WorldWideScience

Sample records for multiple analysis approach

  1. Approaches to data analysis of multiple-choice questions

    OpenAIRE

    Lin Ding; Robert Beichner

    2009-01-01

    This paper introduces five commonly used approaches to analyzing multiple-choice test data. They are classical test theory, factor analysis, cluster analysis, item response theory, and model analysis. Brief descriptions of the goals and algorithms of these approaches are provided, together with examples illustrating their applications in physics education research. We minimize mathematics, instead placing emphasis on data interpretation using these approaches.

  2. Approaches to Data Analysis of Multiple-Choice Questions

    Science.gov (United States)

    Ding, Lin; Beichner, Robert

    2009-01-01

    This paper introduces five commonly used approaches to analyzing multiple-choice test data. They are classical test theory, factor analysis, cluster analysis, item response theory, and model analysis. Brief descriptions of the goals and algorithms of these approaches are provided, together with examples illustrating their applications in physics…

  3. Approaches to data analysis of multiple-choice questions

    Directory of Open Access Journals (Sweden)

    Lin Ding

    2009-09-01

    Full Text Available This paper introduces five commonly used approaches to analyzing multiple-choice test data. They are classical test theory, factor analysis, cluster analysis, item response theory, and model analysis. Brief descriptions of the goals and algorithms of these approaches are provided, together with examples illustrating their applications in physics education research. We minimize mathematics, instead placing emphasis on data interpretation using these approaches.

  4. A Unified Approach to Functional Principal Component Analysis and Functional Multiple-Set Canonical Correlation.

    Science.gov (United States)

    Choi, Ji Yeh; Hwang, Heungsun; Yamamoto, Michio; Jung, Kwanghee; Woodward, Todd S

    2017-06-01

    Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space. In FPCA, low-dimensional components are extracted from a single functional dataset such that they explain the most variance of the dataset, whereas in FMCCA, low-dimensional components are obtained from each of multiple functional datasets in such a way that the associations among the components are maximized across the different sets. In this paper, we propose a unified approach to FPCA and FMCCA. The proposed approach subsumes both techniques as special cases. Furthermore, it permits a compromise between the techniques, such that components are obtained from each set of functional data to maximize their associations across different datasets, while accounting for the variance of the data well. We propose a single optimization criterion for the proposed approach, and develop an alternating regularized least squares algorithm to minimize the criterion in combination with basis function approximations to functions. We conduct a simulation study to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of multiple-subject functional magnetic resonance imaging data to obtain low-dimensional components of blood-oxygen level-dependent signal changes of the brain over time, which are highly correlated across the subjects as well as representative of the data. The extracted components are used to identify networks of neural activity that are commonly activated across the subjects while carrying out a working memory task.

  5. Novel Approach to Tourism Analysis with Multiple Outcome Capability Using Rough Set Theory

    Directory of Open Access Journals (Sweden)

    Chun-Che Huang

    2016-12-01

    Full Text Available To explore the relationship between characteristics and decision-making outcomes of the tourist is critical to keep competitive tourism business. In investigation of tourism development, most of the existing studies lack of a systematic approach to analyze qualitative data. Although the traditional Rough Set (RS based approach is an excellent classification method in qualitative modeling, but it is canarsquo;t deal with the case of multiple outcomes, which is a common situation in tourism. Consequently, the Multiple Outcome Reduct Generation (MORG and Multiple Outcome Rule Extraction (MORE approaches based on RS to handle multiple outcomes are proposed. This study proposes a ranking based approach to induct meaningful reducts and ensure the strength and robustness of decision rules, which helps decision makers understand touristarsquo;s characteristics in a tourism case.

  6. MANGO: a new approach to multiple sequence alignment.

    Science.gov (United States)

    Zhang, Zefeng; Lin, Hao; Li, Ming

    2007-01-01

    Multiple sequence alignment is a classical and challenging task for biological sequence analysis. The problem is NP-hard. The full dynamic programming takes too much time. The progressive alignment heuristics adopted by most state of the art multiple sequence alignment programs suffer from the 'once a gap, always a gap' phenomenon. Is there a radically new way to do multiple sequence alignment? This paper introduces a novel and orthogonal multiple sequence alignment method, using multiple optimized spaced seeds and new algorithms to handle these seeds efficiently. Our new algorithm processes information of all sequences as a whole, avoiding problems caused by the popular progressive approaches. Because the optimized spaced seeds are provably significantly more sensitive than the consecutive k-mers, the new approach promises to be more accurate and reliable. To validate our new approach, we have implemented MANGO: Multiple Alignment with N Gapped Oligos. Experiments were carried out on large 16S RNA benchmarks showing that MANGO compares favorably, in both accuracy and speed, against state-of-art multiple sequence alignment methods, including ClustalW 1.83, MUSCLE 3.6, MAFFT 5.861, Prob-ConsRNA 1.11, Dialign 2.2.1, DIALIGN-T 0.2.1, T-Coffee 4.85, POA 2.0 and Kalign 2.0.

  7. A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Multiple Myeloma.

    Science.gov (United States)

    Raju, G K; Gurumurthi, Karthik; Domike, Reuben; Kazandjian, Dickran; Landgren, Ola; Blumenthal, Gideon M; Farrell, Ann; Pazdur, Richard; Woodcock, Janet

    2018-01-01

    Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analysis. In this work, a quantitative benefit-risk analysis approach captures regulatory decision-making about new drugs to treat multiple myeloma (MM). MM assessments have been based on endpoints such as time to progression (TTP), progression-free survival (PFS), and objective response rate (ORR) which are different than benefit-risk analysis based on overall survival (OS). Twenty-three FDA decisions on MM drugs submitted to FDA between 2003 and 2016 were identified and analyzed. The benefits and risks were quantified relative to comparators (typically the control arm of the clinical trial) to estimate whether the median benefit-risk was positive or negative. A sensitivity analysis was demonstrated using ixazomib to explore the magnitude of uncertainty. FDA approval decision outcomes were consistent and logical using this benefit-risk framework. © 2017 American Society for Clinical Pharmacology and Therapeutics.

  8. Applied immuno-epidemiological research: an approach for integrating existing knowledge into the statistical analysis of multiple immune markers.

    Science.gov (United States)

    Genser, Bernd; Fischer, Joachim E; Figueiredo, Camila A; Alcântara-Neves, Neuza; Barreto, Mauricio L; Cooper, Philip J; Amorim, Leila D; Saemann, Marcus D; Weichhart, Thomas; Rodrigues, Laura C

    2016-05-20

    Immunologists often measure several correlated immunological markers, such as concentrations of different cytokines produced by different immune cells and/or measured under different conditions, to draw insights from complex immunological mechanisms. Although there have been recent methodological efforts to improve the statistical analysis of immunological data, a framework is still needed for the simultaneous analysis of multiple, often correlated, immune markers. This framework would allow the immunologists' hypotheses about the underlying biological mechanisms to be integrated. We present an analytical approach for statistical analysis of correlated immune markers, such as those commonly collected in modern immuno-epidemiological studies. We demonstrate i) how to deal with interdependencies among multiple measurements of the same immune marker, ii) how to analyse association patterns among different markers, iii) how to aggregate different measures and/or markers to immunological summary scores, iv) how to model the inter-relationships among these scores, and v) how to use these scores in epidemiological association analyses. We illustrate the application of our approach to multiple cytokine measurements from 818 children enrolled in a large immuno-epidemiological study (SCAALA Salvador), which aimed to quantify the major immunological mechanisms underlying atopic diseases or asthma. We demonstrate how to aggregate systematically the information captured in multiple cytokine measurements to immunological summary scores aimed at reflecting the presumed underlying immunological mechanisms (Th1/Th2 balance and immune regulatory network). We show how these aggregated immune scores can be used as predictors in regression models with outcomes of immunological studies (e.g. specific IgE) and compare the results to those obtained by a traditional multivariate regression approach. The proposed analytical approach may be especially useful to quantify complex immune

  9. Association analysis of multiple traits by an approach of combining ...

    Indian Academy of Sciences (India)

    Lili Chen

    diseases. Joint analysis of multiple traits can increase statistical power of association analysis and uncover the underlying genetic ... genthaler and Thilly 2007), the combined multivariate and ... Because of using reverse regression model, our.

  10. Simultaneous Two-Way Clustering of Multiple Correspondence Analysis

    Science.gov (United States)

    Hwang, Heungsun; Dillon, William R.

    2010-01-01

    A 2-way clustering approach to multiple correspondence analysis is proposed to account for cluster-level heterogeneity of both respondents and variable categories in multivariate categorical data. Specifically, in the proposed method, multiple correspondence analysis is combined with k-means in a unified framework in which "k"-means is…

  11. Systematic Analysis of the Multiple Bioactivities of Green Tea through a Network Pharmacology Approach

    Directory of Open Access Journals (Sweden)

    Shoude Zhang

    2014-01-01

    Full Text Available During the past decades, a number of studies have demonstrated multiple beneficial health effects of green tea. Polyphenolics are the most biologically active components of green tea. Many targets can be targeted or affected by polyphenolics. In this study, we excavated all of the targets of green tea polyphenolics (GTPs though literature mining and target calculation and analyzed the multiple pharmacology actions of green tea comprehensively through a network pharmacology approach. In the end, a total of 200 Homo sapiens targets were identified for fifteen GTPs. These targets were classified into six groups according to their related disease, which included cancer, diabetes, neurodegenerative disease, cardiovascular disease, muscular disease, and inflammation. Moreover, these targets mapped into 143 KEGG pathways, 26 of which were more enriched, as determined though pathway enrichment analysis and target-pathway network analysis. Among the identified pathways, 20 pathways were selected for analyzing the mechanisms of green tea in these diseases. Overall, this study systematically illustrated the mechanisms of the pleiotropic activity of green tea by analyzing the corresponding “drug-target-pathway-disease” interaction network.

  12. A Semiparametric Bayesian Approach for Analyzing Longitudinal Data from Multiple Related Groups.

    Science.gov (United States)

    Das, Kiranmoy; Afriyie, Prince; Spirko, Lauren

    2015-11-01

    Often the biological and/or clinical experiments result in longitudinal data from multiple related groups. The analysis of such data is quite challenging due to the fact that groups might have shared information on the mean and/or covariance functions. In this article, we consider a Bayesian semiparametric approach of modeling the mean trajectories for longitudinal response coming from multiple related groups. We consider matrix stick-breaking process priors on the group mean parameters which allows information sharing on the mean trajectories across the groups. Simulation studies are performed to demonstrate the effectiveness of the proposed approach compared to the more traditional approaches. We analyze data from a one-year follow-up of nutrition education for hypercholesterolemic children with three different treatments where the children are from different age-groups. Our analysis provides more clinically useful information than the previous analysis of the same dataset. The proposed approach will be a very powerful tool for analyzing data from clinical trials and other medical experiments.

  13. More basic approach to the analysis of multiple specimen R-curves for determination of J/sub c/

    International Nuclear Information System (INIS)

    Carlson, K.W.; Williams, J.A.

    1980-02-01

    Multiple specimen J-R curves were developed for groups of 1T compact specimens with different a/W values and depth of side grooving. The purpose of this investigation was to determine J/sub c/ (J at onset of crack extension) for each group. Judicious selection of points on the load versus load-line deflection record at which to unload and heat tint specimens permitted direct observation of approximate onset of crack extension. It was found that the present recommended procedure for determining J/sub c/ from multiple specimen R-curves, which is being considered for standardization, consistently yielded nonconservative J/sub c/ values. A more basic approach to analyzing multiple specimen R-curves is presented, applied, and discussed. This analysis determined J/sub c/ values that closely corresponded to actual observed onset of crack extension

  14. Approach to proliferation risk assessment based on multiple objective analysis framework

    Energy Technology Data Exchange (ETDEWEB)

    Andrianov, A.; Kuptsov, I. [Obninsk Institute for Nuclear Power Engineering of NNRU MEPhI (Russian Federation); Studgorodok 1, Obninsk, Kaluga region, 249030 (Russian Federation)

    2013-07-01

    The approach to the assessment of proliferation risk using the methods of multi-criteria decision making and multi-objective optimization is presented. The approach allows the taking into account of the specifics features of the national nuclear infrastructure, and possible proliferation strategies (motivations, intentions, and capabilities). 3 examples of applying the approach are shown. First, the approach has been used to evaluate the attractiveness of HEU (high enriched uranium)production scenarios at a clandestine enrichment facility using centrifuge enrichment technology. Secondly, the approach has been applied to assess the attractiveness of scenarios for undeclared production of plutonium or HEU by theft of materials circulating in nuclear fuel cycle facilities and thermal reactors. Thirdly, the approach has been used to perform a comparative analysis of the structures of developing nuclear power systems based on different types of nuclear fuel cycles, the analysis being based on indicators of proliferation risk.

  15. Approach to proliferation risk assessment based on multiple objective analysis framework

    International Nuclear Information System (INIS)

    Andrianov, A.; Kuptsov, I.

    2013-01-01

    The approach to the assessment of proliferation risk using the methods of multi-criteria decision making and multi-objective optimization is presented. The approach allows the taking into account of the specifics features of the national nuclear infrastructure, and possible proliferation strategies (motivations, intentions, and capabilities). 3 examples of applying the approach are shown. First, the approach has been used to evaluate the attractiveness of HEU (high enriched uranium)production scenarios at a clandestine enrichment facility using centrifuge enrichment technology. Secondly, the approach has been applied to assess the attractiveness of scenarios for undeclared production of plutonium or HEU by theft of materials circulating in nuclear fuel cycle facilities and thermal reactors. Thirdly, the approach has been used to perform a comparative analysis of the structures of developing nuclear power systems based on different types of nuclear fuel cycles, the analysis being based on indicators of proliferation risk

  16. Sparse Group Penalized Integrative Analysis of Multiple Cancer Prognosis Datasets

    Science.gov (United States)

    Liu, Jin; Huang, Jian; Xie, Yang; Ma, Shuangge

    2014-01-01

    SUMMARY In cancer research, high-throughput profiling studies have been extensively conducted, searching for markers associated with prognosis. Because of the “large d, small n” characteristic, results generated from the analysis of a single dataset can be unsatisfactory. Recent studies have shown that integrative analysis, which simultaneously analyzes multiple datasets, can be more effective than single-dataset analysis and classic meta-analysis. In most of existing integrative analysis, the homogeneity model has been assumed, which postulates that different datasets share the same set of markers. Several approaches have been designed to reinforce this assumption. In practice, different datasets may differ in terms of patient selection criteria, profiling techniques, and many other aspects. Such differences may make the homogeneity model too restricted. In this study, we assume the heterogeneity model, under which different datasets are allowed to have different sets of markers. With multiple cancer prognosis datasets, we adopt the AFT (accelerated failure time) model to describe survival. This model may have the lowest computational cost among popular semiparametric survival models. For marker selection, we adopt a sparse group MCP (minimax concave penalty) approach. This approach has an intuitive formulation and can be computed using an effective group coordinate descent algorithm. Simulation study shows that it outperforms the existing approaches under both the homogeneity and heterogeneity models. Data analysis further demonstrates the merit of heterogeneity model and proposed approach. PMID:23938111

  17. The Health Action Process Approach as a Motivational Model of Dietary Self-Management for People with Multiple Sclerosis: A Path Analysis

    Science.gov (United States)

    Chiu, Chung-Yi; Lynch, Ruth Torkelson; Chan, Fong; Rose, Lindsey

    2012-01-01

    The main objective of this study was to evaluate the health action process approach (HAPA) as a motivational model for dietary self-management for people with multiple sclerosis (MS). Quantitative descriptive research design using path analysis was used. Participants were 209 individuals with MS recruited from the National MS Society and a…

  18. Mediation Analysis with Multiple Mediators

    OpenAIRE

    VanderWeele, T.J.; Vansteelandt, S.

    2014-01-01

    Recent advances in the causal inference literature on mediation have extended traditional approaches to direct and indirect effects to settings that allow for interactions and non-linearities. In this paper, these approaches from causal inference are further extended to settings in which multiple mediators may be of interest. Two analytic approaches, one based on regression and one based on weighting are proposed to estimate the effect mediated through multiple mediators and the effects throu...

  19. Modular risk analysis for assessing multiple waste sites

    International Nuclear Information System (INIS)

    Whelan, G.; Buck, J.W.; Nazarali, A.

    1994-06-01

    Human-health impacts, especially to the surrounding public, are extremely difficult to assess at installations that contain multiple waste sites and a variety of mixed-waste constituents (e.g., organic, inorganic, and radioactive). These assessments must address different constituents, multiple waste sites, multiple release patterns, different transport pathways (i.e., groundwater, surface water, air, and overland soil), different receptor types and locations, various times of interest, population distributions, land-use patterns, baseline assessments, a variety of exposure scenarios, etc. Although the process is complex, two of the most important difficulties to overcome are associated with (1) establishing an approach that allows for modifying the source term, transport, or exposure component as an individual module without having to re-evaluate the entire installation-wide assessment (i.e., all modules simultaneously), and (2) displaying and communicating the results in an understandable and useable maimer to interested parties. An integrated, physics-based, compartmentalized approach, which is coupled to a Geographical Information System (GIS), captures the regional health impacts associated with multiple waste sites (e.g., hundreds to thousands of waste sites) at locations within and surrounding the installation. Utilizing a modular/GIS-based approach overcomes difficulties in (1) analyzing a wide variety of scenarios for multiple waste sites, and (2) communicating results from a complex human-health-impact analysis by capturing the essence of the assessment in a relatively elegant manner, so the meaning of the results can be quickly conveyed to all who review them

  20. Two-Way Regularized Fuzzy Clustering of Multiple Correspondence Analysis.

    Science.gov (United States)

    Kim, Sunmee; Choi, Ji Yeh; Hwang, Heungsun

    2017-01-01

    Multiple correspondence analysis (MCA) is a useful tool for investigating the interrelationships among dummy-coded categorical variables. MCA has been combined with clustering methods to examine whether there exist heterogeneous subclusters of a population, which exhibit cluster-level heterogeneity. These combined approaches aim to classify either observations only (one-way clustering of MCA) or both observations and variable categories (two-way clustering of MCA). The latter approach is favored because its solutions are easier to interpret by providing explicitly which subgroup of observations is associated with which subset of variable categories. Nonetheless, the two-way approach has been built on hard classification that assumes observations and/or variable categories to belong to only one cluster. To relax this assumption, we propose two-way fuzzy clustering of MCA. Specifically, we combine MCA with fuzzy k-means simultaneously to classify a subgroup of observations and a subset of variable categories into a common cluster, while allowing both observations and variable categories to belong partially to multiple clusters. Importantly, we adopt regularized fuzzy k-means, thereby enabling us to decide the degree of fuzziness in cluster memberships automatically. We evaluate the performance of the proposed approach through the analysis of simulated and real data, in comparison with existing two-way clustering approaches.

  1. Multiple Imputation of a Randomly Censored Covariate Improves Logistic Regression Analysis.

    Science.gov (United States)

    Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A

    2016-01-01

    Randomly censored covariates arise frequently in epidemiologic studies. The most commonly used methods, including complete case and single imputation or substitution, suffer from inefficiency and bias. They make strong parametric assumptions or they consider limit of detection censoring only. We employ multiple imputation, in conjunction with semi-parametric modeling of the censored covariate, to overcome these shortcomings and to facilitate robust estimation. We develop a multiple imputation approach for randomly censored covariates within the framework of a logistic regression model. We use the non-parametric estimate of the covariate distribution or the semiparametric Cox model estimate in the presence of additional covariates in the model. We evaluate this procedure in simulations, and compare its operating characteristics to those from the complete case analysis and a survival regression approach. We apply the procedures to an Alzheimer's study of the association between amyloid positivity and maternal age of onset of dementia. Multiple imputation achieves lower standard errors and higher power than the complete case approach under heavy and moderate censoring and is comparable under light censoring. The survival regression approach achieves the highest power among all procedures, but does not produce interpretable estimates of association. Multiple imputation offers a favorable alternative to complete case analysis and ad hoc substitution methods in the presence of randomly censored covariates within the framework of logistic regression.

  2. Methodological issues underlying multiple decrement life table analysis.

    Science.gov (United States)

    Mode, C J; Avery, R C; Littman, G S; Potter, R G

    1977-02-01

    In this paper, the actuarial method of multiple decrement life table analysis of censored, longitudinal data is examined. The discussion is organized in terms of the first segment of usage of an intrauterine device. Weaknesses of the actuarial approach are pointed out, and an alternative approach, based on the classical model of competing risks, is proposed. Finally, the actuarial and the alternative method of analyzing censored data are compared, using data from the Taichung Medical Study on Intrauterine Devices.

  3. Mediation Analysis with Multiple Mediators.

    Science.gov (United States)

    VanderWeele, T J; Vansteelandt, S

    2014-01-01

    Recent advances in the causal inference literature on mediation have extended traditional approaches to direct and indirect effects to settings that allow for interactions and non-linearities. In this paper, these approaches from causal inference are further extended to settings in which multiple mediators may be of interest. Two analytic approaches, one based on regression and one based on weighting are proposed to estimate the effect mediated through multiple mediators and the effects through other pathways. The approaches proposed here accommodate exposure-mediator interactions and, to a certain extent, mediator-mediator interactions as well. The methods handle binary or continuous mediators and binary, continuous or count outcomes. When the mediators affect one another, the strategy of trying to assess direct and indirect effects one mediator at a time will in general fail; the approach given in this paper can still be used. A characterization is moreover given as to when the sum of the mediated effects for multiple mediators considered separately will be equal to the mediated effect of all of the mediators considered jointly. The approach proposed in this paper is robust to unmeasured common causes of two or more mediators.

  4. Neutron Multiplicity Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Frame, Katherine Chiyoko [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-06-28

    Neutron multiplicity measurements are widely used for nondestructive assay (NDA) of special nuclear material (SNM). When combined with isotopic composition information, neutron multiplicity analysis can be used to estimate the spontaneous fission rate and leakage multiplication of SNM. When combined with isotopic information, the total mass of fissile material can also be determined. This presentation provides an overview of this technique.

  5. A time warping approach to multiple sequence alignment.

    Science.gov (United States)

    Arribas-Gil, Ana; Matias, Catherine

    2017-04-25

    We propose an approach for multiple sequence alignment (MSA) derived from the dynamic time warping viewpoint and recent techniques of curve synchronization developed in the context of functional data analysis. Starting from pairwise alignments of all the sequences (viewed as paths in a certain space), we construct a median path that represents the MSA we are looking for. We establish a proof of concept that our method could be an interesting ingredient to include into refined MSA techniques. We present a simple synthetic experiment as well as the study of a benchmark dataset, together with comparisons with 2 widely used MSA softwares.

  6. Neophyte experiences of football (soccer) match analysis: a multiple case study approach.

    Science.gov (United States)

    McKenna, Mark; Cowan, Daryl Thomas; Stevenson, David; Baker, Julien Steven

    2018-03-05

    Performance analysis is extensively used in sport, but its pedagogical application is little understood. Given its expanding role across football, this study explored the experiences of neophyte performance analysts. Experiences of six analysis interns, across three professional football clubs, were investigated as multiple cases of new match analysis. Each intern was interviewed after their first season, with archival data providing background information. Four themes emerged from qualitative analysis: (1) "building of relationships" was important, along with trust and role clarity; (2) "establishing an analysis system" was difficult due to tacit coach knowledge, but analysis was established; (3) the quality of the "feedback process" hinged on coaching styles, with balance of feedback and athlete engagement considered essential; (4) "establishing effect" was complex with no statistical effects reported; yet enhanced relationships, role clarity, and improved performances were reported. Other emic accounts are required to further understand occupational culture within performance analysis.

  7. Drug induced mortality: a multiple cause approach on Italian causes of death Register

    Directory of Open Access Journals (Sweden)

    Francesco Grippo

    2015-04-01

    Full Text Available Background: Drug-related mortality is a complex phenomenon that has several health, social and economic effects. In this paper trends of drug-induced mortality in Italy are analysed. Two approaches have been followed: the traditional analysis of the underlying cause of death (UC (data refers to the Istat mortality database from 1980 to 2011, and the multiple cause (MCanalysis, that is the analysis of all conditions reported on the death certificate (data for 2003-2011 period.Methods: Data presented in this paper are based on the Italian mortality register. The selection of Icd codes used for the analysis follows the definition of the European Monitoring Centre for Drugs and Drug Addiction. Using different indicators (crude and standardized rates, ratio multiple to underlying, the results obtained from the two approaches (UC and MC have been compared. Moreover, as a measure of association between drug-related causes and specific conditions on the death certificate, an estimation of the age-standardized relative risk (RR has been used.Results: In the years 2009-2011, the total number of certificates whit mention of drug use was 1,293, 60% higher than the number UC based. The groups of conditions more strongly associated with drug-related causes are the mental and behavioral disorders (especially alcohol consumption, viral hepatitis, cirrhosis and fibrosis of liver, AIDS and endocarditis.Conclusions : The analysis based on multiple cause approach shows, for the first time, a more detailed picture of the drug related death; it allows to better describe the mortality profiles and to re-evaluate  the contribution of a specific cause to death.

  8. Optimal planning of multiple distributed generation sources in distribution networks: A new approach

    Energy Technology Data Exchange (ETDEWEB)

    AlRashidi, M.R., E-mail: malrash2002@yahoo.com [Department of Electrical Engineering, College of Technological Studies, Public Authority for Applied Education and Training (PAAET) (Kuwait); AlHajri, M.F., E-mail: mfalhajri@yahoo.com [Department of Electrical Engineering, College of Technological Studies, Public Authority for Applied Education and Training (PAAET) (Kuwait)

    2011-10-15

    Highlights: {yields} A new hybrid PSO for optimal DGs placement and sizing. {yields} Statistical analysis to fine tune PSO parameters. {yields} Novel constraint handling mechanism to handle different constraints types. - Abstract: An improved particle swarm optimization algorithm (PSO) is presented for optimal planning of multiple distributed generation sources (DG). This problem can be divided into two sub-problems: the DG optimal size (continuous optimization) and location (discrete optimization) to minimize real power losses. The proposed approach addresses the two sub-problems simultaneously using an enhanced PSO algorithm capable of handling multiple DG planning in a single run. A design of experiment is used to fine tune the proposed approach via proper analysis of PSO parameters interaction. The proposed algorithm treats the problem constraints differently by adopting a radial power flow algorithm to satisfy the equality constraints, i.e. power flows in distribution networks, while the inequality constraints are handled by making use of some of the PSO features. The proposed algorithm was tested on the practical 69-bus power distribution system. Different test cases were considered to validate the proposed approach consistency in detecting optimal or near optimal solution. Results are compared with those of Sequential Quadratic Programming.

  9. Optimal planning of multiple distributed generation sources in distribution networks: A new approach

    International Nuclear Information System (INIS)

    AlRashidi, M.R.; AlHajri, M.F.

    2011-01-01

    Highlights: → A new hybrid PSO for optimal DGs placement and sizing. → Statistical analysis to fine tune PSO parameters. → Novel constraint handling mechanism to handle different constraints types. - Abstract: An improved particle swarm optimization algorithm (PSO) is presented for optimal planning of multiple distributed generation sources (DG). This problem can be divided into two sub-problems: the DG optimal size (continuous optimization) and location (discrete optimization) to minimize real power losses. The proposed approach addresses the two sub-problems simultaneously using an enhanced PSO algorithm capable of handling multiple DG planning in a single run. A design of experiment is used to fine tune the proposed approach via proper analysis of PSO parameters interaction. The proposed algorithm treats the problem constraints differently by adopting a radial power flow algorithm to satisfy the equality constraints, i.e. power flows in distribution networks, while the inequality constraints are handled by making use of some of the PSO features. The proposed algorithm was tested on the practical 69-bus power distribution system. Different test cases were considered to validate the proposed approach consistency in detecting optimal or near optimal solution. Results are compared with those of Sequential Quadratic Programming.

  10. Functional Multiple-Set Canonical Correlation Analysis

    Science.gov (United States)

    Hwang, Heungsun; Jung, Kwanghee; Takane, Yoshio; Woodward, Todd S.

    2012-01-01

    We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the…

  11. Benefit-Risk Analysis for Decision-Making: An Approach.

    Science.gov (United States)

    Raju, G K; Gurumurthi, K; Domike, R

    2016-12-01

    The analysis of benefit and risk is an important aspect of decision-making throughout the drug lifecycle. In this work, the use of a benefit-risk analysis approach to support decision-making was explored. The proposed approach builds on the qualitative US Food and Drug Administration (FDA) approach to include a more explicit analysis based on international standards and guidance that enables aggregation and comparison of benefit and risk on a common basis and a lifecycle focus. The approach is demonstrated on six decisions over the lifecycle (e.g., accelerated approval, withdrawal, and traditional approval) using two case studies: natalizumab for multiple sclerosis (MS) and bedaquiline for multidrug-resistant tuberculosis (MDR-TB). © 2016 American Society for Clinical Pharmacology and Therapeutics.

  12. A retrospective likelihood approach for efficient integration of multiple omics factors in case-control association studies.

    Science.gov (United States)

    Balliu, Brunilda; Tsonaka, Roula; Boehringer, Stefan; Houwing-Duistermaat, Jeanine

    2015-03-01

    Integrative omics, the joint analysis of outcome and multiple types of omics data, such as genomics, epigenomics, and transcriptomics data, constitute a promising approach for powerful and biologically relevant association studies. These studies often employ a case-control design, and often include nonomics covariates, such as age and gender, that may modify the underlying omics risk factors. An open question is how to best integrate multiple omics and nonomics information to maximize statistical power in case-control studies that ascertain individuals based on the phenotype. Recent work on integrative omics have used prospective approaches, modeling case-control status conditional on omics, and nonomics risk factors. Compared to univariate approaches, jointly analyzing multiple risk factors with a prospective approach increases power in nonascertained cohorts. However, these prospective approaches often lose power in case-control studies. In this article, we propose a novel statistical method for integrating multiple omics and nonomics factors in case-control association studies. Our method is based on a retrospective likelihood function that models the joint distribution of omics and nonomics factors conditional on case-control status. The new method provides accurate control of Type I error rate and has increased efficiency over prospective approaches in both simulated and real data. © 2015 Wiley Periodicals, Inc.

  13. Multiple Score Comparison: a network meta-analysis approach to comparison and external validation of prognostic scores

    Directory of Open Access Journals (Sweden)

    Sarah R. Haile

    2017-12-01

    Full Text Available Abstract Background Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them. Methods Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined. Results We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small. Conclusions We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties

  14. Sensitivity studies on the approaches for addressing multiple initiating events in fire events PSA

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Dae Il; Lim, Ho Gon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2016-10-15

    A single fire event within a fire compartment or a fire scenario can cause multiple initiating events (IEs). As an example, a fire in a turbine building fire area can cause a loss of the main feed-water (LOMF) and loss of off-site power (LOOP) IEs. Previous domestic fire events PSA had considered only the most severe initiating event among multiple initiating events. NUREG/CR-6850 and ANS/ASME PRA Standard require that multiple IEs are to be addressed in fire events PSA. In this paper, sensitivity studies on the approaches for addressing multiple IEs in fire events PSA for Hanul Unit 3 were performed and their results were presented. In this paper, sensitivity studies on the approaches for addressing multiple IEs in fire events PSA are performed and their results were presented. From the sensitivity analysis results, we can find that the incorporations of multiple IEs into fire events PSA model result in the core damage frequency (CDF) increase and may lead to the generation of the duplicate cutsets. Multiple IEs also can occur at internal flooding event or other external events such as seismic event. They should be considered in the constructions of PSA models in order to realistically estimate risk due to flooding or seismic events.

  15. Electromagnetic imaging of multiple-scattering small objects: non-iterative analytical approach

    International Nuclear Information System (INIS)

    Chen, X; Zhong, Y

    2008-01-01

    Multiple signal classification (MUSIC) imaging method and the least squares method are applied to solve the electromagnetic inverse scattering problem of determining the locations and polarization tensors of a collection of small objects embedded in a known background medium. Based on the analysis of induced electric and magnetic dipoles, the proposed MUSIC method is able to deal with some special scenarios, due to the shapes and materials of objects, to which the standard MUSIC doesn't apply. After the locations of objects are obtained, the nonlinear inverse problem of determining the polarization tensors of objects accounting for multiple scattering between objects is solved by a non-iterative analytical approach based on the least squares method

  16. 3D fluid-structure modelling and vibration analysis for fault diagnosis of Francis turbine using multiple ANN and multiple ANFIS

    Science.gov (United States)

    Saeed, R. A.; Galybin, A. N.; Popov, V.

    2013-01-01

    This paper discusses condition monitoring and fault diagnosis in Francis turbine based on integration of numerical modelling with several different artificial intelligence (AI) techniques. In this study, a numerical approach for fluid-structure (turbine runner) analysis is presented. The results of numerical analysis provide frequency response functions (FRFs) data sets along x-, y- and z-directions under different operating load and different position and size of faults in the structure. To extract features and reduce the dimensionality of the obtained FRF data, the principal component analysis (PCA) has been applied. Subsequently, the extracted features are formulated and fed into multiple artificial neural networks (ANN) and multiple adaptive neuro-fuzzy inference systems (ANFIS) in order to identify the size and position of the damage in the runner and estimate the turbine operating conditions. The results demonstrated the effectiveness of this approach and provide satisfactory accuracy even when the input data are corrupted with certain level of noise.

  17. Visualization-based analysis of multiple response survey data

    Science.gov (United States)

    Timofeeva, Anastasiia

    2017-11-01

    During the survey, the respondents are often allowed to tick more than one answer option for a question. Analysis and visualization of such data have difficulties because of the need for processing multiple response variables. With standard representation such as pie and bar charts, information about the association between different answer options is lost. The author proposes a visualization approach for multiple response variables based on Venn diagrams. For a more informative representation with a large number of overlapping groups it is suggested to use similarity and association matrices. Some aggregate indicators of dissimilarity (similarity) are proposed based on the determinant of the similarity matrix and the maximum eigenvalue of association matrix. The application of the proposed approaches is well illustrated by the example of the analysis of advertising sources. Intersection of sets indicates that the same consumer audience is covered by several advertising sources. This information is very important for the allocation of the advertising budget. The differences between target groups in advertising sources are of interest. To identify such differences the hypothesis of homogeneity and independence are tested. Recent approach to the problem are briefly reviewed and compared. An alternative procedure is suggested. It is based on partition of a consumer audience into pairwise disjoint subsets and includes hypothesis testing of the difference between the population proportions. It turned out to be more suitable for the real problem being solved.

  18. Analysis of Genome-Wide Association Studies with Multiple Outcomes Using Penalization

    Science.gov (United States)

    Liu, Jin; Huang, Jian; Ma, Shuangge

    2012-01-01

    Genome-wide association studies have been extensively conducted, searching for markers for biologically meaningful outcomes and phenotypes. Penalization methods have been adopted in the analysis of the joint effects of a large number of SNPs (single nucleotide polymorphisms) and marker identification. This study is partly motivated by the analysis of heterogeneous stock mice dataset, in which multiple correlated phenotypes and a large number of SNPs are available. Existing penalization methods designed to analyze a single response variable cannot accommodate the correlation among multiple response variables. With multiple response variables sharing the same set of markers, joint modeling is first employed to accommodate the correlation. The group Lasso approach is adopted to select markers associated with all the outcome variables. An efficient computational algorithm is developed. Simulation study and analysis of the heterogeneous stock mice dataset show that the proposed method can outperform existing penalization methods. PMID:23272092

  19. IsoGeneGUI : Multiple approaches for dose-response analysis of microarray data using R

    NARCIS (Netherlands)

    Otava, Martin; Sengupta, Rudradev; Shkedy, Ziv; Lin, Dan; Pramana, Setia; Verbeke, Tobias; Haldermans, Philippe; Hothorn, Ludwig A.; Gerhard, Daniel; Kuiper, Rebecca M.; Klinglmueller, Florian; Kasim, Adetayo

    2017-01-01

    The analysis of transcriptomic experiments with ordered covariates, such as dose-response data, has become a central topic in bioinformatics, in particular in omics studies. Consequently, multiple R packages on CRAN and Bioconductor are designed to analyse microarray data from various perspectives

  20. Filter multiplexing by use of spatial Code Division Multiple Access approach.

    Science.gov (United States)

    Solomon, Jonathan; Zalevsky, Zeev; Mendlovic, David; Monreal, Javier Garcia

    2003-02-10

    The increasing popularity of optical communication has also brought a demand for a broader bandwidth. The trend, naturally, was to implement methods from traditional electronic communication. One of the most effective traditional methods is Code Division Multiple Access. In this research, we suggest the use of this approach for spatial coding applied to images. The approach is to multiplex several filters into one plane while keeping their mutual orthogonality. It is shown that if the filters are limited by their bandwidth, the output of all the filters can be sampled in the original image resolution and fully recovered through an all-optical setup. The theoretical analysis of such a setup is verified in an experimental demonstration.

  1. Efficient surrogate models for reliability analysis of systems with multiple failure modes

    International Nuclear Information System (INIS)

    Bichon, Barron J.; McFarland, John M.; Mahadevan, Sankaran

    2011-01-01

    Despite many advances in the field of computational reliability analysis, the efficient estimation of the reliability of a system with multiple failure modes remains a persistent challenge. Various sampling and analytical methods are available, but they typically require accepting a tradeoff between accuracy and computational efficiency. In this work, a surrogate-based approach is presented that simultaneously addresses the issues of accuracy, efficiency, and unimportant failure modes. The method is based on the creation of Gaussian process surrogate models that are required to be locally accurate only in the regions of the component limit states that contribute to system failure. This approach to constructing surrogate models is demonstrated to be both an efficient and accurate method for system-level reliability analysis. - Highlights: → Extends efficient global reliability analysis to systems with multiple failure modes. → Constructs locally accurate Gaussian process models of each response. → Highly efficient and accurate method for assessing system reliability. → Effectiveness is demonstrated on several test problems from the literature.

  2. Multiple scattering approach to X-ray absorption spectroscopy

    International Nuclear Information System (INIS)

    Benfatto, M.; Wu Ziyu

    2003-01-01

    In this paper authors present the state of the art of the theoretical background needed for analyzing X-ray absorption spectra in the whole energy range. The multiple-scattering (MS) theory is presented in detail with some applications on real systems. Authors also describe recent progress in performing geometrical fitting of the XANES (X-ray absorption near-edge structure) energy region and beyond using a full multiple-scattering approach

  3. Multiple Criteria and Multiple Periods Performance Analysis: The Comparison of North African Railways

    Science.gov (United States)

    Sabri, Karim; Colson, Gérard E.; Mbangala, Augustin M.

    2008-10-01

    Multi-period differences of technical and financial performances are analysed by comparing five North African railways over the period (1990-2004). A first approach is based on the Malmquist DEA TFP index for measuring the total factors productivity change, decomposed into technical efficiency change and technological changes. A multiple criteria analysis is also performed using the PROMETHEE II method and the software ARGOS. These methods provide complementary detailed information, especially by discriminating the technological and management progresses by Malmquist and the two dimensions of performance by Promethee: that are the service to the community and the enterprises performances, often in conflict.

  4. Multiple sequential failure model: A probabilistic approach to quantifying human error dependency

    International Nuclear Information System (INIS)

    Samanta

    1985-01-01

    This paper rpesents a probabilistic approach to quantifying human error dependency when multiple tasks are performed. Dependent human failures are dominant contributors to risks from nuclear power plants. An overview of the Multiple Sequential Failure (MSF) model developed and its use in probabilistic risk assessments (PRAs) depending on the available data are discussed. A small-scale psychological experiment was conducted on the nature of human dependency and the interpretation of the experimental data by the MSF model show remarkable accommodation of the dependent failure data. The model, which provides an unique method for quantification of dependent failures in human reliability analysis, can be used in conjunction with any of the general methods currently used for performing the human reliability aspect in PRAs

  5. Hybrid Optimization-Based Approach for Multiple Intelligent Vehicles Requests Allocation

    Directory of Open Access Journals (Sweden)

    Ahmed Hussein

    2018-01-01

    Full Text Available Self-driving cars are attracting significant attention during the last few years, which makes the technology advances jump fast and reach a point of having a number of automated vehicles on the roads. Therefore, the necessity of cooperative driving for these automated vehicles is exponentially increasing. One of the main issues in the cooperative driving world is the Multirobot Task Allocation (MRTA problem. This paper addresses the MRTA problem, specifically for the problem of vehicles and requests allocation. The objective is to introduce a hybrid optimization-based approach to solve the problem of multiple intelligent vehicles requests allocation as an instance of MRTA problem, to find not only a feasible solution, but also an optimized one as per the objective function. Several test scenarios were implemented in order to evaluate the efficiency of the proposed approach. These scenarios are based on well-known benchmarks; thus a comparative study is conducted between the obtained results and the suboptimal results. The analysis of the experimental results shows that the proposed approach was successful in handling various scenarios, especially with the increasing number of vehicles and requests, which displays the proposed approach efficiency and performance.

  6. Multiple factor analysis by example using R

    CERN Document Server

    Pagès, Jérôme

    2014-01-01

    Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR).The first two chapters cover the basic factorial analysis methods of principal component analysis (PCA) and multiple correspondence analysis (MCA). The

  7. A Collaborative Neurodynamic Approach to Multiple-Objective Distributed Optimization.

    Science.gov (United States)

    Yang, Shaofu; Liu, Qingshan; Wang, Jun

    2018-04-01

    This paper is concerned with multiple-objective distributed optimization. Based on objective weighting and decision space decomposition, a collaborative neurodynamic approach to multiobjective distributed optimization is presented. In the approach, a system of collaborative neural networks is developed to search for Pareto optimal solutions, where each neural network is associated with one objective function and given constraints. Sufficient conditions are derived for ascertaining the convergence to a Pareto optimal solution of the collaborative neurodynamic system. In addition, it is proved that each connected subsystem can generate a Pareto optimal solution when the communication topology is disconnected. Then, a switching-topology-based method is proposed to compute multiple Pareto optimal solutions for discretized approximation of Pareto front. Finally, simulation results are discussed to substantiate the performance of the collaborative neurodynamic approach. A portfolio selection application is also given.

  8. Analyzing Statistical Mediation with Multiple Informants: A New Approach with an Application in Clinical Psychology.

    Science.gov (United States)

    Papa, Lesther A; Litson, Kaylee; Lockhart, Ginger; Chassin, Laurie; Geiser, Christian

    2015-01-01

    Testing mediation models is critical for identifying potential variables that need to be targeted to effectively change one or more outcome variables. In addition, it is now common practice for clinicians to use multiple informant (MI) data in studies of statistical mediation. By coupling the use of MI data with statistical mediation analysis, clinical researchers can combine the benefits of both techniques. Integrating the information from MIs into a statistical mediation model creates various methodological and practical challenges. The authors review prior methodological approaches to MI mediation analysis in clinical research and propose a new latent variable approach that overcomes some limitations of prior approaches. An application of the new approach to mother, father, and child reports of impulsivity, frustration tolerance, and externalizing problems (N = 454) is presented. The results showed that frustration tolerance mediated the relationship between impulsivity and externalizing problems. The new approach allows for a more comprehensive and effective use of MI data when testing mediation models.

  9. Estimation of lung tumor position from multiple anatomical features on 4D-CT using multiple regression analysis.

    Science.gov (United States)

    Ono, Tomohiro; Nakamura, Mitsuhiro; Hirose, Yoshinori; Kitsuda, Kenji; Ono, Yuka; Ishigaki, Takashi; Hiraoka, Masahiro

    2017-09-01

    To estimate the lung tumor position from multiple anatomical features on four-dimensional computed tomography (4D-CT) data sets using single regression analysis (SRA) and multiple regression analysis (MRA) approach and evaluate an impact of the approach on internal target volume (ITV) for stereotactic body radiotherapy (SBRT) of the lung. Eleven consecutive lung cancer patients (12 cases) underwent 4D-CT scanning. The three-dimensional (3D) lung tumor motion exceeded 5 mm. The 3D tumor position and anatomical features, including lung volume, diaphragm, abdominal wall, and chest wall positions, were measured on 4D-CT images. The tumor position was estimated by SRA using each anatomical feature and MRA using all anatomical features. The difference between the actual and estimated tumor positions was defined as the root-mean-square error (RMSE). A standard partial regression coefficient for the MRA was evaluated. The 3D lung tumor position showed a high correlation with the lung volume (R = 0.92 ± 0.10). Additionally, ITVs derived from SRA and MRA approaches were compared with ITV derived from contouring gross tumor volumes on all 10 phases of the 4D-CT (conventional ITV). The RMSE of the SRA was within 3.7 mm in all directions. Also, the RMSE of the MRA was within 1.6 mm in all directions. The standard partial regression coefficient for the lung volume was the largest and had the most influence on the estimated tumor position. Compared with conventional ITV, average percentage decrease of ITV were 31.9% and 38.3% using SRA and MRA approaches, respectively. The estimation accuracy of lung tumor position was improved by the MRA approach, which provided smaller ITV than conventional ITV. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

  10. Improving discrimination of savanna tree species through a multiple endmember spectral-angle-mapper (SAM) approach: canopy level analysis

    CSIR Research Space (South Africa)

    Cho, Moses A

    2010-11-01

    Full Text Available sensing. The objectives of this paper were to (i) evaluate the classification performance of a multiple-endmember spectral angle mapper (SAM) classification approach (conventionally known as the nearest neighbour) in discriminating ten common African...

  11. Steady State Analysis of Stochastic Systems with Multiple Time Delays

    Science.gov (United States)

    Xu, W.; Sun, C. Y.; Zhang, H. Q.

    In this paper, attention is focused on the steady state analysis of a class of nonlinear dynamic systems with multi-delayed feedbacks driven by multiplicative correlated Gaussian white noises. The Fokker-Planck equations for delayed variables are at first derived by Novikov's theorem. Then, under small delay assumption, the approximate stationary solutions are obtained by the probability density approach. As a special case, the effects of multidelay feedbacks and the correlated additive and multiplicative Gaussian white noises on the response of a bistable system are considered. It is shown that the obtained analytical results are in good agreement with experimental results in Monte Carlo simulations.

  12. Two approaches to incorporate clinical data uncertainty into multiple criteria decision analysis for benefit-risk assessment of medicinal products.

    Science.gov (United States)

    Wen, Shihua; Zhang, Lanju; Yang, Bo

    2014-07-01

    The Problem formulation, Objectives, Alternatives, Consequences, Trade-offs, Uncertainties, Risk attitude, and Linked decisions (PrOACT-URL) framework and multiple criteria decision analysis (MCDA) have been recommended by the European Medicines Agency for structured benefit-risk assessment of medicinal products undergoing regulatory review. The objective of this article was to provide solutions to incorporate the uncertainty from clinical data into the MCDA model when evaluating the overall benefit-risk profiles among different treatment options. Two statistical approaches, the δ-method approach and the Monte-Carlo approach, were proposed to construct the confidence interval of the overall benefit-risk score from the MCDA model as well as other probabilistic measures for comparing the benefit-risk profiles between treatment options. Both approaches can incorporate the correlation structure between clinical parameters (criteria) in the MCDA model and are straightforward to implement. The two proposed approaches were applied to a case study to evaluate the benefit-risk profile of an add-on therapy for rheumatoid arthritis (drug X) relative to placebo. It demonstrated a straightforward way to quantify the impact of the uncertainty from clinical data to the benefit-risk assessment and enabled statistical inference on evaluating the overall benefit-risk profiles among different treatment options. The δ-method approach provides a closed form to quantify the variability of the overall benefit-risk score in the MCDA model, whereas the Monte-Carlo approach is more computationally intensive but can yield its true sampling distribution for statistical inference. The obtained confidence intervals and other probabilistic measures from the two approaches enhance the benefit-risk decision making of medicinal products. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  13. A Memory/Immunology-Based Control Approach with Applications to Multiple Spacecraft Formation Flying

    Directory of Open Access Journals (Sweden)

    Liguo Weng

    2013-01-01

    Full Text Available This paper addresses the problem of formation control for multiple spacecrafts in Planetary Orbital Environment (POE. Due to the presence of diverse interferences and uncertainties in the outer space, such as the changing spacecraft mass, unavailable space parameters, and varying gravity forces, traditional control methods encounter great difficulties in this area. A new control approach inspired by human memory and immune system is proposed, and this approach is shown to be capable of learning from past control experience and current behavior to improve its performance. It demands much less system dynamic information as compared with traditional controls. Both theoretic analysis and computer simulation verify its effectiveness.

  14. An integrated modeling approach to support management decisions of coupled groundwater-agricultural systems under multiple uncertainties

    Science.gov (United States)

    Hagos Subagadis, Yohannes; Schütze, Niels; Grundmann, Jens

    2015-04-01

    The planning and implementation of effective water resources management strategies need an assessment of multiple (physical, environmental, and socio-economic) issues, and often requires new research in which knowledge of diverse disciplines are combined in a unified methodological and operational frameworks. Such integrative research to link different knowledge domains faces several practical challenges. Such complexities are further compounded by multiple actors frequently with conflicting interests and multiple uncertainties about the consequences of potential management decisions. A fuzzy-stochastic multiple criteria decision analysis tool was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management. It integrated physical process-based models, fuzzy logic, expert involvement and stochastic simulation within a general framework. Subsequently, the proposed new approach is applied to a water-scarce coastal arid region water management problem in northern Oman, where saltwater intrusion into a coastal aquifer due to excessive groundwater extraction for irrigated agriculture has affected the aquifer sustainability, endangering associated socio-economic conditions as well as traditional social structure. Results from the developed method have provided key decision alternatives which can serve as a platform for negotiation and further exploration. In addition, this approach has enabled to systematically quantify both probabilistic and fuzzy uncertainties associated with the decision problem. Sensitivity analysis applied within the developed tool has shown that the decision makers' risk aversion and risk taking attitude may yield in different ranking of decision alternatives. The developed approach can be applied to address the complexities and uncertainties inherent in water resources systems to support management decisions, while serving as a platform for stakeholder participation.

  15. VAUD: A Visual Analysis Approach for Exploring Spatio-Temporal Urban Data.

    Science.gov (United States)

    Chen, Wei; Huang, Zhaosong; Wu, Feiran; Zhu, Minfeng; Guan, Huihua; Maciejewski, Ross

    2017-10-02

    Urban data is massive, heterogeneous, and spatio-temporal, posing a substantial challenge for visualization and analysis. In this paper, we design and implement a novel visual analytics approach, Visual Analyzer for Urban Data (VAUD), that supports the visualization, querying, and exploration of urban data. Our approach allows for cross-domain correlation from multiple data sources by leveraging spatial-temporal and social inter-connectedness features. Through our approach, the analyst is able to select, filter, aggregate across multiple data sources and extract information that would be hidden to a single data subset. To illustrate the effectiveness of our approach, we provide case studies on a real urban dataset that contains the cyber-, physical-, and socialinformation of 14 million citizens over 22 days.

  16. Analyzing Statistical Mediation with Multiple Informants: A New Approach with an Application in Clinical Psychology

    Directory of Open Access Journals (Sweden)

    Lesther ePapa

    2015-11-01

    Full Text Available Testing mediation models is critical for identifying potential variables that need to be targeted to effectively change one or more outcome variables. In addition, it is now common practice for clinicians to use multiple informant (MI data in studies of statistical mediation. By coupling the use of MI data with statistical mediation analysis, clinical researchers can combine the benefits of both techniques. Integrating the information from MIs into a statistical mediation model creates various methodological and practical challenges. The authors review prior methodological approaches to MI mediation analysis in clinical research and propose a new latent variable approach that overcomes some limitations of prior approaches. An application of the new approach to mother, father, and child reports of impulsivity, frustration tolerance, and externalizing problems (N = 454 is presented. The results showed that frustration tolerance mediated the relationship between impulsivity and externalizing problems. Advantages and limitations of the new approach are discussed. The new approach can help clinical researchers overcome limitations of prior techniques. It allows for a more comprehensive and effective use of MI data when testing mediation models.

  17. Strongly and weakly directed approaches to teaching multiple representation use in physics

    Directory of Open Access Journals (Sweden)

    Patrick B. Kohl

    2007-06-01

    Full Text Available Good use of multiple representations is considered key to learning physics, and so there is considerable motivation both to learn how students use multiple representations when solving problems and to learn how best to teach problem solving using multiple representations. In this study of two large-lecture algebra-based physics courses at the University of Colorado (CU and Rutgers, the State University of New Jersey, we address both issues. Students in each of the two courses solved five common electrostatics problems of varying difficulty, and we examine their solutions to clarify the relationship between multiple representation use and performance on problems involving free-body diagrams. We also compare our data across the courses, since the two physics-education-research-based courses take substantially different approaches to teaching the use of multiple representations. The course at Rutgers takes a strongly directed approach, emphasizing specific heuristics and problem-solving strategies. The course at CU takes a weakly directed approach, modeling good problem solving without teaching a specific strategy. We find that, in both courses, students make extensive use of multiple representations, and that this use (when both complete and correct is associated with significantly increased performance. Some minor differences in representation use exist, and are consistent with the types of instruction given. Most significant are the strong and broad similarities in the results, suggesting that either instructional approach or a combination thereof can be useful for helping students learn to use multiple representations for problem solving and concept development.

  18. An agent-based negotiation approach for balancing multiple coupled control domains

    DEFF Research Database (Denmark)

    Umair, Aisha; Clausen, Anders; Jørgensen, Bo Nørregaard

    2015-01-01

    Solving multi-objective multi-issue negotiation problems involving interdependent issues distributed among multiple control domains is inherent to most non-trivial cyber-physical systems. In these systems, the coordinated operation of interconnected subsystems performing autonomous control....... The proposed approach can solve negotiation problems with interdependent issues across multiple coupled control domains. We demonstrate our approach by solving a coordination problem where a Combined Heat and Power Plant must allocate electricity for three commercial greenhouses to ensure the required plant...

  19. Synthesizing monochromatic 3-D images by multiple-exposure rainbow holography with vertical area-partition approach

    Institute of Scientific and Technical Information of China (English)

    翟宏琛; 王明伟; 刘福民; 母国光

    2002-01-01

    We report for the first time the theoretical analysis and experimental results of a white-light reconstructed monochromatic 3-D image synthesizing tomograms by multiple rainbow holo-graphy with vertical-area partition (VAP) approach. The theoretical and experimental results show that 3-D monochromatic image can be synthesized by recording the master hologram by VAP ap-proach without any distortions either in gray scale or in geometrical position. A 3-D monochromatic image synthesized from a series of medical tomograms is presented in this paper for the first time.

  20. Multiple Regression Analysis of Unconfined Compression Strength of Mine Tailings Matrices

    Directory of Open Access Journals (Sweden)

    Mahmood Ali A.

    2017-01-01

    Full Text Available As part of a novel approach of sustainable development of mine tailings, experimental and numerical analysis is carried out on newly formulated tailings matrices. Several physical characteristic tests are carried out including the unconfined compression strength test to ascertain the integrity of these matrices when subjected to loading. The current paper attempts a multiple regression analysis of the unconfined compressive strength test results of these matrices to investigate the most pertinent factors affecting their strength. Results of this analysis showed that the suggested equation is reasonably applicable to the range of binder combinations used.

  1. Robustness Analysis of Real Network Topologies Under Multiple Failure Scenarios

    DEFF Research Database (Denmark)

    Manzano, M.; Marzo, J. L.; Calle, E.

    2012-01-01

    on topological characteristics. Recently approaches also consider the services supported by such networks. In this paper we carry out a robustness analysis of five real backbone telecommunication networks under defined multiple failure scenarios, taking into account the consequences of the loss of established......Nowadays the ubiquity of telecommunication networks, which underpin and fulfill key aspects of modern day living, is taken for granted. Significant large-scale failures have occurred in the last years affecting telecommunication networks. Traditionally, network robustness analysis has been focused...... connections. Results show which networks are more robust in response to a specific type of failure....

  2. Parametric optimization of multiple quality characteristics in laser cutting of Inconel-718 by using hybrid approach of multiple regression analysis and genetic algorithm

    Science.gov (United States)

    Shrivastava, Prashant Kumar; Pandey, Arun Kumar

    2018-06-01

    Inconel-718 has found high demand in different industries due to their superior mechanical properties. The traditional cutting methods are facing difficulties for cutting these alloys due to their low thermal potential, lower elasticity and high chemical compatibility at inflated temperature. The challenges of machining and/or finishing of unusual shapes and/or sizes in these materials have also faced by traditional machining. Laser beam cutting may be applied for the miniaturization and ultra-precision cutting and/or finishing by appropriate control of different process parameter. This paper present multi-objective optimization the kerf deviation, kerf width and kerf taper in the laser cutting of Incone-718 sheet. The second order regression models have been developed for different quality characteristics by using the experimental data obtained through experimentation. The regression models have been used as objective function for multi-objective optimization based on the hybrid approach of multiple regression analysis and genetic algorithm. The comparison of optimization results to experimental results shows an improvement of 88%, 10.63% and 42.15% in kerf deviation, kerf width and kerf taper, respectively. Finally, the effects of different process parameters on quality characteristics have also been discussed.

  3. Detection of fast oscillating magnetic fields using dynamic multiple TR imaging and Fourier analysis.

    Directory of Open Access Journals (Sweden)

    Ki Hwan Kim

    Full Text Available Neuronal oscillations produce oscillating magnetic fields. There have been trials to detect neuronal oscillations using MRI, but the detectability in in vivo is still in debate. Major obstacles to detecting neuronal oscillations are (i weak amplitudes, (ii fast oscillations, which are faster than MRI temporal resolution, and (iii random frequencies and on/off intervals. In this study, we proposed a new approach for direct detection of weak and fast oscillating magnetic fields. The approach consists of (i dynamic acquisitions using multiple times to repeats (TRs and (ii an expanded frequency spectral analysis. Gradient echo echo-planar imaging was used to test the feasibility of the proposed approach with a phantom generating oscillating magnetic fields with various frequencies and amplitudes and random on/off intervals. The results showed that the proposed approach could precisely detect the weak and fast oscillating magnetic fields with random frequencies and on/off intervals. Complex and phase spectra showed reliable signals, while no meaningful signals were observed in magnitude spectra. A two-TR approach provided an absolute frequency spectrum above Nyquist sampling frequency pixel by pixel with no a priori target frequency information. The proposed dynamic multiple-TR imaging and Fourier analysis are promising for direct detection of neuronal oscillations and potentially applicable to any pulse sequences.

  4. Multiple scattering approach to the vibrational excitation of molecules by slow electrons

    International Nuclear Information System (INIS)

    Drukarev, G.

    1976-01-01

    Another approach to the problem of vibrational excitation of homonuclear two-atomic molecules by slow electrons possibly accompanied by rotational transitions is presented based on the picture of multiple scattering of an electron inside the molecule. The scattering of two fixed centers in the zero range potential model is considered. The results indicate that the multiple scattering determines the order of magnitude of the vibrational excitation cross sections in the energy region under consideration even if the zero range potential model is used. Also the connection between the multiple scattering approach and quasi-stationary molecular ion picture is established. 9 refs

  5. A novel bi-level meta-analysis approach: applied to biological pathway analysis.

    Science.gov (United States)

    Nguyen, Tin; Tagett, Rebecca; Donato, Michele; Mitrea, Cristina; Draghici, Sorin

    2016-02-01

    The accumulation of high-throughput data in public repositories creates a pressing need for integrative analysis of multiple datasets from independent experiments. However, study heterogeneity, study bias, outliers and the lack of power of available methods present real challenge in integrating genomic data. One practical drawback of many P-value-based meta-analysis methods, including Fisher's, Stouffer's, minP and maxP, is that they are sensitive to outliers. Another drawback is that, because they perform just one statistical test for each individual experiment, they may not fully exploit the potentially large number of samples within each study. We propose a novel bi-level meta-analysis approach that employs the additive method and the Central Limit Theorem within each individual experiment and also across multiple experiments. We prove that the bi-level framework is robust against bias, less sensitive to outliers than other methods, and more sensitive to small changes in signal. For comparative analysis, we demonstrate that the intra-experiment analysis has more power than the equivalent statistical test performed on a single large experiment. For pathway analysis, we compare the proposed framework versus classical meta-analysis approaches (Fisher's, Stouffer's and the additive method) as well as against a dedicated pathway meta-analysis package (MetaPath), using 1252 samples from 21 datasets related to three human diseases, acute myeloid leukemia (9 datasets), type II diabetes (5 datasets) and Alzheimer's disease (7 datasets). Our framework outperforms its competitors to correctly identify pathways relevant to the phenotypes. The framework is sufficiently general to be applied to any type of statistical meta-analysis. The R scripts are available on demand from the authors. sorin@wayne.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e

  6. The concurrent multiplicative-additive approach for gauge-radar/satellite multisensor precipitation estimates

    Science.gov (United States)

    Garcia-Pintado, J.; Barberá, G. G.; Erena Arrabal, M.; Castillo, V. M.

    2010-12-01

    Objective analysis schemes (OAS), also called ``succesive correction methods'' or ``observation nudging'', have been proposed for multisensor precipitation estimation combining remote sensing data (meteorological radar or satellite) with data from ground-based raingauge networks. However, opposite to the more complex geostatistical approaches, the OAS techniques for this use are not optimized. On the other hand, geostatistical techniques ideally require, at the least, modelling the covariance from the rain gauge data at every time step evaluated, which commonly cannot be soundly done. Here, we propose a new procedure (concurrent multiplicative-additive objective analysis scheme [CMA-OAS]) for operational rainfall estimation using rain gauges and meteorological radar, which does not require explicit modelling of spatial covariances. On the basis of a concurrent multiplicative-additive (CMA) decomposition of the spatially nonuniform radar bias, within-storm variability of rainfall and fractional coverage of rainfall are taken into account. Thus both spatially nonuniform radar bias, given that rainfall is detected, and bias in radar detection of rainfall are handled. The interpolation procedure of CMA-OAS is built on the OAS, whose purpose is to estimate a filtered spatial field of the variable of interest through a successive correction of residuals resulting from a Gaussian kernel smoother applied on spatial samples. The CMA-OAS, first, poses an optimization problem at each gauge-radar support point to obtain both a local multiplicative-additive radar bias decomposition and a regionalization parameter. Second, local biases and regionalization parameters are integrated into an OAS to estimate the multisensor rainfall at the ground level. The approach considers radar estimates as background a priori information (first guess), so that nudging to observations (gauges) may be relaxed smoothly to the first guess, and the relaxation shape is obtained from the sequential

  7. Feedback structure based entropy approach for multiple-model estimation

    Institute of Scientific and Technical Information of China (English)

    Shen-tu Han; Xue Anke; Guo Yunfei

    2013-01-01

    The variable-structure multiple-model (VSMM) approach, one of the multiple-model (MM) methods, is a popular and effective approach in handling problems with mode uncertainties. The model sequence set adaptation (MSA) is the key to design a better VSMM. However, MSA methods in the literature have big room to improve both theoretically and practically. To this end, we propose a feedback structure based entropy approach that could find the model sequence sets with the smallest size under certain conditions. The filtered data are fed back in real time and can be used by the minimum entropy (ME) based VSMM algorithms, i.e., MEVSMM. Firstly, the full Markov chains are used to achieve optimal solutions. Secondly, the myopic method together with particle filter (PF) and the challenge match algorithm are also used to achieve sub-optimal solutions, a trade-off between practicability and optimality. The numerical results show that the proposed algorithm provides not only refined model sets but also a good robustness margin and very high accuracy.

  8. A data fusion approach for track monitoring from multiple in-service trains

    Science.gov (United States)

    Lederman, George; Chen, Siheng; Garrett, James H.; Kovačević, Jelena; Noh, Hae Young; Bielak, Jacobo

    2017-10-01

    We present a data fusion approach for enabling data-driven rail-infrastructure monitoring from multiple in-service trains. A number of researchers have proposed using vibration data collected from in-service trains as a low-cost method to monitor track geometry. The majority of this work has focused on developing novel features to extract information about the tracks from data produced by individual sensors on individual trains. We extend this work by presenting a technique to combine extracted features from multiple passes over the tracks from multiple sensors aboard multiple vehicles. There are a number of challenges in combining multiple data sources, like different relative position coordinates depending on the location of the sensor within the train. Furthermore, as the number of sensors increases, the likelihood that some will malfunction also increases. We use a two-step approach that first minimizes position offset errors through data alignment, then fuses the data with a novel adaptive Kalman filter that weights data according to its estimated reliability. We show the efficacy of this approach both through simulations and on a data-set collected from two instrumented trains operating over a one-year period. Combining data from numerous in-service trains allows for more continuous and more reliable data-driven monitoring than analyzing data from any one train alone; as the number of instrumented trains increases, the proposed fusion approach could facilitate track monitoring of entire rail-networks.

  9. Multiple criteria decision analysis for health technology assessment.

    Science.gov (United States)

    Thokala, Praveen; Duenas, Alejandra

    2012-12-01

    Multicriteria decision analysis (MCDA) has been suggested by some researchers as a method to capture the benefits beyond quality adjusted life-years in a transparent and consistent manner. The objectives of this article were to analyze the possible application of MCDA approaches in health technology assessment and to describe their relative advantages and disadvantages. This article begins with an introduction to the most common types of MCDA models and a critical review of state-of-the-art methods for incorporating multiple criteria in health technology assessment. An overview of MCDA is provided and is compared against the current UK National Institute for Health and Clinical Excellence health technology appraisal process. A generic MCDA modeling approach is described, and the different MCDA modeling approaches are applied to a hypothetical case study. A comparison of the different MCDA approaches is provided, and the generic issues that need consideration before the application of MCDA in health technology assessment are examined. There are general practical issues that might arise from using an MCDA approach, and it is suggested that appropriate care be taken to ensure the success of MCDA techniques in the appraisal process. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  10. A comparison of approaches for simultaneous inference of fixed effects for multiple outcomes using linear mixed models

    DEFF Research Database (Denmark)

    Jensen, Signe Marie; Ritz, Christian

    2018-01-01

    Longitudinal studies with multiple outcomes often pose challenges for the statistical analysis. A joint model including all outcomes has the advantage of incorporating the simultaneous behavior but is often difficult to fit due to computational challenges. We consider 2 alternative approaches to ......, pairwise fitting shows a larger loss in efficiency than the marginal models approach. Using an alternative to the joint modelling strategy will lead to some but not necessarily a large loss of efficiency for small sample sizes....

  11. Heuristic Solution Approaches to the Double TSP with Multiple Stacks

    DEFF Research Database (Denmark)

    Petersen, Hanne Løhmann

    This paper introduces the Double Travelling Salesman Problem with Multiple Stacks and presents a three different metaheuristic approaches to its solution. The Double Travelling Salesman Problem with Multiple Stacks is concerned with finding the shortest route performing pickups and deliveries in ...... are developed for the problem and used with each of the heuristics. Finally some computational results are given along with lower bounds on the objective value....

  12. Heuristic Solution Approaches to the Double TSP with Multiple Stacks

    DEFF Research Database (Denmark)

    Petersen, Hanne Løhmann

    2006-01-01

    This paper introduces the Double Travelling Salesman Problem with Multiple Stacks and presents a three different metaheuristic approaches to its solution. The Double Travelling Salesman Problem with Multiple Stacks is concerned with finding the shortest route performing pickups and deliveries in ...... are developed for the problem and used with each of the heuristics. Finally some computational results are given along with lower bounds on the objective value....

  13. Multiple sclerosis: general features and pharmacologic approach

    International Nuclear Information System (INIS)

    Nielsen Lagumersindez, Denis; Martinez Sanchez, Gregorio

    2009-01-01

    Multiple sclerosis is an autoimmune, inflammatory and desmyelinization disease central nervous system (CNS) of unknown etiology and critical evolution. There different etiological hypotheses talking of a close interrelation among predisposing genetic factors and dissimilar environmental factors, able to give raise to autoimmune response at central nervous system level. Hypothesis of autoimmune pathogeny is based on study of experimental models, and findings in biopsies of affected patients by disease. Accumulative data report that the oxidative stress plays a main role in pathogenesis of multiple sclerosis. Oxygen reactive species generated by macrophages has been involved as mediators of demyelinization and of axon damage, in experimental autoimmune encephalomyelitis and strictly in multiple sclerosis. Disease diagnosis is difficult because of there is not a confirmatory unique test. Management of it covers the treatment of acute relapses, disease modification, and symptoms management. These features require an individualized approach, base on evolution of this affection, and tolerability of treatments. In addition to diet, among non-pharmacologic treatments for multiple sclerosis it is recommended physical therapy. Besides, some clinical assays have been performed in which we used natural extracts, nutrition supplements, and other agents with promising results. Pharmacology allowed neurologists with a broad array of proved effectiveness drugs; however, results of research laboratories in past years make probable that therapeutical possibilities increase notably in future. (Author)

  14. Linear mixed-effects modeling approach to FMRI group analysis.

    Science.gov (United States)

    Chen, Gang; Saad, Ziad S; Britton, Jennifer C; Pine, Daniel S; Cox, Robert W

    2013-06-01

    Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance-covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance-covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity

  15. Conjoint analysis: a pragmatic approach for the accounting of multiple benefits in southern forest management

    Science.gov (United States)

    F. Christian Zinkhan; Thomas P. Holmes; D. Evan Mercer

    1994-01-01

    With conjoint analysis as its foundation, a practical approach for measuring the utility and dollar value of non-market outputs from southern forests is described and analyzed. The approach can be used in the process of evaluating alternative silvicultural and broader natural resource management plans when non-market as well as market outputs are recognized. When...

  16. Confidence ellipses: A variation based on parametric bootstrapping applicable on Multiple Factor Analysis results for rapid graphical evaluation

    DEFF Research Database (Denmark)

    Dehlholm, Christian; Brockhoff, Per B.; Bredie, Wender L. P.

    2012-01-01

    A new way of parametric bootstrapping allows similar construction of confidence ellipses applicable on all results from Multiple Factor Analysis obtained from the FactoMineR package in the statistical program R. With this procedure, a similar approach will be applied to Multiple Factor Analysis r...... in different studies performed on the same set of products. In addition, the graphical display of confidence ellipses eases interpretation and communication of results....

  17. MULTIPLE OBJECTS

    Directory of Open Access Journals (Sweden)

    A. A. Bosov

    2015-04-01

    Full Text Available Purpose. The development of complicated techniques of production and management processes, information systems, computer science, applied objects of systems theory and others requires improvement of mathematical methods, new approaches for researches of application systems. And the variety and diversity of subject systems makes necessary the development of a model that generalizes the classical sets and their development – sets of sets. Multiple objects unlike sets are constructed by multiple structures and represented by the structure and content. The aim of the work is the analysis of multiple structures, generating multiple objects, the further development of operations on these objects in application systems. Methodology. To achieve the objectives of the researches, the structure of multiple objects represents as constructive trio, consisting of media, signatures and axiomatic. Multiple object is determined by the structure and content, as well as represented by hybrid superposition, composed of sets, multi-sets, ordered sets (lists and heterogeneous sets (sequences, corteges. Findings. In this paper we study the properties and characteristics of the components of hybrid multiple objects of complex systems, proposed assessments of their complexity, shown the rules of internal and external operations on objects of implementation. We introduce the relation of arbitrary order over multiple objects, we define the description of functions and display on objects of multiple structures. Originality.In this paper we consider the development of multiple structures, generating multiple objects.Practical value. The transition from the abstract to the subject of multiple structures requires the transformation of the system and multiple objects. Transformation involves three successive stages: specification (binding to the domain, interpretation (multiple sites and particularization (goals. The proposed describe systems approach based on hybrid sets

  18. A multiple multicomponent approach to chimeric peptide-peptoid podands.

    Science.gov (United States)

    Rivera, Daniel G; León, Fredy; Concepción, Odette; Morales, Fidel E; Wessjohann, Ludger A

    2013-05-10

    The success of multi-armed, peptide-based receptors in supramolecular chemistry traditionally is not only based on the sequence but equally on an appropriate positioning of various peptidic chains to create a multivalent array of binding elements. As a faster, more versatile and alternative access toward (pseudo)peptidic receptors, a new approach based on multiple Ugi four-component reactions (Ugi-4CR) is proposed as a means of simultaneously incorporating several binding and catalytic elements into organizing scaffolds. By employing α-amino acids either as the amino or acid components of the Ugi-4CRs, this multiple multicomponent process allows for the one-pot assembly of podands bearing chimeric peptide-peptoid chains as appended arms. Tripodal, bowl-shaped, and concave polyfunctional skeletons are employed as topologically varied platforms for positioning the multiple peptidic chains formed by Ugi-4CRs. In a similar approach, steroidal building blocks with several axially-oriented isocyano groups are synthesized and utilized to align the chimeric chains with conformational constrains, thus providing an alternative to the classical peptido-steroidal receptors. The branched and hybrid peptide-peptoid appendages allow new possibilities for both rational design and combinatorial production of synthetic receptors. The concept is also expandable to other multicomponent reactions. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. The slice balance approach (SBA): a characteristic-based, multiple balance SN approach on unstructured polyhedral meshes

    International Nuclear Information System (INIS)

    Grove, R.E.

    2005-01-01

    The Slice Balance Approach (SBA) is an approach for solving geometrically-complex, neutral-particle transport problems within a multi-group discrete ordinates (S N ) framework. The salient feature is an angle-dependent spatial decomposition. We approximate general surfaces with arbitrary polygonal faces and mesh the geometry with arbitrarily-shaped polyhedral cells. A cell-local spatial decomposition divides cells into angle-dependent slices for each S N direction. This subdivision follows from a characteristic-based view of the transport problem. Most balance-based characteristic methods use it implicitly; we use it explicitly and exploit its properties. Our mathematical approach is a multiple balance approach using exact spatial moments balance equations on cells and slices along with auxiliary relations on slices. We call this the slice balance approach; it is a characteristic-based multiple balance approach. The SBA is intentionally general and can extend differencing schemes to arbitrary 2-D and 3-D meshes. This work contributes to development of general-geometry deterministic transport capability to complement Monte Carlo capability for large, geometrically-complex transport problems. The purpose of this paper is to describe the SBA. We describe the spatial decomposition and mathematical framework and highlight a few interesting properties. We sketch the derivation of two solution schemes, a step characteristic scheme and a diamond-difference-like scheme, to illustrate the approach and we present interesting results for a 2-D problem. (author)

  20. Systematic approach to optimize a pretreatment method for ultrasensitive liquid chromatography with tandem mass spectrometry analysis of multiple target compounds in biological samples.

    Science.gov (United States)

    Togashi, Kazutaka; Mutaguchi, Kuninori; Komuro, Setsuko; Kataoka, Makoto; Yamazaki, Hiroshi; Yamashita, Shinji

    2016-08-01

    In current approaches for new drug development, highly sensitive and robust analytical methods for the determination of test compounds in biological samples are essential. These analytical methods should be optimized for every target compound. However, for biological samples that contain multiple compounds as new drug candidates obtained by cassette dosing tests, it would be preferable to develop a single method that allows the determination of all compounds at once. This study aims to establish a systematic approach that enables a selection of the most appropriate pretreatment method for multiple target compounds without the use of their chemical information. We investigated the retention times of 27 known compounds under different mobile phase conditions and determined the required pretreatment of human plasma samples using several solid-phase and liquid-liquid extractions. From the relationship between retention time and recovery in a principal component analysis, appropriate pretreatments were categorized into several types. Based on the category, we have optimized a pretreatment method for the identification of three calcium channel blockers in human plasma. Plasma concentrations of these drugs in a cassette-dose clinical study at microdose level were successfully determined with a lower limit of quantitation of 0.2 pg/mL for diltiazem, 1 pg/mL for nicardipine, and 2 pg/mL for nifedipine. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Per-Sample Multiple Kernel Approach for Visual Concept Learning

    Directory of Open Access Journals (Sweden)

    Ling-Yu Duan

    2010-01-01

    Full Text Available Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

  2. Per-Sample Multiple Kernel Approach for Visual Concept Learning

    Directory of Open Access Journals (Sweden)

    Tian Yonghong

    2010-01-01

    Full Text Available Abstract Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

  3. Scenario-informed multiple criteria analysis for prioritizing investments in electricity capacity expansion

    International Nuclear Information System (INIS)

    Martinez, Lauro J.; Lambert, James H.; Karvetski, Christopher W.

    2011-01-01

    Planning the expansion and energy security of electricity capacity for a national electricity utility is a complex task in almost any economy. Planning is usually an iterative activity and can involve the use of large scale planning optimization systems accompanied by assessment of uncertain scenarios emerging from economic, technological, environmental, and regulatory developments. This paper applies a multiple criteria decision analysis to prioritize investment portfolios in capacity expansion and energy security while principally studying the robustness of the prioritization to multiple uncertain and emergent scenarios. The scenarios are identified through interaction with decision makers and stakeholders. The approach finds which scenarios most affect the prioritization of the portfolios and which portfolios have the greatest upside and downside potential across scenarios. The approach fosters innovation in the use of robust and efficient technologies, renewable energy sources, and cleaner energy fuels. A demonstration is provided for assessing the performance of technology portfolios constructed from investments in nine electricity generation technologies in Mexico.

  4. Pediatric Multiple Sclerosis: Genes, Environment, and a Comprehensive Therapeutic Approach.

    Science.gov (United States)

    Cappa, Ryan; Theroux, Liana; Brenton, J Nicholas

    2017-10-01

    Pediatric multiple sclerosis is an increasingly recognized and studied disorder that accounts for 3% to 10% of all patients with multiple sclerosis. The risk for pediatric multiple sclerosis is thought to reflect a complex interplay between environmental and genetic risk factors. Environmental exposures, including sunlight (ultraviolet radiation, vitamin D levels), infections (Epstein-Barr virus), passive smoking, and obesity, have been identified as potential risk factors in youth. Genetic predisposition contributes to the risk of multiple sclerosis, and the major histocompatibility complex on chromosome 6 makes the single largest contribution to susceptibility to multiple sclerosis. With the use of large-scale genome-wide association studies, other non-major histocompatibility complex alleles have been identified as independent risk factors for the disease. The bridge between environment and genes likely lies in the study of epigenetic processes, which are environmentally-influenced mechanisms through which gene expression may be modified. This article will review these topics to provide a framework for discussion of a comprehensive approach to counseling and ultimately treating the pediatric patient with multiple sclerosis. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Limitations in Using Multiple Imputation to Harmonize Individual Participant Data for Meta-Analysis.

    Science.gov (United States)

    Siddique, Juned; de Chavez, Peter J; Howe, George; Cruden, Gracelyn; Brown, C Hendricks

    2018-02-01

    Individual participant data (IPD) meta-analysis is a meta-analysis in which the individual-level data for each study are obtained and used for synthesis. A common challenge in IPD meta-analysis is when variables of interest are measured differently in different studies. The term harmonization has been coined to describe the procedure of placing variables on the same scale in order to permit pooling of data from a large number of studies. Using data from an IPD meta-analysis of 19 adolescent depression trials, we describe a multiple imputation approach for harmonizing 10 depression measures across the 19 trials by treating those depression measures that were not used in a study as missing data. We then apply diagnostics to address the fit of our imputation model. Even after reducing the scale of our application, we were still unable to produce accurate imputations of the missing values. We describe those features of the data that made it difficult to harmonize the depression measures and provide some guidelines for using multiple imputation for harmonization in IPD meta-analysis.

  6. Variable precision rough set for multiple decision attribute analysis

    Institute of Scientific and Technical Information of China (English)

    Lai; Kin; Keung

    2008-01-01

    A variable precision rough set (VPRS) model is used to solve the multi-attribute decision analysis (MADA) problem with multiple conflicting decision attributes and multiple condition attributes. By introducing confidence measures and a β-reduct, the VPRS model can rationally solve the conflicting decision analysis problem with multiple decision attributes and multiple condition attributes. For illustration, a medical diagnosis example is utilized to show the feasibility of the VPRS model in solving the MADA...

  7. A risk-adapted approach is beneficial in the management of bilateral femoral shaft fractures in multiple trauma patients: an analysis based on the trauma registry of the German Trauma Society.

    Science.gov (United States)

    Steinhausen, Eva; Lefering, Rolf; Tjardes, Thorsten; Neugebauer, Edmund A M; Bouillon, Bertil; Rixen, Dieter

    2014-05-01

    Today, there is a trend toward damage-control orthopedics (DCO) in the management of multiple trauma patients with long bone fractures. However, there is no widely accepted concept. A risk-adapted approach seems to result in low acute morbidity and mortality. Multiple trauma patients with bilateral femoral shaft fractures (FSFs) are considered to be more severely injured. The objective of this study was to validate the risk-adapted approach in the management of multiple trauma patients with bilateral FSF. Data analysis is based on the trauma registry of the German Trauma Society (1993-2008, n = 42,248). Multiple trauma patients with bilateral FSF were analyzed in subgroups according to the type of primary operative strategy. Outcome parameters were mortality and major complications as (multiple) organ failure and sepsis. A total of 379 patients with bilateral FSF were divided into four groups as follows: (1) no operation (8.4%), (2) bilateral temporary external fixation (DCO) (50.9%), bilateral primary definitive osteosynthesis (early total care [ETC]) (25.1%), and primary definitive osteosynthesis of one FSF and DCO contralaterally (mixed) (15.6%). Compared with the ETC group, the DCO group was more severely injured. The incidence of (multiple) organ failure and mortality rates were higher in the DCO group but without significance. Adjusted for injury severity, there was no significant difference of mortality rates between DCO and ETC. Injury severity and mortality rates were significantly increased in the no-operation group. The mixed group was similar to the ETC group regarding injury severity and outcome. In Germany, both DCO and ETC are practiced in multiple trauma patients with bilateral FSF so far. The unstable or potentially unstable patient is reasonably treated with DCO. The clearly stable patient is reasonably treated with nailing. When in doubt, the patient is probably not totally stable, and the safest precaution may be to use DCO as a risk

  8. Instantiating the multiple levels of analysis perspective in a program of study on externalizing behavior

    Science.gov (United States)

    Beauchaine, Theodore P.; Gatzke-Kopp, Lisa M.

    2014-01-01

    During the last quarter century, developmental psychopathology has become increasingly inclusive and now spans disciplines ranging from psychiatric genetics to primary prevention. As a result, developmental psychopathologists have extended traditional diathesis–stress and transactional models to include causal processes at and across all relevant levels of analysis. Such research is embodied in what is known as the multiple levels of analysis perspective. We describe how multiple levels of analysis research has informed our current thinking about antisocial and borderline personality development among trait impulsive and therefore vulnerable individuals. Our approach extends the multiple levels of analysis perspective beyond simple Biology × Environment interactions by evaluating impulsivity across physiological systems (genetic, autonomic, hormonal, neural), psychological constructs (social, affective, motivational), developmental epochs (preschool, middle childhood, adolescence, adulthood), sexes (male, female), and methods of inquiry (self-report, informant report, treatment outcome, cardiovascular, electrophysiological, neuroimaging). By conducting our research using any and all available methods across these levels of analysis, we have arrived at a developmental model of trait impulsivity that we believe confers a greater understanding of this highly heritable trait and captures at least some heterogeneity in key behavioral outcomes, including delinquency and suicide. PMID:22781868

  9. Proceedings of the workshop on multiple prompt gamma-ray analysis

    International Nuclear Information System (INIS)

    Ebihara, Mitsuru; Hatsukawa, Yuichi; Oshima, Masumi

    2006-10-01

    The workshop on 'Multiple Prompt Gamma-ray Analysis' was held on March 8, 2006 at Tokai. It is based on a project, 'Developments of real time, non-destructive ultra sensitive elemental analysis using multiple gamma-ray detections and prompt gamma ray analysis and its application to real samples', one of the High priority Cooperative Research Programs performed by Japan Atomic Energy Agency and the University of Tokyo. In this workshop, the latest results of the Multiple Prompt Gamma ray Analysis (MPGA) study were presented, together with those of Neutron Activation Analysis with Multiple Gamma-ray Detection (NAAMG). The 9 of the presented papers are indexed individually. (J.P.N.)

  10. The double travelling salesman problem with multiple stacks - Formulation and heuristic solution approaches

    DEFF Research Database (Denmark)

    Petersen, Hanne Løhmann; Madsen, Oli B.G.

    2009-01-01

    This paper introduces the double travelling salesman problem with multiple stacks and presents four different metaheuristic approaches to its solution. The double TSP with multiple stacks is concerned with determining the shortest route performing pickups and deliveries in two separated networks...

  11. Scenario and multiple criteria decision analysis for energy and environmental security of military and industrial installations.

    Science.gov (United States)

    Karvetski, Christopher W; Lambert, James H; Linkov, Igor

    2011-04-01

    Military and industrial facilities need secure and reliable power generation. Grid outages can result in cascading infrastructure failures as well as security breaches and should be avoided. Adding redundancy and increasing reliability can require additional environmental, financial, logistical, and other considerations and resources. Uncertain scenarios consisting of emergent environmental conditions, regulatory changes, growth of regional energy demands, and other concerns result in further complications. Decisions on selecting energy alternatives are made on an ad hoc basis. The present work integrates scenario analysis and multiple criteria decision analysis (MCDA) to identify combinations of impactful emergent conditions and to perform a preliminary benefits analysis of energy and environmental security investments for industrial and military installations. Application of a traditional MCDA approach would require significant stakeholder elicitations under multiple uncertain scenarios. The approach proposed in this study develops and iteratively adjusts a scoring function for investment alternatives to find the scenarios with the most significant impacts on installation security. A robust prioritization of investment alternatives can be achieved by integrating stakeholder preferences and focusing modeling and decision-analytical tools on a few key emergent conditions and scenarios. The approach is described and demonstrated for a campus of several dozen interconnected industrial buildings within a major installation. Copyright © 2010 SETAC.

  12. Perturbative analysis of multiple-field cosmological inflation

    International Nuclear Information System (INIS)

    Lahiri, Joydev; Bhattacharya, Gautam

    2006-01-01

    We develop a general formalism for analyzing linear perturbations in multiple-field cosmological inflation based on the gauge-ready approach. Our inflationary model consists of an arbitrary number of scalar fields with non-minimal kinetic terms. We solve the equations for scalar- and tensor-type perturbations during inflation to the first order in slow roll, and then obtain the super-horizon solutions for adiabatic and isocurvature perturbations after inflation. Analytic expressions for power-spectra and spectral indices arising from multiple-field inflation are presented

  13. Multiple sclerosis: general features and pharmacologic approach; Esclerosis multiple: aspectos generales y abordaje farmacologico

    Energy Technology Data Exchange (ETDEWEB)

    Nielsen Lagumersindez, Denis; Martinez Sanchez, Gregorio [Instituto de Farmacia y Alimentos, Universidad de La Habana, La Habana (Cuba)

    2009-07-01

    Multiple sclerosis is an autoimmune, inflammatory and desmyelinization disease central nervous system (CNS) of unknown etiology and critical evolution. There different etiological hypotheses talking of a close interrelation among predisposing genetic factors and dissimilar environmental factors, able to give raise to autoimmune response at central nervous system level. Hypothesis of autoimmune pathogeny is based on study of experimental models, and findings in biopsies of affected patients by disease. Accumulative data report that the oxidative stress plays a main role in pathogenesis of multiple sclerosis. Oxygen reactive species generated by macrophages has been involved as mediators of demyelinization and of axon damage, in experimental autoimmune encephalomyelitis and strictly in multiple sclerosis. Disease diagnosis is difficult because of there is not a confirmatory unique test. Management of it covers the treatment of acute relapses, disease modification, and symptoms management. These features require an individualized approach, base on evolution of this affection, and tolerability of treatments. In addition to diet, among non-pharmacologic treatments for multiple sclerosis it is recommended physical therapy. Besides, some clinical assays have been performed in which we used natural extracts, nutrition supplements, and other agents with promising results. Pharmacology allowed neurologists with a broad array of proved effectiveness drugs; however, results of research laboratories in past years make probable that therapeutical possibilities increase notably in future. (Author)

  14. Information Retrieval and Graph Analysis Approaches for Book Recommendation

    OpenAIRE

    Chahinez Benkoussas; Patrice Bellot

    2015-01-01

    A combination of multiple information retrieval approaches is proposed for the purpose of book recommendation. In this paper, book recommendation is based on complex user's query. We used different theoretical retrieval models: probabilistic as InL2 (Divergence from Randomness model) and language model and tested their interpolated combination. Graph analysis algorithms such as PageRank have been successful in Web environments. We consider the application of this algorithm in a new retrieval ...

  15. Stepped MS(All) Relied Transition (SMART): An approach to rapidly determine optimal multiple reaction monitoring mass spectrometry parameters for small molecules.

    Science.gov (United States)

    Ye, Hui; Zhu, Lin; Wang, Lin; Liu, Huiying; Zhang, Jun; Wu, Mengqiu; Wang, Guangji; Hao, Haiping

    2016-02-11

    Multiple reaction monitoring (MRM) is a universal approach for quantitative analysis because of its high specificity and sensitivity. Nevertheless, optimization of MRM parameters remains as a time and labor-intensive task particularly in multiplexed quantitative analysis of small molecules in complex mixtures. In this study, we have developed an approach named Stepped MS(All) Relied Transition (SMART) to predict the optimal MRM parameters of small molecules. SMART requires firstly a rapid and high-throughput analysis of samples using a Stepped MS(All) technique (sMS(All)) on a Q-TOF, which consists of serial MS(All) events acquired from low CE to gradually stepped-up CE values in a cycle. The optimal CE values can then be determined by comparing the extracted ion chromatograms for the ion pairs of interest among serial scans. The SMART-predicted parameters were found to agree well with the parameters optimized on a triple quadrupole from the same vendor using a mixture of standards. The parameters optimized on a triple quadrupole from a different vendor was also employed for comparison, and found to be linearly correlated with the SMART-predicted parameters, suggesting the potential applications of the SMART approach among different instrumental platforms. This approach was further validated by applying to simultaneous quantification of 31 herbal components in the plasma of rats treated with a herbal prescription. Because the sMS(All) acquisition can be accomplished in a single run for multiple components independent of standards, the SMART approach are expected to find its wide application in the multiplexed quantitative analysis of complex mixtures. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. A hybrid life cycle and multi-criteria decision analysis approach for identifying sustainable development strategies of Beijing's taxi fleet

    International Nuclear Information System (INIS)

    Cai, Yanpeng; Applegate, Scott; Yue, Wencong; Cai, Jianying; Wang, Xuan; Liu, Gengyuan; Li, Chunhui

    2017-01-01

    To identify and evaluate sustainable strategies of taxi fleet in Beijing in terms of economic, policy, and environmental implications, a hybrid approach was developed through incorporating multi-criteria decision analysis (MCDA) methods within a general life-cycle analysis (LCA) framework. The approach can (a) help comprehensive evaluate environmental impacts of multiple types of vehicles, (b) facilitate analysis of environmental, economic and policy features of such vehicles, and (c) identify desirable taxi fleet development strategies for the city. The developed approach represented an improvement of the decision-making capability for taxi implementation based on multiple available technologies and their performance that can be specifically tailored to Beijing. The results demonstrated that the proposed approach could comprehensively reflect multiple implications of strategies for the taxi fleet in Beijing to reduce air pollution in the city. The results also indicated that the electric vehicle powered with the year 2020 electricity projections would be the ideal solution, outranking the other alternatives. The conventional vehicle ranked the lowest among the alternatives. The plug-in hybrid vehicle powered by 2020 electricity projects ranked the third, followed by the plug-in hybrid vehicle ranking the fourth, and the hybrid vehicle ranking the fifth. - Highlights: • An hybrid approach was proposed for evaluating sustainable strategies of Beijing's taxi fleet. • This approach was based on the combination of multi-criteria decision analysis methods and life-cycle assessment. • Environmental, economic and policy performances of multiple strategies were compared. • Detailed responses of taxi drivers and local residents were interviewed. • The electric vehicle would be the ideal solution for Beijing Taxi fleet.

  17. The optimal approach of detecting stochastic gravitational wave from string cosmology using multiple detectors

    International Nuclear Information System (INIS)

    Fan Xilong; Zhu Zonghong

    2008-01-01

    String cosmology models predict a relic background of gravitational wave produced during the dilaton-driven inflation. It's spectrum is most likely to be detected by ground gravitational wave laser interferometers (IFOs), like LIGO, Virgo, GEO, as the energy density grows rapidly with frequency. We show the certain ranges of the parameters that underlying string cosmology model using two approaches, associated with 5% false alarm and 95% detection rate. The result presents that the approach of combining multiple pairs of IFOs is better than the approach of directly combining the outputs of multiple IFOs for LIGOH, LIGOL, Virgo and GEO

  18. A formal concept analysis approach to consensus clustering of multi-experiment expression data

    Science.gov (United States)

    2014-01-01

    Background Presently, with the increasing number and complexity of available gene expression datasets, the combination of data from multiple microarray studies addressing a similar biological question is gaining importance. The analysis and integration of multiple datasets are expected to yield more reliable and robust results since they are based on a larger number of samples and the effects of the individual study-specific biases are diminished. This is supported by recent studies suggesting that important biological signals are often preserved or enhanced by multiple experiments. An approach to combining data from different experiments is the aggregation of their clusterings into a consensus or representative clustering solution which increases the confidence in the common features of all the datasets and reveals the important differences among them. Results We propose a novel generic consensus clustering technique that applies Formal Concept Analysis (FCA) approach for the consolidation and analysis of clustering solutions derived from several microarray datasets. These datasets are initially divided into groups of related experiments with respect to a predefined criterion. Subsequently, a consensus clustering algorithm is applied to each group resulting in a clustering solution per group. These solutions are pooled together and further analysed by employing FCA which allows extracting valuable insights from the data and generating a gene partition over all the experiments. In order to validate the FCA-enhanced approach two consensus clustering algorithms are adapted to incorporate the FCA analysis. Their performance is evaluated on gene expression data from multi-experiment study examining the global cell-cycle control of fission yeast. The FCA results derived from both methods demonstrate that, although both algorithms optimize different clustering characteristics, FCA is able to overcome and diminish these differences and preserve some relevant biological

  19. Automated patterning and probing with multiple nanoscale tools for single-cell analysis.

    Science.gov (United States)

    Li, Jiayao; Kim, Yeonuk; Liu, Boyin; Qin, Ruwen; Li, Jian; Fu, Jing

    2017-10-01

    The nano-manipulation approach that combines Focused Ion Beam (FIB) milling and various imaging and probing techniques enables researchers to investigate the cellular structures in three dimensions. Such fusion approach, however, requires extensive effort on locating and examining randomly-distributed targets due to limited Field of View (FOV) when high magnification is desired. In the present study, we present the development that automates 'pattern and probe' particularly for single-cell analysis, achieved by computer aided tools including feature recognition and geometric planning algorithms. Scheduling of serial FOVs for imaging and probing of multiple cells was considered as a rectangle covering problem, and optimal or near-optimal solutions were obtained with the heuristics developed. FIB milling was then employed automatically followed by downstream analysis using Atomic Force Microscopy (AFM) to probe the cellular interior. Our strategy was applied to examine bacterial cells (Klebsiella pneumoniae) and achieved high efficiency with limited human interference. The developed algorithms can be easily adapted and integrated with different imaging platforms towards high-throughput imaging analysis of single cells. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Receptivity to Kinetic Fluctuations: A Multiple Scales Approach

    Science.gov (United States)

    Edwards, Luke; Tumin, Anatoli

    2017-11-01

    The receptivity of high-speed compressible boundary layers to kinetic fluctuations (KF) is considered within the framework of fluctuating hydrodynamics. The formulation is based on the idea that KF-induced dissipative fluxes may lead to the generation of unstable modes in the boundary layer. Fedorov and Tumin solved the receptivity problem using an asymptotic matching approach which utilized a resonant inner solution in the vicinity of the generation point of the second Mack mode. Here we take a slightly more general approach based on a multiple scales WKB ansatz which requires fewer assumptions about the behavior of the stability spectrum. The approach is modeled after the one taken by Luchini to study low speed incompressible boundary layers over a swept wing. The new framework is used to study examples of high-enthalpy, flat plate boundary layers whose spectra exhibit nuanced behavior near the generation point, such as first mode instabilities and near-neutral evolution over moderate length scales. The configurations considered exhibit supersonic unstable second Mack modes despite the temperature ratio Tw /Te > 1 , contrary to prior expectations. Supported by AFOSR and ONR.

  1. Using Combinatorial Approach to Improve Students' Learning of the Distributive Law and Multiplicative Identities

    Science.gov (United States)

    Tsai, Yu-Ling; Chang, Ching-Kuch

    2009-01-01

    This article reports an alternative approach, called the combinatorial model, to learning multiplicative identities, and investigates the effects of implementing results for this alternative approach. Based on realistic mathematics education theory, the new instructional materials or modules of the new approach were developed by the authors. From…

  2. A Monte Carlo Study on Multiple Output Stochastic Frontiers: Comparison of Two Approaches

    DEFF Research Database (Denmark)

    Henningsen, Geraldine; Henningsen, Arne; Jensen, Uwe

    , dividing all other output quantities by the selected output quantity, and using these ratios as regressors (OD). Another approach is the stochastic ray production frontier (SR) which transforms the output quantities into their Euclidean distance as the dependent variable and their polar coordinates......In the estimation of multiple output technologies in a primal approach, the main question is how to handle the multiple outputs. Often an output distance function is used, where the classical approach is to exploit its homogeneity property by selecting one output quantity as the dependent variable...... of both specifications for the case of a Translog output distance function with respect to different common statistical problems as well as problems arising as a consequence of zero values in the output quantities. Although, our results partly show clear reactions to statistical misspecifications...

  3. A Multiple Mobility Support Approach (MMSA Based on PEAS for NCW in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Bong-Joo Koo

    2011-01-01

    Full Text Available Wireless Sensor Networks (WSNs can be implemented as one of sensor systems in Network Centric Warfare (NCW. Mobility support and energy efficiency are key concerns for this application, due to multiple mobile users and stimuli in real combat field. However, mobility support approaches that can be adopted in this circumstance are rare. This paper proposes Multiple Mobility Support Approach (MMSA based on Probing Environment and Adaptive Sleeping (PEAS to support the simultaneous mobility of both multiple users and stimuli by sharing the information of stimuli in WSNs. Simulations using Qualnet are conducted, showing that MMSA can support multiple mobile users and stimuli with good energy efficiency. It is expected that the proposed MMSA can be applied to real combat field.

  4. Mediation analysis with multiple versions of the mediator.

    Science.gov (United States)

    Vanderweele, Tyler J

    2012-05-01

    The causal inference literature has provided definitions of direct and indirect effects based on counterfactuals that generalize the approach found in the social science literature. However, these definitions presuppose well-defined hypothetical interventions on the mediator. In many settings, there may be multiple ways to fix the mediator to a particular value, and these various hypothetical interventions may have very different implications for the outcome of interest. In this paper, we consider mediation analysis when multiple versions of the mediator are present. Specifically, we consider the problem of attempting to decompose a total effect of an exposure on an outcome into the portion through the intermediate and the portion through other pathways. We consider the setting in which there are multiple versions of the mediator but the investigator has access only to data on the particular measurement, not information on which version of the mediator may have brought that value about. We show that the quantity that is estimated as a natural indirect effect using only the available data does indeed have an interpretation as a particular type of mediated effect; however, the quantity estimated as a natural direct effect, in fact, captures both a true direct effect and an effect of the exposure on the outcome mediated through the effect of the version of the mediator that is not captured by the mediator measurement. The results are illustrated using 2 examples from the literature, one in which the versions of the mediator are unknown and another in which the mediator itself has been dichotomized.

  5. Catabolite regulation analysis of Escherichia coli for acetate overflow mechanism and co-consumption of multiple sugars based on systems biology approach using computer simulation.

    Science.gov (United States)

    Matsuoka, Yu; Shimizu, Kazuyuki

    2013-10-20

    It is quite important to understand the basic principle embedded in the main metabolism for the interpretation of the fermentation data. For this, it may be useful to understand the regulation mechanism based on systems biology approach. In the present study, we considered the perturbation analysis together with computer simulation based on the models which include the effects of global regulators on the pathway activation for the main metabolism of Escherichia coli. Main focus is the acetate overflow metabolism and the co-fermentation of multiple carbon sources. The perturbation analysis was first made to understand the nature of the feed-forward loop formed by the activation of Pyk by FDP (F1,6BP), and the feed-back loop formed by the inhibition of Pfk by PEP in the glycolysis. Those together with the effect of transcription factor Cra caused by FDP level affected the glycolysis activity. The PTS (phosphotransferase system) acts as the feed-back system by repressing the glucose uptake rate for the increase in the glucose uptake rate. It was also shown that the increased PTS flux (or glucose consumption rate) causes PEP/PYR ratio to be decreased, and EIIA-P, Cya, cAMP-Crp decreased, where cAMP-Crp in turn repressed TCA cycle and more acetate is formed. This was further verified by the detailed computer simulation. In the case of multiple carbon sources such as glucose and xylose, it was shown that the sequential utilization of carbon sources was observed for wild type, while the co-consumption of multiple carbon sources with slow consumption rates were observed for the ptsG mutant by computer simulation, and this was verified by experiments. Moreover, the effect of a specific gene knockout such as Δpyk on the metabolic characteristics was also investigated based on the computer simulation. Copyright © 2013 Elsevier B.V. All rights reserved.

  6. Multiple emotions: a person-centered approach to the relationship between intergroup emotion and action orientation.

    Science.gov (United States)

    Fernando, Julian W; Kashima, Yoshihisa; Laham, Simon M

    2014-08-01

    Although a great deal of research has investigated the relationship between emotions and action orientations, most studies to date have used variable-centered techniques to identify the best emotion predictor(s) of a particular action. Given that people frequently report multiple or blended emotions, a profitable area of research may be to adopt person-centered approaches to examine the action orientations elicited by a particular combination of emotions or "emotion profile." In two studies, across instances of intergroup inequality in Australia and Canada, we examined participants' experiences of six intergroup emotions: sympathy, anger directed at three targets, shame, and pride. In both studies, five groups of participants with similar emotion profiles were identified by cluster analysis and their action orientations were compared; clusters indicated that the majority of participants experienced multiple emotions. Each action orientation was also regressed on the six emotions. There were a number of differences in the results obtained from the person-centered and variable-centered approaches. This was most apparent for sympathy: the group of participants experiencing only sympathy showed little inclination to perform prosocial actions, yet sympathy was a significant predictor of numerous action orientations in regression analyses. These results imply that sympathy may only prompt a desire for action when experienced in combination with other emotions. We suggest that the use of person-centered and variable-centered approaches as complementary analytic strategies may enrich research into not only the affective predictors of action, but emotion research in general.

  7. A Technical Analysis Information Fusion Approach for Stock Price Analysis and Modeling

    Science.gov (United States)

    Lahmiri, Salim

    In this paper, we address the problem of technical analysis information fusion in improving stock market index-level prediction. We present an approach for analyzing stock market price behavior based on different categories of technical analysis metrics and a multiple predictive system. Each category of technical analysis measures is used to characterize stock market price movements. The presented predictive system is based on an ensemble of neural networks (NN) coupled with particle swarm intelligence for parameter optimization where each single neural network is trained with a specific category of technical analysis measures. The experimental evaluation on three international stock market indices and three individual stocks show that the presented ensemble-based technical indicators fusion system significantly improves forecasting accuracy in comparison with single NN. Also, it outperforms the classical neural network trained with index-level lagged values and NN trained with stationary wavelet transform details and approximation coefficients. As a result, technical information fusion in NN ensemble architecture helps improving prediction accuracy.

  8. Application of neutron multiplicity counting to waste assay

    Energy Technology Data Exchange (ETDEWEB)

    Pickrell, M.M.; Ensslin, N. [Los Alamos National Lab., NM (United States); Sharpe, T.J. [North Carolina State Univ., Raleigh, NC (United States)

    1997-11-01

    This paper describes the use of a new figure of merit code that calculates both bias and precision for coincidence and multiplicity counting, and determines the optimum regions for each in waste assay applications. A {open_quotes}tunable multiplicity{close_quotes} approach is developed that uses a combination of coincidence and multiplicity counting to minimize the total assay error. An example is shown where multiplicity analysis is used to solve for mass, alpha, and multiplication and tunable multiplicity is shown to work well. The approach provides a method for selecting coincidence, multiplicity, or tunable multiplicity counting to give the best assay with the lowest total error over a broad spectrum of assay conditions. 9 refs., 6 figs.

  9. Synergy between the Multiple Supply Chain and Green Supply Chain Management (GSCM) approaches: an initial analysis aimed at fostering supply chain sustainability

    OpenAIRE

    Ana Lima de Carvalho; Livia Rodrigues Ignácio; Kleber Francisco Esposto; Aldo Roberto Ometto

    2016-01-01

    The concept of Green Supply Chain Management (GSCM) was created in the 90s to reduce the environmental impacts of productive systems. This approach seeks to improve the environmental performance of all the participants in a supply chain, from the extraction of raw materials to the use and final disposal of the product, through relationships of collaboration or conformity between the parties. The multiple supply chains approach established by Gattorna (2009) brought to light different supply c...

  10. Comparison of the phenolic composition of fruit juices by single step gradient HPLC analysis of multiple components versus multiple chromatographic runs optimised for individual families.

    Science.gov (United States)

    Bremner, P D; Blacklock, C J; Paganga, G; Mullen, W; Rice-Evans, C A; Crozier, A

    2000-06-01

    After minimal sample preparation, two different HPLC methodologies, one based on a single gradient reversed-phase HPLC step, the other on multiple HPLC runs each optimised for specific components, were used to investigate the composition of flavonoids and phenolic acids in apple and tomato juices. The principal components in apple juice were identified as chlorogenic acid, phloridzin, caffeic acid and p-coumaric acid. Tomato juice was found to contain chlorogenic acid, caffeic acid, p-coumaric acid, naringenin and rutin. The quantitative estimates of the levels of these compounds, obtained with the two HPLC procedures, were very similar, demonstrating that either method can be used to analyse accurately the phenolic components of apple and tomato juices. Chlorogenic acid in tomato juice was the only component not fully resolved in the single run study and the multiple run analysis prior to enzyme treatment. The single run system of analysis is recommended for the initial investigation of plant phenolics and the multiple run approach for analyses where chromatographic resolution requires improvement.

  11. Cinteny: flexible analysis and visualization of synteny and genome rearrangements in multiple organisms

    Directory of Open Access Journals (Sweden)

    Meller Jaroslaw

    2007-03-01

    Full Text Available Abstract Background Identifying syntenic regions, i.e., blocks of genes or other markers with evolutionary conserved order, and quantifying evolutionary relatedness between genomes in terms of chromosomal rearrangements is one of the central goals in comparative genomics. However, the analysis of synteny and the resulting assessment of genome rearrangements are sensitive to the choice of a number of arbitrary parameters that affect the detection of synteny blocks. In particular, the choice of a set of markers and the effect of different aggregation strategies, which enable coarse graining of synteny blocks and exclusion of micro-rearrangements, need to be assessed. Therefore, existing tools and resources that facilitate identification, visualization and analysis of synteny need to be further improved to provide a flexible platform for such analysis, especially in the context of multiple genomes. Results We present a new tool, Cinteny, for fast identification and analysis of synteny with different sets of markers and various levels of coarse graining of syntenic blocks. Using Hannenhalli-Pevzner approach and its extensions, Cinteny also enables interactive determination of evolutionary relationships between genomes in terms of the number of rearrangements (the reversal distance. In particular, Cinteny provides: i integration of synteny browsing with assessment of evolutionary distances for multiple genomes; ii flexibility to adjust the parameters and re-compute the results on-the-fly; iii ability to work with user provided data, such as orthologous genes, sequence tags or other conserved markers. In addition, Cinteny provides many annotated mammalian, invertebrate and fungal genomes that are pre-loaded and available for analysis at http://cinteny.cchmc.org. Conclusion Cinteny allows one to automatically compare multiple genomes and perform sensitivity analysis for synteny block detection and for the subsequent computation of reversal distances

  12. Simultaneous estimation of multiple phases in digital holographic interferometry using state space analysis

    Science.gov (United States)

    Kulkarni, Rishikesh; Rastogi, Pramod

    2018-05-01

    A new approach is proposed for the multiple phase estimation from a multicomponent exponential phase signal recorded in multi-beam digital holographic interferometry. It is capable of providing multidimensional measurements in a simultaneous manner from a single recording of the exponential phase signal encoding multiple phases. Each phase within a small window around each pixel is appproximated with a first order polynomial function of spatial coordinates. The problem of accurate estimation of polynomial coefficients, and in turn the unwrapped phases, is formulated as a state space analysis wherein the coefficients and signal amplitudes are set as the elements of a state vector. The state estimation is performed using the extended Kalman filter. An amplitude discrimination criterion is utilized in order to unambiguously estimate the coefficients associated with the individual signal components. The performance of proposed method is stable over a wide range of the ratio of signal amplitudes. The pixelwise phase estimation approach of the proposed method allows it to handle the fringe patterns that may contain invalid regions.

  13. Multiple regression approach to predict turbine-generator output for Chinshan nuclear power plant

    International Nuclear Information System (INIS)

    Chan, Yea-Kuang; Tsai, Yu-Ching

    2017-01-01

    The objective of this study is to develop a turbine cycle model using the multiple regression approach to estimate the turbine-generator output for the Chinshan Nuclear Power Plant (NPP). The plant operating data was verified using a linear regression model with a corresponding 95% confidence interval for the operating data. In this study, the key parameters were selected as inputs for the multiple regression based turbine cycle model. The proposed model was used to estimate the turbine-generator output. The effectiveness of the proposed turbine cycle model was demonstrated by using plant operating data obtained from the Chinshan NPP Unit 2. The results show that this multiple regression based turbine cycle model can be used to accurately estimate the turbine-generator output. In addition, this study also provides an alternative approach with simple and easy features to evaluate the thermal performance for nuclear power plants.

  14. Multiple regression approach to predict turbine-generator output for Chinshan nuclear power plant

    Energy Technology Data Exchange (ETDEWEB)

    Chan, Yea-Kuang; Tsai, Yu-Ching [Institute of Nuclear Energy Research, Taoyuan City, Taiwan (China). Nuclear Engineering Division

    2017-03-15

    The objective of this study is to develop a turbine cycle model using the multiple regression approach to estimate the turbine-generator output for the Chinshan Nuclear Power Plant (NPP). The plant operating data was verified using a linear regression model with a corresponding 95% confidence interval for the operating data. In this study, the key parameters were selected as inputs for the multiple regression based turbine cycle model. The proposed model was used to estimate the turbine-generator output. The effectiveness of the proposed turbine cycle model was demonstrated by using plant operating data obtained from the Chinshan NPP Unit 2. The results show that this multiple regression based turbine cycle model can be used to accurately estimate the turbine-generator output. In addition, this study also provides an alternative approach with simple and easy features to evaluate the thermal performance for nuclear power plants.

  15. Causal mediation analysis with multiple mediators.

    Science.gov (United States)

    Daniel, R M; De Stavola, B L; Cousens, S N; Vansteelandt, S

    2015-03-01

    In diverse fields of empirical research-including many in the biological sciences-attempts are made to decompose the effect of an exposure on an outcome into its effects via a number of different pathways. For example, we may wish to separate the effect of heavy alcohol consumption on systolic blood pressure (SBP) into effects via body mass index (BMI), via gamma-glutamyl transpeptidase (GGT), and via other pathways. Much progress has been made, mainly due to contributions from the field of causal inference, in understanding the precise nature of statistical estimands that capture such intuitive effects, the assumptions under which they can be identified, and statistical methods for doing so. These contributions have focused almost entirely on settings with a single mediator, or a set of mediators considered en bloc; in many applications, however, researchers attempt a much more ambitious decomposition into numerous path-specific effects through many mediators. In this article, we give counterfactual definitions of such path-specific estimands in settings with multiple mediators, when earlier mediators may affect later ones, showing that there are many ways in which decomposition can be done. We discuss the strong assumptions under which the effects are identified, suggesting a sensitivity analysis approach when a particular subset of the assumptions cannot be justified. These ideas are illustrated using data on alcohol consumption, SBP, BMI, and GGT from the Izhevsk Family Study. We aim to bridge the gap from "single mediator theory" to "multiple mediator practice," highlighting the ambitious nature of this endeavor and giving practical suggestions on how to proceed. © 2014 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

  16. Seismic analysis of piping systems subjected to multiple support excitations

    International Nuclear Information System (INIS)

    Sundararajan, C.; Vaish, A.K.; Slagis, G.C.

    1981-01-01

    The paper presents the results of a comparative study between the multiple response spectrum method and the time-history method for the seismic analysis of nuclear piping systems subjected to different excitation at different supports or support groups. First, the necessary equations for the above analysis procedures are derived. Then, three actual nuclear piping systems subjected to single and multiple excitations are analyzed by the different methods, and extensive comparisons of the results (stresses) are made. Based on the results, it is concluded that the multiple response spectrum analysis gives acceptable results as compared to the ''exact'', but much more costly, time-history analysis. 6 refs

  17. Information Retrieval and Graph Analysis Approaches for Book Recommendation

    Directory of Open Access Journals (Sweden)

    Chahinez Benkoussas

    2015-01-01

    Full Text Available A combination of multiple information retrieval approaches is proposed for the purpose of book recommendation. In this paper, book recommendation is based on complex user's query. We used different theoretical retrieval models: probabilistic as InL2 (Divergence from Randomness model and language model and tested their interpolated combination. Graph analysis algorithms such as PageRank have been successful in Web environments. We consider the application of this algorithm in a new retrieval approach to related document network comprised of social links. We called Directed Graph of Documents (DGD a network constructed with documents and social information provided from each one of them. Specifically, this work tackles the problem of book recommendation in the context of INEX (Initiative for the Evaluation of XML retrieval Social Book Search track. A series of reranking experiments demonstrate that combining retrieval models yields significant improvements in terms of standard ranked retrieval metrics. These results extend the applicability of link analysis algorithms to different environments.

  18. Information Retrieval and Graph Analysis Approaches for Book Recommendation.

    Science.gov (United States)

    Benkoussas, Chahinez; Bellot, Patrice

    2015-01-01

    A combination of multiple information retrieval approaches is proposed for the purpose of book recommendation. In this paper, book recommendation is based on complex user's query. We used different theoretical retrieval models: probabilistic as InL2 (Divergence from Randomness model) and language model and tested their interpolated combination. Graph analysis algorithms such as PageRank have been successful in Web environments. We consider the application of this algorithm in a new retrieval approach to related document network comprised of social links. We called Directed Graph of Documents (DGD) a network constructed with documents and social information provided from each one of them. Specifically, this work tackles the problem of book recommendation in the context of INEX (Initiative for the Evaluation of XML retrieval) Social Book Search track. A series of reranking experiments demonstrate that combining retrieval models yields significant improvements in terms of standard ranked retrieval metrics. These results extend the applicability of link analysis algorithms to different environments.

  19. Flexible Mediation Analysis With Multiple Mediators.

    Science.gov (United States)

    Steen, Johan; Loeys, Tom; Moerkerke, Beatrijs; Vansteelandt, Stijn

    2017-07-15

    The advent of counterfactual-based mediation analysis has triggered enormous progress on how, and under what assumptions, one may disentangle path-specific effects upon combining arbitrary (possibly nonlinear) models for mediator and outcome. However, current developments have largely focused on single mediators because required identification assumptions prohibit simple extensions to settings with multiple mediators that may depend on one another. In this article, we propose a procedure for obtaining fine-grained decompositions that may still be recovered from observed data in such complex settings. We first show that existing analytical approaches target specific instances of a more general set of decompositions and may therefore fail to provide a comprehensive assessment of the processes that underpin cause-effect relationships between exposure and outcome. We then outline conditions for obtaining the remaining set of decompositions. Because the number of targeted decompositions increases rapidly with the number of mediators, we introduce natural effects models along with estimation methods that allow for flexible and parsimonious modeling. Our procedure can easily be implemented using off-the-shelf software and is illustrated using a reanalysis of the World Health Organization's Large Analysis and Review of European Housing and Health Status (WHO-LARES) study on the effect of mold exposure on mental health (2002-2003). © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  20. Visualization of a City Sustainability Index (CSI: Towards Transdisciplinary Approaches Involving Multiple Stakeholders

    Directory of Open Access Journals (Sweden)

    Koichiro Mori

    2015-09-01

    Full Text Available We have developed a visualized 3-D model of a City Sustainability Index (CSI based on our original concept of city sustainability in which a sustainable city is defined as one that maximizes socio-economic benefits while meeting constraint conditions of the environment and socio-economic equity on a permanent basis. The CSI is based on constraint and maximization indicators. Constraint indicators assess whether a city meets the necessary minimum conditions for city sustainability. Maximization indicators measure the benefits that a city generates in socio-economic aspects. When used in the policy-making process, the choice of constraint indicators should be implemented using a top-down approach. In contrast, a bottom-up approach is more suitable for defining maximization indicators because this technique involves multiple stakeholders (in a transdisciplinary approach. Using different materials of various colors, shapes, sizes, we designed and constructed the visualized physical model of the CSI to help people evaluate and compare the performance of different cities in terms of sustainability. The visualized model of the CSI can convey complicated information in a simple and straightforward manner to diverse stakeholders so that the sustainability analysis can be understood intuitively by ordinary citizens as well as experts. Thus, the CSI model helps stakeholders to develop critical thinking about city sustainability and enables policymakers to make informed decisions for sustainability through a transdisciplinary approach.

  1. Causal mediation analysis with multiple mediators in the presence of treatment noncompliance.

    Science.gov (United States)

    Park, Soojin; Kürüm, Esra

    2018-05-20

    Randomized experiments are often complicated because of treatment noncompliance. This challenge prevents researchers from identifying the mediated portion of the intention-to-treated (ITT) effect, which is the effect of the assigned treatment that is attributed to a mediator. One solution suggests identifying the mediated ITT effect on the basis of the average causal mediation effect among compliers when there is a single mediator. However, considering the complex nature of the mediating mechanisms, it is natural to assume that there are multiple variables that mediate through the causal path. Motivated by an empirical analysis of a data set collected in a randomized interventional study, we develop a method to estimate the mediated portion of the ITT effect when both multiple dependent mediators and treatment noncompliance exist. This enables researchers to make an informed decision on how to strengthen the intervention effect by identifying relevant mediators despite treatment noncompliance. We propose a nonparametric estimation procedure and provide a sensitivity analysis for key assumptions. We conduct a Monte Carlo simulation study to assess the finite sample performance of the proposed approach. The proposed method is illustrated by an empirical analysis of JOBS II data, in which a job training intervention was used to prevent mental health deterioration among unemployed individuals. Copyright © 2018 John Wiley & Sons, Ltd.

  2. Failure analysis of multiple delaminated composite plates due

    Indian Academy of Sciences (India)

    The present work aims at the first ply failure analysis of laminated composite plates with arbitrarily located multiple delaminations subjected to transverse static load as well as impact. The theoretical formulation is based on a simple multiple delamination model. Conventional first order shear deformation is assumed using ...

  3. Practical considerations for sensitivity analysis after multiple imputation applied to epidemiological studies with incomplete data

    Science.gov (United States)

    2012-01-01

    Background Multiple Imputation as usually implemented assumes that data are Missing At Random (MAR), meaning that the underlying missing data mechanism, given the observed data, is independent of the unobserved data. To explore the sensitivity of the inferences to departures from the MAR assumption, we applied the method proposed by Carpenter et al. (2007). This approach aims to approximate inferences under a Missing Not At random (MNAR) mechanism by reweighting estimates obtained after multiple imputation where the weights depend on the assumed degree of departure from the MAR assumption. Methods The method is illustrated with epidemiological data from a surveillance system of hepatitis C virus (HCV) infection in France during the 2001–2007 period. The subpopulation studied included 4343 HCV infected patients who reported drug use. Risk factors for severe liver disease were assessed. After performing complete-case and multiple imputation analyses, we applied the sensitivity analysis to 3 risk factors of severe liver disease: past excessive alcohol consumption, HIV co-infection and infection with HCV genotype 3. Results In these data, the association between severe liver disease and HIV was underestimated, if given the observed data the chance of observing HIV status is high when this is positive. Inference for two other risk factors were robust to plausible local departures from the MAR assumption. Conclusions We have demonstrated the practical utility of, and advocate, a pragmatic widely applicable approach to exploring plausible departures from the MAR assumption post multiple imputation. We have developed guidelines for applying this approach to epidemiological studies. PMID:22681630

  4. Analytical approach for modeling and performance analysis of microring resonators as optical filters with multiple output bus waveguides

    Science.gov (United States)

    Lakra, Suchita; Mandal, Sanjoy

    2017-06-01

    A quadruple micro-optical ring resonator (QMORR) with multiple output bus waveguides is mathematically modeled and analyzed by making use of the delay-line signal processing approach in Z-domain and Mason's gain formula. The performances of QMORR with two output bus waveguides with vertical coupling are analyzed. This proposed structure is capable of providing wider free spectral response from both the output buses with appreciable cross talk. Thus, this configuration could provide increased capacity to insert a large number of communication channels. The simulated frequency response characteristic and its dispersion and group delay characteristics are graphically presented using the MATLAB environment.

  5. Interactions between cadmium and decabrominated diphenyl ether on blood cells count in rats—Multiple factorial regression analysis

    International Nuclear Information System (INIS)

    Curcic, Marijana; Buha, Aleksandra; Stankovic, Sanja; Milovanovic, Vesna; Bulat, Zorica; Đukić-Ćosić, Danijela; Antonijević, Evica; Vučinić, Slavica; Matović, Vesna; Antonijevic, Biljana

    2017-01-01

    The objective of this study was to assess toxicity of Cd and BDE-209 mixture on haematological parameters in subacutely exposed rats and to determine the presence and type of interactions between these two chemicals using multiple factorial regression analysis. Furthermore, for the assessment of interaction type, an isobologram based methodology was applied and compared with multiple factorial regression analysis. Chemicals were given by oral gavage to the male Wistar rats weighing 200–240 g for 28 days. Animals were divided in 16 groups (8/group): control vehiculum group, three groups of rats were treated with 2.5, 7.5 or 15 mg Cd/kg/day. These doses were chosen on the bases of literature data and reflect relatively high Cd environmental exposure, three groups of rats were treated with 1000, 2000 or 4000 mg BDE-209/kg/bw/day, doses proved to induce toxic effects in rats. Furthermore, nine groups of animals were treated with different mixtures of Cd and BDE-209 containing doses of Cd and BDE-209 stated above. Blood samples were taken at the end of experiment and red blood cells, white blood cells and platelets counts were determined. For interaction assessment multiple factorial regression analysis and fitted isobologram approach were used. In this study, we focused on multiple factorial regression analysis as a method for interaction assessment. We also investigated the interactions between Cd and BDE-209 by the derived model for the description of the obtained fitted isobologram curves. Current study indicated that co-exposure to Cd and BDE-209 can result in significant decrease in RBC count, increase in WBC count and decrease in PLT count, when compared with controls. Multiple factorial regression analysis used for the assessment of interactions type between Cd and BDE-209 indicated synergism for the effect on RBC count and no interactions i.e. additivity for the effects on WBC and PLT counts. On the other hand, isobologram based approach showed slight

  6. Analytical multiple scattering correction to the Mie theory: Application to the analysis of the lidar signal

    Science.gov (United States)

    Flesia, C.; Schwendimann, P.

    1992-01-01

    The contribution of the multiple scattering to the lidar signal is dependent on the optical depth tau. Therefore, the radar analysis, based on the assumption that the multiple scattering can be neglected is limited to cases characterized by low values of the optical depth (tau less than or equal to 0.1) and hence it exclude scattering from most clouds. Moreover, all inversion methods relating lidar signal to number densities and particle size must be modified since the multiple scattering affects the direct analysis. The essential requests of a realistic model for lidar measurements which include the multiple scattering and which can be applied to practical situations follow. (1) Requested are not only a correction term or a rough approximation describing results of a certain experiment, but a general theory of multiple scattering tying together the relevant physical parameter we seek to measure. (2) An analytical generalization of the lidar equation which can be applied in the case of a realistic aerosol is requested. A pure analytical formulation is important in order to avoid the convergency and stability problems which, in the case of numerical approach, are due to the large number of events that have to be taken into account in the presence of large depth and/or a strong experimental noise.

  7. Multiplicative calculus in biomedical image analysis

    NARCIS (Netherlands)

    Florack, L.M.J.; Assen, van H.C.

    2011-01-01

    We advocate the use of an alternative calculus in biomedical image analysis, known as multiplicative (a.k.a. non-Newtonian) calculus. It provides a natural framework in problems in which positive images or positive definite matrix fields and positivity preserving operators are of interest. Indeed,

  8. Multiple performance optimization of electrochemical drilling of Inconel 625 using Taguchi based Grey Relational Analysis

    Directory of Open Access Journals (Sweden)

    N. Manikandan

    2017-04-01

    Full Text Available In this present investigation, a multi performance characteristics optimization based on Taguchi approach with Grey Relational Analysis (GRA is proposed for Electrochemical Drilling process on Inconel 625 material which is used for marine, nuclear, aerospace applications, especially in corrosive environments. Experimental runs have been planned as per Taguchi’s principle with three input machining variables such as feed rate, flow rate of electrolyte and concentration of electrolyte. Besides the material removal rate and surface roughness, the geometric measures such as overcut, form and orientation tolerance are included as performance measures in this investigation. Outcomes of the analysis show that the feed rate is the predominant variable for the desired performance characteristics. On establishing the desired performance measures and multiple regression models are developed to be used as predictive tools. The confirmation test also conducted to validate the results attained by GRA approach and affirmed that there is considerable improvement with the help of proposed approach.

  9. RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,

    Science.gov (United States)

    This memorandum gives instructions for the use and operation of a revised version of RAWS, a multiple regression analysis program. The program...of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. (Author)

  10. Energy dependence of the multiplicity analysis of quark-diquark jets

    CERN Document Server

    Biswal, K; Panda, A R; Parida, B K

    1980-01-01

    Under the assumption of hard scattering, multiplicity analysis of quark-diquark jets is made in a model analogous to the quark-cascade- jet production model developed earlier. In the present approach the diquark is treated as a coherent object consisting of the two quarks which remain after the hard scattering. This is assumed to produce a baryon and an antiquark in the first stage of its fragmentation. The resulting quark-antiquark pair then hadronises as per the cascade model. This picture of quark-diquark fragmentation is adequately supported by the observations made in recent ISR experiments at CERN. The above technique is applied to weak, electromagnetic and strong processes involving quark-diquark hadronisation in a unified manner and with fair agreement with the experimental results. (0 refs).

  11. The Health Action Process Approach as a motivational model for physical activity self-management for people with multiple sclerosis: a path analysis.

    Science.gov (United States)

    Chiu, Chung-Yi; Lynch, Ruth T; Chan, Fong; Berven, Norman L

    2011-08-01

    To evaluate the Health Action Process Approach (HAPA) as a motivational model for physical activity self-management for people with multiple sclerosis (MS). Quantitative descriptive research design using path analysis. One hundred ninety-five individuals with MS were recruited from the National Multiple Sclerosis Society and a neurology clinic at a university teaching hospital in the Midwest. Outcome was measured by the Physical Activity Stages of Change Instrument, along with measures for nine predictors (severity, action self-efficacy, outcome expectancy, risk perception, perceived barriers, intention, maintenance self-efficacy, action and coping planning, and recovery self-efficacy). The respecified HAPA physical activity model fit the data relatively well (goodness-of-fit index = .92, normed fit index = .91, and comparative fit index = .93) explaining 38% of the variance in physical activity. Recovery self-efficacy, action and coping planning, and perceived barriers directly contributed to the prediction of physical activity. Outcome expectancy significantly influenced intention and the relationship between intention and physical activity is mediated by action and coping planning. Action self-efficacy, maintenance self-efficacy, and recovery self-efficacy directly or indirectly affected physical activity. Severity of MS and action self-efficacy had an inverse relationship with perceived barriers and perceived barriers influenced physical activity. Empirical support was found for the proposed HAPA model of physical activity for people with MS. The HAPA model appears to provide useful information for clinical rehabilitation and health promotion interventions.

  12. Multidisciplinary approaches to managing osteoarthritis in multiple joint sites: a systematic review.

    Science.gov (United States)

    Finney, Andrew; Healey, Emma; Jordan, Joanne L; Ryan, Sarah; Dziedzic, Krysia S

    2016-07-08

    The National Institute for Health and Care Excellence's Osteoarthritis (OA) guidelines recommended that future research should consider the benefits of combination therapies in people with OA across multiple joint sites. However, the clinical effectiveness of such approaches to OA management is unknown. This systematic review therefore aimed to identify the clinical and cost effectiveness of multidisciplinary approaches targeting multiple joint sites for OA in primary care. A systematic review of randomised controlled trials. Computerised bibliographic databases were searched (MEDLINE, EMBASE, CINAHL, PsychINFO, BNI, HBE, HMIC, AMED, Web of Science and Cochrane). Studies were included if they met the following criteria; a randomised controlled trial (RCT), a primary care population with OA across at least two different peripheral joint sites (multiple joint sites), and interventions undertaken by at least two different health disciplines (multidisciplinary). The Cochrane 'Risk of Bias' tool and PEDro were used for quality assessment of eligible studies. Clinical and cost effectiveness was determined by extracting and examining self-reported outcomes for pain, function, quality of life (QoL) and health care utilisation. The date range for the search was from database inception until August 2015. The search identified 1148 individual titles of which four were included in the review. A narrative review was conducted due to the heterogeneity of the included trials. Each of the four trials used either educational or exercise interventions facilitated by a range of different health disciplines. Moderate clinical benefits on pain, function and QoL were reported across the studies. The beneficial effects of exercise generally decreased over time within all studies. Two studies were able to show a reduction in healthcare utilisation due to a reduction in visits to a physiotherapist or a reduction in x-rays and orthopaedic referrals. The intervention that showed the most

  13. Performance evaluation of 2D and 3D deep learning approaches for automatic segmentation of multiple organs on CT images

    Science.gov (United States)

    Zhou, Xiangrong; Yamada, Kazuma; Kojima, Takuya; Takayama, Ryosuke; Wang, Song; Zhou, Xinxin; Hara, Takeshi; Fujita, Hiroshi

    2018-02-01

    The purpose of this study is to evaluate and compare the performance of modern deep learning techniques for automatically recognizing and segmenting multiple organ regions on 3D CT images. CT image segmentation is one of the important task in medical image analysis and is still very challenging. Deep learning approaches have demonstrated the capability of scene recognition and semantic segmentation on nature images and have been used to address segmentation problems of medical images. Although several works showed promising results of CT image segmentation by using deep learning approaches, there is no comprehensive evaluation of segmentation performance of the deep learning on segmenting multiple organs on different portions of CT scans. In this paper, we evaluated and compared the segmentation performance of two different deep learning approaches that used 2D- and 3D deep convolutional neural networks (CNN) without- and with a pre-processing step. A conventional approach that presents the state-of-the-art performance of CT image segmentation without deep learning was also used for comparison. A dataset that includes 240 CT images scanned on different portions of human bodies was used for performance evaluation. The maximum number of 17 types of organ regions in each CT scan were segmented automatically and compared to the human annotations by using ratio of intersection over union (IU) as the criterion. The experimental results demonstrated the IUs of the segmentation results had a mean value of 79% and 67% by averaging 17 types of organs that segmented by a 3D- and 2D deep CNN, respectively. All the results of the deep learning approaches showed a better accuracy and robustness than the conventional segmentation method that used probabilistic atlas and graph-cut methods. The effectiveness and the usefulness of deep learning approaches were demonstrated for solving multiple organs segmentation problem on 3D CT images.

  14. Pooling Data from Multiple Longitudinal Studies: The Role of Item Response Theory in Integrative Data Analysis

    Science.gov (United States)

    Curran, Patrick J.; Hussong, Andrea M.; Cai, Li; Huang, Wenjing; Chassin, Laurie; Sher, Kenneth J.; Zucker, Robert A.

    2010-01-01

    There are a number of significant challenges encountered when studying development over an extended period of time including subject attrition, changing measurement structures across group and developmental period, and the need to invest substantial time and money. Integrative data analysis is an emerging set of methodologies that overcomes many of the challenges of single sample designs through the pooling of data drawn from multiple existing developmental studies. This approach is characterized by a host of advantages, but this also introduces several new complexities that must be addressed prior to broad adoption by developmental researchers. In this paper we focus on methods for fitting measurement models and creating scale scores using data drawn from multiple longitudinal studies. We present findings from the analysis of repeated measures of internalizing symptomatology that were pooled from three existing developmental studies. We describe and demonstrate each step in the analysis and we conclude with a discussion of potential limitations and directions for future research. PMID:18331129

  15. A data-driven multiplicative fault diagnosis approach for automation processes.

    Science.gov (United States)

    Hao, Haiyang; Zhang, Kai; Ding, Steven X; Chen, Zhiwen; Lei, Yaguo

    2014-09-01

    This paper presents a new data-driven method for diagnosing multiplicative key performance degradation in automation processes. Different from the well-established additive fault diagnosis approaches, the proposed method aims at identifying those low-level components which increase the variability of process variables and cause performance degradation. Based on process data, features of multiplicative fault are extracted. To identify the root cause, the impact of fault on each process variable is evaluated in the sense of contribution to performance degradation. Then, a numerical example is used to illustrate the functionalities of the method and Monte-Carlo simulation is performed to demonstrate the effectiveness from the statistical viewpoint. Finally, to show the practical applicability, a case study on the Tennessee Eastman process is presented. Copyright © 2013. Published by Elsevier Ltd.

  16. Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research

    NARCIS (Netherlands)

    Golino, H.F.; Epskamp, S.

    2017-01-01

    The estimation of the correct number of dimensions is a long-standing problem in psychometrics. Several methods have been proposed, such as parallel analysis (PA), Kaiser-Guttman’s eigenvalue-greater-than-one rule, multiple average partial procedure (MAP), the maximum-likelihood approaches that use

  17. Integrative Analysis of Prognosis Data on Multiple Cancer Subtypes

    Science.gov (United States)

    Liu, Jin; Huang, Jian; Zhang, Yawei; Lan, Qing; Rothman, Nathaniel; Zheng, Tongzhang; Ma, Shuangge

    2014-01-01

    Summary In cancer research, profiling studies have been extensively conducted, searching for genes/SNPs associated with prognosis. Cancer is diverse. Examining the similarity and difference in the genetic basis of multiple subtypes of the same cancer can lead to a better understanding of their connections and distinctions. Classic meta-analysis methods analyze each subtype separately and then compare analysis results across subtypes. Integrative analysis methods, in contrast, analyze the raw data on multiple subtypes simultaneously and can outperform meta-analysis methods. In this study, prognosis data on multiple subtypes of the same cancer are analyzed. An AFT (accelerated failure time) model is adopted to describe survival. The genetic basis of multiple subtypes is described using the heterogeneity model, which allows a gene/SNP to be associated with prognosis of some subtypes but not others. A compound penalization method is developed to identify genes that contain important SNPs associated with prognosis. The proposed method has an intuitive formulation and is realized using an iterative algorithm. Asymptotic properties are rigorously established. Simulation shows that the proposed method has satisfactory performance and outperforms a penalization-based meta-analysis method and a regularized thresholding method. An NHL (non-Hodgkin lymphoma) prognosis study with SNP measurements is analyzed. Genes associated with the three major subtypes, namely DLBCL, FL, and CLL/SLL, are identified. The proposed method identifies genes that are different from alternatives and have important implications and satisfactory prediction performance. PMID:24766212

  18. The multiple decrement life table: a unifying framework for cause-of-death analysis in ecology.

    Science.gov (United States)

    Carey, James R

    1989-01-01

    The multiple decrement life table is used widely in the human actuarial literature and provides statistical expressions for mortality in three different forms: i) the life table from all causes-of-death combined; ii) the life table disaggregated into selected cause-of-death categories; and iii) the life table with particular causes and combinations of causes eliminated. The purpose of this paper is to introduce the multiple decrement life table to the ecological literature by applying the methods to published death-by-cause information on Rhagoletis pomonella. Interrelations between the current approach and conventional tools used in basic and applied ecology are discussed including the conventional life table, Key Factor Analysis and Abbott's Correction used in toxicological bioassay.

  19. A Hybrid One-Way ANOVA Approach for the Robust and Efficient Estimation of Differential Gene Expression with Multiple Patterns.

    Directory of Open Access Journals (Sweden)

    Mohammad Manir Hossain Mollah

    Full Text Available Identifying genes that are differentially expressed (DE between two or more conditions with multiple patterns of expression is one of the primary objectives of gene expression data analysis. Several statistical approaches, including one-way analysis of variance (ANOVA, are used to identify DE genes. However, most of these methods provide misleading results for two or more conditions with multiple patterns of expression in the presence of outlying genes. In this paper, an attempt is made to develop a hybrid one-way ANOVA approach that unifies the robustness and efficiency of estimation using the minimum β-divergence method to overcome some problems that arise in the existing robust methods for both small- and large-sample cases with multiple patterns of expression.The proposed method relies on a β-weight function, which produces values between 0 and 1. The β-weight function with β = 0.2 is used as a measure of outlier detection. It assigns smaller weights (≥ 0 to outlying expressions and larger weights (≤ 1 to typical expressions. The distribution of the β-weights is used to calculate the cut-off point, which is compared to the observed β-weight of an expression to determine whether that gene expression is an outlier. This weight function plays a key role in unifying the robustness and efficiency of estimation in one-way ANOVA.Analyses of simulated gene expression profiles revealed that all eight methods (ANOVA, SAM, LIMMA, EBarrays, eLNN, KW, robust BetaEB and proposed perform almost identically for m = 2 conditions in the absence of outliers. However, the robust BetaEB method and the proposed method exhibited considerably better performance than the other six methods in the presence of outliers. In this case, the BetaEB method exhibited slightly better performance than the proposed method for the small-sample cases, but the the proposed method exhibited much better performance than the BetaEB method for both the small- and large

  20. Freestyle multiple propeller flap reconstruction (jigsaw puzzle approach) for complicated back defects.

    Science.gov (United States)

    Park, Sung Woo; Oh, Tae Suk; Eom, Jin Sup; Sun, Yoon Chi; Suh, Hyun Suk; Hong, Joon Pio

    2015-05-01

    The reconstruction of the posterior trunk remains to be a challenge as defects can be extensive, with deep dead space, and fixation devices exposed. Our goal was to achieve a tension-free closure for complex defects on the posterior trunk. From August 2006 to May 2013, 18 cases were reconstructed with multiple flaps combining perforator(s) and local skin flaps. The reconstructions were performed using freestyle approach. Starting with propeller flap(s) in single or multilobed design and sequentially in conjunction with adjacent random pattern flaps such as fitting puzzle. All defects achieved tensionless primary closure. The final appearance resembled a jigsaw puzzle-like appearance. The average size of defect was 139.6 cm(2) (range, 36-345 cm(2)). A total of 26 perforator flaps were used in addition to 19 random pattern flaps for 18 cases. In all cases, a single perforator was used for each propeller flap. The defect and the donor site all achieved tension-free closure. The reconstruction was 100% successful without flap loss. One case of late infection was noted at 12 months after surgery. Using multiple lobe designed propeller flaps in conjunction with random pattern flaps in a freestyle approach, resembling putting a jigsaw puzzle together, we can achieve a tension-free closure by distributing the tension to multiple flaps, supplying sufficient volume to obliterate dead space, and have reliable vascularity as the flaps do not need to be oversized. This can be a viable approach to reconstruct extensive defects on the posterior trunk. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

  1. Missing data treatments matter: an analysis of multiple imputation for anterior cervical discectomy and fusion procedures.

    Science.gov (United States)

    Ondeck, Nathaniel T; Fu, Michael C; Skrip, Laura A; McLynn, Ryan P; Cui, Jonathan J; Basques, Bryce A; Albert, Todd J; Grauer, Jonathan N

    2018-04-09

    The presence of missing data is a limitation of large datasets, including the National Surgical Quality Improvement Program (NSQIP). In addressing this issue, most studies use complete case analysis, which excludes cases with missing data, thus potentially introducing selection bias. Multiple imputation, a statistically rigorous approach that approximates missing data and preserves sample size, may be an improvement over complete case analysis. The present study aims to evaluate the impact of using multiple imputation in comparison with complete case analysis for assessing the associations between preoperative laboratory values and adverse outcomes following anterior cervical discectomy and fusion (ACDF) procedures. This is a retrospective review of prospectively collected data. Patients undergoing one-level ACDF were identified in NSQIP 2012-2015. Perioperative adverse outcome variables assessed included the occurrence of any adverse event, severe adverse events, and hospital readmission. Missing preoperative albumin and hematocrit values were handled using complete case analysis and multiple imputation. These preoperative laboratory levels were then tested for associations with 30-day postoperative outcomes using logistic regression. A total of 11,999 patients were included. Of this cohort, 63.5% of patients had missing preoperative albumin and 9.9% had missing preoperative hematocrit. When using complete case analysis, only 4,311 patients were studied. The removed patients were significantly younger, healthier, of a common body mass index, and male. Logistic regression analysis failed to identify either preoperative hypoalbuminemia or preoperative anemia as significantly associated with adverse outcomes. When employing multiple imputation, all 11,999 patients were included. Preoperative hypoalbuminemia was significantly associated with the occurrence of any adverse event and severe adverse events. Preoperative anemia was significantly associated with the

  2. On the Interpretation and Use of Mediation: Multiple Perspectives on Mediation Analysis

    Science.gov (United States)

    Agler, Robert; De Boeck, Paul

    2017-01-01

    Mediation analysis has become a very popular approach in psychology, and it is one that is associated with multiple perspectives that are often at odds, often implicitly. Explicitly discussing these perspectives and their motivations, advantages, and disadvantages can help to provide clarity to conversations and research regarding the use and refinement of mediation models. We discuss five such pairs of perspectives on mediation analysis, their associated advantages and disadvantages, and their implications: with vs. without a mediation hypothesis, specific effects vs. a global model, directness vs. indirectness of causation, effect size vs. null hypothesis testing, and hypothesized vs. alternative explanations. Discussion of the perspectives is facilitated by a small simulation study. Some philosophical and linguistic considerations are briefly discussed, as well as some other perspectives we do not develop here. PMID:29187828

  3. On the Interpretation and Use of Mediation: Multiple Perspectives on Mediation Analysis.

    Science.gov (United States)

    Agler, Robert; De Boeck, Paul

    2017-01-01

    Mediation analysis has become a very popular approach in psychology, and it is one that is associated with multiple perspectives that are often at odds, often implicitly. Explicitly discussing these perspectives and their motivations, advantages, and disadvantages can help to provide clarity to conversations and research regarding the use and refinement of mediation models. We discuss five such pairs of perspectives on mediation analysis, their associated advantages and disadvantages, and their implications: with vs. without a mediation hypothesis, specific effects vs. a global model, directness vs. indirectness of causation, effect size vs. null hypothesis testing, and hypothesized vs. alternative explanations. Discussion of the perspectives is facilitated by a small simulation study. Some philosophical and linguistic considerations are briefly discussed, as well as some other perspectives we do not develop here.

  4. Alternative approaches to reliability modeling of a multiple engineered barrier system

    International Nuclear Information System (INIS)

    Ananda, M.M.A.; Singh, A.K.

    1994-01-01

    The lifetime of the engineered barrier system used for containment of high-level radioactive waste will significantly impact the total performance of a geological repository facility. Currently two types of designs are under consideration for an engineered barrier system, single engineered barrier system and multiple engineered barrier system. Multiple engineered barrier system consists of several metal barriers and the waste form (cladding). Some recent work show that a significant improvement of performance can be achieved by utilizing multiple engineered barrier systems. Considering sequential failures for each barrier, we model the reliability of the multiple engineered barrier system. Weibull and exponential lifetime distributions are used through out the analysis. Furthermore, the number of failed engineered barrier systems in a repository at a given time is modeled using a poisson approximation

  5. A minimally invasive multiple marker approach allows highly efficient detection of meningioma tumors

    Directory of Open Access Journals (Sweden)

    Meese Eckart

    2006-12-01

    Full Text Available Abstract Background The development of effective frameworks that permit an accurate diagnosis of tumors, especially in their early stages, remains a grand challenge in the field of bioinformatics. Our approach uses statistical learning techniques applied to multiple antigen tumor antigen markers utilizing the immune system as a very sensitive marker of molecular pathological processes. For validation purposes we choose the intracranial meningioma tumors as model system since they occur very frequently, are mostly benign, and are genetically stable. Results A total of 183 blood samples from 93 meningioma patients (WHO stages I-III and 90 healthy controls were screened for seroreactivity with a set of 57 meningioma-associated antigens. We tested several established statistical learning methods on the resulting reactivity patterns using 10-fold cross validation. The best performance was achieved by Naïve Bayes Classifiers. With this classification method, our framework, called Minimally Invasive Multiple Marker (MIMM approach, yielded a specificity of 96.2%, a sensitivity of 84.5%, and an accuracy of 90.3%, the respective area under the ROC curve was 0.957. Detailed analysis revealed that prediction performs particularly well on low-grade (WHO I tumors, consistent with our goal of early stage tumor detection. For these tumors the best classification result with a specificity of 97.5%, a sensitivity of 91.3%, an accuracy of 95.6%, and an area under the ROC curve of 0.971 was achieved using a set of 12 antigen markers only. This antigen set was detected by a subset selection method based on Mutual Information. Remarkably, our study proves that the inclusion of non-specific antigens, detected not only in tumor but also in normal sera, increases the performance significantly, since non-specific antigens contribute additional diagnostic information. Conclusion Our approach offers the possibility to screen members of risk groups as a matter of routine

  6. Application of algorithms and artificial-intelligence approach for locating multiple harmonics in distribution systems

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Y.-Y.; Chen, Y.-C. [Chung Yuan University (China). Dept. of Electrical Engineering

    1999-05-01

    A new method is proposed for locating multiple harmonic sources in distribution systems. The proposed method first determines the proper locations for metering measurement using fuzzy clustering. Next, an artificial neural network based on the back-propagation approach is used to identify the most likely location for multiple harmonic sources. A set of systematic algorithmic steps is developed until all harmonic locations are identified. The simulation results for an 18-busbar system show that the proposed method is very efficient in locating the multiple harmonics in a distribution system. (author)

  7. Effectiveness of Cognitive Existential Approach on Decreasing Demoralization in Women with Multiple Sclerosis

    Directory of Open Access Journals (Sweden)

    Nasim Pakniya

    2015-12-01

    Full Text Available Objectives: Multiple Sclerosis is the most prevalent central nervous system diseases thatdue to being chronic, frequent recurrence, uncertainty about its progress, and disability, can lead to various distresses as well as demoralization . Rehabilitation method based on Cognitive-Existential therapy is an integratedapproach which can help to decrease demoralization syndrome in these patients. This study aimed to exploring effectiveness of rehabilitation method based on Cognitive-Existential approach on decreasing demoralization syndrome in patients with MS. Methods: Single subject design is used in this study. Among women who had referred to Tehran MS Association, 3 women (aged between 20-40 were selected through purposeful sampling and separately participated in 10 sessions (90 minutes. Participants were assessed during 7 phases of intervention (2 baselines, 3 measurement during intervention, 2 follow-up through Demoralization Syndrome Scale (2004 and Cognitive Distortion scale (2010. Data were analyzed by calculating process variation index and visual analysis. Results: Comparing patients with MS scores on the diagram during 7 time measurement and calculating recovery percentage, represent decreasing in demoralization syndrome score scale. Discussions: Findings showed that rehabilitation method based on Cognitive Existential approach can decrease demoralization syndrome in patients with MS.

  8. Citation Patterns of Engineering, Statistics, and Computer Science Researchers: An Internal and External Citation Analysis across Multiple Engineering Subfields

    Science.gov (United States)

    Kelly, Madeline

    2015-01-01

    This study takes a multidimensional approach to citation analysis, examining citations in multiple subfields of engineering, from both scholarly journals and doctoral dissertations. The three major goals of the study are to determine whether there are differences between citations drawn from dissertations and those drawn from journal articles; to…

  9. Trace element analysis of environmental samples by multiple prompt gamma-ray analysis method

    International Nuclear Information System (INIS)

    Oshima, Masumi; Matsuo, Motoyuki; Shozugawa, Katsumi

    2011-01-01

    The multiple γ-ray detection method has been proved to be a high-resolution and high-sensitivity method in application to nuclide quantification. The neutron prompt γ-ray analysis method is successfully extended by combining it with the γ-ray detection method, which is called Multiple prompt γ-ray analysis, MPGA. In this review we show the principle of this method and its characteristics. Several examples of its application to environmental samples, especially river sediments in the urban area and sea sediment samples are also described. (author)

  10. Multiple Learning Approaches in the Professional Development of School Leaders -- Theoretical Perspectives and Empirical Findings on Self-assessment and Feedback

    Science.gov (United States)

    Huber, Stephan Gerhard

    2013-01-01

    This article investigates the use of multiple learning approaches and different modes and types of learning in the (continuous) professional development (PD) of school leaders, particularly the use of self-assessment and feedback. First, formats and multiple approaches to professional learning are described. Second, a possible approach to…

  11. The application of multiple intelligence approach to the learning of human circulatory system

    Science.gov (United States)

    Kumalasari, Lita; Yusuf Hilmi, A.; Priyandoko, Didik

    2017-11-01

    The purpose of this study is to offer an alternative teaching approach or strategies which able to accommodate students’ different ability, intelligence and learning style. Also can gives a new idea for the teacher as a facilitator for exploring how to teach the student in creative ways and more student-center activities, for a lesson such as circulatory system. This study was carried out at one private school in Bandung involved eight students to see their responses toward the lesson that delivered by using Multiple Intelligence approach which is include Linguistic, Logical-Mathematical, Visual-Spatial, Musical, Bodily-Kinesthetic, Interpersonal, Intrapersonal, and Naturalistic. Students were test by using MI test based on Howard Gardner’s MI model to see their dominant intelligence. The result showed the percentage of top three ranks of intelligence are Bodily-Kinesthetic (73%), Visual-Spatial (68%), and Logical-Mathematical (61%). The learning process is given by using some different multimedia and activities to engaged their learning style and intelligence such as mini experiment, short clip, and questions. Student response is given by using self-assessment and the result is all students said the lesson gives them a knowledge and skills that useful for their life, they are clear with the explanation given, they didn’t find difficulties to understand the lesson and can complete the assignment given. At the end of the study, it is reveal that the students who are learned by Multiple Intelligence instructional approach have more enhance to the lesson given. It’s also found out that the students participated in the learning process which Multiple Intelligence approach was applied enjoyed the activities and have great fun.

  12. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis.

    Science.gov (United States)

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-03-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.

  13. Interactions between cadmium and decabrominated diphenyl ether on blood cells count in rats-Multiple factorial regression analysis.

    Science.gov (United States)

    Curcic, Marijana; Buha, Aleksandra; Stankovic, Sanja; Milovanovic, Vesna; Bulat, Zorica; Đukić-Ćosić, Danijela; Antonijević, Evica; Vučinić, Slavica; Matović, Vesna; Antonijevic, Biljana

    2017-02-01

    The objective of this study was to assess toxicity of Cd and BDE-209 mixture on haematological parameters in subacutely exposed rats and to determine the presence and type of interactions between these two chemicals using multiple factorial regression analysis. Furthermore, for the assessment of interaction type, an isobologram based methodology was applied and compared with multiple factorial regression analysis. Chemicals were given by oral gavage to the male Wistar rats weighing 200-240g for 28days. Animals were divided in 16 groups (8/group): control vehiculum group, three groups of rats were treated with 2.5, 7.5 or 15mg Cd/kg/day. These doses were chosen on the bases of literature data and reflect relatively high Cd environmental exposure, three groups of rats were treated with 1000, 2000 or 4000mg BDE-209/kg/bw/day, doses proved to induce toxic effects in rats. Furthermore, nine groups of animals were treated with different mixtures of Cd and BDE-209 containing doses of Cd and BDE-209 stated above. Blood samples were taken at the end of experiment and red blood cells, white blood cells and platelets counts were determined. For interaction assessment multiple factorial regression analysis and fitted isobologram approach were used. In this study, we focused on multiple factorial regression analysis as a method for interaction assessment. We also investigated the interactions between Cd and BDE-209 by the derived model for the description of the obtained fitted isobologram curves. Current study indicated that co-exposure to Cd and BDE-209 can result in significant decrease in RBC count, increase in WBC count and decrease in PLT count, when compared with controls. Multiple factorial regression analysis used for the assessment of interactions type between Cd and BDE-209 indicated synergism for the effect on RBC count and no interactions i.e. additivity for the effects on WBC and PLT counts. On the other hand, isobologram based approach showed slight antagonism

  14. A Multiple Streams analysis of the decisions to fund gender-neutral HPV vaccination in Canada.

    Science.gov (United States)

    Shapiro, Gilla K; Guichon, Juliet; Prue, Gillian; Perez, Samara; Rosberger, Zeev

    2017-07-01

    In Canada, the human papillomavirus (HPV) vaccine is licensed and recommended for females and males. Although all Canadian jurisdictions fund school-based HPV vaccine programs for girls, only six jurisdictions fund school-based HPV vaccination for boys. The research aimed to analyze the factors that underpin government decisions to fund HPV vaccine for boys using a theoretical policy model, Kingdon's Multiple Streams framework. This approach assesses policy development by examining three concurrent, but independent, streams that guide analysis: Problem Stream, Policy Stream, and Politics Stream. Analysis from the Problem Stream highlights that males are affected by HPV-related diseases and are involved in transmitting HPV infection to their sexual partners. Policy Stream analysis makes clear that while the inclusion of males in HPV vaccine programs is suitable, equitable, and acceptable; there is debate regarding cost-effectiveness. Politics Stream analysis identifies the perspectives of six different stakeholder groups and highlights the contribution of government officials at the provincial and territorial level. Kingdon's Multiple Streams framework helps clarify the opportunities and barriers for HPV vaccine policy change. This analysis identified that the interpretation of cost-effectiveness models and advocacy of stakeholders such as citizen-advocates and HPV-affected politicians have been particularly important in galvanizing policy change. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. Measurement and Analysis of Multiple Output Transient Propagation in BJT Analog Circuits

    Science.gov (United States)

    Roche, Nicolas J.-H.; Khachatrian, A.; Warner, J. H.; Buchner, S. P.; McMorrow, D.; Clymer, D. A.

    2016-08-01

    The propagation of Analog Single Event Transients (ASETs) to multiple outputs of Bipolar Junction Transistor (BJTs) Integrated Circuits (ICs) is reported for the first time. The results demonstrate that ASETs can appear at several outputs of a BJT amplifier or comparator as a result of a single ion or single laser pulse strike at a single physical location on the chip of a large-scale integrated BJT analog circuit. This is independent of interconnect cross-talk or charge-sharing effects. Laser experiments, together with SPICE simulations and analysis of the ASET's propagation in the s-domain are used to explain how multiple-output transients (MOTs) are generated and propagate in the device. This study demonstrates that both the charge collection associated with an ASET and the ASET's shape, commonly used to characterize the propagation of SETs in devices and systems, are unable to explain quantitatively how MOTs propagate through an integrated analog circuit. The analysis methodology adopted here involves combining the Fourier transform of the propagating signal and the current-source transfer function in the s-domain. This approach reveals the mechanisms involved in the transient signal propagation from its point of generation to one or more outputs without the signal following a continuous interconnect path.

  16. Multiple-Group Analysis Using the sem Package in the R System

    Science.gov (United States)

    Evermann, Joerg

    2010-01-01

    Multiple-group analysis in covariance-based structural equation modeling (SEM) is an important technique to ensure the invariance of latent construct measurements and the validity of theoretical models across different subpopulations. However, not all SEM software packages provide multiple-group analysis capabilities. The sem package for the R…

  17. A Quantitative and Combinatorial Approach to Non-Linear Meanings of Multiplication

    Science.gov (United States)

    Tillema, Erik; Gatza, Andrew

    2016-01-01

    We provide a conceptual analysis of how combinatorics problems have the potential to support students to establish non-linear meanings of multiplication (NLMM). The problems we analyze we have used in a series of studies with 6th, 8th, and 10th grade students. We situate the analysis in prior work on students' quantitative and multiplicative…

  18. Analysis of multiple scattering effects in optical Doppler tomography

    DEFF Research Database (Denmark)

    Yura, H.T.; Thrane, L.; Andersen, Peter E.

    2005-01-01

    Optical Doppler tomography (ODT) combines Doppler velocimetry and optical coherence tomography (OCT) to obtain high-resolution cross-sectional imaging of particle flow velocity in scattering media such as the human retina and skin. Here, we present the results of a theoretical analysis of ODT where...... multiple scattering effects are included. The purpose of this analysis is to determine how multiple scattering affects the estimation of the depth-resolved localized flow velocity. Depth-resolved velocity estimates are obtained directly from the corresponding mean or standard deviation of the observed...

  19. Multiple scattering problems in heavy ion elastic recoil detection analysis

    International Nuclear Information System (INIS)

    Johnston, P.N.; El Bouanani, M.; Stannard, W.B.; Bubb, I.F.; Cohen, D.D.; Dytlewski, N.; Siegele, R.

    1998-01-01

    A number of groups use Heavy Ion Elastic Recoil Detection Analysis (HIERDA) to study materials science problems. Nevertheless, there is no standard methodology for the analysis of HIERDA spectra. To overcome this deficiency we have been establishing codes for 2-dimensional data analysis. A major problem involves the effects of multiple and plural scattering which are very significant, even for quite thin (∼100 nm) layers of the very heavy elements. To examine the effects of multiple scattering we have made comparisons between the small-angle model of Sigmund et al. and TRIM calculations. (authors)

  20. Analysis of (n, 2n) multiplication in lead

    International Nuclear Information System (INIS)

    Segev, M.

    1984-01-01

    Lead is being considered as a possible amplifier of neutrons for fusion blankets. A simple one-group model of neutron multiplications in Pb is presented. Given the 14 MeV neutron cross section on Pb, the model predicts the multiplication. Given measured multiplications, the model enables the determination of the (n, 2n) and transport cross sections. Required for the model are: P-the collision probability for source neutrons in the Pb body-and W- an average collision probability for non-virgin, non-degraded neutrons. In simple geometries, such as a source in the center of a spherical shell, P and an approximate W can be expressed analytically in terms of shell dimensions and the Pb transport cross section. The model was applied to Takahashi's measured multiplications in Pb shells in order to understand the apparent very high multiplicative power of Pb. The results of the analysis are not consistent with basic energy-balance and cross section magnitude constraints in neutron interaction theory. (author)

  1. A Multiple Identity Approach to Gender: Identification with Women, Identification with Feminists, and Their Interaction

    Directory of Open Access Journals (Sweden)

    Jolien A. van Breen

    2017-06-01

    Full Text Available Across four studies, we examine multiple identities in the context of gender and propose that women's attitudes toward gender group membership are governed by two largely orthogonal dimensions of gender identity: identification with women and identification with feminists. We argue that identification with women reflects attitudes toward the content society gives to group membership: what does it mean to be a woman in terms of group characteristics, interests and values? Identification with feminists, on the other hand, is a politicized identity dimension reflecting attitudes toward the social position of the group: what does it mean to be a woman in terms of disadvantage, inequality, and relative status? We examine the utility of this multiple identity approach in four studies. Study 1 showed that identification with women reflects attitudes toward group characteristics, such as femininity and self-stereotyping, while identification with feminists reflects attitudes toward the group's social position, such as perceived sexism. The two dimensions are shown to be largely independent, and as such provide support for the multiple identity approach. In Studies 2–4, we examine the utility of this multiple identity approach in predicting qualitative differences in gender attitudes. Results show that specific combinations of identification with women and feminists predicted attitudes toward collective action and gender stereotypes. Higher identification with feminists led to endorsement of radical collective action (Study 2 and critical attitudes toward gender stereotypes (Studies 3–4, especially at lower levels of identification with women. The different combinations of high vs. low identification with women and feminists can be thought of as reflecting four theoretical identity “types.” A woman can be (1 strongly identified with neither women nor feminists (“low identifier”, (2 strongly identified with women but less so with feminists (

  2. A Multiple Identity Approach to Gender: Identification with Women, Identification with Feminists, and Their Interaction

    Science.gov (United States)

    van Breen, Jolien A.; Spears, Russell; Kuppens, Toon; de Lemus, Soledad

    2017-01-01

    Across four studies, we examine multiple identities in the context of gender and propose that women's attitudes toward gender group membership are governed by two largely orthogonal dimensions of gender identity: identification with women and identification with feminists. We argue that identification with women reflects attitudes toward the content society gives to group membership: what does it mean to be a woman in terms of group characteristics, interests and values? Identification with feminists, on the other hand, is a politicized identity dimension reflecting attitudes toward the social position of the group: what does it mean to be a woman in terms of disadvantage, inequality, and relative status? We examine the utility of this multiple identity approach in four studies. Study 1 showed that identification with women reflects attitudes toward group characteristics, such as femininity and self-stereotyping, while identification with feminists reflects attitudes toward the group's social position, such as perceived sexism. The two dimensions are shown to be largely independent, and as such provide support for the multiple identity approach. In Studies 2–4, we examine the utility of this multiple identity approach in predicting qualitative differences in gender attitudes. Results show that specific combinations of identification with women and feminists predicted attitudes toward collective action and gender stereotypes. Higher identification with feminists led to endorsement of radical collective action (Study 2) and critical attitudes toward gender stereotypes (Studies 3–4), especially at lower levels of identification with women. The different combinations of high vs. low identification with women and feminists can be thought of as reflecting four theoretical identity “types.” A woman can be (1) strongly identified with neither women nor feminists (“low identifier”), (2) strongly identified with women but less so with feminists (

  3. A Multiple Identity Approach to Gender: Identification with Women, Identification with Feminists, and Their Interaction.

    Science.gov (United States)

    van Breen, Jolien A; Spears, Russell; Kuppens, Toon; de Lemus, Soledad

    2017-01-01

    Across four studies, we examine multiple identities in the context of gender and propose that women's attitudes toward gender group membership are governed by two largely orthogonal dimensions of gender identity: identification with women and identification with feminists. We argue that identification with women reflects attitudes toward the content society gives to group membership: what does it mean to be a woman in terms of group characteristics, interests and values? Identification with feminists, on the other hand, is a politicized identity dimension reflecting attitudes toward the social position of the group: what does it mean to be a woman in terms of disadvantage, inequality, and relative status? We examine the utility of this multiple identity approach in four studies. Study 1 showed that identification with women reflects attitudes toward group characteristics, such as femininity and self-stereotyping, while identification with feminists reflects attitudes toward the group's social position, such as perceived sexism. The two dimensions are shown to be largely independent, and as such provide support for the multiple identity approach. In Studies 2-4, we examine the utility of this multiple identity approach in predicting qualitative differences in gender attitudes. Results show that specific combinations of identification with women and feminists predicted attitudes toward collective action and gender stereotypes. Higher identification with feminists led to endorsement of radical collective action (Study 2) and critical attitudes toward gender stereotypes (Studies 3-4), especially at lower levels of identification with women. The different combinations of high vs. low identification with women and feminists can be thought of as reflecting four theoretical identity "types." A woman can be (1) strongly identified with neither women nor feminists ("low identifier"), (2) strongly identified with women but less so with feminists ("traditional identifier"), (3

  4. The multiple imputation method: a case study involving secondary data analysis.

    Science.gov (United States)

    Walani, Salimah R; Cleland, Charles M

    2015-05-01

    To illustrate with the example of a secondary data analysis study the use of the multiple imputation method to replace missing data. Most large public datasets have missing data, which need to be handled by researchers conducting secondary data analysis studies. Multiple imputation is a technique widely used to replace missing values while preserving the sample size and sampling variability of the data. The 2004 National Sample Survey of Registered Nurses. The authors created a model to impute missing values using the chained equation method. They used imputation diagnostics procedures and conducted regression analysis of imputed data to determine the differences between the log hourly wages of internationally educated and US-educated registered nurses. The authors used multiple imputation procedures to replace missing values in a large dataset with 29,059 observations. Five multiple imputed datasets were created. Imputation diagnostics using time series and density plots showed that imputation was successful. The authors also present an example of the use of multiple imputed datasets to conduct regression analysis to answer a substantive research question. Multiple imputation is a powerful technique for imputing missing values in large datasets while preserving the sample size and variance of the data. Even though the chained equation method involves complex statistical computations, recent innovations in software and computation have made it possible for researchers to conduct this technique on large datasets. The authors recommend nurse researchers use multiple imputation methods for handling missing data to improve the statistical power and external validity of their studies.

  5. [Concept analysis of a participatory approach to occupational safety and health].

    Science.gov (United States)

    Yoshikawa, Etsuko

    2013-01-01

    The purpose of this study was to analyze a participatory approach to occupational safety and health, and to examine the possibility of applying the concept to the practice and research of occupational safety and health. According to Rodger's method, descriptive data concerning antecedents, attributes and consequences were qualitatively analyzed. A total of 39 articles were selected for analysis. Attributes with a participatory approach were: "active involvement of both workers and employers", "focusing on action-oriented low-cost and multiple area improvements based on good practices", "the process of emphasis on consensus building", and "utilization of a local network". Antecedents of the participatory approach were classified as: "existing risks at the workplace", "difficulty of occupational safety and health activities", "characteristics of the workplace and workers", and "needs for the workplace". The derived consequences were: "promoting occupational safety and health activities", "emphasis of self-management", "creation of safety and healthy workplace", and "contributing to promotion of quality of life and productivity". A participatory approach in occupational safety and health is defined as, the process of emphasis on consensus building to promote occupational safety and health activities with emphasis on self-management, which focuses on action-oriented low-cost and multiple area improvements based on good practices with active involvement of both workers and employers through utilization of local networks. We recommend that the role of the occupational health professional be clarified and an evaluation framework be established for the participatory approach to promote occupational safety and health activities by involving both workers and employers.

  6. Automatic visual tracking and social behaviour analysis with multiple mice.

    Directory of Open Access Journals (Sweden)

    Luca Giancardo

    Full Text Available Social interactions are made of complex behavioural actions that might be found in all mammalians, including humans and rodents. Recently, mouse models are increasingly being used in preclinical research to understand the biological basis of social-related pathologies or abnormalities. However, reliable and flexible automatic systems able to precisely quantify social behavioural interactions of multiple mice are still missing. Here, we present a system built on two components. A module able to accurately track the position of multiple interacting mice from videos, regardless of their fur colour or light settings, and a module that automatically characterise social and non-social behaviours. The behavioural analysis is obtained by deriving a new set of specialised spatio-temporal features from the tracker output. These features are further employed by a learning-by-example classifier, which predicts for each frame and for each mouse in the cage one of the behaviours learnt from the examples given by the experimenters. The system is validated on an extensive set of experimental trials involving multiple mice in an open arena. In a first evaluation we compare the classifier output with the independent evaluation of two human graders, obtaining comparable results. Then, we show the applicability of our technique to multiple mice settings, using up to four interacting mice. The system is also compared with a solution recently proposed in the literature that, similarly to us, addresses the problem with a learning-by-examples approach. Finally, we further validated our automatic system to differentiate between C57B/6J (a commonly used reference inbred strain and BTBR T+tf/J (a mouse model for autism spectrum disorders. Overall, these data demonstrate the validity and effectiveness of this new machine learning system in the detection of social and non-social behaviours in multiple (>2 interacting mice, and its versatility to deal with different

  7. Multiple Feature Fusion Based on Co-Training Approach and Time Regularization for Place Classification in Wearable Video

    Directory of Open Access Journals (Sweden)

    Vladislavs Dovgalecs

    2013-01-01

    Full Text Available The analysis of video acquired with a wearable camera is a challenge that multimedia community is facing with the proliferation of such sensors in various applications. In this paper, we focus on the problem of automatic visual place recognition in a weakly constrained environment, targeting the indexing of video streams by topological place recognition. We propose to combine several machine learning approaches in a time regularized framework for image-based place recognition indoors. The framework combines the power of multiple visual cues and integrates the temporal continuity information of video. We extend it with computationally efficient semisupervised method leveraging unlabeled video sequences for an improved indexing performance. The proposed approach was applied on challenging video corpora. Experiments on a public and a real-world video sequence databases show the gain brought by the different stages of the method.

  8. Multiple flood vulnerability assessment approach based on fuzzy comprehensive evaluation method and coordinated development degree model.

    Science.gov (United States)

    Yang, Weichao; Xu, Kui; Lian, Jijian; Bin, Lingling; Ma, Chao

    2018-05-01

    Flood is a serious challenge that increasingly affects the residents as well as policymakers. Flood vulnerability assessment is becoming gradually relevant in the world. The purpose of this study is to develop an approach to reveal the relationship between exposure, sensitivity and adaptive capacity for better flood vulnerability assessment, based on the fuzzy comprehensive evaluation method (FCEM) and coordinated development degree model (CDDM). The approach is organized into three parts: establishment of index system, assessment of exposure, sensitivity and adaptive capacity, and multiple flood vulnerability assessment. Hydrodynamic model and statistical data are employed for the establishment of index system; FCEM is used to evaluate exposure, sensitivity and adaptive capacity; and CDDM is applied to express the relationship of the three components of vulnerability. Six multiple flood vulnerability types and four levels are proposed to assess flood vulnerability from multiple perspectives. Then the approach is applied to assess the spatiality of flood vulnerability in Hainan's eastern area, China. Based on the results of multiple flood vulnerability, a decision-making process for rational allocation of limited resources is proposed and applied to the study area. The study shows that multiple flood vulnerability assessment can evaluate vulnerability more completely, and help decision makers learn more information about making decisions in a more comprehensive way. In summary, this study provides a new way for flood vulnerability assessment and disaster prevention decision. Copyright © 2018 Elsevier Ltd. All rights reserved.

  9. Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach.

    Directory of Open Access Journals (Sweden)

    Nilotpal Chowdhury

    Full Text Available Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis.The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets.Four microarray series (having 742 patients were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate - adjusted for expression of Cell cycle related genes and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA.Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed.To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and

  10. Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach.

    Science.gov (United States)

    Chowdhury, Nilotpal; Sapru, Shantanu

    2015-01-01

    Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate - adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting

  11. An efficient Bayesian meta-analysis approach for studying cross-phenotype genetic associations.

    Directory of Open Access Journals (Sweden)

    Arunabha Majumdar

    2018-02-01

    Full Text Available Simultaneous analysis of genetic associations with multiple phenotypes may reveal shared genetic susceptibility across traits (pleiotropy. For a locus exhibiting overall pleiotropy, it is important to identify which specific traits underlie this association. We propose a Bayesian meta-analysis approach (termed CPBayes that uses summary-level data across multiple phenotypes to simultaneously measure the evidence of aggregate-level pleiotropic association and estimate an optimal subset of traits associated with the risk locus. This method uses a unified Bayesian statistical framework based on a spike and slab prior. CPBayes performs a fully Bayesian analysis by employing the Markov Chain Monte Carlo (MCMC technique Gibbs sampling. It takes into account heterogeneity in the size and direction of the genetic effects across traits. It can be applied to both cohort data and separate studies of multiple traits having overlapping or non-overlapping subjects. Simulations show that CPBayes can produce higher accuracy in the selection of associated traits underlying a pleiotropic signal than the subset-based meta-analysis ASSET. We used CPBayes to undertake a genome-wide pleiotropic association study of 22 traits in the large Kaiser GERA cohort and detected six independent pleiotropic loci associated with at least two phenotypes. This includes a locus at chromosomal region 1q24.2 which exhibits an association simultaneously with the risk of five different diseases: Dermatophytosis, Hemorrhoids, Iron Deficiency, Osteoporosis and Peripheral Vascular Disease. We provide an R-package 'CPBayes' implementing the proposed method.

  12. Three-dimensional finite elements for the analysis of soil contamination using a multiple-porosity approach

    Science.gov (United States)

    El-Zein, Abbas; Carter, John P.; Airey, David W.

    2006-06-01

    A three-dimensional finite-element model of contaminant migration in fissured clays or contaminated sand which includes multiple sources of non-equilibrium processes is proposed. The conceptual framework can accommodate a regular network of fissures in 1D, 2D or 3D and immobile solutions in the macro-pores of aggregated topsoils, as well as non-equilibrium sorption. A Galerkin weighted-residual statement for the three-dimensional form of the equations in the Laplace domain is formulated. Equations are discretized using linear and quadratic prism elements. The system of algebraic equations is solved in the Laplace domain and solution is inverted to the time domain numerically. The model is validated and its scope is illustrated through the analysis of three problems: a waste repository deeply buried in fissured clay, a storage tank leaking into sand and a sanitary landfill leaching into fissured clay over a sand aquifer.

  13. Continuum multiple-scattering approach to electron-molecule scattering and molecular photoionization

    International Nuclear Information System (INIS)

    Dehmer, J.L.; Dill, D.

    1979-01-01

    The multiple-scattering approach to the electronic continuum of molecules is described. The continuum multiple-scattering model (CMSM) was developed as a survey tool and, as such was required to satisfy two requirements. First, it had to have a very broad scope, which means (i) molecules of arbitrary geometry and complexity containing any atom in the periodic system, (ii) continuum electron energies from 0-1000 eV, and (iii) capability to treat a large range of processes involving both photoionization and electron scattering. Second, the structure of the theory was required to lend itself to transparent, physical interpretation of major spectral features such as shape resonances. A comprehensive theoretical framework for the continuum multiple scattering method is presented, as well as its applications to electron-molecule scattering and molecular photoionization. Highlights of recent applications in these two areas are reviewed. The major impact of the resulting studies over the last few years has been to establish the importance of shape resonances in electron collisions and photoionization of practically all (non-hydride) molecules

  14. Personalization of models with many model parameters: an efficient sensitivity analysis approach.

    Science.gov (United States)

    Donders, W P; Huberts, W; van de Vosse, F N; Delhaas, T

    2015-10-01

    Uncertainty quantification and global sensitivity analysis are indispensable for patient-specific applications of models that enhance diagnosis or aid decision-making. Variance-based sensitivity analysis methods, which apportion each fraction of the output uncertainty (variance) to the effects of individual input parameters or their interactions, are considered the gold standard. The variance portions are called the Sobol sensitivity indices and can be estimated by a Monte Carlo (MC) approach (e.g., Saltelli's method [1]) or by employing a metamodel (e.g., the (generalized) polynomial chaos expansion (gPCE) [2, 3]). All these methods require a large number of model evaluations when estimating the Sobol sensitivity indices for models with many parameters [4]. To reduce the computational cost, we introduce a two-step approach. In the first step, a subset of important parameters is identified for each output of interest using the screening method of Morris [5]. In the second step, a quantitative variance-based sensitivity analysis is performed using gPCE. Efficient sampling strategies are introduced to minimize the number of model runs required to obtain the sensitivity indices for models considering multiple outputs. The approach is tested using a model that was developed for predicting post-operative flows after creation of a vascular access for renal failure patients. We compare the sensitivity indices obtained with the novel two-step approach with those obtained from a reference analysis that applies Saltelli's MC method. The two-step approach was found to yield accurate estimates of the sensitivity indices at two orders of magnitude lower computational cost. Copyright © 2015 John Wiley & Sons, Ltd.

  15. Multiple-scattering formalism for correlated systems: A KKR-DMFT approach

    International Nuclear Information System (INIS)

    Minar, J.; Perlov, A.; Ebert, H.; Chioncel, L.; Katsnelson, M. I.; Lichtenstein, A.I.

    2005-01-01

    We present a charge and self-energy self-consistent computational scheme for correlated systems based on the Korringa-Kohn-Rostoker (KKR) multiple scattering theory with the many-body effects described by the means of dynamical mean field theory (DMFT). The corresponding local multiorbital and energy dependent self-energy is included into the set of radial differential equations for the single-site wave functions. The KKR Green's function is written in terms of the multiple scattering path operator, the later one being evaluated using the single-site solution for the t-matrix that in turn is determined by the wave functions. An appealing feature of this approach is that it allows to consider local quantum and disorder fluctuations on the same footing. Within the coherent potential approximation (CPA) the correlated atoms are placed into a combined effective medium determined by the DMFT self-consistency condition. Results of corresponding calculations for pure Fe, Ni, and Fe x Ni 1-x alloys are presented

  16. A multi-disciplinary approach for the integrated assessment of multiple risks in delta areas.

    Science.gov (United States)

    Sperotto, Anna; Torresan, Silvia; Critto, Andrea; Marcomini, Antonio

    2016-04-01

    The assessment of climate change related risks is notoriously difficult due to the complex and uncertain combinations of hazardous events that might happen, the multiplicity of physical processes involved, the continuous changes and interactions of environmental and socio-economic systems. One important challenge lies in predicting and modelling cascades of natural and man -made hazard events which can be triggered by climate change, encompassing different spatial and temporal scales. Another regard the potentially difficult integration of environmental, social and economic disciplines in the multi-risk concept. Finally, the effective interaction between scientists and stakeholders is essential to ensure that multi-risk knowledge is translated into efficient adaptation and management strategies. The assessment is even more complex at the scale of deltaic systems which are particularly vulnerable to global environmental changes, due to the fragile equilibrium between the presence of valuable natural ecosystems and relevant economic activities. Improving our capacity to assess the combined effects of multiple hazards (e.g. sea-level rise, storm surges, reduction in sediment load, local subsidence, saltwater intrusion) is therefore essential to identify timely opportunities for adaptation. A holistic multi-risk approach is here proposed to integrate terminology, metrics and methodologies from different research fields (i.e. environmental, social and economic sciences) thus creating shared knowledge areas to advance multi risk assessment and management in delta regions. A first testing of the approach, including the application of Bayesian network analysis for the assessment of impacts of climate change on key natural systems (e.g. wetlands, protected areas, beaches) and socio-economic activities (e.g. agriculture, tourism), is applied in the Po river delta in Northern Italy. The approach is based on a bottom-up process involving local stakeholders early in different

  17. Using Correspondence Analysis in Multiple Case Studies

    NARCIS (Netherlands)

    Kienstra, Natascha; van der Heijden, Peter G.M.

    2015-01-01

    In qualitative research of multiple case studies, Miles and Huberman proposed to summarize the separate cases in a so-called meta-matrix that consists of cases by variables. Yin discusses cross-case synthesis to study this matrix. We propose correspondence analysis (CA) as a useful tool to study

  18. Using correspondence analysis in multiple case studies

    NARCIS (Netherlands)

    Kienstra, N.H.H.; van der Heijden, P.G.M.

    2015-01-01

    In qualitative research of multiple case studies, Miles and Huberman proposed to summarize the separate cases in a so-called meta-matrix that consists of cases by variables. Yin discusses cross-case synthesis to study this matrix. We propose correspondence analysis (CA) as a useful tool to study

  19. Approach and landing guidance design for reusable launch vehicle using multiple sliding surfaces technique

    Directory of Open Access Journals (Sweden)

    Xiangdong LIU

    2017-08-01

    Full Text Available An autonomous approach and landing (A&L guidance law is presented in this paper for landing an unpowered reusable launch vehicle (RLV at the designated runway touchdown. Considering the full nonlinear point-mass dynamics, a guidance scheme is developed in three-dimensional space. In order to guarantee a successful A&L movement, the multiple sliding surfaces guidance (MSSG technique is applied to derive the closed-loop guidance law, which stems from higher order sliding mode control theory and has advantage in the finite time reaching property. The global stability of the proposed guidance approach is proved by the Lyapunov-based method. The designed guidance law can generate new trajectories on-line without any specific requirement on off-line analysis except for the information on the boundary conditions of the A&L phase and instantaneous states of the RLV. Therefore, the designed guidance law is flexible enough to target different touchdown points on the runway and is capable of dealing with large initial condition errors resulted from the previous flight phase. Finally, simulation results show the effectiveness of the proposed guidance law in different scenarios.

  20. A new spatial multiple discrete-continuous modeling approach to land use change analysis.

    Science.gov (United States)

    2013-09-01

    This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a : spatially explicit economic structural framework for land-use change decisions. The spatial : MDCP model is capable of predicting both the type and intensit...

  1. Multiple-scale approach for the expansion scaling of superfluid quantum gases

    International Nuclear Information System (INIS)

    Egusquiza, I. L.; Valle Basagoiti, M. A.; Modugno, M.

    2011-01-01

    We present a general method, based on a multiple-scale approach, for deriving the perturbative solutions of the scaling equations governing the expansion of superfluid ultracold quantum gases released from elongated harmonic traps. We discuss how to treat the secular terms appearing in the usual naive expansion in the trap asymmetry parameter ε and calculate the next-to-leading correction for the asymptotic aspect ratio, with significant improvement over the previous proposals.

  2. Numerical Evaluation and Optimization of Multiple Hydraulically Fractured Parameters Using a Flow-Stress-Damage Coupled Approach

    Directory of Open Access Journals (Sweden)

    Yu Wang

    2016-04-01

    Full Text Available Multiple-factor analysis and optimization play a critical role in the the ability to maximizethe stimulated reservoir volume (SRV and the success of economic shale gas production. In this paper, taking the typical continental naturally fractured silty laminae shale in China as anexample, response surface methodology (RSM was employed to optimize multiple hydraulic fracturing parameters to maximize the stimulated area in combination with numerical modeling based on the coupled flow-stress-damage (FSD approach. This paper demonstrates hydraulic fracturing effectiveness by defining two indicesnamelythe stimulated reservoir area (SRA and stimulated silty laminae area (SLA. Seven uncertain parameters, such as laminae thickness, spacing, dip angle, cohesion, internal friction angle (IFA, in situ stress difference (SD, and an operational parameter-injection rate (IR with a reasonable range based on silty Laminae Shale, Southeastern Ordos Basin, are used to fit a response of SRA and SLA as the objective function, and finally identity the optimum design under the parameters based on simultaneously maximizingSRA and SLA. In addition, asensitivity analysis of the influential factors is conducted for SRA and SLA. The aim of the study is to improve the artificial ability to control the fracturing network by means of multi-parameteroptimization. This work promises to provide insights into the effective exploitation of unconventional shale gas reservoirs via optimization of the fracturing design for continental shale, Southeastern Ordos Basin, China.

  3. Analysis and prediction of Multiple-Site Damage (MSD) fatigue crack growth

    Science.gov (United States)

    Dawicke, D. S.; Newman, J. C., Jr.

    1992-08-01

    A technique was developed to calculate the stress intensity factor for multiple interacting cracks. The analysis was verified through comparison with accepted methods of calculating stress intensity factors. The technique was incorporated into a fatigue crack growth prediction model and used to predict the fatigue crack growth life for multiple-site damage (MSD). The analysis was verified through comparison with experiments conducted on uniaxially loaded flat panels with multiple cracks. Configuration with nearly equal and unequal crack distribution were examined. The fatigue crack growth predictions agreed within 20 percent of the experimental lives for all crack configurations considered.

  4. Analysis and prediction of Multiple-Site Damage (MSD) fatigue crack growth

    Science.gov (United States)

    Dawicke, D. S.; Newman, J. C., Jr.

    1992-01-01

    A technique was developed to calculate the stress intensity factor for multiple interacting cracks. The analysis was verified through comparison with accepted methods of calculating stress intensity factors. The technique was incorporated into a fatigue crack growth prediction model and used to predict the fatigue crack growth life for multiple-site damage (MSD). The analysis was verified through comparison with experiments conducted on uniaxially loaded flat panels with multiple cracks. Configuration with nearly equal and unequal crack distribution were examined. The fatigue crack growth predictions agreed within 20 percent of the experimental lives for all crack configurations considered.

  5. Multiple regression and beyond an introduction to multiple regression and structural equation modeling

    CERN Document Server

    Keith, Timothy Z

    2014-01-01

    Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. Covers both MR and SEM, while explaining their relevance to one another Also includes path analysis, confirmatory factor analysis, and latent growth modeling Figures and tables throughout provide examples and illustrate key concepts and techniques For additional resources, please visit: http://tzkeith.com/.

  6. The Effectiveness of Using a Multiple Gating Approach to Discriminate among ADHD Subtypes

    Science.gov (United States)

    Simonsen, Brandi M.; Bullis, Michael D.

    2007-01-01

    This study explored the ability of Systematically Progressive Assessment (SPA), a multiple gating approach for assessing students with attention-deficit/hyperactivity disorder (ADHD), to discriminate between subtypes of ADHD. A total of 48 students with ADHD (ages 6-11) were evaluated with three "gates" of assessment. Logistic regression analysis…

  7. Cross-species multiple environmental stress responses: An integrated approach to identify candidate genes for multiple stress tolerance in sorghum (Sorghum bicolor (L. Moench and related model species.

    Directory of Open Access Journals (Sweden)

    Adugna Abdi Woldesemayat

    Full Text Available Crop response to the changing climate and unpredictable effects of global warming with adverse conditions such as drought stress has brought concerns about food security to the fore; crop yield loss is a major cause of concern in this regard. Identification of genes with multiple responses across environmental stresses is the genetic foundation that leads to crop adaptation to environmental perturbations.In this paper, we introduce an integrated approach to assess candidate genes for multiple stress responses across-species. The approach combines ontology based semantic data integration with expression profiling, comparative genomics, phylogenomics, functional gene enrichment and gene enrichment network analysis to identify genes associated with plant stress phenotypes. Five different ontologies, viz., Gene Ontology (GO, Trait Ontology (TO, Plant Ontology (PO, Growth Ontology (GRO and Environment Ontology (EO were used to semantically integrate drought related information.Target genes linked to Quantitative Trait Loci (QTLs controlling yield and stress tolerance in sorghum (Sorghum bicolor (L. Moench and closely related species were identified. Based on the enriched GO terms of the biological processes, 1116 sorghum genes with potential responses to 5 different stresses, such as drought (18%, salt (32%, cold (20%, heat (8% and oxidative stress (25% were identified to be over-expressed. Out of 169 sorghum drought responsive QTLs associated genes that were identified based on expression datasets, 56% were shown to have multiple stress responses. On the other hand, out of 168 additional genes that have been evaluated for orthologous pairs, 90% were conserved across species for drought tolerance. Over 50% of identified maize and rice genes were responsive to drought and salt stresses and were co-located within multifunctional QTLs. Among the total identified multi-stress responsive genes, 272 targets were shown to be co-localized within QTLs

  8. A hybrid approach for global sensitivity analysis

    International Nuclear Information System (INIS)

    Chakraborty, Souvik; Chowdhury, Rajib

    2017-01-01

    Distribution based sensitivity analysis (DSA) computes sensitivity of the input random variables with respect to the change in distribution of output response. Although DSA is widely appreciated as the best tool for sensitivity analysis, the computational issue associated with this method prohibits its use for complex structures involving costly finite element analysis. For addressing this issue, this paper presents a method that couples polynomial correlated function expansion (PCFE) with DSA. PCFE is a fully equivalent operational model which integrates the concepts of analysis of variance decomposition, extended bases and homotopy algorithm. By integrating PCFE into DSA, it is possible to considerably alleviate the computational burden. Three examples are presented to demonstrate the performance of the proposed approach for sensitivity analysis. For all the problems, proposed approach yields excellent results with significantly reduced computational effort. The results obtained, to some extent, indicate that proposed approach can be utilized for sensitivity analysis of large scale structures. - Highlights: • A hybrid approach for global sensitivity analysis is proposed. • Proposed approach integrates PCFE within distribution based sensitivity analysis. • Proposed approach is highly efficient.

  9. Weibull and lognormal Taguchi analysis using multiple linear regression

    International Nuclear Information System (INIS)

    Piña-Monarrez, Manuel R.; Ortiz-Yañez, Jesús F.

    2015-01-01

    The paper provides to reliability practitioners with a method (1) to estimate the robust Weibull family when the Taguchi method (TM) is applied, (2) to estimate the normal operational Weibull family in an accelerated life testing (ALT) analysis to give confidence to the extrapolation and (3) to perform the ANOVA analysis to both the robust and the normal operational Weibull family. On the other hand, because the Weibull distribution neither has the normal additive property nor has a direct relationship with the normal parameters (µ, σ), in this paper, the issues of estimating a Weibull family by using a design of experiment (DOE) are first addressed by using an L_9 (3"4) orthogonal array (OA) in both the TM and in the Weibull proportional hazard model approach (WPHM). Then, by using the Weibull/Gumbel and the lognormal/normal relationships and multiple linear regression, the direct relationships between the Weibull and the lifetime parameters are derived and used to formulate the proposed method. Moreover, since the derived direct relationships always hold, the method is generalized to the lognormal and ALT analysis. Finally, the method’s efficiency is shown through its application to the used OA and to a set of ALT data. - Highlights: • It gives the statistical relations and steps to use the Taguchi Method (TM) to analyze Weibull data. • It gives the steps to determine the unknown Weibull family to both the robust TM setting and the normal ALT level. • It gives a method to determine the expected lifetimes and to perform its ANOVA analysis in TM and ALT analysis. • It gives a method to give confidence to the extrapolation in an ALT analysis by using the Weibull family of the normal level.

  10. A Psychoacoustic-Based Multiple Audio Object Coding Approach via Intra-Object Sparsity

    Directory of Open Access Journals (Sweden)

    Maoshen Jia

    2017-12-01

    Full Text Available Rendering spatial sound scenes via audio objects has become popular in recent years, since it can provide more flexibility for different auditory scenarios, such as 3D movies, spatial audio communication and virtual classrooms. To facilitate high-quality bitrate-efficient distribution for spatial audio objects, an encoding scheme based on intra-object sparsity (approximate k-sparsity of the audio object itself is proposed in this paper. The statistical analysis is presented to validate the notion that the audio object has a stronger sparseness in the Modified Discrete Cosine Transform (MDCT domain than in the Short Time Fourier Transform (STFT domain. By exploiting intra-object sparsity in the MDCT domain, multiple simultaneously occurring audio objects are compressed into a mono downmix signal with side information. To ensure a balanced perception quality of audio objects, a Psychoacoustic-based time-frequency instants sorting algorithm and an energy equalized Number of Preserved Time-Frequency Bins (NPTF allocation strategy are proposed, which are employed in the underlying compression framework. The downmix signal can be further encoded via Scalar Quantized Vector Huffman Coding (SQVH technique at a desirable bitrate, and the side information is transmitted in a lossless manner. Both objective and subjective evaluations show that the proposed encoding scheme outperforms the Sparsity Analysis (SPA approach and Spatial Audio Object Coding (SAOC in cases where eight objects were jointly encoded.

  11. Mediation analysis with multiple versions of the mediator

    OpenAIRE

    VanderWeele, Tyler J.

    2012-01-01

    The causal inference literature has provided definitions of direct and indirect effects based on counterfactuals that generalize the approach found in the social science literature. However, these definitions presuppose well defined hypothetical interventions on the mediator. In many settings there may be multiple ways to fix the mediator to a particular value and these different hypothetical interventions may have very different implications for the outcome of interest. In this paper we cons...

  12. Nitrogen Cycle Evaluation (NiCE) Chip for the Simultaneous Analysis of Multiple N-Cycle Associated Genes.

    Science.gov (United States)

    Oshiki, Mamoru; Segawa, Takahiro; Ishii, Satoshi

    2018-02-02

    Various microorganisms play key roles in the Nitrogen (N) cycle. Quantitative PCR (qPCR) and PCR-amplicon sequencing of the N cycle functional genes allow us to analyze the abundance and diversity of microbes responsible in the N transforming reactions in various environmental samples. However, analysis of multiple target genes can be cumbersome and expensive. PCR-independent analysis, such as metagenomics and metatranscriptomics, is useful but expensive especially when we analyze multiple samples and try to detect N cycle functional genes present at relatively low abundance. Here, we present the application of microfluidic qPCR chip technology to simultaneously quantify and prepare amplicon sequence libraries for multiple N cycle functional genes as well as taxon-specific 16S rRNA gene markers for many samples. This approach, named as N cycle evaluation (NiCE) chip, was evaluated by using DNA from pure and artificially mixed bacterial cultures and by comparing the results with those obtained by conventional qPCR and amplicon sequencing methods. Quantitative results obtained by the NiCE chip were comparable to those obtained by conventional qPCR. In addition, the NiCE chip was successfully applied to examine abundance and diversity of N cycle functional genes in wastewater samples. Although non-specific amplification was detected on the NiCE chip, this could be overcome by optimizing the primer sequences in the future. As the NiCE chip can provide high-throughput format to quantify and prepare sequence libraries for multiple N cycle functional genes, this tool should advance our ability to explore N cycling in various samples. Importance. We report a novel approach, namely Nitrogen Cycle Evaluation (NiCE) chip by using microfluidic qPCR chip technology. By sequencing the amplicons recovered from the NiCE chip, we can assess diversities of the N cycle functional genes. The NiCE chip technology is applicable to analyze the temporal dynamics of the N cycle gene

  13. Analysis of dynamic multiplicity fluctuations at PHOBOS

    Science.gov (United States)

    Chai, Zhengwei; PHOBOS Collaboration; Back, B. B.; Baker, M. D.; Ballintijn, M.; Barton, D. S.; Betts, R. R.; Bickley, A. A.; Bindel, R.; Budzanowski, A.; Busza, W.; Carroll, A.; Chai, Z.; Decowski, M. P.; García, E.; George, N.; Gulbrandsen, K.; Gushue, S.; Halliwell, C.; Hamblen, J.; Heintzelman, G. A.; Henderson, C.; Hofman, D. J.; Hollis, R. S.; Holynski, R.; Holzman, B.; Iordanova, A.; Johnson, E.; Kane, J. L.; Katzy, J.; Khan, N.; Kucewicz, W.; Kulinich, P.; Kuo, C. M.; Lin, W. T.; Manly, S.; McLeod, D.; Mignerey, A. C.; Nouicer, R.; Olszewski, A.; Pak, R.; Park, I. C.; Pernegger, H.; Reed, C.; Remsberg, L. P.; Reuter, M.; Roland, C.; Roland, G.; Rosenberg, L.; Sagerer, J.; Sarin, P.; Sawicki, P.; Skulski, W.; Steinberg, P.; Stephans, G. S. F.; Sukhanov, A.; Tang, J. L.; Trzupek, A.; Vale, C.; van Nieuwenhuizen, G. J.; Verdier, R.; Wolfs, F. L. H.; Wosiek, B.; Wozniak, K.; Wuosmaa, A. H.; Wyslouch, B.

    2005-01-01

    This paper presents the analysis of the dynamic fluctuations in the inclusive charged particle multiplicity measured by PHOBOS for Au+Au collisions at surdsNN = 200GeV within the pseudo-rapidity range of -3 < η < 3. First the definition of the fluctuations observables used in this analysis is presented, together with the discussion of their physics meaning. Then the procedure for the extraction of dynamic fluctuations is described. Some preliminary results are included to illustrate the correlation features of the fluctuation observable. New dynamic fluctuations results will be available in a later publication.

  14. Diversity Performance Analysis on Multiple HAP Networks

    Science.gov (United States)

    Dong, Feihong; Li, Min; Gong, Xiangwu; Li, Hongjun; Gao, Fengyue

    2015-01-01

    One of the main design challenges in wireless sensor networks (WSNs) is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP) is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO) techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO) model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV). In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF) and cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) are derived. In addition, the average symbol error rate (ASER) with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI) and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques. PMID:26134102

  15. Diversity Performance Analysis on Multiple HAP Networks

    Directory of Open Access Journals (Sweden)

    Feihong Dong

    2015-06-01

    Full Text Available One of the main design challenges in wireless sensor networks (WSNs is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV. In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF and cumulative distribution function (CDF of the received signal-to-noise ratio (SNR are derived. In addition, the average symbol error rate (ASER with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques.

  16. Whole-body voxel-based personalized dosimetry: Multiple voxel S-value approach for heterogeneous media with non-uniform activity distributions.

    Science.gov (United States)

    Lee, Min Sun; Kim, Joong Hyun; Paeng, Jin Chul; Kang, Keon Wook; Jeong, Jae Min; Lee, Dong Soo; Lee, Jae Sung

    2017-12-14

    Personalized dosimetry with high accuracy is becoming more important because of the growing interests in personalized medicine and targeted radionuclide therapy. Voxel-based dosimetry using dose point kernel or voxel S-value (VSV) convolution is available. However, these approaches do not consider medium heterogeneity. Here, we propose a new method for whole-body voxel-based personalized dosimetry for heterogeneous media with non-uniform activity distributions, which is referred to as the multiple VSV approach. Methods: The multiple numbers (N) of VSVs for media with different densities covering the whole-body density ranges were used instead of using only a single VSV for water. The VSVs were pre-calculated using GATE Monte Carlo simulation; those were convoluted with the time-integrated activity to generate density-specific dose maps. Computed tomography-based segmentation was conducted to generate binary maps for each density region. The final dose map was acquired by the summation of N segmented density-specific dose maps. We tested several sets of VSVs with different densities: N = 1 (single water VSV), 4, 6, 8, 10, and 20. To validate the proposed method, phantom and patient studies were conducted and compared with direct Monte Carlo, which was considered the ground truth. Finally, patient dosimetry (10 subjects) was conducted using the multiple VSV approach and compared with the single VSV and organ-based dosimetry approaches. Errors at the voxel- and organ-levels were reported for eight organs. Results: In the phantom and patient studies, the multiple VSV approach showed significant improvements regarding voxel-level errors, especially for the lung and bone regions. As N increased, voxel-level errors decreased, although some overestimations were observed at lung boundaries. In the case of multiple VSVs ( N = 8), we achieved voxel-level errors of 2.06%. In the dosimetry study, our proposed method showed much improved results compared to the single VSV and

  17. Multivariant design and multiple criteria analysis of building refurbishments

    Energy Technology Data Exchange (ETDEWEB)

    Kaklauskas, A.; Zavadskas, E. K.; Raslanas, S. [Faculty of Civil Engineering, Vilnius Gediminas Technical University, Vilnius (Lithuania)

    2005-07-01

    In order to design and realize an efficient building refurbishment, it is necessary to carry out an exhaustive investigation of all solutions that form it. The efficiency level of the considered building's refurbishment depends on a great many of factors, including: cost of refurbishment, annual fuel economy after refurbishment, tentative pay-back time, harmfulness to health of the materials used, aesthetics, maintenance properties, functionality, comfort, sound insulation and longevity, etc. Solutions of an alternative character allow for a more rational and realistic assessment of economic, ecological, legislative, climatic, social and political conditions, traditions and for better the satisfaction of customer requirements. They also enable one to cut down on refurbishment costs. In carrying out the multivariant design and multiple criteria analysis of a building refurbishment much data was processed and evaluated. Feasible alternatives could be as many as 100,000. How to perform a multivariant design and multiple criteria analysis of alternate alternatives based on the enormous amount of information became the problem. Method of multivariant design and multiple criteria of a building refurbishment's analysis were developed by the authors to solve the above problems. In order to demonstrate the developed method, a practical example is presented in this paper. (author)

  18. The Propagation of Movement Variability in Time: A Methodological Approach for Discrete Movements with Multiple Degrees of Freedom

    Science.gov (United States)

    Krüger, Melanie; Straube, Andreas; Eggert, Thomas

    2017-01-01

    In recent years, theory-building in motor neuroscience and our understanding of the synergistic control of the redundant human motor system has significantly profited from the emergence of a range of different mathematical approaches to analyze the structure of movement variability. Approaches such as the Uncontrolled Manifold method or the Noise-Tolerance-Covariance decomposition method allow to detect and interpret changes in movement coordination due to e.g., learning, external task constraints or disease, by analyzing the structure of within-subject, inter-trial movement variability. Whereas, for cyclical movements (e.g., locomotion), mathematical approaches exist to investigate the propagation of movement variability in time (e.g., time series analysis), similar approaches are missing for discrete, goal-directed movements, such as reaching. Here, we propose canonical correlation analysis as a suitable method to analyze the propagation of within-subject variability across different time points during the execution of discrete movements. While similar analyses have already been applied for discrete movements with only one degree of freedom (DoF; e.g., Pearson's product-moment correlation), canonical correlation analysis allows to evaluate the coupling of inter-trial variability across different time points along the movement trajectory for multiple DoF-effector systems, such as the arm. The theoretical analysis is illustrated by empirical data from a study on reaching movements under normal and disturbed proprioception. The results show increased movement duration, decreased movement amplitude, as well as altered movement coordination under ischemia, which results in a reduced complexity of movement control. Movement endpoint variability is not increased under ischemia. This suggests that healthy adults are able to immediately and efficiently adjust the control of complex reaching movements to compensate for the loss of proprioceptive information. Further, it is

  19. Multiple Model-Based Synchronization Approaches for Time Delayed Slaving Data in a Space Launch Vehicle Tracking System

    Directory of Open Access Journals (Sweden)

    Haryong Song

    2016-01-01

    Full Text Available Due to the inherent characteristics of the flight mission of a space launch vehicle (SLV, which is required to fly over very large distances and have very high fault tolerances, in general, SLV tracking systems (TSs comprise multiple heterogeneous sensors such as radars, GPS, INS, and electrooptical targeting systems installed over widespread areas. To track an SLV without interruption and to hand over the measurement coverage between TSs properly, the mission control system (MCS transfers slaving data to each TS through mission networks. When serious network delays occur, however, the slaving data from the MCS can lead to the failure of the TS. To address this problem, in this paper, we propose multiple model-based synchronization (MMS approaches, which take advantage of the multiple motion models of an SLV. Cubic spline extrapolation, prediction through an α-β-γ filter, and a single model Kalman filter are presented as benchmark approaches. We demonstrate the synchronization accuracy and effectiveness of the proposed MMS approaches using the Monte Carlo simulation with the nominal trajectory data of Korea Space Launch Vehicle-I.

  20. Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

    Science.gov (United States)

    Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

    2012-05-01

    Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

  1. A multiplicative environmental DEA approach to measure efficiency changes in the world's major polluters

    International Nuclear Information System (INIS)

    Valadkhani, Abbas; Roshdi, Israfil; Smyth, Russell

    2016-01-01

    We propose a multiplicative environmental data envelopment analysis (ME-DEA) approach to measure the performance of 46 countries that generate most of the world's carbon dioxide (CO_2) emissions. In the model, we combine economic (labour and capital), environmental (freshwater) and energy inputs with a desirable output (GDP) and three undesirable outputs (CO_2, methane and nitrous oxide emissions). We rank each country according to the optimum use of its resources employing a multiplicative extension of environmental DEA models. By computing partial efficiency scores for each input and output separately, we thus identify major sources of inefficiency for all sample countries. Based on the partial efficiency scores obtained from the model, we define aggregate economic, energy and environmental efficiency indexes for 2002, 2007 and 2011, reflecting points in time before and after the official enactment of the Kyoto Protocol. We find that for most countries efficiency scores increase over this period. In addition, there exists a positive relationship between economic and environmental efficiency, although, at the same time, our results suggest that environmental efficiency cannot be realized without first reaching a certain threshold of economic efficiency. We also find support for the Paradox of Plenty, whereby an abundance of natural and energy resources results in their inefficient use. - Highlights: • This study proposes a multiplicative extension of environmental DEA models. • We examine how countries utilize energy, labour, capital and freshwater over time. • We measure how efficiently countries minimize the emissions of greenhouse gases. • Results support the Paradox of Plenty among 46 countries in 2002, 2007 and 2011. • Countries richest in oil and gas exhibited the worst energy efficiency.

  2. Capturing the experiences of patients across multiple complex interventions: a meta-qualitative approach.

    Science.gov (United States)

    Webster, Fiona; Christian, Jennifer; Mansfield, Elizabeth; Bhattacharyya, Onil; Hawker, Gillian; Levinson, Wendy; Naglie, Gary; Pham, Thuy-Nga; Rose, Louise; Schull, Michael; Sinha, Samir; Stergiopoulos, Vicky; Upshur, Ross; Wilson, Lynn

    2015-09-08

    The perspectives, needs and preferences of individuals with complex health and social needs can be overlooked in the design of healthcare interventions. This study was designed to provide new insights on patient perspectives drawing from the qualitative evaluation of 5 complex healthcare interventions. Patients and their caregivers were recruited from 5 interventions based in primary, hospital and community care in Ontario, Canada. We included 62 interviews from 44 patients and 18 non-clinical caregivers. Our team analysed the transcripts from 5 distinct projects. This approach to qualitative meta-evaluation identifies common issues described by a diverse group of patients, therefore providing potential insights into systems issues. This study is a secondary analysis of qualitative data; therefore, no outcome measures were identified. We identified 5 broad themes that capture the patients' experience and highlight issues that might not be adequately addressed in complex interventions. In our study, we found that: (1) the emergency department is the unavoidable point of care; (2) patients and caregivers are part of complex and variable family systems; (3) non-medical issues mediate patients' experiences of health and healthcare delivery; (4) the unanticipated consequences of complex healthcare interventions are often the most valuable; and (5) patient experiences are shaped by the healthcare discourses on medically complex patients. Our findings suggest that key assumptions about patients that inform intervention design need to be made explicit in order to build capacity to better understand and support patients with multiple chronic diseases. Across many health systems internationally, multiple models are being implemented simultaneously that may have shared features and target similar patients, and a qualitative meta-evaluation approach, thus offers an opportunity for cumulative learning at a system level in addition to informing intervention design and

  3. Predicting Speech Intelligibility with a Multiple Speech Subsystems Approach in Children with Cerebral Palsy

    Science.gov (United States)

    Lee, Jimin; Hustad, Katherine C.; Weismer, Gary

    2014-01-01

    Purpose: Speech acoustic characteristics of children with cerebral palsy (CP) were examined with a multiple speech subsystems approach; speech intelligibility was evaluated using a prediction model in which acoustic measures were selected to represent three speech subsystems. Method: Nine acoustic variables reflecting different subsystems, and…

  4. A Bayesian trans-dimensional approach for the fusion of multiple geophysical datasets

    Science.gov (United States)

    JafarGandomi, Arash; Binley, Andrew

    2013-09-01

    We propose a Bayesian fusion approach to integrate multiple geophysical datasets with different coverage and sensitivity. The fusion strategy is based on the capability of various geophysical methods to provide enough resolution to identify either subsurface material parameters or subsurface structure, or both. We focus on electrical resistivity as the target material parameter and electrical resistivity tomography (ERT), electromagnetic induction (EMI), and ground penetrating radar (GPR) as the set of geophysical methods. However, extending the approach to different sets of geophysical parameters and methods is straightforward. Different geophysical datasets are entered into a trans-dimensional Markov chain Monte Carlo (McMC) search-based joint inversion algorithm. The trans-dimensional property of the McMC algorithm allows dynamic parameterisation of the model space, which in turn helps to avoid bias of the post-inversion results towards a particular model. Given that we are attempting to develop an approach that has practical potential, we discretize the subsurface into an array of one-dimensional earth-models. Accordingly, the ERT data that are collected by using two-dimensional acquisition geometry are re-casted to a set of equivalent vertical electric soundings. Different data are inverted either individually or jointly to estimate one-dimensional subsurface models at discrete locations. We use Shannon's information measure to quantify the information obtained from the inversion of different combinations of geophysical datasets. Information from multiple methods is brought together via introducing joint likelihood function and/or constraining the prior information. A Bayesian maximum entropy approach is used for spatial fusion of spatially dispersed estimated one-dimensional models and mapping of the target parameter. We illustrate the approach with a synthetic dataset and then apply it to a field dataset. We show that the proposed fusion strategy is

  5. Field theoretical approach to proton-nucleus reactions: II-Multiple-step excitation process

    International Nuclear Information System (INIS)

    Eiras, A.; Kodama, T.; Nemes, M.

    1989-01-01

    A field theoretical formulation to multiple step excitation process in proton-nucleus collision within the context of a relativistic eikonal approach is presented. A closed form expression for the double differential cross section can be obtained whose structure is very simple and makes the physics transparent. Glauber's formulation of the same process is obtained as a limit of ours and the necessary approximations are studied and discussed. (author) [pt

  6. Multiplicity Analysis during Photon Interrogation of Fissionable Material

    International Nuclear Information System (INIS)

    Clarke, Shaun D.; Pozzi, Sara A.; Padovani, Enrico; Downar, Thomas J.

    2007-01-01

    Simulation of multiplicity distributions with the Monte Carlo method is difficult because each history is treated individually. In order to accurately model the multiplicity distribution, the intensity and time width of the interrogation pulse must be incorporated into the calculation. This behavior dictates how many photons arrive at the target essentially simultaneously. In order to model the pulse width correctly, a Monte Carlo code system consisting of modified versions of the codes MCNPX and MCNP-PoliMi has been developed in conjunction with a post-processing algorithm to operate on the MCNP-PoliMi output file. The purpose of this subroutine is to assemble the interactions into groups corresponding to the number of interactions which would occur during a given pulse. The resulting multiplicity distributions appear more realistic and capture the higher-order multiplets which are a product of multiple reactions occurring during a single accelerator pulse. Plans are underway to gather relevant experimental data to verify and validate the methodology developed and presented here. This capability will enable the simulation of a large number of materials and detector geometries. Analysis of this information will determine the feasibility of using multiplicity distributions as an identification tool for special nuclear material.

  7. Community Response to Multiple Sound Sources: Integrating Acoustic and Contextual Approaches in the Analysis

    Directory of Open Access Journals (Sweden)

    Peter Lercher

    2017-06-01

    Full Text Available Sufficient data refer to the relevant prevalence of sound exposure by mixed traffic sources in many nations. Furthermore, consideration of the potential effects of combined sound exposure is required in legal procedures such as environmental health impact assessments. Nevertheless, current practice still uses single exposure response functions. It is silently assumed that those standard exposure-response curves accommodate also for mixed exposures—although some evidence from experimental and field studies casts doubt on this practice. The ALPNAP-study population (N = 1641 shows sufficient subgroups with combinations of rail-highway, highway-main road and rail-highway-main road sound exposure. In this paper we apply a few suggested approaches of the literature to investigate exposure-response curves and its major determinants in the case of exposure to multiple traffic sources. Highly/moderate annoyance and full scale mean annoyance served as outcome. The results show several limitations of the current approaches. Even facing the inherent methodological limitations (energy equivalent summation of sound, rating of overall annoyance the consideration of main contextual factors jointly occurring with the sources (such as vibration, air pollution or coping activities and judgments of the wider area soundscape increases the variance explanation from up to 8% (bivariate, up to 15% (base adjustments up to 55% (full contextual model. The added predictors vary significantly, depending on the source combination. (e.g., significant vibration effects with main road/railway, not highway. Although no significant interactions were found, the observed additive effects are of public health importance. Especially in the case of a three source exposure situation the overall annoyance is already high at lower levels and the contribution of the acoustic indicators is small compared with the non-acoustic and contextual predictors. Noise mapping needs to go down to

  8. CHOOSING A HEALTH INSTITUTION WITH MULTIPLE CORRESPONDENCE ANALYSIS AND CLUSTER ANALYSIS IN A POPULATION BASED STUDY

    Directory of Open Access Journals (Sweden)

    ASLI SUNER

    2013-06-01

    Full Text Available Multiple correspondence analysis is a method making easy to interpret the categorical variables given in contingency tables, showing the similarities, associations as well as divergences among these variables via graphics on a lower dimensional space. Clustering methods are helped to classify the grouped data according to their similarities and to get useful summarized data from them. In this study, interpretations of multiple correspondence analysis are supported by cluster analysis; factors affecting referred health institute such as age, disease group and health insurance are examined and it is aimed to compare results of the methods.

  9. Intelligent Systems Approaches to Product Sound Quality Analysis

    Science.gov (United States)

    Pietila, Glenn M.

    As a product market becomes more competitive, consumers become more discriminating in the way in which they differentiate between engineered products. The consumer often makes a purchasing decision based on the sound emitted from the product during operation by using the sound to judge quality or annoyance. Therefore, in recent years, many sound quality analysis tools have been developed to evaluate the consumer preference as it relates to a product sound and to quantify this preference based on objective measurements. This understanding can be used to direct a product design process in order to help differentiate the product from competitive products or to establish an impression on consumers regarding a product's quality or robustness. The sound quality process is typically a statistical tool that is used to model subjective preference, or merit score, based on objective measurements, or metrics. In this way, new product developments can be evaluated in an objective manner without the laborious process of gathering a sample population of consumers for subjective studies each time. The most common model used today is the Multiple Linear Regression (MLR), although recently non-linear Artificial Neural Network (ANN) approaches are gaining popularity. This dissertation will review publicly available published literature and present additional intelligent systems approaches that can be used to improve on the current sound quality process. The focus of this work is to address shortcomings in the current paired comparison approach to sound quality analysis. This research will propose a framework for an adaptive jury analysis approach as an alternative to the current Bradley-Terry model. The adaptive jury framework uses statistical hypothesis testing to focus on sound pairings that are most interesting and is expected to address some of the restrictions required by the Bradley-Terry model. It will also provide a more amicable framework for an intelligent systems approach

  10. General Nature of Multicollinearity in Multiple Regression Analysis.

    Science.gov (United States)

    Liu, Richard

    1981-01-01

    Discusses multiple regression, a very popular statistical technique in the field of education. One of the basic assumptions in regression analysis requires that independent variables in the equation should not be highly correlated. The problem of multicollinearity and some of the solutions to it are discussed. (Author)

  11. Modified Truncated Multiplicity Analysis to Improve Verification of Uranium Fuel Cycle Materials

    International Nuclear Information System (INIS)

    LaFleur, A.; Miller, K.; Swinhoe, M.; Belian, A.; Croft, S.

    2015-01-01

    Accurate verification of 235U enrichment and mass in UF6 storage cylinders and the UO2F2 holdup contained in the process equipment is needed to improve international safeguards and nuclear material accountancy at uranium enrichment plants. Small UF6 cylinders (1.5'' and 5'' diameter) are used to store the full range of enrichments from depleted to highly-enriched UF6. For independent verification of these materials, it is essential that the 235U mass and enrichment measurements do not rely on facility operator declarations. Furthermore, in order to be deployed by IAEA inspectors to detect undeclared activities (e.g., during complementary access), it is also imperative that the measurement technique is quick, portable, and sensitive to a broad range of 235U masses. Truncated multiplicity analysis is a technique that reduces the variance in the measured count rates by only considering moments 1, 2, and 3 of the multiplicity distribution. This is especially important for reducing the uncertainty in the measured doubles and triples rates in environments with a high cosmic ray background relative to the uranium signal strength. However, we believe that the existing truncated multiplicity analysis throws away too much useful data by truncating the distribution after the third moment. This paper describes a modified truncated multiplicity analysis method that determines the optimal moment to truncate the multiplicity distribution based on the measured data. Experimental measurements of small UF6 cylinders and UO2F2 working reference materials were performed at Los Alamos National Laboratory (LANL). The data were analyzed using traditional and modified truncated multiplicity analysis to determine the optimal moment to truncate the multiplicity distribution to minimize the uncertainty in the measured count rates. The results from this analysis directly support nuclear safeguards at enrichment plants and provide a more accurate verification method for UF6

  12. CURRENT APPROACHES FOR RESEARCH OF MULTIPLE SCLEROSIS BIOMARKERS

    Directory of Open Access Journals (Sweden)

    Kolyada T.I

    2016-12-01

    Full Text Available Current data concerning features of multiple sclerosis (MS etiology, pathogenesis, clinical course and treatment of disease indicate the necessity of personalized approach to the management of MS patients. These features are the variety of possible etiological factors and mechanisms that trigger the development of MS, different courses of disease, and significant differences in treatment efficiency. Phenotypic and pathogenetic heterogeneity of MS requires, on the one hand, the stratification of patients into groups with different treatment depending on a number of criteria including genetic characteristics, disease course, stage of the pathological process, and forms of the disease. On the other hand, it requires the use of modern methods for assessment of individual risk of developing MS, its early diagnosis, evaluation and prognosis of the disease course and the treatment efficiency. This approach is based on the identification and determination of biomarkers of MS including the use of systems biology technology platforms such as genomics, proteomics, metabolomics and bioinformatics. Research and practical use of biomarkers of MS in clinical and laboratory practice requires the use of a wide range of modern medical and biological, mathematical and physicochemical methods. The group of "classical" methods used to study MS biomarkers includes physicochemical and immunological methods aimed at the selection and identification of single molecular biomarkers, as well as methods of molecular genetic analysis. This group of methods includes ELISA, western blotting, isoelectric focusing, immunohistochemical methods, flow cytometry, spectrophotometric and nephelometric methods. These techniques make it possible to carry out both qualitative and quantitative assay of molecular biomarkers. The group of "classical methods" can also include methods based on polymerase chain reaction (including multiplex and allele-specific PCR and genome sequencing

  13. Seismic response analysis of structural system subjected to multiple support excitation

    International Nuclear Information System (INIS)

    Wu, R.W.; Hussain, F.A.; Liu, L.K.

    1978-01-01

    In the seismic analysis of a multiply supported structural system subjected to nonuniform excitations at each support point, the single response spectrum, the time history, and the multiple response spectrum are the three commonly employed methods. In the present paper the three methods are developed, evaluated, and the limitations and advantages of each method assessed. A numerical example has been carried out for a typical piping system. Considerably smaller responses have been predicted by the time history method than that by the single response spectrum method. This is mainly due to the fact that the phase and amplitude relations between the support excitations are faithfully retained in the time history method. The multiple response spectrum prediction has been observed to compare favourably with the time history method prediction. Based on the present evaluation, the multiple response spectrum method is the most efficient method for seismic response analysis of structural systems subjected to multiple support excitation. (Auth.)

  14. A Network Pharmacology Approach to Uncover the Multiple Mechanisms of Hedyotis diffusa Willd. on Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Xinkui Liu

    2018-01-01

    Full Text Available Background. As one of the most frequently diagnosed cancer diseases globally, colorectal cancer (CRC remains an important cause of cancer-related death. Although the traditional Chinese herb Hedyotis diffusa Willd. (HDW has been proven to be effective for treating CRC in clinical practice, its definite mechanisms have not been completely deciphered. Objective. The aim of our research is to systematically explore the multiple mechanisms of HDW on CRC. Methods. This study adopted the network pharmacology approach, which was mainly composed of active component gathering, target prediction, CRC gene collection, network analysis, and gene enrichment analysis. Results. The network analysis showed that 10 targets might be the therapeutic targets of HDW on CRC, namely, HRAS, PIK3CA, KRAS, TP53, APC, BRAF, GSK3B, CDK2, AKT1, and RAF1. The gene enrichment analysis implied that HDW probably benefits patients with CRC by modulating pathways related to cancers, infectious diseases, endocrine system, immune system, nervous system, signal transduction, cellular community, and cell motility. Conclusions. This study partially verified and predicted the pharmacological and molecular mechanism of HDW against CRC from a holistic perspective, which will also lay a foundation for the further experimental research and clinical rational application of HDW.

  15. A nonparametric multiple imputation approach for missing categorical data

    Directory of Open Access Journals (Sweden)

    Muhan Zhou

    2017-06-01

    Full Text Available Abstract Background Incomplete categorical variables with more than two categories are common in public health data. However, most of the existing missing-data methods do not use the information from nonresponse (missingness probabilities. Methods We propose a nearest-neighbour multiple imputation approach to impute a missing at random categorical outcome and to estimate the proportion of each category. The donor set for imputation is formed by measuring distances between each missing value with other non-missing values. The distance function is calculated based on a predictive score, which is derived from two working models: one fits a multinomial logistic regression for predicting the missing categorical outcome (the outcome model and the other fits a logistic regression for predicting missingness probabilities (the missingness model. A weighting scheme is used to accommodate contributions from two working models when generating the predictive score. A missing value is imputed by randomly selecting one of the non-missing values with the smallest distances. We conduct a simulation to evaluate the performance of the proposed method and compare it with several alternative methods. A real-data application is also presented. Results The simulation study suggests that the proposed method performs well when missingness probabilities are not extreme under some misspecifications of the working models. However, the calibration estimator, which is also based on two working models, can be highly unstable when missingness probabilities for some observations are extremely high. In this scenario, the proposed method produces more stable and better estimates. In addition, proper weights need to be chosen to balance the contributions from the two working models and achieve optimal results for the proposed method. Conclusions We conclude that the proposed multiple imputation method is a reasonable approach to dealing with missing categorical outcome data with

  16. Using Two Different Approaches to Assess Dietary Patterns: Hypothesis-Driven and Data-Driven Analysis

    Directory of Open Access Journals (Sweden)

    Ágatha Nogueira Previdelli

    2016-09-01

    Full Text Available The use of dietary patterns to assess dietary intake has become increasingly common in nutritional epidemiology studies due to the complexity and multidimensionality of the diet. Currently, two main approaches have been widely used to assess dietary patterns: data-driven and hypothesis-driven analysis. Since the methods explore different angles of dietary intake, using both approaches simultaneously might yield complementary and useful information; thus, we aimed to use both approaches to gain knowledge of adolescents’ dietary patterns. Food intake from a cross-sectional survey with 295 adolescents was assessed by 24 h dietary recall (24HR. In hypothesis-driven analysis, based on the American National Cancer Institute method, the usual intake of Brazilian Healthy Eating Index Revised components were estimated. In the data-driven approach, the usual intake of foods/food groups was estimated by the Multiple Source Method. In the results, hypothesis-driven analysis showed low scores for Whole grains, Total vegetables, Total fruit and Whole fruits, while, in data-driven analysis, fruits and whole grains were not presented in any pattern. High intakes of sodium, fats and sugars were observed in hypothesis-driven analysis with low total scores for Sodium, Saturated fat and SoFAA (calories from solid fat, alcohol and added sugar components in agreement, while the data-driven approach showed the intake of several foods/food groups rich in these nutrients, such as butter/margarine, cookies, chocolate powder, whole milk, cheese, processed meat/cold cuts and candies. In this study, using both approaches at the same time provided consistent and complementary information with regard to assessing the overall dietary habits that will be important in order to drive public health programs, and improve their efficiency to monitor and evaluate the dietary patterns of populations.

  17. An update on the use of cerebrospinal fluid analysis as a diagnostic tool in multiple sclerosis.

    Science.gov (United States)

    Gastaldi, Matteo; Zardini, Elisabetta; Franciotta, Diego

    2017-01-01

    Intrathecal B-lymphocyte activation is a hallmark of multiple sclerosis (MS), a multi-factorial inflammatory-demyelinating disease of the central nervous system. Such activation has a counterpart in the cerebrospinal fluid (CSF) oligoclonal IgG bands (OCB), whose diagnostic role in MS has been downgraded within the current McDonald's criteria. With a theoretico-practical approach, the authors review the physiopathological basis of the CSF dynamics, and the state-of-the-art of routine CSF analysis and CSF biomarkers in MS. Areas covered: The authors discuss pros and cons of CSF analysis, including critical evaluations of both well-established, and promising diagnostic and prognostic laboratory tools. New acquisitions on the CSF and cerebral interstitial fluid dynamics are also presented. The authors searched the PubMed database for English-language articles reported between January 2010 and June 2016, using the key words 'multiple sclerosis', 'cerebrospinal fluid', 'oligoclonal bands'. Reference lists of relevant articles were scanned for additional studies. Expert commentary: The availability of performing high-quality, routine CSF tests in specialized laboratories, the emerging potential of novel CSF biomarkers, and the trend for early treatments should induce a reappraisal of CSF analysis for diagnostic and prognostic purposes in MS. Further procedural and methodological improvements seem to be necessary in both research and translational diagnostic CSF settings.

  18. Flutter analysis of an airfoil with multiple nonlinearities and uncertainties

    Directory of Open Access Journals (Sweden)

    Haitao Liao

    2013-09-01

    Full Text Available An original method for calculating the limit cycle oscillations of nonlinear aero-elastic system is presented. The problem of determining the maximum vibration amplitude of limit cycle is transformed into a nonlinear optimization problem. The harmonic balance method and the Floquet theory are selected to construct the general nonlinear equality and inequality constraints. The resulting constrained maximization problem is then solved by using the MultiStart algorithm. Finally, the proposed approach is validated and used to analyse the limit cycle oscillations of an airfoil with multiple nonlinearities and uncertainties. Numerical examples show that the coexistence of multiple nonlinearities may lead to low amplitude limit cycle oscillation.

  19. A Bayesian joint probability modeling approach for seasonal forecasting of streamflows at multiple sites

    Science.gov (United States)

    Wang, Q. J.; Robertson, D. E.; Chiew, F. H. S.

    2009-05-01

    Seasonal forecasting of streamflows can be highly valuable for water resources management. In this paper, a Bayesian joint probability (BJP) modeling approach for seasonal forecasting of streamflows at multiple sites is presented. A Box-Cox transformed multivariate normal distribution is proposed to model the joint distribution of future streamflows and their predictors such as antecedent streamflows and El Niño-Southern Oscillation indices and other climate indicators. Bayesian inference of model parameters and uncertainties is implemented using Markov chain Monte Carlo sampling, leading to joint probabilistic forecasts of streamflows at multiple sites. The model provides a parametric structure for quantifying relationships between variables, including intersite correlations. The Box-Cox transformed multivariate normal distribution has considerable flexibility for modeling a wide range of predictors and predictands. The Bayesian inference formulated allows the use of data that contain nonconcurrent and missing records. The model flexibility and data-handling ability means that the BJP modeling approach is potentially of wide practical application. The paper also presents a number of statistical measures and graphical methods for verification of probabilistic forecasts of continuous variables. Results for streamflows at three river gauges in the Murrumbidgee River catchment in southeast Australia show that the BJP modeling approach has good forecast quality and that the fitted model is consistent with observed data.

  20. HARMONIC ANALYSIS OF SVPWM INVERTER USING MULTIPLE-PULSES METHOD

    Directory of Open Access Journals (Sweden)

    Mehmet YUMURTACI

    2009-01-01

    Full Text Available Space Vector Modulation (SVM technique is a popular and an important PWM technique for three phases voltage source inverter in the control of Induction Motor. In this study harmonic analysis of Space Vector PWM (SVPWM is investigated using multiple-pulses method. Multiple-Pulses method calculates the Fourier coefficients of individual positive and negative pulses of the output PWM waveform and adds them together using the principle of superposition to calculate the Fourier coefficients of the all PWM output signal. Harmonic magnitudes can be calculated directly by this method without linearization, using look-up tables or Bessel functions. In this study, the results obtained in the application of SVPWM for values of variable parameters are compared with the results obtained with the multiple-pulses method.

  1. Evaluation of dairy effluent management options using multiple criteria analysis.

    Science.gov (United States)

    Hajkowicz, Stefan A; Wheeler, Sarah A

    2008-04-01

    This article describes how options for managing dairy effluent on the Lower Murray River in South Australia were evaluated using multiple criteria analysis (MCA). Multiple criteria analysis is a framework for combining multiple environmental, social, and economic objectives in policy decisions. At the time of the study, dairy irrigation in the region was based on flood irrigation which involved returning effluent to the river. The returned water contained nutrients, salts, and microbial contaminants leading to environmental, human health, and tourism impacts. In this study MCA was used to evaluate 11 options against 6 criteria for managing dairy effluent problems. Of the 11 options, the MCA model selected partial rehabilitation of dairy paddocks with the conversion of remaining land to other agriculture. Soon after, the South Australian Government adopted this course of action and is now providing incentives for dairy farmers in the region to upgrade irrigation infrastructure and/or enter alternative industries.

  2. Variational Approaches for the Existence of Multiple Periodic Solutions of Differential Delay Equations

    Directory of Open Access Journals (Sweden)

    Rong Cheng

    2010-01-01

    Full Text Available The existence of multiple periodic solutions of the following differential delay equation (=−((− is established by applying variational approaches directly, where ∈ℝ, ∈(ℝ,ℝ and >0 is a given constant. This means that we do not need to use Kaplan and Yorke's reduction technique to reduce the existence problem of the above equation to an existence problem for a related coupled system. Such a reduction method introduced first by Kaplan and Yorke in (1974 is often employed in previous papers to study the existence of periodic solutions for the above equation and its similar ones by variational approaches.

  3. Multiple Intelligences within the Cross-Curricular Approach

    Directory of Open Access Journals (Sweden)

    Anthoula Vaiou

    2010-02-01

    Full Text Available The present study was realized in a Greek 6th grade State Primary School class and was based on Howard Gardner’s theory of multiple intelligences, which was first introduced in 1983. More particularly, it was explored to what extent the young learners possess multiple intelligences through the use of a specially-designed questionnaire and a series of interviews. The findings of the above have served as a tool to the construction of a project work based on students’ learning preferences within a cross-curricular framework, easily applicable to the Greek State School curriculum. All learners were activated to participate within a school environment that traditionally promotes linguistic and mathematical skills matching dominant multiple intelligences or a combination of some of them to thematic units already taught by Greek teachers. The suggested project was assessed through observation and student portfolio, showing that the young learners’ multiple intelligences were exploited to a great extent, promoting the learning process satisfactorily. The results of this study can provide a contribution to the literature of multiple intelligences in the Greek reality and suggest a need for further consideration and exploration in the field. Finally, the researcher of this study hopes the present work could function as a springboard for more elaborated studies in the future.

  4. Combining information from multiple flood projections in a hierarchical Bayesian framework

    Science.gov (United States)

    Le Vine, Nataliya

    2016-04-01

    This study demonstrates, in the context of flood frequency analysis, the potential of a recently proposed hierarchical Bayesian approach to combine information from multiple models. The approach explicitly accommodates shared multimodel discrepancy as well as the probabilistic nature of the flood estimates, and treats the available models as a sample from a hypothetical complete (but unobserved) set of models. The methodology is applied to flood estimates from multiple hydrological projections (the Future Flows Hydrology data set) for 135 catchments in the UK. The advantages of the approach are shown to be: (1) to ensure adequate "baseline" with which to compare future changes; (2) to reduce flood estimate uncertainty; (3) to maximize use of statistical information in circumstances where multiple weak predictions individually lack power, but collectively provide meaningful information; (4) to diminish the importance of model consistency when model biases are large; and (5) to explicitly consider the influence of the (model performance) stationarity assumption. Moreover, the analysis indicates that reducing shared model discrepancy is the key to further reduction of uncertainty in the flood frequency analysis. The findings are of value regarding how conclusions about changing exposure to flooding are drawn, and to flood frequency change attribution studies.

  5. The impact of a multiple intelligences teaching approach drug education programme on drug refusal skills of Nigerian pupils.

    Science.gov (United States)

    Nwagu, Evelyn N; Ezedum, Chuks E; Nwagu, Eric K N

    2015-09-01

    The rising incidence of drug abuse among youths in Nigeria is a source of concern for health educators. This study was carried out on primary six pupils to determine the effect of a Multiple Intelligences Teaching Approach Drug Education Programme (MITA-DEP) on pupils' acquisition of drug refusal skills. A programme of drug education based on the Multiple Intelligences Teaching Approach (MITA) was developed. An experimental group was taught using this programme while a control group was taught using the same programme but developed based on the Traditional Teaching Approach. Pupils taught with the MITA acquired more drug refusal skills than those taught with the Traditional Teaching Approach. Urban pupils taught with the MITA acquired more skills than rural pupils. There was no statistically significant difference in the mean refusal skills of male and female pupils taught with the MITA. © The Author(s) 2014.

  6. An Automated Approach to Reasoning Under Multiple Perspectives

    Science.gov (United States)

    deBessonet, Cary

    2004-01-01

    This is the final report with emphasis on research during the last term. The context for the research has been the development of an automated reasoning technology for use in SMS (symbolic Manipulation System), a system used to build and query knowledge bases (KBs) using a special knowledge representation language SL (Symbolic Language). SMS interpreters assertive SL input and enters the results as components of its universe. The system operates in two basic models: 1) constructive mode (for building KBs); and 2) query/search mode (for querying KBs). Query satisfaction consists of matching query components with KB components. The system allows "penumbral matches," that is, matches that do not exactly meet the specifications of the query, but which are deemed relevant for the conversational context. If the user wants to know whether SMS has information that holds, say, for "any chow," the scope of relevancy might be set so that the system would respond based on a finding that it has information that holds for "most dogs," although this is not exactly what was called for by the query. The response would be qualified accordingly, as would normally be the case in ordinary human conversation. The general goal of the research was to develop an approach by which assertive content could be interpreted from multiple perspectives so that reasoning operations could be successfully conducted over the results. The interpretation of an SL statement such as, "{person believes [captain (asserted (perhaps)) (astronaut saw (comet (bright)))]}," which in English would amount to asserting something to the effect that, "Some person believes that a captain perhaps asserted that an astronaut saw a bright comet," would require the recognition of multiple perspectives, including some that are: a) epistemically-based (focusing on "believes"); b) assertion-based (focusing on "asserted"); c) perception-based (focusing on "saw"); d) adjectivally-based (focusing on "bight"); and e) modally

  7. Analysis of Product Sampling for New Product Diffusion Incorporating Multiple-Unit Ownership

    Directory of Open Access Journals (Sweden)

    Zhineng Hu

    2014-01-01

    Full Text Available Multiple-unit ownership of nondurable products is an important component of sales in many product categories. Based on the Bass model, this paper develops a new model considering the multiple-unit adoptions as a diffusion process under the influence of product sampling. Though the analysis aims to determine the optimal dynamic sampling effort for a firm and the results demonstrate that experience sampling can accelerate the diffusion process, the best time to send free samples is just before the product being launched. Multiple-unit purchasing behavior can increase sales to make more profit for a firm, and it needs more samples to make the product known much better. The local sensitivity analysis shows that the increase of both external coefficients and internal coefficients has a negative influence on the sampling level, but the internal influence on the subsequent multiple-unit adoptions has little significant influence on the sampling. Using the logistic regression along with linear regression, the global sensitivity analysis gives a whole analysis of the interaction of all factors, which manifests the external influence and multiunit purchase rate are two most important factors to influence the sampling level and net present value of the new product, and presents a two-stage method to determine the sampling level.

  8. Single-visit or multiple-visit root canal treatment: systematic review, meta-analysis and trial sequential analysis.

    Science.gov (United States)

    Schwendicke, Falk; Göstemeyer, Gerd

    2017-02-01

    Single-visit root canal treatment has some advantages over conventional multivisit treatment, but might increase the risk of complications. We systematically evaluated the risk of complications after single-visit or multiple-visit root canal treatment using meta-analysis and trial-sequential analysis. Controlled trials comparing single-visit versus multiple-visit root canal treatment of permanent teeth were included. Trials needed to assess the risk of long-term complications (pain, infection, new/persisting/increasing periapical lesions ≥1 year after treatment), short-term pain or flare-up (acute exacerbation of initiation or continuation of root canal treatment). Electronic databases (PubMed, EMBASE, Cochrane Central) were screened, random-effects meta-analyses performed and trial-sequential analysis used to control for risk of random errors. Evidence was graded according to GRADE. 29 trials (4341 patients) were included, all but 6 showing high risk of bias. Based on 10 trials (1257 teeth), risk of complications was not significantly different in single-visit versus multiple-visit treatment (risk ratio (RR) 1.00 (95% CI 0.75 to 1.35); weak evidence). Based on 20 studies (3008 teeth), risk of pain did not significantly differ between treatments (RR 0.99 (95% CI 0.76 to 1.30); moderate evidence). Risk of flare-up was recorded by 8 studies (1110 teeth) and was significantly higher after single-visit versus multiple-visit treatment (RR 2.13 (95% CI 1.16 to 3.89); very weak evidence). Trial-sequential analysis revealed that firm evidence for benefit, harm or futility was not reached for any of the outcomes. There is insufficient evidence to rule out whether important differences between both strategies exist. Dentists can provide root canal treatment in 1 or multiple visits. Given the possibly increased risk of flare-ups, multiple-visit treatment might be preferred for certain teeth (eg, those with periapical lesions). Published by the BMJ Publishing Group Limited

  9. CADDIS Volume 4. Data Analysis: Selecting an Analysis Approach

    Science.gov (United States)

    An approach for selecting statistical analyses to inform causal analysis. Describes methods for determining whether test site conditions differ from reference expectations. Describes an approach for estimating stressor-response relationships.

  10. Evaluation of Clinical Gait Analysis parameters in patients affected by Multiple Sclerosis: Analysis of kinematics.

    Science.gov (United States)

    Severini, Giacomo; Manca, Mario; Ferraresi, Giovanni; Caniatti, Luisa Maria; Cosma, Michela; Baldasso, Francesco; Straudi, Sofia; Morelli, Monica; Basaglia, Nino

    2017-06-01

    Clinical Gait Analysis is commonly used to evaluate specific gait characteristics of patients affected by Multiple Sclerosis. The aim of this report is to present a retrospective cross-sectional analysis of the changes in Clinical Gait Analysis parameters in patients affected by Multiple Sclerosis. In this study a sample of 51 patients with different levels of disability (Expanded Disability Status Scale 2-6.5) was analyzed. We extracted a set of 52 parameters from the Clinical Gait Analysis of each patient and used statistical analysis and linear regression to assess differences among several groups of subjects stratified according to the Expanded Disability Status Scale and 6-Minutes Walking Test. The impact of assistive devices (e.g. canes and crutches) on the kinematics was also assessed in a subsample of patients. Subjects showed decreased range of motion at hip, knee and ankle that translated in increased pelvic tilt and hiking. Comparison between the two stratifications showed that gait speed during 6-Minutes Walking Test is better at discriminating patients' kinematics with respect to Expanded Disability Status Scale. Assistive devices were shown not to significantly impact gait kinematics and the Clinical Gait Analysis parameters analyzed. We were able to characterize disability-related trends in gait kinematics. The results presented in this report provide a small atlas of the changes in gait characteristics associated with different disability levels in the Multiple Sclerosis population. This information could be used to effectively track the progression of MS and the effect of different therapies. Copyright © 2017. Published by Elsevier Ltd.

  11. Multiple Family Group Therapy: An Interpersonal/Postmodern Approach.

    Science.gov (United States)

    Thorngren, Jill M.; Kleist, David M.

    2002-01-01

    Multiple Family Group Therapy has been identified as a viable treatment model for a variety of client populations. A combination of family systems theories and therapeutic group factors provide the opportunity to explore multiple levels of intrapersonal and interpersonal relationships between families. This article depicts a Multiple Family Group…

  12. 'Multiple-test' approach to the laboratory diagnosis of tuberculosis -perception of medical doctors from Ujjain, India.

    Science.gov (United States)

    Purohit, Manju Raj; Sharma, Megha; Rosales-Klintz, Senia; Lundborg, Cecilia Stålsby

    2015-08-11

    Delay in diagnosis is one of the most important factors for the control of tuberculosis (TB) in endemic countries like India. As laboratory diagnosis is the mainstay for identification of active disease, we aim to explore and understand the opinions of medical doctors about the laboratory diagnosis of TB in Ujjain, India. Sixteen qualified specialist medical doctors from Ujjain were purposefully selected for the study. Individual interviews with the doctors (13 men and 3 women), were conducted. As one interview could not be completed, data from 15 interviews were analyzed using manifest and latent content analysis. Based on perception of the doctors, the theme; 'challenges and need for the laboratory diagnosis of TB' emerged from the following subthemes: (i) Relationship between basic element of the TB diseases process such as 'Symptoms prior to diagnoses' and 'Clinical characteristics of TB', which were not specific enough to diagnose TB (ii) The prevailing conditions such as lack of explicit diagnostic tools, lead to the doctors using the 'multiple tests' or 'empiric treatment' approach (iii) The doctors proposed that there is a need for access to a rapid, single and simple diagnostic test, and a need for awareness and knowledge of the practitioners regarding specific TB investigations, and early referral to improve the situation at resource-limited settings. The medical specialists use a 'multiple test' or 'empiric treatment' approach to diagnose TB. According to the participants, there is a low dependence and uptake of the available laboratory TB investigations by medical practitioners. There is an urgent need to have a specific, simple and reliable test, and a protocol, to improve diagnosis of TB and to prevent development of resistant TB.

  13. Detecting and accounting for multiple sources of positional variance in peak list registration analysis and spin system grouping.

    Science.gov (United States)

    Smelter, Andrey; Rouchka, Eric C; Moseley, Hunter N B

    2017-08-01

    Peak lists derived from nuclear magnetic resonance (NMR) spectra are commonly used as input data for a variety of computer assisted and automated analyses. These include automated protein resonance assignment and protein structure calculation software tools. Prior to these analyses, peak lists must be aligned to each other and sets of related peaks must be grouped based on common chemical shift dimensions. Even when programs can perform peak grouping, they require the user to provide uniform match tolerances or use default values. However, peak grouping is further complicated by multiple sources of variance in peak position limiting the effectiveness of grouping methods that utilize uniform match tolerances. In addition, no method currently exists for deriving peak positional variances from single peak lists for grouping peaks into spin systems, i.e. spin system grouping within a single peak list. Therefore, we developed a complementary pair of peak list registration analysis and spin system grouping algorithms designed to overcome these limitations. We have implemented these algorithms into an approach that can identify multiple dimension-specific positional variances that exist in a single peak list and group peaks from a single peak list into spin systems. The resulting software tools generate a variety of useful statistics on both a single peak list and pairwise peak list alignment, especially for quality assessment of peak list datasets. We used a range of low and high quality experimental solution NMR and solid-state NMR peak lists to assess performance of our registration analysis and grouping algorithms. Analyses show that an algorithm using a single iteration and uniform match tolerances approach is only able to recover from 50 to 80% of the spin systems due to the presence of multiple sources of variance. Our algorithm recovers additional spin systems by reevaluating match tolerances in multiple iterations. To facilitate evaluation of the

  14. Research and analyze of physical health using multiple regression analysis

    Directory of Open Access Journals (Sweden)

    T. S. Kyi

    2014-01-01

    Full Text Available This paper represents the research which is trying to create a mathematical model of the "healthy people" using the method of regression analysis. The factors are the physical parameters of the person (such as heart rate, lung capacity, blood pressure, breath holding, weight height coefficient, flexibility of the spine, muscles of the shoulder belt, abdominal muscles, squatting, etc.., and the response variable is an indicator of physical working capacity. After performing multiple regression analysis, obtained useful multiple regression models that can predict the physical performance of boys the aged of fourteen to seventeen years. This paper represents the development of regression model for the sixteen year old boys and analyzed results.

  15. Dimensions of cultural consumption among tourists : Multiple correspondence analysis

    NARCIS (Netherlands)

    Richards, G.W.; van der Ark, L.A.

    2013-01-01

    The cultural tourism market has diversified and fragmented into many different niches. Previous attempts to segment cultural tourists have been largely unidimensional, failing to capture the complexity of cultural production and consumption. We employ multiple correspondence analysis to visualize

  16. Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach.

    Science.gov (United States)

    Liang, Muxuan; Li, Zhizhong; Chen, Ting; Zeng, Jianyang

    2015-01-01

    Identification of cancer subtypes plays an important role in revealing useful insights into disease pathogenesis and advancing personalized therapy. The recent development of high-throughput sequencing technologies has enabled the rapid collection of multi-platform genomic data (e.g., gene expression, miRNA expression, and DNA methylation) for the same set of tumor samples. Although numerous integrative clustering approaches have been developed to analyze cancer data, few of them are particularly designed to exploit both deep intrinsic statistical properties of each input modality and complex cross-modality correlations among multi-platform input data. In this paper, we propose a new machine learning model, called multimodal deep belief network (DBN), to cluster cancer patients from multi-platform observation data. In our integrative clustering framework, relationships among inherent features of each single modality are first encoded into multiple layers of hidden variables, and then a joint latent model is employed to fuse common features derived from multiple input modalities. A practical learning algorithm, called contrastive divergence (CD), is applied to infer the parameters of our multimodal DBN model in an unsupervised manner. Tests on two available cancer datasets show that our integrative data analysis approach can effectively extract a unified representation of latent features to capture both intra- and cross-modality correlations, and identify meaningful disease subtypes from multi-platform cancer data. In addition, our approach can identify key genes and miRNAs that may play distinct roles in the pathogenesis of different cancer subtypes. Among those key miRNAs, we found that the expression level of miR-29a is highly correlated with survival time in ovarian cancer patients. These results indicate that our multimodal DBN based data analysis approach may have practical applications in cancer pathogenesis studies and provide useful guidelines for

  17. A quantitative approach for integrating multiple lines of evidence for the evaluation of environmental health risks

    Directory of Open Access Journals (Sweden)

    Jerome J. Schleier III

    2015-01-01

    Full Text Available Decision analysis often considers multiple lines of evidence during the decision making process. Researchers and government agencies have advocated for quantitative weight-of-evidence approaches in which multiple lines of evidence can be considered when estimating risk. Therefore, we utilized Bayesian Markov Chain Monte Carlo to integrate several human-health risk assessment, biomonitoring, and epidemiology studies that have been conducted for two common insecticides (malathion and permethrin used for adult mosquito management to generate an overall estimate of risk quotient (RQ. The utility of the Bayesian inference for risk management is that the estimated risk represents a probability distribution from which the probability of exceeding a threshold can be estimated. The mean RQs after all studies were incorporated were 0.4386, with a variance of 0.0163 for malathion and 0.3281 with a variance of 0.0083 for permethrin. After taking into account all of the evidence available on the risks of ULV insecticides, the probability that malathion or permethrin would exceed a level of concern was less than 0.0001. Bayesian estimates can substantially improve decisions by allowing decision makers to estimate the probability that a risk will exceed a level of concern by considering seemingly disparate lines of evidence.

  18. A comparison of regional flood frequency analysis approaches in a simulation framework

    Science.gov (United States)

    Ganora, D.; Laio, F.

    2016-07-01

    Regional frequency analysis (RFA) is a well-established methodology to provide an estimate of the flood frequency curve at ungauged (or scarcely gauged) sites. Different RFA approaches exist, depending on the way the information is transferred to the site of interest, but it is not clear in the literature if a specific method systematically outperforms the others. The aim of this study is to provide a framework wherein carrying out the intercomparison by building up a virtual environment based on synthetically generated data. The considered regional approaches include: (i) a unique regional curve for the whole region; (ii) a multiple-region model where homogeneous subregions are determined through cluster analysis; (iii) a Region-of-Influence model which defines a homogeneous subregion for each site; (iv) a spatially smooth estimation procedure where the parameters of the regional model vary continuously along the space. Virtual environments are generated considering different patterns of heterogeneity, including step change and smooth variations. If the region is heterogeneous, with the parent distribution changing continuously within the region, the spatially smooth regional approach outperforms the others, with overall errors 10-50% lower than the other methods. In the case of a step-change, the spatially smooth and clustering procedures perform similarly if the heterogeneity is moderate, while clustering procedures work better when the step-change is severe. To extend our findings, an extensive sensitivity analysis has been performed to investigate the effect of sample length, number of virtual stations, return period of the predicted quantile, variability of the scale parameter of the parent distribution, number of predictor variables and different parent distribution. Overall, the spatially smooth approach appears as the most robust approach as its performances are more stable across different patterns of heterogeneity, especially when short records are

  19. Comparing Multiple Intelligences Approach with Traditional Teaching on Eight Grade Students' Achievement in and Attitudes toward Science

    Science.gov (United States)

    Kaya, Osman Nafiz; Dogan, Alev; Gokcek, Nur; Kilic, Ziya; Kilic, Esma

    2007-01-01

    The purpose of this study was to investigate the effects of multiple intelligences (MI) teaching approach on 8th Grade students' achievement in and attitudes toward science. This study used a pretest-posttest control group experimental design. While the experimental group (n=30) was taught a unit on acids and bases using MI teaching approach, the…

  20. Multiple predictor smoothing methods for sensitivity analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Helton, Jon Craig; Storlie, Curtis B.

    2006-08-01

    The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (1) locally weighted regression (LOESS), (2) additive models, (3) projection pursuit regression, and (4) recursive partitioning regression. The indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present.

  1. Multiple predictor smoothing methods for sensitivity analysis

    International Nuclear Information System (INIS)

    Helton, Jon Craig; Storlie, Curtis B.

    2006-01-01

    The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (1) locally weighted regression (LOESS), (2) additive models, (3) projection pursuit regression, and (4) recursive partitioning regression. The indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present

  2. Deconstructing stem cell population heterogeneity: Single-cell analysis and modeling approaches

    Science.gov (United States)

    Wu, Jincheng; Tzanakakis, Emmanuel S.

    2014-01-01

    Isogenic stem cell populations display cell-to-cell variations in a multitude of attributes including gene or protein expression, epigenetic state, morphology, proliferation and proclivity for differentiation. The origins of the observed heterogeneity and its roles in the maintenance of pluripotency and the lineage specification of stem cells remain unclear. Addressing pertinent questions will require the employment of single-cell analysis methods as traditional cell biochemical and biomolecular assays yield mostly population-average data. In addition to time-lapse microscopy and flow cytometry, recent advances in single-cell genomic, transcriptomic and proteomic profiling are reviewed. The application of multiple displacement amplification, next generation sequencing, mass cytometry and spectrometry to stem cell systems is expected to provide a wealth of information affording unprecedented levels of multiparametric characterization of cell ensembles under defined conditions promoting pluripotency or commitment. Establishing connections between single-cell analysis information and the observed phenotypes will also require suitable mathematical models. Stem cell self-renewal and differentiation are orchestrated by the coordinated regulation of subcellular, intercellular and niche-wide processes spanning multiple time scales. Here, we discuss different modeling approaches and challenges arising from their application to stem cell populations. Integrating single-cell analysis with computational methods will fill gaps in our knowledge about the functions of heterogeneity in stem cell physiology. This combination will also aid the rational design of efficient differentiation and reprogramming strategies as well as bioprocesses for the production of clinically valuable stem cell derivatives. PMID:24035899

  3. An Application of Graphical Approach to Construct Multiple Testing Procedure in a Hypothetical Phase III Design

    Directory of Open Access Journals (Sweden)

    Naitee eTing

    2014-01-01

    Full Text Available Many multiple testing procedures (MTP have been developed in recent years. Among these new procedures, the graphical approach is flexible and easy to communicate with non-statisticians. A hypothetical Phase III clinical trial design is introduced in this manuscript to demonstrate how graphical approach can be applied in clinical product development. In this design, an active comparator is used. It is thought that this test drug under development could potentially be superior to this comparator. For comparison of efficacy, the primary endpoint is well established and widely accepted by regulatory agencies. However, an important secondary endpoint based on Phase II findings looks very promising. The target dose may have a good opportunity to deliver superiority to the comparator. Furthermore, a lower dose is included in case the target dose may demonstrate potential safety concerns. This Phase III study is designed as a non-inferiority trial with two doses, and two endpoints. This manuscript will illustrate how graphical approach is applied to this design in handling multiple testing issues.

  4. Risk Governance of Multiple Natural Hazards: Centralized versus Decentralized Approach in Europe

    Science.gov (United States)

    Komendantova, Nadejda; Scolobig, Anna; Vinchon, Charlotte

    2014-05-01

    The multi-risk approach is a relatively new field and its definition includes the need to consider multiple hazards and vulnerabilities in their interdependency (Selva, 2013) and the current multi-hazards disasters, such as the 2011 Tohoku earthquake, tsunami and nuclear catastrophe, showed the need for a multi-risk approach in hazard mitigation and management. Our knowledge about multi-risk assessment, including studies from different scientific disciplines and developed assessment tools, is constantly growing (White et al., 2001). However, the link between scientific knowledge, its implementation and the results in terms of improved governance and decision-making have gained significantly less attention (IRGC, 2005; Kappes et al., 2012), even though the interest to risk governance, in general, has increased significantly during the last years (Verweiy and Thompson, 2006). Therefore, the key research question is how risk assessment is implemented and what is the potential for the implementation of a multi-risk approach in different governance systems across Europe. More precisely, how do the characteristics of risk governance, such as the degree of centralization versus decentralization, influence the implementation of a multi-risk approach. The methodology of this research includes comparative case study analysis of top-down and bottom-up interactions in governance in the city of Naples, (Italy), where the institutional landscape is marked by significant autonomy of Italian regions in decision-making processes for assessing the majority of natural risks, excluding volcanic, and in Guadeloupe, French West Indies, an overseas department of France, where the decision-making process is marked by greater centralization in decision making associated with a well established state governance within regions, delegated to the prefect and decentralised services of central ministries. The research design included documentary analysis and extensive empirical work involving

  5. Multiple breath washout analysis in infants: quality assessment and recommendations for improvement.

    Science.gov (United States)

    Anagnostopoulou, Pinelopi; Egger, Barbara; Lurà, Marco; Usemann, Jakob; Schmidt, Anne; Gorlanova, Olga; Korten, Insa; Roos, Markus; Frey, Urs; Latzin, Philipp

    2016-03-01

    Infant multiple breath washout (MBW) testing serves as a primary outcome in clinical studies. However, it is still unknown whether current software algorithms allow between-centre comparisons. In this study of healthy infants, we quantified MBW measurement errors and tried to improve data quality by simply changing software settings. We analyzed best quality MBW measurements performed with an ultrasonic flowmeter in 24 infants from two centres in Switzerland with the current software settings. To challenge the robustness of these settings, we also used alternative analysis approaches. Using the current analysis software, the coefficient of variation (CV) for functional residual capacity (FRC) differed significantly between centres (mean  ±  SD (%): 9.8  ±  5.6 and 5.8  ±  2.9, respectively, p  =  0.039). In addition, FRC values calculated during the washout differed between  -25 and  +30% from those of the washin of the same tracing. Results were mainly influenced by analysis settings and temperature recordings. Changing few algorithms resulted in significantly more robust analysis. Non-systematic inter-centre differences can be reduced by using correctly recorded environmental data and simple changes in the software algorithms. We provide implications that greatly improve infant MBW outcomes' quality and can be applied when multicentre trials are conducted.

  6. Goal-oriented failure analysis - a systems analysis approach to hazard identification

    International Nuclear Information System (INIS)

    Reeves, A.B.; Davies, J.; Foster, J.; Wells, G.L.

    1990-01-01

    Goal-Oriented Failure Analysis, GOFA, is a methodology which is being developed to identify and analyse the potential failure modes of a hazardous plant or process. The technique will adopt a structured top-down approach, with a particular failure goal being systematically analysed. A systems analysis approach is used, with the analysis being organised around a systems diagram of the plant or process under study. GOFA will also use checklists to supplement the analysis -these checklists will be prepared in advance of a group session and will help to guide the analysis and avoid unnecessary time being spent on identifying obvious failure modes or failing to identify certain hazards or failures. GOFA is being developed with the aim of providing a hazard identification methodology which is more efficient and stimulating than the conventional approach to HAZOP. The top-down approach should ensure that the analysis is more focused and the use of a systems diagram will help to pull the analysis together at an early stage whilst also helping to structure the sessions in a more stimulating way than the conventional techniques. GOFA will be, essentially, an extension of the HAZOP methodology. GOFA is currently being computerised using a knowledge-based systems approach for implementation. The Goldworks II expert systems development tool is being used. (author)

  7. A simplified approach for evaluating multiple test outcomes and multiple disease states in relation to the exercise thallium-201 stress test in suspected coronary artery disease

    International Nuclear Information System (INIS)

    Pollock, S.G.; Watson, D.D.; Gibson, R.S.; Beller, G.A.; Kaul, S.

    1989-01-01

    This study describes a simplified approach for the interpretation of electrocardiographic and thallium-201 imaging data derived from the same patient during exercise. The 383 patients in this study had also undergone selective coronary arteriography within 3 months of the exercise test. This matrix approach allows for multiple test outcomes (both tests positive, both negative, 1 test positive and 1 negative) and multiple disease states (no coronary artery disease vs 1-vessel vs multivessel coronary artery disease). Because this approach analyzes the results of 2 test outcomes simultaneously rather than serially, it also negates the lack of test independence, if such an effect is present. It is also demonstrated that ST-segment depression on the electrocardiogram and defects on initial thallium-201 images provide conditionally independent information regarding the presence of coronary artery disease in patients without prior myocardial infarction. In contrast, ST-segment depression on the electrocardiogram and redistribution on the delayed thallium-201 images may not provide totally independent information regarding the presence of exercise-induced ischemia in patients with or without myocardial infarction

  8. A polynomial-chaos-expansion-based building block approach for stochastic analysis of photonic circuits

    Science.gov (United States)

    Waqas, Abi; Melati, Daniele; Manfredi, Paolo; Grassi, Flavia; Melloni, Andrea

    2018-02-01

    The Building Block (BB) approach has recently emerged in photonic as a suitable strategy for the analysis and design of complex circuits. Each BB can be foundry related and contains a mathematical macro-model of its functionality. As well known, statistical variations in fabrication processes can have a strong effect on their functionality and ultimately affect the yield. In order to predict the statistical behavior of the circuit, proper analysis of the uncertainties effects is crucial. This paper presents a method to build a novel class of Stochastic Process Design Kits for the analysis of photonic circuits. The proposed design kits directly store the information on the stochastic behavior of each building block in the form of a generalized-polynomial-chaos-based augmented macro-model obtained by properly exploiting stochastic collocation and Galerkin methods. Using this approach, we demonstrate that the augmented macro-models of the BBs can be calculated once and stored in a BB (foundry dependent) library and then used for the analysis of any desired circuit. The main advantage of this approach, shown here for the first time in photonics, is that the stochastic moments of an arbitrary photonic circuit can be evaluated by a single simulation only, without the need for repeated simulations. The accuracy and the significant speed-up with respect to the classical Monte Carlo analysis are verified by means of classical photonic circuit example with multiple uncertain variables.

  9. Bootstrap inference when using multiple imputation.

    Science.gov (United States)

    Schomaker, Michael; Heumann, Christian

    2018-04-16

    Many modern estimators require bootstrapping to calculate confidence intervals because either no analytic standard error is available or the distribution of the parameter of interest is nonsymmetric. It remains however unclear how to obtain valid bootstrap inference when dealing with multiple imputation to address missing data. We present 4 methods that are intuitively appealing, easy to implement, and combine bootstrap estimation with multiple imputation. We show that 3 of the 4 approaches yield valid inference, but that the performance of the methods varies with respect to the number of imputed data sets and the extent of missingness. Simulation studies reveal the behavior of our approaches in finite samples. A topical analysis from HIV treatment research, which determines the optimal timing of antiretroviral treatment initiation in young children, demonstrates the practical implications of the 4 methods in a sophisticated and realistic setting. This analysis suffers from missing data and uses the g-formula for inference, a method for which no standard errors are available. Copyright © 2018 John Wiley & Sons, Ltd.

  10. Cumulative health risk assessment: integrated approaches for multiple contaminants, exposures, and effects

    International Nuclear Information System (INIS)

    Rice, Glenn; Teuschler, Linda; MacDonel, Margaret; Butler, Jim; Finster, Molly; Hertzberg, Rick; Harou, Lynne

    2007-01-01

    Available in abstract form only. Full text of publication follows: As information about environmental contamination has increased in recent years, so has public interest in the combined effects of multiple contaminants. This interest has been highlighted by recent tragedies such as the World Trade Center disaster and hurricane Katrina. In fact, assessing multiple contaminants, exposures, and effects has long been an issue for contaminated sites, including U.S. Department of Energy (DOE) legacy waste sites. Local citizens have explicitly asked the federal government to account for cumulative risks, with contaminants moving offsite via groundwater flow, surface runoff, and air dispersal being a common emphasis. Multiple exposures range from ingestion and inhalation to dermal absorption and external gamma irradiation. Three types of concerns can lead to cumulative assessments: (1) specific sources or releases - e.g., industrial facilities or accidental discharges; (2) contaminant levels - in environmental media or human tissues; and (3) elevated rates of disease - e.g., asthma or cancer. The specific initiator frames the assessment strategy, including a determination of appropriate models to be used. Approaches are being developed to better integrate a variety of data, extending from environmental to internal co-location of contaminants and combined effects, to support more practical assessments of cumulative health risks. (authors)

  11. Market segmentation for multiple option healthcare delivery systems--an application of cluster analysis.

    Science.gov (United States)

    Jarboe, G R; Gates, R H; McDaniel, C D

    1990-01-01

    Healthcare providers of multiple option plans may be confronted with special market segmentation problems. This study demonstrates how cluster analysis may be used for discovering distinct patterns of preference for multiple option plans. The availability of metric, as opposed to categorical or ordinal, data provides the ability to use sophisticated analysis techniques which may be superior to frequency distributions and cross-tabulations in revealing preference patterns.

  12. Structured plant metabolomics for the simultaneous exploration of multiple factors.

    Science.gov (United States)

    Vasilev, Nikolay; Boccard, Julien; Lang, Gerhard; Grömping, Ulrike; Fischer, Rainer; Goepfert, Simon; Rudaz, Serge; Schillberg, Stefan

    2016-11-17

    Multiple factors act simultaneously on plants to establish complex interaction networks involving nutrients, elicitors and metabolites. Metabolomics offers a better understanding of complex biological systems, but evaluating the simultaneous impact of different parameters on metabolic pathways that have many components is a challenging task. We therefore developed a novel approach that combines experimental design, untargeted metabolic profiling based on multiple chromatography systems and ionization modes, and multiblock data analysis, facilitating the systematic analysis of metabolic changes in plants caused by different factors acting at the same time. Using this method, target geraniol compounds produced in transgenic tobacco cell cultures were grouped into clusters based on their response to different factors. We hypothesized that our novel approach may provide more robust data for process optimization in plant cell cultures producing any target secondary metabolite, based on the simultaneous exploration of multiple factors rather than varying one factor each time. The suitability of our approach was verified by confirming several previously reported examples of elicitor-metabolite crosstalk. However, unravelling all factor-metabolite networks remains challenging because it requires the identification of all biochemically significant metabolites in the metabolomics dataset.

  13. A General Micro-Level Modeling Approach to Analyzing Interconnected SDGs: Achieving SDG 6 and More through Multiple-Use Water Services (MUS

    Directory of Open Access Journals (Sweden)

    Ralph P. Hall

    2017-02-01

    Full Text Available The 2030 agenda presents an integrated set of Sustainable Development Goals (SDGs and targets that will shape development activities for the coming decade. The challenge now facing development organizations and governments is how to operationalize this interconnected set of goals and targets through effective projects and programs. This paper presents a micro-level modeling approach that can quantitatively assess the impacts associated with rural water interventions that are tailored to specific communities. The analysis focuses on how a multiple-use water services (MUS approach to SDG 6 could reinforce a wide range of other SDGs and targets. The multilevel modeling framework provides a generalizable template that can be used in multiple sectors. In this paper, we apply the methodology to a dataset on rural water services from Mozambique to show that community-specific equivalents of macro-level variables used in the literature such as Cost of Illness (COI avoided can provide a better indication of the impacts of a specific intervention. The proposed modeling framework presents a new frontier for designing projects in any sector that address the specific needs of communities, while also leveraging the knowledge gained from previous projects in any country. The approach also presents a way for agencies and organizations to design projects or programs that bridge sectors/disciplines (water, irrigation, health, energy, economic development, etc. to advance an interconnected set of SDGs and targets.

  14. Quantum functional analysis non-coordinate approach

    CERN Document Server

    Helemskii, A Ya

    2010-01-01

    This book contains a systematic presentation of quantum functional analysis, a mathematical subject also known as operator space theory. Created in the 1980s, it nowadays is one of the most prominent areas of functional analysis, both as a field of active research and as a source of numerous important applications. The approach taken in this book differs significantly from the standard approach used in studying operator space theory. Instead of viewing "quantized coefficients" as matrices in a fixed basis, in this book they are interpreted as finite rank operators in a fixed Hilbert space. This allows the author to replace matrix computations with algebraic techniques of module theory and tensor products, thus achieving a more invariant approach to the subject. The book can be used by graduate students and research mathematicians interested in functional analysis and related areas of mathematics and mathematical physics. Prerequisites include standard courses in abstract algebra and functional analysis.

  15. Identification and analysis of chemical constituents and rat serum metabolites in Suan-Zao-Ren granule using ultra high performance liquid chromatography quadrupole time-of-flight mass spectrometry combined with multiple data processing approaches.

    Science.gov (United States)

    Du, Yiyang; He, Bosai; Li, Qing; He, Jiao; Wang, Di; Bi, Kaishun

    2017-07-01

    Suan-Zao-Ren granule is widely used to treat insomnia in China. However, because of the complexity and diversity of the chemical compositions in traditional Chinese medicine formula, the comprehensive analysis of constituents in vitro and in vivo is rather difficult. In our study, an ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry and the PeakView® software, which uses multiple data processing approaches including product ion filter, neutral loss filter, and mass defect filter, method was developed to characterize the ingredients and rat serum metabolites in Suan-Zao-Ren granule. A total of 101 constituents were detected in vitro. Under the same analysis conditions, 68 constituents were characterized in rat serum, including 35 prototype components and 33 metabolites. The metabolic pathways of main components were also illustrated. Among them, the metabolic pathways of timosaponin AI were firstly revealed. The bioactive compounds mainly underwent the phase I metabolic pathways including hydroxylation, oxidation, hydrolysis, and phase II metabolic pathways including sulfate conjugation, glucuronide conjugation, cysteine conjugation, acetycysteine conjugation, and glutathione conjugation. In conclusion, our results showed that this analysis approach was extremely useful for the in-depth pharmacological research of Suan-Zao-Ren granule and provided a chemical basis for its rational. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. MULGRES: a computer program for stepwise multiple regression analysis

    Science.gov (United States)

    A. Jeff Martin

    1971-01-01

    MULGRES is a computer program source deck that is designed for multiple regression analysis employing the technique of stepwise deletion in the search for most significant variables. The features of the program, along with inputs and outputs, are briefly described, with a note on machine compatibility.

  17. Young Adult and Usual Adult Body Mass Index and Multiple Myeloma Risk: A Pooled Analysis in the International Multiple Myeloma Consortium (IMMC).

    Science.gov (United States)

    Birmann, Brenda M; Andreotti, Gabriella; De Roos, Anneclaire J; Camp, Nicola J; Chiu, Brian C H; Spinelli, John J; Becker, Nikolaus; Benhaim-Luzon, Véronique; Bhatti, Parveen; Boffetta, Paolo; Brennan, Paul; Brown, Elizabeth E; Cocco, Pierluigi; Costas, Laura; Cozen, Wendy; de Sanjosé, Silvia; Foretová, Lenka; Giles, Graham G; Maynadié, Marc; Moysich, Kirsten; Nieters, Alexandra; Staines, Anthony; Tricot, Guido; Weisenburger, Dennis; Zhang, Yawei; Baris, Dalsu; Purdue, Mark P

    2017-06-01

    Background: Multiple myeloma risk increases with higher adult body mass index (BMI). Emerging evidence also supports an association of young adult BMI with multiple myeloma. We undertook a pooled analysis of eight case-control studies to further evaluate anthropometric multiple myeloma risk factors, including young adult BMI. Methods: We conducted multivariable logistic regression analysis of usual adult anthropometric measures of 2,318 multiple myeloma cases and 9,609 controls, and of young adult BMI (age 25 or 30 years) for 1,164 cases and 3,629 controls. Results: In the pooled sample, multiple myeloma risk was positively associated with usual adult BMI; risk increased 9% per 5-kg/m 2 increase in BMI [OR, 1.09; 95% confidence interval (CI), 1.04-1.14; P = 0.007]. We observed significant heterogeneity by study design ( P = 0.04), noting the BMI-multiple myeloma association only for population-based studies ( P trend = 0.0003). Young adult BMI was also positively associated with multiple myeloma (per 5-kg/m 2 ; OR, 1.2; 95% CI, 1.1-1.3; P = 0.0002). Furthermore, we observed strong evidence of interaction between younger and usual adult BMI ( P interaction adult BMI may increase multiple myeloma risk and suggest that healthy BMI maintenance throughout life may confer an added benefit of multiple myeloma prevention. Cancer Epidemiol Biomarkers Prev; 26(6); 876-85. ©2017 AACR . ©2017 American Association for Cancer Research.

  18. Sensitivity analysis approaches applied to systems biology models.

    Science.gov (United States)

    Zi, Z

    2011-11-01

    With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

  19. EMUDRA: Ensemble of Multiple Drug Repositioning Approaches to Improve Prediction Accuracy.

    Science.gov (United States)

    Zhou, Xianxiao; Wang, Minghui; Katsyv, Igor; Irie, Hanna; Zhang, Bin

    2018-04-24

    Availability of large-scale genomic, epigenetic and proteomic data in complex diseases makes it possible to objectively and comprehensively identify therapeutic targets that can lead to new therapies. The Connectivity Map has been widely used to explore novel indications of existing drugs. However, the prediction accuracy of the existing methods, such as Kolmogorov-Smirnov statistic remains low. Here we present a novel high-performance drug repositioning approach that improves over the state-of-the-art methods. We first designed an expression weighted cosine method (EWCos) to minimize the influence of the uninformative expression changes and then developed an ensemble approach termed EMUDRA (Ensemble of Multiple Drug Repositioning Approaches) to integrate EWCos and three existing state-of-the-art methods. EMUDRA significantly outperformed individual drug repositioning methods when applied to simulated and independent evaluation datasets. We predicted using EMUDRA and experimentally validated an antibiotic rifabutin as an inhibitor of cell growth in triple negative breast cancer. EMUDRA can identify drugs that more effectively target disease gene signatures and will thus be a useful tool for identifying novel therapies for complex diseases and predicting new indications for existing drugs. The EMUDRA R package is available at doi:10.7303/syn11510888. bin.zhang@mssm.edu or zhangb@hotmail.com. Supplementary data are available at Bioinformatics online.

  20. Multiple approaches to characterize the microbial community in a thermophilic anaerobic digester running on swine manure: a case study.

    Science.gov (United States)

    Tuan, Nguyen Ngoc; Chang, Yi-Chia; Yu, Chang-Ping; Huang, Shir-Ly

    2014-01-01

    In this study, the first survey of microbial community in thermophilic anaerobic digester using swine manure as sole feedstock was performed by multiple approaches including denaturing gradient gel electrophoresis (DGGE), clone library and pyrosequencing techniques. The integrated analysis of 21 DGGE bands, 126 clones and 8506 pyrosequencing read sequences revealed that Clostridia from the phylum Firmicutes account for the most dominant Bacteria. In addition, our analysis also identified additional taxa that were missed by the previous researches, including members of the bacterial phyla Synergistetes, Planctomycetes, Armatimonadetes, Chloroflexi and Nitrospira which might also play a role in thermophilic anaerobic digester. Most archaeal 16S rRNA sequences could be assigned to the order Methanobacteriales instead of Methanomicrobiales comparing to previous studies. In addition, this study reported that the member of Methanothermobacter genus was firstly found in thermophilic anaerobic digester. Copyright © 2014 Elsevier GmbH. All rights reserved.

  1. Assessing compositional variability through graphical analysis and Bayesian statistical approaches: case studies on transgenic crops.

    Science.gov (United States)

    Harrigan, George G; Harrison, Jay M

    2012-01-01

    New transgenic (GM) crops are subjected to extensive safety assessments that include compositional comparisons with conventional counterparts as a cornerstone of the process. The influence of germplasm, location, environment, and agronomic treatments on compositional variability is, however, often obscured in these pair-wise comparisons. Furthermore, classical statistical significance testing can often provide an incomplete and over-simplified summary of highly responsive variables such as crop composition. In order to more clearly describe the influence of the numerous sources of compositional variation we present an introduction to two alternative but complementary approaches to data analysis and interpretation. These include i) exploratory data analysis (EDA) with its emphasis on visualization and graphics-based approaches and ii) Bayesian statistical methodology that provides easily interpretable and meaningful evaluations of data in terms of probability distributions. The EDA case-studies include analyses of herbicide-tolerant GM soybean and insect-protected GM maize and soybean. Bayesian approaches are presented in an analysis of herbicide-tolerant GM soybean. Advantages of these approaches over classical frequentist significance testing include the more direct interpretation of results in terms of probabilities pertaining to quantities of interest and no confusion over the application of corrections for multiple comparisons. It is concluded that a standardized framework for these methodologies could provide specific advantages through enhanced clarity of presentation and interpretation in comparative assessments of crop composition.

  2. Adaptation to Climate Change in Forestry: A Multiple Correspondence Analysis (MCA

    Directory of Open Access Journals (Sweden)

    Marielle Brunette

    2018-01-01

    Full Text Available We analyze economic perspectives of forest adaptation to risk attributes, caused mostly by climate change. We construct a database with 89 systematically chosen articles, dealing simultaneously with climate, adaptation, risk and economy. We classify the database with regard to 18 variables bearing on the characteristics of the paper, the description of the risk and the adaptation strategy, the topic and the corresponding results. To achieve a “high level-of-evidence”, we realize a multiple correspondence analysis (MCA to identify which variables were found in combination with one other in the literature and make distinct groupings affecting adaptive decisions. We identify three groups: (i profit and production; (ii microeconomic risk-handling; and (iii decision and behavior. The first group includes economic costs and benefits as the driver of adaptation and prioritizes simulation, and a mix of theoretical and empirical economic approach. The second group distinctly involves risk-related issues, in particular its management by adaptation. The third group gathers a large set of social and behavioral variables affecting management decisions collected through questionnaires. Such an approach allows the identification of gaps in the literature, concerning the impact of owners’ preferences towards risk and uncertainty regarding adaptation decisions, the fact that adaptation was often reduced in an attempt to adapt to the increasing risk of wildfire, or the existence of a regional bias.

  3. Histogram analysis parameters identify multiple associations between DWI and DCE MRI in head and neck squamous cell carcinoma.

    Science.gov (United States)

    Meyer, Hans Jonas; Leifels, Leonard; Schob, Stefan; Garnov, Nikita; Surov, Alexey

    2018-01-01

    Nowadays, multiparametric investigations of head and neck squamous cell carcinoma (HNSCC) are established. These approaches can better characterize tumor biology and behavior. Diffusion weighted imaging (DWI) can by means of apparent diffusion coefficient (ADC) quantitatively characterize different tissue compartments. Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) reflects perfusion and vascularization of tissues. Recently, a novel approach of data acquisition, namely histogram analysis of different images is a novel diagnostic approach, which can provide more information of tissue heterogeneity. The purpose of this study was to analyze possible associations between DWI, and DCE parameters derived from histogram analysis in patients with HNSCC. Overall, 34 patients, 9 women and 25 men, mean age, 56.7±10.2years, with different HNSCC were involved in the study. DWI was obtained by using of an axial echo planar imaging sequence with b-values of 0 and 800s/mm 2 . Dynamic T1w DCE sequence after intravenous application of contrast medium was performed for estimation of the following perfusion parameters: volume transfer constant (K trans ), volume of the extravascular extracellular leakage space (Ve), and diffusion of contrast medium from the extravascular extracellular leakage space back to the plasma (Kep). Both ADC and perfusion parameters maps were processed offline in DICOM format with custom-made Matlab-based application. Thereafter, polygonal ROIs were manually drawn on the transferred maps on each slice. For every parameter, mean, maximal, minimal, and median values, as well percentiles 10th, 25th, 75th, 90th, kurtosis, skewness, and entropy were estimated. Сorrelation analysis identified multiple statistically significant correlations between the investigated parameters. Ve related parameters correlated well with different ADC values. Especially, percentiles 10 and 75, mode, and median values showed stronger correlations in comparison to other

  4. Fault diagnosis of sensor networked structures with multiple faults using a virtual beam based approach

    Science.gov (United States)

    Wang, H.; Jing, X. J.

    2017-07-01

    This paper presents a virtual beam based approach suitable for conducting diagnosis of multiple faults in complex structures with limited prior knowledge of the faults involved. The "virtual beam", a recently-proposed concept for fault detection in complex structures, is applied, which consists of a chain of sensors representing a vibration energy transmission path embedded in the complex structure. Statistical tests and adaptive threshold are particularly adopted for fault detection due to limited prior knowledge of normal operational conditions and fault conditions. To isolate the multiple faults within a specific structure or substructure of a more complex one, a 'biased running' strategy is developed and embedded within the bacterial-based optimization method to construct effective virtual beams and thus to improve the accuracy of localization. The proposed method is easy and efficient to implement for multiple fault localization with limited prior knowledge of normal conditions and faults. With extensive experimental results, it is validated that the proposed method can localize both single fault and multiple faults more effectively than the classical trust index subtract on negative add on positive (TI-SNAP) method.

  5. Phylo: a citizen science approach for improving multiple sequence alignment.

    Directory of Open Access Journals (Sweden)

    Alexander Kawrykow

    Full Text Available BACKGROUND: Comparative genomics, or the study of the relationships of genome structure and function across different species, offers a powerful tool for studying evolution, annotating genomes, and understanding the causes of various genetic disorders. However, aligning multiple sequences of DNA, an essential intermediate step for most types of analyses, is a difficult computational task. In parallel, citizen science, an approach that takes advantage of the fact that the human brain is exquisitely tuned to solving specific types of problems, is becoming increasingly popular. There, instances of hard computational problems are dispatched to a crowd of non-expert human game players and solutions are sent back to a central server. METHODOLOGY/PRINCIPAL FINDINGS: We introduce Phylo, a human-based computing framework applying "crowd sourcing" techniques to solve the Multiple Sequence Alignment (MSA problem. The key idea of Phylo is to convert the MSA problem into a casual game that can be played by ordinary web users with a minimal prior knowledge of the biological context. We applied this strategy to improve the alignment of the promoters of disease-related genes from up to 44 vertebrate species. Since the launch in November 2010, we received more than 350,000 solutions submitted from more than 12,000 registered users. Our results show that solutions submitted contributed to improving the accuracy of up to 70% of the alignment blocks considered. CONCLUSIONS/SIGNIFICANCE: We demonstrate that, combined with classical algorithms, crowd computing techniques can be successfully used to help improving the accuracy of MSA. More importantly, we show that an NP-hard computational problem can be embedded in casual game that can be easily played by people without significant scientific training. This suggests that citizen science approaches can be used to exploit the billions of "human-brain peta-flops" of computation that are spent every day playing games

  6. Theoretical analysis of moiré fringe multiplication under a scanning electron microscope

    International Nuclear Information System (INIS)

    Li, Yanjie; Xie, Huimin; Chen, Pengwan; Zhang, Qingming

    2011-01-01

    In this study, theoretical analysis and experimental verification of fringe multiplication under a scanning electron microscope (SEM) are presented. Fringe multiplication can be realized by enhancing the magnification or the number of scanning lines under the SEM. A universal expression of the pitch of moiré fringes is deduced. To apply this method to deformation measurement, the calculation formulas of strain and displacement are derived. Compared to natural moiré, the displacement sensitivity is increased by fringe multiplication while the strain sensitivity may be retained or enhanced depending on the number of scanning lines used. The moiré patterns are formed by the interference of a 2000 lines mm −1 grating with the scanning lines of SEM, and the measured parameters of moiré fringes from experimental results agree well with theoretical analysis

  7. gsSKAT: Rapid gene set analysis and multiple testing correction for rare-variant association studies using weighted linear kernels.

    Science.gov (United States)

    Larson, Nicholas B; McDonnell, Shannon; Cannon Albright, Lisa; Teerlink, Craig; Stanford, Janet; Ostrander, Elaine A; Isaacs, William B; Xu, Jianfeng; Cooney, Kathleen A; Lange, Ethan; Schleutker, Johanna; Carpten, John D; Powell, Isaac; Bailey-Wilson, Joan E; Cussenot, Olivier; Cancel-Tassin, Geraldine; Giles, Graham G; MacInnis, Robert J; Maier, Christiane; Whittemore, Alice S; Hsieh, Chih-Lin; Wiklund, Fredrik; Catalona, William J; Foulkes, William; Mandal, Diptasri; Eeles, Rosalind; Kote-Jarai, Zsofia; Ackerman, Michael J; Olson, Timothy M; Klein, Christopher J; Thibodeau, Stephen N; Schaid, Daniel J

    2017-05-01

    Next-generation sequencing technologies have afforded unprecedented characterization of low-frequency and rare genetic variation. Due to low power for single-variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel-machine regression and adaptive testing methods for aggregative rare-variant association testing have been demonstrated to be powerful approaches for pathway-level analysis, although these methods tend to be computationally intensive at high-variant dimensionality and require access to complete data. An additional analytical issue in scans of large pathway definition sets is multiple testing correction. Gene set definitions may exhibit substantial genic overlap, and the impact of the resultant correlation in test statistics on Type I error rate control for large agnostic gene set scans has not been fully explored. Herein, we first outline a statistical strategy for aggregative rare-variant analysis using component gene-level linear kernel score test summary statistics as well as derive simple estimators of the effective number of tests for family-wise error rate control. We then conduct extensive simulation studies to characterize the behavior of our approach relative to direct application of kernel and adaptive methods under a variety of conditions. We also apply our method to two case-control studies, respectively, evaluating rare variation in hereditary prostate cancer and schizophrenia. Finally, we provide open-source R code for public use to facilitate easy application of our methods to existing rare-variant analysis results. © 2017 WILEY PERIODICALS, INC.

  8. Two-locus linkage analysis in multiple sclerosis (MS)

    Energy Technology Data Exchange (ETDEWEB)

    Tienari, P.J. (National Public Health Institute, Helsinki (Finland) Univ. of Helsinki (Finland)); Terwilliger, J.D.; Ott, J. (Columbia Univ., New York (United States)); Palo, J. (Univ. of Helsinki (Finland)); Peltonen, L. (National Public Health Institute, Helsinki (Finland))

    1994-01-15

    One of the major challenges in genetic linkage analyses is the study of complex diseases. The authors demonstrate here the use of two-locus linkage analysis in multiple sclerosis (MS), a multifactorial disease with a complex mode of inheritance. In a set of Finnish multiplex families, they have previously found evidence for linkage between MS susceptibility and two independent loci, the myelin basic protein gene (MBP) on chromosome 18 and the HLA complex on chromosome 6. This set of families provides a unique opportunity to perform linkage analysis conditional on two loci contributing to the disease. In the two-trait-locus/two-marker-locus analysis, the presence of another disease locus is parametrized and the analysis more appropriately treats information from the unaffected family member than single-disease-locus analysis. As exemplified here in MS, the two-locus analysis can be a powerful method for investigating susceptibility loci in complex traits, best suited for analysis of specific candidate genes, or for situations in which preliminary evidence for linkage already exists or is suggested. 41 refs., 6 tabs.

  9. mma: An R Package for Mediation Analysis with Multiple Mediators

    Directory of Open Access Journals (Sweden)

    Qingzhao Yu

    2017-04-01

    Full Text Available Mediation refers to the effect transmitted by mediators that intervene in the relationship between an exposure and a response variable. Mediation analysis has been broadly studied in many fields. However, it remains a challenge for researchers to consider complicated associations among variables and to differentiate individual effects from multiple mediators. [1] proposed general definitions of mediation effects that were adaptable to all different types of response (categorical or continuous, exposure, or mediation variables. With these definitions, multiple mediators of different types can be considered simultaneously, and the indirect effects carried by individual mediators can be separated from the total effect. Moreover, the derived mediation analysis can be performed with general predictive models. That is, the relationships among variables can be modeled using not only generalized linear models but also nonparametric models such as the Multiple Additive Regression Trees. Therefore, more complicated variable transformations and interactions can be considered in analyzing the mediation effects. The proposed method is realized by the R package 'mma'. We illustrate in this paper the proposed method and how to use 'mma' to estimate mediation effects and make inferences.

  10. An Ethnografic Approach to Video Analysis

    DEFF Research Database (Denmark)

    Holck, Ulla

    2007-01-01

    The overall purpose in the ethnographic approach to video analysis is to become aware of implicit knowledge in those being observed. That is, knowledge that cannot be acquired through interviews. In music therapy this approach can be used to analyse patterns of interaction between client and ther......: Methods, Techniques and Applications in Music Therapy for Music Therapy Clinicians, Educators, Researchers and Students. London: Jessica Kingsley.......The overall purpose in the ethnographic approach to video analysis is to become aware of implicit knowledge in those being observed. That is, knowledge that cannot be acquired through interviews. In music therapy this approach can be used to analyse patterns of interaction between client...... a short introduction to the ethnographic approach, the workshop participants will have a chance to try out the method. First through a common exercise and then applied to video recordings of music therapy with children with severe communicative limitations. Focus will be on patterns of interaction...

  11. Functional analysis screening for multiple topographies of problem behavior.

    Science.gov (United States)

    Bell, Marlesha C; Fahmie, Tara A

    2018-04-23

    The current study evaluated a screening procedure for multiple topographies of problem behavior in the context of an ongoing functional analysis. Experimenters analyzed the function of a topography of primary concern while collecting data on topographies of secondary concern. We used visual analysis to predict the function of secondary topographies and a subsequent functional analysis to test those predictions. Results showed that a general function was accurately predicted for five of six (83%) secondary topographies. A specific function was predicted and supported for a subset of these topographies. The experimenters discuss the implication of these results for clinicians who have limited time for functional assessment. © 2018 Society for the Experimental Analysis of Behavior.

  12. Hierarchical approach to optimization of parallel matrix multiplication on large-scale platforms

    KAUST Repository

    Hasanov, Khalid

    2014-03-04

    © 2014, Springer Science+Business Media New York. Many state-of-the-art parallel algorithms, which are widely used in scientific applications executed on high-end computing systems, were designed in the twentieth century with relatively small-scale parallelism in mind. Indeed, while in 1990s a system with few hundred cores was considered a powerful supercomputer, modern top supercomputers have millions of cores. In this paper, we present a hierarchical approach to optimization of message-passing parallel algorithms for execution on large-scale distributed-memory systems. The idea is to reduce the communication cost by introducing hierarchy and hence more parallelism in the communication scheme. We apply this approach to SUMMA, the state-of-the-art parallel algorithm for matrix–matrix multiplication, and demonstrate both theoretically and experimentally that the modified Hierarchical SUMMA significantly improves the communication cost and the overall performance on large-scale platforms.

  13. FIRE: an SPSS program for variable selection in multiple linear regression analysis via the relative importance of predictors.

    Science.gov (United States)

    Lorenzo-Seva, Urbano; Ferrando, Pere J

    2011-03-01

    We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors. The approach consists of: (1) optimally splitting the data for cross-validation, (2) selecting the final set of predictors to be retained in the equation regression, and (3) assessing the behavior of the chosen model using standard indices and procedures. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.

  14. Application of Multiple Imputation for Missing Values in Three-Way Three-Mode Multi-Environment Trial Data.

    Science.gov (United States)

    Tian, Ting; McLachlan, Geoffrey J; Dieters, Mark J; Basford, Kaye E

    2015-01-01

    It is a common occurrence in plant breeding programs to observe missing values in three-way three-mode multi-environment trial (MET) data. We proposed modifications of models for estimating missing observations for these data arrays, and developed a novel approach in terms of hierarchical clustering. Multiple imputation (MI) was used in four ways, multiple agglomerative hierarchical clustering, normal distribution model, normal regression model, and predictive mean match. The later three models used both Bayesian analysis and non-Bayesian analysis, while the first approach used a clustering procedure with randomly selected attributes and assigned real values from the nearest neighbour to the one with missing observations. Different proportions of data entries in six complete datasets were randomly selected to be missing and the MI methods were compared based on the efficiency and accuracy of estimating those values. The results indicated that the models using Bayesian analysis had slightly higher accuracy of estimation performance than those using non-Bayesian analysis but they were more time-consuming. However, the novel approach of multiple agglomerative hierarchical clustering demonstrated the overall best performances.

  15. Meta-analysis a structural equation modeling approach

    CERN Document Server

    Cheung, Mike W-L

    2015-01-01

    Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the impo

  16. Multiple model analysis with discriminatory data collection (MMA-DDC): A new method for improving measurement selection

    Science.gov (United States)

    Kikuchi, C.; Ferre, P. A.; Vrugt, J. A.

    2011-12-01

    Hydrologic models are developed, tested, and refined based on the ability of those models to explain available hydrologic data. The optimization of model performance based upon mismatch between model outputs and real world observations has been extensively studied. However, identification of plausible models is sensitive not only to the models themselves - including model structure and model parameters - but also to the location, timing, type, and number of observations used in model calibration. Therefore, careful selection of hydrologic observations has the potential to significantly improve the performance of hydrologic models. In this research, we seek to reduce prediction uncertainty through optimization of the data collection process. A new tool - multiple model analysis with discriminatory data collection (MMA-DDC) - was developed to address this challenge. In this approach, multiple hydrologic models are developed and treated as competing hypotheses. Potential new data are then evaluated on their ability to discriminate between competing hypotheses. MMA-DDC is well-suited for use in recursive mode, in which new observations are continuously used in the optimization of subsequent observations. This new approach was applied to a synthetic solute transport experiment, in which ranges of parameter values constitute the multiple hydrologic models, and model predictions are calculated using likelihood-weighted model averaging. MMA-DDC was used to determine the optimal location, timing, number, and type of new observations. From comparison with an exhaustive search of all possible observation sequences, we find that MMA-DDC consistently selects observations which lead to the highest reduction in model prediction uncertainty. We conclude that using MMA-DDC to evaluate potential observations may significantly improve the performance of hydrologic models while reducing the cost associated with collecting new data.

  17. [Cormorbidity in multiple sclerosis and its therapeutic approach].

    Science.gov (United States)

    Estruch, Bonaventura Casanova

    2014-12-01

    Multiple sclerosis (MS) is a long-term chronic disease, in which intercurrent processes develop three times more frequently in affected individuals than in persons without MS. Knowledge of the comorbidity of MS, its definition and measurement (Charlson index) improves patient management. Acting on comorbid conditions delays the progression of disability, which is intimately linked to the number of concurrent processes and with health states and habits. Moreover, the presence of comorbidities delays the diagnosis of MS, which in turn delays the start of treatment. The main comorbidity found in MS includes other autoimmune diseases (thyroiditis, systemic lupus erythematosus, or pemphigus) but can also include general diseases, such as asthma or osteomuscular alterations, and, in particular, psychiatric disturbances. All these alterations should be evaluated with multidimensional scales (Disability Expectancy Table, DET), which allow more accurate determination of the patient's real clinical course and quality of life. These scales also allow identification of how MS, concurrent and intercurrent processes occurring during the clinical course, and the treatment provided affect patients with MS. An overall approach to patients' health status helps to improve quality of life. Copyright © 2014 Elsevier España, S.L.U. All rights reserved.

  18. Use of an iterative convolution approach for qualitative and quantitative peak analysis in low resolution gamma-ray spectra

    International Nuclear Information System (INIS)

    Gardner, Robin P.; Ai Xianyun; Peeples, Cody R.; Wang, Jiaxin; Lee, Kyoung; Peeples, Johanna L.; Calderon, Adan

    2011-01-01

    In many applications, low resolution gamma-ray spectrometers, such as sodium iodide scintillation detectors, are widely used primarily due to their relatively low cost and high detection efficiency. There is widespread interest in improved methods for analyzing spectral data acquired with such devices, using inverse analysis. Peak means and peak areas in gamma- and X-ray spectra are needed for both qualitative and quantitative analysis. This paper introduces the PEAKSI code package that was developed at the Center for Engineering Applications of Radioisotopes (CEAR). The basic approach described here is to use accurate forward models and iterative convolution instead of direct deconvolution. Rather than smoothing and differentiation a combination of linear regression and non-linear searching is used to minimize the reduced chi-square, since this approach retains the capability of establishing uncertainties in the estimated peak parameters. The PEAKSI package uses a Levenberg-Marquardt (LM) non-linear search method combined with multiple linear regression (MLR) to minimize the reduced chi-square value for fitting single or multiple overlapping peaks to determine peak parameters, including peak means, peak standard deviations or full width at half maximum (FWHM), net peak counts, and background counts of peaks in experimental gamma-ray spectra. This approach maintains the natural error structure so that parameter uncertainties can be estimated. The plan is to release this code to the public in the near future.

  19. Multiple-linac approach for tritium production and other applications

    International Nuclear Information System (INIS)

    Ruggiero, A.G.

    1995-01-01

    This report describes an approach to tritium production based on the use of multiple proton linear accelerators. Features of a single APTT Linac as proposed by the Los Alamos National Laboratory are presented and discussed. An alternative approach to the attainment of the same total proton beam power of 200 MW with several lower-performance superconducting Linacs is proposed and discussed. Although each of these accelerators are considerable extrapolations of present technology, the latter can nevertheless be built at less technical risk when compared to the single high-current APT Linac, particularly concerning the design and the performance of the low-energy front-end. The use of superconducting cavities is also proposed as a way of optimizing the accelerating gradient, the overall length, and the operational costs. The superconducting technology has already been successfully demonstrated in a number of large-size projects and should be seriously considered for the acceleration of intense low-energy beams of protons. Finally, each linear accelerator would represent an ideal source of very intense beams of protons for a variety of applications, such as: weapons and waste actinide transmutation processes, isotopes for medical application, spallation neutron sources, and the generation of intense beams of neutrinos and muons for nuclear and high-energy physics research. The research community at large has obviously an interest in providing expertise for, and in having access to, the demonstration, the construction, the operation, and the exploitation of these top-performance accelerators

  20. Multiple Stressors and Ecological Complexity Require A New Approach to Coral Reef Research

    Directory of Open Access Journals (Sweden)

    Linwood Hagan Pendleton

    2016-03-01

    Full Text Available Ocean acidification, climate change, and other environmental stressors threaten coral reef ecosystems and the people who depend upon them. New science reveals that these multiple stressors interact and may affect a multitude of physiological and ecological processes in complex ways. The interaction of multiple stressors and ecological complexity may mean that the negative effects on coral reef ecosystems will happen sooner and be more severe than previously thought. Yet, most research on the effects of global change on coral reefs focus on one or few stressors and pathways or outcomes (e.g. bleaching. Based on a critical review of the literature, we call for a regionally targeted strategy of mesocosm-level research that addresses this complexity and provides more realistic projections about coral reef impacts in the face of global environmental change. We believe similar approaches are needed for other ecosystems that face global environmental change.

  1. [Causal analysis approaches in epidemiology].

    Science.gov (United States)

    Dumas, O; Siroux, V; Le Moual, N; Varraso, R

    2014-02-01

    Epidemiological research is mostly based on observational studies. Whether such studies can provide evidence of causation remains discussed. Several causal analysis methods have been developed in epidemiology. This paper aims at presenting an overview of these methods: graphical models, path analysis and its extensions, and models based on the counterfactual approach, with a special emphasis on marginal structural models. Graphical approaches have been developed to allow synthetic representations of supposed causal relationships in a given problem. They serve as qualitative support in the study of causal relationships. The sufficient-component cause model has been developed to deal with the issue of multicausality raised by the emergence of chronic multifactorial diseases. Directed acyclic graphs are mostly used as a visual tool to identify possible confounding sources in a study. Structural equations models, the main extension of path analysis, combine a system of equations and a path diagram, representing a set of possible causal relationships. They allow quantifying direct and indirect effects in a general model in which several relationships can be tested simultaneously. Dynamic path analysis further takes into account the role of time. The counterfactual approach defines causality by comparing the observed event and the counterfactual event (the event that would have been observed if, contrary to the fact, the subject had received a different exposure than the one he actually received). This theoretical approach has shown limits of traditional methods to address some causality questions. In particular, in longitudinal studies, when there is time-varying confounding, classical methods (regressions) may be biased. Marginal structural models have been developed to address this issue. In conclusion, "causal models", though they were developed partly independently, are based on equivalent logical foundations. A crucial step in the application of these models is the

  2. MULTIPLE CRITERIA DECISION MAKING APPROACH FOR INDUSTRIAL ENGINEER SELECTION USING FUZZY AHP-FUZZY TOPSIS

    OpenAIRE

    Deliktaş, Derya; ÜSTÜN, Özden

    2018-01-01

    In this study, a fuzzy multiple criteria decision-making approach is proposed to select an industrial engineer among ten candidates in a manufacturing environment. The industrial engineer selection problem is a special case of the personal selection problem. This problem, which has hierarchical structure of criteria and many decision makers, contains many criteria. The evaluation process of decision makers also includes ambiguous parameters. The fuzzy AHP is used to determin...

  3. A quantitative approach to choose among multiple mutually exclusive decisions: comparative expected utility theory

    OpenAIRE

    Zhu, Pengyu

    2018-01-01

    Mutually exclusive decisions have been studied for decades. Many well-known decision theories have been defined to help people either to make rational decisions or to interpret people's behaviors, such as expected utility theory, regret theory, prospect theory, and so on. The paper argues that none of these decision theories are designed to provide practical, normative and quantitative approaches for multiple mutually exclusive decisions. Different decision-makers should naturally make differ...

  4. A P-value model for theoretical power analysis and its applications in multiple testing procedures

    Directory of Open Access Journals (Sweden)

    Fengqing Zhang

    2016-10-01

    Full Text Available Abstract Background Power analysis is a critical aspect of the design of experiments to detect an effect of a given size. When multiple hypotheses are tested simultaneously, multiplicity adjustments to p-values should be taken into account in power analysis. There are a limited number of studies on power analysis in multiple testing procedures. For some methods, the theoretical analysis is difficult and extensive numerical simulations are often needed, while other methods oversimplify the information under the alternative hypothesis. To this end, this paper aims to develop a new statistical model for power analysis in multiple testing procedures. Methods We propose a step-function-based p-value model under the alternative hypothesis, which is simple enough to perform power analysis without simulations, but not too simple to lose the information from the alternative hypothesis. The first step is to transform distributions of different test statistics (e.g., t, chi-square or F to distributions of corresponding p-values. We then use a step function to approximate each of the p-value’s distributions by matching the mean and variance. Lastly, the step-function-based p-value model can be used for theoretical power analysis. Results The proposed model is applied to problems in multiple testing procedures. We first show how the most powerful critical constants can be chosen using the step-function-based p-value model. Our model is then applied to the field of multiple testing procedures to explain the assumption of monotonicity of the critical constants. Lastly, we apply our model to a behavioral weight loss and maintenance study to select the optimal critical constants. Conclusions The proposed model is easy to implement and preserves the information from the alternative hypothesis.

  5. Identification of novel adhesins of M. tuberculosis H37Rv using integrated approach of multiple computational algorithms and experimental analysis.

    Directory of Open Access Journals (Sweden)

    Sanjiv Kumar

    Full Text Available Pathogenic bacteria interacting with eukaryotic host express adhesins on their surface. These adhesins aid in bacterial attachment to the host cell receptors during colonization. A few adhesins such as Heparin binding hemagglutinin adhesin (HBHA, Apa, Malate Synthase of M. tuberculosis have been identified using specific experimental interaction models based on the biological knowledge of the pathogen. In the present work, we carried out computational screening for adhesins of M. tuberculosis. We used an integrated computational approach using SPAAN for predicting adhesins, PSORTb, SubLoc and LocTree for extracellular localization, and BLAST for verifying non-similarity to human proteins. These steps are among the first of reverse vaccinology. Multiple claims and attacks from different algorithms were processed through argumentative approach. Additional filtration criteria included selection for proteins with low molecular weights and absence of literature reports. We examined binding potential of the selected proteins using an image based ELISA. The protein Rv2599 (membrane protein binds to human fibronectin, laminin and collagen. Rv3717 (N-acetylmuramoyl-L-alanine amidase and Rv0309 (L,D-transpeptidase bind to fibronectin and laminin. We report Rv2599 (membrane protein, Rv0309 and Rv3717 as novel adhesins of M. tuberculosis H37Rv. Our results expand the number of known adhesins of M. tuberculosis and suggest their regulated expression in different stages.

  6. Analysis of Multiple Genomic Sequence Alignments: A Web Resource, Online Tools, and Lessons Learned From Analysis of Mammalian SCL Loci

    Science.gov (United States)

    Chapman, Michael A.; Donaldson, Ian J.; Gilbert, James; Grafham, Darren; Rogers, Jane; Green, Anthony R.; Göttgens, Berthold

    2004-01-01

    Comparative analysis of genomic sequences is becoming a standard technique for studying gene regulation. However, only a limited number of tools are currently available for the analysis of multiple genomic sequences. An extensive data set for the testing and training of such tools is provided by the SCL gene locus. Here we have expanded the data set to eight vertebrate species by sequencing the dog SCL locus and by annotating the dog and rat SCL loci. To provide a resource for the bioinformatics community, all SCL sequences and functional annotations, comprising a collation of the extensive experimental evidence pertaining to SCL regulation, have been made available via a Web server. A Web interface to new tools specifically designed for the display and analysis of multiple sequence alignments was also implemented. The unique SCL data set and new sequence comparison tools allowed us to perform a rigorous examination of the true benefits of multiple sequence comparisons. We demonstrate that multiple sequence alignments are, overall, superior to pairwise alignments for identification of mammalian regulatory regions. In the search for individual transcription factor binding sites, multiple alignments markedly increase the signal-to-noise ratio compared to pairwise alignments. PMID:14718377

  7. Using Module Analysis for Multiple Choice Responses: A New Method Applied to Force Concept Inventory Data

    Science.gov (United States)

    Brewe, Eric; Bruun, Jesper; Bearden, Ian G.

    2016-01-01

    We describe "Module Analysis for Multiple Choice Responses" (MAMCR), a new methodology for carrying out network analysis on responses to multiple choice assessments. This method is used to identify modules of non-normative responses which can then be interpreted as an alternative to factor analysis. MAMCR allows us to identify conceptual…

  8. Unsupervised multiple kernel learning for heterogeneous data integration.

    Science.gov (United States)

    Mariette, Jérôme; Villa-Vialaneix, Nathalie

    2018-03-15

    Recent high-throughput sequencing advances have expanded the breadth of available omics datasets and the integrated analysis of multiple datasets obtained on the same samples has allowed to gain important insights in a wide range of applications. However, the integration of various sources of information remains a challenge for systems biology since produced datasets are often of heterogeneous types, with the need of developing generic methods to take their different specificities into account. We propose a multiple kernel framework that allows to integrate multiple datasets of various types into a single exploratory analysis. Several solutions are provided to learn either a consensus meta-kernel or a meta-kernel that preserves the original topology of the datasets. We applied our framework to analyse two public multi-omics datasets. First, the multiple metagenomic datasets, collected during the TARA Oceans expedition, was explored to demonstrate that our method is able to retrieve previous findings in a single kernel PCA as well as to provide a new image of the sample structures when a larger number of datasets are included in the analysis. To perform this analysis, a generic procedure is also proposed to improve the interpretability of the kernel PCA in regards with the original data. Second, the multi-omics breast cancer datasets, provided by The Cancer Genome Atlas, is analysed using a kernel Self-Organizing Maps with both single and multi-omics strategies. The comparison of these two approaches demonstrates the benefit of our integration method to improve the representation of the studied biological system. Proposed methods are available in the R package mixKernel, released on CRAN. It is fully compatible with the mixOmics package and a tutorial describing the approach can be found on mixOmics web site http://mixomics.org/mixkernel/. jerome.mariette@inra.fr or nathalie.villa-vialaneix@inra.fr. Supplementary data are available at Bioinformatics online.

  9. A neutron multiplicity analysis method for uranium samples with liquid scintillators

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Hao, E-mail: zhouhao_ciae@126.com [China Institute of Atomic Energy, P.O.BOX 275-8, Beijing 102413 (China); Lin, Hongtao [Xi' an Reasearch Institute of High-tech, Xi' an, Shaanxi 710025 (China); Liu, Guorong; Li, Jinghuai; Liang, Qinglei; Zhao, Yonggang [China Institute of Atomic Energy, P.O.BOX 275-8, Beijing 102413 (China)

    2015-10-11

    A new neutron multiplicity analysis method for uranium samples with liquid scintillators is introduced. An active well-type fast neutron multiplicity counter has been built, which consists of four BC501A liquid scintillators, a n/γdiscrimination module MPD-4, a multi-stop time to digital convertor MCS6A, and two Am–Li sources. A mathematical model is built to symbolize the detection processes of fission neutrons. Based on this model, equations in the form of R=F*P*Q*T could be achieved, where F indicates the induced fission rate by interrogation sources, P indicates the transfer matrix determined by multiplication process, Q indicates the transfer matrix determined by detection efficiency, T indicates the transfer matrix determined by signal recording process and crosstalk in the counter. Unknown parameters about the item are determined by the solutions of the equations. A {sup 252}Cf source and some low enriched uranium items have been measured. The feasibility of the method is proven by its application to the data analysis of the experiments.

  10. Multiple Criteria Decision Analysis for Health Care Decision Making--An Introduction: Report 1 of the ISPOR MCDA Emerging Good Practices Task Force.

    Science.gov (United States)

    Thokala, Praveen; Devlin, Nancy; Marsh, Kevin; Baltussen, Rob; Boysen, Meindert; Kalo, Zoltan; Longrenn, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Ijzerman, Maarten

    2016-01-01

    Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting, objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making and a set of techniques, known under the collective heading multiple criteria decision analysis (MCDA), are useful for this purpose. MCDA methods are widely used in other sectors, and recently there has been an increase in health care applications. In 2014, ISPOR established an MCDA Emerging Good Practices Task Force. It was charged with establishing a common definition for MCDA in health care decision making and developing good practice guidelines for conducting MCDA to aid health care decision making. This initial ISPOR MCDA task force report provides an introduction to MCDA - it defines MCDA; provides examples of its use in different kinds of decision making in health care (including benefit risk analysis, health technology assessment, resource allocation, portfolio decision analysis, shared patient clinician decision making and prioritizing patients' access to services); provides an overview of the principal methods of MCDA; and describes the key steps involved. Upon reviewing this report, readers should have a solid overview of MCDA methods and their potential for supporting health care decision making. Copyright © 2016. Published by Elsevier Inc.

  11. Assessing the use of multiple sources in student essays.

    Science.gov (United States)

    Hastings, Peter; Hughes, Simon; Magliano, Joseph P; Goldman, Susan R; Lawless, Kimberly

    2012-09-01

    The present study explored different approaches for automatically scoring student essays that were written on the basis of multiple texts. Specifically, these approaches were developed to classify whether or not important elements of the texts were present in the essays. The first was a simple pattern-matching approach called "multi-word" that allowed for flexible matching of words and phrases in the sentences. The second technique was latent semantic analysis (LSA), which was used to compare student sentences to original source sentences using its high-dimensional vector-based representation. Finally, the third was a machine-learning technique, support vector machines, which learned a classification scheme from the corpus. The results of the study suggested that the LSA-based system was superior for detecting the presence of explicit content from the texts, but the multi-word pattern-matching approach was better for detecting inferences outside or across texts. These results suggest that the best approach for analyzing essays of this nature should draw upon multiple natural language processing approaches.

  12. Targeted Quantitation of Site-Specific Cysteine Oxidation in Endogenous Proteins Using a Differential Alkylation and Multiple Reaction Monitoring Mass Spectrometry Approach

    Science.gov (United States)

    Held, Jason M.; Danielson, Steven R.; Behring, Jessica B.; Atsriku, Christian; Britton, David J.; Puckett, Rachel L.; Schilling, Birgit; Campisi, Judith; Benz, Christopher C.; Gibson, Bradford W.

    2010-01-01

    Reactive oxygen species (ROS) are both physiological intermediates in cellular signaling and mediators of oxidative stress. The cysteine-specific redox-sensitivity of proteins can shed light on how ROS are regulated and function, but low sensitivity has limited quantification of the redox state of many fundamental cellular regulators in a cellular context. Here we describe a highly sensitive and reproducible oxidation analysis approach (OxMRM) that combines protein purification, differential alkylation with stable isotopes, and multiple reaction monitoring mass spectrometry that can be applied in a targeted manner to virtually any cysteine or protein. Using this approach, we quantified the site-specific cysteine oxidation status of endogenous p53 for the first time and found that Cys182 at the dimerization interface of the DNA binding domain is particularly susceptible to diamide oxidation intracellularly. OxMRM enables analysis of sulfinic and sulfonic acid oxidation levels, which we validate by assessing the oxidation of the catalytic Cys215 of protein tyrosine phosphatase-1B under numerous oxidant conditions. OxMRM also complements unbiased redox proteomics discovery studies as a verification tool through its high sensitivity, accuracy, precision, and throughput. PMID:20233844

  13. MLPAinter for MLPA interpretation: an integrated approach for the analysis, visualisation and data management of Multiplex Ligation-dependent Probe Amplification

    Directory of Open Access Journals (Sweden)

    Morreau Hans

    2010-01-01

    Full Text Available Abstract Background Multiplex Ligation-Dependent Probe Amplification (MLPA is an application that can be used for the detection of multiple chromosomal aberrations in a single experiment. In one reaction, up to 50 different genomic sequences can be analysed. For a reliable work-flow, tools are needed for administrative support, data management, normalisation, visualisation, reporting and interpretation. Results Here, we developed a data management system, MLPAInter for MLPA interpretation, that is windows executable and has a stand-alone database for monitoring and interpreting the MLPA data stream that is generated from the experimental setup to analysis, quality control and visualisation. A statistical approach is applied for the normalisation and analysis of large series of MLPA traces, making use of multiple control samples and internal controls. Conclusions MLPAinter visualises MLPA data in plots with information about sample replicates, normalisation settings, and sample characteristics. This integrated approach helps in the automated handling of large series of MLPA data and guarantees a quick and streamlined dataflow from the beginning of an experiment to an authorised report.

  14. Multiple endmember spectral-angle-mapper (SAM) analysis improves discrimination of Savanna tree species

    CSIR Research Space (South Africa)

    Cho, Moses A

    2009-08-01

    Full Text Available of this paper was to evaluate the classification performance of a multiple-endmember spectral angle mapper (SAM) classification approach in discriminating seven common African savanna tree species and to compare the results with the traditional SAM classifier...

  15. Improving Students' Creative Thinking and Achievement through the Implementation of Multiple Intelligence Approach with Mind Mapping

    Science.gov (United States)

    Widiana, I. Wayan; Jampel, I. Nyoman

    2016-01-01

    This classroom action research aimed to improve the students' creative thinking and achievement in learning science. It conducted through the implementation of multiple intelligences with mind mapping approach and describing the students' responses. The subjects of this research were the fifth grade students of SD 8 Tianyar Barat, Kubu, and…

  16. Multiple calibration decomposition analysis: Energy use and carbon dioxide emissions in the Japanese economy, 1970-1995

    International Nuclear Information System (INIS)

    Okushima, Shinichiro; Tamura, Makoto

    2007-01-01

    The purpose of this paper is to present a new approach to evaluating structural change of the economy in a multisector general equilibrium framework. The multiple calibration technique is applied to an ex post decomposition analysis of structural change between periods, enabling the distinction between price substitution and technological change to be made for each sector. This approach has the advantage of sounder microtheoretical underpinnings when compared with conventional decomposition methods. The proposed technique is empirically applied to changes in energy use and carbon dioxide (CO 2 ) emissions in the Japanese economy from 1970 to 1995. The results show that technological change is of great importance for curtailing energy use and CO 2 emissions in Japan. Total CO 2 emissions increased during this period primarily because of economic growth, which is represented by final demand effects. On the other hand, the effects such as technological change for labor or energy mitigated the increase in CO 2 emissions

  17. Interventional Effects for Mediation Analysis with Multiple Mediators.

    Science.gov (United States)

    Vansteelandt, Stijn; Daniel, Rhian M

    2017-03-01

    The mediation formula for the identification of natural (in)direct effects has facilitated mediation analyses that better respect the nature of the data, with greater consideration of the need for confounding control. The default assumptions on which it relies are strong, however. In particular, they are known to be violated when confounders of the mediator-outcome association are affected by the exposure. This complicates extensions of counterfactual-based mediation analysis to settings that involve repeatedly measured mediators, or multiple correlated mediators. VanderWeele, Vansteelandt, and Robins introduced so-called interventional (in)direct effects. These can be identified under much weaker conditions than natural (in)direct effects, but have the drawback of not adding up to the total effect. In this article, we adapt their proposal to achieve an exact decomposition of the total effect, and extend it to the multiple mediator setting. Interestingly, the proposed effects capture the path-specific effects of an exposure on an outcome that are mediated by distinct mediators, even when-as often-the structural dependence between the multiple mediators is unknown, for instance, when the direction of the causal effects between the mediators is unknown, or there may be unmeasured common causes of the mediators.

  18. Analysis of the thermal balance characteristics for multiple-connected piezoelectric transformers.

    Science.gov (United States)

    Park, Joung-Hu; Cho, Bo-Hyung; Choi, Sung-Jin; Lee, Sang-Min

    2009-08-01

    Because the amount of power that a piezoelectric transformer (PT) can handle is limited, multiple connections of PTs are necessary for the power-capacity improvement of PT-applications. In the connection, thermal imbalance between the PTs should be prevented to avoid the thermal runaway of each PT. The thermal balance of the multiple-connected PTs is dominantly affected by the electrothermal characteristics of individual PTs. In this paper, the thermal balance of both parallel-parallel and parallel-series connections are analyzed by electrical model parameters. For quantitative analysis, the thermal-balance effects are estimated by the simulation of the mechanical loss ratio between the PTs. The analysis results show that with PTs of similar characteristics, the parallel-series connection has better thermal balance characteristics due to the reduced mechanical loss of the higher temperature PT. For experimental verification of the analysis, a hardware-prototype test of a Cs-Lp type 40 W adapter system with radial-vibration mode PTs has been performed.

  19. Interstage Flammability Analysis Approach

    Science.gov (United States)

    Little, Jeffrey K.; Eppard, William M.

    2011-01-01

    The Interstage of the Ares I launch platform houses several key components which are on standby during First Stage operation: the Reaction Control System (ReCS), the Upper Stage (US) Thrust Vector Control (TVC) and the J-2X with the Main Propulsion System (MPS) propellant feed system. Therefore potentially dangerous leaks of propellants could develop. The Interstage leaks analysis addresses the concerns of localized mixing of hydrogen and oxygen gases to produce deflagration zones in the Interstage of the Ares I launch vehicle during First Stage operation. This report details the approach taken to accomplish the analysis. Specified leakage profiles and actual flammability results are not presented due to proprietary and security restrictions. The interior volume formed by the Interstage walls, bounding interfaces with the Upper and First Stages, and surrounding the J2-X engine was modeled using Loci-CHEM to assess the potential for flammable gas mixtures to develop during First Stage operations. The transient analysis included a derived flammability indicator based on mixture ratios to maintain achievable simulation times. Validation of results was based on a comparison to Interstage pressure profiles outlined in prior NASA studies. The approach proved useful in the bounding of flammability risk in supporting program hazard reviews.

  20. Tailor-made rehabilitation approach using multiple types of hybrid assistive limb robots for acute stroke patients: A pilot study.

    Science.gov (United States)

    Fukuda, Hiroyuki; Morishita, Takashi; Ogata, Toshiyasu; Saita, Kazuya; Hyakutake, Koichi; Watanabe, Junko; Shiota, Etsuji; Inoue, Tooru

    2016-01-01

    This article investigated the feasibility of a tailor-made neurorehabilitation approach using multiple types of hybrid assistive limb (HAL) robots for acute stroke patients. We investigated the clinical outcomes of patients who underwent rehabilitation using the HAL robots. The Brunnstrom stage, Barthel index (BI), and functional independence measure (FIM) were evaluated at baseline and when patients were transferred to a rehabilitation facility. Scores were compared between the multiple-robot rehabilitation and single-robot rehabilitation groups. Nine hemiplegic acute stroke patients (five men and four women; mean age 59.4 ± 12.5 years; four hemorrhagic stroke and five ischemic stroke) underwent rehabilitation using multiple types of HAL robots for 19.4 ± 12.5 days, and 14 patients (six men and eight women; mean age 63.2 ± 13.9 years; nine hemorrhagic stroke and five ischemic stroke) underwent rehabilitation using a single type of HAL robot for 14.9 ± 8.9 days. The multiple-robot rehabilitation group showed significantly better outcomes in the Brunnstrom stage of the upper extremity, BI, and FIM scores. To the best of the authors' knowledge, this is the first pilot study demonstrating the feasibility of rehabilitation using multiple exoskeleton robots. The tailor-made rehabilitation approach may be useful for the treatment of acute stroke.

  1. Linear systems with unstructured multiplicative uncertainty: Modeling and robust stability analysis.

    Directory of Open Access Journals (Sweden)

    Radek Matušů

    Full Text Available This article deals with continuous-time Linear Time-Invariant (LTI Single-Input Single-Output (SISO systems affected by unstructured multiplicative uncertainty. More specifically, its aim is to present an approach to the construction of uncertain models based on the appropriate selection of a nominal system and a weight function and to apply the fundamentals of robust stability investigation for considered sort of systems. The initial theoretical parts are followed by three extensive illustrative examples in which the first order time-delay, second order and third order plants with parametric uncertainty are modeled as systems with unstructured multiplicative uncertainty and subsequently, the robust stability of selected feedback loops containing constructed models and chosen controllers is analyzed and obtained results are discussed.

  2. Uncertainty Quantification and Bifurcation Analysis of an Airfoil with Multiple Nonlinearities

    Directory of Open Access Journals (Sweden)

    Haitao Liao

    2013-01-01

    Full Text Available In order to calculate the limit cycle oscillations and bifurcations of nonlinear aeroelastic system, the problem of finding periodic solutions with maximum vibration amplitude is transformed into a nonlinear optimization problem. An algebraic system of equations obtained by the harmonic balance method and the stability condition derived from the Floquet theory are used to construct the general nonlinear equality and inequality constraints. The resulting constrained maximization problem is then solved by using the MultiStart algorithm. Finally, the proposed approach is validated, and the effects of structural parameter uncertainty on the limit cycle oscillations and bifurcations of an airfoil with multiple nonlinearities are studied. Numerical examples show that the coexistence of multiple nonlinearities may lead to low amplitude limit cycle oscillation.

  3. Multifractal detrended fluctuation analysis of analog random multiplicative processes

    Energy Technology Data Exchange (ETDEWEB)

    Silva, L.B.M.; Vermelho, M.V.D. [Instituto de Fisica, Universidade Federal de Alagoas, Maceio - AL, 57072-970 (Brazil); Lyra, M.L. [Instituto de Fisica, Universidade Federal de Alagoas, Maceio - AL, 57072-970 (Brazil)], E-mail: marcelo@if.ufal.br; Viswanathan, G.M. [Instituto de Fisica, Universidade Federal de Alagoas, Maceio - AL, 57072-970 (Brazil)

    2009-09-15

    We investigate non-Gaussian statistical properties of stationary stochastic signals generated by an analog circuit that simulates a random multiplicative process with weak additive noise. The random noises are originated by thermal shot noise and avalanche processes, while the multiplicative process is generated by a fully analog circuit. The resulting signal describes stochastic time series of current interest in several areas such as turbulence, finance, biology and environment, which exhibit power-law distributions. Specifically, we study the correlation properties of the signal by employing a detrended fluctuation analysis and explore its multifractal nature. The singularity spectrum is obtained and analyzed as a function of the control circuit parameter that tunes the asymptotic power-law form of the probability distribution function.

  4. Systemic Analysis Approaches for Air Transportation

    Science.gov (United States)

    Conway, Sheila

    2005-01-01

    Air transportation system designers have had only limited success using traditional operations research and parametric modeling approaches in their analyses of innovations. They need a systemic methodology for modeling of safety-critical infrastructure that is comprehensive, objective, and sufficiently concrete, yet simple enough to be used with reasonable investment. The methodology must also be amenable to quantitative analysis so issues of system safety and stability can be rigorously addressed. However, air transportation has proven itself an extensive, complex system whose behavior is difficult to describe, no less predict. There is a wide range of system analysis techniques available, but some are more appropriate for certain applications than others. Specifically in the area of complex system analysis, the literature suggests that both agent-based models and network analysis techniques may be useful. This paper discusses the theoretical basis for each approach in these applications, and explores their historic and potential further use for air transportation analysis.

  5. Multiple Shooting and Time Domain Decomposition Methods

    CERN Document Server

    Geiger, Michael; Körkel, Stefan; Rannacher, Rolf

    2015-01-01

    This book offers a comprehensive collection of the most advanced numerical techniques for the efficient and effective solution of simulation and optimization problems governed by systems of time-dependent differential equations. The contributions present various approaches to time domain decomposition, focusing on multiple shooting and parareal algorithms.  The range of topics covers theoretical analysis of the methods, as well as their algorithmic formulation and guidelines for practical implementation. Selected examples show that the discussed approaches are mandatory for the solution of challenging practical problems. The practicability and efficiency of the presented methods is illustrated by several case studies from fluid dynamics, data compression, image processing and computational biology, giving rise to possible new research topics.  This volume, resulting from the workshop Multiple Shooting and Time Domain Decomposition Methods, held in Heidelberg in May 2013, will be of great interest to applied...

  6. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis☆

    Science.gov (United States)

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-01-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster–Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty–sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights. PMID:25843987

  7. Analysis of multiple spurions and associated circuits in Cofrentes

    International Nuclear Information System (INIS)

    Molina, J. J.; Celaya, M. A.

    2015-01-01

    The article describes the process followed by the Cofrentes Nuclear Power Plant (CNC) to conduct the analysis of multiple spurious in compliance with regulatory standards IS-30 rev 1 and CSN Safety Guide 1.19 based on the recommendations of the NEI-00-01 Guidance for Post-fire Safe Shutdown Circuit and NUREG/CR-6850. Fire PRA Methodology for Nuclear Power Facilities. (Author)

  8. Multi-level approach for parametric roll analysis

    Science.gov (United States)

    Kim, Taeyoung; Kim, Yonghwan

    2011-03-01

    The present study considers multi-level approach for the analysis of parametric roll phenomena. Three kinds of computation method, GM variation, impulse response function (IRF), and Rankine panel method, are applied for the multi-level approach. IRF and Rankine panel method are based on the weakly nonlinear formulation which includes nonlinear Froude- Krylov and restoring forces. In the computation result of parametric roll occurrence test in regular waves, IRF and Rankine panel method show similar tendency. Although the GM variation approach predicts the occurrence of parametric roll at twice roll natural frequency, its frequency criteria shows a little difference. Nonlinear roll motion in bichromatic wave is also considered in this study. To prove the unstable roll motion in bichromatic waves, theoretical and numerical approaches are applied. The occurrence of parametric roll is theoretically examined by introducing the quasi-periodic Mathieu equation. Instability criteria are well predicted from stability analysis in theoretical approach. From the Fourier analysis, it has been verified that difference-frequency effects create the unstable roll motion. The occurrence of unstable roll motion in bichromatic wave is also observed in the experiment.

  9. Practical guidance for conducting mediation analysis with multiple mediators using inverse odds ratio weighting.

    Science.gov (United States)

    Nguyen, Quynh C; Osypuk, Theresa L; Schmidt, Nicole M; Glymour, M Maria; Tchetgen Tchetgen, Eric J

    2015-03-01

    Despite the recent flourishing of mediation analysis techniques, many modern approaches are difficult to implement or applicable to only a restricted range of regression models. This report provides practical guidance for implementing a new technique utilizing inverse odds ratio weighting (IORW) to estimate natural direct and indirect effects for mediation analyses. IORW takes advantage of the odds ratio's invariance property and condenses information on the odds ratio for the relationship between the exposure (treatment) and multiple mediators, conditional on covariates, by regressing exposure on mediators and covariates. The inverse of the covariate-adjusted exposure-mediator odds ratio association is used to weight the primary analytical regression of the outcome on treatment. The treatment coefficient in such a weighted regression estimates the natural direct effect of treatment on the outcome, and indirect effects are identified by subtracting direct effects from total effects. Weighting renders treatment and mediators independent, thereby deactivating indirect pathways of the mediators. This new mediation technique accommodates multiple discrete or continuous mediators. IORW is easily implemented and is appropriate for any standard regression model, including quantile regression and survival analysis. An empirical example is given using data from the Moving to Opportunity (1994-2002) experiment, testing whether neighborhood context mediated the effects of a housing voucher program on obesity. Relevant Stata code (StataCorp LP, College Station, Texas) is provided. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  10. A relational approach to support software architecture analysis

    NARCIS (Netherlands)

    Feijs, L.M.G.; Krikhaar, R.L.; van Ommering, R.C.

    1998-01-01

    This paper reports on our experience with a relational approach to support the analysis of existing software architectures. The analysis options provide for visualization and view calculation. The approach has been applied for reverse engineering. It is also possible to check concrete designs

  11. Retinal layer segmentation in multiple sclerosis: a systematic review and meta-analysis.

    Science.gov (United States)

    Petzold, Axel; Balcer, Laura J; Calabresi, Peter A; Costello, Fiona; Frohman, Teresa C; Frohman, Elliot M; Martinez-Lapiscina, Elena H; Green, Ari J; Kardon, Randy; Outteryck, Olivier; Paul, Friedemann; Schippling, Sven; Vermersch, Patrik; Villoslada, Pablo; Balk, Lisanne J

    2017-10-01

    Structural retinal imaging biomarkers are important for early recognition and monitoring of inflammation and neurodegeneration in multiple sclerosis. With the introduction of spectral domain optical coherence tomography (SD-OCT), supervised automated segmentation of individual retinal layers is possible. We aimed to investigate which retinal layers show atrophy associated with neurodegeneration in multiple sclerosis when measured with SD-OCT. In this systematic review and meta-analysis, we searched for studies in which SD-OCT was used to look at the retina in people with multiple sclerosis with or without optic neuritis in PubMed, Web of Science, and Google Scholar between Nov 22, 1991, and April 19, 2016. Data were taken from cross-sectional cohorts and from one timepoint from longitudinal studies (at least 3 months after onset in studies of optic neuritis). We classified data on eyes into healthy controls, multiple-sclerosis-associated optic neuritis (MSON), and multiple sclerosis without optic neuritis (MSNON). We assessed thickness of the retinal layers and we rated individual layer segmentation performance by random effects meta-analysis for MSON eyes versus control eyes, MSNON eyes versus control eyes, and MSNON eyes versus MSON eyes. We excluded relevant sources of bias by funnel plots. Of 25 497 records identified, 110 articles were eligible and 40 reported data (in total 5776 eyes from patients with multiple sclerosis [1667 MSON eyes and 4109 MSNON eyes] and 1697 eyes from healthy controls) that met published OCT quality control criteria and were suitable for meta-analysis. Compared with control eyes, the peripapillary retinal nerve fibre layer (RNFL) showed thinning in MSON eyes (mean difference -20·10 μm, 95% CI -22·76 to -17·44; pmultiple sclerosis and control eyes were found in the peripapillary RNFL and macular GCIPL. Inflammatory disease activity might be captured by the INL. Because of the consistency, robustness, and large effect size, we

  12. Predictors of postoperative outcomes of cubital tunnel syndrome treatments using multiple logistic regression analysis.

    Science.gov (United States)

    Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki

    2017-05-01

    This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

  13. The impact of wildland fires on calcareous Mediterranean pedosystems (Sardinia, Italy) - An integrated multiple approach.

    Science.gov (United States)

    Capra, Gian Franco; Tidu, Simona; Lovreglio, Raffaella; Certini, Giacomo; Salis, Michele; Bacciu, Valentina; Ganga, Antonio; Filzmoser, Peter

    2018-05-15

    Sardinia (Italy), the second largest island of the Mediterranean Sea, is a fire-prone land. Most Sardinian environments over time were shaped by fire, but some of them are too intrinsically fragile to withstand the currently increasing fire frequency. Calcareous pedoenvironments represent a significant part of Mediterranean areas, and require important efforts to prevent long-lasting degradation from fire. The aim of this study was to assess through an integrated multiple approach the impact of a single and highly severe wildland fire on limestone-derived soils. For this purpose, we selected two recently burned sites, Sant'Antioco and Laconi. Soil was sampled from 80 points on a 100×100m grid - 40 in the burned area and 40 in unburned one - and analyzed for particle size fractions, pH, electrical conductivity, organic carbon, total N, total P, and water repellency (WR). Fire behavior (surface rate of spread (ROS), fireline intensity (FLI), flame length (FL)) was simulated by BehavePlus 5.0.5 software. Comparisons between burned and unburned areas were done through ANOVA as well as deterministic and stochastic interpolation techniques; multiple correlations among parameters were evaluated by principal factor analysis (PFA) and differences/similarities between areas by principal component analysis (PCA). In both sites, fires were characterized by high severity and determined significant changes to some soil properties. The PFA confirmed the key ecological role played by fire in both sites, with the variability of a four-modeled components mainly explained by fire parameters, although the induced changes on soils were mainly site-specific. The PCA revealed the presence of two main "driving factors": slope (in Sant'Antioco), which increased the magnitude of ROS and FLI; and soil properties (in Laconi), which mostly affected FL. In both sites, such factors played a direct role in differentiating fire behavior and sites, while they played an indirect role in determining

  14. Multiple Skills Underlie Arithmetic Performance: A Large-Scale Structural Equation Modeling Analysis

    Directory of Open Access Journals (Sweden)

    Sarit Ashkenazi

    2017-12-01

    Full Text Available Current theoretical approaches point to the importance of several cognitive skills not specific to mathematics for the etiology of mathematics disorders (MD. In the current study, we examined the role of many of these skills, specifically: rapid automatized naming, attention, reading, and visual perception, on mathematics performance among a large group of college students (N = 1,322 with a wide range of arithmetic proficiency. Using factor analysis, we discovered that our data clustered to four latent variables 1 mathematics, 2 perception speed, 3 attention and 4 reading. In subsequent structural equation modeling, we found that the latent variable perception speed had a strong and meaningful effect on mathematics performance. Moreover, sustained attention, independent from the effect of the latent variable perception speed, had a meaningful, direct effect on arithmetic fact retrieval and procedural knowledge. The latent variable reading had a modest effect on mathematics performance. Specifically, reading comprehension, independent from the effect of the latent variable reading, had a meaningful direct effect on mathematics, and particularly on number line knowledge. Attention, tested by the attention network test, had no effect on mathematics, reading or perception speed. These results indicate that multiple factors can affect mathematics performance supporting a heterogeneous approach to mathematics. These results have meaningful implications for the diagnosis and intervention of pure and comorbid learning disorders.

  15. Possible antecedents and consequences of self-esteem in persons with multiple sclerosis: preliminary evidence from a cross-sectional analysis.

    Science.gov (United States)

    Dlugonski, Deirdre; Motl, Robert W

    2012-02-01

    Persons with multiple sclerosis (MS) have consistently reported lower levels of self-esteem compared with the general population. Despite this, very little is known about the antecedents and consequences of self-esteem in persons with MS. To examine (1) physical activity and social support as potentially modifiable correlates (i.e., antecedents) of self-esteem and (2) physical and psychological health-related quality of life as possible consequences of self-esteem in persons with MS. Participants (N = 46) wore an Actigraph accelerometer for 7 days and then completed a battery of questionnaires, including the Rosenberg Self-Esteem Scale (RSES), Multiple Sclerosis Impact Scale (MSIS-29), and Social Provisions Scale (SPS). The data were analyzed using PASW Statistics 18. Bivariate correlation analysis indicated that average daily step counts (r = .298, p = .026) and social support (r = .366, p = .007) were significantly correlated with self-esteem. Multiple linear regression analysis indicated that only social support was a significant predictor of self-esteem scores (β = .411, p = .004); pedometer steps approached significance as a predictor of self-esteem (β = .178, p = .112). Bivariate correlation analysis further indicated significant negative associations between self-esteem and physical (r = -.391, p = .004) and psychological (r = -.540, p = .0001) domains of health-related quality of life (HRQOL), indicating that higher self-esteem was associated with more positive HRQOL. Social support is a potentially modifiable variable that may be important to target when designing interventions to improve self-esteem and this might have implications for improving physical and psychological HRQOL in persons with MS.

  16. Approach to uncertainty in risk analysis

    Energy Technology Data Exchange (ETDEWEB)

    Rish, W.R.

    1988-08-01

    In the Fall of 1985 EPA's Office of Radiation Programs (ORP) initiated a project to develop a formal approach to dealing with uncertainties encountered when estimating and evaluating risks to human health and the environment. Based on a literature review of modeling uncertainty, interviews with ORP technical and management staff, and input from experts on uncertainty analysis, a comprehensive approach was developed. This approach recognizes by design the constraints on budget, time, manpower, expertise, and availability of information often encountered in ''real world'' modeling. It is based on the observation that in practice risk modeling is usually done to support a decision process. As such, the approach focuses on how to frame a given risk modeling problem, how to use that framing to select an appropriate mixture of uncertainty analyses techniques, and how to integrate the techniques into an uncertainty assessment that effectively communicates important information and insight to decision-makers. The approach is presented in this report. Practical guidance on characterizing and analyzing uncertainties about model form and quantities and on effectively communicating uncertainty analysis results is included. Examples from actual applications are presented.

  17. Approach to uncertainty in risk analysis

    International Nuclear Information System (INIS)

    Rish, W.R.

    1988-08-01

    In the Fall of 1985 EPA's Office of Radiation Programs (ORP) initiated a project to develop a formal approach to dealing with uncertainties encountered when estimating and evaluating risks to human health and the environment. Based on a literature review of modeling uncertainty, interviews with ORP technical and management staff, and input from experts on uncertainty analysis, a comprehensive approach was developed. This approach recognizes by design the constraints on budget, time, manpower, expertise, and availability of information often encountered in ''real world'' modeling. It is based on the observation that in practice risk modeling is usually done to support a decision process. As such, the approach focuses on how to frame a given risk modeling problem, how to use that framing to select an appropriate mixture of uncertainty analyses techniques, and how to integrate the techniques into an uncertainty assessment that effectively communicates important information and insight to decision-makers. The approach is presented in this report. Practical guidance on characterizing and analyzing uncertainties about model form and quantities and on effectively communicating uncertainty analysis results is included. Examples from actual applications are presented

  18. Nonlinear coupled mode approach for modeling counterpropagating solitons in the presence of disorder-induced multiple scattering in photonic crystal waveguides

    Science.gov (United States)

    Mann, Nishan; Hughes, Stephen

    2018-02-01

    We present the analytical and numerical details behind our recently published article [Phys. Rev. Lett. 118, 253901 (2017), 10.1103/PhysRevLett.118.253901], describing the impact of disorder-induced multiple scattering on counterpropagating solitons in photonic crystal waveguides. Unlike current nonlinear approaches using the coupled mode formalism, we account for the effects of intraunit cell multiple scattering. To solve the resulting system of coupled semilinear partial differential equations, we introduce a modified Crank-Nicolson-type norm-preserving implicit finite difference scheme inspired by the transfer matrix method. We provide estimates of the numerical dispersion characteristics of our scheme so that optimal step sizes can be chosen to either minimize numerical dispersion or to mimic the exact dispersion. We then show numerical results of a fundamental soliton propagating in the presence of multiple scattering to demonstrate that choosing a subunit cell spatial step size is critical in accurately capturing the effects of multiple scattering, and illustrate the stochastic nature of disorder by simulating soliton propagation in various instances of disordered photonic crystal waveguides. Our approach is easily extended to include a wide range of optical nonlinearities and is applicable to various photonic nanostructures where power propagation is bidirectional, either by choice, or as a result of multiple scattering.

  19. Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

    Directory of Open Access Journals (Sweden)

    Xiao-meng Song

    2013-01-01

    Full Text Available Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on (1 a screening method (Morris for qualitative ranking of parameters, and (2 a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model (RSMSobol. First, the Morris screening method was used to qualitatively identify the parameters' sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model (RSM were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.

  20. A scenario-based modeling approach for emergency evacuation management and risk analysis under multiple uncertainties

    Energy Technology Data Exchange (ETDEWEB)

    Lv, Y., E-mail: lvyying@hotmail.com [School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044 (China); Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Huang, G.H., E-mail: huang@iseis.org [Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Guo, L., E-mail: guoli8658@hotmail.com [Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Li, Y.P., E-mail: yongping.li@iseis.org [MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China); Dai, C., E-mail: daichao321@gmail.com [College of Environmental Sciences and Engineering, Peking University, Beijing 100871 (China); Wang, X.W., E-mail: wangxingwei0812@gamil.com [State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875 (China); Sun, W., E-mail: sunwei@iseis.org [Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada)

    2013-02-15

    Highlights: ► An interval-parameter joint-probabilistic integer programming method is developed. ► It is useful for nuclear emergency management practices under uncertainties. ► It can schedule optimal routes with maximizing evacuees during a finite time. ► Scenario-based analysis enhances robustness in controlling system risk. ► The method will help to improve the capability of disaster responses. -- Abstract: Nuclear emergency evacuation is important to prevent radioactive harms by hazardous materials and to limit the accidents’ consequences; however, uncertainties are involved in the components and processes of such a management system. In the study, an interval-parameter joint-probabilistic integer programming (IJIP) method is developed for emergency evacuation management under uncertainties. Optimization techniques of interval-parameter programming (IPP) and joint-probabilistic constrained (JPC) programming are incorporated into an integer linear programming framework, so that the approach can deal with uncertainties expressed as joint probability and interval values. The IJIP method can schedule the optimal routes to guarantee the maximum population evacuated away from the effected zone during a finite time. Furthermore, it can also facilitate post optimization analysis to enhance robustness in controlling system violation risk imposed on the joint-probabilistic constraints. The developed method has been applied to a case study of nuclear emergency management; meanwhile, a number of scenarios under different system conditions have been analyzed. It is indicated that the solutions are useful for evacuation management practices. The result of the IJIP method can not only help to raise the capability of disaster responses in a systematic manner, but also provide an insight into complex relationships among evacuation planning, resources utilizations, policy requirements and system risks.

  1. Statistical Methods for Magnetic Resonance Image Analysis with Applications to Multiple Sclerosis

    Science.gov (United States)

    Pomann, Gina-Maria

    Multiple sclerosis (MS) is an immune-mediated neurological disease that causes disability and morbidity. In patients with MS, the accumulation of lesions in the white matter of the brain is associated with disease progression and worse clinical outcomes. In the first part of the dissertation, we present methodology to study to compare the brain anatomy between patients with MS and controls. A nonparametric testing procedure is proposed for testing the null hypothesis that two samples of curves observed at discrete grids and with noise have the same underlying distribution. We propose to decompose the curves using functional principal component analysis of an appropriate mixture process, which we refer to as marginal functional principal component analysis. This approach reduces the dimension of the testing problem in a way that enables the use of traditional nonparametric univariate testing procedures. The procedure is computationally efficient and accommodates different sampling designs. Numerical studies are presented to validate the size and power properties of the test in many realistic scenarios. In these cases, the proposed test is more powerful than its primary competitor. The proposed methodology is illustrated on a state-of-the art diffusion tensor imaging study, where the objective is to compare white matter tract profiles in healthy individuals and MS patients. In the second part of the thesis, we present methods to study the behavior of MS in the white matter of the brain. Breakdown of the blood-brain barrier in newer lesions is indicative of more active disease-related processes and is a primary outcome considered in clinical trials of treatments for MS. Such abnormalities in active MS lesions are evaluated in vivo using contrast-enhanced structural magnetic resonance imaging (MRI), during which patients receive an intravenous infusion of a costly magnetic contrast agent. In some instances, the contrast agents can have toxic effects. Recently, local

  2. Contrast and Critique of Two Approaches to Discourse Analysis: Conversation Analysis and Speech Act Theory

    Directory of Open Access Journals (Sweden)

    Nguyen Van Han

    2014-08-01

    Full Text Available Discourse analysis, as Murcia and Olshtain (2000 assume, is a vast study of language in use that extends beyond sentence level, and it involves a more cognitive and social perspective on language use and communication exchanges. Holding a wide range of phenomena about language with society, culture and thought, discourse analysis contains various approaches: speech act, pragmatics, conversation analysis, variation analysis, and critical discourse analysis. Each approach works in its different domain to discourse. For one dimension, it shares the same assumptions or general problems in discourse analysis with the other approaches: for instance, the explanation on how we organize language into units beyond sentence boundaries, or how language is used to convey information about the world, ourselves and human relationships (Schiffrin 1994: viii. For other dimensions, each approach holds its distinctive characteristics contributing to the vastness of discourse analysis. This paper will mainly discuss two approaches to discourse analysis- conversation analysis and speech act theory- and will attempt to point out some similarities as well as contrasting features between the two approaches, followed by a short reflection on their strengths and weaknesses in the essence of each approach. The organizational and discourse features in the exchanges among three teachers at the College of Finance and Customs in Vietnam will be analysed in terms of conversation analysis and speech act theory.

  3. MultipleColposcopyJCO

    Science.gov (United States)

    Performing multiple biopsies during a procedure known as colposcopy—visual inspection of the cervix—is more effective than performing only a single biopsy of the worst-appearing area for detecting cervical cancer precursors. This multiple biopsy approach

  4. Application of the MIDAS approach for analysis of lysine acetylation sites.

    Science.gov (United States)

    Evans, Caroline A; Griffiths, John R; Unwin, Richard D; Whetton, Anthony D; Corfe, Bernard M

    2013-01-01

    Multiple Reaction Monitoring Initiated Detection and Sequencing (MIDAS™) is a mass spectrometry-based technique for the detection and characterization of specific post-translational modifications (Unwin et al. 4:1134-1144, 2005), for example acetylated lysine residues (Griffiths et al. 18:1423-1428, 2007). The MIDAS™ technique has application for discovery and analysis of acetylation sites. It is a hypothesis-driven approach that requires a priori knowledge of the primary sequence of the target protein and a proteolytic digest of this protein. MIDAS essentially performs a targeted search for the presence of modified, for example acetylated, peptides. The detection is based on the combination of the predicted molecular weight (measured as mass-charge ratio) of the acetylated proteolytic peptide and a diagnostic fragment (product ion of m/z 126.1), which is generated by specific fragmentation of acetylated peptides during collision induced dissociation performed in tandem mass spectrometry (MS) analysis. Sequence information is subsequently obtained which enables acetylation site assignment. The technique of MIDAS was later trademarked by ABSciex for targeted protein analysis where an MRM scan is combined with full MS/MS product ion scan to enable sequence confirmation.

  5. Data analysis and pattern recognition in multiple databases

    CERN Document Server

    Adhikari, Animesh; Pedrycz, Witold

    2014-01-01

    Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyse them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery, and mining patterns of select items provide different...

  6. Breeding approaches in simultaneous selection for multiple stress tolerance of maize in tropical environments

    Directory of Open Access Journals (Sweden)

    Denić M.

    2007-01-01

    Full Text Available Maize is the principal crop and major staple food in the most countries of Sub-Saharan Africa. However, due to the influence of abiotic and biotic stress factors, maize production faces serious constraints. Among the agro-ecological conditions, the main constraints are: lack and poor distribution of rainfall; low soil fertility; diseases (maize streak virus, downy mildew, leaf blights, rusts, gray leaf spot, stem/cob rots and pests (borers and storage pests. Among the socio-economic production constraints are: poor economy, serious shortage of trained manpower; insufficient management expertise, lack of use of improved varieties and poor cultivation practices. To develop desirable varieties, and thus consequently alleviate some of these constraints, appropriate breeding approaches and field-based methodologies in selection for multiple stress tolerance, were implemented. These approaches are mainly based on: a Crossing selected genotypes with more desirable stress tolerant and other agronomic traits; b Using the disease/pest spreader row method, combined with testing and selection of created progenies under strong to intermediate pressure of drought and low soil fertility in nurseries; and c Evaluation of the varieties developed in multi-location trials under low and "normal" inputs. These approaches provide testing and selection of large number of progenies, which is required for simultaneous selection for multiple stress tolerance. Data obtained revealed that remarkable improvement of the traits under selection was achieved. Biggest progress was obtained in selection for maize streak virus and downy mildew resistance, flintiness and earliness. In the case of drought stress, statistical analyses revealed significant negative correlation between yield and anthesis-silking interval, and between yield and days to silk, but positive correlation between yield and grain weight per ear.

  7. A knowledge-driven interaction analysis reveals potential neurodegenerative mechanism of multiple sclerosis susceptibility.

    Science.gov (United States)

    Bush, W S; McCauley, J L; DeJager, P L; Dudek, S M; Hafler, D A; Gibson, R A; Matthews, P M; Kappos, L; Naegelin, Y; Polman, C H; Hauser, S L; Oksenberg, J; Haines, J L; Ritchie, M D

    2011-07-01

    Gene-gene interactions are proposed as an important component of the genetic architecture of complex diseases, and are just beginning to be evaluated in the context of genome-wide association studies (GWAS). In addition to detecting epistasis, a benefit to interaction analysis is that it also increases power to detect weak main effects. We conducted a knowledge-driven interaction analysis of a GWAS of 931 multiple sclerosis (MS) trios to discover gene-gene interactions within established biological contexts. We identify heterogeneous signals, including a gene-gene interaction between CHRM3 (muscarinic cholinergic receptor 3) and MYLK (myosin light-chain kinase) (joint P=0.0002), an interaction between two phospholipase C-β isoforms, PLCβ1 and PLCβ4 (joint P=0.0098), and a modest interaction between ACTN1 (actinin alpha 1) and MYH9 (myosin heavy chain 9) (joint P=0.0326), all localized to calcium-signaled cytoskeletal regulation. Furthermore, we discover a main effect (joint P=5.2E-5) previously unidentified by single-locus analysis within another related gene, SCIN (scinderin), a calcium-binding cytoskeleton regulatory protein. This work illustrates that knowledge-driven interaction analysis of GWAS data is a feasible approach to identify new genetic effects. The results of this study are among the first gene-gene interactions and non-immune susceptibility loci for MS. Further, the implicated genes cluster within inter-related biological mechanisms that suggest a neurodegenerative component to MS.

  8. Assessing Neurocognition via Gamified Experimental Logic: A novel approach to simultaneous acquisition of multiple ERPs

    Directory of Open Access Journals (Sweden)

    Ajay Kumar eNair

    2016-01-01

    Full Text Available The present study describes the development of a neurocognitive paradigm: ‘Assessing Neurocognition via Gamified Experimental Logic’ (ANGEL, for performing the parametric evaluation of multiple neurocognitive functions simultaneously. ANGEL employs an audiovisual sensory motor design for the acquisition of multiple event related potentials (ERPs - the C1, P50, MMN, N1, N170, P2, N2pc, LRP, P300 and ERN. The ANGEL paradigm allows assessment of ten neurocognitive variables over the course of three ‘game’ levels of increasing complexity ranging from simple passive observation to complex discrimination and response in the presence of multiple distractors. The paradigm allows assessment of several levels of rapid decision making: speeded up response vs response-inhibition; responses to easy vs difficult tasks; responses based on gestalt perception of clear vs ambiguous stimuli; and finally, responses with set shifting during challenging tasks. The paradigm has been tested using 18 healthy participants from both sexes and the possibilities of varied data analyses have been presented in this paper. The ANGEL approach provides an ecologically valid assessment (as compared to existing tools that quickly yields a very rich dataset and helps to assess multiple ERPs that can be studied extensively to assess cognitive functions in health and disease conditions.

  9. Assessing Neurocognition via Gamified Experimental Logic: A Novel Approach to Simultaneous Acquisition of Multiple ERPs.

    Science.gov (United States)

    Nair, Ajay K; Sasidharan, Arun; John, John P; Mehrotra, Seema; Kutty, Bindu M

    2016-01-01

    The present study describes the development of a neurocognitive paradigm: "Assessing Neurocognition via Gamified Experimental Logic" (ANGEL), for performing the parametric evaluation of multiple neurocognitive functions simultaneously. ANGEL employs an audiovisual sensory motor design for the acquisition of multiple event related potentials (ERPs)-the C1, P50, MMN, N1, N170, P2, N2pc, LRP, P300, and ERN. The ANGEL paradigm allows assessment of 10 neurocognitive variables over the course of three "game" levels of increasing complexity ranging from simple passive observation to complex discrimination and response in the presence of multiple distractors. The paradigm allows assessment of several levels of rapid decision making: speeded up response vs. response-inhibition; responses to easy vs. difficult tasks; responses based on gestalt perception of clear vs. ambiguous stimuli; and finally, responses with set shifting during challenging tasks. The paradigm has been tested using 18 healthy participants from both sexes and the possibilities of varied data analyses have been presented in this paper. The ANGEL approach provides an ecologically valid assessment (as compared to existing tools) that quickly yields a very rich dataset and helps to assess multiple ERPs that can be studied extensively to assess cognitive functions in health and disease conditions.

  10. A Signal Detection Approach in a Multiple Cohort Study: Different Admission Tools Uniquely Select Different Successful Students

    Directory of Open Access Journals (Sweden)

    Linda van Ooijen-van der Linden

    2018-05-01

    Full Text Available Using multiple admission tools in university admission procedures is common practice. This is particularly useful if different admission tools uniquely select different subgroups of students who will be successful in university programs. A signal-detection approach was used to investigate the accuracy of Secondary School grade point average (SSGPA, an admission test score (ACS, and a non-cognitive score (NCS in uniquely selecting successful students. This was done for three consecutive first year cohorts of a broad psychology program. Each applicant's score on SSGPA, ACS, or NCS alone—and on seven combinations of these scores, all considered separate “admission tools”—was compared at two different (medium and high cut-off scores (criterion levels. Each of the tools selected successful students who were not selected by any of the other tools. Both sensitivity and specificity were enhanced by implementing multiple tools. The signal-detection approach distinctively provided useful information for decisions on admission instruments and cut-off scores.

  11. A Multivariant Stream Analysis Approach to Detect and Mitigate DDoS Attacks in Vehicular Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Raenu Kolandaisamy

    2018-01-01

    Full Text Available Vehicular Ad Hoc Networks (VANETs are rapidly gaining attention due to the diversity of services that they can potentially offer. However, VANET communication is vulnerable to numerous security threats such as Distributed Denial of Service (DDoS attacks. Dealing with these attacks in VANET is a challenging problem. Most of the existing DDoS detection techniques suffer from poor accuracy and high computational overhead. To cope with these problems, we present a novel Multivariant Stream Analysis (MVSA approach. The proposed MVSA approach maintains the multiple stages for detection DDoS attack in network. The Multivariant Stream Analysis gives unique result based on the Vehicle-to-Vehicle communication through Road Side Unit. The approach observes the traffic in different situations and time frames and maintains different rules for various traffic classes in various time windows. The performance of the MVSA is evaluated using an NS2 simulator. Simulation results demonstrate the effectiveness and efficiency of the MVSA regarding detection accuracy and reducing the impact on VANET communication.

  12. Derringer desirability and kinetic plot LC-column comparison approach for MS-compatible lipopeptide analysis.

    Science.gov (United States)

    D'Hondt, Matthias; Verbeke, Frederick; Stalmans, Sofie; Gevaert, Bert; Wynendaele, Evelien; De Spiegeleer, Bart

    2014-06-01

    Lipopeptides are currently re-emerging as an interesting subgroup in the peptide research field, having historical applications as antibacterial and antifungal agents and new potential applications as antiviral, antitumor, immune-modulating and cell-penetrating compounds. However, due to their specific structure, chromatographic analysis often requires special buffer systems or the use of trifluoroacetic acid, limiting mass spectrometry detection. Therefore, we used a traditional aqueous/acetonitrile based gradient system, containing 0.1% (m/v) formic acid, to separate four pharmaceutically relevant lipopeptides (polymyxin B 1 , caspofungin, daptomycin and gramicidin A 1 ), which were selected based upon hierarchical cluster analysis (HCA) and principal component analysis (PCA). In total, the performance of four different C18 columns, including one UPLC column, were evaluated using two parallel approaches. First, a Derringer desirability function was used, whereby six single and multiple chromatographic response values were rescaled into one overall D -value per column. Using this approach, the YMC Pack Pro C18 column was ranked as the best column for general MS-compatible lipopeptide separation. Secondly, the kinetic plot approach was used to compare the different columns at different flow rate ranges. As the optimal kinetic column performance is obtained at its maximal pressure, the length elongation factor λ ( P max / P exp ) was used to transform the obtained experimental data (retention times and peak capacities) and construct kinetic performance limit (KPL) curves, allowing a direct visual and unbiased comparison of the selected columns, whereby the YMC Triart C18 UPLC and ACE C18 columns performed as best. Finally, differences in column performance and the (dis)advantages of both approaches are discussed.

  13. Real Analysis A Historical Approach

    CERN Document Server

    Stahl, Saul

    2011-01-01

    A provocative look at the tools and history of real analysis This new edition of Real Analysis: A Historical Approach continues to serve as an interesting read for students of analysis. Combining historical coverage with a superb introductory treatment, this book helps readers easily make the transition from concrete to abstract ideas. The book begins with an exciting sampling of classic and famous problems first posed by some of the greatest mathematicians of all time. Archimedes, Fermat, Newton, and Euler are each summoned in turn, illuminating the utility of infinite, power, and trigonome

  14. Optimal Route Searching with Multiple Dynamical Constraints—A Geometric Algebra Approach

    Directory of Open Access Journals (Sweden)

    Dongshuang Li

    2018-05-01

    Full Text Available The process of searching for a dynamic constrained optimal path has received increasing attention in traffic planning, evacuation, and personalized or collaborative traffic service. As most existing multiple constrained optimal path (MCOP methods cannot search for a path given various types of constraints that dynamically change during the search, few approaches for dynamic multiple constrained optimal path (DMCOP with type II dynamics are available for practical use. In this study, we develop a method to solve the DMCOP problem with type II dynamics based on the unification of various types of constraints under a geometric algebra (GA framework. In our method, the network topology and three different types of constraints are represented by using algebraic base coding. With a parameterized optimization of the MCOP algorithm based on a greedy search strategy under the generation-refinement paradigm, this algorithm is found to accurately support the discovery of optimal paths as the constraints of numerical values, nodes, and route structure types are dynamically added to the network. The algorithm was tested with simulated cases of optimal tourism route searches in China’s road networks with various combinations of constraints. The case study indicates that our algorithm can not only solve the DMCOP with different types of constraints but also use constraints to speed up the route filtering.

  15. An integrated probabilistic risk analysis decision support methodology for systems with multiple state variables

    International Nuclear Information System (INIS)

    Sen, P.; Tan, John K.G.; Spencer, David

    1999-01-01

    Probabilistic risk analysis (PRA) methods have been proven to be valuable in risk and reliability analysis. However, a weak link seems to exist between methods for analysing risks and those for making rational decisions. The integrated decision support system (IDSS) methodology presented in this paper attempts to address this issue in a practical manner. In consists of three phases: a PRA phase, a risk sensitivity analysis (SA) phase and an optimisation phase, which are implemented through an integrated computer software system. In the risk analysis phase the problem is analysed by the Boolean representation method (BRM), a PRA method that can deal with systems with multiple state variables and feedback loops. In the second phase the results obtained from the BRM are utilised directly to perform importance and risk SA. In the third phase, the problem is formulated as a multiple objective decision making problem in the form of multiple objective reliability optimisation. An industrial example is included. The resultant solutions of a five objective reliability optimisation are presented, on the basis of which rational decision making can be explored

  16. An efficient multiple particle filter based on the variational Bayesian approach

    KAUST Repository

    Ait-El-Fquih, Boujemaa

    2015-12-07

    This paper addresses the filtering problem in large-dimensional systems, in which conventional particle filters (PFs) remain computationally prohibitive owing to the large number of particles needed to obtain reasonable performances. To overcome this drawback, a class of multiple particle filters (MPFs) has been recently introduced in which the state-space is split into low-dimensional subspaces, and then a separate PF is applied to each subspace. In this paper, we adopt the variational Bayesian (VB) approach to propose a new MPF, the VBMPF. The proposed filter is computationally more efficient since the propagation of each particle requires generating one (new) particle only, while in the standard MPFs a set of (children) particles needs to be generated. In a numerical test, the proposed VBMPF behaves better than the PF and MPF.

  17. Modern terrorism: concept and approach analysis

    OpenAIRE

    CHAIKA ALEXANDER VIKTOROVICH

    2015-01-01

    The problem of modern terrorism as an image of counterculture environment is considered. The analysis of concepts and approaches of foreign and native authors, specialists of terrorism problem research was conducted. Separate features of the modern terrorism are considered and emphasized. The author drew conceptual conclusions on the basis of dialectical approach to modern terrorism counterculture phenomenon research.

  18. The impact of farmers’ participation in field trials in creating awareness and stimulating compliance with the World Health Organization’s farm-based multiple-barrier approach

    DEFF Research Database (Denmark)

    Amponsah, Owusu; Vigre, Håkan; Schou, Torben Wilde

    2016-01-01

    -barrier approach field trials. The results of the study show that participation in the field trials has statistically significant effects on farmers’ awareness of the farm-based multiple-barrier approach. Compliance has, however, been undermined by the farmers’ perception that the cost of compliance is more......The results of a study aimed as assessing the extent to which urban vegetable farmers’ participation in field trials can impact on their awareness and engender compliance with the World Health Organization’s farm-based multiple-barrier approach are presented in this paper. Both qualitative...... and quantitative approaches have been used in this paper. One hundred vegetable farmers and four vegetable farmers’ associations in the Kumasi Metropolis in Ghana were covered. The individual farmers were grouped into two, namely: (1) participants and (2) non-participants of the farm-based multiple...

  19. Fuzzy multiple linear regression: A computational approach

    Science.gov (United States)

    Juang, C. H.; Huang, X. H.; Fleming, J. W.

    1992-01-01

    This paper presents a new computational approach for performing fuzzy regression. In contrast to Bardossy's approach, the new approach, while dealing with fuzzy variables, closely follows the conventional regression technique. In this approach, treatment of fuzzy input is more 'computational' than 'symbolic.' The following sections first outline the formulation of the new approach, then deal with the implementation and computational scheme, and this is followed by examples to illustrate the new procedure.

  20. Meta-Analysis With Complex Research Designs: Dealing With Dependence From Multiple Measures and Multiple Group Comparisons

    Science.gov (United States)

    Scammacca, Nancy; Roberts, Greg; Stuebing, Karla K.

    2013-01-01

    Previous research has shown that treating dependent effect sizes as independent inflates the variance of the mean effect size and introduces bias by giving studies with more effect sizes more weight in the meta-analysis. This article summarizes the different approaches to handling dependence that have been advocated by methodologists, some of which are more feasible to implement with education research studies than others. A case study using effect sizes from a recent meta-analysis of reading interventions is presented to compare the results obtained from different approaches to dealing with dependence. Overall, mean effect sizes and variance estimates were found to be similar, but estimates of indexes of heterogeneity varied. Meta-analysts are advised to explore the effect of the method of handling dependence on the heterogeneity estimates before conducting moderator analyses and to choose the approach to dependence that is best suited to their research question and their data set. PMID:25309002

  1. Definition of neutron multiplication in a reception capacity of radioactive waste shop

    International Nuclear Information System (INIS)

    Dulin, V.A.; Dulin, V.V.; Pavlova, O.N.

    2006-01-01

    To determine neutrons multiplication the measurements and calculations of spatial distributions of neutron counting and absolute fission rates in a reception capacity of IPPE radioactive waste shop have been carried out and analyzed. A content of fissionable medium was unknown. The approach developed has allowed implementing a calculation analysis of the experimental data on determination of the most probable spatial distributions of basic parameters of the fissionable medium of unknown content. It has allowed determining the neutrons multiplication factor in a reception capacity of a tank No. 17. It has been found that the value of neutrons multiplication factor in a tank is 1.07 ± 0.03. The developed measurement method and calculation analysis used for experimental data also can be applied in other cases when the multiplication medium content is unknown [ru

  2. Application of range-test in multiple linear regression analysis in ...

    African Journals Online (AJOL)

    Application of range-test in multiple linear regression analysis in the presence of outliers is studied in this paper. First, the plot of the explanatory variables (i.e. Administration, Social/Commercial, Economic services and Transfer) on the dependent variable (i.e. GDP) was done to identify the statistical trend over the years.

  3. Convergence analysis of directed signed networks via an M-matrix approach

    Science.gov (United States)

    Meng, Deyuan

    2018-04-01

    This paper aims at solving convergence problems on directed signed networks with multiple nodes, where interactions among nodes are described by signed digraphs. The convergence analysis is achieved by matrix-theoretic and graph-theoretic tools, in which M-matrices play a central role. The fundamental digon sign-symmetry assumption upon signed digraphs can be removed with the proposed analysis approach. Furthermore, necessary and sufficient conditions are established for semi-positive and positive stabilities of Laplacian matrices of signed digraphs, respectively. A benefit of this result is that given strong connectivity, a directed signed network can achieve bipartite consensus (or state stability) if and only if the signed digraph associated with it is structurally balanced (or unbalanced). If the interactions between nodes are described by a signed digraph only with spanning trees, a directed signed network can achieve interval bipartite consensus (or state stability) if and only if the signed digraph contains a structurally balanced (or unbalanced) rooted subgraph. Simulations are given to illustrate the developed results by considering signed networks associated with digon sign-unsymmetric signed digraphs.

  4. Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines

    NARCIS (Netherlands)

    Ellrott, Kyle; Bailey, Matthew H.; Saksena, Gordon; Covington, Kyle R.; Kandoth, Cyriac; Stewart, Chip; Hess, Julian; Ma, Singer; Chiotti, Kami E.; McLellan, Michael; Sofia, Heidi J.; Hutter, Carolyn M.; Getz, Gad; Wheeler, David A.; Ding, Li; Caesar-Johnson, Samantha J.; Demchok, John A.; Felau, Ina; Kasapi, Melpomeni; Ferguson, Martin L.; Hutter, Carolyn M.; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C.; Zhang, Jiashan (Julia); Chudamani, Sudha; Liu, Jia; Lolla, Laxmi; Naresh, Rashi; Pihl, Todd; Sun, Qiang; Wan, Yunhu; Wu, Ye; Cho, Juok; DeFreitas, Timothy; Frazer, Scott; Gehlenborg, Nils; Getz, Gad; Heiman, David I.; Kim, Jaegil; Lawrence, Michael S.; Lin, Pei; Meier, Sam; Noble, Michael S.; Saksena, Gordon; Voet, Doug; Zhang, Hailei; Bernard, Brady; Chambwe, Nyasha; Dhankani, Varsha; Knijnenburg, Theo; Kramer, Roger; Leinonen, Kalle; Liu, Yuexin; Miller, Michael; Reynolds, Sheila; Shmulevich, Ilya; Thorsson, Vesteinn; Zhang, Wei; Akbani, Rehan; Broom, Bradley M.; Hegde, Apurva M.; Ju, Zhenlin; Kanchi, Rupa S.; Korkut, Anil; Li, Jun; Liang, Han; Ling, Shiyun; Liu, Wenbin; Lu, Yiling; Mills, Gordon B.; Ng, Kwok Shing; Rao, Arvind; Ryan, Michael; Wang, Jing; Weinstein, John N.; Zhang, Jiexin; Abeshouse, Adam; Armenia, Joshua; Chakravarty, Debyani; Chatila, Walid K.; de Bruijn, Ino; Gao, Jianjiong; Gross, Benjamin E.; Heins, Zachary J.; Kundra, Ritika; La, Konnor; Ladanyi, Marc; Luna, Augustin; Nissan, Moriah G.; Ochoa, Angelica; Phillips, Sarah M.; Reznik, Ed; Sanchez-Vega, Francisco; Sander, Chris; Schultz, Nikolaus; Sheridan, Robert; Sumer, S. Onur; Sun, Yichao; Taylor, Barry S.; Wang, Jioajiao; Zhang, Hongxin; Anur, Pavana; Peto, Myron; Spellman, Paul; Benz, Christopher; Stuart, Joshua M.; Wong, Christopher K.; Yau, Christina; Hayes, D. Neil; Wilkerson, Matthew D.; Ally, Adrian; Balasundaram, Miruna; Bowlby, Reanne; Brooks, Denise; Carlsen, Rebecca; Chuah, Eric; Dhalla, Noreen; Holt, Robert; Jones, Steven J.M.; Kasaian, Katayoon; Lee, Darlene; Ma, Yussanne; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Mungall, Karen; Robertson, A. Gordon; Sadeghi, Sara; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Tse, Kane; Wong, Tina; Berger, Ashton C.; Beroukhim, Rameen; Cherniack, Andrew D.; Cibulskis, Carrie; Gabriel, Stacey B.; Gao, Galen F.; Ha, Gavin; Meyerson, Matthew; Schumacher, Steven E.; Shih, Juliann; Kucherlapati, Melanie H.; Kucherlapati, Raju S.; Baylin, Stephen; Cope, Leslie; Danilova, Ludmila; Bootwalla, Moiz S.; Lai, Phillip H.; Maglinte, Dennis T.; Van Den Berg, David J.; Weisenberger, Daniel J.; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Fan, Cheng; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Perou, Amy H.; Perou, Charles M.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Skelly, Tara; Soloway, Matthew G.; Tan, Donghui; Veluvolu, Umadevi; Fan, Huihui; Hinoue, Toshinori; Laird, Peter W.; Shen, Hui; Zhou, Wanding; Bellair, Michelle; Chang, Kyle; Covington, Kyle; Creighton, Chad J.; Dinh, Huyen; Doddapaneni, Harsha Vardhan; Donehower, Lawrence A.; Drummond, Jennifer; Gibbs, Richard A.; Glenn, Robert; Hale, Walker; Han, Yi; Hu, Jianhong; Korchina, Viktoriya; Lee, Sandra; Lewis, Lora; Li, Wei; Liu, Xiuping; Morgan, Margaret; Morton, Donna; Muzny, Donna; Santibanez, Jireh; Sheth, Margi; Shinbrot, Eve; Wang, Linghua; Wang, Min; Wheeler, David A.; Xi, Liu; Zhao, Fengmei; Hess, Julian; Appelbaum, Elizabeth L.; Bailey, Matthew; Cordes, Matthew G.; Ding, Li; Fronick, Catrina C.; Fulton, Lucinda A.; Fulton, Robert S.; Kandoth, Cyriac; Mardis, Elaine R.; McLellan, Michael D.; Miller, Christopher A.; Schmidt, Heather K.; Wilson, Richard K.; Crain, Daniel; Curley, Erin; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candace; Shelton, Troy; Sherman, Mark; Thompson, Eric; Yena, Peggy; Bowen, Jay; Gastier-Foster, Julie M.; Gerken, Mark; Leraas, Kristen M.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Corcoran, Niall; Costello, Tony; Hovens, Christopher; Carvalho, Andre L.; de Carvalho, Ana C.; Fregnani, José H.; Longatto-Filho, Adhemar; Reis, Rui M.; Scapulatempo-Neto, Cristovam; Silveira, Henrique C.S.; Vidal, Daniel O.; Burnette, Andrew; Eschbacher, Jennifer; Hermes, Beth; Noss, Ardene; Singh, Rosy; Anderson, Matthew L.; Castro, Patricia D.; Ittmann, Michael; Huntsman, David; Kohl, Bernard; Le, Xuan; Thorp, Richard; Andry, Chris; Duffy, Elizabeth R.; Lyadov, Vladimir; Paklina, Oxana; Setdikova, Galiya; Shabunin, Alexey; Tavobilov, Mikhail; McPherson, Christopher; Warnick, Ronald; Berkowitz, Ross; Cramer, Daniel; Feltmate, Colleen; Horowitz, Neil; Kibel, Adam; Muto, Michael; Raut, Chandrajit P.; Malykh, Andrei; Barnholtz-Sloan, Jill S.; Barrett, Wendi; Devine, Karen; Fulop, Jordonna; Ostrom, Quinn T.; Shimmel, Kristen; Wolinsky, Yingli; Sloan, Andrew E.; De Rose, Agostino; Giuliante, Felice; Goodman, Marc; Karlan, Beth Y.; Hagedorn, Curt H.; Eckman, John; Harr, Jodi; Myers, Jerome; Tucker, Kelinda; Zach, Leigh Anne; Deyarmin, Brenda; Hu, Hai; Kvecher, Leonid; Larson, Caroline; Mural, Richard J.; Somiari, Stella; Vicha, Ales; Zelinka, Tomas; Bennett, Joseph; Iacocca, Mary; Rabeno, Brenda; Swanson, Patricia; Latour, Mathieu; Lacombe, Louis; Têtu, Bernard; Bergeron, Alain; McGraw, Mary; Staugaitis, Susan M.; Chabot, John; Hibshoosh, Hanina; Sepulveda, Antonia; Su, Tao; Wang, Timothy; Potapova, Olga; Voronina, Olga; Desjardins, Laurence; Mariani, Odette; Roman-Roman, Sergio; Sastre, Xavier; Stern, Marc Henri; Cheng, Feixiong; Signoretti, Sabina; Berchuck, Andrew; Bigner, Darell; Lipp, Eric; Marks, Jeffrey; McCall, Shannon; McLendon, Roger; Secord, Angeles; Sharp, Alexis; Behera, Madhusmita; Brat, Daniel J.; Chen, Amy; Delman, Keith; Force, Seth; Khuri, Fadlo; Magliocca, Kelly; Maithel, Shishir; Olson, Jeffrey J.; Owonikoko, Taofeek; Pickens, Alan; Ramalingam, Suresh; Shin, Dong M.; Sica, Gabriel; Van Meir, Erwin G.; Zhang, Hongzheng; Eijckenboom, Wil; Gillis, Ad; Korpershoek, Esther; Looijenga, Leendert; Oosterhuis, Wolter; Stoop, Hans; van Kessel, Kim E.; Zwarthoff, Ellen C.; Calatozzolo, Chiara; Cuppini, Lucia; Cuzzubbo, Stefania; DiMeco, Francesco; Finocchiaro, Gaetano; Mattei, Luca; Perin, Alessandro; Pollo, Bianca; Chen, Chu; Houck, John; Lohavanichbutr, Pawadee; Hartmann, Arndt; Stoehr, Christine; Stoehr, Robert; Taubert, Helge; Wach, Sven; Wullich, Bernd; Kycler, Witold; Murawa, Dawid; Wiznerowicz, Maciej; Chung, Ki; Edenfield, W. Jeffrey; Martin, Julie; Baudin, Eric; Bubley, Glenn; Bueno, Raphael; De Rienzo, Assunta; Richards, William G.; Kalkanis, Steven; Mikkelsen, Tom; Noushmehr, Houtan; Scarpace, Lisa; Girard, Nicolas; Aymerich, Marta; Campo, Elias; Giné, Eva; Guillermo, Armando López; Van Bang, Nguyen; Hanh, Phan Thi; Phu, Bui Duc; Tang, Yufang; Colman, Howard; Evason, Kimberley; Dottino, Peter R.; Martignetti, John A.; Gabra, Hani; Juhl, Hartmut; Akeredolu, Teniola; Stepa, Serghei; Hoon, Dave; Ahn, Keunsoo; Kang, Koo Jeong; Beuschlein, Felix; Breggia, Anne; Birrer, Michael; Bell, Debra; Borad, Mitesh; Bryce, Alan H.; Castle, Erik; Chandan, Vishal; Cheville, John; Copland, John A.; Farnell, Michael; Flotte, Thomas; Giama, Nasra; Ho, Thai; Kendrick, Michael; Kocher, Jean Pierre; Kopp, Karla; Moser, Catherine; Nagorney, David; O'Brien, Daniel; O'Neill, Brian Patrick; Patel, Tushar; Petersen, Gloria; Que, Florencia; Rivera, Michael; Roberts, Lewis; Smallridge, Robert; Smyrk, Thomas; Stanton, Melissa; Thompson, R. Houston; Torbenson, Michael; Yang, Ju Dong; Zhang, Lizhi; Brimo, Fadi; Ajani, Jaffer A.; Angulo Gonzalez, Ana Maria; Behrens, Carmen; Bondaruk, Jolanta; Broaddus, Russell; Czerniak, Bogdan; Esmaeli, Bita; Fujimoto, Junya; Gershenwald, Jeffrey; Guo, Charles; Lazar, Alexander J.; Logothetis, Christopher; Meric-Bernstam, Funda; Moran, Cesar; Ramondetta, Lois; Rice, David; Sood, Anil; Tamboli, Pheroze; Thompson, Timothy; Troncoso, Patricia; Tsao, Anne; Wistuba, Ignacio; Carter, Candace; Haydu, Lauren; Hersey, Peter; Jakrot, Valerie; Kakavand, Hojabr; Kefford, Richard; Lee, Kenneth; Long, Georgina; Mann, Graham; Quinn, Michael; Saw, Robyn; Scolyer, Richard; Shannon, Kerwin; Spillane, Andrew; Stretch, Jonathan; Synott, Maria; Thompson, John; Wilmott, James; Al-Ahmadie, Hikmat; Chan, Timothy A.; Ghossein, Ronald; Gopalan, Anuradha; Levine, Douglas A.; Reuter, Victor; Singer, Samuel; Singh, Bhuvanesh; Tien, Nguyen Viet; Broudy, Thomas; Mirsaidi, Cyrus; Nair, Praveen; Drwiega, Paul; Miller, Judy; Smith, Jennifer; Zaren, Howard; Park, Joong Won; Hung, Nguyen Phi; Kebebew, Electron; Linehan, W. Marston; Metwalli, Adam R.; Pacak, Karel; Pinto, Peter A.; Schiffman, Mark; Schmidt, Laura S.; Vocke, Cathy D.; Wentzensen, Nicolas; Worrell, Robert; Yang, Hannah; Moncrieff, Marc; Goparaju, Chandra; Melamed, Jonathan; Pass, Harvey; Botnariuc, Natalia; Caraman, Irina; Cernat, Mircea; Chemencedji, Inga; Clipca, Adrian; Doruc, Serghei; Gorincioi, Ghenadie; Mura, Sergiu; Pirtac, Maria; Stancul, Irina; Tcaciuc, Diana; Albert, Monique; Alexopoulou, Iakovina; Arnaout, Angel; Bartlett, John; Engel, Jay; Gilbert, Sebastien; Parfitt, Jeremy; Sekhon, Harman; Thomas, George; Rassl, Doris M.; Rintoul, Robert C.; Bifulco, Carlo; Tamakawa, Raina; Urba, Walter; Hayward, Nicholas; Timmers, Henri; Antenucci, Anna; Facciolo, Francesco; Grazi, Gianluca; Marino, Mirella; Merola, Roberta; de Krijger, Ronald; Gimenez-Roqueplo, Anne Paule; Piché, Alain; Chevalier, Simone; McKercher, Ginette; Birsoy, Kivanc; Barnett, Gene; Brewer, Cathy; Farver, Carol; Naska, Theresa; Pennell, Nathan A.; Raymond, Daniel; Schilero, Cathy; Smolenski, Kathy; Williams, Felicia; Morrison, Carl; Borgia, Jeffrey A.; Liptay, Michael J.; Pool, Mark; Seder, Christopher W.; Junker, Kerstin; Omberg, Larsson; Dinkin, Mikhail; Manikhas, George; Alvaro, Domenico; Bragazzi, Maria Consiglia; Cardinale, Vincenzo; Carpino, Guido; Gaudio, Eugenio; Chesla, David; Cottingham, Sandra; Dubina, Michael; Moiseenko, Fedor; Dhanasekaran, Renumathy; Becker, Karl Friedrich; Janssen, Klaus Peter; Slotta-Huspenina, Julia; Abdel-Rahman, Mohamed H.; Aziz, Dina; Bell, Sue; Cebulla, Colleen M.; Davis, Amy; Duell, Rebecca; Elder, J. Bradley; Hilty, Joe; Kumar, Bahavna; Lang, James; Lehman, Norman L.; Mandt, Randy; Nguyen, Phuong; Pilarski, Robert; Rai, Karan; Schoenfield, Lynn; Senecal, Kelly; Wakely, Paul; Hansen, Paul; Lechan, Ronald; Powers, James; Tischler, Arthur; Grizzle, William E.; Sexton, Katherine C.; Kastl, Alison; Henderson, Joel; Porten, Sima; Waldmann, Jens; Fassnacht, Martin; Asa, Sylvia L.; Schadendorf, Dirk; Couce, Marta; Graefen, Markus; Huland, Hartwig; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald; Tennstedt, Pierre; Olabode, Oluwole; Nelson, Mark; Bathe, Oliver; Carroll, Peter R.; Chan, June M.; Disaia, Philip; Glenn, Pat; Kelley, Robin K.; Landen, Charles N.; Phillips, Joanna; Prados, Michael; Simko, Jeffry; Smith-McCune, Karen; VandenBerg, Scott; Roggin, Kevin; Fehrenbach, Ashley; Kendler, Ady; Sifri, Suzanne; Steele, Ruth; Jimeno, Antonio; Carey, Francis; Forgie, Ian; Mannelli, Massimo; Carney, Michael; Hernandez, Brenda; Campos, Benito; Herold-Mende, Christel; Jungk, Christin; Unterberg, Andreas; von Deimling, Andreas; Bossler, Aaron; Galbraith, Joseph; Jacobus, Laura; Knudson, Michael; Knutson, Tina; Ma, Deqin; Milhem, Mohammed; Sigmund, Rita; Godwin, Andrew K.; Madan, Rashna; Rosenthal, Howard G.; Adebamowo, Clement; Adebamowo, Sally N.; Boussioutas, Alex; Beer, David; Giordano, Thomas; Mes-Masson, Anne Marie; Saad, Fred; Bocklage, Therese; Landrum, Lisa; Mannel, Robert; Moore, Kathleen; Moxley, Katherine; Postier, Russel; Walker, Joan; Zuna, Rosemary; Feldman, Michael; Valdivieso, Federico; Dhir, Rajiv; Luketich, James; Mora Pinero, Edna M.; Quintero-Aguilo, Mario; Carlotti, Carlos Gilberto; Dos Santos, Jose Sebastião; Kemp, Rafael; Sankarankuty, Ajith; Tirapelli, Daniela; Catto, James; Agnew, Kathy; Swisher, Elizabeth; Creaney, Jenette; Robinson, Bruce; Shelley, Carl Simon; Godwin, Eryn M.; Kendall, Sara; Shipman, Cassaundra; Bradford, Carol; Carey, Thomas; Haddad, Andrea; Moyer, Jeffey; Peterson, Lisa; Prince, Mark; Rozek, Laura; Wolf, Gregory; Bowman, Rayleen; Fong, Kwun M.; Yang, Ian; Korst, Robert; Rathmell, W. Kimryn; Fantacone-Campbell, J. Leigh; Hooke, Jeffrey A.; Kovatich, Albert J.; Shriver, Craig D.; DiPersio, John; Drake, Bettina; Govindan, Ramaswamy; Heath, Sharon; Ley, Timothy; Van Tine, Brian; Westervelt, Peter; Rubin, Mark A.; Lee, Jung Il; Aredes, Natália D.; Mariamidze, Armaz

    2018-01-01

    The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a

  5. Pathway Analysis in Attention Deficit Hyperactivity Disorder: An Ensemble Approach

    Science.gov (United States)

    Mooney, Michael A.; McWeeney, Shannon K.; Faraone, Stephen V.; Hinney, Anke; Hebebrand, Johannes; Nigg, Joel T.; Wilmot, Beth

    2016-01-01

    Despite a wealth of evidence for the role of genetics in attention deficit hyperactivity disorder (ADHD), specific and definitive genetic mechanisms have not been identified. Pathway analyses, a subset of gene-set analyses, extend the knowledge gained from genome-wide association studies (GWAS) by providing functional context for genetic associations. However, there are numerous methods for association testing of gene sets and no real consensus regarding the best approach. The present study applied six pathway analysis methods to identify pathways associated with ADHD in two GWAS datasets from the Psychiatric Genomics Consortium. Methods that utilize genotypes to model pathway-level effects identified more replicable pathway associations than methods using summary statistics. In addition, pathways implicated by more than one method were significantly more likely to replicate. A number of brain-relevant pathways, such as RhoA signaling, glycosaminoglycan biosynthesis, fibroblast growth factor receptor activity, and pathways containing potassium channel genes, were nominally significant by multiple methods in both datasets. These results support previous hypotheses about the role of regulation of neurotransmitter release, neurite outgrowth and axon guidance in contributing to the ADHD phenotype and suggest the value of cross-method convergence in evaluating pathway analysis results. PMID:27004716

  6. An SQL-based approach to physics analysis

    International Nuclear Information System (INIS)

    Limper, Dr Maaike

    2014-01-01

    As part of the CERN openlab collaboration a study was made into the possibility of performing analysis of the data collected by the experiments at the Large Hadron Collider (LHC) through SQL-queries on data stored in a relational database. Currently LHC physics analysis is done using data stored in centrally produced 'ROOT-ntuple' files that are distributed through the LHC computing grid. The SQL-based approach to LHC physics analysis presented in this paper allows calculations in the analysis to be done at the database and can make use of the database's in-built parallelism features. Using this approach it was possible to reproduce results for several physics analysis benchmarks. The study shows the capability of the database to handle complex analysis tasks but also illustrates the limits of using row-based storage for storing physics analysis data, as performance was limited by the I/O read speed of the system.

  7. Integrated health messaging for multiple neglected zoonoses: Approaches, challenges and opportunities in Morocco.

    Science.gov (United States)

    Ducrotoy, M J; Yahyaoui Azami, H; El Berbri, I; Bouslikhane, M; Fassi Fihri, O; Boué, F; Petavy, A F; Dakkak, A; Welburn, S; Bardosh, K L

    2015-12-01

    Integrating the control of multiple neglected zoonoses at the community-level holds great potential, but critical data is missing to inform the design and implementation of different interventions. In this paper we present an evaluation of an integrated health messaging intervention, using powerpoint presentations, for five bacterial (brucellosis and bovine tuberculosis) and dog-associated (rabies, cystic echinococcosis and leishmaniasis) zoonotic diseases in Sidi Kacem Province, northwest Morocco. Conducted by veterinary and epidemiology students between 2013 and 2014, this followed a process-based approach that encouraged sequential adaptation of images, key messages, and delivery strategies using auto-evaluation and end-user feedback. We describe the challenges and opportunities of this approach, reflecting on who was targeted, how education was conducted, and what tools and approaches were used. Our results showed that: (1) replacing words with local pictures and using "hands-on" activities improved receptivity; (2) information "overload" easily occurred when disease transmission pathways did not overlap; (3) access and receptivity at schools was greater than at the community-level; and (4) piggy-backing on high-priority diseases like rabies offered an important avenue to increase knowledge of other zoonoses. We conclude by discussing the merits of incorporating our validated education approach into the school curriculum in order to influence long-term behaviour change. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. White matter tract-specific quantitative analysis in multiple sclerosis: Comparison of optic radiation reconstruction techniques.

    Directory of Open Access Journals (Sweden)

    Chenyu Wang

    Full Text Available The posterior visual pathway is commonly affected by multiple sclerosis (MS pathology that results in measurable clinical and electrophysiological impairment. Due to its highly structured retinotopic mapping, the visual pathway represents an ideal substrate for investigating patho-mechanisms in MS. Therefore, a reliable and robust imaging segmentation method for in-vivo delineation of the optic radiations (OR is needed. However, diffusion-based tractography approaches, which are typically used for OR segmentation are confounded by the presence of focal white matter lesions. Current solutions require complex acquisition paradigms and demand expert image analysis, limiting application in both clinical trials and clinical practice. In the current study, using data acquired in a clinical setting on a 3T scanner, we optimised and compared two approaches for optic radiation (OR reconstruction: individual probabilistic tractography-based and template-based methods. OR segmentation results were applied to subjects with MS and volumetric and diffusivity parameters were compared between OR segmentation techniques. Despite differences in reconstructed OR volumes, both OR lesion volume and OR diffusivity measurements in MS subjects were highly comparable using optimised probabilistic tractography-based, and template-based, methods. The choice of OR reconstruction technique should be determined primarily by the research question and the nature of the available dataset. Template-based approaches are particularly suited to the semi-automated analysis of large image datasets and have utility even in the absence of dMRI acquisitions. Individual tractography methods, while more complex than template based OR reconstruction, permit measurement of diffusivity changes along fibre bundles that are affected by specific MS lesions or other focal pathologies.

  9. A coagulation-powdered activated carbon-ultrafiltration - Multiple barrier approach for removing toxins from two Australian cyanobacterial blooms

    International Nuclear Information System (INIS)

    Dixon, Mike B.; Richard, Yann; Ho, Lionel; Chow, Christopher W.K.; O'Neill, Brian K.; Newcombe, Gayle

    2011-01-01

    Cyanobacteria are a major problem for the world wide water industry as they can produce metabolites toxic to humans in addition to taste and odour compounds that make drinking water aesthetically displeasing. Removal of cyanobacterial toxins from drinking water is important to avoid serious illness in consumers. This objective can be confidently achieved through the application of the multiple barrier approach to drinking water quality and safety. In this study the use of a multiple barrier approach incorporating coagulation, powdered activated carbon (PAC) and ultrafiltration (UF) was investigated for the removal of intracellular and extracellular cyanobacterial toxins from two naturally occurring blooms in South Australia. Also investigated was the impact of these treatments on the UF flux. In this multibarrier approach, coagulation was used to remove the cells and thus the intracellular toxin while PAC was used for extracellular toxin adsorption and finally the UF was used for floc, PAC and cell removal. Cyanobacterial cells were completely removed using the UF membrane alone and when used in conjunction with coagulation. Extracellular toxins were removed to varying degrees by PAC addition. UF flux deteriorated dramatically during a trial with a very high cell concentration; however, the flux was improved by coagulation and PAC addition.

  10. Automatic differentiation for design sensitivity analysis of structural systems using multiple processors

    Science.gov (United States)

    Nguyen, Duc T.; Storaasli, Olaf O.; Qin, Jiangning; Qamar, Ramzi

    1994-01-01

    An automatic differentiation tool (ADIFOR) is incorporated into a finite element based structural analysis program for shape and non-shape design sensitivity analysis of structural systems. The entire analysis and sensitivity procedures are parallelized and vectorized for high performance computation. Small scale examples to verify the accuracy of the proposed program and a medium scale example to demonstrate the parallel vector performance on multiple CRAY C90 processors are included.

  11. Mode Shape Analysis of Multiple Cracked Functionally Graded Timoshenko Beams

    Directory of Open Access Journals (Sweden)

    Tran Van Lien

    Full Text Available Abstract The present paper addresses free vibration of multiple cracked Timoshenko beams made of Functionally Graded Material (FGM. Cracks are modeled by rotational spring of stiffness calculated from the crack depth and material properties vary according to the power law throughout the beam thickness. Governing equations for free vibration of the beam are formulated with taking into account actual position of the neutral plane. The obtained frequency equation and mode shapes are used for analysis of the beam mode shapes in dependence on the material and crack parameters. Numerical results validate usefulness of the proposed herein theory and show that mode shapes are good indication for detecting multiple cracks in Timoshenko FGM beams.

  12. Monitoring urban greenness dynamics using multiple endmember spectral mixture analysis.

    Directory of Open Access Journals (Sweden)

    Muye Gan

    Full Text Available Urban greenness is increasingly recognized as an essential constituent of the urban environment and can provide a range of services and enhance residents' quality of life. Understanding the pattern of urban greenness and exploring its spatiotemporal dynamics would contribute valuable information for urban planning. In this paper, we investigated the pattern of urban greenness in Hangzhou, China, over the past two decades using time series Landsat-5 TM data obtained in 1990, 2002, and 2010. Multiple endmember spectral mixture analysis was used to derive vegetation cover fractions at the subpixel level. An RGB-vegetation fraction model, change intensity analysis and the concentric technique were integrated to reveal the detailed, spatial characteristics and the overall pattern of change in the vegetation cover fraction. Our results demonstrated the ability of multiple endmember spectral mixture analysis to accurately model the vegetation cover fraction in pixels despite the complex spectral confusion of different land cover types. The integration of multiple techniques revealed various changing patterns in urban greenness in this region. The overall vegetation cover has exhibited a drastic decrease over the past two decades, while no significant change occurred in the scenic spots that were studied. Meanwhile, a remarkable recovery of greenness was observed in the existing urban area. The increasing coverage of small green patches has played a vital role in the recovery of urban greenness. These changing patterns were more obvious during the period from 2002 to 2010 than from 1990 to 2002, and they revealed the combined effects of rapid urbanization and greening policies. This work demonstrates the usefulness of time series of vegetation cover fractions for conducting accurate and in-depth studies of the long-term trajectories of urban greenness to obtain meaningful information for sustainable urban development.

  13. Design of multiple representations e-learning resources based on a contextual approach for the basic physics course

    Science.gov (United States)

    Bakri, F.; Muliyati, D.

    2018-05-01

    This research aims to design e-learning resources with multiple representations based on a contextual approach for the Basic Physics Course. The research uses the research and development methods accordance Dick & Carey strategy. The development carried out in the digital laboratory of Physics Education Department, Mathematics and Science Faculty, Universitas Negeri Jakarta. The result of the process of product development with Dick & Carey strategy, have produced e-learning design of the Basic Physics Course is presented in multiple representations in contextual learning syntax. The appropriate of representation used in the design of learning basic physics include: concept map, video, figures, data tables of experiment results, charts of data tables, the verbal explanations, mathematical equations, problem and solutions example, and exercise. Multiple representations are presented in the form of contextual learning by stages: relating, experiencing, applying, transferring, and cooperating.

  14. A Fisher Kernel Approach for Multiple Instance Based Object Retrieval in Video Surveillance

    Directory of Open Access Journals (Sweden)

    MIRONICA, I.

    2015-11-01

    Full Text Available This paper presents an automated surveillance system that exploits the Fisher Kernel representation in the context of multiple-instance object retrieval task. The proposed algorithm has the main purpose of tracking a list of persons in several video sources, using only few training examples. In the first step, the Fisher Kernel representation describes a set of features as the derivative with respect to the log-likelihood of the generative probability distribution that models the feature distribution. Then, we learn the generative probability distribution over all features extracted from a reduced set of relevant frames. The proposed approach shows significant improvements and we demonstrate that Fisher kernels are well suited for this task. We demonstrate the generality of our approach in terms of features by conducting an extensive evaluation with a broad range of keypoints features. Also, we evaluate our method on two standard video surveillance datasets attaining superior results comparing to state-of-the-art object recognition algorithms.

  15. [A factor analysis method for contingency table data with unlimited multiple choice questions].

    Science.gov (United States)

    Toyoda, Hideki; Haiden, Reina; Kubo, Saori; Ikehara, Kazuya; Isobe, Yurie

    2016-02-01

    The purpose of this study is to propose a method of factor analysis for analyzing contingency tables developed from the data of unlimited multiple-choice questions. This method assumes that the element of each cell of the contingency table has a binominal distribution and a factor analysis model is applied to the logit of the selection probability. Scree plot and WAIC are used to decide the number of factors, and the standardized residual, the standardized difference between the sample, and the proportion ratio, is used to select items. The proposed method was applied to real product impression research data on advertised chips and energy drinks. Since the results of the analysis showed that this method could be used in conjunction with conventional factor analysis model, and extracted factors were fully interpretable, and suggests the usefulness of the proposed method in the study of psychology using unlimited multiple-choice questions.

  16. Multiple-Relaxation-Time Lattice Boltzmann Approach to Richtmyer-Meshkov Instability

    International Nuclear Information System (INIS)

    Chen Feng; Li Yingjun; Xu Aiguo; Zhang Guangcai

    2011-01-01

    The aims of the present paper are twofold. At first, we further study the Multiple-Relaxation-Time (MRT) Lattice Boltzmann (LB) model proposed in [Europhys. Lett. 90 (2010) 54003]. We discuss the reason why the Gram-Schmidt orthogonalization procedure is not needed in the construction of transformation matrix M; point out a reason why the Kataoka-Tsutahara model [Phys. Rev. E 69 (2004) 035701 (R)] is only valid in subsonic flows. The von Neumann stability analysis is performed. Secondly, we carry out a preliminary quantitative study on the Richtmyer-Meshkov instability using the proposed MRT LB model. When a shock wave travels from a light medium to a heavy one, the simulated growth rate is in qualitative agreement with the perturbation model by Zhang-Sohn. It is about half of the predicted value by the impulsive model and is closer to the experimental result. When the shock wave travels from a heavy medium to a light one, our simulation results are also consistent with physical analysis. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

  17. Real analysis a constructive approach

    CERN Document Server

    Bridger, Mark

    2012-01-01

    A unique approach to analysis that lets you apply mathematics across a range of subjects This innovative text sets forth a thoroughly rigorous modern account of the theoretical underpinnings of calculus: continuity, differentiability, and convergence. Using a constructive approach, every proof of every result is direct and ultimately computationally verifiable. In particular, existence is never established by showing that the assumption of non-existence leads to a contradiction. The ultimate consequence of this method is that it makes sense-not just to math majors but also to students from a

  18. Exergy analysis of an ejector-absorption heat transformer using artificial neural network approach

    International Nuclear Information System (INIS)

    Soezen, Adnan; Arcaklioglu, Erol

    2007-01-01

    This paper proposes artificial neural networks (ANNs) technique as a new approach to determine the exergy losses of an ejector-absorption heat transformer (EAHT). Thermodynamic analysis of the EAHT is too complex due to complex differential equations and complex simulations programs. ANN technique facilitates these complicated situations. This study is considered to be helpful in predicting the exergetic performance of components of an EAHT prior to its setting up in a thermal system where the working temperatures are known. The best approach was investigated using different algorithms with developed software. The best statistical coefficient of multiple determinations (R 2 -value) for training data equals to 0.999715, 0.995627, 0.999497, and 0.997648 obtained by different algorithms with seven neurons for the non-dimensional exergy losses of evaporator, generator, absorber and condenser, respectively. Similarly these values for testing data are 0.999774, 0.994039, 0.999613 and 0.99938, respectively. The results show that this approach has the advantages of computational speed, low cost for feasibility, rapid turnaround, which is especially important during iterative design phases, and easy of design by operators with little technical experience

  19. External phenome analysis enables a rational federated query strategy to detect changing rates of treatment-related complications associated with multiple myeloma.

    Science.gov (United States)

    Warner, Jeremy L; Alterovitz, Gil; Bodio, Kelly; Joyce, Robin M

    2013-01-01

    Electronic health records (EHRs) are increasingly useful for health services research. For relatively uncommon conditions, such as multiple myeloma (MM) and its treatment-related complications, a combination of multiple EHR sources is essential for such research. The Shared Health Research Information Network (SHRINE) enables queries for aggregate results across participating institutions. Development of a rational search strategy in SHRINE may be augmented through analysis of pre-existing databases. We developed a SHRINE query for likely non-infectious treatment-related complications of MM, based upon an analysis of the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC II) database. Using this query strategy, we found that the rate of likely treatment-related complications significantly increased from 2001 to 2007, by an average of 6% a year (p=0.01), across the participating SHRINE institutions. This finding is in keeping with increasingly aggressive strategies in the treatment of MM. This proof of concept demonstrates that a staged approach to federated queries, using external EHR data, can yield potentially clinically meaningful results.

  20. A New Approach to Adaptive Control of Multiple Scales in Plasma Simulations

    Science.gov (United States)

    Omelchenko, Yuri

    2007-04-01

    A new approach to temporal refinement of kinetic (Particle-in-Cell, Vlasov) and fluid (MHD, two-fluid) simulations of plasmas is presented: Discrete-Event Simulation (DES). DES adaptively distributes CPU resources in accordance with local time scales and enables asynchronous integration of inhomogeneous nonlinear systems with multiple time scales on meshes of arbitrary topologies. This removes computational penalties usually incurred in explicit codes due to the global Courant-Friedrich-Levy (CFL) restriction on a time-step size. DES stands apart from multiple time-stepping algorithms in that it requires neither selecting a global synchronization time step nor pre-determining a sequence of time-integration operations for individual parts of the system (local time increments need not bear any integer multiple relations). Instead, elements of a mesh-distributed solution self-adaptively predict and synchronize their temporal trajectories by directly enforcing local causality (accuracy) constraints, which are formulated in terms of incremental changes to the evolving solution. Together with flux-conservative propagation of information, this new paradigm ensures stable and fast asynchronous runs, where idle computation is automatically eliminated. DES is parallelized via a novel Preemptive Event Processing (PEP) technique, which automatically synchronizes elements with similar update rates. In this mode, events with close execution times are projected onto time levels, which are adaptively determined by the program. PEP allows reuse of standard message-passing algorithms on distributed architectures. For optimum accuracy, DES can be combined with adaptive mesh refinement (AMR) techniques for structured and unstructured meshes. Current examples of event-driven models range from electrostatic, hybrid particle-in-cell plasma systems to reactive fluid dynamics simulations. They demonstrate the superior performance of DES in terms of accuracy, speed and robustness.

  1. A computational intelligent approach to multi-factor analysis of violent crime information system

    Science.gov (United States)

    Liu, Hongbo; Yang, Chao; Zhang, Meng; McLoone, Seán; Sun, Yeqing

    2017-02-01

    Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

  2. Structural model analysis of multiple quantitative traits.

    Directory of Open Access Journals (Sweden)

    Renhua Li

    2006-07-01

    Full Text Available We introduce a method for the analysis of multilocus, multitrait genetic data that provides an intuitive and precise characterization of genetic architecture. We show that it is possible to infer the magnitude and direction of causal relationships among multiple correlated phenotypes and illustrate the technique using body composition and bone density data from mouse intercross populations. Using these techniques we are able to distinguish genetic loci that affect adiposity from those that affect overall body size and thus reveal a shortcoming of standardized measures such as body mass index that are widely used in obesity research. The identification of causal networks sheds light on the nature of genetic heterogeneity and pleiotropy in complex genetic systems.

  3. A hybrid approach to parameter identification of linear delay differential equations involving multiple delays

    Science.gov (United States)

    Marzban, Hamid Reza

    2018-05-01

    In this paper, we are concerned with the parameter identification of linear time-invariant systems containing multiple delays. The approach is based upon a hybrid of block-pulse functions and Legendre's polynomials. The convergence of the proposed procedure is established and an upper error bound with respect to the L2-norm associated with the hybrid functions is derived. The problem under consideration is first transformed into a system of algebraic equations. The least squares technique is then employed for identification of the desired parameters. Several multi-delay systems of varying complexity are investigated to evaluate the performance and capability of the proposed approximation method. It is shown that the proposed approach is also applicable to a class of nonlinear multi-delay systems. It is demonstrated that the suggested procedure provides accurate results for the desired parameters.

  4. Failure analysis of high strength pipeline with single and multiple corrosions

    International Nuclear Information System (INIS)

    Chen, Yanfei; Zhang, Hong; Zhang, Juan; Li, Xin; Zhou, Jing

    2015-01-01

    Highlights: • We study failure of high strength pipelines with single corrosion. • We give regression equations for failure pressure prediction. • We propose assessment procedure for pipelines with multiple corrosions. - Abstract: Corrosion will compromise safety operation of oil and gas pipelines, accurate determination of failure pressure finds importance in residual strength assessment and corrosion allowance design of onshore and offshore pipelines. This paper investigates failure pressure of high strength pipeline with single and multiple corrosions using nonlinear finite element analysis. On the basis of developed regression equations for failure pressure prediction of high strength pipeline with single corrosion, the paper proposes an assessment procedure for predicting failure pressure of high strength pipeline with multiple corrosions. Furthermore, failure pressures predicted by proposed solutions are compared with experimental results and various assessment methods available in literature, where accuracy and versatility are demonstrated

  5. Relative accuracy of spatial predictive models for lynx Lynx canadensis derived using logistic regression-AIC, multiple criteria evaluation and Bayesian approaches

    Directory of Open Access Journals (Sweden)

    Shelley M. ALEXANDER

    2009-02-01

    Full Text Available We compared probability surfaces derived using one set of environmental variables in three Geographic Information Systems (GIS-based approaches: logistic regression and Akaike’s Information Criterion (AIC, Multiple Criteria Evaluation (MCE, and Bayesian Analysis (specifically Dempster-Shafer theory. We used lynx Lynx canadensis as our focal species, and developed our environment relationship model using track data collected in Banff National Park, Alberta, Canada, during winters from 1997 to 2000. The accuracy of the three spatial models were compared using a contingency table method. We determined the percentage of cases in which both presence and absence points were correctly classified (overall accuracy, the failure to predict a species where it occurred (omission error and the prediction of presence where there was absence (commission error. Our overall accuracy showed the logistic regression approach was the most accurate (74.51%. The multiple criteria evaluation was intermediate (39.22%, while the Dempster-Shafer (D-S theory model was the poorest (29.90%. However, omission and commission error tell us a different story: logistic regression had the lowest commission error, while D-S theory produced the lowest omission error. Our results provide evidence that habitat modellers should evaluate all three error measures when ascribing confidence in their model. We suggest that for our study area at least, the logistic regression model is optimal. However, where sample size is small or the species is very rare, it may also be useful to explore and/or use a more ecologically cautious modelling approach (e.g. Dempster-Shafer that would over-predict, protect more sites, and thereby minimize the risk of missing critical habitat in conservation plans[Current Zoology 55(1: 28 – 40, 2009].

  6. Multiple Sclerosis Increases Fracture Risk: A Meta-Analysis

    Directory of Open Access Journals (Sweden)

    Guixian Dong

    2015-01-01

    Full Text Available Purpose. The association between multiple sclerosis (MS and fracture risk has been reported, but results of previous studies remain controversial and ambiguous. To assess the association between MS and fracture risk, a meta-analysis was performed. Method. Based on comprehensive searches of the PubMed, Embase, and Web of Science, we identified outcome data from all articles estimating the association between MS and fracture risk. The pooled risk ratios (RRs with 95% confidence intervals (CIs were calculated. Results. A significant association between MS and fracture risk was found. This result remained statistically significant when the adjusted RRs were combined. Subgroup analysis stratified by the site of fracture suggested significant associations between MS and tibia fracture risk, femur fracture risk, hip fracture risk, pelvis fracture risk, vertebrae fracture risk, and humerus fracture risk. In the subgroup analysis by gender, female MS patients had increased fracture risk. When stratified by history of drug use, use of antidepressants, hypnotics/anxiolytics, anticonvulsants, and glucocorticoids increased the risk of fracture risk in MS patients. Conclusions. This meta-analysis demonstrated that MS was significantly associated with fracture risk.

  7. The Research of Multiple Attenuation Based on Feedback Iteration and Independent Component Analysis

    Science.gov (United States)

    Xu, X.; Tong, S.; Wang, L.

    2017-12-01

    How to solve the problem of multiple suppression is a difficult problem in seismic data processing. The traditional technology for multiple attenuation is based on the principle of the minimum output energy of the seismic signal, this criterion is based on the second order statistics, and it can't achieve the multiple attenuation when the primaries and multiples are non-orthogonal. In order to solve the above problems, we combine the feedback iteration method based on the wave equation and the improved independent component analysis (ICA) based on high order statistics to suppress the multiple waves. We first use iterative feedback method to predict the free surface multiples of each order. Then, in order to predict multiples from real multiple in amplitude and phase, we design an expanded pseudo multi-channel matching filtering method to get a more accurate matching multiple result. Finally, we present the improved fast ICA algorithm which is based on the maximum non-Gauss criterion of output signal to the matching multiples and get better separation results of the primaries and the multiples. The advantage of our method is that we don't need any priori information to the prediction of the multiples, and can have a better separation result. The method has been applied to several synthetic data generated by finite-difference model technique and the Sigsbee2B model multiple data, the primaries and multiples are non-orthogonal in these models. The experiments show that after three to four iterations, we can get the perfect multiple results. Using our matching method and Fast ICA adaptive multiple subtraction, we can not only effectively preserve the effective wave energy in seismic records, but also can effectively suppress the free surface multiples, especially the multiples related to the middle and deep areas.

  8. Rasch analysis of the Multiple Sclerosis Impact Scale (MSIS-29

    Directory of Open Access Journals (Sweden)

    Misajon Rose

    2009-06-01

    Full Text Available Abstract Background Multiple Sclerosis (MS is a degenerative neurological disease that causes impairments, including spasticity, pain, fatigue, and bladder dysfunction, which negatively impact on quality of life. The Multiple Sclerosis Impact Scale (MSIS-29 is a disease-specific health-related quality of life (HRQoL instrument, developed using the patient's perspective on disease impact. It consists of two subscales assessing the physical (MSIS-29-PHYS and psychological (MSIS-29-PSYCH impact of MS. Although previous studies have found support for the psychometric properties of the MSIS-29 using traditional methods of scale evaluation, the scale has not been subjected to a detailed Rasch analysis. Therefore, the objective of this study was to use Rasch analysis to assess the internal validity of the scale, and its response format, item fit, targeting, internal consistency and dimensionality. Methods Ninety-two persons with definite MS residing in the community were recruited from a tertiary hospital database. Patients completed the MSIS-29 as part of a larger study. Rasch analysis was undertaken to assess the psychometric properties of the MSIS-29. Results Rasch analysis showed overall support for the psychometric properties of the two MSIS-29 subscales, however it was necessary to reduce the response format of the MSIS-29-PHYS to a 3-point response scale. Both subscales were unidimensional, had good internal consistency, and were free from item bias for sex and age. Dimensionality testing indicated it was not appropriate to combine the two subscales to form a total MSIS score. Conclusion In this first study to use Rasch analysis to fully assess the psychometric properties of the MSIS-29 support was found for the two subscales but not for the use of the total scale. Further use of Rasch analysis on the MSIS-29 in larger and broader samples is recommended to confirm these findings.

  9. Rasch analysis of the Multiple Sclerosis Impact Scale (MSIS-29)

    Science.gov (United States)

    Ramp, Melina; Khan, Fary; Misajon, Rose Anne; Pallant, Julie F

    2009-01-01

    Background Multiple Sclerosis (MS) is a degenerative neurological disease that causes impairments, including spasticity, pain, fatigue, and bladder dysfunction, which negatively impact on quality of life. The Multiple Sclerosis Impact Scale (MSIS-29) is a disease-specific health-related quality of life (HRQoL) instrument, developed using the patient's perspective on disease impact. It consists of two subscales assessing the physical (MSIS-29-PHYS) and psychological (MSIS-29-PSYCH) impact of MS. Although previous studies have found support for the psychometric properties of the MSIS-29 using traditional methods of scale evaluation, the scale has not been subjected to a detailed Rasch analysis. Therefore, the objective of this study was to use Rasch analysis to assess the internal validity of the scale, and its response format, item fit, targeting, internal consistency and dimensionality. Methods Ninety-two persons with definite MS residing in the community were recruited from a tertiary hospital database. Patients completed the MSIS-29 as part of a larger study. Rasch analysis was undertaken to assess the psychometric properties of the MSIS-29. Results Rasch analysis showed overall support for the psychometric properties of the two MSIS-29 subscales, however it was necessary to reduce the response format of the MSIS-29-PHYS to a 3-point response scale. Both subscales were unidimensional, had good internal consistency, and were free from item bias for sex and age. Dimensionality testing indicated it was not appropriate to combine the two subscales to form a total MSIS score. Conclusion In this first study to use Rasch analysis to fully assess the psychometric properties of the MSIS-29 support was found for the two subscales but not for the use of the total scale. Further use of Rasch analysis on the MSIS-29 in larger and broader samples is recommended to confirm these findings. PMID:19545445

  10. A neuro-data envelopment analysis approach for optimization of uncorrelated multiple response problems with smaller the better type controllable factors

    Science.gov (United States)

    Bashiri, Mahdi; Farshbaf-Geranmayeh, Amir; Mogouie, Hamed

    2013-11-01

    In this paper, a new method is proposed to optimize a multi-response optimization problem based on the Taguchi method for the processes where controllable factors are the smaller-the-better (STB)-type variables and the analyzer desires to find an optimal solution with smaller amount of controllable factors. In such processes, the overall output quality of the product should be maximized while the usage of the process inputs, the controllable factors, should be minimized. Since all possible combinations of factors' levels, are not considered in the Taguchi method, the response values of the possible unpracticed treatments are estimated using the artificial neural network (ANN). The neural network is tuned by the central composite design (CCD) and the genetic algorithm (GA). Then data envelopment analysis (DEA) is applied for determining the efficiency of each treatment. Although the important issue for implementation of DEA is its philosophy, which is maximization of outputs versus minimization of inputs, this important issue has been neglected in previous similar studies in multi-response problems. Finally, the most efficient treatment is determined using the maximin weight model approach. The performance of the proposed method is verified in a plastic molding process. Moreover a sensitivity analysis has been done by an efficiency estimator neural network. The results show efficiency of the proposed approach.

  11. Non-destructive assay of fissile materials by detection and multiplicity analysis of spontaneous neutrons

    International Nuclear Information System (INIS)

    Prosdocimi, A.

    1979-01-01

    A method for determining the absolute reaction rate of nuclear events giving rise to neutron emission, according to their neutron multiplicity, is proposed. A typical application is the measurement of the (α, n) and spontaneous fission rates in a fissile material sample, particularly of Pu oxide composition. An analysis of random and correlated neutron pulses is carried out on the basis of sequential order without requiring any time interval analysis, then the primary nuclear events are sorted versus their neutron multiplicity. Suitable theoretical relationships enable to derive the absolute (α, n) and SF reaction rates when the physical parameters of the neutron detector and the multiplicity spectrumm of pulses are known. A typical device is described and the results of experiments leading to Pu-239 and Pu-240 assay are given

  12. [Efficacy of racecadotril vs. smectite, probiotics or zinc as an integral part of treatment of acute diarrhea in children under five years: A meta-analysis of multiple treatments].

    Science.gov (United States)

    Gutiérrez-Castrellón, Pedro; Ortíz-Hernández, Anna Alejandra; Llamosas-Gallardo, Beatriz; Acosta-Bastidas, Mario A; Jiménez-Gutiérrez, Carlos; Diaz-García, Luisa; Anzo-Osorio, Anahí; Estevez-Jiménez, Juliana; Jiménez-Escobar, Irma; Vidal-Vázquez, Rosa Patricia

    2015-01-01

    Despite major advances in treatment, acute diarrhea continues to be a public health problem in children under five years. There is no systematic approach to treatment and most evidence is assembled comparing active treatment vs. placebo. Systematic review of evidence on efficacy of adjuvants for treatment of acute diarrhea through a network meta-analysis. A systematic search of multiple databases searching clinical trials related to the use of racecadotril, smectite, Lactobacillus GG, Lactobacillus reuteri, Saccharomyces boulardii and zinc as adjuvants in acute diarrhea was done. The primary endpoint was duration of diarrhea. Information is displayed through network meta-analysis.The superiority of each coadjutant was analyzed by Sucra approach. Network meta-analysis showed race cadotril was better when compared with placebo and other adjuvants. Sucra analysis showed racecadotril as the first option followed by smectite and Lactobacillus reuteri. Considering a strategic decision making approach, network meta-analysis allows us to establish the therapeutic superiority of racecadotril as an adjunct for the comprehensive management of acute diarrhea in children aged less than five years.

  13. Orchestrating Multiple Intelligences

    Science.gov (United States)

    Moran, Seana; Kornhaber, Mindy; Gardner, Howard

    2006-01-01

    Education policymakers often go astray when they attempt to integrate multiple intelligences theory into schools, according to the originator of the theory, Howard Gardner, and his colleagues. The greatest potential of a multiple intelligences approach to education grows from the concept of a profile of intelligences. Each learner's intelligence…

  14. The Multiple Intelligences Teaching Method and Mathematics ...

    African Journals Online (AJOL)

    The Multiple Intelligences teaching approach has evolved and been embraced widely especially in the United States. The approach has been found to be very effective in changing situations for the better, in the teaching and learning of any subject especially mathematics. Multiple Intelligences teaching approach proposes ...

  15. Extending Data Worth Analyses to Select Multiple Observations Targeting Multiple Forecasts

    DEFF Research Database (Denmark)

    Vilhelmsen, Troels Norvin; Ferre, Ty Paul

    2017-01-01

    . In the present study, we extend previous data worth analyses to include: simultaneous selection of multiple new measurements and consideration of multiple forecasts of interest. We show how the suggested approach can be used to optimize data collection. This can be used in a manner that suggests specific...... measurement sets or that produces probability maps indicating areas likely to be informative for specific forecasts. Moreover, we provide examples documenting that sequential measurement election approaches often lead to suboptimal designs and that estimates of data covariance should be included when...

  16. Integrating multiple programme and policy approaches to hepatitis C prevention and care for injection drug users: a comprehensive approach.

    Science.gov (United States)

    Birkhead, Guthrie S; Klein, Susan J; Candelas, Alma R; O'Connell, Daniel A; Rothman, Jeffrey R; Feldman, Ira S; Tsui, Dennis S; Cotroneo, Richard A; Flanigan, Colleen A

    2007-10-01

    New York State is home to an estimated 230,000 individuals chronically infected with hepatitis C virus (HCV) and roughly 171,500 active injection drug users (IDUs). HCV/HIV co-infection is common and models of service delivery that effectively meet IDUs' needs are required. A HCV strategic plan has stressed integration. HCV prevention and care are integrated within health and human service settings, including HIV/AIDS organisations and drug treatment programmes. Other measures that support comprehensive HCV services for IDUs include reimbursement, clinical guidelines, training and HCV prevention education. Community and provider collaborations inform programme and policy development. IDUs access 5 million syringes annually through harm reduction/syringe exchange programmes (SEPs) and a statewide syringe access programme. Declines in HCV prevalence amongst IDUs in New York City coincided with improved syringe availability. New models of care successfully link IDUs at SEPs and in drug treatment to health care. Over 7000 Medicaid recipients with HCV/HIV co-infection had health care encounters related to their HCV in a 12-month period and 10,547 claims for HCV-related medications were paid. The success rate of transitional case management referrals to drug treatment is over 90%. Training and clinical guidelines promote provider knowledge about HCV and contribute to quality HCV care for IDUs. Chart reviews of 2570 patients with HIV in 2004 documented HCV status 97.4% of the time, overall, in various settings. New HCV surveillance systems are operational. Despite this progress, significant challenges remain. A comprehensive, public health approach, using multiple strategies across systems and mobilizing multiple sectors, can enhance IDUs access to HCV prevention and care. A holisitic approach with integrated services, including for HCV-HIV co-infected IDUs is needed. Leadership, collaboration and resources are essential.

  17. Hearing the voices of service user researchers in collaborative qualitative data analysis: the case for multiple coding.

    Science.gov (United States)

    Sweeney, Angela; Greenwood, Kathryn E; Williams, Sally; Wykes, Til; Rose, Diana S

    2013-12-01

    Health research is frequently conducted in multi-disciplinary teams, with these teams increasingly including service user researchers. Whilst it is common for service user researchers to be involved in data collection--most typically interviewing other service users--it is less common for service user researchers to be involved in data analysis and interpretation. This means that a unique and significant perspective on the data is absent. This study aims to use an empirical report of a study on Cognitive Behavioural Therapy for psychosis (CBTp) to demonstrate the value of multiple coding in enabling service users voices to be heard in team-based qualitative data analysis. The CBTp study employed multiple coding to analyse service users' discussions of CBT for psychosis (CBTp) from the perspectives of a service user researcher, clinical researcher and psychology assistant. Multiple coding was selected to enable multiple perspectives to analyse and interpret data, to understand and explore differences and to build multi-disciplinary consensus. Multiple coding enabled the team to understand where our views were commensurate and incommensurate and to discuss and debate differences. Through the process of multiple coding, we were able to build strong consensus about the data from multiple perspectives, including that of the service user researcher. Multiple coding is an important method for understanding and exploring multiple perspectives on data and building team consensus. This can be contrasted with inter-rater reliability which is only appropriate in limited circumstances. We conclude that multiple coding is an appropriate and important means of hearing service users' voices in qualitative data analysis. © 2012 John Wiley & Sons Ltd.

  18. Supervised Cross-Modal Factor Analysis for Multiple Modal Data Classification

    KAUST Repository

    Wang, Jingbin

    2015-10-09

    In this paper we study the problem of learning from multiple modal data for purpose of document classification. In this problem, each document is composed two different modals of data, i.e., An image and a text. Cross-modal factor analysis (CFA) has been proposed to project the two different modals of data to a shared data space, so that the classification of a image or a text can be performed directly in this space. A disadvantage of CFA is that it has ignored the supervision information. In this paper, we improve CFA by incorporating the supervision information to represent and classify both image and text modals of documents. We project both image and text data to a shared data space by factor analysis, and then train a class label predictor in the shared space to use the class label information. The factor analysis parameter and the predictor parameter are learned jointly by solving one single objective function. With this objective function, we minimize the distance between the projections of image and text of the same document, and the classification error of the projection measured by hinge loss function. The objective function is optimized by an alternate optimization strategy in an iterative algorithm. Experiments in two different multiple modal document data sets show the advantage of the proposed algorithm over other CFA methods.

  19. Approach to evaluation and management of a patient with multiple food allergies.

    Science.gov (United States)

    Bird, J Andrew

    2016-01-01

    Diagnosing food allergy is often challenging, and validated testing modalities are mostly limited to immunoglobulin E (IgE)-mediated reactions to foods. Use of food-specific IgE tests and skin prick tests in individuals without a history that supports an IgE-mediated reaction to the specific food being tested diminishes the predictive capabilities of the test. To review the literature regarding evaluation of patients with a concern for multiple food allergies and to demonstrate an evidence-based approach to diagnosis and management. A literature search was performed and articles identified as relevant based on the search terms "food allergy," "food allergy diagnosis," "skin prick test," "serum IgE test," "oral food challenge", and "food allergy management." Patients at risk of food allergy are often misdiagnosed and appropriate evaluation of patients with concern for food allergy includes taking a thorough diet history and reaction history, performing specific tests intentionally and when indicated, and conducting an oral food challenge in a safe environment by an experienced provider when test results are inconclusive. An evidence-based approach to diagnosing and managing a patient at risk of having a life-threatening food allergy is reviewed.

  20. A heuristic approach using multiple criteria for environmentally benign 3PLs selection

    Science.gov (United States)

    Kongar, Elif

    2005-11-01

    Maintaining competitiveness in an environment where price and quality differences between competing products are disappearing depends on the company's ability to reduce costs and supply time. Timely responses to rapidly changing market conditions require an efficient Supply Chain Management (SCM). Outsourcing logistics to third-party logistics service providers (3PLs) is one commonly used way of increasing the efficiency of logistics operations, while creating a more "core competency focused" business environment. However, this alone may not be sufficient. Due to recent environmental regulations and growing public awareness regarding environmental issues, 3PLs need to be not only efficient but also environmentally benign to maintain companies' competitiveness. Even though an efficient and environmentally benign combination of 3PLs can theoretically be obtained using exhaustive search algorithms, heuristics approaches to the selection process may be superior in terms of the computational complexity. In this paper, a hybrid approach that combines a multiple criteria Genetic Algorithm (GA) with Linear Physical Weighting Algorithm (LPPW) to be used in efficient and environmentally benign 3PLs is proposed. A numerical example is also provided to illustrate the method and the analyses.

  1. Stepwise approach to establishing multiple outreach laboratory information system-electronic medical record interfaces.

    Science.gov (United States)

    Pantanowitz, Liron; Labranche, Wayne; Lareau, William

    2010-05-26

    Clinical laboratory outreach business is changing as more physician practices adopt an electronic medical record (EMR). Physician connectivity with the laboratory information system (LIS) is consequently becoming more important. However, there are no reports available to assist the informatician with establishing and maintaining outreach LIS-EMR connectivity. A four-stage scheme is presented that was successfully employed to establish unidirectional and bidirectional interfaces with multiple physician EMRs. This approach involves planning (step 1), followed by interface building (step 2) with subsequent testing (step 3), and finally ongoing maintenance (step 4). The role of organized project management, software as a service (SAAS), and alternate solutions for outreach connectivity are discussed.

  2. Adjusted permutation method for multiple attribute decision making with meta-heuristic solution approaches

    Directory of Open Access Journals (Sweden)

    Hossein Karimi

    2011-04-01

    Full Text Available The permutation method of multiple attribute decision making has two significant deficiencies: high computational time and wrong priority output in some problem instances. In this paper, a novel permutation method called adjusted permutation method (APM is proposed to compensate deficiencies of conventional permutation method. We propose Tabu search (TS and particle swarm optimization (PSO to find suitable solutions at a reasonable computational time for large problem instances. The proposed method is examined using some numerical examples to evaluate the performance of the proposed method. The preliminary results show that both approaches provide competent solutions in relatively reasonable amounts of time while TS performs better to solve APM.

  3. Multivariate meta-analysis: a robust approach based on the theory of U-statistic.

    Science.gov (United States)

    Ma, Yan; Mazumdar, Madhu

    2011-10-30

    Meta-analysis is the methodology for combining findings from similar research studies asking the same question. When the question of interest involves multiple outcomes, multivariate meta-analysis is used to synthesize the outcomes simultaneously taking into account the correlation between the outcomes. Likelihood-based approaches, in particular restricted maximum likelihood (REML) method, are commonly utilized in this context. REML assumes a multivariate normal distribution for the random-effects model. This assumption is difficult to verify, especially for meta-analysis with small number of component studies. The use of REML also requires iterative estimation between parameters, needing moderately high computation time, especially when the dimension of outcomes is large. A multivariate method of moments (MMM) is available and is shown to perform equally well to REML. However, there is a lack of information on the performance of these two methods when the true data distribution is far from normality. In this paper, we propose a new nonparametric and non-iterative method for multivariate meta-analysis on the basis of the theory of U-statistic and compare the properties of these three procedures under both normal and skewed data through simulation studies. It is shown that the effect on estimates from REML because of non-normal data distribution is marginal and that the estimates from MMM and U-statistic-based approaches are very similar. Therefore, we conclude that for performing multivariate meta-analysis, the U-statistic estimation procedure is a viable alternative to REML and MMM. Easy implementation of all three methods are illustrated by their application to data from two published meta-analysis from the fields of hip fracture and periodontal disease. We discuss ideas for future research based on U-statistic for testing significance of between-study heterogeneity and for extending the work to meta-regression setting. Copyright © 2011 John Wiley & Sons, Ltd.

  4. Application of multiple objective models to water resources planning and management

    International Nuclear Information System (INIS)

    North, R.M.

    1993-01-01

    Over the past 30 years, we have seen the birth and growth of multiple objective analysis from an idea without tools to one with useful applications. Models have been developed and applications have been researched to address the multiple purposes and objectives inherent in the development and management of water resources. A practical approach to multiple objective modelling incorporates macroeconomic-based policies and expectations in order to optimize the results from both engineering (structural) and management (non-structural) alternatives, while taking into account the economic and environmental trade-offs. (author). 27 refs, 4 figs, 3 tabs

  5. a Novel Approach for 3d Neighbourhood Analysis

    Science.gov (United States)

    Emamgholian, S.; Taleai, M.; Shojaei, D.

    2017-09-01

    Population growth and lack of land in urban areas have caused massive developments such as high rises and underground infrastructures. Land authorities in the international context recognizes 3D cadastres as a solution to efficiently manage these developments in complex cities. Although a 2D cadastre does not efficiently register these developments, it is currently being used in many jurisdictions for registering land and property information. Limitations in analysis and presentation are considered as examples of such limitations. 3D neighbourhood analysis by automatically finding 3D spaces has become an issue of major interest in recent years. Whereas the neighbourhood analysis has been in the focus of research, the idea of 3D neighbourhood analysis has rarely been addressed in 3 dimensional information systems (3D GIS) analysis. In this paper, a novel approach for 3D neighbourhood analysis has been proposed by recording spatial and descriptive information of the apartment units and easements. This approach uses the coordinates of the subject apartment unit to find the neighbour spaces. By considering a buffer around the edges of the unit, neighbour spaces are accurately detected. This method was implemented in ESRI ArcScene and three case studies were defined to test the efficiency of this approach. The results show that spaces are accurately detected in various complex scenarios. This approach can also be applied for other applications such as property management and disaster management in order to find the affected apartments around a defined space.

  6. Simultaneous imaging of multiple neurotransmitters and neuroactive substances in the brain by desorption electrospray ionization mass spectrometry

    OpenAIRE

    Shariatgorji, Mohammadreza; Strittmatter, Nicole; Nilsson, Anna; Kallbäck, Patrik; Alvarsson, Alexandra; Zhang, Xiaoqun; Vallianatou, Theodosia; Svenningsson, Per; Goodwin, Richard J. A.; Andrén, Per E.

    2016-01-01

    With neurological processes involving multiple neurotransmitters and neuromodulators, it is important to have the ability to directly map and quantify multiple signaling molecules simultaneously in a single analysis. By utilizing a molecular-specific approach, namely desorption electrospray ionization mass spectrometry imaging (DESI-MSI), we demonstrated that the technique can be used to image multiple neurotransmitters and their metabolites (dopamine, dihydroxyphenylacetic acid, 3-methoxytyr...

  7. Classification of multiple sclerosis patients by latent class analysis of magnetic resonance imaging characteristics.

    Science.gov (United States)

    Zwemmer, J N P; Berkhof, J; Castelijns, J A; Barkhof, F; Polman, C H; Uitdehaag, B M J

    2006-10-01

    Disease heterogeneity is a major issue in multiple sclerosis (MS). Classification of MS patients is usually based on clinical characteristics. More recently, a pathological classification has been presented. While clinical subtypes differ by magnetic resonance imaging (MRI) signature on a group level, a classification of individual MS patients based purely on MRI characteristics has not been presented so far. To investigate whether a restricted classification of MS patients can be made based on a combination of quantitative and qualitative MRI characteristics and to test whether the resulting subgroups are associated with clinical and laboratory characteristics. MRI examinations of the brain and spinal cord of 50 patients were scored for 21 quantitative and qualitative characteristics. Using latent class analysis, subgroups were identified, for whom disease characteristics and laboratory measures were compared. Latent class analysis revealed two subgroups that mainly differed in the extent of lesion confluency and MRI correlates of neuronal loss in the brain. Demographics and disease characteristics were comparable except for cognitive deficits. No correlations with laboratory measures were found. Latent class analysis offers a feasible approach for classifying subgroups of MS patients based on the presence of MRI characteristics. The reproducibility, longitudinal evolution and further clinical or prognostic relevance of the observed classification will have to be explored in a larger and independent sample of patients.

  8. Perceived Intrafamilial Connectedness and Autonomy in Families with and without an Anxious Family Member: A Multiple Informant Approach

    Science.gov (United States)

    de Albuquerque, Jiske E. G.; Schneider, Silvia

    2012-01-01

    Perceived intrafamilial "emotional connectedness" and "autonomy" were investigated within families with and without an anxious family member using a multiple informant approach. The sample consisted of 32 mothers with a current anxiety disorder and 56 controls, their partners, and their anxious and nonanxious teenage children. No differences were…

  9. SiteBinder: an improved approach for comparing multiple protein structural motifs.

    Science.gov (United States)

    Sehnal, David; Vařeková, Radka Svobodová; Huber, Heinrich J; Geidl, Stanislav; Ionescu, Crina-Maria; Wimmerová, Michaela; Koča, Jaroslav

    2012-02-27

    There is a paramount need to develop new techniques and tools that will extract as much information as possible from the ever growing repository of protein 3D structures. We report here on the development of a software tool for the multiple superimposition of large sets of protein structural motifs. Our superimposition methodology performs a systematic search for the atom pairing that provides the best fit. During this search, the RMSD values for all chemically relevant pairings are calculated by quaternion algebra. The number of evaluated pairings is markedly decreased by using PDB annotations for atoms. This approach guarantees that the best fit will be found and can be applied even when sequence similarity is low or does not exist at all. We have implemented this methodology in the Web application SiteBinder, which is able to process up to thousands of protein structural motifs in a very short time, and which provides an intuitive and user-friendly interface. Our benchmarking analysis has shown the robustness, efficiency, and versatility of our methodology and its implementation by the successful superimposition of 1000 experimentally determined structures for each of 32 eukaryotic linear motifs. We also demonstrate the applicability of SiteBinder using three case studies. We first compared the structures of 61 PA-IIL sugar binding sites containing nine different sugars, and we found that the sugar binding sites of PA-IIL and its mutants have a conserved structure despite their binding different sugars. We then superimposed over 300 zinc finger central motifs and revealed that the molecular structure in the vicinity of the Zn atom is highly conserved. Finally, we superimposed 12 BH3 domains from pro-apoptotic proteins. Our findings come to support the hypothesis that there is a structural basis for the functional segregation of BH3-only proteins into activators and enablers.

  10. Research approaches to the analysis of «man-production» relations

    Directory of Open Access Journals (Sweden)

    Liliya A. Otstavnova

    2014-01-01

    Full Text Available Objective to identify and describe research approaches used in the analysis of the relationship between humans and production. Methods in this work we have applied the methods of grouping describing and historical and logical method. Results basing on the characteristics of the main approaches used in the analysis of laquomanproductionraquo relations and taking into account the focus of the research it was established that the application of institutional systematic quantitative regulatory legislative structural functional and integrated approaches allows to pay equal attention to both production and man. Organic humanistic reproductive and situational approaches focus primarily on the man while economic procedural structural and marketing approaches focus on production. The distribution of each approach to a particular group is justified. Scientific novelty the author presents a classification of research approaches to the analysis of the laquomanproductionraquo relations system consisting of two subsystems. Each approach is given a detailed characteristic of both man and production that allows to evaluate the possibility of using these approaches and increasing the efficiency of this system research. Research approaches to the analysis of laquomanproductionraquo relations Practical value is manifested in the ability to optimize the use of research approaches to the analysis of the laquomanproductionraquo relations system to identify problems and ways to address them.

  11. Symptomatic treatment in multiple sclerosis-interim analysis of a nationwide registry.

    Science.gov (United States)

    Skierlo, S; Rommer, P S; Zettl, U K

    2017-04-01

    To analyze symptomatic treatment in patients with multiple sclerosis (MS). Multiple sclerosis is a chronic inflammatory disease of the central nervous system, with accumulating disability symptoms like spasticity, voiding disorders, depression, and pain might occur. The nationwide German MS registry was initiated 2001 under guidance of the German MS society (Deutsche MS Gesellschaft). This study was performed as an interim analysis to lay foundation for future work on this topic. A subcohort of 5113 patients was assessed for this interim analysis. The mean age of the patients was 45.3 years; mean EDSS was 4.2. More than two-third of the enrolled patients were females (70.9%). Most frequent symptoms were fatigue (60%), followed by spasticity (52.5%) and voiding disorders (51.7%). The likelihood of treatment was highest for epileptic disorders (68.8%), spasticity (68.5%), pain (60.7%), and depression (58.9%). Multivariate regression analysis showed that retirement was the strongest factor predictive for antispastic treatment (β=.061, P=.005). Almost all patients in this analysis suffer from symptoms due to advanced MS. Treatment for the various symptoms differed tremendously. The likelihood of treatment correlated with the availability of effective therapeutic agents. Clinicians should put more awareness on MS symptoms. Symptomatic treatment may improve quality of life. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  12. Why is the Arkavathy River drying? A multiple hypothesis approach in a data scarce region

    Science.gov (United States)

    Srinivasan, V.; Thompson, S.; Madhyastha, K.; Penny, G.; Jeremiah, K.; Lele, S.

    2015-01-01

    The developing world faces unique challenges in achieving water security as it is disproportionately exposed to stressors such as climate change while also undergoing demographic growth, agricultural intensification and industrialization. Investigative approaches are needed that can inform sound policy development and planning to address the water security challenge in the context of data scarcity. We investigated the "predictions under change" problem in the Thippagondanahalli (TG Halli) catchment of the Arkavathy sub-basin in South India. River inflows into the TG Halli reservoir have declined since the 1970s, and the reservoir is currently operating at only 20% of its built capacity. The mechanisms responsible for the drying of the river are not understood, resulting in uncoordinated and potentially counter-productive management responses. The objective of this study was to investigate potential explanations of the drying trend and thus obtain predictive insight. We used a multiple working hypothesis approach to investigate the decline in inflow into TG Halli reservoir. Five hypotheses were tested using data from field surveys and reliable secondary sources: (1) changes in rainfall amount, timing and storm intensity, (2) rising temperatures, (3) increased groundwater extraction, (4) expansion of eucalyptus plantations, and (5) increased fragmentation of the river channel. Our results indicate that proximate anthropogenic drivers of change such as groundwater pumping, expansion of eucalyptus plantations, and to a lesser extent channel fragmentation, are much more likely to have caused the decline in surface flows in the TG Halli catchment than changing climate. The case study shows that direct human interventions play a significant role in altering the hydrology of watersheds. The multiple working hypotheses approach presents a systematic way to quantify the relative contributions of anthropogenic drivers to hydrologic change. The approach not only yields a

  13. Multiple steady states detection in a packed-bed reactive distillation column using bifurcation analysis

    DEFF Research Database (Denmark)

    Ramzan, Naveed; Faheem, Muhammad; Gani, Rafiqul

    2010-01-01

    A packed reactive distillation column producing ethyl tert-butyl ether from tert-butyl alcohol and ethanol was simulated for detection of multiple steady states using Aspen Plus®. A rate-based approach was used to make the simulation model more realistic. A base-case was first developed and fine...

  14. Practice-oriented optical thin film growth simulation via multiple scale approach

    Energy Technology Data Exchange (ETDEWEB)

    Turowski, Marcus, E-mail: m.turowski@lzh.de [Laser Zentrum Hannover e.V., Hollerithallee 8, Hannover 30419 (Germany); Jupé, Marco [Laser Zentrum Hannover e.V., Hollerithallee 8, Hannover 30419 (Germany); QUEST: Centre of Quantum Engineering and Space-Time Research, Leibniz Universität Hannover (Germany); Melzig, Thomas [Fraunhofer Institute for Surface Engineering and Thin Films IST, Bienroder Weg 54e, Braunschweig 30108 (Germany); Moskovkin, Pavel [Research Centre for Physics of Matter and Radiation (PMR-LARN), University of Namur (FUNDP), 61 rue de Bruxelles, Namur 5000 (Belgium); Daniel, Alain [Centre for Research in Metallurgy, CRM, 21 Avenue du bois Saint Jean, Liège 4000 (Belgium); Pflug, Andreas [Fraunhofer Institute for Surface Engineering and Thin Films IST, Bienroder Weg 54e, Braunschweig 30108 (Germany); Lucas, Stéphane [Research Centre for Physics of Matter and Radiation (PMR-LARN), University of Namur (FUNDP), 61 rue de Bruxelles, Namur 5000 (Belgium); Ristau, Detlev [Laser Zentrum Hannover e.V., Hollerithallee 8, Hannover 30419 (Germany); QUEST: Centre of Quantum Engineering and Space-Time Research, Leibniz Universität Hannover (Germany)

    2015-10-01

    Simulation of the coating process is a very promising approach for the understanding of thin film formation. Nevertheless, this complex matter cannot be covered by a single simulation technique. To consider all mechanisms and processes influencing the optical properties of the growing thin films, various common theoretical methods have been combined to a multi-scale model approach. The simulation techniques have been selected in order to describe all processes in the coating chamber, especially the various mechanisms of thin film growth, and to enable the analysis of the resulting structural as well as optical and electronic layer properties. All methods are merged with adapted communication interfaces to achieve optimum compatibility of the different approaches and to generate physically meaningful results. The present contribution offers an approach for the full simulation of an Ion Beam Sputtering (IBS) coating process combining direct simulation Monte Carlo, classical molecular dynamics, kinetic Monte Carlo, and density functional theory. The simulation is performed exemplary for an existing IBS-coating plant to achieve a validation of the developed multi-scale approach. Finally, the modeled results are compared to experimental data. - Highlights: • A model approach for simulating an Ion Beam Sputtering (IBS) process is presented. • In order to combine the different techniques, optimized interfaces are developed. • The transport of atomic species in the coating chamber is calculated. • We modeled structural and optical film properties based on simulated IBS parameter. • The modeled and the experimental refractive index data fit very well.

  15. Prediction Approach of Critical Node Based on Multiple Attribute Decision Making for Opportunistic Sensor Networks

    Directory of Open Access Journals (Sweden)

    Qifan Chen

    2016-01-01

    Full Text Available Predicting critical nodes of Opportunistic Sensor Network (OSN can help us not only to improve network performance but also to decrease the cost in network maintenance. However, existing ways of predicting critical nodes in static network are not suitable for OSN. In this paper, the conceptions of critical nodes, region contribution, and cut-vertex in multiregion OSN are defined. We propose an approach to predict critical node for OSN, which is based on multiple attribute decision making (MADM. It takes RC to present the dependence of regions on Ferry nodes. TOPSIS algorithm is employed to find out Ferry node with maximum comprehensive contribution, which is a critical node. The experimental results show that, in different scenarios, this approach can predict the critical nodes of OSN better.

  16. A Key Event Path Analysis Approach for Integrated Systems

    Directory of Open Access Journals (Sweden)

    Jingjing Liao

    2012-01-01

    Full Text Available By studying the key event paths of probabilistic event structure graphs (PESGs, a key event path analysis approach for integrated system models is proposed. According to translation rules concluded from integrated system architecture descriptions, the corresponding PESGs are constructed from the colored Petri Net (CPN models. Then the definitions of cycle event paths, sequence event paths, and key event paths are given. Whereafter based on the statistic results after the simulation of CPN models, key event paths are found out by the sensitive analysis approach. This approach focuses on the logic structures of CPN models, which is reliable and could be the basis of structured analysis for discrete event systems. An example of radar model is given to characterize the application of this approach, and the results are worthy of trust.

  17. Combining results of multiple search engines in proteomics.

    Science.gov (United States)

    Shteynberg, David; Nesvizhskii, Alexey I; Moritz, Robert L; Deutsch, Eric W

    2013-09-01

    A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques.

  18. Combining Results of Multiple Search Engines in Proteomics*

    Science.gov (United States)

    Shteynberg, David; Nesvizhskii, Alexey I.; Moritz, Robert L.; Deutsch, Eric W.

    2013-01-01

    A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques. PMID:23720762

  19. Featureous: an Integrated Approach to Location, Analysis and Modularization of Features in Java Applications

    DEFF Research Database (Denmark)

    Olszak, Andrzej

    , it is essential that features are properly modularized within the structural organization of software systems. Nevertheless, in many object-oriented applications, features are not represented explicitly. Consequently, features typically end up scattered and tangled over multiple source code units......, such as architectural layers, packages and classes. This lack of modularization is known to make application features difficult to locate, to comprehend and to modify in isolation from one another. To overcome these problems, this thesis proposes Featureous, a novel approach to location, analysis and modularization...... quantitative and qualitative results suggest that Featureous succeeds at efficiently locating features in unfamiliar codebases, at aiding feature-oriented comprehension and modification, and at improving modularization of features using Java packages....

  20. A linear multiple balance method for discrete ordinates neutron transport equations

    International Nuclear Information System (INIS)

    Park, Chang Je; Cho, Nam Zin

    2000-01-01

    A linear multiple balance method (LMB) is developed to provide more accurate and positive solutions for the discrete ordinates neutron transport equations. In this multiple balance approach, one mesh cell is divided into two subcells with quadratic approximation of angular flux distribution. Four multiple balance equations are used to relate center angular flux with average angular flux by Simpson's rule. From the analysis of spatial truncation error, the accuracy of the linear multiple balance scheme is ο(Δ 4 ) whereas that of diamond differencing is ο(Δ 2 ). To accelerate the linear multiple balance method, we also describe a simplified additive angular dependent rebalance factor scheme which combines a modified boundary projection acceleration scheme and the angular dependent rebalance factor acceleration schme. It is demonstrated, via fourier analysis of a simple model problem as well as numerical calculations, that the additive angular dependent rebalance factor acceleration scheme is unconditionally stable with spectral radius < 0.2069c (c being the scattering ration). The numerical results tested so far on slab-geometry discrete ordinates transport problems show that the solution method of linear multiple balance is effective and sufficiently efficient

  1. A NOVEL APPROACH FOR 3D NEIGHBOURHOOD ANALYSIS

    Directory of Open Access Journals (Sweden)

    S. Emamgholian

    2017-09-01

    Full Text Available Population growth and lack of land in urban areas have caused massive developments such as high rises and underground infrastructures. Land authorities in the international context recognizes 3D cadastres as a solution to efficiently manage these developments in complex cities. Although a 2D cadastre does not efficiently register these developments, it is currently being used in many jurisdictions for registering land and property information. Limitations in analysis and presentation are considered as examples of such limitations. 3D neighbourhood analysis by automatically finding 3D spaces has become an issue of major interest in recent years. Whereas the neighbourhood analysis has been in the focus of research, the idea of 3D neighbourhood analysis has rarely been addressed in 3 dimensional information systems (3D GIS analysis. In this paper, a novel approach for 3D neighbourhood analysis has been proposed by recording spatial and descriptive information of the apartment units and easements. This approach uses the coordinates of the subject apartment unit to find the neighbour spaces. By considering a buffer around the edges of the unit, neighbour spaces are accurately detected. This method was implemented in ESRI ArcScene and three case studies were defined to test the efficiency of this approach. The results show that spaces are accurately detected in various complex scenarios. This approach can also be applied for other applications such as property management and disaster management in order to find the affected apartments around a defined space.

  2. Climate change, livelihoods and the multiple determinants of water adequacy: two approaches at regional to global scale

    Science.gov (United States)

    Lissner, Tabea; Reusser, Dominik

    2015-04-01

    Inadequate access to water is already a problem in many regions of the world and processes of global change are expected to further exacerbate the situation. Many aspects determine the adequacy of water resources: beside actual physical water stress, where the resource itself is limited, economic and social water stress can be experienced if access to resource is limited by inadequate infrastructure, political or financial constraints. To assess the adequacy of water availability for human use, integrated approaches are needed that allow to view the multiple determinants in conjunction and provide sound results as a basis for informed decisions. This contribution proposes two parts of an integrated approach to look at the multiple dimensions of water scarcity at regional to global scale. These were developed in a joint project with the German Development Agency (GIZ). It first outlines the AHEAD approach to measure Adequate Human livelihood conditions for wEll-being And Development, implemented at global scale and at national resolution. This first approach allows viewing impacts of climate change, e.g. changes in water availability, within the wider context of AHEAD conditions. A specific focus lies on the uncertainties in projections of climate change and future water availability. As adequate water access is not determined by water availability alone, in a second step we develop an approach to assess the water requirements for different sectors in more detail, including aspects of quantity, quality as well as access, in an integrated way. This more detailed approach is exemplified at region-scale in Indonesia and South Africa. Our results show that in many regions of the world, water scarcity is a limitation to AHEAD conditions in many countries, regardless of differing modelling output. The more detailed assessments highlight the relevance of additional aspects to assess the adequacy of water for human use, showing that in many regions, quality and

  3. Global Profiling and Novel Structure Discovery Using Multiple Neutral Loss/Precursor Ion Scanning Combined with Substructure Recognition and Statistical Analysis (MNPSS): Characterization of Terpene-Conjugated Curcuminoids in Curcuma longa as a Case Study.

    Science.gov (United States)

    Qiao, Xue; Lin, Xiong-hao; Ji, Shuai; Zhang, Zheng-xiang; Bo, Tao; Guo, De-an; Ye, Min

    2016-01-05

    To fully understand the chemical diversity of an herbal medicine is challenging. In this work, we describe a new approach to globally profile and discover novel compounds from an herbal extract using multiple neutral loss/precursor ion scanning combined with substructure recognition and statistical analysis. Turmeric (the rhizomes of Curcuma longa L.) was used as an example. This approach consists of three steps: (i) multiple neutral loss/precursor ion scanning to obtain substructure information; (ii) targeted identification of new compounds by extracted ion current and substructure recognition; and (iii) untargeted identification using total ion current and multivariate statistical analysis to discover novel structures. Using this approach, 846 terpecurcumins (terpene-conjugated curcuminoids) were discovered from turmeric, including a number of potentially novel compounds. Furthermore, two unprecedented compounds (terpecurcumins X and Y) were purified, and their structures were identified by NMR spectroscopy. This study extended the application of mass spectrometry to global profiling of natural products in herbal medicines and could help chemists to rapidly discover novel compounds from a complex matrix.

  4. Price competition and equilibrium analysis in multiple hybrid channel supply chain

    Science.gov (United States)

    Kuang, Guihua; Wang, Aihu; Sha, Jin

    2017-06-01

    The amazing boom of Internet and logistics industry prompts more and more enterprises to sell commodity through multiple channels. Such market conditions make the participants of multiple hybrid channel supply chain compete each other in traditional and direct channel at the same time. This paper builds a two-echelon supply chain model with a single manufacturer and a single retailer who both can choose different channel or channel combination for their own sales, then, discusses the price competition and calculates the equilibrium price under different sales channel selection combinations. Our analysis shows that no matter the manufacturer and retailer choose same or different channel price to compete, the equilibrium price does not necessarily exist the equilibrium price in the multiple hybrid channel supply chain and wholesale price change is not always able to coordinate supply chain completely. We also present the sufficient and necessary conditions for the existence of equilibrium price and coordination wholesale price.

  5. Propensity Score Analysis: An Alternative Statistical Approach for HRD Researchers

    Science.gov (United States)

    Keiffer, Greggory L.; Lane, Forrest C.

    2016-01-01

    Purpose: This paper aims to introduce matching in propensity score analysis (PSA) as an alternative statistical approach for researchers looking to make causal inferences using intact groups. Design/methodology/approach: An illustrative example demonstrated the varying results of analysis of variance, analysis of covariance and PSA on a heuristic…

  6. INCLUSION OF CHILDREN WITH INTELLECTUAL AND MULTIPLE DISABILITIES: A COMMUNITY-BASED REHABILITATION APPROACH, INDIA

    Directory of Open Access Journals (Sweden)

    Ram LAKHAN

    2013-03-01

    Full Text Available Background: Inclusion of children with intellectual disabilities (ID and multiple disabilities (MD in regular schools in India is extremely poor. One of the key objectives of community-based rehabilitation (CBR is to include ID & MD children in regular schools. This study attempted to find out association with age, ID severity, poverty, gender, parent education, population, and multiple disabilities comprising one or more disorders cerebral palsy, epilepsy and psychiatric disorders with inclusion among 259 children in Barwani Block of Barwani District in the state of Madhya Pradesh, India.Aim: Inclusion of children with intellectual and multiple disabilities in regular schools through CBR approach in India.Method: Chi square test was conducted to investigate association between inclusion and predictor variables ID categories, age, gender, poverty level, parent education, population type and multiple disabilities. Result: Inclusion was possible for borderline 2(66.4%, mild 54(68.3%, moderate 18(18.2%, and age range from 5 to 12 years 63 (43%. Children living in poor families 63 (30.6%, not poor 11(18.9%, parental edu­ca­ti­on none 52 (26%, primary level 11 (65%, midd­le school 10 (48% high school 0 (0% and bachelor degree 1(7%, female 34 (27.9%, male 40 (29.2%, tribal 40 (28.7%, non-tribal 34(28.3% and multiple disabled with cerebral palsy 1(1.2%, epilepsy 3 (4.8% and psychiatry disorders 12 (22.6% were able to receive inclusive education. Sig­ni­ficant difference in inclusion among ID ca­te­gories (c2=99.8, p < 0.001, poverty (c2=3.37, p 0.044, parental education (c2=23.7, p < 0.001, MD CP (c2=43.9, p < 0.001 and epilepsy (c2=22.4, p < 0.001 were seen.Conclusion: Inclusion through CBR is feasible and acceptable in poor rural settings in India. CBR can facilitate inclusion of children with borderline, mild and moderate categories by involving their parents, teachers and community members.

  7. Estimate the contribution of incubation parameters influence egg hatchability using multiple linear regression analysis.

    Science.gov (United States)

    Khalil, Mohamed H; Shebl, Mostafa K; Kosba, Mohamed A; El-Sabrout, Karim; Zaki, Nesma

    2016-08-01

    This research was conducted to determine the most affecting parameters on hatchability of indigenous and improved local chickens' eggs. Five parameters were studied (fertility, early and late embryonic mortalities, shape index, egg weight, and egg weight loss) on four strains, namely Fayoumi, Alexandria, Matrouh, and Montazah. Multiple linear regression was performed on the studied parameters to determine the most influencing one on hatchability. The results showed significant differences in commercial and scientific hatchability among strains. Alexandria strain has the highest significant commercial hatchability (80.70%). Regarding the studied strains, highly significant differences in hatching chick weight among strains were observed. Using multiple linear regression analysis, fertility made the greatest percent contribution (71.31%) to hatchability, and the lowest percent contributions were made by shape index and egg weight loss. A prediction of hatchability using multiple regression analysis could be a good tool to improve hatchability percentage in chickens.

  8. Weighted least-square approach for simultaneous measurement of multiple reflective surfaces

    Science.gov (United States)

    Tang, Shouhong; Bills, Richard E.; Freischlad, Klaus

    2007-09-01

    Phase shifting interferometry (PSI) is a highly accurate method for measuring the nanometer-scale relative surface height of a semi-reflective test surface. PSI is effectively used in conjunction with Fizeau interferometers for optical testing, hard disk inspection, and semiconductor wafer flatness. However, commonly-used PSI algorithms are unable to produce an accurate phase measurement if more than one reflective surface is present in the Fizeau interferometer test cavity. Examples of test parts that fall into this category include lithography mask blanks and their protective pellicles, and plane parallel optical beam splitters. The plane parallel surfaces of these parts generate multiple interferograms that are superimposed in the recording plane of the Fizeau interferometer. When using wavelength shifting in PSI the phase shifting speed of each interferogram is proportional to the optical path difference (OPD) between the two reflective surfaces. The proposed method is able to differentiate each underlying interferogram from each other in an optimal manner. In this paper, we present a method for simultaneously measuring the multiple test surfaces of all underlying interferograms from these superimposed interferograms through the use of a weighted least-square fitting technique. The theoretical analysis of weighted least-square technique and the measurement results will be described in this paper.

  9. Links between Bloom's Taxonomy and Gardener's Multiple Intelligences: The Issue of Textbook Analysis

    Science.gov (United States)

    Tabari, Mahmoud Abdi; Tabari, Iman Abdi

    2015-01-01

    The major thrust of this research was to investigate the cognitive aspect of the high school textbooks and interchange series, due to their extensive use, through content analysis based on Bloom's taxonomy and Gardner's Multiple Intelligences (MI). This study embraced two perspectives in a grid in order to broaden and deepen the analysis by…

  10. Stepwise approach to establishing multiple outreach laboratory information system-electronic medical record interfaces

    Directory of Open Access Journals (Sweden)

    Liron Pantanowitz

    2010-01-01

    Full Text Available Clinical laboratory outreach business is changing as more physician practices adopt an electronic medical record (EMR. Physician connectivity with the laboratory information system (LIS is consequently becoming more important. However, there are no reports available to assist the informatician with establishing and maintaining outreach LIS-EMR connectivity. A four-stage scheme is presented that was successfully employed to establish unidirectional and bidirectional interfaces with multiple physician EMRs. This approach involves planning (step 1, followed by interface building (step 2 with subsequent testing (step 3, and finally ongoing maintenance (step 4. The role of organized project management, software as a service (SAAS, and alternate solutions for outreach connectivity are discussed.

  11. An improved multiple linear regression and data analysis computer program package

    Science.gov (United States)

    Sidik, S. M.

    1972-01-01

    NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.

  12. Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes.

    Science.gov (United States)

    Achana, Felix A; Cooper, Nicola J; Bujkiewicz, Sylwia; Hubbard, Stephanie J; Kendrick, Denise; Jones, David R; Sutton, Alex J

    2014-07-21

    Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes. The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations. Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on

  13. Discourse Interpretation: A Deconstructive, Reader-oriented Approach to Critical Discourse Analysis

    Directory of Open Access Journals (Sweden)

    Ayman Farid Khafaga

    2017-01-01

    Full Text Available This paper is based on the premise that discourse is always under the influence of different ideological readings which not only formulate its meaning but inspire various interpretations as well; hence, it needs a theoretical cover that could justify its multiplicity of meaning. This paper, therefore, discusses the possibility of introducing a deconstructive, reader-oriented approach (DRA to Critical Discourse Analysis (CDA as a model of discourse interpretation. The paper tries to appraise the theoretical framework of CDA and to offer an overview of the fundamental propels of its interpretative task in the light of two poststructuralist literary theories: the deconstruction theory and the reception theory. The paper also endeavours to emphasize the deconstructive nature of CDA by shedding lights on its relationship with the above mentioned theories. The conclusion drawn from this paper shows that introducing a deconstructive, reader-oriented approach to CDA is relevant to the latter's interpretative nature enough to diminish a part of the criticism levelled against its interpretative framework concerning plurality of meaning; and to establish some sort of exoneration for its theoretical shortcomings. The paper recommends that DRA will bridge the gap between theory and practice as it offers a theoretical base to discourse which could advocate its critiques regarding diversity of interpretation.

  14. Treatments of Missing Values in Large National Data Affect Conclusions: The Impact of Multiple Imputation on Arthroplasty Research.

    Science.gov (United States)

    Ondeck, Nathaniel T; Fu, Michael C; Skrip, Laura A; McLynn, Ryan P; Su, Edwin P; Grauer, Jonathan N

    2018-03-01

    Despite the advantages of large, national datasets, one continuing concern is missing data values. Complete case analysis, where only cases with complete data are analyzed, is commonly used rather than more statistically rigorous approaches such as multiple imputation. This study characterizes the potential selection bias introduced using complete case analysis and compares the results of common regressions using both techniques following unicompartmental knee arthroplasty. Patients undergoing unicompartmental knee arthroplasty were extracted from the 2005 to 2015 National Surgical Quality Improvement Program. As examples, the demographics of patients with and without missing preoperative albumin and hematocrit values were compared. Missing data were then treated with both complete case analysis and multiple imputation (an approach that reproduces the variation and associations that would have been present in a full dataset) and the conclusions of common regressions for adverse outcomes were compared. A total of 6117 patients were included, of which 56.7% were missing at least one value. Younger, female, and healthier patients were more likely to have missing preoperative albumin and hematocrit values. The use of complete case analysis removed 3467 patients from the study in comparison with multiple imputation which included all 6117 patients. The 2 methods of handling missing values led to differing associations of low preoperative laboratory values with commonly studied adverse outcomes. The use of complete case analysis can introduce selection bias and may lead to different conclusions in comparison with the statistically rigorous multiple imputation approach. Joint surgeons should consider the methods of handling missing values when interpreting arthroplasty research. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. Neutron-multiplication measurement instrument

    Energy Technology Data Exchange (ETDEWEB)

    Nixon, K.V.; Dowdy, E.J.; France, S.W.; Millegan, D.R.; Robba, A.A.

    1982-01-01

    The Advanced Nuclear Technology Group of the Los Alamos National Laboratory is now using intelligent data-acquisition and analysis instrumentation for determining the multiplication of nuclear material. Earlier instrumentation, such as the large NIM-crate systems, depended on house power and required additional computation to determine multiplication or to estimate error. The portable, battery-powered multiplication measurement unit, with advanced computational power, acquires data, calculates multiplication, and completes error analysis automatically. Thus, the multiplication is determined easily and an available error estimate enables the user to judge the significance of results.

  16. Neutron multiplication measurement instrument

    International Nuclear Information System (INIS)

    Nixon, K.V.; Dowdy, E.J.; France, S.W.; Millegan, D.R.; Robba, A.A.

    1983-01-01

    The Advanced Nuclear Technology Group of the Los Alamos National Laboratory is now using intelligent data-acquisition and analysis instrumentation for determining the multiplication of nuclear material. Earlier instrumentation, such as the large NIM-crate systems, depended on house power and required additional computation to determine multiplication or to estimate error. The portable, battery-powered multiplication measurement unit, with advanced computational power, acquires data, calculates multiplication, and completes error analysis automatically. Thus, the multiplication is determined easily and an available error estimate enables the user to judge the significance of results

  17. Neutron-multiplication measurement instrument

    International Nuclear Information System (INIS)

    Nixon, K.V.; Dowdy, E.J.; France, S.W.; Millegan, D.R.; Robba, A.A.

    1982-01-01

    The Advanced Nuclear Technology Group of the Los Alamos National Laboratory is now using intelligent data-acquisition and analysis instrumentation for determining the multiplication of nuclear material. Earlier instrumentation, such as the large NIM-crate systems, depended on house power and required additional computation to determine multiplication or to estimate error. The portable, battery-powered multiplication measurement unit, with advanced computational power, acquires data, calculates multiplication, and completes error analysis automatically. Thus, the multiplication is determined easily and an available error estimate enables the user to judge the significance of results

  18. Measuring multiple nano-textured areas simultaneously with imaging scatterometry

    DEFF Research Database (Denmark)

    Madsen, Jonas Skovlund; Hansen, Poul Erik; Bilenberg, Brian

    2017-01-01

    and areas with defects can be avoided. These advantages make imaging scatterometry a very effective and user-friendly characterization method and allow us to determine the homogeneity of a nano- Textured surface by performing pixel-wise analyses. In the analysis an inverse modelling approach is used, where...... measured diffraction efficiencies are compared to simulated diffraction efficiencies using a least-square fitting approach. We demonstrate an imaging scatterometry setup built into an optical microscope. The setup is capable of measuring multiple 2D gratings with pitches of 200 nm simultaneously...

  19. Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research.

    Science.gov (United States)

    Golino, Hudson F; Epskamp, Sacha

    2017-01-01

    The estimation of the correct number of dimensions is a long-standing problem in psychometrics. Several methods have been proposed, such as parallel analysis (PA), Kaiser-Guttman's eigenvalue-greater-than-one rule, multiple average partial procedure (MAP), the maximum-likelihood approaches that use fit indexes as BIC and EBIC and the less used and studied approach called very simple structure (VSS). In the present paper a new approach to estimate the number of dimensions will be introduced and compared via simulation to the traditional techniques pointed above. The approach proposed in the current paper is called exploratory graph analysis (EGA), since it is based on the graphical lasso with the regularization parameter specified using EBIC. The number of dimensions is verified using the walktrap, a random walk algorithm used to identify communities in networks. In total, 32,000 data sets were simulated to fit known factor structures, with the data sets varying across different criteria: number of factors (2 and 4), number of items (5 and 10), sample size (100, 500, 1000 and 5000) and correlation between factors (orthogonal, .20, .50 and .70), resulting in 64 different conditions. For each condition, 500 data sets were simulated using lavaan. The result shows that the EGA performs comparable to parallel analysis, EBIC, eBIC and to Kaiser-Guttman rule in a number of situations, especially when the number of factors was two. However, EGA was the only technique able to correctly estimate the number of dimensions in the four-factor structure when the correlation between factors were .7, showing an accuracy of 100% for a sample size of 5,000 observations. Finally, the EGA was used to estimate the number of factors in a real dataset, in order to compare its performance with the other six techniques tested in the simulation study.

  20. Optimal assignment of multiple utilities in heat exchange networks

    International Nuclear Information System (INIS)

    Salama, A.I.A.

    2009-01-01

    Existing numerical geometry-based techniques, developed by [A.I.A. Salama, Numerical techniques for determining heat energy targets in pinch analysis, Computers and Chemical Engineering 29 (2005) 1861-1866; A.I.A. Salama, Determination of the optimal heat energy targets in heat pinch analysis using a geometry-based approach, Computers and Chemical Engineering 30 (2006) 758-764], have been extended to optimally assign multiple utilities in heat exchange network (HEN). These techniques utilize the horizontal shift between the cold composite curve (CC) and the stationary hot CC to determine the HEN optimal energy targets, grand composite curve (GCC), and the complement grand composite curve (CGCC). The proposed numerical technique developed in this paper is direct and simultaneously determines the optimal heat-energy targets and optimally assigns multiple utilities as compared with an existing technique based on sequential assignment of multiple utilities. The technique starts by arranging in an ascending order the HEN stream and target temperatures, and the resulting set is labelled T. Furthermore, the temperature sets where multiple utilities are introduced are arranged in an ascending order and are labelled T ic and T ih for the cold and hot sides, respectively. The graphical presentation of the results is facilitated by the insertion at each multiple-utility temperature a perturbed temperature equals the insertion temperature minus a small perturbation. Furthermore, using the heat exchanger network (HEN) minimum temperature-differential approach (ΔT min ) and stream heat-capacity flow rates, the presentation is facilitated by using the conventional temperature shift of the HEN CCs. The set of temperature-shifted stream and target temperatures and perturbed temperatures in the overlap range between the CCs is labelled T ol . Using T ol , a simple formula employing enthalpy-flow differences between the hot composite curve CC h and the cold composite curve CC c is

  1. A Novel Approach to Beam Steering Using Arrays Composed of Multiple Unique Radiating Modes

    Science.gov (United States)

    Labadie, Nathan Richard

    Phased array antennas have found wide application in both radar and wireless communications systems particularly as implementation costs continue to decrease. The primary advantages of electronically scanned arrays are speed of beam scan and versatility of beamforming compared to mechanically scanned fixed beam antennas. These benefits come at the cost of a few well known design issues including element pattern rolloff and mutual coupling between elements. Our primary contribution to the field of research is the demonstration of significant improvement in phased array scan performance using multiple unique radiating modes. In short, orthogonal radiating modes have minimal coupling by definition and can also be generated with reduced rolloff at wide scan angles. In this dissertation, we present a combination of analysis, full-wave electromagnetic simulation and measured data to support our claims. The novel folded ring resonator (FRR) antenna is introduced as a wideband and multi-band element embedded in a grounded dielectric substrate. Multiple radiating modes of a small ground plane excited by a four element FRR array were also investigated. A novel hemispherical null steering antenna composed of two collocated radiating elements, each supporting a unique radiating mode, is presented in the context of an anti-jam GPS receiver application. Both the antenna aperture and active feed network were fabricated and measured showing excellent agreement with analytical and simulated data. The concept of using an antenna supporting multiple radiating modes for beam steering is also explored. A 16 element hybrid linear phased array was fabricated and measured demonstrating significantly improved scan range and scanned gain compared to a conventional phased array. This idea is expanded to 2 dimensional scanning arrays by analysis and simulation of a hybrid phased array composed of novel multiple mode monopole on patch antenna sub-arrays. Finally, we fabricated and

  2. Ca analysis: an Excel based program for the analysis of intracellular calcium transients including multiple, simultaneous regression analysis.

    Science.gov (United States)

    Greensmith, David J

    2014-01-01

    Here I present an Excel based program for the analysis of intracellular Ca transients recorded using fluorescent indicators. The program can perform all the necessary steps which convert recorded raw voltage changes into meaningful physiological information. The program performs two fundamental processes. (1) It can prepare the raw signal by several methods. (2) It can then be used to analyze the prepared data to provide information such as absolute intracellular Ca levels. Also, the rates of change of Ca can be measured using multiple, simultaneous regression analysis. I demonstrate that this program performs equally well as commercially available software, but has numerous advantages, namely creating a simplified, self-contained analysis workflow. Copyright © 2013 The Author. Published by Elsevier Ireland Ltd.. All rights reserved.

  3. Multiple predictor smoothing methods for sensitivity analysis: Example results

    International Nuclear Information System (INIS)

    Storlie, Curtis B.; Helton, Jon C.

    2008-01-01

    The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described in the first part of this presentation: (i) locally weighted regression (LOESS), (ii) additive models, (iii) projection pursuit regression, and (iv) recursive partitioning regression. In this, the second and concluding part of the presentation, the indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present

  4. Multiple-Use Services as an Alternative to Rural Water Supply Services: A Characterisation of the Approach

    Directory of Open Access Journals (Sweden)

    Stef Smits

    2010-02-01

    Full Text Available Multiple-use services (MUS have recently gained increased attention as an alternative form of providing rural water services in an integrated manner. This stems from the growing recognition that users anyway tend to use water systems for multiple purposes. This paper aims to characterise this practice on the basis of case evidence collected in eight countries in Africa, Asia and Latin America. The cases show that people almost universally use water for both domestic and productive activities at and around the homestead. Although seldom the main source of people’s income or food production, these activities are of considerable importance for people’s livelihoods. The extent to which people use water for multiple purposes is closely related to the level of access to water expressed in the form of a water ladder in this paper. The case studies presented demonstrate how access is created by different types and combinations of well-known technologies. Additional financial and management measures are required to ensure sustainability of services. Despite the practical feasibility of the MUS approach, it is not yet widely applied by service providers and sector agencies due to observed barriers in institutional uptake. A better characterisation of MUS, alongside a learning-driven stakeholder process was able to overcome some of these barriers and improve the consideration of multiple uses of water in policy and practice.

  5. Analysis of underlying and multiple-cause mortality data.

    Science.gov (United States)

    Moussa, M A; El Sayed, A M; Sugathan, T N; Khogali, M M; Verma, D

    1992-01-01

    "A variety of life table models were used for the analysis of the (1984-86) Kuwaiti cause-specific mortality data. These models comprised total mortality, multiple-decrement, cause-elimination, cause-delay and disease dependency. The models were illustrated by application to a set of four chronic diseases: hypertensive, ischaemic heart, cerebrovascular and diabetes mellitus. The life table methods quantify the relative weights of different diseases as hazards to mortality after adjustment for other causes. They can also evaluate the extent of dependency between underlying cause of death and other causes mentioned on [the] death certificate using an extended underlying-cause model." (SUMMARY IN FRE AND ITA) excerpt

  6. Convergence Analysis for the Multiplicative Schwarz Preconditioned Inexact Newton Algorithm

    KAUST Repository

    Liu, Lulu

    2016-10-26

    The multiplicative Schwarz preconditioned inexact Newton (MSPIN) algorithm, based on decomposition by field type rather than by subdomain, was recently introduced to improve the convergence of systems with unbalanced nonlinearities. This paper provides a convergence analysis of the MSPIN algorithm. Under reasonable assumptions, it is shown that MSPIN is locally convergent, and desired superlinear or even quadratic convergence can be obtained when the forcing terms are picked suitably.

  7. Convergence Analysis for the Multiplicative Schwarz Preconditioned Inexact Newton Algorithm

    KAUST Repository

    Liu, Lulu; Keyes, David E.

    2016-01-01

    The multiplicative Schwarz preconditioned inexact Newton (MSPIN) algorithm, based on decomposition by field type rather than by subdomain, was recently introduced to improve the convergence of systems with unbalanced nonlinearities. This paper provides a convergence analysis of the MSPIN algorithm. Under reasonable assumptions, it is shown that MSPIN is locally convergent, and desired superlinear or even quadratic convergence can be obtained when the forcing terms are picked suitably.

  8. mma: An R Package for Mediation Analysis with Multiple Mediators

    OpenAIRE

    Qingzhao Yu; Bin Li

    2017-01-01

    Mediation refers to the effect transmitted by mediators that intervene in the relationship between an exposure and a response variable. Mediation analysis has been broadly studied in many fields. However, it remains a challenge for researchers to consider complicated associations among variables and to differentiate individual effects from multiple mediators. [1] proposed general definitions of mediation effects that were adaptable to all different types of response (categorical or continuous...

  9. Spinal focal lesion detection in multiple myeloma using multimodal image features

    Science.gov (United States)

    Fränzle, Andrea; Hillengass, Jens; Bendl, Rolf

    2015-03-01

    Multiple myeloma is a tumor disease in the bone marrow that affects the skeleton systemically, i.e. multiple lesions can occur in different sites in the skeleton. To quantify overall tumor mass for determining degree of disease and for analysis of therapy response, volumetry of all lesions is needed. Since the large amount of lesions in one patient impedes manual segmentation of all lesions, quantification of overall tumor volume is not possible until now. Therefore development of automatic lesion detection and segmentation methods is necessary. Since focal tumors in multiple myeloma show different characteristics in different modalities (changes in bone structure in CT images, hypointensity in T1 weighted MR images and hyperintensity in T2 weighted MR images), multimodal image analysis is necessary for the detection of focal tumors. In this paper a pattern recognition approach is presented that identifies focal lesions in lumbar vertebrae based on features from T1 and T2 weighted MR images. Image voxels within bone are classified using random forests based on plain intensities and intensity value derived features (maximum, minimum, mean, median) in a 5 x 5 neighborhood around a voxel from both T1 and T2 weighted MR images. A test data sample of lesions in 8 lumbar vertebrae from 4 multiple myeloma patients can be classified at an accuracy of 95% (using a leave-one-patient-out test). The approach provides a reasonable delineation of the example lesions. This is an important step towards automatic tumor volume quantification in multiple myeloma.

  10. An approach to evaluating alternatives for wind power plant locations

    Directory of Open Access Journals (Sweden)

    Rehman, Ateekh Ur

    2016-12-01

    Full Text Available Multi-criteria decision approaches are preferred for achieving multi-dimensional sustainable renewable energy goals. A more critical issue faced by the wind power industry is the selection of a location to tap prospective energy, which needs to be evaluated on multiple measures. In this paper, the aim is to assess and rank alternative wind power plant locations in Saudi Arabia. The approach presented here takes multiple criteria into consideration, such as wind speed, wind availability, site advantages, terrain details, risk and uncertainty, technology used, third party support, projected demand, types of customers, and government policies. A comparative analysis of feasible alternatives that satisfy all multi- criteria objectives is carried out. The results obtained are subjected to sensitivity analysis. Concepts such as ‘threshold values’ and ‘attribute weights’ make the approach more sensitive.

  11. Stability Properties of Network Diversity Multiple Access with Multiple-Antenna Reception and Imperfect Collision Multiplicity Estimation

    Directory of Open Access Journals (Sweden)

    Ramiro Samano-Robles

    2013-01-01

    Full Text Available In NDMA (network diversity multiple access, protocol-controlled retransmissions are used to create a virtual MIMO (multiple-input multiple-output system, where collisions can be resolved via source separation. By using this retransmission diversity approach for collision resolution, NDMA is the family of random access protocols with the highest potential throughput. However, several issues remain open today in the modeling and design of this type of protocol, particularly in terms of dynamic stable performance and backlog delay. This paper attempts to partially fill this gap by proposing a Markov model for the study of the dynamic-stable performance of a symmetrical and non-blind NDMA protocol assisted by a multiple-antenna receiver. The model is useful in the study of stability aspects in terms of the backlog-user distribution and average backlog delay. It also allows for the investigation of the different states of the system and the transition probabilities between them. Unlike previous works, the proposed approach considers the imperfect estimation of the collision multiplicity, which is a crucial process to the performance of NDMA. The results suggest that NDMA improves not only the throughput performance over previous solutions, but also the average number of backlogged users, the average backlog delay and, in general, the stability of random access protocols. It is also shown that when multiuser detection conditions degrade, ALOHA-type backlog retransmission becomes relevant to the stable operation of NDMA.

  12. Common approach of risks analysis

    International Nuclear Information System (INIS)

    Noviello, L.; Naviglio, A.

    1996-01-01

    Although, following the resolutions of the High German Court, the protection level of the human beings is an objective which can change in time, it is obvious that it is an important point when there is a risk for the population. This is true more particularly for the industrial plants whose possible accidents could affect the population. The accidents risk analysis indicates that there is no conceptual difference between the risks of a nuclear power plant and those of the other industrial plants as chemical plants, the gas distribution system and the hydraulic dams. A legislation analysis induced by the Seveso Directive for the industrial risks give some important indications which should always be followed. This work analyses more particularly the legislative situation in different European countries and identifies some of the most important characteristics. Indeed, for most of the countries, the situation is different and it is a later difficulties source for nuclear power plants. In order to strengthen this reasoning, this paper presents some preliminary results of an analysis of a nuclear power plant following the approach of other industrial plants. In conclusion, it will be necessary to analyse again the risks assessment approach for nuclear power plants because the real protection level of human beings in a country is determined by the less regulated of the dangerous industrial plants existing at the surroundings. (O.M.)

  13. Links between Bloom's Taxonomy and Gardener's Multiple Intelligences: The issue of Textbook Analysis

    Directory of Open Access Journals (Sweden)

    Mahmoud Abdi Tabari

    2015-02-01

    Full Text Available The major thrust of this research was to investigate the cognitive aspect of the high school textbooks and interchange series, due to their extensive use, through content analysis based on Bloom's taxonomy and Gardner's Multiple Intelligences (MI. This study embraced two perspectives in a grid in order to broaden and deepen the analysis by determining the numbers and the types of intelligences with respect to their learning objectives tapped in the textbooks and comparing them. Through codification of Bloom’s learning objectives and Gardner's MI, the results showed that there was a significant difference between the numbers of intelligences with respect to their learning objectives in the textbooks. However, the interchange series enjoyed a large number of the spatial and the interpersonal intelligences across eight levels of learning objectives, whereas they had the least number of the intrapersonal, the musical, and the bodily-kinesthetic intelligences across knowledge understanding and application levels. Keywords: learning objectives, multiple intelligences, textbook analysis

  14. Probabilistic approaches for geotechnical site characterization and slope stability analysis

    CERN Document Server

    Cao, Zijun; Li, Dianqing

    2017-01-01

    This is the first book to revisit geotechnical site characterization from a probabilistic point of view and provide rational tools to probabilistically characterize geotechnical properties and underground stratigraphy using limited information obtained from a specific site. This book not only provides new probabilistic approaches for geotechnical site characterization and slope stability analysis, but also tackles the difficulties in practical implementation of these approaches. In addition, this book also develops efficient Monte Carlo simulation approaches for slope stability analysis and implements these approaches in a commonly available spreadsheet environment. These approaches and the software package are readily available to geotechnical practitioners and alleviate them from reliability computational algorithms. The readers will find useful information for a non-specialist to determine project-specific statistics of geotechnical properties and to perform probabilistic analysis of slope stability.

  15. Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach.

    Science.gov (United States)

    Chandrasekar, A; Rakkiyappan, R; Cao, Jinde

    2015-10-01

    This paper studies the impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. The array of neural networks are coupled in a random fashion which is governed by Bernoulli random variable. The aim of this paper is to obtain the synchronization criteria, which is suitable for both exactly known and partly unknown transition probabilities such that the coupled neural network is synchronized with mixed time-delay. The considered impulsive effects can be synchronized at partly unknown transition probabilities. Besides, a multiple integral approach is also proposed to strengthen the Markovian jumping randomly coupled neural networks with partly unknown transition probabilities. By making use of Kronecker product and some useful integral inequalities, a novel Lyapunov-Krasovskii functional was designed for handling the coupled neural network with mixed delay and then impulsive synchronization criteria are solvable in a set of linear matrix inequalities. Finally, numerical examples are presented to illustrate the effectiveness and advantages of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation.

    Science.gov (United States)

    Lin, Yu-Pin; Chu, Hone-Jay; Huang, Yu-Long; Tang, Chia-Hsi; Rouhani, Shahrokh

    2011-06-01

    This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.

  17. A simplified calculation procedure for mass isotopomer distribution analysis (MIDA) based on multiple linear regression.

    Science.gov (United States)

    Fernández-Fernández, Mario; Rodríguez-González, Pablo; García Alonso, J Ignacio

    2016-10-01

    We have developed a novel, rapid and easy calculation procedure for Mass Isotopomer Distribution Analysis based on multiple linear regression which allows the simultaneous calculation of the precursor pool enrichment and the fraction of newly synthesized labelled proteins (fractional synthesis) using linear algebra. To test this approach, we used the peptide RGGGLK as a model tryptic peptide containing three subunits of glycine. We selected glycine labelled in two 13 C atoms ( 13 C 2 -glycine) as labelled amino acid to demonstrate that spectral overlap is not a problem in the proposed methodology. The developed methodology was tested first in vitro by changing the precursor pool enrichment from 10 to 40% of 13 C 2 -glycine. Secondly, a simulated in vivo synthesis of proteins was designed by combining the natural abundance RGGGLK peptide and 10 or 20% 13 C 2 -glycine at 1 : 1, 1 : 3 and 3 : 1 ratios. Precursor pool enrichments and fractional synthesis values were calculated with satisfactory precision and accuracy using a simple spreadsheet. This novel approach can provide a relatively rapid and easy means to measure protein turnover based on stable isotope tracers. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  18. Discussion on safety analysis approach for sodium fast reactors

    International Nuclear Information System (INIS)

    Hong, Soon Joon; Choo, Yeon Joon; Suh, Nam Duk; Shin, Ahn Dong; Bae, Moo Hoon

    2012-01-01

    Utilization of nuclear energy is increasingly necessary not only because of the increasing energy consumption but also because of the controls on greenhouse emissions against global warming. To keep step with such demands, advanced reactors are now world widely under development with the aims of highly economical advances, and enhanced safety. Recently, further elaborating is encouraged on the research and development program for Generation IV (GEN IV) reactors, and in collaboration with other interested countries through the Generation IV International Forum (GIF). Sodium cooled Fast Reactor (SFR) is a strong contender amongst the GEN IV reactor concepts. Korea also takes part in that program and plans to construct demonstration reactor of SFR. SFR is under the development for a candidate of small modular reactors, for example, PRISM (Power Reactor Innovative Small Module). Understanding of safety analysis approach has also advanced by the demand of increasing comprehensive safety requirement. Reviewing the past development of the licensing and safety basis in the advanced reactors, such approaches seemed primarily not so satisfactory because the reference framework of licensing and safety analysis approach in the advanced reactors was always the one in water reactors. And, the framework is very plant specific one and thereby the advanced reactors and their frameworks don't look like a well assorted couple. Recently as a result of considerable advances in probabilistic safety assessment (PSA), risk informed approaches are increasingly applied together with some of the deterministic approaches like as the ones in water reactors. Technology neutral framework (TNF) can be said to be the utmost works of such risk informed approaches, even though an intensive assessment of the applicability has not been sufficiently accomplished. This study discusses the viable safety analysis approaches for the urgent application to the construction of pool type SFR. As discussed in

  19. Development of a System Analysis Toolkit for Sensitivity Analysis, Uncertainty Propagation, and Estimation of Parameter Distribution

    International Nuclear Information System (INIS)

    Heo, Jaeseok; Kim, Kyung Doo

    2015-01-01

    Statistical approaches to uncertainty quantification and sensitivity analysis are very important in estimating the safety margins for an engineering design application. This paper presents a system analysis and optimization toolkit developed by Korea Atomic Energy Research Institute (KAERI), which includes multiple packages of the sensitivity analysis and uncertainty quantification algorithms. In order to reduce the computing demand, multiple compute resources including multiprocessor computers and a network of workstations are simultaneously used. A Graphical User Interface (GUI) was also developed within the parallel computing framework for users to readily employ the toolkit for an engineering design and optimization problem. The goal of this work is to develop a GUI framework for engineering design and scientific analysis problems by implementing multiple packages of system analysis methods in the parallel computing toolkit. This was done by building an interface between an engineering simulation code and the system analysis software packages. The methods and strategies in the framework were designed to exploit parallel computing resources such as those found in a desktop multiprocessor workstation or a network of workstations. Available approaches in the framework include statistical and mathematical algorithms for use in science and engineering design problems. Currently the toolkit has 6 modules of the system analysis methodologies: deterministic and probabilistic approaches of data assimilation, uncertainty propagation, Chi-square linearity test, sensitivity analysis, and FFTBM

  20. Development of a System Analysis Toolkit for Sensitivity Analysis, Uncertainty Propagation, and Estimation of Parameter Distribution

    Energy Technology Data Exchange (ETDEWEB)

    Heo, Jaeseok; Kim, Kyung Doo [KAERI, Daejeon (Korea, Republic of)

    2015-05-15

    Statistical approaches to uncertainty quantification and sensitivity analysis are very important in estimating the safety margins for an engineering design application. This paper presents a system analysis and optimization toolkit developed by Korea Atomic Energy Research Institute (KAERI), which includes multiple packages of the sensitivity analysis and uncertainty quantification algorithms. In order to reduce the computing demand, multiple compute resources including multiprocessor computers and a network of workstations are simultaneously used. A Graphical User Interface (GUI) was also developed within the parallel computing framework for users to readily employ the toolkit for an engineering design and optimization problem. The goal of this work is to develop a GUI framework for engineering design and scientific analysis problems by implementing multiple packages of system analysis methods in the parallel computing toolkit. This was done by building an interface between an engineering simulation code and the system analysis software packages. The methods and strategies in the framework were designed to exploit parallel computing resources such as those found in a desktop multiprocessor workstation or a network of workstations. Available approaches in the framework include statistical and mathematical algorithms for use in science and engineering design problems. Currently the toolkit has 6 modules of the system analysis methodologies: deterministic and probabilistic approaches of data assimilation, uncertainty propagation, Chi-square linearity test, sensitivity analysis, and FFTBM.

  1. Analysis of stability and quench in HTS devices-New approaches

    International Nuclear Information System (INIS)

    Vysotsky, V.S.; Sytnikov, V.E.; Rakhmanov, A.L.; Ilyin, Y.

    2006-01-01

    R and D of HTS devices are in their full steam-more magnets and devices are developed with larger sizes. But analysis of their stability and quench was still old fashioned, based on normal zone determination, analysis of its appearance and propagation. Some peculiarities of HTS make this traditional, quite impractical and inconvenient approach to consideration of HTS devices stability and quench development using normal zone origination and propagation analysis. The novel approaches were developed that consider the HTS device as a cooled medium with non-linear parameters with no mentioning of 'superconductivity' in the analysis. The approach showed its effectiveness and convenience to analyze the stability and quench development in HTS devices. In this paper the analysis of difference between HTS and LTS quench, dependent on index n and specific heat comparison, is followed by the short approach descriptions and by the consequences from it for the HTS devices design. The further development of the method is presented for the analysis of long HTS objects where 'blow-up' regimes may happen. This is important for design and analysis of HTS power cables operations under overloading conditions

  2. A non-parametric meta-analysis approach for combining independent microarray datasets: application using two microarray datasets pertaining to chronic allograft nephropathy

    Directory of Open Access Journals (Sweden)

    Archer Kellie J

    2008-02-01

    Full Text Available Abstract Background With the popularity of DNA microarray technology, multiple groups of researchers have studied the gene expression of similar biological conditions. Different methods have been developed to integrate the results from various microarray studies, though most of them rely on distributional assumptions, such as the t-statistic based, mixed-effects model, or Bayesian model methods. However, often the sample size for each individual microarray experiment is small. Therefore, in this paper we present a non-parametric meta-analysis approach for combining data from independent microarray studies, and illustrate its application on two independent Affymetrix GeneChip studies that compared the gene expression of biopsies from kidney transplant recipients with chronic allograft nephropathy (CAN to those with normal functioning allograft. Results The simulation study comparing the non-parametric meta-analysis approach to a commonly used t-statistic based approach shows that the non-parametric approach has better sensitivity and specificity. For the application on the two CAN studies, we identified 309 distinct genes that expressed differently in CAN. By applying Fisher's exact test to identify enriched KEGG pathways among those genes called differentially expressed, we found 6 KEGG pathways to be over-represented among the identified genes. We used the expression measurements of the identified genes as predictors to predict the class labels for 6 additional biopsy samples, and the predicted results all conformed to their pathologist diagnosed class labels. Conclusion We present a new approach for combining data from multiple independent microarray studies. This approach is non-parametric and does not rely on any distributional assumptions. The rationale behind the approach is logically intuitive and can be easily understood by researchers not having advanced training in statistics. Some of the identified genes and pathways have been

  3. Introduction to Real Analysis An Educational Approach

    CERN Document Server

    Bauldry, William C

    2011-01-01

    An accessible introduction to real analysis and its connection to elementary calculus Bridging the gap between the development and history of real analysis, Introduction to Real Analysis: An Educational Approach presents a comprehensive introduction to real analysis while also offering a survey of the field. With its balance of historical background, key calculus methods, and hands-on applications, this book provides readers with a solid foundation and fundamental understanding of real analysis. The book begins with an outline of basic calculus, including a close examination of problems illust

  4. Certain theories of multiple scattering in random media of discrete scatterers

    International Nuclear Information System (INIS)

    Olsen, R.L.; Kharadly, M.M.Z.; Corr, D.G.

    1976-01-01

    New information is presented on the accuracy of the heuristic approximations in two important theories of multiple scattering in random media of discrete scatterers: Twersky's ''free-space'' and ''two-space scatterer'' formalisms. Two complementary approaches, based primarily on a one-dimensional model and the one-dimensional forms of the theories, are used. For scatterer distributions of low average density, the ''heuristic'' asymptotic forms for the coherent field and the incoherent intensity are compared with asymptotic forms derived from a systematic analysis of the multiple scattering processes. For distributions of higher density, both in the average number of scatterers per wavelength and in the degree of packing of finite-size scatterers, the analysis is carried out ''experimentally'' by means of a Monte Carlo computer simulation. Approximate series expressions based on the systematic approach are numerically evaluated along with the heuristic expressions. The comparison (for both forward- and back-scattered field moments) is made for the worst-case conditions of strong multiple scattering for which the theories have not previously been evaluated. Several significant conclusions are drawn which have certain practical implications: in application of the theories to describe some of the scattering phenomena which occur in the troposphere, and in the further evaluation of the theories using experiments on physical models

  5. On Multiple Appearances

    DEFF Research Database (Denmark)

    Bork Petersen, Franziska

    2012-01-01

    reduction and epoché to focus on how dancing bodies appear in a stage context. To test these tools’ ability to explore dancing bodies from a third-person perspective, I analyse the Danish choreographer Kitt Johnson’s solo performance Drift (2011) - focussing on her shifting physical appearance. While...... phenomenology helps me to describe the multiple and radically different guises that Johnson assumes in her piece, my analysis, ultimately, does not aim to distil a truer, more real being from her appearances as is often the case in phenomenological philosophy. I complement my analytical approach...... with the Deleuzian notion of becoming animal and suggest that Johnson stages what could, in Judith Butler’s terms, be called a critical contingency of bodily appearance....

  6. Meta-Analysis for Sociology – A Measure-Driven Approach

    Science.gov (United States)

    Roelfs, David J.; Shor, Eran; Falzon, Louise; Davidson, Karina W.; Schwartz, Joseph E.

    2013-01-01

    Meta-analytic methods are becoming increasingly important in sociological research. In this article we present an approach for meta-analysis which is especially helpful for sociologists. Conventional approaches to meta-analysis often prioritize “concept-driven” literature searches. However, in disciplines with high theoretical diversity, such as sociology, this search approach might constrain the researcher’s ability to fully exploit the entire body of relevant work. We explicate a “measure-driven” approach, in which iterative searches and new computerized search techniques are used to increase the range of publications found (and thus the range of possible analyses) and to traverse time and disciplinary boundaries. We demonstrate this measure-driven search approach with two meta-analytic projects, examining the effects of various social variables on all-cause mortality. PMID:24163498

  7. Multiple intelligence: ethical leadership feature consistent financial institutions.

    Directory of Open Access Journals (Sweden)

    Diamela Nava

    2015-03-01

    Full Text Available This study aims to make a theoretical underpinning contrast analysis on the multiple intelligences: consistent feature of Ethical Leadership in Financial Institutions. However, this research was conducted under a qualitative approach, a descriptive, using document analysis, which eventually might be considered that would support multiple intelligences to implement certain capabilities, to achieve the objectives with the purpose and from the rational point of view, to know how to establish significant changes in some ways it is, the way to assess the cognitive abilities of integrating human talent in organizations. Therefore, the role of the leader is to guide and support the development of human potential in their group as a community of interest in order to achieve the aspirations of the organization using intelligence as a strategic tool in different ways to not limit your imagination, judgment, and cooperative action.  

  8. Multiple approaches to microbial source tracking in tropical northern Australia

    KAUST Repository

    Neave, Matthew

    2014-09-16

    Microbial source tracking is an area of research in which multiple approaches are used to identify the sources of elevated bacterial concentrations in recreational lakes and beaches. At our study location in Darwin, northern Australia, water quality in the harbor is generally good, however dry-season beach closures due to elevated Escherichia coli and enterococci counts are a cause for concern. The sources of these high bacteria counts are currently unknown. To address this, we sampled sewage outfalls, other potential inputs, such as urban rivers and drains, and surrounding beaches, and used genetic fingerprints from E. coli and enterococci communities, fecal markers and 454 pyrosequencing to track contamination sources. A sewage effluent outfall (Larrakeyah discharge) was a source of bacteria, including fecal bacteria that impacted nearby beaches. Two other treated effluent discharges did not appear to influence sites other than those directly adjacent. Several beaches contained fecal indicator bacteria that likely originated from urban rivers and creeks within the catchment. Generally, connectivity between the sites was observed within distinct geographical locations and it appeared that most of the bacterial contamination on Darwin beaches was confined to local sources.

  9. Superresolution Imaging Using Resonant Multiples and Plane-wave Migration Velocity Analysis

    KAUST Repository

    Guo, Bowen

    2017-08-28

    Seismic imaging is a technique that uses seismic echoes to map and detect underground geological structures. The conventional seismic image has the resolution limit of λ/2, where λ is the wavelength associated with the seismic waves propagating in the subsurface. To exceed this resolution limit, this thesis develops a new imaging method using resonant multiples, which produces superresolution images with twice or even more the spatial resolution compared to the conventional primary reflection image. A resonant multiple is defined as a seismic reflection that revisits the same subsurface location along coincident reflection raypath. This reverberated raypath is the reason for superresolution imaging because it increases the differences in reflection times associated with subtle changes in the spatial location of the reflector. For the practical implementation of superresolution imaging, I develop a post-stack migration technique that first enhances the signal-to-noise ratios (SNRs) of resonant multiples by a moveout-correction stacking method, and then migrates the post-stacked resonant multiples with the associated Kirchhoff or wave-equation migration formula. I show with synthetic and field data examples that the first-order resonant multiple image has about twice the spatial resolution compared to the primary reflection image. Besides resolution, the correct estimate of the subsurface velocity is crucial for determining the correct depth of reflectors. Towards this goal, wave-equation migration velocity analysis (WEMVA) is an image-domain method which inverts for the velocity model that maximizes the similarity of common image gathers (CIGs). Conventional WEMVA based on subsurface-offset, angle domain or time-lag CIGs requires significant computational and memory resources because it computes higher dimensional migration images in the extended image domain. To mitigate this problem, I present a new WEMVA method using plane-wave CIGs. Plane-wave CIGs reduce the

  10. A statistical approach to plasma profile analysis

    International Nuclear Information System (INIS)

    Kardaun, O.J.W.F.; McCarthy, P.J.; Lackner, K.; Riedel, K.S.

    1990-05-01

    A general statistical approach to the parameterisation and analysis of tokamak profiles is presented. The modelling of the profile dependence on both the radius and the plasma parameters is discussed, and pertinent, classical as well as robust, methods of estimation are reviewed. Special attention is given to statistical tests for discriminating between the various models, and to the construction of confidence intervals for the parameterised profiles and the associated global quantities. The statistical approach is shown to provide a rigorous approach to the empirical testing of plasma profile invariance. (orig.)

  11. A pipeline for the de novo assembly of the Themira biloba (Sepsidae: Diptera) transcriptome using a multiple k-mer length approach.

    Science.gov (United States)

    Melicher, Dacotah; Torson, Alex S; Dworkin, Ian; Bowsher, Julia H

    2014-03-12

    The Sepsidae family of flies is a model for investigating how sexual selection shapes courtship and sexual dimorphism in a comparative framework. However, like many non-model systems, there are few molecular resources available. Large-scale sequencing and assembly have not been performed in any sepsid, and the lack of a closely related genome makes investigation of gene expression challenging. Our goal was to develop an automated pipeline for de novo transcriptome assembly, and to use that pipeline to assemble and analyze the transcriptome of the sepsid Themira biloba. Our bioinformatics pipeline uses cloud computing services to assemble and analyze the transcriptome with off-site data management, processing, and backup. It uses a multiple k-mer length approach combined with a second meta-assembly to extend transcripts and recover more bases of transcript sequences than standard single k-mer assembly. We used 454 sequencing to generate 1.48 million reads from cDNA generated from embryo, larva, and pupae of T. biloba and assembled a transcriptome consisting of 24,495 contigs. Annotation identified 16,705 transcripts, including those involved in embryogenesis and limb patterning. We assembled transcriptomes from an additional three non-model organisms to demonstrate that our pipeline assembled a higher-quality transcriptome than single k-mer approaches across multiple species. The pipeline we have developed for assembly and analysis increases contig length, recovers unique transcripts, and assembles more base pairs than other methods through the use of a meta-assembly. The T. biloba transcriptome is a critical resource for performing large-scale RNA-Seq investigations of gene expression patterns, and is the first transcriptome sequenced in this Dipteran family.

  12. Reliability analysis - systematic approach based on limited data

    International Nuclear Information System (INIS)

    Bourne, A.J.

    1975-11-01

    The initial approaches required for reliability analysis are outlined. These approaches highlight the system boundaries, examine the conditions under which the system is required to operate, and define the overall performance requirements. The discussion is illustrated by a simple example of an automatic protective system for a nuclear reactor. It is then shown how the initial approach leads to a method of defining the system, establishing performance parameters of interest and determining the general form of reliability models to be used. The overall system model and the availability of reliability data at the system level are next examined. An iterative process is then described whereby the reliability model and data requirements are systematically refined at progressively lower hierarchic levels of the system. At each stage, the approach is illustrated with examples from the protective system previously described. The main advantages of the approach put forward are the systematic process of analysis, the concentration of assessment effort in the critical areas and the maximum use of limited reliability data. (author)

  13. Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis.

    Science.gov (United States)

    Tam, Roger C; Traboulsee, Anthony; Riddehough, Andrew; Li, David K B

    2012-01-01

    The change in T 1-hypointense lesion ("black hole") volume is an important marker of pathological progression in multiple sclerosis (MS). Black hole boundaries often have low contrast and are difficult to determine accurately and most (semi-)automated segmentation methods first compute the T 2-hyperintense lesions, which are a superset of the black holes and are typically more distinct, to form a search space for the T 1w lesions. Two main potential sources of measurement noise in longitudinal black hole volume computation are partial volume and variability in the T 2w lesion segmentation. A paired analysis approach is proposed herein that uses registration to equalize partial volume and lesion mask processing to combine T 2w lesion segmentations across time. The scans of 247 MS patients are used to compare a selected black hole computation method with an enhanced version incorporating paired analysis, using rank correlation to a clinical variable (MS functional composite) as the primary outcome measure. The comparison is done at nine different levels of intensity as a previous study suggests that darker black holes may yield stronger correlations. The results demonstrate that paired analysis can strongly improve longitudinal correlation (from -0.148 to -0.303 in this sample) and may produce segmentations that are more sensitive to clinically relevant changes.

  14. Gene features selection for three-class disease classification via multiple orthogonal partial least square discriminant analysis and S-plot using microarray data.

    Science.gov (United States)

    Yang, Mingxing; Li, Xiumin; Li, Zhibin; Ou, Zhimin; Liu, Ming; Liu, Suhuan; Li, Xuejun; Yang, Shuyu

    2013-01-01

    DNA microarray analysis is characterized by obtaining a large number of gene variables from a small number of observations. Cluster analysis is widely used to analyze DNA microarray data to make classification and diagnosis of disease. Because there are so many irrelevant and insignificant genes in a dataset, a feature selection approach must be employed in data analysis. The performance of cluster analysis of this high-throughput data depends on whether the feature selection approach chooses the most relevant genes associated with disease classes. Here we proposed a new method using multiple Orthogonal Partial Least Squares-Discriminant Analysis (mOPLS-DA) models and S-plots to select the most relevant genes to conduct three-class disease classification and prediction. We tested our method using Golub's leukemia microarray data. For three classes with subtypes, we proposed hierarchical orthogonal partial least squares-discriminant analysis (OPLS-DA) models and S-plots to select features for two main classes and their subtypes. For three classes in parallel, we employed three OPLS-DA models and S-plots to choose marker genes for each class. The power of feature selection to classify and predict three-class disease was evaluated using cluster analysis. Further, the general performance of our method was tested using four public datasets and compared with those of four other feature selection methods. The results revealed that our method effectively selected the most relevant features for disease classification and prediction, and its performance was better than that of the other methods.

  15. The Multiplicative Zak Transform, Dimension Reduction, and Wavelet Analysis of LIDAR Data

    Science.gov (United States)

    2010-01-01

    systems is likely to fail. Auslander, Eichmann , Gertner, and Tolimieri defined a multiplicative Zak transform [1], mimicking the construction of the Gabor...L. Auslander, G. Eichmann , I. Gertner and R. Tolimieri, “Time-Frequency Analysis and Synthesis of Non-Stationary Signals,” Proc. Soc. Photo-Opt. In

  16. Smoking and worsening disability in multiple sclerosis: A meta-analysis.

    Science.gov (United States)

    Heydarpour, P; Manouchehrinia, A; Beiki, O; Mousavi, S E; Abdolalizadeh, A; -Lakeh, M Moradi; Sahraian, M A

    2018-03-15

    Multiple sclerosis (MS) is a chronic demyelinating disorder affecting young adults. Environmental factors and lifestyle behaviors are pivotal in MS pathophysiology. Smoking has been considered as an important risk factor in MS. Various recent studies have been conducted to measure the role of smoking on worsening disability in patients with MS, thus we intended to systematically assess effect of smoking on evolution of disability in this study. We queried MEDLINE, EMBASE and Cochrane Library with following keywords "Multiple Sclerosis, Smoking, Tobacco Use, Disability" on December 1st 2016. Original articles were included when smoking history was mentioned, disability was measured via expanded disability status scale (EDSS) or multiple sclerosis severity score (MSSS). Studies with insufficient outcome data, non-human, or in other languages than English were excluded. Through literature review after duplicate removals, 268 articles were retrieved. A total of 56 articles were screened and 15 articles were assessed for eligibility, finally, eleven articles were included in this systematic review and meta-analysis. Ever smoking was significantly associated with increased EDSS (standardized mean difference (SMD) = 0.15, 95% CI = 0.01-0.28), but had no significant association with risk of reaching EDSS 4 (HR = 1.24, 95% CI = 0.89-1.72) or EDSS 6 (HR = 1.17, 95% CI = 0.88-1.57). Smoking had no effect on MSSS (SMD = 0.14, 95% CI = -0.04-0.32) or T2 lesion volume (SMD = 0.07, 95% CI = -0.08-0.22). This meta-analysis showed smoking increased EDSS, insignificant findings were possibly due to the small number of studies, significant differences in methodologies, and variations in reporting of disability outcomes. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  17. Analysis of the quantitative dermatoglyphics of the digito-palmar complex in patients with multiple sclerosis.

    Science.gov (United States)

    Supe, S; Milicić, J; Pavićević, R

    1997-06-01

    Recent studies on the etiopathogenesis of multiple sclerosis (MS) all point out that there is a polygenetical predisposition for this illness. The so called "MS Trait" determines the reactivity of the immunological system upon ecological factors. The development of the glyphological science and the study of the characteristics of the digito-palmar dermatoglyphic complex (for which it was established that they are polygenetically determined characteristics) all enable a better insight into the genetic development during early embriogenesis. The aim of this study was to estimate certain differences in the dermatoglyphics of digito-palmar complexes between the group with multiple sclerosis and the comparable, phenotypically healthy groups of both sexes. This study is based on the analysis of 18 quantitative characteristics of the digito-palmar complex in 125 patients with multiple sclerosis (41 males and 84 females) in comparison to a group of 400 phenotypically healthy patients (200 males and 200 females). The conducted analysis pointed towards a statistically significant decrease of the number of digital and palmar ridges, as well as with lower values of atd angles in a group of MS patients of both sexes. The main discriminators were the characteristic palmar dermatoglyphics with the possibility that the discriminate analysis classifies over 80% of the examinees which exceeds the statistical significance. The results of this study suggest a possible discrimination of patients with MS and the phenotypically health population through the analysis of the dermatoglyphic status, and therefore the possibility that multiple sclerosis is genetically predisposed disease.

  18. Hesitant fuzzy methods for multiple criteria decision analysis

    CERN Document Server

    Zhang, Xiaolu

    2017-01-01

    The book offers a comprehensive introduction to methods for solving multiple criteria decision making and group decision making problems with hesitant fuzzy information. It reports on the authors’ latest research, as well as on others’ research, providing readers with a complete set of decision making tools, such as hesitant fuzzy TOPSIS, hesitant fuzzy TODIM, hesitant fuzzy LINMAP, hesitant fuzzy QUALIFEX, and the deviation modeling approach with heterogeneous fuzzy information. The main focus is on decision making problems in which the criteria values and/or the weights of criteria are not expressed in crisp numbers but are more suitable to be denoted as hesitant fuzzy elements. The largest part of the book is devoted to new methods recently developed by the authors to solve decision making problems in situations where the available information is vague or hesitant. These methods are presented in detail, together with their application to different type of decision-making problems. All in all, the book ...

  19. Closed-Loop Surface Related Multiple Estimation

    NARCIS (Netherlands)

    Lopez Angarita, G.A.

    2016-01-01

    Surface-related multiple elimination (SRME) is one of the most commonly used methods for suppressing surface multiples. However, in order to obtain an accurate surface multiple estimation, dense source and receiver sampling is required. The traditional approach to this problem is performing data

  20. Multiple intelligences: Can they be measured?

    OpenAIRE

    Kirsi Tirri; Petri Nokelainen; Erkki Komulainen

    2013-01-01

    This paper is about issues relating to the assessment of multiple intelligences. The first section introduces the authors’ work on building measures of multiple intelligences and moral sensitivities. It also provides a conceptual definition of multiple intelligences based on Multiple Intelligences theory by Howard Gardner (1983). The second section discusses the context specificity of intelligences and alternative approaches to measuring multiple intelligences. The third section analyses the ...

  1. Taking Multiple Exposure Into Account Can Improve Assessment of Chemical Risks.

    Science.gov (United States)

    Clerc, Frédéric; Bertrand, Nicolas Jean Hyacinthe; La Rocca, Bénédicte

    2017-12-15

    During work, operators may be exposed to several chemicals simultaneously. Most exposure assessment approaches only determine exposure levels for each substance individually. However, such individual-substance approaches may not correctly estimate the toxicity of 'cocktails' of chemicals, as the toxicity of a cocktail may differ from the toxicity of substances on their own. This study presents an approach that can better take into account multiple exposure when assessing chemical risks. Almost 30000 work situations, monitored between 2005 and 2014 and recorded in two French databases, were analysed using MiXie software. The algorithms employed in MiXie can identify toxicological classes associated with several substances, based on the additivity of the selected effects of each substance. The results of our retrospective analysis show that MiXie was able to identify almost 20% more potentially hazardous situations than identified using a single-substance approach. It therefore appears essential to review the ways in which multiple exposure is taken into account during risk assessment. © The Author(s) 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

  2. Analysis of γ spectra in airborne radioactivity measurements using multiple linear regressions

    International Nuclear Information System (INIS)

    Bao Min; Shi Quanlin; Zhang Jiamei

    2004-01-01

    This paper describes the net peak counts calculating of nuclide 137 Cs at 662 keV of γ spectra in airborne radioactivity measurements using multiple linear regressions. Mathematic model is founded by analyzing every factor that has contribution to Cs peak counts in spectra, and multiple linear regression function is established. Calculating process adopts stepwise regression, and the indistinctive factors are eliminated by F check. The regression results and its uncertainty are calculated using Least Square Estimation, then the Cs peak net counts and its uncertainty can be gotten. The analysis results for experimental spectrum are displayed. The influence of energy shift and energy resolution on the analyzing result is discussed. In comparison with the stripping spectra method, multiple linear regression method needn't stripping radios, and the calculating result has relation with the counts in Cs peak only, and the calculating uncertainty is reduced. (authors)

  3. Statistical approaches to assessing single and multiple outcome measures in dry eye therapy and diagnosis.

    Science.gov (United States)

    Tomlinson, Alan; Hair, Mario; McFadyen, Angus

    2013-10-01

    Dry eye is a multifactorial disease which would require a broad spectrum of test measures in the monitoring of its treatment and diagnosis. However, studies have typically reported improvements in individual measures with treatment. Alternative approaches involve multiple, combined outcomes being assessed by different statistical analyses. In order to assess the effect of various statistical approaches to the use of single and combined test measures in dry eye, this review reanalyzed measures from two previous studies (osmolarity, evaporation, tear turnover rate, and lipid film quality). These analyses assessed the measures as single variables within groups, pre- and post-intervention with a lubricant supplement, by creating combinations of these variables and by validating these combinations with the combined sample of data from all groups of dry eye subjects. The effectiveness of single measures and combinations in diagnosis of dry eye was also considered. Copyright © 2013. Published by Elsevier Inc.

  4. Generation Y, wine and alcohol. A semantic differential approach to consumption analysis in Tuscany.

    Science.gov (United States)

    Marinelli, Nicola; Fabbrizzi, Sara; Alampi Sottini, Veronica; Sacchelli, Sandro; Bernetti, Iacopo; Menghini, Silvio

    2014-04-01

    The aim of the study is the elicitation of the consumer's semantic perception of different alcoholic beverages in order to provide information for the definition of communication strategies for both the private sector (and specifically the wine industry) and the public decision maker. Such information can be seen as the basis of a wider social marketing construct aimed at the promotion of responsible drinking among young consumers. The semantic differential approach was used in this study. The data collection was based on a survey to 430 consumers between 18 and 35years old in Tuscany, Italy. The database was organized in a three-way structure, indexing the data in a multiway matrix. The data were processed using a Multiple Factor Analysis (MFA). Moreover, homogeneous clusters of consumers were identified using a Hierarchical Clustering on Principal Components (HCPC) approach. The results of the study highlight that beer and spirits are mainly perceived as "Young", "Social", "Euphoric", "Happy", "Appealing" and "Trendy" beverages, while wine is associated mostly with terms such as "Pleasure", "Quality" and "Comfortable". Furthermore, the cluster analysis allowed for the identification of three groups of individuals with different approaches to alcohol drinking. The results of the study supply a useful information framework for the elaboration of specific communication strategies that, based on the drinking habits of young consumers and their perception of different beverages, can use a language that is very close to the consumer typologies. Such information can be helpful for both private and public communication strategies. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

  5. Multiple electron processes of He and Ne by proton impact

    Science.gov (United States)

    Terekhin, Pavel Nikolaevich; Montenegro, Pablo; Quinto, Michele; Monti, Juan; Fojon, Omar; Rivarola, Roberto

    2016-05-01

    A detailed investigation of multiple electron processes (single and multiple ionization, single capture, transfer-ionization) of He and Ne is presented for proton impact at intermediate and high collision energies. Exclusive absolute cross sections for these processes have been obtained by calculation of transition probabilities in the independent electron and independent event models as a function of impact parameter in the framework of the continuum distorted wave-eikonal initial state theory. A binomial analysis is employed to calculate exclusive probabilities. The comparison with available theoretical and experimental results shows that exclusive probabilities are needed for a reliable description of the experimental data. The developed approach can be used for obtaining the input database for modeling multiple electron processes of charged particles passing through the matter.

  6. Multiple trauma in children: critical care overview.

    Science.gov (United States)

    Wetzel, Randall C; Burns, R Cartland

    2002-11-01

    Multiple trauma is more than the sum of the injuries. Management not only of the physiologic injury but also of the pathophysiologic responses, along with integration of the child's emotional and developmental needs and the child's family, forms the basis of trauma care. Multiple trauma in children also elicits profound psychological responses from the healthcare providers involved with these children. This overview will address the pathophysiology of multiple trauma in children and the general principles of trauma management by an integrated trauma team. Trauma is a systemic disease. Multiple trauma stimulates the release of multiple inflammatory mediators. A lethal triad of hypothermia, acidosis, and coagulopathy is the direct result of trauma and secondary injury from the systemic response to trauma. Controlling and responding to the secondary pathophysiologic sequelae of trauma is the cornerstone of trauma management in the multiply injured, critically ill child. Damage control surgery is a new, rational approach to the child with multiple trauma. The selection of children for damage control surgery depends on the severity of injury. Major abdominal vascular injuries and multiple visceral injuries are best considered for this approach. The effective management of childhood multiple trauma requires a combined team approach, consideration of the child and family, an organized trauma system, and an effective quality assurance and improvement mechanism.

  7. Approaches to Enhance Sensemaking for Intelligence Analysis

    National Research Council Canada - National Science Library

    McBeth, Michael

    2002-01-01

    ..., and to apply persuasion skills to interact more productively with others. Each approach is explained from a sensemaking perspective and linked to Richard Heuer's Psychology of Intelligence Analysis...

  8. Novel approach in quantitative analysis of shearography method

    International Nuclear Information System (INIS)

    Wan Saffiey Wan Abdullah

    2002-01-01

    The application of laser interferometry in industrial non-destructive testing and material characterization is becoming more prevalent since this method provides non-contact full-field inspection of the test object. However their application only limited to the qualitative analysis, current trend has changed to the development of this method by the introduction of quantitative analysis, which attempts to detail the defect examined. This being the design feature for a ranges of object size to be examined. The growing commercial demand for quantitative analysis for NDT and material characterization is determining the quality of optical and analysis instrument. However very little attention is currently being paid to understanding, quantifying and compensating for the numerous error sources which are a function of interferometers. This paper presents a comparison of measurement analysis using the established theoretical approach and the new approach, taken into account the factor of divergence illumination and other geometrical factors. The difference in the measurement system could be associated in the error factor. (Author)

  9. Combining MCDA and risk analysis: dealing with scaling issues in the multiplicative AHP

    DEFF Research Database (Denmark)

    Barfod, Michael Bruhn; van den Honert, Rob; Salling, Kim Bang

    the progression factor 2 is used for calculating scores of alternatives and √2 for calculation of criteria weights when transforming the verbal judgments stemming from pair wise comparisons. However, depending on the decision context, the decision-makers aversion towards risk, etc., it is most likely......This paper proposes a new decision support system (DSS) for applying risk analysis and stochastic simulation to the multiplicative AHP in order to deal with issues concerning the progression factors. The multiplicative AHP makes use of direct rating on a logarithmic scale, and for this purpose...

  10. A pragmatic approach to estimate alpha factors for common cause failure analysis

    International Nuclear Information System (INIS)

    Hassija, Varun; Senthil Kumar, C.; Velusamy, K.

    2014-01-01

    Highlights: • Estimation of coefficients in alpha factor model for common cause analysis. • A derivation of plant specific alpha factors is demonstrated. • We examine sensitivity of common cause contribution to total system failure. • We compare beta factor and alpha factor models for various redundant configurations. • The use of alpha factors is preferable, especially for large redundant systems. - Abstract: Most of the modern technological systems are deployed with high redundancy but still they fail mainly on account of common cause failures (CCF). Various models such as Beta Factor, Multiple Greek Letter, Binomial Failure Rate and Alpha Factor exists for estimation of risk from common cause failures. Amongst all, alpha factor model is considered most suitable for high redundant systems as it arrives at common cause failure probabilities from a set of ratios of failures and the total component failure probability Q T . In the present study, alpha factor model is applied for the assessment of CCF of safety systems deployed at two nuclear power plants. A method to overcome the difficulties in estimation of the coefficients viz., alpha factors in the model, importance of deriving plant specific alpha factors and sensitivity of common cause contribution to the total system failure probability with respect to hazard imposed by various CCF events is highlighted. An approach described in NUREG/CR-5500 is extended in this study to provide more explicit guidance for a statistical approach to derive plant specific coefficients for CCF analysis especially for high redundant systems. The procedure is expected to aid regulators for independent safety assessment

  11. Multiple passage cells theory

    International Nuclear Information System (INIS)

    Riva, R.

    1983-01-01

    A review of the main concepts envolved in non astigmatic multiple passes cells is presented. It is shown that these concepts can be extended to ring cavities in which the analysis of the ray propagation (in the paraxial approaching) in two separated plans is accomplished. The concepts developed are applyed to a simple ring cavity (one curve mirror and two plane ones) showing that the acquired pattern of the rays on the mirrors is the one of a Lissajours figure which allows a better use of the mirror's area and consequently a larger number of passes. The cavity has applications in optical delay lines, measurements of mirrors reflectivities and possibly in passive optical gyroscopes. (Author) [pt

  12. Analysis of different multiplicities and their interference in quasi-elastic cluster knock-out by fast hadrons

    International Nuclear Information System (INIS)

    Golovanova, N.F.; Ibraeva, E.T.; Neudatchin, V.G.

    1978-01-01

    Different multiplicities and their interference in hadron scattering have been investigated on the basis of a new dynamic approach to quasi-elastic knock-out of nucleon clusters by fast hadrons from light nuclei. It is shown that in the region of momentum transfer values p, where scattering multiplicities less than b are predominant, the effective numbers and form factors determined in Refs. 1) -- 3) no longer act as pure structural nuclear factors (b means the number of nucleons in the knocked-out cluster). These characteristics are significantly dependent on the process dynamics. Only in the region of values p, where the maximum hadron scattering multiplicity b is realized, the effective numbers and form factors do assume the purely structural meaning. (auth.)

  13. Detection of multiple AE signal by triaxial hodogram analysis; Sanjiku hodogram ho ni yoru taju acoustic emission no kenshutsu

    Energy Technology Data Exchange (ETDEWEB)

    Nagano, K; Yamashita, T [Muroran Institute of Technology, Hokkaido (Japan)

    1997-05-27

    In order to evaluate dynamic behavior of underground cracks, analysis and detection were attempted on multiple acoustic emission (AE) events. The multiple AE is a phenomenon in which multiple AE signals generated by underground cracks developed in an extremely short time interval are superimposed, and observed as one AE event. The multiple AE signal consists of two AE signals, whereas the second P-wave is supposed to have been inputted before the first S-wave is inputted. The first P-wave is inputted first, where linear three-dimensional particle movements are observed, but the movements are made random due to scattering and sensor characteristics. When the second P-wave is inputted, the linear particle movements are observed again, but are superimposed with the existing input signals and become multiple AE, which creates poor S/N ratio. The multiple AE detection determines it a multiple AE event when three conditions are met, i. e. a condition of equivalent time interval of a maximum value in a scalogram analysis, a condition of P-wave vibrating direction, and a condition of the linear particle movement. Seventy AE signals observed in the Kakkonda geothermal field were analyzed and AE signals that satisfy the multiple AE were detected. However, further development is required on an analysis method with high resolution for the time. 4 refs., 4 figs.

  14. A geostatistical approach to the change-of-support problem and variable-support data fusion in spatial analysis

    Science.gov (United States)

    Wang, Jun; Wang, Yang; Zeng, Hui

    2016-01-01

    A key issue to address in synthesizing spatial data with variable-support in spatial analysis and modeling is the change-of-support problem. We present an approach for solving the change-of-support and variable-support data fusion problems. This approach is based on geostatistical inverse modeling that explicitly accounts for differences in spatial support. The inverse model is applied here to produce both the best predictions of a target support and prediction uncertainties, based on one or more measurements, while honoring measurements. Spatial data covering large geographic areas often exhibit spatial nonstationarity and can lead to computational challenge due to the large data size. We developed a local-window geostatistical inverse modeling approach to accommodate these issues of spatial nonstationarity and alleviate computational burden. We conducted experiments using synthetic and real-world raster data. Synthetic data were generated and aggregated to multiple supports and downscaled back to the original support to analyze the accuracy of spatial predictions and the correctness of prediction uncertainties. Similar experiments were conducted for real-world raster data. Real-world data with variable-support were statistically fused to produce single-support predictions and associated uncertainties. The modeling results demonstrate that geostatistical inverse modeling can produce accurate predictions and associated prediction uncertainties. It is shown that the local-window geostatistical inverse modeling approach suggested offers a practical way to solve the well-known change-of-support problem and variable-support data fusion problem in spatial analysis and modeling.

  15. A mathematical analysis of multiple-target SELEX.

    Science.gov (United States)

    Seo, Yeon-Jung; Chen, Shiliang; Nilsen-Hamilton, Marit; Levine, Howard A

    2010-10-01

    SELEX (Systematic Evolution of Ligands by Exponential Enrichment) is a procedure by which a mixture of nucleic acids can be fractionated with the goal of identifying those with specific biochemical activities. One combines the mixture with a specific target molecule and then separates the target-NA complex from the resulting reactions. The target-NA complex is separated from the unbound NA by mechanical means (such as by filtration), the NA is eluted from the complex, amplified by PCR (polymerase chain reaction), and the process repeated. After several rounds, one should be left with the nucleic acids that best bind to the target. The problem was first formulated mathematically in Irvine et al. (J. Mol. Biol. 222:739-761, 1991). In Levine and Nilsen-Hamilton (Comput. Biol. Chem. 31:11-25, 2007), a mathematical analysis of the process was given. In Vant-Hull et al. (J. Mol. Biol. 278:579-597, 1998), multiple target SELEX was considered. It was assumed that each target has a single nucleic acid binding site that permits occupation by no more than one nucleic acid. Here, we revisit Vant-Hull et al. (J. Mol. Biol. 278:579-597, 1998) using the same assumptions. The iteration scheme is shown to be convergent and a simplified algorithm is given. Our interest here is in the behavior of the multiple target SELEX process as a discrete "time" dynamical system. Our goal is to characterize the limiting states and their dependence on the initial distribution of nucleic acid and target fraction components. (In multiple target SELEX, we vary the target component fractions, but not their concentrations, as fixed and the initial pool of nucleic acids as a variable starting condition). Given N nucleic acids and a target consisting of M subtarget component species, there is an M × N matrix of affinities, the (i,j) entry corresponding to the affinity of the jth nucleic acid for the ith subtarget. We give a structure condition on this matrix that is equivalent to the following

  16. Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach

    Science.gov (United States)

    Ye, Yusen; Gao, Lin; Zhang, Shihua

    2017-01-01

    Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions. PMID:29033978

  17. Multiple predictor smoothing methods for sensitivity analysis: Description of techniques

    International Nuclear Information System (INIS)

    Storlie, Curtis B.; Helton, Jon C.

    2008-01-01

    The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (i) locally weighted regression (LOESS), (ii) additive models, (iii) projection pursuit regression, and (iv) recursive partitioning regression. Then, in the second and concluding part of this presentation, the indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present

  18. Generalized internal multiple imaging

    KAUST Repository

    Zuberi, M. A. H.

    2014-08-05

    Internal multiples deteriorate the image when the imaging procedure assumes only single scattering, especially if the velocity model does not have sharp contrasts to reproduce such scattering in the Green’s function through forward modeling. If properly imaged, internal multiples (internally scattered energy) can enhance the seismic image. Conventionally, to image internal multiples, accurate, sharp contrasts in the velocity model are required to construct a Green’s function with all the scattered energy. As an alternative, we have developed a generalized internal multiple imaging procedure that images any order internal scattering using the background Green’s function (from the surface to each image point), constructed from a smooth velocity model, usually used for conventional imaging. For the first-order internal multiples, the approach consisted of three steps, in which we first back propagated the recorded surface seismic data using the background Green’s function, then crosscorrelated the back-propagated data with the recorded data, and finally crosscorrelated the result with the original background Green’s function. This procedure images the contribution of the recorded first-order internal multiples, and it is almost free of the single-scattering recorded energy. The cost includes one additional crosscorrelation over the conventional single-scattering imaging application. We generalized this method to image internal multiples of any order separately. The resulting images can be added to the conventional single-scattering image, obtained, e.g., from Kirchhoff or reverse-time migration, to enhance the image. Application to synthetic data with reflectors illuminated by multiple scattering (double scattering) demonstrated the effectiveness of the approach.

  19. Optimization of multi-response dynamic systems integrating multiple ...

    African Journals Online (AJOL)

    It also results in better optimization performance than back-propagation neural network-based approach and data mining-based approach reported by the past researchers. Keywords: multiple responses, multiple regression, weighted dynamic signal-to-noise ratio, performance measure modelling, response function ...

  20. Transmission of single and multiple viral variants in primary HIV-1 subtype C infection.

    Directory of Open Access Journals (Sweden)

    Vladimir Novitsky

    2011-02-01

    Full Text Available To address whether sequences of viral gag and env quasispecies collected during the early post-acute period can be utilized to determine multiplicity of transmitted HIV's, recently developed approaches for analysis of viral evolution in acute HIV-1 infection [1,2] were applied. Specifically, phylogenetic reconstruction, inter- and intra-patient distribution of maximum and mean genetic distances, analysis of Poisson fitness, shape of highlighter plots, recombination analysis, and estimation of time to the most recent common ancestor (tMRCA were utilized for resolving multiplicity of HIV-1 transmission in a set of viral quasispecies collected within 50 days post-seroconversion (p/s in 25 HIV-infected individuals with estimated time of seroconversion. The decision on multiplicity of HIV infection was made based on the model's fit with, or failure to explain, the observed extent of viral sequence heterogeneity. The initial analysis was based on phylogeny, inter-patient distribution of maximum and mean distances, and Poisson fitness, and was able to resolve multiplicity of HIV transmission in 20 of 25 (80% cases. Additional analysis involved distribution of individual viral distances, highlighter plots, recombination analysis, and estimation of tMRCA, and resolved 4 of the 5 remaining cases. Overall, transmission of a single viral variant was identified in 16 of 25 (64% cases, and transmission of multiple variants was evident in 8 of 25 (32% cases. In one case multiplicity of HIV-1 transmission could not be determined. In primary HIV-1 subtype C infection, samples collected within 50 days p/s and analyzed by a single-genome amplification/sequencing technique can provide reliable identification of transmission multiplicity in 24 of 25 (96% cases. Observed transmission frequency of a single viral variant and multiple viral variants were within the ranges of 64% to 68%, and 32% to 36%, respectively.

  1. Active neutron multiplicity analysis and Monte Carlo calculations

    International Nuclear Information System (INIS)

    Krick, M.S.; Ensslin, N.; Langner, D.G.; Miller, M.C.; Siebelist, R.; Stewart, J.E.; Ceo, R.N.; May, P.K.; Collins, L.L. Jr

    1994-01-01

    Active neutron multiplicity measurements of high-enrichment uranium metal and oxide samples have been made at Los Alamos and Y-12. The data from the measurements of standards at Los Alamos were analyzed to obtain values for neutron multiplication and source-sample coupling. These results are compared to equivalent results obtained from Monte Carlo calculations. An approximate relationship between coupling and multiplication is derived and used to correct doubles rates for multiplication and coupling. The utility of singles counting for uranium samples is also examined

  2. Material Selection for Dye Sensitized Solar Cells Using Multiple Attribute Decision Making Approach

    Directory of Open Access Journals (Sweden)

    Sarita Baghel

    2014-01-01

    Full Text Available Dye sensitized solar cells (DSCs provide a potential alternative to conventional p-n junction photovoltaic devices. The semiconductor thin film plays a crucial role in the working of DSC. This paper aims at formulating a process for the selection of optimum semiconductor material for nanostructured thin film using multiple attribute decision making (MADM approach. Various possible available semiconducting materials and their properties like band gap, cost, mobility, rate of electron injection, and static dielectric constant are considered and MADM technique is applied to select the best suited material. It was found that, out of all possible candidates, titanium dioxide (TiO2 is the best semiconductor material for application in DSC. It was observed that the proposed results are in good agreement with the experimental findings.

  3. Sit less and move more: perspectives of adults with multiple sclerosis.

    Science.gov (United States)

    Aminian, Saeideh; Ezeugwu, Victor E; Motl, Robert W; Manns, Patricia J

    2017-12-20

    Multiple sclerosis is a chronic neurological disease with the highest prevalence in Canada. Replacing sedentary behavior with light activities may be a feasible approach to manage multiple sclerosis symptoms. This study explored the perspectives of adults with multiple sclerosis about sedentary behavior, physical activity and ways to change behavior. Fifteen adults with multiple sclerosis (age 43 ± 13 years; mean ± standard deviation), recruited through the multiple sclerosis Clinic at the University of Alberta, Edmonton, Canada, participated in semi-structured interviews. Interview audios were transcribed verbatim and coded. NVivo software was used to facilitate the inductive process of thematic analysis. Balancing competing priorities between sitting and moving was the primary theme. Participants were aware of the benefits of physical activity to their overall health, and in the management of fatigue and muscle stiffness. Due to fatigue, they often chose sitting to get their energy back. Further, some barriers included perceived fear of losing balance or embarrassment while walking. Activity monitoring, accountability, educational and individualized programs were suggested strategies to motivate more movement. Adults with multiple sclerosis were open to the idea of replacing sitting with light activities. Motivational and educational programs are required to help them to change sedentary behavior to moving more. IMPLICATIONS FOR REHABILITATION One of the most challenging and common difficulties of multiple sclerosis is walking impairment that worsens because of multiple sclerosis progression, and is a common goal in the rehabilitation of people with multiple sclerosis. The deterioration in walking abilities is related to lower levels of physical activity and more sedentary behavior, such that adults with multiple sclerosis spend 8 to 10.5 h per day sitting. Replacing prolonged sedentary behavior with light physical activities, and incorporating education

  4. Analysis of multiple spurions and associated circuits in Cofrentes; Analisis de espurios multiples y circuitos asociados en C.N. Cofrentes

    Energy Technology Data Exchange (ETDEWEB)

    Molina, J. J.; Celaya, M. A.

    2015-07-01

    The article describes the process followed by the Cofrentes Nuclear Power Plant (CNC) to conduct the analysis of multiple spurious in compliance with regulatory standards IS-30 rev 1 and CSN Safety Guide 1.19 based on the recommendations of the NEI-00-01 Guidance for Post-fire Safe Shutdown Circuit and NUREG/CR-6850. Fire PRA Methodology for Nuclear Power Facilities. (Author)

  5. The Effectiveness of Problem-Based Learning Approach Based on Multiple Intelligences in Terms of Student’s Achievement, Mathematical Connection Ability, and Self-Esteem

    Science.gov (United States)

    Kartikasari, A.; Widjajanti, D. B.

    2017-02-01

    The aim of this study is to explore the effectiveness of learning approach using problem-based learning based on multiple intelligences in developing student’s achievement, mathematical connection ability, and self-esteem. This study is experimental research with research sample was 30 of Grade X students of MIA III MAN Yogyakarta III. Learning materials that were implemented consisting of trigonometry and geometry. For the purpose of this study, researchers designed an achievement test made up of 44 multiple choice questions with respectively 24 questions on the concept of trigonometry and 20 questions for geometry. The researcher also designed a connection mathematical test and self-esteem questionnaire that consisted of 7 essay questions on mathematical connection test and 30 items of self-esteem questionnaire. The learning approach said that to be effective if the proportion of students who achieved KKM on achievement test, the proportion of students who achieved a minimum score of high category on the results of both mathematical connection test and self-esteem questionnaire were greater than or equal to 70%. Based on the hypothesis testing at the significance level of 5%, it can be concluded that the learning approach using problem-based learning based on multiple intelligences was effective in terms of student’s achievement, mathematical connection ability, and self-esteem.

  6. Prediction of hearing outcomes by multiple regression analysis in patients with idiopathic sudden sensorineural hearing loss.

    Science.gov (United States)

    Suzuki, Hideaki; Tabata, Takahisa; Koizumi, Hiroki; Hohchi, Nobusuke; Takeuchi, Shoko; Kitamura, Takuro; Fujino, Yoshihisa; Ohbuchi, Toyoaki

    2014-12-01

    This study aimed to create a multiple regression model for predicting hearing outcomes of idiopathic sudden sensorineural hearing loss (ISSNHL). The participants were 205 consecutive patients (205 ears) with ISSNHL (hearing level ≥ 40 dB, interval between onset and treatment ≤ 30 days). They received systemic steroid administration combined with intratympanic steroid injection. Data were examined by simple and multiple regression analyses. Three hearing indices (percentage hearing improvement, hearing gain, and posttreatment hearing level [HLpost]) and 7 prognostic factors (age, days from onset to treatment, initial hearing level, initial hearing level at low frequencies, initial hearing level at high frequencies, presence of vertigo, and contralateral hearing level) were included in the multiple regression analysis as dependent and explanatory variables, respectively. In the simple regression analysis, the percentage hearing improvement, hearing gain, and HLpost showed significant correlation with 2, 5, and 6 of the 7 prognostic factors, respectively. The multiple correlation coefficients were 0.396, 0.503, and 0.714 for the percentage hearing improvement, hearing gain, and HLpost, respectively. Predicted values of HLpost calculated by the multiple regression equation were reliable with 70% probability with a 40-dB-width prediction interval. Prediction of HLpost by the multiple regression model may be useful to estimate the hearing prognosis of ISSNHL. © The Author(s) 2014.

  7. Preparing a Safety Analysis Report using the building block approach

    International Nuclear Information System (INIS)

    Herrington, C.C.

    1990-01-01

    The credibility of the applicant in a licensing proceeding is severely impacted by the quality of the license application, particularly the Safety Analysis Report. To ensure the highest possible credibility, the building block approach was devised to support the development of a quality Safety Analysis Report. The approach incorporates a comprehensive planning scheme that logically ties together all levels of the investigation and provides the direction necessary to prepare a superior Safety Analysis Report

  8. Direct integration multiple collision integral transport analysis method for high energy fusion neutronics

    International Nuclear Information System (INIS)

    Koch, K.R.

    1985-01-01

    A new analysis method specially suited for the inherent difficulties of fusion neutronics was developed to provide detailed studies of the fusion neutron transport physics. These studies should provide a better understanding of the limitations and accuracies of typical fusion neutronics calculations. The new analysis method is based on the direct integration of the integral form of the neutron transport equation and employs a continuous energy formulation with the exact treatment of the energy angle kinematics of the scattering process. In addition, the overall solution is analyzed in terms of uncollided, once-collided, and multi-collided solution components based on a multiple collision treatment. Furthermore, the numerical evaluations of integrals use quadrature schemes that are based on the actual dependencies exhibited in the integrands. The new DITRAN computer code was developed on the Cyber 205 vector supercomputer to implement this direct integration multiple-collision fusion neutronics analysis. Three representative fusion reactor models were devised and the solutions to these problems were studied to provide suitable choices for the numerical quadrature orders as well as the discretized solution grid and to understand the limitations of the new analysis method. As further verification and as a first step in assessing the accuracy of existing fusion-neutronics calculations, solutions obtained using the new analysis method were compared to typical multigroup discrete ordinates calculations

  9. Algebraic Approaches to Space-Time Code Construction for Multiple-Antenna Communication

    OpenAIRE

    Raviteja, U; Sharanappa, I; Vanamali, B; Kumar, Vijay P

    2011-01-01

    A major challenge in wireless communications is overcoming the deleterious effects of fading, a phenomenon largely responsible for the seemingly inevitable dropped call. Multiple-antennas communication systems, commonly referred to as MIMO systems, employ multiple antennas at both transmitter and receiver, thereby creating a multitude of signalling pathways between transmitter and receiver. These multiple pathways give the signal a diversity advantage with which to combat fading. Apart fro...

  10. An Improved Wake Vortex Tracking Algorithm for Multiple Aircraft

    Science.gov (United States)

    Switzer, George F.; Proctor, Fred H.; Ahmad, Nashat N.; LimonDuparcmeur, Fanny M.

    2010-01-01

    The accurate tracking of vortex evolution from Large Eddy Simulation (LES) data is a complex and computationally intensive problem. The vortex tracking requires the analysis of very large three-dimensional and time-varying datasets. The complexity of the problem is further compounded by the fact that these vortices are embedded in a background turbulence field, and they may interact with the ground surface. Another level of complication can arise, if vortices from multiple aircrafts are simulated. This paper presents a new technique for post-processing LES data to obtain wake vortex tracks and wake intensities. The new approach isolates vortices by defining "regions of interest" (ROI) around each vortex and has the ability to identify vortex pairs from multiple aircraft. The paper describes the new methodology for tracking wake vortices and presents application of the technique for single and multiple aircraft.

  11. Testing Group Mean Differences of Latent Variables in Multilevel Data Using Multiple-Group Multilevel CFA and Multilevel MIMIC Modeling.

    Science.gov (United States)

    Kim, Eun Sook; Cao, Chunhua

    2015-01-01

    Considering that group comparisons are common in social science, we examined two latent group mean testing methods when groups of interest were either at the between or within level of multilevel data: multiple-group multilevel confirmatory factor analysis (MG ML CFA) and multilevel multiple-indicators multiple-causes modeling (ML MIMIC). The performance of these methods were investigated through three Monte Carlo studies. In Studies 1 and 2, either factor variances or residual variances were manipulated to be heterogeneous between groups. In Study 3, which focused on within-level multiple-group analysis, six different model specifications were considered depending on how to model the intra-class group correlation (i.e., correlation between random effect factors for groups within cluster). The results of simulations generally supported the adequacy of MG ML CFA and ML MIMIC for multiple-group analysis with multilevel data. The two methods did not show any notable difference in the latent group mean testing across three studies. Finally, a demonstration with real data and guidelines in selecting an appropriate approach to multilevel multiple-group analysis are provided.

  12. It's Deja Vu All over Again: Using Multiple-Spell Discrete-Time Survival Analysis.

    Science.gov (United States)

    Willett, John B.; Singer, Judith D.

    1995-01-01

    The multiple-spell discrete-time survival analysis method is introduced and illustrated using longitudinal data on exit from and reentry into the teaching profession. The method is applicable to many educational problems involving the sequential occurrence of disparate events or episodes. (SLD)

  13. Multiplicity dependence of 2-particle correlations in proton-proton collisions measured with ALICE at the LHC

    International Nuclear Information System (INIS)

    Sicking, E.

    2014-01-01

    We investigate properties of jets in proton-proton collisions using 2-particle angular correlations. By choosing an analysis approach based on 2-particle angular correlations, also the properties of low-energetic jets can be accessed. Observing the strength of the correlation as a function of the charged particle multiplicity reveals jet fragmentation properties as well as the contribution of jets to the overall charged particle multiplicity. Furthermore, the analysis discloses information on the underlying multiple parton interactions. We present results from proton-proton collisions at the center-of-mass energies √(s) = 0.9, 2.76 and 7 TeV recorded by the ALICE experiment. The ALICE data are compared to Pythia6, Pythia8 and Phojet simulations. (author)

  14. Multiplicity Dependence of Two-Particle Correlations in Proton-Proton Collisions Measured with ALICE at the LHC

    CERN Document Server

    Sicking, Eva

    2012-01-01

    We investigate properties of jets in proton-proton collisions using two-particle angular correlations. By choosing an analysis approach based on two-particle angular correlations, also the properties of low-energetic jets can be accessed. Observing the strength of the correlation as a function of the charged particle multiplicity reveals jet fragmentation properties as well as the contribution of jets to the overall charged particle multiplicity. Furthermore, the analysis discloses information on the underlying multiple parton interactions. We present results from proton-proton collisions at the center-of-mass energies $\\sqrt{s}$ = 0.9, 2.76, and 7.0 TeV recorded by the ALICE experiment. The ALICE data are compared to Pythia6, Pythia8, and Phojet simulations.

  15. Evaluation of multiple approaches to identify genome-wide polymorphisms in closely related genotypes of sweet cherry (Prunus avium L.

    Directory of Open Access Journals (Sweden)

    Seanna Hewitt

    Full Text Available Identification of genetic polymorphisms and subsequent development of molecular markers is important for marker assisted breeding of superior cultivars of economically important species. Sweet cherry (Prunus avium L. is an economically important non-climacteric tree fruit crop in the Rosaceae family and has undergone a genetic bottleneck due to breeding, resulting in limited genetic diversity in the germplasm that is utilized for breeding new cultivars. Therefore, it is critical to recognize the best platforms for identifying genome-wide polymorphisms that can help identify, and consequently preserve, the diversity in a genetically constrained species. For the identification of polymorphisms in five closely related genotypes of sweet cherry, a gel-based approach (TRAP, reduced representation sequencing (TRAPseq, a 6k cherry SNParray, and whole genome sequencing (WGS approaches were evaluated in the identification of genome-wide polymorphisms in sweet cherry cultivars. All platforms facilitated detection of polymorphisms among the genotypes with variable efficiency. In assessing multiple SNP detection platforms, this study has demonstrated that a combination of appropriate approaches is necessary for efficient polymorphism identification, especially between closely related cultivars of a species. The information generated in this study provides a valuable resource for future genetic and genomic studies in sweet cherry, and the insights gained from the evaluation of multiple approaches can be utilized for other closely related species with limited genetic diversity in the breeding germplasm. Keywords: Polymorphisms, Prunus avium, Next-generation sequencing, Target region amplification polymorphism (TRAP, Genetic diversity, SNParray, Reduced representation sequencing, Whole genome sequencing (WGS

  16. Multiple Intelligences: Current Trends in Assessment

    Science.gov (United States)

    Harman, Marsha J.; Kordinak, S. Thomas; Bruce, A. Jerry

    2009-01-01

    With his theory of multiple intelligences, Howard Gardner challenged the presumption that intelligence is a single innate entity. He maintained that multiple intelligences exist and are related to specific brain areas and symbol systems. Each of the intelligences has its merits and limits, but by using a multiple intelligences approach, more…

  17. Surgical approach in patients with hyperparathyroidism in multiple endocrine neoplasia type 1: total versus partial parathyroidectomy

    Directory of Open Access Journals (Sweden)

    Francesco Tonelli

    2012-01-01

    Full Text Available Usually, primary hyperparathyroidism is the first endocrinopathy to be diagnosed in patients with multiple endocrine neoplasia type 1, and is also the most common one. The timing of the surgery and strategy in multiple endocrine neoplasia type 1/hyperparathyroidism are still under debate. The aims of surgery are to: 1 correct hypercalcemia, thus preventing persistent or recurrent hyperparathyroidism; 2 avoid persistent hypoparathyroidism; and 3 facilitate the surgical treatment of possible recurrences. Currently, two types of surgical approach are indicated: 1 subtotal parathyroidectomy with removal of at least 3-3 K glands; and 2 total parathyroidectomy with grafting of autologous parathyroid tissue. Transcervical thymectomy must be performed with both of these procedures. Unsuccessful surgical treatment of hyperparathyroidism is more frequently observed in multiple endocrine neoplasia type 1 than in sporadic hyperparathyroidism. The recurrence rate is strongly influenced by: 1 the lack of a pre-operative multiple endocrine neoplasia type 1 diagnosis; 2 the surgeon's experience; 3 the timing of surgery; 4 the possibility of performing intra-operative confirmation (histologic examination, rapid parathyroid hormone assay of the curative potential of the surgical procedure; and, 5 the surgical strategy. Persistent hyperparathyroidism seems to be more frequent after subtotal parathyroidectomy than after total parathyroidectomy with autologous graft of parathyroid tissue. Conversely, recurrent hyperparathyroidism has a similar frequency in the two surgical strategies. To plan further operations, it is very helpful to know all the available data about previous surgery and to undertake accurate identification of the site of recurrence.

  18. SWAMP+: multiple subsequence alignment using associative massive parallelism

    Energy Technology Data Exchange (ETDEWEB)

    Steinfadt, Shannon Irene [Los Alamos National Laboratory; Baker, Johnnie W [KENT STATE UNIV.

    2010-10-18

    A new parallel algorithm SWAMP+ incorporates the Smith-Waterman sequence alignment on an associative parallel model known as ASC. It is a highly sensitive parallel approach that expands traditional pairwise sequence alignment. This is the first parallel algorithm to provide multiple non-overlapping, non-intersecting subsequence alignments with the accuracy of Smith-Waterman. The efficient algorithm provides multiple alignments similar to BLAST while creating a better workflow for the end users. The parallel portions of the code run in O(m+n) time using m processors. When m = n, the algorithmic analysis becomes O(n) with a coefficient of two, yielding a linear speedup. Implementation of the algorithm on the SIMD ClearSpeed CSX620 confirms this theoretical linear speedup with real timings.

  19. An Updated Meta-Analysis of Risk of Multiple Sclerosis following Infectious Mononucleosis

    Science.gov (United States)

    Handel, Adam E.; Williamson, Alexander J.; Disanto, Giulio; Handunnetthi, Lahiru; Giovannoni, Gavin; Ramagopalan, Sreeram V.

    2010-01-01

    Background Multiple sclerosis (MS) appears to develop in genetically susceptible individuals as a result of environmental exposures. Epstein-Barr virus (EBV) infection is an almost universal finding among individuals with MS. Symptomatic EBV infection as manifested by infectious mononucleosis (IM) has been shown in a previous meta-analysis to be associated with the risk of MS, however a number of much larger studies have since been published. Methods/Principal Findings We performed a Medline search to identify articles published since the original meta-analysis investigating MS risk following IM. A total of 18 articles were included in this study, including 19390 MS patients and 16007 controls. We calculated the relative risk of MS following IM using a generic inverse variance with random effects model. This showed that the risk of MS was strongly associated with IM (relative risk (RR) 2.17; 95% confidence interval 1.97–2.39; pmononucleosis significantly increases the risk of multiple sclerosis. Future work should focus on the mechanism of this association and interaction with other risk factors. PMID:20824132

  20. An updated meta-analysis of risk of multiple sclerosis following infectious mononucleosis.

    Directory of Open Access Journals (Sweden)

    Adam E Handel

    2010-09-01

    Full Text Available Multiple sclerosis (MS appears to develop in genetically susceptible individuals as a result of environmental exposures. Epstein-Barr virus (EBV infection is an almost universal finding among individuals with MS. Symptomatic EBV infection as manifested by infectious mononucleosis (IM has been shown in a previous meta-analysis to be associated with the risk of MS, however a number of much larger studies have since been published.We performed a Medline search to identify articles published since the original meta-analysis investigating MS risk following IM. A total of 18 articles were included in this study, including 19390 MS patients and 16007 controls. We calculated the relative risk of MS following IM using a generic inverse variance with random effects model. This showed that the risk of MS was strongly associated with IM (relative risk (RR 2.17; 95% confidence interval 1.97-2.39; p<10(-54.Our results establish firmly that a history of infectious mononucleosis significantly increases the risk of multiple sclerosis. Future work should focus on the mechanism of this association and interaction with other risk factors.