (United States)

Canaza-Cayo, A W; Silva, M V G B; Cobuci, J A; Martins, M F; Lopes, P S

2016-04-04

The objective of this study was to evaluate the effects of inclusion or non-inclusion of short lactations and cow (CGG) and/or dam (DGG) genetic group on the genetic evaluation of 305-day milk yield (MY305), age at first calving (AFC), and first calving interval (FCI) of Girolando cows. Covariance components were estimated by the restricted maximum likelihood method in an animal model of single trait analyses. The heritability estimates for MY305, AFC, and FCI ranged from 0.23 to 0.29, 0.40 to 0.44, and 0.13 to 0.14, respectively, when short lactations were not included, and from 0.23 to 0.28, 0.39 to 0.43, and 0.13 to 0.14, respectively, when short lactations were included. The inclusion of short lactations caused little variation in the variance components and heritability estimates of traits, but their non-inclusion resulted in the re-ranking of animals. Models with CGG or DGG fixed effects had higher heritability estimates for all traits compared with models that consider these two effects simultaneously. We recommend using the model with fixed effects of CGG and inclusion of short lactations for the genetic evaluation of Girolando cattle.

[Genetics and epigenetics in autism].

Science.gov (United States)

Nakayama, Atsuo; Masaki, Shiego; Aoki, Eiko

2006-11-01

Autism is a behaviorally defined syndrome characterized by impaired social interaction and communication, and restricted, stereotyped interests and behaviors. Several lines of evidence support the contention that genetic factors are a large component to autism etiology. However, in spite of vigorous genetic studies, no single causative or susceptibility gene common in autism has been identified. Thus multiple susceptibility genes in interaction are considered to account for the disorder. Furthermore, environmental risk factors can accelerate the autism development of. Recent advances in understanding the epigenetic regulation may shed light on the interaction among multiple genetic factors and environmental factors.

Genetic influences on schizophrenia and subcortical brain volumes

DEFF Research Database (Denmark)

Franke, Barbara; Stein, Jason L; Ripke, Stephan

2016-01-01

and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between...... genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk...

Assessment of the genetic diversity in five generations of a ...

African Journals Online (AJOL)

Genetic variation among and within five generations of an inbred commercial captive line of Litopenaeus vannamei and genetic distance among them were evaluated by random amplified polymorphic DNA (RAPD), using descriptive and genetic similarity analyses for dominant markers at single- and multi-populational level ...

Genetic effects and reparation of single-stranded DNA breaks in Arabidopsis thaliana populations growing in the vicinity of the Chernobyl Nuclear Power Station

International Nuclear Information System (INIS)

Abramov, V.I.; Sergeeva, S.A.; Ptitsyna, S.N.; Semov, A.B.; Shevchenko, V.A.

1992-01-01

The genetic effects and efficiency of repair of single-stranded DNA breaks in natural populations of Arabidopsis growing within a thirty-kilometer zone of the Chernobyl Nuclear Power Station were studied. A direct relationship was found between the level of radioactive contamination and the frequency of embryonal lethal mutations in the Arabidopsis populations studied. A decrease in the efficiency of reparation of single-stranded DNA breaks was found in Arabidopsis plants growing in the contaminated sites. The level of efficiency of DNA reparation was dependent on the duration for which the Arabidopsis population had been growing in the contaminated sites and on the degree of radioactive contamination of the sites. 9 refs., 4 tabs

Object permanence tests on gibbons (Hylobatidae).

Science.gov (United States)

Fedor, Anna; Skollár, Gabriella; Szerencsy, Nóra; Ujhelyi, Mária

2008-11-01

Ten gibbons of various species (Symphalangus syndactylus, Hylobates lar, Nomascus gabriellae, and Nomascus leucogenys) were tested on object permanence tasks. Three identical wooden boxes, presented in a linear line, were used to hide pieces of food. The authors conducted single visible, single invisible, double invisible, and control displacements, in both random and nonrandom order. During invisible displacements, the experimenter hid the object in her hand before putting it into a box. The performance of gibbons was better than expected by chance in all the tests, except for the randomly ordered double displacement. However, individual analysis of performance showed great variability across subjects, and only 1 gibbon is assumed to have solved single visible and single invisible displacements without recourse to a strategy that the control test eliminated. (PsycINFO Database Record (c) 2008 APA, all rights reserved).

Imaging-Genetics Applications in Child Psychiatry

Science.gov (United States)

Pine, Daniel S.; Ernst, Monique; Leibenluft, Ellen

2010-01-01

Objective: To place imaging-genetics research in the context of child psychiatry. Method: A conceptual overview is provided, followed by discussion of specific research examples. Results: Imaging-genetics research is described linking brain function to two specific genes, for the serotonin-reuptake-transporter protein and a monoamine oxidase…

Optimal design approach for heating irregular-shaped objects in three-dimensional radiant furnaces using a hybrid genetic algorithm-artificial neural network method

Science.gov (United States)

Darvishvand, Leila; Kamkari, Babak; Kowsary, Farshad

2018-03-01

In this article, a new hybrid method based on the combination of the genetic algorithm (GA) and artificial neural network (ANN) is developed to optimize the design of three-dimensional (3-D) radiant furnaces. A 3-D irregular shape design body (DB) heated inside a 3-D radiant furnace is considered as a case study. The uniform thermal conditions on the DB surfaces are obtained by minimizing an objective function. An ANN is developed to predict the objective function value which is trained through the data produced by applying the Monte Carlo method. The trained ANN is used in conjunction with the GA to find the optimal design variables. The results show that the computational time using the GA-ANN approach is significantly less than that of the conventional method. It is concluded that the integration of the ANN with GA is an efficient technique for optimization of the radiant furnaces.

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

Science.gov (United States)

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

2017-07-01

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

To the question the unity of composition of fluids of heterogeneous geological objects.

Science.gov (United States)

Galant, Yuri

2017-04-01

Creation of Unit Theory Oil Generation based on a number of the provisions, one of which is the unity of the hydrocarbon composition in various geological objects. Studies conducted in various geological conditions and tectonic - magmatic environment. In studying the hydrocarbon composition of various geological objects, untraditional for petroleum geology (igneous rocks, metamorphic rocks, mineral deposits, etc.) progressively manifested that hydrocarbons are also distributed and have the following features. Studies have shown: 1. The composition of the hydrocarbon components presented by, light hydrocarbons, heavy hydrocarbons up to including hexane, normal forms, isoforms, saturated and unsaturated hydrocarbons. 2. Hydrocarbon composition and the ratio of methane to heavy hydrocarbons corresponds to the composition of gases gas fields. 3. The composition and the ratio of hydrocarbons do not depend on genetic types of heterogeneous geological objects. 4. Gas saturation meets the prevailing structure of rocks - pores or fractures. The foregoing allows us to speak of a single source of generating and delivering hydrocarbons in the Earth's Crust, regardless of the geological situation. I.e. the presence of hydrocarbons in the Earth's Crust is UNITED! 5. From a practical point of view - virtually unconventional for hydrocarbons rock can serve as unconventional hydrocarbon resources.

Preimplantation genetic diagnosis

DEFF Research Database (Denmark)

Bay, Bjorn; Ingerslev, Hans Jakob; Lemmen, Josephine Gabriela

2016-01-01

OBJECTIVE: To study whether women conceiving after preimplantation genetic diagnosis (PGD) and their children have greater risks of adverse pregnancy and birth outcomes compared with children conceived spontaneously or after IVF with or without intracytoplasmic sperm injection (ICSI). DESIGN...

Compositional mining of multiple object API protocols through state abstraction.

Science.gov (United States)

Dai, Ziying; Mao, Xiaoguang; Lei, Yan; Qi, Yuhua; Wang, Rui; Gu, Bin

2013-01-01

API protocols specify correct sequences of method invocations. Despite their usefulness, API protocols are often unavailable in practice because writing them is cumbersome and error prone. Multiple object API protocols are more expressive than single object API protocols. However, the huge number of objects of typical object-oriented programs poses a major challenge to the automatic mining of multiple object API protocols: besides maintaining scalability, it is important to capture various object interactions. Current approaches utilize various heuristics to focus on small sets of methods. In this paper, we present a general, scalable, multiple object API protocols mining approach that can capture all object interactions. Our approach uses abstract field values to label object states during the mining process. We first mine single object typestates as finite state automata whose transitions are annotated with states of interacting objects before and after the execution of the corresponding method and then construct multiple object API protocols by composing these annotated single object typestates. We implement our approach for Java and evaluate it through a series of experiments.

Pitfalls in genetic testing

DEFF Research Database (Denmark)

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

2016-01-01

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

50 CFR 660.410 - Conservation objectives.

Science.gov (United States)

2010-10-01

... objective: except that the 35,000 natural spawner floor and the de minimis fishing provisions for Klamath... low natural spawner abundance, including the risk of Klamath Basin substocks dropping below crucial genetic thresholds; (ii) A series of low spawner abundance in recent years; (iii) The status of co-mingled...

Journal of Genetics | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Journals; Journal of Genetics. CHU-ZHAO LEI. Articles written in Journal of Genetics. Volume 89 Issue 2 August 2010 pp 233-236 Research Note. Two novel single nucleotide polymorphisms (SNPs) and 4-bp deletion mutation of RBP4 gene in Chinese cattle · Mou Wang Xinsheng Lai Hui Yu Juqiang Wang ...

From tomography to FWI with a single objective function

KAUST Repository

Alkhalifah, Tariq Ali; Choi, Yun Seok

2013-01-01

Reflections in our seismic data induce serious nonlinear behavior in the objective function of full waveform inversion (FWI). Thus, without a good initial velocity model, that can produce the reflections within a cycle of the frequency used

Object Recognition via Information-Theoretic Measures/Metrics

National Research Council Canada - National Science Library

Repperger, Daniel W; Pinkus, Alan R; Skipper, Julie A; Schrider, Christian D

2006-01-01

.... In aerial military images, objects with different orientation can be reasonably approximated by a single identification signature consisting of the average histogram of the object under rotations...

Using genetic algorithms for calibrating simplified models of nuclear reactor dynamics

International Nuclear Information System (INIS)

Marseguerra, Marzio; Zio, Enrico; Canetta, Raffaele

2004-01-01

In this paper the use of genetic algorithms for the estimation of the effective parameters of a model of nuclear reactor dynamics is investigated. The calibration of the effective parameters is achieved by best fitting the model responses of the quantities of interest (e.g., reactor power, average fuel and coolant temperatures) to the actual evolution profiles, here simulated by the Quandry based reactor kinetics (Quark) code available from the Nuclear Energy Agency. Alternative schemes of single- and multi-objective optimization are investigated. The efficiency of convergence of the algorithm with respect to the different effective parameters to be calibrated is studied with reference to the physical relationships involved

Using genetic algorithms for calibrating simplified models of nuclear reactor dynamics

Energy Technology Data Exchange (ETDEWEB)

Marseguerra, Marzio E-mail: marzio.marseguerra@polimi.it; Zio, Enrico E-mail: enrico.zio@polimi.it; Canetta, Raffaele

2004-07-01

In this paper the use of genetic algorithms for the estimation of the effective parameters of a model of nuclear reactor dynamics is investigated. The calibration of the effective parameters is achieved by best fitting the model responses of the quantities of interest (e.g., reactor power, average fuel and coolant temperatures) to the actual evolution profiles, here simulated by the Quandry based reactor kinetics (Quark) code available from the Nuclear Energy Agency. Alternative schemes of single- and multi-objective optimization are investigated. The efficiency of convergence of the algorithm with respect to the different effective parameters to be calibrated is studied with reference to the physical relationships involved.

Some aspects of the genetic consequences of the Chernobyl disaster

International Nuclear Information System (INIS)

Shevchenko, V.A.

1989-01-01

This paper reports on a study of the genetic effects of ionizing radiations resulting from the Chernobyl disaster. It involves application of the laboratory radiosensitive test-objects for the biological dosimetry of the environment; evaluation of primary radiation-genetic effects resulting from the ionizing irradiation of plant and animal populations within the 30-km vicinity and outside this zone; and a study of distant genetic consequences of ionizing radiation exposure (in a number of generations) on the environmental objects

Prediction of peripheral neuropathy in multiple myeloma patients receiving bortezomib and thalidomide: a genetic study based on a single nucleotide polymorphism array.

Science.gov (United States)

García-Sanz, Ramón; Corchete, Luis Antonio; Alcoceba, Miguel; Chillon, María Carmen; Jiménez, Cristina; Prieto, Isabel; García-Álvarez, María; Puig, Noemi; Rapado, Immaculada; Barrio, Santiago; Oriol, Albert; Blanchard, María Jesús; de la Rubia, Javier; Martínez, Rafael; Lahuerta, Juan José; González Díaz, Marcos; Mateos, María Victoria; San Miguel, Jesús Fernando; Martínez-López, Joaquín; Sarasquete, María Eugenia

2017-12-01

Bortezomib- and thalidomide-based therapies have significantly contributed to improved survival of multiple myeloma (MM) patients. However, treatment-induced peripheral neuropathy (TiPN) is a common adverse event associated with them. Risk factors for TiPN in MM patients include advanced age, prior neuropathy, and other drugs, but there are conflicting results about the role of genetics in predicting the risk of TiPN. Thus, we carried out a genome-wide association study based on more than 300 000 exome single nucleotide polymorphisms in 172 MM patients receiving therapy involving bortezomib and thalidomide. We compared patients developing and not developing TiPN under similar treatment conditions (GEM05MAS65, NCT00443235). The highest-ranking single nucleotide polymorphism was rs45443101, located in the PLCG2 gene, but no significant differences were found after multiple comparison correction (adjusted P = .1708). Prediction analyses, cytoband enrichment, and pathway analyses were also performed, but none yielded any significant findings. A copy number approach was also explored, but this gave no significant results either. In summary, our study did not find a consistent genetic component associated with TiPN under bortezomib and thalidomide therapies that could be used for prediction, which makes clinical judgment essential in the practical management of MM treatment. Copyright © 2016 John Wiley & Sons, Ltd.

Genetic variants and multiple myeloma risk

DEFF Research Database (Denmark)

Martino, Alessandro; Campa, Daniele; Jurczyszyn, Artur

2014-01-01

BACKGROUND: Genetic background plays a role in multiple myeloma susceptibility. Several single-nucleotide polymorphisms (SNP) associated with genetic susceptibility to multiple myeloma were identified in the last years, but only a few of them were validated in independent studies. METHODS...... with multiple myeloma risk (P value range, 0.055-0.981), possibly with the exception of the SNP rs2227667 (SERPINE1) in women. CONCLUSIONS: We can exclude that the selected polymorphisms are major multiple myeloma risk factors. IMPACT: Independent validation studies are crucial to identify true genetic risk...

National genetic improvement programmes in the United States beef ...

African Journals Online (AJOL)

cattle industry is accepting, in fact, demanding estimates of genetic values on yearling bulls. Single and multiple analy ... ordinary event occurred with the formation of the Beef ... assumed genetic trend was non-existent or relatively unimportant ...

Effective multi-objective optimization of Stirling engine systems

International Nuclear Information System (INIS)

Punnathanam, Varun; Kotecha, Prakash

2016-01-01

Highlights: • Multi-objective optimization of three recent Stirling engine models. • Use of efficient crossover and mutation operators for real coded Genetic Algorithm. • Demonstrated supremacy of the strategy over the conventionally used algorithm. • Improvements of up to 29% in comparison to literature results. - Abstract: In this article we demonstrate the supremacy of the Non-dominated Sorting Genetic Algorithm-II with Simulated Binary Crossover and Polynomial Mutation operators for the multi-objective optimization of Stirling engine systems by providing three examples, viz., (i) finite time thermodynamic model, (ii) Stirling engine thermal model with associated irreversibility and (iii) polytropic finite speed based thermodynamics. The finite time thermodynamic model involves seven decision variables and consists of three objectives: output power, thermal efficiency and rate of entropy generation. In comparison to literature, it was observed that the used strategy provides a better Pareto front and leads to improvements of up to 29%. The performance is also evaluated on a Stirling engine thermal model which considers the associated irreversibility of the cycle and consists of three objectives involving eleven decision variables. The supremacy of the suggested strategy is also demonstrated on the experimentally validated polytropic finite speed thermodynamics based Stirling engine model for optimization involving two objectives and ten decision variables.

Advances in single chain technology.

Science.gov (United States)

Gonzalez-Burgos, Marina; Latorre-Sanchez, Alejandro; Pomposo, José A

2015-10-07

The recent ability to manipulate and visualize single atoms at atomic level has given rise to modern bottom-up nanotechnology. Similar exquisite degree of control at the individual polymeric chain level for producing functional soft nanoentities is expected to become a reality in the next few years through the full development of so-called "single chain technology". Ultra-small unimolecular soft nano-objects endowed with useful, autonomous and smart functions are the expected, long-term valuable output of single chain technology. This review covers the recent advances in single chain technology for the construction of soft nano-objects via chain compaction, with an emphasis in dynamic, letter-shaped and compositionally unsymmetrical single rings, complex multi-ring systems, single chain nanoparticles, tadpoles, dumbbells and hairpins, as well as the potential end-use applications of individual soft nano-objects endowed with useful functions in catalysis, sensing, drug delivery and other uses.

Genetics for the ophthalmologist

Directory of Open Access Journals (Sweden)

Karthikeyan A Sadagopan

2012-01-01

Full Text Available The eye has played a major role in human genomics including gene therapy. It is the fourth most common organ system after integument (skin, hair and nails, nervous system, and musculoskeletal system to be involved in genetic disorders. The eye is involved in single gene disorders and those caused by multifactorial etiology. Retinoblastoma was the first human cancer gene to be cloned. Leber hereditary optic neuropathy was the first mitochondrial disorder described. X-Linked red-green color deficiency was the first X-linked disorder described. The eye, unlike any other body organ, allows directly visualization of genetic phenomena such as skewed X-inactivation in the fundus of a female carrier of ocular albinism. Basic concepts of genetics and their application to clinical ophthalmological practice are important not only in making a precise diagnosis and appropriate referral, but also in management and genetic counseling.

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 ...

Investigation of Genetic Variants Associated with Alzheimer Disease in Parkinson Disease Cognition.

Science.gov (United States)

Barrett, Matthew J; Koeppel, Alexander F; Flanigan, Joseph L; Turner, Stephen D; Worrall, Bradford B

2016-01-01

Meta-analysis of genome-wide association studies have implicated multiple single nucleotide polymorphisms (SNPs) and associated genes with Alzheimer disease. The role of these SNPs in cognitive impairment in Parkinson disease (PD) remains incompletely evaluated. The objective of this study was to test alleles associated with risk of Alzheimer disease for association with cognitive impairment in Parkinson disease (PD). Two datasets with PD subjects accessed through the NIH database of Genotypes and Phenotypes contained both single nucleotide polymorphism (SNP) arrays and mini-mental state exam (MMSE) scores. Genetic data underwent rigorous quality control and we selected SNPs for genes associated with AD other than APOE. We constructed logistic regression and ordinal regression models, adjusted for sex, age at MMSE, and duration of PD, to assess the association between selected SNPs and MMSE score. In one dataset, PICALM rs3851179 was associated with cognitive impairment (MMSE  70 years old (OR = 2.3; adjusted p-value = 0.017; n = 250) but not in PD subjects ≤ 70 years old. Our finding suggests that PICALM rs3851179 could contribute to cognitive impairment in older patients with PD. It is important that future studies consider the interaction of age and genetic risk factors in the development of cognitive impairment in PD.

Genetic diversity of Coccidioides posadasii from Brazil.

Science.gov (United States)

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

2013-05-01

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

Mapping genetic factors controlling potato - cyst nematode interactions

NARCIS (Netherlands)

Rouppe van der Voort, J.N.A.M.

1998-01-01

The thesis describes strategies for genetic mapping of the genomes of the potato cyst nematode and potato. Mapping in cyst nematodes was achieved by AFLP genotyping of single cysts and subsequent segregation analysis in a family of sibling populations. The genetic map of Globodera