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Sample records for based gene-gene interactions

  1. Multiobjective differential evolution-based multifactor dimensionality reduction for detecting gene-gene interactions.

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    Yang, Cheng-Hong; Chuang, Li-Yeh; Lin, Yu-Da

    2017-10-09

    Epistasis within disease-related genes (gene-gene interactions) was determined through contingency table measures based on multifactor dimensionality reduction (MDR) using single-nucleotide polymorphisms (SNPs). Most MDR-based methods use the single contingency table measure to detect gene-gene interactions; however, some gene-gene interactions may require identification through multiple contingency table measures. In this study, a multiobjective differential evolution method (called MODEMDR) was proposed to merge the various contingency table measures based on MDR to detect significant gene-gene interactions. Two contingency table measures, namely the correct classification rate and normalized mutual information, were selected to design the fitness functions in MODEMDR. The characteristics of multiobjective optimization enable MODEMDR to use multiple measures to efficiently and synchronously detect significant gene-gene interactions within a reasonable time frame. Epistatic models with and without marginal effects under various parameter settings (heritability and minor allele frequencies) were used to assess existing methods by comparing the detection success rates of gene-gene interactions. The results of the simulation datasets show that MODEMDR is superior to existing methods. Moreover, a large dataset obtained from the Wellcome Trust Case Control Consortium was used to assess MODEMDR. MODEMDR exhibited efficiency in identifying significant gene-gene interactions in genome-wide association studies.

  2. IGENT: efficient entropy based algorithm for genome-wide gene-gene interaction analysis.

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    Kwon, Min-Seok; Park, Mira; Park, Taesung

    2014-01-01

    With the development of high-throughput genotyping and sequencing technology, there are growing evidences of association with genetic variants and complex traits. In spite of thousands of genetic variants discovered, such genetic markers have been shown to explain only a very small proportion of the underlying genetic variance of complex traits. Gene-gene interaction (GGI) analysis is expected to unveil a large portion of unexplained heritability of complex traits. In this work, we propose IGENT, Information theory-based GEnome-wide gene-gene iNTeraction method. IGENT is an efficient algorithm for identifying genome-wide gene-gene interactions (GGI) and gene-environment interaction (GEI). For detecting significant GGIs in genome-wide scale, it is important to reduce computational burden significantly. Our method uses information gain (IG) and evaluates its significance without resampling. Through our simulation studies, the power of the IGENT is shown to be better than or equivalent to that of that of BOOST. The proposed method successfully detected GGI for bipolar disorder in the Wellcome Trust Case Control Consortium (WTCCC) and age-related macular degeneration (AMD). The proposed method is implemented by C++ and available on Windows, Linux and MacOSX.

  3. [Detecting gene-gene/environment interactions by model-based multifactor dimensionality reduction].

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    Fan, Wei; Shen, Chao; Guo, Zhirong

    2015-11-01

    This paper introduces a method called model-based multifactor dimensionality reduction (MB-MDR), which was firstly proposed by Calle et al., and can be applied for detecting gene-gene or gene-environment interactions in genetic studies. The basic principle and characteristics of MB-MDR as well as the operation in R program are briefly summarized. Besides, the detailed procedure of MB-MDR is illustrated by using example. Compared with classical MDR, MB-MDR has similar principle, which merges multi-locus genotypes into a one-dimensional construct and can be used in the study with small sample size. However, there is some difference between MB-MDR and classical MDR. First, it has higher statistical power than MDR and other MDR in the presence of different noises due to the different way the genotype cells merged. Second, compared with MDR, it can deal with all binary and quantitative traits, adjust marginal effects of factors and confounders. MBMDR could be a useful method in the analyses of gene-gene/environment interactions.

  4. Log-linear model-based multifactor dimensionality reduction method to detect gene gene interactions.

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    Lee, Seung Yeoun; Chung, Yujin; Elston, Robert C; Kim, Youngchul; Park, Taesung

    2007-10-01

    The identification and characterization of susceptibility genes that influence the risk of common and complex diseases remains a statistical and computational challenge in genetic association studies. This is partly because the effect of any single genetic variant for a common and complex disease may be dependent on other genetic variants (gene-gene interaction) and environmental factors (gene-environment interaction). To address this problem, the multifactor dimensionality reduction (MDR) method has been proposed by Ritchie et al. to detect gene-gene interactions or gene-environment interactions. The MDR method identifies polymorphism combinations associated with the common and complex multifactorial diseases by collapsing high-dimensional genetic factors into a single dimension. That is, the MDR method classifies the combination of multilocus genotypes into high-risk and low-risk groups based on a comparison of the ratios of the numbers of cases and controls. When a high-order interaction model is considered with multi-dimensional factors, however, there may be many sparse or empty cells in the contingency tables. The MDR method cannot classify an empty cell as high risk or low risk and leaves it as undetermined. In this article, we propose the log-linear model-based multifactor dimensionality reduction (LM MDR) method to improve the MDR in classifying sparse or empty cells. The LM MDR method estimates frequencies for empty cells from a parsimonious log-linear model so that they can be assigned to high-and low-risk groups. In addition, LM MDR includes MDR as a special case when the saturated log-linear model is fitted. Simulation studies show that the LM MDR method has greater power and smaller error rates than the MDR method. The LM MDR method is also compared with the MDR method using as an example sporadic Alzheimer's disease.

  5. A faster pedigree-based generalized multifactor dimensionality reduction method for detecting gene-gene interactions.

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    Chen, Guo-Bo; Zhu, Jun; Lou, Xiang-Yang

    2011-01-01

    We proposed a faster pedigree-based generalized multifactor dimensionality reduction algorithm, called PedG-MDR II (PII), to detect gene-gene interactions underlying complex traits. Inherited from our previous framework of PedGMDR (PI), PII can handle both dichotomous and continuous traits in pedigree-based designs and allows for covariate adjustment. Compared with PI, this faster version can theoretically halve the computing burden and memory requirement. To evaluate the performance of PII, we performed comprehensive simulations across a wide variety of experimental scenarios, in which we considered two study designs, discordant sib pairs and mixed families of varying size, and, for each study design, we considered five common factors that may potentially affect statistical power: minor allele frequency, missing rate of parental genotypes, covariate effect, gene-gene interaction, and scheme to adjust phenotypic outcomes. Simulations showed that PII gave well controlled type I error rates against population admixture. Under a total of 4,096 scenarios simulated, PII, in general, had a higher average power than PI for both dichotomous and continuous traits, and the advantage was more pronounced for continuous traits. PII also appeared to be less sensitive than PI to changes in the other four factors than the magnitude of genetic effects considered in this study. Applied to the Mid-South Tobacco Family study, PII detected a significant interaction with a p value of 5.4 × 10(-5) between two taster receptor genes, TAS2R16 and TAS2R38, responsible for nicotine dependence. In conclusion, PII is a faster supplementary version of our previous PI for detecting multifactor interactions.

  6. A novel fuzzy set based multifactor dimensionality reduction method for detecting gene-gene interaction.

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    Jung, Hye-Young; Leem, Sangseob; Lee, Sungyoung; Park, Taesung

    2016-12-01

    Gene-gene interaction (GGI) is one of the most popular approaches for finding the missing heritability of common complex traits in genetic association studies. The multifactor dimensionality reduction (MDR) method has been widely studied for detecting GGIs. In order to identify the best interaction model associated with disease susceptibility, MDR compares all possible genotype combinations in terms of their predictability of disease status from a simple binary high(H) and low(L) risk classification. However, this simple binary classification does not reflect the uncertainty of H/L classification. We regard classifying H/L as equivalent to defining the degree of membership of two risk groups H/L. By adopting the fuzzy set theory, we propose Fuzzy MDR which takes into account the uncertainty of H/L classification. Fuzzy MDR allows the possibility of partial membership of H/L through a membership function which transforms the degree of uncertainty into a [0,1] scale. The best genotype combinations can be selected which maximizes a new fuzzy set based accuracy measure. Two simulation studies are conducted to compare the power of the proposed Fuzzy MDR with that of MDR. Our results show that Fuzzy MDR has higher power than MDR. We illustrate the proposed Fuzzy MDR by analysing bipolar disorder (BD) trait of the WTCCC dataset to detect GGI associated with BD. We propose a novel Fuzzy MDR method to detect gene-gene interaction by taking into account the uncertainly of H/L classification and show that it has higher power than MDR. Fuzzy MDR can be easily extended to handle continuous phenotypes as well. The program written in R for the proposed Fuzzy MDR is available at https://statgen.snu.ac.kr/software/FuzzyMDR. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. A novel evolution-based method for detecting gene-gene interactions.

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    Shaoqi Rao

    Full Text Available BACKGROUND: The rapid advance in large-scale SNP-chip technologies offers us great opportunities in elucidating the genetic basis of complex diseases. Methods for large-scale interactions analysis have been under development from several sources. Due to several difficult issues (e.g., sparseness of data in high dimensions and low replication or validation rate, development of fast, powerful and robust methods for detecting various forms of gene-gene interactions continues to be a challenging task. METHODOLOGY/PRINCIPAL FINDINGS: In this article, we have developed an evolution-based method to search for genome-wide epistasis in a case-control design. From an evolutionary perspective, we view that human diseases originate from ancient mutations and consider that the underlying genetic variants play a role in differentiating human population into the healthy and the diseased. Based on this concept, traditional evolutionary measure, fixation index (Fst for two unlinked loci, which measures the genetic distance between populations, should be able to reveal the responsible genetic interplays for disease traits. To validate our proposal, we first investigated the theoretical distribution of Fst by using extensive simulations. Then, we explored its power for detecting gene-gene interactions via SNP markers, and compared it with the conventional Pearson Chi-square test, mutual information based test and linkage disequilibrium based test under several disease models. The proposed evolution-based method outperformed these compared methods in dominant and additive models, no matter what the disease allele frequencies were. However, its performance was relatively poor in a recessive model. Finally, we applied the proposed evolution-based method to analysis of a published dataset. Our results showed that the P value of the Fst -based statistic is smaller than those obtained by the LD-based statistic or Poisson regression models. CONCLUSIONS/SIGNIFICANCE: With

  8. SVM-based generalized multifactor dimensionality reduction approaches for detecting gene-gene interactions in family studies.

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    Fang, Yao-Hwei; Chiu, Yen-Feng

    2012-02-01

    Gene-gene interaction plays an important role in the etiology of complex diseases, which may exist without a genetic main effect. Most current statistical approaches, however, focus on assessing an interaction effect in the presence of the gene's main effects. It would be very helpful to develop methods that can detect not only the gene's main effects but also gene-gene interaction effects regardless of the existence of the gene's main effects while adjusting for confounding factors. In addition, when a disease variant is rare or when the sample size is quite limited, the statistical asymptotic properties are not applicable; therefore, approaches based on a reasonable and applicable computational framework would be practical and frequently applied. In this study, we have developed an extended support vector machine (SVM) method and an SVM-based pedigree-based generalized multifactor dimensionality reduction (PGMDR) method to study interactions in the presence or absence of main effects of genes with an adjustment for covariates using limited samples of families. A new test statistic is proposed for classifying the affected and the unaffected in the SVM-based PGMDR approach to improve performance in detecting gene-gene interactions. Simulation studies under various scenarios have been performed to compare the performances of the proposed and the original methods. The proposed and original approaches have been applied to a real data example for illustration and comparison. Both the simulation and real data studies show that the proposed SVM and SVM-based PGMDR methods have great prediction accuracies, consistencies, and power in detecting gene-gene interactions. © 2012 Wiley Periodicals, Inc.

  9. A unified model based multifactor dimensionality reduction framework for detecting gene-gene interactions.

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    Yu, Wenbao; Lee, Seungyeoun; Park, Taesung

    2016-09-01

    Gene-gene interaction (GGI) is one of the most popular approaches for finding and explaining the missing heritability of common complex traits in genome-wide association studies. The multifactor dimensionality reduction (MDR) method has been widely studied for detecting GGI effects. However, there are several disadvantages of the existing MDR-based approaches, such as the lack of an efficient way of evaluating the significance of multi-locus models and the high computational burden due to intensive permutation. Furthermore, the MDR method does not distinguish marginal effects from pure interaction effects. We propose a two-step unified model based MDR approach (UM-MDR), in which, the significance of a multi-locus model, even a high-order model, can be easily obtained through a regression framework with a semi-parametric correction procedure for controlling Type I error rates. In comparison to the conventional permutation approach, the proposed semi-parametric correction procedure avoids heavy computation in order to achieve the significance of a multi-locus model. The proposed UM-MDR approach is flexible in the sense that it is able to incorporate different types of traits and evaluate significances of the existing MDR extensions. The simulation studies and the analysis of a real example are provided to demonstrate the utility of the proposed method. UM-MDR can achieve at least the same power as MDR for most scenarios, and it outperforms MDR especially when there are some single nucleotide polymorphisms that only have marginal effects, which masks the detection of causal epistasis for the existing MDR approaches. UM-MDR provides a very good supplement of existing MDR method due to its efficiency in achieving significance for every multi-locus model, its power and its flexibility of handling different types of traits. A R package "umMDR" and other source codes are freely available at http://statgen.snu.ac.kr/software/umMDR/ CONTACT: tspark

  10. Hypothesis-based analysis of gene-gene interactions and risk of myocardial infarction.

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    Gavin Lucas

    Full Text Available The genetic loci that have been found by genome-wide association studies to modulate risk of coronary heart disease explain only a fraction of its total variance, and gene-gene interactions have been proposed as a potential source of the remaining heritability. Given the potentially large testing burden, we sought to enrich our search space with real interactions by analyzing variants that may be more likely to interact on the basis of two distinct hypotheses: a biological hypothesis, under which MI risk is modulated by interactions between variants that are known to be relevant for its risk factors; and a statistical hypothesis, under which interacting variants individually show weak marginal association with MI. In a discovery sample of 2,967 cases of early-onset myocardial infarction (MI and 3,075 controls from the MIGen study, we performed pair-wise SNP interaction testing using a logistic regression framework. Despite having reasonable power to detect interaction effects of plausible magnitudes, we observed no statistically significant evidence of interaction under these hypotheses, and no clear consistency between the top results in our discovery sample and those in a large validation sample of 1,766 cases of coronary heart disease and 2,938 controls from the Wellcome Trust Case-Control Consortium. Our results do not support the existence of strong interaction effects as a common risk factor for MI. Within the scope of the hypotheses we have explored, this study places a modest upper limit on the magnitude that epistatic risk effects are likely to have at the population level (odds ratio for MI risk 1.3-2.0, depending on allele frequency and interaction model.

  11. Weighted risk score-based multifactor dimensionality reduction to detect gene-gene interactions in nasopharyngeal carcinoma.

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    Li, Chao-Feng; Luo, Fu-Tian; Zeng, Yi-Xin; Jia, Wei-Hua

    2014-06-13

    Determining the complex relationships between diseases, polymorphisms in human genes and environmental factors is challenging. Multifactor dimensionality reduction (MDR) has been proven to be capable of effectively detecting the statistical patterns of epistasis, although classification accuracy is required for this approach. The imbalanced dataset can cause seriously negative effects on classification accuracy. Moreover, MDR methods cannot quantitatively assess the disease risk of genotype combinations. Hence, we introduce a novel weighted risk score-based multifactor dimensionality reduction (WRSMDR) method that uses the Bayesian posterior probability of polymorphism combinations as a new quantitative measure of disease risk. First, we compared the WRSMDR to the MDR method in simulated datasets. Our results showed that the WRSMDR method had reasonable power to identify high-order gene-gene interactions, and it was more effective than MDR at detecting four-locus models. Moreover, WRSMDR reveals more information regarding the effect of genotype combination on the disease risk, and the result was easier to determine and apply than with MDR. Finally, we applied WRSMDR to a nasopharyngeal carcinoma (NPC) case-control study and identified a statistically significant high-order interaction among three polymorphisms: rs2860580, rs11865086 and rs2305806.

  12. Weighted Risk Score-Based Multifactor Dimensionality Reduction to Detect Gene-Gene Interactions in Nasopharyngeal Carcinoma

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    Chao-Feng Li

    2014-06-01

    Full Text Available Determining the complex relationships between diseases, polymorphisms in human genes and environmental factors is challenging. Multifactor dimensionality reduction (MDR has been proven to be capable of effectively detecting the statistical patterns of epistasis, although classification accuracy is required for this approach. The imbalanced dataset can cause seriously negative effects on classification accuracy. Moreover, MDR methods cannot quantitatively assess the disease risk of genotype combinations. Hence, we introduce a novel weighted risk score-based multifactor dimensionality reduction (WRSMDR method that uses the Bayesian posterior probability of polymorphism combinations as a new quantitative measure of disease risk. First, we compared the WRSMDR to the MDR method in simulated datasets. Our results showed that the WRSMDR method had reasonable power to identify high-order gene-gene interactions, and it was more effective than MDR at detecting four-locus models. Moreover, WRSMDR reveals more information regarding the effect of genotype combination on the disease risk, and the result was easier to determine and apply than with MDR. Finally, we applied WRSMDR to a nasopharyngeal carcinoma (NPC case-control study and identified a statistically significant high-order interaction among three polymorphisms: rs2860580, rs11865086 and rs2305806.

  13. HSD3B and gene-gene interactions in a pathway-based analysis of genetic susceptibility to bladder cancer.

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    Angeline S Andrew

    Full Text Available Bladder cancer is the 4(th most common cancer among men in the U.S. We analyzed variant genotypes hypothesized to modify major biological processes involved in bladder carcinogenesis, including hormone regulation, apoptosis, DNA repair, immune surveillance, metabolism, proliferation, and telomere maintenance. Logistic regression was used to assess the relationship between genetic variation affecting these processes and susceptibility in 563 genotyped urothelial cell carcinoma cases and 863 controls enrolled in a case-control study of incident bladder cancer conducted in New Hampshire, U.S. We evaluated gene-gene interactions using Multifactor Dimensionality Reduction (MDR and Statistical Epistasis Network analysis. The 3'UTR flanking variant form of the hormone regulation gene HSD3B2 was associated with increased bladder cancer risk in the New Hampshire population (adjusted OR 1.85 95%CI 1.31-2.62. This finding was successfully replicated in the Texas Bladder Cancer Study with 957 controls, 497 cases (adjusted OR 3.66 95%CI 1.06-12.63. The effect of this prevalent SNP was stronger among males (OR 2.13 95%CI 1.40-3.25 than females (OR 1.56 95%CI 0.83-2.95, (SNP-gender interaction P = 0.048. We also identified a SNP-SNP interaction between T-cell activation related genes GATA3 and CD81 (interaction P = 0.0003. The fact that bladder cancer incidence is 3-4 times higher in males suggests the involvement of hormone levels. This biologic process-based analysis suggests candidate susceptibility markers and supports the theory that disrupted hormone regulation plays a role in bladder carcinogenesis.

  14. Odds ratio based multifactor-dimensionality reduction method for detecting gene-gene interactions.

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    Chung, Yujin; Lee, Seung Yeoun; Elston, Robert C; Park, Taesung

    2007-01-01

    The identification and characterization of genes that increase the susceptibility to common complex multifactorial diseases is a challenging task in genetic association studies. The multifactor dimensionality reduction (MDR) method has been proposed and implemented by Ritchie et al. (2001) to identify the combinations of multilocus genotypes and discrete environmental factors that are associated with a particular disease. However, the original MDR method classifies the combination of multilocus genotypes into high-risk and low-risk groups in an ad hoc manner based on a simple comparison of the ratios of the number of cases and controls. Hence, the MDR approach is prone to false positive and negative errors when the ratio of the number of cases and controls in a combination of genotypes is similar to that in the entire data, or when both the number of cases and controls is small. Hence, we propose the odds ratio based multifactor dimensionality reduction (OR MDR) method that uses the odds ratio as a new quantitative measure of disease risk. While the original MDR method provides a simple binary measure of risk, the OR MDR method provides not only the odds ratio as a quantitative measure of risk but also the ordering of the multilocus combinations from the highest risk to lowest risk groups. Furthermore, the OR MDR method provides a confidence interval for the odds ratio for each multilocus combination, which is extremely informative in judging its importance as a risk factor. The proposed OR MDR method is illustrated using the dataset obtained from the CDC Chronic Fatigue Syndrome Research Group. The program written in R is available.

  15. A genetic ensemble approach for gene-gene interaction identification

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    Ho Joshua WK

    2010-10-01

    Full Text Available Abstract Background It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging. Methods In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA and an ensemble of classifiers (called genetic ensemble. Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gene-environment interactions can be extracted using a simple combinatorial ranking method. Also considered in this study is the idea of combining identification results obtained from multiple algorithms. A novel formula based on pairwise double fault is designed to quantify the degree of complementarity. Conclusions Our simulation study demonstrates that the proposed genetic ensemble algorithm has comparable identification power to Multifactor Dimensionality Reduction (MDR and is slightly better than Polymorphism Interaction Analysis (PIA, which are the two most popular methods for gene-gene interaction identification. More importantly, the identification results generated by using our genetic ensemble algorithm are highly complementary to those obtained by PIA and MDR. Experimental results from our simulation studies and real world data application also confirm the effectiveness of the proposed genetic ensemble algorithm, as well as the potential benefits of

  16. Gene-Gene Interaction Analysis for the Accelerated Failure Time Model Using a Unified Model-Based Multifactor Dimensionality Reduction Method.

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    Lee, Seungyeoun; Son, Donghee; Yu, Wenbao; Park, Taesung

    2016-12-01

    Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely applied, since the constructive induction algorithm of MDR efficiently reduces high-order dimensions into one dimension by classifying multi-level genotypes into high- and low-risk groups. The MDR method has been extended to various phenotypes and has been improved to provide a significance test for gene-gene interactions. In this paper, we propose a simple method, called accelerated failure time (AFT) UM-MDR, in which the idea of a unified model-based MDR is extended to the survival phenotype by incorporating AFT-MDR into the classification step. The proposed AFT UM-MDR method is compared with AFT-MDR through simulation studies, and a short discussion is given.

  17. Gene-Gene Interaction Analysis for the Accelerated Failure Time Model Using a Unified Model-Based Multifactor Dimensionality Reduction Method

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    Seungyeoun Lee

    2016-12-01

    Full Text Available Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR method has been widely applied, since the constructive induction algorithm of MDR efficiently reduces high-order dimensions into one dimension by classifying multi-level genotypes into high- and low-risk groups. The MDR method has been extended to various phenotypes and has been improved to provide a significance test for gene-gene interactions. In this paper, we propose a simple method, called accelerated failure time (AFT UM-MDR, in which the idea of a unified model-based MDR is extended to the survival phenotype by incorporating AFT-MDR into the classification step. The proposed AFT UM-MDR method is compared with AFT-MDR through simulation studies, and a short discussion is given.

  18. GEGEINTOOL: A Computer-Based Tool for Automated Analysis of Gene-Gene Interactions in Large Epidemiological Studies in Cardiovascular Genomics

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    Oscar Coltell

    2013-06-01

    Full Text Available Current methods of data analysis of gene-gene interactions in complex diseases, after taking into account environmental factors using traditional approaches, are inefficient. High-throughput methods of analysis in large scale studies including thousands of subjects and hundreds of SNPs should be implemented. We developed an integrative computer tool, GEGEINTOOL (GEne- GEne INTeraction tOOL, for large-scale analysis of gene-gene interactions, in human studies of complex diseases including a large number of subjects, SNPs, as well as environmental factors. That resource uses standard statistical packages (SPSS, etc. to build and fit the gene-gene interaction models by means of syntax scripts in predicting one or more continuous or dichotomic phenotypes. Codominant, dominant and recessive genetic interaction models including control for covariates are automatically created for each SNP in order to test the best model. From the standard outputs, GEGEINTOOL extracts a selected set of parameters (regression coefficients, p-values, adjusted means, etc., and groups them in a single MS Excel Spreadsheet. The tool allows editing the set of filter parameters, filtering the selected results depending on p-values, as well as plotting the selected gene-gene interactions to check consistency. In conclusion, GEGEINTOOL is a useful and friendly tool for exploring and identifying gene-gene interactions in complex diseases.

  19. [The application of multifactor dimensionality reduction for detecting gene-gene interactions].

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    Tang, Xun; Li, Na; Hu, Yong-hua

    2006-05-01

    To introduce the application of Multifactor Dimensionality Reduction (MDR) method for detecting gene-gene interactions in genetic case-control studies. A brief overview on basic steps involved in the implementation, theoretical details, available software as well as the use and features of the MDR method were discussed based on a practical research case. Advantages of MDR were compared to the conventional statistical approaches, showing that MDR method was a novel, nonparametric, genetic model-free approach that was developed specifically for detecting gene-gene interactions. Theoretical and empirical studies suggested that MDR was having reasonable power for detecting gene-gene interactions. Applications of MDR method had found the evidence of gene-gene interactions in several diseases such as sporadic breast cancer, atrial fibrillation and essential hypertension. MDR method could be used for detecting gene-gene interactions in genetic case-control studies as having great advantages versus the conventional statistical approaches.

  20. A detailed view on Model-Based Multifactor Dimensionality Reduction for detecting gene-gene interactions in case-control data in the absence and presence of noise

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    CATTAERT, TOM; CALLE, M. LUZ; DUDEK, SCOTT M.; MAHACHIE JOHN, JESTINAH M.; VAN LISHOUT, FRANÇOIS; URREA, VICTOR; RITCHIE, MARYLYN D.; VAN STEEN, KRISTEL

    2010-01-01

    SUMMARY Analyzing the combined effects of genes and/or environmental factors on the development of complex diseases is a great challenge from both the statistical and computational perspective, even using a relatively small number of genetic and non-genetic exposures. Several data mining methods have been proposed for interaction analysis, among them, the Multifactor Dimensionality Reduction Method (MDR), which has proven its utility in a variety of theoretical and practical settings. Model-Based Multifactor Dimensionality Reduction (MB-MDR), a relatively new MDR-based technique that is able to unify the best of both non-parametric and parametric worlds, was developed to address some of the remaining concerns that go along with an MDR-analysis. These include the restriction to univariate, dichotomous traits, the absence of flexible ways to adjust for lower-order effects and important confounders, and the difficulty to highlight epistasis effects when too many multi-locus genotype cells are pooled into two new genotype groups. Whereas the true value of MB-MDR can only reveal itself by extensive applications of the method in a variety of real-life scenarios, here we investigate the empirical power of MB-MDR to detect gene-gene interactions in the absence of any noise and in the presence of genotyping error, missing data, phenocopy, and genetic heterogeneity. For the considered simulation settings, we show that the power is generally higher for MB-MDR than for MDR, in particular in the presence of genetic heterogeneity, phenocopy, or low minor allele frequencies. PMID:21158747

  1. Gene-gene and gene-environmental interactions of childhood asthma: a multifactor dimension reduction approach.

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    Ming-Wei Su

    Full Text Available BACKGROUND: The importance of gene-gene and gene-environment interactions on asthma is well documented in literature, but a systematic analysis on the interaction between various genetic and environmental factors is still lacking. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a population-based, case-control study comprised of seventh-grade children from 14 Taiwanese communities. A total of 235 asthmatic cases and 1,310 non-asthmatic controls were selected for DNA collection and genotyping. We examined the gene-gene and gene-environment interactions between 17 single-nucleotide polymorphisms in antioxidative, inflammatory and obesity-related genes, and childhood asthma. Environmental exposures and disease status were obtained from parental questionnaires. The model-free and non-parametrical multifactor dimensionality reduction (MDR method was used for the analysis. A three-way gene-gene interaction was elucidated between the gene coding glutathione S-transferase P (GSTP1, the gene coding interleukin-4 receptor alpha chain (IL4Ra and the gene coding insulin induced gene 2 (INSIG2 on the risk of lifetime asthma. The testing-balanced accuracy on asthma was 57.83% with a cross-validation consistency of 10 out of 10. The interaction of preterm birth and indoor dampness had the highest training-balanced accuracy at 59.09%. Indoor dampness also interacted with many genes, including IL13, beta-2 adrenergic receptor (ADRB2, signal transducer and activator of transcription 6 (STAT6. We also used likelihood ratio tests for interaction and chi-square tests to validate our results and all tests showed statistical significance. CONCLUSIONS/SIGNIFICANCE: The results of this study suggest that GSTP1, INSIG2 and IL4Ra may influence the lifetime asthma susceptibility through gene-gene interactions in schoolchildren. Home dampness combined with each one of the genes STAT6, IL13 and ADRB2 could raise the asthma risk.

  2. Research progress in machine learning methods for gene-gene interaction detection.

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    Peng, Zhe-Ye; Tang, Zi-Jun; Xie, Min-Zhu

    2018-03-20

    Complex diseases are results of gene-gene and gene-environment interactions. However, the detection of high-dimensional gene-gene interactions is computationally challenging. In the last two decades, machine-learning approaches have been developed to detect gene-gene interactions with some successes. In this review, we summarize the progress in research on machine learning methods, as applied to gene-gene interaction detection. It systematically examines the principles and limitations of the current machine learning methods used in genome wide association studies (GWAS) to detect gene-gene interactions, such as neural networks (NN), random forest (RF), support vector machines (SVM) and multifactor dimensionality reduction (MDR), and provides some insights on the future research directions in the field.

  3. GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data.

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    Kwon, Minseok; Leem, Sangseob; Yoon, Joon; Park, Taesung

    2018-03-19

    With the rapid advancement of array-based genotyping techniques, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with common complex diseases. However, it has been shown that only a small proportion of the genetic etiology of complex diseases could be explained by the genetic factors identified from GWAS. This missing heritability could possibly be explained by gene-gene interaction (epistasis) and rare variants. There has been an exponential growth of gene-gene interaction analysis for common variants in terms of methodological developments and practical applications. Also, the recent advancement of high-throughput sequencing technologies makes it possible to conduct rare variant analysis. However, little progress has been made in gene-gene interaction analysis for rare variants. Here, we propose GxGrare which is a new gene-gene interaction method for the rare variants in the framework of the multifactor dimensionality reduction (MDR) analysis. The proposed method consists of three steps; 1) collapsing the rare variants, 2) MDR analysis for the collapsed rare variants, and 3) detect top candidate interaction pairs. GxGrare can be used for the detection of not only gene-gene interactions, but also interactions within a single gene. The proposed method is illustrated with 1080 whole exome sequencing data of the Korean population in order to identify causal gene-gene interaction for rare variants for type 2 diabetes. The proposed GxGrare performs well for gene-gene interaction detection with collapsing of rare variants. GxGrare is available at http://bibs.snu.ac.kr/software/gxgrare which contains simulation data and documentation. Supported operating systems include Linux and OS X.

  4. Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

    Science.gov (United States)

    Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

    2015-01-01

    Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these

  5. Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis

    Directory of Open Access Journals (Sweden)

    Ueki Masao

    2012-05-01

    Full Text Available Abstract Background Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed. Results We adopt an up-to-date method for ultrahigh-dimensional variable selection termed the sure independence screening (SIS for appropriate handling of numerous number of SNP-SNP interactions by including them as predictor variables in logistic regression. We propose ranking strategy using promising dummy coding methods and following variable selection procedure in the SIS method suitably modified for gene-gene interaction analysis. We also implemented the procedures in a software program, EPISIS, using the cost-effective GPGPU (General-purpose computing on graphics processing units technology. EPISIS can complete exhaustive search for SNP-SNP interactions in standard GWAS dataset within several hours. The proposed method works successfully in simulation experiments and in application to real WTCCC (Wellcome Trust Case–control Consortium data. Conclusions Based on the machine-learning principle, the proposed method gives powerful and flexible genome-wide search for various patterns of gene-gene interaction.

  6. Gene-Gene and Gene-Environment Interactions in the Etiology of Breast Cancer

    National Research Council Canada - National Science Library

    Adegoke, Olufemi

    2003-01-01

    The objective of this CDA is to evaluate the gene-gene and gene-environment interactions in the etiology of breast cancer in two ongoing case-control studies, the Shanghai Breast Cancer Study (SBCS...

  7. Multivariate Quantitative Multifactor Dimensionality Reduction for Detecting Gene-Gene Interactions.

    Science.gov (United States)

    Yu, Wenbao; Kwon, Min-Seok; Park, Taesung

    2015-01-01

    To determine gene-gene interactions and missing heritability of complex diseases is a challenging topic in genome-wide association studies. The multifactor dimensionality reduction (MDR) method is one of the most commonly used methods for identifying gene-gene interactions with dichotomous phenotypes. For quantitative phenotypes, the generalized MDR or quantitative MDR (QMDR) methods have been proposed. These methods are known as univariate methods because they consider only one phenotype. To date, there are few methods for analyzing multiple phenotypes. To address this problem, we propose a multivariate QMDR method (Multi-QMDR) for multivariate correlated phenotypes. We summarize the multivariate phenotypes into a univariate score by dimensional reduction analysis, and then classify the samples accordingly into high-risk and low-risk groups. We use different ways of summarizing mainly based on the principal components. Multi-QMDR is model-free and easy to implement. Multi-QMDR is applied to lipid-related traits. The properties of Multi- QMDR were investigated through simulation studies. Empirical studies show that Multi-QMDR outperforms existing univariate and multivariate methods at identifying causal interactions. The Multi-QMDR approach improves the performance of QMDR when multiple quantitative phenotypes are available. 2015 S. Karger AG, Basel.

  8. Genome-wide identification of key modulators of gene-gene interaction networks in breast cancer.

    Science.gov (United States)

    Chiu, Yu-Chiao; Wang, Li-Ju; Hsiao, Tzu-Hung; Chuang, Eric Y; Chen, Yidong

    2017-10-03

    With the advances in high-throughput gene profiling technologies, a large volume of gene interaction maps has been constructed. A higher-level layer of gene-gene interaction, namely modulate gene interaction, is composed of gene pairs of which interaction strengths are modulated by (i.e., dependent on) the expression level of a key modulator gene. Systematic investigations into the modulation by estrogen receptor (ER), the best-known modulator gene, have revealed the functional and prognostic significance in breast cancer. However, a genome-wide identification of key modulator genes that may further unveil the landscape of modulated gene interaction is still lacking. We proposed a systematic workflow to screen for key modulators based on genome-wide gene expression profiles. We designed four modularity parameters to measure the ability of a putative modulator to perturb gene interaction networks. Applying the method to a dataset of 286 breast tumors, we comprehensively characterized the modularity parameters and identified a total of 973 key modulator genes. The modularity of these modulators was verified in three independent breast cancer datasets. ESR1, the encoding gene of ER, appeared in the list, and abundant novel modulators were illuminated. For instance, a prognostic predictor of breast cancer, SFRP1, was found the second modulator. Functional annotation analysis of the 973 modulators revealed involvements in ER-related cellular processes as well as immune- and tumor-associated functions. Here we present, as far as we know, the first comprehensive analysis of key modulator genes on a genome-wide scale. The validity of filtering parameters as well as the conservativity of modulators among cohorts were corroborated. Our data bring new insights into the modulated layer of gene-gene interaction and provide candidates for further biological investigations.

  9. A review for detecting gene-gene interactions using machine learning methods in genetic epidemiology.

    Science.gov (United States)

    Koo, Ching Lee; Liew, Mei Jing; Mohamad, Mohd Saberi; Salleh, Abdul Hakim Mohamed

    2013-01-01

    Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs), support vector machine (SVM), and random forests (RFs) in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

  10. Parallel Multifactor Dimensionality Reduction: A tool for the large scale analysis of gene-gene interactions

    Science.gov (United States)

    Bush, William S.; Dudek, Scott M.; Ritchie, Marylyn D.

    2016-01-01

    Summary Parallel multifactor dimensionality reduction is a tool for large scale analysis of gene-gene and gene-environment interactions. The MDR algorithm was redesigned to allow an unlimited number of study subjects, total variables, and variable states, and to remove restrictions on the order of interactions being analyzed. In addition, the algorithm is markedly more efficient, with an approximately 150-fold decrease in runtime for equivalent analyses. To facilitate the processing of large datasets, the algorithm was made parallel. PMID:16809395

  11. Parallel Multifactor Dimensionality Reduction: A tool for the large scale analysis of gene-gene interactions

    OpenAIRE

    Bush, William S.; Dudek, Scott M.; Ritchie, Marylyn D.

    2006-01-01

    Parallel multifactor dimensionality reduction is a tool for large scale analysis of gene-gene and gene-environment interactions. The MDR algorithm was redesigned to allow an unlimited number of study subjects, total variables, and variable states, and to remove restrictions on the order of interactions being analyzed. In addition, the algorithm is markedly more efficient, with an approximately 150-fold decrease in runtime for equivalent analyses. To facilitate the processing of large datasets...

  12. Variable-length haplotype construction for gene-gene interaction studies

    OpenAIRE

    Assawamakin, Anunchai; Chaiyaratana, Nachol; Limwongse, Chanin; Sinsomros, Saravudh; Yenchitsomanus, Pa-thai; Youngkong, Prakarnkiat

    2013-01-01

    This paper presents a non-parametric classification technique for identifying a candidate bi-allelic genetic marker set that best describes disease susceptibility in gene-gene interaction studies. The developed technique functions by creating a mapping between inferred haplotypes and case/control status. The technique cycles through all possible marker combination models generated from the available marker set where the best interaction model is determined from prediction accuracy and two aux...

  13. Robust Gene-Gene Interaction Analysis in Genome Wide Association Studies.

    Directory of Open Access Journals (Sweden)

    Yongkang Kim

    Full Text Available Genome-wide association studies (GWAS have successfully discovered hundreds of associations between genetic variants and complex traits. Most GWAS have focused on the identification of single variants. It has been shown that most of the variants that were discovered by GWAS could only partially explain disease heritability. The explanation for this missing heritability is generally believed to be gene-gene (GG or gene-environment (GE interactions and other structural variants. Generalized multifactor dimensionality reduction (GMDR has been proven to be reasonably powerful in detecting GG and GE interactions; however, its performance has been found to decline when outlying quantitative traits are present. This paper proposes a robust GMDR estimation method (based on the L-estimator and M-estimator estimation methods in an attempt to reduce the effects caused by outlying traits. A comparison of robust GMDR with the original MDR based on simulation studies showed the former method to outperform the latter. The performance of robust GMDR is illustrated through a real GWA example consisting of 8,577 samples from the Korean population using the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR level as a phenotype. Robust GMDR identified the KCNH1 gene to have strong interaction effects with other genes on the function of insulin secretion.

  14. A deeper look at two concepts of measuring gene-gene interactions: logistic regression and interaction information revisited.

    Science.gov (United States)

    Mielniczuk, Jan; Teisseyre, Paweł

    2018-03-01

    Detection of gene-gene interactions is one of the most important challenges in genome-wide case-control studies. Besides traditional logistic regression analysis, recently the entropy-based methods attracted a significant attention. Among entropy-based methods, interaction information is one of the most promising measures having many desirable properties. Although both logistic regression and interaction information have been used in several genome-wide association studies, the relationship between them has not been thoroughly investigated theoretically. The present paper attempts to fill this gap. We show that although certain connections between the two methods exist, in general they refer two different concepts of dependence and looking for interactions in those two senses leads to different approaches to interaction detection. We introduce ordering between interaction measures and specify conditions for independent and dependent genes under which interaction information is more discriminative measure than logistic regression. Moreover, we show that for so-called perfect distributions those measures are equivalent. The numerical experiments illustrate the theoretical findings indicating that interaction information and its modified version are more universal tools for detecting various types of interaction than logistic regression and linkage disequilibrium measures. © 2017 WILEY PERIODICALS, INC.

  15. [Gene-gene interaction on central obesity in school-aged children in China].

    Science.gov (United States)

    Fu, L W; Zhang, M X; Wu, L J; Gao, L W; Mi, J

    2017-07-10

    Objective: To investigate possible effect of 6 obesity-associated SNPs in contribution to central obesity and examine whether there is an interaction in the 6 SNPs in the cause of central obesity in school-aged children in China. Methods: A total of 3 502 school-aged children who were included in Beijing Child and Adolescent Metabolic Syndrome (BCAMS) Study were selected, and based on the age and sex specific waist circumference (WC) standards in the BCAMS study, 1 196 central obese cases and 2 306 controls were identified. Genomic DNA was extracted from peripheral blood white cells using the salt fractionation method. A total of 6 single nucleotide polymorphisms ( FTO rs9939609, MC4R rs17782313, BDNF rs6265, PCSK1 rs6235, SH2B1 rs4788102, and CSK rs1378942) were genotyped by TaqMan allelic discrimination assays with the GeneAmp 7900 sequence detection system (Applied Biosystems, Foster City, CA, USA). Logistic regression model was used to investigate the association between 6 SNPs and central obesity. Gene-gene interactions among 6 polymorphic loci were analyzed by using the Generalized Multifactor Dimensionality Reduction (GMDR) method, and then logistic regression model was constructed to confirm the best combination of loci identified in the GMDR. Results: After adjusting gender, age, Tanner stage, physical activity and family history of obesity, the FTO rs9939609-A, MC4R rs17782313-C and BDNF rs6265-G alleles were associated with central obesity under additive genetic model ( OR =1.24, 95 %CI : 1.06-1.45, P =0.008; OR =1.26, 95 %CI : 1.11-1.43, P =2.98×10(-4); OR =1.18, 95 % CI : 1.06-1.32, P =0.003). GMDR analysis showed a significant gene-gene interaction between MC4R rs17782313 and BDNF rs6265 ( P =0.001). The best two-locus combination showed the cross-validation consistency of 10/10 and testing accuracy of 0.539. This interaction showed the maximum consistency and minimum prediction error among all gene-gene interaction models evaluated. Moreover, the

  16. New evaluation measures for multifactor dimensionality reduction classifiers in gene-gene interaction analysis.

    Science.gov (United States)

    Namkung, Junghyun; Kim, Kyunga; Yi, Sungon; Chung, Wonil; Kwon, Min-Seok; Park, Taesung

    2009-02-01

    Gene-gene interactions are important contributors to complex biological traits. Multifactor dimensionality reduction (MDR) is a method to analyze gene-gene interactions and has been applied to many genetics studies of complex diseases. In order to identify the best interaction model associated with disease susceptibility, MDR classifiers corresponding to interaction models has been constructed and evaluated as a predictor of disease status via a certain measure such as balanced accuracy (BA). It has been shown that the performance of MDR tends to depend on the choice of the evaluation measures. In this article, we introduce two types of new evaluation measures. First, we develop weighted BA (wBA) that utilizes the quantitative information on the effect size of each multi-locus genotype on a trait. Second, we employ ordinal association measures to assess the performance of MDR classifiers. Simulation studies were conducted to compare the proposed measures with BA, a current measure. Our results showed that the wBA and tau(b) improved the power of MDR in detecting gene-gene interactions. Noticeably, the power increment was higher when data contains the greater number of genetic markers. Finally, we applied the proposed evaluation measures to real data.

  17. A Review for Detecting Gene-Gene Interactions Using Machine Learning Methods in Genetic Epidemiology

    Directory of Open Access Journals (Sweden)

    Ching Lee Koo

    2013-01-01

    Full Text Available Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs, support vector machine (SVM, and random forests (RFs in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

  18. Computational analysis of gene-gene interactions using multifactor dimensionality reduction.

    Science.gov (United States)

    Moore, Jason H

    2004-11-01

    Understanding the relationship between DNA sequence variations and biologic traits is expected to improve the diagnosis, prevention and treatment of common human diseases. Success in characterizing genetic architecture will depend on our ability to address nonlinearities in the genotype-to-phenotype mapping relationship as a result of gene-gene interactions, or epistasis. This review addresses the challenges associated with the detection and characterization of epistasis. A novel strategy known as multifactor dimensionality reduction that was specifically designed for the identification of multilocus genetic effects is presented. Several case studies that demonstrate the detection of gene-gene interactions in common diseases such as atrial fibrillation, Type II diabetes and essential hypertension are also discussed.

  19. Association mapping and gene-gene interaction for stem rust resistance in CIMMYT spring wheat germplasm.

    Science.gov (United States)

    Yu, Long-Xi; Lorenz, Aaron; Rutkoski, Jessica; Singh, Ravi P; Bhavani, Sridhar; Huerta-Espino, Julio; Sorrells, Mark E

    2011-12-01

    The recent emergence of wheat stem rust Ug99 and evolution of new races within the lineage threatens global wheat production because they overcome widely deployed stem rust resistance (Sr) genes that had been effective for many years. To identify loci conferring adult plant resistance to races of Ug99 in wheat, we employed an association mapping approach for 276 current spring wheat breeding lines from the International Maize and Wheat Improvement Center (CIMMYT). Breeding lines were genotyped with Diversity Array Technology (DArT) and microsatellite markers. Phenotypic data was collected on these lines for stem rust race Ug99 resistance at the adult plant stage in the stem rust resistance screening nursery in Njoro, Kenya in seasons 2008, 2009 and 2010. Fifteen marker loci were found to be significantly associated with stem rust resistance. Several markers appeared to be linked to known Sr genes, while other significant markers were located in chromosome regions where no Sr genes have been previously reported. Most of these new loci colocalized with QTLs identified recently in different biparental populations. Using the same data and Q + K covariate matrices, we investigated the interactions among marker loci using linear regression models to calculate P values for pairwise marker interactions. Resistance marker loci including the Sr2 locus on 3BS and the wPt1859 locus on 7DL had significant interaction effects with other loci in the same chromosome arm and with markers on chromosome 6B. Other resistance marker loci had significant pairwise interactions with markers on different chromosomes. Based on these results, we propose that a complex network of gene-gene interactions is, in part, responsible for resistance to Ug99. Further investigation may provide insight for understanding mechanisms that contribute to this resistance gene network.

  20. [Application of multifactor dimensionality reduction on the interactions between gene-gene, gene-environment and the risk sporadic colorectal cancer in Chinese population].

    Science.gov (United States)

    Jin, Ming-Juan; Liu, Bing; Zhang, Shuang-Shuang; Zhang, Yong-Jing; Xu, Mei; Ma, Xin-Yuan; Yao, Kai-Yan; Chen, Kun

    2008-06-01

    To identify the association between risk of sporadic colorectal cancer and the common single nucleotide polymorphisms (SNPs) in DNA repairs genes, gene to gene interactions among them and their gene to environment interactions with common environmental factors. In this population-based case-control study, 206 primary colorectal cancer cases and 845 cancer-free healthy controls were enrolled. Genotyping was carried out using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique, with the status of subjects case or controls unknown. Multifactor dimensionality reduction (MDR) and logistic analysis were both used for association analysis. As compared to the younger age group (> or = 42, or = 61 years) increased significantly (OR = 2.04, 95% CI: 1.49-2.80). Similar result was observed in the family cancer history (OR = 1.51, 95% CI: 1.05-2.17). However, no significant association between any single DNA repair gene SNP and colorectal cancer risk was discovered. Results from MDR analysis only showed a significant interaction among the four following factors: age, alcohol drinking, XRCC1 Arg194Trp and OGG1 Ser326Cys (the cross-validation consistency = 10/10, the average testing accuracy = 0.616, P = 0.011). Using a logistic regression model, the "high-risk" individuals had a significantly elevated risk of colorectal cancer compared to those "low- risk" individuals classified by the above MDR model (OR = 2.72, 95% CI: 1.66-4.47). The impact of polymorphisms in DNA repair genes on the risk of sporadic colorectal cancer exhibited a low-penetrance characteristics while the intricate interactions existing among them and with environmental factors.

  1. Gene-Gene Interactions in the Folate Metabolic Pathway and the Risk of Conotruncal Heart Defects

    Directory of Open Access Journals (Sweden)

    Philip J. Lupo

    2010-01-01

    Full Text Available Conotruncal and related heart defects (CTRD are common, complex malformations. Although there are few established risk factors, there is evidence that genetic variation in the folate metabolic pathway influences CTRD risk. This study was undertaken to assess the association between inherited (i.e., case and maternal gene-gene interactions in this pathway and the risk of CTRD. Case-parent triads (n=727, ascertained from the Children's Hospital of Philadelphia, were genotyped for ten functional variants of nine folate metabolic genes. Analyses of inherited genotypes were consistent with the previously reported association between MTHFR A1298C and CTRD (adjusted P=.02, but provided no evidence that CTRD was associated with inherited gene-gene interactions. Analyses of the maternal genotypes provided evidence of a MTHFR C677T/CBS 844ins68 interaction and CTRD risk (unadjusted P=.02. This association is consistent with the effects of this genotype combination on folate-homocysteine biochemistry but remains to be confirmed in independent study populations.

  2. Association testing to detect gene-gene interactions on sex chromosomes in trio data

    Directory of Open Access Journals (Sweden)

    Yeonok eLee

    2013-11-01

    Full Text Available Autism Spectrum Disorder (ASD occurs more often among males than females in a 4:1 ratio. Among theories used to explain the causes of ASD, the X chromosome and the Y chromosome theories attribute ASD to X-linked mutation and the male-limited gene expressions on the Y chromosome, respectively. Despite the rationale of the theory, studies have failed to attribute the sex-biased ratio to the significant linkage or association on the regions of interest on X chromosome. We further study the gender biased ratio by examining the possible interaction effects between two genes in the sex chromosomes. We propose a logistic regression model with mixed effects to detect gene-gene interactions on sex chromosomes. We investigated the power and type I error rates of the approach for a range of minor allele frequencies and varying linkage disequilibrium between markers and QTLs. We also evaluated the robustness of the model to population stratification. We applied the model to a trio-family data set with an ASD affected male child to study gene-gene interactions on sex chromosomes.

  3. Multifactor dimensionality reduction reveals gene-gene interactions associated with multiple sclerosis susceptibility in African Americans.

    Science.gov (United States)

    Brassat, D; Motsinger, A A; Caillier, S J; Erlich, H A; Walker, K; Steiner, L L; Cree, B A C; Barcellos, L F; Pericak-Vance, M A; Schmidt, S; Gregory, S; Hauser, S L; Haines, J L; Oksenberg, J R; Ritchie, M D

    2006-06-01

    Multiple sclerosis (MS) is a common disease of the central nervous system characterized by inflammation, myelin loss, gliosis, varying degrees of axonal pathology, and progressive neurological dysfunction. Multiple sclerosis exhibits many of the characteristics that distinguish complex genetic disorders including polygenic inheritance and environmental exposure risks. Here, we used a highly efficient multilocus genotyping assay representing variation in 34 genes associated with inflammatory pathways to explore gene-gene interactions and disease susceptibility in a well-characterized African-American case-control MS data set. We applied the multifactor dimensionality reduction (MDR) test to detect epistasis, and identified single-IL4R(Q576R)- and three-IL4R(Q576R), IL5RA(-80), CD14(-260)- locus association models that predict MS risk with 75-76% accuracy (P<0.01). These results demonstrate the importance of exploring both main effects and gene-gene interactions in the study of complex diseases.

  4. Efficient two-step testing of gene-gene interactions in genome-wide association studies.

    Science.gov (United States)

    Lewinger, Juan Pablo; Morrison, John L; Thomas, Duncan C; Murcray, Cassandra E; Conti, David V; Li, Dalin; Gauderman, W James

    2013-07-01

    Exhaustive testing of all possible SNP pairs in a genome-wide association study (GWAS) generally yields low power to detect gene-gene (G × G) interactions because of small effect sizes and stringent requirements for multiple-testing correction. We introduce a new two-step procedure for testing G × G interactions in case-control GWAS to detect interacting single nucleotide polymorphisms (SNPs) regardless of their marginal effects. In an initial screening step, all SNP pairs are tested for gene-gene association in the combined sample of cases and controls. In the second step, the pairs that pass the screening are followed up with a traditional test for G × G interaction. We show that the two-step method is substantially more powerful to detect G × G interactions than the exhaustive testing approach. For example, with 2,000 cases and 2,000 controls, the two-step method can have more than 90% power to detect an interaction odds ratio of 2.0 compared to less than 50% power for the exhaustive testing approach. Moreover, we show that a hybrid two-step approach that combines our newly proposed two-step test and the two-step test that screens for marginal effects retains the best power properties of both. The two-step procedures we introduce have the potential to uncover genetic signals that have not been previously identified in an initial single-SNP GWAS. We demonstrate the computational feasibility of the two-step G × G procedure by performing a G × G scan in the asthma GWAS of the University of Southern California Children's Health Study. © 2013 WILEY PERIODICALS, INC.

  5. Gene-gene and gene-environment interactions in prostate, breast and colorectal cancer

    DEFF Research Database (Denmark)

    Kopp, Tine Iskov

    The incidence of cancer in the western world has increased steeply during the last 50 years. For three of the most prevalent cancer types in Denmark, prostate, breast and colorectal cancer (PC, BC and CRC, respectively), only a small fraction (1-15%) of the incidences are caused by highly penetrant......, such as alcohol consumption, smoking, obesity, inflammation and high meat intake; whereas other factors protect against cancer, such as high intake of dietary fibre, fruits and vegetables, and physical activity. Investigating the interactions between genetic variations and environmental factors, such as dietary...... was used to examine gene-gene and geneenvironment interactions in relation to risk of cancer (Paper I-V). A human intervention trial (Paper V) was conducted in order to directly examine the effect on concurrent use of nonsteroidal anti-inflammatory drugs (NSAIDs) and alcohol consumption on circulating...

  6. Enriched power of case-only design in detecting gene-gene interaction using disease concordant twins

    DEFF Research Database (Denmark)

    Li, Weilong; Vandin, Fabio; Baumbach, Jan

    Epistasis, or interactions among genes, have long been recognized to be fundamentally important to understanding both the structure and function of genetic pathways. Detecting gene-gene interaction has been a challenging issue in genetic epidemiology due to the complexity of the interactive genome...

  7. A Comparative Study on Multifactor Dimensionality Reduction Methods for Detecting Gene-Gene Interactions with the Survival Phenotype.

    Science.gov (United States)

    Lee, Seungyeoun; Kim, Yongkang; Kwon, Min-Seok; Park, Taesung

    2015-01-01

    Genome-wide association studies (GWAS) have extensively analyzed single SNP effects on a wide variety of common and complex diseases and found many genetic variants associated with diseases. However, there is still a large portion of the genetic variants left unexplained. This missing heritability problem might be due to the analytical strategy that limits analyses to only single SNPs. One of possible approaches to the missing heritability problem is to consider identifying multi-SNP effects or gene-gene interactions. The multifactor dimensionality reduction method has been widely used to detect gene-gene interactions based on the constructive induction by classifying high-dimensional genotype combinations into one-dimensional variable with two attributes of high risk and low risk for the case-control study. Many modifications of MDR have been proposed and also extended to the survival phenotype. In this study, we propose several extensions of MDR for the survival phenotype and compare the proposed extensions with earlier MDR through comprehensive simulation studies.

  8. A Comparative Study on Multifactor Dimensionality Reduction Methods for Detecting Gene-Gene Interactions with the Survival Phenotype

    Directory of Open Access Journals (Sweden)

    Seungyeoun Lee

    2015-01-01

    Full Text Available Genome-wide association studies (GWAS have extensively analyzed single SNP effects on a wide variety of common and complex diseases and found many genetic variants associated with diseases. However, there is still a large portion of the genetic variants left unexplained. This missing heritability problem might be due to the analytical strategy that limits analyses to only single SNPs. One of possible approaches to the missing heritability problem is to consider identifying multi-SNP effects or gene-gene interactions. The multifactor dimensionality reduction method has been widely used to detect gene-gene interactions based on the constructive induction by classifying high-dimensional genotype combinations into one-dimensional variable with two attributes of high risk and low risk for the case-control study. Many modifications of MDR have been proposed and also extended to the survival phenotype. In this study, we propose several extensions of MDR for the survival phenotype and compare the proposed extensions with earlier MDR through comprehensive simulation studies.

  9. Network graph analysis of gene-gene interactions in genome-wide association study data.

    Science.gov (United States)

    Lee, Sungyoung; Kwon, Min-Seok; Park, Taesung

    2012-12-01

    Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

  10. Spatially uniform relieff (SURF) for computationally-efficient filtering of gene-gene interactions.

    Science.gov (United States)

    Greene, Casey S; Penrod, Nadia M; Kiralis, Jeff; Moore, Jason H

    2009-09-22

    Genome-wide association studies are becoming the de facto standard in the genetic analysis of common human diseases. Given the complexity and robustness of biological networks such diseases are unlikely to be the result of single points of failure but instead likely arise from the joint failure of two or more interacting components. The hope in genome-wide screens is that these points of failure can be linked to single nucleotide polymorphisms (SNPs) which confer disease susceptibility. Detecting interacting variants that lead to disease in the absence of single-gene effects is difficult however, and methods to exhaustively analyze sets of these variants for interactions are combinatorial in nature thus making them computationally infeasible. Efficient algorithms which can detect interacting SNPs are needed. ReliefF is one such promising algorithm, although it has low success rate for noisy datasets when the interaction effect is small. ReliefF has been paired with an iterative approach, Tuned ReliefF (TuRF), which improves the estimation of weights in noisy data but does not fundamentally change the underlying ReliefF algorithm. To improve the sensitivity of studies using these methods to detect small effects we introduce Spatially Uniform ReliefF (SURF). SURF's ability to detect interactions in this domain is significantly greater than that of ReliefF. Similarly SURF, in combination with the TuRF strategy significantly outperforms TuRF alone for SNP selection under an epistasis model. It is important to note that this success rate increase does not require an increase in algorithmic complexity and allows for increased success rate, even with the removal of a nuisance parameter from the algorithm. Researchers performing genetic association studies and aiming to discover gene-gene interactions associated with increased disease susceptibility should use SURF in place of ReliefF. For instance, SURF should be used instead of ReliefF to filter a dataset before an

  11. Spatially Uniform ReliefF (SURF for computationally-efficient filtering of gene-gene interactions

    Directory of Open Access Journals (Sweden)

    Greene Casey S

    2009-09-01

    Full Text Available Abstract Background Genome-wide association studies are becoming the de facto standard in the genetic analysis of common human diseases. Given the complexity and robustness of biological networks such diseases are unlikely to be the result of single points of failure but instead likely arise from the joint failure of two or more interacting components. The hope in genome-wide screens is that these points of failure can be linked to single nucleotide polymorphisms (SNPs which confer disease susceptibility. Detecting interacting variants that lead to disease in the absence of single-gene effects is difficult however, and methods to exhaustively analyze sets of these variants for interactions are combinatorial in nature thus making them computationally infeasible. Efficient algorithms which can detect interacting SNPs are needed. ReliefF is one such promising algorithm, although it has low success rate for noisy datasets when the interaction effect is small. ReliefF has been paired with an iterative approach, Tuned ReliefF (TuRF, which improves the estimation of weights in noisy data but does not fundamentally change the underlying ReliefF algorithm. To improve the sensitivity of studies using these methods to detect small effects we introduce Spatially Uniform ReliefF (SURF. Results SURF's ability to detect interactions in this domain is significantly greater than that of ReliefF. Similarly SURF, in combination with the TuRF strategy significantly outperforms TuRF alone for SNP selection under an epistasis model. It is important to note that this success rate increase does not require an increase in algorithmic complexity and allows for increased success rate, even with the removal of a nuisance parameter from the algorithm. Conclusion Researchers performing genetic association studies and aiming to discover gene-gene interactions associated with increased disease susceptibility should use SURF in place of ReliefF. For instance, SURF should be

  12. Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions.

    Science.gov (United States)

    Hahn, Lance W; Ritchie, Marylyn D; Moore, Jason H

    2003-02-12

    Polymorphisms in human genes are being described in remarkable numbers. Determining which polymorphisms and which environmental factors are associated with common, complex diseases has become a daunting task. This is partly because the effect of any single genetic variation will likely be dependent on other genetic variations (gene-gene interaction or epistasis) and environmental factors (gene-environment interaction). Detecting and characterizing interactions among multiple factors is both a statistical and a computational challenge. To address this problem, we have developed a multifactor dimensionality reduction (MDR) method for collapsing high-dimensional genetic data into a single dimension thus permitting interactions to be detected in relatively small sample sizes. In this paper, we describe the MDR approach and an MDR software package. We developed a program that integrates MDR with a cross-validation strategy for estimating the classification and prediction error of multifactor models. The software can be used to analyze interactions among 2-15 genetic and/or environmental factors. The dataset may contain up to 500 total variables and a maximum of 4000 study subjects. Information on obtaining the executable code, example data, example analysis, and documentation is available upon request. All supplementary information can be found at http://phg.mc.vanderbilt.edu/Software/MDR.

  13. Network Graph Analysis of Gene-Gene Interactions in Genome-Wide Association Study Data

    Directory of Open Access Journals (Sweden)

    Sungyoung Lee

    2012-12-01

    Full Text Available Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs. For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR is one of the powerful and efficient methods for detecting high-order gene-gene (GxG interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI. Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

  14. Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions.

    Science.gov (United States)

    Choi, Jiin; Park, Taesung

    2013-01-01

    Recently, one of the greatest challenges in genome-wide association studies is to detect gene-gene and/or gene-environment interactions for common complex human diseases. Ritchie et al. (2001) proposed multifactor dimensionality reduction (MDR) method for interaction analysis. MDR is a combinatorial approach to reduce multi-locus genotypes into high-risk and low-risk groups. Although MDR has been widely used for case-control studies with binary phenotypes, several extensions have been proposed. One of these methods, a generalized MDR (GMDR) proposed by Lou et al. (2007), allows adjusting for covariates and applying to both dichotomous and continuous phenotypes. GMDR uses the residual score of a generalized linear model of phenotypes to assign either high-risk or low-risk group, while MDR uses the ratio of cases to controls. In this study, we propose multivariate GMDR, an extension of GMDR for multivariate phenotypes. Jointly analysing correlated multivariate phenotypes may have more power to detect susceptible genes and gene-gene interactions. We construct generalized estimating equations (GEE) with multivariate phenotypes to extend generalized linear models. Using the score vectors from GEE we discriminate high-risk from low-risk groups. We applied the multivariate GMDR method to the blood pressure data of the 7,546 subjects from the Korean Association Resource study: systolic blood pressure (SBP) and diastolic blood pressure (DBP). We compare the results of multivariate GMDR for SBP and DBP to the results from separate univariate GMDR for SBP and DBP, respectively. We also applied the multivariate GMDR method to the repeatedly measured hypertension status from 5,466 subjects and compared its result with those of univariate GMDR at each time point. Results from the univariate GMDR and multivariate GMDR in two-locus model with both blood pressures and hypertension phenotypes indicate best combinations of SNPs whose interaction has significant association with risk

  15. Genome-wide search for gene-gene interactions in colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Shuo Jiao

    Full Text Available Genome-wide association studies (GWAS have successfully identified a number of single-nucleotide polymorphisms (SNPs associated with colorectal cancer (CRC risk. However, these susceptibility loci known today explain only a small fraction of the genetic risk. Gene-gene interaction (GxG is considered to be one source of the missing heritability. To address this, we performed a genome-wide search for pair-wise GxG associated with CRC risk using 8,380 cases and 10,558 controls in the discovery phase and 2,527 cases and 2,658 controls in the replication phase. We developed a simple, but powerful method for testing interaction, which we term the Average Risk Due to Interaction (ARDI. With this method, we conducted a genome-wide search to identify SNPs showing evidence for GxG with previously identified CRC susceptibility loci from 14 independent regions. We also conducted a genome-wide search for GxG using the marginal association screening and examining interaction among SNPs that pass the screening threshold (p<10(-4. For the known locus rs10795668 (10p14, we found an interacting SNP rs367615 (5q21 with replication p = 0.01 and combined p = 4.19×10(-8. Among the top marginal SNPs after LD pruning (n = 163, we identified an interaction between rs1571218 (20p12.3 and rs10879357 (12q21.1 (nominal combined p = 2.51×10(-6; Bonferroni adjusted p = 0.03. Our study represents the first comprehensive search for GxG in CRC, and our results may provide new insight into the genetic etiology of CRC.

  16. Novel Likelihood Ratio Tests for Screening Gene-Gene and Gene-Environment Interactions with Unbalanced Repeated-Measures Data

    Science.gov (United States)

    Ko, Yi-An; Saha-Chaudhuri, Paramita; Park, Sung Kyun; Vokonas, Pantel Steve; Mukherjee, Bhramar

    2013-01-01

    There has been extensive literature on modeling gene-gene interaction (GGI) and gene-environment interaction (GEI) in case-control studies with limited literature on statistical methods for GGI and GEI in longitudinal cohort studies. We borrow ideas from the classical two-way analysis of variance (ANOVA) literature to address the issue of robust modeling of interactions in repeated-measures studies. While classical interaction models proposed by Tukey and Mandel have interaction structures as a function of main effects, a newer class of models, additive main effects and multiplicative interaction (AMMI) models, do not have similar restrictive assumptions on the interaction structure. AMMI entails a singular value decomposition of the cell residual matrix after fitting the additive main effects and has been shown to perform well across various interaction structures. We consider these models for testing GGI and GEI from two perspectives: likelihood ratio test based on cell means and a regression based approach using individual observations. Simulation results indicate that both approaches for AMMI models lead to valid tests in terms of maintaining the type I error rate, with the regression approach having better power properties. The performance of these models was evaluated across different interaction structures and 12 common epistasis patterns. In summary, AMMI model is robust with respect to misspecified interaction structure and is a useful screening tool for interaction even in the absence of main effects. We use the proposed methods to examine the interplay between the hemochromatosis gene and cumulative lead exposure on pulse pressure in the Normative Aging Study. PMID:23798480

  17. Identifying gene-gene interactions that are highly associated with Body Mass Index using Quantitative Multifactor Dimensionality Reduction (QMDR)

    NARCIS (Netherlands)

    De, Rishika; Verma, Shefali S; Drenos, Fotios; Holzinger, Emily R; Holmes, Michael V; Hall, Molly A; Crosslin, David R; Carrell, David S; Hakonarson, Hakon; Jarvik, Gail; Larson, Eric; Pacheco, Jennifer A; Rasmussen-Torvik, Laura J; Moore, Carrie B; Asselbergs, Folkert W; Moore, Jason H; Ritchie, Marylyn D; Keating, Brendan J; Gilbert-Diamond, Diane

    2015-01-01

    BACKGROUND: Despite heritability estimates of 40-70 % for obesity, less than 2 % of its variation is explained by Body Mass Index (BMI) associated loci that have been identified so far. Epistasis, or gene-gene interactions are a plausible source to explain portions of the missing heritability of

  18. Multifactor dimensionality reduction for detecting gene-gene and gene-environment interactions in pharmacogenomics studies.

    Science.gov (United States)

    Ritchie, Marylyn D; Motsinger, Alison A

    2005-12-01

    In the quest for discovering disease susceptibility genes, the reality of gene-gene and gene-environment interactions creates difficult challenges for many current statistical approaches. In an attempt to overcome limitations with current disease gene detection methods, the multifactor dimensionality reduction (MDR) approach was previously developed. In brief, MDR is a method that reduces the dimensionality of multilocus information to identify polymorphisms associated with an increased risk of disease. This approach takes multilocus genotypes and develops a model for defining disease risk by pooling high-risk genotype combinations into one group and low-risk combinations into another. Cross-validation and permutation testing are used to identify optimal models. While this approach was initially developed for studies of complex disease, it is also directly applicable to pharmacogenomic studies where the outcome variable is drug treatment response/nonresponse or toxicity/no toxicity. MDR is a nonparametric and model-free approach that has been shown to have reasonable power to detect epistasis in both theoretical and empirical studies. This computational technology is described in detail in this review, and its application in pharmacogenomic studies is demonstrated.

  19. An efficiency analysis of high-order combinations of gene-gene interactions using multifactor-dimensionality reduction.

    Science.gov (United States)

    Yang, Cheng-Hong; Lin, Yu-Da; Yang, Cheng-San; Chuang, Li-Yeh

    2015-07-01

    Multifactor dimensionality reduction (MDR) is widely used to analyze interactions of genes to determine the complex relationship between diseases and polymorphisms in humans. However, the astronomical number of high-order combinations makes MDR a highly time-consuming process which can be difficult to implement for multiple tests to identify more complex interactions between genes. This study proposes a new framework, named fast MDR (FMDR), which is a greedy search strategy based on the joint effect property. Six models with different minor allele frequencies (MAFs) and different sample sizes were used to generate the six simulation data sets. A real data set was obtained from the mitochondrial D-loop of chronic dialysis patients. Comparison of results from the simulation data and real data sets showed that FMDR identified significant gene-gene interaction with less computational complexity than the MDR in high-order interaction analysis. FMDR improves the MDR difficulties associated with the computational loading of high-order SNPs and can be used to evaluate the relative effects of each individual SNP on disease susceptibility. FMDR is freely available at http://bioinfo.kmu.edu.tw/FMDR.rar .

  20. Use of Information Measures and Their Approximations to Detect Predictive Gene-Gene Interaction

    Directory of Open Access Journals (Sweden)

    Jan Mielniczuk

    2017-01-01

    Full Text Available We reconsider the properties and relationships of the interaction information and its modified versions in the context of detecting the interaction of two SNPs for the prediction of a binary outcome when interaction information is positive. This property is called predictive interaction, and we state some new sufficient conditions for it to hold true. We also study chi square approximations to these measures. It is argued that interaction information is a different and sometimes more natural measure of interaction than the logistic interaction parameter especially when SNPs are dependent. We introduce a novel measure of predictive interaction based on interaction information and its modified version. In numerical experiments, which use copulas to model dependence, we study examples when the logistic interaction parameter is zero or close to zero for which predictive interaction is detected by the new measure, while it remains undetected by the likelihood ratio test.

  1. GMDR: Versatile Software for Detecting Gene-Gene and Gene-Environ- ment Interactions Underlying Complex Traits

    Science.gov (United States)

    Xu, Hai-Ming; Xu, Li-Feng; Hou, Ting-Ting; Luo, Lin-Feng; Chen, Guo-Bo; Sun, Xi-Wei; Lou, Xiang-Yang

    2016-01-01

    Identification of multifactor gene-gene (G×G) and gene-environment (G×E) interactions underlying complex traits poses one of the great challenges to today’s genetic study. Development of the generalized multifactor dimensionality reduction (GMDR) method provides a practicable solution to problems in detection of interactions. To exploit the opportunities brought by the availability of diverse data, it is in high demand to develop the corresponding GMDR software that can handle a breadth of phenotypes, such as continuous, count, dichotomous, polytomous nominal, ordinal, survival and multivariate, and various kinds of study designs, such as unrelated case-control, family-based and pooled unrelated and family samples, and also allows adjustment for covariates. We developed a versatile GMDR package to implement this serial of GMDR analyses for various scenarios (e.g., unified analysis of unrelated and family samples) and large-scale (e.g., genome-wide) data. This package includes other desirable features such as data management and preprocessing. Permutation testing strategies are also built in to evaluate the threshold or empirical p values. In addition, its performance is scalable to the computational resources. The software is available at http://www.soph.uab.edu/ssg/software or http://ibi.zju.edu.cn/software. PMID:28479868

  2. An empirical fuzzy multifactor dimensionality reduction method for detecting gene-gene interactions.

    Science.gov (United States)

    Leem, Sangseob; Park, Taesung

    2017-03-14

    Detection of gene-gene interaction (GGI) is a key challenge towards solving the problem of missing heritability in genetics. The multifactor dimensionality reduction (MDR) method has been widely studied for detecting GGIs. MDR reduces the dimensionality of multi-factor by means of binary classification into high-risk (H) or low-risk (L) groups. Unfortunately, this simple binary classification does not reflect the uncertainty of H/L classification. Thus, we proposed Fuzzy MDR to overcome limitations of binary classification by introducing the degree of membership of two fuzzy sets H/L. While Fuzzy MDR demonstrated higher power than that of MDR, its performance is highly dependent on the several tuning parameters. In real applications, it is not easy to choose appropriate tuning parameter values. In this work, we propose an empirical fuzzy MDR (EF-MDR) which does not require specifying tuning parameters values. Here, we propose an empirical approach to estimating the membership degree that can be directly estimated from the data. In EF-MDR, the membership degree is estimated by the maximum likelihood estimator of the proportion of cases(controls) in each genotype combination. We also show that the balanced accuracy measure derived from this new membership function is a linear function of the standard chi-square statistics. This relationship allows us to perform the standard significance test using p-values in the MDR framework without permutation. Through two simulation studies, the power of the proposed EF-MDR is shown to be higher than those of MDR and Fuzzy MDR. We illustrate the proposed EF-MDR by analyzing Crohn's disease (CD) and bipolar disorder (BD) in the Wellcome Trust Case Control Consortium (WTCCC) dataset. We propose an empirical Fuzzy MDR for detecting GGI using the maximum likelihood of the proportion of cases(controls) as the membership degree of the genotype combination. The program written in R for EF-MDR is available at http://statgen.snu.ac.kr/software/EF-MDR .

  3. Pair-wise multifactor dimensionality reduction method to detect gene-gene interactions in a case-control study.

    Science.gov (United States)

    He, H; Oetting, W S; Brott, M J; Basu, S

    2010-01-01

    The identification of gene-gene interactions has been limited by small sample size and large number of potential interactions between genes. To address this issue, Ritchie et al. [2001] have proposed multifactor dimensionality reduction (MDR) method to detect polymorphisms associated with the disease risk. The MDR reduces the dimension of the genetic factors by classifying them into high-risk and low-risk groups. The strong point in favor of MDR is that it can detect interactions in absence of significant main effects. However, it often suffers from the sparseness of the cells in high-dimensional contingency tables, since it cannot classify an empty cell as high risk or low risk. We propose a pair-wise multifactor dimensionality reduction (PWMDR) approach to address the issue of MDR in classifying sparse or empty cells. Instead of looking at the higher dimensional contingency table, we score each pair-wise interaction of the genetic factors involved and combine the scores of all such pairwise interactions. Simulation studies showed that the PWMDR generally had greater power than MDR to detect third order interactions for polymorphisms with low allele frequencies. The PWMDR also outperformed the MDR in detecting gene-gene interaction on a kidney transplant dataset. The PWMDR outperformed the MDR to detect polymorphisms with low frequencies. Copyright 2009 S. Karger AG, Basel.

  4. Multi-factor dimensionality reduction applied to a large prospective investigation on gene-gene and gene-environment interactions.

    Science.gov (United States)

    Manuguerra, M; Matullo, G; Veglia, F; Autrup, H; Dunning, A M; Garte, S; Gormally, E; Malaveille, C; Guarrera, S; Polidoro, S; Saletta, F; Peluso, M; Airoldi, L; Overvad, K; Raaschou-Nielsen, O; Clavel-Chapelon, F; Linseisen, J; Boeing, H; Trichopoulos, D; Kalandidi, A; Palli, D; Krogh, V; Tumino, R; Panico, S; Bueno-De-Mesquita, H B; Peeters, P H; Lund, E; Pera, G; Martinez, C; Amiano, P; Barricarte, A; Tormo, M J; Quiros, J R; Berglund, G; Janzon, L; Jarvholm, B; Day, N E; Allen, N E; Saracci, R; Kaaks, R; Ferrari, P; Riboli, E; Vineis, P

    2007-02-01

    It is becoming increasingly evident that single-locus effects cannot explain complex multifactorial human diseases like cancer. We applied the multi-factor dimensionality reduction (MDR) method to a large cohort study on gene-environment and gene-gene interactions. The study (case-control nested in the EPIC cohort) was established to investigate molecular changes and genetic susceptibility in relation to air pollution and environmental tobacco smoke (ETS) in non-smokers. We have analyzed 757 controls and 409 cases with bladder cancer (n=124), lung cancer (n=116) and myeloid leukemia (n=169). Thirty-six gene variants (DNA repair and metabolic genes) and three environmental exposure variables (measures of air pollution and ETS at home and at work) were analyzed. Interactions were assessed by prediction error percentage and cross-validation consistency (CVC) frequency. For lung cancer, the best model was given by a significant gene-environment association between the base excision repair (BER) XRCC1-Arg399Gln polymorphism, the double-strand break repair (DSBR) BRCA2-Asn372His polymorphism and the exposure variable 'distance from heavy traffic road', an indirect and robust indicator of air pollution (mean prediction error of 26%, PT (mean prediction error of 22%, PT, MnSOD-Ala9Val and CYP1A1-Ile462Val had a minimum prediction error of 31% (P<0.001) and a maximum CVC of 4.40 (P=0.086). The MDR method seems promising, because it provides a limited number of statistically stable interactions; however, the biological interpretation remains to be understood.

  5. Multifactor dimensionality reduction: An analysis strategy for modelling and detecting gene - gene interactions in human genetics and pharmacogenomics studies

    Directory of Open Access Journals (Sweden)

    Motsinger Alison A

    2006-03-01

    Full Text Available Abstract The detection of gene - gene and gene - environment interactions associated with complex human disease or pharmacogenomic endpoints is a difficult challenge for human geneticists. Unlike rare, Mendelian diseases that are associated with a single gene, most common diseases are caused by the non-linear interaction of numerous genetic and environmental variables. The dimensionality involved in the evaluation of combinations of many such variables quickly diminishes the usefulness of traditional, parametric statistical methods. Multifactor dimensionality reduction (MDR is a novel and powerful statistical tool for detecting and modelling epistasis. MDR is a non-parametric and model-free approach that has been shown to have reasonable power to detect epistasis in both theoretical and empirical studies. MDR has detected interactions in diseases such as sporadic breast cancer, multiple sclerosis and essential hypertension. As this method is more frequently applied, and was gained acceptance in the study of human disease and pharmacogenomics, it is becoming increasingly important that the implementation of the MDR approach is properly understood. As with all statistical methods, MDR is only powerful and useful when implemented correctly. Concerns regarding dataset structure, configuration parameters and the proper execution of permutation testing in reference to a particular dataset and configuration are essential to the method's effectiveness. The detection, characterisation and interpretation of gene - gene and gene - environment interactions are expected to improve the diagnosis, prevention and treatment of common human diseases. MDR can be a powerful tool in reaching these goals when used appropriately.

  6. Multifactor dimensionality reduction: An analysis strategy for modelling and detecting gene - gene interactions in human genetics and pharmacogenomics studies

    Science.gov (United States)

    2006-01-01

    The detection of gene - gene and gene - environment interactions associated with complex human disease or pharmacogenomic endpoints is a difficult challenge for human geneticists. Unlike rare, Mendelian diseases that are associated with a single gene, most common diseases are caused by the non-linear interaction of numerous genetic and environmental variables. The dimensionality involved in the evaluation of combinations of many such variables quickly diminishes the usefulness of traditional, parametric statistical methods. Multifactor dimensionality reduction (MDR) is a novel and powerful statistical tool for detecting and modelling epistasis. MDR is a non-parametric and model-free approach that has been shown to have reasonable power to detect epistasis in both theoretical and empirical studies. MDR has detected interactions in diseases such as sporadic breast cancer, multiple sclerosis and essential hypertension. As this method is more frequently applied, and was gained acceptance in the study of human disease and pharmacogenomics, it is becoming increasingly important that the implementation of the MDR approach is properly understood. As with all statistical methods, MDR is only powerful and useful when implemented correctly. Concerns regarding dataset structure, configuration parameters and the proper execution of permutation testing in reference to a particular dataset and configuration are essential to the method's effectiveness. The detection, characterisation and interpretation of gene - gene and gene - environment interactions are expected to improve the diagnosis, prevention and treatment of common human diseases. MDR can be a powerful tool in reaching these goals when used appropriately. PMID:16595076

  7. Multifactor dimensionality reduction: an analysis strategy for modelling and detecting gene-gene interactions in human genetics and pharmacogenomics studies.

    Science.gov (United States)

    Motsinger, Alison A; Ritchie, Marylyn D

    2006-03-01

    The detection of gene-gene and gene-environment interactions associated with complex human disease or pharmacogenomic endpoints is a difficult challenge for human geneticists. Unlike rare, Mendelian diseases that are associated with a single gene, most common diseases are caused by the non-linear interaction of numerous genetic and environmental variables. The dimensionality involved in the evaluation of combinations of many such variables quickly diminishes the usefulness of traditional, parametric statistical methods. Multifactor dimensionality reduction (MDR) is a novel and powerful statistical tool for detecting and modelling epistasis. MDR is a non-parametric and model-free approach that has been shown to have reasonable power to detect epistasis in both theoretical and empirical studies. MDR has detected interactions in diseases such as sporadic breast cancer, multiple sclerosis and essential hypertension. As this method is more frequently applied, and was gained acceptance in the study of human disease and pharmacogenomics, it is becoming increasingly important that the implementation of the MDR approach is properly understood. As with all statistical methods, MDR is only powerful and useful when implemented correctly. Concerns regarding dataset structure, configuration parameters and the proper execution of permutation testing in reference to a particular dataset and configuration are essential to the method's effectiveness. The detection, characterisation and interpretation of gene-gene and gene-environment interactions are expected to improve the diagnosis, prevention and treatment of common human diseases. MDR can be a powerful tool in reaching these goals when used appropriately.

  8. Identifying gene-gene interactions that are highly associated with Body Mass Index using Quantitative Multifactor Dimensionality Reduction (QMDR).

    Science.gov (United States)

    De, Rishika; Verma, Shefali S; Drenos, Fotios; Holzinger, Emily R; Holmes, Michael V; Hall, Molly A; Crosslin, David R; Carrell, David S; Hakonarson, Hakon; Jarvik, Gail; Larson, Eric; Pacheco, Jennifer A; Rasmussen-Torvik, Laura J; Moore, Carrie B; Asselbergs, Folkert W; Moore, Jason H; Ritchie, Marylyn D; Keating, Brendan J; Gilbert-Diamond, Diane

    2015-01-01

    Despite heritability estimates of 40-70 % for obesity, less than 2 % of its variation is explained by Body Mass Index (BMI) associated loci that have been identified so far. Epistasis, or gene-gene interactions are a plausible source to explain portions of the missing heritability of BMI. Using genotypic data from 18,686 individuals across five study cohorts - ARIC, CARDIA, FHS, CHS, MESA - we filtered SNPs (Single Nucleotide Polymorphisms) using two parallel approaches. SNPs were filtered either on the strength of their main effects of association with BMI, or on the number of knowledge sources supporting a specific SNP-SNP interaction in the context of BMI. Filtered SNPs were specifically analyzed for interactions that are highly associated with BMI using QMDR (Quantitative Multifactor Dimensionality Reduction). QMDR is a nonparametric, genetic model-free method that detects non-linear interactions associated with a quantitative trait. We identified seven novel, epistatic models with a Bonferroni corrected p-value of association < 0.1. Prior experimental evidence helps explain the plausible biological interactions highlighted within our results and their relationship with obesity. We identified interactions between genes involved in mitochondrial dysfunction (POLG2), cholesterol metabolism (SOAT2), lipid metabolism (CYP11B2), cell adhesion (EZR), cell proliferation (MAP2K5), and insulin resistance (IGF1R). Moreover, we found an 8.8 % increase in the variance in BMI explained by these seven SNP-SNP interactions, beyond what is explained by the main effects of an index FTO SNP and the SNPs within these interactions. We also replicated one of these interactions and 58 proxy SNP-SNP models representing it in an independent dataset from the eMERGE study. This study highlights a novel approach for discovering gene-gene interactions by combining methods such as QMDR with traditional statistics.

  9. Power of grammatical evolution neural networks to detect gene-gene interactions in the presence of error

    Directory of Open Access Journals (Sweden)

    Davis Anna C

    2008-08-01

    Full Text Available Abstract Background With the advent of increasingly efficient means to obtain genetic information, a great insurgence of data has resulted, leading to the need for methods for analyzing this data beyond that of traditional parametric statistical approaches. Recently we introduced Grammatical Evolution Neural Network (GENN, a machine-learning approach to detect gene-gene or gene-environment interactions, also known as epistasis, in high dimensional genetic epidemiological data. GENN has been shown to be highly successful in a range of simulated data, but the impact of error common to real data is unknown. In the current study, we examine the power of GENN to detect interesting interactions in the presence of noise due to genotyping error, missing data, phenocopy, and genetic heterogeneity. Additionally, we compare the performance of GENN to that of another computational method – Multifactor Dimensionality Reduction (MDR. Findings GENN is extremely robust to missing data and genotyping error. Phenocopy in a dataset reduces the power of both GENN and MDR. GENN is reasonably robust to genetic heterogeneity and find that in some cases GENN has substantially higher power than MDR to detect functional loci in the presence of genetic heterogeneity. Conclusion GENN is a promising method to detect gene-gene interaction, even in the presence of common types of error found in real data.

  10. Power of grammatical evolution neural networks to detect gene-gene interactions in the presence of error.

    Science.gov (United States)

    Motsinger-Reif, Alison A; Fanelli, Theresa J; Davis, Anna C; Ritchie, Marylyn D

    2008-08-13

    With the advent of increasingly efficient means to obtain genetic information, a great insurgence of data has resulted, leading to the need for methods for analyzing this data beyond that of traditional parametric statistical approaches. Recently we introduced Grammatical Evolution Neural Network (GENN), a machine-learning approach to detect gene-gene or gene-environment interactions, also known as epistasis, in high dimensional genetic epidemiological data. GENN has been shown to be highly successful in a range of simulated data, but the impact of error common to real data is unknown. In the current study, we examine the power of GENN to detect interesting interactions in the presence of noise due to genotyping error, missing data, phenocopy, and genetic heterogeneity. Additionally, we compare the performance of GENN to that of another computational method - Multifactor Dimensionality Reduction (MDR). GENN is extremely robust to missing data and genotyping error. Phenocopy in a dataset reduces the power of both GENN and MDR. GENN is reasonably robust to genetic heterogeneity and find that in some cases GENN has substantially higher power than MDR to detect functional loci in the presence of genetic heterogeneity. GENN is a promising method to detect gene-gene interaction, even in the presence of common types of error found in real data.

  11. A robust multifactor dimensionality reduction method for detecting gene-gene interactions with application to the genetic analysis of bladder cancer susceptibility

    Science.gov (United States)

    Gui, Jiang; Andrew, Angeline S.; Andrews, Peter; Nelson, Heather M.; Kelsey, Karl T.; Karagas, Margaret R.; Moore, Jason H.

    2010-01-01

    A central goal of human genetics is to identify and characterize susceptibility genes for common complex human diseases. An important challenge in this endeavor is the modeling of gene-gene interaction or epistasis that can result in non-additivity of genetic effects. The multifactor dimensionality reduction (MDR) method was developed as machine learning alternative to parametric logistic regression for detecting interactions in absence of significant marginal effects. The goal of MDR is to reduce the dimensionality inherent in modeling combinations of polymorphisms using a computational approach called constructive induction. Here, we propose a Robust Multifactor Dimensionality Reduction (RMDR) method that performs constructive induction using a Fisher’s Exact Test rather than a predetermined threshold. The advantage of this approach is that only those genotype combinations that are determined to be statistically significant are considered in the MDR analysis. We use two simulation studies to demonstrate that this approach will increase the success rate of MDR when there are only a few genotype combinations that are significantly associated with case-control status. We show that there is no loss of success rate when this is not the case. We then apply the RMDR method to the detection of gene-gene interactions in genotype data from a population-based study of bladder cancer in New Hampshire. PMID:21091664

  12. A robust multifactor dimensionality reduction method for detecting gene-gene interactions with application to the genetic analysis of bladder cancer susceptibility.

    Science.gov (United States)

    Gui, Jiang; Andrew, Angeline S; Andrews, Peter; Nelson, Heather M; Kelsey, Karl T; Karagas, Margaret R; Moore, Jason H

    2011-01-01

    A central goal of human genetics is to identify susceptibility genes for common human diseases. An important challenge is modelling gene-gene interaction or epistasis that can result in nonadditivity of genetic effects. The multifactor dimensionality reduction (MDR) method was developed as a machine learning alternative to parametric logistic regression for detecting interactions in the absence of significant marginal effects. The goal of MDR is to reduce the dimensionality inherent in modelling combinations of polymorphisms using a computational approach called constructive induction. Here, we propose a Robust Multifactor Dimensionality Reduction (RMDR) method that performs constructive induction using a Fisher's Exact Test rather than a predetermined threshold. The advantage of this approach is that only statistically significant genotype combinations are considered in the MDR analysis. We use simulation studies to demonstrate that this approach will increase the success rate of MDR when there are only a few genotype combinations that are significantly associated with case-control status. We show that there is no loss of success rate when this is not the case. We then apply the RMDR method to the detection of gene-gene interactions in genotype data from a population-based study of bladder cancer in New Hampshire. © 2010 The Authors Annals of Human Genetics © 2010 Blackwell Publishing Ltd/University College London.

  13. Identification of Gene-Gene Interactions in the Presence of Missing Data using the Multifactor Dimensionality Reduction Method

    Science.gov (United States)

    Namkung, Junghyun; Elston, Robert C.; Yang, Jun-Mo; Park, Taesung

    2009-01-01

    Gene-gene interaction is believed to play an important role in understanding complex traits. Multifactor dimensionality reduction (MDR) was proposed by Ritchie, et al. [2001] to identify multiple loci that simultaneously affect disease susceptibility. Although the MDR method has been widely used to detect gene-gene interactions, few studies have been reported on MDR analysis when there are missing data. Currently, there are four approaches available in MDR analysis to handle missing data. The first approach uses only complete observations that have no missing data, which can cause a severe loss of data. The second approach is to treat missing values as an additional genotype category, but interpretation of the results may then be not clear and the conclusions may be misleading. Furthermore, it performs poorly when the missing rates are unbalanced between the case and control groups. The third approach is a simple imputation method that imputes missing genotypes as the most frequent genotype, which also may produce biased results. The fourth approach, Available, uses all data available for the given loci, to increase power. In any real data analysis, it is not clear which MDR approach one should use when there are missing data. In this paper, we consider a new EM Impute approach, to handle missing data more appropriately. Through simulation studies, we compared the performance of the proposed EM Impute approach with the current approaches. Our results showed that Available and EM Impute approaches perform better than the three other current approaches in terms of power and precision. PMID:19241410

  14. Parallel multifactor dimensionality reduction: a tool for the large-scale analysis of gene-gene interactions.

    Science.gov (United States)

    Bush, William S; Dudek, Scott M; Ritchie, Marylyn D

    2006-09-01

    Parallel multifactor dimensionality reduction is a tool for large-scale analysis of gene-gene and gene-environment interactions. The MDR algorithm was redesigned to allow an unlimited number of study subjects, total variables and variable states, and to remove restrictions on the order of interactions being analyzed. In addition, the algorithm is markedly more efficient, with approximately 150-fold decrease in runtime for equivalent analyses. To facilitate the processing of large datasets, the algorithm was made parallel. Parallel MDR is freely available for non-commercial research institutions. For full details see http://chgr.mc.vanderbilt.edu/ritchielab/pMDR. An open-source version of MDR software is available at http://www.epistasis.org.

  15. Dopamine transporter DAT and receptor DRD2 variants affect risk of lethal cocaine abuse: a gene-gene-environment interaction.

    Science.gov (United States)

    Sullivan, D; Pinsonneault, J K; Papp, A C; Zhu, H; Lemeshow, S; Mash, D C; Sadee, W

    2013-01-22

    Epistatic gene-gene interactions could contribute to the heritability of complex multigenic disorders, but few examples have been reported. Here, we focus on the role of aberrant dopaminergic signaling, involving the dopamine transporter DAT, a cocaine target, and the dopamine D2 receptor, which physically interacts with DAT. Splicing polymorphism rs2283265 of DRD2, encoding D2 receptors, were shown to confer risk of cocaine overdose/death (odds ratio ∼3) in subjects and controls from the Miami Dade County Brain Bank.(1) Risk of cocaine-related death attributable to the minor allele of rs2283265 was significantly enhanced to OR=7.5 (P=0.0008) in homozygous carriers of the main 6-repeat allele of DAT rs3836790, a regulatory VNTR in intron8 lacking significant effect itself. In contrast, carriers of the minor 5-repeat DAT allele showed no significant risk (OR=1.1, P=0.84). DAT rs3836790 and DRD2 rs2283265 also interacted by modulating DAT protein activity in the ventral putamen of cocaine abusers. In high-linkage disequilibrium with the VNTR, DAT rs6347 in exon9 yielded similar results. Assessing the impact of DAT alone, a rare DAT haplotype formed by the minor alleles of rs3836790 and rs27072, a regulatory DAT variant in the 3'-UTR, occurred in nearly one-third of the cocaine abusers but was absent in African American controls, apparently conferring strong risk. These results demonstrate gene-gene-drug interaction affecting risk of fatal cocaine intoxication.

  16. TOPS: a versatile software tool for statistical analysis and visualization of combinatorial gene-gene and gene-drug interaction screens.

    Science.gov (United States)

    Muellner, Markus K; Duernberger, Gerhard; Ganglberger, Florian; Kerzendorfer, Claudia; Uras, Iris Z; Schoenegger, Andreas; Bagienski, Klaudia; Colinge, Jacques; Nijman, Sebastian M B

    2014-04-08

    Measuring the impact of combinations of genetic or chemical perturbations on cellular fitness, sometimes referred to as synthetic lethal screening, is a powerful method for obtaining novel insights into gene function and drug action. Especially when performed at large scales, gene-gene or gene-drug interaction screens can reveal complex genetic interactions or drug mechanism of action or even identify novel therapeutics for the treatment of diseases.The result of such large-scale screen results can be represented as a matrix with a numeric score indicating the cellular fitness (e.g. viability or doubling time) for each double perturbation. In a typical screen, the majority of combinations do not impact the cellular fitness. Thus, it is critical to first discern true "hits" from noise. Subsequent data exploration and visualization methods can assist to extract meaningful biological information from the data. However, despite the increasing interest in combination perturbation screens, no user friendly open-source program exists that combines statistical analysis, data exploration tools and visualization. We developed TOPS (Tool for Combination Perturbation Screen Analysis), a Java and R-based software tool with a simple graphical user interface that allows the user to import, analyze, filter and plot data from double perturbation screens as well as other compatible data. TOPS was designed in a modular fashion to allow the user to add alternative importers for data formats or custom analysis scripts not covered by the original release.We demonstrate the utility of TOPS on two datasets derived from functional genetic screens using different methods. Dataset 1 is a gene-drug interaction screen and is based on Luminex xMAP technology. Dataset 2 is a gene-gene short hairpin (sh)RNAi screen exploring the interactions between deubiquitinating enzymes and a number of prominent oncogenes using massive parallel sequencing (MPS). TOPS provides the benchtop scientist with a

  17. [Identification of gene-gene interactions related to the etiology of complex disease: a multifactor dimensionality reduction-genotype pedigree disequilibrium test].

    Science.gov (United States)

    Li, Na; Tang, Xun; Chen, Da-fang; Hu, Yong-hua

    2007-10-01

    To introduce the application of a multifactor dimensionality reduction-genotype pedigree disequilibrium test (MDR-PDT) for detecting gene-gene interactions in the etiology of complex disease. A brief overview on the basic theory, implementing steps and features of MDR-PDT were described, and a practical research case was demonstrated to application of MDR-PDT in nuclear family studies. The MDR-PDT approach was the extension or development of conventional MDR method which could be used for detecting gene-gene interactions in families of diverse structure. MDR-PDT was a new nonparametric and model-free method which might use additional family members in the nuclear families and had a good power to identify gene-gene interactions.

  18. Detecting, characterizing, and interpreting nonlinear gene-gene interactions using multifactor dimensionality reduction.

    Science.gov (United States)

    Moore, Jason H

    2010-01-01

    Human health is a complex process that is dependent on many genes, many environmental factors and chance events that are perhaps not measurable with current technology or are simply unknowable. Success in the design and execution of population-based association studies to identify those genetic and environmental factors that play an important role in human disease will depend on our ability to embrace, rather that ignore, complexity in the genotype to phenotype mapping relationship for any given human ecology. We review here three general computational challenges that must be addressed. First, data mining and machine learning methods are needed to model nonlinear interactions between multiple genetic and environmental factors. Second, filter and wrapper methods are needed to identify attribute interactions in large and complex solution landscapes. Third, visualization methods are needed to help interpret computational models and results. We provide here an overview of the multifactor dimensionality reduction (MDR) method that was developed for addressing each of these challenges. Copyright © 2010 Elsevier Inc. All rights reserved.

  19. Power of multifactor dimensionality reduction and penalized logistic regression for detecting gene-gene Interaction in a case-control study

    Science.gov (United States)

    2009-01-01

    Background There is a growing awareness that interaction between multiple genes play an important role in the risk of common, complex multi-factorial diseases. Many common diseases are affected by certain genotype combinations (associated with some genes and their interactions). The identification and characterization of these susceptibility genes and gene-gene interaction have been limited by small sample size and large number of potential interactions between genes. Several methods have been proposed to detect gene-gene interaction in a case control study. The penalized logistic regression (PLR), a variant of logistic regression with L2 regularization, is a parametric approach to detect gene-gene interaction. On the other hand, the Multifactor Dimensionality Reduction (MDR) is a nonparametric and genetic model-free approach to detect genotype combinations associated with disease risk. Methods We compared the power of MDR and PLR for detecting two-way and three-way interactions in a case-control study through extensive simulations. We generated several interaction models with different magnitudes of interaction effect. For each model, we simulated 100 datasets, each with 200 cases and 200 controls and 20 SNPs. We considered a wide variety of models such as models with just main effects, models with only interaction effects or models with both main and interaction effects. We also compared the performance of MDR and PLR to detect gene-gene interaction associated with acute rejection(AR) in kidney transplant patients. Results In this paper, we have studied the power of MDR and PLR for detecting gene-gene interaction in a case-control study through extensive simulation. We have compared their performances for different two-way and three-way interaction models. We have studied the effect of different allele frequencies on these methods. We have also implemented their performance on a real dataset. As expected, none of these methods were consistently better for all

  20. Power of multifactor dimensionality reduction and penalized logistic regression for detecting gene-gene Interaction in a case-control study

    Directory of Open Access Journals (Sweden)

    Brott Marcia J

    2009-12-01

    Full Text Available Abstract Background There is a growing awareness that interaction between multiple genes play an important role in the risk of common, complex multi-factorial diseases. Many common diseases are affected by certain genotype combinations (associated with some genes and their interactions. The identification and characterization of these susceptibility genes and gene-gene interaction have been limited by small sample size and large number of potential interactions between genes. Several methods have been proposed to detect gene-gene interaction in a case control study. The penalized logistic regression (PLR, a variant of logistic regression with L2 regularization, is a parametric approach to detect gene-gene interaction. On the other hand, the Multifactor Dimensionality Reduction (MDR is a nonparametric and genetic model-free approach to detect genotype combinations associated with disease risk. Methods We compared the power of MDR and PLR for detecting two-way and three-way interactions in a case-control study through extensive simulations. We generated several interaction models with different magnitudes of interaction effect. For each model, we simulated 100 datasets, each with 200 cases and 200 controls and 20 SNPs. We considered a wide variety of models such as models with just main effects, models with only interaction effects or models with both main and interaction effects. We also compared the performance of MDR and PLR to detect gene-gene interaction associated with acute rejection(AR in kidney transplant patients. Results In this paper, we have studied the power of MDR and PLR for detecting gene-gene interaction in a case-control study through extensive simulation. We have compared their performances for different two-way and three-way interaction models. We have studied the effect of different allele frequencies on these methods. We have also implemented their performance on a real dataset. As expected, none of these methods were

  1. Power of multifactor dimensionality reduction and penalized logistic regression for detecting gene-gene interaction in a case-control study.

    Science.gov (United States)

    He, Hua; Oetting, William S; Brott, Marcia J; Basu, Saonli

    2009-12-04

    There is a growing awareness that interaction between multiple genes play an important role in the risk of common, complex multi-factorial diseases. Many common diseases are affected by certain genotype combinations (associated with some genes and their interactions). The identification and characterization of these susceptibility genes and gene-gene interaction have been limited by small sample size and large number of potential interactions between genes. Several methods have been proposed to detect gene-gene interaction in a case control study. The penalized logistic regression (PLR), a variant of logistic regression with L2 regularization, is a parametric approach to detect gene-gene interaction. On the other hand, the Multifactor Dimensionality Reduction (MDR) is a nonparametric and genetic model-free approach to detect genotype combinations associated with disease risk. We compared the power of MDR and PLR for detecting two-way and three-way interactions in a case-control study through extensive simulations. We generated several interaction models with different magnitudes of interaction effect. For each model, we simulated 100 datasets, each with 200 cases and 200 controls and 20 SNPs. We considered a wide variety of models such as models with just main effects, models with only interaction effects or models with both main and interaction effects. We also compared the performance of MDR and PLR to detect gene-gene interaction associated with acute rejection(AR) in kidney transplant patients. In this paper, we have studied the power of MDR and PLR for detecting gene-gene interaction in a case-control study through extensive simulation. We have compared their performances for different two-way and three-way interaction models. We have studied the effect of different allele frequencies on these methods. We have also implemented their performance on a real dataset. As expected, none of these methods were consistently better for all data scenarios, but, generally

  2. Identification of gene-gene interactions in the presence of missing data using the multifactor dimensionality reduction method.

    Science.gov (United States)

    Namkung, Junghyun; Elston, Robert C; Yang, Jun-Mo; Park, Taesung

    2009-11-01

    Gene-gene interaction is believed to play an important role in understanding complex traits. Multifactor dimensionality reduction (MDR) was proposed by Ritchie et al. [2001. Am J Hum Genet 69:138-147] to identify multiple loci that simultaneously affect disease susceptibility. Although the MDR method has been widely used to detect gene-gene interactions, few studies have been reported on MDR analysis when there are missing data. Currently, there are four approaches available in MDR analysis to handle missing data. The first approach uses only complete observations that have no missing data, which can cause a severe loss of data. The second approach is to treat missing values as an additional genotype category, but interpretation of the results may then be not clear and the conclusions may be misleading. Furthermore, it performs poorly when the missing rates are unbalanced between the case and control groups. The third approach is a simple imputation method that imputes missing genotypes as the most frequent genotype, which may also produce biased results. The fourth approach, Available, uses all data available for the given loci to increase power. In any real data analysis, it is not clear which MDR approach one should use when there are missing data. In this article, we consider a new EM Impute approach to handle missing data more appropriately. Through simulation studies, we compared the performance of the proposed EM Impute approach with the current approaches. Our results showed that Available and EM Impute approaches perform better than the three other current approaches in terms of power and precision.

  3. A model of gene-gene and gene-environment interactions and its implications for targeting environmental interventions by genotype.

    Science.gov (United States)

    Wallace, Helen M

    2006-10-09

    The potential public health benefits of targeting environmental interventions by genotype depend on the environmental and genetic contributions to the variance of common diseases, and the magnitude of any gene-environment interaction. In the absence of prior knowledge of all risk factors, twin, family and environmental data may help to define the potential limits of these benefits in a given population. However, a general methodology to analyze twin data is required because of the potential importance of gene-gene interactions (epistasis), gene-environment interactions, and conditions that break the 'equal environments' assumption for monozygotic and dizygotic twins. A new model for gene-gene and gene-environment interactions is developed that abandons the assumptions of the classical twin study, including Fisher's (1918) assumption that genes act as risk factors for common traits in a manner necessarily dominated by an additive polygenic term. Provided there are no confounders, the model can be used to implement a top-down approach to quantifying the potential utility of genetic prediction and prevention, using twin, family and environmental data. The results describe a solution space for each disease or trait, which may or may not include the classical twin study result. Each point in the solution space corresponds to a different model of genotypic risk and gene-environment interaction. The results show that the potential for reducing the incidence of common diseases using environmental interventions targeted by genotype may be limited, except in special cases. The model also confirms that the importance of an individual's genotype in determining their risk of complex diseases tends to be exaggerated by the classical twin studies method, owing to the 'equal environments' assumption and the assumption of no gene-environment interaction. In addition, if phenotypes are genetically robust, because of epistasis, a largely environmental explanation for shared sibling

  4. Systematic Search for Gene-Gene Interaction Effect on Prostate Cancer Risk

    Science.gov (United States)

    2013-07-01

    interact to have stronger effects on PCa risk. 3 4) (Months 3-12) Bayesian epistasis association mapping (BEAM) to identify pairs of SNPs that...in the signaling network that is crucial for the well-being of prostatic cells whereas the genetic variants located within these two genes may...implicated in the top hits of interactions in Type 1 Diabetes and Type 2 Diabetes displayed weak main effects [44,45]. Culverhouse et al. also

  5. Quantitative Multifactor Dimensionality Reduction Method for Detecting Gene-Gene Interaction

    Science.gov (United States)

    Gilbert-Diamond, Diane; Andrews, Peter; Moore, Jason H.; Gui, Jiang

    2013-01-01

    Background and Objective: The problem of identifying SNP-SNP interactions in case-control studies has been studied extensively and a number of new techniques have been developed. Little progress has been made, however in the analysis of SNP-SNP interactions in relation to continuous data. Methods: We present an extension of the two class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of Quantitative trait. The proposed Quantitative MDR (Quant-MDR) method handles continuous data by modifying MDR's constructive induction algorithm to use T Test. Results: We then applied Quant-MDR to genetic data from the ongoing prospective Prevention of Renal and Vascular End-Stage Disease (PREVEND) study. We identified that BR2_58CT&ATR1AC is the top SNP-SNP interaction that assciated with Tissue plasminogen activator (tPA) level for male and ACEID&BRB2EX1 is the top interaction for female tPA expression. Discussion and Conclusions: Quant-MDR is capable of detecting interaction models with weak main effects. These epistatic models tend to be dropped by traditional linear regression approaches. With improved efficiency to handle genome wide datasets, Quant-MDR will play an important role in a research strategy that embraces the complexity of the genotype-phenotype mapping relationship.

  6. Evidence for plasticity genotypes in a gene-gene-environment interaction : the TRAILS study

    NARCIS (Netherlands)

    Nederhof, E; Bouma, Esther; Riese, Harriette; Laceulle, Odilia; Ormel, J.; Oldehinkel, A.J.

    2010-01-01

    The purpose was to study how functional polymorphisms in the brain derived neurotrophic factor gene (BDNF val66met) and the serotonin transporter gene linked promotor region (5-HTTLPR) interact with childhood adversities in predicting Effortful Control. Effortful Control refers to the ability to

  7. Exploring Plant Co-Expression and Gene-Gene Interactions with CORNET 3.0.

    Science.gov (United States)

    Van Bel, Michiel; Coppens, Frederik

    2017-01-01

    Selecting and filtering a reference expression and interaction dataset when studying specific pathways and regulatory interactions can be a very time-consuming and error-prone task. In order to reduce the duplicated efforts required to amass such datasets, we have created the CORNET (CORrelation NETworks) platform which allows for easy access to a wide variety of data types: coexpression data, protein-protein interactions, regulatory interactions, and functional annotations. The CORNET platform outputs its results in either text format or through the Cytoscape framework, which is automatically launched by the CORNET website.CORNET 3.0 is the third iteration of the web platform designed for the user exploration of the coexpression space of plant genomes, with a focus on the model species Arabidopsis thaliana. Here we describe the platform: the tools, data, and best practices when using the platform. We indicate how the platform can be used to infer networks from a set of input genes, such as upregulated genes from an expression experiment. By exploring the network, new target and regulator genes can be discovered, allowing for follow-up experiments and more in-depth study. We also indicate how to avoid common pitfalls when evaluating the networks and how to avoid over interpretation of the results.All CORNET versions are available at http://bioinformatics.psb.ugent.be/cornet/ .

  8. Evidence of gene-gene interaction and age-at-diagnosis effects in type 1 diabetes

    DEFF Research Database (Denmark)

    Howson, Joanna M M; Cooper, Jason D; Smyth, Deborah J

    2012-01-01

    The common genetic loci that independently influence the risk of type 1 diabetes have largely been determined. Their interactions with age-at-diagnosis of type 1 diabetes, sex, or the major susceptibility locus, HLA class II, remain mostly unexplored. A large collection of more than 14,866 type 1...

  9. Comparison of information-theoretic to statistical methods for gene-gene interactions in the presence of genetic heterogeneity

    Directory of Open Access Journals (Sweden)

    Sucheston Lara

    2010-09-01

    Full Text Available Abstract Background Multifactorial diseases such as cancer and cardiovascular diseases are caused by the complex interplay between genes and environment. The detection of these interactions remains challenging due to computational limitations. Information theoretic approaches use computationally efficient directed search strategies and thus provide a feasible solution to this problem. However, the power of information theoretic methods for interaction analysis has not been systematically evaluated. In this work, we compare power and Type I error of an information-theoretic approach to existing interaction analysis methods. Methods The k-way interaction information (KWII metric for identifying variable combinations involved in gene-gene interactions (GGI was assessed using several simulated data sets under models of genetic heterogeneity driven by susceptibility increasing loci with varying allele frequency, penetrance values and heritability. The power and proportion of false positives of the KWII was compared to multifactor dimensionality reduction (MDR, restricted partitioning method (RPM and logistic regression. Results The power of the KWII was considerably greater than MDR on all six simulation models examined. For a given disease prevalence at high values of heritability, the power of both RPM and KWII was greater than 95%. For models with low heritability and/or genetic heterogeneity, the power of the KWII was consistently greater than RPM; the improvements in power for the KWII over RPM ranged from 4.7% to 14.2% at for α = 0.001 in the three models at the lowest heritability values examined. KWII performed similar to logistic regression. Conclusions Information theoretic models are flexible and have excellent power to detect GGI under a variety of conditions that characterize complex diseases.

  10. GENIE: a software package for gene-gene interaction analysis in genetic association studies using multiple GPU or CPU cores

    Directory of Open Access Journals (Sweden)

    Wang Kai

    2011-05-01

    Full Text Available Abstract Background Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs have multiple cores, whereas Graphics Processing Units (GPUs also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic interaction analysis for binary traits. Findings Here we present a novel software package GENIE, which utilizes the power of multiple GPU or CPU processor cores to parallelize the interaction analysis. GENIE reads an entire genetic association study dataset into memory and partitions the dataset into fragments with non-overlapping sets of SNPs. For each fragment, GENIE analyzes: 1 the interaction of SNPs within it in parallel, and 2 the interaction between the SNPs of the current fragment and other fragments in parallel. We tested GENIE on a large-scale candidate gene study on high-density lipoprotein cholesterol. Using an NVIDIA Tesla C1060 graphics card, the GPU mode of GENIE achieves a speedup of 27 times over its single-core CPU mode run. Conclusions GENIE is open-source, economical, user-friendly, and scalable. Since the computing power and memory capacity of graphics cards are increasing rapidly while their cost is going down, we anticipate that GENIE will achieve greater speedups with faster GPU cards. Documentation, source code, and precompiled binaries can be downloaded from http://www.cceb.upenn.edu/~mli/software/GENIE/.

  11. MDM2 SNP309, gene-gene interaction, and tumor susceptibility: an updated meta-analysis

    Directory of Open Access Journals (Sweden)

    Wu Wei

    2011-05-01

    Full Text Available Abstract Background The tumor suppressor gene p53 is involved in multiple cellular pathways including apoptosis, transcriptional control, and cell cycle regulation. In the last decade it has been demonstrated that the single nucleotide polymorphism (SNP at codon 72 of the p53 gene is associated with the risk for development of various neoplasms. MDM2 SNP309 is a single nucleotide T to G polymorphism located in the MDM2 gene promoter. From the time that this well-characterized functional polymorphism was identified, a variety of case-control studies have been published that investigate the possible association between MDM2 SNP309 and cancer risk. However, the results of the published studies, as well as the subsequent meta-analyses, remain contradictory. Methods To investigate whether currently published epidemiological studies can clarify the potential interaction between MDM2 SNP309 and the functional genetic variant in p53 codon72 (Arg72Pro and p53 mutation status, we performed a meta-analysis of the risk estimate on 27,813 cases with various tumor types and 30,295 controls. Results The data we reviewed indicated that variant homozygote 309GG and heterozygote 309TG were associated with a significant increased risk of all tumor types (homozygote comparison: odds ratio (OR = 1.25, 95% confidence interval (CI = 1.13-1.37; heterozygote comparison: OR = 1.10, 95% CI = 1.03-1.17. We also found that the combination of GG and Pro/Pro, TG and Pro/Pro, GG and Arg/Arg significantly increased the risk of cancer (OR = 3.38, 95% CI = 1.77-6.47; OR = 1.88, 95% CI = 1.26-2.81; OR = 1.96, 95% CI = 1.01-3.78, respectively. In a stratified analysis by tumor location, we also found a significant increased risk in brain, liver, stomach and uterus cancer (OR = 1.47, 95% CI = 1.06-2.03; OR = 2.24, 95%CI = 1.57-3.18; OR = 1.54, 95%CI = 1.04-2.29; OR = 1.34, 95%CI = 1.07-1.29, respectively. However, no association was seen between MDM2 SNP309 and tumor susceptibility

  12. MDM2 SNP309, gene-gene interaction, and tumor susceptibility: an updated meta-analysis

    International Nuclear Information System (INIS)

    Wan, Yan; Wu, Wei; Yin, Zhihua; Guan, Peng; Zhou, Baosen

    2011-01-01

    The tumor suppressor gene p53 is involved in multiple cellular pathways including apoptosis, transcriptional control, and cell cycle regulation. In the last decade it has been demonstrated that the single nucleotide polymorphism (SNP) at codon 72 of the p53 gene is associated with the risk for development of various neoplasms. MDM2 SNP309 is a single nucleotide T to G polymorphism located in the MDM2 gene promoter. From the time that this well-characterized functional polymorphism was identified, a variety of case-control studies have been published that investigate the possible association between MDM2 SNP309 and cancer risk. However, the results of the published studies, as well as the subsequent meta-analyses, remain contradictory. To investigate whether currently published epidemiological studies can clarify the potential interaction between MDM2 SNP309 and the functional genetic variant in p53 codon72 (Arg72Pro) and p53 mutation status, we performed a meta-analysis of the risk estimate on 27,813 cases with various tumor types and 30,295 controls. The data we reviewed indicated that variant homozygote 309GG and heterozygote 309TG were associated with a significant increased risk of all tumor types (homozygote comparison: odds ratio (OR) = 1.25, 95% confidence interval (CI) = 1.13-1.37; heterozygote comparison: OR = 1.10, 95% CI = 1.03-1.17). We also found that the combination of GG and Pro/Pro, TG and Pro/Pro, GG and Arg/Arg significantly increased the risk of cancer (OR = 3.38, 95% CI = 1.77-6.47; OR = 1.88, 95% CI = 1.26-2.81; OR = 1.96, 95% CI = 1.01-3.78, respectively). In a stratified analysis by tumor location, we also found a significant increased risk in brain, liver, stomach and uterus cancer (OR = 1.47, 95% CI = 1.06-2.03; OR = 2.24, 95%CI = 1.57-3.18; OR = 1.54, 95%CI = 1.04-2.29; OR = 1.34, 95%CI = 1.07-1.29, respectively). However, no association was seen between MDM2 SNP309 and tumor susceptibility in the stratified analysis by p53 mutation status

  13. Gene-gene interactions of fatty acid synthase (FASN) using multifactor-dimensionality reduction method in Korean cattle.

    Science.gov (United States)

    Lee, Jeayoung; Jin, Mehyun; Lee, Yoonseok; Ha, Jaejung; Yeo, Jungsou; Oh, Dongyep

    2014-01-01

    We examined the gene-gene interactions of five exonic single nucleotide polymorphisms (SNPs) in the gene encoding fatty acid synthase using 513 Korean cattle and using the model free and the non-parametrical multifactor dimensionality reduction method for the analysis. The five SNPs of g.12870 T>C, g.13126 T>C, g.15532 C>A, g.16907 T>C and g.17924 G>A associated with a variety of fatty acid compositions and marbling score were used in this study. The two-factor interaction between g.13126 T>C and g.15532 C>A had the highest training-balanced among the five-factor models and a testing-balanced accuracy at 70.18 % on C18:1 with a cross-validation consistency of 10 out of 10. Also, the two-factor interaction between g.13126 T>C and g.15532 C>A had the highest testing-balanced accuracy at 68.59 % with a 10 out of 10 cross-validation consistency, than any other models on MUFA. In MS, a single SNP g.15532 C>A had the best accuracy at 58.85 % and the two-factor interaction model g.12870 T>C and g.15532 C>A had the highest testing-balanced accuracy at 64.00 %. The three-factor interaction model g.12870 T>C, g.13126 T>C and g.15532 C>A was recorded as having a high testing-balanced accuracy of 63.24 %, but it was lower than the two-factor interaction model. We used likelihood ratio tests for interaction, and Chi square tests to validate our results, with all tests showing statistical significance. We also compared this with mean scores between the high-risk trait group and low-risk trait group. The genotypes of TTCA, TTAA and TCAA at g.15532 and g.13126 on C18:1, genotypes TTCC, TTCA, TTAA, TCAA CCAA at g.15532 and g.13126 on MUFA and genotypes CCCC, TCCA, CCCA, TTAA, TCAA and CCAA at g.15532 and g.12870 on MS were recommended for the genetic improvement of beef quality.

  14. A Comparison of Multifactor Dimensionality Reduction and L1-Penalized Regression to Identify Gene-Gene Interactions in Genetic Association Studies*

    Science.gov (United States)

    Winham, Stacey; Wang, Chong; Motsinger-Reif, Alison A

    2011-01-01

    Recently, the amount of high-dimensional data has exploded, creating new analytical challenges for human genetics. Furthermore, much evidence suggests that common complex diseases may be due to complex etiologies such as gene-gene interactions, which are difficult to identify in high-dimensional data using traditional statistical approaches. Data-mining approaches are gaining popularity for variable selection in association studies, and one of the most commonly used methods to evaluate potential gene-gene interactions is Multifactor Dimensionality Reduction (MDR). Additionally, a number of penalized regression techniques, such as Lasso, are gaining popularity within the statistical community and are now being applied to association studies, including extensions for interactions. In this study, we compare the performance of MDR, the traditional lasso with L1 penalty (TL1), and the group lasso for categorical data with group-wise L1 penalty (GL1) to detect gene-gene interactions through a broad range of simulations. We find that each method has both advantages and disadvantages, and relative performance is context dependent. TL1 frequently over-fits, identifying false positive as well as true positive loci. MDR has higher power for epistatic models that exhibit independent main effects; for both Lasso methods, main effects tend to dominate. For purely epistatic models, GL1 has the best performance for lower minor allele frequencies, but MDR performs best for higher frequencies. These results provide guidance of when each approach might be best suited for detecting and characterizing interactions with different mechanisms. PMID:21291414

  15. A comparison of multifactor dimensionality reduction and L1-penalized regression to identify gene-gene interactions in genetic association studies.

    Science.gov (United States)

    Winham, Stacey; Wang, Chong; Motsinger-Reif, Alison A

    2011-01-01

    Recently, the amount of high-dimensional data has exploded, creating new analytical challenges for human genetics. Furthermore, much evidence suggests that common complex diseases may be due to complex etiologies such as gene-gene interactions, which are difficult to identify in high-dimensional data using traditional statistical approaches. Data-mining approaches are gaining popularity for variable selection in association studies, and one of the most commonly used methods to evaluate potential gene-gene interactions is Multifactor Dimensionality Reduction (MDR). Additionally, a number of penalized regression techniques, such as Lasso, are gaining popularity within the statistical community and are now being applied to association studies, including extensions for interactions. In this study, we compare the performance of MDR, the traditional lasso with L1 penalty (TL1), and the group lasso for categorical data with group-wise L1 penalty (GL1) to detect gene-gene interactions through a broad range of simulations. We find that each method has both advantages and disadvantages, and relative performance is context dependent. TL1 frequently over-fits, identifying false positive as well as true positive loci. MDR has higher power for epistatic models that exhibit independent main effects; for both Lasso methods, main effects tend to dominate. For purely epistatic models, GL1 has the best performance for lower minor allele frequencies, but MDR performs best for higher frequencies. These results provide guidance of when each approach might be best suited for detecting and characterizing interactions with different mechanisms.

  16. Power of multifactor dimensionality reduction for detecting gene-gene interactions in the presence of genotyping error, missing data, phenocopy, and genetic heterogeneity.

    Science.gov (United States)

    Ritchie, Marylyn D; Hahn, Lance W; Moore, Jason H

    2003-02-01

    The identification and characterization of genes that influence the risk of common, complex multifactorial diseases, primarily through interactions with other genes and other environmental factors, remains a statistical and computational challenge in genetic epidemiology. This challenge is partly due to the limitations of parametric statistical methods for detecting genetic effects that are dependent solely or partially on interactions with other genes and environmental exposures. We previously introduced multifactor dimensionality reduction (MDR) as a method for reducing the dimensionality of multilocus genotype information to improve the identification of polymorphism combinations associated with disease risk. The MDR approach is nonparametric (i.e., no hypothesis about the value of a statistical parameter is made), is model-free (i.e., assumes no particular inheritance model), and is directly applicable to case-control and discordant sib-pair study designs. Both empirical and theoretical studies suggest that MDR has excellent power for identifying high-order gene-gene interactions. However, the power of MDR for identifying gene-gene interactions in the presence of common sources of noise is not currently known. The goal of this study was to evaluate the power of MDR for identifying gene-gene interactions in the presence of noise due to genotyping error, missing data, phenocopy, and genetic or locus heterogeneity. Using simulated data, we show that MDR has high power to identify gene-gene interactions in the presence of 5% genotyping error, 5% missing data, or a combination of both. However, MDR has reduced power for some models in the presence of 50% phenocopy, and very limited power in the presence of 50% genetic heterogeneity. Extending MDR to address genetic heterogeneity should be a priority for the continued methodological development of this new approach. Copyright 2003 Wiley-Liss, Inc.

  17. Gene-gene-environment interactions between drugs, transporters, receptors, and metabolizing enzymes: Statins, SLCO1B1, and CYP3A4 as an example.

    Science.gov (United States)

    Sadee, Wolfgang

    2013-09-01

    Pharmacogenetic biomarker tests include mostly specific single gene-drug pairs, capable of accounting for a portion of interindividual variability in drug response and toxicity. However, multiple genes are likely to contribute, either acting independently or epistatically, with the CYP2C9-VKORC1-warfarin test panel, an example of a clinically used gene-gene-dug interaction. I discuss here further instances of gene-gene-drug interactions, including a proposed dynamic effect on statin therapy by genetic variants in both a transporter (SLCO1B1) and a metabolizing enzyme (CYP3A4) in liver cells, the main target site where statins block cholesterol synthesis. These examples set a conceptual framework for developing diagnostic panels involving multiple gene-drug combinations. Copyright © 2013 Wiley Periodicals, Inc.

  18. A gene-gene interaction between polymorphisms in the OCT2 and MATE1 genes influences the renal clearance of metformin

    DEFF Research Database (Denmark)

    Hougaard Christensen, Mette Marie; Pedersen, Rasmus Steen; Stage, Tore Bjerregaard

    2013-01-01

    The aim of this study was to determine the association between the renal clearance (CL(renal)) of metformin in healthy Caucasian volunteers and the single-nucleotide polymorphism (SNP) c.808G>T (rs316019) in OCT2 as well as the relevance of the gene-gene interactions between this SNP and (a......) the promoter SNP g.-66T>C (rs2252281) in MATE1 and (b) the OCT1 reduced-function diplotypes....

  19. Gene-gene interaction between MSX1 and TP63 in Asian case-parent trios with nonsyndromic cleft lip with or without cleft palate.

    Science.gov (United States)

    Liu, Dongjing; Schwender, Holger; Wang, Mengying; Wang, Hong; Wang, Ping; Zhu, Hongping; Zhou, Zhibo; Li, Jing; Wu, Tao; Beaty, Terri H

    2018-03-01

    Small ubiquitin-like modification, also known as sumoylation, is a crucial post-translational regulatory mechanisms involved in development of the lip and palate. Recent studies reported two sumoylation target genes, MSX1 and TP63, to have achieved genome-wide level significance in tests of association with nonsyndromic clefts. Here, we performed a candidate gene analysis considering gene-gene and gene-environment interaction for SUMO1, MSX1, and TP63 to further explore the etiology of nonsyndromic cleft lip with or without cleft palate (NSCL/P). A total of 130 single-nucleotide polymorphisms (SNPs) in or near SUMO1, MSX1, and TP63 was analyzed among 1,038 Asian NSCL/P trios ascertained through an international consortium. Conditional logistic regression models were used to explore gene-gene (G × G) and gene-environment (G × E) interaction involving maternal environmental tobacco smoke and multivitamin supplementation. Bonferroni correction was used for G × E analysis and permutation tests were used for G × G analysis. While transmission disequilibrium tests and gene-environment interaction analysis showed no significant results, we did find signals of gene-gene interaction between SNPs near MSX1 and TP63. Three pairwise interactions yielded significant p values in permutation tests (rs884690 and rs9290890 with p = 9.34 × 10 -5 and empirical p = 1.00 × 10 -4 , rs1022136 and rs4687098 with p = 2.41 × 10 -4 and empirical p = 2.95 × 10 -4 , rs6819546 and rs9681004 with p = 5.15 × 10 -4 and empirical p = 3.02 × 10 -4 ). Gene-gene interaction between MSX1 and TP63 may influence the risk of NSCL/P in Asian populations. Our study provided additional understanding of the genetic etiology of NSCL/P and underlined the importance of considering gene-gene interaction in the etiology of this common craniofacial malformation. © 2018 Wiley Periodicals, Inc.

  20. Gene-gene interaction and functional impact of polymorphisms on innate immune genes in controlling Plasmodium falciparum blood infection level.

    Directory of Open Access Journals (Sweden)

    Madhumita Basu

    Full Text Available Genetic variations in toll-like receptors and cytokine genes of the innate immune pathways have been implicated in controlling parasite growth and the pathogenesis of Plasmodium falciparum mediated malaria. We previously published genetic association of TLR4 non-synonymous and TNF-α promoter polymorphisms with P.falciparum blood infection level and here we extend the study considerably by (i investigating genetic dependence of parasite-load on interleukin-12B polymorphisms, (ii reconstructing gene-gene interactions among candidate TLRs and cytokine loci, (iii exploring genetic and functional impact of epistatic models and (iv providing mechanistic insights into functionality of disease-associated regulatory polymorphisms. Our data revealed that carriage of AA (P = 0.0001 and AC (P = 0.01 genotypes of IL12B 3'UTR polymorphism was associated with a significant increase of mean log-parasitemia relative to rare homozygous genotype CC. Presence of IL12B+1188 polymorphism in five of six multifactor models reinforced its strong genetic impact on malaria phenotype. Elevation of genetic risk in two-component models compared to the corresponding single locus and reduction of IL12B (2.2 fold and lymphotoxin-α (1.7 fold expressions in patients'peripheral-blood-mononuclear-cells under TLR4Thr399Ile risk genotype background substantiated the role of Multifactor Dimensionality Reduction derived models. Marked reduction of promoter activity of TNF-α risk haplotype (C-C-G-G compared to wild-type haplotype (T-C-G-G with (84% and without (78% LPS stimulation and the loss of binding of transcription factors detected in-silico supported a causal role of TNF-1031. Significantly lower expression of IL12B+1188 AA (5 fold and AC (9 fold genotypes compared to CC and under-representation (P = 0.0048 of allele A in transcripts of patients' PBMCs suggested an Allele-Expression-Imbalance. Allele (A+1188C dependent differential stability (2 fold of IL12B-transcripts upon

  1. The Cumulative Effect of Gene-Gene and Gene-Environment Interactions on the Risk of Prostate Cancer in Chinese Men

    Directory of Open Access Journals (Sweden)

    Ming Liu

    2016-01-01

    Full Text Available Prostate cancer (PCa is a multifactorial disease involving complex genetic and environmental factors interactions. Gene-gene and gene-environment interactions associated with PCa in Chinese men are less studied. We explored the association between 36 SNPs and PCa in 574 subjects from northern China. Body mass index (BMI, smoking, and alcohol consumption were determined through self-administered questionnaires in 134 PCa patients. Then gene-gene and gene-environment interactions among the PCa-associated SNPs were analyzed using the generalized multifactor dimensionality reduction (GMDR and logistic regression methods. Allelic and genotypic association analyses showed that six variants were associated with PCa and the cumulative effect suggested men who carried any combination of 1, 2, or ≥3 risk genotypes had a gradually increased PCa risk (odds ratios (ORs = 1.79–4.41. GMDR analysis identified the best gene-gene interaction model with scores of 10 for both the cross-validation consistency and sign tests. For gene-environment interactions, rs6983561 CC and rs16901966 GG in individuals with a BMI ≥ 28 had ORs of 7.66 (p = 0.032 and 5.33 (p = 0.046, respectively. rs7679673 CC + CA and rs12653946 TT in individuals that smoked had ORs of 2.77 (p = 0.007 and 3.11 (p = 0.024, respectively. rs7679673 CC in individuals that consumed alcohol had an OR of 4.37 (p = 0.041. These results suggest that polymorphisms, either individually or by interacting with other genes or environmental factors, contribute to an increased risk of PCa.

  2. Gene-Gene and Gene-Environment Interactions Involving HLA-DRB1, PTPN22, and Smoking in Two Subsets of Rheumatoid Arthritis

    Science.gov (United States)

    Källberg, Henrik; Padyukov, Leonid; Plenge, Robert M.; Rönnelid, Johan; Gregersen, Peter K.; van der Helm-van Mil, Annette H. M.; Toes, Rene E. M.; Huizinga, Tom W.; Klareskog, Lars; Alfredsson, Lars

    2007-01-01

    Gene-gene and gene-environment interactions are key features in the development of rheumatoid arthritis (RA) and other complex diseases. The aim of this study was to use and compare three different definitions of interaction between the two major genetic risk factors of RA—the HLA-DRB1 shared epitope (SE) alleles and the PTPN22 R620W allele—in three large case-control studies: the Swedish Epidemiological Investigation of Rheumatoid Arthritis (EIRA) study, the North American RA Consortium (NARAC) study, and the Dutch Leiden Early Arthritis Clinic study (in total, 1,977 cases and 2,405 controls). The EIRA study was also used to analyze interactions between smoking and the two genes. “Interaction” was defined either as a departure from additivity, as interaction in a multiplicative model, or in terms of linkage disequilibrium—for example, deviation from independence of penetrance of two unlinked loci. Consistent interaction, defined as departure from additivity, between HLA-DRB1 SE alleles and the A allele of PTPN22 R620W was seen in all three studies regarding anti-CCP–positive RA. Testing for multiplicative interactions demonstrated an interaction between the two genes only when the three studies were pooled. The linkage disequilibrium approach indicated a gene-gene interaction in EIRA and NARAC, as well as in the pooled analysis. No interaction was seen between smoking and PTPN22 R620W. A new pattern of interactions is described between the two major known genetic risk factors and the major environmental risk factor concerning the risk of developing anti-CCP–positive RA. The data extend the basis for a pathogenetic hypothesis for RA involving genetic and environmental factors. The study also raises and illustrates principal questions concerning ways to define interactions in complex diseases. PMID:17436241

  3. Glutathione S-transferase P1, gene-gene interaction, and lung cancer susceptibility in the Chinese population: An updated meta-analysis and review

    Directory of Open Access Journals (Sweden)

    Xue-Ming Li

    2015-01-01

    Full Text Available Aim of Study: To assess the impact of glutathione S-transferase P1 (GSTP1 Ile105Val polymorphism on the risk of lung cancer in the Chinese population, an updated meta-analysis and review was performed. Materials and Methods: Relevant studies were identified from PubMed, Springer Link, Ovid, Chinese Wanfang Data Knowledge Service Platform, Chinese National Knowledge Infrastructure, and Chinese Biology Medicine published through January 22, 2015. The odds ratios (ORs and 95% confidence intervals (CIs were calculated to estimate the strength of the associations. Results: A total of 13 case-control studies, including 2026 lung cancer cases and 2451 controls, were included in this meta-analysis. Overall, significantly increased lung cancer risk was associated with the variant genotypes of GSTP1 polymorphism in the Chinese population (GG vs. AA: OR = 1.36, 95% CI = 1.01-1.84. In subgroup analyses stratified by geographic area and source of controls, the significant results were found in population-based studies (GG vs. AA: OR = 1.62, 95% CI: 1.13-2.31; GG vs. AG: OR = 1.49, 95% CI: 1.03-2.16; GG vs. AA + AG: OR = 1.55, 95% CI: 1.12-2.26. A gene-gene interaction analysis showed that there was an interaction for individuals with combination of GSTM1 (or GSTT1 null genotype and GSTP1 (AG + GG mutant genotype for lung cancer risk in Chinese. Conclusion: This meta-analysis suggests that GSTP1 Ile105Val polymorphism may increase the risk of lung cancer in the Chinese population.

  4. A novel survival multifactor dimensionality reduction method for detecting gene-gene interactions with application to bladder cancer prognosis.

    Science.gov (United States)

    Gui, Jiang; Moore, Jason H; Kelsey, Karl T; Marsit, Carmen J; Karagas, Margaret R; Andrew, Angeline S

    2011-01-01

    The widespread use of high-throughput methods of single nucleotide polymorphism (SNP) genotyping has created a number of computational and statistical challenges. The problem of identifying SNP-SNP interactions in case-control studies has been studied extensively, and a number of new techniques have been developed. Little progress has been made, however, in the analysis of SNP-SNP interactions in relation to time-to-event data, such as patient survival time or time to cancer relapse. We present an extension of the two class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of survival analysis. The proposed Survival MDR (Surv-MDR) method handles survival data by modifying MDR's constructive induction algorithm to use the log-rank test. Surv-MDR replaces balanced accuracy with log-rank test statistics as the score to determine the best models. We simulated datasets with a survival outcome related to two loci in the absence of any marginal effects. We compared Surv-MDR with Cox-regression for their ability to identify the true predictive loci in these simulated data. We also used this simulation to construct the empirical distribution of Surv-MDR's testing score. We then applied Surv-MDR to genetic data from a population-based epidemiologic study to find prognostic markers of survival time following a bladder cancer diagnosis. We identified several two-loci SNP combinations that have strong associations with patients' survival outcome. Surv-MDR is capable of detecting interaction models with weak main effects. These epistatic models tend to be dropped by traditional Cox regression approaches to evaluating interactions. With improved efficiency to handle genome wide datasets, Surv-MDR will play an important role in a research strategy that embraces the complexity of the genotype-phenotype mapping relationship since epistatic interactions are an important component of the

  5. Multivariate dimensionality reduction approaches to identify gene-gene and gene-environment interactions underlying multiple complex traits.

    Science.gov (United States)

    Xu, Hai-Ming; Sun, Xi-Wei; Qi, Ting; Lin, Wan-Yu; Liu, Nianjun; Lou, Xiang-Yang

    2014-01-01

    The elusive but ubiquitous multifactor interactions represent a stumbling block that urgently needs to be removed in searching for determinants involved in human complex diseases. The dimensionality reduction approaches are a promising tool for this task. Many complex diseases exhibit composite syndromes required to be measured in a cluster of clinical traits with varying correlations and/or are inherently longitudinal in nature (changing over time and measured dynamically at multiple time points). A multivariate approach for detecting interactions is thus greatly needed on the purposes of handling a multifaceted phenotype and longitudinal data, as well as improving statistical power for multiple significance testing via a two-stage testing procedure that involves a multivariate analysis for grouped phenotypes followed by univariate analysis for the phenotypes in the significant group(s). In this article, we propose a multivariate extension of generalized multifactor dimensionality reduction (GMDR) based on multivariate generalized linear, multivariate quasi-likelihood and generalized estimating equations models. Simulations and real data analysis for the cohort from the Study of Addiction: Genetics and Environment are performed to investigate the properties and performance of the proposed method, as compared with the univariate method. The results suggest that the proposed multivariate GMDR substantially boosts statistical power.

  6. Multivariate dimensionality reduction approaches to identify gene-gene and gene-environment interactions underlying multiple complex traits.

    Directory of Open Access Journals (Sweden)

    Hai-Ming Xu

    Full Text Available The elusive but ubiquitous multifactor interactions represent a stumbling block that urgently needs to be removed in searching for determinants involved in human complex diseases. The dimensionality reduction approaches are a promising tool for this task. Many complex diseases exhibit composite syndromes required to be measured in a cluster of clinical traits with varying correlations and/or are inherently longitudinal in nature (changing over time and measured dynamically at multiple time points. A multivariate approach for detecting interactions is thus greatly needed on the purposes of handling a multifaceted phenotype and longitudinal data, as well as improving statistical power for multiple significance testing via a two-stage testing procedure that involves a multivariate analysis for grouped phenotypes followed by univariate analysis for the phenotypes in the significant group(s. In this article, we propose a multivariate extension of generalized multifactor dimensionality reduction (GMDR based on multivariate generalized linear, multivariate quasi-likelihood and generalized estimating equations models. Simulations and real data analysis for the cohort from the Study of Addiction: Genetics and Environment are performed to investigate the properties and performance of the proposed method, as compared with the univariate method. The results suggest that the proposed multivariate GMDR substantially boosts statistical power.

  7. Ant colony optimisation of decision tree and contingency table models for the discovery of gene-gene interactions.

    Science.gov (United States)

    Sapin, Emmanuel; Keedwell, Ed; Frayling, Tim

    2015-12-01

    In this study, ant colony optimisation (ACO) algorithm is used to derive near-optimal interactions between a number of single nucleotide polymorphisms (SNPs). This approach is used to discover small numbers of SNPs that are combined into a decision tree or contingency table model. The ACO algorithm is shown to be very robust as it is proven to be able to find results that are discriminatory from a statistical perspective with logical interactions, decision tree and contingency table models for various numbers of SNPs considered in the interaction. A large number of the SNPs discovered here have been already identified in large genome-wide association studies to be related to type II diabetes in the literature, lending additional confidence to the results.

  8. A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits.

    Directory of Open Access Journals (Sweden)

    Jiang Gui

    Full Text Available We present an extension of the two-class multifactor dimensionality reduction (MDR algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of a quantitative trait. The proposed Quantitative MDR (QMDR method handles continuous data by modifying MDR's constructive induction algorithm to use a T-test. QMDR replaces the balanced accuracy metric with a T-test statistic as the score to determine the best interaction model. We used a simulation to identify the empirical distribution of QMDR's testing score. We then applied QMDR to genetic data from the ongoing prospective Prevention of Renal and Vascular End-Stage Disease (PREVEND study.

  9. A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits.

    Science.gov (United States)

    Gui, Jiang; Moore, Jason H; Williams, Scott M; Andrews, Peter; Hillege, Hans L; van der Harst, Pim; Navis, Gerjan; Van Gilst, Wiek H; Asselbergs, Folkert W; Gilbert-Diamond, Diane

    2013-01-01

    We present an extension of the two-class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of a quantitative trait. The proposed Quantitative MDR (QMDR) method handles continuous data by modifying MDR's constructive induction algorithm to use a T-test. QMDR replaces the balanced accuracy metric with a T-test statistic as the score to determine the best interaction model. We used a simulation to identify the empirical distribution of QMDR's testing score. We then applied QMDR to genetic data from the ongoing prospective Prevention of Renal and Vascular End-Stage Disease (PREVEND) study.

  10. The importance of replication in gene-gene interaction studies: multifactor dimensionality reduction applied to a two-stage breast cancer case-control study.

    Science.gov (United States)

    Milne, Roger L; Fagerholm, Rainer; Nevanlinna, Heli; Benítez, Javier

    2008-06-01

    A polygenic model has been proposed to explain the bulk of the genetic component of breast cancer aetiology and this is probably to include both main effects and interactions between multiple loci. However, the power to detect the interactions using traditional analytical methods is very limited for most studies. Multifactor dimensionality reduction (MDR) has been suggested to have increased power to detect interactions and is increasing being used in published studies. We applied MDR to a two-stage case-control breast cancer study conducted in Spain and Finland. In the stage 1 Spanish study of 864 cases and 845 controls, we evaluated interaction between 474 single-nucleotide polymorphisms in 120 cancer-related genes, subdivided into 34 genetic pathways and found evidence of a four-way interaction between genes in the FatiGO-defined B-cell receptor-signalling pathway (P < 0.006). However, this result was not replicated in the stage 2 Finnish study of 580 cases and 920 controls (P = 0.99). A number of technical issues in applying MDR to case-control data were identified and discussed. One of these is that the estimated sign test P-value can vary substantially at random, which raises doubts about its reliability. More generally, the present study serves as an important caution in the interpretation of results from single studies of gene-gene or gene-environment interaction in complex diseases. Just as for genetic main effects, the replication of positive findings in additional independent series is essential.

  11. A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits

    NARCIS (Netherlands)

    Gui, Jiang; Moore, Jason H.; Williams, Scott M.; Andrews, Peter; Hillege, Hans L.; van der Harst, Pim; Navis, Gerjan; Van Gilst, Wiek H.; Asselbergs, Folkert W.; Gilbert-Diamond, Diane

    2013-01-01

    We present an extension of the two-class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of a quantitative trait. The proposed Quantitative MDR (QMDR) method handles continuous data by modifying MDR's

  12. Toll-like receptors and microbial exposure : gene-gene and gene-environment interaction in the development of atopy

    NARCIS (Netherlands)

    Reijmerink, N. E.; Kerkhof, M.; Bottema, R. W. B.; Gerritsen, J.; Stelma, F. F.; Thijs, C.; van Schayck, C. P.; Smit, H. A.; Brunekreef, B.; Postma, D. S.; Koppelman, G. H.

    2011-01-01

    Environmental and genetic factors contribute to atopy development. High microbial exposure may confer a protective effect on atopy. Toll-like receptors (TLRs) bind microbial products and are important in activating the immune system. To assess whether interactions between microbial exposures and

  13. Toll-like receptors and microbial exposure: gene-gene and gene-environment interaction in the development of atopy

    NARCIS (Netherlands)

    Reijmerink, N.E.; Kerkhof, M. van de; Bottema, R.W.; Gerritsen, J.; Stelma, F.F.; Thijs, C.; Schayck, C.P. van; Smit, H.A.; Brunekreef, B.; Postma, D.S.; Koppelman, G.H.

    2011-01-01

    Environmental and genetic factors contribute to atopy development. High microbial exposure may confer a protective effect on atopy. Toll-like receptors (TLRs) bind microbial products and are important in activating the immune system. To assess whether interactions between microbial exposures and

  14. A model of gene-gene and gene-environment interactions and its implications for targeting environmental interventions by genotype

    OpenAIRE

    Wallace Helen M

    2006-01-01

    Abstract Background The potential public health benefits of targeting environmental interventions by genotype depend on the environmental and genetic contributions to the variance of common diseases, and the magnitude of any gene-environment interaction. In the absence of prior knowledge of all risk factors, twin, family and environmental data may help to define the potential limits of these benefits in a given population. However, a general methodology to analyze twin data is required becaus...

  15. Gene-Gene Interplay and Gene-Diet Interactions Involving the MTNR1B rs10830963 Variant with Body Weight Loss.

    Science.gov (United States)

    Goni, Leticia; Cuervo, Marta; Milagro, Fermin I; Martínez, J Alfredo

    2014-01-01

    Investigation of the genetic makeup may facilitate the implementation of more personalized nutritional interventions. The aims were to examine whether the rs10830963 MTNR1B polymorphism affects weight loss in response to a hypocaloric diet and to find potential gene-gene interplays and gene-diet interactions. 167 subjects enrolled in a personalized nutritional intervention for weight loss (3-6 weeks) were examined for anthropometric measurements, dietary habits and physical activity at baseline and at the first follow-up visit. Three polymorphisms, which have previously been associated with body weight regulation, rs10830963 (MTNR1B), rs9939609 (FTO) and rs17782313 (MC4R), were analyzed using the Luminex® 100/200™ System. After adjusting for covariates, females with the rs10830963 CG/GG genotype showed lower weight loss than those with the CC genotype. In the total population, carriers of variant alleles of both FTO and MC4R showed a significant association with MTNR1B and weight loss outcome. Moreover, among women, higher total protein and animal protein intakes were associated with a lower weight loss in G allele carriers of the MTNR1B variant. Our data evidenced that rs10830963 MTNR1B polymorphism could be associated with individual differences in weight loss induced by a hypocaloric diet. This association was influenced by FTO and MC4R loci and modified by baseline protein intake. © 2015 S. Karger AG, Basel.

  16. CARAT-GxG: CUDA-Accelerated Regression Analysis Toolkit for Large-Scale Gene-Gene Interaction with GPU Computing System.

    Science.gov (United States)

    Lee, Sungyoung; Kwon, Min-Seok; Park, Taesung

    2014-01-01

    In genome-wide association studies (GWAS), regression analysis has been most commonly used to establish an association between a phenotype and genetic variants, such as single nucleotide polymorphism (SNP). However, most applications of regression analysis have been restricted to the investigation of single marker because of the large computational burden. Thus, there have been limited applications of regression analysis to multiple SNPs, including gene-gene interaction (GGI) in large-scale GWAS data. In order to overcome this limitation, we propose CARAT-GxG, a GPU computing system-oriented toolkit, for performing regression analysis with GGI using CUDA (compute unified device architecture). Compared to other methods, CARAT-GxG achieved almost 700-fold execution speed and delivered highly reliable results through our GPU-specific optimization techniques. In addition, it was possible to achieve almost-linear speed acceleration with the application of a GPU computing system, which is implemented by the TORQUE Resource Manager. We expect that CARAT-GxG will enable large-scale regression analysis with GGI for GWAS data.

  17. Influences of XDH genotype by gene-gene interactions with SUCLA2 for thiopurine-induced leukopenia in Korean patients with Crohn's disease.

    Science.gov (United States)

    Park, Soo-Kyung; Hong, Myunghee; Ye, Byong Duk; Kim, Kyung-Jo; Park, Sang Hyoung; Yang, Dong-Hoon; Hwang, Sung-Wook; Kwak, Min Seob; Lee, Ho-Su; Song, Kyuyoung; Yang, Suk-Kyun

    2016-01-01

    The impact of genetic variation in the thiopurine S-methyltransferase (TPMT) gene on thiopurine-induced leukopenia has been well demonstrated. Although xanthine dehydrogenase (XDH) is the second major contributor to azathioprine breakdown, polymorphisms in XDH have rarely been studied in IBD patients. We aim to access association between XDH variants and thiopurine-induced leukopenia by gene-gene interaction in a Crohn's disease (CD) population. A total of 964 CD patients treated with thiopurines were recruited from a tertiary referral center. The association between four XDH variants (p.Gly172Arg, p.Asn1109Thr, p.Arg149Cys, and p.Thr910Lys) and thiopurine-induced leukopenia was analyzed in cases with early leukopenia (n = 66), late leukopenia (n = 264), and in controls without leukopenia (n = 632). Three non-synonymous SNPs, which we previously reported association with thiopurine-induced leukopenia, NUDT15 (p.Arg139Cys), SUCLA2 (p.Ser199Thr), and TPMT *3C were selected for epistasis analysis with the XDH variants. There was no significant association for two variants of XDH and thiopurine-induced leukopenia. In the epistasis analysis, only XDH (p.Asn1109Thr) * SUCLA2 (p.Ser199Thr) showed a statistically significant association with early leukopenia [odds ratio (OR) = 0.16; p = 0.03]. After genotype stratification, a positive association on the background of SUCLA2 wild-type (199Ser) between the XDH (p.Asn1109Thr) and early leukopenia (OR = 4.39; p = 0.01) was detected. Genes associated with thiopurine-induced leukopenia can act in a complex interactive manner. Further studies are warranted to explore the mechanisms underlying the effects of the combination of XDH (p.Asn1109Thr) and SUCLA2 (199Ser) on thiopurine-induced leukopenia.

  18. Gene-gene combination effect and interactions among ABCA1, APOA1, SR-B1, and CETP polymorphisms for serum high-density lipoprotein-cholesterol in the Japanese population.

    Directory of Open Access Journals (Sweden)

    Akihiko Nakamura

    Full Text Available BACKGROUND/OBJECTIVE: Gene-gene interactions in the reverse cholesterol transport system for high-density lipoprotein-cholesterol (HDL-C are poorly understood. The present study observed gene-gene combination effect and interactions between single nucleotide polymorphisms (SNPs in ABCA1, APOA1, SR-B1, and CETP in serum HDL-C from a cross-sectional study in the Japanese population. METHODS: The study population comprised 1,535 men and 1,515 women aged 35-69 years who were enrolled in the Japan Multi-Institutional Collaborative Cohort (J-MICC Study. We selected 13 SNPs in the ABCA1, APOA1, CETP, and SR-B1 genes in the reverse cholesterol transport system. The effects of genetic and environmental factors were assessed using general linear and logistic regression models after adjusting for age, sex, and region. PRINCIPAL FINDINGS: Alcohol consumption and daily activity were positively associated with HDL-C levels, whereas smoking had a negative relationship. The T allele of CETP, rs3764261, was correlated with higher HDL-C levels and had the highest coefficient (2.93 mg/dL/allele among the 13 SNPs, which was statistically significant after applying the Bonferroni correction (p<0.001. Gene-gene combination analysis revealed that CETP rs3764261 was associated with high HDL-C levels with any combination of SNPs from ABCA1, APOA1, and SR-B1, although no gene-gene interaction was apparent. An increasing trend for serum HDL-C was also observed with an increasing number of alleles (p<0.001. CONCLUSIONS: The present study identified a multiplier effect from a polymorphism in CETP with ABCA1, APOA1, and SR-B1, as well as a dose-dependence according to the number of alleles present.

  19. An application of conditional logistic regression and multifactor dimensionality reduction for detecting gene-gene Interactions on risk of myocardial infarction: The importance of model validation

    Directory of Open Access Journals (Sweden)

    Coffey Christopher S

    2004-04-01

    Full Text Available Abstract Background To examine interactions among the angiotensin converting enzyme (ACE insertion/deletion, plasminogen activator inhibitor-1 (PAI-1 4G/5G, and tissue plasminogen activator (t-PA insertion/deletion gene polymorphisms on risk of myocardial infarction using data from 343 matched case-control pairs from the Physicians Health Study. We examined the data using both conditional logistic regression and the multifactor dimensionality reduction (MDR method. One advantage of the MDR method is that it provides an internal prediction error for validation. We summarize our use of this internal prediction error for model validation. Results The overall results for the two methods were consistent, with both suggesting an interaction between the ACE I/D and PAI-1 4G/5G polymorphisms. However, using ten-fold cross validation, the 46% prediction error for the final MDR model was not significantly lower than that expected by chance. Conclusions The significant interaction initially observed does not validate and may represent a type I error. As data-driven analytic methods continue to be developed and used to examine complex genetic interactions, it will become increasingly important to stress model validation in order to ensure that significant effects represent true relationships rather than chance findings.

  20. An application of conditional logistic regression and multifactor dimensionality reduction for detecting gene-gene interactions on risk of myocardial infarction: the importance of model validation.

    Science.gov (United States)

    Coffey, Christopher S; Hebert, Patricia R; Ritchie, Marylyn D; Krumholz, Harlan M; Gaziano, J Michael; Ridker, Paul M; Brown, Nancy J; Vaughan, Douglas E; Moore, Jason H

    2004-04-30

    To examine interactions among the angiotensin converting enzyme (ACE) insertion/deletion, plasminogen activator inhibitor-1 (PAI-1) 4G/5G, and tissue plasminogen activator (t-PA) insertion/deletion gene polymorphisms on risk of myocardial infarction using data from 343 matched case-control pairs from the Physicians Health Study. We examined the data using both conditional logistic regression and the multifactor dimensionality reduction (MDR) method. One advantage of the MDR method is that it provides an internal prediction error for validation. We summarize our use of this internal prediction error for model validation. The overall results for the two methods were consistent, with both suggesting an interaction between the ACE I/D and PAI-1 4G/5G polymorphisms. However, using ten-fold cross validation, the 46% prediction error for the final MDR model was not significantly lower than that expected by chance. The significant interaction initially observed does not validate and may represent a type I error. As data-driven analytic methods continue to be developed and used to examine complex genetic interactions, it will become increasingly important to stress model validation in order to ensure that significant effects represent true relationships rather than chance findings.

  1. An application of conditional logistic regression and multifactor dimensionality reduction for detecting gene-gene Interactions on risk of myocardial infarction: The importance of model validation

    OpenAIRE

    Coffey, Christopher S; Hebert, Patricia R; Ritchie, Marylyn D; Krumholz, Harlan M; Gaziano, J Michael; Ridker, Paul M; Brown, Nancy J; Vaughan, Douglas E; Moore, Jason H

    2004-01-01

    Abstract Background To examine interactions among the angiotensin converting enzyme (ACE) insertion/deletion, plasminogen activator inhibitor-1 (PAI-1) 4G/5G, and tissue plasminogen activator (t-PA) insertion/deletion gene polymorphisms on risk of myocardial infarction using data from 343 matched case-control pairs from the Physicians Health Study. We examined the data using both conditional logistic regression and the multifactor dimensionality reduction (MDR) method. One advantage of the MD...

  2. Trends in gastrectomy and ADH1B and ALDH2 genotypes in Japanese alcoholic men and their gene-gastrectomy, gene-gene and gene-age interactions for risk of alcoholism.

    Science.gov (United States)

    Yokoyama, Akira; Yokoyama, Tetsuji; Matsui, Toshifumi; Mizukami, Takeshi; Kimura, Mitsuru; Matsushita, Sachio; Higuchi, Susumu; Maruyama, Katsuya

    2013-01-01

    The life-time drinking profiles of Japanese alcoholics have shown that gastrectomy increases susceptibility to alcoholism. We investigated the trends in gastrectomy and alcohol dehydrogenase-1B (ADH1B) and aldehyde dehydrogenase-2 (ALDH2) genotypes and their interactions in alcoholics. This survey was conducted on 4879 Japanese alcoholic men 40 years of age or older who underwent routine gastrointestinal endoscopic screening during the period 1996-2010. ADH1B/ALDH2 genotyping was performed in 3702 patients. A history of gastrectomy was found in 508 (10.4%) patients. The reason for the gastrectomy was peptic ulcer in 317 patients and gastric cancer in 187 patients. The frequency of gastrectomy had gradually decreased from 13.3% in 1996-2000 to 10.5% in 2001-2005 and to 7.8% in 2006-2010 (P alcoholism-susceptibility genotypes, ADH1B*1/*1 and ALDH2*1/*1, modestly but significantly tended not to occur in the same individual (P = 0.026). The frequency of ADH1B*1/*1 decreased with ascending age groups. The high frequency of history of gastrectomy suggested that gastrectomy is still a risk factor for alcoholism, although the percentage decreased during the period. The alcoholism-susceptibility genotype ADH1B*1/*1 was less frequent in the gastrectomy group, suggesting a competitive gene-gastrectomy interaction for alcoholism. A gene-gene interaction and gene-age interactions regarding the ADH1B genotype were observed.

  3. Vision-based interaction

    CERN Document Server

    Turk, Matthew

    2013-01-01

    In its early years, the field of computer vision was largely motivated by researchers seeking computational models of biological vision and solutions to practical problems in manufacturing, defense, and medicine. For the past two decades or so, there has been an increasing interest in computer vision as an input modality in the context of human-computer interaction. Such vision-based interaction can endow interactive systems with visual capabilities similar to those important to human-human interaction, in order to perceive non-verbal cues and incorporate this information in applications such

  4. Gene-based testing of interactions in association studies of quantitative traits.

    Directory of Open Access Journals (Sweden)

    Li Ma

    Full Text Available Various methods have been developed for identifying gene-gene interactions in genome-wide association studies (GWAS. However, most methods focus on individual markers as the testing unit, and the large number of such tests drastically erodes statistical power. In this study, we propose novel interaction tests of quantitative traits that are gene-based and that confer advantage in both statistical power and biological interpretation. The framework of gene-based gene-gene interaction (GGG tests combine marker-based interaction tests between all pairs of markers in two genes to produce a gene-level test for interaction between the two. The tests are based on an analytical formula we derive for the correlation between marker-based interaction tests due to linkage disequilibrium. We propose four GGG tests that extend the following P value combining methods: minimum P value, extended Simes procedure, truncated tail strength, and truncated P value product. Extensive simulations point to correct type I error rates of all tests and show that the two truncated tests are more powerful than the other tests in cases of markers involved in the underlying interaction not being directly genotyped and in cases of multiple underlying interactions. We applied our tests to pairs of genes that exhibit a protein-protein interaction to test for gene-level interactions underlying lipid levels using genotype data from the Atherosclerosis Risk in Communities study. We identified five novel interactions that are not evident from marker-based interaction testing and successfully replicated one of these interactions, between SMAD3 and NEDD9, in an independent sample from the Multi-Ethnic Study of Atherosclerosis. We conclude that our GGG tests show improved power to identify gene-level interactions in existing, as well as emerging, association studies.

  5. Interactive example-based hatching

    NARCIS (Netherlands)

    Gerl, Moritz; Isenberg, Tobias

    2013-01-01

    We present an approach for interactively generating pen-and-ink hatching renderings based on hand-drawn examples. We aim to overcome the regular and synthetic appearance of the results of existing methods by incorporating human virtuosity and illustration skills in the computer generation of such

  6. Interacting With Robots to Investigate the Bases of Social Interaction.

    Science.gov (United States)

    Sciutti, Alessandra; Sandini, Giulio

    2017-12-01

    Humans show a great natural ability at interacting with each other. Such efficiency in joint actions depends on a synergy between planned collaboration and emergent coordination, a subconscious mechanism based on a tight link between action execution and perception. This link supports phenomena as mutual adaptation, synchronization, and anticipation, which cut drastically the delays in the interaction and the need of complex verbal instructions and result in the establishment of joint intentions, the backbone of social interaction. From a neurophysiological perspective, this is possible, because the same neural system supporting action execution is responsible of the understanding and the anticipation of the observed action of others. Defining which human motion features allow for such emergent coordination with another agent would be crucial to establish more natural and efficient interaction paradigms with artificial devices, ranging from assistive and rehabilitative technology to companion robots. However, investigating the behavioral and neural mechanisms supporting natural interaction poses substantial problems. In particular, the unconscious processes at the basis of emergent coordination (e.g., unintentional movements or gazing) are very difficult-if not impossible-to restrain or control in a quantitative way for a human agent. Moreover, during an interaction, participants influence each other continuously in a complex way, resulting in behaviors that go beyond experimental control. In this paper, we propose robotics technology as a potential solution to this methodological problem. Robots indeed can establish an interaction with a human partner, contingently reacting to his actions without losing the controllability of the experiment or the naturalness of the interactive scenario. A robot could represent an "interactive probe" to assess the sensory and motor mechanisms underlying human-human interaction. We discuss this proposal with examples from our

  7. Ontology-based literature mining of E. coli vaccine-associated gene interaction networks.

    Science.gov (United States)

    Hur, Junguk; Özgür, Arzucan; He, Yongqun

    2017-03-14

    these gene interaction networks identified top ranked E. coli genes and 6 INO interaction types (e.g., regulation and gene expression). Vaccine-related E. coli gene-gene interaction network was constructed using ontology-based literature mining strategy, which identified important E. coli vaccine genes and their interactions with other genes through specific interaction types.

  8. Bodystorming for Movement-Based Interaction Design

    Directory of Open Access Journals (Sweden)

    Elena Márquez Segura

    2016-11-01

    Full Text Available After a decade of movement-based interaction in human–computer interaction, designing for the moving body still remains a challenge. Research in this field requires methods to help access, articulate, and harness embodied experiences in ways that can inform the design process. To address this challenge, this article appropriates bodystorming, an embodied ideation method for movement-based interaction design. The proposed method allows for early consideration of the physical, collocated, and social aspects of a designed activity as illustrated with two explorative workshops in different application domains: interactive body games and interactive performances. Using a qualitative methods approach, we used video material from the workshops, feedback from participants, and our own experience as participants and facilitators to outline important characteristics of the bodystorming method in the domain of movement-based interaction. The proposed method is compared with previous ones and application implications are discussed.

  9. Yoink: An interaction-based partitioning API.

    Science.gov (United States)

    Zheng, Min; Waller, Mark P

    2018-05-15

    Herein, we describe the implementation details of our interaction-based partitioning API (application programming interface) called Yoink for QM/MM modeling and fragment-based quantum chemistry studies. Interactions are detected by computing density descriptors such as reduced density gradient, density overlap regions indicator, and single exponential decay detector. Only molecules having an interaction with a user-definable QM core are added to the QM region of a hybrid QM/MM calculation. Moreover, a set of molecule pairs having density-based interactions within a molecular system can be computed in Yoink, and an interaction graph can then be constructed. Standard graph clustering methods can then be applied to construct fragments for further quantum chemical calculations. The Yoink API is licensed under Apache 2.0 and can be accessed via yoink.wallerlab.org. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

  10. Activity-Based Collaboration for Interactive Spaces

    DEFF Research Database (Denmark)

    Bardram, Jakob Eyvind; Esbensen, Morten; Tabard, Aurélien

    2017-01-01

    Activity-based computing (ABC) is a conceptual and technological framework for designing interactive systems that offers a better mapping between the activities people conduct and the digital entities they use. In ABC, rather than interacting directly with lower-level technical entities like file...

  11. Interactive Reliability-Based Optimal Design

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Thoft-Christensen, Palle; Siemaszko, A.

    1994-01-01

    Interactive design/optimization of large, complex structural systems is considered. The objective function is assumed to model the expected costs. The constraints are reliability-based and/or related to deterministic code requirements. Solution of this optimization problem is divided in four main...... be used in interactive optimization....

  12. Immersion in Movement-Based Interaction

    Science.gov (United States)

    Pasch, Marco; Bianchi-Berthouze, Nadia; van Dijk, Betsy; Nijholt, Anton

    The phenomenon of immersing oneself into virtual environments has been established widely. Yet to date (to our best knowledge) the physical dimension has been neglected in studies investigating immersion in Human-Computer Interaction (HCI). In movement-based interaction the user controls the interface via body movements, e.g. direct manipulation of screen objects via gestures or using a handheld controller as a virtual tennis racket. It has been shown that physical activity affects arousal and that movement-based controllers can facilitate engagement in the context of video games. This paper aims at identifying movement features that influence immersion. We first give a brief survey on immersion and movement-based interfaces. Then, we report results from an interview study that investigates how users experience their body movements when interacting with movement-based interfaces. Based on the interviews, we identify four movement-specific features. We recommend them as candidates for further investigation.

  13. An interactive segmentation method based on superpixel

    DEFF Research Database (Denmark)

    Yang, Shu; Zhu, Yaping; Wu, Xiaoyu

    2015-01-01

    This paper proposes an interactive image-segmentation method which is based on superpixel. To achieve fast segmentation, the method is used to establish a Graphcut model using superpixels as nodes, and a new energy function is proposed. Experimental results demonstrate that the authors' method has...... excellent performance in terms of segmentation accuracy and computation efficiency compared with other segmentation algorithm based on pixels....

  14. Tagging of blast resistance gene(s) to DNA markers and marker-assisted selection (MAS) in rice improvement

    International Nuclear Information System (INIS)

    Zhuang, J.Y.; Lu, J.; Qian, H.R.; Lin, H.X.; Zheng, K.L.

    1998-01-01

    This paper reports progress made on the tagging of blast resistance gene(s) to DNA markers and on the initiation of marker-assisted selection (MAS) for blast resistance in rice improvement. A pair of near isogenic lines, K8OR and K79S, were developed using a Chinese landrace Hong-jiao-zhan as the resistance donor. Ten putatively positive markers were identified by screening 177 mapped DNA markers. Using the F 2 population of 143 plants and the derived F 3 lines, three Restriction Fragment Length Polymorphism (RFLP) markers (RG81, RG869 and RZ397) on chromosome 12 of rice were identified to be closely linked to the blast resistance gene Pi-12(t). The genetic distance between Pi-12(t) and the closest marker RG869 was 5.1 cM. By employing the bulk segregant analysis (BSA) procedure, six of 199 arbitrary primers were found to produce positive Randomly Amplified Polymorphic DNA (RAPD) bands. Tight linkage between Pi-12(t) and three RAPD bands, each from a different primer, was confirmed after amplification of DNA of all F 2 individuals. Two fragments were cloned and sequenced, and two sequence characterised amplified re-ion (SCAR) markers were established. In two other F 3 populations, Xian-feng I/Tetep and Xian-feng, 1/Hong-jiao-zhan, the blast resistance was found to be controlled by interactions of two or more genes. One resistance gene was located in the vicinity of RG81 in both populations. Work to identify other gene(s) is currently under way. Marker assisted selection for blast resistance was initiated. Crosses were made between elite varieties and blast resistance donors to develop populations for DNA marker-assisted selection of blast resistance. In addition, 48 varieties widely used in current rice breeding programs were provided by rice breeders. DNA marker-based polymorphism among, these varieties and resistance donors were analysed to produce a database for future MAS program. (author)

  15. Identification of fever and vaccine-associated gene interaction networks using ontology-based literature mining.

    Science.gov (United States)

    Hur, Junguk; Ozgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

    2012-12-20

    Fever is one of the most common adverse events of vaccines. The detailed mechanisms of fever and vaccine-associated gene interaction networks are not fully understood. In the present study, we employed a genome-wide, Centrality and Ontology-based Network Discovery using Literature data (CONDL) approach to analyse the genes and gene interaction networks associated with fever or vaccine-related fever responses. Over 170,000 fever-related articles from PubMed abstracts and titles were retrieved and analysed at the sentence level using natural language processing techniques to identify genes and vaccines (including 186 Vaccine Ontology terms) as well as their interactions. This resulted in a generic fever network consisting of 403 genes and 577 gene interactions. A vaccine-specific fever sub-network consisting of 29 genes and 28 gene interactions was extracted from articles that are related to both fever and vaccines. In addition, gene-vaccine interactions were identified. Vaccines (including 4 specific vaccine names) were found to directly interact with 26 genes. Gene set enrichment analysis was performed using the genes in the generated interaction networks. Moreover, the genes in these networks were prioritized using network centrality metrics. Making scientific discoveries and generating new hypotheses were possible by using network centrality and gene set enrichment analyses. For example, our study found that the genes in the generic fever network were more enriched in cell death and responses to wounding, and the vaccine sub-network had more gene enrichment in leukocyte activation and phosphorylation regulation. The most central genes in the vaccine-specific fever network are predicted to be highly relevant to vaccine-induced fever, whereas genes that are central only in the generic fever network are likely to be highly relevant to generic fever responses. Interestingly, no Toll-like receptors (TLRs) were found in the gene-vaccine interaction network. Since

  16. NMR studies concerning base-base interactions in oligonucleotides

    International Nuclear Information System (INIS)

    Hoogen, Y.T. van den.

    1988-01-01

    Two main subjects are treated in the present thesis. The firsst part principally deals with the base-base interactions in single-stranded oligoribonucleotides. The second part presents NMR and model-building studies of DNA and RNA duplexes containing an unpaired base. (author). 242 refs.; 26 figs.; 24 tabs

  17. Evolution and spatial structure interact to influence plant–herbivore population and community dynamics

    OpenAIRE

    Hartvigsen, G.; Levin, S.

    1997-01-01

    An individual-based model of plant–herbivore interactions was developed to test the potentially interactive effects of explicit space and coevolution on population and community dynamics. Individual plants and herbivores resided in cells on a lattice and carried linked interaction genes. Interaction strength between individual plants and herbivores depended on concordance between these genes (gene-for-gene coevolution). Mating and dispersal among individuals were controlled spatially within v...

  18. Population-based analysis of Alzheimer’s disease risk alleles implicates genetic interactions

    Science.gov (United States)

    Ebbert, Mark T. W.; Ridge, Perry G.; Wilson, Andrew R.; Sharp, Aaron R.; Bailey, Matthew; Norton, Maria C.; Tschanz, JoAnn T.; Munger, Ronald G.; Corcoran, Christopher D.; Kauwe, John S. K.

    2013-01-01

    Background Reported odds ratios and population attributable fractions (PAF) for late-onset Alzheimer’s disease (LOAD) risk loci (BIN1, ABCA7, CR1, MS4A4E, CD2AP, PICALM, MS4A6A, CD33, and CLU) come from clinically ascertained samples. Little is known about the combined PAF for these LOAD risk alleles and the utility of these combined markers for case-control prediction. Here we evaluate these loci in a large population-based sample to estimate PAF and explore the effects of additive and non-additive interactions on LOAD status prediction performance. Methods 2,419 samples from the Cache County Memory Study were genotyped for APOE and nine LOAD risk loci from AlzGene.org. We used logistic regression and ROC analysis to assess the LOAD status prediction performance of these loci using additive and non-additive models, and compared ORs and PAFs between AlzGene.org and Cache County. Results Odds ratios were comparable between Cache County and AlzGene.org when identical SNPs were genotyped. PAFs from AlzGene.org ranged from 2.25–37%; those from Cache County ranged from 0.05–20%. Including non-APOE alleles significantly improved LOAD status prediction performance (AUC = 0.80) over APOE alone (AUC = 0.78) when not constrained to an additive relationship (p < 0.03). We identified potential allelic interactions (p-values uncorrected): CD33-MS4A4E (Synergy Factor = 5.31; p < 0.003) and CLU-MS4A4E (SF = 3.81; p < 0.016). Conclusions While non-additive interactions between loci significantly improve diagnostic ability, the improvement does not reach the desired sensitivity or specificity for clinical use. Nevertheless, these results suggest that understanding gene-gene interactions may be important in resolving Alzheimer’s disease etiology. PMID:23954108

  19. Population-based analysis of Alzheimer's disease risk alleles implicates genetic interactions.

    Science.gov (United States)

    Ebbert, Mark T W; Ridge, Perry G; Wilson, Andrew R; Sharp, Aaron R; Bailey, Matthew; Norton, Maria C; Tschanz, JoAnn T; Munger, Ronald G; Corcoran, Christopher D; Kauwe, John S K

    2014-05-01

    Reported odds ratios and population attributable fractions (PAF) for late-onset Alzheimer's disease (LOAD) risk loci (BIN1, ABCA7, CR1, MS4A4E, CD2AP, PICALM, MS4A6A, CD33, and CLU) come from clinically ascertained samples. Little is known about the combined PAF for these LOAD risk alleles and the utility of these combined markers for case-control prediction. Here we evaluate these loci in a large population-based sample to estimate PAF and explore the effects of additive and nonadditive interactions on LOAD status prediction performance. 2419 samples from the Cache County Memory Study were genotyped for APOE and nine LOAD risk loci from AlzGene.org. We used logistic regression and receiver operator characteristic analysis to assess the LOAD status prediction performance of these loci using additive and nonadditive models and compared odds ratios and PAFs between AlzGene.org and Cache County. Odds ratios were comparable between Cache County and AlzGene.org when identical single nucleotide polymorphisms were genotyped. PAFs from AlzGene.org ranged from 2.25% to 37%; those from Cache County ranged from .05% to 20%. Including non-APOE alleles significantly improved LOAD status prediction performance (area under the curve = .80) over APOE alone (area under the curve = .78) when not constrained to an additive relationship (p < .03). We identified potential allelic interactions (p values uncorrected): CD33-MS4A4E (synergy factor = 5.31; p < .003) and CLU-MS4A4E (synergy factor = 3.81; p < .016). Although nonadditive interactions between loci significantly improve diagnostic ability, the improvement does not reach the desired sensitivity or specificity for clinical use. Nevertheless, these results suggest that understanding gene-gene interactions may be important in resolving Alzheimer's disease etiology. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  20. Risk analysis based on hazards interactions

    Science.gov (United States)

    Rossi, Lauro; Rudari, Roberto; Trasforini, Eva; De Angeli, Silvia; Becker, Joost

    2017-04-01

    Despite an increasing need for open, transparent, and credible multi-hazard risk assessment methods, models, and tools, the availability of comprehensive risk information needed to inform disaster risk reduction is limited, and the level of interaction across hazards is not systematically analysed. Risk assessment methodologies for different hazards often produce risk metrics that are not comparable. Hazard interactions (consecutive occurrence two or more different events) are generally neglected, resulting in strongly underestimated risk assessment in the most exposed areas. This study presents cases of interaction between different hazards, showing how subsidence can affect coastal and river flood risk (Jakarta and Bandung, Indonesia) or how flood risk is modified after a seismic event (Italy). The analysis of well documented real study cases, based on a combination between Earth Observation and in-situ data, would serve as basis the formalisation of a multi-hazard methodology, identifying gaps and research frontiers. Multi-hazard risk analysis is performed through the RASOR platform (Rapid Analysis and Spatialisation Of Risk). A scenario-driven query system allow users to simulate future scenarios based on existing and assumed conditions, to compare with historical scenarios, and to model multi-hazard risk both before and during an event (www.rasor.eu).

  1. Genetic Evaluation for the Scoliosis Gene(s) in Patients with Neurofibromatosis 1 and Scoliosis

    Science.gov (United States)

    2015-10-01

    with a dystrophic genetic predisposition , more. Earlier diagnosis of dystrophic scoliosis could inform clinical decision-making regarding early surgical...AWARD NUMBER: W81XWH-10-1-0469 TITLE: Genetic Evaluation for the Scoliosis Gene(s) in Patients with Neurofibromatosis 1 and Scoliosis...31Jul2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER " Genetic Evaluation for the Scoliosis Gene(s) in Patients with Neurofibromatosis 1 and Scoliosis." 5b

  2. Interactive physically-based sound simulation

    Science.gov (United States)

    Raghuvanshi, Nikunj

    The realization of interactive, immersive virtual worlds requires the ability to present a realistic audio experience that convincingly compliments their visual rendering. Physical simulation is a natural way to achieve such realism, enabling deeply immersive virtual worlds. However, physically-based sound simulation is very computationally expensive owing to the high-frequency, transient oscillations underlying audible sounds. The increasing computational power of desktop computers has served to reduce the gap between required and available computation, and it has become possible to bridge this gap further by using a combination of algorithmic improvements that exploit the physical, as well as perceptual properties of audible sounds. My thesis is a step in this direction. My dissertation concentrates on developing real-time techniques for both sub-problems of sound simulation: synthesis and propagation. Sound synthesis is concerned with generating the sounds produced by objects due to elastic surface vibrations upon interaction with the environment, such as collisions. I present novel techniques that exploit human auditory perception to simulate scenes with hundreds of sounding objects undergoing impact and rolling in real time. Sound propagation is the complementary problem of modeling the high-order scattering and diffraction of sound in an environment as it travels from source to listener. I discuss my work on a novel numerical acoustic simulator (ARD) that is hundred times faster and consumes ten times less memory than a high-accuracy finite-difference technique, allowing acoustic simulations on previously-intractable spaces, such as a cathedral, on a desktop computer. Lastly, I present my work on interactive sound propagation that leverages my ARD simulator to render the acoustics of arbitrary static scenes for multiple moving sources and listener in real time, while accounting for scene-dependent effects such as low-pass filtering and smooth attenuation

  3. Emotion based human-robot interaction

    Directory of Open Access Journals (Sweden)

    Berns Karsten

    2018-01-01

    Full Text Available Human-machine interaction is a major challenge in the development of complex humanoid robots. In addition to verbal communication the use of non-verbal cues such as hand, arm and body gestures or mimics can improve the understanding of the intention of the robot. On the other hand, by perceiving such mechanisms of a human in a typical interaction scenario the humanoid robot can adapt its interaction skills in a better way. In this work, the perception system of two social robots, ROMAN and ROBIN of the RRLAB of the TU Kaiserslautern, is presented in the range of human-robot interaction.

  4. Gene-gene interaction between the cystathionine beta-synthase 31 base pair variable number of tandem repeats and the methylenetetrahydrofolate reductase 677C > T polymorphism on homocysteine levels and risk for neural tube defects.

    NARCIS (Netherlands)

    Afman, L.A.; Lievers, K.J.; Kluijtmans, L.A.J.; Trijbels, J.M.F.; Blom, H.J.

    2003-01-01

    INTRODUCTION: Most studies showed that mothers of children with NTD have elevated homocysteine levels pointing to a disturbed homocysteine metabolism as a risk factor for NTD. Folate lowers homocysteine levels by remethylation of homocysteine to methionine. Homocysteine can be irreversibly converted

  5. Nuclear reaction inputs based on effective interactions

    Energy Technology Data Exchange (ETDEWEB)

    Hilaire, S.; Peru, S.; Dubray, N.; Dupuis, M.; Bauge, E. [CEA, DAM, DIF, Arpajon (France); Goriely, S. [Universite Libre de Bruxelles, Institut d' Astronomie et d' Astrophysique, CP-226, Brussels (Belgium)

    2016-11-15

    Extensive nuclear structure studies have been performed for decades using effective interactions as sole input. They have shown a remarkable ability to describe rather accurately many types of nuclear properties. In the early 2000 s, a major effort has been engaged to produce nuclear reaction input data out of the Gogny interaction, in order to challenge its quality also with respect to nuclear reaction observables. The status of this project, well advanced today thanks to the use of modern computers as well as modern nuclear reaction codes, is reviewed and future developments are discussed. (orig.)

  6. Designing Software-Based Interactive Installations

    DEFF Research Database (Denmark)

    Andreasen, Troels; Juul, Niels Christian; Rosendahl, Mads

    2014-01-01

    installations and support the description of the approach with a single case- a bumper car competition. Why. To some extent, standard techniques for software development can be adapted for interactive installations. However, there is a need to emphasize the unique aspects of installations, bringing tangible...

  7. Immersion in Movement-Based Interaction

    NARCIS (Netherlands)

    Pasch, M.; Bianchi-Berthouze, N.; van Dijk, Elisabeth M.A.G.; Nijholt, Antinus; Nijholt, A.; Reidsma, Dennis; Reidsma, D.; Hondorp, G.H.W.

    2009-01-01

    The phenomenon of immersing oneself into virtual environments has been established widely. Yet to date (to our best knowledge) the physical dimension has been neglected in studies investigating immersion in Human-Computer Interaction (HCI). In this paper we investigate how the concept of immersion

  8. Adaptive Game Level Creation through Rank-based Interactive Evolution

    DEFF Research Database (Denmark)

    Liapis, Antonios; Martínez, Héctor Pérez; Togelius, Julian

    2013-01-01

    This paper introduces Rank-based Interactive Evolution (RIE) which is an alternative to interactive evolution driven by computational models of user preferences to generate personalized content. In RIE, the computational models are adapted to the preferences of users which, in turn, are used...... artificial agents. Results suggest that RIE is both faster and more robust than standard interactive evolution and outperforms other state-of-the-art interactive evolution approaches....

  9. Prediction of Protein-Protein Interactions Related to Protein Complexes Based on Protein Interaction Networks

    Directory of Open Access Journals (Sweden)

    Peng Liu

    2015-01-01

    Full Text Available A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptive k-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction network. Based on different complex sets detected by various algorithms, we can obtain different prediction sets of protein-protein interactions. The reliability of the predicted interaction sets is proved by using estimations with statistical tests and direct confirmation of the biological data. In comparison with the approaches which predict the interactions based on the cliques, the overlap of the predictions is small. Similarly, the overlaps among the predicted sets of interactions derived from various complex sets are also small. Thus, every predicted set of interactions may complement and improve the quality of the original network data. Meanwhile, the predictions from the proposed method replenish protein-protein interactions associated with protein complexes using only the network topology.

  10. Repetition-based Interactive Facade Modeling

    KAUST Repository

    AlHalawani, Sawsan

    2012-07-01

    Modeling and reconstruction of urban environments has gained researchers attention throughout the past few years. It spreads in a variety of directions across multiple disciplines such as image processing, computer graphics and computer vision as well as in architecture, geoscience and remote sensing. Having a virtual world of our real cities is very attractive in various directions such as entertainment, engineering, governments among many others. In this thesis, we address the problem of processing a single fa cade image to acquire useful information that can be utilized to manipulate the fa cade and generate variations of fa cade images which can be later used for buildings\\' texturing. Typical fa cade structures exhibit a rectilinear distribution where in windows and other elements are organized in a grid of horizontal and vertical repetitions of similar patterns. In the firt part of this thesis, we propose an efficient algorithm that exploits information obtained from a single image to identify the distribution grid of the dominant elements i.e. windows. This detection method is initially assisted with the user marking the dominant window followed by an automatic process for identifying its repeated instances which are used to define the structure grid. Given the distribution grid, we allow the user to interactively manipulate the fa cade by adding, deleting, resizing or repositioning the windows in order to generate new fa cade structures. Having the utility for the interactive fa cade is very valuable to create fa cade variations and generate new textures for building models. Ultimately, there is a wide range of interesting possibilities of interactions to be explored.

  11. Physically-based interactive Schlieren flow visualization

    Energy Technology Data Exchange (ETDEWEB)

    Mccormick, Patrick S [Los Alamos National Laboratory; Brownlee, Carson S [Los Alamos National Laboratory; Pegoraro, Vincent [UNIV OF UTAH; Shankar, Siddharth [UNIV OF UTAH; Hansen, Charles D [UNIV OF UTAH

    2009-01-01

    Understanding fluid flow is a difficult problem and of increasing importance as computational fluid dynamics produces an abundance of simulation data. Experimental flow analysis has employed techniques such as shadowgraph and schlieren imaging for centuries which allow empirical observation of inhomogeneous flows. Shadowgraphs provide an intuitive way of looking at small changes in flow dynamics through caustic effects while schlieren cutoffs introduce an intensity gradation for observing large scale directional changes in the flow. The combination of these shading effects provides an informative global analysis of overall fluid flow. Computational solutions for these methods have proven too complex until recently due to the fundamental physical interaction of light refracting through the flow field. In this paper, we introduce a novel method to simulate the refraction of light to generate synthetic shadowgraphs and schlieren images of time-varying scalar fields derived from computational fluid dynamics (CFD) data. Our method computes physically accurate schlieren and shadowgraph images at interactive rates by utilizing a combination of GPGPU programming, acceleration methods, and data-dependent probabilistic schlieren cutoffs. Results comparing this method to previous schlieren approximations are presented.

  12. Computer-Based Interactive Flight Training.

    Science.gov (United States)

    1980-11-01

    window ) display , ground control, and voice communications -- can be simulated even on minicomputer-based systems, at a high level of training fidelity...system has four major logical components: I) the aerodynamics computation, 2) the instrument display, 3) the visual through-the- window display , and 4) the

  13. A Hybrid Recommender System Based on User-Recommender Interaction

    OpenAIRE

    Zhang, Heng-Ru; Min, Fan; He, Xu; Xu, Yuan-Yuan

    2015-01-01

    Recommender systems are used to make recommendations about products, information, or services for users. Most existing recommender systems implicitly assume one particular type of user behavior. However, they seldom consider user-recommender interactive scenarios in real-world environments. In this paper, we propose a hybrid recommender system based on user-recommender interaction and evaluate its performance with recall and diversity metrics. First, we define the user-recommender interaction...

  14. Gene-Gene and Gene-Environment Interactions in the Etiology of Breast Cancer

    Science.gov (United States)

    2007-06-01

    and redissolving in a methanol acetate buffer mixture. Liquid chromatography photo diode array multiple generation mass spectrometry (LC/PDA/MS...delivery liquid chromatography system with multiple channel diode-array detection and a quadrupole ion trap mass spectrometer model ’Advantage...flour) 1 2 3 4 5 120. Elubo lafu 1 2 3 4 5 121. Kpokpo gari 1 2 3 4 5 122. Cassava /Yuka boiled 1 2 3 4 5 123. Fufu 1 2 3 4 5 124. Starch

  15. An agent-based architecture for multimodal interaction

    NARCIS (Netherlands)

    Jonker, C.M.; Treur, J.; Wijngaards, W.C.A.

    2001-01-01

    In this paper, an executable generic process model is proposed for combined verbal and non-verbal communication processes and their interaction. The agent-based architecture can be used to create multimodal interaction. The generic process model has been designed, implemented and used to simulate

  16. An agent-based architecture for multimodal interaction

    NARCIS (Netherlands)

    Jonker, C.M.; Treur, J.; Wijngaards, W.C.A.

    In this paper, an executable generic process model is proposed for combined verbal and non-verbal communication processes and their interaction. The agent-based architecture can be used to create multimodal interaction. The generic process model has been designed, implemented and used to simulate

  17. A Usability Study of Interactive Web-Based Modules

    Science.gov (United States)

    Girard, Tulay; Pinar, Musa

    2011-01-01

    This research advances the understanding of the usability of marketing case study modules in the area of interactive web-based technologies through the assignment of seven interactive case modules in a Principles of Marketing course. The case modules were provided for marketing students by the publisher, McGraw Hill Irwin, of the…

  18. On Interactive Teaching Model of Translation Course Based on Wechat

    Science.gov (United States)

    Lin, Wang

    2017-01-01

    Constructivism is a theory related to knowledge and learning, focusing on learners' subjective initiative, based on which the interactive approach has been proved to play a crucial role in language learning. Accordingly, the interactive approach can also be applied to translation teaching since translation itself is a bilingual transformational…

  19. Olfoto: designing a smell-based interaction

    OpenAIRE

    Brewster, S.A.; McGookin, D.K.; Miller, C.A.

    2006-01-01

    We present a study into the use of smell for searching digi-tal photo collections. Many people now have large photo libraries on their computers and effective search tools are needed. Smell has a strong link to memory and emotion so may be a good way to cue recall when searching. Our study compared text and smell based tagging. For the first stage we generated a set of smell and tag names from user de-scriptions of photos, participants then used these to tag pho-tos, returning two weeks later...

  20. Identification of interactions using model-based multifactor dimensionality reduction.

    Science.gov (United States)

    Gola, Damian; König, Inke R

    2016-01-01

    Common complex traits may involve multiple genetic and environmental factors and their interactions. Many methods have been proposed to identify these interaction effects, among them several machine learning and data mining methods. These are attractive for identifying interactions because they do not rely on specific genetic model assumptions. To handle the computational burden arising from an exhaustive search, including all possible combinations of factors, filter methods try to select promising factors in advance. Model-based multifactor dimensionality reduction (MB-MDR), a semiparametric machine learning method allowing adjustment for confounding variables and lower level effects, is applied to Genetic Analysis Workshop 19 (GAW19) data to identify interaction effects on different traits. Several filtering methods based on the nearest neighbor algorithm are assessed in terms of compatibility with MB-MDR. Single nucleotide polymorphism (SNP) rs859400 shows a significant interaction effect (corrected p value <0.05) with age on systolic blood pressure (SBP). We identified 23 SNP-SNP interaction effects on hypertension status (HS), 42 interaction effects on SBP, and 26 interaction effects on diastolic blood pressure (DBP). Several of these SNPs are in strong linkage disequilibrium (LD). Three of the interaction effects on HS are identified in filtered subsets. The considered filtering methods seem not to be appropriate to use with MB-MDR. LD pruning is further quality control to be incorporated, which can reduce the combinatorial burden by removing redundant SNPs.

  1. Interactive Internet Based Pendulum for Learning Mechatronics

    Science.gov (United States)

    Sethson, Magnus R.

    2003-01-01

    This paper describes an Internet based remote experimental setup of a double lined pendulum mechanism for students experiments at the M. Sc. Level. Some of the first year experience using this web-based setup in classes is referred. In most of the courses given at the division of mechanical engineering systems at Linkoeping Institute of Technology we provide experimental setups to enhance the teaching Of M.Sc. students. Many of these experimental setups involve mechatronical systems. Disciplines like fluid power, electronics, and mechanics and also software technologies are used in each experiment. As our campus has recently been split into two different cities some new concepts for distance learning have been studied. The one described here tries to implement remotely controlled mechatronic setups for teaching basic programming of real-time operating systems and analysis of the dynamics of mechanical systems. The students control the regulators for the pendulum through a web interface and get measurement results and a movie back through their email. The present setup uses a double linked pendulum that is controlled by a DC-motor and monitored through both camera and angular position sensors. All software needed is hosted on a double-processor PC running the RedHat 7.1. distribution complemented with real-time scheduling using DIAPM-RTAI 1.7. The Internet site is presented to the students using PHP, Apache and MySQL. All of the used software originates from the open source domain. The experience from integrating these technologies and security issues is discussed together with the web-camera interface. One of the important experiences from this project so far is the need for a good visual feedback. This is both in terms of video speed but also in resolution. It has been noticed that when the students makes misstates and wants to search the failure they want clear, large images with high resolution to support their personal believes in the cause of the failure. Even

  2. Profile Monitors Based on Residual Gas Interaction

    CERN Document Server

    Forck, P; Giacomini, T; Peters, A

    2005-01-01

    The precise determination of transverse beam profiles at high current hadron accelerators has to be performed non-interceptingly. Two methods will be discussed based on the excitation of the residual gas molecules by the beam particles: Firstly, by beam induced fluorescence (BIF) light is emitted from the residual gas molecules and is observed with an image intensified CCD camera. At most laboratories N2 gas is inserted, which has a large cross section for emission in the blue wave length region. Secondly, a larger signal strength is achieved by detecting the ionization products in an Ionization Profile Monitor (IPM). By applying an electric field all ionization products are accelerated toward a spatial resolving Micro-Channel Plate. The signal read-out can either be performed by observing the light from a phosphor screen behind the MCP or electronically by a wire array. Methods to achieve a high spatial resolution and a fast turn-by-turn readout capability are discussed. Even though various approaches at dif...

  3. Gallium based low-interaction anions

    Science.gov (United States)

    King, Wayne A.; Kubas, Gregory J.

    2000-01-01

    The present invention provides: a composition of the formula M.sup.+x (Ga(Y).sub.4.sup.-).sub.x where M is a metal selected from the group consisting of lithium, sodium, potassium, cesium, calcium, strontium, thallium, and silver, x is an integer selected from the group consisting of 1 or 2, each Y is a ligand selected from the group consisting of aryl, alkyl, hydride and halide with the proviso that at least one Y is a ligand selected from the group consisting of aryl, alkyl and halide; a composition of the formula (R).sub.x Q.sup.+ Ga(Y).sub.4.sup.- where Q is selected from the group consisting of carbon, nitrogen, sulfur, phosphorus and oxygen, each R is a ligand selected from the group consisting of alkyl, aryl, and hydrogen, x is an integer selected from the group consisting of 3 and 4 depending upon Q, and each Y is a ligand selected from the group consisting of aryl, alkyl, hydride and halide with the proviso that at least one Y is a ligand selected from the group consisting of aryl, alkyl and halide; an ionic polymerization catalyst composition including an active cationic portion and a gallium based weakly coordinating anion; and bridged anion species of the formula M.sup.+x.sub.y [X(Ga(Y.sub.3).sub.z ].sup.-y.sub.x where M is a metal selected from the group consisting of lithium, sodium, potassium, magnesium, cesium, calcium, strontium, thallium, and silver, x is an integer selected from the group consisting of 1 or 2, X is a bridging group between two gallium atoms, y is an integer selected from the group consisting 1 and 2, z is an integer of at least 2, each Y is a ligand selected from the group consisting of aryl, alkyl, hydride and halide with the proviso that at least one Y is a ligand selected from the group consisting of aryl, alkyl and halide.

  4. Modeling, Designing, and Implementing an Avatar-based Interactive Map

    Directory of Open Access Journals (Sweden)

    Stefan Andrei

    2016-03-01

    Full Text Available Designing interactive maps has always been a challenge due to the geographical complexity of the earth’s landscape and the difficulty of resolving details to a high resolution. In the past decade or so, one of the most impressive map-based software application, the Global Positioning System (GPS, has probably the highest level of interaction with the user. This article describes an innovative technique for designing an avatar-based virtual interactive map for the Lamar University Campus, which will entail the buildings’ exterior as well as their interiors. Many universities provide 2D or 3D maps and even interactive maps. However, these maps do not provide a complete interaction with the user. To the best of our knowledge, this project is the first avatar-based interaction game that allows 100% interaction with the user. This work provides tremendous help to the freshman students and visitors of Lamar University. As an important marketing tool, the main objective is to get better visibility of the campus worldwide and to increase the number of students attending Lamar University.

  5. Drug-target interaction prediction from PSSM based evolutionary information.

    Science.gov (United States)

    Mousavian, Zaynab; Khakabimamaghani, Sahand; Kavousi, Kaveh; Masoudi-Nejad, Ali

    2016-01-01

    The labor-intensive and expensive experimental process of drug-target interaction prediction has motivated many researchers to focus on in silico prediction, which leads to the helpful information in supporting the experimental interaction data. Therefore, they have proposed several computational approaches for discovering new drug-target interactions. Several learning-based methods have been increasingly developed which can be categorized into two main groups: similarity-based and feature-based. In this paper, we firstly use the bi-gram features extracted from the Position Specific Scoring Matrix (PSSM) of proteins in predicting drug-target interactions. Our results demonstrate the high-confidence prediction ability of the Bigram-PSSM model in terms of several performance indicators specifically for enzymes and ion channels. Moreover, we investigate the impact of negative selection strategy on the performance of the prediction, which is not widely taken into account in the other relevant studies. This is important, as the number of non-interacting drug-target pairs are usually extremely large in comparison with the number of interacting ones in existing drug-target interaction data. An interesting observation is that different levels of performance reduction have been attained for four datasets when we change the sampling method from the random sampling to the balanced sampling. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. Analysis of Verbal Interactions in Problem-based Learning.

    Science.gov (United States)

    Oh, Sun A; Chung, Eun Kyung; Woo, Young Jong; Han, Eui Ryoung; Kim, Young Ok

    2010-06-01

    Problem-based learning (PBL) is a constructive learning environment that solves ill-structured problems through collaborative learning. The purpose of this study was to analyze the interaction of students and a tutor in a small-group PBL discussion. This study examined how the types of interactions are composed over the meeting. Fourteen third-year subjects from Chonnam National University Medical School, Korea formed two tutorial groups. Two tutorial sessions were videotaped and analyzed. All videotapes were transcribed to analyze the interaction type. The criteria of interaction analysis were learning-oriented interaction (exploratory questioning, cumulative reasoning, handling conflicts about the knowledge), procedural interactions, and irrelevant task interactions. Nearly all discourses between tutors and students were learning-oriented interactions. The results showed that students spent more time on cumulative reasoning. In contrast, tutors implemented more exploratory questioning. Little time was spent on handling conflicts about knowledge and procedural and irrelevant/off-task interactions. To improve critical thinking and problem-solving competence in PBL, we should consider various efforts to encourage discussion about conflicting knowledge. A PBL tutor training program should be provided to facilitate PBL group discussions.

  7. An Interactive Tool for Creating Multi-Agent Systems and Interactive Agent-based Games

    DEFF Research Database (Denmark)

    Lund, Henrik Hautop; Pagliarini, Luigi

    2011-01-01

    Utilizing principles from parallel and distributed processing combined with inspiration from modular robotics, we developed the modular interactive tiles. As an educational tool, the modular interactive tiles facilitate the learning of multi-agent systems and interactive agent-based games....... The modular and physical property of the tiles provides students with hands-on experience in exploring the theoretical aspects underlying multi-agent systems which often appear as challenging to students. By changing the representation of the cognitive challenging aspects of multi-agent systems education...... to a physical (hands-on) one, the challenge may become much easier and fun to face for the students....

  8. Interactive Coherence-Based Façade Modeling

    KAUST Repository

    Musialski, Przemyslaw

    2012-05-01

    We propose a novel interactive framework for modeling building facades from images. Our method is based on the notion of coherence-based editing which allows exploiting partial symmetries across the facade at any level of detail. The proposed workflow mixes manual interaction with automatic splitting and grouping operations based on unsupervised cluster analysis. In contrast to previous work, our approach leads to detailed 3d geometric models with up to several thousand regions per facade. We compare our modeling scheme to others and evaluate our approach in a user study with an experienced user and several novice users.

  9. Movement-based interaction in camera spaces: a conceptual framework

    DEFF Research Database (Denmark)

    Eriksson, Eva; Hansen, Thomas Riisgaard; Lykke-Olesen, Andreas

    2007-01-01

    In this paper we present three concepts that address movement-based interaction using camera tracking. Based on our work with several movementbased projects we present four selected applications, and use these applications to leverage our discussion, and to describe our three main concepts space,...

  10. Interactive Assessment and Course Transformation Using Web-Based Tools.

    Science.gov (United States)

    Byers, Celina

    2002-01-01

    Discusses the need for course assessment that includes the instructor's perception, the student's perception, and the student's performance and describes the roles that Web-based tools can play in the active learning process and in interactive assessment based on experiences with a multimedia production course. (LRW)

  11. An Interactive Multimedia Based Instruction in Experimental Modelling

    DEFF Research Database (Denmark)

    Knudsen, Morten; Nielsen, J.N.; Østergaard, J.

    1997-01-01

    A CD-ROM based interactive multimedia instruction in experimental modelling for Danish Engineering School teachers is described. The content is based on a new sensitivity approach for direct estimation of physical parameters in linear and nonlinear dynamic systems. The presentation is inspired...

  12. Chromium based Framework to include Gaze Interaction in Web Browser

    OpenAIRE

    Kumar, Chandan; Menges, Raphael; Müller, Daniel; Staab, Steffen

    2017-01-01

    EnablingWeb interaction by non-conventional input sources like eyes has great potential to enhance Web accessibility. In this paper, we present a Chromium based inclusive framework to adapt eye gaze events in Web interfaces. The frameworkprovides more utility and control to develop a full featured interactive browser, compared to the related approaches of additional mouse and keyboard emulation orbrowser extensions. We demonstrate the framework through a sophisticated gaze driven Web browser,...

  13. Assessing Bacterial Interactions Using Carbohydrate-Based Microarrays

    Directory of Open Access Journals (Sweden)

    Andrea Flannery

    2015-12-01

    Full Text Available Carbohydrates play a crucial role in host-microorganism interactions and many host glycoconjugates are receptors or co-receptors for microbial binding. Host glycosylation varies with species and location in the body, and this contributes to species specificity and tropism of commensal and pathogenic bacteria. Additionally, bacterial glycosylation is often the first bacterial molecular species encountered and responded to by the host system. Accordingly, characterising and identifying the exact structures involved in these critical interactions is an important priority in deciphering microbial pathogenesis. Carbohydrate-based microarray platforms have been an underused tool for screening bacterial interactions with specific carbohydrate structures, but they are growing in popularity in recent years. In this review, we discuss carbohydrate-based microarrays that have been profiled with whole bacteria, recombinantly expressed adhesins or serum antibodies. Three main types of carbohydrate-based microarray platform are considered; (i conventional carbohydrate or glycan microarrays; (ii whole mucin microarrays; and (iii microarrays constructed from bacterial polysaccharides or their components. Determining the nature of the interactions between bacteria and host can help clarify the molecular mechanisms of carbohydrate-mediated interactions in microbial pathogenesis, infectious disease and host immune response and may lead to new strategies to boost therapeutic treatments.

  14. Drug repurposing based on drug-drug interaction.

    Science.gov (United States)

    Zhou, Bin; Wang, Rong; Wu, Ping; Kong, De-Xin

    2015-02-01

    Given the high risk and lengthy procedure of traditional drug development, drug repurposing is gaining more and more attention. Although many types of drug information have been used to repurpose drugs, drug-drug interaction data, which imply possible physiological effects or targets of drugs, remain unexploited. In this work, similarity of drug interaction was employed to infer similarity of the physiological effects or targets for the drugs. We collected 10,835 drug-drug interactions concerning 1074 drugs, and for 700 of them, drug similarity scores based on drug interaction profiles were computed and rendered using a drug association network with 589 nodes (drugs) and 2375 edges (drug similarity scores). The 589 drugs were clustered into 98 groups with Markov Clustering Algorithm, most of which were significantly correlated with certain drug functions. This indicates that the network can be used to infer the physiological effects of drugs. Furthermore, we evaluated the ability of this drug association network to predict drug targets. The results show that the method is effective for 317 of 561 drugs that have known targets. Comparison of this method with the structure-based approach shows that they are complementary. In summary, this study demonstrates the feasibility of drug repurposing based on drug-drug interaction data. © 2014 John Wiley & Sons A/S.

  15. Observations on Experience and Flow in Movement-Based Interaction

    NARCIS (Netherlands)

    Nijholt, Antinus; Pasch, Marco; van Dijk, Elisabeth M.A.G.; Reidsma, Dennis; Heylen, Dirk K.J.; England, David

    2011-01-01

    Movement-based interfaces assume that their users move. Users have to perform exercises, they have to dance, they have to golf or football, or they want to train particular bodily skills. Many examples of those interfaces exist, sometimes asking for subtle interaction between user and interface and

  16. Computer-Based Interaction Analysis with DEGREE Revisited

    Science.gov (United States)

    Barros, B.; Verdejo, M. F.

    2016-01-01

    We review our research with "DEGREE" and analyse how our work has impacted the collaborative learning community since 2000. Our research is framed within the context of computer-based interaction analysis and the development of computer-supported collaborative learning (CSCL) tools. We identify some aspects of our work which have been…

  17. Map-based mobile services design, interaction and usability

    CERN Document Server

    Meng, Liqiu; Winter, Stephan; Popovich, Vasily

    2008-01-01

    This book reports the newest research and technical achievements on the following theme blocks: Design of mobile map services and its constraints; Typology and usability of mobile map services; Visualization solutions on small displays for time-critical tasks; Mobile map users; Interaction and adaptation in mobile environments; and Applications of map-based mobile services.

  18. Design of Experience and Flow in Movement-based Interaction

    NARCIS (Netherlands)

    Nijholt, Antinus; van Dijk, Elisabeth M.A.G.; Reidsma, Dennis; Egges, A.; Kamphuis, A.; Overmars, M.

    2008-01-01

    Movement-based and exertion interfaces assume that their users move. Users have to perform exercises, they have to dance, they have to golf or football, or they want to train particular bodily skills. Many examples of those interfaces exist, sometimes asking for subtle interaction between user and

  19. Interactions between acid- and base-functionalized surfaces

    NARCIS (Netherlands)

    Giesbers, M.; Kleijn, J.M.; Cohen Stuart, M.A.

    2002-01-01

    In this paper we present an AFM force study on interactions between chemically modified surfaces. Surfaces with terminal groups of either NH2 or COOH were obtained by chemisorption of a silane-based compound (3-amino-propyltriethoxysilane) on silica or a thiol compound (11-mercapto undecanoic acid)

  20. Student Satisfaction in Interactive Engagement-Based Physics Classes

    Science.gov (United States)

    Gaffney, Jon D. H.; Gaffney, Amy L. Housley

    2016-01-01

    Interactive engagement-based (IE) physics classes have the potential to invigorate and motivate students, but students may resist or oppose the pedagogy. Understanding the major influences on student satisfaction is a key to successful implementation of such courses. In this study, we note that one of the major differences between IE and…

  1. Optimization of interactive visual-similarity-based search

    NARCIS (Netherlands)

    Nguyen, G.P.; Worring, M.

    2008-01-01

    At one end of the spectrum, research in interactive content-based retrieval concentrates on machine learning methods for effective use of relevance feedback. On the other end, the information visualization community focuses on effective methods for conveying information to the user. What is lacking

  2. A Microcomputer-Based Interactive Presentation Development System.

    Science.gov (United States)

    Moreau, Dennis R.; Dominick, Wayne D.

    1988-01-01

    Reviews research and development projects sponsored by the National Aeronautics and Space Administration (NASA) that address microcomputer-based support for instructional activities at the University of Southwestern Louisiana. Highlights include a graphics project, local area networks, and the Interactive Presentation Development System, which is…

  3. Web-Based Learning Interaction and Learning Styles.

    Science.gov (United States)

    Sabry, Khaled; Baldwin, Lynne

    2003-01-01

    Reports a study exploring the learning styles and perceptions of undergraduate and postgraduate students at Brunel University (United Kingdom) in relation to using the Web for learning. Explores the sequential/global learning style dimension in relation to three categories of Web-based interaction: learner-tutor, learner-leaner, and…

  4. An interactive web-based extranet system model for managing ...

    African Journals Online (AJOL)

    The methodology of the special software to be developed involved the collections of main modern tools and technologies, such as Apache Web Server, PHP and MySQL which can work on any platform, such as windows and Linus. Keywords: Extranet-Model, Interactive, Web-Based, Students, Academic, Records ...

  5. Theoretical analysis of noncanonical base pairing interactions in ...

    Indian Academy of Sciences (India)

    PRAKASH KUMAR

    In keeping with this general trend, all the systems with only one hydrogen bond between the bases, on relaxed optimization, show huge RMS deviation and lead to significant improvements in their interaction energies. As expected, the hydrogen bonding patterns in their relaxed geometries are also very different from their ...

  6. Learning Neuroscience: An Interactive Case-Based Online Network (ICON).

    Science.gov (United States)

    Quattrochi, James J.; Pasquale, Susan; Cerva, Barbara; Lester, John E.

    2002-01-01

    Presents an interactive, case-based online network (ICON) that provides a learning environment that integrates student thinking across different concentration tracks and allows students to get away from interpreting vast amounts of available information, move toward selecting useful information, recognize discriminating findings, and build a…

  7. Protein-protein interaction based on pairwise similarity

    Directory of Open Access Journals (Sweden)

    Zaki Nazar

    2009-05-01

    Full Text Available Abstract Background Protein-protein interaction (PPI is essential to most biological processes. Abnormal interactions may have implications in a number of neurological syndromes. Given that the association and dissociation of protein molecules is crucial, computational tools capable of effectively identifying PPI are desirable. In this paper, we propose a simple yet effective method to detect PPI based on pairwise similarity and using only the primary structure of the protein. The PPI based on Pairwise Similarity (PPI-PS method consists of a representation of each protein sequence by a vector of pairwise similarities against large subsequences of amino acids created by a shifting window which passes over concatenated protein training sequences. Each coordinate of this vector is typically the E-value of the Smith-Waterman score. These vectors are then used to compute the kernel matrix which will be exploited in conjunction with support vector machines. Results To assess the ability of the proposed method to recognize the difference between "interacted" and "non-interacted" proteins pairs, we applied it on different datasets from the available yeast saccharomyces cerevisiae protein interaction. The proposed method achieved reasonable improvement over the existing state-of-the-art methods for PPI prediction. Conclusion Pairwise similarity score provides a relevant measure of similarity between protein sequences. This similarity incorporates biological knowledge about proteins and it is extremely powerful when combined with support vector machine to predict PPI.

  8. Traffic and Driving Simulator Based on Architecture of Interactive Motion

    Science.gov (United States)

    Paz, Alexander; Veeramisti, Naveen; Khaddar, Romesh; de la Fuente-Mella, Hanns; Modorcea, Luiza

    2015-01-01

    This study proposes an architecture for an interactive motion-based traffic simulation environment. In order to enhance modeling realism involving actual human beings, the proposed architecture integrates multiple types of simulation, including: (i) motion-based driving simulation, (ii) pedestrian simulation, (iii) motorcycling and bicycling simulation, and (iv) traffic flow simulation. The architecture has been designed to enable the simulation of the entire network; as a result, the actual driver, pedestrian, and bike rider can navigate anywhere in the system. In addition, the background traffic interacts with the actual human beings. This is accomplished by using a hybrid mesomicroscopic traffic flow simulation modeling approach. The mesoscopic traffic flow simulation model loads the results of a user equilibrium traffic assignment solution and propagates the corresponding traffic through the entire system. The microscopic traffic flow simulation model provides background traffic around the vicinities where actual human beings are navigating the system. The two traffic flow simulation models interact continuously to update system conditions based on the interactions between actual humans and the fully simulated entities. Implementation efforts are currently in progress and some preliminary tests of individual components have been conducted. The implementation of the proposed architecture faces significant challenges ranging from multiplatform and multilanguage integration to multievent communication and coordination. PMID:26491711

  9. Innovation in preregistration midwifery education: Web based interactive storytelling learning.

    Science.gov (United States)

    Scamell, Mandie; Hanley, Thomas

    2017-07-01

    through a critical description of the implementation of a web based interactive storytelling learning activity introduced into an undergraduate, preregistration midwifery education programme, this paper will explore how low-cost, low-fidelity online storytelling, designed using Moodle, can be used to enhance students' understanding of compassion and empathy in practice. cross sectional sample of first year undergraduate Midwifery students (n111) METHOD: drawing from both research and audit data collected in an Higher Education Institution in London England, the paper presents the case for using web based technology to create a sustainable model for midwifery education. initial results indicate that it is both the low cost and positive student evaluations of web based interactive storytelling, which make this approach to preregistration midwifery education which suggests that this approach has significant potential for learning and teaching in midwifery education in diverse settings around the world. Or how about: global relevance? . Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. WAVE: Interactive Wave-based Sound Propagation for Virtual Environments.

    Science.gov (United States)

    Mehra, Ravish; Rungta, Atul; Golas, Abhinav; Ming Lin; Manocha, Dinesh

    2015-04-01

    We present an interactive wave-based sound propagation system that generates accurate, realistic sound in virtual environments for dynamic (moving) sources and listeners. We propose a novel algorithm to accurately solve the wave equation for dynamic sources and listeners using a combination of precomputation techniques and GPU-based runtime evaluation. Our system can handle large environments typically used in VR applications, compute spatial sound corresponding to listener's motion (including head tracking) and handle both omnidirectional and directional sources, all at interactive rates. As compared to prior wave-based techniques applied to large scenes with moving sources, we observe significant improvement in runtime memory. The overall sound-propagation and rendering system has been integrated with the Half-Life 2 game engine, Oculus-Rift head-mounted display, and the Xbox game controller to enable users to experience high-quality acoustic effects (e.g., amplification, diffraction low-passing, high-order scattering) and spatial audio, based on their interactions in the VR application. We provide the results of preliminary user evaluations, conducted to study the impact of wave-based acoustic effects and spatial audio on users' navigation performance in virtual environments.

  11. Deep-Learning-Based Drug-Target Interaction Prediction.

    Science.gov (United States)

    Wen, Ming; Zhang, Zhimin; Niu, Shaoyu; Sha, Haozhi; Yang, Ruihan; Yun, Yonghuan; Lu, Hongmei

    2017-04-07

    Identifying interactions between known drugs and targets is a major challenge in drug repositioning. In silico prediction of drug-target interaction (DTI) can speed up the expensive and time-consuming experimental work by providing the most potent DTIs. In silico prediction of DTI can also provide insights about the potential drug-drug interaction and promote the exploration of drug side effects. Traditionally, the performance of DTI prediction depends heavily on the descriptors used to represent the drugs and the target proteins. In this paper, to accurately predict new DTIs between approved drugs and targets without separating the targets into different classes, we developed a deep-learning-based algorithmic framework named DeepDTIs. It first abstracts representations from raw input descriptors using unsupervised pretraining and then applies known label pairs of interaction to build a classification model. Compared with other methods, it is found that DeepDTIs reaches or outperforms other state-of-the-art methods. The DeepDTIs can be further used to predict whether a new drug targets to some existing targets or whether a new target interacts with some existing drugs.

  12. Web-based Interactive Landform Simulation Model - Grand Canyon

    Science.gov (United States)

    Luo, W.; Pelletier, J. D.; Duffin, K.; Ormand, C. J.; Hung, W.; Iverson, E. A.; Shernoff, D.; Zhai, X.; Chowdary, A.

    2013-12-01

    Earth science educators need interactive tools to engage and enable students to better understand how Earth systems work over geologic time scales. The evolution of landforms is ripe for interactive, inquiry-based learning exercises because landforms exist all around us. The Web-based Interactive Landform Simulation Model - Grand Canyon (WILSIM-GC, http://serc.carleton.edu/landform/) is a continuation and upgrade of the simple cellular automata (CA) rule-based model (WILSIM-CA, http://www.niu.edu/landform/) that can be accessed from anywhere with an Internet connection. Major improvements in WILSIM-GC include adopting a physically based model and the latest Java technology. The physically based model is incorporated to illustrate the fluvial processes involved in land-sculpting pertaining to the development and evolution of one of the most famous landforms on Earth: the Grand Canyon. It is hoped that this focus on a famous and specific landscape will attract greater student interest and provide opportunities for students to learn not only how different processes interact to form the landform we observe today, but also how models and data are used together to enhance our understanding of the processes involved. The latest development in Java technology (such as Java OpenGL for access to ubiquitous fast graphics hardware, Trusted Applet for file input and output, and multithreaded ability to take advantage of modern multi-core CPUs) are incorporated into building WILSIM-GC and active, standards-aligned curricula materials guided by educational psychology theory on science learning will be developed to accompany the model. This project is funded NSF-TUES program.

  13. Violent Interaction Detection in Video Based on Deep Learning

    Science.gov (United States)

    Zhou, Peipei; Ding, Qinghai; Luo, Haibo; Hou, Xinglin

    2017-06-01

    Violent interaction detection is of vital importance in some video surveillance scenarios like railway stations, prisons or psychiatric centres. Existing vision-based methods are mainly based on hand-crafted features such as statistic features between motion regions, leading to a poor adaptability to another dataset. En lightened by the development of convolutional networks on common activity recognition, we construct a FightNet to represent the complicated visual violence interaction. In this paper, a new input modality, image acceleration field is proposed to better extract the motion attributes. Firstly, each video is framed as RGB images. Secondly, optical flow field is computed using the consecutive frames and acceleration field is obtained according to the optical flow field. Thirdly, the FightNet is trained with three kinds of input modalities, i.e., RGB images for spatial networks, optical flow images and acceleration images for temporal networks. By fusing results from different inputs, we conclude whether a video tells a violent event or not. To provide researchers a common ground for comparison, we have collected a violent interaction dataset (VID), containing 2314 videos with 1077 fight ones and 1237 no-fight ones. By comparison with other algorithms, experimental results demonstrate that the proposed model for violent interaction detection shows higher accuracy and better robustness.

  14. An Opinion Interactive Model Based on Individual Persuasiveness.

    Science.gov (United States)

    Zhou, Xin; Chen, Bin; Liu, Liang; Ma, Liang; Qiu, Xiaogang

    2015-01-01

    In order to study the formation process of group opinion in real life, we put forward a new opinion interactive model based on Deffuant model and its improved models in this paper because current models of opinion dynamics lack considering individual persuasiveness. Our model has following advantages: firstly persuasiveness is added to individual's attributes reflecting the importance of persuasiveness, which means that all the individuals are different from others; secondly probability is introduced in the course of interaction which simulates the uncertainty of interaction. In Monte Carlo simulation experiments, sensitivity analysis including the influence of randomness, initial persuasiveness distribution, and number of individuals is studied at first; what comes next is that the range of common opinion based on the initial persuasiveness distribution can be predicted. Simulation experiment results show that when the initial values of agents are fixed, no matter how many times independently replicated experiments, the common opinion will converge at a certain point; however the number of iterations will not always be the same; the range of common opinion can be predicted when initial distribution of opinion and persuasiveness are given. As a result, this model can reflect and interpret some phenomena of opinion interaction in realistic society.

  15. An Integrated Approach for Creating Service-Based Interactive Applications

    Science.gov (United States)

    Feldmann, Marius; Janeiro, Jordan; Nestler, Tobias; Hübsch, Gerald; Jugel, Uwe; Preussner, André; Schill, Alexander

    While the implementation of business logic and business processes based on service-oriented architectures is well-understood and covered by existing development approaches, integrated concepts that empower users to exploit the Internet of Services to create complex interactive applications are missing. In this paper, we present an integrated approach that fills this gap. Our approach builds upon service annotations that add meta-information related to user interface generation, service dependencies, and service composition to existing service descriptions. Services can be composed visually to complex interactive applications based on these annotations without the need to write any code. The application code is generated completely from the service composition description. Our approach is able to support heterogeneous target environments ranging from client/server architectures to mobile platforms.

  16. Using Agent Based Modeling (ABM) to Develop Cultural Interaction Simulations

    Science.gov (United States)

    Drucker, Nick; Jones, Phillip N.

    2012-01-01

    Today, most cultural training is based on or built around "cultural engagements" or discrete interactions between the individual learner and one or more cultural "others". Often, success in the engagement is the end or the objective. In reality, these interactions usually involve secondary and tertiary effects with potentially wide ranging consequences. The concern is that learning culture within a strict engagement context might lead to "checklist" cultural thinking that will not empower learners to understand the full consequence of their actions. We propose the use of agent based modeling (ABM) to collect, store, and, simulating the effects of social networks, promulgate engagement effects over time, distance, and consequence. The ABM development allows for rapid modification to re-create any number of population types, extending the applicability of the model to any requirement for social modeling.

  17. Student satisfaction in interactive engagement-based physics classes

    Science.gov (United States)

    Gaffney, Jon D. H.; Gaffney, Amy L. Housley

    2016-12-01

    Interactive engagement-based (IE) physics classes have the potential to invigorate and motivate students, but students may resist or oppose the pedagogy. Understanding the major influences on student satisfaction is a key to successful implementation of such courses. In this study, we note that one of the major differences between IE and traditional physics classes lies in the interpersonal relationships between the instructor and students. Therefore, we introduce the interpersonal communication constructs of instructor credibility and facework as possible frameworks for understanding how instructors and students navigate the new space of interactions. By interpreting survey data (N =161 respondents in eight sections of an IE introductory algebra-based physics course), we found both frameworks to be useful in explaining variance in student ratings of their satisfaction in the course, although we are unable to distinguish at this point whether instructor credibility acts as a mediating variable between facework and course satisfaction.

  18. Cytoscape Web: an interactive web-based network browser.

    Science.gov (United States)

    Lopes, Christian T; Franz, Max; Kazi, Farzana; Donaldson, Sylva L; Morris, Quaid; Bader, Gary D

    2010-09-15

    Cytoscape Web is a web-based network visualization tool-modeled after Cytoscape-which is open source, interactive, customizable and easily integrated into web sites. Multiple file exchange formats can be used to load data into Cytoscape Web, including GraphML, XGMML and SIF. Cytoscape Web is implemented in Flex/ActionScript with a JavaScript API and is freely available at http://cytoscapeweb.cytoscape.org/.

  19. Competence–Based Support of Interaction between Business Network Members

    OpenAIRE

    Smirnov, Alexander; Kashevnik, Alexey; Shilov, Nikolay

    2008-01-01

    In a complicated business network finding a supplier can be a very time consuming task. The technology of competence management is aimed to support such kind of tasks. The paper presents an approach to support interaction between business network members based on such technologies as competence management and knowledge management. The conceptual models of the context-driven competence management system and production network member competence profile are described. The usage of th...

  20. Quadrupole Beam-Based Alignment in the RHIC Interaction Regions

    Energy Technology Data Exchange (ETDEWEB)

    T. Satogata, J. Ziegler

    2011-03-01

    Continued beam-based alignment (BBA) efforts have provided significant benefit to both heavy ion and polarized proton operations at RHIC. Recent studies demonstrated previously unknown systematic beam position monitor (BPM) offset errors and produced accurate measurements of individual BPM offsets in the experiment interaction regions. Here we describe the algorithm used to collect and analyze data during the 2010 and early 2011 RHIC runs and the results of these measurements.

  1. [Expression of rice dwarf virus outer coat protein gene(S8) in insect cells].

    Science.gov (United States)

    Li, S; Liu, H; Chen, Z; Li, Y

    2001-04-01

    Outer coat protein gene(S8) of RDV was cloned into the transfer vector pVL 1393 to construct a recombinant vector pVL1393-S8. The recombinant vector pVL1393-S8 and the linear baculovirus RP23. LacZ were cotransfected into sf9 cells to produce the recombinant virus RP23-S8. RP23-S8 infected sf9 cells were collected and analysed by SDS-PAGE and Western-blot. The results showed that the S8 gene of RDV was expressed in sf9 cells and the expression level of sf9 cells was higher between 72-96 h after infected.

  2. A genome-wide MeSH-based literature mining system predicts implicit gene-to-gene relationships and networks.

    Science.gov (United States)

    Xiang, Zuoshuang; Qin, Tingting; Qin, Zhaohui S; He, Yongqun

    2013-10-16

    The large amount of literature in the post-genomics era enables the study of gene interactions and networks using all available articles published for a specific organism. MeSH is a controlled vocabulary of medical and scientific terms that is used by biomedical scientists to manually index articles in the PubMed literature database. We hypothesized that genome-wide gene-MeSH term associations from the PubMed literature database could be used to predict implicit gene-to-gene relationships and networks. While the gene-MeSH associations have been used to detect gene-gene interactions in some studies, different methods have not been well compared, and such a strategy has not been evaluated for a genome-wide literature analysis. Genome-wide literature mining of gene-to-gene interactions allows ranking of the best gene interactions and investigation of comprehensive biological networks at a genome level. The genome-wide GenoMesh literature mining algorithm was developed by sequentially generating a gene-article matrix, a normalized gene-MeSH term matrix, and a gene-gene matrix. The gene-gene matrix relies on the calculation of pairwise gene dissimilarities based on gene-MeSH relationships. An optimized dissimilarity score was identified from six well-studied functions based on a receiver operating characteristic (ROC) analysis. Based on the studies with well-studied Escherichia coli and less-studied Brucella spp., GenoMesh was found to accurately identify gene functions using weighted MeSH terms, predict gene-gene interactions not reported in the literature, and cluster all the genes studied from an organism using the MeSH-based gene-gene matrix. A web-based GenoMesh literature mining program is also available at: http://genomesh.hegroup.org. GenoMesh also predicts gene interactions and networks among genes associated with specific MeSH terms or user-selected gene lists. The GenoMesh algorithm and web program provide the first genome-wide, MeSH-based literature mining

  3. A genome-wide MeSH-based literature mining system predicts implicit gene-to-gene relationships and networks

    Science.gov (United States)

    2013-01-01

    Background The large amount of literature in the post-genomics era enables the study of gene interactions and networks using all available articles published for a specific organism. MeSH is a controlled vocabulary of medical and scientific terms that is used by biomedical scientists to manually index articles in the PubMed literature database. We hypothesized that genome-wide gene-MeSH term associations from the PubMed literature database could be used to predict implicit gene-to-gene relationships and networks. While the gene-MeSH associations have been used to detect gene-gene interactions in some studies, different methods have not been well compared, and such a strategy has not been evaluated for a genome-wide literature analysis. Genome-wide literature mining of gene-to-gene interactions allows ranking of the best gene interactions and investigation of comprehensive biological networks at a genome level. Results The genome-wide GenoMesh literature mining algorithm was developed by sequentially generating a gene-article matrix, a normalized gene-MeSH term matrix, and a gene-gene matrix. The gene-gene matrix relies on the calculation of pairwise gene dissimilarities based on gene-MeSH relationships. An optimized dissimilarity score was identified from six well-studied functions based on a receiver operating characteristic (ROC) analysis. Based on the studies with well-studied Escherichia coli and less-studied Brucella spp., GenoMesh was found to accurately identify gene functions using weighted MeSH terms, predict gene-gene interactions not reported in the literature, and cluster all the genes studied from an organism using the MeSH-based gene-gene matrix. A web-based GenoMesh literature mining program is also available at: http://genomesh.hegroup.org. GenoMesh also predicts gene interactions and networks among genes associated with specific MeSH terms or user-selected gene lists. Conclusions The GenoMesh algorithm and web program provide the first genome

  4. Web-based interactive drone control using hand gesture

    Science.gov (United States)

    Zhao, Zhenfei; Luo, Hao; Song, Guang-Hua; Chen, Zhou; Lu, Zhe-Ming; Wu, Xiaofeng

    2018-01-01

    This paper develops a drone control prototype based on web technology with the aid of hand gesture. The uplink control command and downlink data (e.g., video) are transmitted by WiFi communication, and all the information exchange is realized on web. The control command is translated from various predetermined hand gestures. Specifically, the hardware of this friendly interactive control system is composed by a quadrotor drone, a computer vision-based hand gesture sensor, and a cost-effective computer. The software is simplified as a web-based user interface program. Aided by natural hand gestures, this system significantly reduces the complexity of traditional human-computer interaction, making remote drone operation more intuitive. Meanwhile, a web-based automatic control mode is provided in addition to the hand gesture control mode. For both operation modes, no extra application program is needed to be installed on the computer. Experimental results demonstrate the effectiveness and efficiency of the proposed system, including control accuracy, operation latency, etc. This system can be used in many applications such as controlling a drone in global positioning system denied environment or by handlers without professional drone control knowledge since it is easy to get started.

  5. RPLsh: An Interactive Shell for Stack-based Numerical Computation

    Science.gov (United States)

    Rauch, Kevin P.

    RPL shell or RPLsh, is an interactive numerical shell designed to combine the convenience of a hand-held calculator with the computational power and advanced numerical functionality of a workstation. The user interface is modelled after stack-based scientific calculators such as those made by Hewlett-Packard RPL is the name of the Forth-like programming language used in the HP 48 series), but includes many features not found in hand-held devices, such as a multi-threaded kernel with job control, integrated extended precision arithmetic, a large library of special functions, and a dynamic, resizable window display. As a native C/C++ application, it is over 1000 times faster than HP 48 emulators (e.g. Emu48 ) in simple benchmarks; for extended precision numerical analysis, its performance can exceed that of Mathematica by similar amounts. Current development focuses on interactive user functionality, with comprehensive programming and debugging support to follow.

  6. Point based interactive image segmentation using multiquadrics splines

    Science.gov (United States)

    Meena, Sachin; Duraisamy, Prakash; Palniappan, Kannappan; Seetharaman, Guna

    2017-05-01

    Multiquadrics (MQ) are radial basis spline function that can provide an efficient interpolation of data points located in a high dimensional space. MQ were developed by Hardy to approximate geographical surfaces and terrain modelling. In this paper we frame the task of interactive image segmentation as a semi-supervised interpolation where an interpolating function learned from the user provided seed points is used to predict the labels of unlabeled pixel and the spline function used in the semi-supervised interpolation is MQ. This semi-supervised interpolation framework has a nice closed form solution which along with the fact that MQ is a radial basis spline function lead to a very fast interactive image segmentation process. Quantitative and qualitative results on the standard datasets show that MQ outperforms other regression based methods, GEBS, Ridge Regression and Logistic Regression, and popular methods like Graph Cut,4 Random Walk and Random Forest.6

  7. Interactive cell segmentation based on phase contrast optics.

    Science.gov (United States)

    Su, Hang; Su, Zhou; Zheng, Shibao; Yang, Hua; Wei, Sha

    2014-01-01

    Cell segmentation in phase contrast microscopy images lays a crucial foundation for numerous subsequent computer-aided cell image analysis, but it encounters many unsolved challenges due to image qualities and artifacts caused by phase contrast optics. Addressing the unsolved challenges, the authors propose an interactive cell segmentation scheme over phase retardation features. After partitioning the images into phase homogeneous atoms, human annotations are propagated to unlabeled atoms over an affinity graph that is learned based on discrimination analysis. Then, an active query strategy is proposed for which the most informative unlabeled atom is selected for annotation, which is also propagated to the other unlabeled atoms. Cell segmentation converges to quality results after several rounds of interactions involving both the user's intentions and characteristics of image features. Experimental results demonstrate that cells with different optical properties are well segmented via the proposed approach.

  8. Research on Goods and the Ship Interaction Based on ADAMS

    Directory of Open Access Journals (Sweden)

    Song Fangzhen

    2017-01-01

    Full Text Available The equivalent method of the relative movement goods on board is discussed in details. This method is to establish dynamic model based on moving trajectory of gravity-center for goods and to take rigid body geometric model with the trajectory as constraints in ADAMS. The difference of simulation methods for the different goods in carrier rolling is compared. The interact of relative moving objects with bulk carrier is discussed by using the ADAMS model. It is verified that the ballast water can maintain the ship’s stability by means of the ADAMS model.

  9. Optimization of morphing flaps based on fluid structure interaction modeling

    DEFF Research Database (Denmark)

    Barlas, Athanasios; Akay, Busra

    2018-01-01

    This article describes the design optimization of morphing trailing edge flaps for wind turbines with ‘smart blades’. A high fidelity Fluid Structure Interaction (FSI) simulation framework is utilized, comprised of 2D Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) models....... A coupled aero-structural simulation of a 10% chordwise length morphing trailing edge flap for a 4 MW wind turbine rotor is carried out and response surfaces are produced with respect to the flap internal geometry design parameters for the design conditions. Surrogate model based optimization is applied...

  10. POKEHEAD: An Open Source Interactive Headphone Based HCI Platform

    DEFF Research Database (Denmark)

    Højlund, Marie; Trento, Stefano; Goudarzi, Visda

    2012-01-01

    This paper introduces a novel interactive, human-computer interface and remote social communication system based on an augmented, hi-fidelity audio headphone platform. Specifically, this system- named Pokehead, currently utilizes the DUL embedded open-source accelerometer platform to gather 3-axis......, open source implementation. Our rapid prototype proved to be robust enough to work in performance for demonstration purposes and serves as a working proof of concept. In this paper we provide a technical description of our prototype, illustrate the context and motivation behind the project, and offer...

  11. A GDP fluctuation model based on interacting firms

    Science.gov (United States)

    Li, Honggang; Gao, Yan

    2008-09-01

    A distinctive feature of the market economies is the short-run fluctuations in output around the trend of long-run growth over time, and we regard this feature is internal to complex economic systems composed of interacting heterogeneous units. To explore such internal mechanisms of macroeconomic fluctuations, we present a multi-agent Keynesian theory-based model, which can provide a good approximation to the key empirical features of the western business cycles in the 20th Century, such as the structure of the autocorrelation function of overall output growth, correlations between the output growth of individual agents over time, the distribution of recessions, etc.

  12. Interactive multimedia-based teaching material for 3-dimensional geometry

    Science.gov (United States)

    Prabowo, A.; Anggoro, R. P.; Astuti, D.; Fahmi, S.

    2017-12-01

    This study aims to develop the interactive multimedia-based teaching material for 3-dimensional geometry in junior high school. The product was produced through the stages of define, design, develop, and disseminate. Two media experts and two teaching experts had validated it. They judged that the product developed was valid. It had been revised based on their advice. It has been disseminated to 15 mathematics teachers and tried to 30 students of junior high school. Teachers stated that this product gives a new form of teaching material in 3-dimensional geometry. According to the student, the product is interesting. It can motivate them to study mathematics, help them to master the material and increase their interest in mathematics.

  13. Thermoelectric properties of an interacting quantum dot based heat engine

    Science.gov (United States)

    Erdman, Paolo Andrea; Mazza, Francesco; Bosisio, Riccardo; Benenti, Giuliano; Fazio, Rosario; Taddei, Fabio

    2017-06-01

    We study the thermoelectric properties and heat-to-work conversion performance of an interacting, multilevel quantum dot (QD) weakly coupled to electronic reservoirs. We focus on the sequential tunneling regime. The dynamics of the charge in the QD is studied by means of master equations for the probabilities of occupation. From here we compute the charge and heat currents in the linear response regime. Assuming a generic multiterminal setup, and for low temperatures (quantum limit), we obtain analytical expressions for the transport coefficients which account for the interplay between interactions (charging energy) and level quantization. In the case of systems with two and three terminals we derive formulas for the power factor Q and the figure of merit Z T for a QD-based heat engine, identifying optimal working conditions which maximize output power and efficiency of heat-to-work conversion. Beyond the linear response we concentrate on the two-terminal setup. We first study the thermoelectric nonlinear coefficients assessing the consequences of large temperature and voltage biases, focusing on the breakdown of the Onsager reciprocal relation between thermopower and Peltier coefficient. We then investigate the conditions which optimize the performance of a heat engine, finding that in the quantum limit output power and efficiency at maximum power can almost be simultaneously maximized by choosing appropriate values of electrochemical potential and bias voltage. At last we study how energy level degeneracy can increase the output power.

  14. Asymmetric radiation transfer based on linear light-matter interaction

    Science.gov (United States)

    Jia, Zi-xun; Shuai, Yong; Zhang, Jia-hui; Tan, He-ping

    2017-11-01

    In this paper, asymmetric radiation transfer based on linear light-matter interaction has been proposed. Two naturally different numerical methods, finite difference time domain (FDTD) and rigorous coupled wave analysis (RCWA), are utilized to verify that asymmetric radiation transfer can exist for linear plasmonic meta-material. The overall asymmetry has been introduced to evaluate bifacial transmission. Physics for the asymmetric optical responses have been understood via electromagnetic field distributions. Dispersion relation for surface plasmon polariton (SPP) and temporal coupled mode theory (TCMT) have been employed to verify the physics discussed in the paper. Geometric effects and the disappearing of asymmetric transmission have also been investigated. The results gained herein broaden the cognition of linear optical system, facilitate the design of novel energy harvesting device.

  15. Progress in EEG-Based Brain Robot Interaction Systems

    Science.gov (United States)

    Li, Mengfan; Niu, Linwei; Xian, Bin; Zeng, Ming; Chen, Genshe

    2017-01-01

    The most popular noninvasive Brain Robot Interaction (BRI) technology uses the electroencephalogram- (EEG-) based Brain Computer Interface (BCI), to serve as an additional communication channel, for robot control via brainwaves. This technology is promising for elderly or disabled patient assistance with daily life. The key issue of a BRI system is to identify human mental activities, by decoding brainwaves, acquired with an EEG device. Compared with other BCI applications, such as word speller, the development of these applications may be more challenging since control of robot systems via brainwaves must consider surrounding environment feedback in real-time, robot mechanical kinematics, and dynamics, as well as robot control architecture and behavior. This article reviews the major techniques needed for developing BRI systems. In this review article, we first briefly introduce the background and development of mind-controlled robot technologies. Second, we discuss the EEG-based brain signal models with respect to generating principles, evoking mechanisms, and experimental paradigms. Subsequently, we review in detail commonly used methods for decoding brain signals, namely, preprocessing, feature extraction, and feature classification, and summarize several typical application examples. Next, we describe a few BRI applications, including wheelchairs, manipulators, drones, and humanoid robots with respect to synchronous and asynchronous BCI-based techniques. Finally, we address some existing problems and challenges with future BRI techniques. PMID:28484488

  16. Progress in EEG-Based Brain Robot Interaction Systems

    Directory of Open Access Journals (Sweden)

    Xiaoqian Mao

    2017-01-01

    Full Text Available The most popular noninvasive Brain Robot Interaction (BRI technology uses the electroencephalogram- (EEG- based Brain Computer Interface (BCI, to serve as an additional communication channel, for robot control via brainwaves. This technology is promising for elderly or disabled patient assistance with daily life. The key issue of a BRI system is to identify human mental activities, by decoding brainwaves, acquired with an EEG device. Compared with other BCI applications, such as word speller, the development of these applications may be more challenging since control of robot systems via brainwaves must consider surrounding environment feedback in real-time, robot mechanical kinematics, and dynamics, as well as robot control architecture and behavior. This article reviews the major techniques needed for developing BRI systems. In this review article, we first briefly introduce the background and development of mind-controlled robot technologies. Second, we discuss the EEG-based brain signal models with respect to generating principles, evoking mechanisms, and experimental paradigms. Subsequently, we review in detail commonly used methods for decoding brain signals, namely, preprocessing, feature extraction, and feature classification, and summarize several typical application examples. Next, we describe a few BRI applications, including wheelchairs, manipulators, drones, and humanoid robots with respect to synchronous and asynchronous BCI-based techniques. Finally, we address some existing problems and challenges with future BRI techniques.

  17. A Comparison of Interaction in AV-based and Internet-based Distance Courses

    Directory of Open Access Journals (Sweden)

    Melodee Landis

    2001-04-01

    Full Text Available At the center of the debate over the viability of distance education is whether the newer electronic technologies can offer enough interaction to maintain quality learner outcomes and critical mass. Two of the most commonly used forms of distance education are 1 two-way, fully interactive audio-video classrooms and 2 on-line instruction through the Internet or Worldwide Web. This study used qualitative methods to compare and contrast the interaction that occurred in distance learning courses offered via each medium. The research process confirmed findings that there were fundamental differences in the interaction that occurred in the two environments. On-line interaction is so profoundly different than interaction in the traditional and AV-based class room that it appears instructors and students will need a substantial period of adjustment to feel comfortable with it and to fully appreciate its value. It appears that, as distance teaching and learning moves to a “mixed media” approach to teaching and learning, how interaction is handled with each of the media may be important to the success of a distance program.

  18. Enhancing food engineering education with interactive web-based simulations

    Directory of Open Access Journals (Sweden)

    Alexandros Koulouris

    2015-04-01

    Full Text Available In the traditional deductive approach in teaching any engineering topic, teachers would first expose students to the derivation of the equations that govern the behavior of a physical system and then demonstrate the use of equations through a limited number of textbook examples. This methodology, however, is rarely adequate to unmask the cause-effect and quantitative relationships between the system variables that the equations embody. Web-based simulation, which is the integration of simulation and internet technologies, has the potential to enhance the learning experience by offering an interactive and easily accessible platform for quick and effortless experimentation with physical phenomena.This paper presents the design and development of a web-based platform for teaching basic food engineering phenomena to food technology students. The platform contains a variety of modules (“virtual experiments” covering the topics of mass and energy balances, fluid mechanics and heat transfer. In this paper, the design and development of three modules for mass balances and heat transfer is presented. Each webpage representing an educational module has the following features: visualization of the studied phenomenon through graphs, charts or videos, computation through a mathematical model and experimentation.  The student is allowed to edit key parameters of the phenomenon and observe the effect of these changes on the outputs. Experimentation can be done in a free or guided fashion with a set of prefabricated examples that students can run and self-test their knowledge by answering multiple-choice questions.

  19. Pendaphonics: A Tangible Pendulum-based Sonic Interaction Experience

    DEFF Research Database (Denmark)

    Overholt, Daniel; Hansen, Anne-Marie S.; Burleson, Winslow

    2009-01-01

    Pendaphonics is a tangible physical-digital-sonic environment and interactive system that engages users in individual, collaborative, group, and distributed interactive experiences. The development of this system, as an element of urban revitalization and as a trans-disciplinary research endeavor...... along with descriptions of the broad potential of this system as a compositional and choreographic tool, an educational exhibit and classroom manipulative, and as an interface that facilitates playful interaction, exploration, discovery and creativity.......Pendaphonics is a tangible physical-digital-sonic environment and interactive system that engages users in individual, collaborative, group, and distributed interactive experiences. The development of this system, as an element of urban revitalization and as a trans-disciplinary research endeavor......, and is now active within five different research university interaction laboratories. This paper presents the development process and findings from observations and evaluation of Pendaphonics’ users and the social interaction patterns among performers and members of the public. In particular, the repeated...

  20. Evaluating user interactions with clinical information systems: a model based on human-computer interaction models.

    Science.gov (United States)

    Despont-Gros, Christelle; Mueller, Henning; Lovis, Christian

    2005-06-01

    This article proposes a model for dimensions involved in user evaluation of clinical information systems (CIS). The model links the dimensions in traditional CIS evaluation and the dimensions from the human-computer interaction (HCI) perspective. In this article, variables are defined as the properties measured in an evaluation, and dimensions are defined as the factors contributing to the values of the measured variables. The proposed model is based on a two-step methodology with: (1) a general review of information systems (IS) evaluations to highlight studied variables, existing models and frameworks, and (2) a review of HCI literature to provide the theoretical basis to key dimensions of user evaluation. The review of literature led to the identification of eight key variables, among which satisfaction, acceptance, and success were found to be the most referenced. Among those variables, IS acceptance is a relevant candidate to reflect user evaluation of CIS. While their goals are similar, the fields of traditional CIS evaluation, and HCI are not closely connected. Combining those two fields allows for the development of an integrated model which provides a model for summative and comprehensive user evaluation of CIS. All dimensions identified in existing studies can be linked to this model and such an integrated model could provide a new perspective to compare investigations of different CIS systems.

  1. Magnetic interactions in martensitic Ni-Mn based Heusler systems

    Energy Technology Data Exchange (ETDEWEB)

    Aksoy, Seda

    2010-04-22

    In this work, magnetic, magnetocaloric and structural properties are investigated in Ni-Mn-based martensitic Heusler alloys with the aim to tailor these properties as well as to understand in detail the magnetic interactions in the various crystallographic states of these alloys. We choose Ni{sub 50}Mn{sub 34}In{sub 16} as a prototype which undergoes a martensitic transformation and exhibits field-induced strain and the inverse magnetocaloric effect. Using the structural phase diagram of martensitic Ni-Mn-based Heusler alloys, we substitute gallium and tin for indium to carry these effects systematically closer to room temperature by shifting the martensitic transformation. A magneto-calorimeter is designed and built to measure adiabatically the magnetocaloric effect in these alloys. The temperature dependence of strain under an external magnetic field is studied in Ni{sub 50}Mn{sub 50-x}Z{sub x} (Z: Ga, Sn, In and Sb) and Ni{sub 50}Mn{sub 34}In{sub 16-x}Z{sub x} (Z: Ga and Sn). An argument based on the effect of the applied magnetic field on martensite nucleation is adopted to extract information on the direction of the magnetization easy axis in the martensitic unit cell in Heusler alloys. Parallel to these studies, the structure in the presence of an external field is also studied by powder neutron diffraction. It is demonstrated that martensite nucleation is influenced by cooling the sample under a magnetic field such that the austenite phase is arrested within the martensitic state. The magnetic interactions in Ni{sub 50}Mn{sub 37}Sn{sub 13} and Ni{sub 50}Mn{sub 40}Sb{sub 10} are characterized by using neutron polarization analysis. Below the martensitic transformation temperature, M{sub s}, an antiferromagnetically correlated state is found. Ferromagnetic resonance experiments are carried out on Ni{sub 50}Mn{sub 37}Sn{sub 13} and Ni{sub 50}Mn{sub 34}In{sub 16} to gain more detailed information on the nature of the magnetic interactions. The experimental

  2. Feature-Based and String-Based Models for Predicting RNA-Protein Interaction

    Directory of Open Access Journals (Sweden)

    Donald Adjeroh

    2018-03-01

    Full Text Available In this work, we study two approaches for the problem of RNA-Protein Interaction (RPI. In the first approach, we use a feature-based technique by combining extracted features from both sequences and secondary structures. The feature-based approach enhanced the prediction accuracy as it included much more available information about the RNA-protein pairs. In the second approach, we apply search algorithms and data structures to extract effective string patterns for prediction of RPI, using both sequence information (protein and RNA sequences, and structure information (protein and RNA secondary structures. This led to different string-based models for predicting interacting RNA-protein pairs. We show results that demonstrate the effectiveness of the proposed approaches, including comparative results against leading state-of-the-art methods.

  3. Drug-drug interactions : from knowledge base to clinical impact

    OpenAIRE

    Andersson, Marine

    2014-01-01

    Drug usage has increased steadily, and the more drugs used, the higher the risk for adverse effects or loss of effect due to drug-drug interactions. For drug prescribers it is difficult to know what drugs a patient is taking and whether they interact. Computerizing of health care records has made it possible to connect patients’ drug lists to clinical decision support systems giving the prescriber information about e.g. drug-drug interactions, duplicated prescriptions and ...

  4. Pendaphonics: A Tangible Pendulum-based Sonic Interaction Experience

    DEFF Research Database (Denmark)

    Overholt, Daniel; Hansen, Anne-Marie S.; Burleson, Winslow

    2009-01-01

    Pendaphonics is a tangible physical-digital-sonic environment and interactive system that engages users in individual, collaborative, group, and distributed interactive experiences. The development of this system, as an element of urban revitalization and as a trans-disciplinary research endeavor......, and is now active within five different research university interaction laboratories. This paper presents the development process and findings from observations and evaluation of Pendaphonics’ users and the social interaction patterns among performers and members of the public. In particular, the repeated...

  5. Sensing Landscape History with an Interactive Location Based Service

    Science.gov (United States)

    van Lammeren, Ron; Goossen, Martin; Roncken, Paul

    2009-01-01

    This paper introduces the STEAD approach for interpreting data acquired by a “human sensor”, who uses an informal interactive location-based service (iLBS) to sense cultural-historic facts and anecdotes of, and in the landscape. This user-generated data is collected outdoors and in situ. The approach consists of four related facets (who, what, where, when). Three of the four facets are discussed and illustrated by user generated data collected during a Dutch survey in 2008. These data represent the personal cultural-historic knowledge and anecdotes of 150 people using a customized iLBS for experiencing the cultural history of a landscape. The “who” facet shows three dominant mentality groups (cosmopolitans, modern materialists and post modern hedonists) that generated user content. The “what” facet focuses on three subject types of pictures and four picture framing classes. Pictures of the place type showed to be dominant and foreground framing class was slightly favourite. The “where” facet is explored via density, distribution, and distance of the pictures made. The illustrations of the facets indirectly show the role of the “human sensor” with respect to the domain of interest. The STEAD approach needs further development of the when-facet and of the relations between the four facets. Finally the results of the approach may support data archives of iLBS applications. PMID:22399994

  6. Optimization Model for Web Based Multimodal Interactive Simulations.

    Science.gov (United States)

    Halic, Tansel; Ahn, Woojin; De, Suvranu

    2015-07-15

    This paper presents a technique for optimizing the performance of web based multimodal interactive simulations. For such applications where visual quality and the performance of simulations directly influence user experience, overloading of hardware resources may result in unsatisfactory reduction in the quality of the simulation and user satisfaction. However, optimization of simulation performance on individual hardware platforms is not practical. Hence, we present a mixed integer programming model to optimize the performance of graphical rendering and simulation performance while satisfying application specific constraints. Our approach includes three distinct phases: identification, optimization and update . In the identification phase, the computing and rendering capabilities of the client device are evaluated using an exploratory proxy code. This data is utilized in conjunction with user specified design requirements in the optimization phase to ensure best possible computational resource allocation. The optimum solution is used for rendering (e.g. texture size, canvas resolution) and simulation parameters (e.g. simulation domain) in the update phase. Test results are presented on multiple hardware platforms with diverse computing and graphics capabilities to demonstrate the effectiveness of our approach.

  7. Quadrupole beam-based alignment in the RHIC interaction regions

    Energy Technology Data Exchange (ETDEWEB)

    Ziegler, J.; Satogata, T.

    2011-03-28

    Continued beam-based alignment (BBA) efforts have provided significant benefit to both heavy ion and polarized proton operations at RHIC. Recent studies demonstrated previously unknown systematic beam position monitor (BPM) offset errors and produced accurate measurements of individual BPM offsets in the experiment interaction regions. Here we describe the algorithm used to collect and analyze data during the 2010 and early 2011 RHIC runs and the results of these measurements. BBA data has been collected over the past two runs for all three of the active experimental IRs at RHIC, updating results from the 2005 run which were taken with incorrectly installed offsets. The technique was successfully applied to expose a systematic misuse of the BPM survey offsets in the control system. This is likely to benefit polarized proton operations as polarization transmission through acceleration ramps depends on RMS orbit control in the arcs, but a quantitative understanding of its impact is still under active investigation. Data taking is ongoing as are refinements to the BBA technique aimed at reducing systematic errors and properly accounting for dispersive effects. Further development may focus on non-triplet BPMs such as those located near snakes, or arc quadrupoles that do not have individually shunted power supplies (a prerequisite for the current method) and as such, will require a modified procedure.

  8. Movement-based interaction applied to physical rehabilitation therapies.

    Science.gov (United States)

    Garrido Navarro, Juan Enrique; Ruiz Penichet, Victor Manuel; Lozano Pérez, María Dolores

    2014-12-09

    Health care environments are continuously improving conditions, especially regarding the use of current technology. In the field of rehabilitation, the use of video games and related technology has helped to develop new rehabilitation procedures. Patients are able to work on their disabilities through new processes that are more motivating and entertaining. However, these patients are required to leave their home environment to complete their rehabilitation programs. The focus of our research interests is on finding a solution to eliminate the need for patients to interrupt their daily routines to attend rehabilitation therapy. We have developed an innovative system that allows patients with a balance disorder to perform a specific rehabilitation exercise at home. Additionally, the system features an assistive tool to complement the work of physiotherapists. Medical staff are thus provided with a system that avoids the need for them to be present during the exercise in specific cases in which patients are under suitable supervision. A movement-based interaction device was used to achieve a reliable system for monitoring rehabilitation exercises performed at home. The system accurately utilizes parameters previously defined by the specialist for correct performance of the exercise. Accordingly, the system gives instructions and corrects the patient's actions. The data generated during the session are collected for assessment by the specialist to adapt the difficulty of the exercise to the patient's progress. The evaluation of the system was conducted by two experts in balance disorder rehabilitation. They were required to verify the effectiveness of the system, and they also facilitated the simulation of real patient behavior. They used the system freely for a period of time and provided interesting and optimistic feedback. First, they evaluated the system as a tool for real-life rehabilitation therapy. Second, their interaction with the system allowed us to obtain

  9. Evaluating Types of Students' Interactions in a Wiki-Based Collaborative Learning Project

    Science.gov (United States)

    Prokofieva, Maria

    2013-01-01

    Wiki technology has been promoted as a collaborative software platform. This study investigates interactions that occur in a wiki-based collaborative learning project. The study draws on interaction literature and investigates the types of interactions with which students are engaged in wiki-based group projects, clusters that reflect online…

  10. Eye-based head gestures for interaction in the car

    DEFF Research Database (Denmark)

    Mardanbeigi, Diako; Witzner Hansen, Dan

    2013-01-01

    that can be used as an alternative input in the multimodal interaction context. Two approaches are described for using this method for interaction with objects inside or outside the car. Some application examples are described where the discrete or continuous head movements in combination with the driver......’s visual attention can be used for controlling the objects inside the car....

  11. Dendrimer-protein interactions versus dendrimer-based nanomedicine.

    Science.gov (United States)

    Shcharbin, Dzmitry; Shcharbina, Natallia; Dzmitruk, Volha; Pedziwiatr-Werbicka, Elzbieta; Ionov, Maksim; Mignani, Serge; de la Mata, F Javier; Gómez, Rafael; Muñoz-Fernández, Maria Angeles; Majoral, Jean-Pierre; Bryszewska, Maria

    2017-04-01

    Dendrimers are hyperbranched polymers belonging to the huge class of nanomedical devices. Their wide application in biology and medicine requires understanding of the fundamental mechanisms of their interactions with biological systems. Summarizing, electrostatic force plays the predominant role in dendrimer-protein interactions, especially with charged dendrimers. Other kinds of interactions have been proven, such as H-bonding, van der Waals forces, and even hydrophobic interactions. These interactions depend on the characteristics of both participants: flexibility and surface charge of a dendrimer, rigidity of protein structure and the localization of charged amino acids at its surface. pH and ionic strength of solutions can significantly modulate interactions. Ligands and cofactors attached to a protein can also change dendrimer-protein interactions. Binding of dendrimers to a protein can change its secondary structure, conformation, intramolecular mobility and functional activity. However, this strongly depends on rigidity versus flexibility of a protein's structure. In addition, the potential applications of dendrimers to nanomedicine are reviwed related to dendrimer-protein interactions. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Introducing a model of pairing based on base pair specific interactions between identical DNA sequences

    Science.gov (United States)

    (O’ Lee, Dominic J.

    2018-02-01

    At present, there have been suggested two types of physical mechanism that may facilitate preferential pairing between DNA molecules, with identical or similar base pair texts, without separation of base pairs. One mechanism solely relies on base pair specific patterns of helix distortion being the same on the two molecules, discussed extensively in the past. The other mechanism proposes that there are preferential interactions between base pairs of the same composition. We introduce a model, built on this second mechanism, where both thermal stretching and twisting fluctuations are included, as well as the base pair specific helix distortions. Firstly, we consider an approximation for weak pairing interactions, or short molecules. This yields a dependence of the energy on the square root of the molecular length, which could explain recent experimental data. However, analysis suggests that this approximation is no longer valid at large DNA lengths. In a second approximation, for long molecules, we define two adaptation lengths for twisting and stretching, over which the pairing interaction can limit the accumulation of helix disorder. When the pairing interaction is sufficiently strong, both adaptation lengths are finite; however, as we reduce pairing strength, the stretching adaptation length remains finite but the torsional one becomes infinite. This second state persists to arbitrarily weak values of the pairing strength; suggesting that, if the molecules are long enough, the pairing energy scales as length. To probe differences between the two pairing mechanisms, we also construct a model of similar form. However, now, pairing between identical sequences solely relies on the intrinsic helix distortion patterns. Between the two models, we see interesting qualitative differences. We discuss our findings, and suggest new work to distinguish between the two mechanisms.

  13. Web-Based Interactions Support for Information Systems

    Directory of Open Access Journals (Sweden)

    Youcef Baghdadi

    2002-01-01

    Full Text Available Work organization, business innovation and IT have enhanced the distributed nature enterprise information systems. Information systems today are made up of subsystems running on heterogeneous IT platforms with varying implementations of business objects and processes increasing the dual risks of (i inconsistency of business objects views and (ii inefficiency of processes. This paper frames this problem as lack of representation and implementation of interactions among the subsystems and external sources. It proposes an interaction support system to make interactions an explicit element of the Enterprise Information System like data and operations. It describes a solution where the interaction elements are encapsulated into a separate subsystem and located in a web server to be used by other subsystems to exchange and share data and to perform processes with complete transparency. We argue that such Interaction Support System may provide global, unified and consistent view of business objects and synergy of processes.

  14. An ancestry-based approach for detecting interactions.

    Science.gov (United States)

    Park, Danny S; Eskin, Itamar; Kang, Eun Yong; Gamazon, Eric R; Eng, Celeste; Gignoux, Christopher R; Galanter, Joshua M; Burchard, Esteban; Ye, Chun J; Aschard, Hugues; Eskin, Eleazar; Halperin, Eran; Zaitlen, Noah

    2018-02-01

    Epistasis and gene-environment interactions are known to contribute significantly to variation of complex phenotypes in model organisms. However, their identification in human association studies remains challenging for myriad reasons. In the case of epistatic interactions, the large number of potential interacting sets of genes presents computational, multiple hypothesis correction, and other statistical power issues. In the case of gene-environment interactions, the lack of consistently measured environmental covariates in most disease studies precludes searching for interactions and creates difficulties for replicating studies. In this work, we develop a new statistical approach to address these issues that leverages genetic ancestry, defined as the proportion of ancestry derived from each ancestral population (e.g., the fraction of European/African ancestry in African Americans), in admixed populations. We applied our method to gene expression and methylation data from African American and Latino admixed individuals, respectively, identifying nine interactions that were significant at Pancestry can be a useful proxy for unknown and unmeasured covariates in the search for interaction effects. These results have important implications for our understanding of the genetic architecture of complex traits. © 2017 WILEY PERIODICALS, INC.

  15. A network-based approach for predicting missing pathway interactions.

    Directory of Open Access Journals (Sweden)

    Saket Navlakha

    Full Text Available Embedded within large-scale protein interaction networks are signaling pathways that encode response cascades in the cell. Unfortunately, even for well-studied species like S. cerevisiae, only a fraction of all true protein interactions are known, which makes it difficult to reason about the exact flow of signals and the corresponding causal relations in the network. To help address this problem, we introduce a framework for predicting new interactions that aid connectivity between upstream proteins (sources and downstream transcription factors (targets of a particular pathway. Our algorithms attempt to globally minimize the distance between sources and targets by finding a small set of shortcut edges to add to the network. Unlike existing algorithms for predicting general protein interactions, by focusing on proteins involved in specific responses our approach homes-in on pathway-consistent interactions. We applied our method to extend pathways in osmotic stress response in yeast and identified several missing interactions, some of which are supported by published reports. We also performed experiments that support a novel interaction not previously reported. Our framework is general and may be applicable to edge prediction problems in other domains.

  16. In Interactive, Web-Based Approach to Metadata Authoring

    Science.gov (United States)

    Pollack, Janine; Wharton, Stephen W. (Technical Monitor)

    2001-01-01

    NASA's Global Change Master Directory (GCMD) serves a growing number of users by assisting the scientific community in the discovery of and linkage to Earth science data sets and related services. The GCMD holds over 8000 data set descriptions in Directory Interchange Format (DIF) and 200 data service descriptions in Service Entry Resource Format (SERF), encompassing the disciplines of geology, hydrology, oceanography, meteorology, and ecology. Data descriptions also contain geographic coverage information, thus allowing researchers to discover data pertaining to a particular geographic location, as well as subject of interest. The GCMD strives to be the preeminent data locator for world-wide directory level metadata. In this vein, scientists and data providers must have access to intuitive and efficient metadata authoring tools. Existing GCMD tools are not currently attracting. widespread usage. With usage being the prime indicator of utility, it has become apparent that current tools must be improved. As a result, the GCMD has released a new suite of web-based authoring tools that enable a user to create new data and service entries, as well as modify existing data entries. With these tools, a more interactive approach to metadata authoring is taken, as they feature a visual "checklist" of data/service fields that automatically update when a field is completed. In this way, the user can quickly gauge which of the required and optional fields have not been populated. With the release of these tools, the Earth science community will be further assisted in efficiently creating quality data and services metadata. Keywords: metadata, Earth science, metadata authoring tools

  17. Mobile gaze-based screen interaction in 3D environments

    DEFF Research Database (Denmark)

    Mardanbeigi, Diako; Witzner Hansen, Dan

    2011-01-01

    in the field of view of the user is also presented which can be applied in a general scenario in which multiple users can interact with multiple screens. A particular application of using this technique is implemented in a home environment with two big screens and a mobile phone. In this application a user......Head-mounted eye trackers can be used for mobile interaction as well as gaze estimation purposes. This paper presents a method that enables the user to interact with any planar digital display in a 3D environment using a head-mounted eye tracker. An effective method for identifying the screens...

  18. Interactive segmentation: a scalable superpixel-based method

    Science.gov (United States)

    Mathieu, Bérengère; Crouzil, Alain; Puel, Jean-Baptiste

    2017-11-01

    This paper addresses the problem of interactive multiclass segmentation of images. We propose a fast and efficient new interactive segmentation method called superpixel α fusion (SαF). From a few strokes drawn by a user over an image, this method extracts relevant semantic objects. To get a fast calculation and an accurate segmentation, SαF uses superpixel oversegmentation and support vector machine classification. We compare SαF with competing algorithms by evaluating its performances on reference benchmarks. We also suggest four new datasets to evaluate the scalability of interactive segmentation methods, using images from some thousand to several million pixels. We conclude with two applications of SαF.

  19. Interactive, Computer-Based Training Program for Radiological Workers

    International Nuclear Information System (INIS)

    Trinoskey, P.A.; Camacho, P.I.; Wells, L.

    2000-01-01

    Lawrence Livermore National Laboratory (LLNL) is redesigning its Computer-Based Training (CBT) program for radiological workers. The redesign represents a major effort to produce a single, highly interactive and flexible CBT program that will meet the training needs of a wide range of radiological workers--from researchers and x-ray operators to individuals working in tritium, uranium, plutonium, and accelerator facilities. The new CBT program addresses the broad diversity of backgrounds found at a national laboratory. When a training audience is homogeneous in terms of education level and type of work performed, it is difficult to duplicate the effectiveness of a flexible, technically competent instructor who can tailor a course to the express needs and concerns of a course's participants. Unfortunately, such homogeneity is rare. At LLNL, they have a diverse workforce engaged in a wide range of radiological activities, from the fairly common to the quite exotic. As a result, the Laboratory must offer a wide variety of radiological worker courses. These include a general contamination-control course in addition to radioactive-material-handling courses for both low-level laboratory (i.e., bench-top) activities as well as high-level work in tritium, uranium, and plutonium facilities. They also offer training courses for employees who work with radiation-generating devices--x-ray, accelerator, and E-beam operators, for instance. However, even with the number and variety of courses the Laboratory offers, they are constrained by the diversity of backgrounds (i.e., knowledge and experience) of those to be trained. Moreover, time constraints often preclude in-depth coverage of site- and/or task-specific details. In response to this situation, several years ago LLNL began moving toward computer-based training for radiological workers. Today, that CBT effort includes a general radiological safety course developed by the Department of Energy's Hanford facility and a

  20. Interactive computer-based training program for radiological workers

    International Nuclear Information System (INIS)

    Trinoskey, P.A.; Camacho, P.I.; Wells, L.

    2000-01-01

    Lawrence Livermore National Laboratory is redesigning its existing Computer-Based Training (CBT) programs for radiological workers. The redesign represents a major effort that is aimed at producing a single highly interactive and flexible CBT program. The new CBT program is designed to address a variety of radiological workers, including researchers, x-ray operators, and individuals working in tritium, uranium, plutonium, and accelerator facilities. The program addresses the diversity of backgrounds found at a national laboratory. The CBT program includes photographs, line drawings and illustrations, sound, video, and simulations, and it allows for easy insertion and replacement of text, graphics, sound, and video. The new design supports timely updates and customization for use at other University of California sites. The CBT program is divided into ten basic modules. Introduction and Lessons Learned, History and Uses, Fundamentals, Background Radiation, Biological Effects of Radiation, Characteristics of Radionuclides, Radiological Controls, Monitoring, Emergency Response, Responsibilities. Some of the main modules features as many as seven or eight submodules. For example, the module on Characteristics of Radionuclides features submodules on common radionuclides, tritium uranium, plutonium, x-ray machines, E-beam devices, radiographic devices, and accelerators. Required submodules are tailored to an individual's type of work and facility, and they are determined by the answers to an onscreen questionnaire given at the outset of training. Individuals can challenge most individual modules, but certain submodules will be mandatory based on the initial survey. For example, individuals working in the uranium facility will be required to complete the submodule on 'History and Uses of Uranium'. However, all other submodules under the main module, 'History and Uses', will be available if selected for preview. For each module, an opportunity is provided for further

  1. IoT Based Human-Building Interaction

    DEFF Research Database (Denmark)

    Fürst, Jonathan

    Our interactions with built environments are increasingly augmented with digital capabilities. Smart appliances coupled with Building Management Systems (BMS) promise to increase occupant comfort and to reduce energy consumption through automated control and personalized services. However, it is ...

  2. Gene-gene interactions between HNF4A and KCNJ11 in predicting Type 2 diabetes in women

    NARCIS (Netherlands)

    Qi, L.; van Dam, R. M.; Asselbergs, F. W.; Hu, F. B.

    2007-01-01

    Aims Recent studies indicate transcription factor hepatocyte nuclear factor 4 alpha ( HNF-4 alpha, HNF4A) modulates the transcription of the pancreatic B-cell ATP-sensitive K+ ( K-ATP) channel subunit Kir6.2 gene ( KCNJ11). Both HNF4A and KCNJ11 have previously been associated with diabetes risk but

  3. Genetic polymorphisms and possible gene-gene interactions in metabolic and DNA repair genes: Effects on DNA damage

    Czech Academy of Sciences Publication Activity Database

    Naccarati, Alessio; Souček, P.; Štětina, R.; Haufroid, V.; Kumar, R.; Vodičková, Ludmila; Trtková, K.; Dušinská, M.; Hemminki, K.; Vodička, Pavel

    2006-01-01

    Roč. 593, 1-2 (2006), s. 22-31 ISSN 0027-5107 R&D Projects: GA ČR GA310/03/0437 Institutional research plan: CEZ:AV0Z5039906 Keywords : Single-strand breaks * Genetic polymorphisms * Metabolism Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.111, year: 2006

  4. Gene-based interaction analysis shows GABAergic genes interacting with parenting in adolescent depressive symptoms

    NARCIS (Netherlands)

    Van Assche, Evelien; Moons, Tim; Cinar, Ozan; Viechtbauer, Wolfgang; Oldehinkel, Albertine J.; Van Leeuwen, Karla; Verschueren, Karine; Colpin, Hilde; Lambrechts, Diether; Van den Noortgate, Wim; Goossens, Luc; Claes, Stephan; van Winkel, Ruud

    2017-01-01

    BACKGROUND: Most gene-environment interaction studies (G × E) have focused on single candidate genes. This approach is criticized for its expectations of large effect sizes and occurrence of spurious results. We describe an approach that accounts for the polygenic nature of most psychiatric

  5. [Association analysis of polymorphisms of metabolizing enzyme genes with chronic benzene poisoning based on logistic regression and multifactor dimensionality reduction].

    Science.gov (United States)

    Jin, Ru-Feng; Wan, Jun-Xiang; Gu, Shou-Yong; Sun, Pin; Zhang, Zhong-Bin; Jin, Xi-Peng; Xia, Zhao-Lin

    2011-07-01

    To explore the association of polymorphisms of metabolizing enzyme genes with chronic benzene poisoning (CBP) comprehensively by case-control design. 152 CBP patients and 152 workers occupationally exposed to benzene without poisoning manifestations were investigated. 30 single nucleotide polymorphisms (SNPs) in 13 genes such as CYP2E1 were tested by PCR-RFLP, sequencing approaches. Logistic regression model was used to detect main effects and 2-order interaction effects of gene and/or environment. Multifactor dimensionality reduction (MDR) was used to detect high-order gene-gene or gene-environment interactions. Based on logistic regression, the main effects of GSTP1 rs947894, EPHX1 rs1051740, CYP1A1 rs4646903, CYP2D6 rs1065852 and rs1135840 were found to be significant (P 0.05). The other SNPs did not show any significant associations with CBP. According to MDR, a 3-order interaction with the strongest combined effect was found, i.e. the 3-factor combination of CYP1A1 rs4646903, CYP2D6 rs1065852 and CYP2D6 rs1135840. Gene-gene, gene-environment interactions are important mechanism to genetic susceptibility of CBP.

  6. Novel interactive virtual showcase based on 3D multitouch technology

    Science.gov (United States)

    Yang, Tao; Liu, Yue; Lu, You; Wang, Yongtian

    2009-11-01

    A new interactive virtual showcase is proposed in this paper. With the help of virtual reality technology, the user of the proposed system can watch the virtual objects floating in the air from all four sides and interact with the virtual objects by touching the four surfaces of the virtual showcase. Unlike traditional multitouch system, this system cannot only realize multi-touch on a plane to implement 2D translation, 2D scaling, and 2D rotation of the objects; it can also realize the 3D interaction of the virtual objects by recognizing and analyzing the multi-touch that can be simultaneously captured from the four planes. Experimental results show the potential of the proposed system to be applied in the exhibition of historical relics and other precious goods.

  7. Situated dialog in speech-based human-computer interaction

    CERN Document Server

    Raux, Antoine; Lane, Ian; Misu, Teruhisa

    2016-01-01

    This book provides a survey of the state-of-the-art in the practical implementation of Spoken Dialog Systems for applications in everyday settings. It includes contributions on key topics in situated dialog interaction from a number of leading researchers and offers a broad spectrum of perspectives on research and development in the area. In particular, it presents applications in robotics, knowledge access and communication and covers the following topics: dialog for interacting with robots; language understanding and generation; dialog architectures and modeling; core technologies; and the analysis of human discourse and interaction. The contributions are adapted and expanded contributions from the 2014 International Workshop on Spoken Dialog Systems (IWSDS 2014), where researchers and developers from industry and academia alike met to discuss and compare their implementation experiences, analyses and empirical findings.

  8. Molecular microenvironments: Solvent interactions with nucleic acid bases and ions

    Science.gov (United States)

    Macelroy, R. D.; Pohorille, A.

    1986-01-01

    The possibility of reconstructing plausible sequences of events in prebiotic molecular evolution is limited by the lack of fossil remains. However, with hindsight, one goal of molecular evolution was obvious: the development of molecular systems that became constituents of living systems. By understanding the interactions among molecules that are likely to have been present in the prebiotic environment, and that could have served as components in protobiotic molecular systems, plausible evolutionary sequences can be suggested. When stable aggregations of molecules form, a net decrease in free energy is observed in the system. Such changes occur when solvent molecules interact among themselves, as well as when they interact with organic species. A significant decrease in free energy, in systems of solvent and organic molecules, is due to entropy changes in the solvent. Entropy-driven interactioins played a major role in the organization of prebiotic systems, and understanding the energetics of them is essential to understanding molecular evolution.

  9. Magnet-based Around Device Interaction for Playful Music Composition and Gaming

    NARCIS (Netherlands)

    El Ali, A.; Ketabdar, H.

    2013-01-01

    Around Device Interaction (ADI) has expanded the interaction space on mobile devices to allow 3D gesture interaction around the device. In this paper, the authors look specifically at magnet-based ADI and its applied use in a playful, music-related context. Using three musical applications developed

  10. A comparative study on the flow experience in web-based and text-based interaction environments.

    Science.gov (United States)

    Huang, Li-Ting; Chiu, Chen-An; Sung, Kai; Farn, Cheng-Kiang

    2011-01-01

    The purpose of this study was to explore a substantial phenomenon related to flow experiences (immersion) in text-based interaction systems. Most previous research emphasizes the effects of challenge/skill, focused attention, telepresence, web characteristics, and systems' interface design on users' flow experiences in online environments. However, text-based interaction systems without telepresence features and web characteristics still seem to create opportunities for flow experience. To explore this phenomenon, this study incorporates subject involvement and interpersonal interaction as critical antecedents into the model of flow experience, as well as considers the existence of telepresence. Results reveal that subject involvement, interpersonal interaction, and interactivity speed are critical to focused attention, which enhances users' immersion. With regard to the effect of telepresence, the perceived attractiveness of the interface is a significant facilitator determining users' immersion in web-based, rather than in text-based, interaction environments. Interactivity speed is unrelated to immersion in both web-based and text-based interaction environments. The influence of interpersonal involvement is diminished in web-based interaction environments. The implications and limitations of this study are discussed.

  11. Gear-based species selectivity and potential interactions between ...

    African Journals Online (AJOL)

    In this study, we used multivariate and ecological approaches to evaluate gear competition and interactions between artisanal and aquarium fishers using a case study of the Shimoni area, southcoast of Kenya. Aquarium fisher catches were monitored from September 2010 to March 2013; while artisanal fisher catches were ...

  12. Component Based System Framework for Dynamic B2B Interaction

    NARCIS (Netherlands)

    Hu jinmin, Jinmin; Grefen, P.W.P.J.

    Business-to-Business (B2B) collaboration is becoming a pivotal way to bring today's enterprises to success in the dynamically changing e-business environment. Though many business-to-business protocols are developed to support B2B interaction, none are generally accepted. A B2B system should support

  13. The Design of Tools for Sketching Sensor-Based Interaction

    DEFF Research Database (Denmark)

    Brynskov, Martin; Lunding, Rasmus; Vestergaard, Lasse Steenbock

    2012-01-01

    , flexibility and cost, aimed at wearable and ultra-mobile prototyping where fast reaction is needed (e.g. in controlling sound), and we discuss the general issues facing this category of embodied interaction design tools. We then present the platform in more detail, both regarding hard- ware and software...

  14. Attractor Dynamics of Dyadic Interaction: A Recurrence Based Analysis.

    Science.gov (United States)

    Guevara, Marlenny; Cox, Ralf F A; van Dijk, Marijn; van Geert, Paul

    2017-07-01

    The aim of this study was to investigate interpersonal coordination in young children during dyadic problem solving, by using Cross-Recurrence Quantification Analysis (CRQA). We examined the interactions of seven dyads of children (Mage= 5.1 years) in a longitudinal design (6 sessions) with a sequence of problem-solving tasks increasing in difficulty. An innovative implementation of CRQA is presented in order to study the attractor dynamics of dyadic coordination. The analysis consisted of distinguishing two recurrent states in the relationship between children and the task. In other words, the analysis is focused on how the dyadic interaction oscillates between two stable states that for their recurrent presence are considered to be attractors. The distributed dyadic interaction (DDI) state indicates that both children contribute equally to the solution of the task. The unequal dyadic interaction (UDI) state indicating that only one of the children contributes actively to the solution of the task. Results showed that the DDI was more frequent than the UDI but that the dynamics of these two attractor states were quite similar. The behaviors within these states increased in complexity over time, although they did so in DDI more strongly than UDI. The overall recurrence, which indicates the global level of coordination between the individuals in the dyad across all time points, was moderately correlated with the performance of the children.

  15. Referring Expression Generation in Interaction: A Graph-based perspective

    NARCIS (Netherlands)

    Krahmer, E.J.; Goudbeek, M.B.; Theune, M.; Stent, Amanda; Bangalore, Srinivas

    2014-01-01

    An informative and comprehensive overview of the state-of-the-art in natural language generation (NLG) for interactive systems, this guide serves to introduce graduate students and new researchers to the field of natural language processing and artificial intelligence, while inspiring them with

  16. An association study of NRAMP1, VDR, MBL and their interaction with the susceptibility to tuberculosis in a Chinese population

    Directory of Open Access Journals (Sweden)

    Linlin Wu

    2015-09-01

    Conclusions: Our study suggests that genotypes of many polymorphic genes are associated with TB, it is necessary to further explore the mechanism of genotypes and gene-gene interaction in susceptibility to tuberculosis.

  17. INTERACT

    DEFF Research Database (Denmark)

    Jochum, Elizabeth; Borggreen, Gunhild; Murphey, TD

    This paper considers the impact of visual art and performance on robotics and human-computer interaction and outlines a research project that combines puppetry and live performance with robotics. Kinesics—communication through movement—is the foundation of many theatre and performance traditions...... including puppetry and dance. However, the aesthetics of these traditions vary across cultures and carry different associative and interpretive meanings. Puppetry offers a useful frame for understanding the relationship between abstract and imitative gestures and behavior, and instantiates the complex...... interaction between a human operator and an artificial actor or agent. We can apply insights from puppetry to develop culturally-aware robots. Here we describe the development of a robotic marionette theatre wherein robotic controllers assume the role of human puppeteers. The system has been built, tested...

  18. Interactions

    DEFF Research Database (Denmark)

    The main theme of this anthology is the unique interaction between mathematics, physics and philosophy during the beginning of the 20th century. Seminal theories of modern physics and new fundamental mathematical structures were discovered or formed in this period. Significant physicists such as ......The main theme of this anthology is the unique interaction between mathematics, physics and philosophy during the beginning of the 20th century. Seminal theories of modern physics and new fundamental mathematical structures were discovered or formed in this period. Significant physicists...... such as Lorentz and Einstein as well as mathematicians such as Poincare, Minkowski, Hilbert and Weyl contributed to this development. They created the new physical theories and the mathematical disciplines that play such paramount roles in their mathematical formulations. These physicists and mathematicians were...... also key figures in the philosophical discussions of nature and science - from philosophical tendencies like logical empiricism via critical rationalism to various neo-Kantian trends....

  19. 3did: a catalog of domain-based interactions of known three-dimensional structure.

    Science.gov (United States)

    Mosca, Roberto; Céol, Arnaud; Stein, Amelie; Olivella, Roger; Aloy, Patrick

    2014-01-01

    The database of 3D interacting domains (3did, available online for browsing and bulk download at http://3did.irbbarcelona.org) is a catalog of protein-protein interactions for which a high-resolution 3D structure is known. 3did collects and classifies all structural templates of domain-domain interactions in the Protein Data Bank, providing molecular details for such interactions. The current version also includes a pipeline for the discovery and annotation of novel domain-motif interactions. For every interaction, 3did identifies and groups different binding modes by clustering similar interfaces into 'interaction topologies'. By maintaining a constantly updated collection of domain-based structural interaction templates, 3did is a reference source of information for the structural characterization of protein interaction networks. 3did is updated every 6 months.

  20. GAIA: a gram-based interaction analysis tool--an approach for identifying interacting domains in yeast.

    Science.gov (United States)

    Zhang, Kelvin X; Ouellette, B F Francis

    2009-01-30

    Protein-Protein Interactions (PPIs) play important roles in many biological functions. Protein domains, which are defined as independently folding structural blocks of proteins, physically interact with each other to perform these biological functions. Therefore, the identification of Domain-Domain Interactions (DDIs) is of great biological interests because it is generally accepted that PPIs are mediated by DDIs. As a result, much effort has been put on the prediction of domain pair interactions based on computational methods. Many DDI prediction tools using PPIs network and domain evolution information have been reported. However, tools that combine the primary sequences, domain annotations, and structural annotations of proteins have not been evaluated before. In this study, we report a novel approach called Gram-bAsed Interaction Analysis (GAIA). GAIA extracts peptide segments that are composed of fixed length of continuous amino acids, called n-grams (where n is the number of amino acids), from the annotated domain and DDI data set in Saccharomyces cerevisiae (budding yeast) and identifies a list of n-grams that may contribute to DDIs and PPIs based on the frequencies of their appearance. GAIA also reports the coordinate position of gram pairs on each interacting domain pair. We demonstrate that our approach improves on other DDI prediction approaches when tested against a gold-standard data set and achieves a true positive rate of 82% and a false positive rate of 21%. We also identify a list of 4-gram pairs that are significantly over-represented in the DDI data set and may mediate PPIs. GAIA represents a novel and reliable way to predict DDIs that mediate PPIs. Our results, which show the localizations of interacting grams/hotspots, provide testable hypotheses for experimental validation. Complemented with other prediction methods, this study will allow us to elucidate the interactome of cells.

  1. The Design of Tools for Sketching Sensor-Based Interaction

    DEFF Research Database (Denmark)

    Brynskov, Martin; Lunding, Rasmus; Vestergaard, Lasse Steenbock

    2012-01-01

    , flexibility and cost, aimed at wearable and ultra-mobile prototyping where fast reaction is needed (e.g. in controlling sound), and we discuss the general issues facing this category of embodied interaction design tools. We then present the platform in more detail, both regarding hard- ware and software...... users include designers, students, artists etc. with minimal programming and hardware skills, but this paper adresses the issues with designing the tools, which includes technical details....

  2. Web-Based Interactions Support for Information Systems

    OpenAIRE

    Youcef Baghdadi

    2002-01-01

    Work organization, business innovation and IT have enhanced the distributed nature enterprise information systems. Information systems today are made up of subsystems running on heterogeneous IT platforms with varying implementations of business objects and processes increasing the dual risks of (i) inconsistency of business objects views and (ii) inefficiency of processes. This paper frames this problem as lack of representation and implementation of interactions among the subsystems and ext...

  3. Multi-atlas Based Segmentation Editing with Interaction-Guided Constraints

    OpenAIRE

    Park, Sang Hyun; Gao, Yaozong; Shen, Dinggang

    2015-01-01

    We propose a novel multi-atlas based segmentation method to address the editing scenario, when given an incomplete segmentation along with a set of training label images. Unlike previous multi-atlas based methods, which depend solely on appearance features, we incorporate interaction-guided constraints to find appropriate training labels and derive their voting weights. Specifically, we divide user interactions, provided on erroneous parts, into multiple local interaction combinations, and th...

  4. INTERACT

    DEFF Research Database (Denmark)

    Jochum, Elizabeth; Borggreen, Gunhild; Murphey, TD

    This paper considers the impact of visual art and performance on robotics and human-computer interaction and outlines a research project that combines puppetry and live performance with robotics. Kinesics—communication through movement—is the foundation of many theatre and performance traditions...... including puppetry and dance. However, the aesthetics of these traditions vary across cultures and carry different associative and interpretive meanings. Puppetry offers a useful frame for understanding the relationship between abstract and imitative gestures and behavior, and instantiates the complex...

  5. Aerosol-cirrus interactions: a number based phenomenon at all?

    Directory of Open Access Journals (Sweden)

    M. Seifert

    2004-01-01

    Full Text Available In situ measurements of the partitioning of aerosol particles within cirrus clouds were used to investigate aerosol-cloud interactions in ice clouds. The number density of interstitial aerosol particles (non-activated particles in between the cirrus crystals was compared to the number density of cirrus crystal residuals. The data was obtained during the two INCA (Interhemispheric Differences in Cirrus Properties from Anthropogenic Emissions campaigns, performed in the Southern Hemisphere (SH and Northern Hemisphere (NH midlatitudes. Different aerosol-cirrus interactions can be linked to the different stages of the cirrus lifecycle. Cloud formation is linked to positive correlations between the number density of interstitial aerosol (Nint and crystal residuals (Ncvi, whereas the correlations are smaller or even negative in a dissolving cloud. Unlike warm clouds, where the number density of cloud droplets is positively related to the aerosol number density, we observed a rather complex relationship when expressing Ncvi as a function of Nint for forming clouds. The data sets are similar in that they both show local maxima in the Nint range 100 to 200cm, where the SH- maximum is shifted towards the higher value. For lower number densities Nint and Ncvi are positively related. The slopes emerging from the data suggest that a tenfold increase in the aerosol number density corresponds to a 3 to 4 times increase in the crystal number density. As Nint increases beyond the ca. 100 to 200cm, the mean crystal number density decreases at about the same rate for both data sets. For much higher aerosol number densities, only present in the NH data set, the mean Ncvi remains low. The situation for dissolving clouds allows us to offer two possible, but at this point only speculative, alternative interactions between aerosols and cirrus: evaporating clouds might be associated with a source of aerosol particles, or air pollution (high aerosol number density might

  6. Addressing grammar in the interaction task-based learning environment

    Directory of Open Access Journals (Sweden)

    Davis Brent M.

    2017-01-01

    Full Text Available One of the major problems in language teaching is developing grammatical accuracy. This paper proposes that using error correction based on a functional grammar in a task-based learning approach may be a suitable solution. Towards this end an emic (using categories intrinsic to the language functional grammar of the verb phrase is proposed and a description of how this fits into the focus on form component of task-based learning is provided.

  7. Interaction-based transition from passivity to excitability

    Science.gov (United States)

    Petrov, V. S.; Osipov, G. V.

    2014-09-01

    In this paper we study the process of transition from passive to excitable behavior due to interaction between nonlinear dynamical systems. We show that under certain conditions a passive unit may demonstrate qualitatively new excitable dynamics. We study the properties of an excitable medium constructed on the basis of the proposed transition. The effects are demonstrated with the realistic Luo-Rudy model. Application to the cardiac dynamics and functioning is discussed. The qualitative analytic and numerical description is also given for the phenomenological FitzHugh-Nagumo system.

  8. Interaction of Azobenzene and Benzalaniline with Strong Amido Bases.

    Science.gov (United States)

    Kornev, Alexander N; Sushev, Vyacheslav V; Zolotareva, Natalia V; Baranov, Evgenii V; Fukin, Georgy K; Abakumov, Gleb A

    2015-12-18

    The interaction of azobenzene with lithium dicyclohexylamide (Cy2NLi) in THF or Et2O afforded the ion-radical salt of azobenzene (1) structurally characterized for the first time and dicyclohexylaminyl radical, which begins a novel chain of transformations leading eventually to the imino-enamido lithium complex (3). Benzalaniline, being a relative of azobenzene, reacted with Cy2NLi without electron transfer by a proton-abstraction mechanism to form the dilithium salt of N(1),N(2),1,2-tetraphenylethene-1,2-diamine quantitatively.

  9. Sculpting Mountains: Interactive Terrain Modeling Based on Subsurface Geology.

    Science.gov (United States)

    Cordonnier, Guillaume; Cani, Marie-Paule; Benes, Bedrich; Braun, Jean; Galin, Eric

    2018-05-01

    Most mountain ranges are formed by the compression and folding of colliding tectonic plates. Subduction of one plate causes large-scale asymmetry while their layered composition (or stratigraphy) explains the multi-scale folded strata observed on real terrains. We introduce a novel interactive modeling technique to generate visually plausible, large scale terrains that capture these phenomena. Our method draws on both geological knowledge for consistency and on sculpting systems for user interaction. The user is provided hands-on control on the shape and motion of tectonic plates, represented using a new geologically-inspired model for the Earth crust. The model captures their volume preserving and complex folding behaviors under collision, causing mountains to grow. It generates a volumetric uplift map representing the growth rate of subsurface layers. Erosion and uplift movement are jointly simulated to generate the terrain. The stratigraphy allows us to render folded strata on eroded cliffs. We validated the usability of our sculpting interface through a user study, and compare the visual consistency of the earth crust model with geological simulation results and real terrains.

  10. Comprehensive characterization of molecular interactions based on nanomechanics.

    Directory of Open Access Journals (Sweden)

    Murali Krishna Ghatkesar

    Full Text Available Molecular interaction is a key concept in our understanding of the biological mechanisms of life. Two physical properties change when one molecular partner binds to another. Firstly, the masses combine and secondly, the structure of at least one binding partner is altered, mechanically transducing the binding into subsequent biological reactions. Here we present a nanomechanical micro-array technique for bio-medical research, which not only monitors the binding of effector molecules to their target but also the subsequent effect on a biological system in vitro. This label-free and real-time method directly and simultaneously tracks mass and nanomechanical changes at the sensor interface using micro-cantilever technology. To prove the concept we measured lipid vesicle (approximately 748*10(6 Da adsorption on the sensor interface followed by subsequent binding of the bee venom peptide melittin (2840 Da to the vesicles. The results show the high dynamic range of the instrument and that measuring the mass and structural changes simultaneously allow a comprehensive discussion of molecular interactions.

  11. Child second language interaction in science-based tasks

    Science.gov (United States)

    McPhail, Cynthia Leigh

    While quasi-experimental in design, this study utilized qualitative data collection and analysis methods to examine the questions of whether students' speech act behavior and language use would vary by linguistic grouping. Second grade Puerto Rican native speakers of Spanish, and native English speakers completed sets of paired, hands-on, science activities. Children were paired in two linguistic groupings: heterogeneous (English native speaker/non-native speaker), and homogeneous (English non-native speaker/non-native speaker, or English native speaker/native speaker). Speech acts and use of target and native language in the two linguistic groupings were compared. Interviews with both the students and their teachers provided further understanding of the speech act behavior. Most prior research has dealt with university level adults learning English. Previous research that has dealt with children and second language interaction has often focused on teacher talk directed to the children, and no child/child interaction studies have attempted to control for variables such as linguistic grouping. Results indicated that linguistically heterogeneous groupings led to higher percentages of English use for non-native speakers. Homogeneous grouping led to higher percentages of native Spanish use. English native speakers' speech act behavior remained consistent in terms of dominance or passivity of behavior regardless of linguistic grouping, but there is the possibility that non-English speakers may behave in a slightly more passive manner when in heterogeneous grouping.

  12. Task-Based Learning: The Interaction between Tasks and Learners.

    Science.gov (United States)

    Murphy, Jacky

    2003-01-01

    Investigates the relationship between tasks and learners in task-based learning. Findings suggest that manipulation of task characteristics and conditions may not achieve the intended pedagogic outcomes, and that new ways are needed to focus learners' attention of form without sacrificing the meaning-driven principles of task-based learning.…

  13. The interaction triangle as a tool for understanding stakeholder interactions in marine ecosystem based management

    NARCIS (Netherlands)

    Rockmann, C.; Leeuwen, van J.; Goldsborough, D.G.; Kraan, M.L.; Piet, G.J.

    2015-01-01

    Expectations about ecosystem based management (EBM) differ due to diverging perspectives about what EBM should be and how it should work. While EBM by its nature requires trade-offs to be made between ecological, economic and social sustainability criteria, the diversity of cross-sectoral

  14. Hydrogen-plasticity interactions in nickel and nickel base alloys

    International Nuclear Information System (INIS)

    Girardin, G.

    2004-03-01

    We evaluate the different contributions of the hydrogen-dislocation interactions to the plasticity of fcc materials in order to feed predictive models of stress corrosion cracking. Static strain ageing experiments are used to quantify the hardening contribution of solute drag by dislocations to the flow stress. We demonstrate the role of hydrogen transport by dislocations on the fracture mechanism. We model the influence of the screening of the elastic field of dislocations by hydrogen on elementary plasticity mechanisms and we conclude that the decrease of the cross slip ability arises from the combined action of elastic and core effects. The testing of single crystals shows that the major effect is on the cross slip mechanism. Tensile tests on polycrystals enlighten the diversity of macroscopic responses observed in alloys. (author)

  15. Fingerstroke time estimates for touchscreen-based mobile gaming interaction.

    Science.gov (United States)

    Lee, Ahreum; Song, Kiburm; Ryu, Hokyoung Blake; Kim, Jieun; Kwon, Gyuhyun

    2015-12-01

    The growing popularity of gaming applications and ever-faster mobile carrier networks have called attention to an intriguing issue that is closely related to command input performance. A challenging mirroring game service, which simultaneously provides game service to both PC and mobile phone users, allows them to play games against each other with very different control interfaces. Thus, for efficient mobile game design, it is essential to apply a new predictive model for measuring how potential touch input compares to the PC interfaces. The present study empirically tests the keystroke-level model (KLM) for predicting the time performance of basic interaction controls on the touch-sensitive smartphone interface (i.e., tapping, pointing, dragging, and flicking). A modified KLM, tentatively called the fingerstroke-level model (FLM), is proposed using time estimates on regression models. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. A Formal Reuse-Based Approach for Interactively Designing Organizations

    NARCIS (Netherlands)

    Jonker, C.M.; Treur, J.; Yolum, P.; Odell, J.; Giorgini, P.; Müller, J.P.

    2005-01-01

    Multiagent organizations provide a powerful way for developing multiagent systems. This paper presents a methodology for designing organizations based on formal specification of requirements for organizational behavior and requirements refinement related to organizational structure. The approach

  17. A real-time vision-based hand gesture interaction system for virtual EAST

    Energy Technology Data Exchange (ETDEWEB)

    Wang, K.R., E-mail: wangkr@mail.ustc.edu.cn [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); University of Science and Technology of China, Hefei, Anhui (China); Xiao, B.J.; Xia, J.Y. [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); University of Science and Technology of China, Hefei, Anhui (China); Li, Dan [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); Luo, W.L. [709th Research Institute, Shipbuilding Industry Corporation (China)

    2016-11-15

    Highlights: • Hand gesture interaction is first introduced to EAST model interaction. • We can interact with EAST model by a bared hand and a web camera. • We can interact with EAST model with a distance to screen. • Interaction is free, direct and effective. - Abstract: The virtual Experimental Advanced Superconducting Tokamak device (VEAST) is a very complicated 3D model, to interact with which, the traditional interaction devices are limited and inefficient. However, with the development of human-computer interaction (HCI), the hand gesture interaction has become a much popular choice in recent years. In this paper, we propose a real-time vision-based hand gesture interaction system for VEAST. By using one web camera, we can use our bare hand to interact with VEAST at a certain distance, which proves to be more efficient and direct than mouse. The system is composed of four modules: initialization, hand gesture recognition, interaction control and system settings. The hand gesture recognition method is based on codebook (CB) background modeling and open finger counting. Firstly, we build a background model with CB algorithm. Then, we segment the hand region by detecting skin color regions with “elliptical boundary model” in CbCr flat of YCbCr color space. Open finger which is used as a key feature of gesture can be tracked by an improved curvature-based method. Based on the method, we define nine gestures for interaction control of VEAST. Finally, we design a test to demonstrate effectiveness of our system.

  18. A real-time vision-based hand gesture interaction system for virtual EAST

    International Nuclear Information System (INIS)

    Wang, K.R.; Xiao, B.J.; Xia, J.Y.; Li, Dan; Luo, W.L.

    2016-01-01

    Highlights: • Hand gesture interaction is first introduced to EAST model interaction. • We can interact with EAST model by a bared hand and a web camera. • We can interact with EAST model with a distance to screen. • Interaction is free, direct and effective. - Abstract: The virtual Experimental Advanced Superconducting Tokamak device (VEAST) is a very complicated 3D model, to interact with which, the traditional interaction devices are limited and inefficient. However, with the development of human-computer interaction (HCI), the hand gesture interaction has become a much popular choice in recent years. In this paper, we propose a real-time vision-based hand gesture interaction system for VEAST. By using one web camera, we can use our bare hand to interact with VEAST at a certain distance, which proves to be more efficient and direct than mouse. The system is composed of four modules: initialization, hand gesture recognition, interaction control and system settings. The hand gesture recognition method is based on codebook (CB) background modeling and open finger counting. Firstly, we build a background model with CB algorithm. Then, we segment the hand region by detecting skin color regions with “elliptical boundary model” in CbCr flat of YCbCr color space. Open finger which is used as a key feature of gesture can be tracked by an improved curvature-based method. Based on the method, we define nine gestures for interaction control of VEAST. Finally, we design a test to demonstrate effectiveness of our system.

  19. Combining region-based and imprecise boundary-based cues for interactive medical image segmentation.

    Science.gov (United States)

    Jones, Jonathan-Lee; Xie, Xianghua; Essa, Ehab

    2014-12-01

    In this paper, we present an approach combining both region selection and user point selection for user-assisted segmentation as either an enclosed object or an open curve, investigate the method of image segmentation in specific medical applications (user-assisted segmentation of the media-adventitia border in intravascular ultrasound images, and lumen border in optical coherence tomography images), and then demonstrate the method with generic images to show how it could be utilized in other types of medical image and is not limited to the applications described. The proposed method combines point-based soft constraint on object boundary and stroke-based regional constraint. The user points act as attraction points and are treated as soft constraints rather than hard constraints that the segmented boundary has to pass through. The user can also use strokes to specify region of interest. The probabilities of region of interest for each pixel are then calculated, and their discontinuity is used to indicate object boundary. The combinations of different types of user constraints and image features allow flexible and robust segmentation, which is formulated as an energy minimization problem on a multilayered graph and is solved using a shortest path search algorithm. We show that this combinatorial approach allows efficient and effective interactive segmentation, which can be used with both open and closed curves to segment a variety of images in different ways. The proposed method is demonstrated in the two medical applications, that is, intravascular ultrasound and optical coherence tomography images, where image artefacts such as acoustic shadow and calcification are commonplace and thus user guidance is desirable. We carried out both qualitative and quantitative analysis of the results for the medical data; comparing the proposed method against a number of interactive segmentation techniques. Copyright © 2014 John Wiley & Sons, Ltd.

  20. Mixed Reality Environment for Web-Based Laboratory Interactive Learning

    Directory of Open Access Journals (Sweden)

    A. I. Saleem

    2008-02-01

    Full Text Available This paper presents a web-based laboratory fordistance learners by incorporating simulation andhardware implementation into web-based e-learningsystems. It presents a development consisting of laboratorycourse through internet based on mixed reality technique tosetup, run and manipulateset of experiments. Eachexperiment has been designed in a way that allows thelearner to manipulate the components and check if it worksproperly in order to achieve the experiment objective. Theproposed laboratory e-learning tool has web-basedcomponents accessed by authorized users. Learners canacquire the necessary skills they need, while learning thetheory of the experiment and the basic characteristics ofeach component used in the experiment. Finally, a casestudy was conducted to show the feasibility and efficiencyof the proposed method.

  1. Multivalent interaction based carbohydrate biosensors for signal amplification

    Science.gov (United States)

    Wang, Yanyan; Chalagalla, Srinivas; Li, Tiehai; Sun, Xue-long; Zhao, Wei; Wang, Peng; Zeng, Xiangqun

    2010-01-01

    Multivalent interaction between boronic acids immobilized on Quartz Crystal Microbalance (QCM) sensor surface and the carbohydrates modified Au - nanoparticle (AuNP) has been demonstrated for the development of a sensitive carbohydrate biosensor. Briefly, a boronic acid - containing polymer (boropolymer) as multivalent carbohydrate receptor was oriented immobilized on the cysteamine coated electrode through isourea bond formation. Carbohydrates were conjugated to AuNPs to generate a multivalent carbohydrates moiety to amplify the response signal. Thus, the binding of the carbohydrate conjugated AuNPs to the boropolymer surface are multivalent which could simultaneously increase the binding affinity and specificity. We systematically studied the binding between five carbohydrate conjugated AuNPs and the boropolymer. Our studies show that the associate constant (Ka) was in the order of fucose carbohydrate analytes. Furthermore, the multivalent binding between carbohydrates and boronic acids are reversible and allow the regeneration of boropolymer surface by using 1M acetic acid so as to sequentially capture and release the carbohydrate analytes. PMID:20863680

  2. Vehicle-based interactive management with multi-agent approach

    Directory of Open Access Journals (Sweden)

    Yee Ming Chen

    2009-09-01

    Full Text Available Under the energy crisis and global warming, mass transportation becomes more important than before. The disadvantages of mass transportation, plus the high flexibility and efficiency of taxi and with the revolution of technology, electric-taxi is the better transportation choice for metropolis. On the other hand, among the many taxi service types, dial-a-ride (DAR service system is the better way for passenger and taxi. However the electricity replenishing of electric-taxi is the biggest shortage and constraint for DAR operation system. In order to more effectively manage the electric-taxi DAR operation system and the lots of disadvantages of physical system and observe the behaviors and interactions of simulation system, multi-agent simulation technique is the most suitable simulation technique. Finally, we use virtual data as the input of simulation system and analyze the simulation result. We successfully obtain two performance measures: average waiting time and service rate. Result shows the average waiting time is only 3.93 seconds and the service rate (total transport passenger number / total passenger number is 37.073%. So these two performance measures can support us to make management decisions. The multiagent oriented model put forward in this article is the subject of an application intended in the long term to supervise the user information system of an urban transport network.

  3. Interactive storybook-based intervention effects on kindergartners' language development

    NARCIS (Netherlands)

    Druten-Frietman, L.J.G. van; Strating, H.T.; Denessen, E.J.P.G.; Verhoeven, L.T.W.

    2016-01-01

    A dialogic storybook-based intervention integrating dialogic storybook reading with early literacy activities is studied with a longitudinal quasi-experimental study design. The effects of this intervention, in addition to a regular early childhood education (ECE) program, on kindergartners'

  4. Interactive Storybook-Based Intervention Effects on Kindergartners' Language Development

    Science.gov (United States)

    van Druten-Frietman, Loes; Strating, Heleen; Denessen, Eddie; Verhoeven, Ludo

    2016-01-01

    A dialogic storybook-based intervention integrating dialogic storybook reading with early literacy activities is studied with a longitudinal quasi-experimental study design. The effects of this intervention, in addition to a regular early childhood education (ECE) program, on kindergartners' vocabulary and phonological awareness development are…

  5. User interaction with legal knowledge-based systems

    NARCIS (Netherlands)

    Dijkstra, Jacob; Breuker, J.; Leenes, R.; Winkels, R.

    2000-01-01

    This paper gives an overview of my PhD study into the persuasiveness of (legal) knowledge-based systems'. The results of three experiments show the possible problems that may arise when computerised legal decision aids are put into practice. The users in the experiments had great difficulties with

  6. Adaptive Game Level Creation through Rank-based Interactive Evolution

    DEFF Research Database (Denmark)

    Liapis, Antonios; Martínez, Héctor Pérez; Togelius, Julian

    2013-01-01

    as fitness functions for the optimization of the generated content. The preference models are built via ranking-based preference learning, while the content is generated via evolutionary search. The proposed method is evaluated on the creation of strategy game maps, and its performance is tested using...

  7. An interactive Web-based radiation protection course in fluoroscopy

    International Nuclear Information System (INIS)

    Aldrich, J.

    2001-01-01

    The teaching of radiation protection to a large group of physicians, who are separated geographically and have complicated schedules, is a formidable problem. Therefore a Web-based solution is attractive, allowing access to the material at any time and place. In this implementation the didactic material is presented in a Web-based format. Subsequently, students attend a practical demonstration in one of the departments' fluoroscopy rooms. Because of local experience with distance education, WebCT was chosen to present the material. WebCT (Web Course Tools) was developed by the University of British Columbia (UBC) to allow educators, with or without technical expertise, to create a sophisticated Web-base. Authors use a standard Web browser to create courses, and students use their browsers to access course material. WebCT provides a wide variety of tools and features that can be added to a course. Among the most useful tools used in this fluoroscopy course are the glossary, multiple-choice questions for each section, and a final test which is scored by the computer. As with all Web-based material the courses can be viewed in the traditional linear fashion or in any random way through the use of linkages. (author)

  8. iDoRNA: An Interacting Domain-based Tool for Designing RNA-RNA Interaction Systems

    Directory of Open Access Journals (Sweden)

    Jittrawan Thaiprasit

    2016-03-01

    Full Text Available RNA-RNA interactions play a crucial role in gene regulation in living organisms. They have gained increasing interest in the field of synthetic biology because of their potential applications in medicine and biotechnology. However, few novel regulators based on RNA-RNA interactions with desired structures and functions have been developed due to the challenges of developing design tools. Recently, we proposed a novel tool, called iDoDe, for designing RNA-RNA interacting sequences by first decomposing RNA structures into interacting domains and then designing each domain using a stochastic algorithm. However, iDoDe did not provide an optimal solution because it still lacks a mechanism to optimize the design. In this work, we have further developed the tool by incorporating a genetic algorithm (GA to find an RNA solution with maximized structural similarity and minimized hybridized RNA energy, and renamed the tool iDoRNA. A set of suitable parameters for the genetic algorithm were determined and found to be a weighting factor of 0.7, a crossover rate of 0.9, a mutation rate of 0.1, and the number of individuals per population set to 8. We demonstrated the performance of iDoRNA in comparison with iDoDe by using six RNA-RNA interaction models. It was found that iDoRNA could efficiently generate all models of interacting RNAs with far more accuracy and required far less computational time than iDoDe. Moreover, we compared the design performance of our tool against existing design tools using forty-four RNA-RNA interaction models. The results showed that the performance of iDoRNA is better than RiboMaker when considering the ensemble defect, the fitness score and computation time usage. However, it appears that iDoRNA is outperformed by NUPACK and RNAiFold 2.0 when considering the ensemble defect. Nevertheless, iDoRNA can still be an useful alternative tool for designing novel RNA-RNA interactions in synthetic biology research. The source code of i

  9. IoT Based Human-Building Interaction

    DEFF Research Database (Denmark)

    Fürst, Jonathan

    acoustic based localization. We further design and implement a system that uses smartphone sensor based user feedback to automatically select appliance settings. We also mediate conflicts between users locally and building wide energy policies. (iii) On a system level, we present an architecture......, it is not clear how smart appliances, originally designed for smart homes, can be used in the context of non-residential buildings. For example: How can a user be given access to smart appliances in her vicinity? This simple question raises a number of issues in non-residential buildings: What are the smart......? In this thesis, we study how Mark Weiser's original vision for ubiquitous computing can help us tackle such questions. Specifically, our contributions are the following: (i) At the human-building interface, we design and implement a system for a building manager that enables building-wide visualization...

  10. A Framework for Agent-based Human Interaction Support

    Directory of Open Access Journals (Sweden)

    Axel Bürkle

    2008-10-01

    Full Text Available In this paper we describe an agent-based infrastructure for multimodal perceptual systems which aims at developing and realizing computer services that are delivered to humans in an implicit and unobtrusive way. The framework presented here supports the implementation of human-centric context-aware applications providing non-obtrusive assistance to participants in events such as meetings, lectures, conferences and presentations taking place in indoor "smart spaces". We emphasize on the design and implementation of an agent-based framework that supports "pluggable" service logic in the sense that the service developer can concentrate on coding the service logic independently of the underlying middleware. Furthermore, we give an example of the architecture's ability to support the cooperation of multiple services in a meeting scenario using an intelligent connector service and a semantic web oriented travel service.

  11. EyeScreen: A Vision-Based Desktop Interaction System

    OpenAIRE

    Xu, Yihua; Lv, Jingjun; Li, Shanqing; Jia, Yunde

    2007-01-01

    EyeScreen provides a natural HCI interface with vision-based hand tracking and gesture recognition techniques. Multi-view video images captured from two cameras facing a computer screen are used to track and recognize finger and hand motions. Finger tracking is achieved by skin color detection and particle filtering, and is greatly enhanced by the proposed screen background subtraction method that removes the screen images in advance. Finger click on the screen can also be detected from multi...

  12. A novel interacting multiple model based network intrusion detection scheme

    Science.gov (United States)

    Xin, Ruichi; Venkatasubramanian, Vijay; Leung, Henry

    2006-04-01

    In today's information age, information and network security are of primary importance to any organization. Network intrusion is a serious threat to security of computers and data networks. In internet protocol (IP) based network, intrusions originate in different kinds of packets/messages contained in the open system interconnection (OSI) layer 3 or higher layers. Network intrusion detection and prevention systems observe the layer 3 packets (or layer 4 to 7 messages) to screen for intrusions and security threats. Signature based methods use a pre-existing database that document intrusion patterns as perceived in the layer 3 to 7 protocol traffics and match the incoming traffic for potential intrusion attacks. Alternately, network traffic data can be modeled and any huge anomaly from the established traffic pattern can be detected as network intrusion. The latter method, also known as anomaly based detection is gaining popularity for its versatility in learning new patterns and discovering new attacks. It is apparent that for a reliable performance, an accurate model of the network data needs to be established. In this paper, we illustrate using collected data that network traffic is seldom stationary. We propose the use of multiple models to accurately represent the traffic data. The improvement in reliability of the proposed model is verified by measuring the detection and false alarm rates on several datasets.

  13. Systematic analysis of Ca2+ homeostasis in Saccharomyces cerevisiae based on chemical-genetic interaction profiles

    Science.gov (United States)

    Ghanegolmohammadi, Farzan; Yoshida, Mitsunori; Ohnuki, Shinsuke; Sukegawa, Yuko; Okada, Hiroki; Obara, Keisuke; Kihara, Akio; Suzuki, Kuninori; Kojima, Tetsuya; Yachie, Nozomu; Hirata, Dai; Ohya, Yoshikazu

    2017-01-01

    We investigated the global landscape of Ca2+ homeostasis in budding yeast based on high-dimensional chemical-genetic interaction profiles. The morphological responses of 62 Ca2+-sensitive (cls) mutants were quantitatively analyzed with the image processing program CalMorph after exposure to a high concentration of Ca2+. After a generalized linear model was applied, an analysis of covariance model was used to detect significant Ca2+–cls interactions. We found that high-dimensional, morphological Ca2+–cls interactions were mixed with positive (86%) and negative (14%) chemical-genetic interactions, whereas one-dimensional fitness Ca2+–cls interactions were all negative in principle. Clustering analysis with the interaction profiles revealed nine distinct gene groups, six of which were functionally associated. In addition, characterization of Ca2+–cls interactions revealed that morphology-based negative interactions are unique signatures of sensitized cellular processes and pathways. Principal component analysis was used to discriminate between suppression and enhancement of the Ca2+-sensitive phenotypes triggered by inactivation of calcineurin, a Ca2+-dependent phosphatase. Finally, similarity of the interaction profiles was used to reveal a connected network among the Ca2+ homeostasis units acting in different cellular compartments. Our analyses of high-dimensional chemical-genetic interaction profiles provide novel insights into the intracellular network of yeast Ca2+ homeostasis. PMID:28566553

  14. A cell-based method for screening RNA-protein interactions: identification of constitutive transport element-interacting proteins.

    Directory of Open Access Journals (Sweden)

    Robert L Nakamura

    Full Text Available We have developed a mammalian cell-based screening platform to identify proteins that assemble into RNA-protein complexes. Based on Tat-mediated activation of the HIV LTR, proteins that interact with an RNA target elicit expression of a GFP reporter and are captured by fluorescence activated cell sorting. This "Tat-hybrid" screening platform was used to identify proteins that interact with the Mason Pfizer monkey virus (MPMV constitutive transport element (CTE, a structured RNA hairpin that mediates the transport of unspliced viral mRNAs from the nucleus to the cytoplasm. Several hnRNP-like proteins, including hnRNP A1, were identified and shown to interact with the CTE with selectivity in the reporter system comparable to Tap, a known CTE-binding protein. In vitro gel shift and pull-down assays showed that hnRNP A1 is able to form a complex with the CTE and Tap and that the RGG domain of hnRNP A1 mediates binding to Tap. These results suggest that hnRNP-like proteins may be part of larger export-competent RNA-protein complexes and that the RGG domains of these proteins play an important role in directing these binding events. The results also demonstrate the utility of the screening platform for identifying and characterizing new components of RNA-protein complexes.

  15. Creative Multimodal Learning Environments and Blended Interaction for Problem-Based Activity in HCI Education

    Science.gov (United States)

    Ioannou, Andri; Vasiliou, Christina; Zaphiris, Panayiotis; Arh, Tanja; Klobucar, Tomaž; Pipan, Matija

    2015-01-01

    This exploratory case study aims to examine how students benefit from a multimodal learning environment while they engage in collaborative problem-based activity in a Human Computer Interaction (HCI) university course. For 12 weeks, 30 students, in groups of 5-7 each, participated in weekly face-to-face meetings and online interactions.…

  16. Seven-Step Problem-Based Learning in an Interaction Design Course

    Science.gov (United States)

    Schultz, Nette; Christensen, Hans Peter

    2004-01-01

    The objective in this paper is the implementation of the highly structured seven-step problem-based learning (PBL) procedure as part of the learning process in a human-computer interaction (HCI) design course at the Technical University of Denmark, taking into account the common learning processes in PBL and the interaction design process. These…

  17. Virtual-Reality-Based Social Interaction Training for Children with High-Functioning Autism

    Science.gov (United States)

    Ke, Fengfeng; Im, Tami

    2013-01-01

    Employing the multiple-baseline across-subjects design, the authors examined the implementation and potential effect of a virtual-reality-based social interaction program on the interaction and communication performance of children with high functioning autism. The data were collected via behavior observation and analysis, questionnaires, and…

  18. The implementation of real-time interaction in virtual education system based on VRML

    Science.gov (United States)

    Duan, Xinyu; Zhu, Jiejie

    2004-03-01

    This paper introduces the interaction control technique for creating a multimedia virtual education environment system based on VRML97. The techniques include the using of perception sensors, environment sensors, touch sensor and script programming control. In this paper, the author also discusses the methods in accomplishment of different kind of VRML interactions.

  19. Managing Mutual Orientation in the Absence of Physical Copresence: Multiparty Voice-Based Chat Room Interaction

    Science.gov (United States)

    Jenks, Christopher Joseph; Brandt, Adam

    2013-01-01

    This study investigates the interactional work involved in ratifying mutual participation in online, multiparty, voice-based chat rooms. The purpose of this article is to provide a preliminary sketch of how talk and participation is managed in a spoken communication environment that comprises interactants who are not physically copresent but are…

  20. Virtual Reality Simulations and Animations in a Web-Based Interactive Manufacturing Engineering Module

    Science.gov (United States)

    Ong, S. K.; Mannan, M. A.

    2004-01-01

    This paper presents a web-based interactive teaching package that provides a comprehensive and conducive yet dynamic and interactive environment for a module on automated machine tools in the Manufacturing Division at the National University of Singapore. The use of Internet technologies in this teaching tool makes it possible to conjure…

  1. Evaluation of the Interactivity of Web-Based Learning Systems: Principles and Process.

    Science.gov (United States)

    Evans, Chris; Sabry, Khaled

    2003-01-01

    Considers the process of evaluating the interactivity of Web-based learning systems (WBLSs), adapting a heuristic approach usually employed for usability evaluations. Proposes a three-way model of interactivity, reports an evaluation using three different WBLSs, and concludes that heuristic evaluation provides a cheap, intuitive and practical…

  2. An Interactive Computer-Based Circulation System: Design and Development

    Directory of Open Access Journals (Sweden)

    James S. Aagaard

    1972-03-01

    Full Text Available An on-line computer-based circulation control system has been installed at the Northwestern University library. Features of the system include self-service book charge, remote terminal inquiry and update, and automatic production of notices for call-ins and books available. Fine notices are also prepared daily and overdue notices weekly. Important considerations in the design of the system were to minimize costs of operation and to include technical services functions eventually. The system operates on a relatively small computer in a multiprogrammed mode.

  3. Grandmaster: Interactive text-based analytics of social media

    Energy Technology Data Exchange (ETDEWEB)

    Fabian, Nathan D.; Davis, Warren Leon,; Raybourn, Elaine M.; Lakkaraju, Kiran; Whetzel, Jonathan

    2015-11-01

    People use social media resources like Twitter, Facebook, forums etc. to share and discuss various activities or topics. By aggregating topic trends across many individuals using these services, we seek to construct a richer profile of a person’s activities and interests as well as provide a broader context of those activities. This profile may then be used in a variety of ways to understand groups as a collection of interests and affinities and an individual’s participation in those groups. Our approach considers that much of these data will be unstructured, free-form text. By analyzing free-form text directly, we may be able to gain an implicit grouping of individuals with shared interests based on shared conversation, and not on explicit social software linking them. In this paper, we discuss a proof-of-concept application called Grandmaster built to pull short sections of text, a person’s comments or Twitter posts, together by analysis and visualization to allow a gestalt understanding of the full collection of all individuals: how groups are similar and how they differ, based on their text inputs.

  4. Visible and ultraviolet light sources based nonlinear interaction of lasers

    DEFF Research Database (Denmark)

    Andersen, Martin Thalbitzer; Tidemand-Lichtenberg, Peter; Jain, Mayank

    Different light sources can be used for optically stimulated luminescence measurements and usually a halogen lamp in combination with filters or light emitting diodes (LED’s) are used to provide the desired stimulation wavelength. However lasers can provide a much more well-defined beam, very nar...... for synthesizing any wavelength in the visible and ultraviolet light based sum frequency generation between two lasers is presented.......Different light sources can be used for optically stimulated luminescence measurements and usually a halogen lamp in combination with filters or light emitting diodes (LED’s) are used to provide the desired stimulation wavelength. However lasers can provide a much more well-defined beam, very...

  5. Graphite oxide based targets applied in laser matter interaction

    Science.gov (United States)

    Cutroneo, Mariapompea; Torrisi, Lorenzo; Badziak, Jan; Rosinski, Marcin; Havranek, Vladimir; Mackova, Anna; Malinsky, Petr; Sofer, Zdenek; Luxa, Jan; Cannavò, Antonino; Lorincik, Jan

    2018-01-01

    In the present work, we propose the production of a hybrid graphene based material suitable to be laser irradiated with the aim to produce quasi-monoenergetic proton beams using a femtosecond laser system. The unique lattice structure of the irradiated solid thin target can affect the inside electron propagation, their outgoing from the rear side of a thin foil, and subsequently the plasma ion acceleration. The produced targets, have been characterized in composition, roughness and structure and for completeness irradiated. The yield and energy of the ions emitted from the laser-generated plasma have been monitored and the emission of proton stream profile exhibited an acceleration of the order of several MeVs/charge state.

  6. Development of Novel Random Network Theory-Based Approaches to Identify Network Interactions among Nitrifying Bacteria

    Energy Technology Data Exchange (ETDEWEB)

    Shi, Cindy

    2015-07-17

    The interactions among different microbial populations in a community could play more important roles in determining ecosystem functioning than species numbers and their abundances, but very little is known about such network interactions at a community level. The goal of this project is to develop novel framework approaches and associated software tools to characterize the network interactions in microbial communities based on high throughput, large scale high-throughput metagenomics data and apply these approaches to understand the impacts of environmental changes (e.g., climate change, contamination) on network interactions among different nitrifying populations and associated microbial communities.

  7. Interactive Consistency Algorithms Based on Voting and Error-Correding Codes

    NARCIS (Netherlands)

    Krol, Th.

    1995-01-01

    This paper presents a new class of synchronous deterministic non authenticated algorithms for reaching interactive consistency (Byzantine agreement). The algorithms are based on voting and error correcting codes and require considerably less data communication than the original algorithm, whereas

  8. Application of neutron-interaction based radiometric measurements in continuous industrial technologies

    International Nuclear Information System (INIS)

    Faludi, Gy.; Hazi, E.

    1980-01-01

    A number of measuring methods (such as moisture determination, hydrogen content determination, etc.) have been developed based on the interactions of neutrons and various materials (slowing-down, absorption, scattering). This paper deals with the disturbances (mainly with the effects of space-filling changes) of neutron interaction based radiometrical measurement methods used in the continuous industrial technologies and the elimination methods of these disturbances. The socalled dual-channel elimination method is discussed in detail. (author)

  9. Do interactions speak louder than words? Dialogic reading of an interactive tablet-based e-book with children between 16 months and three years of age

    DEFF Research Database (Denmark)

    Knoche, Hendrik; Rasmussen, Niklas Ammitzbøl; Boldreel, Kasper

    2014-01-01

    the effect of interactive elements on speech production of 12 children between the ages of 16 and 33 months when engaged in individual dialogic reading sessions with a tablet-based e-book. Interaction with interactive elements did not reduce the children’s responses to dialogic reading prompts. Spontaneous...

  10. A situation-based multi-agent architecture for handling misunderstandings in interactions

    Directory of Open Access Journals (Sweden)

    Pham Thao Phuong

    2015-09-01

    Full Text Available During interactions, system actors may face up misunderstandings when their local states contain inconsistent data about the same fact. Misunderstandings in interactions are likely to reduce interactivity performances (deviation or deadlock or even affect overall system behavior. In this paper, we characterize misunderstandings in interactions between system actors (that may be human users or system agents in interactive adaptive systems. To deal with such misunderstandings and ensure state consistency, we present an agent-based architecture and a scenario structuring approach. The system includes several agents devoted to scenario unfolding, plot adaptation and consistency management. Scenario structuring is based on the notion of a situation that is an elementary building block dividing the interactions between systems’ actors into contextual scenes. This pattern supports not only scenario execution but consistency management as well. In order to organize and control interactions, the situation contextualizes interactions and activity of the system’s actors. It also includes prevention and tolerance agent-based mechanisms to deal with the misunderstandings and their causes. We validate our consistency management mechanisms using Uppaal simulation and provide some experimental results to show the effectiveness of our approach on an online distance learning case study

  11. Interactive computer-based programs for a cancer learning center.

    Science.gov (United States)

    Besa, E C; Nieman, L Z; Joseph, R R

    1995-01-01

    This paper describes the design and evaluation of a computer-based instruction (CBI) program that was integrated into a multidisciplinary cancer curriculum at the Medical College of Pennsylvania. Instruction took place in a cancer learning center. Modules contained literature, posters, slide sets, videocassette films, and "see, touch, and feel" models to teach and practice breast, testicular, rectal, laryngeal, and colonoscopic examinations. The CBI (programmed on HyperCard) contained tutorials divided into three levels of learning objectives: level one, epidemiology and prevention; level two, diagnosis and staging; and level three, management and prognosis. Simulated cases and test items were developed for each level. To evaluate students' perceptions of the program and provide them with feedback about their performances, the authors designed a questionnaire, held a focus group, and developed a built-in tracking system for the CBI. Results showed that the program was well received, the students answered the test items correctly, and the students wanted more time to study cancer. A description of some of the problems encountered with technology and equipment is provided for faculty who may be interested in designing and implementing similar CBI programs.

  12. Method of predicting Splice Sites based on signal interactions

    Directory of Open Access Journals (Sweden)

    Deogun Jitender S

    2006-04-01

    Full Text Available Abstract Background Predicting and proper ranking of canonical splice sites (SSs is a challenging problem in bioinformatics and machine learning communities. Any progress in SSs recognition will lead to better understanding of splicing mechanism. We introduce several new approaches of combining a priori knowledge for improved SS detection. First, we design our new Bayesian SS sensor based on oligonucleotide counting. To further enhance prediction quality, we applied our new de novo motif detection tool MHMMotif to intronic ends and exons. We combine elements found with sensor information using Naive Bayesian Network, as implemented in our new tool SpliceScan. Results According to our tests, the Bayesian sensor outperforms the contemporary Maximum Entropy sensor for 5' SS detection. We report a number of putative Exonic (ESE and Intronic (ISE Splicing Enhancers found by MHMMotif tool. T-test statistics on mouse/rat intronic alignments indicates, that detected elements are on average more conserved as compared to other oligos, which supports our assumption of their functional importance. The tool has been shown to outperform the SpliceView, GeneSplicer, NNSplice, Genio and NetUTR tools for the test set of human genes. SpliceScan outperforms all contemporary ab initio gene structural prediction tools on the set of 5' UTR gene fragments. Conclusion Designed methods have many attractive properties, compared to existing approaches. Bayesian sensor, MHMMotif program and SpliceScan tools are freely available on our web site. Reviewers This article was reviewed by Manyuan Long, Arcady Mushegian and Mikhail Gelfand.

  13. 4.1 Web-based interactive learning programmes.

    Science.gov (United States)

    Nattestad, Anders; Attstrom, Rolf; Mattheos, Nikos; Ramseier, Christoph; Canegallo, Lorenza; Eaton, Ken; Feeney, Luke; Goffin, Guy; Markovska, Neda; Maixner, William; Persson, Rutger; Reynolds, Patricia; Ruotoistenmaki, Juha; Schittek, Martin; Spohn, Eric; Sudzina, Mike

    2002-01-01

    In the future, the training of competent dentists will need to take advantage of up-to-date digital technologies and learning practices. In order to accomplish this, the following goals should be considered: i) the design of 'customizable' web-based curriculum matrices that accommodate the training philosophies and resources of individual dental schools; ii) the development of digital instructional modules that can be incorporated or downloaded into specific parts of a curriculum; iii) the establishment of an e-consortium, which provides peer view and guidance in the design of teaching modules, and which is responsible for the storage, maintenance, and distribution of teaching modules within the consortium; iv) the development of central human and physical resources at each dental school to enable the seamless delivery of instructional modules in a variety of learning environments; and v) the assessment and provision of ICT training to students and faculty with respect to the use of computers and related digital technologies and educational software programmes. These goals should lead to the creation of a 'virtual dental school'. Within this project summative and formative evaluations should be performed during both the production and development of teaching material (e-learning material) and the learning process. During the learning process the following aspects should be measured and evaluated: i) students' behaviour; and ii) effectiveness, retention and the transfer of e-learned material into the clinical situation. To obtain evidence of the efficacy of e-learning material a certain amount of research has to be done in the near future. It is suggested that all parameters currently known have to be implemented during the development of a learning programme. Previous workers have evaluated the following elements with e-learning: i) planning, ii) programming and technical development, iii) learning behaviours, iv) learning outcomes of both the programme and the

  14. PPI-IRO: A two-stage method for protein-protein interaction extraction based on interaction relation ontology

    KAUST Repository

    Li, Chuanxi

    2014-01-01

    Mining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identifi cation of biological regulatory networks. This paper presents a novel method based on the idea of Interaction Relation Ontology (IRO), which specifi es and organises words of various proteins interaction relationships. Our method is a two-stage PPI extraction method. At fi rst, IRO is applied in a binary classifi er to determine whether sentences contain a relation or not. Then, IRO is taken to guide PPI extraction by building sentence dependency parse tree. Comprehensive and quantitative evaluations and detailed analyses are used to demonstrate the signifi cant performance of IRO on relation sentences classifi cation and PPI extraction. Our PPI extraction method yielded a recall of around 80% and 90% and an F1 of around 54% and 66% on corpora of AIMed and Bioinfer, respectively, which are superior to most existing extraction methods. Copyright © 2014 Inderscience Enterprises Ltd.

  15. Wearable Vibration Based Computer Interaction and Communication System for Deaf

    Directory of Open Access Journals (Sweden)

    Mete Yağanoğlu

    2017-12-01

    Full Text Available In individuals with impaired hearing, determining the direction of sound is a significant problem. The direction of sound was determined in this study, which allowed hearing impaired individuals to perceive where sounds originated. This study also determined whether something was being spoken loudly near the hearing impaired individual. In this manner, it was intended that they should be able to recognize panic conditions more quickly. The developed wearable system has four microphone inlets, two vibration motor outlets, and four Light Emitting Diode (LED outlets. The vibration of motors placed on the right and left fingertips permits the indication of the direction of sound through specific vibration frequencies. This study applies the ReliefF feature selection method to evaluate every feature in comparison to other features and determine which features are more effective in the classification phase. This study primarily selects the best feature extraction and classification methods. Then, the prototype device has been tested using these selected methods on themselves. ReliefF feature selection methods are used in the studies; the success of K nearest neighborhood (Knn classification had a 93% success rate and classification with Support Vector Machine (SVM had a 94% success rate. At close range, SVM and two of the best feature methods were used and returned a 98% success rate. When testing our wearable devices on users in real time, we used a classification technique to detect the direction and our wearable devices responded in 0.68 s; this saves power in comparison to traditional direction detection methods. Meanwhile, if there was an echo in an indoor environment, the success rate increased; the echo canceller was disabled in environments without an echo to save power. We also compared our system with the localization algorithm based on the microphone array; the wearable device that we developed had a high success rate and it produced faster

  16. An interactive game-based shoulder wheel system for rehabilitation

    Directory of Open Access Journals (Sweden)

    Chou LW

    2012-11-01

    Full Text Available Chun-Ming Chang,1,* Yen-Ching Chang,2,3 Hsiao-Yun Chang,4 Li-Wei Chou5,6,* 1Department of Applied Informatics and Multimedia, Asia University, Taichung, Taiwan; 2Department of Medical Informatics, Chung Shan Medical University, Taichung, Taiwan; 3Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan; 4Department of Biotechnology, Asia University, Taichung, Taiwan; 5Department of Physical Medicine and Rehabilitation, China Medical University Hospital, Taichung, Taiwan; 6School of Chinese Medicine, College of Chinese Medicine, China Medical University, Taichung, Taiwan*These authors contributed equally to this workBackground: Increases in the aging population and in the number of accidents have resulted in more people suffering from physical impairments or disabilities. Rehabilitation therapy thus attracts greater attention as a means of helping patients recover and return to a normal life. With the extremely long and tedious nature of traditional rehabilitation, patients are reluctant to continue the entire process, thus the expected effects of the therapy cannot be obtained. Games are well known to help patients improve their concentration and shift their attention away from the discomfort of their injuries during rehabilitation. Thus, incorporating game technology into a rehabilitation program may be a promising approach.Methods: In this study, a gaming system used for shoulder rehabilitation was developed. The mechanical parts and electric circuits were integrated to mimic the functionalities of a shoulder wheel. Several games were also designed to suit the rehabilitation needs of the patients based on the age and gender differences among the individual users, enabling individuals to undergo the rehabilitation process by playing games. Two surveys were conducted to evaluate the satisfaction of the participants regarding the gaming system.Results: The results of the online survey among a larger population

  17. Domain-Based Predictive Models for Protein-Protein Interaction Prediction

    Directory of Open Access Journals (Sweden)

    Chen Xue-Wen

    2006-01-01

    Full Text Available Protein interactions are of biological interest because they orchestrate a number of cellular processes such as metabolic pathways and immunological recognition. Recently, methods for predicting protein interactions using domain information are proposed and preliminary results have demonstrated their feasibility. In this paper, we develop two domain-based statistical models (neural networks and decision trees for protein interaction predictions. Unlike most of the existing methods which consider only domain pairs (one domain from one protein and assume that domain-domain interactions are independent of each other, the proposed methods are capable of exploring all possible interactions between domains and make predictions based on all the domains. Compared to maximum-likelihood estimation methods, our experimental results show that the proposed schemes can predict protein-protein interactions with higher specificity and sensitivity, while requiring less computation time. Furthermore, the decision tree-based model can be used to infer the interactions not only between two domains, but among multiple domains as well.

  18. Calculation of microscopic exchange interactions and modelling of macroscopic magnetic properties in molecule-based magnets.

    Science.gov (United States)

    Novoa, J J; Deumal, M; Jornet-Somoza, J

    2011-06-01

    The state-of-the-art theoretical evaluation and rationalization of the magnetic interactions (J(AB)) in molecule-based magnets is discussed in this critical review, focusing first on isolated radical···radical pair interactions and afterwards on how these interactions cooperate in the solid phase. Concerning isolated radical pairwise magnetic interactions, an initial analysis is done on qualitative grounds, concentrating also on the validity of the most commonly used models to predict their size and angularity (namely, McConnell-I and McConnell-II models, overlap of magnetic orbitals,…). The failure of these models, caused by their oversimplified description of the magnetic interactions, prompted the introduction of quantitative approaches, whose basic principles and relative quality are also evaluated. Concerning the computation of magnetic interactions in solids, we resort to a sum of pairwise magnetic interactions within the Heisenberg Hamiltonian framework, and follow the First-principles Bottom-Up procedure, which allows the accurate study of the magnetic properties of any molecule-based magnet in an unbiased way. The basic principles of this approach are outlined, applied in detail to a model system, and finally demonstrated to properly describe the magnetic properties of molecule-based systems that show a variety of magnetic topologies, which range from 1D to 3D (152 references).

  19. Protein-Protein Interactions Prediction Based on Iterative Clique Extension with Gene Ontology Filtering

    Directory of Open Access Journals (Sweden)

    Lei Yang

    2014-01-01

    Full Text Available Cliques (maximal complete subnets in protein-protein interaction (PPI network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based method of prediction and gene ontology (GO annotations to overcome the shortcoming and improve the accuracy of predictions. According to different GO correcting rules, we generate two predicted interaction sets which guarantee the quality and quantity of predicted protein interactions. The proposed method is applied to the PPI network from the Database of Interacting Proteins (DIP and most of the predicted interactions are verified by another biological database, BioGRID. The predicted protein interactions are appended to the original protein network, which leads to clique extension and shows the significance of biological meaning.

  20. Simplified method to predict mutual interactions of human transcription factors based on their primary structure.

    Directory of Open Access Journals (Sweden)

    Sebastian Schmeier

    Full Text Available BACKGROUND: Physical interactions between transcription factors (TFs are necessary for forming regulatory protein complexes and thus play a crucial role in gene regulation. Currently, knowledge about the mechanisms of these TF interactions is incomplete and the number of known TF interactions is limited. Computational prediction of such interactions can help identify potential new TF interactions as well as contribute to better understanding the complex machinery involved in gene regulation. METHODOLOGY: We propose here such a method for the prediction of TF interactions. The method uses only the primary sequence information of the interacting TFs, resulting in a much greater simplicity of the prediction algorithm. Through an advanced feature selection process, we determined a subset of 97 model features that constitute the optimized model in the subset we considered. The model, based on quadratic discriminant analysis, achieves a prediction accuracy of 85.39% on a blind set of interactions. This result is achieved despite the selection for the negative data set of only those TF from the same type of proteins, i.e. TFs that function in the same cellular compartment (nucleus and in the same type of molecular process (transcription initiation. Such selection poses significant challenges for developing models with high specificity, but at the same time better reflects real-world problems. CONCLUSIONS: The performance of our predictor compares well to those of much more complex approaches for predicting TF and general protein-protein interactions, particularly when taking the reduced complexity of model utilisation into account.

  1. Simplified method to predict mutual interactions of human transcription factors based on their primary structure

    KAUST Repository

    Schmeier, Sebastian

    2011-07-05

    Background: Physical interactions between transcription factors (TFs) are necessary for forming regulatory protein complexes and thus play a crucial role in gene regulation. Currently, knowledge about the mechanisms of these TF interactions is incomplete and the number of known TF interactions is limited. Computational prediction of such interactions can help identify potential new TF interactions as well as contribute to better understanding the complex machinery involved in gene regulation. Methodology: We propose here such a method for the prediction of TF interactions. The method uses only the primary sequence information of the interacting TFs, resulting in a much greater simplicity of the prediction algorithm. Through an advanced feature selection process, we determined a subset of 97 model features that constitute the optimized model in the subset we considered. The model, based on quadratic discriminant analysis, achieves a prediction accuracy of 85.39% on a blind set of interactions. This result is achieved despite the selection for the negative data set of only those TF from the same type of proteins, i.e. TFs that function in the same cellular compartment (nucleus) and in the same type of molecular process (transcription initiation). Such selection poses significant challenges for developing models with high specificity, but at the same time better reflects real-world problems. Conclusions: The performance of our predictor compares well to those of much more complex approaches for predicting TF and general protein-protein interactions, particularly when taking the reduced complexity of model utilisation into account. © 2011 Schmeier et al.

  2. Sub-Synchronous Interaction Analysis between DFIG Based Wind Farm and Series Compensated Network

    OpenAIRE

    Wang, Yun; Wu, Qiuwei; Kang, Shaoli

    2016-01-01

    This paper analyzes the sub-synchronous interaction (SSI) phenomenon between the doubly fed induction generator (DFIG) based wind farm (WF) and the series capacitor compensated network. The possible types of SSI in the DFIG based WF are studied. The factors influencing the SSI of DFIG based WF are investigated. The large signal stability and small signal stability of the DFIG based WF with different series compensation (SC) level and wind speed are simulated and compared.

  3. Sub-Synchronous Interaction Analysis between DFIG Based Wind Farm and Series Compensated Network

    DEFF Research Database (Denmark)

    Wang, Yun; Wu, Qiuwei; Kang, Shaoli

    2016-01-01

    This paper analyzes the sub-synchronous interaction (SSI) phenomenon between the doubly fed induction generator (DFIG) based wind farm (WF) and the series capacitor compensated network. The possible types of SSI in the DFIG based WF are studied. The factors influencing the SSI of DFIG based WF...... are investigated. The large signal stability and small signal stability of the DFIG based WF with different series compensation (SC) level and wind speed are simulated and compared....

  4. Content Interactivity: The Effect of Higher Levels of Interactivity on Learner Performance Outcomes and Satisfaction in Web-Based Military Training

    Science.gov (United States)

    Kenyon, Peggy L.

    2012-01-01

    The effect of content interactivity on performance outcomes and satisfaction has been studied by researchers who compared the results of Web-based and computer-based learning to classroom learning. Few scholars have compared the effects of the same content produced at different levels (low and high) of interactivity and the resulting effects. The…

  5. Reciprocity in computer-human interaction: source-based, norm-based, and affect-based explanations.

    Science.gov (United States)

    Lee, Seungcheol Austin; Liang, Yuhua Jake

    2015-04-01

    Individuals often apply social rules when they interact with computers, and this is known as the Computers Are Social Actors (CASA) effect. Following previous work, one approach to understand the mechanism responsible for CASA is to utilize computer agents and have the agents attempt to gain human compliance (e.g., completing a pattern recognition task). The current study focuses on three key factors frequently cited to influence traditional notions of compliance: evaluations toward the source (competence and warmth), normative influence (reciprocity), and affective influence (mood). Structural equation modeling assessed the effects of these factors on human compliance with computer request. The final model shows that norm-based influence (reciprocity) increased the likelihood of compliance, while evaluations toward the computer agent did not significantly influence compliance.

  6. Does a Case-Based Online Group Project Increase Students' Satisfaction with Interaction in Online Courses?

    Science.gov (United States)

    Lee, Sang Joon; Ngampornchai, Anchalee; Trail-Constant, Trudian; Abril, Andres; Srinivasan, Sandhya

    2016-01-01

    Due to the realistic, complex natures of authentic cases involved in case-based learning, the use of group work has been encouraged and expected to enhance the quality of interaction among participants and to improve students' learning experiences. The purpose of this study was to investigate whether the case-based online group work increased…

  7. Design and implementation of an interactive web-based near real-time forest monitoring system

    NARCIS (Netherlands)

    Pratihast, Arun Kumar; Vries, de Ben; Avitabile, Valerio; Bruin, De Sytze; Herold, Martin; Bergsma, Aldo

    2016-01-01

    This paper describes an interactive web-based near real-time (NRT) forest monitoring system using four levels of geographic information services: 1) the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2) NRT forest disturbance detection

  8. Systematic analysis of Ca2+ homeostasis in Saccharomyces cerevisiae based on chemical-genetic interaction profiles.

    Science.gov (United States)

    Ghanegolmohammadi, Farzan; Yoshida, Mitsunori; Ohnuki, Shinsuke; Sukegawa, Yuko; Okada, Hiroki; Obara, Keisuke; Kihara, Akio; Suzuki, Kuninori; Kojima, Tetsuya; Yachie, Nozomu; Hirata, Dai; Ohya, Yoshikazu

    2017-11-07

    We investigated the global landscape of Ca 2+ homeostasis in budding yeast based on high-dimensional chemical-genetic interaction profiles. The morphological responses of 62 Ca 2+ -sensitive ( cls ) mutants were quantitatively analyzed with the image processing program CalMorph after exposure to a high concentration of Ca 2+ After a generalized linear model was applied, an analysis of covariance model was used to detect significant Ca 2+ - cls interactions. We found that high-dimensional, morphological Ca 2+ - cls interactions were mixed with positive (86%) and negative (14%) chemical-genetic interactions, whereas one-dimensional fitness Ca 2+ - cls interactions were all negative in principle. Clustering analysis with the interaction profiles revealed nine distinct gene groups, six of which were functionally associated. In addition, characterization of Ca 2+ - cls interactions revealed that morphology-based negative interactions are unique signatures of sensitized cellular processes and pathways. Principal component analysis was used to discriminate between suppression and enhancement of the Ca 2+ -sensitive phenotypes triggered by inactivation of calcineurin, a Ca 2+ -dependent phosphatase. Finally, similarity of the interaction profiles was used to reveal a connected network among the Ca 2+ homeostasis units acting in different cellular compartments. Our analyses of high-dimensional chemical-genetic interaction profiles provide novel insights into the intracellular network of yeast Ca 2+ homeostasis. © 2017 Ghanegolmohammadi, Yoshida, et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  9. Genetics-based interactions among plants, pathogens, and herbivores define arthropod community structure.

    Science.gov (United States)

    Busby, Posy E; Lamit, Louis J; Keith, Arthur R; Newcombe, George; Gehring, Catherine A; Whitham, Thomas G; Dirzo, Rodolfo

    2015-07-01

    Plant resistance to pathogens or insect herbivores is common, but its potential for indirectly influencing plant-associated communities is poorly known. Here, we test whether pathogens' indirect effects on arthropod communities and herbivory depend on plant resistance to pathogens and/or herbivores, and address the overarching interacting foundation species hypothesis that genetics-based interactions among a few highly interactive species can structure a much larger community. In a manipulative field experiment using replicated genotypes of two Populus species and their interspecific hybrids, we found that genetic variation in plant resistance to both pathogens and insect herbivores modulated the strength of pathogens' indirect effects on arthropod communities and insect herbivory. First, due in part to the pathogens' differential impacts on leaf biomass among the two Populus species and the hybrids, the pathogen most strongly impacted arthropod community composition, richness, and abundance on the pathogen-susceptible tree species. Second, we found similar patterns comparing pathogen-susceptible and pathogen-resistant genotypes within species. Third, within a plant species, pathogens caused a fivefold greater reduction in herbivory on insect-herbivore-susceptible plant genotypes than on herbivore-resistant genotypes, demonstrating that the pathogen-herbivore interaction is genotype dependent. We conclude that interactions among plants, pathogens, and herbivores can structure multitrophic communities, supporting the interacting foundation species hypothesis. Because these interactions are genetically based, evolutionary changes in genetic resistance could result in ecological changes in associated communities, which may in turn feed back to affect plant fitness.

  10. A New Framework of Human Interaction Recognition Based on Multiple Stage Probability Fusion

    Directory of Open Access Journals (Sweden)

    Xiaofei Ji

    2017-06-01

    Full Text Available Visual-based human interactive behavior recognition is a challenging research topic in computer vision. There exist some important problems in the current interaction recognition algorithms, such as very complex feature representation and inaccurate feature extraction induced by wrong human body segmentation. In order to solve these problems, a novel human interaction recognition method based on multiple stage probability fusion is proposed in this paper. According to the human body’s contact in interaction as a cut-off point, the process of the interaction can be divided into three stages: start stage, execution stage and end stage. Two persons’ motions are respectively extracted and recognizes in the start stage and the finish stage when there is no contact between those persons. The two persons’ motion is extracted as a whole and recognized in the execution stage. In the recognition process, the final recognition results are obtained by the weighted fusing these probabilities in different stages. The proposed method not only simplifies the extraction and representation of features, but also avoids the wrong feature extraction caused by occlusion. Experiment results on the UT-interaction dataset demonstrated that the proposed method results in a better performance than other recent interaction recognition methods.

  11. Interaction of cytotoxic agents: a rule-based system for computer-assisted cell survival analysis.

    Science.gov (United States)

    Gentile, F P; Chiatti, L; Mauro, F; Briganti, G; Floridi, A; Benassi, M

    1992-01-01

    The actual effectiveness of environmental noxious agents or anticancer drugs can be fully determined only by knowing if the effects (in the present case, the cytotoxic effects) induced by a given agent are enhanced by exposure to another (or other) agent(s). Given a certain combination of agents, it is possible to distinguish three types of interaction: (a) zero interaction or additivity; (b) positive interaction or synergism; and (c) negative interaction or antagonism. In this work, the methodological problems involved in evaluating the type and level of interaction between biologically active agents are discussed and an "intelligent" approach to the problem is proposed. In particular, a prototype of a computer-assisted rule based system, named CISA (Cytotoxic Interaction and Survival Analysis), designed in a KES environment (Knowledge Engineering System) and implemented on a personal computer, is described. By constructing isoboles based on experimental cell survival data and taking into account the relative confidence intervals, the system can indicate the appropriate combinations of dosages to be tested and finally determine the type and level of interaction. The system, which represents an attempt to administer "intelligently" the experimental data, is therefore able to identify the best strategy of analysis, to carry out the data processing and to offer suggestions to the investigator about the usefulness of the data and the planning of further experiments.

  12. Interactive Information Service Technology of Tea Industry Based on Demand-Driven

    OpenAIRE

    Shi , Xiaohui; Chen , Tian’en

    2013-01-01

    International audience; Information service technology is a bridge between user and information resource, also is the critical factor to weight the quality of information service. Focusing on the information service features of tea industry, the demand-driven and interaction of information service were emphasized in this paper. User and market as the major criterion for testing the quality of information service, the interactive information service mode based on the demand-driven was proposed...

  13. The acid-base character of interactions between xenon and selected carboxylic and sulfonic acids

    Science.gov (United States)

    Gąszowski, Dawid; Ilczyszyn, Marek

    2017-05-01

    Interactions of Xe atoms with RCO2H and RSO3H (R = CH3 and CF3) acids in different solvents are examined by analysis of 129Xe chemical shifts extrapolated to zero solvent concentration. Obtained results are very sensitive to the Xe contacts with the methyl and trifluoromethyl groups as well as with the carboxylic and sulfonic groups of different acidity. The acid-base character of these acid-Xe interactions is considered.

  14. Web-based interactive visualization in a Grid-enabled neuroimaging application using HTML5.

    Science.gov (United States)

    Siewert, René; Specovius, Svenja; Wu, Jie; Krefting, Dagmar

    2012-01-01

    Interactive visualization and correction of intermediate results are required in many medical image analysis pipelines. To allow certain interaction in the remote execution of compute- and data-intensive applications, new features of HTML5 are used. They allow for transparent integration of user interaction into Grid- or Cloud-enabled scientific workflows. Both 2D and 3D visualization and data manipulation can be performed through a scientific gateway without the need to install specific software or web browser plugins. The possibilities of web-based visualization are presented along the FreeSurfer-pipeline, a popular compute- and data-intensive software tool for quantitative neuroimaging.

  15. A map of directional genetic interactions in a metazoan cell.

    Science.gov (United States)

    Fischer, Bernd; Sandmann, Thomas; Horn, Thomas; Billmann, Maximilian; Chaudhary, Varun; Huber, Wolfgang; Boutros, Michael

    2015-03-06

    Gene-gene interactions shape complex phenotypes and modify the effects of mutations during development and disease. The effects of statistical gene-gene interactions on phenotypes have been used to assign genes to functional modules. However, directional, epistatic interactions, which reflect regulatory relationships between genes, have been challenging to map at large-scale. Here, we used combinatorial RNA interference and automated single-cell phenotyping to generate a large genetic interaction map for 21 phenotypic features of Drosophila cells. We devised a method that combines genetic interactions on multiple phenotypes to reveal directional relationships. This network reconstructed the sequence of protein activities in mitosis. Moreover, it revealed that the Ras pathway interacts with the SWI/SNF chromatin-remodelling complex, an interaction that we show is conserved in human cancer cells. Our study presents a powerful approach for reconstructing directional regulatory networks and provides a resource for the interpretation of functional consequences of genetic alterations.

  16. Assessing causal mechanistic interactions: a peril ratio index of synergy based on multiplicativity.

    Directory of Open Access Journals (Sweden)

    Wen-Chung Lee

    Full Text Available The assessments of interactions in epidemiology have traditionally been based on risk-ratio, odds-ratio or rate-ratio multiplicativity. However, many epidemiologists fail to recognize that this is mainly for statistical conveniences and often will misinterpret a statistically significant interaction as a genuine mechanistic interaction. The author adopts an alternative metric system for risk, the 'peril'. A peril is an exponentiated cumulative rate, or simply, the inverse of a survival (risk complement or one plus an odds. The author proposes a new index based on multiplicativity of peril ratios, the 'peril ratio index of synergy based on multiplicativity' (PRISM. Under the assumption of no redundancy, PRISM can be used to assess synergisms in sufficient cause sense, i.e., causal co-actions or causal mechanistic interactions. It has a less stringent threshold to detect a synergy as compared to a previous index of 'relative excess risk due to interaction'. Using the new PRISM criterion, many situations in which there is not evidence of interaction judged by the traditional indices are in fact corresponding to bona fide positive or negative synergisms.

  17. Assessing causal mechanistic interactions: a peril ratio index of synergy based on multiplicativity.

    Science.gov (United States)

    Lee, Wen-Chung

    2013-01-01

    The assessments of interactions in epidemiology have traditionally been based on risk-ratio, odds-ratio or rate-ratio multiplicativity. However, many epidemiologists fail to recognize that this is mainly for statistical conveniences and often will misinterpret a statistically significant interaction as a genuine mechanistic interaction. The author adopts an alternative metric system for risk, the 'peril'. A peril is an exponentiated cumulative rate, or simply, the inverse of a survival (risk complement) or one plus an odds. The author proposes a new index based on multiplicativity of peril ratios, the 'peril ratio index of synergy based on multiplicativity' (PRISM). Under the assumption of no redundancy, PRISM can be used to assess synergisms in sufficient cause sense, i.e., causal co-actions or causal mechanistic interactions. It has a less stringent threshold to detect a synergy as compared to a previous index of 'relative excess risk due to interaction'. Using the new PRISM criterion, many situations in which there is not evidence of interaction judged by the traditional indices are in fact corresponding to bona fide positive or negative synergisms.

  18. Incorporating information on predicted solvent accessibility to the co-evolution-based study of protein interactions.

    Science.gov (United States)

    Ochoa, David; García-Gutiérrez, Ponciano; Juan, David; Valencia, Alfonso; Pazos, Florencio

    2013-01-27

    A widespread family of methods for studying and predicting protein interactions using sequence information is based on co-evolution, quantified as similarity of phylogenetic trees. Part of the co-evolution observed between interacting proteins could be due to co-adaptation caused by inter-protein contacts. In this case, the co-evolution is expected to be more evident when evaluated on the surface of the proteins or the internal layers close to it. In this work we study the effect of incorporating information on predicted solvent accessibility to three methods for predicting protein interactions based on similarity of phylogenetic trees. We evaluate the performance of these methods in predicting different types of protein associations when trees based on positions with different characteristics of predicted accessibility are used as input. We found that predicted accessibility improves the results of two recent versions of the mirrortree methodology in predicting direct binary physical interactions, while it neither improves these methods, nor the original mirrortree method, in predicting other types of interactions. That improvement comes at no cost in terms of applicability since accessibility can be predicted for any sequence. We also found that predictions of protein-protein interactions are improved when multiple sequence alignments with a richer representation of sequences (including paralogs) are incorporated in the accessibility prediction.

  19. How to Develop Electrochemistry SETS-Based Interactive E-Book?

    Science.gov (United States)

    Munawwarah, M.; Anwar, S.; Sunarya, Y.

    2017-09-01

    This study aims to develop SETS-based interactive e-book teaching material through 4S TMD methode. The research methode in this study is the Development Research (RD) Richey and Klein that consists of design, phase, and evaluation. The design step was to analyze and plan the types of teaching materials instructional developed. There are 12 indicators from 3 standard competences that produced in selection step based new curriculum, the compatibility subject matter and indicators, and the relations between value and subject matter. Structuring steps yield concept map, macro structure, and multiple representation that were arranged to be first draft of teaching material that was used for develop the instruments for characterization step. Chatacterization test have been done to students in 12nd grades with 68 texts. Characterization results indicated that there were some texts included to difficult text. Difficult texts have been reduced with the ways back to qualitative steps and particulation. The second draft of teaching material was arranged based the results of didactic reduction of difficult texts. This draft was used for arranged interactive e-book. The characteristics of this SETS-based interactive e-book that developed were mention about the connection between science with environment, technology, and society. This interactive e-book consists of animation, task, and quizes that taken the interaction of students directly.

  20. Interactions of sugar-based bolaamphiphiles with biomimetic systems of plasma membranes.

    Science.gov (United States)

    Nasir, Mehmet Nail; Crowet, Jean-Marc; Lins, Laurence; Obounou Akong, Firmin; Haudrechy, Arnaud; Bouquillon, Sandrine; Deleu, Magali

    2016-11-01

    Glycolipids constitute a class of molecules with various biological activities. Among them, sugar-based bolaamphiphiles characterized by their biocompatibility, biodegradability and lower toxicity, became interesting for the development of efficient and low cost lipid-based drug delivery systems. Their activity seems to be closely related to their interactions with the lipid components of the plasma membrane of target cells. Despite many works devoted to the chemical synthesis and characterization of sugar-based bolaamphiphiles, their interactions with plasma membrane have not been completely elucidated. In this work, two sugar-based bolaamphiphiles differing only at the level of their sugar residues were chemically synthetized. Their interactions with membranes have been investigated using model membranes containing or not sterol and with in silico approaches. Our findings indicate that the nature of sugar residues has no significant influence for their membrane interacting properties, while the presence of sterol attenuates the interactions of both bolaamphiphiles with the membrane systems. The understanding of this distinct behavior of bolaamphiphiles towards sterol-containing membrane systems could be useful for their applications as drug delivery systems. Copyright © 2016. Published by Elsevier B.V.

  1. Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines.

    Science.gov (United States)

    González, Alvaro J; Liao, Li

    2010-10-29

    Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI) is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. In this paper, we propose a computational method to predict DDI using support vector machines (SVMs), based on domains represented as interaction profile hidden Markov models (ipHMM) where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB). Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD). Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure), an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on the web at http

  2. Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines

    Directory of Open Access Journals (Sweden)

    Liao Li

    2010-10-01

    Full Text Available Abstract Background Protein-protein interaction (PPI plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. Results In this paper, we propose a computational method to predict DDI using support vector machines (SVMs, based on domains represented as interaction profile hidden Markov models (ipHMM where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB. Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD. Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure, an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. Conclusions We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on

  3. Prediction of oncogenic interactions and cancer-related signaling networks based on network topology.

    Directory of Open Access Journals (Sweden)

    Marcio Luis Acencio

    Full Text Available Cancer has been increasingly recognized as a systems biology disease since many investigators have demonstrated that this malignant phenotype emerges from abnormal protein-protein, regulatory and metabolic interactions induced by simultaneous structural and regulatory changes in multiple genes and pathways. Therefore, the identification of oncogenic interactions and cancer-related signaling networks is crucial for better understanding cancer. As experimental techniques for determining such interactions and signaling networks are labor-intensive and time-consuming, the development of a computational approach capable to accomplish this task would be of great value. For this purpose, we present here a novel computational approach based on network topology and machine learning capable to predict oncogenic interactions and extract relevant cancer-related signaling subnetworks from an integrated network of human genes interactions (INHGI. This approach, called graph2sig, is twofold: first, it assigns oncogenic scores to all interactions in the INHGI and then these oncogenic scores are used as edge weights to extract oncogenic signaling subnetworks from INHGI. Regarding the prediction of oncogenic interactions, we showed that graph2sig is able to recover 89% of known oncogenic interactions with a precision of 77%. Moreover, the interactions that received high oncogenic scores are enriched in genes for which mutations have been causally implicated in cancer. We also demonstrated that graph2sig is potentially useful in extracting oncogenic signaling subnetworks: more than 80% of constructed subnetworks contain more than 50% of original interactions in their corresponding oncogenic linear pathways present in the KEGG PATHWAY database. In addition, the potential oncogenic signaling subnetworks discovered by graph2sig are supported by experimental evidence. Taken together, these results suggest that graph2sig can be a useful tool for investigators involved

  4. Search for intracranial aneurysm susceptibility gene(s using Finnish families

    Directory of Open Access Journals (Sweden)

    Ryynänen Markku

    2002-08-01

    Full Text Available Abstract Background Cerebrovascular disease is the third leading cause of death in the United States, and about one-fourth of cerebrovascular deaths are attributed to ruptured intracranial aneurysms (IA. Epidemiological evidence suggests that IAs cluster in families, and are therefore probably genetic. Identification of individuals at risk for developing IAs by genetic tests will allow concentration of diagnostic imaging on high-risk individuals. We used model-free linkage analysis based on allele sharing with a two-stage design for a genome-wide scan to identify chromosomal regions that may harbor IA loci. Methods We previously estimated sibling relative risk in the Finnish population at between 9 and 16, and proceeded with a genome-wide scan for loci predisposing to IA. In 85 Finnish families with two or more affected members, 48 affected sibling pairs (ASPs were available for our genetic study. Power calculations indicated that 48 ASPs were adequate to identify chromosomal regions likely to harbor predisposing genes and that a liberal stage I lod score threshold of 0.8 provided a reasonable balance between detection of false positive regions and failure to detect real loci with moderate effect. Results Seven chromosomal regions exceeded the stage I lod score threshold of 0.8 and five exceeded 1.0. The most significant region, on chromosome 19q, had a maximum multipoint lod score (MLS of 2.6. Conclusions Our study provides evidence for the locations of genes predisposing to IA. Further studies are necessary to elucidate the genes and their role in the pathophysiology of IA, and to design genetic tests.

  5. A hybrid configuration interaction treatment based on seniority number and excitation schemes

    Energy Technology Data Exchange (ETDEWEB)

    Alcoba, Diego R.; Capuzzi, Pablo [Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires and Instituto de Física de Buenos Aires, Consejo Nacional de Investigaciones Científicas y Técnicas, Ciudad Universitaria, 1428 Buenos Aires (Argentina); Torre, Alicia; Lain, Luis, E-mail: qfplapel@lg.ehu.es [Departamento de Química Física, Facultad de Ciencia y Tecnología, Universidad del País Vasco, Apdo. 644 E-48080 Bilbao (Spain); Oña, Ofelia B. [Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas, Universidad Nacional de La Plata, CCT La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, Diag. 113 y 64 (S/N), Sucursal 4, CC 16, 1900 La Plata (Argentina); Van Raemdonck, Mario; Bultinck, Patrick [Department of Inorganic and Physical Chemistry, Ghent University, Krijgslaan 281 (S3), 9000 Gent (Belgium); Van Neck, Dimitri [Center for Molecular Modelling, Ghent University, Technologiepark 903, 9052 Zwijnaarde (Belgium)

    2014-12-28

    We present a configuration interaction method in which the Hamiltonian of an N-electron system is projected on Slater determinants selected according to the seniority-number criterion along with the traditional excitation-based procedure. This proposed method is especially useful to describe systems which exhibit dynamic (weak) correlation at determined geometric arrangements (where the excitation-based procedure is more suitable) but show static (strong) correlation at other arrangements (where the seniority-number technique is preferred). The hybrid method amends the shortcomings of both individual determinant selection procedures, yielding correct shapes of potential energy curves with results closer to those provided by the full configuration interaction method.

  6. Limitations of a metabolic network-based reverse ecology method for inferring host-pathogen interactions.

    Science.gov (United States)

    Takemoto, Kazuhiro; Aie, Kazuki

    2017-05-25

    Host-pathogen interactions are important in a wide range of research fields. Given the importance of metabolic crosstalk between hosts and pathogens, a metabolic network-based reverse ecology method was proposed to infer these interactions. However, the validity of this method remains unclear because of the various explanations presented and the influence of potentially confounding factors that have thus far been neglected. We re-evaluated the importance of the reverse ecology method for evaluating host-pathogen interactions while statistically controlling for confounding effects using oxygen requirement, genome, metabolic network, and phylogeny data. Our data analyses showed that host-pathogen interactions were more strongly influenced by genome size, primary network parameters (e.g., number of edges), oxygen requirement, and phylogeny than the reserve ecology-based measures. These results indicate the limitations of the reverse ecology method; however, they do not discount the importance of adopting reverse ecology approaches altogether. Rather, we highlight the need for developing more suitable methods for inferring host-pathogen interactions and conducting more careful examinations of the relationships between metabolic networks and host-pathogen interactions.

  7. Selection of organisms for the co-evolution-based study of protein interactions.

    Science.gov (United States)

    Herman, Dorota; Ochoa, David; Juan, David; Lopez, Daniel; Valencia, Alfonso; Pazos, Florencio

    2011-09-12

    The prediction and study of protein interactions and functional relationships based on similarity of phylogenetic trees, exemplified by the mirrortree and related methodologies, is being widely used. Although dependence between the performance of these methods and the set of organisms used to build the trees was suspected, so far nobody assessed it in an exhaustive way, and, in general, previous works used as many organisms as possible. In this work we asses the effect of using different sets of organism (chosen according with various phylogenetic criteria) on the performance of this methodology in detecting protein interactions of different nature. We show that the performance of three mirrortree-related methodologies depends on the set of organisms used for building the trees, and it is not always directly related to the number of organisms in a simple way. Certain subsets of organisms seem to be more suitable for the predictions of certain types of interactions. This relationship between type of interaction and optimal set of organism for detecting them makes sense in the light of the phylogenetic distribution of the organisms and the nature of the interactions. In order to obtain an optimal performance when predicting protein interactions, it is recommended to use different sets of organisms depending on the available computational resources and data, as well as the type of interactions of interest.

  8. DEVELOPMENT OF INTERACTIVE E-BOOK BASED ON CHEMICAL REPRESENTATION REFER TO CURRICULUM 2013

    Directory of Open Access Journals (Sweden)

    L. Tania

    2015-11-01

    Full Text Available This research aimed to develop an interactive e-book based representations of chemistry; describes the characteristics of the interactive e-book developed; the teachers responses in content suitability with curriculum and graphics aspects; and student responses in readibility aspects. The method used was research and development. The characteristics of interactive e-book: it was developed referring to the core competencies (KI and basic competence (KD in the curriculum 2013, allowed active interaction between students and e-book, completed with pictures, animations or videos in three levels of the chemical representation. Teachers’ responses to the content suitability and graphic aspects were very good with the percentage of each 98.46% and 97.5%. The students’ responses in readibility aspects was very good with percentage of 88.5%.

  9. Semihard interactions in nuclear collisions based on a unified approach to high energy scattering

    International Nuclear Information System (INIS)

    Drescher, H.J.; Hladik, M.; Werner, K.; Ostapchenko, S.; Centre National de la Recherche Scientifique, 44 - Nantes

    1998-01-01

    Our ultimate goal is the construction of a model for interactions of two nuclei in the energy range between several tens of GeV up to several TeV per nucleon in the centre-of-mass system. Such nuclear collisions are very complex, being composed of many components, and therefore some strategy is needed to construct a reliable model. The central point of our approach is the hypothesis, that the behavior of high energy interactions is universal (universality hypothesis). A model for nuclear interactions in a modular fashion is proposed. The individual modules, based on the universality hypothesis, are identified as building blocks for more elementary interactions (like e + e - , lepton-proton), and can therefore be studied in a much simpler context. With these building blocks under control, a quite reliable model is developed for nucleus-nucleus scattering, providing in particular very useful tests for the complicated numerical procedures using Monte Carlo techniques. (author)

  10. A Framework for Building an Interactive Satellite TV Based M-Learning Environment

    Directory of Open Access Journals (Sweden)

    Ghassan Issa

    2010-07-01

    Full Text Available This paper presents a description of an interactive satellite TV based mobile learning (STV-ML framework, in which a satellite TV station is used as an integral part of a comprehensive interactive mobile learning (M-Learning environment. The proposed framework assists in building a reliable, efficient, and cost-effective environment to meet the growing demands of M-Learning all over the world, especially in developing countries. It utilizes recent advances in satellite reception, broadcasting technologies, and interactive TV to facilitate the delivery of gigantic learning materials. This paper also proposed a simple and flexible three-phase implementation methodology which includes construction of earth station, expansion of broadcasting channels, and developing true user interactivity. The proposed framework and implementation methodology ensure the construction of a true, reliable, and cost effective M-Learning system that can be used efficiently and effectively by a wide range of users and educational institutions to deliver ubiquitous learning.

  11. Improving Vision-Based Motor Rehabilitation Interactive Systems for Users with Disabilities Using Mirror Feedback

    Science.gov (United States)

    Martínez-Bueso, Pau; Moyà-Alcover, Biel

    2014-01-01

    Observation is recommended in motor rehabilitation. For this reason, the aim of this study was to experimentally test the feasibility and benefit of including mirror feedback in vision-based rehabilitation systems: we projected the user on the screen. We conducted a user study by using a previously evaluated system that improved the balance and postural control of adults with cerebral palsy. We used a within-subjects design with the two defined feedback conditions (mirror and no-mirror) with two different groups of users (8 with disabilities and 32 without disabilities) using usability measures (time-to-start (T s) and time-to-complete (T c)). A two-tailed paired samples t-test confirmed that in case of disabilities the mirror feedback facilitated the interaction in vision-based systems for rehabilitation. The measured times were significantly worse in the absence of the user's own visual feedback (T s = 7.09 (P < 0.001) and T c = 4.48 (P < 0.005)). In vision-based interaction systems, the input device is the user's own body; therefore, it makes sense that feedback should be related to the body of the user. In case of disabilities the mirror feedback mechanisms facilitated the interaction in vision-based systems for rehabilitation. Results recommends developers and researchers use this improvement in vision-based motor rehabilitation interactive systems. PMID:25295310

  12. Physics-based scoring of protein-ligand interactions: explicit polarizability, quantum mechanics and free energies.

    Science.gov (United States)

    Bryce, Richard A

    2011-04-01

    The ability to accurately predict the interaction of a ligand with its receptor is a key limitation in computer-aided drug design approaches such as virtual screening and de novo design. In this article, we examine current strategies for a physics-based approach to scoring of protein-ligand affinity, as well as outlining recent developments in force fields and quantum chemical techniques. We also consider advances in the development and application of simulation-based free energy methods to study protein-ligand interactions. Fuelled by recent advances in computational algorithms and hardware, there is the opportunity for increased integration of physics-based scoring approaches at earlier stages in computationally guided drug discovery. Specifically, we envisage increased use of implicit solvent models and simulation-based scoring methods as tools for computing the affinities of large virtual ligand libraries. Approaches based on end point simulations and reference potentials allow the application of more advanced potential energy functions to prediction of protein-ligand binding affinities. Comprehensive evaluation of polarizable force fields and quantum mechanical (QM)/molecular mechanical and QM methods in scoring of protein-ligand interactions is required, particularly in their ability to address challenging targets such as metalloproteins and other proteins that make highly polar interactions. Finally, we anticipate increasingly quantitative free energy perturbation and thermodynamic integration methods that are practical for optimization of hits obtained from screened ligand libraries.

  13. Specular Andreev reflection in graphene-based superconducting junction with substate-induced spin orbit interaction

    International Nuclear Information System (INIS)

    Bai, Chunxu; Yang, Yanling

    2016-01-01

    Based on the Dirac–Bogoliubov–de Gennes equation, the chirality-resolved transport properties through a ballistic graphene-based superconducting heterojunction with both the Rashba and the Dresselhaus spin orbit interaction have been investigated. Our results show that, in contrast to the retro-Andreev reflection suppressed by the spin orbit interaction (SOI), the specular Andreev reflection (SAR) can be enhanced largely by the SOI. Moreover, the Fabry–Perot interferences in the barrier region lead to the oscillating feature of the tunneling conductance. It is anticipated to apply the qualitative different results to diagnose the SAR in single layer graphene in the presence of both kinds of the SOI. - Highlights: • The retro-Andreev reflection in graphene is suppressed by the spin orbit interaction. • The specular Andreev reflection in graphene can be enhanced largely by the spin orbit interaction. • The Fabry–Perot interferences in the graphene-based barrier lead to the oscillating feature of the tunneling conductance. • The spin orbit interaction is also vital in diagnosing the specular Andreev reflection in graphene.

  14. Specular Andreev reflection in graphene-based superconducting junction with substate-induced spin orbit interaction

    Energy Technology Data Exchange (ETDEWEB)

    Bai, Chunxu, E-mail: chunxu_bai@semi.ac.cn [School of Physics, Anyang Normal University, Anyang 455000 (China); Yang, Yanling [School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing 100083 (China); School of Physics, Anyang Normal University, Anyang 455000 (China)

    2016-08-26

    Based on the Dirac–Bogoliubov–de Gennes equation, the chirality-resolved transport properties through a ballistic graphene-based superconducting heterojunction with both the Rashba and the Dresselhaus spin orbit interaction have been investigated. Our results show that, in contrast to the retro-Andreev reflection suppressed by the spin orbit interaction (SOI), the specular Andreev reflection (SAR) can be enhanced largely by the SOI. Moreover, the Fabry–Perot interferences in the barrier region lead to the oscillating feature of the tunneling conductance. It is anticipated to apply the qualitative different results to diagnose the SAR in single layer graphene in the presence of both kinds of the SOI. - Highlights: • The retro-Andreev reflection in graphene is suppressed by the spin orbit interaction. • The specular Andreev reflection in graphene can be enhanced largely by the spin orbit interaction. • The Fabry–Perot interferences in the graphene-based barrier lead to the oscillating feature of the tunneling conductance. • The spin orbit interaction is also vital in diagnosing the specular Andreev reflection in graphene.

  15. Feasibility of an Exoskeleton-Based Interactive Video Game System for Upper Extremity Burn Contractures.

    Science.gov (United States)

    Schneider, Jeffrey C; Ozsecen, Muzaffer Y; Muraoka, Nicholas K; Mancinelli, Chiara; Della Croce, Ugo; Ryan, Colleen M; Bonato, Paolo

    2016-05-01

    Burn contractures are common and difficult to treat. Measuring continuous joint motion would inform the assessment of contracture interventions; however, it is not standard clinical practice. This study examines use of an interactive gaming system to measure continuous joint motion data. To assess the usability of an exoskeleton-based interactive gaming system in the rehabilitation of upper extremity burn contractures. Feasibility study. Eight subjects with a history of burn injury and upper extremity contractures were recruited from the outpatient clinic of a regional inpatient rehabilitation facility. Subjects used an exoskeleton-based interactive gaming system to play 4 different video games. Continuous joint motion data were collected at the shoulder and elbow during game play. Visual analog scale for engagement, difficulty and comfort. Angular range of motion by subject, joint, and game. The study population had an age of 43 ± 16 (mean ± standard deviation) years and total body surface area burned range of 10%-90%. Subjects reported satisfactory levels of enjoyment, comfort, and difficulty. Continuous joint motion data demonstrated variable characteristics by subject, plane of motion, and game. This study demonstrates the feasibility of use of an exoskeleton-based interactive gaming system in the burn population. Future studies are needed that examine the efficacy of tailoring interactive video games to the specific joint impairments of burn survivors. Copyright © 2016 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

  16. MetaMIS: a metagenomic microbial interaction simulator based on microbial community profiles.

    Science.gov (United States)

    Shaw, Grace Tzun-Wen; Pao, Yueh-Yang; Wang, Daryi

    2016-11-25

    The complexity and dynamics of microbial communities are major factors in the ecology of a system. With the NGS technique, metagenomics data provides a new way to explore microbial interactions. Lotka-Volterra models, which have been widely used to infer animal interactions in dynamic systems, have recently been applied to the analysis of metagenomic data. In this paper, we present the Lotka-Volterra model based tool, the Metagenomic Microbial Interacticon Simulator (MetaMIS), which is designed to analyze the time series data of microbial community profiles. MetaMIS first infers underlying microbial interactions from abundance tables for operational taxonomic units (OTUs) and then interprets interaction networks using the Lotka-Volterra model. We also embed a Bray-Curtis dissimilarity method in MetaMIS in order to evaluate the similarity to biological reality. MetaMIS is designed to tolerate a high level of missing data, and can estimate interaction information without the influence of rare microbes. For each interaction network, MetaMIS systematically examines interaction patterns (such as mutualism or competition) and refines the biotic role within microbes. As a case study, we collect a human male fecal microbiome and show that Micrococcaceae, a relatively low abundance OTU, is highly connected with 13 dominant OTUs and seems to play a critical role. MetaMIS is able to organize multiple interaction networks into a consensus network for comparative studies; thus we as a case study have also identified a consensus interaction network between female and male fecal microbiomes. MetaMIS provides an efficient and user-friendly platform that may reveal new insights into metagenomics data. MetaMIS is freely available at: https://sourceforge.net/projects/metamis/ .

  17. Group interaction in problem-based learning tutorials: a systematic review.

    Science.gov (United States)

    Azer, S A; Azer, D

    2015-11-01

    This review aimed at identifying studies on group interaction in problem-based learning (PBL) and elucidate methods used, factors affecting group interaction and the relationship between interaction and student's learning. PubMed, EMBASE, PsycINFO and HighWire were searched (January 1999 to June 2013) using a combination of pre-specified search terms. The search words were also used in searching nine journals in dental and medical education. Also edited research books on PBL were searched. Both qualitative and descriptive studies of group interaction were selected and critically appraised. Finally, 42 of 10,606 papers were included (35 journal articles and seven from research books). The materials used in assessing group interaction varied depending on the methodology design. Forty-three percent of the studies used video recording to evaluate group interaction. Other studies used indirect approaches such as focus groups, interviews and questionnaires. Factors affecting group interactions were students' and tutors' perceptions, tutor's subject-matter expertise, training students, tutor's group dynamics. There was no conclusive evidence about the impact of interaction in PBL on learning. Most studies were from medicine (64%), and 35 papers were published in the last 10 years. The majority of studies were conducted in Europe, North America and Asia. Although there is a progressive increase in publications on PBL group interaction during the last 10 years, there are knowledge gaps and deficiencies in this area and most studies are lacking solid theoretical basis and are descriptive. There is a deficiency in the literature in this area from dentistry and other allied health disciplines. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  18. Stress-Corrosion Interactions in Zr-Based Bulk Metallic Glasses

    Directory of Open Access Journals (Sweden)

    Petre Flaviu Gostin

    2015-07-01

    Full Text Available Stress-corrosion interactions in materials may lead to early unpredictable catastrophic failure of structural parts, which can have dramatic effects. In Zr-based bulk metallic glasses, such interactions are particularly important as these have very high yield strength, limited ductility, and are relatively susceptible to localized corrosion in halide-containing aqueous environments. Relevant features of the mechanical and corrosion behavior of Zr-based bulk metallic glasses are described, and an account of knowledge regarding corrosion-deformation interactions gathered from ex situ experimental procedures is provided. Subsequently the literature on key phenomena including hydrogen damage, stress corrosion cracking, and corrosion fatigue is reviewed. Critical factors for such phenomena will be highlighted. The review also presents an outlook for the topic.

  19. Using a dual safeguard web-based interactive teaching approach in an introductory physics class

    Directory of Open Access Journals (Sweden)

    Lie-Ming Li

    2015-03-01

    Full Text Available We modified the Just-in-Time Teaching approach and developed a dual safeguard web-based interactive (DGWI teaching system for an introductory physics course. The system consists of four instructional components that improve student learning by including warm-up assignments and online homework. Student and instructor activities involve activities both in the classroom and on a designated web site. An experimental study with control groups evaluated the effectiveness of the DGWI teaching method. The results indicate that the DGWI method is an effective way to improve students’ understanding of physics concepts, develop students’ problem-solving abilities through instructor-student interactions, and identify students’ misconceptions through a safeguard framework based on questions that satisfy teaching requirements and cover all of the course material. The empirical study and a follow-up survey found that the DGWI method increased student-teacher interaction and improved student learning outcomes.

  20. An interactive computer-based training aid for nuclear reactor refuelling operations

    International Nuclear Information System (INIS)

    Davey, E.C.; Anderson, L.L.; Simmons, W.S.

    1990-01-01

    An interactive computer-based training aid is being developed for operator training in emergency recognition and response to events involving loss of coolant during refuelling operations for the NRU research reactor. The training aid incorporates both conceptual and functional training components. Conceptual training consists of sequenced presentations of text, graphics and animations to explain the fueling system configuration, operations, abnormal events, and recovery procedures. Functional training consists of procedural practice with an interactive simulation of refueling operations presented on a multi-window display. This paper outlines the project objectives, discusses the approach taken to characterize the training material, describes key features of the training aid and relates our experience in coupling hypermedia and knowledge-based tools for the implementation of an interactive training simulation. (Author) 4 refs., 3 figs

  1. Conservation of Species- and Trait-Based Modeling Network Interactions in Extremely Acidic Microbial Community Assembly

    Directory of Open Access Journals (Sweden)

    Jialiang Kuang

    2017-08-01

    Full Text Available Understanding microbial interactions is essential to decipher the mechanisms of community assembly and their effects on ecosystem functioning, however, the conservation of species- and trait-based network interactions along environmental gradient remains largely unknown. Here, by using the network-based analyses with three paralleled data sets derived from 16S rRNA gene pyrosequencing, functional microarray, and predicted metagenome, we test our hypothesis that the network interactions of traits are more conserved than those of taxonomic measures, with significantly lower variation of network characteristics along the environmental gradient in acid mine drainage. The results showed that although the overall network characteristics remained similar, the structural variation was significantly lower at trait levels. The higher conserved individual node topological properties at trait level rather than at species level indicated that the responses of diverse traits remained relatively consistent even though different species played key roles under different environmental conditions. Additionally, the randomization tests revealed that it could not reject the null hypothesis that species-based correlations were random, while the tests suggested that correlation patterns of traits were non-random. Furthermore, relationships between trait-based network characteristics and environmental properties implied that trait-based networks might be more useful in reflecting the variation of ecosystem function. Taken together, our results suggest that deterministic trait-based community assembly results in greater conservation of network interaction, which may ensure ecosystem function across environmental regimes, emphasizing the potential importance of measuring the complexity and conservation of network interaction in evaluating the ecosystem stability and functioning.

  2. A Nonlinear Model for Gene-Based Gene-Environment Interaction

    Directory of Open Access Journals (Sweden)

    Jian Sa

    2016-06-01

    Full Text Available A vast amount of literature has confirmed the role of gene-environment (G×E interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction.

  3. Guidelines for Interactive Reliability-Based Structural Optimization using Quasi-Newton Algorithms

    DEFF Research Database (Denmark)

    Pedersen, C.; Thoft-Christensen, Palle

    Guidelines for interactive reliability-based structural optimization problems are outlined in terms of modifications of standard quasi-Newton algorithms. The proposed modifications minimize the condition number of the approximate Hessian matrix in each iteration, restrict the relative and absolute...

  4. H∞ Current Damping Control of DFIG based Wind Farm for Sub-Synchronous Control Interaction Mitigation

    DEFF Research Database (Denmark)

    Wang, Yun; Wu, Qiuwei; Yang, Rong

    2018-01-01

    This paper proposes an H∞ damping controller for the doubly-fed induction generator (DFIG) based wind farm (WF) to mitigate sub-synchronous control interactions (SSCI) with series capacitor compensated lines. A multi-input multi-output (MIMO) uncertain state-space model is developed to reflect...

  5. Understanding Manual-Based Behavior Therapy: Some Theoretical Foundations of Parent-Child Interaction Therapy.

    Science.gov (United States)

    Greco, Laurie A.; Sorrell, John T.; McNeil, Cheryl B.

    2001-01-01

    Provides a model of understanding and evaluating manualized treatments by beginning with a review of the theory and data-driven principles upon which one treatment, Parent-Child Interaction Therapy (PCIT), is based. As a point of illustration, several principles of PCIT, such as reinforcement, punishment, and stimulus control, are highlighted, and…

  6. An Evaluation-Driven Design Approach to Develop Learning Environments Based on Full-Body Interaction

    Science.gov (United States)

    Malinverni, Laura; Schaper, Marie-Monique; Pares, Narcís

    2016-01-01

    The development of learning environments based on full-body interaction has become an increasingly important field of research in recent years. However, the design and evaluation strategies currently used present some significant limitations. Two major shortcomings are: the inadequate involvement of children in the design process and a lack of…

  7. Perceptions of the Effectiveness of System Dynamics-Based Interactive Learning Environments: An Empirical Study

    Science.gov (United States)

    Qudrat-Ullah, Hassan

    2010-01-01

    The use of simulations in general and of system dynamics simulation based interactive learning environments (SDILEs) in particular is well recognized as an effective way of improving users' decision making and learning in complex, dynamic tasks. However, the effectiveness of SDILEs in classrooms has rarely been evaluated. This article describes…

  8. INTERACTION BETWEEN ENTERPRISES AND UNIVERSITIES CIVIL AVIATION BASED TECHNOLOGIES OF DISTANCE EDUCATION

    Directory of Open Access Journals (Sweden)

    K. S. Ermakov

    2015-01-01

    Full Text Available Distance education based on modern information technology as a tool for interaction between universities and enterprises of civil aviation. The introduction of the learning process real needs of civil aviation, enabling an airline to use scientific potential of educational institutions for the successful implementation of scientific research aimed at solving urgent problems.

  9. An Investigation of Interactive, Dialogue-Based Instruction for Undergraduate Art History

    Science.gov (United States)

    Gioffre, Penelope

    2012-01-01

    This paper explores the feasibility and efficacy of incorporating an interactive, discussion-based instructional approach into an undergraduate art history survey course and investigates effects of the new pedagogic strategy on students' demonstrated comprehension and retention of required content. The action research project follows a systematic…

  10. Ground-based remote sensing scheme for monitoring aerosol-cloud interactions

    NARCIS (Netherlands)

    Sarna, K.; Russchenberg, H.W.J.

    2016-01-01

    A new method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of the change of the cloud droplet size due to the change in the aerosol concentration. We use high-resolution

  11. Ground-based remote sensing scheme for monitoring aerosol–cloud interactions (discussion)

    NARCIS (Netherlands)

    Sarna, K.; Russchenberg, H.W.J.

    2015-01-01

    A method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of cloud microphysical changes due to the changing aerosol concentration. We use high resolution measurements from

  12. Development of NutriSportEx TM -interactive sport nutrition based ...

    African Journals Online (AJOL)

    Development of NutriSportExTM-interactive sport nutrition based mobile application software. B.S. Pushpa, N.S. Safii, S.H. Hamzah, N Fauzi, W.K. Yeo, P.B. Koon, C.Y. Tsin, M.I. Mohamad, A.H.A. Rahman, C.L. Ming, R.A. Talib, M.R. Shahril ...

  13. Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection

    Directory of Open Access Journals (Sweden)

    Yifei Chen

    2015-01-01

    Full Text Available Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the F1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification.

  14. Interaction in the Internet-Based Distance Learning Researches: Results of a Trend Analysis

    Science.gov (United States)

    Karatas, Sercin

    2008-01-01

    In this research, the articles concerning interaction in the Internet-based distance learning, which were published in three most outstanding journals in 2003, 2004 and until March of 2005, have been examined and classified. The research provides opportunities for discussing topics, methods and some other variables. It is thought that, the…

  15. Memory-Aware Query Routing in Interactive Web-based Information Systems

    NARCIS (Netherlands)

    F. Waas; M.L. Kersten (Martin)

    2001-01-01

    textabstractQuery throughput is one of the primary optimization goals in interactive web-based information systems in order to achieve the performance necessary to serve large user communities. Queries in this application domain differ significantly from those in traditional database applications:

  16. A new bell-shaped function for idiotypic interactions based on cross-linking

    NARCIS (Netherlands)

    Boer, R.J. de; Boerlijst, M.C.; Sulzer, B.; Perelson, A.S.

    1996-01-01

    Most recent models of the immune network are based upon a phenomenological log bell-shaped interaction function. This function depends on a single parameter, the "field," which is the sum of all ligand concentrations weighted by their respective affinities. The typical behavior of these models is

  17. Personality Types and Learners' Interaction in Web-Based Threaded Discussion

    Science.gov (United States)

    Lee, JeongMin; Lee, Youngmin

    2006-01-01

    This study examined the effects of group composition based on the learners' personality types as measured by the Myers-Briggs type indicator as they interacted in threaded discussions. Three groups comprised introverts, extroverts, and mixed introvert-extrovert classifications. Ninety-six participants were divided into 24 groups of 4 participants…

  18. High-throughput and multiplexed regeneration buffer scouting for affinity-based interactions

    NARCIS (Netherlands)

    Geuijen, Karin P.M.; Schasfoort, Richardus B.M.; Wijffels, Rene H.; Eppink, Michel H.M.

    2014-01-01

    Affinity-based analyses on biosensors depend partly on regeneration between measurements. Regeneration is performed with a buffer that efficiently breaks all interactions between ligand and analyte while maintaining the active binding site of the ligand. We demonstrated a regeneration buffer

  19. Studying Children’s friendship activities ethically using the Interaction Based Observation Method

    DEFF Research Database (Denmark)

    Sørensen, Hanne Værum

    2018-01-01

    The aim of this chapter is to acknowledge the influence that the interaction based observation method developed by Mariane Hedegaard has had on my studies of young children’s friendship activities. Hedegaard has problematized how existing methods of evaluating children’s development were inadequate...

  20. On the Transparency of Client/Server-Based Haptic Interaction with Deformable Objects.

    Science.gov (United States)

    Schuwerk, Clemens; Xu, Xiao; Steinbach, Eckehard

    2017-01-01

    This paper studies the transparency of client/server-based haptic interaction with simulated deformable objects. In the considered remote interaction scenario, the server simulates the computationally expensive finite-element-based object deformation at a low temporal update rate and transmits the result to the clients. There, the received deformation data is applied to the polygon mesh, which is used to locally render force feedback with a penalty-based force rendering algorithm at the required high rate. Based on a one-dimensional deformable object example, we analyze the transparency of this multi-rate architecture for a two-user interaction. Communication delay leads to increased force magnitudes and an increased impedance displayed to the clients that actively interact with the object. We propose a method that adjusts the stiffness used in the local force rendering at the clients to compensate for this effect. The conducted objective and subjective evaluations show that the proposed method successfully compensates for the effect of communication delay in the tested delay range of up to 100 ms.

  1. Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection.

    Science.gov (United States)

    Chen, Yifei; Sun, Yuxing; Han, Bing-Qing

    2015-01-01

    Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the F1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification.

  2. An Interactive Web-Based Program for Stepfamilies: Development and Evaluation of Efficacy

    Science.gov (United States)

    Gelatt, Vicky A.; Adler-Baeder, Francesca; Seeley, John R.

    2010-01-01

    This study evaluated the efficacy of a family life education program for stepfamilies that is self-administered, interactive, and web-based. The program uses behavior-modeling videos to demonstrate effective couple, parenting, and stepparenting practices. A diverse sample of 300 parents/stepparents of a child aged 11-15 years were randomized into…

  3. The TEACH Method: An Interactive Approach for Teaching the Needs-Based Theories Of Motivation

    Science.gov (United States)

    Moorer, Cleamon, Jr.

    2014-01-01

    This paper describes an interactive approach for explaining and teaching the Needs-Based Theories of Motivation. The acronym TEACH stands for Theory, Example, Application, Collaboration, and Having Discussion. This method can help business students to better understand and distinguish the implications of Maslow's Hierarchy of Needs,…

  4. Interactive Computer-Assisted Instruction in Acid-Base Physiology for Mobile Computer Platforms

    Science.gov (United States)

    Longmuir, Kenneth J.

    2014-01-01

    In this project, the traditional lecture hall presentation of acid-base physiology in the first-year medical school curriculum was replaced by interactive, computer-assisted instruction designed primarily for the iPad and other mobile computer platforms. Three learning modules were developed, each with ~20 screens of information, on the subjects…

  5. ClicO FS: an interactive web-based service of Circos.

    Science.gov (United States)

    Cheong, Wei-Hien; Tan, Yung-Chie; Yap, Soon-Joo; Ng, Kee-Peng

    2015-11-15

    : We present ClicO Free Service, an online web-service based on Circos, which provides a user-friendly, interactive web-based interface with configurable features to generate Circos circular plots. Online web-service is freely available at http://clicofs.codoncloud.com : soonjoo.yap@codongenomics.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

  6. MultiWaveLink: An interactive data base for the coordination of multiwavelength and multifacility observations

    Science.gov (United States)

    Cordova, F. A.

    1993-01-01

    MultiWaveLink is an interactive, computerized data base that was developed to facilitate a multi-wavelength approach to studying astrophysical sources. It can be used to access information about multiwavelenth resources (observers, telescopes, data bases and analysis facilities) or to organize observing campaigns that require either many telescopes operating in different spectral regimes or a network of similar telescopes circumspanning the Earth.

  7. Exposure to superfluous information reduces cooperation and increases antisocial punishment in reputation-based interactions

    Directory of Open Access Journals (Sweden)

    Miguel edos Santos

    2014-08-01

    Full Text Available Human cooperation is often based on reputation gained from previous interactions with third parties. Such reputation can be built on generous or punitive actions, and both, one’s own reputation and the reputation of others have been shown to influence decision making in experimental games that control for confounding variables. Here we test how reputation-based cooperation and punishment react to disruption of the cognitive processing in different kinds of helping games with observers. Saying a few superfluous words before each interaction was used to possibly interfere with working memory. In a first set of experiments, where reputation could only be based on generosity, the disruption reduced the frequency of cooperation and lowered mean final payoffs. In a second set of experiments where reputation could only be based on punishment, the disruption increased the frequency of antisocial punishment (i.e. of punishing those who helped and reduced the frequency of punishing defectors. Our findings suggest that working memory can easily be constraining in reputation-based interactions within experimental games, even if these games are based on a few simple rules with a visual display that provides all the information the subjects need to play the strategies predicted from current theory. Our findings also highlight a weakness of experimental games, namely that they can be very sensitive to environmental variation and that quantitative conclusions about antisocial punishment or other behavioral strategies can easily be misleading.

  8. RKKY interaction in P-N junction based on surface states of 3D topological insulator

    Science.gov (United States)

    Zhang, Shuhui; Yang, Wen; Chang, Kai

    The RKKY interaction mediated by conduction electrons supplies a mechanism to realize the long-range coupling of localized spins which is desired for the spin devices. Here, we examine the controllability of RKKY interaction in P-N junction (PNJ) based on surface states of 3D topological insulator (3DTI). In this study, through quantum way but not usual classical analogy to light propagation, the intuitive picture for electron waves across the interface of PNJ is obtained, e.g., Klein tunneling, negative refraction and focusing. Moreover, we perform the numerical calculations for all kinds of RKKY interaction including the Heisenberg, Ising, and Dzyaloshinskii-Moriya terms. We find the focusing of surface states leads to the local augmentation of RKKY interaction. Most importantly, a dimension transition occurs, i.e., the decay rate of RKKY interaction from the deserved 1/R 2 to 1/ R . In addition, the quadratic gate-dependence of RKKY interaction is also beneficial to the application of 3DTI PNJ in the fields of spintronics and quantum computation. This work was supported by the MOST (Grant No. 2015CB921503, and No. 2014CB848700) and NSFC (Grant No. 11434010, No. 11274036, No. 11322542, and No. 11504018).

  9. Sequence-based discrimination of protein-RNA interacting residues using a probabilistic approach.

    Science.gov (United States)

    Pai, Priyadarshini P; Dash, Tirtharaj; Mondal, Sukanta

    2017-04-07

    Protein interactions with ribonucleic acids (RNA) are well-known to be crucial for a wide range of cellular processes such as transcriptional regulation, protein synthesis or translation, and post-translational modifications. Identification of the RNA-interacting residues can provide insights into these processes and aid in relevant biotechnological manipulations. Owing to their eventual potential in combating diseases and industrial production, several computational attempts have been made over years using sequence- and structure-based information. Recent comparative studies suggest that despite these developments, many problems are faced with respect to the usability, prerequisites, and accessibility of various tools, thereby calling for an alternative approach and perspective supplementation in the prediction scenario. With this motivation, in this paper, we propose the use of a simple-yet-efficient conditional probabilistic approach based on the application of local occurrence of amino acids in the interacting region in a non-numeric sequence feature space, for discriminating between RNA interacting and non-interacting residues. The proposed method has been meticulously tested for robustness using a cross-estimation method showing MCC of 0.341 and F- measure of 66.84%. Upon exploring large scale applications using benchmark datasets available to date, this approach showed an encouraging performance comparable with the state-of-art. The software is available at https://github.com/ABCgrp/DORAEMON. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Investigating multiple dysregulated pathways in rheumatoid arthritis based on pathway interaction network.

    Science.gov (United States)

    Song, Xian-Dong; Song, Xian-Xu; Liu, Gui-Bo; Ren, Chun-Hui; Sun, Yuan-Bo; Liu, Ke-Xin; Liu, Bo; Liang, Shuang; Zhu, Zhu

    2018-03-01

    The traditional methods of identifying biomarkers in rheumatoid arthritis (RA) have focussed on the differentially expressed pathways or individual pathways, which however, neglect the interactions between pathways. To better understand the pathogenesis of RA, we aimed to identify dysregulated pathway sets using a pathway interaction network (PIN), which considered interactions among pathways. Firstly, RA-related gene expression profile data, protein-protein interactions (PPI) data and pathway data were taken up from the corresponding databases. Secondly, principal component analysis method was used to calculate the pathway activity of each of the pathway, and then a seed pathway was identified using data gleaned from the pathway activity. A PIN was then constructed based on the gene expression profile, pathway data, and PPI information. Finally, the dysregulated pathways were extracted from the PIN based on the seed pathway using the method of support vector machines and an area under the curve (AUC) index. The PIN comprised of a total of 854 pathways and 1064 pathway interactions. The greatest change in the activity score between RA and control samples was observed in the pathway of epigenetic regulation of gene expression, which was extracted and regarded as the seed pathway. Starting with this seed pathway, one maximum pathway set containing 10 dysregulated pathways was extracted from the PIN, having an AUC of 0.8249, and the result indicated that this pathway set could distinguish RA from the controls. These 10 dysregulated pathways might be potential biomarkers for RA diagnosis and treatment in the future.

  11. Agent-based paradigm for integration of interactive cable television operations and business support systems

    Science.gov (United States)

    Wattawa, Scott

    1995-11-01

    Offering interactive services and data in a hybrid fiber/coax cable system requires the coordination of a host of operations and business support systems. New service offerings and network growth and evolution create never-ending changes in the network infrastructure. Agent-based enterprise models provide a flexible mechanism for systems integration of service and support systems. Agent models also provide a mechanism to decouple interactive services from network architecture. By using the Java programming language, agents may be made safe, portable, and intelligent. This paper investigates the application of the Object Management Group's Common Object Request Brokering Architecture to the integration of a multiple services metropolitan area network.

  12. Novel Technology for Protein-Protein Interaction-based Targeted Drug Discovery

    Directory of Open Access Journals (Sweden)

    Jung Me Hwang

    2011-12-01

    Full Text Available We have developed a simple but highly efficient in-cell protein-protein interaction (PPI discovery system based on the translocation properties of protein kinase C- and its C1a domain in live cells. This system allows the visual detection of trimeric and dimeric protein interactions including cytosolic, nuclear, and/or membrane proteins with their cognate ligands. In addition, this system can be used to identify pharmacological small compounds that inhibit specific PPIs. These properties make this PPI system an attractive tool for screening drug candidates and mapping the protein interactome.

  13. From Image Tiles to Web-Based Interactive Measurements in One Stop.

    Science.gov (United States)

    Vandecreme, Antoine; Majurski, Michael; Chalfoun, Joe; Scott, Keana; Scott, John Henry J; Brady, Mary; Bajcsy, Peter

    2015-08-01

    This article introduces readers to a web-based solution useful for interactive nanoscale measurements of centimeter-sized specimens. This solution is a client-server system that promotes collaborative measurements and discovery. The system consists of multiple computational modules that enable uploading microscopy images, extracting metadata, assembling many nanometer-resolution images into an image covering a centimeter-sized area, and interactive viewing and measuring of objects of interest at multiple length scales over terabyte-sized images. We illustrate the use of the system on images of aerosolized nanoparticles and dye particles on printing paper.

  14. Impedance-Based Harmonic Instability Assessment in Multiple Electric Trains and Traction Network Interaction System

    DEFF Research Database (Denmark)

    Tao, Haidong; Hu, Haitao; Wang, Xiongfei

    2018-01-01

    interconnection of the two subsystems, i.e., an equivalent output impedance of the traction network and an equivalent input admittance of the multi-train. Then the harmonic instability is evaluated through a series of pole-zero diagrams drawn from the closed loop transfer matrix of the multi-train and traction......This paper presents an impedance-based method to systematically investigate the interaction between multi-train and traction networks, focusing on evaluating the harmonic instability problems. Firstly, the interaction mechanism of multi-train and the traction network is represented as a feedback...

  15. An Alternative Sorting Procedure for Interactive Group Decision Support Based on the Pseudo-criterion Concept

    Directory of Open Access Journals (Sweden)

    Andrej Bregar

    2003-08-01

    Full Text Available An original interactive procedure is proposed, which aims at overcoming some of the major weaknesses of existing pseudocriterion based methods for group decision analysis. It refers to absolute judgements of feasible alternatives and is focused on complementary activities of opinion elicitation and robustness analysis. As a foundation, four interdependent principles are introduced – problem localization, interactivity on the basis of progressiveness approach, semiautomatic derivation of criteria weights according to selective effects of veto thresholds, and group consensus seeking. The principles are grounded and realized by appropriate methodological solutions.

  16. Fuzzy preference based interactive fuzzy physical programming and its application in multi-objective optimization

    International Nuclear Information System (INIS)

    Zhang, Xu; Huang, Hong Zhong; Yu, Lanfeng

    2006-01-01

    Interactive Fuzzy Physical Programming (IFPP) developed in this paper is a new efficient multi-objective optimization method, which retains the advantages of physical programming while considering the fuzziness of the designer's preferences. The fuzzy preference function is introduced based on the model of linear physical programming, which is used to guide the search for improved solutions by interactive decision analysis. The example of multi-objective optimization design of the spindle of internal grinder demonstrates that the improved preference conforms to the subjective desires of the designer

  17. Ambient Light An integrative, LED based interaction concept for different levels of automation

    OpenAIRE

    Dziennus, Marc; Kelsch, Johann; Schieben, Anna

    2016-01-01

    In the present paper an innovative approach for the driver-automation interaction based on visual signals is presented. A 360° LED stripe which is installed in the interior of the car communicates to the driver via his peripheral vision (Ambient light). A consistent, color-coded interaction design in the peripheral field of vision is used to guide the driver’s attention and to support him in different level of automation by providing automation-related information. The HMI concept uses situat...

  18. Identification of Essential Proteins Based on a New Combination of Local Interaction Density and Protein Complexes.

    Directory of Open Access Journals (Sweden)

    Jiawei Luo

    Full Text Available Computational approaches aided by computer science have been used to predict essential proteins and are faster than expensive, time-consuming, laborious experimental approaches. However, the performance of such approaches is still poor, making practical applications of computational approaches difficult in some fields. Hence, the development of more suitable and efficient computing methods is necessary for identification of essential proteins.In this paper, we propose a new method for predicting essential proteins in a protein interaction network, local interaction density combined with protein complexes (LIDC, based on statistical analyses of essential proteins and protein complexes. First, we introduce a new local topological centrality, local interaction density (LID, of the yeast PPI network; second, we discuss a new integration strategy for multiple bioinformatics. The LIDC method was then developed through a combination of LID and protein complex information based on our new integration strategy. The purpose of LIDC is discovery of important features of essential proteins with their neighbors in real protein complexes, thereby improving the efficiency of identification.Experimental results based on three different PPI(protein-protein interaction networks of Saccharomyces cerevisiae and Escherichia coli showed that LIDC outperformed classical topological centrality measures and some recent combinational methods. Moreover, when predicting MIPS datasets, the better improvement of performance obtained by LIDC is over all nine reference methods (i.e., DC, BC, NC, LID, PeC, CoEWC, WDC, ION, and UC.LIDC is more effective for the prediction of essential proteins than other recently developed methods.

  19. Theoretical study on the interactions between methanol and imidazolium-based ionic liquids.

    Science.gov (United States)

    Zhu, Xueying; Sun, Hui; Zhang, Dongju; Liu, Chengbu

    2011-08-01

    To better understand the property of the binary systems composing of imidazolium salt, [emim](+)A- (A=Cl-, Br-, BF(4)-, and PF(6)-) and methanol, we have investigated in detail the interactions of methanol molecule with anions A-, cation [emim](+), and ion pair [emim](+)A- of several ionic liquids (ILs) based on 1-ethyl-3-methylimidazolium cation by performing density functional theory calculations. It is found that H-bonds are universally involved in these systems, which may play an important role for the miscibility of methanol with imidazolium-based ILs. The interaction mechanisms of methanol molecule with anion and cation are found to be different in nature: the former mainly involves LP(X)-[Formula: see text] interaction, while the latter relates with the decisive orbital overlap of the type of LP(O)-[Formula: see text]. Based on the present calculations, we have provided some reasonable interpretations for properties of the binary mixtures of ILs and alcohol and revealed valuable information for the interaction details between ILs and alcohols, which is expected to be useful for the design of more efficient ILs to form superior solvent system with alcohol.

  20. Sparse representation of higher-order functional interaction patterns in task-based FMRI data.

    Science.gov (United States)

    Zhang, Shu; Li, Xiang; Lv, Jinglei; Jiang, Xi; Zhu, Dajiang; Chen, Hanbo; Zhang, Tuo; Guo, Lei; Liu, Tianming

    2013-01-01

    Traditional task-based fMRI activation detection methods, e.g., the widely used general linear model (GLM), assume that the brain's hemodynamic responses follow the block-based or event-related stimulus paradigm. Typically, these activation detections are performed voxel-wise independently, and then are usually followed by statistical corrections. Despite remarkable successes and wide adoption of these methods, it remains largely unknown how functional brain regions interact with each other within specific networks during task performance blocks and in the baseline. In this paper, we present a novel algorithmic pipeline to statistically infer and sparsely represent higher-order functional interaction patterns within the working memory network during task performance and in the baseline. Specifically, a collection of higher-order interactions are inferred via the greedy equivalence search (GES) algorithm for both task and baseline blocks. In the next stage, an effective online dictionary learning algorithm is utilized for sparse representation of the inferred higher-order interaction patterns. Application of this framework on a working memory task-based fMRI data reveals interesting and meaningful distributions of the learned sparse dictionary atoms in task and baseline blocks. In comparison with traditional voxel-wise activation detection and recent pair-wise functional connectivity analysis, our framework offers a new methodology for representation and exploration of higher-order functional activities in the brain.

  1. Interactive Learning Environment: Web-based Virtual Hydrological Simulation System using Augmented and Immersive Reality

    Science.gov (United States)

    Demir, I.

    2014-12-01

    Recent developments in internet technologies make it possible to manage and visualize large data on the web. Novel visualization techniques and interactive user interfaces allow users to create realistic environments, and interact with data to gain insight from simulations and environmental observations. The hydrological simulation system is a web-based 3D interactive learning environment for teaching hydrological processes and concepts. The simulation systems provides a visually striking platform with realistic terrain information, and water simulation. Students can create or load predefined scenarios, control environmental parameters, and evaluate environmental mitigation alternatives. The web-based simulation system provides an environment for students to learn about the hydrological processes (e.g. flooding and flood damage), and effects of development and human activity in the floodplain. The system utilizes latest web technologies and graphics processing unit (GPU) for water simulation and object collisions on the terrain. Users can access the system in three visualization modes including virtual reality, augmented reality, and immersive reality using heads-up display. The system provides various scenarios customized to fit the age and education level of various users. This presentation provides an overview of the web-based flood simulation system, and demonstrates the capabilities of the system for various visualization and interaction modes.

  2. InterRNA: a database of base interactions in RNA structures.

    Science.gov (United States)

    Appasamy, Sri Devan; Hamdani, Hazrina Yusof; Ramlan, Effirul Ikhwan; Firdaus-Raih, Mohd

    2016-01-04

    A major component of RNA structure stabilization are the hydrogen bonded interactions between the base residues. The importance and biological relevance for large clusters of base interactions can be much more easily investigated when their occurrences have been systematically detected, catalogued and compared. In this paper, we describe the database InterRNA (INTERactions in RNA structures database-http://mfrlab.org/interrna/) that contains records of known RNA 3D motifs as well as records for clusters of bases that are interconnected by hydrogen bonds. The contents of the database were compiled from RNA structural annotations carried out by the NASSAM (http://mfrlab.org/grafss/nassam) and COGNAC (http://mfrlab.org/grafss/cognac) computer programs. An analysis of the database content and comparisons with the existing corpus of knowledge regarding RNA 3D motifs clearly show that InterRNA is able to provide an extension of the annotations for known motifs as well as able to provide novel interactions for further investigations. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  3. Highly Accurate Structure-Based Prediction of HIV-1 Coreceptor Usage Suggests Intermolecular Interactions Driving Tropism.

    Science.gov (United States)

    Kieslich, Chris A; Tamamis, Phanourios; Guzman, Yannis A; Onel, Melis; Floudas, Christodoulos A

    2016-01-01

    HIV-1 entry into host cells is mediated by interactions between the V3-loop of viral glycoprotein gp120 and chemokine receptor CCR5 or CXCR4, collectively known as HIV-1 coreceptors. Accurate genotypic prediction of coreceptor usage is of significant clinical interest and determination of the factors driving tropism has been the focus of extensive study. We have developed a method based on nonlinear support vector machines to elucidate the interacting residue pairs driving coreceptor usage and provide highly accurate coreceptor usage predictions. Our models utilize centroid-centroid interaction energies from computationally derived structures of the V3-loop:coreceptor complexes as primary features, while additional features based on established rules regarding V3-loop sequences are also investigated. We tested our method on 2455 V3-loop sequences of various lengths and subtypes, and produce a median area under the receiver operator curve of 0.977 based on 500 runs of 10-fold cross validation. Our study is the first to elucidate a small set of specific interacting residue pairs between the V3-loop and coreceptors capable of predicting coreceptor usage with high accuracy across major HIV-1 subtypes. The developed method has been implemented as a web tool named CRUSH, CoReceptor USage prediction for HIV-1, which is available at http://ares.tamu.edu/CRUSH/.

  4. Interactive CD based training on NDA instruments for facility operators and international inspectors

    International Nuclear Information System (INIS)

    Horley, E.C.; Smith, H.A.

    1996-01-01

    Interactive multimedia training is rapidly becoming a popular and highly effective medium for learning. An interactive CD based training module on the Active Well Coincidence counter is being developed for on-site training at nuclear facility, including foreign facilities. The training module incorporates interactive text, graphics and video that demonstrate the operating principles, and the use and set-up of the instrument. The user is in control of the pace of learning and of the directions taken to acquire information based on personal need. By being in control, the user stays highly motivated. A mix of visuals (text and graphics), audio clips (in different languages), and video (with audio) clips also keeps the interest level high. Skill reviews and evaluations can be incorporated into the training to provide feedback to the student. In addition, general background information is provided on gamma and neutron based MC and A measurements. This material serves as a condensed MC and A encyclopedia. By supplying an interactive CD with an NDA instrument, nuclear facilities will have greater assurance operators are properly trained in the set-up and operation of the NDA-equipment

  5. Towards a Semantics-based Framework for Meaning Construction in Constructivist Interactions

    DEFF Research Database (Denmark)

    Badie, Farshad

    2015-01-01

    learning was mediated by the construction of mental objects that he called schemas. From his point of view, schemas gradually develop into more conceptual mental entities. According to constructivism, a learner and a mentor, can – based on their preconceptions (concept pre-formations), based on their pre......-structured knowledge and based on their personal knowings – actively participate in an interaction with each other in order to construct personal knowledge. The most significant objective of constructivism is construction of personal knowledge and its development, and producing the own understanding of a world...... (universe of discourse) within the interaction. Therefore, the learner and mentor gain an opportunity to attain deeper personal understandings and comprehensions and greater motivations. The main contribution of the present research is the conceptual and logical analysis of meaning construction...

  6. Design and Implementation of an Interactive Web-Based Near Real-Time Forest Monitoring System.

    Directory of Open Access Journals (Sweden)

    Arun Kumar Pratihast

    Full Text Available This paper describes an interactive web-based near real-time (NRT forest monitoring system using four levels of geographic information services: 1 the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2 NRT forest disturbance detection based on satellite time-series, 3 presentation of forest disturbance data through a web-based application and social media and 4 interaction of the satellite based disturbance alerts with the end-user communities to enhance the collection of ground data. The system is developed using open source technologies and has been implemented together with local experts in the UNESCO Kafa Biosphere Reserve, Ethiopia. The results show that the system is able to provide easy access to information on forest change and considerably improves the collection and storage of ground observation by local experts. Social media leads to higher levels of user interaction and noticeably improves communication among stakeholders. Finally, an evaluation of the system confirms the usability of the system in Ethiopia. The implemented system can provide a foundation for an operational forest monitoring system at the national level for REDD+ MRV applications.

  7. Design and Implementation of an Interactive Web-Based Near Real-Time Forest Monitoring System.

    Science.gov (United States)

    Pratihast, Arun Kumar; DeVries, Ben; Avitabile, Valerio; de Bruin, Sytze; Herold, Martin; Bergsma, Aldo

    2016-01-01

    This paper describes an interactive web-based near real-time (NRT) forest monitoring system using four levels of geographic information services: 1) the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2) NRT forest disturbance detection based on satellite time-series, 3) presentation of forest disturbance data through a web-based application and social media and 4) interaction of the satellite based disturbance alerts with the end-user communities to enhance the collection of ground data. The system is developed using open source technologies and has been implemented together with local experts in the UNESCO Kafa Biosphere Reserve, Ethiopia. The results show that the system is able to provide easy access to information on forest change and considerably improves the collection and storage of ground observation by local experts. Social media leads to higher levels of user interaction and noticeably improves communication among stakeholders. Finally, an evaluation of the system confirms the usability of the system in Ethiopia. The implemented system can provide a foundation for an operational forest monitoring system at the national level for REDD+ MRV applications.

  8. Physically-Based Interactive Flow Visualization Based on Schlieren and Interferometry Experimental Techniques

    KAUST Repository

    Brownlee, C.

    2011-11-01

    Understanding fluid flow is a difficult problem and of increasing importance as computational fluid dynamics (CFD) produces an abundance of simulation data. Experimental flow analysis has employed techniques such as shadowgraph, interferometry, and schlieren imaging for centuries, which allow empirical observation of inhomogeneous flows. Shadowgraphs provide an intuitive way of looking at small changes in flow dynamics through caustic effects while schlieren cutoffs introduce an intensity gradation for observing large scale directional changes in the flow. Interferometry tracks changes in phase-shift resulting in bands appearing. The combination of these shading effects provides an informative global analysis of overall fluid flow. Computational solutions for these methods have proven too complex until recently due to the fundamental physical interaction of light refracting through the flow field. In this paper, we introduce a novel method to simulate the refraction of light to generate synthetic shadowgraph, schlieren and interferometry images of time-varying scalar fields derived from computational fluid dynamics data. Our method computes physically accurate schlieren and shadowgraph images at interactive rates by utilizing a combination of GPGPU programming, acceleration methods, and data-dependent probabilistic schlieren cutoffs. Applications of our method to multifield data and custom application-dependent color filter creation are explored. Results comparing this method to previous schlieren approximations are finally presented. © 2011 IEEE.

  9. [Case-based interactive PACS learning: introduction of a new concept for radiological education of students].

    Science.gov (United States)

    Scherer, A; Kröpil, P; Heusch, P; Buchbender, C; Sewerin, P; Blondin, D; Lanzman, R S; Miese, F; Ostendorf, B; Bölke, E; Mödder, U; Antoch, G

    2011-11-01

    Medical curricula are currently being reformed in order to establish superordinated learning objectives, including, e.g., diagnostic, therapeutic and preventive competences. This requires a shifting from traditional teaching methods towards interactive and case-based teaching concepts. Conceptions, initial experiences and student evaluations of a novel radiological course Co-operative Learning In Clinical Radiology (CLICR) are presented in this article. A novel radiological teaching course (CLICR course), which combines different innovative teaching elements, was established and integrated into the medical curriculum. Radiological case vignettes were created for three clinical teaching modules. By using a PC with PACS (Picture Archiving and Communication System) access, web-based databases and the CASUS platform, a problem-oriented, case-based and independent way of learning was supported as an adjunct to the well established radiological courses and lectures. Student evaluations of the novel CLICR course and the radiological block course were compared. Student evaluations of the novel CLICR course were significantly better compared to the conventional radiological block course. Of the participating students 52% gave the highest rating for the novel CLICR course concerning the endpoint overall satisfaction as compared to 3% of students for the conventional block course. The innovative interactive concept of the course and the opportunity to use a web-based database were favorably accepted by the students. Of the students 95% rated the novel course concept as a substantial gain for the medical curriculum and 95% also commented that interactive working with the PACS and a web-based database (82%) promoted learning and understanding. Interactive, case-based teaching concepts such as the presented CLICR course are considered by both students and teachers as useful extensions to the radiological course program. These concepts fit well into competence-oriented curricula.

  10. Open-Ended Interaction in Cooperative Pro-to-typing: A Video-based Analysis

    DEFF Research Database (Denmark)

    Bødker, Susanne; Grønbæk, Kaj; Trigg, Randal

    1991-01-01

    that are tied concretely to some current version of the prototype. On the other hand, the users learn more about the potential for change in their work practice, whether computer-based or otherwise. This paper presents the results of a field study of the cooperative prototyping process. The study is based...... on a fine-grained video-based analysis of a single prototyping session, and focuses on the effects of an open-ended style of interaction between users and designers around a prototype. An analysis of focus shifts, initiative and storytelling during the session is brought to bear on the question of whether...

  11. Research on distribution equipment training system based on holographic projection interactive simulation technology

    Science.gov (United States)

    Ma, Meng-Chao; Zhang, Yan; Li, Guang-Lei; Gao, Nan-Nan; Huang, Jin-Xin; Ma, Zhi-Guang; Shang, Ling-Ling; Guo, Liang-Feng

    2017-11-01

    This paper presents a three-dimensional (3D) interactive simulation training system based on holographic projection technology, nano-touch technology and interactive training mode, which realize the 3D display without stereoscopic glasses and touch type human computer interaction. 4 sets of holographic training courseware and 2 sets of fault presentation courseware was developed. Every courseware includes four parts: the cognition mode, the operation mode, the disassembling mode and daily maintenance mode. The system can carry out the training course of distribution automation equipment structure, disassembling and assembling, daily maintenance, operation, and the fault handling. A new training mode of power equipment training was created, which opened a new era of power equipment training.

  12. Towards for Analyzing Alternatives of Interaction Design Based on Verbal Decision Analysis of User Experience

    Directory of Open Access Journals (Sweden)

    Marília Soares Mendes

    2010-04-01

    Full Text Available In domains (as digital TV, smart home, and tangible interfaces that represent a new paradigm of interactivity, the decision of the most appropriate interaction design solution is a challenge. HCI researchers have promoted in their works the validation of design alternative solutions with users before producing the final solution. User experience with technology is a subject that has also gained ground in these works in order to analyze the appropriate solution(s. Following this concept, a study was accomplished under the objective of finding a better interaction solution for an application of mobile TV. Three executable applications of mobile TV prototypes were built. A Verbal Decision Analysis model was applied on the investigations for the favorite characteristics in each prototype based on the user’s experience and their intentions of use. This model led a performance of a qualitative analysis which objectified the design of a new prototype.

  13. Our Strength in Families (OSIDF): A Web-Based Interactive Coping Skills and Resiliency Program for Military Families

    National Research Council Canada - National Science Library

    Chiauzzi, Emil

    2006-01-01

    The project builds on existing interventions and available knowledge on family functioning to develop an interactive, Web- based relationship-enhancement intervention for military couples experiencing deployments...

  14. A domain-based approach to predict protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Resat Haluk

    2007-06-01

    Full Text Available Abstract Background Knowing which proteins exist in a certain organism or cell type and how these proteins interact with each other are necessary for the understanding of biological processes at the whole cell level. The determination of the protein-protein interaction (PPI networks has been the subject of extensive research. Despite the development of reasonably successful methods, serious technical difficulties still exist. In this paper we present DomainGA, a quantitative computational approach that uses the information about the domain-domain interactions to predict the interactions between proteins. Results DomainGA is a multi-parameter optimization method in which the available PPI information is used to derive a quantitative scoring scheme for the domain-domain pairs. Obtained domain interaction scores are then used to predict whether a pair of proteins interacts. Using the yeast PPI data and a series of tests, we show the robustness and insensitivity of the DomainGA method to the selection of the parameter sets, score ranges, and detection rules. Our DomainGA method achieves very high explanation ratios for the positive and negative PPIs in yeast. Based on our cross-verification tests on human PPIs, comparison of the optimized scores with the structurally observed domain interactions obtained from the iPFAM database, and sensitivity and specificity analysis; we conclude that our DomainGA method shows great promise to be applicable across multiple organisms. Conclusion We envision the DomainGA as a first step of a multiple tier approach to constructing organism specific PPIs. As it is based on fundamental structural information, the DomainGA approach can be used to create potential PPIs and the accuracy of the constructed interaction template can be further improved using complementary methods. Explanation ratios obtained in the reported test case studies clearly show that the false prediction rates of the template networks constructed

  15. Multiple Attribute Decision-Making Methods Based on Normal Intuitionistic Fuzzy Interaction Aggregation Operators

    Directory of Open Access Journals (Sweden)

    Peide Liu

    2017-11-01

    Full Text Available Normal intuitionistic fuzzy numbers (NIFNs, which combine the normal fuzzy number (NFN with intuitionistic number, can easily express the stochastic fuzzy information existing in real decision making, and power-average (PA operator can consider the relationships of different attributes by assigned weighting vectors which depend upon the input arguments. In this paper, we extended PA operator to process the NIFNs. Firstly, we defined some basic operational rules of NIFNs by considering the interaction operations of intuitionistic fuzzy sets (IFSs, established the distance between two NIFNs, and introduced the comparison method of NIFNs. Then, we proposed some new aggregation operators, including normal intuitionistic fuzzy weighted interaction averaging (NIFWIA operator, normal intuitionistic fuzzy power interaction averaging (NIFPIA operator, normal intuitionistic fuzzy weighted power interaction averaging (NIFWPIA operator, normal intuitionistic fuzzy generalized power interaction averaging (NIFGPIA operator, and normal intuitionistic fuzzy generalized weighted power interaction averaging (NIFGWPIA operator, and studied some properties and some special cases of them. Based on these operators, we developed a decision approach for multiple attribute decision-making (MADM problems with NIFNs. The significant characteristics of the proposed method are that: (1 it is easier to describe the uncertain information than the existing fuzzy sets and stochastic variables; (2 it used the interaction operations in part of IFSs which could overcome the existing weaknesses in operational rules of NIFNs; (3 it adopted PA operator which could relieve the influence of unreasonable data given by biased decision makers; and (4 it made the decision-making results more flexible and reliable because it was with generalized parameter which could be regard as the risk attitude value of decision makers. Finally, an illustrative example is given to verify its feasibility

  16. A comparative study of SMILES-based compound similarity functions for drug-target interaction prediction.

    Science.gov (United States)

    Öztürk, Hakime; Ozkirimli, Elif; Özgür, Arzucan

    2016-03-18

    Molecular structures can be represented as strings of special characters using SMILES. Since each molecule is represented as a string, the similarity between compounds can be computed using SMILES-based string similarity functions. Most previous studies on drug-target interaction prediction use 2D-based compound similarity kernels such as SIMCOMP. To the best of our knowledge, using SMILES-based similarity functions, which are computationally more efficient than the 2D-based kernels, has not been investigated for this task before. In this study, we adapt and evaluate various SMILES-based similarity methods for drug-target interaction prediction. In addition, inspired by the vector space model of Information Retrieval we propose cosine similarity based SMILES kernels that make use of the Term Frequency (TF) and Term Frequency-Inverse Document Frequency (TF-IDF) weighting approaches. We also investigate generating composite kernels by combining our best SMILES-based similarity functions with the SIMCOMP kernel. With this study, we provided a comparison of 13 different ligand similarity functions, each of which utilizes the SMILES string of molecule representation. Additionally, TF and TF-IDF based cosine similarity kernels are proposed. The more efficient SMILES-based similarity functions performed similarly to the more complex 2D-based SIMCOMP kernel in terms of AUC-ROC scores. The TF-IDF based cosine similarity obtained a better AUC-PR score than the SIMCOMP kernel on the GPCR benchmark data set. The composite kernel of TF-IDF based cosine similarity and SIMCOMP achieved the best AUC-PR scores for all data sets.

  17. FT-IR studies on interactions among components in hexanoyl chitosan-based polymer electrolytes

    Science.gov (United States)

    Winie, Tan; Arof, A. K.

    2006-03-01

    Fourier transform infrared (FT-IR) spectroscopic studies have been undertaken to investigate the interactions among components in a system of hexanoyl chitosan-lithium trifluoromethanesulfonate (LiCF 3SO 3)-diethyl carbonate (DEC)/ethylene carbonate (EC). LiCF 3SO 3 interacts with the hexanoyl chitosan to form a hexanoyl chitosan-salt complex that results in the shifting of the N(COR) 2, C dbnd O sbnd NHR and OCOR bands to lower wavenumbers. Interactions between EC and DEC with LiCF 3SO 3 has been noted and discussed. Evidence of interaction between EC and DEC has been obtained experimentally. Studies on polymer-plasticizer spectra suggested that there is no interaction between the polymer host and plasticizers. Competition between plasticizer and polymer on associating with Li + ions was observed from the spectral data for gel polymer electrolytes. The obtained spectroscopic data has been correlated with the conductivity performance of hexanoyl chitosan-based polymer electrolytes.

  18. Photo-physical and structural interactions between viologen phosphorus-based dendrimers and human serum albumin

    Energy Technology Data Exchange (ETDEWEB)

    Ciepluch, Karol, E-mail: ciepluch@biol.uni.lodz.pl [Department of General Biophysics, University of Lodz, 141/143 Pomorska St., 90-236 Lodz (Poland); Katir, Nadia [Laboratoire de Chimie de Coordination du CNRS (LCC), 205 route de Narbonne, F-31077 Toulouse cedex 4 (France); Institute of Nanomaterials and Nanotechnology (INANOTECH)-MAScIR (Moroccan Foundation for Advanced Science, Innovation and Research), ENSET, Avenue de l' Armee Royale, Madinat El Irfane, 10100 Rabat (Morocco); El Kadib, Abdelkrim [Institute of Nanomaterials and Nanotechnology (INANOTECH)-MAScIR (Moroccan Foundation for Advanced Science, Innovation and Research), ENSET, Avenue de l' Armee Royale, Madinat El Irfane, 10100 Rabat (Morocco); Weber, Monika [Department of General Biophysics, University of Lodz, 141/143 Pomorska St., 90-236 Lodz (Poland); Caminade, Anne-Marie [Laboratoire de Chimie de Coordination du CNRS (LCC), 205 route de Narbonne, F-31077 Toulouse cedex 4 (France); Bousmina, Mostapha [Hassan II Academy of Sciences and Technology, Avenue MVI, Km4, 10220 Rabat (Morocco); Pierre Majoral, Jean [Laboratoire de Chimie de Coordination du CNRS (LCC), 205 route de Narbonne, F-31077 Toulouse cedex 4 (France); Hassan II Academy of Sciences and Technology, Avenue MVI, Km4, 10220 Rabat (Morocco); Bryszewska, Maria [Department of General Biophysics, University of Lodz, 141/143 Pomorska St., 90-236 Lodz (Poland)

    2012-06-15

    This work deals with photo-physical and structural interactions between viologen phosphorus dendrimers and human serum albumin (HSA). Viologens are derivatives of 4,4 Prime -bipyridinium salts. Aiming to rationalize the parameters governing such interactions eight types of these polycationic dendrimers in which the generation, the number of charges, the nature of the core and of the terminal groups vary from one to another, were designed and used. The influence of viologen-based dendrimers' on human serum albumin has been investigated. The photo-physical interactions of the two systems have been monitored by fluorescence quenching of free L-tryptophan and of HSA tryptophan residue. Additionally, using circular dichroism (CD) the effect of dendrimers on the secondary structure of albumin was measured. The obtained results show that viologen dendrimers interact with human serum albumin quenching its fluorescence either by collisional (dynamic) way or by forming complexes in a ground state (static quenching). In some cases the quenching is accompanied by changes of the secondary structure of HSA. - Highlights: Black-Right-Pointing-Pointer Photo-physical interactions between viologen phosphorus dendrimers and human serum albumin (HSA) were investigated. Black-Right-Pointing-Pointer The viologen dendrimers can quench the fluorescence of tryptophan in HSA. Black-Right-Pointing-Pointer CD spectra to explain the changes in secondary structure of albumin after exposition of dendrimers.

  19. Regulation of catalytic behaviour of hydrolases through interactions with functionalized carbon-based nanomaterials

    Energy Technology Data Exchange (ETDEWEB)

    Pavlidis, Ioannis V. [University of Ioannina, Laboratory of Biotechnology, Department of Biological Applications and Technologies (Greece); Vorhaben, Torge [Institute of Biochemistry, Greifswald University, Department of Biotechnology and Enzyme Catalysis (Germany); Gournis, Dimitrios [University of Ioannina, Department of Materials Science and Engineering (Greece); Papadopoulos, George K. [Epirus Institute of Technology, Laboratory of Biochemistry and Biophysics, Faculty of Agricultural Technology (Greece); Bornscheuer, Uwe T. [Institute of Biochemistry, Greifswald University, Department of Biotechnology and Enzyme Catalysis (Germany); Stamatis, Haralambos, E-mail: hstamati@cc.uoi.gr [University of Ioannina, Laboratory of Biotechnology, Department of Biological Applications and Technologies (Greece)

    2012-05-15

    The interaction of enzymes with carbon-based nanomaterials (CBNs) is crucial for the function of biomolecules and therefore for the design and development of effective nanobiocatalytic systems. In this study, the effect of functionalized CBNs, such as graphene oxide (GO) and multi-wall carbon nanotubes (CNTs), on the catalytic behaviour of various hydrolases of biotechnological interest was monitored and the interactions between CBNs and proteins were investigated. The enzyme-nanomaterial interactions significantly affect the catalytic behaviour of enzymes, resulting in an increase up to 60 % of the catalytic efficiency of lipases and a decrease up to 30 % of the esterase. Moreover, the use of CNTs and GO derivatives, especially those that are amine-functionalized, led to increased thermal stability of most the hydrolases tested. Fluorescence and circular dichroism studies indicated that the altered catalytic behaviour of enzymes in the presence of CBNs arises from specific enzyme-nanomaterial interactions, which can lead to significant conformational changes. In the case of lipases, the conformational changes led to a more active and rigid structure, while in the case of esterases this led to destabilization and unfolding. Kinetic and spectroscopic studies indicated that the extent of the interactions between CBNs and hydrolases can be mainly controlled by the functionalization of nanomaterials than by their geometry.

  20. Commercial Motion Sensor Based Low-Cost and Convenient Interactive Treadmill

    Directory of Open Access Journals (Sweden)

    Jonghyun Kim

    2015-09-01

    Full Text Available Interactive treadmills were developed to improve the simulation of overground walking when compared to conventional treadmills. However, currently available interactive treadmills are expensive and inconvenient, which limits their use. We propose a low-cost and convenient version of the interactive treadmill that does not require expensive equipment and a complicated setup. As a substitute for high-cost sensors, such as motion capture systems, a low-cost motion sensor was used to recognize the subject’s intention for speed changing. Moreover, the sensor enables the subject to make a convenient and safe stop using gesture recognition. For further cost reduction, the novel interactive treadmill was based on an inexpensive treadmill platform and a novel high-level speed control scheme was applied to maximize performance for simulating overground walking. Pilot tests with ten healthy subjects were conducted and results demonstrated that the proposed treadmill achieves similar performance to a typical, costly, interactive treadmill that contains a motion capture system and an instrumented treadmill, while providing a convenient and safe method for stopping.

  1. Teacher-student interaction: The overlooked dimension of inquiry-based professional development

    Science.gov (United States)

    de Oliveira, Alandeom Wanderlei

    This study explores the teacher-student interactional dimension of inquiry-based science instruction. In it, microethnographic and grounded theory analyses are conducted in order to assess the impact of a professional development program designed to enhance in-service elementary teachers' interactional views (i.e., their understandings of inquiry-based social roles and relationships) and discursive practices (i.e., teachers' abilities to interact with student engaged in classroom inquiries) through a combination of expert instruction, immersion in scientific inquiry, and collaborative analysis of video-recorded classroom discourse. A sociolinguistic theoretical perspective on language use is adopted, viewing classroom discourse as comprising multiple linguistic signs (questions, responses, personal pronouns, hedges, backchannels, reactive tokens, directives, figures of speech, parallel repetitions) that convey not only semantic meanings (the literal information being exchanged) but also pragmatic meanings (information about teachers and students' social roles and relationships). A grounded theory analysis of the professional development activities uncovered a gradual shift in teachers' interactional views from a cognitive, monofunctional and decontextualized perspective to a social, multifunctional and contextualized conception of inquiry-based discourse. Furthermore, teachers developed increased levels of pragmatic awareness, being able to recognize the authoritative interactional functions served by discursive moves such as display questions, cued elicitation, convergent questioning, verbal cloze, affirmation, explicit evaluations of students' responses, verbatim repetitions, IRE triplets, IR couplets, second-person pronouns, "I/you" contrastive pairs, and direct or impolite directives. A comparative microethnographic analysis of teachers' classroom practices revealed that after participating in the program teachers demonstrated an improved ability to share

  2. Protein structure modelling and evaluation based on a 4-distance description of side-chain interactions

    Directory of Open Access Journals (Sweden)

    Inbar Yuval

    2010-07-01

    Full Text Available Abstract Background Accurate evaluation and modelling of residue-residue interactions within and between proteins is a key aspect of computational structure prediction including homology modelling, protein-protein docking, refinement of low-resolution structures, and computational protein design. Results Here we introduce a method for accurate protein structure modelling and evaluation based on a novel 4-distance description of residue-residue interaction geometry. Statistical 4-distance preferences were extracted from high-resolution protein structures and were used as a basis for a knowledge-based potential, called Hunter. We demonstrate that 4-distance description of side chain interactions can be used reliably to discriminate the native structure from a set of decoys. Hunter ranked the native structure as the top one in 217 out of 220 high-resolution decoy sets, in 25 out of 28 "Decoys 'R' Us" decoy sets and in 24 out of 27 high-resolution CASP7/8 decoy sets. The same concept was applied to side chain modelling in protein structures. On a set of very high-resolution protein structures the average RMSD was 1.47 Å for all residues and 0.73 Å for buried residues, which is in the range of attainable accuracy for a model. Finally, we show that Hunter performs as good or better than other top methods in homology modelling based on results from the CASP7 experiment. The supporting web site http://bioinfo.weizmann.ac.il/hunter/ was developed to enable the use of Hunter and for visualization and interactive exploration of 4-distance distributions. Conclusions Our results suggest that Hunter can be used as a tool for evaluation and for accurate modelling of residue-residue interactions in protein structures. The same methodology is applicable to other areas involving high-resolution modelling of biomolecules.

  3. Tolerance-based interaction: a new model targeting opinion formation and diffusion in social networks

    Directory of Open Access Journals (Sweden)

    Alexandru Topirceanu

    2016-01-01

    Full Text Available One of the main motivations behind social network analysis is the quest for understanding opinion formation and diffusion. Previous models have limitations, as they typically assume opinion interaction mechanisms based on thresholds which are either fixed or evolve according to a random process that is external to the social agent. Indeed, our empirical analysis on large real-world datasets such as Twitter, Meme Tracker, and Yelp, uncovers previously unaccounted for dynamic phenomena at population-level, namely the existence of distinct opinion formation phases and social balancing. We also reveal that a phase transition from an erratic behavior to social balancing can be triggered by network topology and by the ratio of opinion sources. Consequently, in order to build a model that properly accounts for these phenomena, we propose a new (individual-level opinion interaction model based on tolerance. As opposed to the existing opinion interaction models, the new tolerance model assumes that individual’s inner willingness to accept new opinions evolves over time according to basic human traits. Finally, by employing discrete event simulation on diverse social network topologies, we validate our opinion interaction model and show that, although the network size and opinion source ratio are important, the phase transition to social balancing is mainly fostered by the democratic structure of the small-world topology.

  4. Noncovalent interactions from electron density topology and solvent effects on spectral properties of Schiff bases

    Science.gov (United States)

    Gandhimathi, S.; Balakrishnan, C.; Theetharappan, M.; Neelakantan, M. A.; Venkataraman, R.

    2017-03-01

    Two Schiff bases were prepared by the condensation of o-allyl substituted 2,4-dihydroxy acetophenone with 1,2-diaminopropane (L1) and ethanediamine (L2) and characterized by elemental analysis, and ESI-MS, IR, UV-Vis, 1H and 13C NMR spectral techniques. The effect of solvents with respect to different polarities on UV-Vis and emission spectra of L1 and L2 was investigated at room temperature show that the compounds exist in keto and enol forms in solution and may be attributed to the intramolecular proton transfer in the ground state. The solute-solvent interactions, change in dipole moment and solvatochromic properties of the compounds were studied based on the solvent polarity parameters. For L1 and L2, the ground and excited state electronic structure calculations were carried out by DFT and TD-DFT at B3LYP/6-311G (d,p) level, respectively. The IR, NMR and electronic absorption spectra computed were compared with the experimental observations. The intramolecular charge transfer within the molecule is evidenced from the HOMO and LUMO energy levels and surface analysis. The noncovalent interactions like hydrogen bonding and van der Waals interactions were identified from the molecular geometry and electron localization function. These interactions in molecules have been studied by using reduced density gradient and graphed by Multiwfn.

  5. Pyrolysis mechanism of microalgae Nannochloropsis sp. based on model compounds and their interaction

    International Nuclear Information System (INIS)

    Wang, Xin; Tang, Xiaohan; Yang, Xiaoyi

    2017-01-01

    Highlights: • Pyrolysis experiments were conducted by model compounds of algal components. • Interaction affected little bio-crude yield of model compounds co-pyrolysis. • Some interaction pathways between microalgae components were recommended. • N-heterocyclic compounds were further pyrolysis products of Maillard reaction products. • Surfactant synthesis (lipid-amino acids and lipid-glucose) between algal components. - Abstract: Pyrolysis is one of important pathways to convert microalgae to liquid biofuels and key components of microalgae have different chemical composition and structure, which provides a barrier for large-scale microalgae-based liquid biofuel application. Microalgae component pyrolysis mechanism should be researched to optimal pyrolysis process parameters. In this study, single pyrolysis and co-pyrolysis of microalgal components (model compounds castor oil, soybean protein and glucose) were conducted to reveal interaction between them by thermogrametric analysis and bio-crude evaluation. Castor oil (model compound of lipid) has higher pyrolysis temperature than other model compounds and has the maximum contribution to bio-crude formation. Bio-crude from soybean protein has higher N-heterocyclic compounds as well as phenols, which could be important aromatic hydrocarbon source during biorefineries and alternative aviation biofuel production. Potential interaction pathways based on model compounds are recommended including further decomposition of Maillard reaction products (MRPs) and surfactant synthesis, which indicate that glucose played an important role on pyrolysis of microalgal protein and lipid components. The results should provide necessary information for microalgae pyrolysis process optimization and large-scale pyrolysis reactor design.

  6. A course-based cross-cultural interaction among pharmacy students in Qatar and Canada.

    Science.gov (United States)

    Wilby, Kyle John; Taylor, Jeff; Khalifa, Sherief I; Jorgenson, Derek

    2015-03-25

    To develop, implement, and evaluate a course-based, cross-cultural student interaction using real-time videoconferencing between universities in Canada and Qatar. A professional skills simulation practice session on smoking cessation was run for students in Qatar (n=22) and Canada (n=22). Students role played cases in small group situations and then interacted with colleagues from the other country regarding culturally challenging situations and communication strategies. Students were assessed on analytical content and communication skills through faculty member and peer evaluation. Cultural competency outcomes were assessed using a postsession survey. Overall, 92.3% of respondents agreed that learning was enhanced through the cross-cultural exchange, and 94.9% agreed that insight was gained into the health-related issues and needs of people from another culture. A course-based, cross-cultural interaction was an effective method to incorporate cultural competency principles into student learning. Future initiatives should increase direct student interaction and focus on culturally sensitive topics.

  7. Development and evaluation of near-isogenic lines for major blast resistance gene(s) in Basmati rice.

    Science.gov (United States)

    Khanna, Apurva; Sharma, Vinay; Ellur, Ranjith K; Shikari, Asif B; Gopala Krishnan, S; Singh, U D; Prakash, G; Sharma, T R; Rathour, Rajeev; Variar, Mukund; Prashanthi, S K; Nagarajan, M; Vinod, K K; Bhowmick, Prolay K; Singh, N K; Prabhu, K V; Singh, B D; Singh, Ashok K

    2015-07-01

    A set of NILs carrying major blast resistance genes in a Basmati rice variety has been developed. Also, the efficacy of pyramids over monogenic NILs against rice blast pathogen Magnaporthe oryzae has been demonstrated. Productivity and quality of Basmati rice is severely affected by rice blast disease. Major genes and QTLs conferring resistance to blast have been reported only in non-Basmati rice germplasm. Here, we report incorporation of seven blast resistance genes from the donor lines DHMASQ164-2a (Pi54, Pi1, Pita), IRBLz5-CA (Pi2), IRBLb-B (Pib), IRBL5-M (Pi5) and IRBL9-W (Pi9) into the genetic background of an elite Basmati rice variety Pusa Basmati 1 (PB1). A total of 36 near-isogenic lines (NILs) comprising of 14 monogenic, 16 two-gene pyramids and six three-gene pyramids were developed through marker-assisted backcross breeding (MABB). Foreground, recombinant and background selection was used to identify the plants with target gene(s), minimize the linkage drag and increase the recurrent parent genome (RPG) recovery (93.5-98.6 %), respectively, in the NILs. Comparative analysis performed using 50,051 SNPs and 500 SSR markers revealed that the SNPs provided better insight into the RPG recovery. Most of the monogenic NILs showed comparable performance in yield and quality, concomitantly, Pusa1637-18-7-6-20 (Pi9), was significantly superior in yield and stable across four different environments as compared to recurrent parent (RP) PB1. Further, among the pyramids, Pusa1930-12-6 (Pi2+Pi5) showed significantly higher yield and Pusa1633-7-8-53-6-8 (Pi54+Pi1+Pita) was superior in cooking quality as compared to RP PB1. The NILs carrying gene Pi9 were found to be the most effective against the concoction of virulent races predominant in the hotspot locations for blast disease. Conversely, when analyzed under artificial inoculation, three-gene pyramids expressed enhanced resistance as compared to the two-gene and monogenic NILs.

  8. Evaluation of an interactive, case-based review session in teaching medical microbiology

    Science.gov (United States)

    Blewett, Earl L; Kisamore, Jennifer L

    2009-01-01

    Background Oklahoma State University-Center for Health Sciences (OSU-CHS) has replaced its microbiology wet laboratory with a variety of tutorials including a case-based interactive session called Microbial Jeopardy!. The question remains whether the time spent by students and faculty in the interactive case-based tutorial is worthwhile? This study was designed to address this question by analyzing both student performance data and assessing students' perceptions regarding the tutorial. Methods Both quantitative and qualitative data were used in the current study. Part One of the study involved assessing student performance using archival records of seven case-based exam questions used in the 2004, 2005, 2006, and 2007 OSU-CHS Medical Microbiology course. Two sample t-tests for proportions were used to test for significant differences related to tutorial usage. Part Two used both quantitative and qualitative means to assess student's perceptions of the Microbial Jeopardy! session. First, a retrospective survey was administered to students who were enrolled in Medical Microbiology in 2006 or 2007. Second, responses to open-ended items from the 2008 course evaluations were reviewed for comments regarding the Microbial Jeopardy! session. Results Both student performance and student perception data support continued use of the tutorials. Quantitative and qualitative data converge to suggest that students like and learn from the interactive, case-based session. Conclusion The case-based tutorial appears to improve student performance on case-based exam questions. Additionally, students perceived the tutorial as helpful in preparing for exam questions and reviewing the course material. The time commitment for use of the case-based tutorial appears to be justified. PMID:19712473

  9. Evaluation of an interactive, case-based review session in teaching medical microbiology.

    Science.gov (United States)

    Blewett, Earl L; Kisamore, Jennifer L

    2009-08-27

    Oklahoma State University-Center for Health Sciences (OSU-CHS) has replaced its microbiology wet laboratory with a variety of tutorials including a case-based interactive session called Microbial Jeopardy!. The question remains whether the time spent by students and faculty in the interactive case-based tutorial is worthwhile? This study was designed to address this question by analyzing both student performance data and assessing students' perceptions regarding the tutorial. Both quantitative and qualitative data were used in the current study. Part One of the study involved assessing student performance using archival records of seven case-based exam questions used in the 2004, 2005, 2006, and 2007 OSU-CHS Medical Microbiology course. Two sample t-tests for proportions were used to test for significant differences related to tutorial usage. Part Two used both quantitative and qualitative means to assess student's perceptions of the Microbial Jeopardy! session. First, a retrospective survey was administered to students who were enrolled in Medical Microbiology in 2006 or 2007. Second, responses to open-ended items from the 2008 course evaluations were reviewed for comments regarding the Microbial Jeopardy! session. Both student performance and student perception data support continued use of the tutorials. Quantitative and qualitative data converge to suggest that students like and learn from the interactive, case-based session. The case-based tutorial appears to improve student performance on case-based exam questions. Additionally, students perceived the tutorial as helpful in preparing for exam questions and reviewing the course material. The time commitment for use of the case-based tutorial appears to be justified.

  10. The Institutional Embedding of Interactive Policy Making Insights From a Comparative Research Based on Eight Interactive Projects in the Netherlands

    NARCIS (Netherlands)

    Edelenbos, Jurian; Klok, Pieter J.; van Tatenhove, Jan

    2009-01-01

    In this article, the authors address citizen involvement at the central government level in the Netherlands. Through comparative research in which they systematically analyze eight interactive projects in three governmental departments, the authors especially pay attention to the relation between

  11. Petri Nets Based Modelling of Control Flow for Memory-Aid Interactive Programs in Telemedicine

    CERN Document Server

    Khoromskaia, V K

    2004-01-01

    Petri Nets (PN) based modelling of the control flow for the interactive memory assistance programs designed for personal pocket computers and having special requirements for robustness is considered. The proposed concept allows one to elaborate the programs which can give users a variety of possibilities for a day-time planning in the presence of environmental and time restrictions. First, a PN model for a known simple algorithm is constructed and analyzed using the corresponding state equations and incidence matrix. Then a PN graph for a complicated algorithm with overlapping actions and choice possibilities is designed, supplemented by an example of its analysis. Dynamic behaviour of this graph is tested by tracing of all possible paths of the flow of control using the PN simulator. It is shown that PN based modelling provides reliably predictable performance of interactive algorithms with branched structures and concurrency requirements.

  12. Development of interactive patient-based multimedia computer programs in veterinary orthopedic radiology

    International Nuclear Information System (INIS)

    Kraft, S.L.; Hoskinson, J.J.; Mussman, J.M.; Michaels, W.E.; Mclaughlin, R.; Gaughan, E.M.; Roush, J.K.

    1998-01-01

    Three computerized multimedia programs on large and small animal veterinary orthopedic radiology were developed and implemented for the radiology curriculum as an alternative to traditional film-based laboratory learning. Programs utilized ''hot words'' (colored text words that displayed an overlaid image label that highlighted lesions) and interactive quizzes which responded appropriately to selected answers. ''Hot words'' helped students develop confidence in accurate lesion detection and the interactive quizzes transformed learning from a passive to an active process. Multiple examples were provided for reinforcement and concepts were incorporated from other clinical disciplines for curriculum integration. Programs were written using a presentation software program, Toolbook for DOS based platform, and contained radiographic images made by laser-scanning digitization. Multiple students could simultaneously access the programs through a network server. These pilot programs were implemented successfully and computerized multimedia presentation proved to be well suited to teaching radiology. Development of the programs required attention to a number of hardware, software, time and cost factors

  13. Pigeon interaction mode switch-based UAV distributed flocking control under obstacle environments.

    Science.gov (United States)

    Qiu, Huaxin; Duan, Haibin

    2017-11-01

    Unmanned aerial vehicle (UAV) flocking control is a serious and challenging problem due to local interactions and changing environments. In this paper, a pigeon flocking model and a pigeon coordinated obstacle-avoiding model are proposed based on a behavior that pigeon flocks will switch between hierarchical and egalitarian interaction mode at different flight phases. Owning to the similarity between bird flocks and UAV swarms in essence, a distributed flocking control algorithm based on the proposed pigeon flocking and coordinated obstacle-avoiding models is designed to coordinate a heterogeneous UAV swarm to fly though obstacle environments with few informed individuals. The comparative simulation results are elaborated to show the feasibility, validity and superiority of our proposed algorithm. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  14. An examination of social interaction profiles based on the factors measured by the screen for social interaction.

    Science.gov (United States)

    Mahoney, Emery B; Breitborde, Nicholas J K; Leone, Sarah L; Ghuman, Jaswinder Kaur

    2014-10-01

    Deficits in the capacity to engage in social interactions are a core deficit associated with Autistic Disorder (AD) and Pervasive Developmental Disorder-Not Otherwise Specified (PDD-NOS). These deficits emerge at a young age, making screening for social interaction deficits and interventions targeted at improving capacity in this area important for early identification and intervention. Screening and early intervention efforts are particularly important given the poor short and long term outcomes for children with Autism Spectrum Disorders (ASDs) who experience social interaction deficits. The Screen for Social Interaction (SSI) is a well-validated screening measure that examines a child's capacity for social interaction using a developmental approach. The present study identified four underlying factors measured by the SSI, namely, Connection with Caregiver, Interaction/Imagination, Social Approach/Interest, and Agreeable Nature. The resulting factors were utilized to compare social interaction profiles across groups of children with AD, PDD-NOS, children with non-ASD developmental and/or psychiatric conditions and typically developing children. The results indicate that children with AD and those with PDD-NOS had similar social interaction profiles, but were able to be distinguished from typically developing children on every factor and were able to be distinguished from children with non-ASD psychiatric conditions on every factor except the Connection with Caregiver factor. In addition, children with non-ASD developmental and/or psychiatric conditions could be distinguished from typically developing children on the Connection with Caregiver factor and the Social Approach/Interest factor. These findings have implications for screening and intervention for children with ASDs and non-ASD psychiatric conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Synthesis and DNA interaction of a Sm(III) complex of a Schiff base ...

    African Journals Online (AJOL)

    The interaction between the Sm(III) complex of an ionic Schiff base [HL]-, derived from vanillin and L-tryptophan, and herring sperm DNA at physiological pH (7.40) has been studied by UV-Vis absorption, fluorescence and viscosity methods. The binding ratios nSm(III) : nK[HL] = 1:1 and nSm(III)L: nDNA =5:1 were confirmed ...

  16. Interaction Model of Mental Disability (IMMD) based on ICIDH

    OpenAIRE

    YAMANE, Hiroshi

    2001-01-01

    I propose an "Interaction Model of Mental Disability (IMMD)". Several models based on ICIDH are being proposed and tested around the world focusing on different aspects of disability. Though ICIDH is an inclusive model in health services, social security, insurance, education, and so on, the remarkable point of IMMD is to visualize the mutual relation of mental disability (impairment, disability and handicap) and other factors (environmental factors, personal factors). IMMD is a practical reh...

  17. A Closer Look at Tracking Human & Computer Interactions in Web-based Communications

    OpenAIRE

    May , Madeth; George , Sébastien; Prévôt , Patrick

    2008-01-01

    International audience; Keeping track of user's communication activities in Web-based environments has always been considered a complex task. It requires tracking systems that are capable of efficiently tracking users' activities and producing tracking data that can be useful to various users. The objectives of this paper are twofold: (i) to present an approach for better observing the different levels of Human & Computer Interactions during a Computer Mediated Communication activity, and (ii...

  18. Implications for Utilizing YouTube based Community Interactions for Destination Marketing

    OpenAIRE

    Sambhanthan, Arunasalam; Thelijjagoda, Samantha; Tan, Joseph

    2013-01-01

    In recent time, YouTube has evolved into a powerful medium for social interaction. Utilizing YouTube for enhancing marketing endeavors is a strategy practiced by marketing professionals across several industries. This paper rationalizes on the different ways and means of leveraging YouTube-based platforms for effective destination marketing by the hospitality industry (hotels). More specifically, the typology of virtual communities is adapted to evaluate the YouTube platform for effective des...

  19. A computational approach for the annotation of hydrogen-bonded base interactions in crystallographic structures of the ribozymes

    Science.gov (United States)

    Hamdani, Hazrina Yusof; Artymiuk, Peter J.; Firdaus-Raih, Mohd

    2015-09-01

    A fundamental understanding of the atomic level interactions in ribonucleic acid (RNA) and how they contribute towards RNA architecture is an important knowledge platform to develop through the discovery of motifs from simple arrangements base pairs, to more complex arrangements such as triples and larger patterns involving non-standard interactions. The network of hydrogen bond interactions is important in connecting bases to form potential tertiary motifs. Therefore, there is an urgent need for the development of automated methods for annotating RNA 3D structures based on hydrogen bond interactions. COnnection tables Graphs for Nucleic ACids (COGNAC) is automated annotation system using graph theoretical approaches that has been developed for the identification of RNA 3D motifs. This program searches for patterns in the unbroken networks of hydrogen bonds for RNA structures and capable of annotating base pairs and higher-order base interactions, which ranges from triples to sextuples. COGNAC was able to discover 22 out of 32 quadruples occurrences of the Haloarcula marismortui large ribosomal subunit (PDB ID: 1FFK) and two out of three occurrences of quintuple interaction reported by the non-canonical interactions in RNA (NCIR) database. These and several other interactions of interest will be discussed in this paper. These examples demonstrate that the COGNAC program can serve as an automated annotation system that can be used to annotate conserved base-base interactions and could be added as additional information to established RNA secondary structure prediction methods.

  20. A computational approach for the annotation of hydrogen-bonded base interactions in crystallographic structures of the ribozymes

    International Nuclear Information System (INIS)

    Hamdani, Hazrina Yusof; Artymiuk, Peter J.; Firdaus-Raih, Mohd

    2015-01-01

    A fundamental understanding of the atomic level interactions in ribonucleic acid (RNA) and how they contribute towards RNA architecture is an important knowledge platform to develop through the discovery of motifs from simple arrangements base pairs, to more complex arrangements such as triples and larger patterns involving non-standard interactions. The network of hydrogen bond interactions is important in connecting bases to form potential tertiary motifs. Therefore, there is an urgent need for the development of automated methods for annotating RNA 3D structures based on hydrogen bond interactions. COnnection tables Graphs for Nucleic ACids (COGNAC) is automated annotation system using graph theoretical approaches that has been developed for the identification of RNA 3D motifs. This program searches for patterns in the unbroken networks of hydrogen bonds for RNA structures and capable of annotating base pairs and higher-order base interactions, which ranges from triples to sextuples. COGNAC was able to discover 22 out of 32 quadruples occurrences of the Haloarcula marismortui large ribosomal subunit (PDB ID: 1FFK) and two out of three occurrences of quintuple interaction reported by the non-canonical interactions in RNA (NCIR) database. These and several other interactions of interest will be discussed in this paper. These examples demonstrate that the COGNAC program can serve as an automated annotation system that can be used to annotate conserved base-base interactions and could be added as additional information to established RNA secondary structure prediction methods

  1. A computational approach for the annotation of hydrogen-bonded base interactions in crystallographic structures of the ribozymes

    Energy Technology Data Exchange (ETDEWEB)

    Hamdani, Hazrina Yusof, E-mail: hazrina@mfrlab.org [School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi (Malaysia); Advanced Medical and Dental Institute, Universiti Sains Malaysia, Bertam, Kepala Batas (Malaysia); Artymiuk, Peter J., E-mail: p.artymiuk@sheffield.ac.uk [Dept. of Molecular Biology and Biotechnology, Firth Court, University of Sheffield, S10 T2N Sheffield (United Kingdom); Firdaus-Raih, Mohd, E-mail: firdaus@mfrlab.org [School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi (Malaysia)

    2015-09-25

    A fundamental understanding of the atomic level interactions in ribonucleic acid (RNA) and how they contribute towards RNA architecture is an important knowledge platform to develop through the discovery of motifs from simple arrangements base pairs, to more complex arrangements such as triples and larger patterns involving non-standard interactions. The network of hydrogen bond interactions is important in connecting bases to form potential tertiary motifs. Therefore, there is an urgent need for the development of automated methods for annotating RNA 3D structures based on hydrogen bond interactions. COnnection tables Graphs for Nucleic ACids (COGNAC) is automated annotation system using graph theoretical approaches that has been developed for the identification of RNA 3D motifs. This program searches for patterns in the unbroken networks of hydrogen bonds for RNA structures and capable of annotating base pairs and higher-order base interactions, which ranges from triples to sextuples. COGNAC was able to discover 22 out of 32 quadruples occurrences of the Haloarcula marismortui large ribosomal subunit (PDB ID: 1FFK) and two out of three occurrences of quintuple interaction reported by the non-canonical interactions in RNA (NCIR) database. These and several other interactions of interest will be discussed in this paper. These examples demonstrate that the COGNAC program can serve as an automated annotation system that can be used to annotate conserved base-base interactions and could be added as additional information to established RNA secondary structure prediction methods.

  2. Performance-based Reward Administration Enhancing Employees’ Feelings of Interactional Justice

    Directory of Open Access Journals (Sweden)

    Azman Ismail

    2017-04-01

    Full Text Available The transformation in international business landscape has changed organizational management especially reward administration. This is done in order to maintain the organization’s competitiveness in global market place. In the field of reward administration, an emerging trend can be observed whereby most organizations are moving toward the application of psychological elements in administering organizational reward system. The ultimate objective of this study is to investigate the association between performance-based reward administration and interactional justice. The proposed model was empirically tested using a sample of 113 employees from fire and rescue agency in Peninsular Malaysia. This study found an evidence that performance-based reward administration (i.e., communication, participation and performance appraisal is positively and significantly associated with interactional justice. This findings proves that the ability of administrators to appropriately implement communication openness, inspire participative decision-making and organize fairness performance appraisal in administering performance-based reward have significantly evoked the feeling of interactional justice when employees perceived that they are being fairly treated in the reward system.

  3. iHand: an interactive bare-hand-based augmented reality interface on commercial mobile phones

    Science.gov (United States)

    Choi, Junyeong; Park, Jungsik; Park, Hanhoon; Park, Jong-Il

    2013-02-01

    The performance of mobile phones has rapidly improved, and they are emerging as a powerful platform. In many vision-based applications, human hands play a key role in natural interaction. However, relatively little attention has been paid to the interaction between human hands and the mobile phone. Thus, we propose a vision- and hand gesture-based interface in which the user holds a mobile phone in one hand but sees the other hand's palm through a built-in camera. The virtual contents are faithfully rendered on the user's palm through palm pose estimation, and reaction with hand and finger movements is achieved that is recognized by hand shape recognition. Since the proposed interface is based on hand gestures familiar to humans and does not require any additional sensors or markers, the user can freely interact with virtual contents anytime and anywhere without any training. We demonstrate that the proposed interface works at over 15 fps on a commercial mobile phone with a 1.2-GHz dual core processor and 1 GB RAM.

  4. The Pathway Active Learning Environment: An interactive web-based tool for physics education

    Science.gov (United States)

    Nakamura, Christopher Matthew

    The work described here represents an effort to design, construct, and test an interactive online multimedia learning environment that can provide physics instruction to students in their homes. The system was designed with one-on-one human tutoring in mind as the mode of instruction. The system uses an original combination of a video-based tutor that incorporates natural language processing video-centered lessons and additional illustrative multimedia. Our Synthetic Interview (SI) tutor provides pre-recorded video answers from expert physics instructors in response to students' typed natural language questions. Our lessons cover Newton's laws and provide a context for the tutoring interaction to occur, connect physics ideas to real-world behavior of mechanical systems, and allow for quantitative testing of physics. Additional multimedia can be used to supplement the SI tutors' explanations and illustrate the physics of interest. The system is targeted at students of algebra-based and concept-based physics at the college and high school level. The system logs queries to the SI tutor, responses to lesson questions and several other interactions with the system, tagging those interactions with a username and timestamp. We have provided several groups of students with access to our system under several different conditions ranging from the controlled conditions of our interview facility to the naturalistic conditions of use at home. In total nearly two-hundred students have accessed the system. To gain insight into the ways students might use the system and understand the utility of its various components we analyzed qualitative interview data collected with 22 algebra-based physics students who worked with our system in our interview facility. We also performed a descriptive analysis of data from the system's log of user interactions. Finally we explored the use of machine learning to explore the possibility of using automated assessment to augment the interactive

  5. GIS-based interactive tool to map the advent of world conquerors

    Science.gov (United States)

    Lakkaraju, Mahesh

    The objective of this thesis is to show the scale and extent of some of the greatest empires the world has ever seen. This is a hybrid project between the GIS based interactive tool and the web-based JavaScript tool. This approach lets the students learn effectively about the emperors themselves while understanding how long and far their empires spread. In the GIS based tool, a map is displayed with various points on it, and when a user clicks on one point, the relevant information of what happened at that particular place is displayed. Apart from this information, users can also select the interactive animation button and can walk through a set of battles in chronological order. As mentioned, this uses Java as the main programming language, and MOJO (Map Objects Java Objects) provided by ESRI. MOJO is very effective as its GIS related features can be included in the application itself. This app. is a simple tool and has been developed for university or high school level students. D3.js is an interactive animation and visualization platform built on the Javascript framework. Though HTML5, CSS3, Javascript and SVG animations can be used to derive custom animations, this tool can help bring out results with less effort and more ease of use. Hence, it has become the most sought after visualization tool for multiple applications. D3.js has provided a map-based visualization feature so that we can easily display text-based data in a map-based interface. To draw the map and the points on it, D3.js uses data rendered in TOPO JSON format. The latitudes and longitudes can be provided, which are interpolated into the Map svg. One of the main advantages of doing it this way is that more information is retained when we use a visual medium.

  6. Interactive computer-assisted instruction in acid-base physiology for mobile computer platforms.

    Science.gov (United States)

    Longmuir, Kenneth J

    2014-03-01

    In this project, the traditional lecture hall presentation of acid-base physiology in the first-year medical school curriculum was replaced by interactive, computer-assisted instruction designed primarily for the iPad and other mobile computer platforms. Three learning modules were developed, each with ∼20 screens of information, on the subjects of the CO2-bicarbonate buffer system, other body buffer systems, and acid-base disorders. Five clinical case modules were also developed. For the learning modules, the interactive, active learning activities were primarily step-by-step learner control of explanations of complex physiological concepts, usually presented graphically. For the clinical cases, the active learning activities were primarily question-and-answer exercises that related clinical findings to the relevant basic science concepts. The student response was remarkably positive, with the interactive, active learning aspect of the instruction cited as the most important feature. Also, students cited the self-paced instruction, extensive use of interactive graphics, and side-by-side presentation of text and graphics as positive features. Most students reported that it took less time to study the subject matter with this online instruction compared with subject matter presented in the lecture hall. However, the approach to learning was highly examination driven, with most students delaying the study of the subject matter until a few days before the scheduled examination. Wider implementation of active learning computer-assisted instruction will require that instructors present subject matter interactively, that students fully embrace the responsibilities of independent learning, and that institutional administrations measure instructional effort by criteria other than scheduled hours of instruction.

  7. Source and listener directivity for interactive wave-based sound propagation.

    Science.gov (United States)

    Mehra, Ravish; Antani, Lakulish; Kim, Sujeong; Manocha, Dinesh

    2014-04-01

    We present an approach to model dynamic, data-driven source and listener directivity for interactive wave-based sound propagation in virtual environments and computer games. Our directional source representation is expressed as a linear combination of elementary spherical harmonic (SH) sources. In the preprocessing stage, we precompute and encode the propagated sound fields due to each SH source. At runtime, we perform the SH decomposition of the varying source directivity interactively and compute the total sound field at the listener position as a weighted sum of precomputed SH sound fields. We propose a novel plane-wave decomposition approach based on higher-order derivatives of the sound field that enables dynamic HRTF-based listener directivity at runtime. We provide a generic framework to incorporate our source and listener directivity in any offline or online frequency-domain wave-based sound propagation algorithm. We have integrated our sound propagation system in Valve's Source game engine and use it to demonstrate realistic acoustic effects such as sound amplification, diffraction low-passing, scattering, localization, externalization, and spatial sound, generated by wave-based propagation of directional sources and listener in complex scenarios. We also present results from our preliminary user study.

  8. Computational prediction of drug-drug interactions based on drugs functional similarities.

    Science.gov (United States)

    Ferdousi, Reza; Safdari, Reza; Omidi, Yadollah

    2017-06-01

    Therapeutic activities of drugs are often influenced by co-administration of drugs that may cause inevitable drug-drug interactions (DDIs) and inadvertent side effects. Prediction and identification of DDIs are extremely vital for the patient safety and success of treatment modalities. A number of computational methods have been employed for the prediction of DDIs based on drugs structures and/or functions. Here, we report on a computational method for DDIs prediction based on functional similarity of drugs. The model was set based on key biological elements including carriers, transporters, enzymes and targets (CTET). The model was applied for 2189 approved drugs. For each drug, all the associated CTETs were collected, and the corresponding binary vectors were constructed to determine the DDIs. Various similarity measures were conducted to detect DDIs. Of the examined similarity methods, the inner product-based similarity measures (IPSMs) were found to provide improved prediction values. Altogether, 2,394,766 potential drug pairs interactions were studied. The model was able to predict over 250,000 unknown potential DDIs. Upon our findings, we propose the current method as a robust, yet simple and fast, universal in silico approach for identification of DDIs. We envision that this proposed method can be used as a practical technique for the detection of possible DDIs based on the functional similarities of drugs. Copyright © 2017. Published by Elsevier Inc.

  9. Literature-Based Discovery of IFN-γ and Vaccine-Mediated Gene Interaction Networks

    Directory of Open Access Journals (Sweden)

    Arzucan Özgür

    2010-01-01

    Full Text Available Interferon-gamma (IFN-γ regulates various immune responses that are often critical for vaccine-induced protection. In order to annotate the IFN-γ-related gene interaction network from a large amount of IFN-γ research reported in the literature, a literature-based discovery approach was applied with a combination of natural language processing (NLP and network centrality analysis. The interaction network of human IFN-γ (Gene symbol: IFNG and its vaccine-specific subnetwork were automatically extracted using abstracts from all articles in PubMed. Four network centrality metrics were further calculated to rank the genes in the constructed networks. The resulting generic IFNG network contains 1060 genes and 26313 interactions among these genes. The vaccine-specific subnetwork contains 102 genes and 154 interactions. Fifty six genes such as TNF, NFKB1, IL2, IL6, and MAPK8 were ranked among the top 25 by at least one of the centrality methods in one or both networks. Gene enrichment analysis indicated that these genes were classified in various immune mechanisms such as response to extracellular stimulus, lymphocyte activation, and regulation of apoptosis. Literature evidence was manually curated for the IFN-γ relatedness of 56 genes and vaccine development relatedness for 52 genes. This study also generated many new hypotheses worth further experimental studies.

  10. CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling

    Science.gov (United States)

    Rose, B. E. J.

    2015-12-01

    Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The IPython notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields. However CLIMLAB is well suited to be deployed as a computational back-end for a graphical gaming environment based on earth-system modeling.

  11. NETAL: a new graph-based method for global alignment of protein-protein interaction networks.

    Science.gov (United States)

    Neyshabur, Behnam; Khadem, Ahmadreza; Hashemifar, Somaye; Arab, Seyed Shahriar

    2013-07-01

    The interactions among proteins and the resulting networks of such interactions have a central role in cell biology. Aligning these networks gives us important information, such as conserved complexes and evolutionary relationships. Although there have been several publications on the global alignment of protein networks; however, none of proposed methods are able to produce a highly conserved and meaningful alignment. Moreover, time complexity of current algorithms makes them impossible to use for multiple alignment of several large networks together. We present a novel algorithm for the global alignment of protein-protein interaction networks. It uses a greedy method, based on the alignment scoring matrix, which is derived from both biological and topological information of input networks to find the best global network alignment. NETAL outperforms other global alignment methods in terms of several measurements, such as Edge Correctness, Largest Common Connected Subgraphs and the number of common Gene Ontology terms between aligned proteins. As the running time of NETAL is much less than other available methods, NETAL can be easily expanded to multiple alignment algorithm. Furthermore, NETAL overpowers all other existing algorithms in term of performance so that the short running time of NETAL allowed us to implement it as the first server for global alignment of protein-protein interaction networks. Binaries supported on linux are freely available for download at http://www.bioinf.cs.ipm.ir/software/netal. Supplementary data are available at Bioinformatics online.

  12. Detection of time delays and directional interactions based on time series from complex dynamical systems

    Science.gov (United States)

    Ma, Huanfei; Leng, Siyang; Tao, Chenyang; Ying, Xiong; Kurths, Jürgen; Lai, Ying-Cheng; Lin, Wei

    2017-07-01

    Data-based and model-free accurate identification of intrinsic time delays and directional interactions is an extremely challenging problem in complex dynamical systems and their networks reconstruction. A model-free method with new scores is proposed to be generally capable of detecting single, multiple, and distributed time delays. The method is applicable not only to mutually interacting dynamical variables but also to self-interacting variables in a time-delayed feedback loop. Validation of the method is carried out using physical, biological, and ecological models and real data sets. Especially, applying the method to air pollution data and hospital admission records of cardiovascular diseases in Hong Kong reveals the major air pollutants as a cause of the diseases and, more importantly, it uncovers a hidden time delay (about 30-40 days) in the causal influence that previous studies failed to detect. The proposed method is expected to be universally applicable to ascertaining and quantifying subtle interactions (e.g., causation) in complex systems arising from a broad range of disciplines.

  13. Interactions of Aqueous Imidazolium-Based Ionic Liquid Mixtures with Solid-Supported Phospholipid Vesicles.

    Directory of Open Access Journals (Sweden)

    Patricia Losada-Pérez

    Full Text Available Despite the environmentally friendly reputation of ionic liquids (ILs, their safety has been recently questioned given their potential as cytotoxic agents. The fundamental mechanisms underlying the interactions between ILs and cells are less studied and by far not completely understood. Biomimetic films are here important biophysical model systems to elucidate fundamental aspects and mechanisms relevant for a large range of biological interaction ranging from signaling to drug reception or toxicity. Here we use dissipative quartz crystal microbalance QCM-D to examine the effect of aqueous imidazolium-based ionic liquid mixtures on solid-supported biomimetic membranes. Specifically, we assess in real time the effect of the cation chain length and the anion nature on a supported vesicle layer of the model phospholipid DMPC. Results indicate that interactions are mainly driven by the hydrophobic components of the IL, which significantly distort the layer and promote vesicle rupture. Our analyses evidence the gradual decrease of the main phase transition temperature upon increasing IL concentration, reflecting increased disorder by weakening of lipid chain interactions. The degree of rupture is significant for ILs with long hydrophobic cation chains and large hydrophobic anions whose behavior is reminiscent of that of antimicrobial peptides.

  14. Interactions of Aqueous Imidazolium-Based Ionic Liquid Mixtures with Solid-Supported Phospholipid Vesicles

    Science.gov (United States)

    Losada-Pérez, Patricia; Khorshid, Mehran; Renner, Frank Uwe

    2016-01-01

    Despite the environmentally friendly reputation of ionic liquids (ILs), their safety has been recently questioned given their potential as cytotoxic agents. The fundamental mechanisms underlying the interactions between ILs and cells are less studied and by far not completely understood. Biomimetic films are here important biophysical model systems to elucidate fundamental aspects and mechanisms relevant for a large range of biological interaction ranging from signaling to drug reception or toxicity. Here we use dissipative quartz crystal microbalance QCM-D to examine the effect of aqueous imidazolium-based ionic liquid mixtures on solid-supported biomimetic membranes. Specifically, we assess in real time the effect of the cation chain length and the anion nature on a supported vesicle layer of the model phospholipid DMPC. Results indicate that interactions are mainly driven by the hydrophobic components of the IL, which significantly distort the layer and promote vesicle rupture. Our analyses evidence the gradual decrease of the main phase transition temperature upon increasing IL concentration, reflecting increased disorder by weakening of lipid chain interactions. The degree of rupture is significant for ILs with long hydrophobic cation chains and large hydrophobic anions whose behavior is reminiscent of that of antimicrobial peptides. PMID:27684947

  15. A Crowdsensing-Based Real-Time System for Finger Interactions in Intelligent Transport System

    Directory of Open Access Journals (Sweden)

    Chengqun Song

    2017-01-01

    Full Text Available Crowdsensing leverages human intelligence/experience from the general public and social interactions to create participatory sensor networks, where context-aware and semantically complex information is gathered, processed, and shared to collaboratively solve specific problems. This paper proposes a real-time projector-camera finger system based on the crowdsensing, in which user can interact with a computer by bare hand touching on arbitrary surfaces. The interaction process of the system can be completely carried out automatically, and it can be used as an intelligent device in intelligent transport system where the driver can watch and interact with the display information while driving, without causing visual distractions. A single camera is used in the system to recover 3D information of fingertip for hand touch detection. A linear-scanning method is used in the system to determine the touch for increasing the users’ collaboration and operationality. Experiments are performed to show the feasibility of the proposed system. The system is robust to different lighting conditions. The average percentage of correct hand touch detection of the system is 92.0% and the average time of processing one video frame is 30 milliseconds.

  16. An Open-Source Web-Based Tool for Resource-Agnostic Interactive Translation Prediction

    Directory of Open Access Journals (Sweden)

    Daniel Torregrosa

    2014-09-01

    Full Text Available We present a web-based open-source tool for interactive translation prediction (ITP and describe its underlying architecture. ITP systems assist human translators by making context-based computer-generated suggestions as they type. Most of the ITP systems in literature are strongly coupled with a statistical machine translation system that is conveniently adapted to provide the suggestions. Our system, however, follows a resource-agnostic approach and suggestions are obtained from any unmodified black-box bilingual resource. This paper reviews our ITP method and describes the architecture of Forecat, a web tool, partly based on the recent technology of web components, that eases the use of our ITP approach in any web application requiring this kind of translation assistance. We also evaluate the performance of our method when using an unmodified Moses-based statistical machine translation system as the bilingual resource.

  17. Predicting protein complex in protein interaction network - a supervised learning based method.

    Science.gov (United States)

    Yu, Feng; Yang, Zhi; Tang, Nan; Lin, Hong; Wang, Jian; Yang, Zhi

    2014-01-01

    Protein complexes are important for understanding principles of cellular organization and function. High-throughput experimental techniques have produced a large amount of protein interactions, making it possible to predict protein complexes from protein -protein interaction networks. However, most of current methods are unsupervised learning based methods which can't utilize the information of the large amount of available known complexes. We present a supervised learning-based method for predicting protein complexes in protein - protein interaction networks. The method extracts rich features from both the unweighted and weighted networks to train a Regression model, which is then used for the cliques filtering, growth, and candidate complex filtering. The model utilizes additional "uncertainty" samples and, therefore, is more discriminative when used in the complex detection algorithm. In addition, our method uses the maximal cliques found by the Cliques algorithm as the initial cliques, which has been proven to be more effective than the method of expanding from the seeding proteins used in other methods. The experimental results on several PIN datasets show that in most cases the performance of our method are superior to comparable state-of-the-art protein complex detection techniques. The results demonstrate the several advantages of our method over other state-of-the-art techniques. Firstly, our method is a supervised learning-based method that can make full use of the information of the available known complexes instead of being only based on the topological structure of the PIN. That also means, if more training samples are provided, our method can achieve better performance than those unsupervised methods. Secondly, we design the rich feature set to describe the properties of the known complexes, which includes not only the features from the unweighted network, but also those from the weighted network built based on the Gene Ontology information. Thirdly

  18. Efficient techniques for wave-based sound propagation in interactive applications

    Science.gov (United States)

    Mehra, Ravish

    Sound propagation techniques model the effect of the environment on sound waves and predict their behavior from point of emission at the source to the final point of arrival at the listener. Sound is a pressure wave produced by mechanical vibration of a surface that propagates through a medium such as air or water, and the problem of sound propagation can be formulated mathematically as a second-order partial differential equation called the wave equation. Accurate techniques based on solving the wave equation, also called the wave-based techniques, are too expensive computationally and memory-wise. Therefore, these techniques face many challenges in terms of their applicability in interactive applications including sound propagation in large environments, time-varying source and listener directivity, and high simulation cost for mid-frequencies. In this dissertation, we propose a set of efficient wave-based sound propagation techniques that solve these three challenges and enable the use of wave-based sound propagation in interactive applications. Firstly, we propose a novel equivalent source technique for interactive wave-based sound propagation in large scenes spanning hundreds of meters. It is based on the equivalent source theory used for solving radiation and scattering problems in acoustics and electromagnetics. Instead of using a volumetric or surface-based approach, this technique takes an object-centric approach to sound propagation. The proposed equivalent source technique generates realistic acoustic effects and takes orders of magnitude less runtime memory compared to prior wave-based techniques. Secondly, we present an efficient framework for handling time-varying source and listener directivity for interactive wave-based sound propagation. The source directivity is represented as a linear combination of elementary spherical harmonic sources. This spherical harmonic-based representation of source directivity can support analytical, data

  19. Nonstationary color tracking for vision-based human-computer interaction.

    Science.gov (United States)

    Wu, Ying; Huang, T S

    2002-01-01

    Skin color offers a strong cue for efficient localization and tracking of human body parts in video sequences for vision-based human-computer interaction. Color-based target localization could be achieved by analyzing segmented skin color regions. However, one of the challenges of color-based target tracking is that color distributions would change in different lighting conditions such that fixed color models would be inadequate to capture nonstationary color distributions over time. Meanwhile, using a fixed skin color model trained by the data of a specific person would probably not work well for other people. Although some work has been done on adaptive color models, this problem still needs further studies. We present our investigation of color-based image segmentation and nonstationary color-based target tracking, by studying two different representations for color distributions. We propose the structure adaptive self-organizing map (SASOM) neural network that serves as a new color model. Our experiments show that such a representation is powerful for efficient image segmentation. Then, we formulate the nonstationary color tracking problem as a model transduction problem, the solution of which offers a way to adapt and transduce color classifiers in nonstationary color distributions. To fulfill model transduction, we propose two algorithms, the SASOM transduction and the discriminant expectation-maximization (EM), based on the SASOM color model and the Gaussian mixture color model, respectively. Our extensive experiments on the task of real-time face/hand localization show that these two algorithms can successfully handle some difficulties in nonstationary color tracking. We also implemented a real-time face/hand localization system based on such algorithms for vision-based human-computer interaction.

  20. Novel Blend Membranes Based on Acid-Base Interactions for Fuel Cells

    Directory of Open Access Journals (Sweden)

    Yongzhu Fu

    2012-10-01

    Full Text Available Fuel cells hold great promise for wide applications in portable, residential, and large-scale power supplies. For low temperature fuel cells, such as the proton exchange membrane fuel cells (PEMFCs and direct methanol fuel cells (DMFCs, proton-exchange membranes (PEMs are a key component determining the fuel cells performance. PEMs with high proton conductivity under anhydrous conditions can allow PEMFCs to be operated above 100 °C, enabling use of hydrogen fuels with high-CO contents and improving the electrocatalytic activity. PEMs with high proton conductivity and low methanol crossover are critical for lowering catalyst loadings at the cathode and improving the performance and long-term stability of DMFCs. This review provides a summary of a number of novel acid-base blend membranes consisting of an acidic polymer and a basic compound containing N-heterocycle groups, which are promising for PEMFCs and DMFCs.

  1. Towards Gesture-Based Multi-User Interactions in Collaborative Virtual Environments

    Science.gov (United States)

    Pretto, N.; Poiesi, F.

    2017-11-01

    We present a virtual reality (VR) setup that enables multiple users to participate in collaborative virtual environments and interact via gestures. A collaborative VR session is established through a network of users that is composed of a server and a set of clients. The server manages the communication amongst clients and is created by one of the users. Each user's VR setup consists of a Head Mounted Display (HMD) for immersive visualisation, a hand tracking system to interact with virtual objects and a single-hand joypad to move in the virtual environment. We use Google Cardboard as a HMD for the VR experience and a Leap Motion for hand tracking, thus making our solution low cost. We evaluate our VR setup though a forensics use case, where real-world objects pertaining to a simulated crime scene are included in a VR environment, acquired using a smartphone-based 3D reconstruction pipeline. Users can interact using virtual gesture-based tools such as pointers and rulers.

  2. Tonal synchrony in mother-infant interaction based on harmonic and pentatonic series.

    Science.gov (United States)

    Van Puyvelde, Martine; Vanfleteren, Pol; Loots, Gerrit; Deschuyffeleer, Sara; Vinck, Bart; Jacquet, Wolfgang; Verhelst, Werner

    2010-12-01

    This study reports the occurrence of 'tonal synchrony' as a new dimension of early mother-infant interaction synchrony. The findings are based on a tonal and temporal analysis of vocal interactions between 15 mothers and their 3-month-old infants during 5 min of free-play in a laboratory setting. In total, 558 vocal exchanges were identified and analysed, of which 84% reflected harmonic or pentatonic series. Another 10% of the exchanges contained absolute and/or relative pitch and/or interval imitations. The total durations of dyads being in tonal synchrony were normally distributed (M=3.71, SD=2.44). Vocalisations based on harmonic series appeared organised around the major triad, containing significantly more simple frequency ratios (octave, fifth and third) than complex ones (non-major triad tones). Tonal synchrony and its characteristics are discussed in relation to infant-directed speech, communicative musicality, pre-reflective communication and its impact on the quality of early mother-infant interaction and child's development. Copyright © 2010 Elsevier Inc. All rights reserved.

  3. Providing Access to Census-based Interaction Data in the UK: That's WICID!

    Directory of Open Access Journals (Sweden)

    John Stillwell

    2006-08-01

    Full Text Available The Census Interaction Data Service (CIDS is funded by the Economic and Social Research Council in the UK to provide access for social science researchers and students to the detailed migration and journey-to-work statistics that are collected by the national statistical agencies. These interaction data sets are known collectively as the Special Migration Statistics (SMS and the Special Workplace Statistics (SWS. This paper outlines how problems of user access to these data have been tackled through the development of a web-based system known as WICID (Web-based Interface to Census Interaction Data. The paper illustrates various interface features including some of the query building facilities that enable users to extract counts of flows of particular groups of individuals between selected origin and destination areas. New tools are outlined for assisting area selection using digital maps of census geographies, for planning output and for adding value to the data through analysis. Mapping of flows of migrants between London boroughs and the rest of the UK demonstrates the value of the data. The paper begins with a summary of the data sets that are contained within the system and an outline of the system architecture.

  4. A Development of Game-Based Learning Environment to Activate Interaction among Learners

    Science.gov (United States)

    Takaoka, Ryo; Shimokawa, Masayuki; Okamoto, Toshio

    Many studies and systems that incorporate elements such as “pleasure” and “fun” in the game to improve a learner's motivation have been developed in the field of learning environments. However, few are the studies of situations where many learners gather at a single computer and participate in a game-based learning environment (GBLE), and where the GBLE designs the learning process by controlling the interactions between learners such as competition, collaboration, and learning by teaching. Therefore, the purpose of this study is to propose a framework of educational control that induces and activates interaction between learners intentionally to create a learning opportunity that is based on the knowledge understanding model of each learner. In this paper, we explain the design philosophy and the framework of our GBLE called “Who becomes the king in the country of mathematics?” from a game viewpoint and describe the method of learning support control in the learning environment. In addition, we report the results of the learning experiment with our GBLE, which we carried out in a junior high school, and include some comments by a principal and a teacher. From the results of the experiment and some comments, we noticed that a game may play a significant role in weakening the learning relationship among students and creating new relationships in the world of the game. Furthermore, we discovered that learning support control of the GBLE has led to activation of the interaction between learners to some extent.

  5. Proposal for Requirement Validation Criteria and Method Based on Actor Interaction

    Science.gov (United States)

    Hattori, Noboru; Yamamoto, Shuichiro; Ajisaka, Tsuneo; Kitani, Tsuyoshi

    We propose requirement validation criteria and a method based on the interaction between actors in an information system. We focus on the cyclical transitions of one actor's situation against another and clarify observable stimuli and responses based on these transitions. Both actors' situations can be listed in a state transition table, which describes the observable stimuli or responses they send or receive. Examination of the interaction between both actors in the state transition tables enables us to detect missing or defective observable stimuli or responses. Typically, this method can be applied to the examination of the interaction between a resource managed by the information system and its user. As a case study, we analyzed 332 requirement defect reports of an actual system development project in Japan. We found that there were a certain amount of defects regarding missing or defective stimuli and responses, which can be detected using our proposed method if this method is used in the requirement definition phase. This means that we can reach a more complete requirement definition with our proposed method.

  6. Detection of gene-environment interactions in a family-based population using SCAD.

    Science.gov (United States)

    Kim, Gwangsu; Lai, Chao-Qiang; Arnett, Donna K; Parnell, Laurence D; Ordovas, Jose M; Kim, Yongdai; Kim, Joungyoun

    2017-09-30

    Gene-environment interaction (GxE) is emphasized as one potential source of missing genetic variation on disease traits, and the ultimate goal of GxE research is prediction of individual risk and prevention of complex diseases. However, there are various challenges in statistical analysis of GxE. In this paper, we focus on the three methodological challenges: (i) the high dimensions of genes; (ii) the hierarchical structure between interaction effects and their corresponding main effects; and (iii) the correlation among subjects from family-based population studies. In this paper, we propose an algorithm that approaches all three challenges simultaneously. This is the first penalized method focusing on an interaction search based on a linear mixed effect model. For verification, we compare the empirical performance of our new method with other existing methods in simulation study. The results demonstrate the superiority of our method under overall simulation setup. In particular, the outperformance obviously becomes greater as the correlation among subjects increases. In addition, the new method provides a robust estimate for the correlation among subjects. We also apply the new method on Genetics of Lipid Lowering Drugs and Diet Network study data. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  7. An entropy-based analysis of lane changing behavior: An interactive approach.

    Science.gov (United States)

    Kosun, Caglar; Ozdemir, Serhan

    2017-05-19

    As a novelty, this article proposes the nonadditive entropy framework for the description of driver behaviors during lane changing. The authors also state that this entropy framework governs the lane changing behavior in traffic flow in accordance with the long-range vehicular interactions and traffic safety. The nonadditive entropy framework is the new generalized theory of thermostatistical mechanics. Vehicular interactions during lane changing are considered within this framework. The interactive approach for the lane changing behavior of the drivers is presented in the traffic flow scenarios presented in the article. According to the traffic flow scenarios, 4 categories of traffic flow and driver behaviors are obtained. Through the scenarios, comparative analyses of nonadditive and additive entropy domains are also provided. Two quadrants of the categories belong to the nonadditive entropy; the rest are involved in the additive entropy domain. Driving behaviors are extracted and the scenarios depict that nonadditivity matches safe driving well, whereas additivity corresponds to unsafe driving. Furthermore, the cooperative traffic system is considered in nonadditivity where the long-range interactions are present. However, the uncooperative traffic system falls into the additivity domain. The analyses also state that there would be possible traffic flow transitions among the quadrants. This article shows that lane changing behavior could be generalized as nonadditive, with additivity as a special case, based on the given traffic conditions. The nearest and close neighbor models are well within the conventional additive entropy framework. In this article, both the long-range vehicular interactions and safe driving behavior in traffic are handled in the nonadditive entropy domain. It is also inferred that the Tsallis entropy region would correspond to mandatory lane changing behavior, whereas additive and either the extensive or nonextensive entropy region would

  8. Interaction of biocompatible natural rosin-based surfactants with human serum albumin: A biophysical study

    Energy Technology Data Exchange (ETDEWEB)

    Ishtikhar, Mohd [Protein Biophysics Laboratory, Interdisciplinary Biotechnology Unit, Aligarh Muslim University, Aligarh 202002 (India); Ali, Mohd Sajid [Surfactant Research Chair, Department of Chemistry, King Saud University, P.O. Box-2455, Riyadh 11451 (Saudi Arabia); Atta, Ayman M. [Surfactant Research Chair, Department of Chemistry, King Saud University, P.O. Box-2455, Riyadh 11451 (Saudi Arabia); Petroleum Application department, Egyptian Petroleum Research Institute, Ahmad Elzomor St., Nasr city, Cairo-11727 (Egypt); Al-Lohedan, H.A. [Surfactant Research Chair, Department of Chemistry, King Saud University, P.O. Box-2455, Riyadh 11451 (Saudi Arabia); Nigam, Lokesh; Subbarao, Naidu [Centre for Computational Biology and Bioinformatics, School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067 (India); Hasan Khan, Rizwan, E-mail: rizwanhkhan@hotmail.com [Protein Biophysics Laboratory, Interdisciplinary Biotechnology Unit, Aligarh Muslim University, Aligarh 202002 (India)

    2015-11-15

    Biophysical insight into interaction of biocompatible rosin-based surfactants with human serum albumin (HSA) was studied at physiological conditions using various spectroscopic, calorimetric and molecular docking approaches. The binding constant (K{sub b}), enthalpy (ΔH{sup 0}), entropy (ΔS{sup 0}) and Gibbs free energy change (ΔG{sup 0}) were calculated by spectroscopic and calorimetric method. We have also calculated the probability of energy transfer by FRET analysis. The circular dichroism study showed that the cationic surfactant QRMAE significantly altered the secondary structure of HSA as compared to the nonionic rosin surfactants. The thermodynamic study was performed by ITC to determine binding constant as well as change in enthalpy of HSA in presence of rosin surfactants. It clearly showed that hydrogen binding and hydrophobic interaction play an important role in the binding of HSA to rosin surfactants. We have also performed molecular docking studies to locate the binding site on HSA and to visualize the mode of interaction. The present study provides a significant insight into HSA–rosin surfactants interaction, which also improves our understanding of the possible effect of rosin surfactants on human health. - Highlights: • RMPEG 750 has the highest Kb, Kq and Ksv value as compared to other rosin surfactants. • The probability of energy transfer from HSA to rosin surfactants was maximum in the case of RMPEG 750. • Cationic surfactant QRMAE significantly altered the secondary structure of the HSA as compared to other rosin surfactants. • Molecular docking and ITC experiment studies, to locate the binding site on HSA and to investigate the mode of interaction.

  9. MOLEonline 2.0: interactive web-based analysis of biomacromolecular channels.

    Science.gov (United States)

    Berka, Karel; Hanák, Ondrej; Sehnal, David; Banás, Pavel; Navrátilová, Veronika; Jaiswal, Deepti; Ionescu, Crina-Maria; Svobodová Vareková, Radka; Koca, Jaroslav; Otyepka, Michal

    2012-07-01

    Biomolecular channels play important roles in many biological systems, e.g. enzymes, ribosomes and ion channels. This article introduces a web-based interactive MOLEonline 2.0 application for the analysis of access/egress paths to interior molecular voids. MOLEonline 2.0 enables platform-independent, easy-to-use and interactive analyses of (bio)macromolecular channels, tunnels and pores. Results are presented in a clear manner, making their interpretation easy. For each channel, MOLEonline displays a 3D graphical representation of the channel, its profile accompanied by a list of lining residues and also its basic physicochemical properties. The users can tune advanced parameters when performing a channel search to direct the search according to their needs. The MOLEonline 2.0 application is freely available via the Internet at http://ncbr.muni.cz/mole or http://mole.upol.cz.

  10. The Development of Interactive Mathematics Learning Material Based on Local Wisdom

    Science.gov (United States)

    Abadi, M. K.; Cahya, E.; Jupri, A.

    2017-09-01

    The purpose of this study is to create interactive learning materials that can be used on smart phones and computer with swf format base on local wisdom. In this study using three stages of research that is observation, literature and mix We found that interactive learning materials are suitable for learning in the digital age. Because from observation to students of senior high school in Serang district there are student do not have mathematics books to study. Local wisdom of the region should be enriched in the subject matter. This is to answer the challenge that many students do not have a package book and have a smart phone. This has impact on students better thinking processes.

  11. An interactive simulation-based education system for BWR emergency, procedure guidelines

    International Nuclear Information System (INIS)

    Tanikawa, Naoshi; Shida, Touichi; Ujita, Hiroshi; Yokota, Takeshi; Kato, Kanji

    1994-01-01

    When applying EPGs (Emergency Procedure Guidelines), an operator decides the operational procedure by predicting the change of parameters from the plant status, because EPGs are described in a symptom style for emergency conditions. Technical knowledge of the plant behavior and its operation are necessary for operator to understand the EPGs. An interactive simulation-based education system, EPG-ICAI (Intelligent Computer Assisted Instruction), has been developed for BWR plant operators to acquire the knowledge of EPGs. EPG-ICAI is designed to realize an effective education by the step-by-step study by using an interactive real time simulator and an individual education by applying an intelligent tutoring function. (orig.) (2 refs., 7 figs., 1 tab.)

  12. Oscillation mode analysis considering the interaction between a DFIG-based wind turbine and the grid

    Science.gov (United States)

    Wu, Wangping; Xie, Da; Lu, Yupu; Zhao, Zuyi; Yu, Songtao

    2017-01-01

    Sub-synchronous interactions between wind farms and transmission networks with series compensation have drawn great attention. As most large wind farms in Europe and Asia employ doubly fed induction generator turbines, there has recently been a growing interest in studying this phenomenon. To study the stability of wind turbine with doubly fed induction generator after a small disturbance, a complete small signal system is built in this paper. By using eigenvalue and participation factor analysis, the relation between the modes and state variables can be discovered. Thereafter, the oscillation modes are classified into electrical resonance, sub-synchronous resonance, sub-synchronous oscillation, sub-synchronous control interaction, and low frequency oscillation. To verify the oscillation frequency of each oscillation mode, time-domain simulation based on MATLAB/Simulink is presented. The simulation results justify the effectiveness of the small-signal models.

  13. KIPSE1: A Knowledge-based Interactive Problem Solving Environment for data estimation and pattern classification

    Science.gov (United States)

    Han, Chia Yung; Wan, Liqun; Wee, William G.

    1990-01-01

    A knowledge-based interactive problem solving environment called KIPSE1 is presented. The KIPSE1 is a system built on a commercial expert system shell, the KEE system. This environment gives user capability to carry out exploratory data analysis and pattern classification tasks. A good solution often consists of a sequence of steps with a set of methods used at each step. In KIPSE1, solution is represented in the form of a decision tree and each node of the solution tree represents a partial solution to the problem. Many methodologies are provided at each node to the user such that the user can interactively select the method and data sets to test and subsequently examine the results. Otherwise, users are allowed to make decisions at various stages of problem solving to subdivide the problem into smaller subproblems such that a large problem can be handled and a better solution can be found.

  14. Contribution of monophenols to beer flavour based on flavour thresholds, interactions and recombination experiments.

    Science.gov (United States)

    Sterckx, Femke L; Missiaen, Jonas; Saison, Daan; Delvaux, Freddy R

    2011-06-15

    Although monophenols are known to contribute to the flavour of many foods and beverages, little is known about their influence on beer flavour. Therefore, the contribution of 11 monophenols to the overall beer flavour was studied by determining their flavour thresholds. Large differences in sensitivity were observed between individual tasters. Next, flavour interactions between monophenols were examined in nine binary mixtures, which showed that strong interactions like synergy and antagonism occur. Based on these results, the flavour contribution of the monophenols was estimated by calculating flavour units. These proved to be rather low for most of the studied monophenols. However, recombination experiments demonstrated that monophenols enriched beer flavour with spicy, smokey and vanilla flavour aspects. This showed how monophenols might influence overall flavour, even at sub-threshold concentrations. Copyright © 2010 Elsevier Ltd. All rights reserved.

  15. An interactive simulation-based education system for BWR emergency, procedure guidelines

    Energy Technology Data Exchange (ETDEWEB)

    Tanikawa, Naoshi; Shida, Touichi [Hitachi Ltd (Japan). Hitachi Works; Ujita, Hiroshi; Yokota, Takeshi; Kato, Kanji [Hitachi Ltd, (Japan). Energy Research Lab.

    1994-12-31

    When applying EPGs (Emergency Procedure Guidelines), an operator decides the operational procedure by predicting the change of parameters from the plant status, because EPGs are described in a symptom style for emergency conditions. Technical knowledge of the plant behavior and its operation are necessary for operator to understand the EPGs. An interactive simulation-based education system, EPG-ICAI (Intelligent Computer Assisted Instruction), has been developed for BWR plant operators to acquire the knowledge of EPGs. EPG-ICAI is designed to realize an effective education by the step-by-step study by using an interactive real time simulator and an individual education by applying an intelligent tutoring function. (orig.) (2 refs., 7 figs., 1 tab.).

  16. Realization on the interactive remote video conference system based on multi-Agent

    Directory of Open Access Journals (Sweden)

    Zheng Yan

    2016-01-01

    Full Text Available To make people at different places participate in the same conference, speak and discuss freely, the interactive remote video conferencing system is designed and realized based on multi-Agent collaboration. FEC (forward error correction and tree P2P technology are firstly used to build a live conference structure to transfer audio and video data; then the branch conference port can participate to speak and discuss through the application of becoming a interactive focus; the introduction of multi-Agent collaboration technology improve the system robustness. The experiments showed that, under normal network conditions, the system can support 350 branch conference node simultaneously to make live broadcasting. The audio and video quality is smooth. It can carry out large-scale remote video conference.

  17. Coronary Heart Disease Preoperative Gesture Interactive Diagnostic System Based on Augmented Reality.

    Science.gov (United States)

    Zou, Yi-Bo; Chen, Yi-Min; Gao, Ming-Ke; Liu, Quan; Jiang, Si-Yu; Lu, Jia-Hui; Huang, Chen; Li, Ze-Yu; Zhang, Dian-Hua

    2017-08-01

    Coronary heart disease preoperative diagnosis plays an important role in the treatment of vascular interventional surgery. Actually, most doctors are used to diagnosing the position of the vascular stenosis and then empirically estimating vascular stenosis by selective coronary angiography images instead of using mouse, keyboard and computer during preoperative diagnosis. The invasive diagnostic modality is short of intuitive and natural interaction and the results are not accurate enough. Aiming at above problems, the coronary heart disease preoperative gesture interactive diagnostic system based on Augmented Reality is proposed. The system uses Leap Motion Controller to capture hand gesture video sequences and extract the features which that are the position and orientation vector of the gesture motion trajectory and the change of the hand shape. The training planet is determined by K-means algorithm and then the effect of gesture training is improved by multi-features and multi-observation sequences for gesture training. The reusability of gesture is improved by establishing the state transition model. The algorithm efficiency is improved by gesture prejudgment which is used by threshold discriminating before recognition. The integrity of the trajectory is preserved and the gesture motion space is extended by employing space rotation transformation of gesture manipulation plane. Ultimately, the gesture recognition based on SRT-HMM is realized. The diagnosis and measurement of the vascular stenosis are intuitively and naturally realized by operating and measuring the coronary artery model with augmented reality and gesture interaction techniques. All of the gesture recognition experiments show the distinguish ability and generalization ability of the algorithm and gesture interaction experiments prove the availability and reliability of the system.

  18. Network theory-based analysis of risk interactions in large engineering projects

    International Nuclear Information System (INIS)

    Fang, Chao; Marle, Franck; Zio, Enrico; Bocquet, Jean-Claude

    2012-01-01

    This paper presents an approach based on network theory to deal with risk interactions in large engineering projects. Indeed, such projects are exposed to numerous and interdependent risks of various nature, which makes their management more difficult. In this paper, a topological analysis based on network theory is presented, which aims at identifying key elements in the structure of interrelated risks potentially affecting a large engineering project. This analysis serves as a powerful complement to classical project risk analysis. Its originality lies in the application of some network theory indicators to the project risk management field. The construction of the risk network requires the involvement of the project manager and other team members assigned to the risk management process. Its interpretation improves their understanding of risks and their potential interactions. The outcomes of the analysis provide a support for decision-making regarding project risk management. An example of application to a real large engineering project is presented. The conclusion is that some new insights can be found about risks, about their interactions and about the global potential behavior of the project. - Highlights: ► The method addresses the modeling of complexity in project risk analysis. ► Network theory indicators enable other risks than classical criticality analysis to be highlighted. ► This topological analysis improves project manager's understanding of risks and risk interactions. ► This helps project manager to make decisions considering the position in the risk network. ► An application to a real tramway implementation project in a city is provided.

  19. Gene Environment Interactions and Predictors of Colorectal Cancer in Family-Based, Multi-Ethnic Groups

    Directory of Open Access Journals (Sweden)

    S. Pamela K. Shiao

    2018-02-01

    Full Text Available For the personalization of polygenic/omics-based health care, the purpose of this study was to examine the gene–environment interactions and predictors of colorectal cancer (CRC by including five key genes in the one-carbon metabolism pathways. In this proof-of-concept study, we included a total of 54 families and 108 participants, 54 CRC cases and 54 matched family friends representing four major racial ethnic groups in southern California (White, Asian, Hispanics, and Black. We used three phases of data analytics, including exploratory, family-based analyses adjusting for the dependence within the family for sharing genetic heritage, the ensemble method, and generalized regression models for predictive modeling with a machine learning validation procedure to validate the results for enhanced prediction and reproducibility. The results revealed that despite the family members sharing genetic heritage, the CRC group had greater combined gene polymorphism rates than the family controls (p < 0.05, on MTHFR C677T, MTR A2756G, MTRR A66G, and DHFR 19 bp except MTHFR A1298C. Four racial groups presented different polymorphism rates for four genes (all p < 0.05 except MTHFR A1298C. Following the ensemble method, the most influential factors were identified, and the best predictive models were generated by using the generalized regression models, with Akaike’s information criterion and leave-one-out cross validation methods. Body mass index (BMI and gender were consistent predictors of CRC for both models when individual genes versus total polymorphism counts were used, and alcohol use was interactive with BMI status. Body mass index status was also interactive with both gender and MTHFR C677T gene polymorphism, and the exposure to environmental pollutants was an additional predictor. These results point to the important roles of environmental and modifiable factors in relation to gene–environment interactions in the prevention of CRC.

  20. Mass-based hygroscopicity parameter interaction model and measurement of atmospheric aerosol water uptake

    Science.gov (United States)

    Mikhailov, E.; Vlasenko, S.; Rose, D.; Pöschl, U.

    2013-01-01

    In this study we derive and apply a mass-based hygroscopicity parameter interaction model for efficient description of concentration-dependent water uptake by atmospheric aerosol particles with complex chemical composition. The model approach builds on the single hygroscopicity parameter model of Petters and Kreidenweis (2007). We introduce an observable mass-based hygroscopicity parameter κm which can be deconvoluted into a dilute hygroscopicity parameter (κm0) and additional self- and cross-interaction parameters describing non-ideal solution behavior and concentration dependencies of single- and multi-component systems. For reference aerosol samples of sodium chloride and ammonium sulfate, the κm-interaction model (KIM) captures the experimentally observed concentration and humidity dependence of the hygroscopicity parameter and is in good agreement with an accurate reference model based on the Pitzer ion-interaction approach (Aerosol Inorganic Model, AIM). Experimental results for pure organic particles (malonic acid, levoglucosan) and for mixed organic-inorganic particles (malonic acid - ammonium sulfate) are also well reproduced by KIM, taking into account apparent or equilibrium solubilities for stepwise or gradual deliquescence and efflorescence transitions. The mixed organic-inorganic particles as well as atmospheric aerosol samples exhibit three distinctly different regimes of hygroscopicity: (I) a quasi-eutonic deliquescence & efflorescence regime at low-humidity where substances are just partly dissolved and exist also in a non-dissolved phase, (II) a gradual deliquescence & efflorescence regime at intermediate humidity where different solutes undergo gradual dissolution or solidification in the aqueous phase; and (III) a dilute regime at high humidity where the solutes are fully dissolved approaching their dilute hygroscopicity. For atmospheric aerosol samples collected from boreal rural air and from pristine tropical rainforest air (secondary

  1. Mass-based hygroscopicity parameter interaction model and measurement of atmospheric aerosol water uptake

    Directory of Open Access Journals (Sweden)

    E. Mikhailov

    2013-01-01

    Full Text Available In this study we derive and apply a mass-based hygroscopicity parameter interaction model for efficient description of concentration-dependent water uptake by atmospheric aerosol particles with complex chemical composition. The model approach builds on the single hygroscopicity parameter model of Petters and Kreidenweis (2007. We introduce an observable mass-based hygroscopicity parameter κm which can be deconvoluted into a dilute hygroscopicity parameter (κm0 and additional self- and cross-interaction parameters describing non-ideal solution behavior and concentration dependencies of single- and multi-component systems.

    For reference aerosol samples of sodium chloride and ammonium sulfate, the κm-interaction model (KIM captures the experimentally observed concentration and humidity dependence of the hygroscopicity parameter and is in good agreement with an accurate reference model based on the Pitzer ion-interaction approach (Aerosol Inorganic Model, AIM. Experimental results for pure organic particles (malonic acid, levoglucosan and for mixed organic-inorganic particles (malonic acid – ammonium sulfate are also well reproduced by KIM, taking into account apparent or equilibrium solubilities for stepwise or gradual deliquescence and efflorescence transitions.

    The mixed organic-inorganic particles as well as atmospheric aerosol samples exhibit three distinctly different regimes of hygroscopicity: (I a quasi-eutonic deliquescence & efflorescence regime at low-humidity where substances are just partly dissolved and exist also in a non-dissolved phase, (II a gradual deliquescence & efflorescence regime at intermediate humidity where different solutes undergo gradual dissolution or solidification in the aqueous phase; and (III a dilute regime at high humidity where the solutes are fully dissolved approaching their dilute hygroscopicity.

    For atmospheric aerosol samples

  2. D Modelling and Interactive Web-Based Visualization of Cultural Heritage Objects

    Science.gov (United States)

    Koeva, M. N.

    2016-06-01

    Nowadays, there are rapid developments in the fields of photogrammetry, laser scanning, computer vision and robotics, together aiming to provide highly accurate 3D data that is useful for various applications. In recent years, various LiDAR and image-based techniques have been investigated for 3D modelling because of their opportunities for fast and accurate model generation. For cultural heritage preservation and the representation of objects that are important for tourism and their interactive visualization, 3D models are highly effective and intuitive for present-day users who have stringent requirements and high expectations. Depending on the complexity of the objects for the specific case, various technological methods can be applied. The selected objects in this particular research are located in Bulgaria - a country with thousands of years of history and cultural heritage dating back to ancient civilizations. This motivates the preservation, visualisation and recreation of undoubtedly valuable historical and architectural objects and places, which has always been a serious challenge for specialists in the field of cultural heritage. In the present research, comparative analyses regarding principles and technological processes needed for 3D modelling and visualization are presented. The recent problems, efforts and developments in interactive representation of precious objects and places in Bulgaria are presented. Three technologies based on real projects are described: (1) image-based modelling using a non-metric hand-held camera; (2) 3D visualization based on spherical panoramic images; (3) and 3D geometric and photorealistic modelling based on architectural CAD drawings. Their suitability for web-based visualization are demonstrated and compared. Moreover the possibilities for integration with additional information such as interactive maps, satellite imagery, sound, video and specific information for the objects are described. This comparative study

  3. 3D MODELLING AND INTERACTIVE WEB-BASED VISUALIZATION OF CULTURAL HERITAGE OBJECTS

    Directory of Open Access Journals (Sweden)

    M. N. Koeva

    2016-06-01

    Full Text Available Nowadays, there are rapid developments in the fields of photogrammetry, laser scanning, computer vision and robotics, together aiming to provide highly accurate 3D data that is useful for various applications. In recent years, various LiDAR and image-based techniques have been investigated for 3D modelling because of their opportunities for fast and accurate model generation. For cultural heritage preservation and the representation of objects that are important for tourism and their interactive visualization, 3D models are highly effective and intuitive for present-day users who have stringent requirements and high expectations. Depending on the complexity of the objects for the specific case, various technological methods can be applied. The selected objects in this particular research are located in Bulgaria – a country with thousands of years of history and cultural heritage dating back to ancient civilizations. \\this motivates the preservation, visualisation and recreation of undoubtedly valuable historical and architectural objects and places, which has always been a serious challenge for specialists in the field of cultural heritage. In the present research, comparative analyses regarding principles and technological processes needed for 3D modelling and visualization are presented. The recent problems, efforts and developments in interactive representation of precious objects and places in Bulgaria are presented. Three technologies based on real projects are described: (1 image-based modelling using a non-metric hand-held camera; (2 3D visualization based on spherical panoramic images; (3 and 3D geometric and photorealistic modelling based on architectural CAD drawings. Their suitability for web-based visualization are demonstrated and compared. Moreover the possibilities for integration with additional information such as interactive maps, satellite imagery, sound, video and specific information for the objects are described. This

  4. The weak π − π interaction originated resonant tunneling and fast switching in the carbon based electronic devices

    Directory of Open Access Journals (Sweden)

    Jun He

    2012-03-01

    Full Text Available By means of the nonequilibrium Green's functions and the density functional theory, we have investigated the electronic transport properties of C60 based electronic device with different intermolecular interactions. It is found that the electronic transport properties vary with the types of the interaction between two C60 molecules. A fast electrical switching behavior based on negative differential resistance has been found when two molecules are coupled by the weak π − π interaction. Compared to the solid bonding, the weak interaction is found to induce resonant tunneling, which is responsible for the fast response to the applied electric field and hence the velocity of switching.

  5. Twenty weeks of home-based interactive training of children with cerebral palsy improves functional abilities

    DEFF Research Database (Denmark)

    Lorentzen, Jakob; Greve, Line Z; Kliim-Due, Mette

    2015-01-01

    (CP). METHODS: Thirty four children with CP (aged 9-16; mean age 10.9 ± 2.4 years) (GMFCS I-II; MACS I-II) were included in this non-randomized controlled clinical training study. 12 children (aged 7-16; mean age: 11.3+/-0.9 years) were allocated to a control group in which measurements were performed......BACKGROUND: Home-based training is becoming ever more important with increasing demands on the public health systems. We investigated whether individualized and supervised interactive home-based training delivered through the internet improves functional abilities in children with cerebral palsy...... with 20 weeks interval without any intervening training. Daily activities, functional abilities of upper- and lower limbs, and balance were evaluated before, immediately after training and 12 weeks after training. The training consisted of 30 min daily home-based training for 20 weeks delivered through...

  6. Tablet-Based Functional MRI of the Trail Making Test: Effect of Tablet Interaction Mode

    Directory of Open Access Journals (Sweden)

    Mahta Karimpoor

    2017-10-01

    Full Text Available The Trail Making Test (TMT is widely used for assessing executive function, frontal lobe abilities, and visual motor skills. Part A of this pen-and-paper test (TMT-A involves linking numbers randomly distributed in space, in ascending order. Part B (TMT-B alternates between linking numbers and letters. TMT-B is more demanding than TMT-A, but the mental processing that supports the performance of this test remains incompletely understood. Functional MRI (fMRI may help to clarify the relationship between TMT performance and brain activity, but providing an environment that supports real-world pen-and-paper interactions during fMRI is challenging. Previously, an fMRI-compatible tablet system was developed for writing and drawing with two modes of interaction: the original cursor-based, proprioceptive approach, and a new mode involving augmented reality to provide visual feedback of hand position (VFHP for enhanced user interaction. This study characterizes the use of the tablet during fMRI of young healthy adults (n = 22, with half of the subjects performing TMT with VFHP and the other half performing TMT without VFHP. Activation maps for both TMT-A and TMT-B performance showed considerable overlap between the two tablet modes, and no statistically differences in brain activity were detected when contrasting TMT-B vs. TMT-A for the two tablet modes. Behavioral results also showed no statistically different interaction effects for TMT-B vs. TMT-A for the two tablet modes. Tablet-based TMT scores showed reasonable convergent validity with those obtained by administering the standard pen-and-paper TMT to the same subjects. Overall, the results suggest that despite the slightly different mechanisms involved for the two modes of tablet interaction, both are suitable for use in fMRI studies involving TMT performance. This study provides information for using tablet-based TMT methods appropriately in future fMRI studies involving patients and healthy

  7. Continued use of an interactive computer game-based visual perception learning system in children with developmental delay.

    Science.gov (United States)

    Lin, Hsien-Cheng; Chiu, Yu-Hsien; Chen, Yenming J; Wuang, Yee-Pay; Chen, Chiu-Ping; Wang, Chih-Chung; Huang, Chien-Ling; Wu, Tang-Meng; Ho, Wen-Hsien

    2017-11-01

    This study developed an interactive computer game-based visual perception learning system for special education children with developmental delay. To investigate whether perceived interactivity affects continued use of the system, this study developed a theoretical model of the process in which learners decide whether to continue using an interactive computer game-based visual perception learning system. The technology acceptance model, which considers perceived ease of use, perceived usefulness, and perceived playfulness, was extended by integrating perceived interaction (i.e., learner-instructor interaction and learner-system interaction) and then analyzing the effects of these perceptions on satisfaction and continued use. Data were collected from 150 participants (rehabilitation therapists, medical paraprofessionals, and parents of children with developmental delay) recruited from a single medical center in Taiwan. Structural equation modeling and partial-least-squares techniques were used to evaluate relationships within the model. The modeling results indicated that both perceived ease of use and perceived usefulness were positively associated with both learner-instructor interaction and learner-system interaction. However, perceived playfulness only had a positive association with learner-system interaction and not with learner-instructor interaction. Moreover, satisfaction was positively affected by perceived ease of use, perceived usefulness, and perceived playfulness. Thus, satisfaction positively affects continued use of the system. The data obtained by this study can be applied by researchers, designers of computer game-based learning systems, special education workers, and medical professionals. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Ni(II) complexes of arginine Schiff-bases and its interaction with DNA

    International Nuclear Information System (INIS)

    Sallam, S.A.; Abbas, A.M.

    2013-01-01

    Ni(II) complexes with Schiff-bases obtained by condensation of arginine with salicylaldehyde; 2,3-; 2,4-; 2,5-dihydroxybenzaldehyde and o-hydroxynaphthaldehyde have been synthesized using the template method in ethanol or ammonia media. They were characterized by elemental analyses, conductivity measurements, magnetic moment, UV, IR and 1 H NMR spectra as well as thermal analysis (TG, DTG and DTA). The Schiff-bases are dibasic tridentate donors and the complexes have diamagnetic square planar and octahedral structures. The complexes decompose in three steps where kinetic and thermodynamic parameters of the decomposition steps were computed. The interactions of the formed complexes with FM-DNA were monitored by UV and fluorescence spectroscopy. -- Highlights: ► Arginine Schiff-bases and their nickel(II) complexes have been synthesized. ► Magnetic and spectral data show diamagnetic square planar and octahedral complexes. ► The complexes thermally decompose in three stages. Interaction with FM-DNA shows hyperchromism with blue shift

  9. AN INDUCTIVE, INTERACTIVE AND ADAPTIVE HYBRID PROBLEM-BASED LEARNING METHODOLOGY: APPLICATION TO STATISTICS

    Directory of Open Access Journals (Sweden)

    ADA ZHENG

    2011-10-01

    Full Text Available We have developed an innovative hybrid problem-based learning (PBL methodology. The methodology has the following distinctive features: i Each complex question was decomposed into a set of coherent finer subquestions by following the carefully designed criteria to maintain a delicate balance between guiding the students and inspiring them to think independently. This learning methodology enabled the students to solve the complex questions progressively in an inductive context. ii Facilitated by the utilization of our web-based learning systems, the teacher was able to interact with the students intensively and could allocate more teaching time to provide tailor-made feedback for individual student. The students were actively engaged in the learning activities, stimulated by the intensive interaction. iii The answers submitted by the students could be automatically consolidated in the report of the Moodle system in real-time. The teacher could adjust the teaching schedule and focus of the class to adapt to the learning progress of the students by analysing the automatically generated report and log files of the web-based learning system. As a result, the attendance rate of the students increased from about 50% to more than 90%, and the students’ learning motivation have been significantly enhanced.

  10. Estimating Development Cost of an Interactive Website Based Cancer Screening Promotion Program

    Science.gov (United States)

    Lairson, David R.; Chung, Tong Han; Smith, Lisa G.; Springston, Jeffrey K.; Champion, Victoria L.

    2015-01-01

    Objectives The aim of this study was to estimate the initial development costs for an innovative talk show format tailored intervention delivered via the interactive web, for increasing cancer screening in women 50 to 75 who were non-adherent to screening guidelines for colorectal cancer and/or breast cancer. Methods The cost of the intervention development was estimated from a societal perspective. Micro costing methods plus vendor contract costs were used to estimate cost. Staff logs were used to track personnel time. Non-personnel costs include all additional resources used to produce the intervention. Results Development cost of the interactive web based intervention was $.39 million, of which 77% was direct cost. About 98% of the cost was incurred in personnel time cost, contract cost and overhead cost. Conclusions The new web-based disease prevention medium required substantial investment in health promotion and media specialist time. The development cost was primarily driven by the high level of human capital required. The cost of intervention development is important information for assessing and planning future public and private investments in web-based health promotion interventions. PMID:25749548

  11. Thermodynamic activity-based intrinsic enzyme kinetic sheds light on enzyme-solvent interactions.

    Science.gov (United States)

    Grosch, Jan-Hendrik; Wagner, David; Nistelkas, Vasilios; Spieß, Antje C

    2017-01-01

    The reaction medium has major impact on biocatalytic reaction systems and on their economic significance. To allow for tailored medium engineering, thermodynamic phenomena, intrinsic enzyme kinetics, and enzyme-solvent interactions have to be discriminated. To this end, enzyme reaction kinetic modeling was coupled with thermodynamic calculations based on investigations of the alcohol dehydrogenase from Lactobacillus brevis (LbADH) in monophasic water/methyl tert-butyl ether (MTBE) mixtures as a model solvent. Substrate concentrations and substrate thermodynamic activities were varied separately to identify the individual thermodynamic and kinetic effects on the enzyme activity. Microkinetic parameters based on concentration and thermodynamic activity were derived to successfully identify a positive effect of MTBE on the availability of the substrate to the enzyme, but a negative effect on the enzyme performance. In conclusion, thermodynamic activity-based kinetic modeling might be a suitable tool to initially curtail the type of enzyme-solvent interactions and thus, a powerful first step to potentially understand the phenomena that occur in nonconventional media in more detail. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 33:96-103, 2017. © 2016 American Institute of Chemical Engineers.

  12. eTOX ALLIES: an automated pipeLine for linear interaction energy-based simulations.

    Science.gov (United States)

    Capoferri, Luigi; van Dijk, Marc; Rustenburg, Ariën S; Wassenaar, Tsjerk A; Kooi, Derk P; Rifai, Eko A; Vermeulen, Nico P E; Geerke, Daan P

    2017-11-21

    Computational methods to predict binding affinities of small ligands toward relevant biological (off-)targets are helpful in prioritizing the screening and synthesis of new drug candidates, thereby speeding up the drug discovery process. However, use of ligand-based approaches can lead to erroneous predictions when structural and dynamic features of the target substantially affect ligand binding. Free energy methods for affinity computation can include steric and electrostatic protein-ligand interactions, solvent effects, and thermal fluctuations, but often they are computationally demanding and require a high level of supervision. As a result their application is typically limited to the screening of small sets of compounds by experts in molecular modeling. We have developed eTOX ALLIES, an open source framework that allows the automated prediction of ligand-binding free energies requiring the ligand structure as only input. eTOX ALLIES is based on the linear interaction energy approach, an efficient end-point free energy method derived from Free Energy Perturbation theory. Upon submission of a ligand or dataset of compounds, the tool performs the multiple steps required for binding free-energy prediction (docking, ligand topology creation, molecular dynamics simulations, data analysis), making use of external open source software where necessary. Moreover, functionalities are also available to enable and assist the creation and calibration of new models. In addition, a web graphical user interface has been developed to allow use of free-energy based models to users that are not an expert in molecular modeling. Because of the user-friendliness, efficiency and free-software licensing, eTOX ALLIES represents a novel extension of the toolbox for computational chemists, pharmaceutical scientists and toxicologists, who are interested in fast affinity predictions of small molecules toward biological (off-)targets for which protein flexibility, solvent and binding site

  13. Interactive Multimedia-Based Animation: A Study of Effectiveness on Fashion Design Technology Learning

    Science.gov (United States)

    Wiana, W.

    2018-01-01

    The learning process is believed will reach optimal results if facilitated by diversity of learning’s device from aspects of the approach, method, media or it’s evaluation system, in individually, groups, or as well as classical. One of the learning’s Device can be developed in an attempt to improve the results of the study is Computer Based Learning (CBL). CBL was developed aim to help students to understand the concepts of the learning material which presented interactively by the system and able to provide information and learning process better. This research is closely related to efforts to improve the quality of Fashion design in digital format learning, with specific targets to generate interactive multimedia-based animation as effective media and learning resources for fashion design learning. Applications that are generated may be an option for delivering learning material as well as to engender interest in learning as well as understanding with students against the subject matter so that it can improve the learning achievements of students. The instruments used to collect data is a test sheet of mastering the concept which developed on the basis of indicators understanding the concept of fashion design, the material elements and principles of fashion design as well as application on making fashion design. As for the skills test is done through test performance to making fashion design in digital format. The results of testing against the mastery of concepts and skills of fashion designing in digital formatted shows that experimental group obtained significantly higher qualifications compared to the control group. That means that the use of interactive multimedia-based animation, effective to increased mastery of concepts and skills on making fashion design in digital format.

  14. Supporting High School Student Accomplishment of Biology Content Using Interactive Computer-Based Curricular Case Studies

    Science.gov (United States)

    Oliver, Joseph Steve; Hodges, Georgia W.; Moore, James N.; Cohen, Allan; Jang, Yoonsun; Brown, Scott A.; Kwon, Kyung A.; Jeong, Sophia; Raven, Sara P.; Jurkiewicz, Melissa; Robertson, Tom P.

    2017-11-01

    Research into the efficacy of modules featuring dynamic visualizations, case studies, and interactive learning environments is reported here. This quasi-experimental 2-year study examined the implementation of three interactive computer-based instructional modules within a curricular unit covering cellular biology concepts in an introductory high school biology course. The modules featured dynamic visualizations and focused on three processes that underlie much of cellular biology: diffusion, osmosis, and filtration. Pre-tests and post-tests were used to assess knowledge growth across the unit. A mixture Rasch model analysis of the post-test data revealed two groups of students. In both years of the study, a large proportion of the students were classified as low-achieving based on their pre-test scores. The use of the modules in the Cell Unit in year 2 was associated with a much larger proportion of the students having transitioned to the high-achieving group than in year 1. In year 2, the same teachers taught the same concepts as year 1 but incorporated the interactive computer-based modules into the cell biology unit of the curriculum. In year 2, 67% of students initially classified as low-achieving were classified as high-achieving at the end of the unit. Examination of responses to assessments embedded within the modules as well as post-test items linked transition to the high-achieving group with correct responses to items that both referenced the visualization and the contextualization of that visualization within the module. This study points to the importance of dynamic visualization within contextualized case studies as a means to support student knowledge acquisition in biology.

  15. A mobile telephone-based interactive self-care system improves asthma control.

    Science.gov (United States)

    Liu, W-T; Huang, C-D; Wang, C-H; Lee, K-Y; Lin, S-M; Kuo, H-P

    2011-02-01

    The self-management of asthma can improve clinical outcomes. Recently, mobile telephones have been widely used as an efficient, instant personal communication tool. This study investigated whether a self-care system will achieve better asthma control through a mobile telephone-based interactive programme. This was a prospective, controlled study in outpatient clinics. From 120 consecutive patients with moderate-to-severe persistent asthma, 89 were eventually recruited for the study, with 43 in the mobile telephone group (with a mobile telephone-based interactive asthma self-care system). In the mobile telephone group, mean ± sem peak expiratory flow rate significantly increased at 4 (378.2 ± 9.3 L·min⁻¹; n = 43; p = 0.020), 5 (378.2 ± 9.2 L·min⁻¹; n = 43; p = 0.008) and 6 months (382.7 ± 8.6 L·min⁻¹; n = 43; p = 0.001) compared to the control group. Mean±sem forced expiratory volume in 1 s significantly increased at 6 months (65.2 ± 3.2% predicted; n = 43; p telephone group had better quality of life after 3 months, as determined using the Short Form-12® physical component score, and fewer episodes of exacerbation and unscheduled visits than the control group. Patients in the mobile telephone group significantly increased their mean daily dose of either systemic or inhaled corticosteroids compared with the control group. The mobile telephone-based interactive self-care system provides a convenient and practical self-monitoring and -management of asthma, and improves asthma control.

  16. Simple Interactions: Piloting a Strengths-Based and Interaction-Based Professional Development Intervention for Out-of-School Time Programs

    Science.gov (United States)

    Akiva, Thomas; Li, Junlei; Martin, Kelly M.; Horner, Christy Galletta; McNamara, Anne R.

    2017-01-01

    Background: Adult-child relational interactions constitute an essential component of out-of-school-time programs, and training staff to effectively interact with children is key to improving program quality. Efficient staff training, that meets the limited time availability of out-of-school time staff, is particularly needed. Objective: This pilot…

  17. Spin wave mediated interaction as a mechanism of pairs formation in iron-based superconductors

    Science.gov (United States)

    Lima, Leonardo S.

    2018-03-01

    The spin wave mediated interaction between electrons has been proposed as mechanism to formation of electron pairs in iron-based superconductors. We employe the diagrammatic expansion to calculate the binding energy of electrons pairs mediated by spin wave. Therefore, we propose the coupling of electrons in high-temperature superconductors mediated by spin waves, since that is well known that this class of superconductors materials if relates with spin-1/2 two-dimensional antiferromagnets, where it is well known there be an interplay between antiferromagnetism 2D and high-temperature superconductivity.

  18. Interactive, three dimensional, CT-based treatment planning of stereotaxic I-125 brain implants. 132

    International Nuclear Information System (INIS)

    Lulu, B.; Lewis, J.; Smith, V.; Stuart, A.

    1987-01-01

    Brain implants of I-125 seeds are done with the Brown-Roberts-Wells stereotaxic frame. The patient is CT scanned with the frame bolted to the skull. In the time between the scan and surgery, while the patient is under anesthesia, an interactive three dimensional CT-based treatment plan is performed on a VAX computer. The program is menu driven, easy to use, and easily modifiable. Device dependencies are limited to a small number of subroutines, and an array processor is used to speed dose calculations

  19. EPRI compact analyzer: A compact, interactive and color-graphics based simulator for power plant analysis

    International Nuclear Information System (INIS)

    Ipakchi, A.; Khadem, M.; Chen, H.; Colley, R.W.

    1986-01-01

    This paper presents the results of an EPRI sponsored project (RP2395-2) for design and development of an interactive, and color graphics based simulator for power plant analysis. The system is called Compact Analyzer and can be applied to engineering and training applications in the utility industry. The Compact Analyzer's software and system design are described. Results of two demonstration system for a nuclear plant, and a fossil plant are presented, and the applications of the Compact Analyzer to operating procedures evaluation are discussed

  20. Fluid-structure interaction-based biomechanical perception model for tactile sensing.

    Directory of Open Access Journals (Sweden)

    Zheng Wang

    Full Text Available The reproduced tactile sensation of haptic interfaces usually selectively reproduces a certain object attribute, such as the object's material reflected by vibration and its surface shape by a pneumatic nozzle array. Tactile biomechanics investigates the relation between responses to an external load stimulus and tactile perception and guides the design of haptic interface devices via a tactile mechanism. Focusing on the pneumatic haptic interface, we established a fluid-structure interaction-based biomechanical model of responses to static and dynamic loads and conducted numerical simulation and experiments. This model provides a theoretical basis for designing haptic interfaces and reproducing tactile textures.